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Chu H, He QX, Wang J, Hu Y, Wang YQ, Lin ZH. In silico design novel dihydropyrimio[4, 5-d]pyrimidine derivatives as inhibitors for colony-stimulating factor-1 receptor based on 3D-QSAR, molecular docking and molecular dynamics simulation. J Mol Struct 2020. [DOI: 10.1016/j.molstruc.2020.128617] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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He Q, Han C, Li G, Guo H, Wang Y, Hu Y, Lin Z, Wang Y. In silico design novel (5-imidazol-2-yl-4-phenylpyrimidin-2-yl)[2-(2-pyridylamino)ethyl]amine derivatives as inhibitors for glycogen synthase kinase 3 based on 3D-QSAR, molecular docking and molecular dynamics simulation. Comput Biol Chem 2020; 88:107328. [PMID: 32688011 DOI: 10.1016/j.compbiolchem.2020.107328] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 06/29/2020] [Accepted: 06/30/2020] [Indexed: 12/27/2022]
Abstract
Glycogen Synthase Kinase 3 (GSK-3) is a member of cellular kinase with various functions, such as glucose regulation, cellular differentiation, neuronal function and cell apoptosis. It has been proved as an important therapeutic target in type 2 diabetes mellitus and Alzheimer's disease. To better understand their structure-activity relationships and mechanism of action, an integrated computational study, including three dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, and molecular dynamics (MD), was performed on 79 (5-Imidazol-2-yl-4-phenylpyrimidin-2-yl)[2-(2-pyridylamino)ethyl]amine GSK-3 inhibitors. In this paper, we constructed 3D-QSAR using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) method. The results showed that the CoMFA model (q2 = 0.743, r2 = 0.980) and the CoMSIA model (q2 = 0.813, r2 = 0.976) had stable and reliable predictive ability. The electrostatic and H-bond donor fields play important roles in the models. The contour maps of the model visually showed the relationship between the activity of compounds and their three-dimensional structure. Molecular docking was used to identify the key amino acid residues at the active site of GSK-3 and explore its binding mode with ligands. Based on 3D-QSAR models, contour maps and the binding feature between GSK-3 and inhibitor, we designed 10 novel compounds with good potential activity and ADME/T profile. Molecular dynamics simulation results validated that Ile62, Val70 and Lys85 located in the active site play a key role for GSK-3 complexed with inhibitors. These results might provide important information for designing GSK-3 inhibitors with high activity.
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Affiliation(s)
- Qingxiu He
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Chu Han
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Guangping Li
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Haiqiong Guo
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Yuxuan Wang
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Yong Hu
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Zhihua Lin
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China; Chongqing the Seventh People's Hospital, Chongqing, 400054, China.
| | - Yuanqiang Wang
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China; Chongqing the Seventh People's Hospital, Chongqing, 400054, China.
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Chu H, He QX, Wang J, Hu Y, Wang YQ, Lin ZH. In silico design of novel benzohydroxamate-based compounds as inhibitors of histone deacetylase 6 based on 3D-QSAR, molecular docking, and molecular dynamics simulations. NEW J CHEM 2020. [DOI: 10.1039/d0nj04704j] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
In silico design of benzohydroxamate-based selective HDAC6 inhibitors.
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Affiliation(s)
- Han Chu
- Department of Pharmacy and Bioengineering
- Chongqing University of Technology
- Chongqing
- P. R. China
- Key Laboratory of Screening and Activity Evaluation of Targeted Drugs
| | - Qing-xiu He
- Department of Pharmacy and Bioengineering
- Chongqing University of Technology
- Chongqing
- P. R. China
- Key Laboratory of Screening and Activity Evaluation of Targeted Drugs
| | - Juan Wang
- Department of Pharmacy and Bioengineering
- Chongqing University of Technology
- Chongqing
- P. R. China
- Key Laboratory of Screening and Activity Evaluation of Targeted Drugs
| | - Yong Hu
- Department of Pharmacy and Bioengineering
- Chongqing University of Technology
- Chongqing
- P. R. China
- Key Laboratory of Screening and Activity Evaluation of Targeted Drugs
| | - Yuan-qiang Wang
- Department of Pharmacy and Bioengineering
- Chongqing University of Technology
- Chongqing
- P. R. China
- Key Laboratory of Screening and Activity Evaluation of Targeted Drugs
| | - Zhi-hua Lin
- Department of Pharmacy and Bioengineering
- Chongqing University of Technology
- Chongqing
- P. R. China
- Key Laboratory of Screening and Activity Evaluation of Targeted Drugs
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Sosnowska A, Brzeski J, Skurski P, Puzyn T. The Acid Strength of the Lewis-Brønsted Superacids - A QSPR Study. Mol Inform 2019; 38:e1800113. [PMID: 30747480 DOI: 10.1002/minf.201800113] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 01/14/2019] [Indexed: 11/12/2022]
Abstract
The acidity of Lewis-Brønsted superacids can be derived from the theoretical calculations as the Gibbs free energy of the deprotonation reaction (ΔGacid ), which describes the tendency of a studied compound to donate a proton. This paper presents the first Quantitative Structure - Property Relationship (QSPR) model that correlates the ΔGacid of superacid (HF/MeX3 formula (X=F, Cl, Br)) with their structure. Developed model is well fitted, roubustness, has good predictive abilities, fulfills all OECD recommendation for good model. Obtained results provide the insight into the relation of structural features of superacids, which are responsible for their acid strength - the structures characterized by strong F-Me dative bond (with relatively large vibrational frequency), small positive partial atomic charge on Me central atom, possibly large polarity exhibit large acid strength. Such assumption can be used in the future as valuable information in the process of the designing new, stronger, more effective superacids.
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Affiliation(s)
- Anita Sosnowska
- Laboratory of Environmental Chemometrics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308, Gdansk, Poland
| | - Jakub Brzeski
- Laboratory of Quantum Chemistry, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308, Gdansk, Poland
| | - Piotr Skurski
- Laboratory of Quantum Chemistry, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308, Gdansk, Poland
| | - Tomasz Puzyn
- Laboratory of Environmental Chemometrics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308, Gdansk, Poland
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Sharma M, Jha P, Verma P, Chopra M. Combined comparative molecular field analysis, comparative molecular similarity indices analysis, molecular docking and molecular dynamics studies of histone deacetylase 6 inhibitors. Chem Biol Drug Des 2019; 93:910-925. [PMID: 30667160 DOI: 10.1111/cbdd.13488] [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: 09/20/2018] [Revised: 01/09/2019] [Accepted: 01/12/2019] [Indexed: 01/04/2023]
Abstract
Human histone deacetylase isoform 6 (HDAC6) has been shown to have an immense role in cell motility and aggresome formation and is being an attractive selective target for the treatment of multiple tumour types and neurodegenerative conditions. The discovery of selective HDAC6 inhibitors with new chemical functionalities is therefore of utmost interest to researchers. In order to examine the structural requirements for HDAC6-specific inhibitors and to derive predictive model which can be used for designing new selective HDAC6 inhibitors, a three-dimensional quantitative structure-activity relationship study was carried out on a diverse set of ligands using common feature-based pharmacophore alignment followed by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The models displayed high correlation of 0.978 and 0.991 for best CoMFA and CoMSIA models, respectively, and a good statistical significance. The model could be used for predicting activities of the test set compounds as well as for deriving useful information regarding steric, electrostatic, hydrophobic properties of the molecules used in this study. Further, the training and test set molecules were docked into the HDAC6 binding site and molecular dynamics was carried out to suggest structural requirements for design of new inhibitors.
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Affiliation(s)
- Monika Sharma
- Laboratory of Molecular Modeling and Anticancer Drug Development, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Prakash Jha
- Laboratory of Molecular Modeling and Anticancer Drug Development, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Priyanka Verma
- Laboratory of Molecular Modeling and Anticancer Drug Development, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Madhu Chopra
- Laboratory of Molecular Modeling and Anticancer Drug Development, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
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Afantitis A, Melagraki G, Tsoumanis A, Valsami-Jones E, Lynch I. A nanoinformatics decision support tool for the virtual screening of gold nanoparticle cellular association using protein corona fingerprints. Nanotoxicology 2018; 12:1148-1165. [PMID: 30182778 DOI: 10.1080/17435390.2018.1504998] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The increasing use of nanoparticles (NPs) in a wide range of consumer and industrial applications has necessitated significant effort to address the challenge of characterizing and quantifying the underlying nanostructure - biological response relationships to ensure that these novel materials can be exploited responsibly and safely. Such efforts demand reliable experimental data not only in terms of the biological dose-response, but also regarding the physicochemical properties of the NPs and their interaction with the biological environment. The latter has not been extensively studied, as a large surface to bind biological macromolecules is a unique feature of NPs that is not relevant for chemicals or pharmaceuticals, and thus only limited data have been reported in the literature quantifying the protein corona formed when NPs interact with a biological medium and linking this with NP cellular association/uptake. In this work we report the development of a predictive model for the assessment of the biological response (cellular association, which can include both internalized NPs and those attached to the cell surface) of surface-modified gold NPs, based on their physicochemical properties and protein corona fingerprints, utilizing a dataset of 105 unique NPs. Cellular association was chosen as the end-point for the original experimental study due to its relevance to inflammatory responses, biodistribution, and toxicity in vivo. The validated predictive model is freely available online through the Enalos Cloud Platform ( http://enalos.insilicotox.com/NanoProteinCorona/ ) to be used as part of a regulatory or NP safe-by-design decision support system. This online tool will allow the virtual screening of NPs, based on a list of the significant NP descriptors, identifying those NPs that would warrant further toxicity testing on the basis of predicted NP cellular association.
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Affiliation(s)
| | | | | | - Eugenia Valsami-Jones
- b School of Geography Earth and Environmental Sciences , University of Birmingham , Birmingham , United Kingdom
| | - Iseult Lynch
- b School of Geography Earth and Environmental Sciences , University of Birmingham , Birmingham , United Kingdom
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Abstract
A number of anti-retroviral drugs are being used for treating Human Immunodeficiency Virus (HIV) infection. Due to emergence of drug resistant strains, there is a constant quest to discover more effective anti-HIV compounds. In this endeavor, computational tools have proven useful in accelerating drug discovery. Although methods were published to design a class of compounds against a specific HIV protein, but an integrated web server for the same is lacking. Therefore, we have developed support vector machine based regression models using experimentally validated data from ChEMBL repository. Quantitative structure activity relationship based features were selected for predicting inhibition activity of a compound against HIV proteins namely protease (PR), reverse transcriptase (RT) and integrase (IN). The models presented a maximum Pearson correlation coefficient of 0.78, 0.76, 0.74 and 0.76, 0.68, 0.72 during tenfold cross-validation on IC50 and percent inhibition datasets of PR, RT, IN respectively.
These models performed equally well on the independent datasets. Chemical space mapping, applicability domain analyses and other statistical tests further support robustness of the predictive models. Currently, we have identified a number of chemical descriptors that are imperative in predicting the compound inhibition potential. HIVprotI platform (http://bioinfo.imtech.res.in/manojk/hivproti) would be useful in virtual screening of inhibitors as well as designing of new molecules against the important HIV proteins for therapeutics development.![]()
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Balasubramanian K, Patil VM. Quantum molecular modeling of hepatitis C virus inhibition through non-structural protein 5B polymerase receptor binding of C 5-arylidene rhodanines. Comput Biol Chem 2018; 73:147-158. [PMID: 29486389 DOI: 10.1016/j.compbiolchem.2018.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 01/09/2018] [Accepted: 01/23/2018] [Indexed: 11/25/2022]
Abstract
We have carried out high-level quantum chemical computations followed by molecular docking studies on a set of 17C5-arylidene rhodanine isomers to provide insights into the binding modes with different reported binding pockets of the nonstructural protein 5B (NS5B) polymerase that contribute to the hepatitis C virus (HCV) inhibition. We optimized the multi-target profile of the selected rhodanine analogs to investigate potential non-nucleotide inhibitors (NNIs) by quantum chemical optimization of the 18 isomers followed by docking with quantum chemically optimized structures of each isomer with NS5B polymerase at multiple binding pockets. The binding affinities of the PP-I, PP-II and TP-II pockets of NS5B polymerase were analyzed for all the 17 isomers of 2-[(5Z)-5-(2,4-dichlorobenzylidene)-4-oxo-2-thioxo-1,3-thiazolidin-3-yl]-3-phenylpropanoic acid. On the basis of binding propensity at the different pockets and inhibitor constants, we ranked these isomers as potential candidates for the HCV inhibition. We have identified four isomers as promising NNIs of NS5B polymerase with comparable binding and inhibition to the standard (1,3) dichloro substituted isomer that exhibits in vitro activity and several other isomers as candidates in a "multi-targeted drug" approach.
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Affiliation(s)
| | - Vaishali M Patil
- Department of Pharmaceutical Chemistry, KIET School of Pharmacy, KIET Group of Institutions, Ghaziabad, Uttar Pradesh, India.
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Dong H, Liu J, Liu X, Yu Y, Cao S. Combining molecular docking and QSAR studies for modeling the anti-tyrosinase activity of aromatic heterocycle thiosemicarbazone analogues. J Mol Struct 2018. [DOI: 10.1016/j.molstruc.2017.08.034] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Varsou DD, Nikolakopoulos S, Tsoumanis A, Melagraki G, Afantitis A. Enalos Suite: New Cheminformatics Platform for Drug Discovery and Computational Toxicology. Methods Mol Biol 2018; 1800:287-311. [PMID: 29934899 DOI: 10.1007/978-1-4939-7899-1_14] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
In this chapter we present and discuss, with the aid of several representative case studies from drug discovery and computational toxicology, a new cheminformatics platform, Enalos Suite, that was developed with open source and freely available software. Enalos Suite ( http://enalossuite.novamechanics.com/ ) was designed and developed as a useful tool to address a variety of cheminformatics problems, given that it expedites tasks performed in predictive modeling and allows access, data mining and manipulation for multiple chemical databases (PubChem, UniChem, etc.). Enalos Suite was carefully designed to permit its extension and adjustment to the special field of interest of each user, including, for instance, nanoinformatics, biomedical, and other applications. To demonstrate the functionalities of Enalos Suite that are useful in different cheminformatics applications, we present indicative case studies that include the exploitation of chemical databases within a drug discovery project, the calculation of molecular descriptors, and finally the development of a predictive QSAR model validated according to OECD principles. We aspire that at the end of this chapter, the reader will capture the effectiveness of different functionalities included in the Enalos Suite that could be of significant value in a multitude of cheminformatics applications.
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Hu CQ, Li K, Yao TT, Hu YZ, Ying HZ, Dong XW. Integrating docking scores and key interaction profiles to improve the accuracy of molecular docking: towards novel B-Raf V600E inhibitors. MEDCHEMCOMM 2017; 8:1835-1844. [PMID: 30108894 PMCID: PMC6084233 DOI: 10.1039/c7md00229g] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Accepted: 07/14/2017] [Indexed: 12/12/2022]
Abstract
A set of ninety-eight B-RafV600E inhibitors was used for the development of a molecular docking based QSAR model using linear and non-linear regression models. The integration of docking scores and key interaction profiles significantly improved the accuracy of the QSAR models, providing reasonable statistical parameters (Rtrain2 = 0.935, Rtest2 = 0.728 and QCV2 = 0.905). The established MD-SVR (molecular docking based SMV regression) model as well as model screening of a natural product database was carried out and two natural products (quercetin and myricetin) with good prediction activities were biologically evaluated. Both compounds exhibited promising B-RafV600E inhibitory activities (ICQuercetin50 = 7.59 μM and ICMyricetin50 = 1.56 μM), suggesting a high reliability and good applicability of the established MD-SVR model in the future development of B-RafV600E inhibitors with high efficacy.
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Affiliation(s)
- Chun-Qi Hu
- Zhejiang Province Key Laboratory of Anti-Cancer Drug Research , College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , P.R. China . ; ; ; Tel: +86 571 88981051
- College of Chemistry & Chemical Engineering , Shaoxing University , Shaoxing , P.R. China
- Yongning Pharma , Taizhou , P.R. China
| | - Kang Li
- Zhejiang Province Key Laboratory of Anti-Cancer Drug Research , College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , P.R. China . ; ; ; Tel: +86 571 88981051
- Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals , Zhejiang University of Technology , Hangzhou , P.R. China
| | - Ting-Ting Yao
- Zhejiang Province Key Laboratory of Anti-Cancer Drug Research , College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , P.R. China . ; ; ; Tel: +86 571 88981051
| | - Yong-Zhou Hu
- Zhejiang Province Key Laboratory of Anti-Cancer Drug Research , College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , P.R. China . ; ; ; Tel: +86 571 88981051
| | - Hua-Zhou Ying
- Zhejiang Province Key Laboratory of Anti-Cancer Drug Research , College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , P.R. China . ; ; ; Tel: +86 571 88981051
| | - Xiao-Wu Dong
- Zhejiang Province Key Laboratory of Anti-Cancer Drug Research , College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , P.R. China . ; ; ; Tel: +86 571 88981051
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Chen M, Yang F, Kang J, Yang X, Lai X, Gao Y. Multi-Layer Identification of Highly-Potent ABCA1 Up-Regulators Targeting LXRβ Using Multiple QSAR Modeling, Structural Similarity Analysis, and Molecular Docking. Molecules 2016; 21:molecules21121639. [PMID: 27916850 PMCID: PMC6273961 DOI: 10.3390/molecules21121639] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Revised: 11/21/2016] [Accepted: 11/26/2016] [Indexed: 12/19/2022] Open
Abstract
In this study, in silico approaches, including multiple QSAR modeling, structural similarity analysis, and molecular docking, were applied to develop QSAR classification models as a fast screening tool for identifying highly-potent ABCA1 up-regulators targeting LXRβ based on a series of new flavonoids. Initially, four modeling approaches, including linear discriminant analysis, support vector machine, radial basis function neural network, and classification and regression trees, were applied to construct different QSAR classification models. The statistics results indicated that these four kinds of QSAR models were powerful tools for screening highly potent ABCA1 up-regulators. Then, a consensus QSAR model was developed by combining the predictions from these four models. To discover new ABCA1 up-regulators at maximum accuracy, the compounds in the ZINC database that fulfilled the requirement of structural similarity of 0.7 compared to known potent ABCA1 up-regulator were subjected to the consensus QSAR model, which led to the discovery of 50 compounds. Finally, they were docked into the LXRβ binding site to understand their role in up-regulating ABCA1 expression. The excellent binding modes and docking scores of 10 hit compounds suggested they were highly-potent ABCA1 up-regulators targeting LXRβ. Overall, this study provided an effective strategy to discover highly potent ABCA1 up-regulators.
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Affiliation(s)
- Meimei Chen
- College of Chemistry and Chemical Engineering, Fujian Normal University, Fuzhou 350007, Fujian, China.
- College of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, Fujian, China.
| | - Fafu Yang
- College of Chemistry and Chemical Engineering, Fujian Normal University, Fuzhou 350007, Fujian, China.
| | - Jie Kang
- College of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, Fujian, China.
| | - Xuemei Yang
- College of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, Fujian, China.
| | - Xinmei Lai
- College of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, Fujian, China.
| | - Yuxing Gao
- College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, Fujian, China.
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Li W, Si H, Li Y, Ge C, Song F, Ma X, Duan Y, Zhai H. 3D-QSAR and molecular docking studies on designing inhibitors of the hepatitis C virus NS5B polymerase. J Mol Struct 2016. [DOI: 10.1016/j.molstruc.2016.03.073] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches. Int J Mol Sci 2016; 17:536. [PMID: 27070594 PMCID: PMC4848992 DOI: 10.3390/ijms17040536] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2016] [Revised: 03/29/2016] [Accepted: 04/05/2016] [Indexed: 12/19/2022] Open
Abstract
In this paper, a three level in silico approach was applied to investigate some important structural and physicochemical aspects of a series of anthranilic acid derivatives (AAD) newly identified as potent partial farnesoid X receptor (FXR) agonists. Initially, both two and three-dimensional quantitative structure activity relationship (2D- and 3D-QSAR) studies were performed based on such AAD by a stepwise technology combined with multiple linear regression and comparative molecular field analysis. The obtained 2D-QSAR model gave a high predictive ability (R²(train) = 0.935, R²(test) = 0.902, Q²(LOO) = 0.899). It also uncovered that number of rotatable single bonds (b_rotN), relative negative partial charges (RPC(-)), oprea's lead-like (opr_leadlike), subdivided van der Waal's surface area (SlogP_VSA2) and accessible surface area (ASA) were important features in defining activity. Additionally, the derived3D-QSAR model presented a higher predictive ability (R²(train) = 0.944, R²(test) = 0.892, Q²(LOO) = 0.802). Meanwhile, the derived contour maps from the 3D-QSAR model revealed the significant structural features (steric and electronic effects) required for improving FXR agonist activity. Finally, nine newly designed AAD with higher predicted EC50 values than the known template compound were docked into the FXR active site. The excellent molecular binding patterns of these molecules also suggested that they can be robust and potent partial FXR agonists in agreement with the QSAR results. Overall, these derived models may help to identify and design novel AAD with better FXR agonist activity.
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Ma S, Zhou S, Lin W, Zhang R, Wu W, Zheng K. Study of novel pyrazolo[3,4-d]pyrimidine derivatives as selective TgCDPK1 inhibitors: molecular docking, structure-based 3D-QSAR and molecular dynamics simulation. RSC Adv 2016. [DOI: 10.1039/c6ra20277b] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
We explored the structural features that have an impact on TgCDPK1 activity and TgCDPK1/Src selectivity by multi-computational methods with different statistical models.
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Affiliation(s)
- Shaojie Ma
- Department of Physical Chemistry
- College of Pharmacy
- Guangdong Pharmaceutical University
- Guangzhou 510006
- PR China
| | - Shengfu Zhou
- Department of Physical Chemistry
- College of Pharmacy
- Guangdong Pharmaceutical University
- Guangzhou 510006
- PR China
| | - Weicong Lin
- Department of Physical Chemistry
- College of Pharmacy
- Guangdong Pharmaceutical University
- Guangzhou 510006
- PR China
| | - Rong Zhang
- Department of Physical Chemistry
- College of Pharmacy
- Guangdong Pharmaceutical University
- Guangzhou 510006
- PR China
| | - Wenjuan Wu
- Department of Physical Chemistry
- College of Pharmacy
- Guangdong Pharmaceutical University
- Guangzhou 510006
- PR China
| | - Kangcheng Zheng
- School of Chemistry and Chemical Engineering
- Sun Yat-Sen University
- Guangzhou 510275
- PR China
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Narayana Moorthy NSH, Poongavanam V. The KNIME based classification models for yellow fever virus inhibition. RSC Adv 2015. [DOI: 10.1039/c4ra15317k] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The Naïve Bayes method as implemented in KNIME platform for classification of YFV inhibition. The best classification model is able to correctly discriminate >90% of inhibitors and non-inhibitors.
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Melagraki G, Afantitis A. Enalos InSilicoNano platform: an online decision support tool for the design and virtual screening of nanoparticles. RSC Adv 2014. [DOI: 10.1039/c4ra07756c] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
A QNAR model, available online through Enalos InSilicoNano platform, has been developed and validated for the risk assessment of nanoparticles (NPs).
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