Increase in antibiotic resistance has forced researchers to develop new drugs against microorganisms. Lipopeptides are produced as secondary metabolites by some microorganisms. Computer-aided Design of Antimicrobial Lipopeptides as Prospective Drug Candidates provides the identification of novel ligands for different antimicrobial lipopeptides. Along with identification, it also provides some of the in silico drug design processes, namely homology modelling, molecular docking, QSAR studies, drug ADMET studies and pharmacophore studies to check the ligand-lipopeptide interaction. Some lipopeptides have shown anti-cancerous properties too, and this book discusses the required templates to design new drugs using computational techniques.
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Jujjavarapu Satya Eswari is as an Assistant Professor in Department of Biotechnology at National Institute of Technology (NIT), Raipur, India. She specialises in biotechnology, process modelling, evolutionary optimization, and artificial intelligence.
Swasti Dhagat is a Research Scholar in Department of Biotechnology at National Institute of Technology Raipur, India. She has five research publications in peer-reviewed journals and an international conference proceeding in the field of in silico drug design of lipopeptides.
Manisha Yadav is a Research Scholar in Department of Biotechnology at National Institute of Technology Raipur, India. Her area of specialization is in the field of Bioinformatics with the expertise in various computational tools and software of genomics, proteomics, and drug design and discovery.
The authors focus on the properties of various lipopeptides which are produced as metabolites by bacteria and have shown to have antimicrobial properties. They provide a step-by-step method in identifying drug molecules for target compounds and testing various properties for drug efficacy. Both experienced researchers and beginners will benefit.
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