title: Identification of Bacterial Cell Wall Lyases via Pseudo Amino Acid Composition.
abstract: Owing to the abuse of antibiotics, drug resistance of pathogenic bacteria becomes more and more serious. Therefore, it is interesting to develop a more reasonable way to solve this issue. Because they can destroy the bacterial cell structure and then kill the infectious bacterium, the bacterial cell wall lyases are suitable candidates of antibacteria sources. Thus, it is urgent to develop an accurate and efficient computational method to predict the lyases. Based on the consideration, in this paper, a set of objective and rigorous data was collected by searching through the Universal Protein Resource (the UniProt database), whereafter a feature selection technique based on the analysis of variance (ANOVA) was used to acquire optimal feature subset. Finally, the support vector machine (SVM) was used to perform prediction. The jackknife cross-validated results showed that the optimal average accuracy of 84.82% was achieved with the sensitivity of 76.47% and the specificity of 93.16%. For the convenience of other scholars, we built a free online server called Lypred. We believe that Lypred will become a practical tool for the research of cell wall lyases and development of antimicrobial agents.
authors.affiliation: Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics and Center for Information in Biomedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.
authors.forename: Xin-Xin
authors.identifier: 0000-0002-2022-0110
authors.initials: XX
authors.lastname: Chen
authors.affiliation: Department of Pathophysiology, Southwest Medical University, Luzhou 646000, China.
authors.forename: Hua
authors.initials: H
authors.lastname: Tang
authors.affiliation: Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics and Center for Information in Biomedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.
authors.forename: Wen-Chao
authors.initials: WC
authors.lastname: Li
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China.
authors.forename: Hao
authors.initials: H
authors.lastname: Wu
authors.affiliation: Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics and Center for Information in Biomedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; Department of Physics, School of Sciences, and Center for Genomics and Computational Biology, North China University of Science and Technology, Tangshan 063000, China.
authors.forename: Wei
authors.identifier: 0000-0002-6857-7696
authors.initials: W
authors.lastname: Chen
authors.affiliation: Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics and Center for Information in Biomedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Ding
authors.affiliation: Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics and Center for Information in Biomedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.
authors.forename: Hao
authors.identifier: 0000-0001-6265-2862
authors.initials: H
authors.lastname: Lin
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry*; D000704:Analysis of Variance; D000900:Anti-Bacterial Agents / Q000009:adverse effects; D001419:Bacteria / Q000201:enzymology*; D001426:Bacterial Proteins / Q000737:chemistry; D002473:Cell Wall / Q000201:enzymology*; D019295:Computational Biology; D003198:Computer Simulation; D030562:Databases, Protein; D024881:Drug Resistance, Bacterial; D008190:Lyases / Q000737:chemistry*; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D060388:Support Vector Machine
chemical_list: D000596:Amino Acids; D000900:Anti-Bacterial Agents; D001426:Bacterial Proteins; D008190:Lyases