Representing protein and peptide structures with parallel-coordinates

Becker, Oren M.

doi:10.1002/(sici)1096-987x(19971130)18:15<1893::aid-jcc5>3.0.co;2-j

Cited by 9 publications

(6 citation statements)

References 29 publications

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“…The different secondary structural elements of the investigated peptides can be illustrated applying the parallel‐coordinates representation 24. For this graphical depiction of the conformers, the axes drawn parallel to each other correspond to the Φ and Ψ torsion angles of the consecutive amino acids.…”

Section: Resultsmentioning

confidence: 99%

Comparative study of SP[6–11] and its analogs using simulated annealing

et al. 2005

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In this study we compared the steric structures of the bioactive part of substance P (SP[6-11]) and its analogs (NY3460 and pHOPA-SP5). The molecular dynamics-simulated annealing method was used to explore the conformational space, and the structural differences and similarities of these molecules were identified. For the three peptides, the conformational distributions were represented in Ramachandran density plots. The occurring secondary structural elements of the investigated molecules were identified, namely alpha-Helix, type III beta-Turn, gamma-Turn, and inverse gamma-Turn. For SP[6-11] and its two analogs, different intramolecular interactions (H-bonds between the main-chain atoms, aromatic-aromatic interactions, and amino-aromatic interactions) that can stabilize the various conformations of the three peptides were investigated. Detailed examination of these intramolecular interactions revealed that H-bonds between the main-chain atoms are relevant in the determination and stabilization of the conformer structures of the peptides, while the aromatic-aromatic interactions do not play an important stabilizing role. Furthermore, in the conformers of NY3460 and pHOPA-SP5, different types of amino-aromatic interactions were identified that contribute to the formation of the various structures of these peptides. For all three molecules, the orientations of the side chains were investigated and the rotamer populations were determined.

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Section: Resultsmentioning

confidence: 99%

Comparative study of SP[6–11] and its analogs using simulated annealing

et al. 2005

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“…Becker [2] visualizes structural similarities of compounds by mapping the compound attributes to the axes of parallel coordinates plots. The approach, however, does not integrate other data sources.…”

Section: Related Workmentioning

confidence: 99%

ConTour: Data-Driven Exploration of Multi-Relational Datasets for Drug Discovery

Partl

Lex

Streit

et al. 2014

IEEE Trans. Visual. Comput. Graphics

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Large scale data analysis is nowadays a crucial part of drug discovery. Biologists and chemists need to quickly explore and evaluate potentially effective yet safe compounds based on many datasets that are in relationship with each other. However, there is a lack of tools that support them in these processes. To remedy this, we developed ConTour, an interactive visual analytics technique that enables the exploration of these complex, multi-relational datasets. At its core ConTour lists all items of each dataset in a column. Relationships between the columns are revealed through interaction: selecting one or multiple items in one column highlights and re-sorts the items in other columns. Filters based on relationships enable drilling down into the large data space. To identify interesting items in the first place, ConTour employs advanced sorting strategies, including strategies based on connectivity strength and uniqueness, as well as sorting based on item attributes. ConTour also introduces interactive nesting of columns, a powerful method to show the related items of a child column for each item in the parent column. Within the columns, ConTour shows rich attribute data about the items as well as information about the connection strengths to other datasets. Finally, ConTour provides a number of detail views, which can show items from multiple datasets and their associated data at the same time. We demonstrate the utility of our system in case studies conducted with a team of chemical biologists, who investigate the effects of chemical compounds on cells and need to understand the underlying mechanisms.

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“…Although these pairwise comparisons are informative and allow a complete description of backbone conformational space for dipeptides, in the case of larger peptides it would be desirable to be able to view relevant information for all torsion angles and percentage contributions on a single plot. The application of some variant of parallel coordinate plots to visualize such complex, multidimensional data could prove valuable here [22].…”

Section: Conformational Preferences Of Tripeptidesmentioning

confidence: 99%

“…However, as useful as these have proved to be for displaying conformational information for dipeptides, their limitations in their current form are highlighted with tripeptides in that at least two plots are needed to adequately display the necessary information. The need to be able to present this complex, conformational data on a single plot has been partly addressed by Becker using parallel plots [22], although there is still no easy way of including conformer weighting in the form of percentage contribution. These limitations will need to be overcome to more easily understand and graphically display oligopeptide conformations.…”

Section: Bioactive Conformationsmentioning

confidence: 99%

Predominant torsional forms adopted by oligopeptide conformers in solution: parameters for molecular recognition

Marshall

Grail

Payne

2001

Journal of Peptide Science

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In this paper, we describe the predominant conformational forms adopted by tripeptides and higher oligopeptides in aqueous solution. About 50 tripeptides and almost 20 higher oligopeptides (4-6 residues) were subjected to conformational analysis using SYBYL Random Search. As with dipeptides (Grail BM, Payne JW. J. Peptide Sci. 2000; 6: 186-199), both tripeptides and higher oligopeptides were found to occupy relatively few combinations of psi-phi space that were distinct from those associated with predominant protein secondary structures (e.g. helices and beta-sheets). Again, the preferred psi (psi) values for the first residue (i - 1) were in sectors encompassed by the ranges from +150 degrees to +/-180 degrees, +60 degrees to +90 degrees and -60 degrees to -90 degrees, which were combined with preferred phi (phi) values for the second residue (i) in sectors with ranges from -150 degrees to +/-180 degrees, -60 degrees to -90 degrees and +30 degrees to +60 degrees. It was notable that tripeptides and, to a greater extent, higher oligopeptides adopted an initial psi (psi) (Tor2) from +150 degrees to +/-180 degrees. For tripeptides, their N-C distances (distance between N-terminal nitrogen and C-terminal carbon atoms) distribute about 6.5 A to give shorter, 'folded' conformers that are similar in length to dipeptides, and longer, 'extended' conformers that are distinct. Furthermore, for higher oligopeptides, their N-C distances did not increment in relation to their increasing number of residues and short, 'folded' conformers were still present. These findings have a bearing upon the recognition of these molecules as substrates for widely distributed peptidases and peptide transporters.

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Representing protein and peptide structures with parallel-coordinates

Cited by 9 publications

References 29 publications

Comparative study of SP[6–11] and its analogs using simulated annealing

Comparative study of SP[6–11] and its analogs using simulated annealing

ConTour: Data-Driven Exploration of Multi-Relational Datasets for Drug Discovery

Predominant torsional forms adopted by oligopeptide conformers in solution: parameters for molecular recognition

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