scholarly journals Chandrasekharan Ramakrishnan (1939–2019): The student behind the Ramachandran map

2019 ◽  
Vol 28 (11) ◽  
pp. 1920-1922
Author(s):  
Narayanaswamy Srinivasan
Keyword(s):  
Ramachandran Map

Conformational attractors on the Ramachandran map

1999 ◽  
Vol 55 (2) ◽  
pp. 506-517 ◽  
Author(s):  
Dirk Walther ◽  
Fred E. Cohen
Keyword(s):  
Protein Structures ◽  
Structural Data ◽  
Random Coil ◽  
Helical Conformation ◽  
Structure Quality ◽  
Frequency Distributions ◽  
Ramachandran Map ◽  
Structural Types ◽  
Apparent Correlation ◽  
Independent Parameters

Frequency distributions of protein backbone dihedral angles φ and ψ have been analyzed systematically for their apparent correlation with various crystallographic parameters, including the resolution at which the protein structures had been determined, the R factor and the free R factor, and the results have been displayed in novel differential Ramachandran maps. With improved sensitivity compared with conventionally derived heuristic Ramachandran maps, such differential maps automatically reveal conformational `attractors' to which φ/ψ distributions converge as the crystallographic resolution improves, as well as conformations tied specifically to low-resolution structures. In particular, backbone angular combinations associated with residues in α-helical conformation show a pronounced consolidation with substantially narrowed φ/ψ distributions at higher (better) resolution. Convergence to distinct conformational attractors was also observed for all other secondary-structural types and random-coil conformations. Similar resolution-dependent φ/ψ evolutions were obtained for different crystallographic refinement packages, documenting the absence of any significant artificial biases in the refinement programs investigated here. A comparison of differential Ramachandran maps derived for the R factor and the free R factor as independent parameters proved the better suitability of the free R factor for structure-quality assessment. The resolution-based differential Ramachandran map is available as a reference for comparison with actual protein structural data under WebMol, a Java-based structure viewing and analysis program (http://www.cmpharm.ucsf.edu/cgi-bin/webmol.pl).

On residues in the disallowed region of the Ramachandran map

Biopolymers ◽  
2002 ◽  
Vol 63 (3) ◽  
pp. 195-206 ◽  
Author(s):  
Debnath Pal ◽  
Pinak Chakrabarti
Keyword(s):  
Ramachandran Map

THE RAMACHANDRAN MAP OF MORE THAN 6,500 PERFECT POLYPEPTIDE CHAINS

2007 ◽  
Vol 02 (03n04) ◽  
pp. 267-271
Author(s):  
ZOLTÁN SZABADKA ◽  
RAFAEL ÖRDÖG ◽  
VINCE GROLMUSZ
Keyword(s):  
Protein Data Bank ◽  
Structural Information ◽  
Data Bank ◽  
Ramachandran Map ◽  
Tenfold Increase ◽  
Automated Processing ◽  
Data Points ◽  
Α Helix ◽  
The Right ◽  
Polypeptide Chains

The Protein Data Bank (PDB) is the most important depository of protein structural information, containing more than 45,000 deposited entries today. Because of its inhomogeneous structure, its fully automated processing is almost impossible. In a previous work, we cleaned and re-structured the entries in the Protein Data Bank, and from the result we have built the RS-PDB database. Using the RS-PDB database, we draw a Ramachandran-plot from 6,593 "perfect" polypeptide chains found in the PDB, containing 1,192,689 residues. This is a more than tenfold increase in the size of data analyzed before this work. The density of the data points makes it possible to draw a logarithmic heat map enhanced Ramachandran map, showing the fine inner structure of the right-handed α-helix region.

Conformational Dependence of Electronic Coupling Across Peptide Bonds: A Ramachandran Map

2010 ◽  
Vol 114 (48) ◽  
pp. 20809-20812 ◽  
Author(s):  
Joseph B. Issa ◽  
Karsten Krogh-Jespersen ◽  
Stephan S. Isied
Keyword(s):  
Electronic Coupling ◽  
Peptide Bonds ◽  
Ramachandran Map

The utility of the four-dimensional ramachandran map for the description of peptide conformations

1991 ◽  
Vol 232 ◽  
pp. 291-319 ◽  
Author(s):  
Aandrás Perczel ◽  
Márton Kajtar ◽  
John F. Marcoccia ◽  
Imre G. Csizmadia
Keyword(s):  
Ramachandran Map ◽  
Peptide Conformations

scholarly journals Limitations of the ABEGO representation: ambiguity between αα-corner and αα-hairpin

2021 ◽  
Author(s):  
Koya Sakuma
Keyword(s):  
Protein Design ◽  
Amino Acid Sequences ◽  
Coarse Grained ◽  
Dihedral Angles ◽  
Torsion Angles ◽  
Fragment Assembly ◽  
Local Conformation ◽  
Ramachandran Map ◽  
Polypeptide Backbone ◽  
Polypeptide Chains

SummaryABEGO is a coarse-grained representation for polypeptide backbone dihedral angles. The Ramachandran map is divided into four segments denoted as A, B, E, and G to represent the local conformation of polypeptide chains in the character strings. Although the ABEGO representation is widely used in structural informatics and protein design, it cannot capture minor differences in backbone dihedral angles, which potentially leads to ambiguity between two structurally distinct fragments. Here, we show a nontrivial example of two local motifs that could not be distinguished by their ABEGO representations. We found that two well-known local motifs αα-hairpins and αα-corners are both represented as α-GBB-α and thus indistinguishable in the ABEGO representation, although they show distinct arrangements of the flanking α-helices. We also found that α-GBB-α motifs caused a loss of efficiency in the ABEGO-based fragment-assembly simulations for protein backbone design. Nevertheless, we designed amino-acid sequences that were predicted to fold into the target topologies that contained these α-GBB-α motifs. Our finding that certain local motifs bottleneck the ABEGO-based fragment-assembly simulations for construction of backbone structures suggests that finer representations of backbone torsion angles are required for efficiently generating diverse topologies containing such indistinguishable local motifs.

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