Literature DB >> 18402435

Indirect similarity based methods for effective scaffold-hopping in chemical compounds.

Nikil Wale1, Ian A Watson, George Karypis.   

Abstract

Methods that can screen large databases to retrieve a structurally diverse set of compounds with desirable bioactivity properties are critical in the drug discovery and development process. This paper presents a set of such methods that are designed to find compounds that are structurally different to a certain query compound while retaining its bioactivity properties (scaffold hops). These methods utilize various indirect ways of measuring the similarity between the query and a compound that take into account additional information beyond their structure-based similarities. The set of techniques that are presented capture these indirect similarities using approaches based on analyzing the similarity network formed by the query and the database compounds. Experimental evaluation shows that most of these methods substantially outperform previously developed approaches both in terms of their ability to identify structurally diverse active compounds as well as active compounds in general.

Mesh:

Year:  2008        PMID: 18402435      PMCID: PMC2575819          DOI: 10.1021/ci700369e

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  14 in total

1.  Similarity searching using reduced graphs.

Authors:  Valerie J Gillet; Peter Willett; John Bradshaw
Journal:  J Chem Inf Comput Sci       Date:  2003 Mar-Apr

2.  Do structurally similar molecules have similar biological activity?

Authors:  Yvonne C Martin; James L Kofron; Linda M Traphagen
Journal:  J Med Chem       Date:  2002-09-12       Impact factor: 7.446

3.  Enhancing the effectiveness of virtual screening by fusing nearest neighbor lists: a comparison of similarity coefficients.

Authors:  Martin Whittle; Valerie J Gillet; Peter Willett; Alexander Alex; Jens Loesel
Journal:  J Chem Inf Comput Sci       Date:  2004 Sep-Oct

4.  Comparison of topological descriptors for similarity-based virtual screening using multiple bioactive reference structures.

Authors:  Jérôme Hert; Peter Willett; David J Wilton; Pierre Acklin; Kamal Azzaoui; Edgar Jacoby; Ansgar Schuffenhauer
Journal:  Org Biomol Chem       Date:  2004-09-29       Impact factor: 3.876

5.  The reduced graph descriptor in virtual screening and data-driven clustering of high-throughput screening data.

Authors:  G Harper; G S Bravi; S D Pickett; J Hussain; D V S Green
Journal:  J Chem Inf Comput Sci       Date:  2004 Nov-Dec

6.  Using extended-connectivity fingerprints with Laplacian-modified Bayesian analysis in high-throughput screening follow-up.

Authors:  David Rogers; Robert D Brown; Mathew Hahn
Journal:  J Biomol Screen       Date:  2005-09-16

7.  Virtual screening of molecular databases using a support vector machine.

Authors:  Robert N Jorissen; Michael K Gilson
Journal:  J Chem Inf Model       Date:  2005 May-Jun       Impact factor: 4.956

8.  Lead hopping using SVM and 3D pharmacophore fingerprints.

Authors:  Jamal C Saeh; Paul D Lyne; Bryan K Takasaki; David A Cosgrove
Journal:  J Chem Inf Model       Date:  2005 Jul-Aug       Impact factor: 4.956

9.  New methods for ligand-based virtual screening: use of data fusion and machine learning to enhance the effectiveness of similarity searching.

Authors:  Jérôme Hert; Peter Willett; David J Wilton; Pierre Acklin; Kamal Azzaoui; Edgar Jacoby; Ansgar Schuffenhauer
Journal:  J Chem Inf Model       Date:  2006 Mar-Apr       Impact factor: 4.956

10.  Structural unit analysis identifies lead series and facilitates scaffold hopping in combinatorial chemistry.

Authors:  Philippa R N Wolohan; Lakshmi B Akella; Roman J Dorfman; Peter G Nell; Stefan M Mundt; Robert D Clark
Journal:  J Chem Inf Model       Date:  2006 May-Jun       Impact factor: 4.956

View more
  1 in total

1.  Target fishing for chemical compounds using target-ligand activity data and ranking based methods.

Authors:  Nikil Wale; George Karypis
Journal:  J Chem Inf Model       Date:  2009-10       Impact factor: 4.956

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.