Literature DB >> 12431058

A new approach to finding natural chemical structure classes.

Jun Xu1.   

Abstract

In modern drug discovery, large compound libraries need to be compared and the diversity of compound libraries needs to be analyzed. Classification algorithms are important tools for accomplishing these tasks. In this paper, a chemical structural scaffold based classification approach is reported. The goals of the approach are to find natural structure families from a large (millions of entries) compound library within a feasible time period and to view the library in two-dimensional data space using chemically meaningful methods.

Mesh:

Year:  2002        PMID: 12431058     DOI: 10.1021/jm010520k

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  30 in total

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2.  Activity cliffs and activity cliff generators based on chemotype-related activity landscapes.

Authors:  Jaime Pérez-Villanueva; Oscar Méndez-Lucio; Olivia Soria-Arteche; José L Medina-Franco
Journal:  Mol Divers       Date:  2015-07-07       Impact factor: 2.943

3.  Crystal structure-based virtual screening for fragment-like ligands of the human histamine H(1) receptor.

Authors:  Chris de Graaf; Albert J Kooistra; Henry F Vischer; Vsevolod Katritch; Martien Kuijer; Mitsunori Shiroishi; So Iwata; Tatsuro Shimamura; Raymond C Stevens; Iwan J P de Esch; Rob Leurs
Journal:  J Med Chem       Date:  2011-11-07       Impact factor: 7.446

4.  Toward automated biochemotype annotation for large compound libraries.

Authors:  Xian Chen; Yizeng Liang; Jun Xu
Journal:  Mol Divers       Date:  2006-09-12       Impact factor: 2.943

5.  Leadlikeness and structural diversity of synthetic screening libraries.

Authors:  Herman J Verheij
Journal:  Mol Divers       Date:  2006-09-21       Impact factor: 2.943

6.  ScafBank: a public comprehensive Scaffold database to support molecular hopping.

Authors:  Bi-Bo Yan; Meng-Zhu Xue; Bing Xiong; Ke Liu; Ding-Yu Hu; Jing-Kang Shen
Journal:  Acta Pharmacol Sin       Date:  2009-01-19       Impact factor: 6.150

7.  Predicting DPP-IV inhibitors with machine learning approaches.

Authors:  Jie Cai; Chanjuan Li; Zhihong Liu; Jiewen Du; Jiming Ye; Qiong Gu; Jun Xu
Journal:  J Comput Aided Mol Des       Date:  2017-02-02       Impact factor: 3.686

8.  Machine Learning Platform to Discover Novel Growth Inhibitors of Neisseria gonorrhoeae.

Authors:  Janaina Cruz Pereira; Samer S Daher; Kimberley M Zorn; Matthew Sherwood; Riccardo Russo; Alexander L Perryman; Xin Wang; Madeleine J Freundlich; Sean Ekins; Joel S Freundlich
Journal:  Pharm Res       Date:  2020-07-13       Impact factor: 4.200

9.  Computer-aided drug discovery research at a global contract research organization.

Authors:  Douglas B Kitchen
Journal:  J Comput Aided Mol Des       Date:  2016-11-01       Impact factor: 3.686

10.  Discovery of indoleamine 2,3-dioxygenase inhibitors using machine learning based virtual screening.

Authors:  Hongao Zhang; Wei Liu; Zhihong Liu; Yingchen Ju; Mengyang Xu; Yue Zhang; Xinyu Wu; Qiong Gu; Zhong Wang; Jun Xu
Journal:  Medchemcomm       Date:  2018-03-01       Impact factor: 3.597

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