


Volume 9 No 4 (2011)
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The Quantum Workings of the Rotating 64‐Grid Genetic Code
Fernando Castro‐Chavez
Abstract
In this article, the pattern learned from the classic or conventional rotating circular
genetic code is transferred to a 64‐grid model. In this non‐static representation, the
codons for the same amino acid within each quadrant could be exchanged, wobbling
or rotating in a quantic way similar to the electrons within an atomic orbit.
Represented in this 64‐grid format are the three rules of variation encompassing 4, 2,
or 1 quadrant, respectively: 1) same position in four quadrants for the essential
hydrophobic amino acids that have U at the center, 2) same or contiguous position for
the same or related amino acids in two quadrants, and 3) equivalent amino acids
within one quadrant. Also represented is the mathematical balance of the odd and
even codons, and the most used codons per amino acid in humans compared to one
diametrically opposed organism: the plant Arabidopsis thaliana, a comparison that
depicts the difference in third nucleotide preferences: a C/U exchange for 11 amino
acids, a G/A exchange for 2 amino acids, and G/U or C/A exchanges for one amino
acid, respectively; by studying these codon usage preferences per amino acid we
present our two hypotheses: 1) A slower translation in vertebrates and 2) a faster
translation in invertebrates, possibly due to the aqueous environments where they
live. These codon usage preferences may also be able to determine genomic
compatibility by comparing individual mRNAs and their functional third dimensional
structure, transport and translation within cells and organisms. These observations
are aimed to the design of bioinformatics computational tools to compare human
genomes and to determine the exchange between compatible codons and amino
acids, to preserve and/or to bring back extinct biodiversity, and for the early detection
of incompatible changes that lead to genetic diseases.
Keywords
compatible genomics, compatibility, genome, adaptability, adaptation, variation, biomathematics, bioinformatics, computational biology
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