Flexible 3D pharmacophores as descriptors of dynamic biological space
详细信息    查看全文
文摘
Development of a pharmacophore hypothesis related to small-molecule activity is pivotal to chemical optimization of a series, since it defines features beneficial or detrimental to activity. Although crystal structures may provide detailed 3D interaction information for one molecule with its receptor, docking a different ligand to that model often leads to unreliable results due to protein flexibility. Graham Richards’ lab was one of the first groups to utilize “fuzzy” pattern recognition algorithms taken from the field of image processing to solve problems in protein modeling. Thus, descriptor “fuzziness” was partly able to emulate conformational flexibility of the target while simultaneously enhancing the speed of the search. In this work, we extend these developments to a ligand-based method for describing and aligning molecules in flexible chemical space termed FEature POint PharmacophoreS (FEPOPS), which allows exploration of dynamic biological space. We develop a novel, combinatorial algorithm for molecular comparisons and evaluate it using the WOMBAT dataset. The new approach shows superior retrospective virtual screening performance than earlier shape-based or charge-based algorithms. Additionally, we use target prediction to evaluate how FEPOPS alignments match the molecules biological activity by identifying the atoms and features that make the key contributions to overall chemical similarity. Overall, we find that FEPOPS are sufficiently fuzzy and flexible to find not only new ligand scaffolds, but also challenging molecules that occupy different conformational states of dynamic biological space as from induced fits.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700