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MBind: A Web-Based Platform for Metalloprotein and Nonmetalloprotein Docking with Optional ML Docking Integration
Harrish Ganesh1, Sahith Mada2, Suhani Aryal3
1VCU Life Sciences, Virginia Commonwealth University, Richmond, VA 23284, USA.
Molecules (Basel, Switzerland)
|August 13, 2026
Summary
MBind v2026 is a new web-based graphical user interface (GUI) for metalloprotein docking. It simplifies complex steps and shows high accuracy for zinc metalloprotein and non-metalloprotein docking.
Area of Science:
- Computational chemistry
- Structural biology
- Bioinformatics
Background:
- Metalloprotein docking is challenging due to complex preparation steps like grid box definition, charge assignment, and metal coordination geometry.
- Existing graphical user interfaces (GUIs) often lack robust support for these specialized metalloprotein docking requirements.
Purpose of the Study:
- To introduce MBind v2026, a novel web-based GUI designed to streamline standard and metalloprotein docking.
- To integrate established docking tools (AutoDock Vina, AutoGrid4, AutoDock4) and optionally machine learning (ML) programs (GNINA v1.0) into a unified workflow.
- To provide validated workflows for zinc metalloprotein docking and preliminary support for magnesium, iron, and copper metalloproteins.
Main Methods:
- MBind v2026 was developed as a web-based GUI integrating AutoDock Vina, AutoGrid4, and AutoDock4, with optional GNINA v1.0 ML integration.
- The primary validated workflow utilizes AutoDock4Zn parameterization for zinc, with experimental workflows for Mg, Fe, and Cu.
- Benchmarking involved eight zinc metalloproteins and eight non-metalloproteins, comparing MBind's performance against various ML and non-ML docking and prediction tools using DockRMSD for pose accuracy and IC50-derived ΔG for binding energy trends.
Main Results:
- MBind achieved a mean RMSD of 0.49 Å on the zinc metalloprotein benchmark set.
- For non-metalloprotein targets, MBind demonstrated a mean RMSD of 0.62 Å.
- The platform successfully executed zinc metalloprotein and non-metalloprotein docking, indicating its utility, while Mg, Fe, and Cu workflows require further validation.
Conclusions:
- MBind v2026 offers a user-friendly, web-based solution for metalloprotein docking, simplifying complex computational procedures.
- The tool exhibits high accuracy for zinc-based metalloprotein docking and general non-metalloprotein docking tasks.
- Further development and validation are recommended for the preliminary workflows targeting magnesium, iron, and copper metalloproteins.
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