Project

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Fall 2024 challenge: phase 2 contestant

Structure-Based Design of Noval UBE2N Inhibitors to Overcome PARP Inhibitor Resistance

Shafi Ullah Khan, UNIVERSITE DE CAEN NORMANDIE -ANTICIPE, Caen, France

As a BioSolveIT Challenge contestant, I've had the privilege of utilizing their advanced computational tools over the past three months. My research has focused on identifying potential binding sites for UBE2Ni inhibitors, exploring both covalent and non-covalent binding modes. Initial analysis of the co-crystallized ligand, which is actually a partial moiety of the full covalent UBE2Ni inhibitor, hindered accurate prediction of binding poses and potential interactions. Its incomplete nature made it difficult to discern the correct binding orientation. To overcome these limitations, I am grateful for access to the SeeSAR tool, which has been invaluable in exploring alternative binding modes and identifying binding sites of known UBE2Ni
After 3 months, Shafi Ullah has achieved the following milestones:
  1. Initial Challenges: Difficulty in accurately predicting binding poses for the partial cocrystal moiety UBENi using docking approaches. This hindered the accurate prediction of binding orientations for non-covalent inhibitors. Innovative Approach: Utilized SeeSAR's "Find similar binding site in PDB" tool to identify 7 unique proteins with similar binding sites. These sites were predominantly biased towards covalent inhibitors. Uncovering New Pockets: Employed SeeSAR's unoccupied pocket prediction capabilities to identify three distinct pockets (1, 2, and 3). Assessing Non-Covalent Inhibitor Binding: Conducted docking simulations using three approaches: Single-site docking Pairwise pocket docking All-pocket site selection Utilized the HYDE score to evaluate the preliminary affinity of known non-covalent UBE2Ni inhibitors within these pockets. The unexplored binding sites identified by SeeSAR offer a promising approach for challenging target proteins.
  2. MD simulation analyses (which are underway) will inform optimization strategies for future SBVS campaigns for UBE2Ni. In addition to SBVS, LBVS has been planned to utilize the InfinSee tool, employing known UBE2Ni molecules as query structures. The identified hits will be further optimized for binding affinity using FlexS and the FastGrow tool in SeeSAR.
  3. Despite the challenges associated with the target protein and the limited molecular modeling information available for designing UBE2Ni, I remain optimistic about the potential of the BioSolveIT tool to successfully advance our ongoing research project.