DeepMind, a prominent AI company based in the UK, announced this groundbreaking achievement, which is anticipated to have far-reaching implications, particularly in accelerating the development of new medications (
).
Proteins are composed of diverse sequences of amino acids. It attains its intricate 3D structures through numerous interactions between these building blocks of amino sequence. Understanding these shapes is pivotal for designing drugs that can interact with specific proteins and for developing enzymes that facilitate biofuel production and plastic degradation.
Janet Thornton, director emeritus of the European Bioinformatics Institute, expresses enthusiasm and emphasizes its potential to revolutionize structural biology and protein research. John Moult, co-founder of the Critical Assessment of Protein Structure Prediction (CASP) competition and a structural biologist at the University of Maryland, Shady Grove, shares the sentiment, stating that he never expected to witness this advancement during his lifetime.
DeepMind and Protein Structure Development
In 2018, DeepMind introduced AlphaFold, which combined comparative strategies with deep learning. They trained the algorithm on extensive data of known protein sequences and structures.
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AlphaFold’s performance surpassed its competitors significantly, but the predictions were still limited in precision. To address this, the developers integrated deep learning with an “attention algorithm,” resembling assembling a jigsaw puzzle, to improve accuracy.
The recent CASP competition showcased AlphaFold’s remarkable progress, achieving high accuracy scores and outperforming other groups by a wide margin, even in solving complex membrane proteins, known for their difficulty.
The achievement received praise from the scientific community, and AlphaFold’s method is set to be shared. This can benefit experimentalists in interpreting data from techniques like x-ray crystallography and cryo-EM, as well as drug designers working on potential treatments for diseases like SARS-CoV-2.
How can AI Aid Medical Development?
According to the researchers, knowing the form of these proteins will provide insight into their structure and process. These structures have so far remained elusive and could be the most significant impact of AI in the field of biology.
The availability of protein structures may aid in the study of cell-building components and lead to the improved discovery of new medications to cure ailments. DeepMind stated that the protein database will enable researchers in their search for medical cures. It can also provide solutions to other major issues confronting humanity, such as antibiotic resistance, microplastic contamination, and global warming.
Despite this significant advancement, AlphaFold still faces challenges in handling certain complex protein structures and protein complexes. Nonetheless, the breakthrough marks the beginning of new possibilities in the field of protein research, with many exciting avenues lying ahead.
,Reference :
- ‘The game has changed.’ AI triumphs at solving protein structures – (https:www.science.org/content/article/game-has-changed-ai-triumphs-solving-protein-structures)
Source: Medindia
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