Title
Towards biophysical validation of constraint modeling for rigidity analysis of proteins
Abstract
Proteins are dynamic molecules, and understanding how they flex and bend provides fundamental insights to their functions. Methods such as molecular dynamics are computationally expensive, and can simulate protein motions on limited timescales. Rigidity analysis is an alternative method, in which a protein structure is analyzed to infer which portions of the molecule are flexible. To perform rigidity analysis, a model is first constructed in which various inter-atomic stabilizing interactions are modeled according to their strength. No detailed study has been conducted as to what is the most plausible, chemically validated modeling scheme. All previous implementations have relied on heuristics, which allowed for extracting relevant observations but only for a very limited set of proteins. We used our recently released KINARI-Web server for protein rigidity analysis to systematically vary how stabilizing interactions are modeled. Computational experiments that vary how hydrogen bonds and hydrophobic interactions are modeled to test which of them gives rigidity results that best correlate with experimental data has not been performed until this study. We collected a dataset of 159 Protein Data Bank files representing the wild-type and 158 variants of Lysozyme from bacteriophage T4, for which we retrieved experimentally derived stability data from the literature. We present here a systematic study seeking a possible correlation between some rigidity parameters and this experimental data. In particular, we compare rigidity results obtained from several methods for modeling interatomic interactions.
Year
DOI
Venue
2012
10.1145/2382936.2382988
BCB
Keywords
Field
DocType
rigidity result,detailed study,protein rigidity analysis,constraint modeling,protein structure,towards biophysical validation,systematic study,rigidity parameter,stability data,experimental data,rigidity analysis,protein motion,protein modeling
Rigidity (psychology),Protein structure prediction,Nanotechnology,Experimental data,Biological system,Chemistry,Heuristics,Molecular dynamics,Hydrophobic effect,Protein Data Bank,Protein structure
Conference
Citations 
PageRank 
References 
0
0.34
4
Authors
2
Name
Order
Citations
PageRank
Filip Jagodzinski17114.83
Ileana Streinu251064.64