In Silico Elucidation of the Molecular Mechanism Defining the Adverse Effect of Selective Estrogen Receptor Modulators

Author SummaryEarly identification of the side effects of preclinical and commercial drugs is crucial in developing highly efficient therapeutics, as unexpected side effects account for one-third of all drug failures in drug development and lead to drugs being withdrawn from the market. Compared with the experimental identification of off-target proteins that cause side effects, computational approaches not only save time and costs by providing a candidate list of potential off-targets, but also provide insight into understanding the molecular mechanisms of protein–drug interactions. In this paper we describe an integrated approach to identifying similar drug binding pockets across protein families that have different global shapes. In a case study, we elucidate a possible molecular mechanism for the observed side effects of selective estrogen receptor modulators (SERMs), which are widely used to treat and prevent breast cancer and other diseases. The prediction provides molecular insight into reducing the side effects of SERMs and is supported by clinical and biochemical observations. The strategy used in this case study is being applied to discover off-targets for other commercially available pharmaceuticals and to repurpose existing safe pharmaceuticals to treat different diseases. The process can be included in a drug discovery pipeline in an effort to optimize drug leads, reduce unwanted side effects, and accelerate development of new drugs.