Skip to main content

A package for conformer generation of transition-metal-containing complexes

Project description

License Latest Version DOI DOI

Latest:

Please update version 1.0.2 to 1.0.3 to fix a bug with generating parameters. Versions before 1.0.2 should not be affected.

Changelog from v 1.0.1:

  • More counterions are parametrized and supported by default
  • Box size can not be specified using the -box parameter

PyConSolv

A python based interface for generation of conformers of transition metal complexes in explicit solvent. The interface bridges to the well known MCPB.py package available within ambertools. The input required consists of only a simple xyz file and all required steps for parametrization are performed automatically, with minimal user intervention.

Publication:

PyConSolv: A Python Package for Conformer Generation of (Metal-Containing) Systems in Explicit Solvent R. A. Talmazan and M. Podewitz Journal of Chemical Information and Modeling 2023, 63, 17, 5400–5407 DOI: 10.1021/acs.jcim.3c00798

Features

Utilizes freely available software, with high performance

18 predefined solvents and 6 counterions (along with 40+ single atom ions), with the ability to use any solvent or counterion

Automated molecule splitting for transition metal parametrization

Utilizes ORCA 5.0 for quantum mechanical optimizations/frequency calculations

Utilizes MultiWfn for the generation of the RESP charges

Automated equilibration of simulation box

Automated clustering

Requirements

Python >= 3.10

AmberTools >= 20

ORCA >= 5.0

MultiWfn >= 3.8

Installation

The creation of a new virtual environment is highly recommended:

using conda:

conda create -c conda-forge --name PyConSolv python=3.10 rdkit numpy pandas parmed
conda activate PyConSolv
pip install PyConSolv

using pip:

python3 -m venv env
source env/bin/activate
pip install numpy pandas rdkit parmed PyConSolv

Usage

Console:

pyconsolv [-h] [-c [CHARGE]] [-m [METHOD]] [-b [BASIS]] [-d [DISPERSION]] [-s [SOLVENT]] [-p [CPU]] [-mult [MULTIPLICITY]] [-noopt] [-a [ANALYZE]] [-mask [MASK]] [-cluster [CLUSTER]] [-nosp] [-v] input

positional arguments:
input file in XYZ format

options that affect simulation setup:

-c [CHARGE], --charge [CHARGE] charge of the system, default 0
-m [METHOD], --method [METHOD] ORCA optimization/frequency calculations method of choice, default PBE0
-b [BASIS], --basis [BASIS] basis set to be used for calculations, default def2-SVP
-d [DISPERSION], --dispersion [DISPERSION] dispersion corrections, default = D4
-s [SOLVENT], --solvent [SOLVENT] solvent to be used for MD simulations/ OM Calculations, default Water
-p [CPU], --cpu [CPU] number of cpu cores to be used for calculations, default 12
-mult [MULTIPLICITY], --multiplicity [MULTIPLICITY] multiplicity of the system, default 1
-noopt perform a single point calculation instead of a geometry optimization

options that affect analysis:
-a , --analyze analyze a simulation
-mask [MASK], --mask [MASK] atomid mask for clustering
-cluster [CLUSTER], --cluster [CLUSTER] clustering method
-e, --engine choice of simulation engine
-nosp skip single point calculations for clusters

general options: -h, --help show this help message and exit
-v, --version show program's version number and exit

see user manual for more details

Jupyter Notebook

from PyConSolv import ConfGen

conf = ConfGen(path/to/input.xyz)

conf.run([options])

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyconsolv-1.0.3.tar.gz (85.2 MB view hashes)

Uploaded Source

Built Distribution

pyconsolv-1.0.3-py3-none-any.whl (113.9 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page