In silico ADMET Traffic Lights and PhysChem Scores and Their Application to Kinase Inhibitors
Mario Lobell, Computational Chemist, Bayer HealthCare
Date Posted: Tuesday, May 06, 2008
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About the speaker
Dr. Mario Lobell holds a PhD in Chemistry and a Postgraduate Certificate in Software Development. From 1994 to 2003 he worked as a Computational Chemist in various places in academia and the pharmaceutical industry in the UK. Since 2004 he is a member of the Computational Chemistry group at Bayer HealthCare in Germany. His research interests include structure-based design, virtual screening, and in silico ADMET prediction. He is the principal author on a number of key publications in the field of in silico ADMET prediction
The need for in silico characterization of HTS hit structures as part of a data driven hit selection process is demonstrated. A solution is described in form of the in silico ADMET Traffic Light and PhysChem scoring system. The described in silico system has been extensively validated with Bayer in-house data, literature data and a collection of launched small molecule drugs. The system is applied to examples of kinase inhibitor drugs and drug candidates.
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