CRC Press Computer-Aided Design of Antimicrobial Lipopeptides as Prospective Drug Candidates

Product Description 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. Key Features: Focuses on the use lipopeptides as new antimicrobial compounds Presents the basics of in silico modelling for design and development of new drug molecules, and is therefore of interest to beginners in the field Provides a step-by-step process for identification of drug molecules and testing its efficacy in silico Couples with courses on patents and intellectual property rights About the Author 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.