A Structural Refinement Technique for Protein-RNA Complexes Based on a Combination of AI-based Modeling and Flexible Docking: A Study of Musashi-1 Protein

Abstract

An efficient structural refinement technique for protein-RNA complexes is proposed based on a combination of AI-based modeling and flexible docking. Specifically, an enhanced sampling method called parallel cascade selection molecular dynamics (PaCS-MD) was extended to include flexible docking to construct protein-RNA complexes from those obtained by AI-based modeling (AlphaFold2). With the present technique, the conformational sampling of flexible RNA regions is accelerated by PaCS-MD, enabling one to construct plausible models for protein-RNA complexes. For demonstration, PaCS-MD constructed several protein-RNA complexes of the RNA-binding Musashi-1 (MSI1) family of proteins, which were validated by comparing a group of crucial residues for RNA-binding with experimental complexes. Our analyses suggest that PaCS-MD improves the quality of complex modeling compared to the standard protocol based on template-based modeling (Phyre2). Furthermore, PaCS-MD could also be a beneficial technique for constructing complexes of non-native RNA-binding to proteins.

Preferential Door for Ligand Binding and Unbinding Pathways in Inhibited Human Acetylcholinesterase

“…To overcome this difficulty, we used an enhanced method called ligand-binding path sampling via parallel cascade selection molecular dynamics (LB-PaCS-MD). 8,9 The LB-PaCS-MD method involves repeating multiple shorttime scale MD simulations in parallel, beginning from a highpotential configuration capable of inducing ligand binding or unbinding processes. 10 restarted from the initial structures selected in the previous cycle.…”

“…However, it is challenging when sampling long-time scale dynamics such as ligand binding and unbinding processes. To overcome this difficulty, we used an enhanced method called ligand-binding path sampling via parallel cascade selection molecular dynamics (LB-PaCS-MD). , The LB-PaCS-MD method involves repeating multiple short-time scale MD simulations in parallel, beginning from a high-potential configuration capable of inducing ligand binding or unbinding processes . Subsequently, this technique ranks and selects configurations as the initial structures for the next cycle from each short-time-scale MD simulation based on the shortest distance between the center-of-mass (COM) of a ligand and the targeted atom or residue in a protein.…”