Background: The current study recognizes the significance of estrogen receptor alpha (ERα) as a member of the nuclear receptor protein family, which holds a central role in the pathophysiology of breast cancer. ERα serves as a valuable prognostic marker, with its established relevance in predicting disease outcomes and treatment responses. Methods: In this study, computational methods are utilized to search for suitable drug-like compounds that demonstrate analogous ligand binding kinetics to ERα. Results: Docking-based simulation screened out the top 5 compounds - ZINC13377936, NCI35753, ZINC35465238, ZINC14726791, and NCI663569 against the targeted protein. Further, their dynamics studies reveal that the compounds ZINC13377936 and NCI35753 exhibit the highest binding stability and affinity. Conclusion: Anticipating the competitive inhibition of ERα protein expression in breast cancer, we envision that both ZINC13377936 and NCI35753 compounds hold substantial promise as potential therapeutic agents. These candidates warrant thorough consideration for rigorous In vitro and In vivo evaluations within the context of clinical trials. The findings from this current investigation carry significant implications for the advancement of future diagnostic and therapeutic approaches for breast cancer.

This paper presents the concept of incremental traceback for determining changes in the trace of a network as it evolves with time. A distributed algorithm, based on the methodology of algebraic traceback developed by Dean et al., is proposed that can determine a path of d nodes using O(d) marked packets, and subsequently determine the changes in it using O(log d) marked packets. The algorithm is established to be order-wise optimal, i.e. no other distributed algorithm can determine changes in the path topology using lesser order of bits (or marked packets). The algorithm is shown to have a computational complexity of O(d log d), which is significantly less than that of any existing non-incremental algorithm for algebraic traceback. The extension of the traceback mechanism to systems deploying network coding is also considered.