Coumarin-Based Sulfonamide Derivatives as Potential DPP-IV Inhibitors: Pre-ADME Analysis, Toxicity Profile, Computational Analysis, and In Vitro Enzyme Assay.

Recent research on dipeptidyl peptidase-IV (DPP-IV) inhibitors has made it feasible to treat type 2 diabetes mellitus (T2DM) with minimal side effects. Therefore, in the present investigation, we aimed to discover and develop some coumarin-based sulphonamides as potential DPP-IV inhibitors in light of the fact that molecular hybridization of many bioactive pharmacophores frequently results in synergistic activity. Each of the proposed derivatives was subjected to an in silico virtual screening, and those that met all of the criteria and had a higher binding affinity with the DPP-IV enzyme were then subjected to wet lab synthesis, followed by an in vitro biological evaluation. The results of the pre-ADME and pre-tox predictions indicated that compounds 6e, 6f, 6h, and 6m to 6q were inferior and violated the most drug-like criteria. It was observed that 6a, 6b, 6c, 6d, 6i, 6j, 6r, 6s, and 6t displayed less binding free energy (PDB ID: 5Y7H) than the reference inhibitor and demonstrated drug-likeness properties, hence being selected for wet lab synthesis and the structures being confirmed by spectral analysis. In the in vitro enzyme assay, the standard drug Sitagliptin had an IC50 of 0.018 µM in the experiment which is the most potent. All the tested compounds also displayed significant inhibition of the DPP-IV enzyme, but 6i and 6j demonstrated 10.98 and 10.14 µM IC50 values, respectively, i.e., the most potent among the synthesized compounds. Based on our findings, we concluded that coumarin-based sulphonamide derivatives have significant DPP-IV binding ability and exhibit optimal enzyme inhibition in an in vitro enzyme assay.

An Efficient and Robust Digital Fractional Order Differentiator Based ECG Pre-Processor Design for QRS Detection.

This paper presents an efficient infinite impulse response type digital fractional order differentiator (DFOD) based electrocardiogram (ECG) pre-processor to detect QRS complexes. First, an efficient optimizer namely, Antlion optimization algorithm is employed to solve the proposed DFOD design problem. Then, the designed DFOD is deployed in the pre-processing stage of a threshold independent R-peak detection technique. Finally, the proposed QRS complex detector is thoroughly assessed on the standard ECG datasets of MIT/BIH Arrhythmia, MIT/BIH ST Change, MIT/BIH Supraventricular Arrhythmia, European ST-T, QT, and T-Wave Alternans Challenge databases to show the wide sense practicability of the proposed DFOD-based QRS detector. The root-means-square magnitude error (RMSME) and the average group delay (τDD) metrics of the proposed DFOD are as low as -38.17 dB and 0.04 samples, respectively. The percentage of improvement in terms of RMSME metric compared to the best-reported approach is 15%. The overall sensitivity of 99.89% and positive predictivity of 99.88% are incurred by considering all the six databases. To the best of the authors' knowledge, it is the first time when the evolutionary algorithm based IIR-type DFOD is employed for the QRS complex detection and establishing its performance superiority. The results so obtained are compared with the results of all the recently reported QRS detectors. The proposed DFOD based ECG pre-processor has a great potential to robustly generate the feature signal related to the ECG QRS complex irrespective of the ECG morphology. Thus, the proposed DFOD based QRS detector can be employed in clinical ECG monitoring devices to augment the QRS detection performance.