PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS蛋白质：结构、功能与生物信息学
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS(英文缩写 PROTEINS),ISSN 0887-3585,eISSN 1097-0134,中文译名:蛋白质：结构、功能与生物信息学 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-09-27 至 2026-09-27，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 4.088 | Q2 |
| 2022 | 2.900 | Q3 |
| 2023 | 3.200 | Q2 |
| 2024 | 2.800 | Q2 |
| 2025 | 3.300 | Q2 |
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS 最新收录文献
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1. Impact of Stabilizing Osmolytes on the Conformational Dynamics of Human and Rat Islet Amyloid Polypeptides.
PMID:日期:2026-10-01The aggregation of human islet amyloid polypeptide (hIAPP) into cytotoxic oligomers and amyloid fibrils is a hallmark of type 2 diabetes mellitus (T2DM), leading to pancreatic β-cell dysfunction. In contrast, rat IAPP (rIAPP) is largely non-amyloidogenic. Osmolytes such as glucose, glycerol, and sorbitol are known to stabilize globular protein structures; however, in the case of intrinsically disordered proteins (IDPs), they modulate amyloidogenic aggregation in a concentration-dependent manner. Understanding the molecular mechanism of action of these osmolytes on IDPs remains limited. Well-tempered bias exchange metadynamics (WT-BEMD) simulations were used to study the conformational energy landscape of hIAPP and rIAPP in solution across varying osmolyte concentrations (125, 250, and 500 mM). The addition of osmolytes resulted in subtle changes in secondary structure propensity and content in both hIAPP and rIAPP. In the case of hIAPP, a general reduction in the likelihood of α-helical conformations was observed, particularly in the amyloidogenic core, suggesting a molecular mechanism for reduced aggregation in the presence of osmolytes. There was a notable lack of significant direct H-bonding and hydrophobic protein-osmolyte interactions, confirming the presence of a strong osmophobic effect. These findings suggest that these stabilizing osmolytes influence the conformational ensemble of hIAPP and rIAPP through exclusion from the protein surface, rather than by directly stabilizing specific conformations. The potential osmolyte-mediated reduction in aggregation-prone conformations in IDPs such as hIAPP may disrupt early aggregation and offer a potential strategy to mitigate hIAPP cytotoxicity.
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2. Stabilization of Bone Morphogenetic Protein-2 at Physiological pH: Contrasting Roles of CHAPS and Arginine in Aggregation Inhibition.
PMID:日期:2026-10-01Bone morphogenetic protein-2 (BMP-2) is a key osteoinductive growth factor employed clinically in spinal fusion and fracture repair where bone regeneration is insufficient. However, its therapeutic efficacy is limited by low solubility and aggregation at physiological pH. This study investigates BMP-2 aggregation and identifies additives that stabilize its native, biologically active dimer form under physiological conditions. We demonstrate that 3-[(3-cholamidopropyl) dimethylammonio]-1-propanesulfonate (CHAPS) efficiently refolded monomeric BMP-2 from inclusion bodies into dimeric form but failed to prevent aggregation of the folded dimer. In contrast, arginine did not promote refolding but significantly enhanced solubility and stability of the native dimer against aggregation as evidenced by turbidity, Rayleigh scattering, nanoparticle tracking analysis (NTA), dynamic light scattering (DLS) and microscopic analyzes. Functional assays, including alkaline phosphatase (ALP) activity, calcium deposition, and native PAGE, verified that BMP-2 retained its biological activity in presence of arginine. Tryptophan fluorescence and in silico analysis revealed distinct interaction mechanisms to BMP-2: CHAPS interacts with aromatic residues, enhancing flexibility and stabilizes open conformation, whereas arginine binds preferentially to acidic residues, promoting a compact, closed conformation. Collectively, arginine confers robust stabilization of BMP-2 at physiological pH, offering a rational framework for developing stable and therapeutically effective BMP-2 formulations.
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3. Structural Insights Into the Function of Leishmania major Adenylosuccinate Lyase.
PMID:日期:2026-10-01One of several intriguing aspects of kinetoplastid biochemistry is the complete dependence on host purines and purine recycling due to the lack of a de novo purine biosynthesis pathway. Adenylosuccinate lyase (ASL, EC 4.3.2.2) is a key enzyme in the purine synthesis pathway responsible for the conversion of adenylosuccinate into adenosine monophosphate (AMP), representing a potential target for an effective drug design against leishmaniasis. Here, we report the in vitro kinetics studies and the crystal structure of the Leishmania major Friedlin adenylosuccinate lyase (LmASL). Furthermore, we characterize allosteric communication networks within the protein. We propose a phenylpiperazine derivative, itraconazole, as a promising candidate for selective interaction with the LmASL substrate-binding site by molecular docking and molecular dynamics simulations. Finally, we expand the current understanding on trypanosomatid ASL by demonstrating its requirement for the normal growth of Trypanosoma brucei procyclic form. Our data will substantiate future studies aimed at developing an effective and specific treatment against leishmaniasis.
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4. Generalizing the Gaussian Network Model: Spanning-Tree Thermodynamics Shows Entropy-Driven KRAS Activation.
PMID:日期:2026-10-01The GTPase KRAS executes a conformational switch between a GTP-bound active state and a GDP-bound inactive state, a process central to oncogenic signaling. However, the structural basis of this switching at the level of residue-contact organization remains incompletely characterized by traditional binary structural models. Here, we present a statistical-mechanical generalization of the Gaussian Network Model (GNM) by constructing spanning-tree partition functions for residue-contact graphs using the weighted Kirchhoff Laplacian in conjunction with the Matrix-Tree Theorem. Within this framework, the standard GNM is recovered in the high-temperature limit, whereas the present formulation enables a continuous Boltzmann-weighted ensemble analysis. We compute the network free energy , mean contact energy , heat capacity , and thermodynamic entropy across an effective temperature sweep that maps the combinatorial diversity of the contact network, thereby probing the topological landscape rather than structural melting. Differential analysis reveals that KRAS activation reflects a systematic entropy-enthalpy compensation mechanism: the active state incurs a systematic energetic penalty that is offset by a marked gain in conformational entropy , with a free-energy crossover occurring at . Edge marginal inclusion probabilities, obtained via effective-resistance theory, identify Switch I (residues 25-40) as the primary allosteric locus of nucleotide-driven network reorganization. This approach provides a thermodynamically grounded perspective on KRAS allostery, quantitatively demonstrating how network architecture enables functional versatility through entropy-driven conformational flexibility.
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5. Structural Basis for Single-Site Cleavage of Lactoferrin by Diverse Proteases for Prolonged Antibacterial Action: Structure of the Chymotrypsin-Cleaved Lactoferrin C-Lobe.
PMID:日期:2026-10-01The stable lactoferrin C-lobe offers strong potential for therapeutic applications as an antibacterial agent. Lactoferrin is a 78 kDa (Ala1Arg689) iron-binding glycoprotein which is composed of two homologous N- and C-lobes, connected by an 11-residue α-helical linker (Thr334Arg344). The limited proteolysis of lactoferrin, carried out using chymotrypsin, generated a 40 kDa, fully functional C-lobe. The structure determination revealed that the protein chain consisted of residues from Thr343 to Leu680 together with a disulfide-linked tripeptide, Ala683Cys684Ala685. It showed that the cleavage occurred specifically at the Tyr342Thr343 peptide bond within the inter-lobe 11-residue-long peptide. Remarkably, previous studies using proteinase K, trypsin, and pepsin also produced an identical C-lobe. Thus, the inter-lobe region seems to be stereochemically designed by nature for the single-site cleavage by multiple digestive enzymes. The proteolytically generated C-lobe, with three observed glycosylation sites, remains stable for 3 days in the presence of digestive enzymes. The stable C-lobe continues to sequester iron, thus showing a prolonged antibacterial property. This is a unique example of evolutionary convergence whereby multiple digestive enzymes cleave a native protein into a stable half molecule with full antibacterial action.
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6. Universal and Lineage-Specific Patterns in the Distribution of ECOD Domain Homology Groups Across Superkingdoms.
PMID:日期:2026-10-01Proteins are built from modular domains that serve as fundamental units of structure and evolution. While individual domains have been extensively cataloged, their collective distribution across the lineages of life has remained poorly resolved. Here, we use the Evolutionary Classification of Protein Domains (ECOD) to chart the occurrence of domain homology groups (H-groups) across 44 model proteomes representing Eukaryota, Bacteria, and Archaea, in which 1.16 million domains are assigned to 3320 H-groups. H-groups are categorized as universal (occupying all three superkingdoms), shared between superkingdoms, or lineage-specific. The fold architecture distributions were examined: α/β sandwiches and other mixed architectures were abundant in universal H-groups, whereas α-rich architectures are expanded in eukaryotic H-groups and β-rich folds in bacterial H-groups. 126 (3.8%) H-groups occur in all organisms, forming a universal structural core that supports central processes of energy conversion, metabolism, and information flow. These widely distributed folds coincide with canonical superfolds-robust, adaptable architectures repeatedly repurposed for key biochemical roles. Two superkingdom groups trace evolutionary connections between lineages: bacterial metabolic and chaperone systems inherited by eukaryotes, archaeal informational machinery conserved in eukaryotic nuclei, and ancient redox scaffolds linking bacteria and archaea. Lineage-exclusive domains, in turn, highlight distinct adaptive strategies-regulatory and cytoskeletal innovation in eukaryotes, envelope and motility specialization in bacteria, and redox or replication refinements in archaea. Together, these data provide a quantitative, structure-based view of protein domain evolution across the tree of life, showing that the essential architecture of life relies on a conserved set of ancient folds, while lineage-specific diversity has largely arisen through the recombination and functional diversification of pre-existing domains.
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7. Ankh-Score Produces Better Sequence Alignments Than AlphaFold3.
PMID:日期:2026-10-01Protein sequence alignment is one of the most fundamental procedures in bioinformatics. Due to its many downstream applications, improvements to this procedure are of great importance. We consider two revolutionary concepts that emerged recently as candidates for improving the state-of-the-art alignment methods: AlphaFold and protein language models such as Ankh, ProtT5, or ESM-C. Alignment improvements can come from the structural alignment of AlphaFold-predicted structures or the scoring based on the similarity of protein embeddings produced by the protein language models. Thorough comparison on many domains from BAliBASE and CDD demonstrates that the Ankh-score method produces much better sequence alignments than the structural alignments using US-align of AlphaFold3-predicted structures. Both are better than the traditional method using BLOSUM matrices. This suggests that Ankh embeddings may possess certain information that is not available in the AlphaFold3-predicted structures. The alignment software is freely available as a web server at e-score.csd.uwo.ca and as source code at github.com/lucian-ilie/E-score.
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8. Decoding RNA-Dependent Protein Phase Separation Using an Ensemble-Based Deep Learning Framework Integrating ProtBERT Embeddings With Physicochemical Features.
PMID:日期:2026-09-24Liquid-liquid phase separation (LLPS) drives the formation of membraneless biomolecular condensates that regulate essential cellular processes including gene expression, stress response, and signal transduction. A critical challenge in this field is distinguishing RNA-dependent from RNA-independent condensates, a distinction central to the pathology of neurodegenerative disorders. Current computational approaches typically overlook this separation. Here, we introduce an interpretable two-stage deep learning framework that first predicts the likelihood of a protein sequence undergoing phase separation, and subsequently determines whether condensate formation is RNA-dependent. Our framework integrates deep contextual embeddings obtained from ProtBERT, a pretrained protein language transformer with 66 handcrafted sequence-derived features. These representations are processed using an ensemble of machine learning classifiers, and their outputs are combined using a stacked artificial neural network, capturing both local sequence traits and global contextual information. Interpretability analyses like SHAP and feature correlation demonstrate that the most predictive ProtBERT embedding dimensions are associated with sequence-derived hallmarks of LLPS, including descriptors related to intrinsic disorder and multivalent interaction motifs. Benchmarking shows that our framework achieves superior performance compared to the existing predictors on the external test set with 96.5% accuracy, F1-score of 0.965, and MCC of 0.931. It also shows superior performance over the sole existing RNA-dependent LLPS predictor. Structural analysis of representative misclassifications further reveals how spatial constraints and topology modulate phase separation beyond sequence features. This study offers a unified approach for modeling RNA-mediated phase separation from protein sequence and establishes a foundation for bridging sequence-based prediction with structural understanding of biomolecular condensates.
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9. Method for the Determination of Dynamic Domains in Proteins From Structural Pairs and Conformational Ensembles.
PMID:日期:2026-09-24A straightforward method for the determination of dynamic domains from pairs of conformations or general conformational ensembles of proteins is presented. The method applies metric multi-dimensional scaling (MDS) to distance-differences or root-mean square-fluctuations of inter-atomic distances (RMSFIDs). The approach determines points in a low-dimensional space, each representing an amino-acid residue, where distances between the points give an approximation to the distance-differences, in the case of a pair of conformations, or RMSFIDs for an ensemble. This point-based representation enables top-down clustering methods to be used to determine dynamic domains. The two implementations, Pair-DD and Ensemble-DD, are demonstrated on idealized examples where domains move as perfect rigid bodies, on conformational pairs and ensembles derived from X-ray structures both monomeric and multimeric, and on trajectories derived from simulation methods. A parameter is proposed which can be used as a threshold for acceptance of dynamic domains to enable automatic assignment. The results show excellent correspondence with a well-established approach, but the method has the added advantage of being versatile in that it is applicable to both a pair of structures and an ensemble of conformations. Furthermore, for a pair of conformations, a one-dimensional MDS coordinate seems to be sufficient, meaning that the degree of association of a residue with a dynamic domain can be visualized in a simple plot.
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10. Evolution of the SARS-CoV-2 Main Protease Under Fitness Constraints Imposed by Folding Stability and Activity.
PMID:日期:2026-09-24The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve and diversify, leading to the emergence of immune-evasive variants and underscoring the need for complementary antiviral strategies targeting conserved viral machinery. In this context, the main protease (Mpro) represents a potential therapeutic target because of its central role in viral replication and its low similarity to human proteases. However, the evolutionary consequences of Mpro variation on substrate recognition and potential resistance remain insufficiently explored. Through the analysis of multiple SARS-CoV-2 Mpro variants, we show that, despite ongoing viral diversification, Mpro evolution has remained remarkably constrained since the emergence of the Omicron-associated P132H lineage in 2022, with limited amino-acid substitutions in the active-site and dimerization-interface regions. Across the most prevalent SARS-CoV-2 variants, overall substrate recognition by Mpro was largely preserved, although specific variant-substrate pairs exhibited some heterogeneity in per-residue interactions and hydrogen-bond patterns. Ensemble dynamics revealed conserved large-scale motions alongside modest substrate-dependent shifts in secondary motions in certain Mpro variants. Overall, SARS-CoV-2 Mpro evolution is strongly constrained by structural and functional requirements, supporting the suitability of this protein as an effective antiviral target. The findings further suggest that incorporating viral evolutionary dynamics may help inform the design of therapeutic strategies with improved long-term robustness.