diff --git a/user-doc/tutorials/others/isdb-1.txt b/user-doc/tutorials/others/isdb-1.txt
index afec09ab22ac7ab6873fcf1763979ba8b82d9bf2..2d202ea623a5940b1e8781f0bd2afcc317137c03 100644
--- a/user-doc/tutorials/others/isdb-1.txt
+++ b/user-doc/tutorials/others/isdb-1.txt
@@ -60,17 +60,6 @@ gmx_mpi mdrun -s run.tpr -table table.xvg -tablep table.xvg -plumed plumed-eef1.
In order to have a converged sampling for this reference ensemble calculation it is usefull to setup a Metadynamics calculation. In particular we will use \ref PBMETAD because it is then a natural choice for Metadynamic Metainference later.
\plumedfile
-# this is optional and tell to VIM that this is a PLUMED file
-# vim: ft=plumed
-# see comments just below this input file
-MOLINFO MOLTYPE=protein STRUCTURE=egaawaass.pdb
-WHOLEMOLECULES ENTITY0=1-111
-
-# EEF1SB Implicit solvation
-protein-h: GROUP NDX_FILE=index.ndx NDX_GROUP=Protein-H
-solv: IMPLICIT ATOMS=protein-h NOPBC NL_STRIDE=10 NL_BUFFER=0.1
-bias: BIASVALUE ARG=solv
-
# CVs, Psi9, Phi1 are not defined
psi1: TORSION ATOMS=@psi-1
psi2: TORSION ATOMS=@psi-2
@@ -121,74 +110,13 @@ PRINT FILE=ENERGY ARG=bias.bias,pb.bias STRIDE=200
ENDPLUMED
\endplumedfile
-In this case we are already running a multiple-replica simulation where the sampling is used to parallelise the Metadynamics time-dependent potential through the use of multiple walkers.
+In this case we arerunning a multiple-replica simulation where the sampling is used to parallelise the Metadynamics time-dependent potential through the use of multiple walkers.
\verbatim
mpiexec -np 14 gmx_mpi mdrun -s topolnew -multi 14 -plumed plumed-eef1-pbmetad.dat -table table.xvg -tablep table.xvg >& log.out &
\endverbatim
\plumedfile
-# this is optional and tell to VIM that this is a PLUMED file
-# vim: ft=plumed
-# see comments just below this input file
-MOLINFO MOLTYPE=protein STRUCTURE=egaawaass.pdb
-WHOLEMOLECULES ENTITY0=1-111
-
-# EEF1SB Implicit solvation
-protein-h: GROUP NDX_FILE=index.ndx NDX_GROUP=Protein-H
-solv: IMPLICIT ATOMS=protein-h NOPBC NL_STRIDE=10 NL_BUFFER=0.1
-bias: BIASVALUE ARG=solv
-
-# CVs, Psi9, Phi1 are not defined
-psi1: TORSION ATOMS=@psi-1
-psi2: TORSION ATOMS=@psi-2
-psi3: TORSION ATOMS=@psi-3
-psi4: TORSION ATOMS=@psi-4
-psi5: TORSION ATOMS=@psi-5
-psi6: TORSION ATOMS=@psi-6
-psi7: TORSION ATOMS=@psi-7
-psi8: TORSION ATOMS=@psi-8
-
-phi2: TORSION ATOMS=@phi-2
-phi3: TORSION ATOMS=@phi-3
-phi4: TORSION ATOMS=@phi-4
-phi5: TORSION ATOMS=@phi-5
-phi6: TORSION ATOMS=@phi-6
-phi7: TORSION ATOMS=@phi-7
-phi8: TORSION ATOMS=@phi-8
-phi9: TORSION ATOMS=@phi-9
-
-ahc: ALPHARMSD RESIDUES=all TYPE=OPTIMAL LESS_THAN={RATIONAL R_0=0.12}
-
-# Bulky Trp residue dihedral
-dihtrp_cacb: TORSION ATOMS=67,47,49,52
-dihtrp_cbcg: TORSION ATOMS=47,49,52,53
-
-protein-ca: GROUP NDX_FILE=index.ndx NDX_GROUP=C-alpha
-gyr: GYRATION TYPE=RADIUS ATOMS=protein-ca NOPBC
-
-# PBMetaD
-PBMETAD ...
- LABEL=pb
- ARG=phi2,phi3,phi4,phi5,phi6,phi7,phi8,phi9,psi1,psi2,psi3,psi4,psi5,psi6,psi7,psi8,dihtrp_cacb,dihtrp_cbcg,ahc.lessthan
- SIGMA=1000
- SIGMA_MIN=0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.06,0.001
- SIGMA_MAX=0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.6,0.2
- ADAPTIVE=DIFF
- HEIGHT=0.5
- PACE=200
- BIASFACTOR=40
- GRID_MIN=-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,-pi,0
- GRID_MAX=pi,pi,pi,pi,pi,pi,pi,pi,pi,pi,pi,pi,pi,pi,pi,pi,pi,pi,5
- GRID_WSTRIDE=5000
- WALKERS_MPI
-... PBMETAD
-
-# output from the collective variable
-PRINT FILE=COLVAR ARG=phi2,phi3,phi4,phi5,phi6,phi7,phi8,phi9,psi1,psi2,psi3,psi4,psi5,psi6,psi7,psi8,dihtrp_cacb,dihtrp_cbcg,ahc.lessthan STRIDE=200
-# output from PBMETAD and BIASVALUE
-PRINT FILE=ENERGY ARG=bias.bias,pb.bias STRIDE=200
-
# EXPERIMENTAL DATA SECTION
# RDCs (Grzesiek et al.)
@@ -264,7 +192,7 @@ JCOUPLING ...
ATOMS1=47,49,52,53 COUPLING1=1.21
LABEL=jncg
... JCOUPLING
-#
+
# Chemical shifts
cs: CS2BACKBONE ATOMS=1-111 NRES=9 DATA=data TEMPLATE=egaawaass.pdb
@@ -317,14 +245,15 @@ PRINT ARG=cahast.* STRIDE=2000 FILE=ST.RDC.CAHA
PRINT ARG=csst.* STRIDE=2000 FILE=ST.CS
PRINT ARG=jhanst.*,jhahnst.*,jw5ccyst.*,jw5ncyst.* STRIDE=2000 FILE=ST.J
-
# metainference entries
METAINFERENCE ...
ARG=(nh\.rdc_.*),pb.bias
PARARG=(nh\.exp_.*)
- NOISETYPE=MGAUSS SCALEDATA REWEIGHT OPTSIGMAMEAN=SEM AVERAGING=200
- SCALE_PRIOR=GAUSSIAN SCALE0=8.0 DSCALE=0.5
+ REWEIGHT
+ NOISETYPE=MGAUSS
+ OPTSIGMAMEAN=SEM AVERAGING=200
+ SCALEDATA SCALE_PRIOR=GAUSSIAN SCALE0=8.0 DSCALE=0.5
SIGMA0=5.0 SIGMA_MIN=0.0001 SIGMA_MAX=15.0 DSIGMA=0.1
WRITE_STRIDE=10000
LABEL=byrdcnh
@@ -333,8 +262,10 @@ METAINFERENCE ...
METAINFERENCE ...
ARG=(caha\.rdc_.*),pb.bias
PARARG=(caha\.exp_.*)
- NOISETYPE=MGAUSS SCALEDATA REWEIGHT OPTSIGMAMEAN=SEM AVERAGING=200
- SCALE_PRIOR=GAUSSIAN SCALE0=9.0 DSCALE=0.5
+ REWEIGHT
+ NOISETYPE=MGAUSS
+ OPTSIGMAMEAN=SEM AVERAGING=200
+ SCALEDATA SCALE_PRIOR=GAUSSIAN SCALE0=9.0 DSCALE=0.5
SIGMA0=5.0 SIGMA_MIN=0.0001 SIGMA_MAX=15.0 DSIGMA=0.1
WRITE_STRIDE=10000
LABEL=byrdccaha
@@ -343,7 +274,9 @@ METAINFERENCE ...
METAINFERENCE ...
ARG=(jhan\.j_.*),(jhahn\.j_.*),(jccg\.j.*),(jncg\.j.*),pb.bias
PARARG=(jhan\.exp_.*),(jhahn\.exp_.*),(jccg\.exp.*),(jncg\.exp.*)
- NOISETYPE=MGAUSS REWEIGHT OPTSIGMAMEAN=SEM AVERAGING=200
+ REWEIGHT
+ NOISETYPE=MGAUSS
+ OPTSIGMAMEAN=SEM AVERAGING=200
SIGMA0=5.0 SIGMA_MIN=0.0001 SIGMA_MAX=15.0 DSIGMA=0.1
WRITE_STRIDE=10000
LABEL=byj
@@ -352,7 +285,9 @@ METAINFERENCE ...
METAINFERENCE ...
ARG=(cs\.ca_.*),(cs\.cb_.*),pb.bias
PARARG=(cs\.expca.*),(cs\.expcb.*)
- NOISETYPE=MOUTLIERS REWEIGHT OPTSIGMAMEAN=SEM AVERAGING=200
+ REWEIGHT
+ NOISETYPE=MOUTLIERS
+ OPTSIGMAMEAN=SEM AVERAGING=200
SIGMA0=5.0 SIGMA_MIN=0.0001 SIGMA_MAX=15.0 DSIGMA=0.1
WRITE_STRIDE=10000
LABEL=bycs
@@ -369,6 +304,14 @@ PRINT ARG=bycs.* STRIDE=200 FILE=BAYES.CS
ENDPLUMED
\endplumedfile
+As for the former case we are running a multiple-replica simulation where in addition to multiple-walker metadynamics we are also coupling the replicas through Metainference. The use
+of multiple-walkers metadynamics is here key in order to have the same bias defined for all the replicas. This allows us to calculate a weighted average of the experimental observables
+where the weights are defined univocally from the bias \cite Bonomi:2016ge .
+
+\verbatim
+mpiexec -np 14 gmx_mpi mdrun -s topolnew -multi 14 -plumed plumed-eef1-pbmetad-m_m.dat -table table.xvg -tablep table.xvg >& log.out &
+\endverbatim
+
*/
link: @subpage isdb-1