Proteins-Structure Function and Bioinformatics最新文献

{"title":"Docking With Rosetta and Deep Learning Approaches in CAPRI Rounds 47-55.","authors":"Ameya Harmalkar, Lee-Shin Chu, Samuel W Canner, Rituparna Samanta, Rahel Frick, Fatima A Davila-Hernandez, Sudeep Sarma, Fatima Hitawala, Jeffrey J Gray","doi":"10.1002/prot.70016","DOIUrl":"10.1002/prot.70016","url":null,"abstract":"<p><p>Critical Assessment of PRediction of Interactions (CAPRI) rounds 47 through 55 introduced 49 targets comprising multistage assemblies, antibody-antigen complexes, and flexible interfaces. For these rounds, we combined various Rosetta docking approaches (RosettaDock, ReplicaDock, and SymDock) with deep learning approaches (AlphaFold2, IgFold, and AlphaRED). Since prior CAPRI rounds, we have developed methods to better capture conformational changes, updated our scoring function, and integrated structure prediction tools such as AlphaFold2 in our docking routines. Here, we highlight several notable CAPRI targets and address the major challenges in the blind prediction of protein-protein interactions, including binding-induced conformational changes, large multimeric proteins, and antibody-antigen interactions. Although predictors have achieved modest improvements in accuracy for simpler targets post-AlphaFold2, performance for more flexible complexes remains limited. We employed RosettaDock 4.0, ReplicaDock 2.0, and AlphaRED to enhance backbone conformational sampling for flexible complexes. Our docking routines improved the DockQ score (0.77 vs. 0.62 for AF2-multimer) for a GP2 bacteriophage protein (T194), effectively capturing binding-induced conformational changes. Additionally, we introduce a fold-and-dock approach for predicting the assembly of a surface-layer SAP protein derived from Bacillus anthracis (T160), a large hetero-multimer comprising six distinct sub-units. For large symmetric complexes, we used Rosetta-based SymDock 2.0, successfully predicting a human DNA repair protein complex with A10 stoichiometry (T230) with high CAPRI-quality ranking. We also address the challenges in modeling antibody/nanobody-antigen interactions, particularly through the integration of deep learning tools and docking methods. Despite advances with tools like IgFold and AlphaFold2, accurately predicting CDR H3 loops and antibody-antigen binding interfaces remains challenging. Combining ReplicaDock 2.0 with deep learning highlights these difficulties and underscores the need for extensive sampling and CDR-focused strategies to improve prediction accuracy.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12462888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115054","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":"Metal-Coordination Specificity and Structural Dynamics of C. elegans Metallothionein I: Insights From 3D Modeling and MD Simulations.","authors":"Nilvea Ramalho de Oliveira, Andrei Santos Siqueira, Paulo Sérgio Alves Bueno, Evonnildo Costa Gonçalves, Juliano Zanette","doi":"10.1002/prot.70054","DOIUrl":"https://doi.org/10.1002/prot.70054","url":null,"abstract":"<p><p>Metallothioneins (MTLs) are small, cysteine-rich proteins known for their ability to bind metal ions and exhibit flexible, disordered structures. The structural and functional characteristics of metallothionein I (MTL-1) from Caenorhabditis elegans were investigated, focusing on its behavior in both metal free (MTL-1 Apo) and metal-bond states with Zn²⁺, Cd²⁺, Cu²⁺, Hg²⁺, and Pb²⁺ divalent metal ions. Using molecular dynamics simulations and 3D modeling via AlphaFold, we characterized the flexibility and stability of MTL. The MTL-1 Apo form displayed high flexibility, aligning with its intrinsically disordered protein (IDP) nature, with 89.3% of its structure composed of coils, bends, and turns. Metal binding significantly enhanced the protein's stability, particularly with Zn²⁺, Cd²⁺, Cu²⁺, and Hg²⁺, reducing root mean square deviation (RMSD), root mean square fluctuation (RMSF), accessible surface area (SASA) and radius of gyration (R_g) values, indicating structural compaction. Conversely, Pb²⁺ showed a weaker stabilizing effect, with a more dynamic and less stable structure. Structural analysis revealed that conserved cysteine residues coordinate the metal through strong thiolate interactions, with additional contributions from non-cysteine residues, such as Glu and Lys. The study underscores the importance of incorporating intrinsically disordered protein models in MD simulations to provide deeper insights into how metallothionein's flexibility and stability vary in response to different metal ions, offering a structural perspective on their biological interactions and behavior under diverse environmental conditions. While thermodynamic aspects were not directly assessed, the results reveal consistent conformation trends across different metal coordination states.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115073","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":"In Silico Characterization of Bromo-DragonFLY Binding to the 5-HT_2A Receptor: Molecular Insights Into a Potent Designer Psychedelic.","authors":"Syeda Sumayya Tariq, Urooj Qureshi, Mamona Mushtaq, Sajida Munsif, Mohammad Nur-E-Alam, Mohammed F Hawwal, Yan Wang, Zaheer Ul-Haq","doi":"10.1002/prot.70055","DOIUrl":"https://doi.org/10.1002/prot.70055","url":null,"abstract":"<p><p>Bromo-DragonFLY (BDF), a potent designer psychedelic drug with hallucinogenic properties, has recently emerged as a significant recreational substance. Named for its dragonfly-like molecular structure, BDF induces prolonged psychedelic effects, with hallucinations lasting several days. Clinical reports highlight severe toxicity, including confusion, tachycardia, hypertension, seizures, renal failure, and, in extreme cases, death. BDF acts as a potent agonist of the 5-HT2A serotonin receptor subtype, which mediates the behavioral and psychedelic effects of hallucinogens. Despite its increasing prevalence and associated clinical implications, the precise molecular mechanisms underlying BDF's interaction with 5-HT2A remain inadequately characterized, particularly from an in silico perspective. This study addresses this gap by employing a comprehensive in silico framework to investigate the molecular interactions of BDF with the 5-HT_2A receptor. Molecular docking was used to identify binding sites, while all-atom molecular dynamics (MD) simulations provided insights into the stability of the protein-ligand complex, assessing deviations, local flexibility, and time-dependent gyration patterns. The results revealed stable and compact complex formation between BDF and 5-HT_2A, characterized by minimal per-residue fluctuations and high hydrogen bond occupancy, suggesting a highly stable interaction as shown experimentally. Additionally, principal component analysis, leveraging machine learning algorithms, demonstrated consistent motion, while free energy profiles highlighted stable energy basins with minimal variations for the BDF-5-HT_2A complex. These findings suggest strong binding affinities of BDF with the serotonin receptor, leading to highly stable complex formation. This study provides a foundational understanding of BDF's molecular interactions, offering critical insights into its role as a potent psychedelic agent and laying the groundwork for future investigations into the risks posed by novel designer drugs.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145076829","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":"AlphaFold Kinase Optimizer: Enhancing Virtual Screening Performance Through Automated Refinement of AlphaFold-Based Kinase Structures.","authors":"Sergei Evteev, Yan Ivanenkov, Andrew Aiginin, Maksim Kuznetsov, Rim Shayakhmetov, Maksim Knyazev, Dmitry Bezrukov, Alex Malyshev, Maxim Malkov, Alex Aliper, Alex Zhavoronkov","doi":"10.1002/prot.70056","DOIUrl":"https://doi.org/10.1002/prot.70056","url":null,"abstract":"<p><p>AlphaFold (AF) is a valuable tool for generating protein 3D structures, but its application in structure-based drug design is limited. In this study, we introduce AF Optimizer-a new deep learning-assisted approach that refines binding site geometry based on neural network scores and calculated free binding energy. We refined TTK protein geometry using AF Optimizer and performed virtual screening using the optimized version of the AF-generated protein model. The application of the model showed a decrease in steric clashes with ligands from known crystal complexes, more precise results of molecular docking and virtual screening, and hits enrichment during a prospective in vitro study.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145071078","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":"Kinetic Characterization of Inhibition of Cathepsins L and S by Peptides With Anticancer Potential.","authors":"Olga E Chepikova, Victoria I Bunik, Ivan V Rodionov, Neonila V Gorokhovets, Andrey A Zamyatnin, Lyudmila V Savvateeva","doi":"10.1002/prot.70047","DOIUrl":"https://doi.org/10.1002/prot.70047","url":null,"abstract":"<p><p>Cysteine cathepsins have been suggested as attractive therapeutic targets due to their critical role in several pathologies. In particular, inhibitors of cysteine cathepsins reduce the viability of tumor cells. The present study uses enzyme kinetics to characterize the interaction of human cathepsins L and S with their peptide substrate acetyl-QLLR-7-amino-4-methylcoumarin (Ac-QLLR-AMC) and peptide inhibitors with anti-tumor activity: FFSFGGAL (CS-PEP1) and acetyl-PLVE-fluoromethyl-ketone (Ac-PLVE-fmk). Due to multiple cellular locations of cathepsins, our study is conducted under different pH conditions, simulating lysosomal and cytosolic environments (pH 4.6 and 6.5-7.0). Catalytic activities of both cathepsins are higher at pH 6.5-7.0 compared to pH 4.6. Affinities for the substrate or inhibitor CS-PEP1 are higher for cathepsin L than S independent of pH, but show different pH sensitivities, reciprocating different pI's of the cathepsins. Mixed inhibition by CS-PEP1 is demonstrated for both cathepsins. While preincubation of cathepsins with CS-PEP1 does not enhance the inhibition, Ac-PLVE-fmk inactivates both cathepsins in the preincubation medium. A strong increase in the inactivation rate is observed with increasing pH in the interval including pK_a of the active site cysteine residues of cathepsins, in agreement with the irreversible modification by mono-fluoromethyl ketones of the catalytic thiolate anion. At pH 4.6, cathepsin L has a higher affinity for Ac-PLVE-fmk, but a slower rate of the irreversible modification compared to cathepsin S. Our findings highlight opportunities for differential targeting of L and S cathepsins by peptide inhibitors in different cellular compartments, providing directions for cathepsin- and location-specific drug design.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145042463","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":"Effect of L110M Mutation on the Structure and Stability of ATTR(105-115) Peptide Assembly: A Computational Study.","authors":"Prabuddha Bhattacharya, Sumit Mittal","doi":"10.1002/prot.70046","DOIUrl":"https://doi.org/10.1002/prot.70046","url":null,"abstract":"<p><p>The mechanisms driving amyloid assembly have long intrigued structural biologists, as they offer insights into systemic fibrotic changes and the dynamic behavior of transthyretin (TTR) aggregation, crucial for developing amyloid-targeted therapies. In TTR-associated amyloidosis, amyloid fibrils form via destabilization of the tetramer into dimers and monomers. While many TTR mutations have been studied, the atomistic impact of multiple mutations on amyloid transthyretin (ATTR) self-assembly remains underexplored. To the best of our knowledge, this is the first computational analysis reporting the impact of the L110M mutation on ATTR peptide aggregation. Using triplicate 1 μs all-atom molecular dynamics (MD) simulations, totaling 18 μs, the conformational dynamics of cross-β amyloid fibrils in the ATTR(105-115) segment were examined for both wild-type and L110M mutant TTR. The L110M mutation consistently enhanced the β-sheet content in all oligomers, with increases of ~1%, ~5%, and ~4% over the wild-type in the 2-, 4-, and 8-peptide systems, respectively. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations revealed higher effective binding free energy for the L110M mutant, with residue M110 contributing significantly to stabilization. These results suggest that L110M modestly enhances conformational order and stability in the TTR peptide assemblies without major structural disruption, deepening our understanding of amyloidogenesis in TTR-related disorders.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144994772","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":"Functional Relevance of CASP16 Nucleic Acid Predictions as Evaluated by Structure Providers.","authors":"Rachael C Kretsch, Reinhard Albrecht, Ebbe S Andersen, Hsuan-Ai Chen, Wah Chiu, Rhiju Das, Jeanine G Gezelle, Marcus D Hartmann, Claudia Höbartner, Yimin Hu, Shekhar Jadhav, Philip E Johnson, Christopher P Jones, Deepak Koirala, Emil L Kristoffersen, Eric Largy, Anna Lewicka, Cameron D Mackereth, Marco Marcia, Michela Nigro, Manju Ojha, Joseph A Piccirilli, Phoebe A Rice, Heewhan Shin, Anna-Lena Steckelberg, Zhaoming Su, Yoshita Srivastava, Liu Wang, Yuan Wu, Jiahao Xie, Nikolaj H Zwergius, John Moult, Andriy Kryshtafovych","doi":"10.1002/prot.70043","DOIUrl":"10.1002/prot.70043","url":null,"abstract":"<p><p>Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non-canonical regions where, for example, the nucleic-acid backbone bends, deviating from an A-form helix geometry, or a base forms a non-standard hydrogen bond (not a Watson-Crick base pair). These bends and non-canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12412911/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144994734","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":"Protein-RNA Docking Benchmark v3.0 Integrated With Binding Affinity.","authors":"Shri Kant, Chandran Nithin, Sunandan Mukherjee, Atanu Maity, Ranjit Prasad Bahadur","doi":"10.1002/prot.26825","DOIUrl":"10.1002/prot.26825","url":null,"abstract":"<p><p>We introduce an updated non-redundant protein-RNA docking benchmark version 3.0 (PRDBv3.0) containing 197 test cases curated from 288 unique protein-RNA complexes available in the Protein Data Bank until July 2024. Among these, 27 are unbound-unbound (UU) type where both the binding partners are available in their unbound states, 160 are unbound-bound (UB) type where only the protein is available in unbound state and remaining 10 are bound-unbound (BU) type where only the RNA is available in unbound state. The benchmark is categorized into three classes based on the conformational flexibility of the protein interface: 117 rigid-body (R) complexes with minimal structural changes, 41 semi-flexible (S) complexes showing moderate conformational changes and 29 full-flexible (F) complexes with significant conformational changes. The current benchmark represents a 62% increase in the number of test cases compared to its previous version. Binding affinity (K_d) values for a subset of 105 protein-RNA complexes from PRDBv3.0 are catalogued along with additional experimental details to develop a comprehensive protein-RNA affinity benchmark. Moreover, a total of 255 unique RNA-binding domains, present in RNA-binding proteins, are also catalogued in this updated benchmark. PRDBv3.0 will facilitate the evaluation of both rigid-body and flexible docking methods as well as the methods that aim to predict binding affinity. The updated benchmark is freely available at http://www.csb.iitkgp.ac.in/applications/PRDBv3/PRDBv3.php.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1534-1552"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813025","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":"Insights Into the Conformational Dynamics of the Cytoplasmic Domain of Metal-Sensing Sensor Histidine Kinase ZraS.","authors":"Nilima Mahapatra, Pranjal Mahanta, Shubhant Pandey, Rudresh Acharya","doi":"10.1002/prot.26819","DOIUrl":"10.1002/prot.26819","url":null,"abstract":"<p><p>ZraS is a metal sensor integral to ZraPSR, a two-component signaling system found in enterobacters. It belongs to a family of bifunctional sensor histidine kinases (SHKs) and is speculated to sense zinc-induced stress on the bacterial envelope. Information on the structure-function relationship of sensor kinases is elusive due to the lack of full-length structures, intrinsically dynamic behavior, and difficulty trapping them in active state conformations. While the kinase domains (KDs) of a few SHKs are well characterized, they exhibit significant functional diversity attributed to their modular multi-domain arrangement in the cytoplasmic region, combined with other signal transducing elements such as simple helices, HAMP, and PAS domains. We report the crystal structure of the entire cytoplasmic region of Escherichia coli ZraS (EcZraS-CD) resolved at a resolution of 2.49 Å, comprising a unique helical linker and the KD. In the asymmetric unit, four molecules of ZraS assemble as homodimers trapped as two ligand-bound occluded conformers. Our analysis using these conformers shows that modulation of the dimer bundle through segmental helical bending, sliding, and rotation leads to the reorganization of the dimerization interface during kinase activation. Further, our analysis reveals the significance of aromatic amino acid interactions and loop residues at the dimer base in regulating the directionality of rotation during autophosphorylation. We also performed an in vitro coupled assay to determine ATPase activity. Overall, our findings provide structure-based mechanistic insights into the process of autophosphorylation in trans-acting SHKs.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1465-1480"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12314577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588007","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":"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}