Publication: Quantitative structure-activity relationship study of betulinic acid derivatives against HIV using SMILES-based descriptors
Submitted Date
Received Date
Accepted Date
Issued Date
2018-01-01
Copyright Date
Announcement No.
Application No.
Patent No.
Valid Date
Resource Type
Edition
Resource Version
Language
File Type
No. of Pages/File Size
ISBN
ISSN
18756697
15734099
15734099
eISSN
Scopus ID
WOS ID
Pubmed ID
arXiv ID
Call No.
Other identifier(s)
2-s2.0-85049036371
Journal Title
Volume
Issue
item.page.oaire.edition
Start Page
End Page
Access Rights
Access Status
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Physical Location
Bibliographic Citation
Current Computer-Aided Drug Design. Vol.14, No.2 (2018), 152-159
Citation
Apilak Worachartcheewan, Alla P. Toropova, Andrey A. Toropov, Suphakit Siriwong, Jatupat Prapojanasomboon, Virapong Prachayasittikul, Chanin Nantasenamat (2018). Quantitative structure-activity relationship study of betulinic acid derivatives against HIV using SMILES-based descriptors. Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/45289.
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Quantitative structure-activity relationship study of betulinic acid derivatives against HIV using SMILES-based descriptors
Alternative Title(s)
Author's Affiliation
Author's E-mail
Editor(s)
Editor's Affiliation
Corresponding Author(s)
Creator(s)
Compiler
Advisor(s)
Illustrator(s)
Applicant(s)
Inventor(s)
Issuer
Assignee
Other Contributor(s)
Series
Has Part
Abstract
© 2018 Bentham Science Publishers. Background: Human Immunodeficiency Virus (HIV) is the causative agent of Acquired Immunodeficiency Syndrome (AIDS) that imposes a global health burden. Therefore, HIV therapeutic agents have been discovery and development. Objective: To construct Quantitative-structure Activity Relationship (QSAR) models of betulinic acid derivatives with anti-HIV activity using Simplified Molecular-Input Line-Entry System (SMILES)-based descriptors. Methods: A data set of 107 betulinic acid derivatives and their anti-HIV activity was used to develop QSAR models. The SMILES format of the compounds was employed as descriptors for model construction using the CORAL software by means of the Monte Carlo method. Results: Constructed QSAR models provided good correlation coefficients (R2) and root mean square error (RMSE) with values in the range of 0.5660-0.5890 and 0.963-1.020, respectively, for the training set, R2 value of 0.7206-0.7837 and RMSE as 0.609-1.250, respectively, for the calibration set, and R2 value of 0.6257-0.7748 and RMSE as 0.837-0.995, respectively, for the validation set. The best QSAR model displayed statistical parameters for training set: R2 = 0.5660 and RMSE = 0.963; calibration set: R2 = 0.7273 and RMSE = 0.609, and validation set: R2 = 0.7748 and RMSE = 0.972. In addition, features of the molecular structure that are promoters of the endpoint increase and decrease were defined and discussed. These are the basis for the mechanistic interpretation of the suggested models. Conclusion: These findings provide useful knowledge for guiding the design of novel compounds with promising anti-HIV activity.