PRISM - Protein Receptor Interaction Simulation Modeler

PRISM is a comprehensive tool for building protein-ligand systems for molecular dynamics simulations in GROMACS. It supports multiple force fields for ligands including GAFF, GAFF2, OpenFF, CGenFF, OPLS-AA, and SwissParam (MMFF/MATCH/Hybrid).

Features

Multiple Force Field Support
- GAFF/GAFF2 via AmberTools
- OpenFF via openff-toolkit
- CGenFF (CHARMM General Force Field) via web download
- OPLS-AA via LigParGen server
- SwissParam (MMFF/MATCH/Hybrid) via SwissParam server
Automatic System Building: Complete workflow from PDB/MOL2/SDF to simulation-ready files
Flexible Configuration: YAML-based configuration for easy customization
Smart File Processing: Handles various input formats with automatic conversion
Position Restraints: Automatic generation for equilibration protocols
Complete MDP Files: Pre-configured protocols for minimization, equilibration, and production
Metal Ion Support: Intelligent recognition and handling of metal ions (Zn, Ca, Mg, Fe, etc.) with distance-based filtering
Advanced Protein Cleaning: Smart removal of heteroatoms and crystallization artifacts while preserving structural metals
Protonation State Prediction: Optional pKa-based protonation for ionizable residues with PROPKA (HIS/ASP/GLU/LYS/CYS/TYR)
Protonation States: Support for special residue protonation states (CYM, HID, HIE, HIP, CYX, LYN, ASH, GLH)
CADD-Agent

Installation

Prerequisites

GROMACS (required)

# Ubuntu/Debian, CUDA-toolkit is needed, Dependence installation
nvcc --version # For check
sudo apt-get install gcc
sudo apt-get install g++
sudo apt-get install cmake

# Download GROMACS Package
wget https://ftp.gromacs.org/gromacs/gromacs-2025.1.tar.gz
tar xfz gromacs-2025.1.tar.gz

# Prepare to build GROMACS with cmake
cd gromacs-2025.1
mkdir build
cd build

# Installation
cmake .. -DGMX_MPI=ON \
-DGMX_BUILD_OWN_FFTW=ON \
-DGMX_GPU=CUDA \
-DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda \
-DCUDA_INCLUDE_DIRS=/usr/local/cuda/include \
-DCUDA_CUDART_LIBRARY=/usr/local/cuda/lib64 \
-DCMAKE_INSTALL_PREFIX=~/gromacs-2025.1

make -j${nproc}
make check # Optional but recommended
sudo make install
source /mnt/data/zf/gromacs-2024.3/bin/GMXRC

# install bioconda
conda install -c bioconda

Python 3.10 with required packages:

# create environment 
conda create -n prism python=3.10
conda activate prism

PDBFixer and pyyaml (required)

conda install -c conda-forge pdbfixer numpy scipy
pip install pyyaml

Optional Dependencies

For Protonation State Prediction (optional):

# PROPKA for pKa-based protonation prediction (optional)
conda install -c conda-forge propka
# or
pip install propka>=3.4.0

# Or install with PRISM protonation extras
pip install -e .[protonation]

Force Field Specific Dependencies

For GAFF/GAFF2 Support:

# AmberTools (required)
conda install conda-forge::ambertools
# ACPYPE (required)
pip install acpype
# Optional but recommended
conda install -c conda-forge rdkit

For OpenFF Support:

# OpenFF toolkit and dependencies
conda install -c conda-forge openff-toolkit openff-interchange

# RDKit (required for SDF handling)
conda install -c conda-forge rdkit

# OpenBabel (Optional but Recommended)
conda install conda-forge::openbabel

For CGenFF Support:

CGenFF requires downloading force field files from the web server:

Visit https://cgenff.com/
Upload your ligand structure (MOL2/SDF)
Download the generated files (PDB and TOP files)
Place them in a directory
Use --ligand-forcefield cgenff --forcefield-path /path/to/cgenff_files

Note: For halogens (F, Cl, Br, I), PRISM automatically removes lone pair (LP) atoms and transfers their charges to halogen atoms.

For OPLS-AA Support:

OPLS-AA uses the LigParGen web server (requires internet connection):

# Required Python packages
pip install requests

Usage: --ligand-forcefield opls

Note: Internet connection required during force field generation.

For SwissParam Support (MMFF/MATCH/Hybrid):

SwissParam uses the SwissParam web server (requires internet connection):

# Required Python packages
pip install mechanize

Usage:

--ligand-forcefield mmff (MMFF-based)
--ligand-forcefield match (MATCH)
--ligand-forcefield hybrid (Hybrid MMFF-based-MATCH)

Note: Internet connection required during force field generation.

Installing PRISM

Clone or download the PRISM package
Install in development mode:
```
cd PRISM
pip install -e .
```

Or use directly without installation:

python /path/to/PRISM/prism/builder.py

Documentation

For detailed tutorials, guides, and API references, visit the PRISM documentation:

📚 https://prism-tutorial.com/

The documentation includes:

Basic Tutorial: Get started with PRISM from scratch
FEP Tutorial: Learn free energy perturbation calculations
Configuration Guide: Detailed parameter reference
Analysis Tools: Trajectory and energy analysis
FEP User Guide: Complete FEP workflow documentation

Quick Start

Basic Usage

Using GAFF (default):

prism protein.pdb ligand.mol2 -o output_dir

Using GAFF2 (improved GAFF):

prism protein.pdb ligand.mol2 -o output_dir --ligand-forcefield gaff2

Using OpenFF:

prism protein.pdb ligand.sdf -o output_dir --ligand-forcefield openff

Using CGenFF:

# First download CGenFF files from https://cgenff.com/

# Single ligand:
prism protein.pdb ligand.mol2 -o output_dir --ligand-forcefield cgenff --forcefield-path /path/to/cgenff_files

# Multiple ligands (requires one --forcefield-path per ligand):
prism -pf protein.pdb -lf ligand1.mol2 -lf ligand2.mol2 -o output_dir \
  --ligand-forcefield cgenff \
  -ffp /path/to/cgenff_ligand1 \
  -ffp /path/to/cgenff_ligand2

Using OPLS-AA:

prism protein.pdb ligand.mol2 -o output_dir --ligand-forcefield opls

Using SwissParam force fields:

# MMFF-based
prism protein.pdb ligand.mol2 -o output_dir --ligand-forcefield mmff

# MATCH
prism protein.pdb ligand.mol2 -o output_dir --ligand-forcefield match

# Hybrid MMFF-based-MATCH
prism protein.pdb ligand.mol2 -o output_dir --ligand-forcefield hybrid

With custom configuration:

prism protein.pdb ligand.mol2 -o output_dir --config my_config.yaml

With specific protein force field:

prism protein.pdb ligand.mol2 -o output_dir --forcefield amber14sb --water tip4p

With advanced protein cleaning:

# Keep all metal ions
prism protein.pdb ligand.mol2 -o output_dir --ion-mode keep_all

# Remove all metal ions
prism protein.pdb ligand.mol2 -o output_dir --ion-mode remove_all

# Custom distance cutoff for metals
prism protein.pdb ligand.mol2 -o output_dir --distance-cutoff 8.0

# Keep crystal water molecules
prism protein.pdb ligand.mol2 -o output_dir --keep-crystal-water

With protonation prediction (PROPKA):

# Use PROPKA at pH 7.0
prism protein.pdb ligand.mol2 -o output_dir --protonation propka

# Custom pH (7.4)
prism protein.pdb ligand.mol2 -o output_dir --protonation propka --pH 7.4

Running MD Simulations

After PRISM completes, you can run the simulations:

cd output_dir/GMX_PROLIG_MD

Create and save localrun.sh:

#!/bin/bash

######################################################
# SIMULATION PART
######################################################

# Energy Minimization (EM)
mkdir -p em
if [ -f ./em/em.gro ]; then
    echo "EM already completed, skipping..."
elif [ -f ./em/em.tpr ]; then
    echo "EM tpr file found, continuing from checkpoint..."
    gmx mdrun -s ./em/em.tpr -deffnm ./em/em -ntmpi 1 -ntomp 10 -gpu_id 0 -v -cpi ./em/em.cpt
else
    echo "Starting EM from scratch..."
    gmx grompp -f ../mdps/em.mdp -c solv_ions.gro -r solv_ions.gro -p topol.top -o ./em/em.tpr -maxwarn 999
    gmx mdrun -s ./em/em.tpr -deffnm ./em/em -ntmpi 1 -ntomp 10 -gpu_id 0 -v
fi

# NVT Equilibration
mkdir -p nvt
if [ -f ./nvt/nvt.gro ]; then
    echo "NVT already completed, skipping..."
elif [ -f ./nvt/nvt.tpr ]; then
    echo "NVT tpr file found, continuing from checkpoint..."
    gmx mdrun -ntmpi 1 -ntomp 10 -nb gpu -bonded gpu -pme gpu -gpu_id 0 -s ./nvt/nvt.tpr -deffnm ./nvt/nvt -v -cpi ./nvt/nvt.cpt
else
    echo "Starting NVT from scratch..."
    gmx grompp -f ../mdps/nvt.mdp -c ./em/em.gro -r ./em/em.gro -p topol.top -o ./nvt/nvt.tpr -maxwarn 999
    gmx mdrun -ntmpi 1 -ntomp 10 -nb gpu -bonded gpu -pme gpu -gpu_id 0 -s ./nvt/nvt.tpr -deffnm ./nvt/nvt -v
fi

# NPT Equilibration
mkdir -p npt
if [ -f ./npt/npt.gro ]; then
    echo "NPT already completed, skipping..."
elif [ -f ./npt/npt.tpr ]; then
    echo "NPT tpr file found, continuing from checkpoint..."
    gmx mdrun -ntmpi 1 -ntomp 10 -nb gpu -bonded gpu -pme gpu -gpu_id 0 -s ./npt/npt.tpr -deffnm ./npt/npt -v -cpi ./npt/npt.cpt
else
    echo "Starting NPT from scratch..."
    gmx grompp -f ../mdps/npt.mdp -c ./nvt/nvt.gro -r ./nvt/nvt.gro -t ./nvt/nvt.cpt -p topol.top -o ./npt/npt.tpr -maxwarn 999
    gmx mdrun -ntmpi 1 -ntomp 10 -nb gpu -bonded gpu -pme gpu -gpu_id 0 -s ./npt/npt.tpr -deffnm ./npt/npt -v
fi

# Production MD
mkdir -p prod
if [ -f ./prod/md.gro ]; then
    echo "Production MD already completed, skipping..."
elif [ -f ./prod/md.tpr ]; then
    echo "Production MD tpr file found, continuing from checkpoint..."
    gmx mdrun -ntmpi 1 -ntomp 10 -nb gpu -bonded gpu -pme gpu -gpu_id 0 -s ./prod/md.tpr -deffnm ./prod/md -v -cpi ./prod/md.cpt
else
    echo "Starting Production MD from scratch..."
    gmx grompp -f ../mdps/md.mdp -c ./npt/npt.gro -r ./npt/npt.gro -p topol.top -o ./prod/md.tpr -maxwarn 999
    gmx mdrun -ntmpi 1 -ntomp 10 -nb gpu -bonded gpu -pme gpu -gpu_id 0 -s ./prod/md.tpr -deffnm ./prod/md -v
fi

run bash localrun.sh

Command-Line Parameters

PRISM provides convenient shortcuts for frequently used parameters, allowing you to write more concise commands while maintaining full compatibility with the complete parameter names.

Common Parameters and Shortcuts

Basic Setup

-pf, --protein-file: Protein PDB file path (alternative to positional argument)
-lf, --ligand-file: Ligand structure file (MOL2/SDF) (alternative to positional argument)
-o, --output: Output directory for generated files
-c, --config: Custom configuration YAML file
-f, --overwrite: Force overwrite existing files

Force Field Options

-ff, --forcefield: Protein force field (e.g., amber99sb, amber14sb, charmm36)
-lff, --ligand-forcefield: Ligand force field (gaff, gaff2, openff, cgenff, opls, mmff, match, hybrid)
-w, --water: Water model (tip3p, tip4p, spce)
-ffp, --forcefield-path: Path to CGenFF downloaded files (required for cgenff)

⚠️ Important Distinction:

-pf/-lf are for file paths (where to find protein/ligand files)
-ff/-lff are for force fields (which force field to use for protein/ligand)

System Configuration

-d, --box-distance: Distance from protein to box edge in nm (default: 1.5)
-bs, --box-shape: Simulation box shape (cubic, dodecahedron, octahedron)
-t, --temperature: Simulation temperature in Kelvin (default: 310)
-p, --pressure: Simulation pressure in bar (default: 1.0)

Ion Parameters

-sc, --salt-concentration: Salt concentration in M (default: 0.15)
-pion, --positive-ion: Positive ion type (default: NA)
-nion, --negative-ion: Negative ion type (default: CL)

Protein Preparation Parameters

-im, --ion-mode: Ion handling mode (smart, keep_all, remove_all; default: smart)
-dc, --distance-cutoff: Distance cutoff for metal ions in Å (default: 5.0)
-kcw, --keep-crystal-water: Preserve crystal water molecules (default: false)
-nra, --no-remove-artifacts: Keep crystallization artifacts (default: false)
-proton, --protonation: Protonation method (gromacs or propka; default: gromacs)
--pH: Target pH for protonation prediction (default: 7.0)

MM/PBSA Analysis

-pbsa, --mmpbsa: Run MM/PBSA binding energy calculation
-m, --mode: MM/PBSA mode (single-frame or trajectory)
-s, --structure: Structure file for single-frame calculation
-sd, --system-dir: PRISM-generated system directory
-po, --mmpbsa-output: Output directory for MM/PBSA results

Usage Examples with Shortcuts

Quick start with minimal typing:

prism protein.pdb ligand.mol2 -o output -f

Specify force fields using shortcuts:

prism protein.pdb ligand.mol2 -o output -ff amber14sb -lff gaff2 -w tip4p

Customize system parameters:

prism protein.pdb ligand.mol2 -o output -d 2.0 -t 300 -sc 0.1 -f

Run MM/PBSA calculation:

prism -pbsa -m single-frame -s em.gro -sd system_dir -f

Mix shortcuts and full names (fully compatible):

prism protein.pdb ligand.mol2 -o output --forcefield amber99sb -lff openff --box-distance 1.8

Advanced example combining multiple options:

prism protein.pdb ligand.sdf \
    -o my_simulation \
    -ff amber14sb \
    -lff openff \
    -w tip4p \
    -d 2.0 \
    -t 310 \
    -sc 0.15 \
    -f

All shortcuts are designed to be intuitive while maintaining backward compatibility with existing scripts that use full parameter names.

Force Field Selection Guide

When to Use Each Force Field

Force Field	Best For	Pros	Cons	Internet Required
GAFF	General small molecules	Widely used, well-tested	Older parameters	No
GAFF2	General small molecules	Improved over GAFF, better for pharmaceuticals	Newer, less tested	No
OpenFF	Drug-like molecules	Modern, data-driven parameters	Requires more dependencies	No
CGenFF	CHARMM compatibility	Consistent with CHARMM protein FF	Manual web download required	For download
OPLS-AA	All-atom simulations	Good for organic molecules	Internet required	Yes
MMFF	Quick parameterization	Fast, general purpose	Less accurate for MD	Yes
MATCH	CHARMM-style parameters	Good transferability	May fail for complex molecules	Yes
Hybrid	Balanced approach	Combines MMFF and MATCH	Internet required	Yes

Special Features

Metal Ions: Automatically recognized and handled (Zn²⁺, Ca²⁺, Mg²⁺, Fe²⁺/³⁺, Cu²⁺, Mn²⁺, etc.)
Protonation States: Support for CYM, HID, HIE, HIP, CYX, LYN, ASH, GLH
Halogen Handling: CGenFF lone pairs (LP) automatically removed and charges transferred

Protein Preparation

PRISM provides advanced protein preparation with intelligent cleaning and optional protonation state optimization to ensure your protein structure is properly prepared for molecular dynamics simulations.

Protein Cleaning

The ProteinCleaner class automatically processes protein PDB files with intelligent handling of metal ions and crystallization artifacts.

Ion Handling Modes

PRISM offers three modes for handling metal ions and heteroatoms:

smart (default): Keeps structural metals (Zn, Mg, Ca, Fe, Cu, Mn, etc.) while removing non-structural ions (Na, Cl, K, etc.)
keep_all: Preserves all metal ions and heteroatoms (except water unless specified)
remove_all: Removes all metal ions and heteroatoms

Structural metals preserved in smart mode: ZN, MG, CA, FE, CU, MN, CO, NI, CD, HG
Non-structural ions removed in smart mode: NA, CL, K, BR, I, F, SO4, PO4, NO3, CO3

Distance-Based Filtering

Metals are only kept if they are within a specified distance from the protein:

Default cutoff: 5.0 Å
Configurable: Adjust via --distance-cutoff parameter
Purpose: Removes distant, non-coordinating metals that may be crystallization artifacts

Crystallization Artifact Removal

Common crystallization additives are automatically removed:

Polyols: Glycerol (GOL), ethylene glycol (EDO), MPD
PEG oligomers: PEG, PGE, 1PE, P6G, etc.
Sugars: NAG, NDG, BMA (unless covalently linked to protein)
Detergents: DMS, BOG, LMT, etc.
Other additives: ACT, ACE, FMT, TRS, etc.

GROMACS Compatibility

The cleaner automatically handles GROMACS requirements:

HETATM → ATOM conversion: Metal ions are converted from HETATM to ATOM records
Chain reassignment: Proteins and metals are placed in separate chains for pdb2gmx compatibility
Terminal atom fixing: Automatic correction of C-terminal oxygen atoms

Protonation State Prediction (PROPKA)

PRISM can optionally use PROPKA to predict pKa values and assign protonation states for ionizable residues (HIS/ASP/GLU/LYS/CYS/TYR) at a target pH. It renames residues in the PDB, and GROMACS pdb2gmx -ignh regenerates hydrogens based on those states.

Features

PROPKA integration: pKa-based ionizable residue prediction
pH-based control: Choose target pH for prediction
GROMACS-ready: Residue renaming for pdb2gmx (e.g., HID/HIE/HIP, ASH/GLH, LYN/CYM/TYH)

Requirements

# Install PROPKA (required for protonation prediction)
conda install -c conda-forge propka
# or
pip install propka>=3.4.0

# Or install with PRISM protonation extras
pip install -e .[protonation]

Protonation Control

Method: Choose gromacs (default) or propka
Target pH: Configurable pH for PROPKA prediction (default: 7.0)

Configuration

PRISM uses YAML configuration files for customization. Key parameters include:

Force fields: Choose from AMBER, CHARMM, or OPLS variants
Water models: TIP3P, TIP4P, SPC, SPCE
Simulation parameters: Temperature, pressure, time, etc.
Box settings: Size, shape, solvation
Output controls: Trajectory frequency, compression
Protein preparation: Advanced cleaning and ion handling options
Protonation: Optional pKa-based protonation for ionizable residues with PROPKA

Protein Preparation Configuration

# Protein preparation settings
protein_preparation:
  ion_handling_mode: smart      # keep_all, smart, remove_all
  distance_cutoff: 5.0        # Distance cutoff for metals (Å)
  keep_crystal_water: false    # Preserve crystal water
  remove_artifacts: true      # Remove crystallization artifacts

Protonation Configuration

# Protonation state prediction
protonation:
  method: gromacs  # 'gromacs' (default) or 'propka'
  ph: 7.0          # Target pH for PROPKA pKa prediction

See configs/default.yaml for a complete example.

File Structure

PRISM/
├── prism/                    # Core modules
│   ├── __init__.py
│   ├── builder.py           # Main program
│   ├── forcefield/          # Force field generators
│   │   ├── __init__.py
│   │   ├── base.py         # Base class
│   │   ├── gaff.py         # GAFF force field
│   │   ├── gaff2.py        # GAFF2 force field
│   │   ├── openff.py       # OpenFF force field
│   │   ├── cgenff.py       # CGenFF force field
│   │   ├── opls_aa.py      # OPLS-AA force field
│   │   └── swissparam.py   # SwissParam force fields
│   └── utils/              # Utilities
│       ├── cleaner.py      # Protein cleaning & metal handling
│       ├── system.py       # System building
│       ├── config.py       # Configuration management
│       └── mdp.py          # MDP file generation
├── configs/                 # Example configurations
├── examples/               # Example input files
├── docs/                   # Documentation
└── README.md              # This file

Output Files

PRISM generates a complete set of files ready for MD simulation:

Force field files (directory name depends on force field):
- LIG.amb2gmx/ (GAFF/GAFF2)
- LIG.openff2gmx/ (OpenFF)
- LIG.cgenff2gmx/ (CGenFF)
- LIG.opls2gmx/ (OPLS-AA)
- LIG.mmff2gmx/, LIG.match2gmx/, LIG.hybrid2gmx/ (SwissParam)
Each contains:
- LIG.gro: Ligand coordinates
- LIG.itp: Ligand topology
- atomtypes_LIG.itp: Atom type definitions
- posre_LIG.itp: Position restraints
System files (GMX_PROLIG_MD/):
- solv_ions.gro: Complete solvated system
- topol.top: System topology
- protein_clean.pdb: Cleaned protein structure
- topol_Protein.itp: Protein topology
- topol_Ion*.itp: Metal ion topologies (if present)
Protocol files (mdps/):
- em.mdp: Energy minimization
- nvt.mdp: NVT equilibration
- npt.mdp: NPT equilibration
- md.mdp: Production run
Configuration backup:
- prism_config.yaml: Complete configuration used for this build

Troubleshooting

Common Issues

"Command not found" errors: Ensure all dependencies are installed and in PATH

# Check GROMACS
gmx --version

# Check AmberTools (for GAFF/GAFF2)
antechamber -h

# Check Python packages
python -c "import openff.toolkit"  # For OpenFF
python -c "import requests"         # For OPLS-AA
python -c "import mechanize"        # For SwissParam

Force field errors:
- GAFF/GAFF2: Ensure AmberTools and ACPYPE are installed
- OpenFF: Check openff-toolkit and openff-interchange
- CGenFF: Verify you downloaded the correct files from the web server
- OPLS-AA: Check internet connection and requests package
- SwissParam: Check internet connection and mechanize package
SwissParam errors:
- MATCH ERROR: Could not Finish Charging: Try --ligand-forcefield mmff or --ligand-forcefield hybrid
- Tautomer issues: Use a different force field (GAFF2 recommended)
CGenFF halogen issues:
- LP (lone pair) atoms are automatically removed
- If you see LP-related errors, please report as a bug
Metal ion issues:
- PRISM automatically detects common metal ions
- Supported: Zn, Ca, Mg, Fe, Cu, Mn, Co, Ni, K, Na, Cl
- If a metal is not recognized, it may be treated as a regular atom
Protonation state issues:
- Ensure residues use standard names (CYM, HID, HIE, HIP, CYX, LYN, ASH, GLH)
- GROMACS pdb2gmx should handle these automatically
Protein Preparation Issues:

PROPKA Not Available:
- Error: "PROPKA not found" or similar
- Solution: Install with conda install -c conda-forge propka or pip install propka>=3.4.0 (or pip install -e .[protonation])
- Note: If you do not want PROPKA, keep protonation.method: gromacs (default)
Metal Ions Removed by Distance:
- Message: "Removed ZN at distance 6.2 Å from protein"
- Solution: Increase distance cutoff if metal is important: --distance-cutoff 8.0
Unknown Metal/Ion Warnings:
- Message: "Warning: Unknown metal/ion MO, keeping by default"
- Solution: Add custom metal to keep list in configuration or use --ion-mode keep_all
PROPKA Renaming Summary:
- Message: "PROPKA: Renamed X residue(s)"
- Note: This is expected when --protonation propka is enabled
Terminal Atom Issues:
- Message: "Fixed C-terminal residues with misplaced oxygen atoms"
- Note: This is normal behavior. PRISM automatically fixes terminal atom naming for GROMACS compatibility
Memory errors: Large systems may require more RAM, especially during parameterization

Getting Help

Check the log files in the output directory
Ensure input files are properly formatted (PDB/MOL2/SDF)
Verify all dependencies are correctly installed
Check PRISM configuration in prism_config.yaml
For internet-based force fields, verify network connectivity

CADD-Agent: AI-Driven Drug Screening Pipeline

PRISM includes CADD-Agent, an AI agent workflow that orchestrates a complete computer-aided drug design pipeline through Claude Code and MCP (Model Context Protocol).

Pipeline

chemblfind (1000) -> MolScope (100) -> AutoDock Vina (top 10) -> PRISM (10 MD systems)

Stage	Tool	Function
1. Target search	ChEMBLFind	Search ChEMBL for bioactive molecules
2. Chemical space selection	MolScope	Select representative molecules covering chemical space
3. Molecular docking	AutoDock Vina MCP	Blind docking with AutoDock Vina
4. MD system building	PRISM	Build GROMACS-ready MD systems
5. Stability analysis	PRISM	RMSD, contacts, trajectory analysis

Prerequisites

Python >= 3.10 required (MCP server libraries mcp and fastmcp do not support Python 3.9).

# Create conda environment with Python 3.10+
conda create -n cadd python=3.12
conda activate cadd

# Install computational dependencies
conda install -c conda-forge ambertools openbabel
pip install vina rdkit

Install the 4 MCP server packages:

# 1. ChEMBLFind - ChEMBL molecule search
pip install git+https://github.com/AIB001/ChEMBLFind

# 2. MolScope - Chemical space coverage selection
pip install git+https://github.com/AIB001/MolScope

# 3. AutoDock Vina MCP - Molecular docking
pip install git+https://github.com/AIB001/AutodockVina_MCP

# 4. PRISM (this package)
pip install -e .

# 5. Claude Code (requires Node.js)
npm install -g @anthropic-ai/claude-code

One-Command Setup

Run (packages do not need to be fully installed first — missing ones will be reported):

prism --add cadd-agent

This will:

Auto-detect installed MCP server paths (Python interpreter, server scripts)
Configure ~/.claude/settings.json with found MCP servers (global, works in any directory)
Create ~/.claude/CLAUDE.md with CADD workflow trigger rules
Copy .mcp.json and CLAUDE.md templates to the current directory
Report any missing packages with install commands

Usage

After setup, start Claude Code in any directory containing a protein PDB file:

mkdir my_project && cd my_project
cp /path/to/protein.pdb .
claude

Then simply tell the agent what you want:

"I want to screen inhibitors for Riboflavin Synthase"

The agent will guide you through the full pipeline, confirming parameters at each step.

Manual Setup (Alternative)

If you prefer manual configuration, copy the template files from prism/prompts/resources/:

cp prism/prompts/resources/CLAUDE.md ~/.claude/CLAUDE.md
# Then edit ~/.claude/settings.json to add MCP server paths
# (see prism/prompts/resources/.mcp.json for the template)

Citation

If you use PRISM in your research, please cite:

Paper (methodology and applications):

@article{PRISM,
  title = {PRISM: A High-Throughput Simulation Infrastructure for CADD Agents},
  author = {Shi, Zhaoqi and Gao, Xufan and Xu, Mingyu and Zhu, Xuanyi and Wang, Peng and Yang, Yuxuan and Yang, Zaixing and Zhou, Ruhong},
  year = {2026},
  doi = {https://doi.org/10.64898/2026.04.02.716083},
  publisher = {BioRxiv Preprints},
  url = {https://doi.org/10.64898/2026.04.02.716083}
}

Code (software archive):

@software{PRISM_Code,
  author = {Shi, Zhaoqi and Gao, Xufan and Xu, Mingyu and Zhu, Xuanyi and Wang, Peng and Yang, Yuxuan and Yang, Zaixing and Zhou, Ruhong},
  title = {PRISM: Protein Receptor Interaction Simulation Modeler},
  year = {2026},
  doi = {https://doi.org/10.5281/zenodo.19163575},
  publisher = {Zenodo},
  url = {https://zenodo.org/records/19163575}
}

Links:

Paper: https://doi.org/10.64898/2026.04.02.716083
Code: https://doi.org/10.5281/zenodo.19163575
Local PDF: tests/gxf/FEP/plan/2026.04.02.716083v1.full.pdf

License

PRISM is released under the MIT License. Force field parameters are subject to their respective licenses.

Name		Name	Last commit message	Last commit date
Latest commit History 370 Commits
prism		prism
tests		tests
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
CLAUDE.md		CLAUDE.md
README.md		README.md
pyproject.toml		pyproject.toml
requirements.txt		requirements.txt
setup.py		setup.py

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PRISM - Protein Receptor Interaction Simulation Modeler

Features

Installation

Prerequisites

Optional Dependencies

For Protonation State Prediction (optional):

Force Field Specific Dependencies

For GAFF/GAFF2 Support:

For OpenFF Support:

For CGenFF Support:

For OPLS-AA Support:

For SwissParam Support (MMFF/MATCH/Hybrid):

Installing PRISM

Documentation

Quick Start

Basic Usage

Running MD Simulations

Command-Line Parameters

Common Parameters and Shortcuts

Usage Examples with Shortcuts

Force Field Selection Guide

When to Use Each Force Field

Special Features

Protein Preparation

Protein Cleaning

Ion Handling Modes

Distance-Based Filtering

Crystallization Artifact Removal

GROMACS Compatibility

Protonation State Prediction (PROPKA)

Features

Requirements

Protonation Control

Configuration

Protein Preparation Configuration

Protonation Configuration

File Structure

Output Files

Troubleshooting

Common Issues

Getting Help

CADD-Agent: AI-Driven Drug Screening Pipeline

Pipeline

Prerequisites

One-Command Setup

Usage

Manual Setup (Alternative)

Citation

License

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