Fragment-based QSAR study to explore the structural requirements of DPP-4 inhibitors: a stepping stone towards better type 2 diabetes mellitus management

ABSTRACT

Dipeptidyl peptidase-4 (DPP-4) inhibitors belong to a prominent group of pharmaceutical agents that are used in the governance of type 2 diabetes mellitus (T2DM). They exert their antidiabetic effects by inhibiting the incretin hormones like glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide which, play a pivotal role in the regulation of blood glucose homoeostasis in our body. DPP-4 inhibitors have emerged as an important class of oral antidiabetic drugs for the treatment of T2DM. Surprisingly, only a few 2D-QSAR studies have been reported on DPP-4 inhibitors. Here, fragment-based QSAR (Laplacian-modified Bayesian modelling and Recursive partitioning (RP) approaches have been utilized on a dataset of 108 DPP-4 inhibitors to achieve a deeper understanding of the association among their molecular structures. The Bayesian analysis demonstrated satisfactory ROC values for the training as well as the test sets. Meanwhile, the RP analysis resulted in decision tree 3 with 2 leaves (Tree 3: 2 leaves). This present study is an effort to get an insight into the pivotal fragments modulating DPP-4 inhibition.

KEYWORDS:

• T2DM
• DPP-4 inhibitor
• QSAR
• fingerprint
• molecular docking
• MD simulation

Acknowledgements

We sincerely appreciate the comments of learned reviewers and the learned editor-in-chief which helped to modify the manuscript in its current form. Authors sincerely acknowledge the Department of Pharmaceutical Technology, JIS University, Kolkata; Jadavpur University, Kolkata; Centre for Modelling Simulation & Design (CMSD), University of Hyderabad, Hyderabad, India for providing the research and computational facilities. SG is thankful to SERB, India for funding under the MATRICS Scheme [Ref. No.: MTR/2022/000286]. We thankfully acknowledge Prof. Tarun Jha of Jadavpur University, India, for his continuous motivation, and for providing the facilities to use Discovery Studio 3.0 (DS 3.0).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed at: https://doi.org/10.1080/1062936X.2024.2366886.

Additional information

Funding

The work was supported by the Science and Engineering Research Board [Ref. No.: MTR/2022/000286].