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Open AccessArticle

Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening

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Laboratory of Organic Chemistry and Biochemistry, University of the State of Amapá, Macapá 68900-070, AP, Brazil
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Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, Brazil
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Graduate Program of Pharmaceutical Innovation, Federal University of Amapá, Macapá 68902-280, AP, Brazil
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Laboratory of Mathematic Modeling, Federal Institute of Education, Science and Technology of Amapá, Macapá 68909-398, AP, Brazil
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Computational Laboratory of Pharmaceutical Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, São Paulo 14040-903, Brazil
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Department of Pharmaceutical and Organic Chemistry, Faculty of Pharmacy, Campus of Cartuja, University of Granada, 18071 Granada, Spain
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Biosanitary Institute of Granada (ibs.GRANADA), University of Granada, 18071 Granada, Spain
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Laboratory of Molecular Modeling and Simulation System, Federal Rural University of Amazônia, Rua João Pessoa, 121, Capanema 68700-030, PA, Brazil
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Author to whom correspondence should be addressed.
Academic Editor: Julio Caballero
Molecules 2019, 24(16), 2943; https://doi.org/10.3390/molecules24162943
Received: 3 July 2019 / Revised: 8 August 2019 / Accepted: 10 August 2019 / Published: 14 August 2019
(This article belongs to the Special Issue Computational Methods for Drug Discovery and Design)
Leukemias are neoplasms that affect hematopoietic cells, which are developed by genetic alterations (mutations) that lead to the loss of proliferation control mechanisms (maturation and/or cell death). The α4β1 integrin receptor is a therapeutic target for inflammation, autoimmune diseases and lymphoid tumors. This study was carried out to search through the antagonists-based virtual screening for α4β1 receptor. Initially, seventeen (17) structures were selected (based on the inhibitory activity values, IC50) and the structure with the best value was chosen as the pivot. The pharmacophoric pattern was determined from the online PharmaGist server and resulted in a model of score value equal to 97.940 with 15 pharmacophoric characteristics that were statistically evaluated via Pearson correlations, principal component analysis (PCA) and hierarchical clustering analysis (HCA). A refined model generated four pharmacophoric hypotheses totaling 1.478 structures set of Zinc_database. After, the pharmacokinetic, toxicological and biological activity predictions were realized comparing with pivot structure that resulted in five (ZINC72088291, ZINC68842860, ZINC14365931, ZINC09588345 and ZINC91247798) structures with optimal in silico predictions. Therefore, future studies are needed to confirm antitumor potential activity of molecules selected this work with in vitro and in vivo assays. View Full-Text
Keywords: leukemia; α4β1 receptor; pharmacophore; PCA; HCA leukemia; α4β1 receptor; pharmacophore; PCA; HCA
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Ferreira, E.F.B.; Silva, L.B.; Costa, G.V.; Costa, J.S.; Fujishima, M.A.T.; Leão, R.P.; Ferreira, A.L.S.; Federico, L.B.; Silva, C.H.T.P.; Rosa, J.M.C.; Macêdo, W.J.C.; Santos, C.B.R. Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening. Molecules 2019, 24, 2943.

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