pinecone/core-2020-05-10-deduplication huggingface dataset:
New insight into the architecture of oxy-anion pocket in unliganded conformation of GAT domains: A MD-simulation study

Human Guanine Monophosphate Synthetase (hGMPS) converts XMP to GMP, and acts as a bifunctional enzyme with N-terminal ``glutaminase'' (GAT) and C-terminal ``synthetase'' domain. The enzyme is identified as a potential target for anticancer and immunosuppressive therapies. GAT domain of enzyme plays central role in metabolism, and contains conserved catalytic residues Cys104, His190, and Glu192. MD simulation studies on GAT domain suggest that position of oxyanion in unliganded conformation is occupied by one conserved water molecule (W1), which also stabilizes that pocket. This position is occupied by a negatively charged atom of the substrate or ligand in ligand bound crystal structures. In fact, MD simulation study of Ser75 to Val indicates that W1 conserved water molecule is stabilized by Ser75, while Thr152, and His190 also act as anchor residues to maintain appropriate architecture of oxyanion pocket through water mediated H-bond interactions. Possibly, four conserved water molecules stabilize oxyanion hole in unliganded state, but they vacate these positions when the enzyme (hGMPS)-substrate complex is formed. Thus this study not only reveals functionally important role of conserved water molecules in GAT domain, but also highlights essential role of other non-catalytic residues such as Ser75 and Thr152 in this enzymatic domain. The results from this computational study could be of interest to experimental community and provide a testable hypothesis for experimental validation. Conserved sites of water molecules near and at oxyanion hole highlight structural importance of water molecules and suggest a rethink of the conventional definition of chemical geometry of inhibitor binding site
Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy.We are most grateful to the PDBe at the European Bioinformatics Institute in Hinxton, UK, for hosting the CAPRI website. Our deepest thanks go to all the structural biologists and to the following structural genomics initiatives: Northeast Structural Genomics Consortium, Joint Center for Structural Genomics, NatPro PSI:Biology, New York Structural Genomics Research Center, Midwest Center for Structural Genomics, Structural Genomics Consortium, for contributing the targets for this joint CASP-CAPRI experiment. MFL acknowledges support from the FRABio FR3688 Research Federation “Structural & Functional Biochemistry of Biomolecular Assemblies.”Peer ReviewedPostprint (published version
Blind testing of cross-linking/mass spectrometry hybrid methods in CASP11

Hybrid approaches combine computational methods with experimental data. The information contained in the experimental data can be leveraged to probe the structure of proteins otherwise elusive to computational methods. Compared with computational methods, the structures produced by hybrid methods exhibit some degree of experimental validation. In spite of these advantages, most hybrid methods have not yet been validated in blind tests, hampering their development. Here, we describe the first blind test of a specific cross-link based hybrid method in CASP. This blind test was coordinated by the CASP organizers and utilized a novel, high-density cross-linking/mass-spectrometry (CLMS) approach that is able to collect high-density CLMS data in a matter of days. This experimental protocol was developed in the Rappsilber laboratory. This approach exploits the chemistry of a highly reactive, photoactivatable cross-linker to produce an order of magnitude more cross-links than homobifunctional cross-linkers. The Rappsilber laboratory generated experimental CLMS data based on this protocol, submitted the data to the CASP organizers which then released this data to the CASP11 prediction groups in a separate, CLMS assisted modeling experiment. We did not observe a clear improvement of assisted models, presumably because the properties of the CLMS data-uncertainty in cross-link identification and residue-residue assignment, and uneven distribution over the protein-were largely unknown to the prediction groups and their approaches were not yet tailored to this kind of data. We also suggest modifications to the CLMS-CASP experiment and discuss the importance of rigorous blind testing in the development of hybrid methods. (C) 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc
Dissecting the roles of local packing density and longer-range effects
  in protein sequence evolution

What are the structural determinants of protein sequence evolution? A number
of site-specific structural characteristics have been proposed, most of which
are broadly related to either the density of contacts or the solvent
accessibility of individual residues. Most importantly, there has been
disagreement in the literature over the relative importance of solvent
accessibility and local packing density for explaining site-specific sequence
variability in proteins. We show here that this discussion has been confounded
by the definition of local packing density. The most commonly used measures of
local packing, such as the contact number and the weighted contact number,
represent by definition the combined effects of local packing density and
longer-range effects. As an alternative, we here propose a truly local measure
of packing density around a single residue, based on the Voronoi cell volume.
We show that the Voronoi cell volume, when calculated relative to the geometric
center of amino-acid side chains, behaves nearly identically to the relative
solvent accessibility, and both can explain, on average, approximately 34\% of
the site-specific variation in evolutionary rate in a data set of 209 enzymes.
An additional 10\% of variation can be explained by non-local effects that are
captured in the weighted contact number. Consequently, evolutionary variation
at a site is determined by the combined action of the immediate amino-acid
neighbors of that site and of effects mediated by more distant amino acids. We
conclude that instead of contrasting solvent accessibility and local packing
density, future research should emphasize the relative importance of immediate
contacts and longer-range effects on evolutionary variation.Comment: Published in the Journal of Proteins: Structure, Function, and
  Bioinformatics. http://onlinelibrary.wiley.com/doi/10.1002/prot.25034/ful
Great interactions: How binding incorrect partners can teach us about protein recognition and function

International audienceProtein–protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross-docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein's binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross-docking predictions using the area under the specificity-sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on the binding patches that are scattered on the protein surface show that their distribution and growth will depend on the protein's functional group. Finally, in several cases, the binding-site predictions resulting from the cross-docking simulations will lead to the identification of an alternate interface, which corresponds to the interaction with a biomolecular partner that is not included in the original benchmark
A multi-resolution model to capture both global fluctuations of an
  enzyme and molecular recognition in the ligand-binding site

In multi-resolution simulations, different system components are
simultaneously modelled at different levels of resolution, these being smoothly
coupled together. In the case of enzyme systems, computationally expensive
atomistic detail is needed in the active site to capture the chemistry of
substrate binding. Global properties of the rest of the protein also play an
essential role, determining the structure and fluctuations of the binding site;
however, these can be modelled on a coarser level. Similarly, in the most
computationally efficient scheme only the solvent hydrating the active site
requires atomistic detail. We present a methodology to couple atomistic and
coarse-grained protein models, while solvating the atomistic part of the
protein in atomistic water. This allows a free choice of which protein and
solvent degrees of freedom to include atomistically, without loss of accuracy
in the atomistic description. This multi-resolution methodology can
successfully model stable ligand binding, and we further confirm its validity
via an exploration of system properties relevant to enzymatic function. In
addition to a computational speedup, such an approach can allow the
identification of the essential degrees of freedom playing a role in a given
process, potentially yielding new insights into biomolecular function
Modeling and minimizing CAPRI round 30 symmetrical protein complexes from CASP-11 structural models

International audienceMany of the modeling targets in the blind CASP-11/CAPRI-30 experiment were protein homo-dimers and homo-tetramers. Here, we perform a retrospective docking-based analysis of the perfectly symmetrical CAPRI Round 30 targets whose crystal structures have been published. Starting from the CASP “stage-2” fold prediction models, we show that using our recently developed “SAM” polar Fourier symmetry docking algorithm combined with NAMD energy minimization often gives acceptable or better 3D models of the target complexes. We also use SAM to analyze the overall quality of all CASP structural models for the selected targets from a docking-based perspective. We demonstrate that docking only CASP “center” structures for the selected targets provides a fruitful and economical docking strategy. Furthermore, our results show that many of the CASP models are dockable in the sense that they can lead to acceptable or better models of symmetrical complexes. Even though SAM is very fast, using docking and NAMD energy minimization to pull out acceptable docking models from a large ensemble of docked CASP models is computationally expensive. Nonetheless, thanks to our SAM docking algorithm, we expect that applying our docking protocol on a modern computer cluster will give us the ability to routinely model 3D structures of symmetrical protein complexes from CASP-quality models
pyDock scoring for the new modeling challenges in docking: protein-peptide, homo-multimers and domain-domain interactions

The 6th CAPRI edition included new modelling challenges, such as the prediction of protein-peptide complexes, and the modelling of homo-oligomers and domain-domain interactions as part of the first joint CASP-CAPRI experiment. Other non-standard targets included the prediction of interfacial water positions and the modelling of the interactions between proteins and nucleic acids. We have participated in all proposed targets of this CAPRI edition both as predictors and as scorers, with new protocols to efficiently use our docking and scoring scheme pyDock in a large variety of scenarios. In addition, we have participated for the first time in the server section, with our recently developed webserver, pyDockWeb. Excluding the CASP-CAPRI cases, we submitted acceptable models (or better) for 7 out of the 18 evaluated targets as predictors, 4 out of the 11 targets as scorers, and 6 out of the 18 targets as servers. The overall success rates were below those in past CAPRI editions. This shows the challenging nature of this last edition, with many difficult targets for which no participant submitted a single acceptable model. Interestingly, we submitted acceptable models for 83% of the evaluated protein-peptide targets. As for the 25 cases of the CASP-CAPRI experiment, in which we used a larger variety of modelling techniques (template-based, symmetry restraints, literature information, etc.), we submitted acceptable models for 56% of the targets. In summary, this CAPRI edition showed that pyDock scheme can be efficiently adapted to the increasing variety of problems that the protein interactions field is currently facing. This article is protected by copyright. All rights reserved.Peer ReviewedPostprint (author's final draft
Methods for estimation of model accuracy in CASP12

Methods to reliably estimate the quality of 3D models of proteins are essential drivers for the wide adoption and serious acceptance of protein structure predictions by life scientists. In this paper, the most successful groups in CASP12 describe their latest methods for Estimates of Model Accuracy (EMA). We show that pure single model accuracy estimation methods have shown clear progress since CASP11; the three top methods (MESHI, ProQ3, SVMQA) all perform better than the top method of CASP11 (ProQ2). While the pure single model accuracy estimation methods outperform quasi-single (ModFOLD6 variations) and consensus methods (Pcons, ModFOLDclust2, Pcomb-domain and Wallner) in model selection, they are still not as good as those methods in absolute model quality estimation and predictions of local quality. Finally, we show that when using contact based model quality measures (CAD, lDDT) the single model quality methods perform relatively better
Molecular modeling of an antigenic complex between a viral peptide and a class I major histocompatibility glycoprotein

Computer simulation of the
conformations of short antigenic peptides (&lo
residues) either free or bound to their receptor,
the major histocompatibility complex (MHC)-
encoded glycoprotein H-2 Ld, was employed to
explain experimentally determined differences
in the antigenic activities within a set of related
peptides. Starting for each sequence from the
most probable conformations disclosed by a
pattern-recognition technique, several energyminimized
structures were subjected to molecular
dynamics simulations (MD) either in vacuo
or solvated by water molecules. Notably, antigenic
potencies were found to correlate to the
peptides propensity to form and maintain an
overall a-helical conformation through regular
i,i + 4 hydrogen bonds. Accordingly, less active
or inactive peptides showed a strong tendency
to form i,i+3 hydrogen bonds at their Nterminal
end. Experimental data documented
that the C-terminal residue is critical for interaction
of the peptide with H-2 Ld. This finding
could be satisfactorily explained by a 3-D
Q.S.A.R. analysis postulating interactions between
ligand and receptor by hydrophobic
forces. A 3-D model is proposed for the complex
between a high-affinity nonapeptide and the H-
2 Ld receptor. First, the H-2 Ld molecule was
built from X-ray coordinates of two homologous
proteins: HLA-A2 and HLA-Aw68, energyminimized
and studied by MD simulations. With
HLA-A2 as template, the only realistic simulation
was achieved for a solvated model with minor
deviations of the MD mean structure from
the X-ray conformation. Water simulation of the
H-2 Ld protein in complex with the antigenic
nonapeptide was then achieved with the template-
derived optimal parameters. The bound
peptide retains mainly its a-helical conformation
and binds to hydrophobic residues of H-2
Ld that correspond to highly polymorphic positions
of MHC proteins. The orientation of the
nonapeptide in the binding cleft is in accordance
with the experimentally determined distribution
of its MHC receptor-binding residues
(agretope residues). Thus, computer simulation was successfully employed to explain functional
data and predicts a-helical conformation
for the bound peptide
A single-dose mass balance and metabolite-profiling study of vemurafenib in patients with metastatic melanoma

Vemurafenib, a selective inhibitor of oncogenic BRAF kinase carrying the V600 mutation, is approved for treatment of advanced BRAF mutation-positive melanoma. This study characterized mass balance, metabolism, rates/routes of elimination, and disposition of (14)C-labeled vemurafenib in patients with metastatic melanoma. Seven patients with metastatic BRAF-mutated melanoma received unlabeled vemurafenib 960 mg twice daily for 14 days. On the morning of day 15, patients received (14)C-labeled vemurafenib 960 mg (maximum 2.56 MBq [69.2 μCi]). Thereafter, patients resumed unlabeled vemurafenib (960 mg twice daily). Blood, urine, and feces were collected for metabolism, pharmacokinetic, and dose recovery analysis. Within 18 days after dose, ∽95% of (14)C-vemurafenib-related material was recovered from feces (94.1%) and urine (<1%). The parent compound was the predominant component (95%) in plasma. The mean plasma elimination half-life of (14)C-vemurafenib-related material was 71.1 h. Each metabolite accounted for <0.5% and ≤6% of the total administered dose in urine and feces, respectively (0-96 h postdose). No new metabolites were detected. Vemurafenib was well-tolerated. Excretion of vemurafenib via bile into feces is considered the predominant elimination route from plasma with minor renal elimination (<1%). e00113
Pharmacological profiling of the hemodynamic effects of cannabinoid ligands: a combined in vitro and in vivo approach

The receptors mediating the hemodynamic responses to cannabinoids are not clearly defined due to the multifarious pharmacology of many commonly used cannabinoid ligands. While both CB1 and TRPV1 receptors are implicated, G protein-coupled receptor 55 (GPR55) may also mediate some of the hemodynamic effects of several atypical cannabinoid ligands. The present studies attempted to unravel the pharmacology underlying the in vivo hemodynamic responses to ACEA (CB1 agonist), O-1602 (GPR55 agonist), AM251 (CB1 antagonist), and cannabidiol (CBD; GPR55 antagonist). Agonist and antagonist profiles of each ligand were determined by ligand-induced GTPγS binding in membrane preparations expressing rat and mouse CB1 and GPR55 receptors. Blood pressure responses to ACEA and O-1602 were recorded in anesthetized and conscious mice (wild type, CB1−/− and GPR55−/−) and rats in the absence and presence of AM251 and CBD. ACEA demonstrated GTPγS activation at both receptors, while O-1602 only activated GPR55. AM251 exhibited antagonist activity at CB1 and agonist activity at GPR55, while CBD demonstrated selective antagonist activity at GPR55. The depressor response to ACEA was blocked by AM251 and attenuated by CBD, while O-1602 did not induce a depressor response. AM251 caused a depressor response that was absent in GPR55−/− mice but enhanced by CBD, while CBD caused a small vasodepressor response that persisted in GPR55−/− mice. Our findings show that assessment of the pharmacological profile of receptor activation by cannabinoid ligands in in vitro studies alongside in vivo functional studies is essential to understand the role of cannabinoids in hemodynamic control
On the role of bioactive sphingolipids and their metabolizing enzymes in cancer

Ceramide is a family of closely related molecules, which are presumed to be in the center of
sphingolipid metabolism. Among sphingolipid metabolites, several ceramide subspecies and
sphingosine induce apoptosis, cell cycle arrest and death, whereas sphingosine 1-phosphate
(S1P) mediates cell proliferation, invasion, angiogenesis and metastasis. Cell fate is largely
dependent on the balance of ceramide and sphingosine versus S1P. The sphingosine kinases
(SKs) are responsible for maintaining this balance, which leans towards S1P in many cancers.
Thereby SKs have been suggested as targets for cancer therapy. The overall aim of this thesis
was to target SKs in order to enhance the effects of anti-cancer agents in hepatocellular
carcinoma (HCC) and bladder cancer cells.



In study I, we have treated HCC cell lines with selenite in combination with pharmacological
inhibitors of sphingolipid-metabolizing enzymes. Selenite treatment induced the activity of
neutral sphingomyelinase and increased the levels of long chain ceramides. Moreover, the
sphingosine kinase 1 inhibitor 2-(p-hydroxyanilino)-4-(p-chlorophenyl) thiazole (SKI-II)
sensitized HCC cells to selenite treatment by increasing the levels of ceramide subspecies,
inducing reactive oxygen species formation and apoptosis, and inhibiting cell cycle
progression and cell viability.



In study II, HCC cell lines were co-treated with the multi-tyrosine kinase inhibitor sorafenib
and the sphingosine agonist FTY720 in order to improve the efficacy of sorafenib treatment.
We have shown that a marginally toxic dose of FTY720 synergistically increased the
cytotoxicity of sorafenib towards the Huh7 and HepG2 cell lines. Combined treatment with
FTY720 and sorafenib mediated cell cycle arrest, caspase-dependent and –independent
apoptosis, autophagy blockage and cell death in Huh7 cells.



In study III, the treatment effects of supernatant from Bacillus Calmette-Guérin -activated
macrophages (SupBCG) and SKI-II on murine bladder cancer cell lines were studied.
Combined treatment with SKI-II and SupBCG mediated a decrease in cell viability compared
to SupBCG treatment alone. There was a transient increase in Sphk1 mRNA level following
SupBCG treatment, but the SK1 protein level was unaffected. SupBCG and SKI-II
individually induced PARP-cleavage. The level of dihydro C16-ceramide was increased
following SKI-II treatment alone, and was further enhanced after combined treatment with
SupBCG.



In our studies we have observed that inhibition of SKs enhanced the cytotoxicity of treatment
with selenite or sorafenib in HCC cell lines, and of BCG in bladder cancer cell lines.
Therefore, we conclude that targeting these enzymes could potentiate other treatment effects
in HCC and bladder cancer cells