Autocorrelation Descriptor Improvements for QSAR:
2DA_Sign and 3DA_Sign
Gregory Sliwoski, Jeffrey Mendenhall, Jens Meiler
Supplemental Figures
Supplemental Figure S1: Percent of neutral actives does not correlate with
performance increase across datasets. Nine tested datasets vary significantly in
the percent of active compounds that are neutral. This variability does not appear
to correlate with performance increase (as measured by logAUC) when using
novel 2DA/3DA_Sign descriptors (2DA: r = 0.10, 3DA: r = 0.18, n = 9).
Supplemental Figure S2: Percent of actives with positive formal charge
correlates with performance increase with signed 3DA only. Percent of active
compounds with positive formal charge varies across nine tested datasets.
Variation does not correlate with performance increase when using 2DA_Sign (r =
-0.24, n=9). However, there is a statistically significant negative correlation
between percent of actives with positive formal charge and performance increase
with 3DA_Sign (r = -0.67, n=9, one-tailed p < .05).
Supplemental Figure S3: Percent of actives with negative formal charge
correlates with performance increase with signed 3DA only. Percent of active
compounds with negative formal charge varies across nine tested datasets.
Variation does not correlate with performance increase when using 2DA_Sign (r =
0.12, n=9). However, there is a statistically significant positive correlation
between percent of actives with positive formal charge and performance increase
with 3DA_Sign (r = 0.67, n=9, one-tailed p < .05).
Supplemental Figure S4: Percent of zwitterion actives does not correlate with
performance increase across datasets. Nine tested datasets vary slightly in the
percent of active compounds that are zwitterions. Variation does not correlate
with performance increase with 2DA/3DA_Sign descriptors (2DA: r = -0.26, 3DA: r
= 0.04, n=9).