This book covers a broad range of computational biophysics and chemistry methods and their applications to study various phenomena in molecular biology. Highlighting recent advances, it emphasizes enhanced modeling accuracy, longer timescales, and the ability to simulate large biological macromolecules. From molecular dynamics simulations to quantum mechanical methods, the book discusses innovations like polarizable force fields and the integration of machine learning (ML) and artificial intelligence (AI) for improved predictive accuracy. It examines how these techniques predict the pKa of ionizable groups in biological macromolecules such as proteins, DNAs, and RNAs. It is demonstrated that the abovementioned computational techniques can be used to infer the pathogenicity of DNA variants and to reveal the molecular mechanism of diseases.By providing extensive coverage of various methods and diverse applications, this book is a valuable resource that links computational approaches to understanding molecular effects in human diseases, ultimately advancing the field of personalized medicine.
