Correlation between protein secondary structure, backbone bond angles, and side-chain orientations

Lundgren, Martin; Niemi, Antti J.

doi:10.1103/physreve.86.021904

Cited by 16 publications

(13 citation statements)

References 32 publications

(98 reference statements)

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“…We note clear rotamer structures: The C β , C, N and O atoms are each localised, in a manner that depends on the underlying secondary structure [ 43 ]. Both in the case of C β and N, the left-handed α-region (L-α) is a distinct rotamer which is detached from the rest.…”

Section: Methods and Resultsmentioning

confidence: 99%

“…For example, the deviation of the C β atom from its ideal position is among the validation criteria in MolProbity [ 1 ], that uses it to identify potential backbone distortions around C α . But several authors [ 43 , 44 ] have pointed out that certain variation in the values of the ϑ NC can be expected, and is in fact present in PDB data. Accordingly, the protein backbone geometry does not appear to obey the single ideal value paradigm [ 10 , 11 ]; we refer to [ 15 , 18 , 19 ] for extended analysis.…”

Section: Methods and Resultsmentioning

confidence: 99%

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A three dimensional visualisation approach to protein heavy-atom structure reconstruction

Peng

Chenani

et al. 2014

BMC Struct Biol

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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.

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Section: Methods and Resultsmentioning

confidence: 99%

Section: Methods and Resultsmentioning

confidence: 99%

A three dimensional visualisation approach to protein heavy-atom structure reconstruction

Peng

Chenani

et al. 2014

BMC Struct Biol

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“…In order to find the residues that are most affected by the disulfide bonds reductions in ORF8, we employ the visualization method described in the references, [27][28][29] where we introduced the Discrete Frenet Framework (DFF) to describe the C α trace of a protein chain.…”

Section: Local Geometry Visualizationmentioning

confidence: 99%

“…From the MD simulations on ORF8 with different disulfide bonds reduced, we find the most affected residues/segments through a new visualization technique based on the Discrete Frenet Frame (DFF). [27][28][29] Based on the conformational ensembles sampled from MD simulations, we further investigate the influences of the disulfide bonds on the binding sites between ORF8 and HLA-A using the docking method. In the end, we compared the binding affinities between ORF8 and HLA-A when different disulfide bonds in ORF8 get reduced.…”

Section: Introductionmentioning

confidence: 99%

In silico study on the effects of disulfide bonds in ORF8 of SARS-CoV-2

Cheng

Peng

2021

Preprint

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The COVID-19 epidemic, caused by virus SARS-CoV-2, has been a pandemic and threatening everyone’s health in the past two years. In SARS-CoV-2, the accessory protein ORF8 plays an important role in immune modulation. Here we present an in silico study on the effects of the disulfide bonds in ORF8, including the effects on the structures, the binding sites and free energy when ORF8 binds to the human leukocyte antigen (HLA-A). Using the explicit solvent Molecular Dynamics (MD) simulations, we collect the conformational ensembles on ORF8 with different disulfide bonds reduction schemes. With a new visualization technique on the local geometry, we analyze the effects of the disulfide bonds on the structure of ORF8. We find that the disulfide bonds have large influences on the loop regions of the surface. Moreover, by performing docking between HLA-A and the conformational ensembles of ORF8, we predict the preferred binding sites and find that most of them are little affected by the disulfide bonds.Further, we estimate the binding free energy between HLA-A and ORF8 with different disulfide bonds reductions. In the end, from the comparison with the available experimental results on the epitopes of ORF8, we validated our binding sites prediction. All the above observations may provide inspirations on inhibitor/drug design against ORF8 based on the binding pathway with HLA-A.

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“…A hierarchical Dirichlet process was used to define 20×20 neighbor-dependent Ramachandran plots [52], spreading the effect of related information to counteract small sample size. The combination of backbone and sidechain dimensions is also being explored [53, 54], uncovering relationships not seen in the simpler versions.…”

Section: Current Developments (2009-2013)mentioning

confidence: 99%

Crystallographic model validation: from diagnosis to healing

Richardson

Prisant

Richardson

2013

Current Opinion in Structural Biology

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Model validation has evolved from a passive final gatekeeping step to an ongoing diagnosis and healing process that enables significant improvement of accuracy. A recent phase of active development was spurred by the worldwide Protein Data Bank requiring data deposition and establishing Validation Task Force committees, by strong growth in high-quality reference data, by new speed and ease of computations, and by an upswing of interest in large molecular machines and structural ensembles. Progress includes automated correction methods, concise and user-friendly validation reports for referees and on the PDB websites, extension of error correction to RNA and error diagnosis to ligands, carbohydrates, and membrane proteins, and a good start on better methods for low resolution and for multiple conformations.

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Correlation between protein secondary structure, backbone bond angles, and side-chain orientations

Cited by 16 publications

References 32 publications

A three dimensional visualisation approach to protein heavy-atom structure reconstruction

A three dimensional visualisation approach to protein heavy-atom structure reconstruction

In silico study on the effects of disulfide bonds in ORF8 of SARS-CoV-2

Crystallographic model validation: from diagnosis to healing

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