Bioisosteric replacement is widely used in drug design for lead optimization. In this work we present MolOpt, a web server for in silico drug design using bioisostetric transformation. Potential bioisosteric transformation rules were derived from data mining, deep generative machine learning and similarity comparison. MolOpt is useful for the identification of suitable lead optimization ideas. By replacing molecular substructures with similar chemical groups, MolOpt automatically generates lists of analogues. MolOpt also evaluates forty important pharmacokinetic and toxic properties for each newly designed molecule. The transformed analogues can be assessed for possible future study. MolOpt tries to assist the medicinal chemist in his/her search for what to make next. The MolOpt Server is freely available for use on the web at http://xundrug.cn/molopt.
Keywords: drug design, bioisosteric transformation, lead optimization, web server
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