dbtop:: Toporner similarity searching of conventional structure databases

被引:45
|
作者
Cramer, RD [1 ]
Jilek, RJ [1 ]
Andrews, KM [1 ]
机构
[1] Tripos Inc, St Louis, MO 63144 USA
来源
关键词
topomers; 3D database searching; pharmacophoric features; similarity searching; HTS data analysis; PDE4; inhibitors; serotonin receptor modulators; dbtop;
D O I
10.1016/S1093-3263(01)00146-2
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
A new topomer-based method for 3D searching of conventional structural databases is described, according to which 3D molecular structures are compared as sets of fragments or topomers, in single rule-generated conformations oriented by superposition of their fragmentation bonds. A topomer is characterized by its CoMFA-like steric shape and now also by its pharmacophoric features, in some novel ways that are detailed and discussed. To illustrate the behavior of topomer similarity searching, a new dbtop program was used to generate a topomer distance matrix for a diverse set of 26 PDE4 inhibitors and 15 serotonin receptor modulators. With the best of three parameter settings tried, within the 210 shortest topomer distances (of 1460), 94.7% involved pairs of compounds having the same biological activity, and the nearest neighbor to every compound also shared its activity. The standard similarity metric, Tanimoto coefficients of "2D fingerprints", could achieve a similar selectivity performance only for the 108 shortest distances, and three Tanimoto nearest neighbors had a different biological activity. Topomer similarity also allowed "lead-hopping" among 22 of the 26 PDE4 inhibitors, notably between rolipram and cipamfylline, while "2D fingerprints" Tanimotos recognized similarity only within generally recognized structural classes. In 370 searches of authentic high-throughput screening (HTS) data sets, the typical topomer similarity search rate was about 200 structures per s. (C) 2002 Elsevier Science Inc. All rights reserved.
引用
收藏
页码:447 / 462
页数:16
相关论文
共 50 条
  • [41] SEARCHING THE ENGINEERING DATABASES
    ANDERSON, VN
    DATABASE, 1987, 10 (02): : 23 - 27
  • [42] SEARCHING THE BIOSIS DATABASES
    FLIS, BJ
    DATABASE, 1990, 13 (02): : 89 - 90
  • [43] Searching Databases with keywords
    Wang, S
    Zhang, KL
    JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2005, 20 (01) : 55 - 62
  • [44] Searching Databases with Keywords
    Shan Wang
    Kun-Long Zhang
    Journal of Computer Science and Technology, 2005, 20 : 55 - 62
  • [45] DEVELOPMENT OF AN ATOM MAPPING PROCEDURE FOR SIMILARITY SEARCHING IN DATABASES OF 3-DIMENSIONAL CHEMICAL STRUCTURES
    PEPPERRELL, CA
    POIRRETTE, AR
    WILLETT, P
    TAYLOR, R
    PESTICIDE SCIENCE, 1991, 33 (01): : 97 - 111
  • [46] An adaptive index structure for similarity search in large image databases
    Wu, P
    Manjunath, BS
    INTERNET MULTIMEDIA MANAGEMENT SYSTEMS II, 2001, 4519 : 32 - 41
  • [47] Fast similarity search in three-dimensional structure databases
    Wang, X
    Wang, JTL
    JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2000, 40 (02): : 442 - 451
  • [48] An index structure for pattern similarity searching in DNA microarray data
    Wang, HX
    Perng, CS
    Fan, W
    Yu, PS
    CSB2002: IEEE COMPUTER SOCIETY BIOINFORMATICS CONFERENCE, 2002, : 256 - 267
  • [49] Chemical similarity searching
    Willett, P
    Barnard, JM
    Downs, GM
    JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1998, 38 (06): : 983 - 996
  • [50] Turbo similarity searching
    Hert, J
    Willett, P
    Wilton, D
    Azzaoui, K
    Jacoby, E
    Schuffenhauer, A
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2005, 230 : U1020 - U1021