Our goal is to answer the why question instead of the how question for the observed behavior of materials using computational techniques as the tool. Our focus is on the dynamics of complex molecular systems. We address understanding of the working principles of molecular machines. We study organic self-assembled molecules in general, and proteins in particular. We utilize atomistic and coarse-grained simulations supplemented by theoretical developments to cover the pico-millisecond time scales, and nano-micrometer length scales. We have developed network-based models to study the basic features contributing to structure/function relationships in these systems. These include:
G. Ozbaykal, A.R. Atilgan, C. Atilgan, “In Silico Mutational Studies of Hsp70 Disclose Sites with Distinct Functional Attributes,” Proteins: Structure, Function, Bioinformatics, 83, 2077-2090 (2015). On the cover
G. Guven, A.R. Atilgan, C. Atilgan, “Protonation States of Remote Residues Affect Binding-Release Dynamics of the Ligand but not the Conformation of apo Ferric Binding Protein,” J. Phys. Chem. B, 118, 11677-11687 (2014).
O. Aykut, A.R. Atilgan, C. Atilgan, “Designing Molecular Dynamics Simulations to Shift Populations of the Conformational States of Calmodulin,” PLoS Computational Biology, 9, e1003366 (2013).
E. Ozden-Yenigun, E. Simsek, Y.Z. Menceloglu, C. Atilgan, “Molecular Basis for Solvent Dependent Morphologies Observed inElectro-Sprayed Surfaces,” Phys. Chem. Chem. Phys., 15, 17862 (2013).
A.R. Atilgan, C. Atilgan, "Local Motifs in Proteins Combine to Generate Global Functional Moves," Briefings in Functional Genomics, 11, 479-488 (2012).
C. Atilgan, I. Inanc, A.R. Atilgan, "On Modifying Properties of Polymeric Melts by Nanoscopic Particles," Journal of Polymer Science Part B – Polymer Physics, 50, 1653-1662 (2012). On the cover
C. Atilgan, O.B. Okan, A.R. Atilgan, "Network-based Models as Tools Hinting at Non-Evident Protein Functionality," Annual Review of Biophysics, 41, 205-225 (2012).