1. belfast 8 and 9

2. More residues in MOLINFO

src/tools/MolDataClass.cpp

@@ -55,7 +55,16 @@ bool MolDataClass::allowedResidue( const std::string& type, const std::string& r
       else if(residuename=="VAL") return true;     
 // Terminal groups
       else if(residuename=="ACE") return true;
-      else if(residuename=="NME") return true;   
+      else if(residuename=="NME") return true;
+// Alternative residue names in common force fiels   
+      else if(residuename=="GLH") return true; // neutral GLU
+      else if(residuename=="ASH") return true; // neutral ASP
+      else if(residuename=="HID") return true; // neutral HIS-D amber
+      else if(residuename=="HSD") return true; // neutral HIS-D charmm
+      else if(residuename=="HIE") return true; // neutral HIS-E amber
+      else if(residuename=="HSE") return true; // neutral HIS-E charmm
+      else if(residuename=="HIP") return true; // neutral HIS-P amber
+      else if(residuename=="HSP") return true; // neutral HIS-P charmm
       else return false; 
   } 
   return false;

user-doc/tutorials/belfast-8.txt

@@ -194,8 +194,10 @@ HILLS.#:
 \endverbatim
 
 The above notes hold for the HILLS files as well. In the folder metagui the script check_for_metagui.sh checks if the header of your file is compatible
-with METAGUI, but remember that this is not enough! Synchronisation of COLVAR and trajctory files is also needed. HILLS files can be written with a
-different frequency but times must be consistent.
+with METAGUI, but remember that this is not enough! Synchronisation of COLVAR and trajectory files is also needed. HILLS files can be written with a
+different frequency but times must be consistent. 
+
+NOTE: It is important to copy HILLS files in the metagui folder.
 
 \verbatim
 ./check_for_metagui.sh ../COLVAR.0
@@ -209,15 +211,15 @@ In the metagui folder there is a metagui.input file:
 WHAM_EXE 	wham_bemeta.x
 BASINS_EXE 	kinetic_basins.x
 KT 2.4900
-HILLS_FILE   ../HILLS.0  
-HILLS_FILE   ../HILLS.1  
-HILLS_FILE   ../HILLS.2  
-HILLS_FILE   ../HILLS.3  
+HILLS_FILE   HILLS.0  
+HILLS_FILE   HILLS.1  
+HILLS_FILE   HILLS.2  
+HILLS_FILE   HILLS.3  
 GRO_FILE     VIL.pdb 
-COLVAR_FILE ../COLVAR.0 ../traj0.xtc "psi-1"
-COLVAR_FILE ../COLVAR.1 ../traj1.xtc "phi-2"
-COLVAR_FILE ../COLVAR.2 ../traj2.xtc "psi-2"
-COLVAR_FILE ../COLVAR.3 ../traj3.xtc "phi-3"
+COLVAR_FILE COLVAR.0 ../traj0.xtc "psi-1"
+COLVAR_FILE COLVAR.1 ../traj1.xtc "phi-2"
+COLVAR_FILE COLVAR.2 ../traj2.xtc "psi-2"
+COLVAR_FILE COLVAR.3 ../traj3.xtc "phi-3"
 TRAJ_SKIP 10
 CVGRID 1  -3.1415 3.1415 15 PERIODIC
 CVGRID 2  -3.1415 3.1415 15 PERIODIC
@@ -246,7 +248,7 @@ in Extensions->Analysis.
 
 One or more microstates can be visualised by selecting them and clicking show.
 
-You can sort the microstate using the column name tabs, for example by clicking on size the microstates will be ordered from the larger
+You can sort the microstates using the column name tabs, for example by clicking on size the microstates will be ordered from the larger
 to the smaller. If you look at the largest one it is possible to observe that by using the four selected collective variables the backbone
 conformation of the peptide is well defined while the sidechains can populate different rotameric states.
 
@@ -331,6 +333,8 @@ More materials can be found in
 1. Marinelli, F., Pietrucci, F., Laio, A. & Piana, S. A kinetic model of trp-cage folding from multiple biased molecular dynamics simulations. PLoS Comput. Biol. 5, e1000452 (2009).
 2. Biarnés, X., Pietrucci, F., Marinelli, F. & Laio, A. METAGUI. A VMD interface for analyzing metadynamics and molecular dynamics simulations. Comput. Phys. Commun. 183, 203–211 (2012).
 3. Baftizadeh, F., Cossio, P., Pietrucci, F. & Laio, A. Protein folding and ligand-enzyme binding from bias-exchange metadynamics simulations. Current Physical Chemistry 2, 79–91 (2012).
+4. Granata, D., Camilloni, C., Vendruscolo, M. & Laio, A. Characterization of the free-energy landscapes of proteins by NMR-guided metadynamics. Proc. Natl. Acad. Sci. U.S.A. 110, 6817–6822 (2013).
+
 
 */
 

user-doc/tutorials/belfast-9a.txt

@@ -9,11 +9,17 @@ the latter is an approach that can be used to increase the quality of a force-fi
 \section belfast-9-lo Learning Outcomes
 
 Once this tutorial is completed students will:
-- know multiple ways of using experimental data in MD simulations
-- know how to use replica-averaged restrained MD simulations
+- know why and how to use experimental data to define a collective variable 
+- know why and how to use experimental data as replica-averaged restraints in MD simulations
 
 \section Resources
 
+The <a href="tutorial-resources/belfast-9a.tar.gz" download="belfast-9a.tar.gz"> tarball </a> for this project contains the following:
+- system: the files use to generate the topol?.tpr files of the first and second example
+- first: an example on the use of chemical shifts as a collective variable
+- second: an example on the use of chemical shifts as replica-averaged restraints
+- third: an example on the use of RDCs (calculated with the theta-method) as replica-averaged restrains 
+
 \section Instructions
 
 \subsection expdata Experimental data as Collective Variables
@@ -22,10 +28,10 @@ In the former tutorials it has been often discussed the possibility of measuring
 some kind of state for a system, i.e. \ref belfast-5. An alternative possibility is to use as a reference a set of experimental data
 that represent a state and measure the current deviation from the set. In plumed there are currently implemented the following NMR
 experimental observables: Chemical Shifts (only for proteins) \ref CS2BACKBONE and \ref CH3SHIFTS, \ref NOE distances and Residual Dipolar
-couplings \ref RDC. In addition \ref NOE collective variable can be also used for PRE distances and 3J Couplings will be implemented
-shortly. Among the above listed collective variables those based on chemical shifts make use of an external library, ALMOST, that  must
-be downloaded and compiled separately. In addition plumed must be configured in such a way to link ALMOST. Detailed instructions on how
-to compile PLUMED with ALMOST can be found in \ref CS2BACKBONE.
+couplings \ref RDC. In addition \ref NOE collective variable can be also used for PRE distances and 3J Couplings can be implemented using
+\ref TORSION and \ref MATHEVAL. Among the above listed collective variables those based on chemical shifts make use of an external library, 
+ALMOST, that  must be downloaded and compiled separately. In addition plumed must be configured in such a way to link ALMOST. 
+Detailed instructions on how to compile PLUMED with ALMOST can be found in \ref CS2BACKBONE.
 
 In the following we will write the CS2BACKBONE collective variable that has been used in Gratana et al. (2013).
 
@@ -35,22 +41,104 @@ WHOLEMOLECULES ENTITY0=prot
 
 cs: CS2BACKBONE ATOMS=prot DATA=data FF=a03_gromacs.mdb NRES=56 FLAT=1.0 WRITE_CS=50 
 
-
-
 PRINT ARG=cs FILE=COLVAR STRIDE=100
 
 ENDPLUMED
 \endverbatim 
 
+In this case the chemical shifts are those measured for the native state of the protein and can be used, together with other CVs and Bias-Exchange
+Metadynanics, to guide the system back and forth from the native structure. The experimental chemical shifts are in six files inside the "data/"
+folder (see first example in the resources tarball), one file for each nucleus. A 0 chemical shift is used where a chemical shift doesn't exist
+(i.e. CB of GLY) or where it has not been assigned. Additionally the data folder contains:
 
+- camshift.db: this file is a parameter file for camshift, it is a standard file needed to calculate the chemical shifts from a structure
+- a03_gromacs.mdb: this is a Amber force field in ALMOST format and it is used to map the atom names from plumed and almost (in this case we are using amber for our simulation)
+- template.pdb: this is a pdb file for the protein we are simulating (i.e. editconf -f conf.gro -o template.pdb) where atoms are ordered in the same way in which are included in the main code and again it is used to map the atom in plumed with those in almost.
+
+This example can be executed as
+
+\verbatim
+mdrun_mpi -s topol -plumed plumed
+\endverbatim
 
 \subsection replica Replica-Averaged Restrained Simulations 
 
 NMR data, as all the equilibrium experimental data, are the result of a measure over an ensemble of structures and over time.
 In principle a "perfect" molecular dynamics simulations, that is a simulations with a perfect force-field and a perfect sampling
 can predict the outcome of an experiments in a quantitative way. Actually in most of the cases obtaining a qualitative agreement
-is already a lucky outcome.
+is already a fortunate outcome. In order to increase the accuracy of a force field in a system dependent manner it is possible
+to add to the force-field an additional term based on the agreement with a set of experimental data. This agreement is not enforced
+as a simple restraint because this would mean to ask the system to be always in agreement with all the experimental data at the
+same time, instead the restraint is applied over an AVERAGED COLLECTIVE VARIABLE where the average is performed over multiple
+identical simulations. In this way the is not a single replica that must be in agreement with the experimental data but they should
+be in agreement on average. It has been shown that this approach is equivalent in solving the problem of finding a modified
+version of the force field that will reproduce the provided set of experimental data withouth any additional assumption on the
+data themselves.
+
+Currently ENSEMBLE AVERAGING of a collective variable can be performed only using the NMR variables (\ref CS2BACKBONE, \ref CH3SHIFTS,
+\ref NOE and \ref RDC).
+
+The second example included in the resources show how the amber force field can be improved in the case of protein domain GB3 using
+the native state chemical shifts a replica-averaged restraint. By the fact that replica-averaging needs the use of multiple replica
+simulated in parallel in the same conditions it is easily complemented with BIAS-EXCHANGE or MULTIPLE WALKER metadynamics to enhance
+the sampling.
+
+\verbatim
+prot: GROUP ATOMS=1-862
+WHOLEMOLECULES ENTITY0=prot
+
+cs: CS2BACKBONE ATOMS=prot DATA=data FF=a03_gromacs.mdb NRES=56 FLAT=0.0 WRITE_CS=500 ENSEMBLE
+
+cse: RESTRAINT ARG=cs AT=0. KAPPA=0. SLOPE=24
+
+PRINT ARG=cs FILE=COLVAR STRIDE=10
+
+ENDPLUMED
+\endverbatim
+
+with respect to the case in which chemical shifts are used to define a standard collective variable, in this case the keyword ENSEMBLE
+tells plumed to calculate all the chemical shifts from the replicas (i.e. 4 replicas) average them and only after the averaging calculate
+the difference with respect to the experimental ones. On this difference that is the AVERAGED Collective Variable it is possible to apply
+a linear \ref RESTRAINT (because the variable is already a sum of squared differences) that is the new term we are adding to the underlying
+force field.
+
+This example can be executed as
+\verbatim
+mpiexec -np 4 mdrun_mpi -s topol -plumed plumed -multi 4
+\endverbatim
+
+The third example show how \ref RDC (calculated with the theta-methods) can be employed in the same way, in this case to describe the native state of Ubiquitin. In 
+particular it is possible to observe how the RDC averaged restraint applied on the correlation between the calculated and experimental 
+N-H and CA-HA RDCs result in the increase of the correlation of the RDCs for other bonds already on a very short time scale.
+
+\verbatim
+RDC ...
+ENSEMBLE
+CORRELATION
+GYROM=-72.5388
+SCALE=0.001060 
+ATOMS1=20,21 COUPLING1=8.17
+ATOMS2=37,38 COUPLING2=-8.271
+ATOMS3=56,57 COUPLING3=-10.489
+ATOMS4=76,77 COUPLING4=-9.871
+#continue....
+\endverbatim
+
+In this input the first four N-H RDCs are defined.
+ 
+This example can be executed as
+\verbatim
+mpiexec -np 8 mdrun_mpi -s topol -plumed plumed -multi 8
+\endverbatim
+
+\Reference
 
+1. Granata, D., Camilloni, C., Vendruscolo, M. & Laio, A. Characterization of the free-energy landscapes of proteins by NMR-guided metadynamics. Proc. Natl. Acad. Sci. U.S.A. 110, 6817–6822 (2013).
+2. Cavalli, A., Camilloni, C. & Vendruscolo, M.  Molecular dynamics simulations with replica-averaged structural restraints generate structural ensembles according to the maximum entropy principle. J. Chem. Phys. 138, 094112 (2013).
+3. Camilloni, C., Cavalli, A. & Vendruscolo, M. Replica-Averaged Metadynamics. Journal of Chemical Theory … 9, 5610–5617 (2013).
+4. Roux, B. & Weare, J. On the statistical equivalence of restrained-ensemble simulations with the maximum entropy method. J. Chem. Phys. 138, 084107 (2013).
+5. Boomsma, W., Lindorff-Larsen, K. & Ferkinghoff-Borg, J. Combining Experiments and Simulations Using the Maximum Entropy Principle. PLoS Comput. Biol. 10, e1003406 (2014).
+6. Camilloni, C. & Vendruscolo M. A Tensor-Free Method for the Structural and Dynamical Refinement of Proteins using Residual Dipolar Couplings. J. PHYS. CHEM. B XXX (2014).
 
 */
 
@@ -58,4 +146,5 @@ link: @subpage belfast-9
 
 description: NMR constraints
 
+additional-files: belfast-9a.tar.gz