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Khedraoui M, Abchir O, Nour H, Yamari I, Errougui A, Samadi A, Chtita S. An In Silico Study Based on QSAR and Molecular Docking and Molecular Dynamics Simulation for the Discovery of Novel Potent Inhibitor against AChE. Pharmaceuticals (Basel) 2024; 17:830. [PMID: 39065681 PMCID: PMC11280381 DOI: 10.3390/ph17070830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 06/09/2024] [Accepted: 06/17/2024] [Indexed: 07/28/2024] Open
Abstract
Acetylcholinesterase (AChE) is one of the main drug targets for treating Alzheimer's disease. This current study relies on multiple molecular modeling approaches to develop new potent inhibitors of AChE. We explored a 2D QSAR study using the statistical method of multiple linear regression based on a set of substituted 5-phenyl-1,3,4-oxadiazole and N-benzylpiperidine analogs, which were recently synthesized and proved their inhibitory activities against acetylcholinesterase (AChE). The molecular descriptors, polar surface area, dipole moment, and molecular weight are the key structural properties governing AChE inhibition activity. The MLR model was selected based on its statistical parameters: R2 = 0.701, R2test = 0.76, Q2CV = 0.638, and RMSE = 0.336, demonstrating its predictive reliability. Randomization tests, VIF tests, and applicability domain tests were adopted to verify the model's robustness. As a result, 11 new molecules were designed with higher anti-Alzheimer's activities than the model molecule. We demonstrated their improved pharmacokinetic properties through an in silico ADMET study. A molecular docking study was conducted to explore their AChE inhibition mechanisms and binding affinities in the active site. The binding scores of compounds M1, M2, and M6 were (-12.6 kcal/mol), (-13 kcal/mol), and (-12.4 kcal/mol), respectively, which are higher than the standard inhibitor Donepezil with a binding score of (-10.8 kcal/mol). Molecular dynamics simulations over 100 ns were used to validate the molecular docking results, indicating that compounds M1 and M2 remain stable in the active site, confirming their potential as promising anti-AChE inhibitors.
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Affiliation(s)
- Meriem Khedraoui
- Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Casablanca 20670, Morocco; (M.K.); (O.A.); (H.N.); (I.Y.); (A.E.)
| | - Oussama Abchir
- Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Casablanca 20670, Morocco; (M.K.); (O.A.); (H.N.); (I.Y.); (A.E.)
| | - Hassan Nour
- Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Casablanca 20670, Morocco; (M.K.); (O.A.); (H.N.); (I.Y.); (A.E.)
| | - Imane Yamari
- Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Casablanca 20670, Morocco; (M.K.); (O.A.); (H.N.); (I.Y.); (A.E.)
| | - Abdelkbir Errougui
- Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Casablanca 20670, Morocco; (M.K.); (O.A.); (H.N.); (I.Y.); (A.E.)
| | - Abdelouahid Samadi
- Department of Chemistry, College of Science, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
| | - Samir Chtita
- Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Casablanca 20670, Morocco; (M.K.); (O.A.); (H.N.); (I.Y.); (A.E.)
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Al-Sha'er MA, Basheer HA, Taha MO. Discovery of new PKN2 inhibitory chemotypes via QSAR-guided selection of docking-based pharmacophores. Mol Divers 2023; 27:443-462. [PMID: 35507210 DOI: 10.1007/s11030-022-10434-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 04/05/2022] [Indexed: 12/13/2022]
Abstract
Serine/threonine-protein kinase N2 (PKN2) plays an important role in cell cycle progression, cell migration, cell adhesion and transcription activation signaling processes. In cancer, however, it plays important roles in tumor cell migration, invasion and apoptosis. PKN2 inhibitors have been shown to be promising in treating cancer. This prompted us to model this interesting target using our QSAR-guided selection of docking-based pharmacophores approach where numerous pharmacophores are extracted from docked ligand poses and allowed to compete within the context of QSAR. The optimal pharmacophore was sterically-refined, validated by receiver operating characteristic (ROC) curve analysis and used as virtual search query to screen the National Cancer Institute (NCI) database for new promising anti-PKN2 leads of novel chemotypes. Three low micromolar hits were identified with IC50 values ranging between 9.9 and 18.6 µM. Pharmacological assays showed promising cytotoxic properties for active hits in MTT and wound healing assays against MCF-7 and PANC-1 cancer cells.
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Affiliation(s)
- Mahmoud A Al-Sha'er
- Faculty of Pharmacy, Zarqa University, P.O. Box 132222, Zarqa, 13132, Jordan.
| | - Haneen A Basheer
- Faculty of Pharmacy, Zarqa University, P.O. Box 132222, Zarqa, 13132, Jordan
| | - Mutasem O Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan.
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Saleh MM, Abuirmeileh AN, Al-Rousan RM, Abudoleh SM, Hassouneh LK, Zihlif MA, Taha MO, Abutayeh RF, Mansour H, Abu-Irmaileh B. Biological Evaluation and Reverse Pharmacophore Mapping of Innovative Bis-Triazoles as Promising Anticancer Agents. THE OPEN MEDICINAL CHEMISTRY JOURNAL 2022; 16. [DOI: 10.2174/18741045-v16-e2207200] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/31/2022] [Accepted: 04/28/2022] [Indexed: 07/10/2024]
Abstract
Here, we describe further cytotoxic studies and reverse pharmacophore mapping (pharmacophore profiling) for bis-triazoles MS44-53, which were designed and synthesized previously to stabilize the G-quadruplex nucleic acids capable of being formed at the telomeric region and promoter sequences of genes involved in cellular proliferation and oncogenes. Pharmacophore-based activity profiling screen demonstrated some biological targets that MS44-53 may modulate their biological response, and thus can be considered as potential drugs to treat different kinds of diseases, such as carcinoma, diabetes type II, bacterial infection and cardiovascular diseases. Potent cell growth inhibitory properties were shown by ligands MS47 and MS49 against human melanoma MDA-MB-435, colon cancer HCT-116 and COLO 205, and pancreatic cancer MIA PaCa-2 cell lines, as evidenced by MTT assay. Both ligands were more potent against cancer cells than in skin normal CCD-1064Sk fibroblasts.
Aim:
The aim of this study is to identify the molecular target and mechanism of action of our promising anticancer bis-triazoles MS44-53, focusing specifically on the G-quadruplex stabilizers MS47 and MS49.
Background:
In molecular biology, G-quadruplexes (also known as G4-DNA), one of the higher-order structures of polynucleotides, are four stranded structures formed by nucleic acid sequences which are rich in guanine. They are formed mainly at the single-stranded G-overhang of telomeric DNA and within promoter sequences of genes involved in cellular proliferation and oncogenes such as c-myc, c-kit, and Hsp90. Stabilization of DNA G-quadruplexes is one of the anticancer strategies that has the potential to treat all cancers regardless of the type. A new series of bis-triazoles MS44-53 were developed to stabilize G-quadruplex structures selectively, as G4 ligands and experimental antitumour agents. FRET assay showed that MS47 and MS49 were only the best binders towards the Hsp90 promoter G-guadruplexes. While all bis-triazoles MS44-53 exhibited potent cell growth inhibitory activity against human carcinoma cell lines, suggesting that the ligands perturb molecular targets and mechanisms of action, other than stabilizing G-quadruplexes, contributing to antitumor activity. Therefore, the molecular targets and mechanisms of action of bis-triazoles MS44-53 in different types of human cancer cell lines should be determined by performing further computational studies to MS44-53 and in vitro evaluations for the G-quadruplex stabilizers MS47 and MS49.
Objectives:
1- Determining the exact IC50 for bis-triazoles MS47 & MS49 against four different types of human cancer cell lines; melanoma MDA-MB-435, pancreatic cancer MIA PaCa-2, and colon cancer HCT-116 and COLO 205 cell lines.
2- Predicting the biological targets that bis-triazoles MS44-53 may interact with to trigger or block their biological response.
Methods:
1- MTT assay was used for in vitro evaluation of the antiproliferative activities of MS47 and MS49, and determination of IC50 values.
2- Reverse pharmacophore mapping (pharmacophore profiling) was used for predicting the biological targets of bis-triazoles MS44-53, and determining the % binding probabilities.
Results:
MS49 exhibited more potent proliferation inhibitory activity than MS47 and higher IC50 value against skin normal fibroblasts. Pharmacophore profiling demonstrated FGFR1, PDGFR2, FLT3, mTOR, PPAR-gamma, MUR-F and CETP as biological targets for bis-triazoles MS44-53.
Conclusion:
Bis-triazoles MS47 and MS49 are promising selective innovative compounds with wide spectrum cytotoxic activities against distinct cancer types. Bis-triazoles MS44-53 can be considered as potential drugs to treat different types of carcinoma, in addition to diabetes type II, bacterial infection and cardiovascular diseases.
Other:
Further in vitro evaluations will be performed for bis-triazoles MS44-53 in order to identify their molecular targets and mechanisms of action in different types of human cancer cell lines.
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Abudayah A, Daoud S, Al-Sha'er M, Taha M. Pharmacophore Modeling of Targets Infested with Activity Cliffs via Molecular Dynamics Simulation Coupled with QSAR and Comparison with other Pharmacophore Generation Methods: KDR as Case Study. Mol Inform 2022; 41:e2200049. [PMID: 35973966 DOI: 10.1002/minf.202200049] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 08/15/2022] [Indexed: 11/07/2022]
Abstract
Activity cliffs (ACs) are defined as pairs of structurally similar compounds with large difference in their potencies against certain biotarget. We recently proposed that potent AC members induce significant entropically-driven conformational modifications of the target that unveil additional binding interactions, while their weakly-potent counterparts are enthalpically-driven binders with little influence on the protein target. We herein propose to extract pharmacophores for ACs-infested target(s) from molecular dynamics (MD) frames of purely "enthalpic" potent binder(s) complexed within the particular target. Genetic function algorithm/machine learning (GFA/ML) can then be employed to search for the best possible combination of MD pharmacophore(s) capable of explaining bioactivity variations within a list of inhibitors. We compared the performance of this approach with established ligand-based and structure-based methods. Kinase inserts domain receptor (KDR) was used as a case study. KDR plays a crucial role in angiogenic signaling and its inhibitors have been approved in cancer treatment. Interestingly, GFA/ML selected, MD-based, pharmacophores were of comparable performances to ligand-based and structure-based pharmacophores. The resulting pharmacophores and QSAR models were used to capture hits from the national cancer institute list of compounds. The most active hit showed anti-KDR IC50 of 2.76 µM.
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Affiliation(s)
| | | | | | - Mutasem Taha
- Faculty of pharmacy,University of jordan, JORDAN
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Exploiting activity cliffs for building pharmacophore models and comparison with other pharmacophore generation methods: sphingosine kinase 1 as case study. J Comput Aided Mol Des 2022; 36:39-62. [PMID: 35059939 DOI: 10.1007/s10822-021-00435-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 11/24/2021] [Indexed: 12/20/2022]
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Daoud S, Taha M. Ligand-Based Modeling of CXC Chemokine Receptor 4 and Identification of Inhibitors of Novel Chemotypes as Potential Leads towards New Anti-COVID-19 Treatments. Med Chem 2022; 18:871-883. [PMID: 35040417 DOI: 10.2174/1573406418666220118153541] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/05/2021] [Accepted: 12/08/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Chemokines are involved in several human diseases and in different stages of COVID-19 infection and play critical role in the pathophysiology of the associated acute respiratory disease syndrome, a major complication leading to death among COVID-19 patients. In particular, CXC chemokine receptor 4 (CXCR4) was found to be highly expressed in COVID-19 patients. METHODS We herein describe a computational workflow based on combining pharmacophore modeling and QSAR analysis towards the discovery of novel CXCR4 inhibitors. Subsequent virtual screening identified two promising CXCR4 inhibitors from the National Cancer Institute (NCI) list of compounds. The most active hit showed in vitro IC50 value of 24.4 µM. RESULTS AND CONCLUSION These results prove the validity of the QSAR model and associated pharmacophore models as means to screen virtual databases towards new CXCR4 inhibitors as leads for the development of new COVID-19 therapies.
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Affiliation(s)
- Safa Daoud
- Department of Pharmaceutical Chemistry and Pharmacognosy, Faculty of Pharmacy, Applied Sciences Private University, Amman, Jordan
| | - Mutasem Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan
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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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Bagri K, Kumar A, Manisha, Kumar P. Computational Studies on Acetylcholinesterase Inhibitors: From Biochemistry to Chemistry. Mini Rev Med Chem 2021; 20:1403-1435. [PMID: 31884928 DOI: 10.2174/1389557520666191224144346] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 10/23/2019] [Accepted: 10/28/2019] [Indexed: 11/22/2022]
Abstract
Acetylcholinesterase inhibitors are the most promising therapeutics for Alzheimer's disease treatment as these prevent the loss of acetylcholine and slows the progression of the disease. The drugs approved for the management of Alzheimer's disease by the FDA are acetylcholinesterase inhibitors but are associated with side effects. Consistent and stringent efforts by the researchers with the help of computational methods opened new ways of developing novel molecules with good acetylcholinesterase inhibitory activity. In this manuscript, we reviewed the studies that identified the essential structural features of acetylcholinesterase inhibitors at the molecular level as well as the techniques like molecular docking, molecular dynamics, quantitative structure-activity relationship, virtual screening, and pharmacophore modelling that were used in designing these inhibitors.
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Affiliation(s)
- Kiran Bagri
- Department of Pharmaceutical Sciences, Guru Jambheshwar University of Science & Technology, Hisar 125001, India
| | - Ashwani Kumar
- Department of Pharmaceutical Sciences, Guru Jambheshwar University of Science & Technology, Hisar 125001, India
| | - Manisha
- Department of Pharmaceutical Sciences, Guru Jambheshwar University of Science & Technology, Hisar 125001, India
| | - Parvin Kumar
- Department of Chemistry, Kurukshetra University, Kurukshetra, India
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De Boer D, Nguyen N, Mao J, Moore J, Sorin EJ. A Comprehensive Review of Cholinesterase Modeling and Simulation. Biomolecules 2021; 11:580. [PMID: 33920972 PMCID: PMC8071298 DOI: 10.3390/biom11040580] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 04/08/2021] [Accepted: 04/11/2021] [Indexed: 01/18/2023] Open
Abstract
The present article reviews published efforts to study acetylcholinesterase and butyrylcholinesterase structure and function using computer-based modeling and simulation techniques. Structures and models of both enzymes from various organisms, including rays, mice, and humans, are discussed to highlight key structural similarities in the active site gorges of the two enzymes, such as flexibility, binding site location, and function, as well as differences, such as gorge volume and binding site residue composition. Catalytic studies are also described, with an emphasis on the mechanism of acetylcholine hydrolysis by each enzyme and novel mutants that increase catalytic efficiency. The inhibitory activities of myriad compounds have been computationally assessed, primarily through Monte Carlo-based docking calculations and molecular dynamics simulations. Pharmaceutical compounds examined herein include FDA-approved therapeutics and their derivatives, as well as several other prescription drug derivatives. Cholinesterase interactions with both narcotics and organophosphate compounds are discussed, with the latter focusing primarily on molecular recognition studies of potential therapeutic value and on improving our understanding of the reactivation of cholinesterases that are bound to toxins. This review also explores the inhibitory properties of several other organic and biological moieties, as well as advancements in virtual screening methodologies with respect to these enzymes.
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Affiliation(s)
- Danna De Boer
- Department of Chemistry & Biochemistry, California State University, Long Beach, CA 90840, USA;
| | - Nguyet Nguyen
- Department of Chemical Engineering, California State University, Long Beach, CA 90840, USA; (N.N.); (J.M.)
| | - Jia Mao
- Department of Chemical Engineering, California State University, Long Beach, CA 90840, USA; (N.N.); (J.M.)
| | - Jessica Moore
- Department of Biomedical Engineering, California State University, Long Beach, CA 90840, USA;
| | - Eric J. Sorin
- Department of Chemistry & Biochemistry, California State University, Long Beach, CA 90840, USA;
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Beato A, Gori A, Boucherle B, Peuchmaur M, Haudecoeur R. β-Carboline as a Privileged Scaffold for Multitarget Strategies in Alzheimer's Disease Therapy. J Med Chem 2021; 64:1392-1422. [PMID: 33528252 DOI: 10.1021/acs.jmedchem.0c01887] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The natural β-carboline alkaloids display similarities with neurotransmitters that can be favorably exploited to design bioactive and bioavailable drugs for Alzheimer's disease (AD) therapy. Several AD targets are currently and intensively being investigated, divided in different hypotheses: mainly the cholinergic, the amyloid β (Aβ), and the Tau hypotheses. To date, only symptomatic treatments are available involving acetylcholinesterase and NMDA inhibitors. On the basis of plethoric single-target structure-activity relationship studies, the β-carboline scaffold was identified as a powerful tool for fostering activity and molecular interactions with a wide range of AD-related targets. This knowledge can undoubtedly be used to design multitarget-directed ligands, a highly relevant strategy preferred in the context of multifactorial pathology with intricate etiology such as AD. In this review, we first individually discuss the AD targets of the β-carbolines, and then we focus on the multitarget strategies dedicated to the deliberate design of new efficient scaffolds.
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Affiliation(s)
| | - Anthonin Gori
- Univ. Grenoble Alpes, CNRS, DPM, 38000 Grenoble, France.,CHANEL Parfums Beauté, F-93500 Pantin, France
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Tran TS, Le MT, Tran TD, Tran TH, Thai KM. Design of Curcumin and Flavonoid Derivatives with Acetylcholinesterase and Beta-Secretase Inhibitory Activities Using in Silico Approaches. Molecules 2020; 25:molecules25163644. [PMID: 32785161 PMCID: PMC7464027 DOI: 10.3390/molecules25163644] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 07/20/2020] [Accepted: 08/07/2020] [Indexed: 12/25/2022] Open
Abstract
Acetylcholinesterase (AChE) and beta-secretase (BACE-1) are the two crucial enzymes involved in the pathology of Alzheimer's disease. The former is responsible for many defects in cholinergic signaling pathway and the latter is the primary enzyme in the biosynthesis of beta-amyloid as the main component of the amyloid plaques. These both abnormalities are found in the brains of Alzheimer's patients. In this study, in silico models were developed, including 3D-pharmacophore, 2D-QSAR (two-dimensional quantitative structure-activity relationship), and molecular docking, to screen virtually a database of compounds for AChE and BACE-1 inhibitory activities. A combinatorial library containing more than 3 million structures of curcumin and flavonoid derivatives was generated and screened for drug-likeness and enzymatic inhibitory bioactivities against AChE and BACE-1 through the validated in silico models. A total of 47 substances (two curcumins and 45 flavonoids), with remarkable predicted pIC50 values against AChE and BACE-1 ranging from 4.24-5.11 (AChE) and 4.52-10.27 (BACE-1), were designed. The in vitro assays on AChE and BACE-1 were performed and confirmed the in silico results. The study indicated that, by using in silico methods, a series of curcumin and flavonoid structures were generated with promising predicted bioactivities. This would be a helpful foundation for the experimental investigations in the future. Designed compounds which were the most feasible for chemical synthesis could be potential candidates for further research and lead optimization.
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Affiliation(s)
- Thai-Son Tran
- Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam or (T.-S.T.); (T.-D.T.)
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, College of Medicine and Pharmacy, Hue University, Hue City 530000, Vietnam;
| | - Minh-Tri Le
- Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam or (T.-S.T.); (T.-D.T.)
- School of Medicine, Vietnam National University Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam
- Correspondence: or (M.-T.L.); or (K.-M.T.); Tel.: +84-903-718-190 (M-T.L.); +84-28-3855-2225 or +84-909-680-385 (K-M.T.); Fax: +84-28-3822-5435 (K-M.T.)
| | - Thanh-Dao Tran
- Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam or (T.-S.T.); (T.-D.T.)
| | - The-Huan Tran
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, College of Medicine and Pharmacy, Hue University, Hue City 530000, Vietnam;
| | - Khac-Minh Thai
- Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam or (T.-S.T.); (T.-D.T.)
- Correspondence: or (M.-T.L.); or (K.-M.T.); Tel.: +84-903-718-190 (M-T.L.); +84-28-3855-2225 or +84-909-680-385 (K-M.T.); Fax: +84-28-3822-5435 (K-M.T.)
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Daoud S, Taha MO. Pharmacophore modeling of JAK1: A target infested with activity-cliffs. J Mol Graph Model 2020; 99:107615. [PMID: 32339898 DOI: 10.1016/j.jmgm.2020.107615] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Revised: 04/01/2020] [Accepted: 04/02/2020] [Indexed: 12/14/2022]
Abstract
Janus kinase 1 (JAK1) is protein kinase involved in autoimmune diseases (AIDs). JAK1 inhibitors have shown promising results in treating AIDs. JAK1 inhibitors are known to exhibit regions of SAR discontinuity or activity cliffs (ACs). ACs represent fundamental challenge to successful QSAR/pharmacophore modeling because QSAR modeling rely on the basic premise that activity is a smooth continuous function of structure. We propose that ACs exist because active ACs members exhibit subtle, albeit critical, enthalpic features absent from their inactive twins. In this context we compared the performances of two computational modeling workflows in extracting valid pharmacophores from 151 diverse JAK1 inhibitors that include ACs: QSAR-guided pharmacophore selection versus docking-based comparative intermolecular contacts analysis (db-CICA). The two methods were judged based on the receiver operating characteristic (ROC) curves of their corresponding pharmacophore models and their abilities to distinguish active members among established JAK1 ACs. db-CICA modeling significantly outperformed ligand-based pharmacophore modeling. The resulting optimal db-CICA pharmacophore was used as virtual search query to scan the National Cancer Institute (NCI) database for novel JAK1 inhibitory leads. The most active hit showed IC50 of 1.04 μM. This study proposes the use of db-CICA modeling as means to extract valid pharmacophores from SAR data infested with ACs.
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Affiliation(s)
- Safa Daoud
- Department of Pharmaceutical Chemistry and Pharmacognosy, Faculty of Pharmacy, Applied Science Private University, Amman, Jordan
| | - Mutasem O Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan.
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Abutayeh RF, Taha MO. Discovery of novel Flt3 inhibitory chemotypes through extensive ligand-based and new structure-based pharmacophore modelling methods. J Mol Graph Model 2019; 88:128-151. [PMID: 30703688 DOI: 10.1016/j.jmgm.2019.01.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Revised: 01/03/2019] [Accepted: 01/17/2019] [Indexed: 01/10/2023]
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Al-Sha'er MA, Al-Aqtash RA, Taha MO. Discovery of New Phosphoinositide 3-kinase Delta (PI3Kδ) Inhibitors via Virtual Screening using Crystallography-derived Pharmacophore Modelling and QSAR Analysis. Med Chem 2019; 15:588-601. [PMID: 30799792 DOI: 10.2174/1573406415666190222125333] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 01/31/2019] [Accepted: 02/07/2019] [Indexed: 01/29/2023]
Abstract
BACKGROUND PI3Kδ is predominantly expressed in hematopoietic cells and participates in the activation of leukocytes. PI3Kδ inhibition is a promising approach for treating inflammatory diseases and leukocyte malignancies. Accordingly, we decided to model PI3Kδ binding. METHODS Seventeen PI3Kδ crystallographic complexes were used to extract 94 pharmacophore models. QSAR modelling was subsequently used to select the superior pharmacophore(s) that best explain bioactivity variation within a list of 79 diverse inhibitors (i.e., upon combination with other physicochemical descriptors). RESULTS The best QSAR model (r2 = 0.71, r2 LOO = 0.70, r2 press against external testing list of 15 compounds = 0.80) included a single crystallographic pharmacophore of optimal explanatory qualities. The resulting pharmacophore and QSAR model were used to screen the National Cancer Institute (NCI) database for new PI3Kδ inhibitors. Two hits showed low micromolar IC50 values. CONCLUSION Crystallography-based pharmacophores were successfully combined with QSAR analysis for the identification of novel PI3Kδ inhibitors.
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Affiliation(s)
- Mahmoud A Al-Sha'er
- Faculty of Pharmacy, Zarqa University, P.O. Box 132222, Zarqa, 13132, Jordan
| | - Rua'a A Al-Aqtash
- Faculty of Pharmacy, Zarqa University, P.O. Box 132222, Zarqa, 13132, Jordan
| | - Mutasem O Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, The University of Jordan, Amman, Jordan
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Hatmal MM, Taha MO. Combining Stochastic Deformation/Relaxation and Intermolecular Contacts Analysis for Extracting Pharmacophores from Ligand-Receptor Complexes. J Chem Inf Model 2018. [PMID: 29529367 DOI: 10.1021/acs.jcim.7b00708] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
We previously combined molecular dynamics (classical or simulated annealing) with ligand-receptor contacts analysis as a means to extract valid pharmacophore model(s) from single ligand-receptor complexes. However, molecular dynamics methods are computationally expensive and time-consuming. Here we describe a novel method for extracting valid pharmacophore model(s) from a single crystallographic structure within a reasonable time scale. The new method is based on ligand-receptor contacts analysis following energy relaxation of a predetermined set of randomly deformed complexes generated from the targeted crystallographic structure. Ligand-receptor contacts maintained across many deformed/relaxed structures are assumed to be critical and used to guide pharmacophore development. This methodology was implemented to develop valid pharmacophore models for PI3K-γ, RENIN, and JAK1. The resulting pharmacophore models were validated by receiver operating characteristic (ROC) analysis against inhibitors extracted from the CHEMBL database. Additionally, we implemented pharmacophores extracted from PI3K-γ to search for new inhibitors from the National Cancer Institute list of compounds. The process culminated in new PI3K-γ/mTOR inhibitory leads of low micromolar IC50s.
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Affiliation(s)
- Ma'mon M Hatmal
- Department of Medical Laboratory Sciences, Faculty of Allied Health Sciences , The Hashemite University , P.O. Box 330127 , Zarqa 13133 , Jordan
| | - Mutasem O Taha
- Drug Discovery Unit, Department of Pharmaceutical Sciences, Faculty of Pharmacy , University of Jordan , Amman 11942 , Jordan
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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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Al-Aqtash RA, Zihlif MA, Hammad H, Nassar ZD, Meliti JA, Taha MO. Ligand-based computational modelling of platelet-derived growth factor beta receptor leading to new angiogenesis inhibitory leads. Comput Biol Chem 2017; 71:170-179. [PMID: 29101826 DOI: 10.1016/j.compbiolchem.2017.10.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 10/02/2017] [Accepted: 10/05/2017] [Indexed: 01/03/2023]
Abstract
Platelet derived growth factor beta receptor (PDGFR- β) plays an important role in angiogenesis. PDGFR-β expression is correlated with increased vascularity and maturation of blood vessels in cancer. Pharmacophore modeling and quantitative structure-activity relationship (QSAR) analysis were combined to explore the structural requirements for ligand-PDGFR-β recognition using 107 known PDGFR-β inhibitors. Genetic function algorithm (GFA) coupled to k nearest neighbor (kNN) and multiple linear regression (MLR) analysis were employed to generate predictive QSAR models based on optimal combinations of pharmacophores and physicochemical descriptors. The successful pharmacophores were complemented with exclusion spheres to optimize their receiver operating characteristic curve (ROC) profiles. The QSAR models and their associated pharmacophore hypotheses were validated by identification and experimental evaluation of new angiogenesis inhibitory leads retrieved from the National Cancer Institute (NCI) structural database. Two hits illustrated low micromolar IC50 values in two distinct anti-angiogenesis bioassays.
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Affiliation(s)
- Rua'a A Al-Aqtash
- Department of Pharmacology, Faculty of Medicine, University of Jordan, Amman, Jordan
| | - Malek A Zihlif
- Department of Pharmacology, Faculty of Medicine, University of Jordan, Amman, Jordan
| | - Hana Hammad
- Department of Biology, University of Jordan, Amman, Jordan
| | - Zeyad D Nassar
- School of Medicine, University of Adelaide, Adelaide, South Australia, Australia
| | - Jehad Al Meliti
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Mutasem O Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan.
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18
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Simulated annealing molecular dynamics and ligand-receptor contacts analysis for pharmacophore modeling. Future Med Chem 2017; 9:1141-1159. [PMID: 28722471 DOI: 10.4155/fmc-2017-0061] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
AIM Ligand-based pharmacophore modeling requires long list of inhibitors, while pharmacophores based on single ligand-receptor crystallographic structure can be too restricted or promiscuous. METHODOLOGY This prompted us to combine simulated annealing molecular dynamics (SAMD) with ligand-receptor contacts analysis as means to construct pharmacophore model(s) from single ligand-receptor complex. Ligand-receptor contacts that survive numerous heating-cooling SAMD cycles are considered critical and are used to guide pharmacophore development. RESULTS This methodology was implemented to develop pharmacophores for acetylcholinesterase and protein kinase C-θ. The resulting models were validated by receiver-operating characteristic analysis and in vitro bioassay. Assay identified four new protein kinase C-θ inhibitors among captured hits, two of which exhibited nanomolar potencies. CONCLUSION The results illustrate the ability of the new method to extract valid pharmacophores from single ligand-protein complex.
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Docking-based comparative intermolecular contacts analysis and in silico screening reveal new potent acetylcholinesterase inhibitors. Med Chem Res 2017. [DOI: 10.1007/s00044-017-1976-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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20
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Abuhammad A, Al-Aqtash RA, Anson BJ, Mesecar AD, Taha MO. Computational modeling of the bat HKU4 coronavirus 3CL pro inhibitors as a tool for the development of antivirals against the emerging Middle East respiratory syndrome (MERS) coronavirus. J Mol Recognit 2017; 30. [PMID: 28608547 PMCID: PMC7166879 DOI: 10.1002/jmr.2644] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2017] [Revised: 05/01/2017] [Accepted: 05/09/2017] [Indexed: 12/22/2022]
Abstract
The Middle East respiratory syndrome coronavirus (MERS‐CoV) is an emerging virus that poses a major challenge to clinical management. The 3C‐like protease (3CLpro) is essential for viral replication and thus represents a potential target for antiviral drug development. Presently, very few data are available on MERS‐CoV 3CLpro inhibition by small molecules. We conducted extensive exploration of the pharmacophoric space of a recently identified set of peptidomimetic inhibitors of the bat HKU4‐CoV 3CLpro. HKU4‐CoV 3CLpro shares high sequence identity (81%) with the MERS‐CoV enzyme and thus represents a potential surrogate model for anti‐MERS drug discovery. We used 2 well‐established methods: Quantitative structure‐activity relationship (QSAR)‐guided modeling and docking‐based comparative intermolecular contacts analysis. The established pharmacophore models highlight structural features needed for ligand recognition and revealed important binding‐pocket regions involved in 3CLpro‐ligand interactions. The best models were used as 3D queries to screen the National Cancer Institute database for novel nonpeptidomimetic 3CLpro inhibitors. The identified hits were tested for HKU4‐CoV and MERS‐CoV 3CLpro inhibition. Two hits, which share the phenylsulfonamide fragment, showed moderate inhibitory activity against the MERS‐CoV 3CLpro and represent a potential starting point for the development of novel anti‐MERS agents. To the best of our knowledge, this is the first pharmacophore modeling study supported by in vitro validation on the MERS‐CoV 3CLpro. Highlights MERS‐CoV is an emerging virus that is closely related to the bat HKU4‐CoV. 3CLpro is a potential drug target for coronavirus infection. HKU4‐CoV 3CLpro is a useful surrogate model for the identification of MERS‐CoV 3CLpro enzyme inhibitors. dbCICA is a very robust modeling method for hit identification. The phenylsulfonamide scaffold represents a potential starting point for MERS coronavirus 3CLpro inhibitors development.
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Affiliation(s)
- Areej Abuhammad
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Rua'a A Al-Aqtash
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Brandon J Anson
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Andrew D Mesecar
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.,Department of Chemistry, Purdue University, West Lafayette, IN, USA.,Centers for Cancer Research & Drug Discovery, Purdue University, West Lafayette, IN, USA
| | - Mutasem O Taha
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman, Jordan
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Ismaili L, Refouvelet B, Benchekroun M, Brogi S, Brindisi M, Gemma S, Campiani G, Filipic S, Agbaba D, Esteban G, Unzeta M, Nikolic K, Butini S, Marco-Contelles J. Multitarget compounds bearing tacrine- and donepezil-like structural and functional motifs for the potential treatment of Alzheimer's disease. Prog Neurobiol 2017; 151:4-34. [DOI: 10.1016/j.pneurobio.2015.12.003] [Citation(s) in RCA: 87] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 11/11/2015] [Accepted: 12/11/2015] [Indexed: 01/16/2023]
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Khanfar MA, Taha MO. Unsupervised pharmacophore modeling combined with QSAR analyses revealed novel low micromolar SIRT2 inhibitors. J Mol Recognit 2017; 30. [PMID: 28299833 DOI: 10.1002/jmr.2623] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 01/18/2017] [Accepted: 02/13/2017] [Indexed: 11/10/2022]
Abstract
Situin 2 (SIRT2) enzyme is a histone deacetylase that has important role in neuronal development. SIRT2 is clinically validated target for neurodegenerative diseases and some cancers. In this study, exhaustive unsupervised pharmacophore modeling was combined with quantitative structure-activity relationship (QSAR) analysis to explore the structural requirements for potent SIRT2 inhibitors using 146 known SIRT2 ligands. A computational workflow that combines genetic function algorithm with k-nearest neighbor or multiple linear regression was implemented to build self-consistent and predictive QSAR models based on combinations of pharmacophores and physicochemical descriptors. Successful pharmacophores were complemented with exclusion spheres to optimize their receiver operating characteristic curve profiles. Optimal QSAR models and their associated pharmacophore hypotheses were experimentally validated by identification and in vitro evaluation of several new promising SIRT2 inhibitory leads retrieved from the National Cancer Institute structural database. The most potent hit illustrated IC50 value of 5.4μM. The chemical structures of active hits were validated by proton nuclear magnetic resonance and mass spectroscopy.
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Affiliation(s)
- Mohammad A Khanfar
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, Univerity of Jordan, Amman, Jordan
| | - Mutasem O Taha
- Drug Discovery Unit, Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan
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Minovski N, Novič M. Integrated in Silico Methods for the Design and Optimization of Novel Drug Candidates. Oncology 2017. [DOI: 10.4018/978-1-5225-0549-5.ch016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Although almost fully automated, the discovery of novel, effective, and safe drugs is still a long-term and highly expensive process. Consequently, the need for fleet, rational, and cost-efficient development of novel drugs is crucial, and nowadays the advanced in silico drug design methodologies seem to effectively meet these issues. The aim of this chapter is to provide a comprehensive overview of some of the current trends and advances in the in silico design of novel drug candidates with a special emphasis on 6-fluoroquinolone (6-FQ) antibacterials as potential novel Mycobacterium tuberculosis DNA gyrase inhibitors. In particular, the chapter covers some of the recent aspects of a wide range of in silico drug discovery approaches including multidimensional machine-learning methods, ligand-based and structure-based methodologies, as well as their proficient combination and integration into an intelligent virtual screening protocol for design and optimization of novel 6-FQ analogs.
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Combining molecular dynamics simulation and ligand-receptor contacts analysis as a new approach for pharmacophore modeling: beta-secretase 1 and check point kinase 1 as case studies. J Comput Aided Mol Des 2016; 30:1149-1163. [PMID: 27722817 DOI: 10.1007/s10822-016-9984-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Accepted: 10/03/2016] [Indexed: 01/19/2023]
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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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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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Combining docking-based comparative intermolecular contacts analysis and k-nearest neighbor correlation for the discovery of new check point kinase 1 inhibitors. J Comput Aided Mol Des 2015; 29:561-81. [PMID: 25956379 DOI: 10.1007/s10822-015-9848-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2014] [Accepted: 05/03/2015] [Indexed: 01/15/2023]
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Martis EA, Chandarana RC, Shaikh MS, Ambre PK, D’Souza JS, Iyer KR, Coutinho EC, Nandan SR, Pissurlenkar RR. Quantifying ligand–receptor interactions for gorge-spanning acetylcholinesterase inhibitors for the treatment of Alzheimer’s disease. J Biomol Struct Dyn 2014; 33:1107-25. [DOI: 10.1080/07391102.2014.931824] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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