3

To expand on Matteo Ferla's comment as an answer, there are two approaches to getting these "allowed" contours: From probabilities found in observed crystal structures. You could imagine plotting a Ramachandran plot for the whole PDB and colouring the points by assigned secondary structure from DSSP. The contours would then be regions that encompass e.g. 99%...


3

Asking how to visualise the disordered region of a protein is a bit like asking how to visualise the location of an electron. An intrinsically disordered protein, by definition, has regions that are disordered. In other words, their location is variable under observation, so they cannot be precisely placed in a 3D model.


3

Yes, RDKit can be used, however, if you installed it with conda it will not work out of the box for inChi key fetching. You can either spend some time installing the missing bit or use something else. It is not like Mol2 support in RDKit, which shouldn't be used, it is just not worth the bother. I would suggest PubChem's RESTFul API. Say import requests ...


3

Hydrogens Most crystallographic structures are X-ray and the hydrogens are absent. In the case of neutron diffraction models, there may be many missing high b-factor ones (example in PDB:5MOP). As a consequence models are reprotonated. Also missing carbons and missing loop residues are added for some in silico applications too (not docking). However, it is ...


3

My answer is mainly based on molecular dynamics,but in this context it shouldn't make much of a difference. The main reason has to do with the force-field-water model used during the simulation. Examples of water models are SPC, TIP3P or TIP4P; same molecule (water) but different topology. A pdb usually comes from different sources and it can contain ...


2

'label_size' is a object-state-level setting, which means that you will have to rely on the 'create' command to create a new object for every different label size. It can certainly be automated, and for this I'd recommend getting into Pyhton Scripting for PyMOL


2

As others have said, there is no short cut and you will need to spend some time with a good book. I would say there are 3 broad areas of understanding you have to have as a structural bioinformatician: Solid understanding of the basic science. This includes molecular biology but also chemistry, which is often overlooked. Knowledge of the databases and data ...


2

There are a few steps in between pdb and .maps.fld. Here is the list of several scripts that can do tasks for you that you downloaded with autodock MGLTools: http://autodock.scripps.edu/faqs-help/faq/where-can-i-find-the-python-scripts-for-preparing-and-analysing-autodock-dockings. Look at the prepare_ files. Also note that the scripts come with a pre-...


2

Slightly modified Matteos answer: import requests def get_smiles_from_inchikey(inchikey): r = requests.get(f'https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/inchikey/{inchikey}/property/CanonicalSMILES/JSON').json() return r['PropertyTable']['Properties'][0]['CanonicalSMILES'] inchikey = 'SGNXVBOIDPPRJJ-UHFFFAOYSA-N' get_smiles_from_inchikey(...


2

I believe PDB2PQR CLI will do the work wonderfully. Don't let the name trick you: PQR files are organized like PDB ones. Under the hood it runs propka, which is state-of-the-art for predicting a protein residues protonation state. The best part is that you can use PDB2PQR web server and they will give you the corresponding CLI arguments for each option you ...


2

It is best to contextualise the numbers. -1 kcal/mol is about the potential energy gained from a hydrogen bond —technically described in the r^6 part of the Lenard–Jones term, it is also the average collision energy of a water molecule at 37°C as that is RT ($\frac{k_b\cdot T}{N_A}$, wiki)under a Maxwell–Boltzmann distribution. A salt bridge –2 kcal/mol (...


2

The difference between different force-fields is not going to be major, it is the side steps which are. When If you are starting from a SMILES string, optimisation is a must obviously. If you are using a 3D conformer from PubChem or even an actual sub-1 Å crystal structure from CSD, optimisation is nice for consistency. Which MMF94 is a solid choice. ...


1

I do not know much about statistics but I will try my best to explain. First, random effects are defined as the factors (categories) in the population that we are not aware of (not observed), so we are randomly sampling levels of those factors when we sample the population. Practically speaking, random effects can be found when there are hierarchical ...


1

Your title says holistic. This is a tad problematic as there's layers upon layers. Say, post-translation regulation, inhibiting metabolites, interacting protein etc. That is why when talking of an enzyme inhibitor, at the biochemical level one speaks in terms of k_i (inhibition constant), while at the cellular level ("holistic") one talks of IC50. ...


1

TM-align has some options to do this, see for example https://zhanglab.ccmb.med.umich.edu/TM-align/help.html. TM-align is similar to TM-score but the alignment is purely structural.


1

Open the PyMOL session. Use the load command to load your PDB file(s): load file.pdb. Use the align or super commands to overlay structures, e.g. align prot1, prot2.


1

Thanks a lot to all who commented/replied, the author of the scripts provided a response. It was down to a syntax change in PyMol of which I wasn't aware that caused my selection to come up empty.


1

I ended up fixing this by just putting this into the boilerplate code: copy PolyA-MC_4, PolyA-MC copy PolyA-MC_6, PolyA-MC copy PolyA-MC_8, PolyA-MC copy PolyA-MC_10, PolyA-MC copy PolyA-MC_12, PolyA-MC copy PolyA-MC_14, PolyA-MC copy PolyA-MC_16, PolyA-MC copy PolyA-MC_18, PolyA-MC copy PolyA-MC_20, PolyA-MC This copied my object such that I had one per ...


1

A good starting point could be this book by Gu and Bourne: Structural Bioinformatics, 2nd Edition


1

You could also take a look at Infernal. I think your best bet is to use RNA-focused programs; I'm not aware of a DNA-specific one, which makes some sense because DNA is typically double-stranded, so the secondary structure community is primarily focused on RNA. I would predict that secondary structure potential of single-stranded DNA would be similar to ...


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