Paper Citing NAMD - Abstract
Adrian, Png Eak Hock; Soo, Tan Tsu; Wah, Choo Keng
Large-scale simulation and prediction of HLA-epitope complex structures
GRID COMPUTING IN LIFE SCIENCES, 189-196, 2006
The predictability of Human Leukocyte Antigens (HLA) binding to their target epitopes has been a holy grail in the field of Immunoinformatics. Currently, predictions are performed using two approaches: machine learning techniques and structural analysis. The latter often requires a large amount of computation in performing molecular simulations and post-process analysis. In this study, our objective is to create a vast number of hypothetical structural variations of HLA-peptide complexes. We present a prototype large-scale molecular modeling system to generate molecular structures that can then be used to determine binding efficiencies of HLA-peptide pairs. Understanding the binding potential of various epitopes allows us to suggest potential vaccine candidates for downstream validation. The system was implemented using Grid Services that embed functionalities of various software tools used for the molecular modeling of protein structures.
