Potent bace-1 inhibitor design using pharmacophore modeling, <it>in silico</it> screening and molecular docking studies

<p>Abstract</p> <p>Background</p> <p>Beta-site amyloid precursor protein cleaving enzyme (BACE-1) is a single-membrane protein belongs to the aspartyl protease class of catabolic enzymes. This enzyme involved in the processing of the amyloid precursor protein (APP). The...

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Main Authors: Lee Keun, Sakkiah Sugunadevi, Thangapandian Sundarapandian, John Shalini
Format: Article
Language:English
Published: BMC 2011-02-01
Series:BMC Bioinformatics
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spelling doaj-ce6a108518af4910b6d1920d1296daa62020-11-25T00:01:44ZengBMCBMC Bioinformatics1471-21052011-02-0112Suppl 1S2810.1186/1471-2105-12-S1-S28Potent bace-1 inhibitor design using pharmacophore modeling, <it>in silico</it> screening and molecular docking studiesLee KeunSakkiah SugunadeviThangapandian SundarapandianJohn Shalini<p>Abstract</p> <p>Background</p> <p>Beta-site amyloid precursor protein cleaving enzyme (BACE-1) is a single-membrane protein belongs to the aspartyl protease class of catabolic enzymes. This enzyme involved in the processing of the amyloid precursor protein (APP). The cleavage of APP by BACE-1 is the rate-limiting step in the amyloid cascade leading to the production of two peptide fragments Aβ<sub>40</sub> and Aβ<sub>42</sub>. Among two peptide fragments Aβ<sub>42</sub> is the primary species thought to be responsible for the neurotoxicity and amyloid plaque formation that lead to memory and cognitive defects in Alzheimer’s disease (AD). AD is a ravaging neurodegenerative disorder for which no disease-modifying treatment is currently available. Inhibition of BACE-1 is expected to stop amyloid plaque formation and emerged as an interesting and attractive therapeutic target for AD.</p> <p>Methods</p> <p>Ligand-based computational approach was used to identify the molecular chemical features required for the inhibition of BACE-1 enzyme. A training set of 20 compounds with known experimental activity was used to generate pharmacophore hypotheses using <it>3D QSAR Pharmacophore Generation</it> module available in Discovery studio. The hypothesis was validated by four different methods and the best hypothesis was utilized in database screening of four chemical databases like Maybridge, Chembridge, NCI and Asinex. The retrieved hit compounds were subjected to molecular docking study using GOLD 4.1 program.</p> <p>Results</p> <p>Among ten generated pharmacophore hypotheses, Hypo 1 was chosen as best pharmacophore hypothesis. Hypo 1 consists of one hydrogen bond donor, one positive ionizable, one ring aromatic and two hydrophobic features with high correlation coefficient of 0.977, highest cost difference of 121.98 bits and lowest RMSD value of 0.804. Hypo 1 was validated using Fischer randomization method, test set with a correlation coefficient of 0.917, leave-one-out method and decoy set with a goodness of hit score of 0.76. The validated Hypo 1 was used as a 3D query in database screening and retrieved 773 compounds with the estimated activity value <100 nM. These hits were docked into the active site of BACE-1 and further refined based on molecular interactions with the essential amino acids and good GOLD fitness score.</p> <p>Conclusion</p> <p>The best pharmacophore hypothesis, Hypo 1, with high predictive ability contains chemical features required for the effective inhibition of BACE-1. Using Hypo 1, we have identified two compounds with diverse chemical scaffolds as potential virtual leads which, as such or upon further optimization, can be used in the designing of new BACE-1 inhibitors.</p>
collection DOAJ
language English
format Article
sources DOAJ
author Lee Keun
Sakkiah Sugunadevi
Thangapandian Sundarapandian
John Shalini
spellingShingle Lee Keun
Sakkiah Sugunadevi
Thangapandian Sundarapandian
John Shalini
Potent bace-1 inhibitor design using pharmacophore modeling, <it>in silico</it> screening and molecular docking studies
BMC Bioinformatics
author_facet Lee Keun
Sakkiah Sugunadevi
Thangapandian Sundarapandian
John Shalini
author_sort Lee Keun
title Potent bace-1 inhibitor design using pharmacophore modeling, <it>in silico</it> screening and molecular docking studies
title_short Potent bace-1 inhibitor design using pharmacophore modeling, <it>in silico</it> screening and molecular docking studies
title_full Potent bace-1 inhibitor design using pharmacophore modeling, <it>in silico</it> screening and molecular docking studies
title_fullStr Potent bace-1 inhibitor design using pharmacophore modeling, <it>in silico</it> screening and molecular docking studies
title_full_unstemmed Potent bace-1 inhibitor design using pharmacophore modeling, <it>in silico</it> screening and molecular docking studies
title_sort potent bace-1 inhibitor design using pharmacophore modeling, <it>in silico</it> screening and molecular docking studies
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2011-02-01
description <p>Abstract</p> <p>Background</p> <p>Beta-site amyloid precursor protein cleaving enzyme (BACE-1) is a single-membrane protein belongs to the aspartyl protease class of catabolic enzymes. This enzyme involved in the processing of the amyloid precursor protein (APP). The cleavage of APP by BACE-1 is the rate-limiting step in the amyloid cascade leading to the production of two peptide fragments Aβ<sub>40</sub> and Aβ<sub>42</sub>. Among two peptide fragments Aβ<sub>42</sub> is the primary species thought to be responsible for the neurotoxicity and amyloid plaque formation that lead to memory and cognitive defects in Alzheimer’s disease (AD). AD is a ravaging neurodegenerative disorder for which no disease-modifying treatment is currently available. Inhibition of BACE-1 is expected to stop amyloid plaque formation and emerged as an interesting and attractive therapeutic target for AD.</p> <p>Methods</p> <p>Ligand-based computational approach was used to identify the molecular chemical features required for the inhibition of BACE-1 enzyme. A training set of 20 compounds with known experimental activity was used to generate pharmacophore hypotheses using <it>3D QSAR Pharmacophore Generation</it> module available in Discovery studio. The hypothesis was validated by four different methods and the best hypothesis was utilized in database screening of four chemical databases like Maybridge, Chembridge, NCI and Asinex. The retrieved hit compounds were subjected to molecular docking study using GOLD 4.1 program.</p> <p>Results</p> <p>Among ten generated pharmacophore hypotheses, Hypo 1 was chosen as best pharmacophore hypothesis. Hypo 1 consists of one hydrogen bond donor, one positive ionizable, one ring aromatic and two hydrophobic features with high correlation coefficient of 0.977, highest cost difference of 121.98 bits and lowest RMSD value of 0.804. Hypo 1 was validated using Fischer randomization method, test set with a correlation coefficient of 0.917, leave-one-out method and decoy set with a goodness of hit score of 0.76. The validated Hypo 1 was used as a 3D query in database screening and retrieved 773 compounds with the estimated activity value <100 nM. These hits were docked into the active site of BACE-1 and further refined based on molecular interactions with the essential amino acids and good GOLD fitness score.</p> <p>Conclusion</p> <p>The best pharmacophore hypothesis, Hypo 1, with high predictive ability contains chemical features required for the effective inhibition of BACE-1. Using Hypo 1, we have identified two compounds with diverse chemical scaffolds as potential virtual leads which, as such or upon further optimization, can be used in the designing of new BACE-1 inhibitors.</p>
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