Integrating computation and visualization for biomolecular analysis: an example using python and AVS.
One of the challenges in biocomputing is to enable the efficient use of a wide variety of fast-evolving computational methods to simulate, analyze, and understand the complex properties and 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 an approach based on the Python programming language to achieve a high level of integration between these different computational methods and our primary visualization system AVS. This approach removes many limitations of AVS while increasing dramatically the inter-operability of our computational tools. Several examples are shown to illustrate how this approach enables a high level of integration and inter-operability between different tools, while retaining modularity and avoiding the creation of a large monolithic package that is difficult to extend and maintain.
Sanner
M F
MF
Scripps Research Institute, La Jolla, CA-92037, USA.
Duncan
B S
BS
Carrillo
C J
CJ
Olson
A J
AJ
D002213:Capsid / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D003205:Computing Methodologies; D008958:Models, Molecular; D011381:Programming Languages; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D014027:Tobacco Mosaic Virus; D014584:User-Computer Interface
D011506:Proteins