Structural bioinformatics

Three-dimensional structure of a protein

Structural bioinformatics is the branch of bioinformatics which is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structure such as comparisons of overall folds and local motifs, principles of molecular folding, evolution, and binding interactions, and structure/function relationships, working both from experimentally solved structures and from computational models. The term structural has the same meaning as in structural biology, and structural bioinformatics can be seen as a part of computational structural biology.

Overview

Informatics approaches used in structural bioinformatics are

  • Selection of Target - Potential targets are identified by comparing them with databases of known structures and sequence. The importance of a target can be decided on the basis of published literature. Target can also be selected on the basis of its protein domain. Protein domain are building blocks that can be rearranged to form new proteins. They can be studied in isolation initially.
  • Tracking X-ray crystallography trials - X-Ray crystallography can be used to reveal three-dimensional structure of a protein. But, in order to use X-ray for studying protein crystals, pure proteins crystals must be formed, which can take a lot of trials. This leads to a need for tracking the conditions and results of trials. Furthermore, supervised machine learning algorithms can be used on the stored data to identify conditions that might increase the yield of pure crystals.
  • Analysis of X-Ray crystallographic data - The diffraction pattern obtained as a result of bombarding X-rays on electrons is Fourier transform of electron density distribution. There is a need for algorithms that can deconvolve Fourier transform with partial information ( due to missing phase information, as the detectors can only measure amplitude of diffracted X-rays, and not the phase shifts ). Extrapolation technique such as Multiwavelength anomalous dispersion can be used to generate electron density map, which uses the location of selenium atoms as a reference to determine rest of the structure. Standard Ball-and-stick model is generated from the electron density map.
  • Analysis of NMR spectroscopy data - Nuclear magnetic resonance spectroscopy experiments produce two (or higher) dimensional data, with each peak corresponding to a chemical group within the sample. Optimization methods are used to convert spectra into three dimensional structures.
  • Correlating Structural information with functional information - Structural studies can be used as probe for structural-functional relationship.

See also

References

Books

  • Bourne, P.E., and Gu, J. (2009) Structural Bioinformatics (2nd edition), John Wiley & Sons, New York, ISBN 978-0-470-18105-8
  • Bourne, P.E., and Weissig, H. (2003) Structural Bioinformatics, Wiley ISBN 0-471-20199-5
  • Leach, Andrew (2001) Molecular Modelling: Principles and Applications (2nd edition), Prentice Hall, ISBN 978-0-582-38210-7
  • Peitsch, M.C., and Schwede, T. (2008) Computational Structural Biology: Methods and Applications World Scientific, ISBN 978-9812778772

Hallmark publications

  • Leontis NB, Westhof E (2001). "Geometric nomenclature and classification of RNA base pairs". RNA. 7 (4): 499&ndash, 512. doi:10.1017/S1355838201002515. PMC 1370104. PMID 11345429.
  • Richardson JS (1981). "The anatomy and taxonomy of protein structure". Adv Protein Chem. Advances in Protein Chemistry. 34: 167&ndash, 339. doi:10.1016/S0065-3233(08)60520-3. ISBN 978-0-12-034234-1. PMID 7020376.
  • Ramachandran GN, Sasisekharan V (1968). "Conformation of polypeptides and proteins". Adv Protein Chem. Advances in Protein Chemistry. 23: 283&ndash, 438. doi:10.1016/S0065-3233(08)60402-7. ISBN 978-0-12-034223-5. PMID 4882249.
  • Ramachandran GN, Ramakrishnan C, Sasisekharan V (1963). "Stereochemistry of polypeptide chain configurations". J Mol Biol. 7: 95&ndash, 9. doi:10.1016/S0022-2836(63)80023-6. PMID 13990617.

Databases

Software

  • Molecular Operating Environment (MOE) Extensive platform including structural modelling for proteins, protein families and antibodies
  • SBL The Structural Bioinformatics Library: end-user applications and advanced algorithms
  • BALLView molecular modeling and visualization
  • FRIEND visualization and analysis
  • STING visualization and analysis
  • PyMOL viewer and modeling
  • VMD viewer, molecular dynamics
  • KiNG, an open-source Java kinemage viewer
  • MolMol viewer, NMR
  • SPDBV DeepView viewer
  • STRIDE determination of secondary structure from coordinates
  • MolProbity structure-validation web server
  • PROCHECK, a structure-validation web service
  • CheShift, a protein structure-validation on-line application
  • MolTalk, structural bioinformatics software
  • Jmol, a molecular viewer Java applet with rasmol-like scripting capabilities and Javascript interaction
  • PROPKA, rapid prediction of protein pKa values based on empirical structure/function relationships
  • CARA – Computer Aided Resonance Assignment
  • Docking Server, a molecular docking web server
  • StarBiochem, a java protein viewer, features direct search of protein databank
  • Biskit, a python platform for structural bioinformatics
  • SPADE the structural proteomics application development environment
  • UGENE, an opensource multiplatform viewer for PDB and MMDB files
  • PocketSuite, a web portal for various web-servers for binding site level analysis
  • MSL, an open-source C++ molecular modeling software library for the implementation of structural analysis, prediction and design methods
  • PSSpred – Protein secondary structure prediction
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