Welcome To Website IAS

Hot news
Achievement

Independence Award

- First Rank - Second Rank - Third Rank

Labour Award

- First Rank - Second Rank -Third Rank

National Award

 - Study on food stuff for animal(2005)

 - Study on rice breeding for export and domestic consumption(2005)

VIFOTEC Award

- Hybrid Maize by Single Cross V2002 (2003)

- Tomato Grafting to Manage Ralstonia Disease(2005)

- Cassava variety KM140(2010)

Centres
Website links
Vietnamese calendar
Library
Visitors summary
 Curently online :  7
 Total visitors :  7329836

Highly accurate protein structure prediction with AlphaFold
Wednesday, 2021/07/21 | 09:04:17

John Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko, Alex Bridgland, ClemensMeyer, SimonA.A.Kohl, Andrew J.Ballard, Andrew Cowie, BernardinoRomera-Paredes, Stanislav Nikolov, Rishub Jain, Jonas Adler, Trevor Back, Stig Petersen, David Reiman, Ellen Clancy, Michal Zielinski, Martin Steinegger, Michalina Pacholska, Tamas Berghammer, Sebastian Bodenstein, David Silver, Oriol Vinyals, Andrew W. Senior, Koray Kavukcuoglu, Pushmeet Kohli & Demis Hassabis

 

NATURE Published online 15 July 2021 (Nature | www.nature.com)

 

Abstract

 

Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental efort1–4 , the structures of around 100,000 unique proteins have been determined5 , but this represents a small fraction of the billions of known protein sequences6,7 . Structural coverage is bottlenecked by the months to years of painstaking efort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the 3-D structure that a protein will adopt based solely on its amino acid sequence, the structure prediction component of the ‘protein folding problem’8 , has been an important open research problem for more than 50 years9 . Despite recent progress10–14, existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the frst computational method that can regularly predict protein structures with atomic accuracy even where no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14)15, demonstrating accuracy competitive with experiment in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.

 

See www.nature.com

 

Figure 1: AlphaFold produces highly accurate structures. (a) AlphaFold’s performance on the CASP14 set (N=87 protein domains) relative to the top-15 entries (out of 146), group numbers correspond to the numbers assigned to entrants by CASP; error bars represent the 95% confidence interval of the median, estimated with 10,000 bootstrap samples. (b) Our prediction of CASP14 target T1049 (blue) compared to the true (experimental) structure (green). Four residues from the C-terminus of the crystal structure are B-factor outliers and are not depicted. (c) An example of a well predicted zinc binding site (AlphaFold has accurate side chains even though it does not explicitly predict the zinc ion). (d) CASP target T1044, a 2,180-residue single chain, predicted with correct domain packing (prediction made after CASP using AlphaFold without intervention). (e) Model architecture. Arrows show the information flow among the various components described in this paper. Array shapes are shown in brackets with s: number of sequences, r: number of residues and c: number of channels.

Back      Print      View: 300

[ Other News ]___________________________________________________
  • Genome-wide analysis of autophagy-associated genes in foxtail millet (Setaria italica L.) and characterization of the function of SiATG8a in conferring tolerance to nitrogen starvation in rice.
  • Arabidopsis small nucleolar RNA monitors the efficient pre-rRNA processing during ribosome biogenesis
  • XA21-specific induction of stress-related genes following Xanthomonas infection of detached rice leaves.
  • Reducing the Use of Pesticides with Site-Specific Application: The Chemical Control of Rhizoctonia solani as a Case of Study for the Management of Soil-Borne Diseases
  • OsJRL, a rice jacalin-related mannose-binding lectin gene, enhances Escherichia coli viability under high-salinity stress and improves salinity tolerance of rice.
  • Production of lipopeptide biosurfactants by Bacillus atrophaeus 5-2a and their potential use in microbial enhanced oil recovery.
  • GhABF2, a bZIP transcription factor, confers drought and salinity tolerance in cotton (Gossypium hirsutum L.).
  • Resilience of cassava (Manihot esculenta Crantz) to salinity: implications for food security in low-lying regions.
  • Cellulose synthase complexes act in a concerted fashion to synthesize highly aggregated cellulose in secondary cell walls of plants
  • No adverse effects of transgenic maize on population dynamics of endophytic Bacillus subtilis strain B916-gfp
  • Identification and expression analysis of OsLPR family revealed the potential roles of OsLPR3 and 5 in maintaining phosphate homeostasis in rice
  • Functional analysis of molecular interactions in synthetic auxin response circuits
  • Titanium dioxide nanoparticles strongly impact soil microbial function by affecting archaeal nitrifiers.
  • Inducible Expression of the De-Novo Designed Antimicrobial Peptide SP1-1 in Tomato Confers Resistance to Xanthomonas campestris pv. vesicatoria.
  • Toward combined delignification and saccharification of wheat straw by a laccase-containing designer cellulosome
  • SNP-based discovery of salinity-tolerant QTLs in a bi-parental population of rice (Oryza sativa)
  • Pinpointing genes underlying the quantitative trait loci for root-knot nematode resistance in palaeopolyploid soybean by whole genome resequencing.
  • Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum -Phytophthora capsici Phytopathosystem.
  • Brassinosteroids participate in the control of basal and acquired freezing tolerance of plants
  • Rapid hyperosmotic-induced Ca2+ responses in Arabidopsis thaliana exhibit sensory potentiation and involvement of plastidial KEA transporters

 

Designed & Powered by WEBSO CO.,LTD