An Integrated Approach for Navigating Energy Surface of Functional Proteins

Our group's research program is based-on predicting the functions of proteins whose three-dimensional structures are known using dynamical information obtained from trajectories and to foretell how the shifts in the environmental conditions will change these functions. Most folded proteins occupy multiple conformations that are close on the conformational space (CS) but are separated by high energy barriers. Computational and experimental methods determine only one or a few of these at best. Moreover, transitions on the CS occur on the timescales that are beyond the reach of most current computers. To further complicate matters, minor changes in environmental variables also affect the dynamics of transitions between the various conformations and their populations.
 
Our aimis to develop an efficient and integrated method that maps transitions between functional conformations of any given folded protein to its energy surface (1). To achieve this aim the students in this project will work towards putting together a package program for the surveillance of the CS of a protein under a selected set of conditions. This will include taking previously generated MD simulations on sample systems, select a reaction coordinate using one of two methods, tICA (2) or multiply perturbed residues (MPR) recently developed in our group (3), and finally applying metadynamics to navigate the protein surface.
 
Students working in groups of two will work on different proteins. Each subgroup will map the conformational surface of their selected system and predict transitions between its various states.
 
References:
(1) A.R. Atilgan, C. Atilgan, "Computational strategies for protein conformational ensemble detection," Current Opinion in Structural Biology, 72, 79-87 (2022).
(2) G. Pérez-Hernández et al. “Identification of slow molecular order parameters for Markov model construction,” Journal of Chemical Physics, 139(1), 015102. (2013).
(3) M. Berksoz, A. R. Atilgan, B. Kocuk, C. Atilgan, “Multiply Perturbed Response to Disclose Allosteric Control of Conformational Change: Application to Fluorescent Biosensor Design,” Biorxiv (2025). https://www.biorxiv.org/content/10.1101/2025.02.01.636023v1