STUDY OF PROTEIN LIGAND BINDING USING COARSE GRAIN SIMULATIONS
Bhupendra R Dandekar, Jagannath Mondal*
Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad 500107, India. Email: bhupendrard[at]tifrh.res.in
Abstract
Protein-ligand binding is a dynamic process and can have single or multiple binding pathways. Understanding the thermodynamics as well kinetics of these binding processes is essential and can be then used either to enhance the binding (for example in case of protein-drug binding) or to inhibit the binding (in case of protein-inhibitor binding). But gaining these understandings merely form experiments and that too with great atomic detail is not only difficult but also challenging.
In recent years the MD simulations have played a very important role in providing the understanding of binding processes in not only in great detail but also with experimental accuracy. But in spite of advanced developments in the field of MD simulations (such as the use of HPCs and GPUs) we are still limited by the system size which we can handle and the length scale which we can achieve from unbiased All-atom (AA) MD simulations. Therefore many interesting and important biological systems are still inaccessible with the AA MD simulation. Here come the advantages of using Coarse Grain (CG) MD simulations over the AA MD simulations. We are using one of the most popular Martini Force Field for Coarse grain simulation.
In the present work, we are going to check the efficiency of CG simulation done using Martini FF simulations and comparing it with the AA MD simulation results for studying the binding processes of tow protein-ligand systems namely T4lysozymeL99A-Benzene binding and CytochromeP450-Camphor binding. We are going to ask questions like, At what extent the CG simulations can describe the accurate binding results compared to AA MD simulations? Can they show single as well as multiple paths as seen in the AA MD simulations? Can they provide right kinetics and thermodynamics for protein-ligand binding systems similar to the experimental accuracy?
References:
1. J Mondal*, N. Ahalawat, S. Pandit, L. Kay, and P. Vallurupalli, 2018. Atomic resolution mechanism of ligand binding to a solvent inaccessible cavity in T4 lysozyme. PLOS Computational Biology,14,5, e1006180.
2. Navjeet Ahalawat and Jagannath Mondal, 2018. Mapping the Substrate Recognition Pathway in Cytochrome P450, J. Am. Chem. Soc DOI: 10.1021/jacs.8b10840