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CHARMM-GUI PDB Reader and Manipulator: Covalent Ligand Modeling and Simulation.

Lingyang Kong¹, Sang-Jun Park¹, Wonpil Im¹

¹Departments of Biological Sciences, Bioengineering, and Computer Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA.

Journal of Molecular Biology

|September 5, 2024

Summary

CHARMM-GUI now models covalent drugs, which form bonds with proteins for stronger effects. This new feature simplifies complex molecular simulations for drug discovery researchers.

Keywords:

All-atom Modeling Covalent Ligands Drug Discovery Molecular Dynamics Simulation Structure-based Virtual Screening

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Area of Science:

Biochemistry and Structural Biology
Computational Chemistry
Drug Discovery

Background:

Molecular modeling and simulation are crucial for understanding protein functions, complementing experimental approaches.
CHARMM-GUI is a web-based tool that simplifies the creation of molecular simulation systems.
Covalent drug discovery is a growing field due to the enhanced potency and prolonged inhibition offered by covalent inhibitors.

Purpose of the Study:

To introduce a new CHARMM-GUI functionality for modeling diverse covalent ligand-protein interactions.
To address the challenges in accurately representing covalent bonds in molecular simulations.
To enhance the accessibility of molecular dynamics simulations for studying covalent ligands.

Main Methods:

Development of a new module within CHARMM-GUI PDB Reader & Manipulator.
Implementation of algorithms to handle various ligand-amino acid linkage types.
Validation through a benchmark study of over 1,000 covalent ligand structures from the RCSB Protein Data Bank.

Main Results:

Successful integration of a new functionality in CHARMM-GUI for modeling covalent ligand-protein linkages.
Demonstrated accuracy and versatility in handling diverse covalent interactions.
Validated performance across a large dataset of experimentally determined structures.

Conclusions:

The enhanced CHARMM-GUI functionality facilitates the modeling and simulation of covalent ligands.
This development is expected to accelerate research in covalent drug discovery.
Improved accessibility to molecular dynamics simulations for studying covalent drug mechanisms.