{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T01:26:47Z","timestamp":1789003607966,"version":"build-2803163510"},"reference-count":52,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T00:00:00Z","timestamp":1673481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:p>\u03b2-Lactams are a broad class of antimicrobial agents with a high safety profile, making them the most widely used class in clinical, agricultural, and veterinary setups. The widespread use of \u03b2-lactams has induced the extensive spread of \u03b2-lactamase hydrolyzing enzymes known as \u03b2-lactamases (BLs). To neutralize the effect of \u03b2-lactamases, newer generations of \u03b2-lactams have been developed, which ultimately led to the evolution of a highly diverse family of BLs. Based on sequence homology, BLs are categorized into four classes: A\u2013D in Ambler\u2019s classification system. Further, each class is subdivided into families. Class B is first divided into subclasses B1\u2013B3, and then each subclass is divided into families. The class to which a BL belongs gives a lot of insight into its hydrolytic profile. Traditional methods of determining the hydrolytic profile of BLs and their classification are time-consuming and require resources. Hence we developed a machine-learning-based <jats:italic>in silico<\/jats:italic> method, named as \u03b2-LacFamPred, for the prediction and annotation of Ambler\u2019s class, subclass, and 96 families of BLs. During leave-one-out cross-validation, except one all \u03b2-LacFamPred model HMMs showed 100% accuracy. Benchmarking with other BL family prediction methods showed \u03b2-LacFamPred to be the most accurate. Out of 60 penicillin-binding proteins (PBPs) and 57 glyoxalase II proteins, \u03b2-LacFamPred correctly predicted 56 PBPs and none of the glyoxalase II sequences as non-BLs. Proteome-wide annotation of BLs by \u03b2-LacFamPred showed a very less number of false-positive predictions in comparison to the recently developed BL class prediction tool DeepBL. \u03b2-LacFamPred is available both as a web-server and standalone tool at <jats:ext-link>http:\/\/proteininformatics.org\/mkumar\/blacfampred<\/jats:ext-link> and GitHub repository <jats:ext-link>https:\/\/github.com\/mkubiophysics\/B-LacFamPred<\/jats:ext-link> respectively.<\/jats:p>","DOI":"10.3389\/fmicb.2022.1039687","type":"journal-article","created":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T06:39:51Z","timestamp":1673505591000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["\u03b2-LacFamPred: An online tool for prediction and classification of \u03b2-lactamase class, subclass, and family"],"prefix":"10.3389","volume":"13","author":[{"given":"Deeksha","family":"Pandey","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neelja","family":"Singhal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manish","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,1,12]]},"reference":[{"key":"ref1","first-page":"677","article-title":"An enzyme from bacteria able to destroy penicillin","volume":"10","author":"Abraham","year":"","journal-title":"Rev. Infect. Dis."},{"key":"ref2","first-page":"321","article-title":"The structure of beta-lactamases","volume":"289","author":"Ambler","year":"1980","journal-title":"Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci."},{"key":"ref4","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1186\/s40168-018-0401-z","article-title":"DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data","volume":"6","author":"Arango-Argoty","year":"2018","journal-title":"Microbiome"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"8974265","DOI":"10.1155\/2021\/8974265","article-title":"\u03b2Lact-Pred: a predictor developed for identification of beta-lactamases using statistical moments and PseAAC via 5-step rule","volume":"2021","author":"Ashraf","year":"2021","journal-title":"Comput. Intell. Neurosci."},{"key":"ref6","doi-asserted-by":"publisher","first-page":"1445","DOI":"10.1093\/cid\/cit070","article-title":"Seven ways to preserve the miracle of antibiotics","volume":"56","author":"Bartlett","year":"2013","journal-title":"Clin. Infect. Dis."},{"key":"ref7","doi-asserted-by":"publisher","first-page":"S48","DOI":"10.1086\/514922","article-title":"Metallo-beta-lactamases: a class apart","volume":"27","author":"Bush","year":"1998","journal-title":"Clin. Infect. Dis."},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1211","DOI":"10.1128\/AAC.39.6.1211","article-title":"A functional classification scheme for beta-lactamases and its correlation with molecular structure","volume":"39","author":"Bush","year":"1995","journal-title":"Antimicrob. Agents Chemother."},{"key":"ref9","doi-asserted-by":"publisher","first-page":"2515","DOI":"10.1093\/bioinformatics\/btt417","article-title":"BLAD: a comprehensive database of widely circulated beta-lactamases","volume":"29","author":"Danishuddin","year":"2013","journal-title":"Bioinformatics"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"1792","DOI":"10.1093\/nar\/gkh340","article-title":"MUSCLE: multiple sequence alignment with high accuracy and high throughput","volume":"32","author":"Edgar","year":"2004","journal-title":"Nucleic Acids Res."},{"key":"ref11","doi-asserted-by":"publisher","first-page":"12728","DOI":"10.1038\/s41598-021-91456-0","article-title":"AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence","volume":"11","author":"Feldgarden","year":"2021","journal-title":"Sci. Rep."},{"key":"ref12","doi-asserted-by":"publisher","first-page":"W29","DOI":"10.1093\/nar\/gkr367","article-title":"HMMER web server: interactive sequence similarity searching","volume":"39","author":"Finn","year":"2011","journal-title":"Nucleic Acids Res."},{"key":"ref13","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1128\/AAC.45.3.660-663.2001","article-title":"Standard numbering scheme for Class B beta-lactamases","volume":"45","author":"Galleni","year":"2001","journal-title":"Antimicrob. Agents Chemother."},{"key":"ref14","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1038\/ismej.2014.106","article-title":"Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology","volume":"9","author":"Gibson","year":"2015","journal-title":"ISME J."},{"key":"ref15","doi-asserted-by":"publisher","first-page":"129","DOI":"10.3855\/jidc.3573","article-title":"Bacteriophage therapy: a potential solution for the antibiotic resistance crisis","volume":"8","author":"Golkar","year":"2014","journal-title":"J. Infect. Dev. Ctries."},{"key":"ref16","doi-asserted-by":"publisher","first-page":"185","DOI":"10.4161\/viru.22507","article-title":"New antibiotic agents in the pipeline and how they can help overcome microbial resistance","volume":"4","author":"Gould","year":"2013","journal-title":"Virulence"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"R1063","DOI":"10.1016\/j.cub.2013.11.057","article-title":"Antibiotics in crisis","volume":"23","author":"Gross","year":"2013","journal-title":"Curr. Biol."},{"key":"ref18","doi-asserted-by":"publisher","first-page":"D566","DOI":"10.1093\/nar\/gkw1004","article-title":"CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database","volume":"45","author":"Jia","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"ref19","doi-asserted-by":"publisher","first-page":"937","DOI":"10.1016\/S1074-5521(96)90182-9","article-title":"Molecular evolution of bacterial beta-lactam resistance","volume":"3","author":"Knox","year":"1996","journal-title":"Chem. Biol."},{"key":"ref20","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.jtbi.2014.10.008","article-title":"Prediction of \u03b2-lactamase and its class by Chou\u2019s pseudo-amino acid composition and support vector machine","volume":"365","author":"Kumar","year":"2015","journal-title":"J. Theor. Biol."},{"key":"ref21","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1038\/s42003-019-0545-9","article-title":"Hierarchical hidden Markov models enable accurate and diverse detection of antimicrobial resistance sequences","volume":"2","author":"Lakin","year":"2019","journal-title":"Commun. Biol."},{"key":"ref22","doi-asserted-by":"publisher","first-page":"5967","DOI":"10.1128\/AAC.04634-14","article-title":"Fast and accurate large-scale detection of \u03b2-lactamase genes conferring antibiotic resistance","volume":"59","author":"Lee","year":"2015","journal-title":"Antimicrob. Agents Chemother."},{"key":"ref23","doi-asserted-by":"publisher","first-page":"D443","DOI":"10.1093\/nar\/gkn656","article-title":"ARDB--antibiotic resistance genes database","volume":"37","author":"Liu","year":"2009","journal-title":"Nucleic Acids Res."},{"key":"ref24","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1093\/jac\/48.suppl_1.87","article-title":"Interpretative reading: recognizing the unusual and inferring resistance mechanisms from resistance phenotypes","volume":"48","author":"Livermore","year":"2001","journal-title":"J. Antimicrob. Chemother."},{"key":"ref25","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1177\/003335491412900402","article-title":"Antibiotic resistance: a public health crisis","volume":"129","author":"Lushniak","year":"2014","journal-title":"Public Health Rep."},{"key":"ref26","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1128\/AAC.01841-19","article-title":"A standard numbering scheme for class C \u03b2-lactamases","volume":"64","author":"Mack","year":"2020","journal-title":"Antimicrob. Agents Chemother."},{"key":"ref27","doi-asserted-by":"publisher","first-page":"3348","DOI":"10.1128\/AAC.00419-13","article-title":"The comprehensive antibiotic resistance database","volume":"57","author":"McArthur","year":"2013","journal-title":"Antimicrob. Agents Chemother."},{"key":"ref28","doi-asserted-by":"publisher","first-page":"S8","DOI":"10.1016\/S0966-842X(02)02429-0","article-title":"Microbial and viral drug resistance mechanisms","volume":"10","author":"McKeegan","year":"2002","journal-title":"Trends Microbiol."},{"key":"ref29","doi-asserted-by":"publisher","first-page":"9612","DOI":"10.1021\/ja034861u","article-title":"Structural aspects for evolution of beta-lactamases from penicillin-binding proteins","volume":"125","author":"Meroueh","year":"2003","journal-title":"J. Am. Chem. Soc."},{"key":"ref30","doi-asserted-by":"publisher","first-page":"145","DOI":"10.3389\/fpubh.2014.00145","article-title":"The antimicrobial resistance crisis: causes, consequences, and management","volume":"2","author":"Michael","year":"2014","journal-title":"Front. Public Health"},{"key":"ref31","doi-asserted-by":"publisher","first-page":"e1006258","DOI":"10.1371\/journal.pcbi.1006258","article-title":"Prediction of antibiotic resistance in Escherichia coli from large-scale pan-genome data","volume":"14","author":"Moradigaravand","year":"2018","journal-title":"PLoS Comput. Biol."},{"key":"ref32","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1080\/14756366.2017.1344235","article-title":"Beta-lactamase database (BLDB) \u2013 structure and function","volume":"32","author":"Naas","year":"2017","journal-title":"J. Enzyme Inhib. Med. Chem."},{"key":"ref33","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.compbiolchem.2017.02.006","article-title":"Enhanced identification of \u03b2-lactamases and its classes using sequence, physicochemical and evolutionary information with sequence feature characterization of the classes","volume":"68","author":"Nath","year":"2017","journal-title":"Comput. Biol. Chem."},{"key":"ref34","doi-asserted-by":"publisher","first-page":"9287","DOI":"10.1038\/s41598-020-65981-3","article-title":"BacEffluxPred: a two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins","volume":"10","author":"Pandey","year":"2020","journal-title":"Sci. Rep."},{"key":"ref35","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1016\/S0966-842X(98)01317-1","article-title":"Beta-lactamases: protein evolution in real time","volume":"6","author":"Petrosino","year":"1998","journal-title":"Trends Microbiol."},{"key":"ref36","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/S1473-3099(11)70316-4","article-title":"The crisis of no new antibiotics--what is the way forward?","volume":"12","author":"Piddock","year":"2012","journal-title":"Lancet Infect. Dis."},{"key":"ref37","author":"Powers","year":"2020"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1093\/emph\/eou024","article-title":"Antibiotic resistance management","volume":"2014","author":"Read","year":"2014","journal-title":"Evol. Med. Public Health"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"47","DOI":"10.3389\/fmicb.2013.00047","article-title":"The multifaceted roles of antibiotics and antibiotic resistance in nature","volume":"4","author":"Sengupta","year":"2013","journal-title":"Front. Microbiol."},{"key":"ref40","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1093\/jac\/dkh365","article-title":"Detection and assay of beta-lactamases in clinical and non-clinical strains of Yersinia enterocolitica biovar 1A","volume":"54","author":"Sharma","year":"2004","journal-title":"J. Antimicrob. Chemother."},{"key":"ref41","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1186\/1423-0127-16-109","article-title":"Identification of group specific motifs in beta-lactamase family of proteins","volume":"16","author":"Singh","year":"2009","journal-title":"J. Biomed. Sci."},{"key":"ref42","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.jtbi.2018.08.030","article-title":"BlaPred: predicting and classifying \u03b2-lactamase using a 3-tier prediction system via Chou\u2019s general PseAAC","volume":"457","author":"Srivastava","year":"2018","journal-title":"J. Theor. Biol."},{"key":"ref43","doi-asserted-by":"publisher","first-page":"980572","DOI":"10.1155\/2014\/980572","article-title":"Identification of family specific fingerprints in \u03b2-lactamase families","volume":"2014","author":"Srivastava","year":"","journal-title":"Sci. World J."},{"key":"ref44","doi-asserted-by":"publisher","first-page":"bau111","DOI":"10.1093\/database\/bau111","article-title":"CBMAR: a comprehensive \u03b2-lactamase molecular annotation resource","volume":"2014","author":"Srivastava","year":"","journal-title":"Database"},{"key":"ref45","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1186\/1471-2164-10-390","article-title":"The lactamase engineering database: a critical survey of TEM sequences in public databases","volume":"10","author":"Thai","year":"2009","journal-title":"BMC Genomics"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1038\/495141a","volume":"495","year":"2013","journal-title":"Nat."},{"key":"ref46","doi-asserted-by":"publisher","first-page":"3","DOI":"10.4161\/gmic.28027","article-title":"Off-label abuse of antibiotics by bacteria","volume":"5","author":"Viswanathan","year":"2014","journal-title":"Gut Microbes"},{"key":"ref47","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1128\/CMR.18.2.306-325.2005","article-title":"Metallo-Beta-lactamases: the quiet before the storm?","volume":"18","author":"Walsh","year":"2005","journal-title":"Clin. Microbiol. Rev."},{"key":"ref48","doi-asserted-by":"publisher","first-page":"bbaa301","DOI":"10.1093\/bib\/bbaa301","article-title":"DeepBL: a deep learning-based approach for in silico discovery of beta-lactamases","volume":"22","author":"Wang","year":"2021","journal-title":"Brief. Bioinform."},{"key":"ref49","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1186\/s12859-017-1972-6","article-title":"CNN-BLPred: a convolutional neural network based predictor for \u03b2-lactamases (BL) and their classes","volume":"18","author":"White","year":"2017","journal-title":"BMC Bioinformatics"},{"key":"ref50","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1139\/cjm-2014-0063","article-title":"Something old, something new: revisiting natural products in antibiotic drug discovery","volume":"60","author":"Wright","year":"2014","journal-title":"Can. J. Microbiol."},{"key":"ref51","doi-asserted-by":"publisher","first-page":"2640","DOI":"10.1093\/jac\/dks261","article-title":"Identification of acquired antimicrobial resistance genes","volume":"67","author":"Zankari","year":"2012","journal-title":"J. Antimicrob. Chemother."},{"key":"ref52","doi-asserted-by":"publisher","first-page":"12478","DOI":"10.3390\/molecules171112478","article-title":"Development of new drugs for an old target: the penicillin binding proteins","volume":"17","author":"Zervosen","year":"2012","journal-title":"Molecules"}],"container-title":["Frontiers in Microbiology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmicb.2022.1039687\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T06:39:54Z","timestamp":1673505594000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmicb.2022.1039687\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,12]]},"references-count":52,"alternative-id":["10.3389\/fmicb.2022.1039687"],"URL":"https:\/\/doi.org\/10.3389\/fmicb.2022.1039687","relation":{},"ISSN":["1664-302X"],"issn-type":[{"value":"1664-302X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,12]]},"article-number":"1039687"}}