Metadata-Version: 2.1
Name: ommtk
Version: 0.1.2
Summary: OpenMM Toolkit by Redesign Science
Home-page: https://github.com/RedesignScience/RSSimTools
Author: Gavin Bascom, Haotian Li, Janan Zhu
Author-email: gavin@redesignscience.com
License: UNKNOWN
Description: # OMMTK
        ## OpenMM Wrappers for General and Enhanced MDSimulations
        
        This repo contains several simulation classes wrapped around openMM infrastructure that allow for rapid devlopment and usage of various MD Simulations.
        
        Currently Supported are the following simulations: Minimization, Standard MD (base class); Heating and Equil MD simulations (NVT and NPT respectively), Gentle Heat Sims (heat/release restraints over a range of stages), simulated tempering, metadynamics and metadynamics with focused sampling on ligand unbinding (Segment Walker Sims). The simulations support a full API with a range of functions and easily adapted run statements for specialized protocols.  
        
        # Installation
        
        Dependencies:
        
        OMMTK requires very few dependencies. Below is a list you can install with conda or pip:
        
            python 3.6 or higher
            simtk.openmm
            numpy
            mdtraj
            
        To install the latest stable version we recommend using pip with the following command (this is the only method guaranteed to provide a stable version).
        
            pip install ommtk
          
        # Documentation
        
        The most recent documentation: https://redesignscience.github.io/OMMTK/
        
        ## Quickstart run
        
                # Load packages
                import parmed
                from ommtk import MDSimulation, select_atoms, unit
                
                # Note: Requires parameterized parmed in memory named parmed_structure!
        
                #instantiate sim from parmed alone, minimize (save h5 file) and run
                mdsim = MDSimulation(parmed_structure=parmed_structure)
                mdsim.minimize()
                minimized_parmed = mdsim.run(2 * unit.nanosecond)
        
                #build sim using a previous trajectory or h5 file
                mdsim = MDSimulation(parmed_structure=parmed_structure, coordinates=trajectory.h5)
        
                #build sim with positional restraints, run some equilibration and remove them for longer run
                protein_atoms = select_atoms(parmed_structure=parmed_structure, keyword_selection='protein')
                mdsim = MDSimulation(parmed_structure=parmed_structure, atoms_to_restrain=protein_atoms, restraint_weight=4)
                mdsim.run(1*unit.nanosecond)
                mdsim.update_restraint_weight(2)
                mdsim.run(1*unit.nanosecond)
                mdsim.remove_positional_restraints()
                end_parmed = mdsim.run(4 * unit.nanosecond)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
