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Comparing Molecules Generated by MMPDB and REINVENT4 with Ideas from Drug Discovery Design Teams

药物发现 药品 数据科学 计算机科学 化学 药理学 医学 生物化学
作者
Shan Sun,David J. Huggins
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
标识
DOI:10.1021/acs.jcim.5c00250
摘要

This study compares molecules designed by drug discovery project teams from the Sanders Tri-Institutional Therapeutics Discovery Institute with molecules generated by two computational tools: MMPDB and REINVENT4. Seven different test cases with diverse chemotypes are studied in order to explore the potential of these computational tools in complementing human expertise in the early stages of drug discovery. By comparing the molecular structures and properties generated by MMPDB and REINVENT4 to those designed by project design teams, we aim to assess the value of such tools. The results indicate that MMPDB and REINVENT4 cover regions of chemical space larger than those covered by ideas from the drug discovery project teams. However, the chemical spaces covered by the two methods are quite different, and neither method completely covers the chemical space identified by the drug discovery project teams. Thus, the computational methods are complementary to one another and to drug discovery project team ideation. Effective application of generative molecule design tools has the potential to accelerate the identification of novel therapeutic candidates by expanding the chemical space explored during drug discovery and enabling optimal exploration.
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