| 1. |
- Chen, Pan, et al.
(författare)
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Quantifying the Contribution of the Dispersion Interaction and Hydrogen Bonding to the Anisotropic Elastic Properties of Chitin and Chitosan
- 2022
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Ingår i: Biomacromolecules. - : American Chemical Society (ACS). - 1525-7797 .- 1526-4602. ; 23:4, s. 1633-1642
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Tidskriftsartikel (refereegranskat)abstract
- The elastic tensors of chitin and chitosan allomorphs were calculated using density functional theory (DFT) with and without the dispersion correction and compared with experimental values. The longitudinal Young's moduli were 114.9 or 126.9 GPa for alpha-chitin depending on the hydrogen bond pattern: 129.0 GPa for beta-chitin and 191.5 GPa for chitosan. Furthermore, the moduli were found to vary between 17.0 and 52.8 GPa in the transverse directions and between 2.2 and 15.2 GPa in shear. Switching off the dispersion correction led to a decrease in modulus by up to 63%, depending on the direction. The transverse Young's moduli of a-chitin strongly depended on the hydroxylmethyl group conformation coupled with the dispersion correction, suggesting a synergy between hydrogen bonding and dispersion interactions. The calculated longitudinal Young's moduli were, in general, higher than experimental values obtained in static conditions, and the Poisson's ratios were lower than experimental values obtained in static conditions.
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| 2. |
- Lensink, Marc F., et al.
(författare)
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Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment
- 2023
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Ingår i: Proteins. - : WILEY. - 0887-3585 .- 1097-0134.
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Tidskriftsartikel (refereegranskat)abstract
- We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average similar to 70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.
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