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AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is "solved". However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability (ΔΔG) and function. To study the question we extracted the pLDDT and metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known ΔΔG values. Additionally, we correlated the same AlphaFold pLDDT metrics with the impact of a single mutation on structure using a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold may not be immediately applied to other problems or applications in protein folding., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Pak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Granulomatosis was induced in male Wistar rats by intravenous injection of SiO(2). The course of SiO(2) granulomatosis was cyclic in animals receiving radon baths: phase 1 was characterized by an increase in the number and size of granulomas, while during phase 2 the intensity of the inflammatory process decreased and fibrosing of granulomas progressed. No trends to alleviation of the inflammatory process were noted in rats with SiO(2) granulocytosis receiving tap water baths.

Morphologic types L1 and L2 (FAB) of acute lymphoblastic leukemia were classified by computer morphometry of bone marrow blast cells in 57 patients. Measurements were made on MOP-Videoplan Analyser (Reichert) by means of cell image contouring. The decision rule that had been deduced by us on the basis of multidimensional analysis of variance in two-cell training sets, and the selection of the following combination of the best discriminating features [the discriminant coefficients are in brackets: maximal nuclear diameter (-0.338), nuclear perimeter (-6.145), cell area (-0.044), nuclear area (1.007), relative nucleoli eccentricity (-0.279), cytoplasmic/nuclear relation (-5.920) and integral nucleoli area (-0.640)] were used for computer classification of L1 and L2 blast cells. The threshold score for discriminant function in this case was -117.766. Complete clinical remission rates in L1 ALL appeared to be higher than in L2 but remission duration in those groups did not differ significantly. The morphometric parameters of leukemic cells seem to characterize their maturity or their position in cell cycle phases and may be used in acute leukemia patient monitoring.