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Structural and Chemical Biology @ Vanderbilt University |
Novel Schizophrenia Therapeutics by Virtual High-Throughput Screening
Members: Eric Dawson, Ralf Mueller, Mariusz Butkiewicz
all research projects
Selective potentiators of the metabotropic glutamate receptor subtype mGluR5 have exciting potential for development of novel treatment strategies for schizophrenia and other disorders that disrupt cognitive function. The latest generation of selective mGluR5 potentiators is based on the lead compound CDPPB and features systemically active compounds with long half-lives that cross the blood-brain barrier.
A high-throughput screen (HTS) for mGluR5 potentiators at the Vanderbilt molecular library screening center network facility revealed a large and diverse set of about 1400 substances whose activity was validated in independent experiments. The present ChemInformatics proposal targets utilizing the power of recent machine learning techniques such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) to model the complex relationship between chemical structure and biological activity of mGluR5 potentiators reflected in the HTS results.
An innovative encoding scheme is developed that allows mapping of the diverse chemical space into a single mathematical model. The resulting Quantitative Structure Activity Relation (QSAR) models will serve a three-fold purpose: (a) a comprehensive binding site pharmacophore will be obtained to facilitate understanding of the SAR and rationalize further experiments; (b) the models will be used to virtually screen libraries of millions of compounds which are known but not physically available for HTS at Vanderbilt to gain a priority list for acquisition or synthesis; and (c) in combination with an existing Genetic Algorithm (GA) structure generator existing lead compounds will be optimized and new structures will be designed to identify potential new targets for synthesis.
Overall we hope to not only identify novel allosteric potentiators of mGluR5 and understand their activity as potential treatment of schizophrenia and other disorders that disrupt cognitive function, but also to build an innovative ChemInformatics software and database tool which can be adopted for other drug discovery projects in schizophrenia and bipolar disorder research. The developed applications will be made freely and readily accessible for academic research using a WWW interface deeply integrated in the drug development pipeline. The employed QSAR models require no crystal structure of the target protein. Hence the method can be readily applied to membrane proteins.
SPECIFIC AIMS:
Aim I: Develop Encoding Scheme and Critically Assess its Capabilities for Modeling QSARs.
Aim II: Pharmacophore, Virtual Screening, and Virtual Design Method Implementation.
Aim III: Mine External Substance Libraries for Novel mGluR5 Potentiator Leads.
Flowchart
Members: Eric Dawson, Ralf Mueller, Mariusz Butkiewicz
all research projects
Selective potentiators of the metabotropic glutamate receptor subtype mGluR5 have exciting potential for development of novel treatment strategies for schizophrenia and other disorders that disrupt cognitive function. The latest generation of selective mGluR5 potentiators is based on the lead compound CDPPB and features systemically active compounds with long half-lives that cross the blood-brain barrier.
A high-throughput screen (HTS) for mGluR5 potentiators at the Vanderbilt molecular library screening center network facility revealed a large and diverse set of about 1400 substances whose activity was validated in independent experiments. The present ChemInformatics proposal targets utilizing the power of recent machine learning techniques such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) to model the complex relationship between chemical structure and biological activity of mGluR5 potentiators reflected in the HTS results.
An innovative encoding scheme is developed that allows mapping of the diverse chemical space into a single mathematical model. The resulting Quantitative Structure Activity Relation (QSAR) models will serve a three-fold purpose: (a) a comprehensive binding site pharmacophore will be obtained to facilitate understanding of the SAR and rationalize further experiments; (b) the models will be used to virtually screen libraries of millions of compounds which are known but not physically available for HTS at Vanderbilt to gain a priority list for acquisition or synthesis; and (c) in combination with an existing Genetic Algorithm (GA) structure generator existing lead compounds will be optimized and new structures will be designed to identify potential new targets for synthesis.
Overall we hope to not only identify novel allosteric potentiators of mGluR5 and understand their activity as potential treatment of schizophrenia and other disorders that disrupt cognitive function, but also to build an innovative ChemInformatics software and database tool which can be adopted for other drug discovery projects in schizophrenia and bipolar disorder research. The developed applications will be made freely and readily accessible for academic research using a WWW interface deeply integrated in the drug development pipeline. The employed QSAR models require no crystal structure of the target protein. Hence the method can be readily applied to membrane proteins.
SPECIFIC AIMS:
Aim I: Develop Encoding Scheme and Critically Assess its Capabilities for Modeling QSARs.
Aim II: Pharmacophore, Virtual Screening, and Virtual Design Method Implementation.
Aim III: Mine External Substance Libraries for Novel mGluR5 Potentiator Leads.
Flowchart