Literature DB >> 17707666

Pharmacophore modeling and virtual screening studies to design some potential histone deacetylase inhibitors as new leads.

S Vadivelan1, B N Sinha, G Rambabu, Kiran Boppana, Sarma A R P Jagarlapudi.   

Abstract

Histone deacetylase is one of the important targets in the treatment of solid tumors and hematological cancers. A total of 20 well-defined inhibitors were used to generate Pharmacophore models using and HypoGen module of Catalyst. These 20 molecules broadly represent 3 different chemotypes. The best HypoGen model consists of four-pharmacophore features--one hydrogen bond acceptor, one hydrophobic aliphatic and two ring aromatic centers. This model was validated against 378 known HDAC inhibitors with a correlation of 0.897 as well as enrichment factor of 2.68 against a maximum value of 3. This model was further used to retrieve molecules from NCI database with 238,819 molecules. A total of 4638 molecules from a pool of 238,819 molecules were identified as hits while 297 molecules were indicated as highly active. Also, a Similarity analysis has been carried out for set of 4638 hits with respect to most active molecule of each chemotypes which validated not only the Virtual Screening potential of the model but also identified the possible new Chemotypes. This type of Similarity analysis would prove to be efficient not only for lead generation but also for lead optimization.

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Year:  2007        PMID: 17707666     DOI: 10.1016/j.jmgm.2007.07.002

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  19 in total

1.  Predictive QSAR workflow for the in silico identification and screening of novel HDAC inhibitors.

Authors:  Georgia Melagraki; Antreas Afantitis; Haralambos Sarimveis; Panayiotis A Koutentis; George Kollias; Olga Igglessi-Markopoulou
Journal:  Mol Divers       Date:  2009-02-10       Impact factor: 2.943

2.  Identification of novel, less toxic PTP-LAR inhibitors using in silico strategies: pharmacophore modeling, SADMET-based virtual screening and docking.

Authors:  Dara Ajay; M Elizabeth Sobhia
Journal:  J Mol Model       Date:  2011-04-27       Impact factor: 1.810

3.  Comparative modeling and benchmarking data sets for human histone deacetylases and sirtuin families.

Authors:  Jie Xia; Ermias Lemma Tilahun; Eyob Hailu Kebede; Terry-Elinor Reid; Liangren Zhang; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2015-02-09       Impact factor: 4.956

4.  Discovery of potent inhibitors for interleukin-2-inducible T-cell kinase: structure-based virtual screening and molecular dynamics simulation approaches.

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

Review 5.  Big Data and Artificial Intelligence Modeling for Drug Discovery.

Authors:  Hao Zhu
Journal:  Annu Rev Pharmacol Toxicol       Date:  2019-09-13       Impact factor: 13.820

6.  Pharmacophore-based virtual screening of ZINC database, molecular modeling and designing new derivatives as potential HDAC6 inhibitors.

Authors:  Priya Poonia; Monika Sharma; Prakash Jha; Madhu Chopra
Journal:  Mol Divers       Date:  2022-10-10       Impact factor: 3.364

7.  Exploration of structural and physicochemical requirements and search of virtual hits for aminopeptidase N inhibitors.

Authors:  Amit K Halder; Achintya Saha; Tarun Jha
Journal:  Mol Divers       Date:  2013-01-23       Impact factor: 2.943

Review 8.  Computer-aided Molecular Design of Compounds Targeting Histone Modifying Enzymes.

Authors:  Federico Andreoli; Alberto Del Rio
Journal:  Comput Struct Biotechnol J       Date:  2015-05-07       Impact factor: 7.271

9.  Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays.

Authors:  Zainab Noor; Noreen Afzal; Sajid Rashid
Journal:  PLoS One       Date:  2015-10-02       Impact factor: 3.240

10.  Dual binding site and selective acetylcholinesterase inhibitors derived from integrated pharmacophore models and sequential virtual screening.

Authors:  Shikhar Gupta; C Gopi Mohan
Journal:  Biomed Res Int       Date:  2014-06-25       Impact factor: 3.411

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