# Unraveling the link between thermal adaptation and latent allotery in malate dehydrogenase from Methanococcales

Caroline Simões Pereira, Sandrine Coquille, Céline Brochier-Armanet, Fabio Sterpone, Dominique Madern

<figure><img src="image_1.png" /></figure>

## To cite this version:

Caroline Simões Pereira, Sandrine Coquille, Céline Brochier-Armanet, Fabio Sterpone, Dominique Madern. Unraveling the link between thermal adaptation and latent allotery in malate dehydrogenase from Methanococcales. Journal of Molecular Biology, In press, pp.169552. 10.1016/j.jmb.2025.169552. hal-05381056

HAL Id: hal-05381056

https://hal.science/hal-05381056v1

Submitted on 25 Nov 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Unraveling the link between thermal adaptation and latent allostery
in malate dehydrogenase from Methanococcales

Caroline Simões Pereira¹*, Sandrine Coquille²*, Céline Brochier-Armanet³,⁴, Fabio Sterpone¹
and Dominique Madern²

¹CNRS, Université de Paris, UPR 9080, Laboratoire de Biochimie Théorique, Paris, France; Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, Paris, France.

²Univ. Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France.

³Université Claude Bernard Lyon1, LBBE, UMR 5558 CNRS, VAS, Villeurbanne, F-69622, France

⁴Institut Universitaire de France (IUF)

Corresponding authors: Dominique.madern@ibs.fr, Fabio.sterpone@ibpc.fr, Celine.brochier-armanet@univ-lyon1.fr

<footnote>* These authors contributed equally.</footnote>
**Abstract**

Malate dehydrogenase (MalDH) (EC.1.1.1.37) is an enzyme engaged in the central
metabolism of cells, catalyzing the interconversion between oxaloacetate and malate using
NADH or NADPH as coenzyme. These enzymes are particularly interesting models for
studying how proteins adapt to physical and chemical environmental constraints. In this
study, we investigated the molecular mechanisms that have enabled MalDHs to adapt to
changes in temperature, using Methanococcales archaea as a model organism. We solved
the crystal structure of ancestral MalDHs in these archaea. Structural comparison with
present-day MalDHs such as those from *Methanocaldococcus infernus* (M. inf) and
*Methanocaldococcus jannaschii* (M. jan), highlights the role salt-bridges in thermal
adaptation. We also found that present-day MalDHs from M. inf and M. jan, show structural
features that resemble the extended or compact states typical of allosteric lactate
dehydrogenases. To test hypotheses about a possible link between thermal adaptation and
the emergence of allosteric regulation, we characterized structurally two M. jan MalDH
mesophilic-like mutants. Molecular dynamics simulations using the Wt M. jan and mutant
MalDHs were used to rationalize the experimental data. The results indicate that
uncompetent and competent catalytic site configurations are in an equilibrium that depends
on temperature conditions. At low temperature the Wt M. jan MalDH select non-competent
conformers, whereas high temperature favours active conformers. In contrast, the M. jan
MalDH mutants explore competent conformers for catalysis at a lowest temperature, a
phenomenon that fits well with their biochemical behaviour. Our work reveals that thermal
adaptation and evolution of allostery are strongly linked via the modulation of the protein
conformational landscape.

**Keywords**

Thermal adaptation of enzymes, malate dehydrogenase, allostery, ancestral sequence,
evolution, archaea, protein dynamics, structure
Introduction

On Earth, environmental conditions such as hydrostatic pressure, temperature, radiation, or desiccation, salinity, pH and redox potential, impose strong physical and chemical constraints on organisms and their proteins [1, 2, 3]. Microorganisms that thrive in extreme environments are relevant models to unravel the evolutionary and adaptive processes that allow their enzymes to cope with harsh conditions [4, 5]. Among these, temperature is probably the most extensively studied. Comparisons of sequence, structure and dynamics between modern enzymes from psychrophiles and hyperthermophiles have provided significant insights into adaptive strategies [6-14]. Meanwhile, ancestral sequence reconstruction (ASR) and protein resurrection have revealed the underlying evolutionary processes [15-22]. With regard to thermoadaptation, it has been shown that there is a strong relationship between the abundance of amino acids in proteomes and the optimal growth temperature (OGT) of organisms [23-27]. This relationship has been used to develop molecular thermometers that can predict the OGTs of organisms from their proteome sequences. Coupling it with ASR and molecular phylogenetics makes it possible to model OGT thermal drift over evolutionary time [24, 28-30].

In relation to these questions, methanogens have been proposed as relevant models for studying thermoadaptation, given that they have colonised habitats with very different environmental temperatures [31]. Among these, *Methanococcales* are of particular interest, as the OGT is the main factor responsible for variation in proteome amino acid content in these organisms, whereas in other taxa, the dominant factor is genomic GC content (see [29] and references therein). This means that the signal related to thermoadaptation is overall stronger in *Methanococcales* proteins. Using ASR, a recent study showed that during the diversification of the *Methanococcales* several *Methanococcaceae* species have independently adapted to moderate environments from hyperthermophilic ancestors, while all *Methanocaldococcaceae* species remained hyperthermophilic [29]. They also found that amino acid substitution is the main driver of thermoadaptation, sequentially shaping the amino acid content of proteomes, with lysine playing a key role in this process. ASR suggested that the ancestors of *Methanococcales* and of *Methanocaldococcaceae* had OGTs close to 80°C, whereas the OGT of *Methanococcaceae* was lower at around 65°C [29]. These results were recently tested by recording the temperature-dependent activity and conformational stability profiles of different ancestral and modern Malate dehydrogenase (MalDH) [32]. MalDHs were used because, they are suitable enzyme models for studying molecular evolution and extremophily [7, 19, 30, 33-39]. MalDHs are homotetramers or
homodimers enzymes [37, 40, 41] belonging to the large superfamily of Malate/Lactate Dehydrogenases (MalDH/LDH) [38, 42-46]. MalDHs are involved in the tricarboxylic acid cycle. They convert oxidized oxaloacetate to malate using either NADPH or NADH as a coenzyme, whereas LDH are involved in the anaerobic metabolism of glucose, by catalysing the conversion of pyruvate to lactate.

The study by Madern et al. (2024) [32] found that the MalDH inferred in the ancestor of *Methanococcales* (referred hereafter to as A35) is a polyextremophilic enzyme capable both of withstanding both strong radiation and thermal stress, with an optimum temperature for activity (OT<sub>A</sub>) of 80°C. The MalDH enzyme inferred in the ancestor of *Methanocaldococcaceae* (referred hereafter to as A34) has conserved a similar OT<sub>A</sub>, whereas it drops to 67°C in the ancestor of *Methanococcaceae* (hereafter referred to as A19) [32]. These results are consistent with the OGTs predicted from the amino acid composition of the proteomes (see above). Surprisingly, however, these three ancestral MalDHs exhibited a strong resistance to thermal unfolding, demonstrating therefore that adaptation to mesophily in *Methanococcales* was initially shaped by a process in which activity and conformational stability were decoupled. By introducing a few substitutions into the MalDH of *Methanocaldococcus jannaschii*, a hyperthermophilic species belonging to the *Methanocaldococcaceae*, we were able to reproduce the phenomenon, i.e. both the reduction of OTA and the preservation of thermal stability, in two mutants (referred hereafter to as C7 and C7GP mutants) [32].

Here, we have analysed the thermal adaptation mechanism of *Methanococcales* MalDHs by combining X-ray crystallography and molecular dynamics simulations. We solved several structures, including the ancestral MalDHs inferred in A34 and A19, the MalDH of *Methanocaldococcus infernus*, and the C7 and C7GP mutants, which have mesophilic-like enzymatic activity profiles. We found that the main difference between the MalDHs of different thermally adapted lineages is their ability to form a network of stabilising electrostatic interactions in a hinge region. We also found that these tetrameric MalDHs exhibit two different states of compactness. These extended or compact states, strongly resemble those sampled by allosteric LDHs. This unexpected observation, agrees with evolutionary studies showing that latent allosteric capacity evolved in tetrameric MalDH before its full achievement in LDHs [38]. Finally, we showed that the OT<sub>A</sub> of activity shifts towards mesophilic conditions in *Methanococcales* MalDHs is the consequence of modifying the equilibrium between catalytically competent and non-competent states.

## Results and discussion
The study by Madern et al. (2024) [32] determined experimentally that the MalDH inferred in the ancestor of *Methanococcales* has an $OT_A$ of 85°C (A35 marked with a star in Figure 1). According to phylogeny, two MalDH lineages with different thermal trajectories emerged from this ancestral enzyme. The first one corresponds to MalDHs found in *Methanocaldococcaceae* that are (hyper)thermophilic and the second to MalDHs found in *Methanococcaceae*, which are mesophilic or thermophilic (Figure 1).

## The overall structure of ancestral, modern, and mutant MalDHs

To gain further insight into the MalDHs thermal adaptation, we have solved the structure of MalDH of A34, A19, *M. infernus*, and the C7 and C7GP mutants. The *M. jannaschii* MalDH is already available in the PDB [47]. The structural analysis of these MalDHs was carried out in two different ways. The first was to compare the structures of A34 and A19 with each other and with those of *M. jannaschii* and *M. infernus*, which are representative of modern hyperthermophilic enzymes. In a second step, we performed a comparative structural analysis combining crystallographic information and AlphaFold models in order to study the effects of introducing mutations that lead to a decrease in $OT_A$ when using the *M. jannaschii* MalDH as template. The crystallization protocol, data collection and refinement processes for the enzymes are described in Materials and Methods. The Data collection and refinement statistics are given in Table S1. The atomic coordinates have been deposited at the RCSB PDB data bank (Table 1).

<table><thead><tr><td>MalDH Sequence</td><td>PDB accession number</td><td>Resolution</td><td>Tetrameric state</td><td>OT<sub>A</sub></td></tr></thead><tbody><tr><td>Wt M. infernus</td><td>9SD3</td><td>2.2 Å</td><td>Compact</td><td>80°C</td></tr><tr><td>Ancestral A34</td><td>9S3K</td><td>2.7 Å</td><td>Compact</td><td>85°C</td></tr><tr><td>Ancestral A19</td><td>9S3Y</td><td>2.05 Å</td><td>Compact</td><td>60°C</td></tr><tr><td>Wt M. jannaschii</td><td>1HYE</td><td>2.8 Å</td><td>Extended</td><td>90°C</td></tr><tr><td>C7 M. jannaschii</td><td>9SA7</td><td>2.8 Å</td><td>Extended</td><td>65°C</td></tr><tr><td>C7GP M. jannaschii</td><td>9SC9</td><td>3.0 Å</td><td>Compact</td><td>60°C</td></tr></tbody></table>
Table 1. Crystal structures of Malate dehydrogenase used in this study. The resolution and the global shape of the tetrameric state are given (see explanations in the main text). The optimal temperature for activity is from [32].

As expected, the final structures of the five enzymes correspond to tetramers, in agreement with the oligomeric state found in solution [32]. The overall architecture of their respective monomers is similar to previously reported MalDH structures. It contains the typical NAD(P)-binding Rossmann-like Domain (Figure 2). The tetrameric state contains four active sites organized as two functional dimers (A//B and C//D), respectively in red-blue and green yellow, Figure 2A). The subunit contacts that maintain the tetrameric assembly occur through interfaces (AD-like and AB-like, small arrows Figure 2A) along the P, Q and R axes. In contrast to the *M. jannaschii* MalDH which has an extended tetrameric conformation [47], all the MalDH structures solved here are in a more compact state as analyzed below.

Various parameters such as the buried surface, hydrogen bonds (HB), salt bridges (SB) at the various interfaces, calculated using PBDePISA (https://www.ebi.ac.uk/pdbe/pisa/) are presented in Table S2. The data indicate even if the global content of intra and interchain hydrogen bonds, and hydrophobic surface in tetramers are similar, the HB and SB distribution differ at their interfaces suggesting a role in thermal adaptation of MalDH from Methanococcales.

**The ancestral A19 and A34 MalDH structures give insight into the initial step of thermoadaptation in *Methanococcales***

Sequence comparison of A35, A34, and A19 revealed that 16 substitutions occurred along the branch connecting A35 and A34, and 12 on the branch leading from A35 to A19 (Figure 2 and Figure S1)[32]. Interestingly, there is no overlap between the two sets of substitutions. The following comparison describes how these substitutions could have affected the structural properties (Figure 2 A-D) and favored the shift of $OT_A$ observed in A19 (see below). We tested a huge number of conditions and failed to get crystals of A35, the ancestral *Methanococcales* MalDH. However, our previous work showed that the hyperthermophilic behavior (OTA and folding stability) of MalDH inferred in A35, is conserved in A34 and the *Methanocaldococcaceae* MalDH lineage, which includes the modern enzymes of *M. jannaschii* and *M. infernus* MalDHs [32].

The study by Lecocq et al. (2021) [29] has revealed the central role of lysine in finely controlling the pool of key amino acids in the thermoadaptation process (i.e. arginine, serine, threonine, asparagine, and glutamine) [29]. This is consistent with other studies showing that
hyperthermophilic enzymes contain, on average, more salt-bridges (SB) than their mesophilic homologues [48]. This is because complex SB networks can be resistant to temperature increases and are therefore particularly suitable for increasing protein thermostability [20, 49-51]. SB are formed between positively (K/R) and negatively (D/E) charged amino acids. Consistently, in the hyperthermophilic *M. jannaschii* MalDH, there are 45 positively and 49 negatively charged residues, whereas in the mesophilic *M. maripaludis* C7 MalDH, their respective numbers are only 40 and 43, which could result in a lower number of SBs.

Analysis of the substitutional trajectories in the light of the structural information provides an explanation for these observations. Indeed, the structural comparison between A34, A19, *M. jannaschii* and *M. infernus* MalDHs structures revealed that, despite of similar folds, local reorganizations exist (Ellipsed area colored in blue in Figure 2), in particular at the interface between A and B monomers (referred hereafter as to the AB interface) (Figure 3). We used PDB:PISA, ESBRI [53] and Vadar [54] to calculate H-bonds and SB formation in A19, A34 and *M. jannaschii* and *M. infernus* MalDHs.

We considered the kinked α1G-α2G helix and the αC helix located at the AB interface (Figure 3). This region surrounds the key substrate-binding residue R154 that is strictly conserved in all MalDHs and LDHs [38]. The R154 side chain is always located within the catalytic site of MalDH (inside configuration), whereas it may move outside in the inactive T-state of allosteric LDHs [46, and references therein]. The structure of the A34 MalDH shows that the K217 forms a SB with D50 (Figure 3A). This stabilizing interaction is unlikely to be present in A35 MalDHs due to the presence of an alanine at position 217, or in A19 due to the presence of a glutamine at this position. The structure of A19 MalDH shows that the G217 prevents SB formation at the AB interface (Figure 3D). This implies that the steric contacts that hold the side chain of R154 within the catalytic site are more relaxed in the A19 than in the A34 MalDH (Figure S2).

In A34 MalDH, the unfavourable thermally induced deformations of R154 for catalysis are strongly prevented due to an increased local packing density. The different steps in the evolution of SB formation in present-day *Methanocaldococcus* species are illustrated by the *M. infernus* and *M. jannaschii* MalDH (Figure 3B-C). The structures of their MalDHs indicate that the AB interface is stabilized by more SBs than in the A34 MalDH (Figure 3). However, the SBs are not in the same position in the two MalDHs due to some side chain reorganization and different amino acid patterns. This suggests that, despite different substitution patterns, the adaptive process was compensatory to maintain the
hyperthermophilic behaviour of these two enzymes. The analysis of the substitutional amino acid flux in mesophilic and thermophilic *Methanococcales* species has revealed the central role of lysine [29]. Overall, the comparison of MalDH sequences and structures confirms the important role of this amino acid, for which i) the number increases and ii) substitutions toward arginine are favored, allowing the formation of new SBs, in hyperthermophiles, while the opposite trend is observed in the root of *Methanococcaceae* (A19) where a decrease in OGT is observed (Figures 1 and 3).

These observations are consistent with a recent structural analysis of the bacterial HMPPK enzymes involved in vitamin B1 biosynthesis, which found that the adaptation to colder environments was associated to a decrease in the number of SBs [55].

Comparison of MalDH sequences in *Methanococcaceae* (A19 and its descendants), which are all thermophilic or mesophilic, shows that positively charged residues have never been selected at position 217 that corresponds to the middle of the kinked α1G-α2G helix (Figure 3). Structural and molecular dynamical studies of MalDHs and LDHs have revealed that conformational changes of various amplitude, involving the kinked α1G-α2G helix, occur during catalysis [52, 56]. Thus, it is reasonable to propose that the increase in SBs at the AB-like interface in *Methanocaldococcaceae* (A34 and its descendants, all of which are (hyper)thermophilic, was an efficient mechanism to avoid local unfolding of the kinked helix and subsequent deformation of compactness of the catalytic site near R154 at high temperature. Our observation agrees with the favorable effect of SBs on thermal stability [57, 58]. Some studies suggested that an increase of G also contributes to the thermal adaptation to low temperature [59]. This is due to their strong propensity to induce high local conformational flexibility of the protein backbone. We propose that the selection of G217 in A19 MalDH, contributed strongly to the $OT_A$ decrease recorded in our previous study (see [32]). This was very likely due to a change in the α1G-α2G helix dynamics propagating directly to the catalytic site, thus favoring the sampling of competent conformers for catalysis without necessity of high thermal energy as with A35 MalDH.

Biophysical models of protein evolution propose that, during evolution, the structure, function and dynamic properties of proteins tend to be conserved despite the fixation of substitutions in the sequences [60, 61]. Consistently, we have shown that the strong conformational thermal stability was conserved in *Methanocaldococaceae* MalDHs even if many substitutions accumulated since A35 [32]. Here, we show that these substitutions are responsible for a subtle reorganization of electrostatic networks at the monomer interfaces, as charged side-chains have established new interactions with neighboring amino acids
without impacting the overall thermal stability. The reason why electrostatic interaction
networks are one of the most striking factors associated with the increased thermal stability
of hyperthermophilic proteins is linked to conformational entropy. Indeed, when thermal
motions break an ion-pair, the side chain flexibility of charged residues (particularly arginine)
often allows the formation of a new ion pair which can help maintain the structural stability
[62-65].

Distribution of T and R allosteric LDH-like structure in Methanococcales MalDH

Until this work, the *M. jannaschii* MalDH structure (1HYG) was the only representative
structure of MalDH in *Methanocaldococcales* [47]. It is a tetramer that resembles the
extended T-inactive state of allosteric LDH rather than the compact R-active state of
tetrameric MalDH or LDH. Previous biophysical studies have shown that the *M. jannaschii*
MalDH in solution, experiences large structural reorganizations suggesting it exhibits a partial
allosteric-like behavior [56]. A recent work has shown that the compact or extended
tetrameric state can be identified using the distance measurement between the αC of the
amino acids at position 225 in monomer C and D of MalDH or LDH structures [30] . In the *M.
jannaschii* MalDH structure, this distance is 17.1 Å (Figure 2A, red dots) indicating an
extended T-like conformation, whereas the distance is 11.6 Å in A34 and A19 MalDHs, and
12.5 Å in *M. infernus* MalDH indicating that they are in a compact R-state.

We analyzed how the amino acid substitutions in ancestral and modern MalDHs have
redistributed interactions between the AD-like and AC-like interfaces, allowing the
coexistence of compact and extended tetrameric states in some modern MalDHs. The
structure of the A19 and A34 MalDHs, show local drastic reorganization upon acquisition of
amino acid substitutions (Figure 4A-D). The A19 structure shows that the R57 side chain
protrudes into the central water-accessible cavity and that there are no interactions with a
complex network of electrostatic interactions formed by residues from monomers B and C.
The lack of structural information about the A35 MalDH does not allow us to draw any
definitive conclusions about the A//D interfaces topology of this ancestral enzyme. However,
compared to A35, we note that there is no amino acid substitution in this A19 MalDHs,
whereas there are two mutations (G56R and R57S) in A34 that may have important
consequences (Figure 4A). In particular, it allows the side chain of R56A to promote SBs with
D168C, which belongs to an electrostatic network made up of several amino acids of
monomers C and D. Recall that the minimal unit that maintains activity in the MalDH and
LDH superfamily is the dimer AB [38, 66].
We propose that the presence of R56 and its SB interaction with D168 in A34 was beneficial to increase the stabilization of the active AB-like dimers, allowing to make a compact and more stable tetrameric assembly at high temperature. However, since the *M. jannaschii* MalDH has a more extended structure, due its latent allosteric capacity [52], this implies that some other substitutions have partially relaxed the stabilizing interaction of R56 with D168. A biophysical study of the *M. jannaschii* MalDH, has shown that the compact state can be sampled at high temperature [52], suggesting therefore that the SB between R56 and D168 can be transiently restored. A study using allosteric LDHs has shown that thermal adaptation and evolution of allosteric properties are intimately mixed [39]. Furthermore, the importance of side-chain reorganization induced by substitutions at position 57 on the allosteric capacity has been underlined in the recent study of a mesophilic LDH [67]. The comparison of this region in the A34 and *M. infernus* MalDHs shows three substitutions (Figure 4C). One of them, R57 restores the amino acid predicted in the A35 MalDH, while K56 and E69, and the side-chain reorganization of some other amino acids, contribute to slightly rearrange the electrostatic interactions between the monomers. In agreement to our structural work, we propose that the most representative state of Methanococcales MalDH is the compact R-active state as it has been observed with the ancestral and the *M. infernus* enzymes. The *M. jannaschii* MalDH with an extended T-like conformation would be considered therefore as a specific case. Our results suggest that the amino acid substitutions that were fixed in *Methanocaldococcaceae* MalDH have more likely shifted their capacity to exist in compact or extended states, indicating an action on the latent allosteric capacity rather than on their thermal properties. Going further and identifying the substitutions that have specifically modulated the latent allosteric capacity of these MalDHs would require the structural characterization of additional modern and ancestral enzymes along the complete lineage.

## Cation-binding sites in Methanococcales MalDHs

A recent study has shown that the *M. kandleri* MalDH displays a hidden allosteric capacity, which can be revealed by introducing a very few LDH-related mutations. The resulting allosterized mutants are able to sample extended or compact states [30]. This T/R state equilibrium depends on the KCl concentration. In frame with that, the *M. kandleri* MalDH structure shows the tetrameric state binds four potassium ions, which contribute to its conformational stability [30]. Analysis of A34 and *M. infernus* MalDHs structures revealed that they also contain four K⁺, one per monomer, whereas Na⁺ is present in A19 MalDH
(Figure S3). The binding of Na⁺ is very likely the consequence of the high concentration of sodium malonate that has favoured crystal growth of A19 MalDH. We analyzed them with respect to the *M. kandleri* cation-BS and found that they are at the same position within a monomer. We note that *M. kandleri* is an archaeon that accumulates high potassium concentration within its cytoplasm [68]. The cation-BS formation involves a set of eight amino acids located on two connecting loops between αC-βC and βC-αB (Figure S3). The cation-BS are located in an area that participates to maintain interactions at AD like interfaces, which maintain the tetrameric assembly. Even if there is a noticeable amino acid pattern variation, this does not prevent a cation to occupy a site because most of the binding is due to the main chain oxygen. This observation suggests therefore some differences in their cation-binding capacity due to local dynamical changes induced by the side-chain ability to create interaction of various strength with close partners. We note that there is a water molecule instead of a cation in *M. jannaschii* MalDH. We propose that the cation-BS local topology in the extended state of *M. jannaschii* MalDH is not favorable for cation binding because of local unfolding (see arrow in Figure S3).

## Crystal structure of *M. jannaschii* MalDH and mesophilic-like mutants

With the exception of A19 MalDH, it has not been possible to obtain structural information on ancestral and modern MalDHs of the *Methanococcaceae* which thermo/mesophilic despite numerous attempts [32]. To overcome this problem, we designed two mesophilic-like mutants (C7 and C7GP) using the *M. jannaschii* MalDH scaffold as a template [32]. Compared to the Wt *M. jannaschii* MalDH, which has an $OT_A$ of 85°C, the OTA of the C7 and C7GP mutants decreases to 65°C and 60°C, respectively [32]. In the present work, we succeeded in obtaining crystals of C7 and C7GP mutants, collecting diffraction data, and solving their structure. The structure of the C7 mutant was solved at a resolution of 2.7 Å with relatively good statistics, however the crystals of the C7GP mutant diffracted at low resolution between 3-4 Å with poor statistics. We nevertheless obtained two models (9SC9) confirming the compact fold of the C7GP mutant, but further analysis of side-chain orientation was not possible. To move forward, we generated a predicted atomic model with AlphaFold3 [69]. The $C_α$ root mean square deviation (RMSD) between the model and structure was 0.54 Å for 313 aligned residues. The goal was to compare the different conformational states of *M. jannaschii* MalDH WT and C7 and C7GP mutants, as well as to perform MD simulations. When considering the tetrameric assembly, the distance between αC of N245 reflects the accessibility of the solvent accessible central cavity (SAC). The distance between αC of C307 gives an additional indication of the size. In the Wt *M. jannaschii* MalDH, these distances are 17.1 Å and 76.8 Å, respectively (Figure 5). The global
shape of the structure shows that this MalDH has an extended tetrameric conformation, more similar to the T-extended inactive state of allosteric LDHs than the compact state commonly observed for tetrameric MalDH. Interestingly, the measurement shows that the C7 mutant MalDH is still in an extended state with distances of 17.1 Å and 76.8 Å (Figure 5), whereas the C7GP mutant MalDH shows shorter distances (13.1 Å and 71.9 Å), corresponding to a more compact state (Figure 5). This observation indicates that the first set of substitutions, which were mainly aimed at disrupting the intra-monomeric SB, has an effect on the enzymatic activity [32], without affecting the shape of the C7 mutant MalDH.

A previous study of Wt *M. jannaschii* MalDH at high temperature showed that this enzyme can explore a compact state in solution by dewetting of the SAC, demonstrating a hidden allosteric-like capacity [52]. Here, the C7GP mutant observed in a compact state indicates that the second set of mutations has completely shifted the conformational sampling towards an R-like active state, confirming that an allosteric capacity was already present in the *M. jannaschii* MalDH used as a scaffold. Studies on imidazole glycerol phosphate synthase and allosteric LDHs have shown that temperature is a modulator of allosteric motions. In particular, high temperature induces the melting of stabilizing interactions that normally contribute to the maintenance of strong energy barriers between the T- and R- states, and thus favours the R-active state [70-72]. Here, mutations have disrupted numerous interactions in the C7GP mutant. We assume that such a situation has favoured the crossing of energy barriers between conformers, and thus the stabilization of the compact state.

**Temperature effects vs. allosteric like reorganization: a dynamical perspective.**

We performed 1µs of classical molecular dynamics (MD) simulations of the systems described in table MD1 to analyze the changes in interactions responsible for the *M. jannaschii* MalDH $OT_A$ decrease from 90°C in the Wt, to 65°C and 60°C in the C7 and C7GP mutants, respectively. The crystal structure obtained for C7GP MalDH was of low resolution. To address this limitation, we used AlphaFold model at compact state (conformation suggested by the experimental crystal structure), as the starting point for the simulation. AlphaFold models have been shown to provide high-resolution templates suitable for exploring atomic-scale enzyme dynamics through molecular dynamics simulations [73-75]. To further validate the results, we also generated a C7GP *M. jannaschii* MalDH model in an extended conformation by introducing the GP mutations into the extended C7 *M. jannaschii* MalDH structure.
<table><caption>Table MD1. Description of the initial structures used for MD simulation.</caption><thead><tr><td>Systems</td><td>Initial configuration for MD simulation</td><td>Initial state</td></tr></thead><tbody><tr><td>Wt M. jan</td><td>Crystal structure of Wt (PDB code: 1HYE)</td><td>Extended</td></tr><tr><td>C7 M. jan</td><td>Crystal structure of C7</td><td>Extended</td></tr><tr><td>C7GP M. jan</td><td>Alphafold model of C7GP</td><td>Compact</td></tr><tr><td>C7GP (mut) M. jan</td><td>Crystal structure of C7 including GP mutations</td><td>Extended</td></tr></tbody></table>

The Wt and the mutants were simulated at their $OT_A$, and at 45°C and 75°C. Tetrameric compaction can be measured by the distances between the $C\alpha$ of the residues at position 245 of the monomer pairs A-C and B-D (Figure 6A). At the $OT_A$, these distances were approximately 1.2 nm for WT and C7GP, and 1.55 nm for C7 (Figure 6 A-B), indicating that WT and C7GP adopt a more compacted conformation compared to C7. Lowering the temperature to 45°C causes the three enzymes to adopt an asymmetric conformation, where the distances between the chain pairs A-C in Wt, C7 and C7GP show values around 2.1, 1.75 and 1.45 nm, respectively, whereas no significant change is observed for the chain pair B-D (Figure 6A-C). At 75 °C, C7 and C7GP adopted a more compacted state, and Wt an intermediary state between the values observed at $OT_A$ and 45 °C (Figure S4). These observations indicate that increasing the temperature promotes a more compact conformation in all three enzymes. This finding is consistent with a biophysical study of *M. jan* MalDH WT, which showed that the compact state is preferentially sampled at high temperatures [52]. However, this effect is markedly more pronounced in WT, suggesting that the introduced mutations weaken the coupling between temperature and conformational expansion.

Then, we have analyzed the variations in SB interactions around residue 245 to explore their possible role in the exploration of extended or compact conformations by MalDH (Figure 6D). In the Wt, R56 can adopt two different conformations: (i) interacting with D58 of the same chain, as seen in the Wt crystal structure (Figure 6D-E), or (ii) interacting with D168 on the adjacent A-B chain (Figure 6C-D). In the latter case, it allows D58 to form a hydrogen bond with the intersecting AC-like chain (Figure 6F), contributing to the asymmetry observed in the distances between the 245 $C\alpha$ carbons at 45°C, and to the formation of the D58(A)-K161(B) SB (Figure S5).

The conformation of helices $\alpha$B(A) and $\alpha$3G(A) is associated with R56(A) interactions. The R56(A)-D58(A) SB is associated with the formation of the E23(A)-R241(A) SB within monomer A (Figure 6D-G). Conversely, the R56(A)-D168(B) SB formation enables the
formation of the E23(A)-K22(B) SB between monomers A and B (Figure 6D-H). Thus, two primary SB arrangements are favored in the WT: (i) the intramonomer SB (i.e. R56(A)-D58(A) and E23(A)-R241(A)), and (ii) the interchains AB-like SB (i.e. R56(A)-D168(B), E23(A)-K22(B), and D58(A)-K161(B)) and the AC-like SB/hydrogen bonds.

In the MD simulations of WT, the intra monomeric SB appears only at 45°C (Figure 6E), adopting a more extended conformation (Figure 6C), and the SBs between monomers predominate at higher temperatures (Figure 6F). In the C7 mutant, intra monomeric SBs are frequently observed at both 45°C and 65°C, which may contribute to the extended conformation observed at these temperatures. However, in the C7GP mutant, R56 is replaced by glycine, which does not form the SBs involved in inter monomeric interactions. These results indicate that the absence of R56 in the C7GP mutant allows it to adopt a more compacted conformation even at 45°C by reducing the interactions of the extended form. These results were confirmed by MD simulations starting from the extended-state C7 crystal structure bearing the GP mutations (Figure S6), which evolved toward the compact conformation and salt-bridge pattern observed in simulations initiated from the compact structure, reinforcing the stability and preference for this structural arrangement. WT forms a more expanded salt-bridge network compared to the mutants. This network increases the potential for dynamic rearrangements and supports the structural flexibility required to transition between different conformational states, including competent and non-competent forms. Even if, our work highlights that disrupting stabilizing electrostatic interactions plays a role in adaptation from an ancestral hyperthermophilic MalDH toward mesophilic-adapted enzyme, the efficiency of this adaptative process can be modulated by other interactions. For example, the role of hydrophobic contacts was observed on a work using ancestral reconstruction of 3-isopropylmalate dehydrogenase [76].

Our atomistic descriptions elucidate how thermally induced local interactions redistribute and trigger large-scale, allosteric-like conformational reorganizations similar to those observed with canonical allosteric LDHs upon effector binding. This observation confirms that thermally driven motions and allosteric signaling are intimately linked [70-72].

## Catalytic site reconfiguration and thermal adaptation.

We are continuing our investigations to explain the downshift of the $OT_A$ observed in the C7 and C7GP mutants, which should be due to changes in the catalytic cycle rate of the enzyme [32]. In our previous studies, we found that the dynamic properties of two universally conserved residues are strong proxies for the organization and efficiency of the catalytic site ([39, 71]. R154 is the substrate binding residue and H178 is the reactive histidine. They are located at αH helix and loop 176-183, respectively. We have observed that the R154 side
chain, in the Wt, C7 and C7GP enzymes, is maintained in its favorable state for substrate
binding throughout all the simulations, whereas only a slight decrease in fluctuations is
observed with the loop 176-183 carrying His178 (Figure S7). These observations still do not
clarify the $OT_A$ shift.

In MalDHs and LDHs, the motion of the mobile loop (MgL) formed by the residues 81-92 is
crucial for the enzyme catalytic cycle, as it must open to bind the substrate and expel the
product, but also close to allow the chemical reaction to proceed, as R86 binds the substrate
and R92 stabilizes the transition state (Figure 7) [38, 46 and reference therein ]. Thus, the
motion of the Mbl impacts the catalytic rate, as has been monitored in LDHs [77-80]. In
allosteric LDHs, additional concerted conformational reorganizations involving the α1G/2G
helix are observed [9, 46, 81].

Here, in the *M. jannaschii* MalDH and C7 and C7GP mutants, the MgL motion depends on
the conformation of the αD/E and α1G/2G helices, which can be described by the distance
between the Cα of the residues 92 and 225 (Figure 8A-B). The principal component analysis
of the Wt chain B at 75°C (Figure S8), which had the largest amplitude of movement, shows
that this movement consists of a bending and displacement of the two helices, allowing the
opening and closing motion of the loop (Figure 8C). This observation, which is in complete
agreement with the successive steps that make up MaDH catalysis [82], was plotted on the
Wt *M. jannaschii* MalDH relevant conformer sampled during the simulation (Figure 7).

We continued our analysis, by calculating the free energy profile for the open-closed motion
of the helices in the Wt MalDH using a collective variable (sss) generated with configurations
along the path of chain B at 75°C (see Methods). Surprisingly, the free energy profile at 45°C
indicates that the helices remain in a fully closed conformation, with a global minimum at
sss=9 (Figure 8D-E). The amplitude of the open-close motion increases with temperature,
allowing almost unrestricted sampling of sss from 13 to 26 at 75°C, and from 13 to 36 at
90°C (Figure 8D-E). The free energy profiles of the C7 and C7GP mutants were obtained at
60°C to evaluate the open-closed motion of the helices around their $OT_A$. They show the
same amplitude of motion as the WT at 90°C (Figure 9A), except for sss lower than 18, for
which the mutants show a higher free energy. This indicates that the open conformations are
stabilized by the mutations. To analyze the effects of lower temperatures, free energy profiles
were also obtained at 45°C (Figure 9B). In the two mutants, the amplitude of the open-closed
motion is reduced at 45°C, but is still larger than the Wt at this temperature. Even at lower
temperatures, the mutations further stabilize the open conformation. We performed a 0.5µs
of MD simulation of Wt at 45°C starting with the chain A in closed conformation to sample
this state and compare it with the last 0.5µs sampling at 75°C and 90°C. It appears that the
K105 and K217 play a key role in stabilizing the closed conformation by forming SBs with
D66 and E46(B), respectively (Figure 9C, D), respectively. K217 also forms a water-
intermediate interaction with D47(B) (Figure 9C, D). We analyzed that these interactions in
the Wt M. jannaschii MalDH change as a function of temperature (Figure 9D). The interaction with
D50(B) remained similar across different temperatures, only alternating between direct SB
and water-mediated interactions (Figure 9D). We conclude that the destabilization of the
closed state can be explained by the loss of these electrostatic interactions in the C7 and
C7GP mutants because the K105 and K217 present in the Wt have been substituted by
asparagine and tyrosine, respectively, in the C7 and C7GP mutants MalDH.

Here, the data show that the hyperthermophilic Wt *M. jannaschii* MalDH exists mainly as a
tetramer with restricted access to the active site due to its closure by the MbL, an
unfavorable conformation for substrate and coenzyme binding. As the temperature
increases, the motion of the MbL open access to the catalytic site due to the increased
transience of SB, which become more dynamic and less persistent at higher temperatures,
creating favorable conditions for the catalytic cycle to occur. This is consistent with previous
studies, which have shown that under catalytic conditions, LDH has a fast equilibrium
between open and closed conformations [78, 80]. The results show that the substitutions
introduced in the Wt *M. jannaschii* MalDH to create the two "mesophilic" mutants allow them
to adapt their $OT_A$, through the selection of re-shaped conformers with more accessible
catalytic sites at low temperature.

Our previous study showed that the C7 and C7GP mutants has retained a hyper-
thermostable scaffolds. Consistently, we proposed that the decrease of their activity at
temperatures exceeding their $OT_A$ of 60°C and 65°C, respectively, could be due to the
presence of non-competent conformers sampled at these elevated temperatures [32].
According to the two-state models for loss of activity without denaturation, altered enzyme-
substrate or transition-state-like interactions could explain the loss of activity [83-85].
However, this is unlikely to be the case here, as none of the substitutions introduced in C7
and C7GP are within or close to the catalytic site. Instead, our data suggest that higher
temperatures may further stabilize inactive conformations that involve changes in the
catalytic site. This is analyzed in the next paragraph.

**Unproductive conformers beyond optimal temperature for activity.**
To investigate whether the opening-closure motion of the αD/E and α1G/2G helices contributes to the reduced catalytic rate at higher temperatures, we obtained the free energy profiles of C7 and C7GP at 90°C and 75°C, respectively. These profiles show a reduction in the amplitude of motion compared to WT at 90°C (Figure 10), with global minima at sss values of 24 and 39 for C7 and C7GP, respectively. This suggests that higher temperatures reduce the amplitude of the open-closed motion of the helices, although the apo form remains more stable in the open conformation.

We performed MD simulations of C7 and C7GP at 90°C and 75°C, respectively, starting with sss of the chain A at the global minimum of the free energy profiles to allow the equilibration of the MbL. We observed that this loop interacts closely with the loop formed by the residues from 176 to 182, as shown by the number of contacts between the loops (Figure 10 B-C), which are 48 ± 14 and 36 ± 8 for C7 and C7GP, respectively. In the Wt at 90°C, the number of contacts between these loops is 28 ± 13, which is lower than that observed in the mutants. These loops include the catalytic H178 and also the residues R86 and R92, which are involved in transition state stabilization and the substrate recognition, respectively. Furthermore, the increased proximity and interaction between these loops obstructs the catalytic site for the substrate binding. We therefore propose that the increase in the interaction of these loops at higher temperatures led the enzyme to sample unproductive conformations due to the obstruction of the catalytic site and changes in the position of the residues involved in the reaction. This molecular description explains the high increase in Km for OAA and the low catalytic efficiency observed in our previous study [32]. These observations are fully consistent with model suggesting that $OT_A$ depends on the equilibrium between non-competent and competent conformers [83-85].

## Conclusion

Allostery is the mechanism by which enzymes convey the effects of binding at one site to another distal functional site, allowing for fine-tuning of activity. Lactate dehydrogenase is a model enzyme to study allostery, in particular the allosteric regulation by activation [46 and reference therein]. Extensive phylogenetic analysis has revealed that archaeal MalDHs, including those from *Methanococcales*, belong to an intermediate group of sequences (IGS) located in-between the non-allosteric MalDH-type 3 and the allosterically regulated LDHs [38, 46]. Characterization of the enzymes from the IGS has shown that some of them have some latent allosteric capacity, demonstrating that allosteric regulation in LDHs has evolved from an ancestral MalDH-type 3 belonging to the IGS [30, 37, 39, 67]. The extended or
compact tetrameric states of *Methanococcales* MalDH, which mimic the T-R states sampled
by allosteric LDHs, observed here, provide an additional clue to explain the evolutionary
process that led to the emergence of allosteric regulation in the IGS group of MalDH/ LDH.
We propose that the cation-binding sites we observed with MalDHs from Methanococcales
and Methanopyrales corresponds to pseudo-effector binding sites that may have had an
impact on the conformational sampling capacity between an extended and compact state
during evolution of the MalDH/LDH superfamily, but they were not selected as efficient
binding site for activation because the extended state of these enzymes as exemplified by *M.
jannaschii* MalDH is active instead of inactive in allosteric LDHs. We propose that they are
the relics of evolutionnary dead ends mechanisms on the evolutionary route leading to
allosteric LDH from non-allosteric tetrameric MalDHs. Their conservation was very likely due
to a favorable role in conformational stability, probing this hypothesis was out of the scope of
this study.

Since the seminal publications revisiting the link between conformational diversity and
protein evolution [61, 86], there has been a growing body of literature showing that
evolutionary mutations enrich (or depopulate) some transient conformers sampled during the
exploration of the conformational landscape of a given protein, leading to new phenotypes.
This has been well established with respect to the selection of new functionalities and the
enhancement of catalytic efficiency [87-91]. The commonly assumed concept of an
activity/stability trade-off that accounts for thermal adaptation [92] has been challenged by
some studies using adenylate kinase as a model enzyme. These studies report a link
between dynamics and thermal adaptation of enzymes (without functional changes). In
particular, they show that the low activity of the hyperthermophilic enzymes at ambient
temperature is due to the closure of lids, which limit the accessibility of the catalytic site [18,
93, 94].

According to our data, we propose that thermal adaptation and the emergence of latent
allostery in enzymes are tightly embedded processes through intrinsic protein dynamics.
Specifically, thermal adaptation involves shifts in the equilibrium between competent and
non-competent conformational states, with mutations modulating this balance by tuning
structural flexibility rather than stability. This reinforces the view that allosteric potential and
thermal responsiveness share a common dynamic foundation.

**Materials and methods.**

**Structural superposition and representations**
PyMOL was used for representation (http://www.pymol.org/pymol). To perform
homogeneous comparisons between PDB files, chains LDH standards, as monomers A, B, C
and D, respectively located at upper left, upper right, down right and down left positions.

## Crystallization data collection and structure determination

An initial crystallization screening of each MalDH (*A19*, *A34*, *MJC7*, *MJC7GP* and *M. infernus*) was performed at 20 °C using a robotic crystallization system (https://htxlab.embl.org). The protein concentrations tested were from 1.5 to 10 mg.mL⁻¹ in the following buffer: 50 mM Tris-HCl pH7.2, 50 mM NaCl, 0.2 mM NADPH. The optimized crystallization solutions contain: 1) 2.7-2.9 M sodium malonate pH 5 (*A19*), 2) 0.2 M ammonium citrate dibasic, 24% PEG 3350 (*A34*), 3) 19-29% ethylene glycol (*MJC7*), 4) 0.2 M potassium sodium tartrate, 0.1M Bis-tris propane pH 7.5, 16-18% PEG 3350 (*MJC7GP*) and 5) 0.2M ammonium acetate, 0.1M Hepes pH 7.5, 43-48% Methylpentanediol (MPD) (*M. infernus* MalDH). The crystals grew in 24-72 h using the hanging drop vapor diffusion method. The drops were done by mixing 1-2 µL of the protein solution with 1-2 µL of the crystallization solution. The crystals were harvested, soaked in a cryo protection solution and flash-frozen in liquid nitrogen. The cryo protection solution was the mother liquor containing 10% of glycerol (*M. infernus*), 20% of glycerol (*A19*, *A34* and *MJC7GP*) or 35% of ethylene glycol (*MJC7*).

*A19*, *A34*, *MJC7*, *MJC7GP* and *M. infernus* MalDHs diffraction data were collected on FIP2-BM07 or ID30B beamlines at the European Synchrotron Radiation Facility (ESRF) (Grenoble, France). Data sets were indexed and integrated using XDS (*A19*, *M. infernus*) [95] or AutoPROC (*A34*, *MJC7*, *MJC7GP*) [96, 97]. Scaling was done with XSCALE (*A19*, *M. infernus*) [95] or STARANISO (*A34*, *MJC7*, *MJC7GP*) in order to apply an anisotropic correction to the data. STARANISO (http://staraniso.globalphasing.org/cgi-bin/staraniso.cgi) [97]. Automatic PAIRed REFinement protocol (PAIREF) was used to estimate the optimal high-resolution cutoff of the different data sets [98]. Reflection data files were converted in appropriate format required by software packages for crystal structure determination using XDSCONV [95]. Molecular replacement was performed with the CCP4 suite using PHASER [99]. The models used for molecular replacement were the published structures of *Methanocaldococcus jannaschii* LDH (RCSB PDB accession codes: 1HYE, 1HYG) [47] or the calculated Alphafold models on the latch.bio platform (https://console.latch.bio/se/alphafold). The structures were refined with multiple cycles of manual building using COOT [100] and data processing using phenix.refine (PHENIX suite, [101]). The refinement processes included successive rounds of simulated annealing, energy
minimization, coordinate/atomic displacement parameters/occupancy refinements, TLS,
ligand geometry improvement as well as calculation of difference Fourier electron density
maps. Water molecules and ions were added in the late stage of the refinement. Model
quality was validated with MolProbity (http://molprobity.biochem.duke.edu) [102, 103] and
wwPDB validation service (https://validate-rcsb-1.wwpdb.org) [104]. The table of data
collections and refinement statistics in (Table S1) was obtained using phenix.table-one
(PHENIX suite).

As it observed with structure of MalDH or LDHs some regions are not modeled because of
local dynamics within the crystals in particular with the Mobile active site loop [30, 71]).
Accordingly, to perform MD simulations, which require complete structural models
(i.e without any missing residues or atoms) we used Alphafold model building to reconstruct
these areas (https://console.latch.bio/se/alphafold).

Molecular dynamics

All-atom molecular dynamics simulations of the WT *Methanocaldococcus jannaschii* MalDH,
and C7 and C7GP mutants were performed considering apo state. The initial configurations
for the simulations were as follows: the crystallographic structure with PDB code 1HYE for
WT, and the crystal structure obtained in this study for C7. For C7GP, two systems were
simulated—one started from the AlphaFold structure prediction and the other from the C7
crystal structure incorporating the GP mutations. To perform MD simulations, which require
complete structural models (i.e without any missing residues or atoms) we used Alphafold
model building to reconstruct these small missing loops of crystal structures.

Protonation states of titratable residues were estimated using propKa [105] at pH 7. Missing
hydrogen atoms were then added and all crystallographic waters were maintained. The
whole system was immersed in a water box at least 15 Å thick from the protein, and Na⁺ and
Cl⁻ ions were added to render the system electrically neutral and at 0.2M.

All simulations were conducted with GROMACS (version 2022.3) [106]. Long-range
electrostatics were treated with the Particle Mesh Ewald method [107], short-range
interactions truncated at a cutoff radius of 12 Å and a step of 2fs were used. The interactions
were described with the all-atom CHARMM36m force field (charmm36-mar2021 ff) [108] and
water was represented by the standard TIP3P model [109]. The systems were equilibrated
at 348.15K with the following steps: (1) 1000 steps of steepest descent minimization and
100ps of MD with the whole protein restrained at NVT ensemble, (2) 1000 steps of steepest
descent minimization and 1ns of MD with protein backbone restrained at NVT ensemble, (3) 1ns of MD without any restraint at NVT ensemble and (4) 20ns of MD without any restraint at NPT ensemble with constant pressure of 1 atm. (5) MD simulations resting 1µs were performed at 318.15K (45°C) and 348.15K (75°C) for all systems, including at optimum temperatures 363.15K (90°C), 338.15K (65°C), and 333.15 (60°C) for WT, C7 and C7GP, respectively. The last 0.5µs was used for the analysis. In the analysis of SBs, two residues were considered to have a SB interaction when the distance between the center of mass of the oxygens in the acidic side chain and center of mass of the nitrogen in the basic side chain is less than 0.5nm.

Well-tempered metadynamics simulations [110] were performed with PLUMED [111, 112] to obtain the free energy profiles along the helices αD/E and α1G/2G movement of open and closed. A pathway collective variable (CV) [113] was used to describe the helices conformation. The CV measures the progress along a set of 45 frames obtained from an unrestrained simulation of WT chain B at 75°C, which exhibited the widest range of sampled conformations. This CV includes the Cα atoms from residues 94 to 111 and 206 to 225, with a lambda value of 290 applied. The well-tempered metadynamics simulations started from the configurations at 1µs of its respective system and temperature, and it was activated on p1.sss with Gaussians deposited every 500-time steps (1 ps) with initial height of 1.0 kJ mol⁻¹, width of 0.75 and a bias factor of 15.0. A lower wall was included to maintain p1.sss > 2.5 with force constant of 500 kJ mol⁻¹ nm⁻¹ and an upper wall to maintain p1.zzz < 0.02 with force constant of 1000 kJ mol⁻¹ nm⁻¹, these walls were applied to prevent loose of secondary structure. The convergence was considered reached when the Gaussian hills was less than 0.005 kJ mol⁻¹ for more than 5 ns and the shortest run was of 208 ns. The variable p1.sss was subjected to the operation sss= -1 * p1.sss + 50 to invert its direction, so it is displayed from closed to open in the graphics.

Extra simulations were conducted using as starting points configurations obtained from metadynamics simulations, with the reaction coordinates set at the free energy minimum values derived from profiles obtained at 75°C. For C7, simulations were performed at 363.15 K (90°C), and for C7GP at 348.15 K (75°C), each lasting 1 µs to enable the equilibration of the loop formed by the residues from 84 to 93 at this helix conformation and the last 0.5 µs of the MD simulation were used for analysis. Additionally, for WT, simulations were carried out at 318.15 K (45°C) based on the profile obtained at 45°C, with a simulation duration of 0.5 µs that was used for analysis considering that it already started from an equilibrated structure.
**Protein expression and purification.**

Overexpression system, purification procedure and measurements for detecting enzymatic activity of Methanococcales MalDHs and mutants was described previously [32, 114]. The stock proteins (10 mg/mL) were stored at 4°C in a buffer containing 50 mM Tris-HCl buffered at pH 7.2 supplemented with 100 mM KCl.

**Acknowledgements**

The authors also acknowledge funding by Agence Nationale de la Recherche (ANR) grant to DM (AlloSpace ANR-21-CE44-0034-01) and grant to CBA (Thermadapt ANR-22-CE02-0027) . This work used the platforms of the Grenoble Instruct center (ISBG; UMS 3518 CNRS-CEA-UJF-EMBL) with support from FRISBI (ANR-10-INSB-05-02) and GRAL (ANR-10-LABX-49-01) within the Grenoble Partnership for Structural Biology (PSB).

FS acknowledges the financial support by the Initiative d'Excellence program from the French State (Grant DYNAMO, ANR-11-LABX-0011-01, and CACSICE, ANR-11-EQPX-0008). The work was performed using HPC resources from GENCI [CINES, TGCC, IDRIS] (grant X20206818) and from LBT.

We acknowledge the ESRF (Grenoble, France) for provision of synchrotron radiation
beamtime on beamline BM07-FIP2, supported by the French ANR PIA3 (France
2030) EquipEx+ project MAGNIFIX under grant agreement ANR-21-ESRE-0011.
We thank Dr Sylvain Engilberge for support during the experiment.

**Data availability**

The structural coordinates are deposited at the RCSB PDB data bank under the accession numbers: 9SD3, 9S3K, 9S3Y,9SA7 and 9SC9.

The molecular dynamics trajectories are accessible at https://zenodo.org

10.5281/zenodo.14237681

CRediT authorship contribution statement
**Caroline Simões Pereira**: Molecular dynamics simulation methodology, investigation, formal analysis, writing original draft. **Sandrine Coquille**: Crystallization and crystallography methodology, investigation, formal analysis. **Céline Brochier-Armanet**: Funding acquisition, conceptualisation, review and editing. **Fabio Sterpone**: Molecular dynamics simulation methodology, formal analysis, supervision, review and editing. **Dominique Madern**: Funding acquisition, conceptualization, formal analysis, writing original draft, supervision.

**Declaration of competing interest**

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this manuscript.

**References**

[1] Rothschild, L. J., Mancinelli, R. L., (2001). Life in extreme environments. *Nature*, **409**(6823), 1092–1101. https://doi.org/10.1038/35059215

[2] Pikuta, E. V., Hoover, R. B., Tang, J., (2007). Microbial extremophiles at the limits of life. *Crit Rev Microbiol.* **33**(3), 183–209. https://doi.org/10.1080/10408410701451948

[3] Merino, N., Aronson, H. S., Bojanova, D. P., Feyhl-Buska, J., Wong, M. L., Zhang, S., Giovannelli, D., (2019). Living at the Extremes: Extremophiles and the Limits of Life in a Planetary Context. *Front microbiol.* **10**, 780. https://doi.org/10.3389/fmicb.2019.00780

[3] Rothschild, L.J., Mancinelli, R.L., (2001). Life in extreme environments. *Nature*. **409**(6823):1092-1101. doi:10.1038/35059215

[4] Ando, N., Barquera, B., Bartlett, D.H., Boyd, E., Burnim, A.A., Byer, A.S., Colman, D., Gillilan, R.E., Gruebele, M., Makhatadze, G., Royer, C.A., Shock, E., Wand, A.J., Watkins, M.B., (2021). The molecular basis for life in extreme environments. *Annu Rev Biophys* **50**, 343-372. https://doi: 10.1146/annurev-biophys-100120-072804.

[5] Carré, L., Zaccai, G., Delfosse, X., Girard, E., Franzetti, B., (2022). Relevance of earth-bound extremophiles in the search for extraterrestrial life. *Astrobiology* **22** (3), 322-367. https://doi: 10.1089/ast.2021.0033.

[6] Bogin, O., Levin, I., Hacham, Y., Tel-Or, S., Peretz, M., Frolow, F., Burstein, Y., (2002). Structural basis for the enhanced thermal stability of alcohol dehydrogenase mutants from
the mesophilic bacterium *Clostridium beijerinckii*: contribution of salt bridging. *Protein Sci* **11**(11), 2561-2574. https://doi.org: 10.1110/ps.0222102.

[7] Dalhus, B., Saarinen, M., Sauer, U. H., Eklund, P., Johansson, K., Karlsson, A., Ramaswamy, S., Bjørk, A., Synstad, B., Naterstad, K., Sirevåg, R., Eklund, H., (2002). Structural basis for thermophilic protein stability: structures of thermophilic and mesophilic malate dehydrogenases. *J. Mol. Biol.* **318**(3), 707-721. https://doi.org/10.1016/S0022-2836(02)00050-5.

[8] Stokke, R., Karlström, M., Yang, N., Leiros, I., Ladenstein, R., Birkeland, N.K., Steen, I.H., (2007). Thermal stability of isocitrate dehydrogenase from Archaeoglobus fulgidus studied by crystal structure analysis and engineering of chimers. *Extremophiles* **11**(3), 481-493. https://doi.org: 10.1007/s00792-006-0060-z.

[9] Coquelle, N., Fioravanti, E., Weik, M., Vellieux, F., Madern, D., (2007). Activity, stability and structural studies of lactate dehydrogenases adapted to extreme thermal environments. *J. Mol. Biol.* **374** (2), 547-562. https://doi.org/10.1016/j.jmb.2007.09.049.

[10] Peng, H.L., Egawa, T., Chang, E., Deng, H., Callender, R., (2015). Mechanism of thermal adaptation in the Lactate dehydrogenases. *J Phys Chem B.* **119**(49), 15256-15262.
https://doi.org: 10.1021/acs.jpcb.5b09909.

[11] Katava, M., Kalimeri, M., Stirnemann, G., Sterpone, F., (2016). Stability and Function at High Temperature. What Makes a Thermophilic GTPase Different from Its Mesophilic Homologue. *J Phys Chem B.* **120**(10), 2721-2730. https://doi.org/10.1021/acs.jpcb.6b00306.

[12] Xia, Y.L., Sun, J.H., Ai, S.M., Li, Y., Du, X., Sang, P., Yang, L.Q., Fu, Y.X., Liu, S.Q., (2018). Insights into the role of electrostatics in temperature adaptation: a comparative study of psychrophilic, mesophilic, and thermophilic subtilisin-like serine proteases. *RSC Adv.* **8**(52), 29698-29713. https://doi.org: 10.1039/c8ra05845h.

[13] Maffucci, I., Laage, D., Stirnemann, G., Sterpone, F., (2020). Differences in thermal structural changes and melting between mesophilic and thermophilic dihydrofolate reductase enzymes. *Phys Chem Chem Phys.* **22**(33), 18361-18373. https://doi.org: 10.1039/d0cp02738c.
[14] Fusco, G., Bemporad, F., Chiti, F., Dobson, C.M., De Simone, A., (2022). The role of structural dynamics in the thermal adaptation of hyperthermophilic enzymes. *Front Mol Biosci.* **9**,981312. https://doi: 10.3389/fmolb.2022.

[15] Gaucher, E.A., Thomson, J.M., Burgan, M.F., Benner, S.A., (2003). Inferring the palaeoenvironment of ancient bacteria on the basis of resurrected proteins. *Nature*. **425** (6955), 285-258. https://doi: 10.1038/nature01977.

[16] Harms, M. J., Thornton, J.W., (2010). Analyzing protein structure and function using ancestral gene reconstruction. *Curr Opin Struct Biol.* **20**(3), 360-366. https://doi: 10.1016/j.sbi.2010.03.005.

[17] Perez-Jimenez, R., Inglés-Prieto, A., Zhao, Z.M., Sanchez-Romero, I., Alegre-Cebollada, J., Kosuri, P., Garcia-Manyes, S., Kappock, T.J., Tanokura, M., Holmgren, A., Sanchez-Ruiz, J.M., Gaucher, E.A., Fernandez, J.M., (2011). Single-molecule paleoenzymology probes the chemistry of resurrected enzymes. *Nat Struct Mol Biol.* **18**(5),592-596. https://doi: 10.1038/nsmb.2020.

[18] Nguyen, V., Wilson, C., Hoemberger, M., Stiller, J.B., Agafonov, R.V., Kutter, S., English, J., Theobald, D.L., Kern, D., (2017). Evolutionary drivers of thermoadaptation in enzyme catalysis. *Science* **355**(6322), 289-294. https://doi: 10.1126/science.aah3717.

[19] Blanquart, S., Groussin, M., Le Roy, A., Szöllosi, G.J., Girard, E., Franzetti, B., Gouy, M., Madern, D., (2021). Resurrection of ancestral malate dehydrogenases reveals the evolutionary history of halobacterial proteins: deciphering gene trajectories and changes in biochemical properties. *Mol Biol Evol* **38**(9), 3754-3774. https://doi: 10.1093/molbev/msab146.

[20] Pinney, M.M., Mokhtari, D.A., Akiva, E., Yabukarski, F., Sanchez, D.M., Liang, R., Doukov, T., Martinez, T.J., Babbitt, P.C., Herschlag, D., (2012). Parallel molecular mechanisms for enzyme temperature adaptation. *Science* **371**(6533):eaay2784. https://doi: 10.1126/science.aay2784.

[21] Hueting, D.A., Vanga, S.R., Syrén, P.O., (2022). Thermoadaptation in an ancestral diterpene cyclase by altered loop stability. *J Phys Chem B.* **126**(21), 3809-3821. https://doi: 10.1021/acs.jpcb.1c10605.
[22] Lu, Z., Xia, R., Zhang, S., Pan, J., Liu, Y., Wolf, Y.I., Koonin, E.V., Li, M., (2024). Evolution of optimal growth temperature in Asgard archaea inferred from the temperature dependence of GDP binding to EF-1A. *Nat Commun.* **15**(1),515. https://doi: 10.1038/s41467-024-44806-1.

[23] Zeldovich, K. B., Berezovsky, I. N., Shakhnovich, E. I., (2007). Protein and DNA sequence determinants of thermophilic adaptation. *PLoS computational biology* **3**(1), e5. https://doi.org/10.1371/journal.pcbi.0030005

[24] Boussau, B., Blanquart, S., Necsulea, A., Lartillot, N., Gouy, M., (2008). Parallel adaptations to high temperatures in the Archaean eon. *Nature* **456**(7224), 942–945.
https://doi.org/10.1038/nature07393.

[25] Smole, Z., Nikolic, N., Supek, F., Šmuc, T., Sbalzarini, I. F., Krisko, A., (2011). Proteome sequence features carry signatures of the environmental niche of prokaryotes. *BMC evolutionary biology* **11**, 26. https://doi.org/10.1186/1471-2148-11-26.

[26] Fontanillas, E., Galzitskaya, O. V., Lecompte, O., Lobanov, M. Y., Tanguy, A., Mary, J., Girguis, P. R., Hourdez, S., Jollivet, D., (2017). Proteome evolution of deep-sea hydrothermal vent alvinellid polychaetes supports the ancestry of thermophily and subsequent adaptation to cold in some lineages. *Genome Biol Evol.* **9**(2), 279–296.
https://doi.org/10.1093/gbe/evw298.

[27] Kurokawa, M., Higashi, K., Yoshida, K., Sato, T., Maruyama, S., Mori, H., Kurokawa, K., (2023). Metagenomic Thermometer. *DNA research* **30** (6), dsad024
https://doi.org/10.1093/dnares/dsad024.

[28] Groussin, M., Gouy, M., (2011). Adaptation to environmental temperature is a major determinant of molecular evolutionary rates in archaea. *Mol. Biol. Evol.* **28**(9), 2661–2674.
https://doi.org/10.1093/molbev/msr098

[29] Lecocq, M., Groussin, M., Gouy, M., Brochier-Armanet, C., (2021). The molecular determinants of thermoadaptation: methanococcales as a case study. *Mol. Biol. Evol.* **38**(5), 1761–1776. https://doi.org/10.1093/molbev/msaa312

[30] Coquille, S., Pereira, C. S., Roche, J., Santoni, G., Engilberge, S., Brochier-Armanet, C., Girard, E., Sterpone, F., Madern, D., (2025). Allostery and Evolution: A molecular journey
through the structural and dynamical landscape of an enzyme super family. *Mol Biol Evol.* **42**(1), msae265. https://doi.org/10.1093/molbev/msae265

[31] Prondzinsky, P., Toyoda, S., McGlynn, S. E., (2023). The methanogen core and pangenome: conservation and variability across biology's growth temperature extremes. *DNA research* **30**(1), dsac048. https://doi.org/10.1093/dnares/dsac048

[32] Madern, D., Halgand, F., Houée-Levin, C., Dufour, A. B., Coquille, S., Ansanay-Alex, S., Sacquin-Mora, S., Brochier-Armanet, C., (2024). The characterization of ancient methanococcales malate dehydrogenases reveals that strong thermal stability prevents unfolding under intense γ-irradiation. *Mol. Biol. Evol.* **41**(12), msae231.
https://doi.org/10.1093/molbev/msae231

[33] Richard, S. B., Madern, D., Garcin, E., Zaccai, G., (2000). Halophilic adaptation: novel solvent protein interactions observed in the 2.9 and 2.6 Å resolution structures of the wild type and a mutant of malate dehydrogenase from Haloarcula marismortui. *Biochemistry* **39**(5), 992–1000. https://doi.org/10.1021/bi991001a

[34] Irimia, A., Vellieux, F. M., Madern, D., Zaccaï, G., Karshikoff, A., Tibbelin, G., Ladenstein, R., Lien, T., Birkeland, N. K., (2004). The 2.9Å resolution crystal structure of malate dehydrogenase from Archaeoglobus fulgidus: mechanisms of oligomerisation and thermal stabilisation. *J. Mol. Biol.* **335**(1), 343–356. https://doi.org/10.1016/j.jmb.2003.10.054

[35] Coquelle, N., Talon, R., Juers, D. H., Girard, E., Kahn, R., Madern, D., (2010). Gradual adaptive changes of a protein facing high salt concentrations. *J. Mol. Biol.* **404**(3), 493–505. https://doi.org/10.1016/j.jmb.2010.09.055.

[36] Kalimeri, M., Girard, E., Madern, D., Sterpone, F., (2014). Interface matters: the stiffness route to stability of a thermophilic tetrameric malate dehydrogenase. *PloS one*, **9**(12), e113895. https://doi.org/10.1371/journal.pone.0113895

[37] Roche, J., Girard, E., Mas, C., Madern, D., (2019). The archaeal LDH-like malate dehydrogenase from Ignicoccus islandicus displays dual substrate recognition, hidden allostery and a non-canonical tetrameric oligomeric organization. *J. Struct. Biol.* **208**(1), 7–17. https://doi.org/10.1016/j.jsb.2019.07.006
[38] Brochier-Armanet, C., Madern, D., (2021). Phylogenetics and biochemistry elucidate the evolutionary link between L-malate and L-lactate dehydrogenases and disclose an intermediate group of sequences with mix functional properties. *Biochimie* **191**, 140-153.
https://doi: 10.1016/j.biochi.2021.08.004.

[39] Iorio, A., Brochier-Armanet, C., Mas, C., Sterpone, F., Madern, D., (2022). Protein conformational space at the edge of allostery: turning a non allosteric malate dehydrogenase into an "allosterized" enzyme using evolution-guided punctual mutations. *Mol. Biol. Evol.* **39**(9), msac186. https://doi.org/10.1093/molbev/msac186.

[40] Talon, R., Coquelle, N., Madern, D., Girard, E., (2014). An experimental point of view on hydration/solvation in halophilic proteins. *Frontiers in microbiology* **5**, 66.
https://doi.org/10.3389/fmicb.2014.00066

[41] McCue, W. M., Finzel, B. C., (2021). Structural characterization of the human cytosolic malate dehydrogenase I. *ACS omega* **7**(1), 207–214.
https://doi.org/10.1021/acsomega.1c04385

[42] Birktoft, J. J., Fernley, R. T., Bradshaw, R. A., Banaszak, L. J., (1982). Amino acid sequence homology among the 2-hydroxy acid dehydrogenases: mitochondrial and cytoplasmic malate dehydrogenases form a homologous system with lactate dehydrogenase. *Proc. Natl. Acad. Sci. USA* **79**(20), 6166–6170. https://doi.org/10.1073/pnas.79.20.6166.

[43] Madern, D., (2002). Molecular evolution within the L-malate and L-lactate dehydrogenase super-family. *J. Mol. Evol*, **54**(6), 825–840. https://doi.org/10.1007/s00239-001-0088-8.

[44] Madern, D., Cai, X., Abrahamsen, M. S., Zhu, G., (2004). Evolution of Cryptosporidium parvum lactate dehydrogenase from malate dehydrogenase by a very recent event of gene duplication. *Mol. Biol. Evol*, **21**(3), 489–497. https://doi.org/10.1093/molbev/msh042.

[45] Boucher, J. I., Jacobowitz, J. R., Beckett, B. C., Classen, S., Theobald, D. L., (2014). An atomic-resolution view of neofunctionalization in the evolution of apicomplexan lactate dehydrogenases. *ELife* **3** e02304. https://doi.org/10.7554/eLife.02304

[46] Robin, A. Y., Brochier-Armanet, C., Bertrand, Q., Barette, C., Girard, E., Madern, D. (2023). Deciphering evolutionary trajectories of lactate dehydrogenases provides new in-
sights into allostery. *Mol. Biol. Evol.* **40**(10), msad223.

https://doi.org/10.1093/molbev/msad223

[47] Lee, B. I., Chang, C., Cho, S. J., Eom, S. H., Kim, K. K., Yu, Y. G., Suh, S. W., (2001). Crystal structure of the MJ0490 gene product of the hyperthermophilic archaebacterium Methanococcus jannaschii, a novel member of the lactate/malate family of dehydrogenases. *J. Mol. Biol.* **307**(5), 1351–1362. https://doi.org/10.1006/jmbi.2001.4532

[48] Karshikoff, A., Ladenstein, R., (2001). Ion pairs and the thermotolerance of proteins from hyperthermophiles: a "traffic rule" for hot roads. *Trends Biochem Sci.* **26**(9), 550–556.
https://doi.org/10.1016/s0968-0004(01)01918-1

[49] Kumar, S., Tsai, C.J., Ma, B., Nussinov, R., (2000). Contribution of salt bridges toward protein thermostability. *J. Biomol. Struct. Dyn.* **17** Suppl 1, 79-85. https://doi.org/10.1080/07391102.2000.10506606.

[50] Ge, M., Xia, X.Y., Pan, X.M., (2008). Salt bridges in the hyperthermophilic protein Ssh10b are resilient to temperature increases. *J Biol Chem.* **283**(46):31690-31696.
https://doi.org/10.1074/jbc.M805750200.

[51] Boucher, L., Somani, S., Negron, C., Ma, W., Jacobs, S., Chan, W., Malia, T., Obmolova, G., Teplyakov, A., Gilliland, G.L., Luo, J., (2022). Surface salt bridges contribute to the extreme thermal stability of an FN3-like domain from a thermophilic bacterium. *Proteins* **90**(1), 270-281. https://doi.org/10.1002/prot.26218.

[52] Katava, M., Marchi, M., Madern, D., Sztucki, M., Maccarini, M., Sterpone, F., (2020). Temperature Unmasks Allosteric Propensity in a Thermophilic Malate Dehydrogenase via Dewetting and Collapse. *J. Phys. Chem. B* **124**(6), 1001–1008.
https://doi.org/10.1021/acs.jpcb.9b10776.

[53] Costantini, S., Colonna, G., Facchiano, A. M., (2008). ESBRI: a web server for evaluating salt bridges in proteins. *Bioinformation*, **3**(3), 137–138.
https://doi.org/10.6026/97320630003137

[54] Willard, L., Ranjan, A., Zhang, H., Monzavi, H., Boyko, R.F., Sykes, B.D., Wishart, D.S., (2003). VADAR: a web server for quantitative evaluation of protein structure quality. *Nucleic Acids Res.* **31**(13), 3316-3319. https://doi.org/10.1093/nar/gkg565.
[55] Cea, P.A., Pérez, M., Herrera, S.M., Muñoz, S.M., Fuentes-Ugarte, N., Coche-Miranda, J., Maturana, P., Guixé, V., Castro-Fernandez, V., (2024). Deciphering structural traits for thermal and kinetic stability across protein family evolution through ancestral sequence reconstruction. *Mol Biol Evol* **41**(7):msae127. https://doi: 10.1093/molbev/msae127.

[56] Katava, M., Maccarini, M., Villain, G., Paciaroni, A., Sztucki, M., Ivanova, O., Madern, D., Sterpone, F., (2017). Thermal activation of ‘allosteric-like’ large-scale motions in a eukaryotic Lactate Dehydrogenase. *Sci. Rep.* **7**, 41092. https://doi.org/10.1038/srep41092.

[57] Donald, J.E., Kulp, D.W., DeGrado, W. F., (2011). Salt bridges: geometrically specific, designable interactions. *Proteins* **79**(3), 898-915. https://doi: 10.1002/prot.22927.

[58] Sammond, D. W., Kastelowitz, N., Himmel, M. E., Yin, H., Crowley, M. F., Bomble, Y. J., (2016). Comparing residue clusters from thermophilic and mesophilic enzymes reveals adaptive mechanisms. *PloS one* **11**(1), e0145848.
https://doi.org/10.1371/journal.pone.0145848

[59] Feller G., (2010). Protein stability and enzyme activity at extreme biological temperatures. *J. Phys. Condens Matter.* **22**(32), 323101. https://doi.org/10.1088/0953-8984/22/32/323101

[60] DePristo, M. A., Weinreich, D. M., Hartl, D. L., (2005). Missense meanderings in sequence space: a biophysical view of protein evolution. *Nat Rev Genet.* **6**(9), 678–687.
https://doi.org/10.1038/nrg1672

[61] Tokuriki, N., Tawfik, D. S., (2009). Protein dynamism and evolvability. *Science* **324**(5924), 203–207. https://doi.org/10.1126/science.1169375.

[62] Missimer, J.H., Steinmetz, M.O., Baron, R., Winkler, F.K., Kammerer, R.A., Daura, X., van Gunsteren, W. F., (2007). Configurational entropy elucidates the role of salt-bridge networks in protein thermostability. *Protein Sci.* **16**(7),1349-1359. https://doi: 10.1110/ps.062542907.

[63] Kalimeri, M., Rahaman, O., Melchionna, S., Sterpone, F., (2013). How conformational flexibility stabilizes the hyperthermophilic elongation factor G-domain. *J. Phys. Chem. B.* **117**(44), 13775–13785. https://doi.org/10.1021/jp407078z.
[64] Karshikoff, A., Nilsson, L., Ladenstein, R., (2015). Rigidity versus flexibility: the dilemma of understanding protein thermal stability. FEBS J. **282**(20), 3899-3917. https://doi.org/10.1111/febs.13343.

[65] Borges, B., Gallo, G., Coelho, C., Negri, N., Maiello, F., Hardy, L., Würtele, M., (2021). Dynamic cross correlation analysis of Thermus thermophilus alkaline phosphatase and determinants of thermostability. *Biochim Biophys Acta Gen Subj* **1865**(7), 129895. https://doi.org/10.1016/j.bbagen.2021.129895.

[66] Madern, D., Ebel, C., Mevarech, M., Richard, S. B., Pfister, C., Zaccai, G., (2000). Insights into the molecular relationships between malate and lactate dehydrogenases: structural and biochemical properties of monomeric and dimeric intermediates of a mutant of tetrameric L-[LDH-like] malate dehydrogenase from the halophilic archaeon Haloarcula marismortui. *Biochemistry* **39**(5), 1001–1010. https://doi.org/10.1021/bi9910023

[67] Bertrand, Q., Coquille, S., Iorio, A., Sterpone, F., Madern, D., (2023). Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases. *J Struct Biol.* **215**(4), 108039. https://doi.org/10.1016/j.jsb.2023.108039.

[68] Shima, S., Thauer, R. K., Ermler, U., (2004). Hyperthermophilic and salt-dependent formyltransferase from Methanopyrus kandleri. *Biochem Soc Trans.* **32**(2), 269-272. https://doi.org/10.1042/bst0320269

[69] Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A. J., Bambrick, J., Bodenstein, S. W., Evans, D. A., Hung, C. C., O'Neill, M., Reiman, D., Tunyasuvunakool, K., Wu, Z., Žemgulytė, A., Arvaniti, E., Beattie, C., ... Jumper, J. M. (2024). Accurate structure prediction of biomolecular interactions with AlphaFold 3. *Nature*, **630**(8016), 493–500. https://doi.org/10.1038/s41586-024-07487-w

[70] Lisi, G. P., Currier, A. A., Loria, J. P., (2018). Glutamine hydrolysis by imidazole glycerol phosphate synthase displays temperature dependent allosteric activation. *Front Mol Biosci.* **5**, 4. https://doi.org/10.3389/fmolb.2018.00004.

[71] Iorio, A., Roche, J., Engilberge, S., Coquelle, N., Girard, E., Sterpone, F., Madern, D., (2021). Biochemical, structural and dynamical studies reveal strong differences in the ther-
mal-dependent allosteric behavior of two extremophilic lactate dehydrogenases. *J. Struct. Biol.* **213**(3), 107769. https://doi.org/10.1016/j.jsb.2021.107769.

[72] Maschietto, F., Morzan, U. N., Tofoleanu, F., Gheeraert, A., Chaudhuri, A., Kyro, G. W., Nekrasov, P., Brooks, B., Loria, J. P., Rivalta, I., Batista, V. S., (2023). Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase. *Nat Commun.* **14**(1), 2239. https://doi.org/10.1038/s41467-023-37956-1.

[73] Djulbegovic, M. B., Gonzalez, D. J. T., Laratelli, L., Antonietti, M., Uversky, V. N., Shields, C. L., Karp, C. L., (2025). A Computational Approach to Characterize the Protein S-Mer Tyrosine Kinase (PROS1-MERTK) Protein-Protein Interaction Dynamics. *Cell Biochem Biophys*, **83**(2), 1743-1755. https://doi.org/10.1007/s12013-024-01582-5

[74] Ohnuki, J., Okazaki, K. I., (2024). Integration of alphafold with molecular dynamics for efficient conformational sampling of transporter protein NarK. *J Phys Chem B.* **128**(31), 7530-7537. https://doi.org/10.1021/acs.jpcb.4c02726

[75] Agwora, D., Gufu, B., Marik, T., Papp, T., Vágvölgyi, C., Kredics, L., Tyagi, C., (2025). Structural elucidation of four fungal hydrophobins belonging to classes I and II: Results from Alphafold and accelerated molecular dynamics simulations. *Comput Struct Biotechnol J.* **27**, 1067-1080. https://doi.org/10.1016/j.csbj.2025.03.015

[76] Cui, S., Dasgupta, S., Yagi, S., Kimura, M., Furukawa, R., Tagami, S., Akanuma, S., (2025). Insights into the low-temperature adaptation of an enzyme as studied through ancestral sequence reconstruction. *Protein Sci.* **34**(3), e70071. https://doi.org/10.1002/pro.70071

[77] Qiu, L., Gulotta, M., Callender, R., (2007). Lactate dehydrogenase undergoes a substantial structural change to bind its substrate. *Biophysical J.* **93**(5), 1677-1686. https://doi.org/10.1529/biophysj.107.109397

[78] Reddish, M. J., Callender, R., Dyer, R. B., (2017). Resolution of submillisecond kinetics of multiple reaction pathways for lactate dehydrogenase. *Bioph J.* **112**(9), 1852-1862. https://doi.org/10.1016/j.bpj.2017.03.031

[79] Suzuki, K., Maeda, S., Morokuma, K., (2019). Roles of closed- and open-loop conformations in large-scale structural transitions of l-lactate dehydrogenase. *ACS omega*, **4**(1), 1178-1184. https://doi.org/10.1021/acsomega.8b02813.
[80] Blacker, T. S., Duchen, M. R., Bain, A. J., (2023). NAD(P)H binding configurations revealed by time-resolved fluorescence and two-photon absorption. *Biophys J.* **122**(7), 1240–1253. https://doi.org/10.1016/j.bpj.2023.02.014

[81] Taguchi, H., (2017). The Simple and Unique Allosteric Machinery of Thermus caldophilus lactate dehydrogenase, structure-function relationship in bacterial allosteric LDHs. *Adv. Exp. Med. Biol.* **925**, 117-145. https://doi.org/10.1007/55842016171.

[82] Shimozawa, Y., Himiyama, T., Nakamura, T., Nishiya, Y., (2021). Structural analysis and reaction mechanism of malate dehydrogenase from Geobacillus stearothermophilus. *J Biochem.* **170**(1), 97–105. https://doi.org/10.1093/jb/mvab027

[83] Daniel, R. M., Danson, M. J., (2010). A new understanding of how temperature affects the catalytic activity of enzymes. *TIBS.* **35**(10), 584–591.
https://doi.org/10.1016/j.tibs.2010.05.001.

[84] Åqvist, J., Sočan, J., Purg, M., (2020). Hidden conformational states and strange temperature optima in enzyme catalysis. *Biochemistry* **59**(40), 3844–3855.
https://doi.org/10.1021/acs.biochem.0c00705.

[85] Walker, E. J., Hamill, C. J., Crean, R., Connolly, M. S., Warrender, A. K., Kraakman, K. L., Prentice, E. J., Steyn-Ross, A., Steyn-Ross, M., Pudney, C. R., van der Kamp, M. W., Schipper, L. A., Mulholland, A. J., Arcus, V. L., (2024). Cooperative conformational transitions underpin the activation heat capacity in the temperature dependence of enzyme catalysis. *ACS catalysis* **14**(7), 4379–4394. https://doi.org/10.1021/acscatal.3c05584.

[86] James, L. C., Tawfik, D. S., (2003). Conformational diversity and protein evolution--a 60-year-old hypothesis revisited. *Trends Biochem Sci.* **28**(7), 361–368.
https://doi.org/10.1016/S0968-0004(03)00135-X

[87] Campbell, E., Kaltenbach, M., Correy, G. J., Carr, P. D., Porebski, B. T., Livingstone, E. K., Afriat-Jurnou, L., Buckle, A. M., Weik, M., Hollfelder, F., Tokuriki, N., Jackson, C. J., (2016). The role of protein dynamics in the evolution of new enzyme function. *Nat Chem Biol.* **12**(11), 944–950. https://doi.org/10.1038/nchembio.2175.
[88] Hong, N. S., Petrović, D., Lee, R., Gryn'ova, G., Purg, M., Saunders, J., Bauer, P., Carr, P. D., Lin, C. Y., Mabbitt, P. D., Zhang, W., Altamore, T., Easton, C., Coote, M. L., Kamerlin, S. C. L., Jackson, C. J., (2018). The evolution of multiple active site configurations in a designed enzyme. *Nat commun.* **9**(1), 3900. https://doi.org/10.1038/s41467-018-06305-y.

[89] Kaczmarski, J. A., Mahawaththa, M. C., Feintuch, A., Clifton, B. E., Adams, L. A., Goldfarb, D., Otting, G., Jackson, C. J., (2020). Altered conformational sampling along an evolutionary trajectory changes the catalytic activity of an enzyme. *Nat Comm.* **11**(1), 5945. https://doi.org/10.1038/s41467-020-19695-9.

[90] Otten, R., Pádua, R. A. P., Bunzel, H. A., Nguyen, V., Pitsawong, W., Patterson, M., Sui, S., Perry, S. L., Cohen, A. E., Hilvert, D., Kern, D., (2020). How directed evolution reshapes the energy landscape in an enzyme to boost catalysis. *Science* **370**(6523), 1442–1446. https://doi.org/10.1126/science.abd3623.

[91] St-Jacques, A. D., Rodriguez, J. M., Eason, M. G., Foster, S. M., Khan, S. T., Damry, A. M., Goto, N. K., Thompson, M. C., Chica, R. A., (2023). Computational remodeling of an enzyme conformational landscape for altered substrate selectivity. *Nat Commun.* **14**(1), 6058. https://doi.org/10.1038/s41467-023-41762-0.

[92] Somero G. N., (2004). Adaptation of enzymes to temperature: searching for basic "strategies". *Comp Biochem Physiol B Biochem Mol Biol.* **139**(3), 321–333. https://doi.org/10.1016/j.cbpc.2004.05.003

[93] Saavedra, H. G., Wrabl, J. O., Anderson, J. A., Li, J., Hilser, V. J., (2018). Dynamic allostery can drive cold adaptation in enzymes. *Nature* **558**(7709), 324–328. https://doi.org/10.1038/s41586-018-0183-2

[94] Wolf-Watz, M., Thai, V., Henzler-Wildman, K., Hadjipavlou, G., Eisenmesser, E.Z., Kern, D., (2004) Linkage between dynamics and catalysis in a thermophilic-mesophilic enzyme pair. *Nat. Struct. Mol. Biol.* **11**(10),945-949. https://doi: 10.1038/nsmb821.

[95] Kabsch, W., (2010). XDS. *Acta Crystallogr. D.* **66**,125–132.
https://doi.org/10.1107/S0907444909047337.
[96] Vonrhein, C., Flensburg, C., Keller, P., Sharff, A., Smart, O., Paciorek, W., Womack, T., Bricogne, G., (2011). Data processing and analysis with the autoPROC toolbox. *Acta Crystallogr D Biol Crystallogr.* **67**(Pt 4), 293–302.
https://doi.org/10.1107/S0907444911007773

[97] Tickle, I.J., Flensburg, C., Keller, P., Paciorek, W., Sharff, A., Vonrhein, C., Bricogne, G. (2018). STARANISO. Cambridge, United Kingdom: Global Phasing Ltd.

[98] Malý, M., Diederichs, K., Dohnálek, J., Kolenko, P., (2020). Paired refinement under the control of *PAIREF*. *IUCrJ*, **7**, 681–692. https://doi.org/10.1107/S2052252520005916

[99] McCoy, A. J., Grosse-Kunstleve, R. W., Adams, P. D., Winn, M. D., Storoni, L. C., Read, R.J., (2007). Phaser crystallographic software. *J Appl Crystallogr.* **40**(Pt 4), 658–674.
https://doi.org/10.1107/S0021889807021206

[100] Emsley, P., Lohkamp, B., Scott, W. G., Cowtan, K., (2010). Features and development of Coot. *Acta Cryst.* **D**. **66**, 486–501. https://doi.org/10.1107/S0907444910007493.

[101] Adams, P. D., Afonine, P. V., Bunkóczi, G., Chen, V. B., Davis, I. W., Echols, N., Headd, J. J., Hung, L. W., Kapral, G. J., Grosse-Kunstleve, R. W., McCoy, A. J., Moriarty, N. W., Oeffner, R., Read, R. J., Richardson, D. C., Richardson, J. S., Terwilliger, T. C., Zwart, P. H., (2010). PHENIX: a comprehensive Python-based system for macromolecular structure solution. *Acta Crystallogr D Biol Crystallogr.* **66**, 213–221.
https://doi.org/10.1107/S0907444909052925

[102] Davis, I. W., Leaver-Fay, A., Chen, V. B., Block, J. N., Kapral, G. J., Wang, X., Murray, L. W., Arendall, W. B., 3rd, Snoeyink, J., Richardson, J. S., Richardson, D. C., (2007). MolProbity: all-atom contacts and structure validation for proteins and nucleic acids. *Nucl. Ac. Res.* **35**, W375–W383. https://doi.org/10.1093/nar/gkm216.

[103] Chen, V.B., Arendall, W. B., Headd, J.J., Keedy, D. A., Immormino, R. M., Kapral, G. J. Murray, L. W., Richardson, J. S., Richardson, D.C., (2010). MolProbity, all-atom structure validation for macromolecular crystallography. *Acta Cryst.* **D** **66**, 12-21.
https://doi.org/10.1107/S0907444909042073

[104] Berman, H., Henrick, K., Nakamura, H., (2003). Announcing the worldwide Protein Data Bank. *Nat Struct Biol.* **10**(12), 980. https://doi.org/10.1038/nsb1203-980
[105] Olsson, M. H., Søndergaard, C. R., Rostkowski, M., Jensen, J. H., (2011). PROPKA3: consistent treatment of internal and surface residues in empirical pKa predictions. *J Chem Theory Comput.* **7**(2), 525–537. https://doi.org/10.1021/ct100578z.

[106] Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J., C., Hess, B., Lindahl, E., (2015). GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. *SoftwareX* **1**, 19-25.
https://doi.org/10.1016/j.softx.2015.06.001.

[107] Darden, T., York, D., Pedersen, L., (1993). Particle mesh Ewald - an N.log(N) method for Ewald sums in large systems. *J. Chem. Phys.* **98**, 10089-10092.
https://doi.org/10.1063/1.464397

[108] Huang, J., Rauscher, S., Nawrocki, G., Ran, T., Feig, M., de Groot, B. L., Grubmüller, H., MacKerell, A. D., Jr (2017). CHARMM36m: an improved force field for folded and intrinsically disordered proteins. *Nat Methods.* **14**(1), 71–73. https://doi.org/10.1038/nmeth.4067.

[109] Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., Klein, M. L., (1983). Comparison of simple potential functions for simulating liquid water. *J. Chem. Phys.* **79**, 926–935. https://doi.org/10.1063/1.445869.

[110] Barducci, A., Bussi, G., Parrinello, M., (2008). Well-tempered metadynamics: a smoothly converging and tunable free-energy method. *Phys Rev Lett.* **100**(2), 020603.
https://doi.org/10.1103/PhysRevLett.100.020603.

[111] Bonomi, M., Branduardi, D., Bussi, G., Camilloni, C., Provasi, D., Raiteri, P., ... Parrinello, M., (2009). PLUMED: A portable plugin for free-energy calculations with molecular dynamics. *Comp Phys Comm.* **180**(10), 1961-1972. https://doi.org/10.1016/j.cpc.2009.05.011

[112] PLUMED consortium (2019). Promoting transparency and reproducibility in enhanced molecular simulations. *Nature methods* **16**(8), 670–673. https://doi.org/10.1038/s41592-019-0506-8.

[113] Branduardi, D., Gervasio, F. L., Parrinello, M., (2007). From A to B in free energy space. *J Chem Phys.* **126**(5). https://doi.org/10.1063/1.2432340
[114] Madern D., (2000). The putative L-lactate dehydrogenase from Methanococcus jannaschii is an NADPH-dependent L-malate dehydrogenase. *Mol Microbiol, **37*(6), 1515–1520. https://doi.org/10.1046/j.1365-2958.2000.02113.x.

Figures and legends

<figure><img src="image_3.png" /></figure>

**Figure 1.** Phylogenetic tree of the *Methanococcales* MalDH. Schematic representation of the MalDH phylogeny adapted from [32]. The ancestor of these enzymes (A35) is indicated by a star. Circles indicate the MalDH studied here: the MalDH inferred in the ancestor of *Methanocaldococcaceae* (A34) and in the ancestor of the *Methanococcaceae* (A19), the modern MalDHs of *M. jannaschii* and *M. infernus*, and the two mutants of the *M. jannaschii* MalDH (C7 and C7GP) designed by introducing a few amino acids present in the enzyme of the mesophilic *Methanococcus maripaludis*. The $OT_A$s of these MalDH are given.
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Structural comparison of tetrameric ancestral MalDHs from *Methanococcales*. The figure illustrates the major changes that have occurred at the root of the *Methanococcales* MalDHs. The number of amino acid substitutions from A35, the ancestor of the *Methanococcales* MalDHs and A34, the ancestor of the *Methanocaldococcaceae* MalDH on the one hand, and A19, the ancestor of the *Methanococcaceae* MalDH, on the other hand, are indicated in yellow boxes. The number of substitutions in modern enzymes is also indicated. The substitutions are shown as blue sticks on the structures. The two regions specifically analyzed in this work are indicated by blue ellipses. (A) Cartoon representation (20% of transparency) of A34 MalDH. (B) Cartoon representation of the *M. jannaschii* MalDH. The red dots indicate the amino acid at position 225, which is used to monitor distance, reflects the overall compactness of the tetramers [52]. (C) Cartoon representation of *M. infernus* MalDH. (D) Cartoon representation of A19 MalDH. (E) Representation of the A34 MalDH monomer representation. Helices are colored in red whereas beta-stand and loops are in yellow and green, respectively. Secondary structure elements are labelled. The subunits of the tetrameric assembly are related by three molecular dyads, *P*, *Q* and *R*.</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Close-up views showing SB formation at the AB interface. (A) Ribbon drawing of the A34 MalDH structure. (B) *M. jannaschii* MalDH structure (1HYG). (C) *M. infernus* MalDH structure. (D) A19 MalDH structure. Amino acid substitutions relative to A35 sequence are shown in red. SB are indicated by yellow dashed lines.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Effect of amino acid substitutions at the AD-like interface. (A) Close-up view of αC helices in the A34 MalDH pseudo crystallographic dimer AD. Amino acids are shown in sticks, colored and named according to the monomers (A, B, C and D). Substitutions that occurred in A34 and A19 are shown in red. Cs corresponds to different conformations of the amino acid side chains. (B) Close-up view of the *M. jannaschii* MalDH. (C) Close-up view of *M. infernus* MalDH. (D) Close-up view of the A19 MalDH. Black arrows indicate the location of cation binding sites, analyzed below.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Figure 5.** Comparison between *M. jan* MalDH and mesophilic-like mutants. Cartoon representation of the tetrameric state. (A) Wild type *M. jannaschii* MalDH (1HYG). (B) C7 mutant MalDH (PDB new code). (C) AlphaFold 3 model of the C7GP mutant MalDH. The yellow dashed lines indicate either the distance between αC of amino acid at position 225 (center of the tetramer) or between αC of amino acid at position 307. The respective values are given in Angstroms. Close-up views of interface AB, centered on substrate-binding amino acid R154. (D) Wt *M. jannaschii* MalDH. (E) C7 mutant MalDH. (F) C7GP mutant MalDH. Close-up views showing the effect of mutations on electrostatic interactions. (G) Wild type *M. jannaschii* MalDH. (H) C7 mutant MalDH. (I) C7GP mutant MalDH. The amino acids in the Wt enzyme are indicated in black, those that differ in the mutants are indicated in red. Cs refers to the conformational sub-state of a given amino acid. Yellow dashed lines indicate salt-bridges.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Figure 6.** Compactness and salt-bridge dynamics as a function of temperature in WT and mutants. (A) Representative configurations of WT showing the distances between the Cα from the residues 245 of chains A and C. Distribution of the distances between the Cα from the residues 245: (B) at 45°C for the three systems and (C) at 90°C, 65°C and 60°C for WT, C7 and C7GP, respectively. Representative configurations of the SBs: (D) in the WT at 45°C and (E) at 90°C. Percentage of time during the MD simulations that a SB was formed between the residues: (F) D58 and R56 within a given monomer, (G) R56 and D168 from A-B like chains, (H) E23 and R241 within a given monomer. (I) E23 and K22 from chains A-B like.</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>**Figure 7.** Simplified illustration of the enzyme catalytic cycle, only one monomer is shown and the cycle represents the malate/oxalate and nicotinamide adenine dinucleotide (in green) before and (in red) after the chemical reaction.</figcaption></figure>
<figure><img src="image_10.png" /></figure>

**Figure 8.** Temperature-dependent open-closed motion of Wt. (A) Representative configuration of a monomer showing (dashed line) the distance between the Cα from the residues 92 and 225 and (in dark blue) the helices αD/E and α1G/2G. (B) Distribution of distances between the Cα from the residues 92 and 225 in the WT simulations. (C) Superposed configurations of the filtered second principal component mode showing that the open-closed motion is a movement of the two helices α-1G/2G and αD/E conformations. (D) Free energy profiles obtained along the reaction coordinate (sss) of the open-closed helices pathway, and (E) Representative configurations of minimum states.

<figure><img src="image_11.png" /></figure>

**Figure 9.** Temperature-dependent open-closed motion of mutants. Free energy profile along a reaction coordinate describing the opened-close motion (sss) for at (A) closer to the OTA (90°C for Wt and 60°C for C7 and C7GP), and (B) lower temperature (45°C). (C) Representative configuration of Wt showing the electrostatic interactions between K105 and D66 and Lys217 with E46, D47 and D50 and (D) the distances between their side-chains NZ, CG and CD atoms for lysine, aspartate and glutamate, respectively.
<figure><img src="image_12.png" /><figcaption>**Figure 10.** Stabilization of unproductive loop-loop interactions at high temperature in mutants. (A) Free energy profile along a reaction coordinate describing the opened-close motion (sss) for at higher temperature. (B) Representative configuration of C7GP with sss value around the global minimum of the free energy profile at 75°C showing the tight interaction between the loops formed by the residues from 84 to 93 and 176 to 182 and (C) distribution of the number of contacts formed by these two loops in the classical simulations.</figcaption></figure>