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Antoniou M, Papavasileiou KD, Melagraki G, Dondero F, Lynch I, Afantitis A. Development of a Robust Read-Across Model for the Prediction of Biological Potency of Novel Peroxisome Proliferator-Activated Receptor Delta Agonists. Int J Mol Sci 2024; 25:5216. [PMID: 38791255 PMCID: PMC11121726 DOI: 10.3390/ijms25105216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 05/02/2024] [Accepted: 05/03/2024] [Indexed: 05/26/2024] Open
Abstract
A robust predictive model was developed using 136 novel peroxisome proliferator-activated receptor delta (PPARδ) agonists, a distinct subtype of lipid-activated transcription factors of the nuclear receptor superfamily that regulate target genes by binding to characteristic sequences of DNA bases. The model employs various structural descriptors and docking calculations and provides predictions of the biological activity of PPARδ agonists, following the criteria of the Organization for Economic Co-operation and Development (OECD) for the development and validation of quantitative structure-activity relationship (QSAR) models. Specifically focused on small molecules, the model facilitates the identification of highly potent and selective PPARδ agonists and offers a read-across concept by providing the chemical neighbours of the compound under study. The model development process was conducted on Isalos Analytics Software (v. 0.1.17) which provides an intuitive environment for machine-learning applications. The final model was released as a user-friendly web tool and can be accessed through the Enalos Cloud platform's graphical user interface (GUI).
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Affiliation(s)
- Maria Antoniou
- Department of Chemoinformatics, NovaMechanics Ltd., Nicosia 1046, Cyprus; (M.A.); (K.D.P.)
- Department of ChemoInformatics, NovaMechanics MIKE, 18545 Piraeus, Greece
- Entelos Institute, Larnaca 6059, Cyprus; (F.D.); (I.L.)
| | - Konstantinos D. Papavasileiou
- Department of Chemoinformatics, NovaMechanics Ltd., Nicosia 1046, Cyprus; (M.A.); (K.D.P.)
- Department of ChemoInformatics, NovaMechanics MIKE, 18545 Piraeus, Greece
- Entelos Institute, Larnaca 6059, Cyprus; (F.D.); (I.L.)
| | - Georgia Melagraki
- Division of Physical Sciences & Applications, Hellenic Military Academy, 16672 Vari, Greece;
| | - Francesco Dondero
- Entelos Institute, Larnaca 6059, Cyprus; (F.D.); (I.L.)
- Department of Science and Technological Innovation, Università del Piemonte Orientale, 15121 Alessandria, Italy
| | - Iseult Lynch
- Entelos Institute, Larnaca 6059, Cyprus; (F.D.); (I.L.)
- School of Geography, Earth and Environmental Sciences, University of Birmingham Edgbaston, Birmingham B15 2TT, UK
| | - Antreas Afantitis
- Department of Chemoinformatics, NovaMechanics Ltd., Nicosia 1046, Cyprus; (M.A.); (K.D.P.)
- Department of ChemoInformatics, NovaMechanics MIKE, 18545 Piraeus, Greece
- Entelos Institute, Larnaca 6059, Cyprus; (F.D.); (I.L.)
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Gupta MK, Gouda G, Sultana S, Punekar SM, Vadde R, Ravikiran T. Structure-related relationship: Plant-derived antidiabetic compounds. STUDIES IN NATURAL PRODUCTS CHEMISTRY 2023:241-295. [DOI: 10.1016/b978-0-323-91294-5.00008-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/06/2023]
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Pantaleão SQ, Philot EA, de Oliveira Almeida M, Lima AN, de Sairre MI, Scott AL, Honorio KM. Integrated Protocol to Design Potential Inhibitors of Dipeptidyl Peptidase- 4 (DPP-4). Curr Top Med Chem 2019; 20:209-226. [PMID: 31878857 DOI: 10.2174/1568026620666191226101543] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 12/04/2019] [Accepted: 12/06/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND A strategy for the treatment of type II diabetes mellitus is the inhibition of the enzyme known as dipeptidyl peptidase-4 (DPP-4). AIMS This study aims to investigate the main interactions between DPP-4 and a set of inhibitors, as well as proposing potential candidates to inhibit this enzyme. METHODS We performed molecular docking studies followed by the construction and validation of CoMFA and CoMSIA models. The information provided from these models was used to aid in the search for new candidates to inhibit DPP-4 and the design of new bioactive ligands from structural modifications in the most active molecule of the studied series. RESULTS We were able to propose a set of analogues with biological activity predicted by the CoMFA and CoMSIA models, suggesting that our protocol can be used to guide the design of new DPP-4 inhibitors as drug candidates to treat diabetes. CONCLUSION Once the integration of the techniques mentioned in this article was effective, our strategy can be applied to design possible new DPP-4 inhibitors as candidates to treat diabetes.
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Affiliation(s)
- Simone Queiroz Pantaleão
- Center for Sciences Natural and Human, Federal University of ABC, Santo Andre, Sao Paulo, Brazil
| | - Eric Allison Philot
- Center for Mathematics, Computing and Cognition, Federal University of ABC, Santo Andre, Sao Paulo, Brazil
| | | | - Angelica Nakagawa Lima
- Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo André, Sao Paulo, Brazil
| | - Mirela Inês de Sairre
- Center for Sciences Natural and Human, Federal University of ABC, Santo Andre, Sao Paulo, Brazil
| | - Ana Ligia Scott
- Center for Mathematics, Computing and Cognition, Federal University of ABC, Santo Andre, Sao Paulo, Brazil
| | - Kathia Maria Honorio
- Center for Sciences Natural and Human, Federal University of ABC, Santo Andre, Sao Paulo, Brazil.,School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, Brazil
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Understanding PPAR-δ affinity and selectivity using hologram quantitative structure-activity modeling, molecular docking and GRID calculations. Future Med Chem 2016; 8:1913-1926. [PMID: 27689854 DOI: 10.4155/fmc-2016-0061] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
AIM Type 2 diabetes mellitus and metabolic syndrome are two diseases related to disorders of lipid and carbohydrate metabolism and insulin resistance. Peroxisome proliferator-activated receptors (PPARs) are a class of nuclear receptors that control the metabolism of lipids/carbohydrates and are considered targets for both diseases. PPAR affinity and selectivity are critical points to design drug candidates with appropriated pharmacodynamic/kinetic profiles. MATERIALS & METHODS Hologram quantitative structure-activity relationships studies were conducted, as well molecular docking and molecular interaction field calculations, in order to explain affinity and selectivity of selected compounds. RESULTS The constructed hologram quantitative structure-activity relationship models are robust and predictive (values of q2 and r2test above 0.70). CONCLUSION The quantitative structure-activity relationship models and docking/GRID analyses indicated that carboxyl group of indole-sulfonamide derivatives could interact at helix-3 region, being considered important point of PPAR-δ selectivity.
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Abuhammad A, Taha MO. QSAR studies in the discovery of novel type-II diabetic therapies. Expert Opin Drug Discov 2015; 11:197-214. [PMID: 26558613 DOI: 10.1517/17460441.2016.1118046] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
INTRODUCTION Type-II diabetes mellitus (T2DM) is a complex chronic disease that represents a major therapeutic challenge. Despite extensive efforts in T2DM drug development, therapies remain unsatisfactory. Currently, there are many novel and important antidiabetic drug targets under investigation by many research groups worldwide. One of the main challenges to develop effective orally active hypoglycemic agents is off-target effects. Computational tools have impacted drug discovery at many levels. One of the earliest methods is quantitative structure-activity relationship (QSAR) studies. QSAR strategies help medicinal chemists understand the relationship between hypoglycemic activity and molecular properties. Hence, QSAR may hold promise in guiding the synthesis of specifically designed novel ligands that demonstrate high potency and target selectivity. AREAS COVERED This review aims to provide an overview of the QSAR strategies used to model antidiabetic agents. In particular, this review focuses on drug targets that raised recent scientific interest and/or led to successful antidiabetic agents in the market. Special emphasis has been made on studies that led to the identification of novel antidiabetic scaffolds. EXPERT OPINION Computer-aided molecular design and discovery techniques like QSAR have a great potential in designing leads against complex diseases such as T2DM. Combined with other in silico techniques, QSAR can provide more useful and rational insights to facilitate the discovery of novel compounds. However, since T2DM is a complex disease that includes several faulty biological targets, multi-target QSAR studies are recommended in the future to achieve efficient antidiabetic therapies.
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Affiliation(s)
- Areej Abuhammad
- a Department of Pharmaceutical Sciences, Faculty of Pharmacy , The University of Jordan , Amman 11942 , Jordan
| | - Mutasem O Taha
- a Department of Pharmaceutical Sciences, Faculty of Pharmacy , The University of Jordan , Amman 11942 , Jordan
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Hologram quantitative structure–activity relationship and comparative molecular interaction field analysis of aminothiazole and thiazolesulfonamide as reversible LSD1 inhibitors. Future Med Chem 2015; 7:1381-94. [DOI: 10.4155/fmc.15.68] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Background: LSD-1 is an enzyme that removes methyl groups from lysine residues of histone proteins. LSD-1 inhibition decreases cellular proliferation and therefore represents a therapeutic target for cancer treatment. MAO and LSD-1 are both flavin adenine dinucleotide-dependent MAOs, and the MAO inhibitor, tranylcypromine, is currently undergoing clinical trials for cancer treatment because it acts as an irreversible LSD-1 inhibitor. Materials & methods: The present study investigated new reversible LSD-1 inhibitors, in order to develop novel selective anticancer agents. We constructed 2 and 3D quantitative structure–activity relationship models by using a series of 54 aminothiazole and thiazolesulfonamide derivatives. Results: The models were validated internally and externally (q2 , 0.691 and 0.701; r2 , 0.894 and 0.937; r2 test , 0.785 and 0.644, for 2 and 3D models, respectively). Fragment contribution maps, as well as steric and electrostatic contour maps were generated in order to obtain chemical information related to LSD-1 inhibition. Conclusion: The thiazolesulfonamide group was fundamental to the inhibition of LSD-1 by these compounds and that bulky and aromatic substituents at the thiazole ring were important for their steric and electrostatic interactions with the active site of LSD-1.
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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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Li X, Ye L, Shi W, Liu H, Liu C, Qian X, Zhu Y, Yu H. In silico study on hydroxylated polychlorinated biphenyls as androgen receptor antagonists. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2013; 92:258-264. [PMID: 23582771 DOI: 10.1016/j.ecoenv.2013.03.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2012] [Revised: 03/04/2013] [Accepted: 03/05/2013] [Indexed: 06/02/2023]
Abstract
Hydroxylated polychlorinated biphenyls (HO-PCBs), major metabolites of PCBs, may have the potential to disrupt androgen hormone homeostasis. However, there is a lack of systematic investigation into the intermolecular interaction mechanism between HO-PCBs and the androgen receptor (AR). In this study, the combination of three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations was performed to elucidate structural characteristics that influence the anti-androgen activity of HO-PCBs, and to provide a better understanding of the binding modes between HO-PCBs and AR. A predictive comparative molecular field analysis (CoMFA) model was developed with good robustness and predictive ability. Graphical interpretation of the model provided some insights into the structural features that affect the anti-androgen activity of HO-PCBs. The hydrogen bond interaction with Gln711, and hydrophobic interactions with residues in the hydrophobic pocket played important roles in the binding of ligand with receptor. These results are expected to be beneficial to predict anti-androgen activities of other HO-PCBs and provided possible clues for further elucidation of the binding mechanism of HO-PCBs with AR.
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Affiliation(s)
- Xiaolin Li
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
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