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machine learning algorithm alphafold2  (Deepmind Technologies Ltd)

 
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    Structured Review

    Deepmind Technologies Ltd machine learning algorithm alphafold2
    Molecular characterisation of HCO_011565 and docking with UMW-868. (A) Structure of HCO_011565 protein predicted in silico using the <t>Alphafold2</t> algorithm. The per-residue confidence scores (pLDDT; left to right) for individual sections of the protein are indicated. (B) Transcription and expression profiles for the gene encoding HCO_011565 in different developmental stages/sexes of Haemonchus contortus larvae: eggs, first-, second- and third-stage larvae (L1, L2 and L3, respectively), exsheathed third-stage larvae (xL3s), fourth-stage larvae (L4s), female and male L4s (L4f and L4m, respectively), and female and male adults (Af and Am, respectively). Heatmaps indicate levels of transcription/expression: red indicates moderate to high transcription/expression; green is low expression; and grey indicates that expression was not detected. (C) Three-dimensional structure of the protein HCO_011565 and its interaction with compound UMW-868; the inset shows the positioning of UMW-868 in the pocket predicted within HCO_011565. (D) Phylogenetic relationship of protein HCO_011565 with its orthologs in five other species of nematode (left) and the structural models of these orthologs predicted using Alphafold (right).
    Machine Learning Algorithm Alphafold2, supplied by Deepmind Technologies Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/machine+learning+algorithm+alphafold2/alphafold/pmc09616048-228-9-23
    Average 90 stars, based on 1 article reviews
    machine learning algorithm alphafold2 - by Bioz Stars, 2026-11
    90/100 stars

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    1) Product Images from "Thermal proteome profiling reveals Haemonchus orphan protein HCO_011565 as a target of the nematocidal small molecule UMW-868"

    Article Title: Thermal proteome profiling reveals Haemonchus orphan protein HCO_011565 as a target of the nematocidal small molecule UMW-868

    Journal: Frontiers in Pharmacology

    doi: 10.3389/fphar.2022.1014804

    Molecular characterisation of HCO_011565 and docking with UMW-868. (A) Structure of HCO_011565 protein predicted in silico using the Alphafold2 algorithm. The per-residue confidence scores (pLDDT; left to right) for individual sections of the protein are indicated. (B) Transcription and expression profiles for the gene encoding HCO_011565 in different developmental stages/sexes of Haemonchus contortus larvae: eggs, first-, second- and third-stage larvae (L1, L2 and L3, respectively), exsheathed third-stage larvae (xL3s), fourth-stage larvae (L4s), female and male L4s (L4f and L4m, respectively), and female and male adults (Af and Am, respectively). Heatmaps indicate levels of transcription/expression: red indicates moderate to high transcription/expression; green is low expression; and grey indicates that expression was not detected. (C) Three-dimensional structure of the protein HCO_011565 and its interaction with compound UMW-868; the inset shows the positioning of UMW-868 in the pocket predicted within HCO_011565. (D) Phylogenetic relationship of protein HCO_011565 with its orthologs in five other species of nematode (left) and the structural models of these orthologs predicted using Alphafold (right).
    Figure Legend Snippet: Molecular characterisation of HCO_011565 and docking with UMW-868. (A) Structure of HCO_011565 protein predicted in silico using the Alphafold2 algorithm. The per-residue confidence scores (pLDDT; left to right) for individual sections of the protein are indicated. (B) Transcription and expression profiles for the gene encoding HCO_011565 in different developmental stages/sexes of Haemonchus contortus larvae: eggs, first-, second- and third-stage larvae (L1, L2 and L3, respectively), exsheathed third-stage larvae (xL3s), fourth-stage larvae (L4s), female and male L4s (L4f and L4m, respectively), and female and male adults (Af and Am, respectively). Heatmaps indicate levels of transcription/expression: red indicates moderate to high transcription/expression; green is low expression; and grey indicates that expression was not detected. (C) Three-dimensional structure of the protein HCO_011565 and its interaction with compound UMW-868; the inset shows the positioning of UMW-868 in the pocket predicted within HCO_011565. (D) Phylogenetic relationship of protein HCO_011565 with its orthologs in five other species of nematode (left) and the structural models of these orthologs predicted using Alphafold (right).

    Techniques Used: In Silico, Residue, Expressing

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    Article Snippet: AlphaFold is a deep learning model developed by DeepMind that accurately predicts protein three-dimensional structures from amino acid sequences; its creators were awarded the 2024 Nobel Prize in Chemistry for this breakthrough.

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    Article Snippet: Developed by DeepMind, AlphaFold represents a groundbreaking artificial intelligence system for predicting protein conformations (Omran et al., 2022; Abramson et al., 2024).

    Article Title: Decoding the genetic basis of demyelination: Prediction of potential pathogenic coding and regulatory noncoding MBP SNPs in multiple sclerosis
    Article Snippet: We used AlphaFold ( https://alphafold.ebi.ac.uk ,), an advanced artificial intelligence system developed by Google DeepMind, to predict the three-dimensional structure of the MBP.

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    Article Snippet: AlphaFold, developed by DeepMind, has demonstrated unparalleled accuracy in structure prediction, particularly in the CASP13 and CASP14 challenges, using the Evoformer module and evolutionary data.

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    Article Title: Activation of the olfactory receptors OR7D2 and OR10A4 by natural odorants modulates inflammatory responses in human keratinocytes.
    Article Snippet: Olfactory receptors (ORs) are increasingly being recognized for their ectopic functions beyond olfaction, including roles in skin.. Keratinocytes, the predominant cell type in the epidermis, not only provide structural integrity but also regulate inflammatory responses through activation of the nuclear factor kappa B (NF-κB) signaling pathway, which controls the expression of pro-inflammatory cytokines such as interleukin-1 beta (IL1β), IL-6, and IL-8.. In this study, we investigated the role of ectopically expressed ORs in keratinocyte inflammation.

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    Article Snippet: .. The predicted protein structures were generated using AlphaFold (https://deepmind.google/technologies/alphafold/). .. Both struc‐ tures were subsequently prepared with AutoDockTools‐1.5.7 (https://autodock.scripps.edu), including manual removal of water molecules, addition of hydrogens, and other structural refinements.



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    machine learning algorithm alphafold2  (Deepmind Technologies Ltd)
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    Deepmind Technologies Ltd machine learning algorithm alphafold2
    Molecular characterisation of HCO_011565 and docking with UMW-868. (A) Structure of HCO_011565 protein predicted in silico using the <t>Alphafold2</t> algorithm. The per-residue confidence scores (pLDDT; left to right) for individual sections of the protein are indicated. (B) Transcription and expression profiles for the gene encoding HCO_011565 in different developmental stages/sexes of Haemonchus contortus larvae: eggs, first-, second- and third-stage larvae (L1, L2 and L3, respectively), exsheathed third-stage larvae (xL3s), fourth-stage larvae (L4s), female and male L4s (L4f and L4m, respectively), and female and male adults (Af and Am, respectively). Heatmaps indicate levels of transcription/expression: red indicates moderate to high transcription/expression; green is low expression; and grey indicates that expression was not detected. (C) Three-dimensional structure of the protein HCO_011565 and its interaction with compound UMW-868; the inset shows the positioning of UMW-868 in the pocket predicted within HCO_011565. (D) Phylogenetic relationship of protein HCO_011565 with its orthologs in five other species of nematode (left) and the structural models of these orthologs predicted using Alphafold (right).
    Machine Learning Algorithm Alphafold2, supplied by Deepmind Technologies Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/machine+learning+algorithm+alphafold2/alphafold/pmc09616048-228-9-23
    Average 90 stars, based on 1 article reviews
    machine learning algorithm alphafold2 - by Bioz Stars, 2026-11
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Molecular characterisation of HCO_011565 and docking with UMW-868. (A) Structure of HCO_011565 protein predicted in silico using the Alphafold2 algorithm. The per-residue confidence scores (pLDDT; left to right) for individual sections of the protein are indicated. (B) Transcription and expression profiles for the gene encoding HCO_011565 in different developmental stages/sexes of Haemonchus contortus larvae: eggs, first-, second- and third-stage larvae (L1, L2 and L3, respectively), exsheathed third-stage larvae (xL3s), fourth-stage larvae (L4s), female and male L4s (L4f and L4m, respectively), and female and male adults (Af and Am, respectively). Heatmaps indicate levels of transcription/expression: red indicates moderate to high transcription/expression; green is low expression; and grey indicates that expression was not detected. (C) Three-dimensional structure of the protein HCO_011565 and its interaction with compound UMW-868; the inset shows the positioning of UMW-868 in the pocket predicted within HCO_011565. (D) Phylogenetic relationship of protein HCO_011565 with its orthologs in five other species of nematode (left) and the structural models of these orthologs predicted using Alphafold (right).

    Journal: Frontiers in Pharmacology

    Article Title: Thermal proteome profiling reveals Haemonchus orphan protein HCO_011565 as a target of the nematocidal small molecule UMW-868

    doi: 10.3389/fphar.2022.1014804

    Figure Lengend Snippet: Molecular characterisation of HCO_011565 and docking with UMW-868. (A) Structure of HCO_011565 protein predicted in silico using the Alphafold2 algorithm. The per-residue confidence scores (pLDDT; left to right) for individual sections of the protein are indicated. (B) Transcription and expression profiles for the gene encoding HCO_011565 in different developmental stages/sexes of Haemonchus contortus larvae: eggs, first-, second- and third-stage larvae (L1, L2 and L3, respectively), exsheathed third-stage larvae (xL3s), fourth-stage larvae (L4s), female and male L4s (L4f and L4m, respectively), and female and male adults (Af and Am, respectively). Heatmaps indicate levels of transcription/expression: red indicates moderate to high transcription/expression; green is low expression; and grey indicates that expression was not detected. (C) Three-dimensional structure of the protein HCO_011565 and its interaction with compound UMW-868; the inset shows the positioning of UMW-868 in the pocket predicted within HCO_011565. (D) Phylogenetic relationship of protein HCO_011565 with its orthologs in five other species of nematode (left) and the structural models of these orthologs predicted using Alphafold (right).

    Article Snippet: The three-dimensional structures of proteins were predicted using the machine learning algorithm AlphaFold2 , which is an advanced, artificial intelligence (AI) program—developed by DeepMind and acquired by Alphabet/Google; this program uses a neural network (deep-learning) ( ) to predict the three-dimensional structures of proteins from their primary amino acid sequences, and achieves high levels of accuracy/confidence compared with conventional, homology-based modelling methods.

    Techniques: In Silico, Residue, Expressing