Exploration in the Therapeutic and Multi-Target Mechanism of Ketamine on Cerebral Ischemia Based on Network Pharmacology and Molecular Docking

Abstract

Background Ketamine is famous for its dissociative anesthetic properties. It is also analgesic, anti-inflammatory and anti-depressant, and even has a cerebral protective effect. We searched the evidence of the correlation between ketamine target and clinical efficacy and utilized network pharmacology to gather information about the multi-target mechanism of ketamine against cerebral ischemia (CI). We found that ketamine’s clinical significance may be more extensive than previously thought. Methods The drug target of ketamine and CI-related genes were predicted by SwissTargetPrediction, DrugBank, PubChem, GeneCards and DisGeNET databases. The intersection of ketamine’s drug-targets and CI-related genes was analyzed by using GO and KEGG. We predicted the molecular docking between the potential target and ketamine. Results The results indicated that the effect of ketamine on CI was primarily associated with the target of α-synuclein (SNCA), muscarinic acetylcholine receptor M1 (CHRM1) and nitric oxide synthase 1 (NOS1). It principally regulates the signal pathways of circadian transmission, calcium signaling pathway, dopaminergic synapse, cholinergic synapse and glutamatergic synapse. Molecular docking analysis exhibited that hydrogen bond and Pi-Pi interaction were the predominant modes of interaction. Conclusion There are protein targets affected by ketamine in the treatment of CI. Three pivotal targets involving 298 proteins, SNCA, CHRM1 and NOS1, have emerged as multi-target mechanisms for ketamine in CI therapy. Similarly, this study also provides a new idea for introducing network pharmacology into the evaluation of multi-targeted drugs for CI and cerebral protection.

Coptidis rhizoma and evodiae fructus against lipid droplet deposition in nonalcoholic fatty liver disease‐related liver cancer by AKT

“…The compound‐target PPI network was calculated by ‘Network Analyzer’ of Cytoscape software., and the top 4 active compounds were screened according to degree value. The 2D structures of active compounds were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov) (Xiong et al, 2022) database. Chem3D (Xiong et al, 2022) software was used for energy minimization.…”

“…The 2D structures of active compounds were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov) (Xiong et al, 2022) database. Chem3D (Xiong et al, 2022) software was used for energy minimization. The protein ID number corresponding to the key target was searched using Uniport (https://www.uniprot.org/; The UniProt Consortium, 2017) database.…”

“…The 2D structures of active compounds were obtained from PubChem (https://pubch em.ncbi.nlm. nih.gov) (Xiong et al, 2022) database. Chem3D (Xiong et al, 2022) software was used for energy minimization.…”

Exploring the Molecular Targets for the Antidepressant and Antisuicidal Effects of Ketamine Enantiomers by Using Network Pharmacology and Molecular Docking

“…CC, DC, and BC are variables based on independence, connectivity, and control in the network, respectively, and describe distinct topological properties in the network, which, in combination, may be relevant for selecting more important biological targets [ 76 ]. It is common practice to select/filter targets from network pharmacology for molecular docking that obtain good scores of at least these three characteristics [ 14 , 16 , 77 ]. The filters were applied to the already computed model.…”