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Virtual High-Throughput AI-Driven Structure Based Screening and Experimental Validation for Hit Discovery

ORRxD has developed a computational approach to discover target-specific chemical ligands that modulate gene functions.  ORRxD brings together genomics, structural biology, HPC-driven molecular dynamics simulations, ensemble docking and virtual high throughput screening of compounds at a large (up to billion-compound) scale to discover chemicals that bind to and alter the function of specific protein targets in the human genome.

ORRxD uses enhanced sampling molecular dynamics (MD) and ensemble docking in a HPC-driven in-silico drug discovery platform. ORRxD's structure-based computational virtual high throughput screening paradigm has had a 100% success rate in identifying small molecules for developing therapeutic leads to specific disease targets. 

In selected cases experimental assay validation is also available.

ORRxD has created a constantly evolving database of small molecules ranked by calculated affinity and drug-like properties to protein targets to be used as a starting point for investigators to develop new drugs to all human protein targets.


ORRxD's ability to identify chemical probes to a protein target over a short period of time will allow ORRxD to rapidly increase chemogenomic information on the human genome.  The impact of creating a small molecule database library of chemical probes that bind to and modify the function of all proteins in the human genome will become the starting point for future discovery of safe and effective drugs. 

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