Restrained Electrostatic Potential

Installation

This RESP code is a plug-in to the Psi4 quantum chemistry package. To install Psi4, go to the this website: https://admiring-tesla-08529a.netlify.com/installs/latest/ and choose your preferred option (conda package recommended). If the RESP program was not installed by default, execute conda install resp -c psi4. To test that the RESP plug-in works, execute python -c "import resp, sys; sys.exit(resp.test('long'))". Two examples on how to use the plug-in are available in the directory examples.

Code

The following codes are available:

• resp/espfit.py: The restrained electrostatic potential (RESP) fitting procedure.
• resp/driver.py: Driver of the code.
• resp/tests/test_resp.py contains:
  • test_resp_1: Example for two-stage charge fitting for one conformer.
  • test_resp_2: Example for two-stage charge fitting for two conformers.

Helper programs:

• resp/vdw_surface.py
• resp/stage2_helper.py

Examples

There are several examples in examples on how to use the code for computing RESP charges and for enforcing charge constraints

RESP Method Summary

RESP charges result from fitting the classical electrostatic potential (ESP) generated by atom-centered point charges to the quantum ESP computed outside the van der Waals surface of the molecule. The fitted charges are restrained by a hyperbolic term, which requires an iterative fitting procedure to compute the charges.

The charges (q) are computed by solving the following equation:

A q = B.

The left-hand side contains the information about the classical ESP while the right-hand side contains information about the quantum ESP. A hyperbolic restraint term that depends on the charges is added to the diagonal elements of matrix A. The charges and the diagonal elements of A are changed iteratively until the charges converge.

References:

• [Bayly:93:10269-10280] C. I. Bayly et. al. J. Phys. Chem. 97, 10269 (1993)

Please cite this article if you use this program:

• [Alenaizan:19] A. Alenaizan, L. A. Burns, C. D. Sherrill, Python implementation of the restrained electrostatic potential charge model. Int. J. Quantum Chem.. (2019)