Comparative Molecular Field Analysis (CoMFA), Molecular Docking and ADMET Study on Thiazolidine-4-carboxylic acid Derivatives as New Neuraminidase Inhibitors

Abstract

The objective of this research was to create a 3D-QSAR CoMFA model for a set of twenty-five neuraminidase inhibitors containing thiazolidine-4-carboxylic acid derivatives and to identify a new potent neuraminidase inhibitor for the treatment of influenza. The statistical parameters of the generated model are excellent: Q2 = 0.708, R2 = 0.997. The external validation results were (r2 0 = 0.922, K= 1.016, R2 pred = 0.674, r2 m= 0.778) indicating that the constructed model has good predictive power. Based on the contour map of the CoMFA model, we were able to propose six novel compounds with higher neuraminidase inhibitory activity than the most active compound. The six proposed molecules were submitted to molecular docking to analyse the bindings formed between the newly designed molecules and the neuraminidase. All of the proposed molecules were found to be more stable on the active site of neuraminidase than the reference molecule (1SJ). SwissADME was used to estimate the pharmacokinetic properties of each proposed molecule, while ProToxII and VEGA QSAR were used to investigate any potential toxicity. Finally, a reaction mechanism for synthesizing the six proposed compounds was described, which could potentially be explored further in the search for novel neuraminidase inhibitors. In conclusion, this study has identified potential candidates for the development of more effective neuraminidase inhibitors for the treatment of influenza.

Computer-Aided Strategy on 5-(Substituted benzylidene) Thiazolidine-2,4-Diones to Develop New and Potent PTP1B Inhibitors: QSAR Modeling, Molecular Docking, Molecular Dynamics, PASS Predictions, and DFT Investigations

“…A drug’s success can be gauged, not simply through its effectiveness but also by a satisfactory ADMET identity. While there are several high-throughput in vitro ADMET screens accessible, having the ability to predict a number of these features occurs in silico [ 61 , 62 ]. The drug-likeness prediction and pharmacokinetics properties of the newly designed compounds were calculated using free web tools including the SwissADME web server [ 63 ] and the ProTox-II platform, which was implemented to evaluate the toxicity of the selected compounds [ 64 ].…”

“…The HOMO and LUMO energies are used for the determination of global reactivity descriptors such as chemical potential (μ), hardness (η), softness (δ), and electrophilicity (ω). These parameters are calculated by the following equations [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 ]: …”