Local descriptors of protein structure

We have introduced the concept of local descriptors of protein structure to characterize local neighborhoods of amino acids in proteins including short- and long-range interactions. We have build a library of recurring local descriptors and show that this library is general enough to allow assembly of unseen protein structures. Thus the method identifies, in a systematic way, the local building blocks that are common to many proteins with otherwise unrelated global structures (folds). The descriptor building block approach has many possible applications and we have applied them to prediction of protein-ligand interactions, fold recognition, residue-residue contact prediction and prediction of function from structure.

Presentation at Stockholm Bioinformatics Centre, 2009.

Articles using local descriptors

  1. P. Daniluk and B. Lesyng. Theoretical and computational aspects of protein structural alignment, Book chapter in Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes, Springer, 557-598, 2014.
  2. P. Daniluk, M. Dziubiński, B. Lesyng. From experimental, structural probability distributions to the theoretical causality analysis of molecular changes. Computer Assisted Methods in Engineering and Science 19.3: 257-276, 2012.
  3. P. Daniluk and B. Lesyng. A novel method to compare protein structures using local descriptors. BMC Bioinformatics 12:344, 2011.
  4. P. Lukasiak, K. Fidelis, M. Antczak, A. Kryshtafovych andJ. Blazewicz. Automated prediction of 3D structure of proteins based on descriptors approach. The annual Polish-German workshop on Computational Biology, Scheduling, and Machine Learning (ICOLE 2010), Lessach, Austria.
  5. T. R. Hvidsten, A. Lægreid, A. Kryshtafovych, G. Andersson, K. Fidelis and J. Komorowski. A comprehensive analysis of the structure-function relationship in proteins based on local structure similarity. PLoS ONE 4(7): e6266, 2009.
  6. P. Björkholm, P. Daniluk, A. Krystofovich, K. Fidelis, R. Andersson and TR Hvidsten. Using multi-data hidden Markov models trained on local neigh-borhoods of protein structure to predict residue-residue contacts. Bioinformatics 25: 1264-1270, 2009.
  7. T. R. Hvidsten*, A. Kryshtafovych* and K. Fidelis. Local descriptors of protein structure: A systematic analysis of the sequence-structure relationship in proteins using short- and long-range interactions, Proteins: Structure, Function, and Bioinformatics 75 (4): 870-884, 2009.
  8. H. Strömbergsson, P. Daniluk, A. Kryshtafovych, K. Fidelis, J. E. S. Wikberg, G. J. Kleywegt and T. R. Hvidsten. Interaction Model Based on Local Protein Substructures Generalizes to the Entire Structural Enzyme-Ligand Space, Journal of Chemical Information and Modeling 48 (11): 2278–2288, 2008.
  9. A. Kryshtafovych, A. Prlic, Z. Dmytriv, P. Daniluk, M. Milostan, V. Eyrich, T. Hubbard, K. Fidelis. New tools and expanded data analysis capabilities at the protein structure prediction center. Proteins: Structure, Function and Bioinformatics 69 (S8): 19-26, 2007.
  10. M. Drabikowski, S. Nowakowski and J. Tiuryn. Library of local descriptors models the core of proteins accurately. Proteins: Structure, Function and Bioinformatics 69: 499-510, 2007.
  11. S. Nowakowski and M. Drabikowski. Efficient Local Protein Structure Prediction, Lecture Notes in Computer Science 4481: 308-315, Springer-Verlag Berlin Heidelberg New York, 2007.
  12. H. Strömbergsson, A. Kryshtafovych, P. Prusis, K. Fidelis, J. E. S. Wikberg, J. Komorowski and T. R. Hvidsten. Generalized modeling of enzyme-ligand interactions using proteochemometrics and local protein substructures, Proteins: Structure, Function and Bioinformatics 65: 568-579, 2006.
  13. S. Nowakowski, K. Fidelis and J. Tiuryn. Introducing Dependencies into Alignment Analysis and Its Use for Local Structure Prediction in Proteins, Lecture Notes in Computer Science 3911: 1106-1113, Springer-Verlag Berlin Heidelberg New York, 2006.
  14. A. Kryshtafovych, M. Milostan, L. Szajkowski, P. Daniluk and K. Fidelis. CASP6 data processing and automatic evaluation at the protein structure prediction center. Proteins: Structure, Function and Bioinformatics 61 (S7): 19-23, 2005.
  15. T. R. Hvidsten, A. Kryshtafovych, J. Komorowski and K. Fidelis. A novel approach to fold recognition using sequence-derived properties from sets of structurally similar local fragments of proteins, ECCB2003, Bioinformatics 19 Suppl 2: II81-II91, 2003.

*Contributed equally.

Theses using local descriptors

  1. A. Mykowiecka. Analysis of RNA tertiary structure using local descriptors of structure, Master thesis, Faculty of Mathematics, Informatics, and Mechanics, University of Warsaw, 2014.
  2. P. Daniluk. Analiza podobieństwa struktur przestrzennych białek przy użyciu deskryptorów lokalnej struktury, PhD thesis, Faculty of Mathematics, Informatics, and Mechanics, University of Warsaw, 2011. [Extensive summary in English]
  3. Helena Strömmbergsson. Chemogenomics: Models of Protein-Ligand Interaction Space, PhD thesis, Uppsala University, 2009.
  4. Patrik Björkholm. Method for recognizing local descriptors of protein structures using Hidden Markov Models, Master thesis, Uppsala University, 2008.
  5. Johan Alexander Källberg Zvrskovec. Protein structure prediction by search among combinations of reoccurring structural components, Student project (10 points), Uppsala University, 2008.
  6. M. Drabikowski. Groups and signals analyzes. Assembling proteins structure from local descriptors, PhD thesis, University of Warsaw, 2006.
  7. S. Nowakowski. Estimating Probability Distributions of a Sequence Occuring in an Alignment and Its Use in 3D Protein Structure Prediction, PhD thesis, Insitute of Informatics, Warsaw University, 2006.
  8. Minyan Hong. Fold recognition using local descriptors of protein structure and Hidden Markov Models, Student project (10 points), 2006 and Master thesis, Uppsala University, 2007.
  9. Marta Luksza. A System for Predicting Protein Function from Structure, Master thesis, Uppsala University, 2005.
  10. Anna Hennecke. Predicting protein function from its 3-dimensional structure - Biological validation of protein function predictions, Student project (10 points), Uppsala University, 2005.
  11. T. R. Hvidsten. Predicting function of genes and proteins from sequence, structure and expression data, PhD thesis, Department of Information Technology and Linnaeus Centre for Bioinformatics, Uppsala University, 2004.
  12. P. Daniluk. Klastering fragmentów struktur białkowych z uwzględnieniem sekwencji kodujących, Master thesis, Faculty of Mathematics, Informatics, and Mechanics, University of Warsaw, 2002.