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The main contributions of our group during the last 15 years developing and using biomolecular simulation tools in drug lead discovery and design, in close collaboration with experimental researchers, are presented. Special emphasis has been given to methodological improvements in the following areas: (1) target homology modeling incorporating knowledge about known ligands to accurately characterize the binding site; (2) designing alternative strategies to account for protein flexibility in high‐throughput docking; (3) development of stochastic‐ and normal‐mode‐based methods to de novo design structurally diverse protein conformers; (4) development and validation of quantum mechanical semi‐empirical linear‐scaling calculations to correctly estimate ligand binding free energy. Several successful cases of computer‐aided drug discovery are also presented, especially our recent work on viral targets. Computational chemistry is today a consolidated highly valuable tool in the drug discovery pipeline. In spite of the tremendous progress and achievements in the field, there is an urgent need of further method development and benchmarking for accurate pose prediction, ligand binding free energy calculation, target homology modeling, and structure‐based virtual screening. In this review, the key contributions our lab has made throughout the last 15 years in those challenging areas are presented and discussed. [ABSTRACT FROM AUTHOR]