Proteins-Structure Function and Bioinformatics最新文献

{"title":"Integrative Protein Assembly With LZerD and Deep Learning in CAPRI 47-55.","authors":"Charles Christoffer, Yuki Kagaya, Jacob Verburgt, Genki Terashi, Woong-Hee Shin, Anika Jain, Daipayan Sarkar, Tunde Aderinwale, Sai Raghavendra Maddhuri Venkata Subramaniya, Xiao Wang, Zicong Zhang, Yuanyuan Zhang, Daisuke Kihara","doi":"10.1002/prot.26818","DOIUrl":"https://doi.org/10.1002/prot.26818","url":null,"abstract":"<p><p>We report the performance of the protein complex prediction approaches of our group and their results in CAPRI Rounds 47-55, excluding the joint CASP Rounds 50 and 54, as well as the special COVID-19 Round 51. Our approaches integrated classical pipelines developed in our group as well as more recently developed deep learning pipelines. In the cases of human group prediction, we surveyed the literature to find information to integrate into the modeling, such as assayed interface residues. In addition to any literature information, generated complex models were selected by a rank aggregation of statistical scoring functions, by generative model confidence, or by expert inspection. In these CAPRI rounds, our human group successfully modeled eight interfaces and achieved the top quality level among the submissions for all of them, including two where no other group did. We note that components of our modeling pipelines have become increasingly unified within deep learning approaches. Finally, we discuss several case studies that illustrate successful and unsuccessful modeling using our approaches.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143652274","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":"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":"https://doi.org/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":""},"PeriodicalIF":3.2,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","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":"","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":"https://doi.org/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":""},"PeriodicalIF":3.2,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","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":"","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":"https://doi.org/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":""},"PeriodicalIF":3.2,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","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":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the Role of RING-Between-RING E3 Ligase of the Human Malaria Parasite.","authors":"Varsha Kumari, Seema Vidyarthi, Aradhya Tripathi, Nirupa Chaurasia, Niharika Rai, Richa Shukla, Shagufa Nisrat Noorie, Girdhar Bhati, Simmi Anjum, Mohammad Anas, Shakil Ahmed, Niti Kumar","doi":"10.1002/prot.26813","DOIUrl":"https://doi.org/10.1002/prot.26813","url":null,"abstract":"<p><p>E3 ligases constitute an important component of proteostasis machinery, which plays a critical role in the survival of malaria parasites through post-translational modifications of their protein substrates. In contrast to humans, parasite E3 ligases have not been extensively studied. Here, we characterize a unique Plasmodium E3 ligase that has both RING and HECT-like features with zinc-coordinating domains. Plasmodium encodes a single RING-between-RING (RBR) E3 ligase that has evolutionarily diverged from human and other intracellular parasites. This RBR-E3 ligase is expressed throughout the erythrocytic phase of the P. falciparum lifecycle. Immunoprecipitation experiments showed that Pf RBR-E3 ligase catalyzes K6, K11, K48, and K63 mediated polyubiquitination, hinting towards its probable biological roles (DNA repair, proteasomal degradation, mitochondrial quality control). We observed that Pf RBR-E3 ligase interacts with UBCH5 and UBC13 family of E2-conjugating enzymes. Through mutational analysis in Pf RBR-E3 ligase, we identified residues in RING1 and RING2 domains that are critical for ubiquitination activity and its protein stability. Pf RBR-E3 ligase exhibits differences in immunofluorescence profile upon exposure of the parasite to different genotoxic (MMS) and proteotoxic (MG132, FCCP and artemisinin derivative) stress. Our study opens up avenues for exploring the client substrates of Pf RBR-E3 ligase and using this knowledge to design substrate-specific protein degradation-based alternative intervention strategies for malaria.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544641","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":"https://doi.org/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":""},"PeriodicalIF":3.2,"publicationDate":"2025-03-03","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":"Towards a Greener AlphaFold2 Protocol for Antibody-Antigen Modeling: Insights From CAPRI Round 55.","authors":"Büşra Savaş, İrem Yılmazbilek, Atakan Özsan, Ezgi Karaca","doi":"10.1002/prot.26820","DOIUrl":"https://doi.org/10.1002/prot.26820","url":null,"abstract":"<p><p>In the 55th round of CAPRI, we used enhanced AlphaFold2 (AF2) sampling and data-driven docking. Our AF2 protocol relies on Wallner's massive sampling approach, which combines different AF2 versions and sampling parameters to produce thousands of models per target. For T231 (an antibody-peptide complex) and T232 (PP2A:TIPRL complex), we employed a 50-fold reduced MinnieFold sampling and a custom ranking approach, leading to a top-ranking medium prediction in both cases. For T233 and T234 (two antibody bound MHC I complexes), we followed data-driven docking, which did not lead to an acceptable model. Our post-CAPRI55 analysis showed that if we had used our MinnieFold approach on T233 and T234, we could have submitted a medium-quality model for T233 as well. In the scoring challenge, we utilized the scoring function of FoldX, which was effective in selecting acceptable models for T231 and medium-quality models for T232. Our success, especially in predicting and ranking a medium-quality model for T231 and potentially for T233, underscores the feasibility of green and accurate enhanced AF2 sampling in antibody complex prediction.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544689","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":"SARS-CoV-2 Mpro Dihedral Angles Reveal Allosteric Signaling.","authors":"Daniel Evans, Samreen Sheraz, Albert Y Lau","doi":"10.1002/prot.26814","DOIUrl":"10.1002/prot.26814","url":null,"abstract":"<p><p>In allosteric proteins, identifying the pathways that signals take from allosteric ligand-binding sites to enzyme active sites or binding pockets and interfaces remains challenging. This avenue of research is motivated by the goals of understanding particular macromolecular systems of interest and creating general methods for their study. An especially important protein that is the subject of many investigations in allostery is the SARS-CoV-2 main protease (Mpro), which is necessary for coronaviral replication. It is both an attractive drug target and, due to intense interest in it for the development of pharmaceutical compounds, a gauge of the state of the art approaches in studying protein inhibition. Here we develop a computational method for characterizing protein allostery and use it to study Mpro. We propose a role of the protein's C-terminal tail in allosteric modulation and warn of unintuitive traps that can plague studies of the role of protein dihedral angles in transmitting allosteric signals.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544684","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":"LGS-PPIS: A Local-Global Structural Information Aggregation Framework for Predicting Protein-Protein Interaction Sites.","authors":"Zhengli Zhai, Shiya Xu, Wenjian Ma, Niuwangjie Niu, Chunyu Qu, Chao Zong","doi":"10.1002/prot.26763","DOIUrl":"10.1002/prot.26763","url":null,"abstract":"<p><p>Exploring protein-protein interaction sites (PPIS) is of significance to elucidating the intrinsic mechanisms of diverse biological processes. On this basis, recent studies have applied deep learning-based technologies to overcome the high cost of wet experiments for PPIS determination. However, the existing methods still suffer from two limitations that remain to be solved. Firstly, the process of feature aggregation in most methods only took into account node features, but ignored the complex edge features of the target residue to its neighbor residues, resulting in insufficient local feature extraction. Secondly, such feature aggregation was limited to aggregating spatially adjacent residues, and could not capture the \"remote\" residues that played a critical role in determining PPIS, which can be summed up as the lack of global feature at the residue level. To break the above limitations, a local-global structural information aggregation framework, LGS-PPIS, was proposed in this study, including two modules of edge-aware graph convolutional network (EA-GCN) and self-attention integrated with initial residual and identity mapping (SA-RIM), which achieved the aggregation of local and global information for PPIS prediction. Evaluation results of LGS-PPIS showed that the proposed method outperformed state-of-the-art deep learning methods on three widely used PPIS prediction benchmarks. Besides, the results of ablation experiments demonstrated that the local features from spatially adjacent residues and global features from \"remote\" residues separately captured by EA-GCN and SA-RIM could benefit the model performance. Among them, the former was shown to have a more significant role in the PPIS prediction.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"716-727"},"PeriodicalIF":3.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142633086","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":"The Crystal Structure of the Domain of Unknown Function 1480 (DUF1480) From Klebsiella pneumoniae.","authors":"Dhruvin H Patel, Nobuhiko Watanabe, Alexei Savchenko, Cameron Semper","doi":"10.1002/prot.26752","DOIUrl":"10.1002/prot.26752","url":null,"abstract":"<p><p>Domains of unknown function (DUFs) continue to comprise a significant portion of bacterial proteomes, with more than 20% of bacterial proteins remaining annotated as DUFs. The characterization of their molecular structure can provide valuable insight that is not captured by the primary sequence analysis, thus providing a segue into the identification of the molecular function of DUF representatives. Here, we present the crystal structure of KPN_02352 from Klebsiella pneumoniae subsp. pneumoniae, a DUF1480 domain-containing protein, which was determined to be 1.75 Å resolution. Representatives of the DUF1480 family are found broadly across Enterobacterales and have been previously shown to contribute to the antibiotic response. Our structural analysis suggests that DUF1480 is comprised of a six-stranded split barrel fold featuring a small alpha helix that is positioned to cap one end of the split barrel. DUF1480 was found to be monomeric in solution, and harbors structural similarity to response regulators. The crystal structure of DUF1480 is the first experimental insight into the molecular structure of this conserved protein family, revealing several conserved features that may be functionally relevant.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"569-574"},"PeriodicalIF":3.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11809132/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333377","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}