Obtain aligned eigenvectors from nma modes

[George Tzotzos]

Hi,

My objective is to obtain the eigenvectors of the first three non-trivial modes. I assume that these are stored in the modes$U.subspace attribute. First, I'd like to ask if this assumption is correct and second what is the exact R syntax to obtain the vectors separately and all three together. As my competence with R is rather rudimentary, I'd be most grateful for any suggestions.

Many thanks in advance

[Xinqiu Yao]

If you are using nma.pdbs(), yes, your assumption is correct.

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Note that ‘modes$U.subspace’ is a 3D array, with each “slice” along the 3rd dimension representing eigenvectors of each structure (columns of that “slice” are the first, second, etc. eigenvector).

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So, for example, if you want to access the second eigenvector of the first structure, use modes$U.subspace[, 2, 1]. Or, if you want the first 3 vectors of the second structure, use modes$U.subspace[, 1:3, 2].

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Also note that the vectors are aligned according to the sequence alignment. So, if your sequences have gaps, the corresponding position in the vector will be shown as NA.

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For single PDB NMA (called by nma.pdb()), the vectors are stored in ‘modes$U’, and it is a matrix and so much easier to understand.

[George Tzotzos]

Thank you very much. I would be grateful for some additional clarifications.

Starting with the simplest case. Assume that the length of a protein is 125 amino acids. The GNM non-trivial modes are 137. The matrix dimension dim(modes1$U) is 125 x 137. First question: How does one slice out, for example, mode 2 (1st non-trivial) mode of the protein?

Moving to the more difficult question, involving an ensemble of proteins. In my example:

modes2 <- gnm(pdbs)

Details of Scheduled Calculation:
... 17 input structures
... storing 96 eigenvectors for each structure
... dimension of x$U.subspace: ( 97x96x17 )
... coordinate superposition prior to NM calculation
... aligned eigenvectors (gap containing positions removed)
... estimated memory usage of final 'eGNM' object: 1.2 Mb

Second question. Using your suggestion modes$U.subspace[, 2, 1] I obtain a 292x2 array. What does this array represent?

Final question. I’m trying to obtain the line shapes of the first three non-trivial modes. Something like the attached screenshot. Maybe, I’m going around the wrong way trying to slice out the eigenvectors for the modes$U object.

Thanks again for your attention

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