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Changes for page Distance-Fluctuations

Last modified by emacasali on 2022/09/15 13:34

From version 7.3
edited by emacasali
on 2022/09/14 21:51
Change comment: There is no comment for this version
To version 8.1
edited by emacasali
on 2022/09/14 21:52
Change comment: There is no comment for this version

Summary

Details

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Content
... ... @@ -42,6 +42,8 @@
42 42  For more information run:
43 43  
44 44  {{{ python3 distance_fluctuation.py -h}}}
45 +
46 +
45 45  )))
46 46  
47 47  
... ... @@ -57,4 +57,69 @@
57 57  )))
58 58  )))
59 59  
60 -
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.