Molecular design can be understood as the application of molecular modeling and simulations, among other HPC-based techniques of computational biology, to produce atom-level models of biological macromolecules.
In spite of the availability of experimental techniques to model the 3D structure of biological macromolecules, computational biology techniques to produce comparative models are very helpful when dealing with proteins of unknown 3D structure whose sequence identity to proteins with known 3D structure is above 30% (the safe zone). Figure 1 shows a typical workflow to produce comparative models of proteins whose 3D structure is not known.
Molecular modeling tools by satisfaction of spatial restrains, such as Modeller, are widely used to produce models of proteins whose 3D structure is not known. However, the effective usage of those models depends on the resolution of the used template and the sequence identity, between other important factors such a those depicted in Figure 2.
Using mathematical approximations such as Hamiltonian dynamics and force-fields, biological molecules to be simulated are depicted, atom by atom, into a three-dimensional box on the computer where the set of forces -defined in the force-field- interact with the atomic structure to produce a dynamical behavior of the system through time. Due to the high-end computer requirements to produce molecular simulations, HPC techniques such as parallel and programming are commonly used to implement molecular simulation engines such as NAMD. Figure 3 represents the CHARMM classical force field.
Using the CHARMM and other classical force fields, the vectorial field F is obtained through the computation of the potential energy gradient that depends on the coordinates r1 to rn. The summation of the different energy terms expressed in the functional form of the force field (Figure 3), generates the potential energy of the molecular system’s conformation. The dynamical behavior of biological macromolecules can provide insight into the function of such complex systems. Applications of molecular simulations range from protein engineering to computer-based drug design and nanobiotechnology.
Computer Based Drug Design
Modern drug design efforts are focused towards reducing the attrition costs that occur during the late phases of the development of drug discovery. Thus, during the first phases of drug discovery (Figure 4), computational biology tools such as comparative modeling, docking and molecular dynamics are broadly used to the discovery of therapeutical targets, to identify hit compounds, to produce lead compounds and to evaluate important pharmaceutical properties such as ADME/TOX (Adsorption, Distribution, Metabolism, Excretion and Toxicity).
Docking: Evaluating the interaction energy between molecules
In order to determine the feasibility that two molecules can interact by complementarity of their physicochemical properties, computational biology tools such Docking can be used to get an estimation of the delta G involved during the interaction procedure (Figure 5).
Computational biology programs such as Autodock are commonly used to produce different conformations of ligands interacting with proteins. Once those molecular poses are obtained, the delta G of interaction can be computed by producing the cycle shown in figure 5.