Re: [gmx-users] pca-based MD

Hi, Thomas! I'd like to ask you some addition questions about FMA. As I understood from the FMA page that technique is something like integrator of principal components (merge some PCs with identical functional motion seen in the X-ray structures for instance) calculated from g_covar. So FMA is al

Re: [gmx-users] pca-based MD

Dear all! I've read some reference papers about EDA sampling methods and found such usefull things. First of all as I understood for biassing MD simulation along several PCs extracted from another run the make_edi -radacc 1-3 option is exactly what I need. But I havent still understood about m

Re: [gmx-users] pca-based MD

I've still made such 'only c-alpha ensemble' of my structures by the other software and performed x-ray PCA. As the result I've extracted eigenvectors and obtained reasonable distribution (projection) of the structures along that eigenvectors. Now I have questions about pca-biassed MD_run. I've ma

Re: [gmx-users] pca-based MD

I've tried to make PCA from my X-ray data and forced with many problems :) Firstly I've made pdb trajectory in NMR-like format ( by means of pymol) consisted of all X-ray structures. than I've make .tpr file (From the tpr of the same protein which I've simulated previously) for the subset of C-al

Re: [gmx-users] pca-based MD

Hi, thanks again for explanation. Its also intresting to me is it possible > to do further biassed MD guided on that FMA modes as well as obtain > projections onto that FMA sub-spaces of X-ray datasets for instance ? > ( e.g for comparison of the results from FMA of experimental data as > well as

Re: [gmx-users] pca-based MD

Thomas, thanks again for explanation. Its also intresting to me is it possible to do further biassed MD guided on that FMA modes as well as obtain projections onto that FMA sub-spaces of X-ray datasets for instance ? ( e.g for comparison of the results from FMA of experimental data as well as MD_d

Re: [gmx-users] pca-based MD

On 23 September 2012 17:18, James Starlight wrote: > Thomas, > > thank you for the explanation > > 1) Indeed ED sampling was exactly that I need. It's not quite > understand for me about correct chose of that parameters for biassing > simulation > > -linfix string Indices of eigenvec

Re: [gmx-users] pca-based MD

Thomas, thank you for the explanation 1) Indeed ED sampling was exactly that I need. It's not quite understand for me about correct chose of that parameters for biassing simulation -linfix string Indices of eigenvectors for fixed increment linear sampling

Re: [gmx-users] pca-based MD

I presume you are referring to Essential Dynamics Sampling, described in section 3.14 of the manual (v4.5.4). There is also a great tool that finds the few PCs that are maximally correlated to a functional quantity (e.g. the volume of the active site). The technique is coined Functional Mode Analys