Virtual screening of dipeptidyl peptidase-4 inhibitors using quantitative structure–activity relationship-based artificial intelligence and molecular docking of hit compounds

Virtual screening of dipeptidyl peptidase-4 inhibitors using quantitative structure–activity relationship-based artificial intelligence and molecular docking of hit compounds

Dipeptidyl peptidase-4 (DPP-4) inhibitors are becoming an essential drug in the treatment of type 2 diabetes mellitus; however, some classes of these drugs exert side effects, including joint pain and pancreatitis. Studies suggest that these side effects might be related to secondary inhibition of D...

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Bibliographic Details
Main Authors: Bustamam, A. (Author), Hermansyah, O. (Author), Yanuar, A. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2021
Subjects:
artificial intelligence
Artificial intelligence
Artificial Intelligence
chemistry
Computational chemistry
Decision trees
Dipeptidyl peptidase
Dipeptidyl Peptidase 4
dipeptidyl peptidase IV
dipeptidyl peptidase IV inhibitor
Dipeptidyl peptidase-4
Dipeptidyl-Peptidase IV Inhibitors
DPP-4
Drug Evaluation, Preclinical
E-learning
human
Humans
KNIME
Learning algorithms
Machine learning
Machine learning algorithms
metabolism
molecular docking
Molecular docking
Molecular Docking Simulation
Molecular graphics
Molecular modeling
Molecules
preclinical study
QSAR
quantitative structure activity relation
Quantitative structure activity relationship
Quantitative Structure-Activity Relationship
Quantitative structure-activity relationship modeling
Side effect
Virtual screening
Virtual Screening
Work-flows
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