Current trends in computational modeling for drug discovery This contributed volume offers a comprehensive discussion on how to design and discover pharmaceuticals using computational modeling techniques. The different chapters deal with the classical and most advanced techniques theories protocols databases and tools employed in computer aided drug design (CADD) covering diverse therapeutic classes. Multiple components of Structure Based Drug Discovery (SBDD) along with its workflow and associated challenges are presented while potential leads for Alzheimer’s disease (AD) antiviral agents anti human immunodeficiency virus (HIV) drugs and leads for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) disease are discussed in detail. Computational toxicological aspects in drug design and discovery screening adverse effects and existing or future in silico tools are highlighted while a novel in silico tool RASAR which can be a major technique for small to big datasets when not much experimental data are present is presented. The book also introduces the reader to the major drug databases covering drug molecules chemicals therapeutic targets metabolomics and peptides which are great resources for drug discovery employing drug repurposing high throughput and virtual screening. This volume is a great tool for graduates researchers academics and industrial scientists working in the fields of cheminformatics bioinformatics computational biology and chemistry.