Molecular modeling applied to anti-cancer drug development

In the past, anti-cancer drugs were identified and developed without focusing on a particular macromolecular target. Currently, the fields of molecular biochemistry, molecular biology, genetics and pharmacology, among other disciplines, have grown considerably in their ability to identify biological targets. These disciplines are now searching for specific targets to treat cancer. These targets exist in different cellular compartments (membrane, cytoplasm, nucleus) as proteins, glycoproteins, nucleic acids, etc. Computational tools have recently been used to explore such targets and to corroborate previously obtained experimental data. These methods have also been used to design new drugs with the aim of decreasing illness and the economic resources needed to discover drug candidates. Some of these computational methods include quantum mechanics (ab initio and density functional theories) and molecular mechanics (docking, molecular dynamics, and protein folding). Docking and molecular dynamics are the most commonly used computational tools for elucidating cancer targets. Using these tools, one can identify the recognition processes between ligands and targets at the atomic level. In addition, one can identify the affinity and conformational changes of these molecular complexes. In conclusion, we propose that the use of such tools is necessary in order to identify new anti-cancer drugs.