YB-1 is one of the major mRNA binding proteins and a master regulator of translation in cancer cells. It has been recently considered as a therapeutic target for the treatment of cancer and drug-resistant cancer. However, no small molecules with high affinity and specificity against YB-1 have been proposed so far, and the structural data essential to interrogate their relevance are missing. Understanding the function of translation regulation systems in order to design drug candidates is a very delicate procedure that requires a high level of accuracy and state-of-the-art techniques. Based on a promising preliminary finding of an active compound, we will focus in depth on studying the inhibition mechanism of YB-1 in order to help design new anti-cancer drugs able to overcome drug resistance. The research approach developed in this context aims to use in synergy advanced computational and experimental techniques while overcoming all limitations in a concerted way. This work is concerned with providing a sufficiently accurate computational model that is computationally efficient, specific experimental data and combining them with data mining techniques, for a molecular-level characterization of the inhibition dynamics and thermodynamics. This project is based on a multidisciplinary approach that requires knowledge of biology, biochemistry, physical chemistry, theoretical chemistry and bioinformatics in order to contribute to the medicine of the future.