Kinematic assessment to characterize protein and macromolecular conformations

Proteins are dynamic biomolecules with diverse cellular functions, and understanding their conformational ensemble is crucial for comprehending their role in health and disease. Over the past 50 years, extensive research investigated characterizing the structural and dynamic aspects of proteins, aided by experimental and computational advancements. However, the need for effective computational techniques that can capture functional movements across various levels remains substantial. This thesis introduces a kinematic model inspired by robotics, which adeptly captures both minor and major collective motions exhibited by pro- teins. By employing dihedral angles as torsional degrees of freedom (DoFs) and utilizing non-covalent interactions as constraints, the model provides a comprehensive understanding of protein dynamics. Additionally, a universal theory is developed for kinematic flexibility analysis using kinematic tools. Biophysically guided by protein structure, this approach of- fers atomically detailed insights into molecular mechanisms. To demonstrate the practical application of this model, this thesis investigates the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) and its main protease (Mpro), an indispensable enzyme for the replication of viruses and serving as a promising target for therapeutic intervention. The flexibility of Mpro conformations is analyzed in the presence of mutations and ligand bind- ing using kinematic flexibility analysis (KFA). Through the analysis of 47 mutation sites across 69 Mpro-ligand complexes, encompassing over 3,300 structures, these mutations are observed generally increase the conformational flexibility of the protein. These findings are vital for identifying potential drug targets against SARS-CoV-2 and provide valuable infor- mation about mechanisms of molecular recognition. Furthermore, this thesis addresses the computational challenge of estimating the entropic contribution to protein-ligand complex formation. By applying KFA, efficiently determining the vibrational frequencies of protein and protein-ligand structures is the primary focus, this is allowing for the determination of vibrational entropies. Estimates have been conducted that exhibit promising comparisons to results obtained through dynamic Normal Mode Analysis. By modifying the distance threshold within the potential energy model, enhancements are observed in correlation fac- tors. Employing this approach, this thesis investigated alterations in entropy within the SARS-CoV-2 main protease when interacting with different ligand inhibitors, facilitating the design of potential drugs. Additionally, protein kinases play a crucial role in cellular ac- tivities through phosphorylation. The conformational states of kinase activation loops and surrounding regions are informative for developing selective kinase inhibitors. By employing KFA, this thesis categorizes various conformations of the DFG motif located within the ac- tivation loop. This investigation focuses on examining disparities in the process of becoming rigid between the active and inactive states. Extensive examination of numerous kinases unveils a notable observation: the activation loop contributes to the rigidification of active kinase conformations, whereas this influence is comparatively less in the inactive state. In- terestingly, oncogenic mutations show reduced rigidification, indicating increased flexibility in the activated state. Overall, this kinematic modeling methodology provides a resilient and effective avenue for acquiring comprehensive perspectives on molecular mechanisms spanning diverse magnitudes. This approach holds extensive utility in fields such as protein engineer- ing, pharmaceutical formulation, and human well-being, bolstering comprehension of protein dynamics and facilitating the advancement of inventive therapeutic approaches. The integra- tion of experimental and computational techniques in this research advances the knowledge of the intricate relationship between protein structure and functionality, leading to new avenues for exploring the potential of proteins in various drug development applications.