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Ding H, Xing F, Zou L, Zhao L. QSAR analysis of VEGFR-2 inhibitors based on machine learning, Topomer CoMFA and molecule docking. BMC Chem 2024; 18:59. [PMID: 38555462 PMCID: PMC10981835 DOI: 10.1186/s13065-024-01165-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 03/12/2024] [Indexed: 04/02/2024] Open
Abstract
VEGFR-2 kinase inhibitors are clinically approved drugs that can effectively target cancer angiogenesis. However, such inhibitors have adverse effects such as skin toxicity, gastrointestinal reactions and hepatic impairment. In this study, machine learning and Topomer CoMFA, which is an alignment-dependent, descriptor-based method, were employed to build structural activity relationship models of potentially new VEGFR-2 inhibitors. The prediction ac-curacy of the training and test sets of the 2D-SAR model were 82.4 and 80.1%, respectively, with KNN. Topomer CoMFA approach was then used for 3D-QSAR modeling of VEGFR-2 inhibitors. The coefficient of q2 for cross-validation of the model 1 was greater than 0.5, suggesting that a stable drug activity-prediction model was obtained. Molecular docking was further performed to simulate the interactions between the five most promising compounds and VEGFR-2 target protein and the Total Scores were all greater than 6, indicating that they had a strong hydrogen bond interactions were present. This study successfully used machine learning to obtain five potentially novel VEGFR-2 inhibitors to increase our arsenal of drugs to combat cancer.
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Affiliation(s)
- Hao Ding
- Department of Ultrasound, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China
| | - Fei Xing
- Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China
| | - Lin Zou
- Medical College of Guangxi University, Nanning, 530004, Guangxi, China
| | - Liang Zhao
- Hepatobiliary and Splenic Surgery Ward, Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China.
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Damavandi S, Shiri F, Emamjomeh A, Pirhadi S, Beyzaei H. A study of the interaction space of two lactate dehydrogenase isoforms (LDHA and LDHB) and some of their inhibitors using proteochemometrics modeling. BMC Chem 2023; 17:70. [PMID: 37415191 DOI: 10.1186/s13065-023-00991-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 06/30/2023] [Indexed: 07/08/2023] Open
Abstract
Lactate dehydrogenase (LDH) is a tetramer enzyme that converts pyruvate to lactate reversibly. This enzyme becomes important because it is associated with diseases such as cancers, heart disease, liver problems, and most importantly, corona disease. As a system-based method, proteochemometrics does not require knowledge of the protein's three-dimensional structure, but rather depends on the amino acid sequence and protein descriptors. Here, we applied this methodology to model a set of LDHA and LDHB isoenzyme inhibitors. To implement the proteochemetrics method, the camb package in the R Studio Server programming environment was used. The activity of 312 compounds of LDHA and LDHB isoenzyme inhibitors from the valid Binding DB database was retrieved. The proteochemometrics method was applied to three machine learning algorithms gradient amplification model, random forest, and support vector machine as regression methods to find the best model. Through the combination of different models into an ensemble (greedy and stacking optimization), we explored the possibility of improving the performance of models. For the RF best ensemble model of inhibitors of LDHA and LDHB isoenzymes, and were 0.66 and 0.62, respectively. LDH inhibitory activation is influenced by Morgan fingerprints and topological structure descriptors.
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Affiliation(s)
- Sedigheh Damavandi
- Department of Bioinformatics, Laboratory of Computational Biotechnology and Bioinformatics (CBB Lab), University of Zabol, Zabol, Iran
| | - Fereshteh Shiri
- Department of Chemistry, Faculty of Science, University of Zabol, Zabol, Iran.
| | - Abbasali Emamjomeh
- Department of Bioinformatics, Laboratory of Computational Biotechnology and Bioinformatics (CBB Lab), University of Zabol, Zabol, Iran
- Department of Plant Breeding and Biotechnology (PBB), Faculty of Agriculture, University of Zabol, Zabol, Iran
| | - Somayeh Pirhadi
- Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Hamid Beyzaei
- Department of Chemistry, Faculty of Science, University of Zabol, Zabol, Iran
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Tvaroška I, Kozmon S, Kóňa J. Molecular Modeling Insights into the Structure and Behavior of Integrins: A Review. Cells 2023; 12:cells12020324. [PMID: 36672259 PMCID: PMC9856412 DOI: 10.3390/cells12020324] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 01/09/2023] [Accepted: 01/11/2023] [Indexed: 01/18/2023] Open
Abstract
Integrins are heterodimeric glycoproteins crucial to the physiology and pathology of many biological functions. As adhesion molecules, they mediate immune cell trafficking, migration, and immunological synapse formation during inflammation and cancer. The recognition of the vital roles of integrins in various diseases revealed their therapeutic potential. Despite the great effort in the last thirty years, up to now, only seven integrin-based drugs have entered the market. Recent progress in deciphering integrin functions, signaling, and interactions with ligands, along with advancement in rational drug design strategies, provide an opportunity to exploit their therapeutic potential and discover novel agents. This review will discuss the molecular modeling methods used in determining integrins' dynamic properties and in providing information toward understanding their properties and function at the atomic level. Then, we will survey the relevant contributions and the current understanding of integrin structure, activation, the binding of essential ligands, and the role of molecular modeling methods in the rational design of antagonists. We will emphasize the role played by molecular modeling methods in progress in these areas and the designing of integrin antagonists.
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Affiliation(s)
- Igor Tvaroška
- Institute of Chemistry, Slovak Academy of Sciences, Dúbravska cesta 9, 845 38 Bratislava, Slovakia
- Correspondence:
| | - Stanislav Kozmon
- Institute of Chemistry, Slovak Academy of Sciences, Dúbravska cesta 9, 845 38 Bratislava, Slovakia
- Medical Vision o. z., Záhradnícka 4837/55, 821 08 Bratislava, Slovakia
| | - Juraj Kóňa
- Institute of Chemistry, Slovak Academy of Sciences, Dúbravska cesta 9, 845 38 Bratislava, Slovakia
- Medical Vision o. z., Záhradnícka 4837/55, 821 08 Bratislava, Slovakia
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Beheshti A, Pourbasheer E, Ganjali MR. Density function theory calculation to study the oxidation potential of electron-donating compounds; affirming the oxidation mechanism by NICS calculations. J Mol Model 2023; 29:32. [PMID: 36609766 DOI: 10.1007/s00894-022-05431-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 12/18/2022] [Indexed: 01/09/2023]
Abstract
The manuscript describes a method for understanding the correlation of structural features and first oxidation potentials [Formula: see text] of electron-donating compounds (EDCs) with tetrathiafulvalene (TTF), dithiadiazafulvalenes (DTDAF), and tetraazafulvalene (TAF) frameworks. The density functional theory (DFT) procedure at B3LYP (6-31 + g(d)) was used for geometric optimization, given the large dimensions of the molecules studied, and their high structural similarity. First of all, the correlation between the oxidation potential and the highest occupied molecular orbital (HOMO) energy level as an effective quantum chemical descriptor was examined. Then, nucleus-independent chemical shifts (NICSs) calculation was applied to affirm the oxidation mechanism and interpret the effect of replacing the sulfur atoms by nitrogen, on the oxidation process. Finally, a more comprehensive investigation of structural features that affect the oxidation potential, topological, geometrical, constitutional, as well as, electrostatic, charged partial surface area, quantum-chemical, molecular orbital, and thermodynamic descriptors was calculated. A predictive model was developed based on the genetic algorithm multivariate linear regression (GA-MLR). There was an outstanding agreement between the theoretical and the experimental values obtained for the first oxidation potentials of the test set (Q2Ext = 0.981).
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Affiliation(s)
- Abolghasem Beheshti
- Department of Chemistry, Payame Noor University (PNU), P.O. Box, 19395-3697, Tehran, Iran.
| | - Eslam Pourbasheer
- Department of Chemistry, Faculty of Science, University of Mohaghegh Ardabili, P.O. Box 179, Ardabil, Iran
| | - Mohammad Reza Ganjali
- Center of Excellence in Electrochemistry, Faculty of Chemistry, University of Tehran, Tehran, Iran.,National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran
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Das S, Amin SA, Gayen S, Jha T. Insight into the structural requirements of gelatinases (MMP-2 and MMP-9) inhibitors by multiple validated molecular modelling approaches: Part II. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2022; 33:167-192. [PMID: 35301933 DOI: 10.1080/1062936x.2022.2041722] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
Abstract
Inhibition of the matrix metalloproteinases (MMPs) is effective against metastasis of secondary tumours. Previous MMP inhibitors have failed in clinical trials due to their off-target toxicity in solid tumours. Thus, newer MMP inhibitors now have paramount importance. Here, different molecular modelling techniques were applied on a dataset of 110 gelatinase (MMP-2 and MMP-9) inhibitors. The objectives of the present study were to identify structural fingerprints for gelatinase inhibition and also to develop statistically validated QSAR models for the screening and prediction of different derivatives as MMP-2 (gelatinase A) and MMP-9 (gelatinase B) inhibitors. The Bayesian classification study provided the ROC values for the training set of 0.837 and 0.815 for MMP-2 and MMP-9, respectively. The linear model also produced the leave-one-out cross-validated Q2 of 0.805 (eq. 1, MMP-2) and 0.724 (eq. 2, MMP-9), an r2 of 0.845 (eq. 1, MMP-2) and 0.782 (eq. 2, MMP-9), an r2Pred of 0.806 (eq. 1, MMP-2) and 0.732 (eq. 2, MMP-9). Similarly, non-linear learning models were also statistically significant and reliable. Overall, this study may help in the rational design of newer compounds with higher gelatinase inhibition to fight against both primary and secondary cancers in future.
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Affiliation(s)
- S Das
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - S A Amin
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - S Gayen
- Laboratory of Drug Design and Discovery, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - T Jha
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
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QSAR investigations and structure-based virtual screening on a series of nitrobenzoxadiazole derivatives targeting human glutathione-S-transferases. J Mol Struct 2020. [DOI: 10.1016/j.molstruc.2020.128015] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Faramarzi Z, Abbasitabar F, Zare-Shahabadi V, Jahromi HJ. Novel mixture descriptors for the development of quantitative structure−property relationship models for the boiling points of binary azeotropic mixtures. J Mol Liq 2019. [DOI: 10.1016/j.molliq.2019.111854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Pourbasheer E, Aalizadeh R, Ganjali MR. QSAR study of CK2 inhibitors by GA-MLR and GA-SVM methods. ARAB J CHEM 2019. [DOI: 10.1016/j.arabjc.2014.12.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
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Labjar H, Cherif W, Nadir S, Digua K, Sallek B, Chaair H. Support vector machines for modelling phosphocalcic hydroxyapatite by precipitation from a calcium carbonate solution and phosphoric acid solution. JOURNAL OF TAIBAH UNIVERSITY FOR SCIENCE 2018. [DOI: 10.1016/j.jtusci.2015.09.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Houda Labjar
- Laboratoire des génies des procédés et environnement, Faculté des sciences et techniques, Université Hassan II-Casablanca, B.P.: 146, Mohammedia, Morocco
| | - Walid Cherif
- Laboratoire d’informatique et de mathématiques et leurs applications, Faculté des sciences, Université Chouaib Doukkali, B.P.: 20, El Jadida, 24000, Morocco
| | - Salah Nadir
- Laboratoire de Chimie-Physique des Matériaux, Ecole Hassania des Travaux Publics, B.P.: 8108, Casablanca, Morocco
| | - Khalid Digua
- Laboratoire des génies des procédés et environnement, Faculté des sciences et techniques, Université Hassan II-Casablanca, B.P.: 146, Mohammedia, Morocco
| | - Brahim Sallek
- Laboratoire d’Agroressources et Génie des Procédés, Faculté des Sciences, Université Ibn Tofail, B.P.: 133, Kénitra, Morocco
| | - Hassan Chaair
- Laboratoire des génies des procédés et environnement, Faculté des sciences et techniques, Université Hassan II-Casablanca, B.P.: 146, Mohammedia, Morocco
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Bellera CL, Di Ianni ME, Talevi A. The application of molecular topology for ulcerative colitis drug discovery. Expert Opin Drug Discov 2017; 13:89-101. [PMID: 29088918 DOI: 10.1080/17460441.2018.1396314] [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: 12/13/2022]
Abstract
INTRODUCTION Although the therapeutic arsenal against ulcerative colitis has greatly expanded (including the revolutionary advent of biologics), there remain patients who are refractory to current medications while the safety of the available therapeutics could also be improved. Molecular topology provides a theoretic framework for the discovery of new therapeutic agents in a very efficient manner, and its applications in the field of ulcerative colitis have slowly begun to flourish. Areas covered: After discussing the basics of molecular topology, the authors review QSAR models focusing on validated targets for the treatment of ulcerative colitis, entirely or partially based on topological descriptors. Expert opinion: The application of molecular topology to ulcerative colitis drug discovery is still very limited, and many of the existing reports seem to be strictly theoretic, with no experimental validation or practical applications. Interestingly, mechanism-independent models based on phenotypic responses have recently been reported. Such models are in agreement with the recent interest raised by network pharmacology as a potential solution for complex disorders. These and other similar studies applying molecular topology suggest that some therapeutic categories may present a 'topological pattern' that goes beyond a specific mechanism of action.
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Affiliation(s)
- Carolina L Bellera
- a Medicinal Chemistry/Laboratory of Bioactive Research and Development, Department of Biological Sciences, Faculty of Exact Sciences , University of La Plata (UNLP) , La Plata , Buenos Aires , Argentina
| | - Mauricio E Di Ianni
- a Medicinal Chemistry/Laboratory of Bioactive Research and Development, Department of Biological Sciences, Faculty of Exact Sciences , University of La Plata (UNLP) , La Plata , Buenos Aires , Argentina
| | - Alan Talevi
- a Medicinal Chemistry/Laboratory of Bioactive Research and Development, Department of Biological Sciences, Faculty of Exact Sciences , University of La Plata (UNLP) , La Plata , Buenos Aires , Argentina
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Comparison between the gas-liquid solubility of methanol and ethanol in different organic phases using structural properties of solvents. J Mol Liq 2017. [DOI: 10.1016/j.molliq.2017.06.081] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Pourbasheer E, Aalizadeh R. 3D-QSAR and molecular docking study of LRRK2 kinase inhibitors by CoMFA and CoMSIA methods. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2016; 27:385-407. [PMID: 27228480 DOI: 10.1080/1062936x.2016.1184713] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2016] [Accepted: 04/11/2016] [Indexed: 06/05/2023]
Abstract
Three-dimensional quantitative structure-activity relationship (3D-QSAR) modelling was conducted on a series of leucine-rich repeat kinase 2 (LRRK2) antagonists using CoMFA and CoMSIA methods. The data set, which consisted of 37 molecules, was divided into training and test subsets by using a hierarchical clustering method. Both CoMFA and CoMSIA models were derived using a training set on the basis of the common substructure-based alignment. The optimum PLS model built by CoMFA and CoMSIA provided satisfactory statistical results (q(2) = 0.589 and r(2) = 0.927 and q(2) = 0.473 and r(2) = 0.802, respectively). The external predictive ability of the models was evaluated by using seven compounds. Moreover, an external evaluation set with known experimental data was used to evaluate the external predictive ability of the porposed models. The statistical parameters indicated that CoMFA (after region focusing) has high predictive ability in comparison with standard CoMFA and CoMSIA models. Molecular docking was also performed on the most active compound to investigate the existence of interactions between the most active inhibitor and the LRRK2 receptor. Based on the obtained results and CoMFA contour maps, some features were introduced to provide useful insights for designing novel and potent LRRK2 inhibitors.
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Affiliation(s)
- E Pourbasheer
- a Department of Chemistry , Payame Noor University , Tehran , Iran
| | - R Aalizadeh
- b Laboratory of Analytical Chemistry, Department of Chemistry , National and Kapodistrian University of Athens , Athens , Greece
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Shibi I, Aswathy L, Jisha R, Masand V, Divyachandran A, Gajbhiye J. Molecular docking and QSAR analyses for understanding the antimalarial activity of some 7-substituted-4-aminoquinoline derivatives. Eur J Pharm Sci 2015; 77:9-23. [DOI: 10.1016/j.ejps.2015.05.025] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Revised: 05/02/2015] [Accepted: 05/21/2015] [Indexed: 12/28/2022]
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Aalizadeh R, Pourbasheer E, Ganjali MR. Analysis of B-Raf $$^{\mathrm{V600E}}$$ V 600 E inhibitors using 2D and 3D-QSAR, molecular docking and pharmacophore studies. Mol Divers 2015; 19:915-30. [DOI: 10.1007/s11030-015-9626-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2015] [Accepted: 07/27/2015] [Indexed: 12/14/2022]
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Ponikvar-Svet M, Zeiger DN, Liebman JF. Interplay of thermochemistry and structural chemistry, the journal (volume 25, 2014, issues 1–2) and the discipline. Struct Chem 2015. [DOI: 10.1007/s11224-015-0572-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Pourbasheer E, Banaei A, Aalizadeh R, Ganjali MR, Norouzi P, Shadmanesh J, Methenitis C. Prediction of PCE of fullerene (C 60 ) derivatives as polymer solar cell acceptors by genetic algorithm–multiple linear regression. J IND ENG CHEM 2015. [DOI: 10.1016/j.jiec.2014.05.016] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Pourbasheer E, Aalizadeh R, Shokouhi Tabar S, Ganjali MR, Norouzi P, Shadmanesh J. 2D and 3D Quantitative Structure–Activity Relationship Study of Hepatitis C Virus NS5B Polymerase Inhibitors by Comparative Molecular Field Analysis and Comparative Molecular Similarity Indices Analysis Methods. J Chem Inf Model 2014; 54:2902-14. [DOI: 10.1021/ci500216c] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Eslam Pourbasheer
- Department
of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697, Tehran, Iran
| | | | - Samira Shokouhi Tabar
- Department
of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697, Tehran, Iran
| | - Mohammad Reza Ganjali
- Center
of Excellence in Electrochemistry, Faculty of Chemistry, University of Tehran, P.O. Box 143981-7435, Tehran, Iran
- Biosensor
Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences
Institute, Tehran University of Medical Sciences, P. O. Box,
14114-13137, Tehran, Iran
| | - Parviz Norouzi
- Center
of Excellence in Electrochemistry, Faculty of Chemistry, University of Tehran, P.O. Box 143981-7435, Tehran, Iran
- Biosensor
Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences
Institute, Tehran University of Medical Sciences, P. O. Box,
14114-13137, Tehran, Iran
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