Steroidal alkaloid cortistatin is a promising marine natural compound isolated from marine sponges Corticium simplex. Experimental studies and clinical evidence have shown that cortistatin and its derivatives have a curative effect in patients with autoimmune disorders, HIV infection and several types of cancer. The objective of our study was to examine the potential cancer-related therapeutic objectives of Cortistatin using a network pharmacology method, which is a computational approach, including inverse pharmacophore research, enrichment analysis, molecular docking and dynamics study. Systematic protocol also involves the assessment of ADMET parameters to define the pharmacokinetic profile of cortistatin. Inverse pharmacophore search method was used for computational target fishing and target proteins were ranked based on the graph theory approach. Cancer target proteins, namely HSP90, EGFR, CDK2, MMP13, MAPK13, AR, ESR1, PTPN11 and SRC, were classified as top-ranking proteins according to graph theory parameters, namely MCC, DMNC, MNC, Degree(Local-based methods), EPC, Bottleneck, Eccentricity, Closeness, Radiality, Betweenness, Stress(Global-based methods) and Clustering Coefficient. Enrichment assessment established on Gene Ontology and pathway analysis of these proteins that play a vital role in cancer pathways, FaxO Signalling pathways, Ras Signalling pathways and tyrosine metabolism. Molecular docking and dynamic simulation studies of cortistatin with proposed target proteins were found to be stable and conformers generated after 3ns were consistent with stable inter-molecular interactions. The current study summarized here would provide a broad perspective on the therapeutic potential of cortistatin and provide new insights into the future development of cancer therapy strategies. © 2021, Association of Pharmaceutical Teachers of India. All rights reserved.