Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents
Favourite N Cele, Muthusamy Ramesh, Mahmoud ES Soliman Molecular Modelling and Drug Design Research Group, School of Health Sciences, University of KwaZulu-Natal, Durban, South Africa Abstract: A novel virtual screening approach is implemented herein, which is a further improvement of our previous...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Dove Medical Press
2016-04-01
|
| Series: | Drug Design, Development and Therapy |
| Subjects: | |
| Online Access: | https://www.dovepress.com/per-residue-energy-decomposition-pharmacophore-model-to-enhance-virtua-peer-reviewed-article-DDDT |
| _version_ | 1818531607346151424 |
|---|---|
| author | Cele FN Ramesh M Soliman ME |
| author_facet | Cele FN Ramesh M Soliman ME |
| author_sort | Cele FN |
| collection | DOAJ |
| description | Favourite N Cele, Muthusamy Ramesh, Mahmoud ES Soliman Molecular Modelling and Drug Design Research Group, School of Health Sciences, University of KwaZulu-Natal, Durban, South Africa Abstract: A novel virtual screening approach is implemented herein, which is a further improvement of our previously published “target-bound pharmacophore modeling approach”. The generated pharmacophore library is based only on highly contributing amino acid residues, instead of arbitrary pharmacophores, which are most commonly used in the conventional approaches in literature. Highly contributing amino acid residues were distinguished based on free binding energy contributions obtained from calculation from molecular dynamic (MD) simulations. To the best of our knowledge; this is the first attempt in the literature using such an approach; previous approaches have relied on the docking score to generate energy-based pharmacophore models. However, docking scores are reportedly unreliable. Thus, we present a model for a per-residue energy decomposition, constructed from MD simulation ensembles generating a more trustworthy pharmacophore model, which can be applied in drug discovery workflow. This work is aimed at introducing a more rational approach to the field of drug design, rather than comparing the validity of this approach against those previously reported. We recommend additional computational and experimental work to further validate this approach. This approach was used to screen for potential reverse transcriptase inhibitors using the pharmacophoric features of compound GSK952. The complex was subjected to docking, thereafter, MD simulation confirmed the stability of the system. Experimentally determined inhibitors with known HIV-reverse transcriptase inhibitory activity were used to validate the protocol. Two potential hits (ZINC46849657 and ZINC54359621) showed a significant potential with regard to free binding energy. Reported results obtained from this work confirm that this new approach is favorable in the future of the drug design industry. Keywords: HIV-1, reverse transcriptase, GSK952, molecular dynamic simulations, pharmacophore model, molecular docking |
| first_indexed | 2024-12-11T17:34:39Z |
| format | Article |
| id | doaj.art-31ae9508af074e4ab0f9733dcef1921e |
| institution | Directory Open Access Journal |
| issn | 1177-8881 |
| language | English |
| last_indexed | 2024-12-11T17:34:39Z |
| publishDate | 2016-04-01 |
| publisher | Dove Medical Press |
| record_format | Article |
| series | Drug Design, Development and Therapy |
| spelling | doaj.art-31ae9508af074e4ab0f9733dcef1921e2022-12-22T00:56:42ZengDove Medical PressDrug Design, Development and Therapy1177-88812016-04-012016Issue 11365137726377Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agentsCele FNRamesh MSoliman MEFavourite N Cele, Muthusamy Ramesh, Mahmoud ES Soliman Molecular Modelling and Drug Design Research Group, School of Health Sciences, University of KwaZulu-Natal, Durban, South Africa Abstract: A novel virtual screening approach is implemented herein, which is a further improvement of our previously published “target-bound pharmacophore modeling approach”. The generated pharmacophore library is based only on highly contributing amino acid residues, instead of arbitrary pharmacophores, which are most commonly used in the conventional approaches in literature. Highly contributing amino acid residues were distinguished based on free binding energy contributions obtained from calculation from molecular dynamic (MD) simulations. To the best of our knowledge; this is the first attempt in the literature using such an approach; previous approaches have relied on the docking score to generate energy-based pharmacophore models. However, docking scores are reportedly unreliable. Thus, we present a model for a per-residue energy decomposition, constructed from MD simulation ensembles generating a more trustworthy pharmacophore model, which can be applied in drug discovery workflow. This work is aimed at introducing a more rational approach to the field of drug design, rather than comparing the validity of this approach against those previously reported. We recommend additional computational and experimental work to further validate this approach. This approach was used to screen for potential reverse transcriptase inhibitors using the pharmacophoric features of compound GSK952. The complex was subjected to docking, thereafter, MD simulation confirmed the stability of the system. Experimentally determined inhibitors with known HIV-reverse transcriptase inhibitory activity were used to validate the protocol. Two potential hits (ZINC46849657 and ZINC54359621) showed a significant potential with regard to free binding energy. Reported results obtained from this work confirm that this new approach is favorable in the future of the drug design industry. Keywords: HIV-1, reverse transcriptase, GSK952, molecular dynamic simulations, pharmacophore model, molecular dockinghttps://www.dovepress.com/per-residue-energy-decomposition-pharmacophore-model-to-enhance-virtua-peer-reviewed-article-DDDTHIV-1Reverse TranscriptaseGSK952Molecular Dynamic simulations |
| spellingShingle | Cele FN Ramesh M Soliman ME Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents Drug Design, Development and Therapy HIV-1 Reverse Transcriptase GSK952 Molecular Dynamic simulations |
| title | Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents |
| title_full | Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents |
| title_fullStr | Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents |
| title_full_unstemmed | Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents |
| title_short | Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents |
| title_sort | per residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery a study for identification of reverse transcriptase inhibitors as potential anti hiv agents |
| topic | HIV-1 Reverse Transcriptase GSK952 Molecular Dynamic simulations |
| url | https://www.dovepress.com/per-residue-energy-decomposition-pharmacophore-model-to-enhance-virtua-peer-reviewed-article-DDDT |
| work_keys_str_mv | AT celefn perresidueenergydecompositionpharmacophoremodeltoenhancevirtualscreeningindrugdiscoveryastudyforidentificationofreversetranscriptaseinhibitorsaspotentialantihivagents AT rameshm perresidueenergydecompositionpharmacophoremodeltoenhancevirtualscreeningindrugdiscoveryastudyforidentificationofreversetranscriptaseinhibitorsaspotentialantihivagents AT solimanme perresidueenergydecompositionpharmacophoremodeltoenhancevirtualscreeningindrugdiscoveryastudyforidentificationofreversetranscriptaseinhibitorsaspotentialantihivagents |