Introduction

The material on this page present test runs of the ASC molecular surface computation software. The tests were done on a Pentium II 266 Mhz with 128RAM and RedHat 7.3 Operating System. As input the pdb structures in column(1) from table 1 are used. We are going to investigate the relationship between the number of atoms in the pdb structure and the time necessary to compute the molecular surface. Column(3) gives informaiton for the number of atoms in the molecule as given in the pdb file while column(2) is the number of atoms ASC selected from the pdb and used in the actual calculation. In the results at the end column(2) is used. Column(4) from Table 1 shows the computed molecular surface.

Test

Table 1

Input Structure

Num of Atoms ASC

Num of Atoms PDB
Computed Surface
Time
4INS.pdb
806
1158
6,072.619
0:00:00,48
1MX2.pdb
2375
2567
15,713.375
0:00:01,50
1A4G.pdb
6072
6641
2,7230.447
0:00:04,52
1AFV.pdb
9022
9024
52,541.226
0:00:06,24
1IYJ.pdb
10,092
10,092
61,247.224
0:00:07,01
1IAS.pdb
13,106
13,187
73,650.333
0:00:09,04
1M2O.pdb
13,884
14,123
72,060.265
0:00:09,95
1I84.pdb
16,492
16,580
114,438.048
0:00:11,93
1jmu.pdb
23,268
23,657
96,523.548
0:00:19,52
2btv.pdb
49,061
49,061
219,625.206
check_topol: reallocation 1, max_at_que incremented ...!
0:00:40,32
1M8Q.pdb
74892
76,872
436,460.096
liquvx is enlarged - mnquvx = 120 ...!
check_topol: reallocation 1, max_at_que incremented 0:00:57,34

 

Results

Fitting the produced results to a curve with DataFit software I came up with the following results:

n*Log(n)
DataFit version 8.0.32
Results from project "Untitled1"
Equation ID: a+b*x*log(x)
Model Definition:
Y = a+b*x*log(x)
Number of observations = 11
Number of missing observations = 0
Solver type: Nonlinear
Nonlinear iteration limit = 250
Diverging nonlinear iteration limit =10
Number of nonlinear iterations performed = 1
Residual tolerance = 0.0000000001
Sum of Residuals = 2.66453525910038E-15
Average Residual = 2.42230478100034E-16
Residual Sum of Squares (Absolute) = 17.8415994549841
Residual Sum of Squares (Relative) = 17.8415994549841
Standard Error of the Estimate = 1.40797725103877
Coefficient of Multiple Determination (R^2) = 0.9943671285
Proportion of Variance Explained = 99.43671285%
Adjusted coefficient of multiple determination (Ra^2) = 0.9937412539
Durbin-Watson statistic = 1.56762730765125
Regression Variable Results
Variable Value Standard Error t-ratio Prob(t)
a 0.868451493 0.557283673 1.55836522 0.15358
b 6.96355E-05 1.74703E-06 39.85930403 0.0
68% Confidence Intervals
Variable Value 68% (+/-) Lower Limit Upper Limit
a 0.868451493 0.586541066 0.281910428 1.454992559
b 6.96355E-05 1.83875E-06 6.77967E-05 7.14742E-05
90% Confidence Intervals
Variable Value 90% (+/-) Lower Limit Upper Limit
a 0.868451493 1.021556701 -0.153105208 1.890008194
b 6.96355E-05 3.20248E-06 6.6433E-05 7.2838E-05
95% Confidence Intervals
Variable Value 95% (+/-) Lower Limit Upper Limit
a 0.868451493 1.260687125 -0.392235632 2.129138618
b 6.96355E-05 3.95214E-06 6.56833E-05 7.35876E-05
99% Confidence Intervals
Variable Value 99% (+/-) Lower Limit Upper Limit
a 0.868451493 1.81106048 -0.942608987 2.679511974
b 6.96355E-05 5.6775E-06 6.3958E-05 7.5313E-05
Variance Analysis
Source DF Sum of Squares Mean Square F Ratio Prob(F)
Regression 1 3149.565891 3149.565891 1588.764118 0
Error 9 17.84159945 1.982399939
Total 10 3167.407491

n+nLog(n)


DataFit version 8.0.32
Results from project "Untitled1"
Equation ID: a+b*x+c*x*log(x)
Model Definition:
Y = a+b*x+c*x*log(x)
Number of observations = 11
Number of missing observations = 0
Solver type: Nonlinear
Nonlinear iteration limit = 250
Diverging nonlinear iteration limit =10
Number of nonlinear iterations performed = 11
Residual tolerance = 0.0000000001
Sum of Residuals = -8.12692135809812E-11
Average Residual = -7.38811032554374E-12
Residual Sum of Squares (Absolute) = 9.64649945688396
Residual Sum of Squares (Relative) = 9.64649945688396
Standard Error of the Estimate = 1.09809491033812
Coefficient of Multiple Determination (R^2) = 0.9969544495
Proportion of Variance Explained = 99.69544495%
Adjusted coefficient of multiple determination (Ra^2) = 0.9961930619
Durbin-Watson statistic = 1.41251328998518
Regression Variable Results
Variable Value Standard Error t-ratio Prob(t)
a -1.113906053 0.875853383 -1.271795114 0.23917
b 0.001172319 0.000449685 2.606977303 0.03128
c -3.37481E-05 3.96799E-05 -0.850509113 0.41977
68% Confidence Intervals
Variable Value 68% (+/-) Lower Limit Upper Limit
a -1.113906053 0.928579757 -2.04248581 -0.185326296
b 0.001172319 0.000476756 0.000695563 0.001649076
c -3.37481E-05 4.20686E-05 -7.58167E-05 8.32051E-06
90% Confidence Intervals
Variable Value 90% (+/-) Lower Limit Upper Limit
a -1.113906053 1.628649366 -2.742555419 0.514743313
b 0.001172319 0.00083619 0.00033613 0.002008509
c -3.37481E-05 7.37848E-05 -0.000107533 4.00367E-05
95% Confidence Intervals
Variable Value 95% (+/-) Lower Limit Upper Limit
a -1.113906053 2.019717902 -3.133623955 0.905811849
b 0.001172319 0.001036974 0.000135345 0.002209294
c -3.37481E-05 9.15018E-05 -0.00012525 5.77537E-05
99% Confidence Intervals
Variable Value 99% (+/-) Lower Limit Upper Limit
a -1.113906053 2.938838442 -4.052744495 1.824932389
b 0.001172319 0.001508874 -0.000336555 0.002681193
c -3.37481E-05 0.000133142 -0.00016689 9.93938E-05
Variance Analysis
Source DF Sum of Squares Mean Square F Ratio Prob(F)
Regression 2 3157.760991 1578.880496 1309.391456 0
Error 8 9.646499457 1.205812432
Total 10 3167.407491

 

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