Abstract:
Euclidean distance matrix analysis (EDMA) methods are used to distinguish whether
or not significant difference exists between conformational samples of antibody
complementarity determining region (CDR) loops, isolated LI loop and LI in three-loop
assembly (LI, L3 and H3) obtained from Monte Carlo simulation. After the significant
difference is detected, the specific inter-Ca distance which contributes to the difference is
identified using EDMA.The estimated and improved mean forms of the conformational samples of isolated
LI loop and LI loop in three-loop assembly, CDR loops of antibody binding site, are
described using EDMA and distance geometry (DGEOM). To the best of our knowledge,
it is the first time the EDMA methods are used to analyze conformational samples of
molecules obtained from Monte Carlo simulations. Therefore, validations of the EDMA
methods using both positive control and negative control tests for the conformational
samples of isolated LI loop and LI in three-loop assembly must be done.
The EDMA-I bootstrap null hypothesis tests showed false positive results for the
comparison of six samples of the isolated LI loop and true positive results for
comparison of conformational samples of isolated LI loop and LI in three-loop assembly.
The bootstrap confidence interval tests revealed true negative results for comparisons of
six samples of the isolated LI loop, and false negative results for the conformational
comparisons between isolated LI loop and LI in three-loop assembly. Different
conformational sample sizes are further explored by combining the samples of isolated
LI loop to increase the sample size, or by clustering the sample using self-organizing
map (SOM) to narrow the conformational distribution of the samples being comparedmolecular conformations. However, there is no improvement made for both bootstrap
null hypothesis and confidence interval tests. These results show that more work is
required before EDMA methods can be used reliably as a method for comparison of
samples obtained by Monte Carlo simulations.
