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Imagine if given an amino acid sequence, you could quickly calculate what the shape of the corresponding protein would be. You would be able to predict what effect a mutation would have on the shape of the protein. Switching just one glutamic acid with valine completely changes the shape of hemoglobin to the extent that people with this mutation are said to ...

17

Great question! Protein folding has been in open question for decades. Just recently, there's been a lot of discussion regarding DeepMind's AlphaFold project, which was discussed at length on our very own site here. My answer will be complementary to the one above, but the references I will provide will be closer to the physics side of the problem. First ...

16

It's a great question! Some of my answer will be taken from my answer to your question on the AI stack exchange, but cross-site questions are allowed and your question here is slightly different so my answer is slightly different. I'll address your points in reverse chronological order: (4) Most proteins don't have metals at all. It was estimated in 1999 ...

14

The "Lost atoms" error typically happens when huge forces blow up an MD calculation. This is also the problem here: The main issue are the units. The input parameters for reax force fields are given in "real" units by default. Unless they are converted real units have to be used in the lammps input file. Setting the units appropriately ...

12

The simulation speed and efficiency depends on the hardware and software that you use. Things that you should keep in mind are, Every computer is unique in its ability. So only someone with access to the exact same hardware (processor, gpu etc.) can test this out and tell you. As far as I know, there is no established method of calculating the computational ...

11

Someone more familiar with the problem might have a better suggestion, but I recently came across Daniel B. Dix' notes on Mathematical Models of Protein Folding. This is not my field, so I won't guarantee correctness. However, to a layman at least, these notes seem well suited for someone with your background. The abstract reads We present an elementary ...

11

The main requirement is to have structures files with good resolution. According to RSCB PDB documentation: Resolution is a measure of the quality of the data that has been collected on the crystal containing the protein or nucleic acid. The figure bellow is an example of how the resolution indicates the quality of the structure (linked from original ...

9

Preamble Since I don't know your specific background, this is a generic answer for any applied mathematician wishing to enter the field of protein folding. Not everything will apply specifically to you, and please don't feel offended if there's something I assume you don't already know or do! First of all, as a fellow mathematician (I was trained in ...

9

Short answer: Do a short test run for performance estimates. Once you're familiar with a specific hardware/software combination, you may be able to estimate based on the size of the system, but the general advice (especially with hardware you're not familiar with) is to do a short benchmarking run. Gromacs-specific practical advice: Use the -maxh option to ...

8

H++ H++ is a web service that permits to protonate your macromolecules using using different pH conditions. From its site: H++ is an automated system that computes pK values of ionizable groups in macromolecules and adds missing hydrogen atoms according to the specified pH of the environment. Given a (PDB) structure file on input, H++ outputs the completed ...

8

HADDOCK HADDOCK is both a web service and a standalone code. From the web server: HADDOCK (High Ambiguity Driven protein-protein DOCKing) is an information-driven flexible docking approach for the modeling of biomolecular complexes. HADDOCK distinguishes itself from ab-initio docking methods in the fact that it encodes information from identified or ...

7

Keep in mind that many if not most proteins have multiple quasi-stable conformations, so their 3D structure is not actually a single conformation but rather a Markov matrix of conformations, with probabilities of a given conformation and probabilities of transition from each conformation to its neighbors varying according to temperature, pH, and other ...

7

Probably one of the important applications is Computer Aided Drug Discovery (CADD). If the protein structure could be accurately predicted, one could design protein-ligand docking on the binding pockets and run molecule dynamics simulations. In the lead identification process of a CADD, the starting point is normally be the experimental data for the crystal ...

6

I don't think that any classification of dihedral angles exists. α and β that you see in the picture refer to alpha helices and beta sheets – structural elements of proteins (secondary structure). What is neither a helix nor β-strand is called a loop or coil. Sometimes more detailed categories are used – for example, 310 and π helices can be used as separate ...

6

Proteopedia suggests that the $\phi$ and $\psi$ angles of a Ramachandran plot only involve carbon and nitrogen atoms in their definition and specifically the carbons and nitrogens in the backbone of the protein or $n$-peptide. These definitions are also used in an article from BioMol Concepts, describing new ways of presenting Ramachandran plots, which ...

6

It depends on your actual scenario. If we assume that you have two Molecular Dynamics (MD) replicas for the same protein (and their respective trajectories), then when you perform a Radius of Gyration ($R_g$) computation from a MD trajectory you commonly end up with a time series for the values for it, $R_g(t)$. From $R_g(t)$ you can already plot the time ...

6

Normally, if various proteins have the "same" cavities/clefts, this means that they are part of the same family and the amino acids that form the cavity are conserved. I really don't think that the electronic properties (charges and electrostatic potential surface) are directly related to the geometrical shape. Instead, they are related to the ...

6

The problem in the sript I had written was that my system was not able to handle that many variables at one go. So I made the calculations piecewise i.e. 40 atoms at a time and the results closely match the values one gets from the inbuilt function. In any case, calculating RMSF for just the C alpha atoms gives more information about the structural changes ...

6

I'm adding another answer because I recently find these news. The machine learning-based methods alphafold and rosettafold were recently released on github. Someone has just implemented it in Google colab as Jupiter notebook that you can simply reuse with your colab account. The only thing that you need to do is change the AA sequence. It seems that in the ...

6

Here's what I did. Assuming that you have a part of the protein crystal structure. In my case, I have an incomplete structure of the protein. Lets say if I have an amino acid (AA) sequence of 520 (full length), I have the pdb for certain domains which are functionally important. So, I went for homology modelling. I used two predictors Robetta and tr-Rosetta. ...

6

I have found the solution to the problem. One needs to use the animate command to change the frame in the top molecule in VMD. The corrected script which produces the desired output is as follows: set outfile [open ./percent_helix.dat w] set lookup {H G I} set frame_num [molinfo top get numframes] set full [atomselect top "name CA"] set len [...

6

Do you have access to OpenBabel to run from the terminal? For the purpose of demonstration, the example following is demonstrated on a file listing SMILES strings. However, the concept may be applied on a .pdb with multiple models (and equally works well enough on multi-model .sdf). The input file input.smi is a small set of aromatics. SMILES strings and ...

6

I'd use OpenMM's openmmforcefields package, which is available on GitHub. I haven't used it extensively, but I recommended to a student in a colleague's lab and they've found it useful. Small molecule force fields: GAFF 1.x and 2.x parameters OpenFF parameters Biomolecule force fields: Amber-type (albeit not Amber ff19SB yet) CHARMM-type And it will, if ...

5

Generally not. The pH difference between the two sides of a membrane can be very noticeable, for example when the membrane is that of a mitochondrion. Actually mitochondria works by actively transporting protons from one side of the membrane to the other side, using the chemical energy released by reducing O2 to H2O, and then use the proton gradient to ...

5

You don't specify what the algorithms shall do. If represented does not equal to visualization, then a the structures may be stored, transferred and processed via the atomic coordinates of the protein. For proteins, the .pdb format is quite common. After a header, the (x,y,z) are described in a block like ATOM 1 N PRO A 1 8.316 21.206 21....

5

In the past I had the same question and after a long search I found that every two year there is a worldwide competition to assess the quality of 3D structure prediction of proteins. In the past the winner was an online services called I-tasser that you can find here. I tested it also in the past year with the covid spike protein and after the publication of ...

5

Your protocol is right and rigorous in the sense as if you don't have the crystal structure of your protein and want to do some predictions, them the only way is using homology modeling. I am not a big fan of homology modeling, so I always recommend to avoid it as possible. My addition will be that, instead using only one resource to model the 3D structure, ...

5

Not a full answer, and it's too big for as a comment, but I can explain the linefix charge all qeq/reax 1 0.0 10.0 1.0e-6 reax/c. This function uses the charge equilibration method (QEq) from Rappe and Goddard (https://doi.org/10.1021/j100161a070) to calculate the partial charges on each atom in the simulation. It's not moving anything in the simulation and ...

5

Another factor to consider might be blind docking or targeted. In this latter, only a region indicated on protein is targeted. In blind docking, the ligand will bind wherever suited on the protein while in targeted only the region indicated will be accessible to the ligand. Blind docking is closer to the real biological setting but computationally expensive. ...

4

The main issue here is not about the type of ligands (glycans) even when it is known that there are force fields that are specific for each type of system. The main issue is about how flexible and big is the ligand you are using to dock. The GLIDE software, for example, has been increasing the number of atoms and rotatable bonds it is able to handle. Since ...

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