Design, synthesis, characterization, and molecular modeling studies of novel oxadiazole derivatives of nipecotic acid as potential anticonvulsant and antidepressant agents

Design, synthesis, molecular docking and pharmacological evaluation of some thiadiazole based nipecotic acid derivatives as a potential anticonvulsant and antidepressant agents

In our continuous effort to develop novel antiepileptic drug, a new series of nipecotic acid derivatives having1,3,4-thiadiazole nucleus were designed and synthesized. This study aims to improve the lipophilicity of nipecotic acid by attaching some lipophilic anchors like thiadiazole and substituted aryl acid derivatives. In our previous study, we noticed that the N-substituted oxadiazole derivative of nipecotic acid exhibited significant antiepileptic activity in the rodent model. The synthesized compounds were characterized by FT-IR, 1H-NMR, 13C-NMR, Mass, and elemental analysis. The anticonvulsant activity was evaluated by using the maximal electroshock-induced seizure model in rats (MES) and the subcutaneous pentylenetetrazol (scPTZ) test in mice. None of the compounds were found to be active in the MES model whereas compounds (TN2, TN9, TN12, TN13, and TN15) produced significant protection against the scPTZ-induced seizures model. The compounds showing antiepileptic activity were additionally evaluated for antidepressant activity by using the forced swim test, 5-hydroxytryptophan (5-HTP)-induced head twitch test, and learned helplessness test. All the molecules that showed anticonvulsant activity (TN2, TN9, TN12, TN13, and TN15), also exerted significant antidepressant effects in the animal models. The selected compounds were subjected to different toxicity studies. Compounds were found to have no neurotoxicity in the rota-rod test and devoid of hepatic and renal toxicity in 30 days repeated oral toxicity test. Further, a homology model was developed to perform the in-silico molecular docking and dynamics studies which revealed the similar binding of compound TN9 within the active binding pocket and were found to be the most potent anti-epileptic agent. The market expectation for newly developed antiepileptic thiadiazole-based nipecotic acid derivatives is significant, driven by their potential to offer improved therapeutic outcomes and reduced side effects, addressing a critical need in epilepsy treatment. These innovative compounds hold promise for meeting the demand for more effective and safer antiepileptic medications.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03897-1.

Homology modeling in drug discovery: Overview, current applications, and future perspectives

Homology modeling is one of the computational structure prediction methods that are used to determine protein 3D structure from its amino acid sequence. It is considered to be the most accurate of the computational structure prediction methods. It consists of multiple steps that are straightforward and easy to apply. There are many tools and servers that are used for homology modeling. There is no single modeling program or server which is superior in every aspect to others. Since the functionality of the model depends on the quality of the generated protein 3D structure, maximizing the quality of homology modeling is crucial. Homology modeling has many applications in the drug discovery process. Since drugs interact with receptors that consist mainly of proteins, protein 3D structure determination, and thus homology modeling is important in drug discovery. Accordingly, there has been the clarification of protein interactions using 3D structures of proteins that are built with homology modeling. This contributes to the identification of novel drug candidates. Homology modeling plays an important role in making drug discovery faster, easier, cheaper, and more practical. As new modeling methods and combinations are introduced, the scope of its applications widens.