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13

It looks like the equations you're dealing with are all polynomial after clearing denominators. That's a good thing (transcendental functions are often a little harder to deal with algebraically). However, it's not a guarantee that your equations have a closed-form solution. This is an essential point that many people don't really "get", even if they know it ...


8

There is a C++ library which is quite mature. This is probably as close as you will get to C. I myself haven't found any usable C library yet. You could use the C++ library and still write most of your code in C using extern C { } in the C++ code.


8

The most popular molecular dynamics codes are namd and gromacs, and maybe also desmond. These packages are freely available and "open source" in the sense that the source code is made available for free. Wikipedia hosts a list of software for molecular modeling which may contain other good links. These codes, however, are also quite complex and therefore if ...


7

The professional way is to write your equations in a modeling language such as AMPL or GAMS, and solve it with a solver such as IPOPT. AMPL is a commercial system, but a free student version of AMPL is able to pose problems with up to 300 equations and variables. If you just want to solve one or a few problems, you can have it solved online freely by ...


6

According to Wing-Kin Sung's excellent "Algorithms in Bioinformatics" (2010, pp 30-39), the fastest algorithm was discovered in 1980 by Masek and Paterson and can solve the global alignment problem in $O(nm /\log(n))$ time, which is barely better than the Needleman-Wunsch algorithm: W.J Masek and M.S. Paterson. 1980. "A faster algorithm computing string ...


6

OpenBabel is C++, but it's commonly used for general structural things - its main focus is conversion between and the ability to read a wide range of formats. As far as I know it doesn't have the ability to calculate SAS areas, though.


6

To write out the entire solution is impossible within reason. But here are some equations to reduce the system down a bit: $U_{S}$ doesn't appear in any equations other than equations 1 and 2. Furthermore, these equations are a dependent set (equation 1 is -1 times equation 2), so equation 1 can be solved for $U_{S}$ in terms of all other variables, and ...


6

You're trying to have your cake and it it too. This does not work. As a general rule, for problems with features on different length scales, you need meshes that are fine in at least some parts of the mesh. This results in many cells, and this results in long computations, small time steps, and many linear iterations. All of these implications are rather ...


5

Besides Pedro's suggestions, you could also look at Quantum Espresso, which among other things allows for Car-Parrinello computations. It is (or at least, it was) written in Fortran 90.


5

With conforming triangular meshes, it will be difficult to make an isotropic mesh which adapts to multiple dramatically different length scales in such a short space without introducing extraneous triangles, some of which may have very large/small angles. I'm not very familiar with them so take this with a grain of salt, but you may have better luck using ...


4

I don't work in that business but naively I think there are three parts to a complete description A description of the data landscape they live in. Describe this in terms of the data structure (graph (directed or undirected, weighted or unweighted); tree; array; ...) and the data associated with each node. Make note of special case handling such as periodic ...


4

I suggest either Shapiro's RNA2D3D or MC-FOLD: RNA2D3D -> http://www-lmmb.ncifcrf.gov/~bshapiro/rna2d3d/rna2d3d.html. MC-FOLD -> http://www.major.iric.ca/MC-Pipeline/. These programs require the 2D structure to generate the 3D structure, but you can easily find a program for that. Actually there's one on the MC-Pipeline website so you can get from the RNA ...


4

To start with your "related question": I do PDB parsing in Python, even when the subsequent processing needs to be done in some compiled language for speed. C is simply not a good language for parsing, in particular not for messy formats like PDB. And that's probably why there aren't any stable and mature PDB parsers in C. Something else you can consider, ...


4

It's been known for quite some time that quantum methods have a useful role to play in studying protein-ligand docking. However, the challenge that you have—which has not really changed too much in recent years—is that ab initio methods do not cope well with very large systems. It's probably possible to study the interaction of a ligand with the relevant ...


4

So Is it neccesary to use Poisson - Boltzmann equation if I only need to build electrostatic potential from a PQR file? No. You can use Poisson. Since you know the positions of each point charge, you know the charge distribution $\rho$, which is a sum of delta functions. You can thus solve numerically the Poisson's equation that links the charge ...


3

The term "energy minimization" usually refers to the minimization of the potential energy. For protein folding simulations, you really need to minimize free energy. If you run plain energy minimization on an unfolded protein, you will pretty soon get stuck in a local minimum. So you probably do want molecular dynamics, and use some protocol such as simulated ...


3

It depends on the structure of your equations. If you're looking for all steady states of your set of equations, and you can rearrange them as ErikP says into polynomials, you can use methods from real algebraic geometry to calculate all numerical solutions to high precision. Bertini is one such package that I know of, but there are others. I went to a ...


3

I know this is about C, but there is a great way to do this using the GLGRAPHICS library, which implements OPENGL in Processing (a java based framework with c++ like syntax). OpenGL is basically the same regardless of what language you use, so Java shouldn't make too big of a performance difference. Anyway, the GLGRAPHICS library comes with a pdb viewer that ...


3

If you're willing to go with C++, then I'd recommend ESBTL. Instead of dealing with files in PDB format, you might consider downloading them from the Protein Data Bank in PDBML format, which is actually XML. You can then parse PDBML files using your favorite XML library for C (for example, with Libxml2).


3

A general answer to the question is just impossible. This answer is limited to modeling the electrostatic term. We have recently published a detailed comparison of different methods to compute atomic charges, using two sets of 100+ penta-alanine conformers. (link) We tested both the robustness of the charges with respect to conformational changes and the ...


3

To ask about all ways is too ask too much, I guess. For the computationally most efficient way to encode the geometric information, see Section 2 of my survey paper Molecular modeling of proteins and mathematical prediction of protein structure, SIAM Rev. 39 (1997), 407-460.


3

Since you are specifically looking for a library, you might be interested in OpenMM. Two popular visualization packages are PyMol and VMD.


3

I'm not particularly familiar with biofilm literature. But in most computational literature, the border of the entire domain of a problem are usually referred to as the boundary. Outside of a boundary, there are no nodes, elements, or anything else under consideration. The entire domain may also be subdivided into smaller regions. Some of these regions ...


3

The Van der Walls radius - last column in the output - is calculated from the force field. Probably pdb2pqr and editconf uses different force fields, hence different radius. I don't use pdb2pqr, but it seems (1) AMBER99 is the default force field, though CHARMM, PARSE and TYL06 are supported. Gromacs' editconf reads force field from topology file generated ...


3

The answer as of 2017, to the best of my knowledge, is "not yet." Your question is treated in detail here and in the references therein.


3

Your model seems to have a single stable critical point that attracts all orbits. You're plotting $(S(t), I(t), R(t))$ as functions of time for specific initial conditions, but actually the easier way to see this directly is to plot the vector field $(\dot S, \dot I)$ in the $S$-$I$ plane like so: Immediately you can see that for this particular choice of ...


2

There exist hybrid methods such as ONIOM and QUILD (a rough cognate of ONIOM) that address the interface between QM and MM calculations and are well-suited to investigation of protein cofactors and probably refining ligand docking models. The ONIOM methodology is very simple but clever - you break the calculation into the bulk protein which is handled with ...


2

There is something called the ODD (Overview, Design, and Details) protocol, proposed by Volker Grimm and others for describing an agent based model. It consists of a list of elements that are needed for understanding the functioning of an ABM and aims at making descriptions of such models more standardised. The checklist of what has to be described consists ...


2

I do not think this would be useful and am not aware of it being implemented anywhere, but as they say, absence of evidence is not evidence of absence. I saw a lecture a while back about research by Reimers and coworkers concerning the use of ab initio methods in the final refinement of XRD fits, in addition to the restrained MD often used in refinement, ...


2

The AIC function need an 'lm' or 'glm' object (linear models). See functions lm and glm So just do : AIC(lm(logCPK~dataPOW))


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