Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening
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...
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MDPI AG
2019-08-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/24/16/2943 |
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| author | Elenilze F. B. Ferreira Luciane B. Silva Glauber V. Costa Josivan S. Costa Mayara A. T. Fujishima Rozires P. Leão André L. S. Ferreira Leonardo B. Federico Carlos H. T. P. Silva Joaquín M. C. Rosa Williams J. C. Macêdo Cleydson B. R. Santos |
| author_facet | Elenilze F. B. Ferreira Luciane B. Silva Glauber V. Costa Josivan S. Costa Mayara A. T. Fujishima Rozires P. Leão André L. S. Ferreira Leonardo B. Federico Carlos H. T. P. Silva Joaquín M. C. Rosa Williams J. C. Macêdo Cleydson B. R. Santos |
| author_sort | Elenilze F. B. Ferreira |
| collection | DOAJ |
| description | 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, IC<sub>50</sub>) 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. |
| first_indexed | 2024-12-19T16:34:13Z |
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| last_indexed | 2024-12-19T16:34:13Z |
| publishDate | 2019-08-01 |
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| series | Molecules |
| spelling | doaj.art-bcc61fa09add40c685cabc6606af5e322022-12-21T20:14:02ZengMDPI AGMolecules1420-30492019-08-012416294310.3390/molecules24162943molecules24162943Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual ScreeningElenilze F. B. Ferreira0Luciane B. Silva1Glauber V. Costa2Josivan S. Costa3Mayara A. T. Fujishima4Rozires P. Leão5André L. S. Ferreira6Leonardo B. Federico7Carlos H. T. P. Silva8Joaquín M. C. Rosa9Williams J. C. Macêdo10Cleydson B. R. Santos11Laboratory of Organic Chemistry and Biochemistry, University of the State of Amapá, Macapá 68900-070, AP, BrazilLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, BrazilLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, BrazilLaboratory of Organic Chemistry and Biochemistry, University of the State of Amapá, Macapá 68900-070, AP, BrazilLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, BrazilLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, BrazilLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, BrazilComputational Laboratory of Pharmaceutical Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, São Paulo 14040-903, BrazilComputational Laboratory of Pharmaceutical Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, São Paulo 14040-903, BrazilDepartment of Pharmaceutical and Organic Chemistry, Faculty of Pharmacy, Campus of Cartuja, University of Granada, 18071 Granada, SpainLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, BrazilLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, BrazilLeukemias 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, IC<sub>50</sub>) 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.https://www.mdpi.com/1420-3049/24/16/2943leukemiaα4β1 receptorpharmacophorePCAHCA |
| spellingShingle | Elenilze F. B. Ferreira Luciane B. Silva Glauber V. Costa Josivan S. Costa Mayara A. T. Fujishima Rozires P. Leão André L. S. Ferreira Leonardo B. Federico Carlos H. T. P. Silva Joaquín M. C. Rosa Williams J. C. Macêdo Cleydson B. R. Santos Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening Molecules leukemia α4β1 receptor pharmacophore PCA HCA |
| title | Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening |
| title_full | Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening |
| title_fullStr | Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening |
| title_full_unstemmed | Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening |
| title_short | Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening |
| title_sort | identification of new inhibitors with potential antitumor activity from polypeptide structures via hierarchical virtual screening |
| topic | leukemia α4β1 receptor pharmacophore PCA HCA |
| url | https://www.mdpi.com/1420-3049/24/16/2943 |
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