New spirooxindole-thiazolidine derivatives as antiseizure agents: Biological evaluation and computational studies

Background: Oxindoles and spirooxindoles are considered privileged scaffolds in medicinal chemistry due to their diverse biological activities, which include anticonvulsant, anticancer, and antimicrobial properties. Their distinctive structural characteristics render them appealing targets for synthetic modification and the development of innovative therapeutic agents. Notably, their significance in pharmaceutical drug discovery arises from their capacity to interact with various biological targets implicated in disease pathogenesis. Objective: To evaluate the effects of several new spirooxindole derivatives in animal models of epilepsy, specifically using intravenous pentylenetetrazole (PTZ)-induced epilepsy mouse models and maximal electroshock (MES) models. Methods: This research examined the anticonvulsant properties of spiroindole thiazolidine derivatives (A1-A8) through intraperitoneal administration of pentylenetetrazole (PTZ) and maximal electroshock (MES) seizure models in NMRI mice. The compounds were given via intraperitoneal injection, and the latency, occurrence, and duration of seizures were measured. To investigate interactions with the GABA-A receptor, molecular docking and dynamics simulations were carried out. Statistical analysis was performed using ANOVA, and the results were presented as means ± SEM. Results: Some spirooxindole derivatives exhibited anticonvulsant effects in animal models of epilepsy; however, this effect was not consistent across all models and compounds. Among the compounds evaluated, A6 and A8 emerged as the most effective anticonvulsants, demonstrating an elevation in seizure threshold at administered doses of 25, 50, and 100 mg/kg. Docking studies indicated that certain compounds may act as GABA-A agonists. Furthermore, a docking study revealed that compounds A4 and A6 exhibited lower binding energy as GABA-A agonists. Molecular dynamics (MD) simulations were also conducted, confirming that A6 exhibited excellent binding affinity for GABA aminotransferase. Conclusion: These findings suggest the potential of certain new spirooxindole derivatives as candidates for anticonvulsant drugs. However, further studies are required to validate these results and to explore their mechanisms of action.

Authors

Publication Details

Journal
Results in Chemistry
Published
2025-04-06
DOI
https://doi.org/10.1016/j.rechem.2025.102243
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

New spirooxindole-thiazolidine derivatives as antiseizure agents: Biological evaluation and computational studies

Elaheh Ataollahi, Soghra Khabnadideh, Pegah Mardaneh, Masoumeh Divar et al.
1 citations
Results in Chemistry
Computational Drug Discovery Methods
1.50
article

New spirooxindole-thiazolidine derivatives as antiseizure agents: Biological evaluation and computational studies

Elaheh Ataollahi, Soghra Khabnadideh, Pegah Mardaneh, Masoumeh Divar, Leila Emami, Leila Moezi, Sara Sadeghian, Razieh Sabet, Sahar Zarei, Saeed Agah
article en
1 citations

Abstract

Background: Oxindoles and spirooxindoles are considered privileged scaffolds in medicinal chemistry due to their diverse biological activities, which include anticonvulsant, anticancer, and antimicrobial properties. Their distinctive structural characteristics render them appealing targets for synthetic modification and the development of innovative therapeutic agents. Notably, their significance in pharmaceutical drug discovery arises from their capacity to interact with various biological targets implicated in disease pathogenesis. Objective: To evaluate the effects of several new spirooxindole derivatives in animal models of epilepsy, specifically using intravenous pentylenetetrazole (PTZ)-induced epilepsy mouse models and maximal electroshock (MES) models. Methods: This research examined the anticonvulsant properties of spiroindole thiazolidine derivatives (A1-A8) through intraperitoneal administration of pentylenetetrazole (PTZ) and maximal electroshock (MES) seizure models in NMRI mice. The compounds were given via intraperitoneal injection, and the latency, occurrence, and duration of seizures were measured. To investigate interactions with the GABA-A receptor, molecular docking and dynamics simulations were carried out. Statistical analysis was performed using ANOVA, and the results were presented as means ± SEM. Results: Some spirooxindole derivatives exhibited anticonvulsant effects in animal models of epilepsy; however, this effect was not consistent across all models and compounds. Among the compounds evaluated, A6 and A8 emerged as the most effective anticonvulsants, demonstrating an elevation in seizure threshold at administered doses of 25, 50, and 100 mg/kg. Docking studies indicated that certain compounds may act as GABA-A agonists. Furthermore, a docking study revealed that compounds A4 and A6 exhibited lower binding energy as GABA-A agonists. Molecular dynamics (MD) simulations were also conducted, confirming that A6 exhibited excellent binding affinity for GABA aminotransferase. Conclusion: These findings suggest the potential of certain new spirooxindole derivatives as candidates for anticonvulsant drugs. However, further studies are required to validate these results and to explore their mechanisms of action.

Results in ChemistryVol. 15
Shiraz University of Medical Sciences
Openalex Percentile: Top 18%
Computational Drug Discovery Methods
1.50
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.