Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence
. This problem is of fundamental importance as the structure of a protein ...largely determines its function
; however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures
. Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force
that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction
(CASP13)-a blind assessment of the state of the field-AlphaFold created high-accuracy structures (with template modelling (TM) scores
of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined
.
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FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Density functional theory describes matter at the quantum level, but all popular approximations suffer from systematic errors that arise from the violation of mathematical properties of the exact ...functional. We overcame this fundamental limitation by training a neural network on molecular data and on fictitious systems with fractional charge and spin. The resulting functional, DM21 (DeepMind 21), correctly describes typical examples of artificial charge delocalization and strong correlation and performs better than traditional functionals on thorough benchmarks for main-group atoms and molecules. DM21 accurately models complex systems such as hydrogen chains, charged DNA base pairs, and diradical transition states. More crucially for the field, because our methodology relies on data and constraints, which are continually improving, it represents a viable pathway toward the exact universal functional.
We describe AlphaFold, the protein structure prediction system that was entered by the group A7D in CASP13. Submissions were made by three free‐modeling (FM) methods which combine the predictions of ...three neural networks. All three systems were guided by predictions of distances between pairs of residues produced by a neural network. Two systems assembled fragments produced by a generative neural network, one using scores from a network trained to regress GDT_TS. The third system shows that simple gradient descent on a properly constructed potential is able to perform on par with more expensive traditional search techniques and without requiring domain segmentation. In the CASP13 FM assessors' ranking by summed z‐scores, this system scored highest with 68.3 vs 48.2 for the next closest group (an average GDT_TS of 61.4). The system produced high‐accuracy structures (with GDT_TS scores of 70 or higher) for 11 out of 43 FM domains. Despite not explicitly using template information, the results in the template category were comparable to the best performing template‐based methods.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Global warming, air pollution, and energy insecurity are three of the greatest problems facing humanity. Roadmaps are developed and grid analyses are performed here for 145 countries to address these ...problems. The roadmaps call for a 100% transition of all-purpose business-as-usual (BAU) energy to wind-water-solar (WWS) energy, efficiency, and storage, ideally by 2035, but by no later than 2050, with at least 80% by 2030. Grid stability analyses find that the countries, grouped into 24 regions, can exactly match demand with 100% WWS supply and storage, from 2050-2052. Worldwide, WWS reduces end-use energy by 56.4%, private annual energy costs by 62.7% (from $17.8 to $6.6 trillion per year), and social (private plus health plus climate) annual energy costs by 92.0% (from $83.2 to $6.6 trillion per year) at a present-value cost of ∼$61.5 trillion. The mean payback times of the capital cost due to energy- and social-cost savings are 5.5 and 0.8 years, respectively. WWS is estimated to create 28.4 million more long-term, full-time jobs than lost worldwide and may need only ∼0.17% and ∼0.36% of world land for new footprint and spacing, respectively. Thus, WWS requires less energy, costs less, and creates more jobs than BAU. Sensitivity test indicate the following. Increasing district heating and cooling may reduce costs by allowing flexible loads to replace inflexible loads, thereby replacing electricity storage and overgeneration with low-cost heat storage. A battery cost that is 50% higher than in the base case increases mean overall energy costs by only 3.2 (0.03-14.5)%. Almost all regions need fewer hours of load shifting than assumed in the base case, suggesting that actual load shifting may be easier than assumed. Increasing the use of electricity for hydrogen fuel-cell-electric vehicles instead of for battery-electric vehicles increases overall cost in most regions tested, due to the greater efficiency of battery-electric vehicles, but decreases overall cost in some regions by improving grid stability. Finally, shifting battery vehicle charging from day-night to mostly day charging reduces cost in the regions tested; shifting to mostly night charging increases cost. Ninety-five percent of the technologies needed to implement the plans proposed are already commercial.
Timeline to transition 145 countries to 100% wind-water-solar by 2035, with 80% by 2030.
There has been a long wait for the Theory of Sampling (TOS) to make any inroads within the medical profession. Indeed, a few intrepid explorers have tried, but this has resulted only in getting ...nowhere fast...so far. Here, Alexander lays out what can only be described as a paradigm shift within the field of tumor diagnostics, nothing less. And it all came about because of a young scientist's inspired application of the TOS; indeed "all that was needed" was...a blender.
Characteristic Subgroups Nelson, Alexander M.
Formalized mathematics,
07/2022, Volume:
30, Issue:
2
Journal Article
Peer reviewed
Open access
We formalize in Mizar 1, 2 the notion of characteristic subgroups using the definition found in Dummit and Foote 3, as subgroups invariant under automorphisms from its parent group. Along the way, we ...formalize notions of Automorphism and results concerning centralizers. Much of what we formalize may be found sprinkled throughout the literature, in particular Gorenstein 4 and Isaacs 5. We show all our favorite subgroups turn out to be characteristic: the center, the derived subgroup, the commutator subgroup generated by characteristic subgroups, and the intersection of all subgroups satisfying a generic group property.
The Ca
-independent phospholipases, designated as group VI iPLA
s, also referred to as PNPLAs due to their shared homology with patatin, include the β, γ, δ, ε, ζ, and η forms of the enzyme. The iPLA
...s are ubiquitously expressed, share a consensus GXSXG catalytic motif, and exhibit organelle/cell-specific localization. Among the iPLA
s, iPLA
β has received wide attention as it is recognized to be involved in membrane remodeling, cell proliferation, cell death, and signal transduction. Ongoing studies implicate participation of iPLA
β in a variety of disease processes including cancer, cardiovascular abnormalities, glaucoma, and peridonditis. This review will focus on iPLA
β and its links to male fertility, neurological disorders, metabolic disorders, and inflammation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Invadopodia are actin-rich subcellular protrusions with associated proteases used by cancer cells to degrade extracellular matrix (ECM)
1. Molecular components of invadopodia include branched ...actin-assembly proteins, membrane trafficking proteins, signaling proteins, and transmembrane proteinases
1. Similar structures exist in nontransformed cells, such as osteoclasts and dendritic cells, but are generally called podosomes and are thought to be more involved in cell-matrix adhesion than invadopodia
2–4. Despite intimate contact with their ECM substrates, it is unknown whether physical or chemical ECM signals regulate invadopodia function. Here, we report that ECM rigidity directly increases both the number and activity of invadopodia. Transduction of ECM-rigidity signals depends on the cellular contractile apparatus
5–7, given that inhibition of nonmuscle myosin II, myosin light chain kinase, and Rho kinase all abrogate invadopodia-associated ECM degradation. Whereas myosin IIA, IIB, and phosphorylated myosin light chain do not localize to invadopodia puncta, active phosphorylated forms of the mechanosensing proteins p130Cas (Cas) and focal adhesion kinase (FAK) are present in actively degrading invadopodia, and the levels of phospho-Cas and phospho-FAK in invadopodia are sensitive to myosin inhibitors. Overexpression of Cas or FAK further enhances invadopodia activity in cells plated on rigid polyacrylamide substrates. Thus, in invasive cells, ECM-rigidity signals lead to increased matrix-degrading activity at invadopodia, via a myosin II-FAK/Cas pathway. These data suggest a potential mechanism, via invadopodia, for the reported correlation of tissue density with cancer aggressiveness.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The aim of this study was to determine the prevalence of MB2 canals in permanent maxillary molars utilising CBCT; in patients attending a university hospital. A total of 200 patient scans, (100 ...female and 100 male patients), were enrolled in the study. In total, 800 teeth were analysed, and teeth with additional canals in their MB roots (MB2) were identified. First maxillary molar teeth exhibited the highest prevalence of MB2 canals, 92% and 87%, for teeth 16 and 26, respectively. Second maxillary molar teeth showed a lower prevalence of MB2 canals, 69% and 65%, for the 17 and 27, respectively. There were no associations of significance between the prevalence of MB2 canals and patient age or gender. Root morphology and anatomy of permanent maxillary first and second molar teeth was found to be highly variable. The prevalence of additional canals in the MB roots is a frequent finding which has previously been underreported.
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CMK, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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