Literature DB >> 19184499

Fragment-based QSAR: perspectives in drug design.

Lívia B Salum1, Adriano D Andricopulo.   

Abstract

Drug design is a process driven by innovation and technological breakthroughs involving a combination of advanced experimental and computational methods. A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of leads, as well as to accelerate the optimization of leads into drug candidates. Quantitative structure-activity relationship (QSAR) methods are among the most important strategies that can be applied for the successful design of small molecule modulators having clinical utility. Hologram QSAR (HQSAR) is a modern 2D fragment-based QSAR method that employs specialized molecular fingerprints. HQSAR can be applied to large data sets of compounds, as well as traditional-size sets, being a versatile tool in drug design. The HQSAR approach has evolved from a classical use in the generation of standard QSAR models for data correlation and prediction into advanced drug design tools for virtual screening and pharmacokinetic property prediction. This paper provides a brief perspective on the evolution and current status of HQSAR, highlighting present challenges and new opportunities in drug design.

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Year:  2009        PMID: 19184499     DOI: 10.1007/s11030-009-9112-5

Source DB:  PubMed          Journal:  Mol Divers        ISSN: 1381-1991            Impact factor:   2.943


  55 in total

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Authors:  Lívia B Salum; Igor Polikarpov; Adriano D Andricopulo
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9.  Structural and chemical basis for enhanced affinity and potency for a large series of estrogen receptor ligands: 2D and 3D QSAR studies.

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10.  Structure-activity relationships for a class of selective inhibitors of the major cysteine protease from Trypanosoma cruzi.

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  15 in total

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6.  Ligand biological activity predictions using fingerprint-based artificial neural networks (FANN-QSAR).

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7.  Two- and three-dimensional QSAR studies on hURAT1 inhibitors with flexible linkers: topomer CoMFA and HQSAR.

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Journal:  Mol Divers       Date:  2019-03-13       Impact factor: 2.943

8.  Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening.

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Review 10.  Physiologically based pharmacokinetic models: integration of in silico approaches with micro cell culture analogues.

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Journal:  Curr Drug Metab       Date:  2012-07       Impact factor: 3.731

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