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Dey PK, Dutta R, Ray M, Jakkula P, Banerjee S, Qureshi IA, Gayen S, Amin SA. Fragment-based QSAR study to explore the structural requirements of DPP-4 inhibitors: a stepping stone towards better type 2 diabetes mellitus management. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2024; 35:483-504. [PMID: 38904353 DOI: 10.1080/1062936x.2024.2366886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 06/05/2024] [Indexed: 06/22/2024]
Abstract
Dipeptidyl peptidase-4 (DPP-4) inhibitors belong to a prominent group of pharmaceutical agents that are used in the governance of type 2 diabetes mellitus (T2DM). They exert their antidiabetic effects by inhibiting the incretin hormones like glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide which, play a pivotal role in the regulation of blood glucose homoeostasis in our body. DPP-4 inhibitors have emerged as an important class of oral antidiabetic drugs for the treatment of T2DM. Surprisingly, only a few 2D-QSAR studies have been reported on DPP-4 inhibitors. Here, fragment-based QSAR (Laplacian-modified Bayesian modelling and Recursive partitioning (RP) approaches have been utilized on a dataset of 108 DPP-4 inhibitors to achieve a deeper understanding of the association among their molecular structures. The Bayesian analysis demonstrated satisfactory ROC values for the training as well as the test sets. Meanwhile, the RP analysis resulted in decision tree 3 with 2 leaves (Tree 3: 2 leaves). This present study is an effort to get an insight into the pivotal fragments modulating DPP-4 inhibition.
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Affiliation(s)
- P K Dey
- Department of Pharmaceutical Technology, JIS University, Kolkata, West Bengal, India
| | - R Dutta
- Department of Pharmaceutical Technology, JIS University, Kolkata, West Bengal, India
| | - M Ray
- Department of Pharmaceutical Technology, JIS University, Kolkata, West Bengal, India
| | - P Jakkula
- Department of Biotechnology and Bioinformatics, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana, India
| | - S Banerjee
- Department of Pharmaceutical Technology, JIS University, Kolkata, West Bengal, India
| | - I A Qureshi
- Department of Biotechnology and Bioinformatics, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana, India
| | - S Gayen
- Laboratory of Drug Design and Discovery, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - S A Amin
- Department of Pharmaceutical Technology, JIS University, Kolkata, West Bengal, India
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2
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Banat R, Daoud S, Taha MO. Ligand-based pharmacophore modeling and machine learning for the discovery of potent aurora A kinase inhibitory leads of novel chemotypes. Mol Divers 2024:10.1007/s11030-024-10814-y. [PMID: 38446372 DOI: 10.1007/s11030-024-10814-y] [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: 10/02/2023] [Accepted: 01/19/2024] [Indexed: 03/07/2024]
Abstract
Aurora-A (AURKA) is serine/threonine protein kinase involved in the regulation of numerous processes of cell division. Numerous studies have demonstrated strong association between AURKA and cancer. AURKA is overexpressed in many cancers, such as colon, breast and prostate cancers. Consequently, AURKA has emerged as promising target for therapeutic intervention in cancer management. Herein, we describe a computational workflow for the discovery of novel anti-AURKA inhibitory leads starting with ligand-based assessment of the pharmacophoric space of six diverse sets of inhibitors. Subsequently, machine learning/QSAR modeling was coupled with genetic function algorithm to search for the best possible combination of machine learner, ligand-based pharmacophore(s) and molecular descriptors capable of explaining variation in anti-AURKA bioactivities within a collected list of inhibitors. Two learners succeeded in achieving acceptable structure/activity correlations, namely, random forests and extreme gradient boosting (XGBoost). Three pharmacophores emerged in the successful ML models. These were then used as 3D search queries to mine the National Cancer Institute database for novel anti-AURKA leads. Top-ranking 38 hits were assessed in vitro for their anti-AURKA bioactivities. Among them, three compounds exhibited promising dose-response curves, demonstrating experimental IC50 values ranging from sub-micromolar to low micromolar values. Remarkably, two of these compounds are of novel chemotypes.
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Affiliation(s)
- Rajaa Banat
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan
| | - Safa Daoud
- Department of Pharmaceutical Chemistry and Pharmacognosy, Faculty of Pharmacy, Applied Sciences Private University, Amman, Jordan
| | - Mutasem Omar Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan.
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3
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Zerroug E, Belaidi S, Chtita S, Tuffaha G, AbulQais F, Kciuk M, Dubey A, Taha MO. Structure‐Based Approaches for the Prediction of Alzheimer's Disease Inhibitors: Comparative Interactions Analysis, Pharmacophore Modeling and Molecular Dynamics Simulations. ChemistrySelect 2024; 9. [DOI: 10.1002/slct.202303307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 12/18/2023] [Indexed: 07/10/2024]
Abstract
AbstractDue to its significant role in neurodegeneration, Cyclin‐dependent kinase 5 (CDK5) has emerged as a potential target for addressing neuropathological disorders, including Alzheimer's disease (AD). The application of CDK5 inhibitors has demonstrated promise in the treatment of AD. This prompted us to model this interesting target using a computational workflow named Docking‐based Comparative Intermolecular Contacts Analysis (dbCICA). Approaches including 3D‐QSAR, genetic algorithm, and pharmacophore modeling were employed to discover new CDK inhibitors.
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Affiliation(s)
- Enfale Zerroug
- Group of Computational and Pharmaceutical Chemistry LMCE Laboratory University of Biskra, BP 145 Biskra 07000 Algeria
| | - Salah Belaidi
- Group of Computational and Pharmaceutical Chemistry LMCE Laboratory University of Biskra, BP 145 Biskra 07000 Algeria
| | - Samir Chtita
- Faculty of Sciences Ben M'Sik Hassan II University of Casablanca Sidi Othman, Casablanca Morocco
| | | | - Faizan AbulQais
- Department of Agricultural Microbiology Aligarh Muslim University Aligarh UP 202002 India
| | - Mateusz Kciuk
- Doctoral School of Exact and Natural Sciences University of Lodz Banacha Street 12/16 90-237 Lodz Poland
- Department of Molecular Biotechnology and Genetics University of Lodz Banacha 12/16 90-237 Lodz Poland
| | - Amit Dubey
- Department of Pharmacology Saveetha Dental College and Hospital Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India
| | - Mutasem O. Taha
- Drug Discovery Unit Department of Pharmaceutical Sciences Faculty of Pharmacy University of Jordan 11942 Amman Jordan
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Al-Sha’er MA, Taha M, Alelaimat MA. Development of phosphoinositide 3-kinase delta (PI3Kδ) inhibitors as potential anticancer agents through the generation of ligand-based pharmacophores and biological screening. Med Chem Res 2023; 32:1109-1121. [DOI: 10.1007/s00044-023-03057-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 03/27/2023] [Indexed: 07/10/2024]
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5
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Rusinov VL, Sapozhnikova IM, Spasov AA, Chupakhin ON. Fused azoloazines with antidiabetic activity. Russ Chem Bull 2022. [DOI: 10.1007/s11172-022-3687-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
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6
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Al-Tawil MF, Daoud S, Hatmal MM, Taha MO. Discovery of new Cdc2-like kinase 4 (CLK4) inhibitors via pharmacophore exploration combined with flexible docking-based ligand/receptor contact fingerprints and machine learning. RSC Adv 2022; 12:10686-10700. [PMID: 35424985 PMCID: PMC8982525 DOI: 10.1039/d2ra00136e] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 03/31/2022] [Indexed: 11/21/2022] Open
Abstract
Cdc2-like kinase 4 (CLK4) inhibitors are of potential therapeutic value in many diseases particularly cancer. In this study, we combined extensive ligand-based pharmacophore exploration, ligand–receptor contact fingerprints generated by flexible docking, physicochemical descriptors and machine learning-quantitative structure–activity relationship (ML-QSAR) analysis to investigate the pharmacophoric/binding requirements for potent CLK4 antagonists. Several ML methods were attempted to tie these properties with anti-CLK4 bioactivities including multiple linear regression (MLR), random forests (RF), extreme gradient boosting (XGBoost), probabilistic neural network (PNN), and support vector regression (SVR). A genetic function algorithm (GFA) was combined with each method for feature selection. Eventually, GFA-SVR was found to produce the best self-consistent and predictive model. The model selected three pharmacophores, three ligand–receptor contacts and two physicochemical descriptors. The GFA-SVR model and associated pharmacophore models were used to screen the National Cancer Institute (NCI) structural database for novel CLK4 antagonists. Three potent hits were identified with the best one showing an anti-CLK4 IC50 value of 57 nM. Ligand-based pharmacophores, ligand–receptor contact fingerprints, physicochemical descriptors and machine learning were combined to probe binding of potent CLK4 antagonists. GFA-SVR gave the best model. Virtual screening identified 3 nanomolar hits.![]()
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Affiliation(s)
- Mai Fayiz Al-Tawil
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan Amman 11942 Jordan
| | - Safa Daoud
- Department of Pharmaceutical Chemistry and Pharmacognosy, Faculty of Pharmacy, Applied Sciences Private University Amman Jordan
| | - Ma'mon M Hatmal
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, The Hashemite University PO Box 330127 Zarqa 13133 Jordan
| | - Mutasem Omar Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan Amman 11942 Jordan
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7
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Shahin R, Al-Hashimi NN, Daoud NEH, Aljamal S, Shaheen O. QSAR-guided pharmacophoric modeling reveals important structural requirements for Polo kinase 1 (Plk1) inhibitors. J Mol Graph Model 2021; 109:108022. [PMID: 34562852 DOI: 10.1016/j.jmgm.2021.108022] [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: 04/14/2021] [Revised: 09/02/2021] [Accepted: 09/02/2021] [Indexed: 10/20/2022]
Abstract
Targeting Polo-like kinase 1 (Plk1) by molecular inhibitors is being a promising approach for tumor therapy. Nevertheless, insufficient methodical analyses have been done to characterize the interactions inside the Plk1 binding pocket. In this study, an extensive combined ligand and structure-based drug design workflow was conducted to data-mine the structural requirements for Plk1 inhibition. Consequently, the binding modes of 368 previously known Plk1 inhibitors were investigated by pharmacophore generation technique. The resulted pharmacophores were engaged in the context of Genetic function algorithm (GFA) and Multiple linear regression (MLR) analyses to search for a prognostic QSAR model. The most successful QSAR model was with statistical criteria of (r2277 = 0.76, r2adj = 0.76, r2pred = 0.75, Q2 = 0.73). Our QSAR-selected pharmacophores were validated by Receiver Operating Characteristic (ROC) curve analysis. Later on, the best QSAR model and its associated pharmacophoric hypotheses (HypoB-T4-5, HypoI-T2-7, HypoD-T4-3, and HypoC-T3-3) were used to identify new Plk1 inhibitory hits retrieved from the National Cancer Institute (NCI) database. The most potent hits exhibited experimental anti-Plk1 IC50 of 1.49, 3.79. 5.26 and 6.35 μM. Noticeably, our hits, were found to interact with the Plk1 kinase domain through some important amino acid residues namely, Cys67, Lys82, Cys133, Phe183, and Asp194.
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Affiliation(s)
- Rand Shahin
- Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, The Hashemite University, Zarqa, 13133, Jordan.
| | - Nabil N Al-Hashimi
- Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, The Hashemite University, Zarqa, 13133, Jordan.
| | - Nour El-Huda Daoud
- Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, The Hashemite University, Zarqa, 13133, Jordan.
| | - Salah Aljamal
- Faculty of Pharmacy, University of Jordan, Amman, Jordan.
| | - Omar Shaheen
- Department of Pharmacology, Faculty of Medicine, University of Jordan, Amman, Jordan.
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Zhao J, Xu P, Liu X, Ji X, Li M, Dev S, Qu X, Lu W, Niu B. Application of machine learning methods for the development of antidiabetic drugs. Curr Pharm Des 2021; 28:260-271. [PMID: 34161205 DOI: 10.2174/1381612827666210622104428] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 05/10/2021] [Indexed: 11/22/2022]
Abstract
Diabetes is a chronic non-communicable disease caused by several different routes, which has attracted increasing attention. In order to speed up the development of new selective drugs, machine learning (ML) technology has been applied in the process of diabetes drug development, which opens up a new blueprint for drug design. This review provides a comprehensive portrayal of the application of ML in antidiabetic drug use.
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Affiliation(s)
- Juanjuan Zhao
- Department of Chemistry, College of Sciences, Shanghai University, 200444, China
| | - Pengcheng Xu
- Materials Genome Institute, Shanghai University, Shanghai 200444, China
| | - Xiujuan Liu
- Department of Chemistry, College of Sciences, Shanghai University, 200444, China
| | - Xiaobo Ji
- Department of Chemistry, College of Sciences, Shanghai University, 200444, China
| | - Minjie Li
- Department of Chemistry, College of Sciences, Shanghai University, 200444, China
| | - Sooranna Dev
- Department of Obstetrics and Gynaecology, Imperial College London, Fulham Road, London SW10 9 NH, United Kingdom
| | - Xiaosheng Qu
- National Engineering Laboratory of Southwest Endangered Medicinal Resources Development, Guangxi Botanical Garden of Medicinal Plants, No. 189, Changgang Road, 530023, Nanning, China
| | - Wencong Lu
- Department of Chemistry, College of Sciences, Shanghai University, 200444, China
| | - Bing Niu
- School of Life Sciences, Shanghai University, 200444, China
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9
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Mansi I, Al-Sha'er MA, Mhaidat N, Taha M. Ligand Based Pharmacophore Modeling Followed by Biological Screening Lead to Discovery of Novel PDK1 Inhibitors as Anticancer Agents. Anticancer Agents Med Chem 2020; 20:476-485. [PMID: 31889497 DOI: 10.2174/1871520620666191224110600] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 08/21/2019] [Accepted: 10/22/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND Phosphoinositide-Dependent Kinase-1 (PDK1) is a serine/threonine kinase, which belongs to AGC kinase family required by cancer cells. METHODS Pharmacophoric space of 86 PDK1 inhibitors using six diverse sets of inhibitors was explored to identify high-quality pharmacophores. The best combination of pharmacophoric models and physicochemical descriptors was selected by genetic algorithm-based QSAR analysis that can elucidate the variation of bioactivity within the training inhibitors. Two successful orthogonal pharmacophores emerged in the optimum QSAR equation (r2 69 = 0.90, r2 LOO= 0.86, F= 51.92, r2 PRESS against 17 test inhibitors = 0.79). Receiver Operating Characteristic (ROC) curve analyses were used to estimate the QSAR-selected pharmacophores. RESULTS 5 out of 11 compounds tested had shown potential intracellular PDK1 inhibition with the highest inhibition percent for compounds 92 and 93 as follows; 90 and 92% PDK1 inhibition, respectively. CONCLUSION PDK1 inhibitors are potential anticancer agents that can be discovered by combination method of ligand based design with QSAR and ROC analysis.
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Affiliation(s)
- Iman Mansi
- Faculty of Pharmaceutical Sciences, The Hashemite University, P.O. Box 330127 Zarqa, 13133, Jordan
| | | | - Nizar Mhaidat
- Clinical Pharmacy Department, Faculty of Pharmacy, Jordan University of Science & Technology, Irbid, Jordan
| | - Mutasem Taha
- Drug Design Center, Faculty of Pharmacy, University of Jordan, Amman, Jordan
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Champion C, Barigye SJ, Wei W, Liu Z, Labute P, Moitessier N. Atom Type Independent Modeling of the Conformational Energy of Benzylic, Allylic, and Other Bonds Adjacent to Conjugated Systems. J Chem Inf Model 2019; 59:4750-4763. [PMID: 31589815 DOI: 10.1021/acs.jcim.9b00581] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Applications of computational methods to predict binding affinities for protein/drug complexes are routinely used in structure-based drug discovery. Applications of these methods often rely on empirical force fields (FFs) and their associated parameter sets and atom types. However, it is widely accepted that FFs cannot accurately cover the entire chemical space of drug-like molecules, due to the restrictive cost of parametrization and the poor transferability of existing parameters. To address these limitations, initiatives have been carried out to develop more transferable methods, in order to allow for more rigorous descriptions of any drug-like molecule. We have previously reported H-TEQ, a method which does not rely on atom types and incorporates well established chemical principles to assign parameters to organic molecules. The previous implementation of H-TEQ (a torsional barrier prediction method) only covered saturated and lone pair containing molecules; here, we report our efforts to incorporate conjugated systems into our model. The next step was the evaluation of the introduction of unsaturations. The developed model (H-TEQ3.0) has been validated on a wide variety of molecules containing heteroaromatic groups, alkyls, and fused ring systems. Our method performs on par with one of the most commonly used FFs (GAFF2), without relying on atom types or any prior parametrization.
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Affiliation(s)
- Candide Champion
- Department of Chemistry , McGill University , 801 Sherbrooke Street W. , Montréal , QC , Canada H3A 0B8
| | - Stephen J Barigye
- Department of Chemistry , McGill University , 801 Sherbrooke Street W. , Montréal , QC , Canada H3A 0B8
| | - Wanlei Wei
- Department of Chemistry , McGill University , 801 Sherbrooke Street W. , Montréal , QC , Canada H3A 0B8
| | - Zhaomin Liu
- Department of Chemistry , McGill University , 801 Sherbrooke Street W. , Montréal , QC , Canada H3A 0B8
| | - Paul Labute
- Chemical Computing Group Inc. , 1010 Sherbrooke Street W. , Montréal , QC , Canada H3A 2R7
| | - Nicolas Moitessier
- Department of Chemistry , McGill University , 801 Sherbrooke Street W. , Montréal , QC , Canada H3A 0B8
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Musoev A, Numonov S, You Z, Gao H. Discovery of Novel DPP-IV Inhibitors as Potential Candidates for the Treatment of Type 2 Diabetes mellitus Predicted by 3D QSAR Pharmacophore Models, Molecular Docking and de novo Evolution. Molecules 2019; 24:molecules24162870. [PMID: 31394858 PMCID: PMC6720998 DOI: 10.3390/molecules24162870] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2019] [Revised: 08/02/2019] [Accepted: 08/05/2019] [Indexed: 12/31/2022] Open
Abstract
Dipeptidyl peptidase-IV (DPP-IV) rapidly breaks down the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP). Thus, the use of DPP-IV inhibitors to retard the degradation of endogenous GLP-1 is a possible mode of therapy correcting the defect in incretin-related physiology. The aim of this study is to find a new small molecule and explore the inhibition activity to the DPP-IV enzyme using a computer aided simulation. In this study, the predicted compounds were suggested as potent anti-diabetic candidates. Chosen structures were applied following computational strategies: The generation of the three-dimensional quantitative structure-activity relationship (3D QSAR) pharmacophore models, virtual screening, molecular docking, and de novo Evolution. The method also validated by performing re-docking and cross-docking studies of seven protein systems for which crystal structures were available for all bound ligands. The molecular docking experiments of predicted compounds within the binding pocket of DPP-IV were conducted. By using 25 training set inhibitors, ten pharmacophore models were generated, among which hypo1 was the best pharmacophore model with the best predictive power on account of the highest cost difference (352.03), the lowest root mean squared deviation (RMSD) (2.234), and the best correlation coefficient (0.925). Hypo1 pharmacophore model was used for virtual screening. A total of 161 compounds including 120 from the databases, 25 from the training set, 16 from the test set were selected for molecular docking. Analyzing the amino acid residues of the ligand-receptor interaction, it can be concluded that Arg125, Glu205, Glu206, Tyr547, Tyr662, and Tyr666 are the main amino acid residues. The last step in this study was de novo Evolution that generated 11 novel compounds. The derivative dpp4_45_Evo_1 by all scores CDOCKER_ENERGY (CDOCKER, -41.79), LigScore1 (LScore1, 5.86), LigScore2 (LScore2, 7.07), PLP1 (-112.01), PLP2 (-105.77), PMF (-162.5)—have exceeded the control compound. Thus the most active compound among 11 derivative compounds is dpp4_45_Evo_1. Additionally, for derivatives dpp4_42_Evo_1, dpp4_43_Evo2, dpp4_46_Evo_4, and dpp4_47_Evo_2, significant upward shifts were recorded. The consensus score for the derivatives of dpp4_45_Evo_1 from 1 to 6, dpp4_43_Evo2 from 4 to 6, dpp4_46_Evo_4 from 1 to 6, and dpp4_47_Evo_2 from 0 to 6 were increased. Generally, predicted candidates can act as potent occurring DPP-IV inhibitors given their ability to bind directly to the active sites of DPP-IV. Our result described that the 6 re-docked and 27 cross-docked protein-ligand complexes showed RMSD values of less than 2 Å. Further investigation will result in the development of novel and potential antidiabetic drugs.
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Affiliation(s)
- Azizullo Musoev
- Key Laboratory of Plant Resources and Chemistry in Arid Regions, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi 830011, China
- University of Chinese Academy of Sciences, Beijing 100190, China
| | - Sodik Numonov
- Key Laboratory of Plant Resources and Chemistry in Arid Regions, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi 830011, China
- Research Institution "Chinese-Tajik Innovation Center for Natural Products", Dushanbe 734063, Tajikistan
| | - Zhuhong You
- Key Laboratory of Plant Resources and Chemistry in Arid Regions, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi 830011, China
| | - Hongwei Gao
- School of Life Science, Ludong University, Yantai 264025, China.
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12
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Ismail MM, Farrag AM, Harras MF. Novel 1,3,4-Triaryl Pyrazoles: Synthesis, QSAR Studies and Cytotoxicity against Breast Cancer. Anticancer Agents Med Chem 2019; 19:948-959. [DOI: 10.2174/1871520619666190207094610] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 12/20/2018] [Accepted: 01/10/2019] [Indexed: 12/29/2022]
Abstract
Background:The existence of drug-resistance and lack of selectivity encourages scientists to search for novel and more selective cytotoxic agents.Objective:In this work, novel 1,3,4-triarylpyrazole derivatives were synthesized to study their cytotoxicity on MCF7 (human breast Cell Line). In addition, QSAR studies were performed to show the relation between the cytotoxic activity and the structural features of our new synthesized pyrazole derivatives.Methods:Pyrazole-4-carbaldehyde derivative 3 was utilized as a starting material for the preparation of the new pyarazole derivatives. These target compounds were screened for their cytotoxic activity against MCF-7 followed by study cell cycle of the most active compounds. Finally, pharmacophore modeling and QSAR Studies was carried out.Results:Among these compounds; 5d and 8b showed the highest anti-proliferative activity (IC50 = 4.9 and 2.11 µM, respectively). Flow cytometric analysis showed that, compounds 5d and 8b arrested the cell cycle in addition to induction of apoptosis in MCF7 cells. Moreover, their stimulation effect on caspases 3/7 was examined to explore their mechanism of induction of apoptosis and the results showed that their proapoptotic activity could be due to the activation of caspases 3/7.Conclusion:Pyrazole derivatives 5d and 8b displayed potent bioactivities, indicating that these compounds could be considered as a new lead for more investigation in the future
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Affiliation(s)
- Magda M.F. Ismail
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy (Girls), Al-Azhar University, Cairo, Egypt
| | - Amel M. Farrag
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy (Girls), Al-Azhar University, Cairo, Egypt
| | - Marwa F. Harras
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy (Girls), Al-Azhar University, Cairo, Egypt
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13
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Ojeda-Montes MJ, Gimeno A, Tomas-Hernández S, Cereto-Massagué A, Beltrán-Debón R, Valls C, Mulero M, Pujadas G, Garcia-Vallvé S. Activity and selectivity cliffs for DPP-IV inhibitors: Lessons we can learn from SAR studies and their application to virtual screening. Med Res Rev 2018; 38:1874-1915. [PMID: 29660786 DOI: 10.1002/med.21499] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Revised: 02/06/2018] [Accepted: 03/02/2018] [Indexed: 12/13/2022]
Abstract
The inhibition of dipeptidyl peptidase-IV (DPP-IV) has emerged over the last decade as one of the most effective treatments for type 2 diabetes mellitus, and consequently (a) 11 DPP-IV inhibitors have been on the market since 2006 (three in 2015), and (b) 74 noncovalent complexes involving human DPP-IV and drug-like inhibitors are available at the Protein Data Bank (PDB). The present review aims to (a) explain the most important activity cliffs for DPP-IV noncovalent inhibition according to the binding site structure of DPP-IV, (b) explain the most important selectivity cliffs for DPP-IV noncovalent inhibition in comparison with other related enzymes (i.e., DPP8 and DPP9), and (c) use the information deriving from this activity/selectivity cliff analysis to suggest how virtual screening protocols might be improved to favor the early identification of potent and selective DPP-IV inhibitors in molecular databases (because they have not succeeded in identifying selective DPP-IV inhibitors with IC50 ≤ 100 nM). All these goals are achieved with the help of available homology models for DPP8 and DPP9 and an analysis of the structure-activity studies used to develop the noncovalent inhibitors that form part of some of the complexes with human DPP-IV available at the PDB.
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Affiliation(s)
- María José Ojeda-Montes
- Research Group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, Tarragona, Spain
| | - Aleix Gimeno
- Research Group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, Tarragona, Spain
| | - Sarah Tomas-Hernández
- Research Group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, Tarragona, Spain
| | - Adrià Cereto-Massagué
- Research Group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, Tarragona, Spain
| | - Raúl Beltrán-Debón
- Research Group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, Tarragona, Spain
| | - Cristina Valls
- Research Group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, Tarragona, Spain
| | - Miquel Mulero
- Research Group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, Tarragona, Spain
| | - Gerard Pujadas
- Research Group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, Tarragona, Spain.,EURECAT, TECNIO, CEICS, Avinguda Universitat 1, Reus, Spain
| | - Santiago Garcia-Vallvé
- Research Group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, Tarragona, Spain.,EURECAT, TECNIO, CEICS, Avinguda Universitat 1, Reus, Spain
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Shahin R, Mansi I, Swellmeen L, Alwidyan T, Al-Hashimi N, Al-Qarar'h Y, Shaheen O. Ligand-based computer aided drug design reveals new tropomycin receptor kinase a (TrkA) inhibitors. J Mol Graph Model 2018; 80:327-352. [PMID: 29454290 DOI: 10.1016/j.jmgm.2018.01.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Revised: 12/26/2017] [Accepted: 01/10/2018] [Indexed: 01/01/2023]
Abstract
Targeting tropomycin kinase A (TrkA) by small molecule inhibitors is considered as a promising strategy for treating several human cancers. To achieve this goal, a ligand based QSAR model was applied using the Discovery studio 4.5 (DS 4.5). Hence, a total list of 161 TrkA inhibitors was investigated. The TrkA inhibitors were extensively explored to detect their optimal physicochemical properties and pharmacophoric binding modes, which were converted into numeric descriptors and allowed to compete within the context of the Genetic Function Algorithm (GFA) approximations to find the subset of terms that correlates best with the activity. The resulted successful QSAR equation had statistical criteria of (r2129=0.67, r2LOO=0.61 r2PRESS against 32 external test inhibitors=0.50). Afterwards, the most successful pharmacophore: HypoB-T5-3, was used to screen compounds within the National Cancer institute (NCI) database. Only 41 compounds were retrieved and 21 of them exhibited anti-TrkA activity. The most potent hit had an IC50 value of 2.4μM. Later, upon docking the active hits into the TrkA binding pocket, important interactions were revealed including hydrogen bonding with the amino acids Asp668 and Lys544 in addition to the cation-π interactions with the sidechain of Arg559.
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Affiliation(s)
- Rand Shahin
- Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical sciences, Hashemite University, Zarqa, Jordan.
| | - Iman Mansi
- Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmaceutical sciences, Hashemite University, Zarqa, Jordan.
| | - Lubna Swellmeen
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, Zarqa University, Zarqa, Jordan.
| | - Tahani Alwidyan
- Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmaceutical sciences, Hashemite University, Zarqa, Jordan
| | - Nabil Al-Hashimi
- Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical sciences, Hashemite University, Zarqa, Jordan
| | - Yaser Al-Qarar'h
- Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical sciences, Hashemite University, Zarqa, Jordan
| | - Omar Shaheen
- Department of Pharmacology, Faculty of Medicine, University of Jordan, Amman, Jordan.
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15
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Al-Sha'er MA, Taha MO. Ligand-based modeling of Akt3 lead to potent dual Akt1/Akt3 inhibitor. J Mol Graph Model 2018; 83:153-166. [PMID: 29456101 DOI: 10.1016/j.jmgm.2018.02.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 01/01/2018] [Accepted: 02/02/2018] [Indexed: 11/26/2022]
Abstract
Akt1 and Akt3 are important serine/threonine-specific protein kinases involved in G2 phase required by cancer cells to maintain cell cycle and to prevent cell death. Accordingly, inhibitors of these kinases should have potent anti-cancer properties. This prompted us to use pharmacophore/QSAR modeling to identify optimal binding models and physicochemical descriptors that explain bioactivity variation within a set of 74 diverse Akt3 inhibitors. Two successful orthogonal pharmacophores were identified and further validated using receiver operating characteristic (ROC) curve analyses. The pharmacophoric models and associated QSAR equation were applied to screen the national cancer institute (NCI) list of compounds for new Akt3 inhibitors. Six hits showed significant experimental anti-Akt3 IC50 values, out of which one compound exhibited dual low micromolar anti-Akt1 and anti-Akt3 inhibitory profiles.
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Affiliation(s)
| | - Mutasem O Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, The University of Jordan, Amman, Jordan.
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16
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Yao S, Agyei D, Udenigwe CC. Structural Basis of Bioactivity of Food Peptides in Promoting Metabolic Health. ADVANCES IN FOOD AND NUTRITION RESEARCH 2018; 84:145-181. [PMID: 29555068 DOI: 10.1016/bs.afnr.2017.12.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Bioactive peptides have many structural features that enable them to become functional in controlling several biological processes in the body, especially those related to metabolic health. This chapter provides an overview of the multiple targets of food-derived peptides against metabolic health problems (e.g., hypertension, dyslipidemia, hyperglycemia, oxidative stress) and discusses the importance of structural chemistry in determining the bioactivities of peptides and protein hydrolysates.
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Affiliation(s)
- Shixiang Yao
- Southwest University, Chongqing, PR China; University of Ottawa, Ottawa, ON, Canada
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18
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Al-Sha'er MA, Almazari IS, Taha MO. Discovery of novel potent nuclear factor kappa-B inhibitors (IKK-β) via extensive ligand-based modeling and virtual screening. J Mol Recognit 2016; 30. [PMID: 28008665 DOI: 10.1002/jmr.2604] [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] [Received: 08/25/2016] [Revised: 10/23/2016] [Accepted: 11/22/2016] [Indexed: 12/12/2022]
Abstract
Inhibitor kappa-B kinase-beta (IKK-β) controls the activation of nuclear transcription factor kappa-B and has been linked to inflammation and cancer. Therefore, inhibitors of this kinase should have potent anti-inflammatory and anticancer properties. Accordingly, we explored the pharmacophoric space of 218 IKK-β inhibitors to identify high-quality binding models. Subsequently, genetic algorithm-based quantitative structure activity relationship (QSAR) analysis was employed to select the best possible combination of pharmacophoric models and physicochemical descriptors that explain bioactivity variation among training compounds. Three successful pharmacophores emerged in 2 optimal QSAR equations (r12175 = 0.733, r12LOO = 0.52, F1 = 65.62, r12PRESS against 43 test inhibitors = 0.63 and r22175 = 0.683, r22LOO = 0.52, F2 = 72.66, r22PRESS against 43 test inhibitors = 0.65). Two pharmacophores were merged in a single binding model. Receiver operating characteristic curve validation proved the excellent qualities of this model. The merged pharmacophore and the associated QSAR equations were applied to screen the National Cancer Institute list of compounds. Ten hits were found to exhibit potent anti-IKK-β bioactivity, out of which, one illustrates IC50 of 11.0nM.
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Affiliation(s)
| | | | - Mutasem O Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, The University of Jordan, Amman, Jordan
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Computer-aided discovery of new FGFR-1 inhibitors followed by in vitro validation. Future Med Chem 2016; 8:1841-1869. [PMID: 27643626 DOI: 10.4155/fmc-2016-0056] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
AIM FGFR-1 is an oncogenic kinase involved in several cancers. FGFR1-specific inhibitors have shown promising results against several human cancers prompting us to model this interesting target. Toward the end, we implemented elaborate ligand-based and structure-based computational workflows to explore the pharmacophoric requirements for potent FGFR-1 inhibitors. Results & methodology: Structure-based and ligand-based modeling applied on 59 diverse FGFR-1 inhibitors yielded novel pharmacophore and quantitative structure-activity relationship models that were used to scan the National Cancer Institute's structural database for novel leads. Four potent hits were captured, with the most active having IC50 of 426 nM. Identities and purities of active hits were established using nuclear magnetic resonance and mass spectroscopy. CONCLUSION Elaborate ligand-based (pharmacophore/quantitaive structure-activity relationship) and structure-based (docking-based comparative intermolecular contacts analysis) modeling provided deep understanding of ligand binding within FGFR-1 as evidenced by the virtually captured new potent leads.
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Aboalhaija NH, Zihlif MA, Taha MO. Discovery of new selective cytotoxic agents against Bcl-2 expressing cancer cells using ligand-based modeling. Chem Biol Interact 2016; 250:12-26. [PMID: 26954606 DOI: 10.1016/j.cbi.2016.03.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2015] [Revised: 02/28/2016] [Accepted: 03/02/2016] [Indexed: 12/11/2022]
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Dave LA, Hayes M, Moughan PJ, Rutherfurd SM. Novel Dipeptidyl Peptidase IV Inhibitory and Antioxidant Peptides Derived from Human Gastrointestinal Endogenous Proteins. Int J Pept Res Ther 2016. [DOI: 10.1007/s10989-016-9515-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Ligand-based modeling of diverse aryalkylamines yields new potent P-glycoprotein inhibitors. Eur J Med Chem 2016; 110:204-23. [PMID: 26840362 DOI: 10.1016/j.ejmech.2016.01.034] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Revised: 11/14/2015] [Accepted: 01/18/2016] [Indexed: 02/02/2023]
Abstract
The P-glycoprotein (P-gp) efflux pump has an important role as a natural detoxification system in many types of normal and cancer cells. P-gp is implicated in multiple drug resistance (MDR) exhibited by several types of cancer against a multitude of anticancer chemotherapeutic agents, and therefore, it is clinically validated target for cancer therapy. Accordingly, in this study we combined exhaustive pharmacophore modeling and quantitative structure-activity relationship (QSAR) analysis to explore the structural requirements for potent P-gp inhibitors employing 130 known P-gp ligands. Genetic function algorithm (GFA) coupled with k nearest neighbor (kNN) or multiple linear regression (MLR) analyses were employed to build self-consistent and predictive QSAR models based on optimal combinations of pharmacophores and physicochemical descriptors. Successful pharmacophores were complemented with exclusion spheres to optimize their receiver operating characteristic curve (ROC) profiles. Optimal QSAR models and their associated pharmacophore hypotheses were validated by identification and experimental evaluation of new promising P-gp inhibitory leads retrieved from the National Cancer Institute (NCI) structural database. Several potent hits were captured. The most potent hit decreased the IC50 of doxorubicin from 0.906 to 0.190 μM on doxorubicin resistant MCF7 cell-line.
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Identification of novel inhibitors for Pim-1 kinase using pharmacophore modeling based on a novel method for selecting pharmacophore generation subsets. J Comput Aided Mol Des 2015; 30:39-68. [PMID: 26685860 DOI: 10.1007/s10822-015-9887-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2015] [Accepted: 12/07/2015] [Indexed: 10/22/2022]
Abstract
Targeting Proviral integration-site of murine Moloney leukemia virus 1 kinase, hereafter called Pim-1 kinase, is a promising strategy for treating different kinds of human cancer. Headed for this a total list of 328 formerly reported Pim-1 kinase inhibitors has been explored and divided based on the pharmacophoric features of the most active molecules into 10 subsets projected to represent potential active binding manners accessible to ligands within the binding pocket of Pim-1 kinase. Discovery Studio 4.1 (DS 4.1) was employed to detect potential pharmacophoric active binding manners anticipated by Pim-1 Kinase inhibitors. The pharmacophoric models were then allowed to compete within Quantitative Structure Activity Relationship (QSAR) framework with other 2D descriptors. Accordingly Genetic algorithm and multiple linear regression investigation were engaged to find the finest QSAR equation that has the best predictive power r262(2) = 0.70, F = 119.14, rLOO(2) = 0.693, rPRESS(2) against 66 external test inhibitors = 0.71 q(2) = 0.55. Three different pharmacophores appeared in the successful QSAR equation this represents three different binding modes for inhibitors within the Pim-1 kinase binding pocket. Pharmacophoric models were later used to screen compounds within the National Cancer Institute database. Several low micromolar Pim-1 Kinase inhibitors were captured. The most potent hits show IC50 values of 0.77 and 1.03 µM. Also, upon analyzing the successful QSAR Equation we found that some polycyclic aromatic electron-rich structures namely 6-Chloro-2-methoxy-acridine can be considered as putative hits for Pim-1 kinase inhibition.
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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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25
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Patel BD, Ghate MD. 3D-QSAR studies of dipeptidyl peptidase-4 inhibitors using various alignment methods. Med Chem Res 2014. [DOI: 10.1007/s00044-014-1178-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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26
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Taha MO, Al-Sha'er MA, Khanfar MA, Al-Nadaf AH. Discovery of nanomolar phosphoinositide 3-kinase gamma (PI3Kγ) inhibitors using ligand-based modeling and virtual screening followed by in vitro analysis. Eur J Med Chem 2014; 84:454-65. [PMID: 25050878 DOI: 10.1016/j.ejmech.2014.07.056] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2014] [Revised: 07/03/2014] [Accepted: 07/17/2014] [Indexed: 11/30/2022]
Abstract
Phosphoinositide 3-kinase gamma (PI3Kγ) is member of a family of enzymes involved in cancer pathogenesis. Accordingly, considerable efforts have been carried out to develop new PI3Kγ inhibitors. Towards this end we explored the pharmacophoric space of PI3Kγ using three diverse sets of inhibitors. Subsequently, we employed genetic algorithm-based QSAR analysis to select optimal combination of pharmacophoric models and physicochemical descriptors that can explain bioactivity variation within training inhibitors. Interestingly, two successful pharmacophores were selected within two statistically consistent QSAR models. The close similarity among the two binding models prompted us to merge them in a hybrid pharmacophore. The resulting model showed superior receiver operator characteristic curve (ROC) and closely resembled binding interactions seen in crystallographic ligand-PI3Kγ complexes. The resulting model was employed to screen the national cancer institute (NCI) list of compounds to search for new PI3Kγ ligands. After testing captured hits in vitro, 19 compounds showed nanomolar IC50 values against PI3Kγ. The chemical structures and purities of most potent hits were validated using NMR and MS experiments.
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Affiliation(s)
- Mutasem O Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, The University of Jordan, Amman, Jordan.
| | | | - Mohammad A Khanfar
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, The University of Jordan, Amman, Jordan
| | - Afaf H Al-Nadaf
- Department of Pharmaceutical Chemistry, Applied Science University, Amman, Jordan
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Taha MO, Habash M, Khanfar MA. The use of docking-based comparative intermolecular contacts analysis to identify optimal docking conditions within glucokinase and to discover of new GK activators. J Comput Aided Mol Des 2014; 28:509-47. [PMID: 24610240 DOI: 10.1007/s10822-014-9740-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2013] [Accepted: 02/25/2014] [Indexed: 11/30/2022]
Abstract
Glucokinase (GK) is involved in normal glucose homeostasis and therefore it is a valid target for drug design and discovery efforts. GK activators (GKAs) have excellent potential as treatments of hyperglycemia and diabetes. The combined recent interest in GKAs, together with docking limitations and shortages of docking validation methods prompted us to use our new 3D-QSAR analysis, namely, docking-based comparative intermolecular contacts analysis (dbCICA), to validate docking configurations performed on a group of GKAs within GK binding site. dbCICA assesses the consistency of docking by assessing the correlation between ligands' affinities and their contacts with binding site spots. Optimal dbCICA models were validated by receiver operating characteristic curve analysis and comparative molecular field analysis. dbCICA models were also converted into valid pharmacophores that were used as search queries to mine 3D structural databases for new GKAs. The search yielded several potent bioactivators that experimentally increased GK bioactivity up to 7.5-folds at 10 μM.
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Affiliation(s)
- Mutasem O Taha
- Drug Discovery Unit, Department of Pharmaceutical Sciences, Faculty of Pharmacy, The University of Jordan, Amman, Jordan,
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29
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Al-Sha’er MA, Khanfar MA, Taha MO. Discovery of novel urokinase plasminogen activator (uPA) inhibitors using ligand-based modeling and virtual screening followed by in vitro analysis. J Mol Model 2014; 20:2080. [PMID: 24469103 DOI: 10.1007/s00894-014-2080-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2013] [Accepted: 10/28/2013] [Indexed: 02/07/2023]
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30
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Abuhamdah S, Habash M, Taha MO. Elaborate ligand-based modeling coupled with QSAR analysis and in silico screening reveal new potent acetylcholinesterase inhibitors. J Comput Aided Mol Des 2013; 27:1075-92. [PMID: 24338032 DOI: 10.1007/s10822-013-9699-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2013] [Accepted: 12/03/2013] [Indexed: 10/25/2022]
Abstract
Inhibition of the enzyme acetylcholinesterase (AChE) has been shown to alleviate neurodegenerative diseases prompting several attempts to discover and optimize new AChE inhibitors. In this direction, we explored the pharmacophoric space of 85 AChE inhibitors to identify high quality pharmacophores. Subsequently, we implemented genetic algorithm-based quantitative structure-activity relationship (QSAR) modeling to select optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of explaining bioactivity variation among training compounds (r2(68)=0.94, F-statistic=125.8, r2 LOO=0.92, r2 PRESS against 17 external test inhibitors = 0.84). Two orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least two binding modes accessible to ligands within AChE binding pocket. The successful pharmacophores were comparable with crystallographically resolved AChE binding pocket. We employed the pharmacophoric models and associated QSAR equation to screen the national cancer institute list of compounds. Twenty-four low micromolar AChE inhibitors were identified. The most potent gave IC50 value of 1.0 μM.
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Affiliation(s)
- Sawsan Abuhamdah
- Department of Biopharmaceutics and Clinical Pharmacy, Faculty of Pharmacy, The University of Jordan, Amman, Jordan
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31
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Shaaban OG, Rizk OH, Bayad AE, El-Ashmawy IM. Synthesis of Some 4,5-Dihydrothieno[3,2-e][1,2,4]Triazolo[4,3-a] Pyrimi-dine-2-Carboxamides as Anti-Inflammatory and Analgesic Agents. THE OPEN MEDICINAL CHEMISTRY JOURNAL 2013; 7:49-65. [PMID: 24379893 PMCID: PMC3873713 DOI: 10.2174/1874104501307010039] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2013] [Revised: 11/11/2013] [Accepted: 11/11/2013] [Indexed: 12/27/2022]
Abstract
A new series 4,5-dihydrothieno[3,2-e][1,2,4]triazolo[4,3-a]pyrimidine-2-carboxamide was synthesized. Twenty one newly synthesized compounds were investigated for their anti-inflammatory and analgesic activity using acute and subacute formalin-induced paw edema models and diclofenac Na as a reference. The acute toxicity (ALD50) and ulcerogenic effects of the active compounds were also determined. The thienotriazolopyrimidines 10a, 10c and 11c were found to exhibit remarkable anti-inflammatory activity at both models in addition to good analgesic activity with a delayed onset of action. Moreover, the active compounds showed high GI safety level and are well tolerated by experimental animals with high safety margin (ALD50 > 0.4 g/kg). Docking study using Molecular Operating Environment (MOE) version 2008.10 into COX-2 has been made for derivatives of highest anti-inflammatory activity.
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Affiliation(s)
- Omaima G. Shaaban
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Alexandria, Alexandria 21521, Egypt
| | - Ola H. Rizk
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Alexandria, Alexandria 21521, Egypt
| | - Aida E. Bayad
- Univ. Fellow, Veterinary Services Unit, Faculty of Veterinary Medicine, University of Alexandria, Egypt
| | - Ibrahim M. El-Ashmawy
- Department of Veterinary Medicine, Faculty of Agricultural and Veterinary Medicine, Qassim University, Buraydah 1482, Al-Qassim, Saudi Arabia
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Almasri IM, Taha MO, Mohammad MK. New leads for DPP IV inhibition: structure-based pharmacophore mapping and virtual screening study. Arch Pharm Res 2013; 36:1326-37. [PMID: 23918649 DOI: 10.1007/s12272-013-0224-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2011] [Accepted: 11/03/2011] [Indexed: 10/26/2022]
Abstract
Dipeptidyl peptidase IV (DPP IV) is an attractive target for the development of new antidiabetic drugs. DPP IV inhibitors improve glycemic control by preventing the rapid inactivation of the incretin hormones; glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic peptide. In the current study, virtual screening, using 2D and 3D filters implemented in a hierarchical cascade, was employed to identify new DPP IV inhibitors. Co-crystallized ligands, with potent DPP IV-inhibitory activities, were utilized to generate structure-based pharmacophore models using DS Visualizer software. The derived pharmacophore maps were validated using in-house built database containing active and inactive DPP IV inhibitors. Subsequently, the optimum validated pharmacophore model was used as a search query against two 3D-databases (NCI and in-house built drug databases). Further hit filtration was carried out employing 2D virtual filters based on Lipinski's rule of 5; number of rotatable bonds and other physicochemical filters. 3D filter using high-throughput molecular docking was also applied. As a result, 5 novel DPP IV inhibitors were discovered as potential lead compounds and later confirmed via in vitro bioassay.
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Affiliation(s)
- Ihab M Almasri
- Department of Chemistry and Pharmaceutical Chemistry, Faculty of Pharmacy, Al-Azhar University, Gaza, Gaza Strip,
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Al-Sha'er MA, VanPatten S, Al-Abed Y, Taha MO. Elaborate ligand-based modeling reveal new migration inhibitory factor inhibitors. J Mol Graph Model 2013; 42:104-14. [PMID: 23603608 DOI: 10.1016/j.jmgm.2013.03.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2013] [Revised: 03/14/2013] [Accepted: 03/16/2013] [Indexed: 11/19/2022]
Abstract
Recent research suggested the involvement of migration inhibitor factor (MIF) in cancer and inflammatory diseases, which prompted several attempts to develop new MIF inhibitors. Accordingly, we investigated the pharmacophoric space of 79 MIF inhibitors using seven diverse subsets of inhibitors to identify plausible binding hypotheses (pharmacophores). Subsequently, we implemented genetic algorithm and multiple linear regression analysis to select optimal combination of pharmacophores and physicochemical descriptors capable of explaining bioactivity variation within the training compounds (QSAR model, r63=0.62, F=42.8, rLOO(2)=0.721,rPRESS(2) against 16 external test inhibitors=0.58). Two orthogonal pharmacophores appeared in the optimal QSAR model suggestive of at least two binding modes available to ligands inside MIF binding pocket. Subsequent validation using receiver operating characteristic (ROC) curves analysis established the validity of these two pharmacophores. We employed these pharmacophoric models and associated QSAR equation to screen the National Cancer Institute (NCI) list of compounds. Eight compounds gave >50% inhibition at 100μM. Two molecules illustrated >75% inhibition at 10μM.
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Computational studies on structurally diverse dipeptidyl peptidase IV inhibitors: an approach for new antidiabetic drug development. Med Chem Res 2013. [DOI: 10.1007/s00044-012-0455-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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35
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Suaifan GA, Shehadehh M, Al-Ijel H, Taha MO. Extensive ligand-based modeling and in silico screening reveal nanomolar inducible nitric oxide synthase (iNOS) inhibitors. J Mol Graph Model 2012; 37:1-26. [PMID: 22609742 DOI: 10.1016/j.jmgm.2012.04.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2011] [Revised: 02/20/2012] [Accepted: 04/02/2012] [Indexed: 01/21/2023]
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36
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Parmar HS, Jain P, Chauhan DS, Bhinchar MK, Munjal V, Yusuf M, Choube K, Tawani A, Tiwari V, Manivannan E, Kumar A. DPP-IV inhibitory potential of naringin: an in silico, in vitro and in vivo study. Diabetes Res Clin Pract 2012; 97:105-11. [PMID: 22410395 DOI: 10.1016/j.diabres.2012.02.011] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2011] [Revised: 02/09/2012] [Accepted: 02/14/2012] [Indexed: 11/26/2022]
Abstract
The incretin based therapies are an emerging class of antidiabetic drugs, with two categories: one is glucagone like peptide-1 (GLP-1) agonists and the other one is dipeptidyl peptidase (CD26; DPP-IV) inhibitors. However, in the DPP-IV inhibitors category only few compounds are commercially available and also have some undesirable effects. Therefore, in the present work we tried to explore a naturally occurring compound naringin for its potential DPP-IV inhibition and antidiabetic potential. It is noteworthy that this compound is abundantly present in orange peel and thus may provide cost effective treatment for diabetes, especially type 2 diabetes mellitus. In the present study, we have conducted virtual docking study and observed tight binding of naringin, as shown by higher negative values of H bond lengths, while in vitro DPP-IV inhibition assay has also shown better inhibition by naringin. In vivo study, in response to 10 days administration of 40 mg/kg of naringin twice daily to Wistar albino rats, inhibited the serum levels of DPP-IV activity, random glucose concentration with concomitant increase in insulin levels. All the comparisons were made with the standard commercially available drug sitagliptin.
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Affiliation(s)
- Hamendra Singh Parmar
- School of Biotechnology, Devi Ahilya University, Takshashila Campus, Khandwa Road, Indore 452001, MP, India.
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37
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Al-Sha'er MA, Taha MO. Application of docking-based comparative intermolecular contacts analysis to validate Hsp90α docking studies and subsequent in silico screening for inhibitors. J Mol Model 2012; 18:4843-63. [PMID: 22707278 DOI: 10.1007/s00894-012-1479-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2012] [Accepted: 05/21/2012] [Indexed: 12/23/2022]
Abstract
Heat shock protein (Hsp90α) has been recently implicated in cancer, prompting several attempts to discover and optimize new Hsp90α inhibitors. Towards this end, we docked 83 diverse Hsp90α inhibitors into the ATP-binding site of this chaperone using several docking-scoring settings. Subsequently, we applied our newly developed computational tool--docking-based comparative intramolecular contacts analysis (dbCICA)--to assess the different docking conditions and select the best settings. dbCICA is based on the number and quality of contacts between docked ligands and amino acid residues within the binding pocket. It assesses a particular docking configuration based on its ability to align a set of ligands within a corresponding binding pocket in such a way that potent ligands come into contact with binding site spots distinct from those approached by low-affinity ligands, and vice versa. The optimal dbCICA models were translated into valid pharmacophore models that were used as 3D search queries to mine the National Cancer Institute's structural database for new inhibitors of Hsp90α that could potentially be used as anticancer agents. The process culminated in 15 micromolar Hsp90α ATPase inhibitors.
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Hanna MM, George RF. Facile Synthesis and Quantitative Structure–Activity Relationship Study of Antitumor Active 2-(4-Oxo-thiazolidin-2-ylidene)-3-oxo-propionitriles. Chem Pharm Bull (Tokyo) 2012; 60:1195-206. [DOI: 10.1248/cpb.c12-00498] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
- Mona Maurice Hanna
- Pharmaceutical Chemistry Department, Faculty of Pharmacy, Cairo University
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Shahin R, Taha MO. Elaborate ligand-based modeling and subsequent synthetic exploration unveil new nanomolar Ca2+/calmodulin-dependent protein kinase II inhibitory leads. Bioorg Med Chem 2012; 20:377-400. [PMID: 22112539 DOI: 10.1016/j.bmc.2011.10.071] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2011] [Revised: 10/23/2011] [Accepted: 10/25/2011] [Indexed: 10/15/2022]
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40
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George RF. Stereoselective synthesis and QSAR study of cytotoxic 2-(4-oxo-thiazolidin-2-ylidene)-2-cyano-N-arylacetamides. Eur J Med Chem 2012; 47:377-86. [DOI: 10.1016/j.ejmech.2011.11.006] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2011] [Revised: 10/30/2011] [Accepted: 11/02/2011] [Indexed: 11/28/2022]
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Shih KC, Lin CY, Chi HC, Hwang CS, Chen TS, Tang CY, Hsiao NW. Design of novel FLT-3 inhibitors based on dual-layer 3D-QSAR model and fragment-based compounds in silico. J Chem Inf Model 2011; 52:146-55. [PMID: 22142286 DOI: 10.1021/ci200434f] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
FMS-like tyrosine kinase 3 (FLT-3) is strongly correlated with acute myeloid leukemia, but no FLT-3-inhibitor cocomplex structure is available to assist the design of therapeutic inhibitors. Hence, we propose a dual-layer 3D-QSAR model for FLT-3 that integrates the pharmacophore, CoMFA, and CoMSIA. We then coupled the model with the fragment-based design strategy to identify novel FLT-3 inhibitors. In the first layer, the previously established model, Hypo02, was evaluated in terms of its correlation coefficient (r), RMS, cost difference, and configuration cost, with values of 0.930, 1.24, 106.45, and 16.44, respectively. Moreover, Fischer's cross-validation test of data generated by Hypo02 yielded a 98% confidence level, and the validation of the testing set yielded a best r value of 0.87. The features of Hypo02 were separated into two parts and then used to screen the MiniMaybridge fragment compound database. Nine novel FLT-3 inhibitors were generated in this layer. In the second layer, Hypo02 was subjected to an alignment rule to generate CoMFA- and CoMSIA-based models, for which the partial least-squares validation method was utilized. The values of q(2), r(2), and predictive r(2) were 0.58, 0.98, and 0.76, respectively, derived from the CoMFA model with steric and electrostatic fields. The CoMSIA model with five different fields yielded values of 0.54, 0.97, and 0.76 for q(2), r(2), and predictive r(2), respectively. The CoMFA and CoMSIA models were used to constrain 3D structures of the nine novel FLT-3 inhibitors. This dual-layer 3D-QSAR model constitutes a valuable tool to easily and quickly screen and optimize novel potential FLT-3 inhibitors for the treatment of acute myeloid leukemia.
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Affiliation(s)
- Kuei-Chung Shih
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
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42
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Shahin R, AlQtaishat S, Taha MO. Elaborate ligand-based modeling reveal new submicromolar Rho kinase inhibitors. J Comput Aided Mol Des 2011; 26:249-66. [PMID: 22167443 DOI: 10.1007/s10822-011-9509-y] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2011] [Accepted: 12/01/2011] [Indexed: 11/25/2022]
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43
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Girgis AS, Stawinski J, Ismail NSM, Farag H. Synthesis and QSAR study of novel cytotoxic spiro[3H-indole-3,2'(1'H)-pyrrolo[3,4-c]pyrrole]-2,3',5'(1H,2'aH,4'H)-triones. Eur J Med Chem 2011; 47:312-22. [PMID: 22119131 DOI: 10.1016/j.ejmech.2011.10.058] [Citation(s) in RCA: 92] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2011] [Revised: 10/27/2011] [Accepted: 10/28/2011] [Indexed: 11/19/2022]
Abstract
1,3-Dipolar cycloaddition reaction of 1-aryl-1H-pyrrole-2,5-diones 1a-e with non-stabilized azomethine ylides, generated in situ via decarboxylative condensation of isatins 2a-c and sarcosine (3) in refluxing ethanol, afforded 4'-aryl-5'a,6'-dihydro-1'-methyl-spiro[3H-indole-3,2'(1'H)-pyrrolo[3,4-c]pyrrole]-2,3',5'(1H,2'aH,4'H)-triones 4a-o in good yields. Compound 4l exhibited high anti-tumor activity against HEPG2 (liver cancer) cell line (IC(50) = 12.16 μM) compared to that of Doxorubicin (IC(50) = 7.36 μM), and the other synthesized compounds revealed moderate anti-tumor properties against HCT116 (colon), MCF7 (breast) and HEPG2 (liver) human tumor cell lines. 3D-Pharmacophore modeling and quantitative structure-activity relationship (QSAR) analysis were combined to explore the structural requirements controlling the observed anti-tumor properties. It was found that the major structural factors affecting potency of these compounds were related to their basic skeleton.
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Affiliation(s)
- Adel S Girgis
- Pesticide Chemistry Department, National Research Centre, Dokki, Cairo 12622, Egypt.
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44
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Habash M, Taha MO. Ligand-based modelling followed by synthetic exploration unveil novel glycogen phosphorylase inhibitory leads. Bioorg Med Chem 2011; 19:4746-71. [PMID: 21788139 DOI: 10.1016/j.bmc.2011.06.086] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2011] [Revised: 06/28/2011] [Accepted: 06/29/2011] [Indexed: 10/18/2022]
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45
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Al-Najjar BO, Wahab HA, Tengku Muhammad TS, Shu-Chien AC, Ahmad Noruddin NA, Taha MO. Discovery of new nanomolar peroxisome proliferator-activated receptor γ activators via elaborate ligand-based modeling. Eur J Med Chem 2011; 46:2513-29. [PMID: 21482446 DOI: 10.1016/j.ejmech.2011.03.040] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2011] [Revised: 03/12/2011] [Accepted: 03/16/2011] [Indexed: 11/30/2022]
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46
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Taha MO, Habash M, Al-Hadidi Z, Al-Bakri A, Younis K, Sisan S. Docking-based comparative intermolecular contacts analysis as new 3-D QSAR concept for validating docking studies and in silico screening: NMT and GP inhibitors as case studies. J Chem Inf Model 2011; 51:647-69. [PMID: 21370899 DOI: 10.1021/ci100368t] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The significant role played by docking algorithms in drug discovery combined with their serious pitfalls prompted us to envisage a novel concept for validating docking solutions, namely, docking-based comparative intermolecular contacts analysis (dbCICA). This novel approach is based on the number and quality of contacts between docked ligands and amino acid residues within the binding pocket. It assesses a particular docking configuration on the basis of its ability to align a set of ligands within a corresponding binding pocket in such a way that potent ligands come into contact with binding site spots distinct from those approached by low-affinity ligands and vice versa. In other words, dbCICA evaluates the consistency of docking by assessing the correlation between ligands' affinities and their contacts with binding site spots. Optimal dbCICA models can be translated into valid pharmacophore models that can be used as 3-D search queries to mine structural databases for new bioactive compounds. dbCICA was implemented to search for new inhibitors of candida N-myristoyl transferase as potential antifungal agents and glycogen phosphorylase (GP) inhibitors as potential antidiabetic agents. The process culminated in five selective micromolar antifungal leads and nine GP inhibitory leads.
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Affiliation(s)
- Mutasem O Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan.
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47
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Al-Sha'er MA, Taha MO. Elaborate ligand-based modeling reveals new nanomolar heat shock protein 90α inhibitors. J Chem Inf Model 2011; 50:1706-23. [PMID: 20831219 DOI: 10.1021/ci100222k] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Heat shock protein (Hsp90α) has been recently implicated in cancer prompting several attempts to discover and optimize new Hsp90α inhibitors. Toward this end, we explored the pharmacophoric space of 83 Hsp90α inhibitors using six diverse sets of inhibitors to identify high-quality pharmacophores. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of accessing a self-consistent quantitative structure activity relationship (QSAR) of optimal predictive potential (r(67)(2)=0.811, F 42.8, r(LOO)(2)=0.748, r(PRESS)(2) (against 16 external test inhibitors) = 0.619). Three orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least three binding modes accessible to ligands within the Hsp90α binding pocket. Receiver operating characteristic (ROC) curves analysis established the validity of QSAR-selected pharmacophores. We employed the pharmacophoric models and associated QSAR equation to screen the national cancer institute (NCI) list of compounds and our in-house-built drugs and agrochemicals database (DAC). Twenty-five nanomolar and low micromolar Hsp90α inhibitors were identified. The most potent were formoterol, amodaquine, primaquine, and midodrine with IC(50) values of 3, 5, 6, and 20 nM, respectively.
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Affiliation(s)
- Mahmoud A Al-Sha'er
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan
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48
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Shih KC, Lin CY, Zhou J, Chi HC, Chen TS, Wang CC, Tseng HW, Tang CY. Development of Novel 3D-QSAR Combination Approach for Screening and Optimizing B-Raf Inhibitors in silico. J Chem Inf Model 2010; 51:398-407. [DOI: 10.1021/ci100351s] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Affiliation(s)
- Kuei-Chung Shih
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Chun-Yuan Lin
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
- Research Center for Emerging Viral Infections, Chang Gung University, Taoyuan 33302, Taiwan
| | - Jiayi Zhou
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Hsiao-Chieh Chi
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Ting-Shou Chen
- Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan
| | - Chun-Chung Wang
- Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan
| | - Hsiang-Wen Tseng
- Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan
| | - Chuan-Yi Tang
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
- Department of Computer Science and Information Engineering, Providence University, Taichung 43301, Taiwan
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Abdula AM, Khalaf RA, Mubarak MS, Taha MO. Discovery of new β-D-galactosidase inhibitors via pharmacophore modeling and QSAR analysis followed by in silico screening. J Comput Chem 2010; 32:463-82. [PMID: 20730780 DOI: 10.1002/jcc.21635] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2010] [Revised: 05/14/2010] [Accepted: 06/23/2010] [Indexed: 11/11/2022]
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50
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Discovery of new β-d-glucosidase inhibitors via pharmacophore modeling and QSAR analysis followed by in silico screening. J Mol Model 2010; 17:443-64. [PMID: 20490878 DOI: 10.1007/s00894-010-0737-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2010] [Accepted: 04/28/2010] [Indexed: 10/19/2022]
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