Abstract
BackgroundA commonly recurring problem in structural protein studies, is the determination of all heavy atom positions from the knowledge of the central α-carbon coordinates.ResultsWe employ advances in virtual reality to address the problem. The outcome is a 3D visualisation based technique where all the heavy backbone and side chain atoms are treated on equal footing, in terms of the Cα coordinates. Each heavy atom is visualised on the surfaces of a different two-sphere, that is centered at another heavy backbone and side chain atoms. In particular, the rotamers are visible as clusters, that display a clear and strong dependence on the underlying backbone secondary structure.ConclusionsWe demonstrate that there is a clear interdependence between rotameric states and secondary structure. Our method easily detects those atoms in a crystallographic protein structure which are either outliers or have been likely misplaced, possibly due to radiation damage. Our approach forms a basis for the development of a new generation, visualization based side chain construction, validation and refinement tools. The heavy atom positions are identified in a manner which accounts for the secondary structure environment, leading to improved accuracy.Electronic supplementary materialThe online version of this article (doi:10.1186/s12900-014-0027-8) contains supplementary material, which is available to authorized users.
Highlights
A commonly recurring problem in structural protein studies, is the determination of all heavy atom positions from the knowledge of the central α-carbon coordinates
The Ramachandran map describes the statistical distribution of the two dihedral angles φ and ψ that are adjacent to the Cα carbons along the protein backbone
We propose the concept of an imaginary observer, chosen so that the discrete Frenet frames determine the orientation of the observer when she rollercoasts along the backbone and climbs up the side chains
Summary
A commonly recurring problem in structural protein studies, is the determination of all heavy atom positions from the knowledge of the central α-carbon coordinates. Protein structure validation methods like MolProbity [1] and Procheck [2] help crystallographers to find and fix potential problems that are incurred during fitting and refinement. These methods are commonly based on a priori chemical knowledge and utilise various well tested and broadly accepted stereochemical paradigms. The Ramachandran map describes the statistical distribution of the two dihedral angles φ and ψ that are adjacent to the Cα carbons along the protein backbone. A comparison between the observed values of the individual dihedrals in a given protein with the statistical
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