Computational Drug Discovery

Preface Volume 1: PART I. MOLECULAR DYNAMICS AND RELATED METHODS IN DRUG DISCOVERY Binding Free Energy Calculations in Drug Discovery Gaussian Accelerated Molecular Dynamics in Drug Discovery MD Simulations for Drug-Target (Un)Binding Kinetics Solvation Thermodynamics and its Competitive Saturation as a Paradigm of Co-Solvent Methods PART II. QUANTUM MECHANICS APPLICATION FOR DRUG DISCOVERY QM/MM Approaches for Structure Based Drug Design: Techniques and Applications Recent Advances in Practical Quantum Mechanics and Mixed-QM/MM Driven X-Ray Crystallography and Cryo-Electron Microscopy (Cryo-EM) and their Impact on Structure-Based Drug Discovery Quantum-Mechanical Analyses of Interactions for Biochemical Applications PART III. ARTIFICIAL INTELLIGENCE IN PRE-CLINICAL DRUG DISCOVERY The Role of Computer Aided Drug Design in Drug Discovery - An Introduction AI-Based Protein Structure Predictions and their Implications in Drug Discovery Deep Learning for the Structure-Based Binding Free Energy Prediction of Small Molecule Ligands Using Artificial Intelligence for the De Novo Drug Design and Retrosynthesis Reliability and Applicability Assessment for Machine Learning Models Volume 2: PART IV. CHEMICAL SPACE AND KNOWLEDGE BASED DRUG DISCOVERY Enumerable Libraries and Accessible Chemical Space Navigating Chemical Space Visualization, Exploration, and Screening of Chemical Space in Drug Discovery SAR Knowledge Based for Driving Drug Discovery Cambridge Structural Database (CSD) - Drug Discovery through Data Mining and Knowledge Based Tools PART V. STRUCTURE-BASED VIRTUAL SCREENING USING DOCKING Structure-Based Ultra-Large Scale Virtual Screenings Community Benchmarking Exercises for Docking and Scoring PART VI. IN SILICO ADMET MODELLING Advances in the Application of In Silico ADMET Models - An Industry Perspective PART VII. COMPUTATIONAL APPROACHES FOR NEW THERAPEUTIC MODALITIES Modelling the Structures of Ternary Complexes Mediated by Molecular Glues Free Energy

Vasanthanathan Poongavanam is a senior scientist in the Department of Chemistry-BMC, Uppsala University, Sweden. Before starting at Uppsala University in 2016, he was a postdoctoral fellow at the University of Vienna, Austria, and at the University of Southern Denmark. He obtained his Ph.D. degree in Computational Medicinal Chemistry as a Drug Research Academy (DRA) Fellow at the University of Copenhagen, Denmark, on computational modeling of cytochrome P450. He has published more than 65 scientific articles, including reviews and book chapters. His scientific interests focus on in silico ADMET modeling including cell permeability and solubility, and he has worked extensively on understanding the molecular properties that govern the pharmacokinetic profile of molecules bRo5 property space, including macrocycles and PROTACs.

Vijayan Ramaswamy (R.S.K. Vijayan) is a senior research scientist affiliated with the Structural Chemistry division at the Institute for Applied Cancer Science, University of Texas MD Anderson Cancer, TX, USA. In 2016, he joined MD Anderson Cancer after a brief tenure as a scientist, at PMC Advanced Technologies, New Jersey, USA. He undertook postdoctoral training at Rutgers University in New Jersey, USA, and Temple University in Pennsylvania, USA. He received his Ph.D. in Pharmacy as a CSIR senior research fellow from the Indian Institute of Chemical Biology, Kolkata, India. He is a named co-inventor on 7 issued US patents, including an ATR kinase inhibitor that has advanced to Phase 2 clinical trials. He has published more than 20 scientific articles and authored one book chapter. His research focuses on applying computational chemistry methods to drive small molecule drug discovery programs, particularly for oncology and neurodegenerative diseases.