日時 2016年10月27日(木) 12:00~13:30
場所 タワーホール船橋 研修室
発表者 Dr Giovanna Tedesco
Title: A picture tells a thousand words – using activity cliffs maps to understand SAR.
Authors: Giovanna Tedesco, Tim Cheeseright, Susana Tomasio, Paolo Tosco, Mark Mackey
Cresset, Cambridgeshire, United Kingdom
Summarizing and understanding the Structure-Activity Relationships (SAR) for a series of compounds can be a difficult and time-consuming exercise. A method capable of quickly identifying and deciphering the most relevant features underlying the biological activity of small and large data sets, even in those cases where limited structural information is available about ligand-target interaction, would be of invaluable help during the early stages of drug discovery projects.
Activity Atlas1 is a novel, qualitative method available in Forge2, Cresset’s powerful workbench for ligand design and SAR analysis. Activity Atlas is a probabilistic method for analyzing the SAR of a set of aligned compounds as a function of their 3D electrostatic, hydrophobic and shape properties, calculated with Cresset’s proprietary XED force field3. The method uses a Bayesian approach to take a global view of the data in a qualitative manner, taking into account the probability that a molecule is correctly aligned. Results are displayed using Forge visualization capabilities as highly visual 3D maps that inform the design and optimization of new compounds.
In this presentation, Activity Atlas and Activity Miner4, a module of Forge enabling rapid navigation of activity cliffs, will be used to analyze the SAR of a few example data sets of different size and complexity taken from the literature.
Activity Atlas activity cliffs summary maps will be used to get an overview of the SAR landscape, focusing on the prevalent SAR signals. Activity Miner will be used to drill down into the Activity Atlas maps to understand subtle molecule-to-molecule structure-activity changes and identify potential outliers.
The information derived from this analysis can be of invaluable help for drug discovery projects to inform design decisions and help prioritize molecules for synthesis.
3. J. G. Vinter, Journal of Computer Aided Molecular Design 8 (1994) 653-668