Antisense peptide technology (APT) is based on a useful heuristic algorithm for rational peptide design. It was deduced from empirical observations that peptides consisting of complementary (sense ...and antisense) amino acids interact with higher probability and affinity than the randomly selected ones. This phenomenon is closely related to the structure of the standard genetic code table, and at the same time, is unrelated to the direction of its codon sequence translation. The concept of
is discussed, and its possible applications to diagnostic tests and bioengineering research are summarized. Problems and difficulties that may arise using APT are discussed, and possible solutions are proposed. The methodology was tested on the example of SARS-CoV-2. It is shown that the CABS-dock server accurately predicts the binding of antisense peptides to the SARS-CoV-2 receptor binding domain without requiring predefinition of the binding site. It is concluded that the benefits of APT outweigh the costs of random peptide screening and could lead to considerable savings in time and resources, especially if combined with other computational and immunochemical methods.
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).
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 1st horizontal, 2nd vertical and 3rd 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 1st and 3rd 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.
Prostate cancer is among the leading cancers according to both incidence and mortality. Due to the high molecular, morphological and clinical heterogeneity, the course of prostate cancer ranges from ...slow growth that usually does not require immediate therapeutic intervention to aggressive and fatal disease that spreads quickly. However, currently available biomarkers cannot precisely predict the course of a disease, and novel strategies are needed to guide prostate cancer management. Amino acids serve numerous roles in cancers, among which are energy production, building block reservoirs, maintenance of redox homeostasis, epigenetic regulation, immune system modulation and resistance to therapy. In this article, by using The Cancer Genome Atlas (TCGA) data, we found that the expression of amino acid metabolism-related genes is highly aberrant in prostate cancer, which holds potential to be exploited in biomarker design or in treatment strategies. This change in expression is especially evident for catabolism genes and transporters from the solute carrier family. Furthermore, by using recursive partitioning, we confirmed that the Gleason score is strongly prognostic for progression-free survival. However, the expression of the genes
(phosphatidylserine and sphingolipids generation) and
(hypotaurine generation) can refine prognosis for high and low Gleason scores, respectively. Therefore, our results hold potential for novel prostate cancer progression biomarkers.
Prostate cancer is a heterogeneous disease, and one of the main obstacles in its management is the inability to foresee its course. Therefore, novel biomarkers are needed that will guide the ...treatment options. The extracellular matrix (ECM) is an important part of the tumor microenvironment that largely influences cell behavior. ECM components are ligands for integrin receptors which are involved in every step of tumor progression. An underlying characteristic of integrin activation and ligation is the formation of integrin adhesion complexes (IACs), intracellular structures that carry information conveyed by integrins. By using The Cancer Genome Atlas data, we show that the expression of ECM- and IACs-related genes is changed in prostate cancer. Moreover, machine learning methods revealed that they are a source of biomarkers for progression-free survival of patients that are stratified according to the Gleason score. Namely, low expression of
and high expression of
genes are associated with worse survival of patients with a Gleason score lower than 9. The
gene encodes protein that may play a role in the assembly of the ECM and the
gene product is a protein tyrosine phosphatase activated by integrins. Our results suggest potential biomarkers of prostate cancer progression.
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.
The effect of five essential oils (anise, peppermint, basil, rosemary and true lavander) and their two most common components on the mycelial growth in Colletotrichum coccodes, economically important ...phytopathogic fungi and compared with fungicides have been investigated in the study. Tests were conducted in vitro conditions in eight volumes on a PDA substrate in four replicates. The increase in mycelium was measured on the eighth and fifteenth day after the mycelium inoculation. It was found out that some essential oils and components applied at a given volume have a significant antifungal effect, in some examples comparable to fungicides. Anise and peppermint essential oils as well as the anethole component had the best activity and the lowest IC50. Fifteen days after the inoculation of the mycelium, the essential oils had a significantly better antifungal activity compared to their second most represented component.
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.
A multimycotoxin analysis approach in grains results in frequent simultaneous findings of nephrotoxic mycotoxins ochratoxin A (OTA) and citrinin (CTN). The mechanism of CTN and OTA toxicities in ...biological systems is not fully understood but it is known that oxidative stress is involved. In this study, oxidative damage of DNA, lipids, and the concentration of glutathione (GSH), as well as possible antioxidative effects of resveratrol (RSV) were studied in vivo. Male adult Wistar rats were treated orally with OTA (0.125 and 0.250 mg kg−1 b.w.), RSV (20 mg kg−1 b.w.) for 21 days, CTN (20 mg kg−1 b.w.) for two days or with their combinations. The hOGG1 modified comet assay revealed kidneys and liver oxidative DNA damage in OTA + CTN treated animals, which was not reversed by RSV. CTN did not reduce glutathione (GSH) or increase malondialdehyde (MDA) concentration in any tissue, while OTA reduced kidneys GSH and increased kidneys and liver MDA. RSV increased GSH concentrations in all tissues and decreased MDA concentration in the liver only. Oxidative stress is involved in the toxicity of OTA and CTN but it seems that it differs significantly in organs. Most of the effects on GSH and MDA in combined toxicity may be attributed to the toxic effects of OTA. RSV was effective in restoring the depleted GSH in all tissues but had no effect on the MDA concentration and DNA damage.
•Combined effects of ochratoxin A and citrinin were studied on male Wistar rats.•The oxidative stress parameters were measured in kidneys, liver and plasma.•It was confirmed that oxidative stress is involved in ochratoxin A and citrinin toxicity.•Involvement of oxidative stress in the mechanism of their combined toxicity differs significantly by organ.•RSV was effective in restoring depleted GSH in all tissues but had no effect on MDA concentration or DNA damage.
We present the data concerning the clustering of sense and antisense amino acid pairs into polar, nonpolar and neutral groups, as measured using hydrophobicity parameter—logarithmic equilibrium ...constants (Log10 Kw>c)—at 25 °C and 100 °C (Wolfenden et al., 2015). The Log10 Kw>c, values, of the complementary amino acid pairs are strongly correlated to the central (2nd) purine base of the mRNA codon and the complementary pyrimidine base of the tRNA anticodon. Clustering of amino acids is temperature independent with regard to the direction of translation (3′ → 5′ or 5′ → 3′). The Log10 Kw>c discriminate between artificial Hecht α- and β-protein datasets at 25 °C and 100 °C. Interpretation of this data may be found in the research article entitled “Determining amino acid scores of the genetic code table: complementarity, structure, function and evolution” (Štambuk and Konjevoda, 2020).
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