A package for conformer generation of transition-metal-containing complexes
Project description
Latest:
Please update version 1.0.2 to 1.0.3.1+ 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 now be specified using the
-box
parameter - Support for multiple non-covalently bound solutes
- Support for QM/MM calculations as criteria for the energy ranking of generated conformers
- Support for restrained simulations involving transition states (Currently only for AmberMD)
- Support for cartesian coordinate restraints for residues, suitable for GIST analysis using
-cart
for the residues and-cartstr
for the restraint strength
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:
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
-box specify box size for your system
-e, --engine choice of simulation engine
-rst, --restraint perform a restrained simulation, useful for transition states
-cart, --cartesianrst [Mask] set up system for a simulation with cartesian restraints, uses the amber mask format. Use all for all solvent residues
-cartstr, --cartesianrststr [Value] strength of cartesian restraints in kcal/mol
options that affect analysis:
-a , --analyze analyze a simulation
-mask [MASK], --mask [MASK] atomid mask for clustering
-cluster [CLUSTER], --cluster [CLUSTER] clustering method
-nosp skip single point calculations for clusters
-qmmm, --qmmm use a qmmm approach to determine cluster energy ranking
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])
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