. Author manuscript; available in PMC: 2012 Jun 1.

Published in final edited form as: Bioorg Med Chem. 2011 Apr 24;19(11):3347–3356. doi: 10.1016/j.bmc.2011.04.042

Table 5.

Analysis of the effect of different fragment distinction sets on HQSAR models.

Model	Fragment distinction ^a	q²^b	SE ^c	r²^d	SE ^c	Components	HL ^e
7	None	0.193	0.502	0.408	0.430	6	353
8	A	0.046	0.529	0.256	0.467	6	353
9	A B	0.333	0.442	0.574	0.353	2	353
10	A B C	0.237	0.476	0.572	0.357	3	97
11	A B C H	0.250	0.484	0.705	0.303	6	151
12	A B C D	0.361	0.443	0.793	0.252	5	199
13	A B C H D	0.250	0.484	0.773	0.266	6	199
14	A B H	0.268	0.467	0.522	0.377	3	353
15	A B H D	0.212	0.496	0.794	0.254	6	151
16	A B D	0.082	0.535	0.788	0.257	6	257
17	A C	0.250	0.472	0.588	0.350	3	353
18	A C H	0.281	0.473	0.734	0.288	6	257
19	A C H D	0.201	0.491	0.659	.0321	4	199
20	A C D	0.322	0.456	0.734	0.285	5	97
21	A D	0.028	0.551	0.683	0.314	6	257
22	A H D	0.199	0.488	0.472	0.396	3	199

Footnotes.

Fragment distinction; molecular features to be used in distinguishing among fragments, include A, atom, B, bond, C, connections, H, hydrogens, D, donor acceptor.

q², cross validated r².

SE, standard error.

r², non-cross-validated correlation coefficient. All models were generated using a fragment atom count range of 4 to 7 and selected based on best cross-validated r².

HL, Hologram Length.