Key role of computational CNS penetration studies in selecting and advancing compounds in P2X7 analgesia project

COMP 239

Sanjay Srivastava, Sanjay.Srivastava@AstraZeneca.com1, Marie Roumi2, Rosemarie Panetta2, Annie-Kim Gilbert3, and Simon J. Teague, simon.teague@astrazeneca.com4. (1) Department of Medicinal Chemistry, AstraZeneca R&D Montreal, 7171 Frederick Banting, Ville St-Laurent (Montreal), QC H4S1Z9, Canada, (2) Department of Drug Metabolism and Pharmacokinetics, AstraZeneca R&D Montréal, 7171 Frédérick-Banting, St. Laurent (Montréal), QC H4S 1Z9, Canada, (3) Department of Biosciences, AstraZeneca R&D Montréal, 7171 Frederick Banting, Ville St. Laurent, QC H4S1Z9, Canada, (4) Charnwood, AstraZeneca R&D, Bakewell Rd, Loughborough, Leicestershire, LE11 5RH, United Kingdom
This poster describes a successful in-silico CNS prediction based compound screening approach that was integrated into a project cascade, with an objective to find new antagonists in a P2X7 Neuropathic Pain (NP) project. Due to an availability of multiple LI and LO chemical series from a P2X7 project imported from another Research Area, an opportunity existed to exploit these by cross testing in NP targets. However, an absence of an understanding of their CNS penetration potential stood as a barrier from advancing compounds in PK experiments. Lack of synthetic resources also prevented from running a normal LI optimization protocol. Our approach therefore employed in-silico Blood Brain Barrier (BBB) models to validate and then predict the CNS penetration of these compounds. The predicted CNS profile was combined with other known key experimental attributes, such as P2X7 rat potency, Metabolic Clearance, Permeability etc. These considerations led to a short-listing of a small set of compounds that was eventually tested in rat NP models and some were found to yield positive results, in both CNS penetration as well as in-vivo pain models.
 

Poster Session
6:00 PM-8:00 PM, Tuesday, August 18, 2009 Walter E. Washington Convention Center -- Ballroom A, Poster

Division of Computers in Chemistry

The 238th ACS National Meeting, Washington, DC, August 16-20, 2009