Library Enhancement through the Wisdom of Crowds

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• 作者：Michael D. Hack ; Dmitrii N. Rassokhin ; Christophe Buyck ; Mark Seierstad ; Andrew Skalkin ; Peter ten Holte ; Todd K. Jones ; Taraneh Mirzadegan ; Dimitris K. Agrafiotis
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2011
• 出版时间：December 27, 2011
• 年：2011
• 卷：51
• 期：12
• 页码：3275-3286
• 全文大小：608K
• 年卷期：v.51,no.12(December 27, 2011)
• ISSN：1549-960X

文摘

We present a novel approach for enhancing the diversity of a chemical library rooted on the theory of the wisdom of crowds. Our approach was motivated by a desire to tap into the collective experience of our global medicinal chemistry community and involved four basic steps: (1) Candidate compounds for acquisition were screened using various structural and property filters in order to eliminate clearly nondrug-like matter. (2) The remaining compounds were clustered together with our in-house collection using a novel fingerprint-based clustering algorithm that emphasizes common substructures and works with millions of molecules. (3) Clusters populated exclusively by external compounds were identified as 鈥渄iversity holes,鈥?and representative members of these clusters were presented to our global medicinal chemistry community, who were asked to specify which ones they liked, disliked, or were indifferent to using a simple point-and-click interface. (4) The resulting votes were used to rank the clusters from most to least desirable, and to prioritize which ones should be targeted for acquisition. Analysis of the voting results reveals interesting voter behaviors and distinct preferences for certain molecular property ranges that are fully consistent with lead-like profiles established through systematic analysis of large historical databases.