title: PCalign: a method to quantify physicochemical similarity of protein-protein interfaces.
abstract: BACKGROUND
  Structural comparison of protein-protein interfaces provides valuable insights into the functional relationship between proteins, which may not solely arise from shared evolutionary origin. A few methods that exist for such comparative studies have focused on structural models determined at atomic resolution, and may miss out interesting patterns present in large macromolecular complexes that are typically solved by low-resolution techniques.
  
  
  RESULTS
  We developed a coarse-grained method, PCalign, to quantitatively evaluate physicochemical similarities between a given pair of protein-protein interfaces. This method uses an order-independent algorithm, geometric hashing, to superimpose the backbone atoms of a given pair of interfaces, and provides a normalized scoring function, PC-score, to account for the extent of overlap in terms of both geometric and chemical characteristics. We demonstrate that PCalign outperforms existing methods, and additionally facilitates comparative studies across models of different resolutions, which are not accommodated by existing methods. Furthermore, we illustrate potential application of our method to recognize interesting biological relationships masked by apparent lack of structural similarity.
  
  
  CONCLUSIONS
  PCalign is a useful method in recognizing shared chemical and spatial patterns among protein-protein interfaces. It outperforms existing methods for high-quality data, and additionally facilitates comparison across structural models with different levels of details with proven robustness against noise.
authors: Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA. sscheng@umich.edu.
authors: Shanshan
authors: S
authors: Cheng
authors: Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA. zhng@umich.edu.|Department of Biological Chemistry, Medical School, University of Michigan, Ann Arbor, MI, USA. zhng@umich.edu.
authors: Yang
authors: Y
authors: Zhang
authors: Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA. brookscl@umich.edu.|Department of Chemistry, University of Michigan, Ann Arbor, MI, USA. brookscl@umich.edu.|Biophysics Program, University of Michigan, Ann Arbor, MI, USA. brookscl@umich.edu.
authors: Charles L
authors: CL
authors: Brooks
mesh_terms: D000465:Algorithms; D055598:Chemical Phenomena; D006801:Humans; D008958:Models, Molecular; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D012984:Software
chemical_list: D011506:Proteins
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