Skip to content
2000
Volume 23, Issue 19
  • ISSN: 1871-5206
  • E-ISSN: 1875-5992

Abstract

Background: The new tetrandrine derivative is an anti-human liver cancer cell inhibitor which can be used to design and develop anti-human-liver-cancer drugs.Objective: A quantitative structure-activity relationship (QSAR) model was established to predict the physical properties of new tetrandrine derivatives using their chemical structures.Methods: The best descriptors were selected through CODESSA software to build a multiple linear regression model. Then, gene expression programming (GEP) was used to establish a nonlinear quantitative QSAR model with descriptors to predict the activity of a series of novel tetrandrine chemotherapy drugs. The best active compound 31 was subjected to molecular docking experiments through SYBYL software with a small fragment of the protein receptor (PDB ID:2J6M).Results: Four descriptors were selected to build a multiple linear regression model with correlation coefficients R2, R2CV and S2 with the values of 0.8352, 0.7806 and 0.0119, respectively. The training and test sets with a correlation coefficient of 0.85 and 0.83 were obtained via an automatic problem-solving program (APS) using the four selected operators as parameters, with a mean error of 1.49 and 1.08. Compound 31 had a good docking ability with an overall score of 5.8892, a collision rate of -2.8004 and an extreme value of 0.9836.Conclusion: The computer-constructed drug molecular model reveals the factors affecting the activity of human hepatocellular carcinoma cells, which provides directions and guidance for the development of highly effective anti-humanhepatocellular- carcinoma drugs in the future.

Loading

Article metrics loading...

/content/journals/acamc/10.2174/1871520623666230831103936
2023-11-01
2025-03-15
Loading full text...

Full text loading...

/content/journals/acamc/10.2174/1871520623666230831103936
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test