Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening
| Autor: | Luciane B. Silva, André L S Ferreira, Carlos Henrique Tomich de Paula da Silva, Mayara Amoras Teles Fujishima, Glauber V da Costa, Leonardo B Federico, Cleydson B. R. Santos, Williams Jorge da Cruz Macêdo, Elenilze F B Ferreira, Joaquín María Campos Rosa, Rozires P Leão, Josivan da Silva Costa |
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| Rok vydání: | 2019 |
| Předmět: |
Models
Molecular In silico Molecular Conformation Pharmaceutical Science Antineoplastic Agents Computational biology Biology 01 natural sciences Article Analytical Chemistry lcsh:QD241-441 Structure-Activity Relationship 03 medical and health sciences lcsh:Organic chemistry In vivo α4β1 receptor Drug Discovery Cluster Analysis Humans Computer Simulation HCA Physical and Theoretical Chemistry Receptor 030304 developmental biology PCA 0303 health sciences Virtual screening Leukemia Molecular Structure Pharmacophore pharmacophore INTEGRINAS 010405 organic chemistry Organic Chemistry leukemia Biological activity In vitro 0104 chemical sciences Hierarchical clustering Chemistry (miscellaneous) Molecular Medicine Drug Screening Assays Antitumor Peptides |
| Zdroj: | Molecules Volume 24 Issue 16 Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP Digibug. Repositorio Institucional de la Universidad de Granada instname Molecules, Vol 24, Iss 16, p 2943 (2019) |
| ISSN: | 1420-3049 |
| DOI: | 10.3390/molecules24162943 |
| Popis: | 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 &alpha 4&beta 1 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 &alpha 1 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. |
| Databáze: | OpenAIRE |
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