Computational studies on Membrane Proteins (bovine CNGA1 & mouse TSPO)

Around thirty percent of total proteins are present in the membrane and play an important role to communicate intracellular and extracellular region. Their presence in the membrane is one of the limiting steps to determine protein structure and to understand their mechanisms. Hence bioinformatics techniques and computational tools play an important role to overcome these issues in characterizing the structural/functional mechanism of membrane proteins. In this thesis, I have developed and used state of the art computational techniques applied to two different pharmaceutically relevant membrane proteins, Cyclic nucleotide-gated channels (CNG) and translocator membrane protein (TSPO). CNG ion channels are embedded into the neuronal membrane. Till date, the structure and their gating mechanism are subject to interest. Different approaches like electrophysiology, single molecule force spectroscopy, biophysics, etc. have been employed to study these channels. Here I studied the gating mechanism of the CNGA1 ion channel by use of homology modeling and coarse-grained molecular dynamics. TSPO is a key biomarker for the diagnostics of inflammation in the brain. Limited Structural and functional information available on mammalian TSPOs homodimers. Computational studies suggested that the NMR-solved structure is not prone to dimer formation and is not stable in a membrane environment and has been an object of vivid criticism. To address this issue we use homology modeling technique and molecular dynamics approach. Principle results are: 1. I have successfully created homology models for CNGA1 homotetramer and performed coarse-grained simulation in the presence and absence of cGMP molecule and developed the coarse-grained force-field parameters for cGMP. 2. I have proposed a new model of the functionally relevant dimeric form of mTSPO. The model is fully consistent with solid-state NMR spectral data. Our predictions provide for the first time structural insights on this pharmaceutically important target fully consistent with experimental data. 3. During these studies, and in order to optimize the preparation of the systems it was necessary to develop an automated tool for creating the input files for doing coarse-grained simulations. These tools are shared with the community through a publically available online web-server that simplifies the task of generating input files which help in performing simulation and retrieving the result data for small simulations. The web-server, MERMAID is available at MERMAID (http://molsim.sci.univr.it/mangesh/). The application of novel computational approaches in this thesis allowed me to characterize extensively both systems by offering a rational to a huge amount of experimental data on biological relevant systems.