Development of novel inhibitors targeting DRP1-MID49/51 interaction at mitochondrial fission

Abstract

Mitochondria are responsible for the production of the majority of our energy known as Adenosine Triphosphate(ATP). Energy production is the best-known role of mitochondria but they are responsible for other important tasks as well. Mitochondrial fission and fusion are necessary process for naturally dynamic mitochondria. Mitochondrial dysfunction plays a significant role in the development and progression of several diseases such as cancer and diabetes. Mitochondria continually undergo shape and number changes by fission and fusion. Cytoplasmic GTPase Dynamin-related protein 1 (DRP1) regulates mitochondrial fission. It is a protein, part of the dynamin family which is made up of an N-terminal GTPase domain and a C-terminal GTPase effector domain. MiD49 and MiD51 are mitochondrial dynamics proteins linked to the mitochondrial outer membrane. These two proteins directly recruit Drp1 protein to the mitochondrial membrane to form a ring around and start the fission process. Recent studies have shown that cancer tumors alter mitochondrial dynamics to resist apoptosis by causing fission protein, Dynamin-related protein 1 (DRP1) to overexpress. In addition, this is the cause of neurodegenerative and diabetes type 1 disorders. As a result, designing new inhibitors will have a great impact on finding ways to overcome mitochondrial disorders. While there have been many molecular docking studies about Drp1-MiD49/51 inhibition recently, in order to design small molecules that can be utilized as drugs, and not have side effects like Mdivi1 and Dynasore we performed this study in a specific way. Molecular docking calculation is an important approach in the field of drug design and discovery which is used when we want to predict a ligand-receptor complex structure. Docking is accomplished in two phases that are intertwined. First, sampling the structure of the ligand, as well as its position and orientation inside the protein's active site, and then these created conformations will be ranked among all conformations by a scoring function. Structure-based virtual screening (SBVS), also known as target-based virtual screening (TBVS), is a computational technique used in drug discovery which computationally screens a library of small molecules against a target to identify the best binding and high scored molecules. This study comprises two phases, first phase uses computational approaches that may improve resource utilization and speed drug development, and in the second phase, found novel compounds will be synthesized for further steps. In this thesis, the main focus will be on the computational phase of the work. Here we aim to inhibit DRP1-MiD49/MiD51 proteins interaction in several ways. In the first packet, we tried to design new inhibitors targeting the DRP1-GTPase nucleotide-binding domain. For this goal, docking calculations were performed in several stages. To start docking calculations, 3.5 million, in-stock, lead-like small molecules from the ZINC database were used. Autodock vina, Ledock and Schrodinger Glide(XP) programs were used in different steps for docking calculations. The reason for choosing these three programs was their high performance in different studies so far. After docking calculations for 3.5 million molecules another step was performed which was the docking of the previous step's high scored molecules to DRP1 protein's off-target proteins and in the same way to DRP1 protein using Vina(exhaustiveness 24) and Ledock. In the next step, molecules with specific criteria were selected for docking using Glide XP and then clustering and ADME/T (absorption, distribution, metabolism, and excretion/toxicity) properties to select optimum ligands for their possible pharmaceutical use. As the final step of the first path, high-scored molecules from the previous step were selected for molecular Dynamic simulations to calculate binding free energy using the OSPL2005 force field and TIP3P water model of Schrödinger Desmond Software and MMGBSA calculations. Finally, 30 molecules were selected as the molecules with the highest free binding energies. In the second packet, every step in packet 1 was repeated identically for MiD49 and MiD51 proteins.