Bound Protein-Ligand MD [MDPrep] [MDRun]¶
Purpose:
This Floe performs MD simulations given a prepared protein and a set of posed and prepared ligands.
Method Recommendations/Requirements:
The ligands need to have reasonable 3D coordinates, all atoms, and correct chemistry (in particular bond orders and formal charges).
Each ligand can have multiple conformers but each conformer will be run separately as a different ligand.
The starting poses should not have very high gradients, in particular no bad clashes with the protein.
The protein needs to be prepared to MD standards: protein chains must be capped, all atoms in protein residues (including hydrogens) must be present, and missing protein loops resolved or capped.
Crystallographic internal waters should be retained where possible.
Limitations
Currently this floe cannot handle covalent bonds between different components such as ligand, protein, and cofactors.
Glycosylation on proteins is truncated and the amino acid is capped with H.
Expertise Level:
Regular/Intermediate/Advanced
Compute Resource:
Depends on simulation length; Minimal resources for default 2 ns.
Keywords:
MD, MDPrep
Related Floes:
Short Trajectory MD with Analysis [MDPrep] [MD]
Ligand Bound and Unbound Equilibration for NES [MDPrep] [MD]
Given the inputs of the protein and posed ligands, the complex is formed with each ligand/conformer separately, and the complex is solvated and parametrized according to the selected force fields. A minimization stage is performed on the system followed by a warm up (NVT ensemble) and several equilibration stages (NPT ensemble). In the minimization, warm up, and equilibration stages, positional harmonic restraints are applied on the ligand and protein. At the end of the equilibration stages a production run (by default only 2 ns) is performed on the unrestrained system. The trajectory and final state are written out in the results record; no analysis is performed.
Promoted Parameters
flask_title (string) : Prefix name used to identify the Protein. If not specified, it will use the title of the input protein.Default: “” HMR (boolean) : On enables Hydrogen Mass Repartitioning. Not currently implemented in GromacsDefault: True md_engine (string) : Select the MD available engineDefault: OpenMMChoices: OpenMM, Gromacs cpu_count_md (integer) : The number of CPUs to run this cube withDefault: 16 Min: 1 Max: 128 gpu_count_md (integer) : The number of GPUs to run this cube withDefault: 1 Max: 16 spot_policy_md (string) : Control cube placement on spot market instancesDefault: AllowedChoices: Allowed, Preferred, NotPreferred, Prohibited, Required out (dataset_out) : MD Dataset out charge_ligands (boolean) : Assign ligand partial charges or notDefault: True protein (data_source) : Protein Dataset max_md_runs (integer) : The maximum allowed number of MD runsDefault: 500 n_md_starts (integer) : The number of MD starts for each ligand/conformerDefault: 1 protein_ff (string) : Force field parameters to be applied to the proteinDefault: Amber14SBChoices: Amber14SB, Amber99SB, Amber99SBildn, AmberFB15 ligand_ff (string) : Force field to be applied to the ligandDefault: OpenFF_2.0.0Choices: Gaff_1.81, Gaff_2.11, OpenFF_1.1.1, OpenFF_1.2.1, OpenFF_1.3.1, OpenFF_2.0.0, Smirnoff99Frosst prod_ns (decimal) : Length of MD run in nanosecondsDefault: 2.0 prod_trajectory_interval (decimal) : Trajectory saving interval in nanosecondsDefault: 0.004 fail (dataset_out) : MD Dataset Failures out ligands (data_source) : Ligand Dataset
Extra Required Parameters
Log Field (Field Type: String) : The field to store messages to floe reportDefault: Log Field Log Field (Field Type: String) : The field to store messages to floe reportDefault: Log Field Log Field (Field Type: String) : The field to store messages to floe reportDefault: Log Field