Assessing how well a modeling protocol captures a structure-activity landscape

被引:61
作者
Guha, Rajarshi [2 ]
Van Drie, John H. [1 ]
机构
[1] Van Drie Res LLC, Andover, MA 01810 USA
[2] Indiana Univ, Sch Informat, Bloomington, IN 47406 USA
关键词
D O I
10.1021/ci8001414
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
We introduce the notion of structure-activity landscape index (SALI) curves as a way to assess a model and a modeling protocol, applied to structure-activity relationships. We start from our earlier work [J. Chem. Inf. Model., 2008, 48, 646-658], where we show how to study a structure-activity relationship pairwise, based on the notion of "activity cliffs"pairs of molecules that are structurally similar but have large differences in activity. There, we also introduced the SALI parameter, which allows one to identify cliffs easily, and which allows one to represent a structure-activity relationship as a graph. This graph orders every pair of molecules by their activity. Here, we introduce the new idea of a SALI curve, which tallies how many of these orderings a model is able to predict. Empirically, testing these SALI curves against a variety of models, ranging over two-dimensional quantitative structure-activity relationship (2D-QSAR), three-dimensional quantitative structure-activity relationship (3D-QSAR), and structure-based design models, the utility of a model seems to correspond to characteristics of these curves. In particular, the integral of these curves, denoted as SCI and being a number ranging from-1.0 to 1.0, approaches a value of 1.0 for two literature models, which are both known to be prospectively useful.
引用
收藏
页码:1716 / 1728
页数:13
相关论文
共 36 条
[11]  
GUHA R, SALI VIEWER
[12]   Structure-activity landscape index: Identifying and quantifying activity cliffs [J].
Guha, Rajarshi ;
Van Drie, John H. .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2008, 48 (03) :646-658
[13]   A-PRIORI PREDICTION OF ACTIVITY FOR HIV-1 PROTEASE INHIBITORS EMPLOYING ENERGY MINIMIZATION IN THE ACTIVE-SITE [J].
HOLLOWAY, MK ;
WAI, JM ;
HALGREN, TA ;
FITZGERALD, PMD ;
VACCA, JP ;
DORSEY, BD ;
LEVIN, RB ;
THOMPSON, WJ ;
CHEN, LJ ;
DESOLMS, SJ ;
GAFFIN, N ;
GHOSH, AK ;
GIULIANI, EA ;
GRAHAM, SL ;
GUARE, JP ;
HUNGATE, RW ;
LYLE, TA ;
SANDERS, WM ;
TUCKER, TJ ;
WIGGINS, M ;
WISCOUNT, CM ;
WOLTERSDORF, OW ;
YOUNG, SD ;
DARKE, PL ;
ZUGAY, JA .
JOURNAL OF MEDICINAL CHEMISTRY, 1995, 38 (02) :305-317
[14]  
Kier L.H., 1986, Molecular Connectivity in Structure-Activity Analysis
[15]   Three-dimensional quantitative similarity-activity relationships (3D QSiAR) from SEAL similarity matrices [J].
Kubinyi, H ;
Hamprecht, FA ;
Mietzner, T .
JOURNAL OF MEDICINAL CHEMISTRY, 1998, 41 (14) :2553-2564
[16]   Drug research: myths, hype and reality [J].
Kubinyi, H .
NATURE REVIEWS DRUG DISCOVERY, 2003, 2 (08) :665-668
[17]   Approach to estimation and prediction for normal boiling point (NBP) of alkanes based on a novel molecular distance-edge (MDE) vector, λ [J].
Liu, SS ;
Cao, CZ ;
Li, ZL .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1998, 38 (03) :387-394
[18]   On outliers and activity cliffs - Why QSAR often disappoints [J].
Maggiora, Gerald M. .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2006, 46 (04) :1535-1535
[19]  
Norinder U, 1996, J CHEMOMETR, V10, P95, DOI 10.1002/(SICI)1099-128X(199603)10:2<95::AID-CEM407>3.0.CO
[20]  
2-M