Accelerated Drug Design Through Computational Biology

New computer-based modeling and data mining tools are continuously being developed to help assess and exploit targets uncovered in genomic research. Traditional computer-aided drug design software has several serious shortcomings. Cross-vendor incompatibilities induce users to use single software exclusively. The user's ability of `Mix & Match' software, unattainable with any current offering, has been shown to enhance in silico hits discovery and enrichments and to lead to increased hit rates. Additionally, low throughput of compute-intensive jobs in commercial seriously limits `Docking-scoring-hit identification' due to its inability to partition and streamline jobs execution across a cluster of compute servers. These limitations inspired TransTech Pharma to introduce innovations to circumvent them. The proposed system features a graphical user interface, `Mixing & Matching' cross-vendor software, uses a `divide-and-conquer' strategy to increase throughput across a multi-unit/multi operating system distributed processing architecture to parallelize job execution across a cluster of compute servers. This parallelization would maximize throughput of complex and compute-intensive computational chemistry tasks. The system will be validated using structure-activity information for three cyclin dependent kinase inhibitors - PfPK5, PfPK6, and Pfmrk as targets. Initial work showed that Pfmrk has 40% sequence identity to MAP-Kinase P38 whose crystal structure would serve as threading & homology model template for Pfmrk.