DBAASP Special prediction as a tool for the prediction of antimicrobial potency against particular target species

B. Vishnepolsky, M. Grigolava, G. Zaalishvili, M. Karapetian, M. Pirtskhalava
{"title":"DBAASP Special prediction as a tool for the prediction of antimicrobial potency against particular target species","authors":"B. Vishnepolsky, M. Grigolava, G. Zaalishvili, M. Karapetian, M. Pirtskhalava","doi":"10.3390/ecmc-4-05608","DOIUrl":null,"url":null,"abstract":"Antimicrobial peptides (AMPs) have been identified as a potentially new class of antibiotics. There are a lot of computational methods of AMP prediction. Although most of them can predict antimicrobial potency against any microbe (microbe is not identified) with rather high accuracy, prediction quality of these tools against particular bacterial strains is low [1,2]. Special prediction is a tool for the prediction of antimicrobial potency of peptides against particular target species with high accuracy. This tool is included into the Database of Antimicrobial Activity and Structure of Peptides (DBAASP, https://dbaasp.org [3]). In this presentation we describe this tool and predictive models for some Gram positive bacterial strains (Staphylococcus aureus ATCC 25923 and Bacillus subtilis) and a model for the prediction of hemolytic activity. Predictive model for Gram negative Escherichia coli ATCC 25922 was presented earlier [2,4]. Special prediction tool can be used for the design of peptides being active against particular strain. To demonstrate the capability of the tool, peptides predicted as active against E-coli ATCC 25922 and Staphylococcus aureus ATCC 25923 have been synthesized, and tested in vitro. The results have shown the justification of using special prediction tool for the design of new AMPs","PeriodicalId":20450,"journal":{"name":"Proceedings of 4th International Electronic Conference on Medicinal Chemistry","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 4th International Electronic Conference on Medicinal Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/ecmc-4-05608","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Antimicrobial peptides (AMPs) have been identified as a potentially new class of antibiotics. There are a lot of computational methods of AMP prediction. Although most of them can predict antimicrobial potency against any microbe (microbe is not identified) with rather high accuracy, prediction quality of these tools against particular bacterial strains is low [1,2]. Special prediction is a tool for the prediction of antimicrobial potency of peptides against particular target species with high accuracy. This tool is included into the Database of Antimicrobial Activity and Structure of Peptides (DBAASP, https://dbaasp.org [3]). In this presentation we describe this tool and predictive models for some Gram positive bacterial strains (Staphylococcus aureus ATCC 25923 and Bacillus subtilis) and a model for the prediction of hemolytic activity. Predictive model for Gram negative Escherichia coli ATCC 25922 was presented earlier [2,4]. Special prediction tool can be used for the design of peptides being active against particular strain. To demonstrate the capability of the tool, peptides predicted as active against E-coli ATCC 25922 and Staphylococcus aureus ATCC 25923 have been synthesized, and tested in vitro. The results have shown the justification of using special prediction tool for the design of new AMPs
DBAASP作为一种特殊预测工具,用于预测对特定目标物种的抗菌效力
抗菌肽(AMPs)已被确定为一类潜在的新型抗生素。AMP预测的计算方法有很多。虽然大多数工具能够以相当高的准确度预测对任何微生物(未鉴定的微生物)的抗菌效力,但这些工具对特定细菌菌株的预测质量很低[1,2]。特殊预测是一种预测多肽对特定靶种抗菌效力的工具,具有较高的准确性。该工具已被纳入抗菌活性和肽结构数据库(DBAASP, https://dbaasp.org[3])。在本报告中,我们描述了该工具和一些革兰氏阳性细菌菌株(金黄色葡萄球菌ATCC 25923和枯草芽孢杆菌)的预测模型,以及预测溶血活性的模型。革兰氏阴性大肠杆菌ATCC 25922的预测模型早前提出[2,4]。特殊的预测工具可用于设计对特定菌株有活性的肽。为了证明该工具的能力,我们合成了预测对大肠杆菌ATCC 25922和金黄色葡萄球菌ATCC 25923有活性的肽,并在体外进行了测试。结果表明,使用专用预测工具设计新型amp是合理的
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
文献相关原料
公司名称 产品信息 采购帮参考价格
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信