Multi-objective optimization methods in drug design
Drug discovery is a challenging multi-objective problem where numerous pharmaceutically important objectives need to be adequately satisfied for a solution to be found. The problem is characterized by vast, complex solution spaces further perplexed by the presence of conflicting objectives. Multi-objective optimization methods, designed specifically to address such problems, have been introduced to the drug discovery field over a decade ago and have steadily gained in acceptance ever since. This paper reviews the latest multi-objective methods and applications reported in the literature, specifically in quantitative structure–activity modeling, docking, de novo design and library design. Further, the paper reports on related developments in drug discovery research and advances in the multi-objective optimization field. Drugs must satisfy multiple objectives to be approved by licensing authorities. Each of these objectives must be optimized during a drug discovery program. Multi-objective optimization methods enable searching for solutions meeting numerous objectives simultaneously.