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12	12	(((
13	13	(% class="col-xs-12 col-sm-8" %)
14	14	(((
15		-= What can I find here? =
	15	+= What DF matrices are? =
16	16
17		-* Notice how the table of contents on the right
18		-* is automatically updated
19		-* to hold this page's headers
	17	+The analysis of the results of a MD simulation can performed using the Distance Fluctuation matrices (DF), based on the Coordination Propensity hypothesis:
20	20
21		-= Who has access? =
	19	+(% style="text-align:center" %)
	20	+[[image:CodeCogsEqn-58.png||height="34" width="181"]]
22	22
23		-Describe the audience of this collab.
	22	+low CP values, corresponding to low pair-distance fluctuations, highlight groups of residues that move in a mechanically coordinated way.
	23	+
	24	+
	25	+= How to use the script =
	26	+
	27	+• __Requisites__
	28	+
	29	+ - Python 3.0 (or newer version)
	30	+
	31	+ - Numpy
	32	+
	33	+ - Scipy
	34	+
	35	+
	36	+• __Usage__
	37	+
	38	+The script can analyze a MD trajectory and identify the coordinated motions between residues. It can then filter the output matrix based on the distance to identify long-range coordinated motions.
	39	+
	40	+The script can work both using only C-alphas (using either a pdb or a xyz file) or the sidechains (using a pdb file).
	41	+
	42	+For more information run:
	43	+
	44	+{{{ python3 distance_fluctuation.py -h}}}
	45	+
	46	+
24	24	)))
25	25
26	26
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28	28	(((
29	29	{{box title="**Contents**"}}
30	30	{{toc/}}
	54	+
	55	+
31	31	{{/box}}
32	32
33	33
34	34	)))
35	35	)))
	61	+
	62	+• __How to read the output__
	63	+
	64	+The script generate different output file.
	65	+
	66	+
	67	+A) Average Distance (avgdist) file:
	68	+
	69	+ The name of the file is avgdist_out_x_y_type.dat with x = start frame of the analysis, y = end frame of the analysis, type = type of analysis (CA or sidechains)
	70	+
	71	+ The file contains a matrix using the residue indexes as axes and the average value of the distance between the residues as the data (r1 r2  avgdist).
	72	+
	73	+ The distance is calculated as the average of the euclidean distance between the residues.
	74	+
	75	+
	76	+B) Distance Fluctuation (rmsdist) file:
	77	+
	78	+ The name of the file is rmsdist_out_x_y_type.dat with x = start frame of the analysis, y = end frame of the analysis, type = type of analysis (CA or sidechains).
	79	+
	80	+ The file contains a matrix using the residue indexes as axes and the distance fluctuation between the residues as the data (r1 r2 rmsdist).
	81	+
	82	+ The distance fluctuation is calculated for the residues that are at least 3 residues away from each other (x-2 to x+2) as follow:
	83	+
	84	+ 1) Calculate the average euclidean distance between the residues (either CA or center of mass)
	85	+
	86	+ 2) Calculate the average distance vector
	87	+
	88	+ 3) Substract the distance fluctuation to the average distance
	89	+
	90	+ 4) Calculate the power of the difference between distance fluctuation and local fluctuation
	91	+
	92	+ 5) Filter the values of the close residues (1-x, x, 1+x)
	93	+
	94	+ 6) Divide the obtained value for the number of frames
	95	+
	96	+
	97	+C) Profile Sequence (profile_sequence) file:
	98	+
	99	+ The name of the file is profile_sequence_x_y_type.dat with x = start frame of the analysis, y = end frame of the analysis, type = type of analysis (CA or sidechains).
	100	+
	101	+ The file is a vector containing the residue number and the local flucutation value.
	102	+
	103	+ The local fluctuation is calculated as the average fluctuation of the residues close to each other (that is the residues ranging from x-2 to x+2 with x = residue number).
	104	+
	105	+ Since the value contains the average distance fluctuation for a range of residues the output starts from residue 4 and ends at residue n-3).
	106	+
	107	+
	108	+D) Distance Analysis (distance_analysis_out) file:
	109	+
	110	+ The name of the file is distance_analysis_out_c_x_y_type.dat with c = cutoff value, x = start frame of the analysis, y = end frame of the analysis, type = type of analysis (CA or sidechains).
	111	+
	112	+ This fail contains the distance fluctuation filtered by the cutoff value (the value are kept if the distance fluctuation is smaller than the cutoff value).
	113	+
	114	+ The cutoff value is calculated as the sum between the nearcutoff and the tolerance value specified by the user.
	115	+
	116	+ The nearcutoff can be calcolated either using sequence proximity or 3d proximity and can be specified by command line using the option -l or ~-~-local (see the command line help for further details).
	117	+
	118	+ In the case of sequence proximity it is calculated as the average of the distance fluctuation value for residues in the range of x-2,x+2 (x = residue index)
	119	+
	120	+ In the case of 3d proximity is calculated as the average distance fluctuation of the residues within a certain radius from the current one (default value = 6.5 A)
	121	+
	122	+
	123	+E) Blocks Averaging: (rmsdist_out_b)
	124	+
	125	+It is possible to obtain a distance fluctuation matrix average on protein domains ( or blocks).
	126	+
	127	+The script requires an input file with the borders of the protein blocks defined by the user, in the form of two columns: the first with the lower limit and the second with the upper limit.