Computational Aspect of Actinomycetes Bioprospection for API/NCE

Le résumé fourni par la source

Bacteria are a renewable source of diverse and functionally versatile chemical entities, which can be developed into different therapeutics. Among the Actinomycetes particularly members of Streptomyces genus are prolific (SMs) producers with extensive therapeutic value, making them an essential source of novel chemical entities (NCEs) and active pharmaceutical ingredients (APIs). Mining Actinomycetes for bioactive compounds has received renewed attention due to the increase in antibiotic resistance and the stalling of drug discovery pipelines. This chapter offers an in-depth overview of the computational approaches that have revolutionised Actinomycetes ’ bioprospecting by combining systems biology, genomics, metagenomics, machine learning (ML), new artificial intelligence (AI), and molecular modelling, ought to be employed to speed up genome–metabolome connections, genome mining and prediction, compound dereplication, and structure-function modelling. Furthermore, in contemporary problems such as data integration, research possibilities with the ability to increase our understanding of actinomycete biosynthetic potential and speed up the development of next-generation APIs and NCEs were also explored. The chapter emphasises the critical role that computational tools play in revitalising natural product-based medication development from Actinomycetes by illuminating the current state of affairs as well as possible future paths.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.