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Identification of Novel HIV 1- Protease Inhibitors: Application of Ligand and Structure Based Pharmacophore Mapping and Virtual Screening

Overview of attention for article published in PLOS ONE, November 2012
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Title
Identification of Novel HIV 1- Protease Inhibitors: Application of Ligand and Structure Based Pharmacophore Mapping and Virtual Screening
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0048942
Pubmed ID
Authors

Divya Yadav, Sarvesh Paliwal, Rakesh Yadav, Mahima Pal, Anubhuti Pandey

Abstract

A combined ligand and structure-based drug design approach provides a synergistic advantage over either methods performed individually. Present work bestows a good assembly of ligand and structure-based pharmacophore generation concept. Ligand-oriented study was accomplished by employing the HypoGen module of Catalyst in which we have translated the experimental findings into 3-D pharmacophore models by identifying key features (four point pharmacophore) necessary for interaction of the inhibitors with the active site of HIV-1 protease enzyme using a training set of 33 compounds belonging to the cyclic cyanoguanidines and cyclic urea derivatives. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, two hydrogen bond acceptors and two hydrophobic, showed a correlation (r) of 0.90 and a root mean square of 0.71 and cost difference of 56.59 bits between null cost and fixed cost. The model was validated using CatScramble technique, internal and external test set prediction. In the second phase of our study, a structure-based five feature pharmacophore hypothesis was generated which signifies the importance of hydrogen bond donor, hydrogen bond acceptors and hydrophobic interaction between the HIV-1 protease enzyme and its inhibitors. This work has taken a significant step towards the full integration of ligand and structure-based drug design methodologies as pharmacophoric features retrieved from structure-based strategy complemented the features from ligand-based study hence proving the accuracy of the developed models. The ligand-based pharmacophore model was used in virtual screening of Maybridge and NCI compound database resulting in the identification of four structurally diverse druggable compounds with nM activities.

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Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
United States 1 2%
Romania 1 2%
Unknown 52 95%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 16%
Student > Ph. D. Student 7 13%
Student > Doctoral Student 6 11%
Student > Master 6 11%
Researcher 4 7%
Other 13 24%
Unknown 10 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 24%
Biochemistry, Genetics and Molecular Biology 9 16%
Chemistry 7 13%
Pharmacology, Toxicology and Pharmaceutical Science 4 7%
Computer Science 3 5%
Other 8 15%
Unknown 11 20%