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Benny S, Rajappan Krishnendu P, Kumar S, Bhaskar V, Manisha DS, Abdelgawad MA, Ghoneim MM, Naguib IA, Pappachen LK, Mary Zachariah S, Mathew B, Tp A. A computational investigation of thymidylate synthase inhibitors through a combined approach of 3D-QSAR and pharmacophore modelling. J Biomol Struct Dyn 2023:1-20. [PMID: 37870113 DOI: 10.1080/07391102.2023.2270752] [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: 05/04/2023] [Accepted: 08/03/2023] [Indexed: 10/24/2023]
Abstract
Thymidylate synthase (TS) is a crucial target of cancer drug discovery and is mainly involved in the De novo synthesis of the DNA precursor thymine. In the present study, to generate reliable models and identify a few promising molecules, we combined QSAR modelling with the pharmacophore hypothesis-generating technique. Input molecules were clustered on their similarity, and a cluster of 74 molecules with a pyrimidine moiety was chosen as the set for 3D-QSAR and pharmacophore modelling. Atom-based and field-based 3D-QSAR models were generated and statistically validated with R2 > 0.90 and Q2 > 0.75. The common pharmacophore hypothesis(CPH) generation identified the best six-point model ADHRRR. Using these best models, a library of FDA-approved drugs was screened for activity and filtered via molecular docking, ADME profiling, and molecular dynamics simulations. The top ten promising TS-inhibiting candidates were identified, and their chemical features profitable for TS inhibitors were explored.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Sonu Benny
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India
| | - Prayaga Rajappan Krishnendu
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India
| | - Sunil Kumar
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India
| | - Vaishnav Bhaskar
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India
| | - Deepthi S Manisha
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India
| | - Mohamed A Abdelgawad
- Department of pharmaceutical chemistry, College of Pharmacy, Jouf University, Sakaka, Saudi Arabia
- Department of Pharmaceutical Organic Chemistry, Faculty of Pharmacy, Beni-Suef University, Beni-Suef, Egypt
| | - Mohammed M Ghoneim
- Department of Pharmacy Practice, College of Pharmacy, AlMaarefa University, Saudi Arabia
| | - Ibrahim A Naguib
- Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, Taif, Saudi Arabia
| | - Leena K Pappachen
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India
| | - Subin Mary Zachariah
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India
| | - Bijo Mathew
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India
| | - Aneesh Tp
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India
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Kim SH, Choi J, Lee K, No KT. Comparison of Three-Dimensional Ligand-based Pharmacophores among 11 Phosphodiesterases (PDE 1 to PDE 11) Pharmacophores. B KOREAN CHEM SOC 2017. [DOI: 10.1002/bkcs.11214] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Sei-Hwan Kim
- Department of Biotechnology, College of Life Sciences and Biotechnology; Yonsei University; Seoul 03722 Republic of Korea
| | - Jiwon Choi
- Bioinformatics and Molecular Design Research Center; Seoul 03722 Republic of Korea
| | - Kyungro Lee
- Bioinformatics and Molecular Design Research Center; Seoul 03722 Republic of Korea
| | - Kyoung Tai No
- Department of Biotechnology, College of Life Sciences and Biotechnology; Yonsei University; Seoul 03722 Republic of Korea
- Bioinformatics and Molecular Design Research Center; Seoul 03722 Republic of Korea
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Aher RB, Roy K. Exploring structural requirements for the inhibition of Plasmodium falciparum calcium-dependent protein kinase-4 (PfCDPK-4) using multiple in silico approaches. RSC Adv 2016. [DOI: 10.1039/c6ra05692j] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Plasmodial protein kinases represent one of the most important thrust areas for antimalarial drug discovery.
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Affiliation(s)
- Rahul Balasaheb Aher
- Drug Theoretics and Cheminformatics Laboratory
- Department of Pharmaceutical Technology
- Jadavpur University
- Kolkata 700032
- India
| | - Kunal Roy
- Drug Theoretics and Cheminformatics Laboratory
- Department of Pharmaceutical Technology
- Jadavpur University
- Kolkata 700032
- India
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Arooj M, Sakkiah S, Cao GP, Lee KW. An innovative strategy for dual inhibitor design and its application in dual inhibition of human thymidylate synthase and dihydrofolate reductase enzymes. PLoS One 2013; 8:e60470. [PMID: 23577115 PMCID: PMC3618229 DOI: 10.1371/journal.pone.0060470] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2012] [Accepted: 02/26/2013] [Indexed: 11/26/2022] Open
Abstract
Due to the diligence of inherent redundancy and robustness in many biological networks and pathways, multitarget inhibitors present a new prospect in the pharmaceutical industry for treatment of complex diseases. Nevertheless, to design multitarget inhibitors is concurrently a great challenge for medicinal chemists. We have developed a novel computational approach by integrating the affinity predictions from structure-based virtual screening with dual ligand-based pharmacophore to discover potential dual inhibitors of human Thymidylate synthase (hTS) and human dihydrofolate reductase (hDHFR). These are the key enzymes in folate metabolic pathway that is necessary for the biosynthesis of RNA, DNA, and protein. Their inhibition has found clinical utility as antitumor, antimicrobial, and antiprotozoal agents. A druglike database was utilized to perform dual-target docking studies. Hits identified through docking experiments were mapped over a dual pharmacophore which was developed from experimentally known dual inhibitors of hTS and hDHFR. Pharmacophore mapping procedure helped us in eliminating the compounds which do not possess basic chemical features necessary for dual inhibition. Finally, three structurally diverse hit compounds that showed key interactions at both active sites, mapped well upon the dual pharmacophore, and exhibited lowest binding energies were regarded as possible dual inhibitors of hTS and hDHFR. Furthermore, optimization studies were performed for final dual hit compound and eight optimized dual hits demonstrating excellent binding features at target systems were also regarded as possible dual inhibitors of hTS and hDHFR. In general, the strategy used in the current study could be a promising computational approach and may be generally applicable to other dual target drug designs.
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Affiliation(s)
- Mahreen Arooj
- Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center (SSAC), Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Research Institute of Natural Science(RINS), Gyeongsang National University (GNU), Jinju, Republic of Korea
| | - Sugunadevi Sakkiah
- Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center (SSAC), Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Research Institute of Natural Science(RINS), Gyeongsang National University (GNU), Jinju, Republic of Korea
| | - Guang ping Cao
- Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center (SSAC), Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Research Institute of Natural Science(RINS), Gyeongsang National University (GNU), Jinju, Republic of Korea
| | - Keun Woo Lee
- Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center (SSAC), Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Research Institute of Natural Science(RINS), Gyeongsang National University (GNU), Jinju, Republic of Korea
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Gupta AK, Varshney K, Saxena AK. Toward the identification of a reliable 3D QSAR pharmacophore model for the CCK2 receptor antagonism. J Chem Inf Model 2012; 52:1376-90. [PMID: 22530718 DOI: 10.1021/ci300094e] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The present study describes application of computational approaches to identify a validated and reliable 3D QSAR pharmacophore model for the CCK-2R antagonism through integrated ligand and structure based studies using anthranilic sulfonamide and 1,3,4-benzotriazepine based CCK-2R antagonists. The best hypothesis consisted five features viz. two aliphatic hydrophobic, one aromatic hydrophobic, one H-bond acceptor, and one ring aromatic feature with an excellent correlation for 34 training set (r²(training) = 0.83) and 58 test set compounds (r²(test) = 0.74). This model was validated through F-test and docking studies at the active site of the plausible CCK-2R where the 99% significance and well corroboration with the pharmacophore model respectively describes the model's reliability. The model also predicts well to other known clinically effective CCK-2R antagonists. Therefore, the developed model may useful in finding new scaffolds that may aid in design and develop new chemical entities (NCEs) as potent CCK-2R antagonists before their synthesis.
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Affiliation(s)
- Amit K Gupta
- Medicinal and Process Chemistry Division, C.S.I.R.-Central Drug Research Institute, Lucknow 226001, India
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Gupta AK, Bhunia SS, Balaramnavar VM, Saxena AK. Pharmacophore modelling, molecular docking and virtual screening for EGFR (HER 1) tyrosine kinase inhibitors. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2011; 22:239-263. [PMID: 21400356 DOI: 10.1080/1062936x.2010.548830] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
A pharmacophore model has been developed using diverse classes of epidermal growth factor receptor (EGFR) tyrosine kinase (TK) inhibitors useful in the treatment of human tumours. Among the top 10 generated hypotheses, the second hypothesis, with one hydrogen bond acceptor, one ring aromatic and three hydrophobic features, was found to be the best on the basis of Cat Scramble validation as well as test set prediction (r(training) = 0.89, r(test) = 0.82). The model also maps well to the external test set molecules as well as clinically active molecules and corroborates the docking studies. Finally, 10 hits were identified as potential leads after virtual screening of ZINC database for EGFR TK inhibition. The study may facilitate the designing and discovery of novel EGFR TK inhibitors.
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Affiliation(s)
- A K Gupta
- Medicinal and Process Chemistry Division, Central Drug Research Institute, CSIR, Lucknow, India
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Gupta AK, Chakroborty S, Srivastava K, Puri SK, Saxena AK. Pharmacophore Modeling of Substituted 1,2,4-Trioxanes for Quantitative Prediction of their Antimalarial Activity. J Chem Inf Model 2010; 50:1510-20. [DOI: 10.1021/ci100180e] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Amit K. Gupta
- Medicinal and Process Chemistry Division and Parasitology Division, Central Drug Research Institute, CSIR, Lucknow, 226001, India
| | - S. Chakroborty
- Medicinal and Process Chemistry Division and Parasitology Division, Central Drug Research Institute, CSIR, Lucknow, 226001, India
| | - Kumkum Srivastava
- Medicinal and Process Chemistry Division and Parasitology Division, Central Drug Research Institute, CSIR, Lucknow, 226001, India
| | - Sunil K. Puri
- Medicinal and Process Chemistry Division and Parasitology Division, Central Drug Research Institute, CSIR, Lucknow, 226001, India
| | - Anil K. Saxena
- Medicinal and Process Chemistry Division and Parasitology Division, Central Drug Research Institute, CSIR, Lucknow, 226001, India
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Kristam R, Gillet VJ, Lewis RA, Thorner D. Comparison of Conformational Analysis Techniques To Generate Pharmacophore Hypotheses Using Catalyst. J Chem Inf Model 2005; 45:461-76. [PMID: 15807512 DOI: 10.1021/ci049731z] [Citation(s) in RCA: 65] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Generation of reliable pharmacophore models is a key strategy in drug design. The quality of a pharmacophore model is known to depend on several factors, with the quality of the conformer sets used perhaps being one of the most important. The goal of this study was to compare different conformational analysis methods to determine if one was superior to the others for pharmacophore generation using Catalyst/HypoGen. The five methods selected were Catalyst/Fast, Catalyst/Best, Omega, Chem-X and MacroModel. Data sets for which Catalysts models had previously been published were selected using defined quality measures. Hypotheses were generated for each of the data sets and the performance of the different conformational analysis methods was compared using both quantitative (cost and correlation coefficients) and qualitative measures (by comparing the hypotheses in terms of the features present and their spatial relationships). Two main conclusions emerged from the study. First, it was not always possible to replicate the literature results. The reasons for these failures are explored in detail, and a template for use in publications that apply the Catalyst methodology is proposed. Second, the faster rule-based methods for conformational analysis give pharmacophore models that are just as good as, and in some cases better than, the models generated using the slower, more rigorous approaches.
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Affiliation(s)
- Rajendra Kristam
- Department of Information Studies, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, U.K
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