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Ma L, Zhao DX, Yang ZZ. A software tool for visualization of molecular face (VMF) by improving marching cubes algorithm. COMPUT THEOR CHEM 2014. [DOI: 10.1016/j.comptc.2013.11.021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Integrating structure-based and ligand-based approaches for computational drug design. Future Med Chem 2011; 3:735-50. [PMID: 21554079 DOI: 10.4155/fmc.11.18] [Citation(s) in RCA: 103] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.
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Tanrikulu Y, Schneider G. Pseudoreceptor models in drug design: bridging ligand- and receptor-based virtual screening. Nat Rev Drug Discov 2008; 7:667-77. [DOI: 10.1038/nrd2615] [Citation(s) in RCA: 66] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Bender A, Jenkins JL, Li Q, Adams SE, Cannon EO, Glen RC. Chapter 9 Molecular Similarity: Advances in Methods, Applications and Validations in Virtual Screening and QSAR. ACTA ACUST UNITED AC 2006; 2:141-168. [PMID: 32362803 PMCID: PMC7185533 DOI: 10.1016/s1574-1400(06)02009-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
This chapter discusses recent developments in some of the areas that exploit the molecular similarity principle, novel approaches to capture molecular properties by the use of novel descriptors, focuses on a crucial aspect of computational models-their validity, and discusses additional ways to examine data available, such as those from high-throughput screening (HTS) campaigns and to gain more knowledge from this data. The chapter also presents some of the recent applications of methods discussed focusing on the successes of virtual screening applications, database clustering and comparisons (such as drug- and in-house-likeness), and the recent large-scale validations of docking and scoring programs. While a great number of descriptors and modeling methods has been proposed until today, the recent trend toward proper model validation is very much appreciated. Although some of their limitations are surely because of underlying principles and limitations of fundamental concepts, others will certainly be eliminated in the future.
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Affiliation(s)
- Andreas Bender
- Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.,Lead Discovery Center, Novartis Institutes for BioMedical Research Inc., 250 Massachusetts Ave., Cambridge, MA 02139, USA
| | - Jeremy L Jenkins
- Lead Discovery Center, Novartis Institutes for BioMedical Research Inc., 250 Massachusetts Ave., Cambridge, MA 02139, USA
| | - Qingliang Li
- College of Chemistry and Molecular Engineering, Center for Theoretical Biology, Peking University, Beijing 100871, China
| | - Sam E Adams
- Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
| | - Edward O Cannon
- Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
| | - Robert C Glen
- Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
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