Aram Davtyan received his B.S. in Physics in 2007 from Yerevan State University in Armenia, where he worked in the areas of Quantum Field Theory, Quantum Optics, and Quantum Informatics. He further studied molecular modeling techniques at the University of North Carolina at Chapel Hill completing his M.S. in Chemistry in 2010. During his doctoral studies at the University of Maryland he has worked on several projects using coarse-grained molecular dynamics simulations of proteins and DNA using CPU and GPU platforms. He has completed his Ph.D. in Chemistry in 2013 and subsequently joined the Voth Group at the University of Chicago, where he is currently working on developing, extending and implementing various multiscale methods.
I am interested in dynamics and function of large macromolecular complexes that play vital role in living organisms. Examples of such complexes can either be the ion channels, which transport ions across the cell membrane, or chromatin, which is an enormous protein-DNA complex contained in eukaryotic cell nucleus. Despite significant improvement in computational power in the recent years many of the essential biological problems are still difficult or not possible to address using detailed all-atom simulations. For this reason, I am currently working on development and implementation of simplified macromolecular models, where sampling of possible states of the system is greatly increased due to reduction of degrees of freedom of the system. One particularly promising type of those simplified models is called ultra-coarse-grained (UCG) model, where each “coarse-graining” site may represent not only a group of atoms, but also an internal state of the system. I also work on extension and implementation of mesoscopic methods for modeling of lipid membranes. The Mesoscopic Membrane with Proteins Model (MesM-P) employs discrete quasiparticle approach to describe protein-facilitated membrane remolding on length and time scales unthinkable when using all-atom simulations.
1. A. Davtyan, G. A. Voth, H. C. Andersen, “Dynamic Force Matching: Construction of Dynamical Coarse-grained Models for Simultaneous Capturing of Translational and Rotational Diffusion Rates”, J. Chem. Phys., (accepted)
2. A. Davtyan, M. Simunovic, G. A. Voth, “Multiscale Simulations of Protein Facilitated Membrane Remodeling”, J. Struct. Biol., 2016, 196(1), 57-63
3. A. Davtyan, M. Platkov, M. Gruebele, G. A. Papoian, “Stochastic Resonance in Protein Folding Dynamics”, ChemPhysChem, 2016, 17(9), 1305-1313
4. K. Dave, A. Davtyan, M. Platkov, G. A. Papoian, M. Gruebele, “Environmental Fluctuations and Stochastic Resonance in Protein Folding”, ChemPhysChem, 2016, 17(9), 1341-1348
5. A. Davtyan, J. F. Dama, G. A. Voth, H. C. Andersen, “Dynamic Force Matching: A Method for Constructing Dynamical Coarse-Grained Models with Realistic Time Dependence”, J. Chem. Phys., 2015, 142, 154104
6. A. Davtyan, J. F. Dama, A. V. Sinitskiy, G. A. Voth, “The Theory of Ultra-Coarse-Graining. 2. Numerical Implementation”, J. Chem. Theory Comput., 2014, 10(12), 5265-5275
7. W. Zheng, N. Schafer, A. Davtyan, G. A. Papoian, P. G. Wolynes , “Predictive Energy Landscapes for Protein-Protein Association”, PNAS, 2012, 109(47), 19244-19249
8. A. Davtyan, W. Zheng, N. Schafer, C. Clementi, P. G. Wolynes and G. A. Papoian, “AWSEM-MD: Protein Structure Prediction Using Coarse-grained Physical Potential and Bioinformatically Based Local Structure Biasing”, J. Phys. Chem. B., 2012, 116(29), 8494-8503
· Implementation of ultra-coarse-grained models for actin filaments
· Development and implementation of dynamically accurate coarse-grained models
· Investigation of lipid membrane remolding using mesoscopic modeling techniques