Using matched molecular series as a predictive tool to optimize biological activity

  • O'Boyle N
  • Boström J
  • Sayle R
 et al. 
  • 118

    Readers

    Mendeley users who have this article in their library.
  • 26

    Citations

    Citations of this article.

Abstract

A matched molecular series is the general form of a matched molecular pair and refers to a set of two or more molecules with the same scaffold but different R groups at the same position. We describe Matsy, a knowledge-based method that uses matched series to predict R groups likely to improve activity given an observed activity order for some R groups. We compare the Matsy predictions based on activity data from ChEMBLdb to the recommendations of the Topliss tree and carry out a large scale retrospective test to measure performance. We show that the basis for predictive success is preferred orders in matched series and that this preference is stronger for longer series. The Matsy algorithm allows medicinal chemists to integrate activity trends from diverse medicinal chemistry programs and apply them to problems of interest as a Topliss-like recommendation or as a hypothesis generator to aid compound design.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Get full text

Authors

  • Noel M. O'Boyle

  • Jonas Boström

  • Roger A. Sayle

  • Adrian Gill

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free