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Wang Y, Jia S, Wang F, Jiang R, Yin X, Wang S, Jin R, Guo H, Tang Y, Wang Y. 3D-QSAR, Scaffold Hopping, Virtual Screening, and Molecular Dynamics Simulations of Pyridin-2-one as mIDH1 Inhibitors. Int J Mol Sci 2024; 25:7434. [PMID: 39000539 PMCID: PMC11242256 DOI: 10.3390/ijms25137434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 06/30/2024] [Accepted: 07/04/2024] [Indexed: 07/16/2024] Open
Abstract
Isocitrate dehydrogenase 1 (IDH1) is a necessary enzyme for cellular respiration in the tricarboxylic acid cycle. Mutant isocitrate dehydrogenase 1 (mIDH1) has been detected overexpressed in a variety of cancers. mIDH1 inhibitor ivosidenib (AG-120) was only approved by the Food and Drug Administration (FDA) for marketing, nevertheless, a range of resistance has been frequently reported. In this study, several mIDH1 inhibitors with the common backbone pyridin-2-one were explored using the three-dimensional structure-activity relationship (3D-QSAR), scaffold hopping, absorption, distribution, metabolism, excretion (ADME) prediction, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, R2 = 0.980, Q2 = 0.765) and comparative molecular similarity index analysis (CoMSIA, R2 = 0.997, Q2 = 0.770) were used to build 3D-QSAR models, which yielded notably decent predictive ability. A series of novel structures was designed through scaffold hopping. The predicted pIC50 values of C3, C6, and C9 were higher in the model of 3D-QSAR. Additionally, MD simulations culminated in the identification of potent mIDH1 inhibitors, exhibiting strong binding interactions, while the analyzed parameters were free energy landscape (FEL), radius of gyration (Rg), solvent accessible surface area (SASA), and polar surface area (PSA). Binding free energy demonstrated that C2 exhibited the highest binding free energy with IDH1, which was -93.25 ± 5.20 kcal/mol. This research offers theoretical guidance for the rational design of novel mIDH1 inhibitors.
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Affiliation(s)
- Yifan Wang
- College of Pharmacy, Shaanxi University of Chinese Medicine, Shiji Ave, Xi'an-Xianyang New Economic Zone, Xianyang 712046, China
| | - Shunjiang Jia
- College of Pharmacy, Shaanxi University of Chinese Medicine, Shiji Ave, Xi'an-Xianyang New Economic Zone, Xianyang 712046, China
| | - Fan Wang
- Second Clinical Medical College, Shaanxi University of Chinese Medicine, Shiji Ave, Xi'an-Xianyang New Economic Zone, Xianyang 712046, China
| | - Ruizhe Jiang
- Second Clinical Medical College, Shaanxi University of Chinese Medicine, Shiji Ave, Xi'an-Xianyang New Economic Zone, Xianyang 712046, China
| | - Xiaodan Yin
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau 999078, China
| | - Shuo Wang
- College of Pharmacy, Lanzhou University, Lanzhou 730000, China
| | - Ruyi Jin
- College of Pharmacy, Shaanxi University of Chinese Medicine, Shiji Ave, Xi'an-Xianyang New Economic Zone, Xianyang 712046, China
| | - Hui Guo
- College of Pharmacy, Shaanxi University of Chinese Medicine, Shiji Ave, Xi'an-Xianyang New Economic Zone, Xianyang 712046, China
| | - Yuping Tang
- College of Pharmacy, Shaanxi University of Chinese Medicine, Shiji Ave, Xi'an-Xianyang New Economic Zone, Xianyang 712046, China
| | - Yuwei Wang
- College of Pharmacy, Shaanxi University of Chinese Medicine, Shiji Ave, Xi'an-Xianyang New Economic Zone, Xianyang 712046, China
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2
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Khaled DM, Elshakre ME, Noamaan MA, Butt H, Abdel Fattah MM, Gaber DA. A Computational QSAR, Molecular Docking and In Vitro Cytotoxicity Study of Novel Thiouracil-Based Drugs with Anticancer Activity against Human-DNA Topoisomerase II. Int J Mol Sci 2022; 23:11799. [PMID: 36233102 PMCID: PMC9570267 DOI: 10.3390/ijms231911799] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 09/16/2022] [Accepted: 09/18/2022] [Indexed: 11/30/2022] Open
Abstract
Computational chemistry, molecular docking, and drug design approaches, combined with the biochemical evaluation of the antitumor activity of selected derivatives of the thiouracil-based dihydroindeno pyrido pyrimidines against topoisomerase I and II. The IC50 of other cell lines including the normal human lung cell line W138, lung cancer cell line, A549, breast cancer cell line, MCF-7, cervical cancer, HeLa, and liver cancer cell line HepG2 was evaluated using biochemical methods. The global reactivity descriptors and physicochemical parameters were computed, showing good agreement with the Lipinski and Veber's rules of the drug criteria. The molecular docking study of the ligands with the topoisomerase protein provides the binding sites, binding energies, and deactivation constant for the inhibition pocket. Various biochemical methods were used to evaluate the IC50 of the cell lines. The QSAR model was developed for colorectal cell line HCT as a case study. Four QSAR statistical models were predicted between the IC50 of the colorectal cell line HCT to correlate the anticancer activity and the computed physicochemical and quantum chemical global reactivity descriptors. The predictive power of the models indicates a good correlation between the observed and the predicted activity.
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Affiliation(s)
- Doaa M. Khaled
- Histology and Cytology Department, Faculty of Medicine, Helwan University, Cairo 11795, Egypt
| | - Mohamed E. Elshakre
- Chemistry Department, Faculty of Science, Cairo University, Cairo 12613, Egypt
| | - Mahmoud A. Noamaan
- Mathematics Department, Faculty of Science, Cairo University, Cairo 12613, Egypt
| | - Haider Butt
- Department of Mechanical Engineering, Khalifa University, Abu Dhabi 127788, United Arab Emirates
| | - Marwa M. Abdel Fattah
- Histology and Cytology Department, Faculty of Medicine, Misr University for Science & Technology, Cairo P.O. Box 77, Egypt
| | - Dalia A. Gaber
- Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Helwan University, Cairo 11795, Egypt
- Department of Biomedical Sciences, College of Medicine, Gulf Medical University, Ajman 4184, United Arab Emirates
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Song T, Zhang X, Ding M, Rodriguez-Paton A, Wang S, Wang G. DeepFusion: A Deep Learning Based Multi-Scale Feature Fusion Method for Predicting Drug-Target Interactions. Methods 2022; 204:269-277. [DOI: 10.1016/j.ymeth.2022.02.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/28/2022] [Accepted: 02/20/2022] [Indexed: 12/15/2022] Open
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da Silva TH, Hachigian TZ, Lee J, King MD. Using computers to ESKAPE the antibiotic resistance crisis. Drug Discov Today 2021; 27:456-470. [PMID: 34688913 DOI: 10.1016/j.drudis.2021.10.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 08/01/2021] [Accepted: 10/15/2021] [Indexed: 12/16/2022]
Abstract
Since the discovery of penicillin, the development and use of antibiotics have promoted safe and effective control of bacterial infections. However, the number of antibiotic-resistance cases has been ever increasing over time. Thus, the drug discovery process demands fast, efficient and cost-effective alternative approaches for developing lead candidates with outstanding performance. Computational approaches are appealing techniques to develop lead candidates in an in silico fashion. In this review, we provide an overview of the implementation of current in silico state-of-the-art techniques, including machine learning (ML) and deep learning (DL), in drug discovery. We also discuss the development of quantum computing and its potential benefits for antibiotics research and current bottlenecks that limit computational drug discovery advancement.
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Affiliation(s)
- Thiago H da Silva
- Micron School of Materials Science and Engineering, Boise State University, Boise, ID 83725, USA
| | - Timothy Z Hachigian
- Micron School of Materials Science and Engineering, Boise State University, Boise, ID 83725, USA
| | - Jeunghoon Lee
- Micron School of Materials Science and Engineering, Boise State University, Boise, ID 83725, USA; Department of Chemistry and Biochemistry, Boise State University, Boise, ID 83725, USA
| | - Matthew D King
- Micron School of Materials Science and Engineering, Boise State University, Boise, ID 83725, USA; Department of Chemistry and Biochemistry, Boise State University, Boise, ID 83725, USA.
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5
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A partial least squares and artificial neural network study for a series of arylpiperazines as antidepressant agents. J Mol Model 2021; 27:297. [PMID: 34558019 DOI: 10.1007/s00894-021-04906-x] [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: 07/01/2021] [Accepted: 09/08/2021] [Indexed: 10/20/2022]
Abstract
Depression affects more than 300 million people around the world and can lead to suicide. About 30% of patients on treatment for depression drop out of therapy due to side effects or to latency time associated to therapeutic effects. 5-HT receptor, known as serotonin, is considered the key in depression treatment. Arylpiperazine compounds are responsible for several pharmacological effects and are considered as ligands in serotonin receptors, such as the subtype 5-HT2a. Here, in silico studies were developed using partial least squares (PLSs) and artificial neural networks (ANNs) to design new arylpiperazine compounds that could interact with the 5-HT2a receptor. First, molecular and electronic descriptors were calculated and posteriorly selected from correlation matrixes and genetic algorithm (GA). Then, the selected descriptors were used to construct PLS and ANN models that showed to be robust and predictive. Lastly, new arylpiperazine compounds were designed and their biological activity values were predicted by both PLS and ANN models. It is worth to highlight compounds G5 and G7 (predicted by the PLS model) and G3 and G15 (predicted by the ANN model), whose predicted pIC50 values were as high as the three highest values from the arylpiperazine original set studied here. Therefore, it can be asserted that the two models (PLS and ANN) proposed in this work are promising for the prediction of the biological activity of new arylpiperazine compounds and may significantly contribute to the design of new drugs for the treatment of depression.
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Araujo SC, Sousa FS, Costa-Silva TA, Tempone AG, Lago JHG, Honorio KM. Discovery of New Hits as Antitrypanosomal Agents by In Silico and In Vitro Assays Using Neolignan-Inspired Natural Products from Nectandra leucantha. Molecules 2021; 26:molecules26144116. [PMID: 34299391 PMCID: PMC8306904 DOI: 10.3390/molecules26144116] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 06/25/2021] [Accepted: 06/30/2021] [Indexed: 11/17/2022] Open
Abstract
In the present study, the phytochemical study of the n-hexane extract from flowers of Nectandra leucantha (Lauraceae) afforded six known neolignans (1–6) as well as one new metabolite (7), which were characterized by analysis of NMR, IR, UV, and ESI-HRMS data. The new compound 7 exhibited potent activity against the clinically relevant intracellular forms of T. cruzi (amastigotes), with an IC50 value of 4.3 μM and no observed mammalian cytotoxicity in fibroblasts (CC50 > 200 μM). Based on the results obtained and our previous antitrypanosomal data of 50 natural and semi-synthetic related neolignans, 2D and 3D molecular modeling techniques were employed to help the design of new neolignan-based compounds with higher activity. The results obtained from the models were important to understand the main structural features related to the biological response of the neolignans and to aid in the design of new neolignan-based compounds with better biological activity. Therefore, the results acquired from phytochemical, biological, and in silico studies showed that the integration of experimental and computational techniques consists of a powerful tool for the discovery of new prototypes for development of new drugs to treat CD.
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Affiliation(s)
- Sheila C. Araujo
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Avenida dos Estados, 5001 Bangu, Santo André 09210-580, SP, Brazil; (S.C.A.); (T.A.C.-S.)
| | - Fernanda S. Sousa
- Instituto de Ciências Ambientais, Químicas e Farmacêuticas, Universidade Federal de São Paulo, Rua Prof. Arthur Riedel, 275, Diadema 09972-271, SP, Brazil;
- Departamento de Fisiologia e Biofísica, Universidade Federal de Minas Gerais, Avenida Presidente Antônio Carlos, 6627, Belo Horizonte 31270-901, MG, Brazil
| | - Thais A. Costa-Silva
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Avenida dos Estados, 5001 Bangu, Santo André 09210-580, SP, Brazil; (S.C.A.); (T.A.C.-S.)
| | - Andre G. Tempone
- Centre for Parasitology and Mycology, Instituto Adolfo Lutz, Avenida Doutor Arnaldo, 351, São Paulo 01246-000, SP, Brazil;
| | - João Henrique G. Lago
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Avenida dos Estados, 5001 Bangu, Santo André 09210-580, SP, Brazil; (S.C.A.); (T.A.C.-S.)
- Correspondence: (J.H.G.L.); (K.M.H.)
| | - Kathia M. Honorio
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Avenida dos Estados, 5001 Bangu, Santo André 09210-580, SP, Brazil; (S.C.A.); (T.A.C.-S.)
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo, Rua Arlindo Bettio, 1000 Ermelino Matarazzo, São Paulo 03828-000, SP, Brazil
- Correspondence: (J.H.G.L.); (K.M.H.)
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7
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Chemical Graph Theory for Property Modeling in QSAR and QSPR—Charming QSAR & QSPR. MATHEMATICS 2020. [DOI: 10.3390/math9010060] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Quantitative structure-activity relationship (QSAR) and Quantitative structure-property relationship (QSPR) are mathematical models for the prediction of the chemical, physical or biological properties of chemical compounds. Usually, they are based on structural (grounded on fragment contribution) or calculated (centered on QSAR three-dimensional (QSAR-3D) or chemical descriptors) parameters. Hereby, we describe a Graph Theory approach for generating and mining molecular fragments to be used in QSAR or QSPR modeling based exclusively on fragment contributions. Merging of Molecular Graph Theory, Simplified Molecular Input Line Entry Specification (SMILES) notation, and the connection table data allows a precise way to differentiate and count the molecular fragments. Machine learning strategies generated models with outstanding root mean square error (RMSE) and R2 values. We also present the software Charming QSAR & QSPR, written in Python, for the property prediction of chemical compounds while using this approach.
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8
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Kumar SP, Patel CN, Rawal RM, Pandya HA. Energetic contributions of amino acid residues and its cross‐talk to delineate ligand‐binding mechanism. Proteins 2020; 88:1207-1225. [DOI: 10.1002/prot.25894] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 02/20/2020] [Accepted: 04/03/2020] [Indexed: 02/02/2023]
Affiliation(s)
| | - Chirag N. Patel
- Department of Botany, Bioinformatics, and Climate Change Impacts ManagementUniversity School of Sciences, Gujarat University Ahmedabad India
| | - Rakesh M. Rawal
- Department of Life SciencesUniversity School of Sciences, Gujarat University Ahmedabad India
| | - Himanshu A. Pandya
- Department of Life SciencesUniversity School of Sciences, Gujarat University Ahmedabad India
- Department of Botany, Bioinformatics, and Climate Change Impacts ManagementUniversity School of Sciences, Gujarat University Ahmedabad India
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9
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Elshakre ME, Noamaan MA, Moustafa H, Butt H. Density Functional Theory, Chemical Reactivity, Pharmacological Potential and Molecular Docking of Dihydrothiouracil-Indenopyridopyrimidines with Human-DNA Topoisomerase II. Int J Mol Sci 2020; 21:E1253. [PMID: 32070048 PMCID: PMC7072893 DOI: 10.3390/ijms21041253] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 01/25/2020] [Accepted: 01/27/2020] [Indexed: 01/31/2023] Open
Abstract
In this work, three computational methods (Hatree-Fock (HF), Møller-Plesset 2 (MP2), and Density Functional Theory (DFT)) using a variety of basis sets are used to determine the atomic and molecular properties of dihydrothiouracil-based indenopyridopyrimidine (TUDHIPP) derivatives. Reactivity descriptors of this system, including chemical potential (µ), chemical hardness (η), electrophilicity (ω), condensed Fukui function and dual descriptors are calculated at B3LYP/6-311++ G (d,p) to identify reactivity changes of these molecules in both gas and aqueous phases. We determined the molecular electrostatic surface potential (MESP) to determine the most active site in these molecules. Molecular docking study of TUDHIPP with topoisomerase II α and β is performed, predicting binding sites and binding energies with amino acids of both proteins. Docking studies of TUDHIPP versus etoposide suggest their potential as antitumor candidates. We have applied Lipinski, Veber's rules and analysis of the Golden triangle and structure activity/property relationship for a series of TUDHIPP derivatives indicate that the proposed compounds exhibit good oral bioavailability. The comparison of the drug likeness descriptors of TUDHIPP with those of etoposide, which is known to be an antitumor drug, indicates that TUDHIPP can be considered as an antitumor drug. The overall study indicates that TUDHIPP has comparable and even better descriptors than etoposide proposing that it can be as effective antitumor drug, especially 2H, 6H and 7H compounds.
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Affiliation(s)
- Mohamed E. Elshakre
- Chemistry Department, College of Science, Cairo University, Cairo 12613, Egypt;
| | - Mahmoud A. Noamaan
- Chemistry Department, College of Science, Cairo University, Cairo 12613, Egypt;
| | - Hussein Moustafa
- Chemistry Department, College of Science, Cairo University, Cairo 12613, Egypt;
| | - Haider Butt
- Department of Mechanical Engineering, Khalifa University, Abu Dhabi 127788, UAE;
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Two- and three-dimensional QSAR studies on hURAT1 inhibitors with flexible linkers: topomer CoMFA and HQSAR. Mol Divers 2019; 24:141-154. [PMID: 30868332 DOI: 10.1007/s11030-019-09936-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 03/01/2019] [Indexed: 12/20/2022]
Abstract
hURAT1 (human urate transporter 1) is a successful target for hyperuricemia. Recently, the modification work on hURAT1 inhibitors showed that the flexible linkers would benefit biological activity. The study aimed to investigate the contribution of the linkers and give modification strategies on this kind of structures based on QSAR models (HQSAR and topomer CoMFA). The most effective HQSAR and topomer CoMFA models were generated by applying the training set containing 63 compounds, with the cross-validated q2 values of 0.869/0.818 and the non-cross-validated correlation coefficients r2 of 0.951/0.978, respectively. The Y-randomization test was applied to ensure the robustness of the models. The external predictive correlation coefficient (rpred2) grounded on the external test set (21 compounds) of two models was 0.910 and 0.907, respectively. In addition, the models were validated by Golbraikh-Tropsha and Roy methods, as well as other statistical metrics. The results showed that both models were reliable. Topomer CoMFA steric/electrostatic contours and HQSAR atomic contribution maps illustrated the structural features which governed their inhibitory potency. The dependable results could provide important insights to guide the designing of more potential hURAT1 inhibitors.
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11
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Kimani NM, Matasyoh JC, Kaiser M, Nogueira MS, Trossini GHG, Schmidt TJ. Complementary Quantitative Structure⁻Activity Relationship Models for the Antitrypanosomal Activity of Sesquiterpene Lactones. Int J Mol Sci 2018; 19:ijms19123721. [PMID: 30467296 PMCID: PMC6321053 DOI: 10.3390/ijms19123721] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 11/17/2018] [Accepted: 11/19/2018] [Indexed: 02/01/2023] Open
Abstract
Three complementary quantitative structure–activity relationship (QSAR) methodologies, namely, regression modeling based on (i) “classical” molecular descriptors, (ii) 3D pharmacophore features, and (iii) 2D molecular holograms (HQSAR) were employed on the antitrypanosomal activity of sesquiterpene lactones (STLs) toward Trypanosoma brucei rhodesiense (Tbr), the causative agent of the East African form of human African trypanosomiasis. In this study, an extension of a previous QSAR study on 69 STLs, models for a much larger and more diverse set of such natural products, now comprising 130 STLs of various structural subclasses, were established. The extended data set comprises a variety of STLs isolated and tested for antitrypanosomal activity within our group and is furthermore enhanced by 12 compounds obtained from literature, which have been tested in the same laboratory under identical conditions. Detailed QSAR analyses yielded models with comparable and good internal and external predictive ability. For a set of compounds as chemically diverse as the one under study, the models exhibited good coefficients of determination (R2) ranging from 0.71 to 0.85, as well as internal (leave-one-out Q2 values ranging from 0.62 to 0.72) and external validation coefficients (P2 values ranging from 0.54 to 0.73). The contributions of the various tested descriptors to the generated models are in good agreement with the results of previous QSAR studies and corroborate the fact that the antitrypanosomal activity of STLs is very much dependent on the presence and relative position of reactive enone groups within the molecular structure but is influenced by their hydrophilic/hydrophobic properties and molecular shape.
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Affiliation(s)
- Njogu M Kimani
- Institute of Pharmaceutical Biology and Phytochemistry (IPBP), University of Muenster, PharmaCampus Corrensstrasse 48, D-48149 Muenster, Germany.
| | - Josphat C Matasyoh
- Department of Chemistry, Egerton University, P.O. Box 536, Egerton 20115, Kenya.
| | - Marcel Kaiser
- Swiss Tropical and Public Health Institute (Swiss TPH), Socinstrasse 57, CH-4051 Basel, Switzerland.
- University of Basel, Petersplatz 1, CH-4003 Basel, Switzerland.
| | - Mauro S Nogueira
- Institute of Pharmaceutical Biology and Phytochemistry (IPBP), University of Muenster, PharmaCampus Corrensstrasse 48, D-48149 Muenster, Germany.
| | - Gustavo H G Trossini
- Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, Av. Lineu Prestes 580, 05508-000 São Paulo, Brazil.
| | - Thomas J Schmidt
- Institute of Pharmaceutical Biology and Phytochemistry (IPBP), University of Muenster, PharmaCampus Corrensstrasse 48, D-48149 Muenster, Germany.
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12
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Makhouri FR, Ghasemi JB. In Silico Studies in Drug Research Against Neurodegenerative Diseases. Curr Neuropharmacol 2018; 16:664-725. [PMID: 28831921 PMCID: PMC6080098 DOI: 10.2174/1570159x15666170823095628] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 07/24/2017] [Accepted: 08/16/2017] [Indexed: 01/14/2023] Open
Abstract
Background Neurodegenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis, Parkinson's disease (PD), spinal cerebellar ataxias, and spinal and bulbar muscular atrophy are described by slow and selective degeneration of neurons and axons in the central nervous system (CNS) and constitute one of the major challenges of modern medicine. Computer-aided or in silico drug design methods have matured into powerful tools for reducing the number of ligands that should be screened in experimental assays. Methods In the present review, the authors provide a basic background about neurodegenerative diseases and in silico techniques in the drug research. Furthermore, they review the various in silico studies reported against various targets in neurodegenerative diseases, including homology modeling, molecular docking, virtual high-throughput screening, quantitative structure activity relationship (QSAR), hologram quantitative structure activity relationship (HQSAR), 3D pharmacophore mapping, proteochemometrics modeling (PCM), fingerprints, fragment-based drug discovery, Monte Carlo simulation, molecular dynamic (MD) simulation, quantum-mechanical methods for drug design, support vector machines, and machine learning approaches. Results Detailed analysis of the recently reported case studies revealed that the majority of them use a sequential combination of ligand and structure-based virtual screening techniques, with particular focus on pharmacophore models and the docking approach. Conclusion Neurodegenerative diseases have a multifactorial pathoetiological origin, so scientists have become persuaded that a multi-target therapeutic strategy aimed at the simultaneous targeting of multiple proteins (and therefore etiologies) involved in the development of a disease is recommended in future.
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Affiliation(s)
| | - Jahan B Ghasemi
- Chemistry Department, Faculty of Sciences, University of Tehran, Tehran, Iran
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13
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Comparative molecular field analysis and hologram quantitative structure activity relationship studies of pyrimidine series as potent phosphodiesterase 10A inhibitors. J CHIN CHEM SOC-TAIP 2018. [DOI: 10.1002/jccs.201700435] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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14
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Aguiar ACC, Panciera M, Simão dos Santos EF, Singh MK, Garcia ML, de Souza GE, Nakabashi M, Costa JL, Garcia CRS, Oliva G, Correia CRD, Guido RVC. Discovery of Marinoquinolines as Potent and Fast-Acting Plasmodium falciparum Inhibitors with in Vivo Activity. J Med Chem 2018; 61:5547-5568. [DOI: 10.1021/acs.jmedchem.8b00143] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- Anna Caroline Campos Aguiar
- Sao Carlos Institute of Physics, University of Sao Paulo, Av. Joao Dagnone, 1100 Jardim Santa Angelina, São Carlos, SP 13563-120, Brazil
| | - Michele Panciera
- Institute of Chemistry, State University of Campinas, Josue de Castro St., Campinas, SP 13083-970, Brazil
| | | | - Maneesh Kumar Singh
- Faculty of Pharmaceutical Sciences, University of Sao Paulo, Av. Prof. Lineu Prestes, 580 Cidade Universitária, São Paulo, SP 05508-900, Brazil
- Department of Physiology, University of Sao Paulo, Rua do Matão 101, Travessa 14, São Paulo, SP 05508-090, Brazil
| | - Mariana Lopes Garcia
- Sao Carlos Institute of Physics, University of Sao Paulo, Av. Joao Dagnone, 1100 Jardim Santa Angelina, São Carlos, SP 13563-120, Brazil
| | - Guilherme Eduardo de Souza
- Sao Carlos Institute of Physics, University of Sao Paulo, Av. Joao Dagnone, 1100 Jardim Santa Angelina, São Carlos, SP 13563-120, Brazil
| | - Myna Nakabashi
- Department of Physiology, University of Sao Paulo, Rua do Matão 101, Travessa 14, São Paulo, SP 05508-090, Brazil
| | - José Luiz Costa
- Faculty of Pharmaceutical Sciences, State University of Campinas, Rua Oswaldo Cruz, 2° Andar, Bloco F3, Cidade Universitária, Campinas, SP 13083-859, Brazil
| | - Célia R. S. Garcia
- Faculty of Pharmaceutical Sciences, University of Sao Paulo, Av. Prof. Lineu Prestes, 580 Cidade Universitária, São Paulo, SP 05508-900, Brazil
| | - Glaucius Oliva
- Sao Carlos Institute of Physics, University of Sao Paulo, Av. Joao Dagnone, 1100 Jardim Santa Angelina, São Carlos, SP 13563-120, Brazil
| | | | - Rafael Victorio Carvalho Guido
- Sao Carlos Institute of Physics, University of Sao Paulo, Av. Joao Dagnone, 1100 Jardim Santa Angelina, São Carlos, SP 13563-120, Brazil
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Wang T, Yuan XS, Wu MB, Lin JP, Yang LR. The advancement of multidimensional QSAR for novel drug discovery - where are we headed? Expert Opin Drug Discov 2017; 12:769-784. [PMID: 28562095 DOI: 10.1080/17460441.2017.1336157] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
INTRODUCTION The Multidimensional quantitative structure-activity relationship (multidimensional-QSAR) method is one of the most popular computational methods employed to predict interesting biochemical properties of existing or hypothetical molecules. With continuous progress, the QSAR method has made remarkable success in various fields, such as medicinal chemistry, material science and predictive toxicology. Areas covered: In this review, the authors cover the basic elements of multidimensional -QSAR including model construction, validation and application. It includes and emphasizes the very recent developments of multidimensional -QSAR such as: HQSAR, G-QSAR, MIA-QSAR, multi-target QSAR. The advantages and disadvantages of each method are also discussed and typical examples of their application are detailed. Expert opinion: Although there are defects in multidimensional-QSAR modeling, it is still of enormous help to chemists, biologists and other researchers in various fields. In the authors' opinion, the latest more precise and feasible QSAR models should be further developed by integrating new descriptors, algorithms and other relevant computational techniques. Apart from being applied in traditional fields (e.g. lead optimization and predictive risk assessment), QSAR should be used more widely as a routine method in other emerging research fields including the modeling of nanoparticles(NPs), mixture toxicity and peptides.
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Affiliation(s)
- Tao Wang
- a School of biological science , Jining Medical University , Jining , China.,b Department of Chemical and Biological Engineering , Zhejiang University , Hangzhou , China
| | - Xin-Song Yuan
- b Department of Chemical and Biological Engineering , Zhejiang University , Hangzhou , China
| | - Mian-Bin Wu
- b Department of Chemical and Biological Engineering , Zhejiang University , Hangzhou , China
| | - Jian-Ping Lin
- b Department of Chemical and Biological Engineering , Zhejiang University , Hangzhou , China
| | - Li-Rong Yang
- b Department of Chemical and Biological Engineering , Zhejiang University , Hangzhou , China
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16
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Combined HQSAR, topomer CoMFA, homology modeling and docking studies on triazole derivatives as SGLT2 inhibitors. Future Med Chem 2017. [DOI: 10.4155/fmc-2017-0002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Aim: Sodium–glucose cotransporter 2 (SGLT2) is a promising target for diabetes therapy. We aimed to develop computational approaches to identify structural features for more potential SGLT2 inhibitors. Materials & methods: In this work, 46 triazole derivatives as SGLT2 inhibitors were studied using a combination of several approaches, including hologram quantitative structure–activity relationships (HQSAR), topomer comparative molecular field analysis (CoMFA), homology modeling, and molecular docking. HQSAR and topomer CoMFA were used to construct models. Molecular docking was conducted to investigate the interaction of triazole derivatives and homology modeling of SGLT2, as well as to validate the results of the HQSAR and topomer CoMFA models. Results: The most effective HQSAR and topomer CoMFA models exhibited noncross-validated correlation coefficients of 0.928 and 0.891 for the training set, respectively. External predictions were made successfully on a test set and then compared with previously reported models. The graphical results of HQSAR and topomer CoMFA were proven to be consistent with the binding mode of the inhibitors and SGLT2 from molecular docking. Conclusion: The models and docking provided important insights into the design of potent inhibitors for SGLT2.
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Podlewska S, Czarnecki WM, Kafel R, Bojarski AJ. Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization. J Chem Inf Model 2017; 57:133-147. [DOI: 10.1021/acs.jcim.6b00426] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Sabina Podlewska
- Department of Medicinal
Chemistry, Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343 Kraków, Poland
| | - Wojciech M. Czarnecki
- Faculty
of Mathematics and Computer Science, Jagiellonian University, 30-348 Kraków, Poland
| | - Rafał Kafel
- Department of Medicinal
Chemistry, Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343 Kraków, Poland
| | - Andrzej J. Bojarski
- Department of Medicinal
Chemistry, Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343 Kraków, Poland
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18
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Heidari A, Fatemi MH. Comparative molecular field analysis (CoMFA), topomer CoMFA, and hologram QSAR studies on a series of novel HIV-1 protease inhibitors. Chem Biol Drug Des 2017; 89:918-931. [DOI: 10.1111/cbdd.12917] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Revised: 08/03/2016] [Accepted: 10/30/2016] [Indexed: 12/01/2022]
Affiliation(s)
- Afsane Heidari
- Chemometrics Laboratory; Faculty of Chemistry; University of Mazandaran; Babolsar Iran
| | - Mohammad H. Fatemi
- Chemometrics Laboratory; Faculty of Chemistry; University of Mazandaran; Babolsar Iran
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Studies of Staphylococcus aureus FabI inhibitors: fragment-based approach based on holographic structure-activity relationship analyses. Future Med Chem 2017; 9:135-151. [PMID: 28128979 DOI: 10.4155/fmc-2016-0179] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
AIM FabI is a key enzyme in the fatty acid metabolism of Gram-positive bacteria such as Staphylococcus aureus and is an established drug target for known antibiotics such as triclosan. However, due to increasing antibacterial resistance, there is an urgent demand for new drug discovery. Recently, aminopyridine derivatives have been proposed as promising competitive inhibitors of FabI. METHODS In the present study, holographic structure-activity relationship (HQSAR) analyses were employed for determining structural contributions of a series containing 105 FabI inhibitors. RESULTS & CONCLUSION The final HQSAR model was robust and predictive according to statistical validation (q2 and r2pred equal to 0.696 and 0.854, respectively) and could be further employed to generate fragment contribution maps. Then, final HQSAR model together with FabI active site information can be useful for designing novel bioactive ligands.
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20
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Aswathy L, Jisha RS, Masand VH, Gajbhiye JM, Shibi IG. Computational strategies to explore antimalarial thiazine alkaloid lead compounds based on an Australian marine sponge Plakortis Lita. J Biomol Struct Dyn 2016; 35:2407-2429. [PMID: 27494993 DOI: 10.1080/07391102.2016.1220870] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
In this work, an attempt was made to propose new leads based on the natural scaffold Thiaplakortone-A active against malaria. The 2D QSAR studies suggested that three descriptors correlate with the anti-malarial activity with an R2 value of 0.814. Robustness, reliability, and predictive power of the model were tested by internal validation, external validation, Y-scrambling, and applicability domain analysis. HQSAR studies were carried out as an additional tool to find the sub-structural fingerprints. The CoMFA and CoMSIA models gave Q2 values of 0.813 and 0.647, and [Formula: see text] values of 0.994 and 0.984, respectively. Using the 2D-QSAR equation, the activity values of the seven modified compounds were calculated and it was found that three molecules showed good anti-malarial activity. Molecular docking of the 42 Thiaplakortone-A derivatives with Plasmodium falciparum calcium-dependent protein kinase 1 (PfCDPK1) was carried out to find out protein-ligand interactions. Data mining of the bioassay data-set AID: 504850 using the classifier based on Random Forest of Weka suggested that all of the eight molecules selected and three out of the seven virtual molecules were anti-malarial active. Both the virtual molecules and drug molecules were docked with CYP3A4, indicating that the virtual molecules could metabolize easily. Toxicity studies using Osiris shows that three molecules showed no toxic characters.
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Affiliation(s)
- Lilly Aswathy
- a Department of Chemistry , Sree Narayana College , Thiruvananthapuram , Kerala , India
| | - Radhakrishnan S Jisha
- a Department of Chemistry , Sree Narayana College , Thiruvananthapuram , Kerala , India
| | - Vijay H Masand
- b Department of Chemistry , Vidya Bharati College , Camp, Amravati , Maharashtra , India
| | - Jayant M Gajbhiye
- c Division of Organic Chemistry , CSIR-National Chemical Laboratory , Pune , India
| | - Indira G Shibi
- a Department of Chemistry , Sree Narayana College , Thiruvananthapuram , Kerala , India
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21
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Yuan J, Yu S, Zhang T, Yuan X, Cao Y, Yu X, Yang X, Yao W. QSPR models for predicting generator-column-derived octanol/water and octanol/air partition coefficients of polychlorinated biphenyls. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2016; 128:171-80. [PMID: 26943944 DOI: 10.1016/j.ecoenv.2016.02.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Revised: 01/24/2016] [Accepted: 02/22/2016] [Indexed: 05/26/2023]
Abstract
Octanol/water (K(OW)) and octanol/air (K(OA)) partition coefficients are two important physicochemical properties of organic substances. In current practice, K(OW) and K(OA) values of some polychlorinated biphenyls (PCBs) are measured using generator column method. Quantitative structure-property relationship (QSPR) models can serve as a valuable alternative method of replacing or reducing experimental steps in the determination of K(OW) and K(OA). In this paper, two different methods, i.e., multiple linear regression based on dragon descriptors and hologram quantitative structure-activity relationship, were used to predict generator-column-derived log K(OW) and log K(OA) values of PCBs. The predictive ability of the developed models was validated using a test set, and the performances of all generated models were compared with those of three previously reported models. All results indicated that the proposed models were robust and satisfactory and can thus be used as alternative models for the rapid assessment of the K(OW) and K(OA) of PCBs.
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Affiliation(s)
- Jintao Yuan
- School of Public Health, Zhengzhou University, Zhengzhou 450001, China; Key Laboratory of Environmental Medicine Engineering of Ministry of Education, Southeast University, Nanjing 210009, China
| | - Shuling Yu
- Key Laboratory of Natural Medicine and Immune-Engineering of Henan Province, Henan University, Kaifeng 475004, China
| | - Ting Zhang
- Key Laboratory of Environmental Medicine Engineering of Ministry of Education, Southeast University, Nanjing 210009, China
| | - Xuejie Yuan
- Shangqiu Medical College, Shangqiu, Henan Province 476100, China
| | - Yunyuan Cao
- School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Xingchen Yu
- School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Xuan Yang
- School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Wu Yao
- School of Public Health, Zhengzhou University, Zhengzhou 450001, China.
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22
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Primi MC, Maltarollo VG, Magalhães JG, de Sá MM, Rangel-Yagui CO, Trossini GHG. Convergent QSAR studies on a series of NK₃ receptor antagonists for schizophrenia treatment. J Enzyme Inhib Med Chem 2015; 31:283-94. [PMID: 25856571 DOI: 10.3109/14756366.2015.1021250] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The dopamine hypothesis states that decreased dopaminergic neurotransmission reduces schizophrenia symptoms. Neurokinin-3 receptor (NK3) antagonists reduce dopamine release and have shown positive effects in pre-clinical and clinical trials. We employed 2D and 3D-QSAR analysis on a series of 40 non-peptide NK3 antagonists. Multivariate statistical analysis, PCA and HCA, were performed to rational training/test set splitting and PLS regression was employed to construct all QSAR models. We constructed one highly predictive CoMFA model (q(2)= 0.810 and r(2)= 0.929) and acceptable HQSAR and CoMSIA models (HQSAR q(2)= 0.644 and r(2)= 0.910; CoMSIA q(2)= 0.691, r(2)= 0.911). The three different techniques provided convergent physicochemical results. All models indicate cyclopropane, piperidine and di-chloro-phenyl ring attached to cyclopropane ring and also the amide group attached to the piperidine ring could play an important role in ligand-receptor interactions. These findings may contribute to develop potential NK3 receptor antagonists for schizophrenia.
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Affiliation(s)
- Marina Candido Primi
- a Department of Pharmacy, Faculty of Pharmaceutical Sciences , University of São Paulo , SP , Brazil
| | | | | | - Matheus Malta de Sá
- b Laboratory of Genetics and Molecular Cardiology , Heart Institute (InCor), University of São Paulo Medical School , SP , Brazil , and
| | - Carlota Oliveira Rangel-Yagui
- c Department of Biochemical and Pharmaceutical Technology, Faculty of Pharmaceutical Sciences , University of São Paulo , SP , Brazil
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23
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Xing J, Yang L, Li H, Li Q, Zhao L, Wang X, Zhang Y, Zhou M, Zhou J, Zhang H. Identification of anthranilamide derivatives as potential factor Xa inhibitors: drug design, synthesis and biological evaluation. Eur J Med Chem 2015; 95:388-99. [PMID: 25839438 DOI: 10.1016/j.ejmech.2015.03.052] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2014] [Revised: 03/21/2015] [Accepted: 03/23/2015] [Indexed: 11/30/2022]
Abstract
The coagulation enzyme factor Xa (fXa) plays a crucial role in the blood coagulation cascade. In this study, three-dimensional fragment based drug design (FBDD) combined with structure-based pharmacophore (SBP) model and structural consensus docking were employed to identify novel fXa inhibitors. After a multi-stage virtual screening (VS) workflow, two hit compounds 3780 and 319 having persistent high performance were identified. Then, these two hit compounds and several analogs were synthesized and screened for in-vitro inhibition of fXa. The experimental data showed that most of the designed compounds displayed significant in vitro potency against fXa. Among them, compound 9b displayed the greatest in vitro potency against fXa with the IC50 value of 23 nM and excellent selectivity versus thrombin (IC50 = 40 μM). Moreover, the prolongation of the prothrombin time (PT) was measured for compound 9b to evaluate its in vitro anticoagulant activity. As a result, compound 9b exhibited pronounced anticoagulant activity with the 2 × PT value of 8.7 μM.
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Affiliation(s)
- Junhao Xing
- Center of Drug Discovery, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing 210009, PR China.
| | - Lingyun Yang
- Center of Drug Discovery, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing 210009, PR China
| | - Hui Li
- Center of Drug Discovery, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing 210009, PR China
| | - Qing Li
- Center of Drug Discovery, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing 210009, PR China
| | - Leilei Zhao
- Center of Drug Discovery, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing 210009, PR China
| | - Xinning Wang
- Center of Drug Discovery, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing 210009, PR China
| | - Yuan Zhang
- Department of Medicinal Chemistry, China Pharmaceutical University, TongjiaXiang 24, 210009 Nanjing, PR China
| | - Muxing Zhou
- Center of Drug Discovery, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing 210009, PR China
| | - Jinpei Zhou
- Department of Medicinal Chemistry, China Pharmaceutical University, TongjiaXiang 24, 210009 Nanjing, PR China
| | - Huibin Zhang
- Center of Drug Discovery, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing 210009, PR China; Jiangsu Key Laboratory of Drug Discovery for Metabolic Disease, China Pharmaceutical University, Nanjing 210009, PR China.
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24
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Ligand biological activity predictions using fingerprint-based artificial neural networks (FANN-QSAR). Methods Mol Biol 2015; 1260:149-64. [PMID: 25502380 DOI: 10.1007/978-1-4939-2239-0_9] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In addition, the FANN-QSAR model was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds. We discovered several compounds with good CB2 binding affinities ranging from 6.70 nM to 3.75 μM. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research.
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25
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Hologram QSAR studies of antiprotozoal activities of sesquiterpene lactones. Molecules 2014; 19:10546-62. [PMID: 25045893 PMCID: PMC6271290 DOI: 10.3390/molecules190710546] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2014] [Revised: 07/08/2014] [Accepted: 07/09/2014] [Indexed: 11/26/2022] Open
Abstract
Infectious diseases such as trypanosomiasis and leishmaniasis are considered neglected tropical diseases due the lack for many years of research and development into new drug treatments besides the high incidence of mortality and the lack of current safe and effective drug therapies. Natural products such as sesquiterpene lactones have shown activity against T. brucei and L. donovani, the parasites responsible for these neglected diseases. To evaluate structure activity relationships, HQSAR models were constructed to relate a series of 40 sesquiterpene lactones (STLs) with activity against T. brucei, T. cruzi, L. donovani and P. falciparum and also with their cytotoxicity. All constructed models showed good internal (leave-one-out q2 values ranging from 0.637 to 0.775) and external validation coefficients (r2test values ranging from 0.653 to 0.944). From HQSAR contribution maps, several differences between the most and least potent compounds were found. The fragment contribution of PLS-generated models confirmed the results of previous QSAR studies that the presence of α,β-unsatured carbonyl groups is fundamental to biological activity. QSAR models for the activity of these compounds against T. cruzi, L. donovani and P. falciparum are reported here for the first time. The constructed HQSAR models are suitable to predict the activity of untested STLs.
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26
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Quantitative structure–activity relationship (QSAR) studies as strategic approach in drug discovery. Med Chem Res 2014. [DOI: 10.1007/s00044-014-1072-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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27
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Cho M, Yoon H, Park M, Kim YH, Lim Y. Flavonoids promoting HaCaT migration: I. Hologram quantitative structure-activity relationships. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2014; 21:560-569. [PMID: 24252338 DOI: 10.1016/j.phymed.2013.10.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2013] [Accepted: 10/11/2013] [Indexed: 06/02/2023]
Abstract
Cell migration plays an important role in multicellular development and preservation. Because wound healing requires cell migration, compounds promoting cell migration can be used for wound repair therapy. Several plant-derived polyphenols are known to promote cell migration, which improves wound healing. Previous studies of flavonoids on cell lines have focused on their inhibitory effects and not on wound healing. In addition, studies of flavonoids on wound healing have been performed using mixtures. In this study, individual flavonoids were used for cellular migration measurements. Relationships between the cell migration effects of flavonoids and their structural properties have never been reported. Here, we investigated the migration of keratinocytes caused by 100 flavonoids and examined their relationships using hologram quantitative structure-activity relationships. The structural conditions responsible for efficient cell migration on keratinocyte cell lines determined from the current study will facilitate the design of flavonoids with improved activity.
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Affiliation(s)
- Moonjae Cho
- Department of Biochemistry, School of Medicine, Jeju National University, Jeju 690-756, Republic of Korea
| | - Hyuk Yoon
- Division of Bioscience and Biotechnology, BMIC, Konkuk University, Seoul 143-701, Republic of Korea
| | - Mijoo Park
- Division of Bioscience and Biotechnology, BMIC, Konkuk University, Seoul 143-701, Republic of Korea
| | - Young Hwa Kim
- National Institute of Animal Science, Rural Development Administration, Cheonan 330-801, Republic of Korea
| | - Yoongho Lim
- Division of Bioscience and Biotechnology, BMIC, Konkuk University, Seoul 143-701, Republic of Korea.
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28
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Kahn I, Lomaka A, Karelson M. Topological Fingerprints as an Aid in Finding Structural Patterns for LRRK2 Inhibition. Mol Inform 2014; 33:269-75. [DOI: 10.1002/minf.201300057] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2013] [Accepted: 11/12/2013] [Indexed: 11/12/2022]
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29
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Bhansali SG, Kulkarni VM. Combined 2D and 3D-QSAR, molecular modelling and docking studies of pyrazolodiazepinones as novel phosphodiesterase 2 inhibitors. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2014; 25:905-937. [PMID: 25401514 DOI: 10.1080/1062936x.2014.969309] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Selective inhibition of phosphodiesterase 2 (PDE2) in cells where it is located elevates cyclic guanosine monophosphate (cGMP) and acts as novel analgesic with antinociceptive activity. Three-dimensional quantitative structure-activity relationship (QSAR) studies for pyrazolodiazepinone inhibitors exhibiting PDE2 inhibition were performed using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and Topomer CoMFA, and two-dimensional QSAR study was performed using a Hologram QSAR (HQSAR) method. QSAR models were generated using training set of 23 compounds and were validated using test set of nine compounds. The optimum partial least squares (PLS) for CoMFA-Focusing, CoMSIA-SDH, Topomer CoMFA and HQSAR models exhibited good 'leave-one-out' cross validated correlation coefficient (q(2)) of 0.790, 0.769, 0.840 and 0.787, coefficient of determination (r(2)) of 0.999, 0.964, 0.979 and 0.980, and high predictive power (r(2)(pred)) of 0.796, 0.833, 0.820 and 0.803 respectively. Docking studies revealed that those inhibitors able to bind to amino acid Gln859 by cGMP binding orientation called 'glutamine-switch', and also bind to the hydrophobic clamp of PDE2 isoform, could possess high selectivity for PDE2. From the results of all the studies, structure-activity relationships and structural requirements for binding to active site of PDE2 were established which provide useful guidance for the design and future synthesis of potent PDE2 inhibitors.
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Affiliation(s)
- S G Bhansali
- a Department of Pharmaceutical Chemistry, Poona College of Pharmacy , Bharati Vidyapeeth Deemed University , Pune , Maharashtra , India
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30
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Paz OS, Brito CCB, Castilho MS. Quantitative insights towards the design of potent deazaxanthine antagonists of adenosine 2B receptors. J Enzyme Inhib Med Chem 2013; 29:590-8. [DOI: 10.3109/14756366.2013.830113] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Affiliation(s)
- Odailson Santos Paz
- Programa de Pós-graduação em Biotecnologia, Universidade Estadual de Feira de Santana, Ondina – Salvador
BahiaBrazil
| | - Camila Carane Bitencourt Brito
- Programa de Pós-graduação em Farmácia, Faculdade de Farmácia, Universidade Federal da Bahia, Ondina – Salvador
BahiaBrazil
| | - Marcelo Santos Castilho
- Programa de Pós-graduação em Farmácia, Faculdade de Farmácia, Universidade Federal da Bahia, Ondina – Salvador
BahiaBrazil
- Instituto Nacional de Ciência e Tecnologia em Biologia Estrutural e Bioimagem, Ondina – Salvador
BahiaBrazil
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31
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Palangsuntikul R, Berner H, Berger ML, Wolschann P. Holographic quantitative structure-activity relationships of tryptamine derivatives at NMDA, 5HT(1A) and 5HT(2A) receptors. Molecules 2013; 18:8799-811. [PMID: 23887721 PMCID: PMC6270498 DOI: 10.3390/molecules18088799] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2013] [Revised: 07/17/2013] [Accepted: 07/18/2013] [Indexed: 11/16/2022] Open
Abstract
Tryptamine derivatives (Ts) were found to inhibit the binding of [3H]MK-801, [3H]ketanserin and [3H]8-OH-DPAT to rat brain membranes. [3H]MK-801 labels the NMDA (N-methyl-D-aspartate) receptor, a ionotropic glutamate receptor which controls synaptic plasticity and memory function in the brain, whereas [3H]ketanserin and [3H]8-OH-DPAT label 5HT2A and 5HT1A receptors, respectively. The inhibitory potencies of 64 Ts (as given by IC50 values) were correlated with their structural properties by using the Holographic QSAR procedure (HQSAR). This method uses structural fragments and connectivities as descriptors which were encoded in a hologram thus avoiding the usual problems with conformation and alignment of the structures. Four correlation equations with high predictive ability and appropriate statistical test values could be established. The results are visualized by generation of maps reflecting the contribution of individual structural parts to the biological activities.
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Affiliation(s)
- Rungtiva Palangsuntikul
- Biological Engineering Program, Faculty of Enigineering, King Mongkut's University of Technology Thonburi, Bangmod Campus, Bangkok 10140, Thailand.
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Araujo SC, Maltarollo VG, Honorio KM. Computational studies of TGF-βRI (ALK-5) inhibitors: analysis of the binding interactions between ligand-receptor using 2D and 3D techniques. Eur J Pharm Sci 2013; 49:542-9. [PMID: 23727056 DOI: 10.1016/j.ejps.2013.05.015] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2013] [Revised: 05/16/2013] [Accepted: 05/18/2013] [Indexed: 11/25/2022]
Abstract
ALK-5 (Activin-Like Kinase 5) is a biological receptor involved in a variety of pathological processes such as cancer and fibrosis. ALK-5 receptor propagates an intracellular signaling that forms a protein complex capable of reaching the nucleus and modulating the gene transcription. In the present study, comparative molecular field analysis (CoMFA) and hologram quantitative structure-activity relationship (HQSAR) studies were conducted on a series of potent ALK-5 inhibitors. Significant correlation coefficients (CoMFA, r(2)=0.99 and q(2)=0.85; HQSAR, r(2)=0.92 and q(2)=0.72) were obtained, indicating the predictive potential of the 2D and 3D models for untested compounds. The models were then used to predict the potency of a test set, and the predicted values from the HQSAR and CoMFA models were in good agreement with the experimental results. The final QSAR models, along with the information obtained from 3D (steric and electrostatic) contour maps and 2D contribution maps, can be useful for the design of novel bioactive ligands.
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Affiliation(s)
- Sheila C Araujo
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, R. Santa Adélia 166, 09210-170 Santo André, SP, Brazil
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Myint KZ, Wang L, Tong Q, Xie XQ. Molecular fingerprint-based artificial neural networks QSAR for ligand biological activity predictions. Mol Pharm 2012; 9:2912-23. [PMID: 22937990 PMCID: PMC3462244 DOI: 10.1021/mp300237z] [Citation(s) in RCA: 71] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
In this manuscript, we have reported a novel 2D fingerprint-based artificial neural network QSAR (FANN-QSAR) method in order to effectively predict biological activities of structurally diverse chemical ligands. Three different types of fingerprints, namely, ECFP6, FP2 and MACCS, were used in FANN-QSAR algorithm development, and FANN-QSAR models were compared to known 3D and 2D QSAR methods using five data sets previously reported. In addition, the derived models were used to predict GPCR cannabinoid ligand binding affinities using our manually curated cannabinoid ligand database containing 1699 structurally diverse compounds with reported cannabinoid receptor subtype CB(2) activities. To demonstrate its useful applications, the established FANN-QSAR algorithm was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds, and we have discovered several compounds with good CB(2) binding affinities ranging from 6.70 nM to 3.75 μM. To the best of our knowledge, this is the first report for a fingerprint-based neural network approach validated with a successful virtual screening application in identifying lead compounds. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research.
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Affiliation(s)
- Kyaw-Zeyar Myint
- Department of Computational Biology, Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program, School of Medicine; Pittsburgh, Pennsylvania 15260
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; Pittsburgh, Pennsylvania 15260
- Drug Discovery Institute; University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Lirong Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; Pittsburgh, Pennsylvania 15260
- Drug Discovery Institute; University of Pittsburgh, Pittsburgh, Pennsylvania 15260
- Pittsburgh Chemical Methods and Library Development (CMLD) Center; University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Qin Tong
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; Pittsburgh, Pennsylvania 15260
| | - Xiang-Qun Xie
- Department of Computational Biology, Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program, School of Medicine; Pittsburgh, Pennsylvania 15260
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; Pittsburgh, Pennsylvania 15260
- Drug Discovery Institute; University of Pittsburgh, Pittsburgh, Pennsylvania 15260
- Pittsburgh Chemical Methods and Library Development (CMLD) Center; University of Pittsburgh, Pittsburgh, Pennsylvania 15260
- Department of Structural Biology, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
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Henen M, Coudevylle N, Geist L, Konrat R. Toward rational fragment-based lead design without 3D structures. J Med Chem 2012; 55:7909-19. [PMID: 22889313 PMCID: PMC3557921 DOI: 10.1021/jm301016m] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2012] [Indexed: 01/21/2023]
Abstract
Fragment-based lead discovery (FBLD) has become a prime component of the armamentarium of modern drug design programs. FBLD identifies low molecular weight ligands that weakly bind to important biological targets. Three-dimensional structural information about the binding mode is provided by X-ray crystallography or NMR spectroscopy and is subsequently used to improve the lead compounds. Despite tremendous success rates, FBLD relies on the availability of high-resolution structural information, still a bottleneck in drug discovery programs. To overcome these limitations, we recently demonstrated that the meta-structure approach provides an alternative route to rational lead identification in cases where no 3D structure information about the biological target is available. Combined with information-rich NMR data, this strategy provides valuable information for lead development programs. We demonstrate with several examples the feasibility of the combined NMR and meta-structure approach to devise a rational strategy for fragment evolution without resorting to highly resolved protein complex structures.
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Affiliation(s)
- Morkos
A. Henen
- Department of Structural and Computational Biology,
Max F. Perutz Laboratories, University of Vienna, Vienna Biocenter Campus 5, A-1030 Vienna, Austria
| | - Nicolas Coudevylle
- Department of Structural and Computational Biology,
Max F. Perutz Laboratories, University of Vienna, Vienna Biocenter Campus 5, A-1030 Vienna, Austria
| | - Leonhard Geist
- Department of Structural and Computational Biology,
Max F. Perutz Laboratories, University of Vienna, Vienna Biocenter Campus 5, A-1030 Vienna, Austria
| | - Robert Konrat
- Department of Structural and Computational Biology,
Max F. Perutz Laboratories, University of Vienna, Vienna Biocenter Campus 5, A-1030 Vienna, Austria
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Bueno RV, Toledo NR, Neves BJ, Braga RC, Andrade CH. Structural and chemical basis for enhanced affinity to a series of mycobacterial thymidine monophosphate kinase inhibitors: fragment-based QSAR and QM/MM docking studies. J Mol Model 2012; 19:179-92. [DOI: 10.1007/s00894-012-1527-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2012] [Accepted: 07/03/2012] [Indexed: 10/28/2022]
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Abstract
Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein–ligand interactions. Structure- (SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.
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Moda TL, Andricopulo AD. Consensus hologram QSAR modeling for the prediction of human intestinal absorption. Bioorg Med Chem Lett 2012; 22:2889-93. [DOI: 10.1016/j.bmcl.2012.02.061] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2012] [Revised: 02/16/2012] [Accepted: 02/17/2012] [Indexed: 11/28/2022]
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Biniashvili T, Schreiber E, Kliger Y. Improving Classical Substructure-Based Virtual Screening to Handle Extrapolation Challenges. J Chem Inf Model 2012; 52:678-85. [DOI: 10.1021/ci200472s] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Tammy Biniashvili
- Compugen LTD, Tel Aviv 69512, Israel
- The Mina and Everard Goodman
Faculty of Life Sciences, Bar Ilan University, Ramat-Gan 52900, Israel
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A fragment-based approach for ligand binding affinity and selectivity for the liver X receptor beta. J Mol Graph Model 2012; 32:19-31. [DOI: 10.1016/j.jmgm.2011.09.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2011] [Revised: 09/21/2011] [Accepted: 09/25/2011] [Indexed: 11/22/2022]
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40
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Maganti L, Das SK, Mascarenhas NM, Ghoshal N. Deciphering the Structural Requirements of Nucleoside Bisubstrate Analogues for Inhibition of MbtA in Mycobacterium tuberculosis: A FB-QSAR Study and Combinatorial Library Generation for Identifying Potential Hits. Mol Inform 2011; 30:863-72. [DOI: 10.1002/minf.201100056] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2011] [Accepted: 07/05/2011] [Indexed: 11/06/2022]
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Myint KZ, Ma C, Wang L, Xie XQ. Fragment-similarity-based QSAR (FS-QSAR) algorithm for ligand biological activity predictions. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2011; 22:385-410. [PMID: 21598200 DOI: 10.1080/1062936x.2011.569943] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Quantitative structure-activity relationship (QSAR) studies are useful computational tools often used in drug discovery research and in many scientific disciplines. In this study, a robust fragment-similarity-based QSAR (FS-QSAR) algorithm was developed to correlate structures with biological activities by integrating fragment-based drug design concept and a multiple linear regression method. Similarity between any pair of training and testing fragments was determined by calculating the difference of lowest or highest eigenvalues of the chemistry space BCUT matrices of corresponding fragments. In addition to the BCUT-similarity function, molecular fingerprint Tanimoto coefficient (Tc) similarity function was also used as an alternative for comparison. For validation studies, the FS-QSAR algorithm was applied to several case studies, including a dataset of COX2 inhibitors and a dataset of cannabinoid CB2 triaryl bis-sulfone antagonist analogues, to build predictive models achieving average coefficient of determination (r(2)) of 0.62 and 0.68, respectively. The developed FS-QSAR method is proved to give more accurate predictions than the traditional and one-nearest-neighbour QSAR methods and can be a useful tool in the fragment-based drug discovery for ligand activity prediction.
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Affiliation(s)
- K Z Myint
- Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, USA
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4-aminoquinolines active against chloroquine-resistant Plasmodium falciparum: basis of antiparasite activity and quantitative structure-activity relationship analyses. Antimicrob Agents Chemother 2011; 55:2233-44. [PMID: 21383099 DOI: 10.1128/aac.00675-10] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Chloroquine (CQ) is a safe and economical 4-aminoquinoline (AQ) antimalarial. However, its value has been severely compromised by the increasing prevalence of CQ resistance. This study examined 108 AQs, including 68 newly synthesized compounds. Of these 108 AQs, 32 (30%) were active only against CQ-susceptible Plasmodium falciparum strains and 59 (55%) were active against both CQ-susceptible and CQ-resistant P. falciparum strains (50% inhibitory concentrations [IC50s], ≤25 nM). All AQs active against both CQ-susceptible and CQ-resistant P. falciparum strains shared four structural features: (i) an AQ ring without alkyl substitution, (ii) a halogen at position 7 (Cl, Br, or I but not F), (iii) a protonatable nitrogen at position 1, and (iv) a second protonatable nitrogen at the end of the side chain distal from the point of attachment to the AQ ring via the nitrogen at position 4. For activity against CQ-resistant parasites, side chain lengths of ≤3 or ≥10 carbons were necessary but not sufficient; they were identified as essential factors by visual comparison of 2-dimensional (2-D) structures in relation to the antiparasite activities of the AQs and were confirmed by computer-based 3-D comparisons and differential contour plots of activity against P. falciparum. The advantage of the method reported here (refinement of quantitative structure-activity relationship [QSAR] descriptors by random assignment of compounds to multiple training and test sets) is that it retains QSAR descriptors according to their abilities to predict the activities of unknown test compounds rather than according to how well they fit the activities of the compounds in the training sets.
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43
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Computational medicinal chemistry in fragment-based drug discovery: what, how and when. Future Med Chem 2011; 3:95-134. [DOI: 10.4155/fmc.10.277] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
The use of fragment-based drug discovery (FBDD) has increased in the last decade due to the encouraging results obtained to date. In this scenario, computational approaches, together with experimental information, play an important role to guide and speed up the process. By default, FBDD is generally considered as a constructive approach. However, such additive behavior is not always present, therefore, simple fragment maturation will not always deliver the expected results. In this review, computational approaches utilized in FBDD are reported together with real case studies, where applicability domains are exemplified, in order to analyze them, and then, maximize their performance and reliability. Thus, a proper use of these computational tools can minimize misleading conclusions, keeping the credit on FBDD strategy, as well as achieve higher impact in the drug-discovery process. FBDD goes one step beyond a simple constructive approach. A broad set of computational tools: docking, R group quantitative structure–activity relationship, fragmentation tools, fragments management tools, patents analysis and fragment-hopping, for example, can be utilized in FBDD, providing a clear positive impact if they are utilized in the proper scenario – what, how and when. An initial assessment of additive/non-additive behavior is a critical point to define the most convenient approach for fragments elaboration.
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Afantitis A, Melagraki G, Koutentis PA, Sarimveis H, Kollias G. Ligand-based virtual screening procedure for the prediction and the identification of novel β-amyloid aggregation inhibitors using Kohonen maps and Counterpropagation Artificial Neural Networks. Eur J Med Chem 2010; 46:497-508. [PMID: 21167625 DOI: 10.1016/j.ejmech.2010.11.029] [Citation(s) in RCA: 78] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2010] [Revised: 11/15/2010] [Accepted: 11/17/2010] [Indexed: 12/15/2022]
Abstract
In this work we have developed an in silico model to predict the inhibition of β-amyloid aggregation by small organic molecules. In particular we have explored the inhibitory activity of a series of 62 N-phenylanthranilic acids using Kohonen maps and Counterpropagation Artificial Neural Networks. The effects of various structural modifications on biological activity are investigated and novel structures are designed using the developed in silico model. More specifically a search for optimized pharmacophore patterns by insertions, substitutions, and ring fusions of pharmacophoric substituents of the main building block scaffolds is described. The detection of the domain of applicability defines compounds whose estimations can be accepted with confidence.
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Affiliation(s)
- Antreas Afantitis
- Department of ChemoInformatics, NovaMechanics Ltd, John Kennedy Ave 62-64, Nicosia 1046, Cyprus.
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45
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Myint KZ, Xie XQ. Recent advances in fragment-based QSAR and multi-dimensional QSAR methods. Int J Mol Sci 2010; 11:3846-66. [PMID: 21152304 PMCID: PMC2996787 DOI: 10.3390/ijms11103846] [Citation(s) in RCA: 76] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2010] [Revised: 09/17/2010] [Accepted: 09/23/2010] [Indexed: 12/13/2022] Open
Abstract
This paper provides an overview of recently developed two dimensional (2D) fragment-based QSAR methods as well as other multi-dimensional approaches. In particular, we present recent fragment-based QSAR methods such as fragment-similarity-based QSAR (FS-QSAR), fragment-based QSAR (FB-QSAR), Hologram QSAR (HQSAR), and top priority fragment QSAR in addition to 3D- and nD-QSAR methods such as comparative molecular field analysis (CoMFA), comparative molecular similarity analysis (CoMSIA), Topomer CoMFA, self-organizing molecular field analysis (SOMFA), comparative molecular moment analysis (COMMA), autocorrelation of molecular surfaces properties (AMSP), weighted holistic invariant molecular (WHIM) descriptor-based QSAR (WHIM), grid-independent descriptors (GRIND)-based QSAR, 4D-QSAR, 5D-QSAR and 6D-QSAR methods.
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Affiliation(s)
- Kyaw Zeyar Myint
- Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; E-Mail:
| | - Xiang-Qun Xie
- Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; E-Mail:
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Pittsburgh Chemical Methodologies & Library Development (PCMLD) and Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
- * Author to whom correspondence should be addressed; E-Mail: ; Tel.: +1-412-383-5276; Fax: +1-412-383-7436
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46
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Andrade CH, Pasqualoto KFM, Ferreira EI, Hopfinger AJ. 4D-QSAR: perspectives in drug design. Molecules 2010; 15:3281-94. [PMID: 20657478 PMCID: PMC6263259 DOI: 10.3390/molecules15053281] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2010] [Revised: 03/30/2010] [Accepted: 04/06/2010] [Indexed: 12/05/2022] Open
Abstract
Drug design is a process driven by innovation and technological breakthroughs involving a combination of advanced experimental and computational methods. A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of leads, as well as to accelerate the optimization of leads into drug candidates. The quantitative structure–activity relationship (QSAR) formalisms are among the most important strategies that can be applied for the successful design new molecules. This review provides a comprehensive review on the evolution and current status of 4D-QSAR, highlighting present challenges and new opportunities in drug design.
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Affiliation(s)
- Carolina H. Andrade
- Laboratory of Molecular Modeling, Faculty of Pharmacy, Federal University of Goiás, 1ª Av. c/ Praça Universitária, S/N., Goiânia, Goiás, 74605-220, Brazil
- College of Pharmacy, MSC09 5360, 1 University of New Mexico, Albuquerque, New Mexico 87131-0001, USA; E-Mail: (A.J.H.)
- Author to whom correspondence should be addressed; E-Mail:
| | - Kerly F. M. Pasqualoto
- Faculty of Pharmaceutical Sciences, Av. Prof. Lineu Prestes, 580, University of Sao Paulo, Sao Paulo, 05508-900, Brazil; E-Mails: (K.F.M.P.); (E.I.F.)
| | - Elizabeth I. Ferreira
- Faculty of Pharmaceutical Sciences, Av. Prof. Lineu Prestes, 580, University of Sao Paulo, Sao Paulo, 05508-900, Brazil; E-Mails: (K.F.M.P.); (E.I.F.)
| | - Anton J. Hopfinger
- College of Pharmacy, MSC09 5360, 1 University of New Mexico, Albuquerque, New Mexico 87131-0001, USA; E-Mail: (A.J.H.)
- The Chem21 Group, Inc., 17870 Wilson Drive. Lake Forest, IL 60045, USA
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Mueller R, Rodriguez AL, Dawson ES, Butkiewicz M, Nguyen TT, Oleszkiewicz S, Bleckmann A, Weaver CD, Lindsley CW, Conn PJ, Meiler J. Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening. ACS Chem Neurosci 2010; 1:288-305. [PMID: 20414370 PMCID: PMC2857954 DOI: 10.1021/cn9000389] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2009] [Accepted: 01/04/2010] [Indexed: 11/30/2022] Open
Abstract
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Selective potentiators of glutamate response at metabotropic glutamate receptor subtype 5 (mGluR5) have exciting potential for the development of novel treatment strategies for schizophrenia. A total of 1,382 compounds with positive allosteric modulation (PAM) of the mGluR5 glutamate response were identified through high-throughput screening (HTS) of a diverse library of 144,475 substances utilizing a functional assay measuring receptor-induced intracellular release of calcium. Primary hits were tested for concentration-dependent activity, and potency data (EC50 values) were used for training artificial neural network (ANN) quantitative structure−activity relationship (QSAR) models that predict biological potency from the chemical structure. While all models were trained to predict EC50, the quality of the models was assessed by using both continuous measures and binary classification. Numerical descriptors of chemical structure were used as input for the machine learning procedure and optimized in an iterative protocol. The ANN models achieved theoretical enrichment ratios of up to 38 for an independent data set not used in training the model. A database of ∼450,000 commercially available drug-like compounds was targeted in a virtual screen. A set of 824 compounds was obtained for testing based on the highest predicted potency values. Biological testing found 28.2% (232/824) of these compounds with various activities at mGluR5 including 177 pure potentiators and 55 partial agonists. These results represent an enrichment factor of 23 for pure potentiation of the mGluR5 glutamate response and 30 for overall mGluR5 modulation activity when compared with those of the original mGluR5 experimental screening data (0.94% hit rate). The active compounds identified contained 72% close derivatives of previously identified PAMs as well as 28% nontrivial derivatives of known active compounds.
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Affiliation(s)
| | | | - Eric S. Dawson
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37232-6600
| | | | | | | | | | | | - Craig W. Lindsley
- Department of Chemistry
- Department of Pharmacology
- Institute for Chemical Biology
| | | | - Jens Meiler
- Department of Chemistry
- Department of Pharmacology
- Institute for Chemical Biology
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37232-6600
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48
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Salum LB, Andricopulo AD. Fragment-based QSAR strategies in drug design. Expert Opin Drug Discov 2010; 5:405-12. [DOI: 10.1517/17460441003782277] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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49
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Alonso M, Chicharro R, Miranda C, Arán VJ, Maestro MA, Herradón B. X-ray Diffraction, Solution Structure, and Computational Studies on Derivatives of (3-sec-Butyl-2,3-dihydro-1H-isoquinolin-4-ylidene)acetic Acid: Compounds with Activity as Calpain Inhibitors. J Org Chem 2009; 75:342-52. [DOI: 10.1021/jo902091u] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Mercedes Alonso
- Instituto de Química Orgánica General, CSIC, Juan de la Cierva 3, 28006 Madrid, Spain
| | - Roberto Chicharro
- Instituto de Química Orgánica General, CSIC, Juan de la Cierva 3, 28006 Madrid, Spain
| | - Carlos Miranda
- Instituto de Química Orgánica General, CSIC, Juan de la Cierva 3, 28006 Madrid, Spain
| | - Vicente J. Arán
- Instituto de Química Médica, CSIC, Juan de la Cierva 3, 28006 Madrid, Spain
| | - Miguel A. Maestro
- Departamento de Quıímica Fundamental, Facultad de Ciencias, Universidade da Coruña, Campus da Zapateira, 15071 A Coruña, Spain
| | - Bernardo Herradón
- Instituto de Química Orgánica General, CSIC, Juan de la Cierva 3, 28006 Madrid, Spain
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