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Bao LQ, Baecker D, Mai Dung DT, Phuong Nhung N, Thi Thuan N, Nguyen PL, Phuong Dung PT, Huong TTL, Rasulev B, Casanola-Martin GM, Nam NH, Pham-The H. Development of Activity Rules and Chemical Fragment Design for In Silico Discovery of AChE and BACE1 Dual Inhibitors against Alzheimer's Disease. Molecules 2023; 28:molecules28083588. [PMID: 37110831 PMCID: PMC10142303 DOI: 10.3390/molecules28083588] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 04/15/2023] [Accepted: 04/18/2023] [Indexed: 04/29/2023] Open
Abstract
Multi-target drug development has become an attractive strategy in the discovery of drugs to treat of Alzheimer's disease (AzD). In this study, for the first time, a rule-based machine learning (ML) approach with classification trees (CT) was applied for the rational design of novel dual-target acetylcholinesterase (AChE) and β-site amyloid-protein precursor cleaving enzyme 1 (BACE1) inhibitors. Updated data from 3524 compounds with AChE and BACE1 measurements were curated from the ChEMBL database. The best global accuracies of training/external validation for AChE and BACE1 were 0.85/0.80 and 0.83/0.81, respectively. The rules were then applied to screen dual inhibitors from the original databases. Based on the best rules obtained from each classification tree, a set of potential AChE and BACE1 inhibitors were identified, and active fragments were extracted using Murcko-type decomposition analysis. More than 250 novel inhibitors were designed in silico based on active fragments and predicted AChE and BACE1 inhibitory activity using consensus QSAR models and docking validations. The rule-based and ML approach applied in this study may be useful for the in silico design and screening of new AChE and BACE1 dual inhibitors against AzD.
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Affiliation(s)
- Le-Quang Bao
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Daniel Baecker
- Department of Pharmaceutical and Medicinal Chemistry, Institute of Pharmacy, University of Greifswald, Friedrich-Ludwig-Jahn-Straße 17, 17489 Greifswald, Germany
| | - Do Thi Mai Dung
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Nguyen Phuong Nhung
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Nguyen Thi Thuan
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Phuong Linh Nguyen
- College of Computing & Informatics, Drexel University, 3141 Chestnut St., Philadelphia, PA 19104, USA
| | - Phan Thi Phuong Dung
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Tran Thi Lan Huong
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Bakhtiyor Rasulev
- Department of Coatings and Polymeric Materials, North Dakota State University, Fargo, ND 58102, USA
| | | | - Nguyen-Hai Nam
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Hai Pham-The
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
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Ojo OA, Ojo AB, Okolie C, Nwakama MAC, Iyobhebhe M, Evbuomwan IO, Nwonuma CO, Maimako RF, Adegboyega AE, Taiwo OA, Alsharif KF, Batiha GES. Deciphering the Interactions of Bioactive Compounds in Selected Traditional Medicinal Plants against Alzheimer's Diseases via Pharmacophore Modeling, Auto-QSAR, and Molecular Docking Approaches. Molecules 2021; 26:molecules26071996. [PMID: 33915968 PMCID: PMC8037217 DOI: 10.3390/molecules26071996] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 03/22/2021] [Accepted: 03/29/2021] [Indexed: 02/06/2023] Open
Abstract
Neurodegenerative diseases, for example Alzheimer’s, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds’ pIC50 values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R2 = 0.86 and Q2 = 0.73), pls_38 (R2 = 0.77 and Q2 = 0.72), kpls_desc_44 (R2 = 0.81 and Q2 = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of −9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of −9.60 and −9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (−6.30 kcal/mol). The docking scores of our standards were −10.40 and −7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same.
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Affiliation(s)
- Oluwafemi Adeleke Ojo
- Medicinal Biochemistry and Biochemical Toxicology Group, Department of Biochemistry, Landmark University, Omu-Aran PMB 1001, Nigeria; (M.-A.C.N.); (M.I.); (C.O.N.); (R.F.M.)
- Correspondence: ; Tel.: +234-703-782-4647
| | - Adebola Busola Ojo
- Department of Biochemistry, Faculty of Sciences, Ekiti State University, Ado-Ekiti PMB 5363, Nigeria;
| | - Charles Okolie
- Department of Microbiology, Landmark University, Omu-Aran PMB 1001, Nigeria; (C.O.); (I.O.E.)
| | - Mary-Ann Chinyere Nwakama
- Medicinal Biochemistry and Biochemical Toxicology Group, Department of Biochemistry, Landmark University, Omu-Aran PMB 1001, Nigeria; (M.-A.C.N.); (M.I.); (C.O.N.); (R.F.M.)
| | - Matthew Iyobhebhe
- Medicinal Biochemistry and Biochemical Toxicology Group, Department of Biochemistry, Landmark University, Omu-Aran PMB 1001, Nigeria; (M.-A.C.N.); (M.I.); (C.O.N.); (R.F.M.)
| | | | - Charles Obiora Nwonuma
- Medicinal Biochemistry and Biochemical Toxicology Group, Department of Biochemistry, Landmark University, Omu-Aran PMB 1001, Nigeria; (M.-A.C.N.); (M.I.); (C.O.N.); (R.F.M.)
| | - Rotdelmwa Filibus Maimako
- Medicinal Biochemistry and Biochemical Toxicology Group, Department of Biochemistry, Landmark University, Omu-Aran PMB 1001, Nigeria; (M.-A.C.N.); (M.I.); (C.O.N.); (R.F.M.)
| | | | | | - Khalaf F. Alsharif
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
| | - Gaber El-Saber Batiha
- Department of Pharmacology and Therapeutics, Faculty of Veterinary Medicine, Damanhour University, Damanhour, AlBeheira 22511, Egypt;
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3
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Synthesis, In Silico and In Vitro Evaluation for Acetylcholinesterase and BACE-1 Inhibitory Activity of Some N-Substituted-4-Phenothiazine-Chalcones. Molecules 2020; 25:molecules25173916. [PMID: 32867308 PMCID: PMC7504348 DOI: 10.3390/molecules25173916] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 08/24/2020] [Accepted: 08/24/2020] [Indexed: 11/25/2022] Open
Abstract
Acetylcholinesterase (AChE) and beta-secretase (BACE-1) are two attractive targets in the discovery of novel substances that could control multiple aspects of Alzheimer’s disease (AD). Chalcones are the flavonoid derivatives with diverse bioactivities, including AChE and BACE-1 inhibition. In this study, a series of N-substituted-4-phenothiazine-chalcones was synthesized and tested for AChE and BACE-1 inhibitory activities. In silico models, including two-dimensional quantitative structure–activity relationship (2D-QSAR) for AChE and BACE-1 inhibitors, and molecular docking investigation, were developed to elucidate the experimental process. The results indicated that 13 chalcone derivatives were synthesized with relatively high yields (39–81%). The bioactivities of these substances were examined with pIC50 3.73–5.96 (AChE) and 5.20–6.81 (BACE-1). Eleven of synthesized chalcones had completely new structures. Two substances AC4 and AC12 exhibited the highest biological activities on both AChE and BACE-1. These substances could be employed for further researches. In addition to this, the present study results suggested that, by using a combination of two types of predictive models, 2D-QSAR and molecular docking, it was possible to estimate the biological activities of the prepared compounds with relatively high accuracy.
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Tran TS, Le MT, Tran TD, Tran TH, Thai KM. Design of Curcumin and Flavonoid Derivatives with Acetylcholinesterase and Beta-Secretase Inhibitory Activities Using in Silico Approaches. Molecules 2020; 25:molecules25163644. [PMID: 32785161 PMCID: PMC7464027 DOI: 10.3390/molecules25163644] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 07/20/2020] [Accepted: 08/07/2020] [Indexed: 12/25/2022] Open
Abstract
Acetylcholinesterase (AChE) and beta-secretase (BACE-1) are the two crucial enzymes involved in the pathology of Alzheimer's disease. The former is responsible for many defects in cholinergic signaling pathway and the latter is the primary enzyme in the biosynthesis of beta-amyloid as the main component of the amyloid plaques. These both abnormalities are found in the brains of Alzheimer's patients. In this study, in silico models were developed, including 3D-pharmacophore, 2D-QSAR (two-dimensional quantitative structure-activity relationship), and molecular docking, to screen virtually a database of compounds for AChE and BACE-1 inhibitory activities. A combinatorial library containing more than 3 million structures of curcumin and flavonoid derivatives was generated and screened for drug-likeness and enzymatic inhibitory bioactivities against AChE and BACE-1 through the validated in silico models. A total of 47 substances (two curcumins and 45 flavonoids), with remarkable predicted pIC50 values against AChE and BACE-1 ranging from 4.24-5.11 (AChE) and 4.52-10.27 (BACE-1), were designed. The in vitro assays on AChE and BACE-1 were performed and confirmed the in silico results. The study indicated that, by using in silico methods, a series of curcumin and flavonoid structures were generated with promising predicted bioactivities. This would be a helpful foundation for the experimental investigations in the future. Designed compounds which were the most feasible for chemical synthesis could be potential candidates for further research and lead optimization.
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Affiliation(s)
- Thai-Son Tran
- Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam or (T.-S.T.); (T.-D.T.)
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, College of Medicine and Pharmacy, Hue University, Hue City 530000, Vietnam;
| | - Minh-Tri Le
- Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam or (T.-S.T.); (T.-D.T.)
- School of Medicine, Vietnam National University Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam
- Correspondence: or (M.-T.L.); or (K.-M.T.); Tel.: +84-903-718-190 (M-T.L.); +84-28-3855-2225 or +84-909-680-385 (K-M.T.); Fax: +84-28-3822-5435 (K-M.T.)
| | - Thanh-Dao Tran
- Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam or (T.-S.T.); (T.-D.T.)
| | - The-Huan Tran
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, College of Medicine and Pharmacy, Hue University, Hue City 530000, Vietnam;
| | - Khac-Minh Thai
- Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam or (T.-S.T.); (T.-D.T.)
- Correspondence: or (M.-T.L.); or (K.-M.T.); Tel.: +84-903-718-190 (M-T.L.); +84-28-3855-2225 or +84-909-680-385 (K-M.T.); Fax: +84-28-3822-5435 (K-M.T.)
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5
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Kumar V, Ojha PK, Saha A, Roy K. Exploring 2D-QSAR for prediction of beta-secretase 1 (BACE1) inhibitory activity against Alzheimer's disease. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2020; 31:87-133. [PMID: 31865778 DOI: 10.1080/1062936x.2019.1695226] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 11/17/2019] [Indexed: 06/10/2023]
Abstract
We have developed a robust quantitative structure-activity relationship (QSAR) model employing a dataset of 98 heterocycle compounds to identify structural features responsible for BACE1 (beta-secretase 1) enzyme inhibition. We have used only 2D descriptors for model development purpose thus avoiding the conformational complications arising due to 3D geometry considerations. Following the strict Organization for Economic Co-operation and Development (OECD) guidelines, we have developed models using stepwise regression analysis followed by the best subset selection, while the final model was developed by partial least squares regression technique. The model was validated using various internationally accepted stringent validation parameters. From the insights obtained from the developed model, we have concluded that heteroatoms (nitrogen, oxygen, etc.) present within to an aromatic nucleus and the structural features such as hydrophobic, ring aromatic and hydrogen bond acceptor/donor are responsible for the enhancement of the BACE1 enzyme inhibitory activity. Moreover, we have performed the pharmacophore modelling to unveil the structural requirements for the inhibitory activity against the BACE1 enzyme. Furthermore, molecular docking studies were carried out to understand the molecular interactions involved in binding, and the results are then correlated with the requisite structural features obtained from the QSAR and pharmacophore models.
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Affiliation(s)
- V Kumar
- Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - P K Ojha
- Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - A Saha
- Department of Chemical Technology, University of Calcutta, Kolkata, India
| | - K Roy
- Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
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6
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Hampsch RA, Shee K, Bates D, Lewis LD, Désiré L, Leblond B, Demidenko E, Stefan K, Huang YH, Miller TW. Therapeutic sensitivity to Rac GTPase inhibition requires consequential suppression of mTORC1, AKT, and MEK signaling in breast cancer. Oncotarget 2017; 8:21806-21817. [PMID: 28423521 PMCID: PMC5400625 DOI: 10.18632/oncotarget.15586] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Accepted: 01/27/2017] [Indexed: 12/15/2022] Open
Abstract
Rac GTPases have oncogenic roles in cell growth, survival, and migration. We tested response to the Rac inhibitor EHT1864 in a panel of breast cancer cell lines. EHT1864-induced growth inhibition was associated with dual inhibition of the PI3K/AKT/mTORC1 and MEK/ERK pathways. Breast cancer cells harboring PIK3CA mutations or HER2 overexpression were most sensitive to Rac inhibition, suggesting that such oncogenic alterations link Rac activation with PI3K/AKT/mTORC1 and MEK/ERK signaling. Interestingly, EHT1864 decreased activation of the mTORC1 substrate p70S6K earlier than AKT inhibition, suggesting that Rac may activate mTORC1/p70S6K independently of AKT. Comparison of the growth-inhibitory profile of EHT1864 to 137 other anti-cancer drugs across 656 cancer cell lines revealed significant correlation with the p70S6K inhibitor PF-4708671. We confirmed that Rac complexes contain MEK1/2 and ERK1/2, but also contain p70S6K; these interactions were disrupted by EHT1864. Pharmacokinetic profiles revealed that EHT1864 was present in mouse plasma at concentrations effective in vitro for approximately 1 h after intraperitoneal administration. EHT1864 suppressed growth of HER2+ tumors, and enhanced response to anti-estrogen treatment in ER+ tumors. Further therapeutic development of Rac inhibitors for HER2+ and PIK3CA-mutant cancers is warranted.
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Affiliation(s)
- Riley A Hampsch
- Department of Molecular & Systems Biology, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Kevin Shee
- Department of Molecular & Systems Biology, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Darcy Bates
- Department of Medicine, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Lionel D Lewis
- Department of Medicine, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | | | | | - Eugene Demidenko
- Department of Community & Family Medicine, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Kurtis Stefan
- Department of Molecular & Systems Biology, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Yina H Huang
- Department of Microbiology and Immunology, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Todd W Miller
- Department of Molecular & Systems Biology, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.,Comprehensive Breast Program, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
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7
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Structural exploration of PPARγ modulators through pharmacophore mapping, fragment-based design, docking, and molecular dynamics simulation analyses. Med Chem Res 2016. [DOI: 10.1007/s00044-016-1727-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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8
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Wu Q, Li X, Gao Q, Wang J, Li Y, Yang L. Interaction mechanism exploration of HEA derivatives as BACE1 inhibitors by in silico analysis. MOLECULAR BIOSYSTEMS 2016; 12:1151-65. [DOI: 10.1039/c5mb00859j] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The β-site amyloid precursor protein cleaving enzyme 1 (BACE1) initiates the generation of β-amyloid (Aβ) peptides which play a critical early role in the pathogenesis of Alzheimer's disease (AD), and thus it is a prime target for lowering the Aβ levels to treat AD.
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Affiliation(s)
- Qian Wu
- Key Laboratory of Marine Chemistry Theory and Technology
- Ministry of Education
- Ocean University of China
- Qingdao
- China
| | - Xianguo Li
- Key Laboratory of Marine Chemistry Theory and Technology
- Ministry of Education
- Ocean University of China
- Qingdao
- China
| | - Qingping Gao
- School of Chemical Engineering
- Weifang Vocational College
- Weifang
- China
| | - Jinghui Wang
- Department of Materials Science and Chemical Engineering
- Dalian University of Technology
- Dalian
- China
| | - Yan Li
- Department of Materials Science and Chemical Engineering
- Dalian University of Technology
- Dalian
- China
| | - Ling Yang
- Lab of Pharmaceutical Resource Discovery
- Dalian Institute of Chemical Physics
- Graduate School of the Chinese Academy of Sciences
- Dalian
- China
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9
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Nandy A, Roy K, Saha A. Exploring molecular fingerprints of selective PPARδ agonists through comparative and validated chemometric techniques. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2015; 26:363-382. [PMID: 25986170 DOI: 10.1080/1062936x.2015.1039576] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Peroxysome proliferator-activated receptors (PPARs) have grown greatly in importance due to their role in the metabolic profile. Among three subtypes (α, γ and δ), we here consider the least investigated δ subtype to explore the molecular fingerprints of selective PPARδ agonists. Validated QSAR models (regression based 2D-QSAR, HQSAR and KPLS) and molecular docking with dynamics analyses support the inference of classification-based Bayesian and recursive models. Chemometric studies indicate that the presence of ether linkages and heterocyclic rings has optimum influence in imparting selective bioactivity. Pharmacophore models and docking with molecular dynamics analyses postulate the occurrence of aromatic rings, HB acceptor and a hydrophobic region as crucial molecular fragments for development of PPARδ modulators. Multi-chemometric studies suggest the essential structural requirements of a molecule for imparting potent and selective PPARδ modulation.
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Affiliation(s)
- A Nandy
- a Department of Chemical Technology , University of Calcutta , Kolkata , India
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Hossain T, Mukherjee A, Saha A. Chemometric design to explore pharmacophore features of BACE inhibitors for controlling Alzheimer's disease. MOLECULAR BIOSYSTEMS 2015; 11:549-57. [DOI: 10.1039/c4mb00540f] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Pharmacophoric features of potent BACE inhibitors derived from multi-chemometric studies.
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Affiliation(s)
- Tabassum Hossain
- Department of Chemical Technology
- University of Calcutta
- Kolkata-700009
- India
| | - Arup Mukherjee
- Department of Chemical Technology
- University of Calcutta
- Kolkata-700009
- India
| | - Achintya Saha
- Department of Chemical Technology
- University of Calcutta
- Kolkata-700009
- India
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Ambure P, Roy K. Advances in quantitative structure–activity relationship models of anti-Alzheimer’s agents. Expert Opin Drug Discov 2014; 9:697-723. [DOI: 10.1517/17460441.2014.909404] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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