Possible Implications of AlphaFold2 for Crystallographic Phasing by Molecular Replacement

Aj, McCoy; Sammito, Massimo; Rj, Read

doi:10.1101/2021.05.18.444614

Cited by 17 publications

(20 citation statements)

References 56 publications

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“…For R1052-D2, R1053v1, R1082, and R1091-D2. However, in each of these cases either the Ample MR pipeline 36 or the Phaser-voyager pipeline 37 was able to succeed using AlphaFold2 models.…”

Section: Success Of the Refined Models In Mrmentioning

confidence: 99%

Assessing the utility of CASP14 models for molecular replacement

et al. 2021

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The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real-world application. In CASP7, the metric for molecular replacement assessment involved full likelihood-based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood-based rigid-body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined log-likelihood-gain (LLG) score. This enabled multi-copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative-expected-LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X-ray, NMR or cryo-EM.We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.

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“…For R1052-D2, R1053v1, R1082, and R1091-D2. However, in each of these cases either the Ample MR pipeline 36 or the Phaser-voyager pipeline 37 was able to succeed using AlphaFold2 models.…”

Section: Success Of the Refined Models In Mrmentioning

confidence: 99%

Assessing the utility of CASP14 models for molecular replacement

et al. 2021

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“…AlphaFold2 is being suggested to be exploited in molecular replacement protocol aiding experimental structure determination 43 . One of our results, that the register shift in ABCG8 NBD is corrected by AF2 (Fig.…”

Section: Discussionmentioning

confidence: 99%

AlphaFold2 transmembrane protein structure prediction shines

Hegedüs

Geisler

Lukacs

et al. 2021

Preprint

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Transmembrane (TM) proteins are major drug targets, indicated by the high percentage of prescription drugs acting on them. For a rational drug design and an understanding of mutational effects on protein function, structural data at atomic resolution are required. However, hydrophobic TM proteins often resist experimental structure determination and in spite of the increasing number of cryo-EM structures, the available TM folds are still limited in the Protein Data Bank. Recently, the DeepMind’s AlphaFold2 machine learning method greatly expanded the structural coverage of sequences, with high accuracy. Since the employed algorithm did not take specific properties of TM proteins into account, the validity of the generated TM structures should be assessed. Therefore, we investigated the quality of structures at genome scales, at the level of ABC protein superfamily folds, and also in specific individual cases. We tested template-free structure prediction also with a new TM fold, dimer modeling, and stability in molecular dynamics simulations. Our results strongly suggest that AlphaFold2 performs astoundingly well in the case of TM proteins and that its neural network is not overfitted. We conclude that a careful application of its structural models will advance TM protein associated studies at an unexpected level.

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“…One required manual splitting of model domains. In a separate study 35 , in depth MR trials using only the AlphaFold2 models were carried out when data had become available for 34 crystal structures, from which 72 EUs had been defined. Of the 34 structures, 31 could be solved with AlphaFold2 models, 2 could be solved partially and one could not (though it could be solved with generic helix models), at least confirming the result for AlphaFold2 models.…”

Section: Discussionmentioning

confidence: 99%

Assessing the utility of CASP14 models for molecular replacement

Millán

Keegan

Pereira

et al. 2021

Preprint

Self Cite

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The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real-world application. In CASP7, the metric for molecular replacement assessment involved full likelihood-based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood-based rigid-body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined likelihood (LLG) score. This enabled multi-copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative-expected-LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X-ray, NMR or cryo-EM. We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.

show abstract

Possible Implications of AlphaFold2 for Crystallographic Phasing by Molecular Replacement

Cited by 17 publications

References 56 publications

Assessing the utility of CASP14 models for molecular replacement

Assessing the utility of CASP14 models for molecular replacement

AlphaFold2 transmembrane protein structure prediction shines

Assessing the utility of CASP14 models for molecular replacement

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