**7. Conclusion**

Through the current chapter, the more relevant techniques for finding drugs and targets employing computational approaches were described. Special considerations should be made when using the homology searching approach for finding drug targets as the context of protein interactions is important for the definition of essentiality. Protein interaction network analysis together with metabolic flux balance analysis are becoming useful alternatives to understand protein function and to systematically select drug targets. The selection of new inhibitory compounds can be done by using virtual screening. Predicted structures can also be used in virtual screening when experimentally derived structures are absent. Finally, machine learning techniques are a promising option to search for antileishmanial drugs, especially when experimental or predicted structures are not available, as may occur with many *Leishmania* proteins. It is important to state that any computational analysis is considered exploratory, and experimental validation is necessary to guide final decisions about potential compounds that can advance to the next stage of drug discovery. However, by using computational tools the search space for drugs and targets is reduced, allowing more focused experiments that could reduce the cost and time of drug development.
