Event: Dr. Lance Westerhoff, President and General Manager, will attend the CCG User Group Meeting & Conference in Montreal, Canada and present a poster focused on QuantumBio’s new free energy technology: MovableType

Title: MTScore: a method for fast, free energy-based protein:ligand binding affinity determination using MovableType

Poster Download: available here!

Abstract: Energy sampling against biomolecular ensembles has been of significant interest for decades, and with recent advances in the field, interest in these methods has only grown. The multi-dimensional integral of the partition function is analytically inaccessible which has led to the development and application of numerical approximations for molecular ensemble sampling and partition function calculation. Unfortunately, these methods are generally quite slow, complicated to use, and expensive. We have addressed the sampling problem by using a novel, patented methodology termed “MovableType” (MT) which is conceptually analogous to the way the movable type printing press works. By separating the inter/intra-molecular energy into pair potentials, the MT method simulates the molecular energies through pair potential sampling and (re)combination. In the MT algorithm, we have devised rules to progressively decompose a molecular system into components (as the printing forme) with independent integrals over pairwise distances between the components. The MT algorithm has been validated against several benchmark sets demonstrating that it is competitive with other, much slower methods in the prediction of the free energy of ligand binding, small molecule conformational free energy surface search, and protein:ligand docking. Since the method works in seconds (versus hours or days for conventional methods), investigators can use the method to quickly study protein:ligand binding on the free energy surface. When installed, the software includes command line, webservice, and MOE based interfaces and can even be run in real time through the MOE “Molecule Builder.”

Literature:

1. Zheng, Z., Pei, J., Bansal, N., Liu, H., Song, L. F., & Merz, K. M., Jr. (2018). Generation of Pairwise Potentials Using Multidimensional DataMining. Journal of Chemical Theory and Computation, 14(10), 5045–5067. http://doi.org/10.1021/acs.jctc.8b00516
2. Bansal, N., Zheng, Z., Song, L. F., Pei, J., & Merz, K. M., Jr. (2018). The Role of the Active Site Flap in Streptavidin/Biotin Complex Formation. Journal of the American Chemical Society, 140(16), 5434–5446. http://doi.org/10.1021/jacs.8b00743
3. Bansal, N., Zheng, Z., & Merz, K. M., Jr. (2016). Incorporation of side chain flexibility into protein binding pockets using MTFlex. Bioorganic & Medicinal Chemistry, 24(20), 4978–4987. http://doi.org/10.1016/j.bmc.2016.08.030
4. Zheng, Z., Wang, T., Li, P., & Merz, K. M., Jr. (2015). KECSA-Movable Type Implicit Solvation Model (KMTISM). Journal of Chemical Theory and Computation, 11(2), 667–682. http://doi.org/10.1021/ct5007828
5. Pan, L.-L., Zheng, Z., Wang, T., & Merz, K. M., Jr. (2015). Free Energy-Based Conformational Search Algorithm Using the Movable Type Sampling Method. Journal of Chemical Theory and Computation, 11(12), 5853–5864. http://doi.org/10.1021/acs.jctc.5b00930
6. Zheng, Z., Ucisik, M. N., & Merz, K. M. (2013). The Movable Type Method Applied to Protein–Ligand Binding. Journal of Chemical Theory and Computation, 9(12), 5526–5538. http://doi.org/10.1021/ct4005992