Use of evolutionary information in the fitting of atomic level protein models in low resolution cryo-EM map of a protein assembly improves the accuracy of the fitting

Joseph, Agnel Praveen; Swapna, Lakshmipuram S.; Rakesh, Ramachandran; Srinivasan, Narayanaswamy

doi:10.1016/j.jsb.2016.07.012

Cited by 11 publications

(10 citation statements)

References 82 publications

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“…In this way, one can find biologically more meaningful solutions by sampling more relevant conformations with reduced simulation time. The use of evolutionary conservation of residues is already being used to detect incorrectly fitted proteins [ 103 , 104 ] in cryo-EM maps, to predict protein structures [ 105 , 106 ] and druggable interfaces of protein–protein interactions [ 107 ].…”

Section: Discussionmentioning

confidence: 99%

Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model

Kim

Sanbonmatsu

2017

Bioscience Reports

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Section: Discussionmentioning

confidence: 99%

Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model

Kim

Sanbonmatsu

2017

Bioscience Reports

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“…The most obvious application is therefore to assist in the interpretation of density for multisubunit complexes. Proteins that are significantly anisotropic can often be fitted quite reliably even at lower density, but three-dimensional forms with fewer features often fit equally well to a map or envelope in several ways (Joseph et al, 2016). Disambiguating these situations using sequence conservation has recently been explored (Joseph et al, 2016), but predicted contacts arguably offer a more direct signal of intermolecular interaction and are independent of existing interaction information (Segura et al, 2016).…”

Section: Fitting Structures and Tracing Sequences In Lower Resolutionmentioning

confidence: 99%

“…Proteins that are significantly anisotropic can often be fitted quite reliably even at lower density, but three-dimensional forms with fewer features often fit equally well to a map or envelope in several ways (Joseph et al, 2016). Disambiguating these situations using sequence conservation has recently been explored (Joseph et al, 2016), but predicted contacts arguably offer a more direct signal of intermolecular interaction and are independent of existing interaction information (Segura et al, 2016). For example, in the cytochrome bd oxidase work mentioned above, covariation information was used to confirm the intermolecular interactions resulting from the placement of the covariance-assisted ab initio models (Safarian et al, 2016).…”

Section: Fitting Structures and Tracing Sequences In Lower Resolutionmentioning

confidence: 99%

Applications of contact predictions to structural biology

Šimkovic

Овчинников

Baker

et al. 2017

IUCrJ

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Evolutionary pressure on residue interactions, intramolecular or intermolecular, that are important for protein structure or function can lead to covariance between the two positions. Recent methodological advances allow much more accurate contact predictions to be derived from this evolutionary covariance signal. The practical application of contact predictions has largely been confined to structural bioinformatics, yet, as this work seeks to demonstrate, the data can be of enormous value to the structural biologist working in X-ray crystallography, cryo-EM or NMR. Integrative structural bioinformatics packages such as Rosetta can already exploit contact predictions in a variety of ways. The contribution of contact predictions begins at construct design, where structural domains may need to be expressed separately and contact predictions can help to predict domain limits. Structure solution by molecular replacement (MR) benefits from contact predictions in diverse ways: in difficult cases, more accurate search models can be constructed using ab initio modelling when predictions are available, while intermolecular contact predictions can allow the construction of larger, oligomeric search models. Furthermore, MR using supersecondary motifs or large-scale screens against the PDB can exploit information, such as the parallel or antiparallel nature of any -strand pairing in the target, that can be inferred from contact predictions. Contact information will be particularly valuable in the determination of lower resolution structures by helping to assign sequence register. In large complexes, contact information may allow the identity of a protein responsible for a certain region of density to be determined and then assist in the orientation of an available model within that density. In NMR, predicted contacts can provide long-range information to extend the upper size limit of the technique in a manner analogous but complementary to experimental methods. Finally, predicted contacts can distinguish between biologically relevant interfaces and mere lattice contacts in a final crystal structure, and have potential in the identification of functionally important regions and in foreseeing the consequences of mutations.

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“…The features that characterise the interfaces can be used to build an overall metric, and while being density-independent, to provide an additional complementary quality measure to assess the quality of the modelled assembly in the cryo-EM map. Features that have been shown to be discriminatory in identifying biological ('native-like') interfaces are, for example, conservation of residues present at interface [12][13][14][15][16] , shape 17,18 and electrostatic complementarity 19,20 , residue contact pairs 21,22 , types of interactions [23][24][25][26] , and interface size and area 25,27−29 . Although these features are useful in identifying the quality of interfaces, these derivations are often done in isolation, and largely relies on the expertise of the scientists for validation based on their experience. As such, computational algorithms for computing scores based on the metrics and features described above, ignores one major aspect -extraction and reuse of the knowledge from different datasets.…”

Section: Introductionmentioning

confidence: 99%

Assessment of protein-protein interfaces in cryo-EM derived assemblies

Malhotra

Joseph

Thiyagalingam

et al. 2020

Preprint

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Structures of macromolecular assemblies derived from cryo-EM maps often contain errors that become more abundant with decreasing resolution. Despite efforts in the cryo-EM community to develop metrics for the map and atomistic model validation, thus far, no specific scoring metrics have been applied systematically to assess the interface between the assembly subunits. Here, we have assessed protein-protein interfaces in macromolecular assemblies derived by cryo-EM. To this end, we developed PI-score, a density-independent machine learning-based metric, trained using protein-protein interfaces’ features in high-resolution crystal structures. Using PI-score, we were able to identify errors at interfaces in the PDB-deposited cryo-EM structures (including SARS-CoV-2 complexes) and in the models submitted for cryo-EM targets in CASP13 and the EM model challenge. Some of the identified errors, especially at medium-to-low resolution structures, were not captured by density-based assessment scores. Our method can therefore provide a powerful complementary assessment tool for the increasing number of complexes solved by cryo-EM.

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Use of evolutionary information in the fitting of atomic level protein models in low resolution cryo-EM map of a protein assembly improves the accuracy of the fitting

Cited by 11 publications

References 82 publications

Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model

Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model

Applications of contact predictions to structural biology

Assessment of protein-protein interfaces in cryo-EM derived assemblies

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