QUANTUMBIO INC — Department of Health and Human Services SBIR Phase I: 400

Description

Abstract The study of protein ligand binding is one of the central problems in computational biology because of its importance in understanding intermolecular interactionsand because of its practical payoff in drug discovery effortsThe transformative impact accurate target ligand structure can have in the design of next generation medicines cannot be overstatedIf we could routinely and accurately design molecules using these approaches it would revolutionize drug discovery by winnowing out compounds with no activity while focusing more effort and scrutiny on highly active compoundsDetermining the structure of a small moleculedrug candidate or lead compoundbound to a biological receptorprotein implicated in diseaseis a necessary step in this approach to drug discoveryIn this proposal we describe a novel method we call MovableTypeMTwhich addresses the protein ligand binding and scoring problem using fundamental statistical mechanics combined with a novel way to generate the ensemble of a ligand in a protein binding pocketVia a rapid assembly of the necessary partition functions we directly obtain binding free energies and the low free energy posesConceptuallythe MT method is analogous to block and type set printingwhich allows us to efficiently evaluate partition functions describing regions or systems of interestIn this approach we construct two databases thatdescribe the probability of certain pairwise interactions as a function of r obtained from a knowledge baseProtein DatabankPDBor the Cambridge Structural DatabaseCSDandthe energetics of the pairwise interactions as a function of r obtained from empirical potentialswhich can be either derived from the probabilities or can utilize extant pairwise potentials like AMBEROverallthe MT method is a general one and can use a broad range of two body potential functions and can be extended to higher order interactions if so desiredRecent work with the MT method has led to the launch of three core product modulesMTScoreboth endstate and ensemble binding affinity predictionMTDockligand placementand MTCSligand conformational searchIn this projectwe will extend our MT product line and deliver this methodology to X ray crystallographers and computational chemists for use in automated sidechain rotamer and target loop sampling within and around the active siteaccurate binding affinity prediction and minima selectionand crystallographic density matching and placementThis work will involve development of a newintegrated tool for automated structure model preparationrotamer loop selectionrotamer loop generationMTFlex properloop totamer minimizationand analysisWe will commercially deploy the technologywhich we will call MTFlexconstruct graphical user interfaces for use in MOEPhenixand our web based cloud platformFinallythis software will be used in real life structure based drug discovery problems with our pharmaceutical collaboratorssee Letters of SupportProject NarrativeThe successful completion of the SBIR grant will have a major impact on improving human healthIt will improve the quality of protein structuresfacilitate our understanding of biomolecular structure and function and will provide higher quality structural insights into protein liganddruginteractions which will enhance our ability to rationally design novel therapeutics for human diseases