Network pharmacology-driven computational exploration of cryptotanshinone targets in lung carcinoma

This is the authors' abstract. We don't add key points for this paper.

Cryptotanshinone (CPT), a bioactive compound derived from the traditional Chinese herb Salvia miltiorrhiza Bunge, has shown anti-lung carcinoma properties. In this study, a comprehensive network pharmacology analysis was performed to identify potential targets of CPT in lung carcinoma therapy. The Traditional Chinese Medicine Systems Pharmacology and Analysis Platform (TCMSP), SwissTargetPrediction, STITCH, and SuperPred databases were explored to retrieve lung carcinoma-related genes and CPT targets. After identifying the lung carcinoma-specific CPT targets, the five most potential interacting targets of CPT were identified as AKT1, EGFR, HSP90AA1, STAT3, and TNF. Expression and survival analyses of the selected targets, using the data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project, showed their clinical importance in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients. Subsequently, molecular docking studies were performed between CPT and the five target proteins to evaluate the binding affinity. The binding energy and inhibition constant (Ki) for the interactions were analysed to further predict the potential role of CPT in lung carcinoma treatment. The molecular docking results showed binding energies of -9.22 kcal/mol for HSP90AA1, -8.45 kcal/mol for AKT1, -8.38 kcal/mol for TNF, -8.09 kcal/mol for EGFR, and -6.55 kcal/mol for STAT3, indicating their potentiality as anti-lung carcinoma agents. As indicated by the binding energies, CPT is predicted to target HSP90AA1 with the comparatively higher efficacy among these five proteins. Molecular dynamics (MD) simulations analysis of the two most promising targets, HSP90AA1 and AKT1 predicted stable CPT interactions. MM-PBSA analysis further estimated favourable binding free energies of CPT for both targets. Overall, this integrated network pharmacology-driven in silico analysis predicted key targets and pathways affected by CPT, including those involved in cell proliferation, apoptosis, angiogenesis, and inflammation. Further studies are required to validate these findings before considering CPT as an effective agent in lung carcinoma therapy.