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We can improve protein binding affinity by improving the enthalpy and entropy of binding. We need to improve amino acid side chain interactions (stronger interactions) and minimize the motion of the decoy when it is not bound to the viral spike protein (minimal entropic penalty). We want to add as many of Dr Procko's mutations into ACE2 or our decoy as possible. It is our job to examine the nature of these side chain interactions (Video). The table below shows the systems that need to be investigated with MD simulations.
Goal 1: Analyze MD simulation trajectories of SARS-CoV-2 RBD complex (with hACE2, 6m17) with gRINN (or NAMD Energy Extension of VMD) and test the idea of Renzi and Ghersi that ~90% of interaction energies come from alpha-1 helix of hACE2. Replicate the MD simulation and gRINN results. Can we replicate the results with Modeller?
Goal 2: Run MD simulations with combinations of Dr Procko's mutations and analyze interaction energies with gRINN and NAMDEnergy NAMDEnergy script can be used in the VMD Tk console. Design a decoy with optimal mutations for binding with SARS-CoV-2 Spike Protein.
As you can see in the table above, 6 mutants of sACE2 must be defined to investigate Dr Procko's mutations. The table below shows the current suggestions generated with a random sampling approach. Hannah is working on an exhaustive search method.
Dr Procko's Mutations: S19P, Q24T, A25V, K26D etc
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