Informatics and Big Data, Council of Scientific and Industrial Research - Institute of Genomics and Integrative Biology (CSIR-IGIB), Room No. 130, Mathura Road, New Delhi 110025, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
Informatics and Big Data, Council of Scientific and Industrial Research - Institute of Genomics and Integrative Biology (CSIR-IGIB), Room No. 130, Mathura Road, New Delhi 110025, India.
Comput Biol Chem. 2022 Dec;101:107772. doi: 10.1016/j.compbiolchem.2022.107772. Epub 2022 Sep 16.
Antimicrobial resistance (AMR), a top threat to global health, challenges preventive and treatment strategies of infections. AMR strains of microbial pathogens arise through multiple mechanisms. The underlying "antibiotic resistance genes" (ARGs) spread through various species by lateral gene transfer thereby causing global dissemination. Human methods also augment this process through inappropriate use, non-compliance to treatment schedule, and environmental waste. Worldwide significant efforts are being invested to discover novel therapeutic solutions for tackling resistant pathogens. Diverse therapeutic strategies have evolved over recent years. In this work we have developed a comprehensive knowledgebase by collecting alternative antimicrobial therapeutic strategies from literature data. Therapeutic strategies against bacteria, virus, fungus and parasites were extracted from PubMed literature using text mining. We have used a subjective (sentimental) approach for data mining new strategies, resulting in broad coverage of novel entities and subsequently add objective data like entity name (including IUPAC), potency, and safety information. The extracted data was organized in a freely accessible web platform, KOMBAT. The KOMBAT comprises 1104 Chemical compounds, 220 of newly identified antimicrobial peptides, 42 bacteriophages, 242 phytochemicals, 106 nanocomposites, and 94 novel entities for phototherapy. Entities tested and evaluated on AMR pathogens are included. We envision that this database will be useful for developing future therapeutics against AMR pathogens. The database can be accessed through http://kombat.igib.res.in/.
抗菌药物耐药性(AMR)是对全球健康的最大威胁之一,对感染的预防和治疗策略提出了挑战。微生物病原体的 AMR 株通过多种机制产生。潜在的“抗生素耐药基因”(ARGs)通过水平基因转移在各种物种中传播,从而导致全球传播。人类方法也通过不当使用、不遵守治疗方案和环境废物来加速这一过程。全球范围内正在投入大量精力来发现针对耐药病原体的新型治疗方法。近年来已经出现了多种治疗策略。在这项工作中,我们通过从文献数据中收集替代抗菌治疗策略,开发了一个综合性的知识库。使用文本挖掘从 PubMed 文献中提取了针对细菌、病毒、真菌和寄生虫的治疗策略。我们使用了主观(情感)方法进行数据挖掘新策略,从而广泛涵盖了新的实体,并随后添加了客观数据,如实体名称(包括 IUPAC)、效力和安全性信息。提取的数据组织在一个免费访问的网络平台 KOMBAT 中。KOMBAT 包含 1104 种化学化合物、220 种新鉴定的抗菌肽、42 种噬菌体、242 种植物化学物质、106 种纳米复合材料和 94 种用于光疗的新实体。包括针对 AMR 病原体进行测试和评估的实体。我们设想这个数据库将有助于开发针对 AMR 病原体的未来疗法。可以通过 http://kombat.igib.res.in/ 访问该数据库。