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Perugino F, Pedroni L, Galaverna G, Dall'Asta C, Dellafiora L. A mechanistic toxicology study to grasp the mechanics of zearalenone estrogenicity: Spotlighting aromatase and the effects of its genetic variability. Toxicology 2024; 501:153686. [PMID: 38036094 DOI: 10.1016/j.tox.2023.153686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 11/23/2023] [Accepted: 11/25/2023] [Indexed: 12/02/2023]
Abstract
Zearalenone (ZEN) is a mycoestrogen produced by Fusarium fungi contaminating cereals and in grain-based products threatening human and animal health due to its endocrine disrupting effects. Germane to the mechanisms of action, ZEN may activate the estrogen receptors and inhibit the estrogens-producing enzyme aromatase (CYP19A1). Both show single nucleotide variants (SNVs) among humans associated with a diverse susceptibility of being activated or inhibited. These variations might modify the endocrine disrupting action of ZEN, requiring dedicated studies to improve its toxicological understanding. This work focused on human aromatase investigating via 3D molecular modelling whether some of the SNVs reported so far (n = 434) may affect the inhibitory potential of ZEN. It has been also calculated the inhibition capability of α-zearalenol, the most prominent and estrogenically potent phase I metabolite of ZEN, toward those aromatase variants with an expected diverse sensitivity of being inhibited by ZEN. The study: i) described SNVs likely associated with a different susceptibility to ZEN and α-zearalenol inhibition - like T310S that is likely more susceptible to inhibition, or D309G and S478F that are possibly inactive variants; ii) proofed the possible existence of inter-individual susceptibility to ZEN; iii) prioritized aromatase variants for future investigations toward a better comprehension of ZEN xenoestrogenicity at an individual level.
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Affiliation(s)
- Florinda Perugino
- Department of Food and Drug, University of Parma, Parma, Italy; Department of Biology, University of Naples Federico II, Naples, Italy
| | - Lorenzo Pedroni
- Department of Food and Drug, University of Parma, Parma, Italy
| | | | | | - Luca Dellafiora
- Department of Food and Drug, University of Parma, Parma, Italy.
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Banjare L, Verma SK, Jain AK, Thareja S. Design and pharmacophoric identification of flavonoid scaffold‐based aromatase inhibitors. J Heterocycl Chem 2020. [DOI: 10.1002/jhet.4068] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Laxmi Banjare
- School of Pharmaceutical SciencesGuru Ghasidas Central University Bilaspur Chhattisgarh India
| | - Sant Kumar Verma
- School of Pharmaceutical SciencesGuru Ghasidas Central University Bilaspur Chhattisgarh India
| | - Akhlesh Kumar Jain
- School of Pharmaceutical SciencesGuru Ghasidas Central University Bilaspur Chhattisgarh India
| | - Suresh Thareja
- Department of Pharmaceutical Sciences and Natural ProductsCentral University of Punjab Bathinda Punjab India
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Jha T, Adhikari N, Halder AK, Saha A. Ligand- and Structure-Based Drug Design of Non-Steroidal Aromatase Inhibitors (NSAIs) in Breast Cancer. Oncology 2017. [DOI: 10.4018/978-1-5225-0549-5.ch004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Aromatase is a multienzyme complex overexpressed in breast cancer and responsible for estrogen production. It is the potential target for designing anti-breast cancer drugs. Ligand and Structure-Based Drug Designing approaches (LBDD and SBDD) are involved in development of active and more specific Nonsteroidal Aromatase Inhibitors (NSAIs). Different LBDD and SBDD approaches are presented here to understand their utility in designing novel NSAIs. It is observed that molecules should possess a five or six membered heterocyclic nitrogen containing ring to coordinate with heme portion of aromatase for inhibition. Moreover, one or two hydrogen bond acceptor features, hydrophobicity, and steric factors may play crucial roles for anti-aromatase activity. Electrostatic, van der Waals, and p-p interactions are other important factors that determine binding affinity of inhibitors. HQSAR, LDA-QSAR, GQSAR, CoMFA, and CoMSIA approaches, pharmacophore mapping followed by virtual screening, docking, and dynamic simulation may be effective approaches for designing new potent anti-aromatase molecules.
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Jha T, Adhikari N, Halder AK, Saha A. Ligand- and Structure-Based Drug Design of Non-Steroidal Aromatase Inhibitors (NSAIs) in Breast Cancer. QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS IN DRUG DESIGN, PREDICTIVE TOXICOLOGY, AND RISK ASSESSMENT 2015. [DOI: 10.4018/978-1-4666-8136-1.ch011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Aromatase is a multienzyme complex overexpressed in breast cancer and responsible for estrogen production. It is the potential target for designing anti-breast cancer drugs. Ligand and Structure-Based Drug Designing approaches (LBDD and SBDD) are involved in development of active and more specific Nonsteroidal Aromatase Inhibitors (NSAIs). Different LBDD and SBDD approaches are presented here to understand their utility in designing novel NSAIs. It is observed that molecules should possess a five or six membered heterocyclic nitrogen containing ring to coordinate with heme portion of aromatase for inhibition. Moreover, one or two hydrogen bond acceptor features, hydrophobicity, and steric factors may play crucial roles for anti-aromatase activity. Electrostatic, van der Waals, and p-p interactions are other important factors that determine binding affinity of inhibitors. HQSAR, LDA-QSAR, GQSAR, CoMFA, and CoMSIA approaches, pharmacophore mapping followed by virtual screening, docking, and dynamic simulation may be effective approaches for designing new potent anti-aromatase molecules.
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Awasthi M, Singh S, Pandey VP, Dwivedi UN. Molecular docking and 3D-QSAR-based virtual screening of flavonoids as potential aromatase inhibitors against estrogen-dependent breast cancer. J Biomol Struct Dyn 2014; 33:804-19. [DOI: 10.1080/07391102.2014.912152] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Affiliation(s)
- Manika Awasthi
- Department of Biochemistry, Bioinformatics Infrastructure Facility, Centre of Excellence in Bioinformatics, University of Lucknow, Lucknow 226007, Uttar Pradesh, India
| | - Swati Singh
- Department of Biochemistry, Bioinformatics Infrastructure Facility, Centre of Excellence in Bioinformatics, University of Lucknow, Lucknow 226007, Uttar Pradesh, India
| | - Veda P. Pandey
- Department of Biochemistry, Bioinformatics Infrastructure Facility, Centre of Excellence in Bioinformatics, University of Lucknow, Lucknow 226007, Uttar Pradesh, India
| | - Upendra N. Dwivedi
- Department of Biochemistry, Bioinformatics Infrastructure Facility, Centre of Excellence in Bioinformatics, University of Lucknow, Lucknow 226007, Uttar Pradesh, India
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Bohari MH, Sastry GN. FDA approved drugs complexed to their targets: evaluating pose prediction accuracy of docking protocols. J Mol Model 2012; 18:4263-74. [PMID: 22562231 DOI: 10.1007/s00894-012-1416-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2011] [Accepted: 03/26/2012] [Indexed: 11/29/2022]
Abstract
Efficient drug discovery programs can be designed by utilizing existing pools of knowledge from the already approved drugs. This can be achieved in one way by repositioning of drugs approved for some indications to newer indications. Complex of drug to its target gives fundamental insight into molecular recognition and a clear understanding of putative binding site. Five popular docking protocols, Glide, Gold, FlexX, Cdocker and LigandFit have been evaluated on a dataset of 199 FDA approved drug-target complexes for their accuracy in predicting the experimental pose. Performance for all the protocols is assessed at default settings, with root mean square deviation (RMSD) between the experimental ligand pose and the docked pose of less than 2.0 Å as the success criteria in predicting the pose. Glide (38.7 %) is found to be the most accurate in top ranked pose and Cdocker (58.8 %) in top RMSD pose. Ligand flexibility is a major bottleneck in failure of docking protocols to correctly predict the pose. Resolution of the crystal structure shows an inverse relationship with the performance of docking protocol. All the protocols perform optimally when a balanced type of hydrophilic and hydrophobic interaction or dominant hydrophilic interaction exists. Overall in 16 different target classes, hydrophobic interactions dominate in the binding site and maximum success is achieved for all the docking protocols in nuclear hormone receptor class while performance for the rest of the classes varied based on individual protocol.
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Affiliation(s)
- Mohammed H Bohari
- Molecular Modeling Group, Indian Institute of Chemical Technology, Hyderabad,, 500 607, Andhra Pradesh, India
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Narayana BL, Pran Kishore D, Balakumar C, Rao KV, Kaur R, Rao AR, Murthy JN, Ravikumar M. Molecular modeling evaluation of non-steroidal aromatase inhibitors. Chem Biol Drug Des 2012; 79:674-82. [PMID: 22129073 DOI: 10.1111/j.1747-0285.2011.01277.x] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A recent discovery of aromatase crystal structure triggered the efforts to design novel aromatase inhibitors for breast cancer therapy. While correlating docking scores with inhibitory potencies of known ligands, feeble robustness of scoring functions toward prediction was observed. This prompted us to develop new prediction models using stepwise regression analysis based on consensus of different docking and their scoring methods (GOLD, LIGANDFIT, and GLIDE). Quantitative structure-activity relationships were developed between the aromatase inhibitory activity (pIC(50) ) of flavonoid derivatives (n=39) and docking scores and docking descriptors. QSAR models have been validated internally [using leave-one-out cross-validated r(2)(cv) (LOO-Q2))] and externally to ensure the predictive capacity of the models. Model 2 [M2] developed using consensus of docking scores of scoring functions viz. ASP, potential of mean force and DOCK Score (r(2)(cv)=0.850, r(2) = 0.870, r(2)(pred) = 0.633, RMSE = 0.363 μm, r(2)(m(test)) =0.831, r(2)(m(overall)) =0.832) was found to be better in predicting aromatase inhibitory potency (pIC(50) ) compared to the Model 1 [M1] based on docking descriptors (r(2)(cv)= 0.848, r(2) = 0.825, r(2)(pred) =0.788, RMSE=0.421μm, r(2)(m(test)) =0.808, r(2)(m(overall)) =0.821). It has been observed that the natural flavonoids and their derivatives were less potent compared to these scaffolds with imidazolylmethyl substitution owing to the interaction of nitrogen atom of the imidazole ring toward the heme (Fe(3+) ) of the aromatase. Results confirm the potential of our methodology for the design of new potent non-steroidal aromatase inhibitors.
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Affiliation(s)
- Bheemanapalli Lakshmi Narayana
- Department of Pharmaceutical Chemistry, University Institute of Pharmaceutical Sciences and Centre of Advanced Study in Pharmaceutical Sciences, Panjab University, Chandigarh, India
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Synthesis, evaluation of 6,8-dibromo-2-aryl-2,3-dihydroquinolin-4(1H)-ones in MCF-7 (breast cancer) cell lines and their docking studies. Med Chem Res 2011. [DOI: 10.1007/s00044-011-9688-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Ranga Rao R, Tiwari AK, Prabhakar Reddy P, Suresh Babu K, Suresh G, Ali AZ, Madhusudana K, Agawane SB, Badrinarayan P, Narahari Sastry G, Madhusudana Rao J. Synthesis of antihyperglycemic, α-glucosidase inhibitory, and DPPH free radical scavenging furanochalcones. Med Chem Res 2011. [DOI: 10.1007/s00044-011-9583-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Roy PP, Roy K. Molecular docking and QSAR studies of aromatase inhibitor androstenedione derivatives. J Pharm Pharmacol 2010; 62:1717-28. [DOI: 10.1111/j.2042-7158.2010.01154.x] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Abstract
Objectives
Aromatase (CYP19) inhibitors have emerged as promising candidates for the treatment of estrogen-dependent breast cancer. In this study, a series of androstenedione derivatives with CYP19 inhibitory activity was subjected to a molecular docking study followed by quantitative structure–activity relationship (QSAR) analyses in search of ideal physicochemical characteristics of potential aromatase inhibitors.
Methods
The QSAR studies were carried out using both two-dimensional (topological, and structural) and three-dimesional (spatial) descriptors. We also used thermodynamic parameters along with 2D and 3D descriptors. Genetic function approximation (GFA) and genetic partial least squares (G/PLS) were used as chemometric tools for QSAR modelling.
Key findings
The docking study indicated that the important interacting amino acids in the active site were Met374, Arg115, Ile133, Ala306, Thr310, Asp309, Val370, Leu477 and Ser478. The 17-keto oxygen of the ligands is responsible for the formation of a hydrogen bond with Met374 and the remaining parts of the molecules are stabilized by the hydrophobic interactions with the non-polar amino acids. The C2 and C19 positions in the ligands are important for maintaining the appropriate orientation of the molecules in the active site. The results of docking experiments and QSAR studies supported each other.
Conclusions
The developed QSAR models indicated the importance of some Jurs parameters, structural parameters, topological branching index and E-state indices of different fragments. All the developed QSAR models were statistically significant according to the internal and external validation parameters.
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Affiliation(s)
- Partha Pratim Roy
- Drug Theoretics and Cheminformatics Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - Kunal Roy
- Drug Theoretics and Cheminformatics Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
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Pharmacophore modeling strategies for the development of novel nonsteroidal inhibitors of human aromatase (CYP19). Bioorg Med Chem Lett 2010; 20:3050-64. [DOI: 10.1016/j.bmcl.2010.03.113] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2009] [Revised: 03/27/2010] [Accepted: 03/31/2010] [Indexed: 12/17/2022]
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Roy PP, Roy K. Docking and 3D-QSAR studies of diverse classes of human aromatase (CYP19) inhibitors. J Mol Model 2010; 16:1597-616. [DOI: 10.1007/s00894-010-0667-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2009] [Accepted: 01/18/2010] [Indexed: 11/30/2022]
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Usharani D, Srivani P, Sastry GN, Jemmis ED. pH Dependence of a 310-Helix versus a Turn in the M-Loop Region of PDE4: Observations on PDB Entries and an Electronic Structure Study. J Chem Theory Comput 2008; 4:974-84. [DOI: 10.1021/ct700261b] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Dandamudi Usharani
- School of Chemistry, University of Hyderabad, Hyderabad 500046 India, Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore 560012, India, and Molecular Modeling Group, Organic Chemical Sciences, Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, India
| | - Palakuri Srivani
- School of Chemistry, University of Hyderabad, Hyderabad 500046 India, Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore 560012, India, and Molecular Modeling Group, Organic Chemical Sciences, Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, India
| | - G. Narahari Sastry
- School of Chemistry, University of Hyderabad, Hyderabad 500046 India, Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore 560012, India, and Molecular Modeling Group, Organic Chemical Sciences, Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, India
| | - Eluvathingal D. Jemmis
- School of Chemistry, University of Hyderabad, Hyderabad 500046 India, Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore 560012, India, and Molecular Modeling Group, Organic Chemical Sciences, Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, India
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