Computer-aided prediction of inhibitors against STAT3 for managing COVID-19 associated cytokine storm. (October 2021)

• Record Type: Journal Article
• Authors: Dhall, Anjali; Patiyal, Sumeet; Sharma, Neelam; Devi, Naorem Leimarembi; Raghava, Gajendra.P.S.
• Is Part Of: Computers in biology and medicine. Volume 137(2021)
• Publication Date: 2021-10
• Subjects: STAT3 -- COVID-19 -- FDA-Approved -- Cytokine -- Inhibitors; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2021.104780
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Background: Proinflammatory cytokines are correlated with the severity of disease in patients with COVID-19. IL6-mediated activation of STAT3 proliferates proinflammatory responses that lead to cytokine storm promotion. Thus, STAT3 inhibitors may play a crucial role in managing the COVID-19 pathogenesis. The present study discusses a method for predicting inhibitors against the STAT3 signaling pathway. Method: The main dataset comprises 1565 STAT3 inhibitors and 1671 non-inhibitors used for training, testing, and evaluation of models. A number of machine learning classifiers have been implemented to develop the models. Results: The outcomes of the data analysis show that rings and aromatic groups are significantly abundant in STAT3 inhibitors compared to non-inhibitors. First, we developed models using 2-D and 3-D chemical descriptors and achieved a maximum AUC of 0.84 and 0.73, respectively. Second, fingerprints are used to build predictive models and achieved 0.86 AUC with an accuracy of 78.70% on the validation dataset. Finally, models were developed using hybrid descriptors, which achieved a maximum of 0.87 AUC with 78.55% accuracy on the validation dataset. Conclusion: We used the best model to identify STAT3 inhibitors in FDA-approved drugs and found few drugs (e.g., Tamoxifen and Perindopril) to manage the cytokine storm in COVID-19 patients. A webserver "STAT3In" (https://webs.iiitd.edu.in/raghava/stat3in/ ) has been developed to predict and design STAT3 inhibitors. Graphical abstract: Image 1 Highlights: IL6-mediated activation of STAT3 is responsible for cytokine storm. STAT3 inhibition is an important strategy to mitigate COVID-19 severity. In silico models have been developed for predicting STAT3 inhibitors. Repurposing of FDA-approved drug for managing COVID-19 via STAT3 inhibition. A webserver STAT3In developed for designing and predicting STAT3 inhibitors.