Skip to main content

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

Project description

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.

Features

Utilizes freely available software, with high performance

18 predefined solvents and 6 counterions, 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
conda activate PyConSolv
pip install PyConSolv

using pip:

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

Usage

Console:

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

positional arguments:
input input file in XYZ format

options:
-h, --help show this help message and exit
-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
-nosp skip single point calculations for clusters -a , --analyze analyze a simulation
-mask [MASK], --mask [MASK] atomid mask for clustering
-cluster [CLUSTER], --cluster [CLUSTER] clustering method
-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-0.9.2.1.tar.gz (82.2 MB view hashes)

Uploaded Source

Built Distribution

pyconsolv-0.9.2.1-py3-none-any.whl (98.8 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