Frontiers in Computational Chemistry for Drug Discovery

Abstract

Computational methods pervade almost all aspects of drug discovery [1-3]. Computer-assisted tools contribute to the decision-making process along the entire drug discovery pipeline, including the validation of suitable targets, high-throughput screening of molecular libraries, the optimization of lead compounds, and the balance between pharmacological potency and physico-chemical and pharmacokinetic properties. This tendency will be reinforced in the next few years due to the continued increases in computer power, and the elaboration of sophisticated algorithms to capture the physico-chemical principles that underlie the activity of drugs. This effort should enable drug discovery methodology to evolve from approximate to more rigorous methods. How should computational methods evolve to ameliorate the success of drug discovery? The answer to this question is related to the identification of the current limitations faced by computational algorithms to unveil the delicate balance between factors that determine both potency and ADMET (absorption, distribution, metabolism, excretion, and toxicology) properties of drug candidates.