Search

The article presents IUPAC ambiguity codes for incomplete nucleic acid specification, and their use in Code Biology. It is shown how to use this nomenclature in order to extract accurate information on different properties of the biological systems. We investigated the use of ambiguity codes, as mathematical and logical operators and truth table elements, for the encoding of amino acids by means of the Standard Genetic Code. It is explained how to use ambiguity codes and truth functions in order to obtain accurate information on different properties of the biological systems. Nucleotide ambiguity codes could be applied to: 1. encoding descriptive information of nucleotides, amino acids and proteins (e.g., of polarity, relative solvent accessibility, atom depth, etc.), and 2. system modelling ranging from standard bioinformatics tools to classic evolutionary models (i.e. from Miyazawa-Jernigan statistical potential to Kimura three-substitution-type model, respectively). It is shown that the algorithms based on IUPAC ambiguity codes, Boolean functions and truth table, Probabilistic Square of Opposition/Semiotic Square and Klein 4-groups-could be used for the bioinformatics analyses and Relational data modelling in natural science. Underlying mathematical, logical and semiotic concepts of interest are presented and addressed., Competing Interests: Declaration of competing interest Authors declare no conflict of Interest for their Article., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Phylogenetics is the study of ancestral relationships among biological species. Such sequence analyses are often represented as phylogenetic trees. The branching pattern of each tree and its topology reflect the evolutionary relatedness between analyzed sequences. We present a Klein four-group algorithm (K4A) for the evolutionary analysis of nucleotide and amino acid sequences. Klein four-group set of operators consists of: identity e (U), and three elements-a = transition (C), b = transversion (G) and c = transition-transversion or complementarity (A). We generated Klein four-group based distance matrices of: 1. Cayley table (CK4), 2. Table rows (K4R), 3. Table columns (K4C), and 4. Euclidean 2D distance (K4E). The performance of the matrices was tested on a dataset of RecA proteins in bacteria, eukaryotes (Rad51 homolog) and archaea (RadA homolog). RecA and its functional homologs are found in all species, and are essential for the repair and maintenance of DNA. Consequently, they represent a good model for the study of evolutionary relationship of protein and nucleotide sequences. The ancestral relationship between the sequences was correctly classified by all K4A matrices concerning general topology. All distance matrices exhibited small variations among species, and overall results of tree classification were in agreement with the general patterns obtained by standard BLOSUM and PAM substitution matrices. During the evolution of a code there is a phase of optimization of system rules, the ambiguity of a code is eliminated, and the system starts producing specific components. Klein four-group algorithm is consistent with the concept of ambiguity reduction. It also enables the use of different genetic code table variants optimized for particular transitions in evolution based on biological specificity., Competing Interests: Declaration of competing interest Authors declare no conflict of Interest for their article., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The genetic code is a set of rules that establishes mapping between triplets in messenger RNA and amino acids in proteins. The most common way to display these rules is the Standard Genetic Code (SGC) table. This paper takes an alternative approach, based on the relational data model by Edgar F. Codd (Commun. ACM, 13:377-387, 1970). The relational model (RM) proposes a distributed storage of data into a collection of tables (called relations), that can be connected by shared communality. Basic elements of the table are rows (called records or tuples), and columns (called fields or attributes). The SGC table, according to the relational data model, represents the so called unnormalized form of a table. Using normalization rules it is possible to subdivide the SGC table into four tables. The rows and columns of single tables are defined by the first and second base and individual tables by the third codon base. The result of this model is an approach to managing genetic code data, represented in terms of tuples and grouped into relations, with table structure and language consistent with first-order (predicate) logic. The RM explains that the final step in the development of the SGC was the adoption of coding function by the third base, which makes an informational/functional unit with the first base, despite the different physical location in a triplet. This enabled the synthesis of specific proteins without ambiguity, in accordance with the concept of ambiguity reduction and five phases of the general model on the origin of biological codes by Marcello Barbieri (BioSystems 181:11-19, 2019)., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The Standard Genetic Code (SGC) table was investigated with respect to the three-dimensional codon arrangement, and all possible 24 hierarchical base partitions (4! = 24). This was done by determining the amino acid scores for each codon hierarchy in relation to the 1 st horizontal, 2 nd vertical and 3 rd horizontal sub-tables. Marked differences were observed for the hydrophobicity and lipophilicity parameters encoded by the second base of the SGC table. The nucleotide hierarchy U < C < G < A and its complement A < G < C < U at the second base correlated best with the amino acid hydrophobicity and polarity. By contrast, the hierarchy C < G < U < A and its backwards transcript A < U < G < C at the second base were associated with the amino acid parameters of lipophilicity and accessible surface area. No association was observed between 24 base hierarchies of the codons at the 1 st and 3 rd positions with respect to the hydropathy, polarity, lipophilicity and accessible surface area. The results imply that the second base possesses the majority of information content with respect to the physicochemical properties observed. It is shown that amino acid information obtained by determining the scores of the bases and codon weightings in digital form coincides with physicochemical properties, and the temperature range between 25 °C and 100 °C does not affect the hydrophobicity, the related prediction of α- and β-protein structure, codon scores, or the complementarity code for sense and antisense peptide interactions. The amino acid scores determined for the SGC table enable the construction of rules and algorithms for the analysis of the structure, function and evolution of proteins. It has been demonstrated that IUPAC-based encoding of nucleobase and amino acid sequences could be used for the representation of the bases with the Semiotic (Greimas) Square and probabilistic square of opposition. It is concluded that the structural, functional and evolutionary patterns of the protein sequences may be modeled using codon based amino acid information, instead of using the information based on amino acid physicochemical properties only., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Sense and antisense peptides, i.e. peptides specified by complementary DNA and RNA sequences, interact with increased probability. Biro, Blalock, Mekler, Root-Bernstein and Siemion investigated the recognition rules of peptide-peptide interaction based on the complementary coding of DNA and RNA sequences in 3'→5' and 5'→3' directions. After more than three decades of theoretical and experimental investigations, the efficiency of this approach to predict peptide-peptide binding has been experimentally verified for more than 50 ligand-receptor systems, and represents a promising field of research. The natural genetic coding algorithm for sense and antisense peptide interactions combines following elements: of amino acid physico-chemical properties, stereochemical interaction, and bidirectional transcription. The interplay of these factors influences the specificity of sense-antisense peptide interactions, and affects the selection and evolution of peptide ligand-receptor systems. Complementary mRNA codon-tRNA anticodon complexes, and recently discovered Carter-Wolfenden tRNA acceptor-stem code, provide the basis for the rational modeling of peptide interactions based on their hydrophobic and lipophilic amino acid physico-chemical properties. It is shown that the interactions of complementary amino acid pairs according to the hydrophobic and lipophilic properties strongly depend on the central (second) purine base of the mRNA codon and its pyrimidine complement of the tRNA anticodon. This enables the development of new algorithms for the analysis of structure, function and evolution of protein and nucleotide sequences that take into account the residue's tendency to leave water and enter a nonpolar condensed phase considering its mass, size and accessible surface area. The practical applications of the sense-antisense peptide modeling are illustrated using different interaction assay types based on: microscale thermophoresis (MST), tryptophan fluorescence spectroscopy (TFS), nuclear magnetic resonance spectroscopy (NMR), and magnetic particles enzyme immunoassay (MPEIA). Various binding events and circumstances were considered, e.g., in situations with-short antisense peptide ligand (MST), L- and D-enantiomer acceptors (TFS), in low affinity conditions (NMR), and with more than one antisense peptide targeting hormone (MPEIA)., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)