Literature DB >> 18498326

Virtual screening of cathepsin k inhibitors using docking and pharmacophore models.

Muttineni Ravikumar1, S Pavan, Santhosh Bairy, A B Pramod, M Sumakanth, Madala Kishore, Tirunagaram Sumithra.   

Abstract

Cathepsin K is a lysosomal cysteine protease that is highly and selectively expressed in osteoclasts, the cells which degrade bone during the continuous cycle of bone degradation and formation. Inhibition of cathepsin K represents a potential therapeutic approach for diseases characterized by excessive bone resorption such as osteoporosis. In order to elucidate the essential structural features for cathepsin K, a three-dimensional pharmacophore hypotheses were built on the basis of a set of known cathepsin K inhibitors selected from the literature using catalyst program. Several methods are used in validation of pharmacophore hypothesis were presented, and the fourth hypothesis (Hypo4) was considered to be the best pharmacophore hypothesis which has a correlation coefficient of 0.944 with training set and has high prediction of activity for a set of 30 test molecules with correlation of 0.909. The model (Hypo4) was then employed as 3D search query to screen the Maybridge database containing 59,000 compounds, to discover novel and highly potent ligands. For analyzing intermolecular interactions between protein and ligand, all the molecules were docked using Glide software. The result showed that the type and spatial location of chemical features encoded in the pharmacophore are in full agreement with the enzyme inhibitor interaction pattern identified from molecular docking.

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Year:  2008        PMID: 18498326     DOI: 10.1111/j.1747-0285.2008.00667.x

Source DB:  PubMed          Journal:  Chem Biol Drug Des        ISSN: 1747-0277            Impact factor:   2.817


  5 in total

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Authors:  Chandrasekaran Meganathan; Sugunadevi Sakkiah; Yuno Lee; Jayavelu Venkat Narayanan; Keun Woo Lee
Journal:  J Mol Model       Date:  2012-09-27       Impact factor: 1.810

2.  3D QSAR pharmacophore model based on diverse IKKβ inhibitors.

Authors:  Shanthi Nagarajan; Asif Ahmed; Hyunah Choo; Yong Seo Cho; Kwang-Seok Oh; Byung Ho Lee; Kye Jung Shin; Ae Nim Pae
Journal:  J Mol Model       Date:  2010-04-25       Impact factor: 1.810

3.  Residue-specific annotation of disorder-to-order transition and cathepsin inhibition of a propeptide-like crammer from D. melanogaster.

Authors:  Tien-Sheng Tseng; Chao-Sheng Cheng; Shang-Te Danny Hsu; Min-Fang Shih; Pei-Lin He; Ping-Chiang Lyu
Journal:  PLoS One       Date:  2013-01-21       Impact factor: 3.240

4.  Accelerating Multiple Compound Comparison Using LINGO-Based Load-Balancing Strategies on Multi-GPUs.

Authors:  Chun-Yuan Lin; Chung-Hung Wang; Che-Lun Hung; Yu-Shiang Lin
Journal:  Int J Genomics       Date:  2015-10-13       Impact factor: 2.326

5.  New compounds identified through in silico approaches reduce the α-synuclein expression by inhibiting prolyl oligopeptidase in vitro.

Authors:  Raj Kumar; Rohit Bavi; Min Gi Jo; Venkatesh Arulalapperumal; Ayoung Baek; Shailima Rampogu; Myeong Ok Kim; Keun Woo Lee
Journal:  Sci Rep       Date:  2017-09-07       Impact factor: 4.379

  5 in total

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