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charmm force field develeopment based on Monte Carlo simulation
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charmm-mcsa/README.md

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Here's a README file based on the provided code:
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```
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# Monte Carlo Reweight Dihedral Force Constant
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This Python script implements Monte Carlo reweighting of dihedral force constants, primarily for molecular dynamics simulations. The code has been updated for Python 3 compatibility and improved practices.
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## Usage
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1. **Run the Script**: Execute the script using Python 3 with the required command-line arguments.
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```bash
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python3 monte_carlo_reweight.py <run> <thread> <jobid> <f>
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```
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- `<run>`: Integer representing the run number.
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- `<thread>`: Number of threads to use for parallel execution.
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- `<jobid>`: Integer representing the job ID.
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- `<f>`: String representing the filename.
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2. **Input Files**: Ensure the necessary input files are available, including parameters (`parm.parm`), QM data (`<f>.qm`), and CHARMM scripts (`charmm.<jobid>.sh`).
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3. **Output**: The script generates parameter files with optimized parameters (`optimized.<f>.<run>.str`) and intermediate parameter files during each iteration of the Monte Carlo simulation.
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## Dependencies
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- Python 3
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- `mcsa_module` (Assumed to be updated for Python 3 compatibility)
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- CHARMM (for molecular dynamics simulations)
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## Details
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- The script performs Monte Carlo simulations to optimize dihedral force constants based on a target function, using NMR data.
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- It utilizes multi-threading to speed up the optimization process.
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- Intermediate parameter files (`tmp.<jobid>.<f>.<run>.<thread>.<istep>.str`) are generated for each iteration of the simulation.
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- The best parameter set (`optimized.<f>.<run>.str`) is saved with the lowest RMSE value.
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- Execution time is displayed at the end of the script.
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## License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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```
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This README provides information on how to use the script, its dependencies, details about the implementation, and licensing information. Feel free to adjust or expand it further based on your needs.

reweight-trj-helix/README.md

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Sure, here's a simple README file based on the provided code:
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```
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# Monte Carlo Reweight Dihedral Force Constant
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This Python script performs Monte Carlo reweighting of dihedral force constants using RMSD with NMR J-coupling as a target function. It is designed to optimize parameters in molecular dynamics simulations.
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## Usage
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1. **Run the Script**: Execute the script using Python (version 2 or 3) with appropriate command-line arguments.
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```bash
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python monte_carlo_reweight.py
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```
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2. **Input Files**: The script requires input files containing information about dihedral angles, parameters, NMR data, and phi/psi angles. These files should be provided interactively during script execution.
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3. **Parameters**: Set the number of Monte Carlo steps (`nstep`) and the temperature (`tempr0`) in the script file.
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4. **Output**: The script generates parameter files (`reweight.<run>.str`) and energy files (`reweight.<run>.ene`) in the specified directory.
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## Dependencies
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- Python 2 or 3
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- Standard Python libraries (math, random, string, sys, copy)
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## License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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```
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This README provides a brief overview of the script, instructions on usage, dependencies, and licensing information. Feel free to expand or customize it further based on your needs.

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