I am a computational biologist, and my research focuses on the development and application of computational methods to understand and predict the structure, function and dynamics of proteins. I am currently a postdoctoral research fellow at Stanford University, working with Russ Altman and Michael Levitt in Simbios, the National Center for Physics-based Simulation of Biological Structures. As a postdoc, I work on two main projects: torsion angle normal mode analysis and using machine learning to discover novel protein ATP binding sites.
I am originally from Oregon, where I earned by B.S. in chemistry and mathematics at the University of Oregon, in the Clark Honors College. I developed my love of the outdoors growing up there, and I still believe Oregon has the best waterfalls, berries, and beer in the world.
Torsion Angle Normal Mode Analysis
Normal mode analysis identifies the natural, resonant motion of a protein. It can be used to quickly model the global conformational changes of large proteins, when other methods like molecular dynamics are too computationally intensive to reach such long time scales. Traditionally, normal mode analysis has been carried out in Cartesian coordinates, but there are many advantages to calculating normal modes in torsion (dihedral) angle space. I work on developing torsion angle normal mode analysis methods, and I have shown that the method is faster, takes fewer degrees of freedom, and is more accurate at modeling protein conformational changes than Cartesian normal mode analysis. A new faster, more accurate normal mode analysis method is an important new tool for computational biologists because in addition to predicting conformational changes of proteins, normal modes can be used to help solve x-ray crystallography structures or to improve protein-ligand docking calculations for rational drug design.
For more detail on this research, read the technical paper.
Here's a short video of me giving an overview of this research.
ATP Binding Site Recognition Through Machine Learning
ATP transports chemical energy within cells, and it is one of the most abundant molecules in cells. However, there is currently no method to identify ATP protein binding sites in proteins. I am working on using machine learning within FEATURE to make an ATP binding model to help experimental and computational biologists discover novel protein ATP binding sites.
GPCR Structure Prediction
G-protein coupled receptors (GPCRs) are a superfamily of transmembrane proteins that regulate signal transduction. They are targets of 50% of recently released drugs, and 25 of the top 100 best-selling drugs. However, the structures of GPCRs are very hard to determine experimentally, so there are very few solved 3D structures. Therefore, I developed computational methods to predict the structures and ligand binding of GPCRs, which are expected to aid in designing drugs that target GPCRs.
- Abrol R, Sim SK, Bray JK, Trzaskowski B, Goddard WA. "Conformational Ensemble View of G Protein-Coupled Receptors and the Effect of Mutations and Ligand Binding." Methods in Enzymology. 2013; 520: 31-48.
- Abrol R, Bray JK, Goddard WA. "Bihelix: Towards De Novo Structure Prediction of an Ensemble of G-Protein Coupled Receptor Conformations." Proteins. 2012 Feb; 80(2): 505-518.
- Bray JK, Weiss DR, Levitt M. “Optimized Torsion-Angle Normal Modes Reproduce Conformational Changes More Accurately Than Cartesian Modes.” Biophysical Journal. 2011 Dec 21; 101(12): 2966-2969.
- Abrol R, Kim SK, Bray JK, Griffith AR, Goddard WA. “Characterizing and Predicting the Functional and Conformational Diversity of Seven-Transmembrane Proteins.” Methods. 2011 Dec; 55(4): 405-414.
- Bray JK. “The Development and Application of Computational Methods for the Prediction of G-Protein Coupled Receptor Structures.” Doctoral Thesis, California Institute of Technology, 2009.
- Bray JK, Goddard WA. “The Structure of Human Serotonin 2c G-Protein-Coupled Receptor Bound to Agonists and Antagonists.” Journal of Molecular Graphics and Modelling. 2008 Aug; 27(1): 66-81.
- Kozisek M, Bray J, Rezacova P, Saskova K, Brynda J, Pokorna J, Mammano F, Rulisek L, Konvalinka J. “Molecular Analysis of the HIV-1 Resistance Development: Enzymatic Activities, Crystal Structures, and Thermodynamics of Nelfinavir-resistant HIV Protease Mutants.” Journal of Molecular Biology. 2007 Dec 7; 374(4): 1005-1016.
- Caballero-Manrique E, Bray JK, Deutschman WA, Dahlquist FW, Guenza MG. “A Theory of Protein Dynamics to Predict NMR Relaxation.” Biophysical Journal. 2007 Dec 15: 93(12): 4128-4140.