A Python script for computing environment-aware RESP charges of ligands using QM/MM calculations with electrostatic embedding. The script supports both ORCA and PySCF as quantum mechanics engines and uses Multiwfn for RESP charge fitting.

• Overview
• Features
• Installation
• Dependencies
• Usage
• Input Files
• Output Files
• Examples
• Citation
• License

QMMESP calculates RESP (Restrained Electrostatic Potential) charges for ligands while considering their local protein environment through QM/MM calculations. Unlike traditional gas-phase RESP calculations, this approach:

• Includes environmental effects: The ligand is treated quantum mechanically while the protein environment is modeled with classical force fields
• Uses electrostatic embedding: Point charges from the MM region polarize the QM wavefunction
• Supports multiple QM engines: Choose between PySCF (default) or ORCA for quantum calculations
• Automated workflow: From prepared MD structures to final RESP charges in one step

• ✅ Dual QM Engine Support: PySCF (default) or ORCA
• ✅ Environment-aware Charges: QM/MM approach includes protein effects
• ✅ AMBER Integration: Direct prepi file updates for MD simulations

git clone https://github.com/miqueleg/QMMESP.git
cd QMMESP

#Create conda environment
conda create -n qmmesp python=3.13
conda activate qmmesp

#Install required packages
pip install numpy mdtraj

See Dependencies section for detailed installation instructions.

#Add to your ~/.bashrc or ~/.zshrc
export Multiwfnpath="/path/to/multiwfn"
export ORCADIR="/path/to/orca" # Only if using ORCA

python QMMESP.py --pdb complex.pdb --prmtop complex.prmtop --inpcrd complex.inpcrd --resid 1

python QMMESP.py
--pdb solvated_complex.pdb
--prmtop complex.prmtop
--inpcrd complex.inpcrd
--prepi ligand.prepi
--resid 285
--charge 0
--functional HF
--basis 6-31G*
--qm_engine pyscf
--output resp_results
--numcores 4

1. PDB File (--pdb): Solvated protein-ligand complex

   • Must contain properly numbered residues
   • Ligand should have a unique residue name
   • Can include crystallographic waters

2. Topology File (--prmtop): AMBER parameter/topology file

   • Generated using tleap with appropriate force fields
   • Must include parameters for all system components

3. Coordinate File (--inpcrd): AMBER coordinate file

   • Matching the topology file
   • Typically from energy minimization or equilibration

4. Prepi File (--prepi): AMBER residue library file
   • Will be updated with new RESP charges
   • Useful for subsequent MD simulations

python QMMESP.py
--pdb protein_ligand.pdb
--prmtop system.prmtop
--inpcrd system.inpcrd
--resid 500
--charge -1

python QMMESP.py
--pdb complex_solvated.pdb
--prmtop complex.prmtop
--inpcrd complex.inpcrd
--resid 285
--functional PW6B95
--basis aug-cc-pVDZ
--qm_engine orca
--numcores 16
--output resp2_results

python QMMESP.py
--pdb equilibrated.pdb
--prmtop system.prmtop
--inpcrd system.inpcrd
--prepi original_ligand.prepi
--resid 1
--functional B3LYP
--basis 6-31G*
--output updated_params

• Use PySCF for routine calculations: Generally faster and more stable
• Optimize core usage: Start with 4-8 cores, increase for large systems
• Monitor memory usage: Large basis sets may require significant RAM
• Use recomended basis sets: HF/6-31G* for ff14SB, PW6B95/aug-cc-pVDZ for ff19SB

• QM Region: Ligand of interest (specified by residue ID)
• MM Region: Protein, water, and ions
• Embedding: Electrostatic (point charges polarize QM wavefunction)
• Boundary: Automatic detection based on residue boundaries

1. ESP Generation: Quantum mechanical electrostatic potential on molecular surface
2. Grid Points: Multiwfn automatically generates fitting points
3. Restraints: Standard RESP restraints applied (0.0005 au for C,N,O,S; 0.001 au for H)
4. Fitting: Two-stage RESP procedure with buried carbon restraints

If you use this software in your research, please cite:

@software{qmmesp2025,
author = {Miquel Estévez-Gay},
title = {QMMESP: Environment-aware RESP charge derivation using QM/MM},
url = {https://github.com/miqueleg/QMMESP},
year = {2025}
}

• Bayly, C. I.; Cieplak, P.; Cornell, W.; Kollman, P. A. J. Phys. Chem. 1993, 97, 10269-10280. (Original RESP method)
• Schauperl, M.; Nerenberg, P. S.; Jang, H.; et al. J. Chem. Theory Comput. 2020, 16, 7044-7060. (RESP2 method)

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

This project is licensed under the MIT License - see the LICENSE file for details.

For questions, issues, or suggestions:

1. GitHub Issues: Create an issue
2. Email: [Your email if you want to provide it]
3. ORCA Forum: For ORCA-specific questions
4. PySCF Community: For PySCF-related issues
5. ASH GitHub: For ASH-related issues

Note: This software is provided as-is for research purposes. Always validate results against experimental data or established benchmarks for your specific systems.