Improving AlphaFold modeling using implicit information from experimental density maps

Machine learning prediction algorithms such as AlphaFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including experimental information, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt based on experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We find that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for crystallographic and electron cryo-microscopy map interpretation.

Nb/Sn Liquid-Solid Reactive Diffusion Couples and Their Application to Determination of Phase Equilibria and Interdiffusion Coefficients of Nb-Sn Binary System

Nb3Sn plays an irreplaceable role in superconducting parts due to its stable performance under high field conditions. Accurate phase equilibria and interdiffusion coefficients are of great significance for designing novel Nb3Sn superconductors. However, the related experimental information is still in a state of scarcity because of the difficulty in fabrication of Nb-Sn alloys caused by the large difference in melting points of Nb and Sn. In this paper, a simple but pragmatic approach was first proposed to prepare the Nb/Sn liquid-solid reactive diffusion couples (LSDCs) at 1100 °C and 1200 °C, of which the phase identification of the formed layer and the measurement of composition-distance profiles were conducted. The formed layer in Nb/Sn LSDCs was confirmed to be Nb3Sn compound. While the measured composition profiles were employed to determine the phase equilibria according to the local equilibrium hypothesis and the interdiffusion coefficients with an aid of the latest version of HitDIC software. The determined phase equilibria of Nb3Sn, (Nb) and liquid show good agreement with the assessed phase diagram. While the calculated interdiffusion coefficients and activation energy for diffusion in Nb3Sn are consistent with both experimental and theoretical data in the literature. Moreover, the growth of the formed Nb3Sn layer in Nb/Sn LSDCs was also found to be diffusion controlled. All the obtained phase equilibria and interdiffusion coefficients are of great value for further thermodynamic and kinetic modeling of the Nb-Sn system. Furthermore, it is anticipated that the presently proposed approach of fabricating liquid-solid reactive diffusion couple should serve as a general one for various alloy systems with large differences in melting points.

Justification of the Application of Resource-Saving Technology for the Restoration of Metal-Intensive Rear Semi-Axles of Trucks Using Hot Plastic Deformation

The article is devoted to the substantiation of technological foundations for the restoration of extremely worn-out, metal-consuming, and resource-consuming parts, in a method consisting of applying a compensating metal wear with subsequent plastic deformation. Currently, there are no technologies for their restoration in a repair facility that guarantee the resilience of the factory product. The proposed technological process of repair consists of butt welding onto the end of the spline semi-axle shank, compensating for the wear of the metal, the volume of which takes into account the losses resulting from the wear of the slots, as well as allowances for their machining. In the example of forging the axle shaft of a truck’s driving axle, the regularities of the plastic flow of metal during part deformation in the stamp are revealed. In the process of hot volumetric upsetting of long cylindrical parts with a variable diameter, it is important to know the possible directions of metal movements, as well as the energy-power characteristics of the process at various stages of forging. The evaluation criteria of the level of perfection of the technology were indicators of resource conservation and efficiency of the recovery route. The technological direction of the conducted research was analyzed, step by step, from the standpoint of saving repair materials and energy resources. The results of theoretical studies are crucial in the design of die tooling, for the manufacture of blanks, when restoring the rear axle shafts of trucks with pressure. Production tests carried out on the models, obtained as a result of mathematical processing of experimental data, confirmed the reliability of the experimental information. The introduction of the proposed set of repair equipment for the restoration of semi-axles will allow the formation of additional production in the region for the recycling of worn-out metal-intensive steel parts of agricultural machinery.

EXPERIMENTAL INVESTIGATION INTO THE EFFECTS OF REDUCED VERTICAL CENTRE OF GRAVITY OF AN ARTICULATED CONCRETE MATTRESS IN CURRENT FLOW

An articulated concrete mattress model has been utilised to investigate the effects of reduced vertical centre of gravity on the stability of a 400 series block. Experimental testing was conducted at the AMC CWC, Beauty Point. To determine the effects that a reduced centre of gravity has on stability, the 3 by 3 articulated concrete mattress model was subject to pure uniform current flow. The subsequent forces were analysed with a six degree of freedom underwater force sensor. In order to gain a range of real world scenarios, the experimental model was tested at six flow angles ranging from -15 degrees through to 60 degrees, at 15 degree increments. Additionally, five fluid velocities starting at 0.6 m/s through to 1.4 m/s, at 0.2 m/s increments were investigated. These results explain how the inversion of a 400 series block increases its hydrodynamic coefficients and subsequently decreases its stability performance in current flow. Ultimately, this study provides experimental information for the installation of 400 series articulated concrete mattresses in the inverted orientation.

Towards More Realistic Models

This chapter is devoted to the presentation of a more realistic version of the model, Risk and Rumours, which extends the previous, theoretical version (Routes and Rumours) by including additional empirical and experimental information following the process described in Part II of this book. We begin by offering a reflection on the integration of the five elements of the modelling process, followed by a more detailed description of the Risk and Rumours model, and how it differs from the previous version. Subsequently, we present selected results of the uncertainty and sensitivity analysis, enabling us to make further inference on the information gaps and areas for potential data collection. We also present model calibration for an empirically grounded version of the model, Risk and Rumours with Reality. In that way, we can evaluate to what extent the iterative modelling process has enabled a reduction in the uncertainty of the migrant route formation. In the final part of the chapter, we reflect on the model-building process and its implementation.

Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction

Specific proteins and processes have been identified in post-myocardial infarction (MI) pathological remodeling, but a comprehensive understanding of the complete molecular evolution is lacking. We generated microarray data from swine heart biopsies at baseline and 6, 30, and 45 days after infarction to feed machine-learning algorithms. We cross-validated the results using available clinical and experimental information. MI progression was accompanied by the regulation of adipogenesis, fatty acid metabolism, and epithelial–mesenchymal transition. The infarct core region was enriched in processes related to muscle contraction and membrane depolarization. Angiogenesis was among the first morphogenic responses detected as being sustained over time, but other processes suggesting post-ischemic recapitulation of embryogenic processes were also observed. Finally, protein-triggering analysis established the key genes mediating each process at each time point, as well as the complete adverse remodeling response. We modeled the behaviors of these genes, generating a description of the integrative mechanism of action for MI progression. This mechanistic analysis overlapped at different time points; the common pathways between the source proteins and cardiac remodeling involved IGF1R, RAF1, KPCA, JUN, and PTN11 as modulators. Thus, our data delineate a structured and comprehensive picture of the molecular remodeling process, identify new potential biomarkers or therapeutic targets, and establish therapeutic windows during disease progression.

Validation of a full-plasma integrated modeling approach on ASDEX Upgrade

In this work we present the extensive validation of a refined version of the integrated model based on engineering parameters (IMEP) introduced in reference (Luda et al 2020 Nucl. Fusion 60 036023). The modeling workflow is now fully automated, computationally faster thanks to the reduced radial resolution of the TGLF calculation, and it includes the modeling of the toroidal rotation, which was still taken from experimental measurements in our previous work. The updated model maintains the same accuracy as its previous version when tested on the cases presented in the initial publication. The confined plasma, from the magnetic axis to the separatrix, is simulated without using any experimental information from profiles measurements, and the inputs of IMEP are the same engineering parameters used when programming a plasma discharge. The model validation database consists of 50 ASDEX Upgrade (AUG) stationary (over a few energy confinement time) H-mode phases, which largely cover the entire AUG operational domain. The prediction of IMEP is compared with experimental measurements and with scaling laws, such as the IPB98(y,2), the ITPA20-IL, and AUG specific regressions. This modeling framework has proven to be very accurate over the entire set of 50 cases, with a significantly lower mean relative error with respect to each of the scaling laws considered, accurately reproducing the change in pedestal and core confinement caused by a change in plasma current, heating power, fueling rate, triangularity, magnetic field, NBI voltage (i.e. the effect of a change in the core particle source), and heating mix (e.g. correctly predicting the effect on confinement caused by a change in T e/T i). Plasma confinement is correctly described by IMEP also for two particular operating regimes, such as the ITER baseline scenario, and the QCE regime (quasi continuous exhaust, also referred as type-II and small ELMs). This work clearly demonstrates the power of this approach in pulling out physics mechanisms to interpret subtle interdependencies and that a 1D integrated model can reproduce experimental results over very large parameter variations with a higher accuracy than any statistical regression. This approach has therefore the potential to improve the prediction of the fusion performance in future tokamak reactors.

Using BERT to identify drug-target interactions from whole PubMed

Background: Drug-target interactions (DTIs) are critical for drug repurposing and elucidation of drug mechanisms, and are manually curated by large databases, such as ChEMBL, BindingDB, DrugBank and DrugTargetCommons. However, the number of articles providing this data (~0.1 million) likely constitutes only a fraction of all articles on PubMed that contain experimentally determined DTIs. Finding such articles and extracting the experimental information is a challenging task, and there is a pressing need for systematic approaches to assist the curation of DTIs. To this end, we propose Bidirectional Encoder Representations from Transformers (BERT) to identify such articles. Because DTI data intimately depends on the type of assays used to generate it, we also aimed to incorporate functions to predict the assay format. Results: Our novel method identified ~2.1 million articles (along with drug and protein information) that are not previously included in public DTI databases. Using 10-fold cross-validation, we obtained ~99% accuracy for identifying articles containing quantitative drug-target profiles. The accuracy for the prediction of assay format is ~90%, which leaves room for improvement in future studies. Conclusion: The BERT model in this study is robust and the proposed pipeline can be used to identify previously overlooked articles containing quantitative DTIs. Overall, our method provides a significant advancement in machine-assisted DTI extraction and curation. We expect it to be a useful addition to drug mechanism discovery and repurposing.

When Order Meets Disorder: Modeling and Function of the Protein Interface in Fuzzy Complexes

The degree of proteins structural organization ranges from highly structured, compact folding to intrinsic disorder, where each degree of self-organization corresponds to specific functions: well-organized structural motifs in enzymes offer a proper environment for precisely positioned functional groups to participate in catalytic reactions; at the other end of the self-organization spectrum, intrinsically disordered proteins act as binding hubs via the formation of multiple, transient and often non-specific interactions. This review focusses on cases where structurally organized proteins or domains associate with highly disordered protein chains, leading to the formation of interfaces with varying degrees of fuzziness. We present a review of the computational methods developed to provide us with information on such fuzzy interfaces, and how they integrate experimental information. The discussion focusses on two specific cases, microtubules and homologous recombination nucleoprotein filaments, where a network of intrinsically disordered tails exerts regulatory function in recruiting partner macromolecules, proteins or DNA and tuning the atomic level association. Notably, we show how computational approaches such as molecular dynamics simulations can bring new knowledge to help bridging the gap between experimental analysis, that mostly concerns ensemble properties, and the behavior of individual disordered protein chains that contribute to regulation functions.