Background: Bioisosteric replacement is widely used in drug design for lead optimization. However, the identification of a suitable bioisosteric group is not an easy task.

Methods: In this work, we present MolOpt, a web server for in silico drug design using bioisosteric transformation. Potential bioisosteric transformation rules were derived from data mining, deep generative machine learning and similarity comparison. MolOpt tries to assist the medicinal chemist in his/her search for what to make next.

Results and Discussion: 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.

Conclusion: MolOpt is useful for the identification of suitable lead optimization ideas. The MolOpt Server is freely available for use on the web at http://xundrug.cn/molopt.

背景：生物等位线替代在药物设计中广泛用于铅优化。但是，确定合适的生物立体异构基团并非易事。

方法：在这项工作中，我们介绍了MolOpt，这是一个使用生物等排变构进行计算机药物设计的Web服务器。潜在的生物立体转换规则来自数据挖掘，深度生成式机器学习和相似性比较。MolOpt试图协助药物化学家寻找下一步的方法。

结果与讨论：通过用相似的化学基团取代分子亚结构，MolOpt会自动生成类似物列表。MolOpt还为每个新设计的分子评估40种重要的药代动力学和毒性。可以评估转化的类似物，以备将来研究之用。

结论：MolOpt对于确定合适的线索优化思路很有用。可在http://xundrug.cn/molopt上免费使用MolOpt服务器。