{"title":"Repurposing FDA-approved drugs for combating tigecycline resistance in Acinetobacter baumannii: in silico screening against BaeR protein.","authors":"Karthika Alagesan, Hemavathy Nagarajan, Jeyaraman Jeyakanthan","doi":"10.1007/s11030-024-10988-5","DOIUrl":null,"url":null,"abstract":"<p><p>Acinetobacter baumannii is becoming a gravely threatening nosocomial infection with a higher mortality rate. The present study targets the BaeR protein that mediates resistance to tigecycline antibiotics. The BaeR protein, along with the aid of BaeS, senses the incoming antibiotics and stimulates the expression of resistance proteins. These resistance proteins efflux the antibiotics and protect the cells from its effect. The main goal of the current study is to determine potential inhibitors from already existing FDA-approved drugs that could mitigate the BaeR protein. A range of in silico approaches, including molecular dynamics, virtual screening, SIFT analysis, ADMET, DFT, MM/GBSA, MMPBSA and per residue interaction analysis, were performed to identify inhibitors against this protein. The screening of FDA-approved compounds against the BaeR protein yielded 620 compounds. These compounds were clustered by SIFT to distinguish related compounds, it resulted in 20 different clusters. The top five clusters that can accommodate the binding site with better interaction and score by fulfilling all criteria were selected. The DFT analysis showed a smaller energy gap among all the compounds, indicating the ability of the compound to form firm interactions. All the compounds showed less binding free energy in both MM/GBSA and MM/PBSA analyses. The compounds were observed to be stable throughout the simulation. The per-residue interaction analysis confirmed that interactions with binding site residues were stable throughout the simulation. As a result of the study, four compounds, namely ZINC000003801919, DB01203, DB11217 and ZINC0000000056652, were identified as efficient candidates to deal with antimicrobial resistance in A. baumannii.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Diversity","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1007/s11030-024-10988-5","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
Acinetobacter baumannii is becoming a gravely threatening nosocomial infection with a higher mortality rate. The present study targets the BaeR protein that mediates resistance to tigecycline antibiotics. The BaeR protein, along with the aid of BaeS, senses the incoming antibiotics and stimulates the expression of resistance proteins. These resistance proteins efflux the antibiotics and protect the cells from its effect. The main goal of the current study is to determine potential inhibitors from already existing FDA-approved drugs that could mitigate the BaeR protein. A range of in silico approaches, including molecular dynamics, virtual screening, SIFT analysis, ADMET, DFT, MM/GBSA, MMPBSA and per residue interaction analysis, were performed to identify inhibitors against this protein. The screening of FDA-approved compounds against the BaeR protein yielded 620 compounds. These compounds were clustered by SIFT to distinguish related compounds, it resulted in 20 different clusters. The top five clusters that can accommodate the binding site with better interaction and score by fulfilling all criteria were selected. The DFT analysis showed a smaller energy gap among all the compounds, indicating the ability of the compound to form firm interactions. All the compounds showed less binding free energy in both MM/GBSA and MM/PBSA analyses. The compounds were observed to be stable throughout the simulation. The per-residue interaction analysis confirmed that interactions with binding site residues were stable throughout the simulation. As a result of the study, four compounds, namely ZINC000003801919, DB01203, DB11217 and ZINC0000000056652, were identified as efficient candidates to deal with antimicrobial resistance in A. baumannii.
期刊介绍:
Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including:
combinatorial chemistry and parallel synthesis;
small molecule libraries;
microwave synthesis;
flow synthesis;
fluorous synthesis;
diversity oriented synthesis (DOS);
nanoreactors;
click chemistry;
multiplex technologies;
fragment- and ligand-based design;
structure/function/SAR;
computational chemistry and molecular design;
chemoinformatics;
screening techniques and screening interfaces;
analytical and purification methods;
robotics, automation and miniaturization;
targeted libraries;
display libraries;
peptides and peptoids;
proteins;
oligonucleotides;
carbohydrates;
natural diversity;
new methods of library formulation and deconvolution;
directed evolution, origin of life and recombination;
search techniques, landscapes, random chemistry and more;