HERBAL INFORMATICS: A UNIQUE MODEL TO IDENTIFY THE ANTI-CANCEROUS AGENTS FOR TARGETING LUNG CANCER

The incidence of lung cancer has increased in recent years and causes major mortalities across the globe. Besides, the availability of the several chemotherapeutics modalities in the management, there is still a challenge to find out an efficient remedy with lesser or no toxic effects. Hence, there is a necessity to employ complementary research to establish effective management for lung cancer. In this study, we have implemented a novel herbal informatics model to find out the alternative remedy in the treatment of lung cancer. This model utilizes five major steps of the bioprospection process based on the classical surge followed by the binary index and rationale-based selection of herbal products targeting the cancer-causing factors which are explained in detail in the methodology section of this model. In this bioprospection study, screening has been done utilizing the database of 50 herbals, in which 19 scrutinized based on the relevance-binary weightage scoring and 07 herbals were finalized as most potential herbals such as Withania somnifera (Ws), Berberis vulgaris(Bv), Glycyrrhiza glabra(Gg), Andrographis paniculate(Ap), Azadirachta indica(Ai), Cinnamomum verum(Cv), Piper longum(Pl) based on the fuzzy set optimization scoring ( =0.6-1). These identified leads could be further studied at in vitro and in vivo level for utilization in the management of lung cancer.