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Cellular Automata (CA) Model for Protein

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A New Kind of Computational Biology

Abstract

CA model for protein is covered in this chapter. Design of CA rule for amino acid backbone is reported followed by the design of PCAM (Protein Modelling CA Machine). A protein chain with n amino acids is represented by 8n cell PCAM, each amino acid is represented with 8 CA cells. Digitally encoded amino acid side chain with 8-bit string is used as the initial state of 8 CA cells used for its backbone. For a protein chain, provision of 64 PCAMs is provided for modelling its interaction with different biomolecules. Protein interaction modelling is reported for two applications—(i) predicting binding contact residues for protein–protein interaction, and (ii) mutational study. Predicted results derived out of PCAM model are validated against the wet lab experimental results reported in databases and publications. In addition to validation of the results, the case study identifies which specific PCAM (out of the available 64) is appropriate for modelling the interaction. The binding affinity of two Monoclonal Antibodies (MAbs) on wild and mutated version of PD-L1 (implicated cancer immunotherapy) are reported confirming the CA rule appropriate for the mutational study of PD-L1 for a specific MAb.

“Genes are effectively one-dimensional. If you write down the sequence of A, C, G and T, that’s kind of what you need to know about that gene. But proteins are three-dimensional. They have to be because we are three-dimensional, and we’re made of those proteins. Otherwise we’d all sort of be linear, unimaginably weird creatures”.

—Francis Collins

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Authors and Affiliations

  1. CARLBio Pvt. Ltd., Kolkata, West Bengal, India

    Parimal Pal Chaudhuri, Soumyabrata Ghosh, Adip Dutta & Somshubhro Pal Choudhury

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  1. Parimal Pal Chaudhuri
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  2. Soumyabrata Ghosh
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  3. Adip Dutta
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  4. Somshubhro Pal Choudhury
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Correspondence to Parimal Pal Chaudhuri .

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Pal Chaudhuri, P., Ghosh, S., Dutta, A., Pal Choudhury, S. (2018). Cellular Automata (CA) Model for Protein. In: A New Kind of Computational Biology. Springer, Singapore. https://doi.org/10.1007/978-981-13-1639-5_5

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  • DOI: https://doi.org/10.1007/978-981-13-1639-5_5

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