Browse the lessons
The lessons that have been submitted to the PLUMED-TUTORIALS are listed below. PLUMED-TUTORIALS monitors whether PLUMED input files in these lessons are compatible with the current and development versions of the code and integrates links from these files to the PLUMED manual. Inputs in the tutorials listed below were last tested on .
Suggestions for an order to work through the tutorials can be found here. A complete bibliography of papers connected to these lessons can be found here.
ID | Name | Instructors | Description | Tags | Actions | Modules |
---|---|---|---|---|---|---|
23.001 | Developments in PLUMED | Gareth Tribello | A series of articles were I outline some development work that I have been doing with PLUMED over the last few years | Q6 POSITION PRINT AVERAGE DUMPGRID ONES DISTANCE_MATRIX CONCATENATE RDF CLUSTER_PROPERTIES DISTANCE ACCUMULATE GROUP RESTRAINT COORDINATIONNUMBER WHOLEMOLECULES MORE_THAN PDB2CONSTANT VSTACK LESS_THAN TORSION BIASVALUE PAIRENTROPY VOLUME CONTACT_MATRIX FIXEDATOM PATH MATRIX_VECTOR_PRODUCT PCAVARS KDE TRANSPOSE RMSD_VECTOR CONSTANT Q1 GET_VOLUME_ELEMENT EUCLIDEAN_DISTANCE INSPHERE LOCAL_AVERAGE CENTER LOCAL_Q1 DIFFERENCE REFERENCE_GRID DISPLACEMENT GPATH MATRIX_PRODUCT COM CLUSTER_WEIGHTS GEOMETRIC_PATH HISTOGRAM MEAN DFSCLUSTERING DIAGONALIZE DISTANCES COMBINE SUM LOWEST OUTER_PRODUCT CUSTOM SORT GSYMFUNC_THREEBODY SELECT_COMPONENTS RMSD DOMAIN_DECOMPOSITION GATHER_REPLICAS SPHERICAL_HARMONIC INTEGRATE_GRID INTERPOLATE_GRID Q4 SPRINT | mapping core vatom adjmat refdist volumes multicolvar function colvar generic bias symfunc valtools matrixtools sprint gridtools clusters | |
25.002 | Refining AlphaFold models for virtual screening | Samiran Sen | A tutorial to use bAIes to refine AlphaFold models for small-molecule virtual screening | PRINT BAIES BIASVALUE GROUP | core generic isdb bias | |
24.014 | Alpha-Fold Metainference for structural ensemble prediction of a partially disordered protein | Faidon Brotzakis, Hussein Murtada and Michele Vendruscolo | A tutorial about how metainference can be used in tandem with Alpha-fold to predict the ensemble of structures for a partially disordered protein. | Protein dynamics, AlphaFold2, Metainference, PB-MetaD, CALVADOS2, partially disordered proteins | PBMETAD RMSD ENDPLUMED GYRATION WHOLEMOLECULES FLUSH PRINT MOLINFO CENTER UPPER_WALLS METAINFERENCE CONTACTMAP CONSTANT TORSION | bias colvar vatom generic isdb |
24.013 | Permutationally Invariant Networks for Enhanced Sampling (PINES) | Nicholas S.M. Herringer, Aniruddha Seal, Armin Shayesteh Zadeh, Siva Dasetty, Andrew L. Ferguson | An introduction to using permutationally invariant networks for enhanced sampling | Metadynamics, Permutationally invariant vectors, machine learning collective variable, parallel bias metadynamics | ||
24.012 | Exploring Free Energy Surfaces with MACE-PLUMED Metadynamics | S.G.H. Brookes, C. Schran, A. Michaelides | Performing metadynamics simulations with LAMMPS, MACE and PLUMED | metadynamics, machine learning | PRINT UNITS | setup generic |
24.006 | Standard binding free energies from cylindrical restraints | Blake I Armstrong, Paolo Raiteri and Julian D Gale | Calculating standard binding free energies with metadynamics, PLUMED and OpenMM | metadynamics, surface binding, cylindrical restraint, standard state, volume correction, multiple-walkers | METAD FLUSH PRINT FIXEDATOM UNITS DISTANCE LOWER_WALLS CUSTOM UPPER_WALLS BIASVALUE RESTART | bias setup colvar vatom generic function |
23.003 | Profiling, GPUs and PLUMED | Ketan Bhardwaj | A report based on some profiling work on PLUMED that has been performed by the SSEC | developers, C++, profiling | ||
23.002 | Introduction to the PLUMED parallel features for developers | Daniele Rapetti | A simple presentation of some of the available features in PLUMED to simplify the interface with OpenMP and MPI. The lesson contains also a very simple example of how to implement a CV with CUDA. | developers, C++, parallelism | ||
22.015 | Mechanical pulling + FISST module | Guillaume Stirnemann and Glen Hocky | This tutorial explains how mechanical forces can be modeled using PLUMED and the FISST module | masterclass-2022 | DUMPATOMS METAD FISST RESTRAINT PRINT UNITS MATHEVAL DISTANCE BIASVALUE | bias fisst setup colvar generic function |
22.012 | Free energy calculations in crystalline solids | Pablo Piaggi | An introduction to the Environmental similarity CV and the calculation of chemical potentials of liquids and solids | masterclass-2022 | ENVIRONMENTSIMILARITY Q6 HISTOGRAM SUM ONES OPES_METAD MATHEVAL LOWER_WALLS DUMPGRID CUSTOM MORE_THAN UPPER_WALLS MATRIX_VECTOR_PRODUCT DISTANCE_MATRIX MEAN GROUP | envsim bias core opes matrixtools adjmat gridtools symfunc generic function |
22.009 | Using path collective variables to find reaction mechanisms in complex free energy landscapes | Bernd Ensing | An introduction to using path collective variables for describing and simulating activated molecular processes | masterclass-2022 | METAD PRINT UNITS DISTANCE LOWER_WALLS UPPER_WALLS | colvar setup generic bias |
22.008 | Modelling Concentration-driven processes with PLUMED | Matteo Salvalaglio | An introduction to the tools that are available in PLUMED for simulating concentration-driven processes such as nucleation, growth and diffusion. | masterclass-2022 | DFSCLUSTERING FLUSH SUM PRINT RESTRAINT CLUSTER_DISTRIBUTION CLUSTER_NATOMS COORDINATIONNUMBER GROUP MORE_THAN CONTACT_MATRIX MATRIX_VECTOR_PRODUCT ONES | bias core adjmat matrixtools symfunc clusters generic function |
22.007 | Learning and enhancing fluctuations along information bottleneck for automated enhanced sampling | Pratyush Tiwary | An introduction to the state predictive information bottleneck (SPIB) deep-learning-based framework for learning reaction coordinates from high dimensional molecular simulation trajectories. | masterclass-2022 | ||
22.003 | Rethinking Metadynamics using the OPES method | Michele Invernizzi | An introduction to the On-the-fly Probability Enhanced Sampling method | masterclass-2022 | OPES_METAD ECV_MULTITHERMAL ENERGY ECV_UMBRELLAS_LINE OPES_EXPANDED OPES_METAD_EXPLORE TORSION | colvar opes |
21.005 | Replica exchange methods | Giovanni Bussi | Running umbrella sampling with replica exchange, bias exchange metadynamics and parallel tempering metadynamics | masterclass-2021 | METAD RESTRAINT PRINT RANDOM_EXCHANGES MOLINFO TORSION | colvar generic bias |
21.003 | Umbrella Sampling | Giovanni Bussi | How to calculate statistical averages and free energy surfaces using umbrella sampling | masterclass-2021 | CONVERT_TO_FES HISTOGRAM PRINT RESTRAINT MOLINFO DUMPGRID CUSTOM READ BIASVALUE REWEIGHT_BIAS TORSION | bias gridtools colvar generic function |
21.002 | Statistical errors in MD | Gareth Tribello | How to calculate errors on averages calculated from unbiased and biased MD simulations using the method of block averages. | masterclass-2021 | HISTOGRAM CONVERT_TO_FES METAD COM PRINT RESTRAINT UNITS DISTANCE COORDINATIONNUMBER DUMPGRID CUSTOM CONSTANT UPPER_WALLS READ AVERAGE REWEIGHT_BIAS | bias setup gridtools symfunc colvar vatom generic function |
25.003 | Defining custom machine learning CV with metatomic | Guillaume Fraux, Rohit Goswami and Michele Ceriotti | An introduction to the use of interface between plumed and the metatomic library | SELECT_COMPONENTS METAD METATOMIC | bias metatomic valtools | |
25.001 | VisMetaDynamics | Christian Phillips | A graphical tool that allows you to visually inspect how the free energy surface for a metadynamics simulation is affected by the choice of hyperparameters | |||
24.019 | ASE-PLUMED interface | Daniel Sucerquia, Pilar Cossio, Olga Lopez-Acevedo | Using PLUMED from ASE | atomistic calculations, ab-initio, molecular dynamics | GROUP COM FLUSH UPPER_WALLS ONES CUSTOM METAD PRINT MATRIX_VECTOR_PRODUCT UNITS COMBINE COORDINATIONNUMBER DISTANCE COORDINATION MEAN CONTACT_MATRIX LOWER_WALLS GYRATION | symfunc setup colvar function generic bias vatom matrixtools adjmat core |
24.017 | Enhanced sampling for magnesium-RNA binding dynamics | Olivier Languin Cattoen | This tutorial will teach you how to use PLUMED, GROMACS and Python notebooks to implement an enhanced sampling strategy for magnesium-RNA binding dynamics. | CASP, RNA, Magnesium | GROUP UPPER_WALLS CUSTOM METAD PRINT COORDINATION DISTANCES LOWER_WALLS BIASVALUE | colvar function generic bias multicolvar core |
24.016 | Host-Guest binding free energies using an automated OneOPES protocol | Pedro Febrer Martinez, Valerio Rizzi, Simone Aureli, Francesco Luigi Gervasio | A tutorial on an automated OneOPES protocol for calculating host-guest binding free energies | OneOPES, ligand binding, binding free energy, SAMPL challenge, host-guest | GROUP ECV_MULTITHERMAL UPPER_WALLS OPES_METAD_EXPLORE WHOLEMOLECULES ANGLE PRINT ENERGY DISTANCE FIT_TO_TEMPLATE COORDINATION OPES_EXPANDED LOWER_WALLS CENTER MATHEVAL FIXEDATOM | colvar function opes generic bias vatom core |
24.015 | How to use the PLUMED PyCV plugin | Daniele Rapetti, Toni Giorgino | An introduction to the pycv module. This module provides you with an action that allows you to call python from PLUMED. | manual, python | DISTANCE PRINT LOAD | setup colvar generic |
24.011 | Parameterization of Path CVs for drug-target binding | Mattia Bernetti and Matteo Masetti | Using path CVs to study drug target binding with metadynamics | drug-target binding, Path CVs, metadynamics | MOVINGRESTRAINT UPPER_WALLS METAD WHOLEMOLECULES PRINT PATHMSD MOLINFO DISTANCE LOWER_WALLS CENTER | colvar generic bias vatom |
24.009 | Multiple Walkers Metadynamics Simulations with a Reactive Machine Learning Interatomic Potential | Kam-Tung Chan and Davide Donadio | Running metadynamics with a reactive, machine-learning interaction potential | metadynamics, nitrate anion, machine learning interatomic potential | GROUP FLUSH UPPER_WALLS CUSTOM METAD ANGLE PRINT UNITS DISTANCE READ DUMPGRID COORDINATION REWEIGHT_METAD HBOND_MATRIX HISTOGRAM | gridtools setup colvar function generic bias adjmat core |
24.004 | Volume-based Metadynamics | Riccardo Capelli | This tutorial teaches you how to run free energy calculations to investigate protein-ligand binding | Metadynamics, protein-ligand binding, free energy calculations | COM PRINT WRAPAROUND RESTRAINT HISTOGRAM GROUP FLUSH UPPER_WALLS WHOLEMOLECULES FIT_TO_TEMPLATE CONVERT_TO_FES REWEIGHT_BIAS DUMPGRID MATHEVAL ONES CUSTOM READ POSITION RMSD METAD KDE COORDINATION ACCUMULATE | gridtools colvar function generic bias vatom core |
24.002 | Trans-Cis isomerization in the ground and excited states using PLUMED | Adriana Pietropaolo | A guide to perform ground and excited state simulations using PLUMED to simulate a trans to cis isomerization process. | TORSION WHOLEMOLECULES PRINT PBMETAD CONSTANT MATHEVAL BIASVALUE | colvar function generic bias | |
23.004 | Rewriting coordination CVs in CUDA | Daniele Rapetti | How to implement a basic version of the coordination CV with CUDA | developers, C++, parallelism, Cuda | ||
22.010 | Hamiltonian replica exchange with PLUMED and GROMACS | Giovanni Bussi | An introduction to running Hamiltonian replica exchange calculations using PLUMED and GROMACS. | masterclass-2022 | TORSION MOLINFO PRINT | colvar generic |
22.006 | EDS module and Coarse-Grained directed simulations | Glen Hocky and Andrew White | This tutorials describes how to bias simulations to agree with experimental data using experiment directed simulation. | masterclass-2022 | EDS TORSION PRINT MOLINFO DISTANCE MATHEVAL BIASVALUE | colvar function generic bias eds |
22.002 | Analysis of PLUMED output by Metadynminer | Vojtech Spiwok | An introduction to the R package Metadynminer which can be used to analyse the output from metadynamics simulations | masterclass-2022 | ||
22.001 | Funnel Metadynamics | Stefano Raniolo and Vittorio Limongelli | An introduction to modelling ligand binding using funnel metadynamics | masterclass-2022 Funnel Metadynamics ligand/target binding | ||
21.006 | Dimensionality reduction | Gareth Tribello | An introduction to techniques such as dimensionality reduction, path collective variables, and indistinguishability that you may need to use in your own research projects. | masterclass-2021 | TORSION PRINT MORE_THAN SKETCHMAP HISTOGRAM PROJECT_POINTS PARABETARMSD GROUP ANTIBETARMSD PCAVARS FCCUBIC CLASSICAL_MDS ALPHARMSD DUMPGRID PATH PCA COMMITTOR MOLINFO COORDINATIONNUMBER DUMPVECTOR RMSD DUMPMULTICOLVAR UNITS COLLECT_FRAMES LANDMARK_SELECT_FPS DUMPPDB | gridtools dimred mapping symfunc setup colvar function generic secondarystructure multicolvar landmarks core |
21.004 | Metadynamics | Max Bonomi | How to calculate statistical averages and free energy surfaces using metadynamics | masterclass-2021 | TORSION METAD PRINT MOLINFO HISTOGRAM DUMPGRID CONVERT_TO_FES REWEIGHT_BIAS | gridtools colvar generic bias |
24.021 | Setting Up and Analyzing Bias-Exchange Metadynamics Simulations | Fabrizio Marinelli and Vanessa Ariadna Leone Alvarez | This tutorial offers a comprehensive protocol, complemented by practical examples, for setting up and performing free energy analysis of bias-exchange metadynamics simulations of cis-trans isomerization in a proline-containing peptide. | molecular dynamics, metadynamics, bias exchange metadynamics, weighted histogram analysis method, mean forces, cis-trans isomerization, peptidyl-prolyl peptide | DUMPFORCES INCLUDE TORSION METAD RANDOM_EXCHANGES PRINT | generic colvar bias |
24.020 | An introduction to CpH-Metadynamics simulations | Tomas Silva | This tutorial aims to train users to perform CpH-Metadynamics simulations using the stochastic titration constant-pH Molecular Dynamics method and PLUMED. | RNA, Constant pH | ||
24.018 | Permutation Invariant Vector and Water Crystallisation | Silvio Pipolo, Fabio Pietrucci | Modelling water crystallisation using PIV variables | PIV, PathCV, Water Crystallisation | FUNCPATHMSD LOWER_WALLS CELL PIV METAD UPPER_WALLS PRINT | function generic colvar bias piv |
24.010 | Modelling mechanobiological processes | Claire Pritchard, Guillaume Stirnemann and Glen Hocky | A tutorial on modelling mechanobiological processes | Metadynamics, pulling, force, rates, GPCR | MATHEVAL DISTANCE COMMITTOR BIASVALUE COM UNITS DUMPATOMS RESTRAINT METAD PRINT | function vatom generic setup colvar bias |
24.008 | Using the maze module | Jakub Rydzewski | Sampling ligand-protein dissociation using the maze module | protein, ligand, dissociation, unbinding, maze | CENTER DISTANCE COMMITTOR GROUP | generic colvar vatom core |
24.007 | Transition-Tempered Metadynamics | Jiangbo Wu and Gregory A. Voth | An introduction to the transition tempered metadynamics method | metadynamics, free energy sampling, reaction mechanism | RESTART EXTENDED_LAGRANGIAN COORDINATION FLUSH LOWER_WALLS DISTANCE UPPER_WALLS GROUP COM TORSION MOLINFO UNITS RESTRAINT METAD WHOLEMOLECULES PRINT | core vatom setup generic colvar bias |
24.005 | Path integral metadynamics | Guillaume Fraux and Michele Ceriotti | Incorporating nuclear quantum effects in metadynamics simulations using path integrals | Metadynamics, path integrals, nuclear quantum effects | COMBINE FLUSH DISTANCE LESS_THAN DISTANCES METAD SUM UPPER_WALLS PRINT | function generic multicolvar colvar bias |
24.003 | Benchmarking PLUMED | Daniele Rapetti | This tutorial shows you how to use the plumed benchmark tool to measure the performance of the code | developers, benchmark, manual | FLUSH COORDINATION PRINT | generic colvar |
24.001 | hybrid Small Angle Scattering — hands-on guide | Federico Ballabio | Practical guide to the use of the hySAS module. | ENSEMBLE GYRATION STATS BIASVALUE SAXS MOLINFO RESTRAINT PRINT | function generic isdb colvar bias | |
22.017 | A Bayesian approach to integrate cryo-EM data into MD simulations with PLUMED | Samuel Hoff and Max Bonomi | How to use PLUMED to perform single-structure and ensemble refinement using cryo-EM maps and EMMIVox. | masterclass-2022 | BIASVALUE GROUP MOLINFO EMMIVOX WHOLEMOLECULES PRINT | generic isdb bias core |
22.013 | SASA module - The solvent accessible surface area of proteins as a collective variable, and the application of PLUMED for implicit solvent simulations | Andrea Arsiccio | An introduction to the SASA module and a description of how PLUMED can be used for implicit solvent simulations. | masterclass-2022 | ANTIBETARMSD PARABETARMSD SASA_HASEL GYRATION DISTANCE BIASVALUE SECONDARY_STRUCTURE_DRMSD LESS_THAN ALPHARMSD MOLINFO LOWEST CUSTOM SUM PRINT | secondarystructure function sasa generic colvar bias |
22.011 | Variationally Enhanced Sampling | Omar Valsson | An introduction to running Variationally Enhanced Sampling (VES) using PLUMED. | masterclass-2022 Variationally Enhanced Sampling VES | VES_LINEAR_EXPANSION TD_UNIFORM COORDINATION READ OPT_AVERAGED_SGD DISTANCE CONVERT_TO_FES DUMPGRID TD_WELLTEMPERED HISTOGRAM REWEIGHT_BIAS BF_WAVELETS BF_LEGENDRE UPPER_WALLS PRINT | ves generic colvar bias gridtools |
22.005 | Machine learning collective variables with PyTorch | Luigi Bonati | An introduction to designing data-driven CVs using two methods (DeepLDA and DeepTICA). | masterclass-2022 | PRINT TORSION PYTORCH_MODEL | generic colvar pytorch |
21.007 | Optimizing PLUMED performances | Max Bonomi | Some lessons on monitoring and improving the performance of PLUMED and gromacs | masterclass-2021 | COMBINE COORDINATION EFFECTIVE_ENERGY_DRIFT DISTANCE DEBUG GROUP METAD CUSTOM RMSD WHOLEMOLECULES PRINT | core function generic colvar bias |
21.001 | PLUMED syntax and analysis | Max Bonomi | Basic features of the PLUMED input syntax with a particular focus on PBCs and selection tools | masterclass-2021 | COMBINE ANTIBETARMSD PARABETARMSD ALPHARMSD GYRATION DISTANCE CENTER TORSION MOLINFO DUMPATOMS WHOLEMOLECULES PRINT | secondarystructure function vatom generic colvar |
20.001 | Installing PLUMED | Gareth Tribello | An interactive tutorial resource on compiling PLUMED and linking it with MD codes. |