As computational sciences have become more ingrained in current research, the individual researcher needs expertise beyond basic data acquisition and analysis. The minimum skill sets for computational scientists are key cross-disciplinary concepts, involving a combination of knowledge and proficiency in the fields of biology, chemistry, computer science, and mathematics. As a result, this cross disciplined data generated by computational science, e.g. bioinformatics, supports a bridge between various disciplines. The combination of significant advances in modeling methods, and the exponential increase in available computational power means that computational modeling is having a revolutionary impact on scientific research and discovery. Sub-specialties such as molecular modeling encompasses a wide collection of computational techniques, including visualization, transition state modeling, ab initio (Quantum Mechanics), Molecular Docking, and Molecular Dynamics (MD). Biomedical simulations have the ability to address these disease mechanisms at the molecular level. This insight into mechanisms can lead investigators into new directions, relieving the need for extensive costly laboratory lead identification and testing. These methods are now standard tools used by theoretical /computational chemists and biologists for predicting chemical structural properties of biomolecules.