Unlike current silicon-based computing systems that utilize one layer of linear binary coding system, biological systems apply multiple layers of coding. In addition, each layer of coding in a biological system involves different types of coding subunits. For example, multilayer coding in biological systems involves coding languages of DNA, mRNA, amino acids, peptides, protein-protein interaction, signalling pathways, systemic signalling pathways of endocrine hormones, as well as neurotransmitters and neural networks. Figure a illustrates schematic images representative of DNA, amino acid, and protein-coding layers in a cell versus linear binary coding in an electronic-based computer.
(a–d) Schematic representative of multilayer coding in biological systems.
(a) Formation of genetic coding layer by special sequences of nucleotides in DNA molecule.
(b) Translation of DNA genetic code from nucleotides’ coding language to amino acids’ coding system and formation of a protein which would be a coding subunit of a cell signalling network.
(c) Interactions of signalling protein units with each other and formation of a protein-based cell signal transduction network.
(d) Dynamic data operation in a cell by protein-based cell signalling networks
Figure c illustrates schematic representative of standard DNA-amino acid codon in biological systems. Despite several attempts for generation of biologically inspired computing algorithms, the current biologically inspired algorithms almost are established only based on one layer of coding. The exquisite accuracy and efficiency of data operation in living cells is due through highly complex and interconnected DNA-protein NP (nondeterministic polynomial time) networks.
Schematic image representative of alphabetic symbols of nucleotide and amino acids in DNA, RNA, and protein-coding layers, respectively. The nucleic acid coding layer is made of four coding subunits including A, U, G, and C. Protein-coding layer is made of 20 amino acid coding subunits
The figure above illustrates a schematic image representative of multilayer property of the biological coding system. Codes are defined by alphabetic symbols. The nucleic acid coding layer is made of four coding subunits and protein-coding layer is made of 20 amino acid coding subunits.
Molecular Coding and Algorithmic Chemistry
Unlike silicon-based computers that are operated by an electronic-based coding system, all biological functions in living cells are operated by chemical-based coding systems. Figure above illustrates alphabetic symbols of the universal nucleotide/ amino acid coding system in living systems. Although typically molecular codes in cognitive chemistry system are presented as sequences of molecular sub-units (e.g with sequences of 4 DNA nucleo-tides or 20 amino acids), the real codes in this molecular coding system are hidden in electrochemical attractive forces among molecules and atoms. Figure a illustrates a schematic image representative of electrochemical attractive forces
among molecules which can be applied in designing of different types of coding molecules.
(a–c) Schematic image representative of electrochemical interactions between four coding subunits of DNA nucleotides as well as the side chains of two exemplary amino acids.
(a) Illustrates a schematic image representative of electrochemical attractive forces among molecules which can be applied in designing of different types of coding molecules.
(b) Indicates a schematic image representative of electrochemical interactions between two amino acids (aspartate and lysine).
(c) Indicates electrochemical interactions between nucleotides A-T and G-C
Figure b indicates a schematic image representative of electrochemical interactions between two amino acids (aspartate and lysine). Dynamic electrochemical interactions between amino acids with each other in a protein or among different proteins provide a highly efficient coding and signal transduction system in living cells. Figure c indicates electrochemical interactions between nucleotides A-T and G-C. Electrochemical attractive forces among different types of coding molecules can be quantified by specific affinity indexes. Affinity indexes among coding molecules can be translated to the values and integers and be applied in designing of novel chemical-based operating systems for solving complex mathematical problems such as nondeterministic polynomial time (NP) problems. Biological systems provide highly efficient models for solving complex problems.
1. Molecular Mechanisms of Autonomy in Biological Systems Relativity of Code, Energy and Mass, page 34