Re-usable components for structural bioinformatics

One of the challenges in biocomputing is to enable the efficient use of a wide variety of rapidly evolving computational methods to simulate, analyze and understand the complex interactions of molecular systems. Our laboratory investigates several areas including molecular visualization, protein-ligand docking, protein-protein docking, molecular surfaces and the derivation of phenomenological potentials. In this paper, we present how we have used Python to develop independent components to deal with different aspects of structural bioinformatics. We contrast this “language-centric” approach with an “applicationcentric” approach. We will describe the following packages: MolKit: to read, write, represent and manipulate molecules; DejaVu: a 3D geometry visualization component; ViewerFramework: a component providing support for building dynamically extensible visualization applications. We then describe how these components have been combined together to create extensible applications such as the Python Molecule Viewer (PMV) and the AutoDock Toolkit (ADT).