In silico computational research of alpha tubulin inhibitors, their binding sites and comparison between human and plant organisms.

In this study, an advanced computational in silico approach was applied to explore how various naturally derived compounds interact with alpha tubulin, focusing on well-known binding sites in human isotypes commonly expressed in tumors. The primary objective was to determine the binding affinities of these compounds and compare them with similar interactions in several plant species to assess potential similarities. The methodology followed a step-by-step process, starting with the creation of 3D structures of tubulin heterodimers using homology modeling. Binding site geometries were reconstructed through molecular modeling tools, and docking simulations were performed to analyze the interactions of various inhibitors with the human tubulin isotypes TUBA1A, TUBA1B, and TUBA4A. The binding affinities of these compounds were evaluated based on the S-score, which measures the strength and stability of molecular interactions. Additionally, plant-derived tubulin sequences were obtained and analyzed to explore similarities with human tubulin, and docking simulations were performed on selected plant tubulin structures. The study revealed that many plant tubulin sequences share a high degree of similarity with human ones, particularly from species like Taxus baccata and Prunus dulcis, offering new opportunities for sustainable drug discovery using plant-based sources. Results from the docking simulations highlighted several promising compounds, with notable interactions involving compounds like Eribulin, Cevipabulin, and Gatorbulin, which showed high binding affinities to specific tubulin isotypes. This research highlights the potential of using computational models to predict molecular interactions for drug development, with a particular focus on anticancer therapies targeting microtubules.