Mechanisms
QSAR modelling and molecular docking chart a path to new CETP inhibitor compounds for coronary heart disease (J Biomol Struct Dyn 2020)
Original title: Design and development of novel therapeutics for coronary heart disease treatment based on cholesteryl ester transfer protein inhibition - in silico approach
A computational medicinal chemistry study built quantitative structure-activity relationship (QSAR) models for known CETP inhibitor compounds using Monte Carlo optimisation of SMILES notation and molecular graph descriptors, alongside a field-based three-dimensional model. A 3D QSAR model was built for one random training/test split, and conformation-independent models for three further splits, showing strong correlation across all four; statistical checks of robustness and predictability were favourable, including a novel index of ideality of correlation. The authors identified molecular fragments that raise or lower CETP inhibitory activity and used them to computationally design new candidate CETP inhibitor compounds, validated by molecular docking that agreed well with the QSAR predictions. An entirely in silico drug-design study, with no synthesis or biological testing of the proposed compounds.
Original abstract
Cholesteryl ester transfer protein (CETP) belongs to the group of enzymes which inhibition have the application in the treatment of cardiovascular diseases. This study presents QSAR modeling for a set of compounds acting as CETP inhibitors based on the Monte Carlo optimization with SMILES notation and molecular graph-based descriptors, and field-based 3D modeling. A 3D QSAR model was developed for one random split into the training and test sets, whereas conformation independent QSAR models were developed for three random splits, with the results suggesting there is an excellent correlation between them. Various statistical approaches were used to assess the statistical quality of the developed models, including robustness and predictability, and the obtained results were very good. This study used a novel statistical metric known as the index of ideality of correlation for the final assessment of the model, and the results that were obtained suggested that the model was good. Also, molecular fragments which account for the increases and/or decreases of a studied activity were defined and then used for the computer-aided design of new compounds as potential CETP inhibitors. The final assessment of the developed QSAR model and designed inhibitors was done using molecular docking, which revealed an excellent correlation with the results from QSAR modeling.Communicated by Ramaswamy H. Sarma.
Summary written by cetpinhibition.org from the published abstract; figures as published. Page updated 18 August 2026. Methods.