Alex Stivala, Michael Wybrow, Anthony Wirth, James C. Whisstock, Peter J. Stuckey, Automated technology of protein construction cartoons with Professional-origami, Bioinformatics, Quantity 27, Challenge 23, 1 December 2011, Pages 3315–3316, https://doi.org/10.1093/bioinformatics/btr575
Comparisons between structurally associated proteins are aided by simplified topology maps of protein construction [e.g. TOPS cartoons (Westhead et al., 1999)]. Such diagrams are notably helpful when evaluating very distantly associated folds [e.g. (Rosado et al., 2007)]. The automated technology of such cartoons is a difficult drawback, requiring because it does the simplification of a posh 3D object right into a 2D illustration, with the (typically competing) necessities of correctness, maximizing the quantity of knowledge conveyed, ease of comprehension and aesthetic enchantment. To the most effective of our data, there are three current programs for the automated technology of such diagrams from atomic co-ordinates in PDB information. HERA (Hutchinson and Thornton, 1990) generates detailed hydrogen-bonding diagrams. TOPS generates topological cartoons with a ‘top-down’ view in a method much like the hand-drawn diagrams of Sternberg and Thornton, (1977). A latest addition to the PDBsum web site (Laskowski, 2009) generates topology diagrams for protein domains in an ‘exploded’ type derived from HERA. These kinds of diagram should not all the time ample for the needs of structural biologists and specifically don’t precisely convey the relative place of β-sheets and α-helices. One resolution is to attract appropriate diagrams manually, and the TopDraw program (Bond, 2003) is an easy diagram editor designed to help the handbook drawing of protein construction cartoons in a perpendicular view, wanting ‘side-on’ to secondary construction components (SSEs).
Professional-origami is an method for routinely producing protein construction cartoons in a scientific vogue, related to those who is likely to be manually produced by way of human cognition and depicted utilizing TopDraw. β-strands and α-helices are drawn as arrows and cylinders, respectively, proportional in size to the variety of residues they comprise. β-sheets are proven as teams of β-strands positioned relative to one another based on their precise relative positions (Fig. 1). Most significantly, Professional-origami offers an answer to essentially the most advanced a part of the issue; reaching a format that is still understandable whereas sustaining as a lot of the 3D structural info as potential.
The primary stage of the Professional-origami course of is, optionally, to decompose the protein into domains, utilizing both a CATH (Pearl et al., 2005) CDF file or the DDOMAIN program (Zhou et al., 2007). Secondary construction is decided utilizing both the secondary construction assignments within the PDB file, or the DSSP (Kabsch and Sander, 1983) or STRIDE (Frishman and Argos, 1995) packages, from which hydrogen bond info can be obtained. Constraints derived embody groupings of strands inside sheets and the relative positions of strands in a sheet, separation between adjoining strands in a sheet, and the alignment of strands and helices on horizontal or vertical axes. β-strands are grouped into sheets utilizing algorithms much like these employed by TOPS, making use of hydrogen bond and 3D geometrical info. β-barrels are displayed ‘flattened’ into sheets by breaking the bridge relationship between two of the strands. These strands are marked within the cartoon to point this case. Sheets are positioned relative to one another based on the contact map and tableau (Kamat and Lesk, 2007) computed for the protein, which defines the relative orientation of secondary construction components. Helices are positioned utilizing a heuristic which makes an attempt to make the diagram as simple as potential to learn, often by putting them aligned on the axis of the closest strand.
The preliminary positions of the cartoon components and the set of constraints and connectors are used because the enter to the Dunnart constraint-based diagram editor (Dwyer et al., 2009). Dunnart then lays out the diagram based on the constraints, with specialised coding to make sure that components don’t overlap. Connectors between the weather are routed in order to not collide with components and to attempt to scale back pointless crossings (Wybrow et al., 2010).
Along with offering protein construction cartoons, Professional-origami acts as a consumer interface to a protein substructure looking algorithm (Stivala et al., 2009). The consumer can choose a set of SSEs on the cartoon to behave as a motif question, and have the matching SSEs highlighted within the Professional-origami cartoons of the matched constructions.
One of many goals of Professional-origami is to make cartoons simple to interpret visually. One of many standards for straightforward interpretation is that the sequence of helices and strands ought to be simple to observe by eye alongside the connectors, and Professional-origami makes an attempt to reduce the variety of instances by which connectors run too shut to one another, a state of affairs we describe as a connector ‘overlap’, which Professional-origami detects and makes an attempt to right routinely. We ran Professional-origami on a database of non-redundant protein domains, leading to a complete of 16 602 cartoons. Professional-origami produces a cartoon with a minimum of one ‘overlap’ for less than 2.29% of those domains. On our server (Dell PowerEdge R200), the common time taken to generate a cartoon on this set is 2.3 s.
Professional-origami automates the method of producing protein topology diagrams, exhibiting the relative dimension of strands and helices, the alignment of strands in a sheet and the overall positioning of sheets and helices with respect to at least one one other. Such info isn’t fully conveyed by the topological type of TOPS cartoons or HERA (PDBsum) diagrams. Our method additionally reduces pointless connector crossings and generates diagrams which are interactively editable with an editor (Dunnart). The latter method permits preservation of significant constraints such because the positions of strands in a sheet, and the connectors between SSEs, whereas the consumer edits the diagram. Professional-origami additionally permits interactive graphical development of queries to a protein substructural search system.
Discussions with Dr Tim Dwyer and Prof. Kim Marriott have assisted our work. Dr Arun Konagurthu supplied us with supply code to generate protein tableaux.
Funding: We thank the Australian Analysis Council and NICTA for assist. ARC Federation Fellow and Honorary Nationwide Well being and Medical Analysis Council Principal Analysis Fellow (to J.C.W.). Australian Postgraduate Award (to A.S.).
Battle of Curiosity: none declared.
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