Proteins-Structure Function and Bioinformatics最新文献

{"title":"Investigating Local Sequence-Structural Attributes of Amyloidogenic Light Chain Variable Domains.","authors":"Puneet Rawat, R Prabakaran, Divya Sharma, Vasanth Mandala, Victor Greiff, Sandeep Kumar, M Michael Gromiha","doi":"10.1002/prot.26815","DOIUrl":"10.1002/prot.26815","url":null,"abstract":"<p><p>Light chain amyloidosis is a medical condition characterized by the aggregation of misfolded antibody light chains into insoluble amyloid fibrils in the target organs, causing organ dysfunction, organ failure, and death. Despite extensive research to understand the factors contributing to amyloidogenesis, accurately predicting whether a given protein will form amyloids under specific conditions remains a formidable challenge. In this study, we have conducted a comprehensive analysis to understand the amyloidogenic tendencies within a dataset containing 1828 (348 amyloidogenic and 1480 non-amyloidogenic) antibody light chain variable region (V_L) sequences obtained from the AL-Base database. Physicochemical and structural features often associated with protein aggregation, such as net charge, isoelectric point (pI), and solvent-exposed hydrophobic regions did not reveal a consistent association with the aggregation capability of the antibody light chains. However, the solvent-exposed aggregation-prone regions (APRs) occur with higher frequencies among the amyloidogenic light chains when compared with the non-amyloidogenic ones, with the difference ranging from 2% to 15% at various relative solvent-accessible surface area (rASA) cutoffs. We have, for the first time, identified structural gatekeeping residues around the APRs and assessed their impact on the amyloidogenicity of the antibody light chains. The non-amyloidogenic light chains contain these structural gatekeeper residues vicinal to their APRs more often than the amyloidogenic ones. We observed that the rASA cutoff of 35% is optimal for identifying the surface-exposed APRs, and a 4 Å distance cutoff from the APR motif(s) is optimal for identifying the structural gatekeeper residues. Moreover, lambda light chains were found to contain solvent-exposed APRs more often and surrounded by fewer gatekeepers, rendering them more susceptible to aggregation. The insights gained from this report have significant implications for understanding the molecular origins of light-chain amyloidosis in humans and the design of aggregation-resistant therapeutic antibodies.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1451-1464"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12314586/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural and Functional Differences of Rhodostomin and Echistatin in Integrin Recognition and Biological Implications.","authors":"Yi-Chun Chen, Chun-Hao Huang, Yao-Tsung Chang, Chiu-Yueh Chen, Jia-Hau Shiu, Chun-Ho Cheng, Yu-Fang Su, Woei-Jer Chuang","doi":"10.1002/prot.26834","DOIUrl":"10.1002/prot.26834","url":null,"abstract":"<p><p>Rhodostomin (Rho) and Echistatin (Ech) are RGD-containing disintegrins with different sizes, disulfide bond patterns, and amino acid sequences in their RGD loops and C-termini. Cell adhesion analyzes showed that Rho exhibited a 5.2-, 18.9-, 2.2-, and 1.7-fold lower inhibitory activity against integrins αvβ3, α5β1, αIIbβ3, and αvβ5 in comparison with those of Ech. In contrast, Rho exhibited an 8.8-fold higher activity than Ech in inhibiting integrin αvβ6. The swapping of Ech's RGD loop and C-terminal sequences into those of Rho cannot increase its integrins' inhibitory activities. Interestingly, the mutation of Ech into Rho's RGD loop PRGDMP sequence and C-terminal YH sequence caused an 8.2-fold higher activity in inhibiting integrin αvβ6. Structural analyzes of Rho and Ech showed that they have similar conformations in their RGD loop and different conformations in their C-terminal regions. Molecular docking found that not only the RGD loop but also the C-terminal region of Rho and Ech interacted with integrins, showing that the C-terminal region is also important for integrin recognition. The docking of Rho into integrin αvβ6 showed that the C-terminal H68 residue of Rho interacted with D129 of β6. In contrast, the docking of Ech into integrin α5β1 showed that the C-terminal H44 residue of Ech interacted with Q191 of β1. Ech exhibited 78.5- and 10.9-fold higher activities in inhibiting HUVEC proliferation and A375 melanoma cell migration than those of Rho. These findings demonstrate that the disulfide bond pattern, RGD loop, and C-terminal region of disintegrins may cause their functional differences. The functional and structural differences between Rho and Ech support their potential as scaffolds to design drugs targeting their respective integrins.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1627-1644"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural Investigation of the Anti-CRISPR Protein AcrIE7.","authors":"Jeehee Kang, Changkon Park, Gyujin Lee, Jasung Koo, Hyejin Oh, Eun-Hee Kim, Euiyoung Bae, Jeong-Yong Suh","doi":"10.1002/prot.26832","DOIUrl":"10.1002/prot.26832","url":null,"abstract":"<p><p>The CRISPR-Cas system is an adaptive immune system in prokaryotes that provides protection against bacteriophages. As a countermeasure, bacteriophages have evolved various anti-CRISPR proteins that neutralize CRISPR-Cas immunity. Here, we report the structural and functional investigation of AcrIE7, which inhibits the type I-E CRISPR-Cas system in Pseudomonas aeruginosa. We determined both crystal and solution structures of AcrIE7, which revealed a novel helical fold. In binding assays using various biochemical methods, AcrIE7 did not tightly interact with a single Cas component in the type I-E Cascade complex or the CRISPR adaptation machinery. In contrast, AlphaFold modeling with our experimentally determined AcrIE7 structure predicted that AcrIE7 interacts with Cas3 in the type I-E CRISPR-Cas system in P. aeruginosa. Our findings are consistent with a model where AcrIE7 inhibits Cas3 and also highlight the effectiveness and limitations of AlphaFold modeling.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1645-1656"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144058566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Overview of Property, Design, and Functionality of Linkers for Fusion Protein Construction.","authors":"Hadis Chatrdooz, Javad Sargolzaei","doi":"10.1002/prot.26812","DOIUrl":"10.1002/prot.26812","url":null,"abstract":"<p><p>Linkers are naturally occurring short amino acid sequences that are used to separate domains within a protein. The advent of recombinant DNA technology has made it possible to combine two interacting partners by introducing artificial linkers that often, allow for the production of stable and functional proteins. Glycine-rich linkers are useful for transient interactions, especially where the interaction is weak, by covalently linking proteins and forming a stable protein-protein complex. These linkers have also been used to generate covalently stable dimers and to connect two independent domains that create a ligand binding site or recognition sequence. Various structures of covalently linked protein complexes have been described using nuclear magnetic resonance methods, cryo-electron microscopy techniques, and X-ray crystallography; in addition, several structures where linkers have been used to generate stable protein-protein complexes, improve protein solubility, and obtain protein dimers are investigated, and also the design and engineering of the linker in fusion proteins is discussed. Therefore, one of the main factors for linker design and optimization is their flexibility, which can directly contribute to the physical distance between the domains of a fusion protein and describe the tendency of a linker to maintain a stable conformation during expression. We summarize the research on design and bioinformatics can be used to predict the spatial structure of the fusion protein. To perform simulations of spatial structures and drug molecule design, future research will concentrate on various correlation models.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1411-1425"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural Implications of HIV-1 Protease Subtype C Bound to Darunavir: A Molecular Dynamics Study.","authors":"Sankaran Venkatachalam, Sowmya Ramaswamy Krishnan, Ramesh Pandian, Yasien Sayed, M Michael Gromiha","doi":"10.1002/prot.26817","DOIUrl":"10.1002/prot.26817","url":null,"abstract":"<p><p>In recent years, Human Immunodeficiency Virus (HIV) remains a significant global health challenge, with millions affected worldwide, particularly in Africa and sub-Saharan regions. Despite advances in antiretroviral therapies, the genetic variability of HIV, including different subtypes and drug-resistant strains, poses persistent obstacles in the development of universally effective treatments. This study focuses on the dynamics of HIV protease, a key enzyme in viral replication and maturation, particularly targeting subtype C and its double insertion (HL) variant L38HL, in the context of interaction with Darunavir (DRV), a second-generation nonpeptidic protease inhibitor approved by the FDA in 2006. Through molecular dynamics simulations, structural analyses, dynamic cross-correlation analyses, and binding energy calculations, we investigated differences in the binding of DRV to WT and L38HL HIV-1 protease. The findings highlight that the double insertion at the hinge induces variation in Φ and Ψ angles, leading to increased residue fluctuations, solvent-accessible surface area (SASA), and radius of gyration (R_g). This alters the overall structural compactness and the hydrophobic core crucial for drug binding. Subtle structural changes result in the loss of hydrogen bond interactions, reducing the binding energy of L38HL HIV-1 protease subtype C bound to DRV, leading to drug resistance.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1426-1435"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PCANN Program for Structure-Based Prediction of Protein-Protein Binding Affinity: Comparison With Other Neural-Network Predictors.","authors":"Olga O Lebedenko, Mikhail S Polovinkin, Anastasiia A Kazovskaia, Nikolai R Skrynnikov","doi":"10.1002/prot.26821","DOIUrl":"10.1002/prot.26821","url":null,"abstract":"<p><p>In this communication, we introduce a new structure-based affinity predictor for protein-protein complexes. This predictor, dubbed PCANN (Protein Complex Affinity by Neural Network), uses the ESM-2 language model to encode the information about protein binding interfaces and graph attention network (GAT) to parlay this information into <math> <semantics> <mrow><msub><mi>K</mi> <mi>d</mi></msub> </mrow> </semantics> </math> predictions. In the tests employing two previously unused literature-extracted datasets, PCANN performed better than the best of the publicly available predictors, BindPPI, with mean absolute error (MAE) of 1.3 versus 1.4 kcal/mol. Further progress in the development of <math> <semantics> <mrow><msub><mi>K</mi> <mi>d</mi></msub> </mrow> </semantics> </math> predictors using deep learning models is faced with two problems: (i) the amount of experimental data available to train and test new predictors is limited and (ii) the available <math> <semantics> <mrow><msub><mi>K</mi> <mi>d</mi></msub> </mrow> </semantics> </math> data are often not very accurate and lack internal consistency with respect to measurement conditions. These issues can be potentially addressed through an AI-leveraged literature search followed by careful human curation and by introducing additional parameters to account for variations in experimental conditions.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1498-1506"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12314579/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143671758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Actin-Binding Prolyl-Isomerase Par17 Sustains Its Substrate Selectivity by Interdomain Allostery.","authors":"Anna Sternberg, Jennifer Lynne Borger, Mathilda Thies, Anja Matena, Mike Blueggel, Bianca E Kamba, Christine Beuck, Farnusch Kaschani, Markus Kaiser, Peter Bayer","doi":"10.1002/prot.26807","DOIUrl":"10.1002/prot.26807","url":null,"abstract":"<p><p>The human peptidyl-prolyl-cis/trans isomerases (PPIases), Parvulin 14 and Parvulin 17, accelerate the cis/trans isomerization of Xaa-Pro moieties within protein sequences. By modulating the respective binding interfaces of their target proteins, they play a crucial role in determining the fate of their substrates within the cell. Although both enzymes share the same amino acid sequence, they have different cellular functions. This difference is due to a 25 residue N-terminal extension present in Par17 but absent in Par14. Using activity assays, NMR spectroscopy, and mass spectrometry, we demonstrate that the N-terminal extension of Par17 determines substrate selectivity by an intramolecular allosteric mechanism and exhibits a target-binding motif that interacts with actin.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1481-1497"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12314576/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction and Evaluation of Coronavirus and Human Protein-Protein Interactions Integrating Five Different Computational Methods.","authors":"Binghua Li, Xiaoyu Li, Xian Tang, Jia Wang","doi":"10.1002/prot.26826","DOIUrl":"10.1002/prot.26826","url":null,"abstract":"<p><p>The high lethality and infectiousness of coronaviruses, particularly SARS-Cov-2, pose a significant threat to human society. Understanding coronaviruses, especially the interactions between these viruses and humans, is crucial for mitigating the coronavirus pandemic. In this study, we conducted a comprehensive comparison and evaluation of five prevalent computational methods: interolog mapping, domain-domain interaction methodology, domain-motif interaction methodology, structure-based approaches, and machine learning techniques. These methods were assessed using unbiased datasets that include C1, C2h, C2v, and C3 test sets. Ultimately, we integrated these five methodologies into a unified model for predicting protein-protein interactions (PPIs) between coronaviruses and human proteins. Our final model demonstrates relatively better performance, particularly with the C2v and C3 test sets, which are frequently used datasets in practical applications. Based on this model, we further established a high-confidence PPI network between coronaviruses and humans, consisting of 18,012 interactions between 3843 human proteins and 129 coronavirus proteins. The reliability of our predictions was further validated through the current knowledge framework and network analysis. This study is anticipated to enhance mechanistic understanding of the coronavirus-human relationship a while facilitating the rediscovery of antiviral drug targets. The source codes and datasets are accessible at https://github.com/covhppilab/CoVHPPI.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1553-1570"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144014202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Structural Classification Using AlphaFold2 Models Through ECOD-Based Comparative Analysis.","authors":"Takeshi Kawabata, Kengo Kinoshita","doi":"10.1002/prot.26828","DOIUrl":"10.1002/prot.26828","url":null,"abstract":"<p><p>Identifying homologous proteins is a fundamental task in structural bioinformatics. While AlphaFold2 has revolutionized protein structure prediction, the extent to which structure comparison of its models can reliably detect homologs remains unclear. In this study, we evaluate the feasibility of homology detection using AlphaFold2-predicted structures through structural comparisons. We considered the classification of the ECOD database for experimental structures as the correct standard and obtained their corresponding predicted models from AlphaFoldDB. To ensure blind assessment, we divided the structures into test and train sets according to their release date. Predicted and experimental 3D structures in the test and train sets were compared using 3D structure comparisons (MATRAS, Dali, and Foldseek) and sequence comparisons (BLAST and HHsearch). The results were evaluated based on the homology annotations in the ECOD database. For top-1 accuracy, the performance of structural comparisons was comparable to that of HHsearch. However, when considering metrics that included all structural pairs, including more remote homology, structural comparisons outperformed HHsearch. No significant differences were observed between comparisons of experimental versus experimental, predicted versus experimental, and predicted versus predicted structures with pLDDT (prediction confidence) values greater than 60. We also demonstrate that predicted protein structures, determined by NMR, had lower pLDDT values and contained fewer coils than their experimental counterparts. These findings highlight the potential of AlphaFold2 models in structural classification and suggest that 3D structural searches should be conducted not only against the PDB but also against AlphaFoldDB to identify more potential homologs.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1571-1585"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12314581/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144035619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Updates to the CASP Infrastructure in 2024.","authors":"Andriy Kryshtafovych, Maciej Milostan, Marc F Lensink, Sameer Velankar, Alexandre M J J Bonvin, John Moult, Krzysztof Fidelis","doi":"10.1002/prot.70042","DOIUrl":"10.1002/prot.70042","url":null,"abstract":"<p><p>CASP (critical assessment of structure prediction) conducts community experiments to determine the state of the art in calculating macromolecular structures. The CASP data management system is continually evolving to address the changing needs of the experiments. For CASP16, we expanded the infrastructure to enable data handling of newly introduced categories and fully support pilot categories introduced in CASP15. This technical note also documents the integration of the CASP and CAPRI (Critical Assessment of PRedicted Interactions) systems.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12422709/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}