Bump version: 0.0.25 → 0.0.26

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.0.25
+current_version = 0.0.26
 commit = True
 tag = True
 

.github/workflows/ci.yml

@@ -24,7 +24,7 @@ jobs:
           platforms: linux/amd64
           load: true
           push: false
-          tags: ghcr.io/${{ github.repository }}:0.0.25, ghcr.io/${{ github.repository }}:latest
+          tags: ghcr.io/${{ github.repository }}:0.0.26, ghcr.io/${{ github.repository }}:latest
       - name: 'Install Nextflow'
         uses: stracquadaniolab/gh-action-setup-nextflow@v0.2.0
       - name: 'Testing Nextflow pipeline with test profile'
@@ -39,4 +39,4 @@ jobs:
           file: containers/Dockerfile
           platforms: linux/amd64
           push: true
-          tags: ghcr.io/${{ github.repository }}:0.0.25, ghcr.io/${{ github.repository }}:latest
+          tags: ghcr.io/${{ github.repository }}:0.0.26, ghcr.io/${{ github.repository }}:latest

bin/openmmMD.py

@@ -142,11 +142,11 @@ def md_nvt(simulation, csvname: str, totalsteps: int, reprate: int, pdbname, int
     simulation.context.setVelocitiesToTemperature(300*kelvin)
     simulation.reporters.append(app.PDBReporter(pdbname, reprate))
     simulation.reporters.append(app.StateDataReporter(stdout, reprate, step=True, potentialEnergy=True, temperature=True, volume=True))
-    prepdf = {'Step':[], 'Potential Energy (kJ/mole)':[], 'Temperature (K)':[], 'Box Volume (nm^3)':[]}
+    prepdf = {'Step':[], 'Potential Energy (kJ/mole)':[], 'Temperature (K)':[], 'Box Volume (nm^3)':[], 'Pressure (kPa)':[]}
     inidf = pd.DataFrame(prepdf)
     inidf.to_csv(csvname, index=False)
     simulation.reporters.append(app.StateDataReporter(csvname, reprate, step=True,
-        potentialEnergy=True, temperature=True, volume=True, append=True))
+        potentialEnergy=True, temperature=True, volume=True, pressure=True, append=True))
     simulation.step(totalsteps)
     final_state = simulation.context.getState(getEnergy=True, getPositions=True)
     final_pe = final_state.getPotentialEnergy().value_in_unit(kilocalories_per_mole)
@@ -167,7 +167,7 @@ def md_nvt(simulation, csvname: str, totalsteps: int, reprate: int, pdbname, int
 
 def rmsf_analysis(pdb_traj: str, rmsfcsv: str):
     u = mda.Universe(pdb_traj)
-    u.trajectory.dt = 0.001
+    #u.trajectory.dt = 0.001
     average = align.AverageStructure(u, u, select='protein and name CA', ref_frame=0).run()
     ref = average.results.universe
     aligner = align.AlignTraj(u, ref, select='protein and name CA', in_memory=True).run()
@@ -177,6 +177,7 @@ def rmsf_analysis(pdb_traj: str, rmsfcsv: str):
     residue_names = [residue.resname for residue in c_alphas.residues]
     rmsf_values = R.rmsf
     df = pd.DataFrame({'Res_ID': residue_ids, 'Res_Name': residue_names, 'RMSF': rmsf_values })
+    print(df)
     df.to_csv(rmsfcsv, index=False)
 
 def main():
@@ -199,6 +200,21 @@ def main():
         app.PDBFile.writeFile(sim_run[4], sim_run[5], open(wt_ref, "w"), keepIds=True)
         rmsfout = str("wt_rmsf" + strj + ".csv")
         rmsf_analysis(pdbname, rmsfout)
+        for mutant in new_rep_cleaned.splitlines():
+            mutpdb = create_mutants(wt_out, mutant, arguments['--chain'], arguments['--pH'])
+            modeller = setup_modeller(mutpdb)
+            mut_pdb = energy_minimization(modeller)
+            mut_out = str(mutant + "_minimised" + strj + ".pdb")
+            app.PDBFile.writeFile(mut_pdb[0], mut_pdb[1], open(mut_out, "w"), keepIds=True)
+            simulation = mut_pdb[3]
+            integrator = mut_pdb[4]
+            csvname = str(mutant + "_traj" + strj + ".csv")
+            pdbname = str(mutant + "_traj" + strj + ".pdb")
+            sim_run = md_nvt(simulation, csvname, 10000, 1000, pdbname, integrator)
+            mut_ref = str(mutant + "reference" + strj + ".pdb")
+            app.PDBFile.writeFile(sim_run[4], sim_run[5], open(mut_ref, "w"), keepIds=True)
+            rmsfout = str(mutant + "_rmsf" + strj + ".csv")
+            rmsf_analysis(pdbname, rmsfout)
 
 if __name__ == '__main__':
     arguments = docopt(__doc__, version='openmmMD.py')

conf/base.config

@@ -2,7 +2,7 @@
 manifest {
   name = 'quickmd-nf'
   description = 'A workflow to anperform molecular dynamics (MD) simulations and analysis of proteins in solution'
-  version = '0.0.25'
+  version = '0.0.26'
   homePage = 'https://github.com/stracquadaniolab/quickmd-nf.git'
   author = 'Josh David Littlefair'
   nextflowVersion = '>=20.07.1'
@@ -40,7 +40,7 @@ profiles {
         shifter.enabled        = false
         charliecloud.enabled   = false
 
-        process.container = "ghcr.io/stracquadaniolab/quickmd-nf:0.0.25"
+        process.container = "ghcr.io/stracquadaniolab/quickmd-nf:0.0.26"
     }
 
     singularity {
@@ -51,7 +51,7 @@ profiles {
         shifter.enabled        = false
         charliecloud.enabled   = false
 
-        process.container = "docker://ghcr.io/stracquadaniolab/quickmd-nf:0.0.25"
+        process.container = "docker://ghcr.io/stracquadaniolab/quickmd-nf:0.0.26"
     }
 
     slurm {

containers/Dockerfile

@@ -22,7 +22,7 @@ LABEL org.opencontainers.image.documentation="https://github.com/stracquadaniola
 LABEL org.opencontainers.image.source="https://github.com/stracquadaniolab/quickmd-nf"
 LABEL org.opencontainers.image.vendor="stracquadaniolab"
 LABEL org.opencontainers.image.authors="Josh David Littlefair"
-LABEL org.opencontainers.image.revision="v0.0.25"
+LABEL org.opencontainers.image.revision="v0.0.26"
 
 COPY --chown=micromamba:micromamba ${CONDA_FILE} /tmp
 RUN micromamba install -y -n base -f /tmp/`basename ${CONDA_FILE}` && \

readme.md

@@ -1,6 +1,6 @@
 # quickmd-nf
 
-![](https://img.shields.io/badge/current_version-0.0.25-blue)
+![](https://img.shields.io/badge/current_version-0.0.26-blue)
 ![](https://github.com/stracquadaniolab/quickmd-nf/workflows/build/badge.svg)
 ## Overview
 A workflow to anperform molecular dynamics (MD) simulations and analysis of proteins in solution