Role of local environments in stabilizing protein structures

Abstract

Protein local environments, or clusters of interacting residues, play a crucial role in contributing to the stability and function of proteins. Perturbations to local environments, such as those resulting from interactions with other molecules or mutations, can lead to changes in protein structure and function. In this study, I characterized local environments in three different contexts: conformational changes in G protein-coupled receptors (GPCRs, the effect of mutations on protein stability, and designing small molecule inhibitors against the Nipah virus. GPCRs are a type of cell surface receptor that plays a crucial role in signaling pathways. When activated by a stimulus, GPCRs undergo conformational changes that lead to downstream signaling events. In the study, I used geometric and chemical similarity measures to compare the inactive and active states of Class A GPCRs, a subfamily of GPCRs. I identified approximately 25 conserved local environments that are likely to be involved in the conformational changes. These 25 local environments are conserved in at least 60% of Class A receptors, indicating evolutionary relationships in the Class A subfamily. To further validate the conserved local environments, I utilized existing data from the literature and conducted molecular dynamics simulations. The data from this study can be used to design novel GPCRs that respond to stimuli of our interest. We also developed a tool called Packpred that predicts the destabilizing effect of mutations on proteins. Packpred was trained on the T4 lysozyme saturation mutagenesis dataset and tested on the CcdB saturation mutagenesis dataset and the Missense3D dataset. Packpred was found to be more effective than 6 other state-of-the-art methods. By understanding the impact of perturbations on local environments, it may be possible to design strategies to modulate protein stability and function in a controlled manner. Finally, we attempted to identify drug-like small molecule inhibitors against the Nipah Virus proteome. We developed a novel methodology to obtain the putative lead molecules with higher confidence. To do this, we used a library of drug-like small molecules from the ZINC database and performed local docking on five proteins of the Nipah virus using two different docking software. Further, we selected only those small molecules that scored as top 150 in both the docking exercises. We then imposed a criteria of geometrical similarity between the poses predicted by the two docking software to gain higher confidence. Additionally, we performed molecular dynamics simulations to assess the stability of the small-molecule - protein interaction.