Vasanthanathan Poongavanam – författare

This publication is based on peer-reviewed manuscripts from the 2019 Conference on Drug Design & Discovery Technologies (CDDT) held at Ramaiah University of Applied Sciences, India. Providing a wide range of up to date topics on the latest advancements in drug design and discovery technologies, this book ensures the reader receives a good understanding of the scope of the field. Aimed at scientists, students, regulators, academics and consultants throughout the world, this book is an ideal resource for anyone interested in the state of the art in drug design and discovery.

Computational Drug DiscoveryA comprehensive resource that explains a wide array of computational technologies and methods driving innovation in drug discoveryComputational Drug Discovery: Methods and Applications (2 volume set) covers a wide range of cutting-edge computational technologies and computational chemistry methods that are transforming drug discovery. The book delves into recent advances, particularly focusing on artificial intelligence (AI) and its application for protein structure prediction, AI-enabled virtual screening, and generative modeling for compound design. Additionally, it covers key technological advancements in computing such as quantum and cloud computing that are driving innovations in drug discovery.Furthermore, dedicated chapters that addresses the recent trends in the field of computer aided drug design, including ultra-large-scale virtual screening for hit identification, computational strategies for designing new therapeutic modalities like PROTACs and covalent inhibitors that target residues beyond cysteine are also presented.To offer the most up-to-date information on computational methods utilized in Computational Drug Discovery, it covers chapters highlighting the use of molecular dynamics and other related methods, application of QM and QM/MM methods in computational drug design, and techniques for navigating and visualizing the chemical space, as well as leveraging big data to drive drug discovery efforts.The book is thoughtfully organized into eight thematic sections, each focusing on a specific computational method or technology applied to drug discovery. Authored by renowned experts from academia, pharmaceutical industry, and major drug discovery software providers, it offers an overview of the latest advances in computational drug discovery.Key topics covered in the book include: Application of molecular dynamics simulations and related approaches in drug discoveryThe application of QM, hybrid approaches such as QM/MM, and fragment molecular orbital framework for understanding protein-ligand interactionsAdoption of artificial intelligence in pre-clinical drug discovery, encompassing protein structure prediction, generative modeling for de novo design, and virtual screening.Techniques for navigating and visualizing the chemical space, along with harnessing big data to drive drug discovery efforts.Methods for performing ultra-large-scale virtual screening for hit identification.Computational strategies for designing new therapeutic models, including PROTACs and molecular glues.In silico ADMET approaches for predicting a variety of pharmacokinetic and physicochemical endpoints.The role of computing technologies like quantum computing and cloud computing in accelerating drug discoveryThis book will provide readers an overview of the latest advancements in Computational Drug Discovery and serve as a valuable resource for professionals engaged in drug discovery.

This book summarizes state-of-the-art antiviral drug design and discovery approaches starting from natural products to de novo design, and provides a timely update on recently approved antiviral drugs and compounds in advanced clinical development.