bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perovskite Solar Cell Stability Analysis Using Entropy‐Based Support Vector Machines Learning
Authors: Bhaduri Rupam , Manasa S. 
Published: November 2024

ABSTRACTLead halide perovskites have demonstrated significant potential for photovoltaic (PV) applications over the past 10 years. Perovskite solar cells (PSCs) stability, however, continues to limit their commercialization, and the inability to compare previous stability data to assess possible directions for increasing device stability is caused by a lack of effectively established unified stability testing and disseminating standards. In this article, we suggest applying machine learning (ML) to improve the thermal, chemical, and structural stability of PSCs. Data normalization and data augmentation are common preprocessing steps that are where the process starts. Then, using the Modified Grasshopper Optimisation Algorithm (MGO), feature selection techniques are used to remove unnecessary or irrelevant features. Finally, there is a novel machine learning technique that uses support vector machines (ESVM) that are based on entropy to forecast the stability classification of stable/unstable. The proposed reaches an accuracy of 0.99% far better than the proposed methods.
In‐Depth Proteome Profiling of the Hippocampus of LDLR Knockout Mice Reveals Alternation in Synaptic Signaling Pathway
Authors: Park Hong‐Beom , Kim Hyeyoon , Han Dohyun 
Published: November 2024

ABSTRACTThe low‐density lipoprotein receptor (LDLR) is a major apolipoprotein receptor that regulates cholesterol homeostasis. LDLR deficiency is associated with cognitive impairment by the induction of synaptopathy in the hippocampus. Despite the close relationship between LDLR and neurodegenerative disorders, proteomics research for protein profiling in the LDLR knockout (KO) model remains insufficient. Therefore, understanding LDLR KO‐mediated differential protein expression within the hippocampus is crucial for elucidating a role of LDLR in neurodegenerative disorders. In this study, we conducted first‐time proteomic profiling of hippocampus tissue from LDLR KO mice using tandem mass tag (TMT)‐based MS analysis. LDLR deficiency induces changes in proteins associated with the transport of diverse molecules, and activity of kinase and catalyst within the hippocampus. Additionally, significant alterations in the expression of components in the major synaptic pathways were found. Furthermore, these synaptic effects were verified using a data‐independent acquisition (DIA)‐based proteomic method. Our data will serve as a valuable resource for further studies to discover the molecular function of LDLR in neurodegenerative disorders.
Production of Polylactide Nanoparticles Loaded With Isoniazid and Vitamin C: A Promising Candidate for the Treatment of Resistant Forms of Tuberculosis
Authors: Galiyeva Aldana , Daribay Arailym , Tabriz Nurlan , Tazhbayev Yerkeblan 
Published: November 2024

ABSTRACTNowadays, the method of directed transport of drugs is becoming increasingly important in medicine and pharmacology. It allows for increasing the concentration of delivered substances in a certain place and blocking or severely limiting their accumulation in healthy organs and tissues. One of the promising drug carriers used in the development of controlled drug delivery systems is polylactic acid (PLA). We were interested in using biodegradable polymeric nanoparticles (NPs) loaded with isoniazid (INH) and vitamin C (VC) which have sustained action, targeted delivery, high efficacy, and low toxicity. It will help to expand the use of these simple drugs for the rapid treatment of multidrug‐resistant forms of tuberculosis. Thus, in this work, PLA‐INH‐VC NPs were prepared by double emulsion method where several factors affecting particle size were investigated. TGA/DSC and IR spectroscopy studies identified the presence of molecularly dispersed drugs (INH and VC) in polylactide nanoparticles. VC was found to reduce the degradation of the polymer and thus prolonged the release of the drug from the polymer matrix. PLA‐INH‐VC nanoparticles were analyzed for mycobacterial activity and the nanoparticles were found to inhibit the growth of INH‐resistant mycobacteria.
Synchronized motion of interface residues for evaluating protein–RNA complex binding affinity: Application to aptamer‐mediated inhibition of TDP‐43 aggregates
Authors: Panei Francesco Paolo , Di Rienzo Lorenzo , Zacco Elsa , Armaos Alexandros , Tartaglia Gian Gaetano , Ruocco Giancarlo , Milanetti Edoardo 
Published: November 2024

AbstractInvestigating the binding between proteins and aptamers, such as peptides or RNA molecules, is of crucial importance both for understanding the molecular mechanisms that regulate cellular activities and for therapeutic applications in several pathologies. Here, a new computational procedure, employing mainly docking, clustering analysis, and molecular dynamics simulations, was designed to estimate the binding affinities between a protein and some RNA aptamers, through the investigation of the dynamical behavior of the predicted molecular complex. Using the state‐of‐the‐art software catRAPID, we computationally designed a set of RNA aptamers interacting with the TAR DNA‐binding protein 43 (TDP‐43), a protein associated with several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). We thus devised a computational protocol to predict the RNA–protein molecular complex, so that the structural and dynamical behavior of such a complex can be investigated through extensive molecular dynamics simulation. We hypothesized that the coordinated and synchronized motion of the protein‐binding residues, when in contact with RNA molecule, is a critical requisite in order to have a stable binding. Indeed, we calculated the motion covariance exhibited by the interface residues during molecular dynamics simulation: we tested the results against experimental measurements of binding affinity (in this case, the dissociation constant) for six RNA molecules, resulting in a linear correlation of about 0.9. Our findings suggest that the synchronized movement of interface residues plays a pivotal role in ensuring the stability within RNA–protein complexes, moreover providing insights into the contribution of each interface residue. This promising pipeline could thus contribute to the design of RNA aptamers interacting with proteins.
Why is binding of a divalent metal cation to a structural motif containing four carboxylate residues not accompanied by a conformational change?
Authors: Lushchekina Sofya , Weiner Lev , Ashani Yacov , Emrizal Reeki , Firdaus‐Raih Mohd , Silman Israel , Sussman Joel L. 
Published: November 2024

AbstractWe earlier showed that Torpedo californica acetylcholinesterase (AChE) contains a cluster of four conserved aspartates that can strongly bind divalent cations, which we named the 4D motif. Binding of the divalent metal cations greatly increases its thermal stability. Here we systematically examined all available crystallographic structures of T. californica AChE. Two additional metal‐binding sites were identified, both composed of acidic and histidine residues. Relative binding to the 4D and additional sites was studied using metadynamics simulations. It was observed that in crystal structures devoid of metal ions in the 4D site, the conformation of T. californica AChE is almost identical to that in structures in which it is occupied by a divalent metal ion. Closer examination of the 4D motif reveals that three of the four acidic residues form ion pairs with conserved basic residues surrounding them. We named this new motif the 4A/3B motif. Molecular dynamics with quantum potential simulations was used to quantify the 4D motif's binding strength compared with that of the metal‐binding site in the protein fXIIIa, which consists of four aspartates, but is devoid of adjacent cationic residues. Whereas fXIIIa's 4D site, in the absence of a metal cation, expanded significantly in the simulation, that of Torpedo AChE displayed only minor periodic changes in size. Furthermore, the energy of metal ion unbinding from the two sites differs by ca. 10 kcal/mol. We identified several other proteins in the PDB that contain the 4A/3B motif, whose conformations are identical in the presence or absence of a metal ion. An animated Interactive 3D Complement (I3DC) is available in Proteopedia at https://proteopedia.org/w/Journal:Protein_Science:4.
A protein fitness predictive framework based on feature combination and intelligent searching
Authors: Zhang Zhihui , Li Zhixuan , Wang Qianyue , Wu Hanlin , Yang Manli , Zhao Fengguang , Tan Mingkui , Han Shuangyan 
Published: November 2024

AbstractMachine learning (ML) constructs predictive models by understanding the relationship between protein sequences and their functions, enabling efficient identification of protein sequences with high fitness values without falling into local optima, like directional evolution. However, how to extract the most pertinent functional feature information from a limited number of protein sequences is vital for optimizing the performance of ML models. Here, we propose scut_ProFP (Protein Fitness Predictor), a predictive framework that integrates feature combination and feature selection techniques. Feature combination offers comprehensive sequence information, while feature selection searches for the most beneficial features to enhance model performance, enabling accurate sequence‐to‐function mapping. Compared to similar frameworks, scut_ProFP demonstrates superior performance and is also competitive with more complex deep learning models—ECNet, EVmutation, and UniRep. In addition, scut_ProFP enables generalization from low‐order mutants to high‐order mutants. Finally, we utilized scut_ProFP to simulate the engineering of the fluorescent protein CreiLOV and highly enriched mutants with high fluorescence based on only a small number of low‐fluorescence mutants. Essentially, the developed method is advantageous for ML in protein engineering, providing an effective approach to data‐driven protein engineering. The code and datasets for scut_ProFP are available at https://github.com/Zhang66-star/scut_ProFP.
Amino acid variability at W194 of Staphylococcus aureus sortase A alters nucleophile specificity
Authors: Kodama Hanna M. , Lindblom Katy M. , Walkenhauer Erich G. , Antos John M. , Amacher Jeanine F. 
Published: November 2024

AbstractBacterial sortases are a family of cysteine transpeptidases in Gram‐positive bacteria of which sortase A (SrtA) enzymes are responsible for ligating proteins to the peptidoglycan layer of the cell surface. Engineered versions of sortases are also used in sortase‐mediated ligation (SML) strategies for a variety of protein engineering applications. Although a versatile tool, substrate recognition by Staphylococcus aureus SrtA (saSrtA), the most commonly utilized enzyme in SML, is stringent and relies on an LPXTG pentapeptide motif. Previous structural studies revealed that the requirement of a glycine in the binding motif may be due to potential steric hindrance of amino acids possessing a β‐carbon by W194, a tryptophan located in the β7‐β8 loop of the enzyme. Here, we measured the effect of seven single point mutants of W194 (A, D, F, G, N, S, Y) saSrtA using a FRET‐based activity assay. We found that while the LPXTG motif remains a requirement for initial proteolytic cleavage, the nucleophile specificity of our variants is altered. In particular, W194A and W194S saSrtA recognize a D‐Ala nucleophile and are able to perform ligation reactions. Notably, an LPXT(D‐Ala) peptide was not cleaved by either mutant enzyme. We hypothesize that these variants may potentially be utilized to develop an irreversible sortase‐mediated reaction. Taken together, this experiment reveals new insight into sortase specificity and possible future SML strategies.
Re‐engineering of a carotenoid‐binding protein based on NMR structure
Authors: Nikolaev Andrey S. , Lunegova Daria A. , Raevskii Roman I. , Shishkin Pavel E. , Remeeva Alina A. , Ge Baosheng , Maksimov Eugene G. , Gushchin Ivan Yu. , Sluchanko Nikolai N. 
Published: November 2024

AbstractRecently, a number of message passing neural network (MPNN)‐based methods have been introduced that, based on backbone atom coordinates, efficiently recover native amino acid sequences of proteins and predict modifications that result in better expressing, more soluble, and stable variants. However, usually, X‐ray structures, or artificial structures generated by algorithms trained on X‐ray structures, were employed to define target backbone conformations. Here, we show that commonly used algorithms ProteinMPNN and SolubleMPNN display low sequence recovery on structures determined using NMR. We subsequently propose a computational approach that we successfully apply to re‐engineer AstaP, a protein that natively binds a large hydrophobic ligand astaxanthin (C40H52O4), and for which only a structure determined using NMR is currently available. The engineered variants, designated NeuroAstaP, are 51 amino acid shorter than the 22 kDa parent protein, have 38%–42% sequence identity to it, exhibit good yields, are expressed in a soluble, mostly monomeric form, and demonstrate efficient binding of carotenoids in vitro and in cells. Altogether, our work further tests the limits of using machine learning for protein engineering and paves the way for MPNN‐based modification of proteins based on NMR‐derived structures.
The molecular architecture of the desmosomal outer dense plaque by integrative structural modeling
Authors: Pasani Satwik , Menon Kavya S. , Viswanath Shruthi 
Published: November 2024

AbstractDesmosomes mediate cell–cell adhesion and are prevalent in tissues under mechanical stress. However, their detailed structural characterization is not available. Here, we characterized the molecular architecture of the desmosomal outer dense plaque (ODP) using Bayesian integrative structural modeling via the Integrative Modeling Platform. Starting principally from the structural interpretation of a cryo‐electron tomography (cryo‐ET) map of the ODP, we integrated information from x‐ray crystallography, an immuno‐electron microscopy study, biochemical assays, in silico predictions of transmembrane and disordered regions, homology modeling, and stereochemistry information. The integrative structure was validated by information from imaging, tomography, and biochemical studies that were not used in modeling. The ODP resembles a densely packed cylinder with a plakophilin (PKP) layer and a plakoglobin (PG) layer; the desmosomal cadherins and PKP span these two layers. Our integrative approach allowed us to localize disordered regions, such as the N‐terminus of PKP and the C‐terminus of PG. We refined previous protein–protein interactions between desmosomal proteins and provided possible structural hypotheses for defective cell–cell adhesion in several diseases by mapping disease‐related mutations on the structure. Finally, we point to features of the structure that could confer resilience to mechanical stress. Our model provides a basis for generating experimentally verifiable hypotheses on the structure and function of desmosomal proteins in normal and disease states.
Impact of primary sequence changes on the self‐association properties of mammalian cystathionine beta‐synthase enzymes
Authors: Lee Hyung‐Ok , Gupta Kushol , Wang Liqun , Dunbrack Roland L. , Majtan Tomas , Kruger Warren D. 
Published: November 2024

AbstractCystathionine beta‐synthase (CBS) is an evolutionarily conserved enzyme that plays a key role in mammalian sulfur amino acid biochemistry, mutations in which are the cause of classical homocystinuria (HCU), an inborn error of metabolism. Although there is agreement in the literature that CBS is a homomultimer, its precise structure is a source of confusion. Here, we performed a series of experiments examining the quaternary structure of various wild‐type and mutant CBS enzymes using a combination of native gel electrophoresis, in situ activity assays, analytical ultracentrifugation, and gel filtration. Our data show that recombinantly expressed and purified full‐length wild‐type human CBS enzyme (hCBS) and HCU‐causing variants (p.P422L, p.I435T, and p.R125Q CBS) form high molecular weight assemblies that are consistent with the properties expected of a filament. The filament is enzymatically active, and its size is sensitive to protein concentration. This behavior contrasts sharply with hCBS enzymes containing small deletions within the Bateman domain, which form stable tetramers and octamers regardless of concentration. Examination of liver lysates from humans and mice confirms the existence of enzymatically active high molecular weight aggregates in vivo, but also shows that these aggregates are specific to human CBS and do not occur in mice. Molecular modeling using AlphaFold2 suggests that these experimentally observed differences may be explained by subtle differences in the interaction mediated by the Bateman domains. Our results show that small differences in amino acid sequence can cause large differences in the size and shape of CBS multimers.
Complexity associated with caprylate binding to bovine serum albumin: Dimerization, allostery, and variance between the change in free energy and enthalpy of binding
Authors: Capili Marc Joseph A. , Oerlemans Sophie K. , Wright Leah , Falconer Robert J. 
Published: November 2024

AbstractIsothermal titration calorimetry (ITC), differential scanning calorimetry (DSC), and pressure perturbation calorimetry (PPC) were used to study different aspects of the diverse interaction between the fatty acid caprylate and bovine serum albumin (BSA). The ITC thermogram was consistent with exothermic binding to a single site on BSA, which was electrostatic but had little or no hydrophobic contribution. ITC revealed that small changes to solution conditions and temperature were associated with apparent enthalpy–entropy compensation, causing large changes in enthalpy (ΔH) during binding, but with little corresponding changes in free energy (ΔG). ITC also detected a slower endothermic interaction at a low mole ratio. Dynamic light scattering suggested that this was due to dimerization or similar self‐association. DSC demonstrated that further interactions took place at higher mole ratios. This was consistent with weak binding of caprylate to multiple binding sites which had a considerable impact on the structural conformation of BSA. PPC showed that the conformational change of BSA was accompanied with a reduction in surface hydrophobicity of the protein. PPC also demonstrated that in solution caprylate's hydrocarbon tail is hidden from water as no clathrate‐like water is evident, which is consistent with the lack of hydrophobic contribution during binding. Cumulatively, the three calorimetric techniques offer a comprehensive view of caprylate and BSA interactions, highlighting the role of electrostatic interaction in binding accompanied by probably dimerization and considerable structural change associated with weaker binding to BSA.
Market informed portfolio optimization methods with hybrid quantum computing
Authors: Salirrosas Giancarlo Martínez , Gao Jinglun , Yu Arthur , Verma Anish Ravi 
Published: November 2024

AbstractThis document presents a portfolio optimization framework that employs a hybrid quantum computing algorithm and a futures market sentiment indicator—The Market Sentiment Meter (MSM) variable, developed jointly by CME Group and 1QBit. The methodology used was the Variational Quantum Eigensolver (VQE). The work presented here is divided into four portfolio optimization problem formulations, of binary and continuous variable formulations, determining which assets to pick their weights. This work demonstrates that adding the MSM variable can improve the performance of hybrid quantum solutions, by informing the asset selection problem with market environment information through the four MSM states.
Percolation on High‐Dimensional Product Graphs
Authors: Diskin Sahar , Erde Joshua , Kang Mihyun , Krivelevich Michael 
Published: November 2024

ABSTRACTWe consider percolation on high‐dimensional product graphs, where the base graphs are regular and of bounded order. In the subcritical regime, we show that typically the largest component is of order logarithmic in the number of vertices. In the supercritical regime, our main result recovers the sharp asymptotic of the order of the largest component and shows that all the other components are typically of order logarithmic in the number of vertices. In particular, we show that this phase transition is quantitatively similar to the one of the binomial random graph. This generalizes the results of Ajtai, Komlós, and Szemerédi [1] and of Bollobás, Kohayakawa, and Łuczak [5] who showed that the ‐dimensional hypercube, which is the ‐fold Cartesian product of an edge, undergoes a phase transition quantitatively similar to the one of the binomial random graph.
Impact of rural transformation on rural income and poverty for sustainable development inBangladesh: A moments‐quantile regression with fixed‐effects models Approach
Authors: Al Abbasi Al Amin , Alam Mohammad Jahangir , Saha Subrata , Begum Ismat Ara , Rola‐Rubzen Maria Fay 
Published: November 2024

AbstractThis study examines the impact of rural transformation on income and poverty in Bangladesh using district‐level panel data from five rounds of the Household Income and Expenditure Survey conducted in 1995, 2000, 2005, 2010, and 2016. Two key indicators are assessed: the share of high‐value agriculture and non‐farm employment. Fixed effects and moments‐quantile regression models are employed to analyze the relationships between rural transformation, income, and poverty, accounting for education, healthcare, electricity access, and land ownership. The results show that both high‐value agriculture and non‐farm employment significantly boost rural income and reduce poverty. Geographic disparities are evident, with high‐value agriculture being most effective in agriculturally favorable regions, while non‐farm employment has a stronger impact in areas with fewer agricultural opportunities. These findings are critical in shaping policies aligned with Sustainable Development Goal 1, which seeks to eradicate poverty. The findings indicate the need for policies to prioritize high‐value agriculture and non‐farm employment to promote income growth and reduce poverty. Expanding agricultural extension services and vocational training is vital for this transformation, alongside targeted investments in infrastructure, education, healthcare, and energy access to enhance rural development and poverty alleviation across Bangladesh.
Violent sustainability: Blitzscale and counteraccounting in an Indian agtech start‐up
Authors: Agrawal Nikhit 
Published: November 2024

AbstractIn recent years, there has been rapid digitalization in agriculture, with India seeing a significant rise in agricultural technology (agtech) start‐ups. Many of these start‐ups promise to address the climate crisis by promoting the economic and ecological sustainability of agriculture through market‐driven business models. Using institutional ethnography and counteraccounting at an Indian agtech start‐up, this article illuminates social, economic, and ecological relationships that are obscured by one firm's accounting practices. It shows how, despite tech‐entrepreneurs intending to help farmers, violence remains built into the design and effects of rapidly scaled‐up (“blitzscaled”) sustainability programs. The article proposes violent sustainability as a concept to highlight the unintended harm caused to potential beneficiaries due to structural violence underlying tech‐entrepreneurialism and inherent design flaws in blitzscaled sustainability programs. In doing so, it challenges the normalization and monetization of recurrent failures prevalent in tech‐entrepreneurial ventures.