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MixMD Probeview: Robust Binding Site Prediction from Cosolvent Simulations.

Sarah E Graham, Noah Leja, Heather A Carlson

Journal of Chemical Information and Modeling

|June 16, 2018

Summary

Mixed-solvent molecular dynamics (MixMD) simulations can now be analyzed more easily. MixMD Probeview, a PyMOL plugin, automates the identification of protein binding sites from cosolvent simulations.

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Area of Science:

Computational chemistry
Structural biology
Drug discovery

Background:

Mixed-solvent molecular dynamics (MixMD) is a computational technique used to identify protein binding sites.
Current MixMD analysis methods often require extensive manual interpretation of simulation data.
Identifying specific binding hotspots and favorable interactions on protein surfaces is crucial for understanding molecular recognition.

Purpose of the Study:

To develop an automated tool for analyzing MixMD simulations.
To simplify the identification and ranking of binding sites and probe interactions.
To enhance the accessibility and efficiency of MixMD data analysis.

Main Methods:

Development of MixMD Probeview, a plugin for the PyMOL molecular visualization software.
Implementation of two analysis procedures: whole binding site identification/ranking and local maxima identification/ranking per probe type.
Validation of the plugin using four benchmark proteins, including those with active and allosteric sites.
Comparison of three cosolvent simulation strategies to assess their impact.

Main Results:

MixMD Probeview successfully identified known active and allosteric binding sites across all tested systems.
The plugin accurately ranked binding sites based on the total occupancy of neutral probe molecules.
The analysis of different cosolvent procedures provided insights into simulation strategy optimization.

Conclusions:

MixMD Probeview significantly streamlines the analysis of cosolvent molecular dynamics simulations.
The plugin facilitates the identification of biologically relevant binding sites on protein surfaces.
This tool is expected to accelerate drug discovery and molecular interaction studies by improving MixMD analysis efficiency.