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Cancer Res ; 53(4): 766-71, 1993 Feb 15.
Article in English | MEDLINE | ID: mdl-8428356

ABSTRACT

Computer assisted quantitative structure-activity studies using comparative molecular field analysis (CoMFA) were performed on a series of alkylamides that induce cell differentiation. The series included alkylformamides, alkylacetamides, alkylureas, and substituted hexyl analogues of acetamide. The biological activity studied for correlation with structure was the ability of each compound to induce differentiation of the human promyelocytic leukemia cell line, HL-60, to granulocyte-like cells. In the CoMFA study, both steric and electrostatic fields were used along with molecular weight to determine a correlation between biological activity of the compounds and their structural features. The CoMFA results indicated a linear structure-activity correlation with a high predictive value. There was almost an even contribution towards activity from steric interactions, electrostatic potential, and molecular weight. These findings confirm a previous report by Langdon and Hickman (S. P. Langdon and J. A. Hickman, Cancer Res., 47: 140-144, 1987) that the ability to induce cell differentiation is highly dependent on molecular weight. Additionally, CoMFA contour maps provided information about regions of the molecule that are favorable to increased steric bulk and electrostatic charge. CoMFA was used to predict the activities of six hexamethylene acetamide analogues: ethyl 6-acetamidohexanoate; 6-acetamidohexanol; 1,5-bis(acetamido)hexane; 6-acetamidohexanonitrile; 6-acetamidohexanoic acid; and caprolactam. Although the model incorrectly predicted high activity for 6-acetamidohexanoic acid, the predicted activities for the remaining compounds were 0.3 to 1.5 times that of the corresponding experimental activities, which is comparable to the results obtained from other published CoMFA studies.


Subject(s)
Cell Differentiation/drug effects , Leukemia, Promyelocytic, Acute/pathology , Oligopeptides/pharmacology , Computer Graphics , Humans , Least-Squares Analysis , Oligopeptides/chemistry , Structure-Activity Relationship , Tumor Cells, Cultured
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