{"doi":"10.1093/pnasnexus/pgae541","title":"In silico screening of protein-binding peptides with an application to developing peptide inhibitors against antibiotic resistance","abstract":"Abstract The field of therapeutic peptides is experiencing a surge, fueled by their advantageous features. These include predictable metabolism, enhanced safety profile, high selectivity, and reduced off-target effects compared with small-molecule drugs. Despite progress in addressing limitations associated with peptide drugs, a significant bottleneck remains: the absence of a large-scale in silico screening method for a given protein target structure. Such methods have proven invaluable in accelerating small-molecule drug discovery. The high flexibility of peptide structures and the large diversity of peptide sequences greatly hinder the development of urgently needed computational methods. Here, we report a method called MDockPeP2_VS to address these challenges. It integrates molecular docking with structural conservation between protein folding and protein–peptide binding. Briefly, we discovered that when the interfacial residues are conserved, a sequence fragment derived from a monomeric protein exhibits a high propensity to bind a target protein with a similar conformation. This valuable insight significantly reduces the search space for peptide conformations, resulting in a substantial reduction in computational time and making in silico peptide screening practical. We applied MDockPeP2_VS to develop peptide inhibitors targeting the TEM-1 β-lactamase of Escherichia coli, a key mechanism behind antibiotic resistance in gram-negative bacteria. Among the top 10 peptides selected from in silico screening, TF7 (KTYLAQAAATG) showed significant inhibition of β-lactamase activity with a Ki value of 1.37 ± 0.37 µM. This fully automated, large-scale structure-based in silico peptide screening software is available for free download at https://zougrouptoolkit.missouri.edu/mdockpep2_vs/download.html.","journal":"PNAS Nexus","year":2024,"id":447951,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9516,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1266564,"name":"Wei-Ling Kao","orcid":null,"position":1,"is_corresponding":false},{"id":574648,"name":"Allison B. Wang","orcid":"0000-0002-0660-9138","position":2,"is_corresponding":false},{"id":1266565,"name":"Hsin-Jou Lee","orcid":null,"position":3,"is_corresponding":false},{"id":1057589,"name":"Rui Duan","orcid":"0000-0003-1646-4013","position":4,"is_corresponding":false},{"id":510157,"name":"Hannah Holmes","orcid":"0000-0002-2004-6423","position":5,"is_corresponding":false},{"id":345010,"name":"Fabio Gallazzi","orcid":"0000-0002-2441-2398","position":6,"is_corresponding":false},{"id":785933,"name":"Juan Ji","orcid":"0000-0003-4154-1674","position":7,"is_corresponding":false},{"id":329249,"name":"Hongmin Sun","orcid":"0000-0003-4545-2417","position":8,"is_corresponding":false},{"id":452955,"name":"Xiao Heng","orcid":"0000-0001-8448-3596","position":9,"is_corresponding":false},{"id":315107,"name":"Xiaoqin Zou","orcid":"0000-0003-0637-8648","position":10,"is_corresponding":false},{"id":759498,"name":"Xianjin Xu","orcid":"0000-0002-5011-2997","position":0,"is_corresponding":true}],"reference_count":51,"raw_metadata":null,"created_at":"2026-07-19T02:02:03.354708Z","pmid":"39660074","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}