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- Volume 9, Issue 20, 2003
Current Pharmaceutical Design - Volume 9, Issue 20, 2003
Volume 9, Issue 20, 2003
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Pharmacophore Identification and Quantitative Bioactivity Prediction Using the Electron-Conformational Method
More LessA review of the Electron-Conformational (EC) method of pharmacophore (Pha) identification and quantitative bioactivity prediction in drug design and toxicology is presented, which includes the latest advances and improvements of the method as a whole and details of its realization with illustration of results. In the first part devoted to Pha identification the data of conformational analysis and electronic structure calculatio Read More
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Pharmacophores for Ligand Recognition and Activation / Inactivation of the Cannabinoid Receptors
More LessThe cannabinoid CB1 and CB2 receptors belong to the Class A, rhodopsin-like family of G protein-coupled receptors. Antagonists for each receptor sub-type, as well as four structural classes of agonists that bind to both receptors, have been identified. An extensive amount of SAR has been developed for agonists and antagonists that bind at CB1, while the SAR of CB2 ligands is only now emerging in the literature. Cannabinoi Read More
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Conformational Flexibility Models for the Receptor in Structure Based Drug Design
Authors: M. L. Teodoro and L. E. KavrakiThe problem of incorporating receptor flexibility in routine in silico screening of databases of small chemical compounds for the purposes of structure based drug design is still an unsolved problem. The main reason behind this difficulty is the large number of degrees of freedom that have to be considered to represent receptor flexibility. In this paper we review protein flexibility models that have been developed to limit the Read More
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Pharmacophore Discovery - Lessons Learned
More LessPharmacophore discovery is one of the major elements of molecular modeling in the absence of X-ray structural data. While pharmacophores initially made their debut as a means for lead discovery, more recent refinements have brought them into the domain of lead optimization, e.g. as a means to define the molecular alignment in 3D-QSAR. In this review, the experiences of over a decade of confronting and solving the Read More
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Volumes & issues
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Volume 31 (2025)
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Volume 30 (2024)
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Volume 29 (2023)
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Volume 28 (2022)
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Volume 27 (2021)
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Volume 26 (2020)
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Volume 25 (2019)
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Volume 24 (2018)
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Volume 23 (2017)
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Volume 22 (2016)
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Volume 21 (2015)
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Volume 20 (2014)
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Volume 19 (2013)
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Volume 18 (2012)
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Volume 17 (2011)
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Volume 16 (2010)
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Volume 15 (2009)
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Volume 14 (2008)
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Volume 13 (2007)
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Volume 12 (2006)
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Volume 11 (2005)
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Volume 10 (2004)
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Volume 9 (2003)
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Volume 8 (2002)
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Volume 7 (2001)
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Volume 6 (2000)
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