plumed-us

Run umbrella sampling workflows with PLUMED and GROMACS, including WHAM reweighting and free-energy surface construction.

1|1|Updated Apr 16, 2026
One-click install
npx skills add https://github.com/BioKT/Skills-BIOKT --skill plumed-us
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: plumed-us
Source: https://github.com/BioKT/Skills-BIOKT/tree/main/plumed-us
Command: npx skills add https://github.com/BioKT/Skills-BIOKT --skill plumed-us

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Umbrella sampling uses a series of harmonic restraint potentials (windows) to force the system to sample different regions along a reaction coordinate. The unbiased free energy is recovered by combining all windows via WHAM.

Core Features & Use Cases

  • Generate per-window PLUMED inputs to drive multi-window sampling and WHAM-based reweighting.
  • Run serial or MPI/REMD umbrella sampling across windows, then concatenate trajectories and compute WHAM weights to obtain reweighted free-energy surfaces.
  • Validate convergence with bootstrap-style error analysis and initial-condition checks; support for RMSD, distance, torsion, and other CVs with PLUMED.

Quick Start

Define the collective variable and its range, generate the plumed window inputs, and run the umbrella sampling workflow to obtain WHAM-reweighted FES.

Frequently Asked Questions about plumed-us

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run umbrella sampling with PLUMED and GROMACS to get a free energy surface?

Umbrella sampling with PLUMED and GROMACS is performed by defining a collective variable, generating per-window restraint inputs, running multi-window simulations, and combining the results via WHAM to construct the reweighted free energy surface.

What collective variables can I use for PLUMED umbrella sampling when calculating free energy?

Collective variables for PLUMED umbrella sampling include distances, torsions, and RMSD. You define these CVs across a specified range to generate window inputs that drive the sampling and subsequent WHAM-based reweighting.

How do I calculate WHAM weights and perform reweighting for molecular simulations?

WHAM weights for molecular simulations are calculated by concatenating trajectories from per-window runs. The umbrella sampling workflow computes these weights to reweight the biased data and recover the unbiased free energy surface.

Can I use MPI or REMD for multi-window umbrella sampling across replicas?

Yes, the umbrella sampling workflow supports serial and MPI or REMD execution across windows. It also includes optional replicas support to run multi-window simulations and concatenate trajectories for WHAM analysis.

How do I validate umbrella sampling convergence and check initial conditions?

Umbrella sampling convergence is validated using bootstrap-style error analysis alongside initial-condition checks. These steps ensure the WHAM-reweighted free energy surface is statistically reliable before finalizing the results.

Why do I need harmonic restraint potentials for protein dynamics free energy calculations?

Harmonic restraint potentials are needed for protein dynamics free energy calculations to force the system to sample different regions along a reaction coordinate. WHAM then combines these restrained windows to recover the unbiased free energy.