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Molecular docking as a popular tool in drug design, an in silico travel

Overview of attention for article published in Advances and Applications in Bioinformatics and Chemistry : AABC, June 2016
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Title
Molecular docking as a popular tool in drug design, an in silico travel
Published in
Advances and Applications in Bioinformatics and Chemistry : AABC, June 2016
DOI 10.2147/aabc.s105289
Pubmed ID
Authors

Jerome de Ruyck, Guillaume Brysbaert, Ralf Blossey, Marc F Lensink

Abstract

New molecular modeling approaches, driven by rapidly improving computational platforms, have allowed many success stories for the use of computer-assisted drug design in the discovery of new mechanism-or structure-based drugs. In this overview, we highlight three aspects of the use of molecular docking. First, we discuss the combination of molecular and quantum mechanics to investigate an unusual enzymatic mechanism of a flavoprotein. Second, we present recent advances in anti-infectious agents' synthesis driven by structural insights. At the end, we focus on larger biological complexes made by protein-protein interactions and discuss their relevance in drug design. This review provides information on how these large systems, even in the presence of the solvent, can be investigated with the outlook of drug discovery.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 704 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 <1%
Italy 1 <1%
Austria 1 <1%
Argentina 1 <1%
China 1 <1%
Unknown 699 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 103 15%
Student > Ph. D. Student 99 14%
Student > Master 80 11%
Researcher 53 8%
Student > Doctoral Student 28 4%
Other 98 14%
Unknown 243 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 125 18%
Chemistry 112 16%
Pharmacology, Toxicology and Pharmaceutical Science 71 10%
Agricultural and Biological Sciences 49 7%
Engineering 15 2%
Other 71 10%
Unknown 261 37%