Merge pull request #687 from haddocking/structuralbioinfo-2025-updates

Structuralbioinfo 2025 updates

education/molmod_online/modelling.md

@@ -89,8 +89,8 @@ Take the time to browse through the UniProt page of mouse MDM2. The header of th
 protein, gene, and organism names for this particular entry, as well as its unique UniProt
 accession code. On the left, below the header, there is a sidebar listing the several sections of
 the page. You can use these to navigate directly to the **Structure** section to verify if there are
-already published experimental structures for mouse MDM2. Fortunately, there aren't any _yet_; otherwise
-this tutorial would end here.
+already published experimental structures for mouse MDM2 (not a predicted model by AlphaFold2 !). 
+Fortunately, there aren't any _yet_; otherwise this tutorial would end here.
 
 
 Similarly as man, no protein is an island, entire of itself, every protein is a piece of the cell, a part of the main. Thus if we imagine the cytoplasm as a thick molecular soup, proteins are constantly in contact, interacting and exchanging information. Currently, predicting the entire cell interactome is close to impossible, however UniProt offers us a possibility to see experimentally confirmed interaction partners of proteins.
@@ -149,7 +149,7 @@ the first region (positions 1-110), the SWIB domain, or whatever seems best in y
   Why can the first ~20 amino acids of MDM2 be neglected for the modelling?
 </a>
 
-Clicking on the *position(s)* column of a particular region/domain (*Family and Domains* section) opens a new window showing the
+Clicking on the *position(s)* column of a particular region/domain (*Family and Domains* section) opens a drop-down section showing the
 corresponding sequence as well as the region in the context of the full sequence.
 Although this window provides a shortcut to launch a *BLAST* similarity search against the UniProtKB (or another)
 database, there are other more sensitive methods for this purpose. For now, pay attention to the
@@ -229,9 +229,9 @@ sequence, the _hit_, which was deemed similar to the query. It will contain the
 itself and also some quantitative statistics, namely the sequence similarity, the bit score of the
 alignment, and its expectation (E) value. Sequence similarity is a quantitative measure of how
 evolutionarily related two sequences are. It is essentially a comparison of every amino acid to its
-aligned equivalent. There are three possible outcomes out of this comparison: the amino acids are
-exactly the same, i.e. identical; they are different but share common physicochemical
-characteristics, i.e. similar; they are neither. It is also possible that the alignment algorithm
+aligned equivalent. There are three possible outcomes out of this comparison: i) the amino acids are
+exactly the same, i.e. identical; ii) they are different but share common physicochemical
+characteristics, i.e. similar; iii) they are neither, they are very different. It is also possible that the alignment algorithm
 introduced _gaps_ in either of the sequences, meaning that there was possibly an insertion or a
 deletion event during evolution. While identity is straightforward, similarity depends on specific
 criteria that group amino acids together, e.g. D/E, K/R/H, F/Y/W. The bit score is the likelihood

education/molmod_online/simulation.md

@@ -116,7 +116,7 @@ algorithms in place, during the simulation, that maintain these two properties c
 
 Despite decades of research, as well as advances in computer science and hardware development, most
 simulations are able to sample only a few microseconds of *real time*, although they take several
-days/weeks running on multiple processors. The millisecond (*ms*) barrier was broken only recently, by
+days/weeks running on multiple processors. The millisecond (*ms*) barrier was broken in 2010, by
 simulating on a purpose-built computer ([Anton](https://en.wikipedia.org/wiki/Anton_(computer))). Moreover, the force fields used in biomolecular simulation
 are approximating the interactions happening in reality. This results in errors in the estimation
 of energies of interacting atoms and groups of atoms. As such, molecular dynamics are not a
@@ -146,13 +146,13 @@ Take your time to know your system and what particularities its simulation entai
 
 
 In NMRBox, after you open the terminal prompt you notice `username@machine`, where your username is the same as the NMRbox username.
-You will find your own copy of the course material in `~/EVENTS/2024-struct-bioinfo-uu/` directory.
+You will find your own copy of the course material in `~/EVENTS/2025-struct-bioinfo-uu/` directory.
 You can store your data in your `home` directory but we recommend creating a new directory where you will store your data and work in.
 
 
 __Note__: The data are automatically copied to your home directory under the `EVENTS` directory provided you have registered for this event on NMRBox. The event can be found at [https://nmrbox.nmrhub.org/events](https://nmrbox.nmrhub.org/events){:target="_blank"}. In order to register for the course you need to have an NMRBox account.
 
-__Note__: In case you are following this tutorial on your own, you will have to manually copy all the required data and edit possibly some files to correct the paths (e.g. the `setup.sh` and the `bashrc` scripts). The data for the course can be found once logged in into a VM in the following directory: `/public/EVENTS/2024-struct-bioinfo-uu/`.This directory will however automatically be copied to your home directory when you register for the course on NMRBox
+__Note__: In case you are following this tutorial on your own, you will have to manually copy all the required data and edit possibly some files to correct the paths (e.g. the `setup.sh` and the `bashrc` scripts). The data for the course can be found once logged in into a VM in the following directory: `/public/EVENTS/2025-struct-bioinfo-uu/`.This directory will however automatically be copied to your home directory when you register for the course on NMRBox
 
 Open the terminal and create a directory where you will work in with name of your choice:
 <a class="prompt prompt-cmd">
@@ -212,14 +212,18 @@ The successful completion of the tutorial requires, however, all three conformat
   Generate an ideal structure for the peptide sequence using the fab script in PyMOL, choose between helix/polypro/beta.
 </a>
 
-<a class="prompt prompt-pymol" style="dispay: none;">
+<a class="prompt prompt-pymol">
   fab SQETFSGLWKLLPPE, peptide_helix, ss=1
 </a>
-
+or
 <a class="prompt prompt-pymol">
   build_seq peptide_helix, SQETFSGLWKLLPPE, ss=helix
 </a>
 
+Note that both commands will produce the same for helices.
+The `build_seq` script is a home made one, while the `fab` command is a native PyMOL implementation.
+You can get more information on how to use the `fab` command by typing `help fab`.
+
 <a class="prompt prompt-pymol">
   save p53_helix.pdb, peptide_helix
 </a>