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New algorithm predicting dynamic language of protein can help investigation of genetic diseases

Posted:  Monday, November 02, 2015

Let us go beyond the assertion ‘proteins help build muscles and repair tissues,’ shall we? Researchers from the Structural Biology Computational Group of the Spanish National Cancer Research Centre (CNIO) teamed up with scientists at University College London to establish the first computational method that predicts changes in the dimensional structure of proteins during their interaction with other compounds.

The study has been published in the journal Proceedings of the National Academy of Sciences. The amino acids that constitute proteins fold to form 3D structures; knowledge of the co-evolution (change in a coordinated way) of amino acids can help grasp the complete picture of the structure of proteins when present in their natural surroundings.

The protein structure undergoes changes in response to interactions with biological compounds or drugs and this concept goes by the name of protein dynamics. The researchers developed a model where amino acids that have a strong co-evolutionary relationship attracted each other, and used simulations of the folding process to predict alterations in protein shape.

Alfonso Valencia, who led the team at CNIO said, "By analysing the sequences of a given family of proteins, we can predict physical contacts between amino acids with great precision, in sufficient number to reconstruct the folding of a protein accurately and, therefore, its structure or form."

The model uses sequence analysis and 3D modelling technology to seamlessly combine experimental and genomic information. This helps predict the dynamics of protein in the presence of other compounds and drugs, and therefore its functions. This is crucial in the study of genetic diseases, such as cancer, or the design of drugs, amongst other uses.

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