Protein structure and the sequential structure of mRNA: alpha-helix and beta-sheet signals at the nucleotide level

Analysis for codon usage bias in membrane anchor of nonstructural protein 5A from BVDV

The nonstructural protein 5A (NS5A) of the bovine viral diarrhea virus (BVDV) is a monotopic membrane protein. This protein can anchor to the cell membrane by an in-plane amphipathic ⍺-helix, which participates in the viral replication complex. In this study, the effects of synonymous codon usage pattern of NS5A and the overall transfer RNA (tRNA) abundance in cells on the formation of the in-plane membrane anchor of NS5A were analyzed, based on NS5A coding sequences of different BVDV genotypes. BVDV NS5A coding sequences represent the most potential for BVDV genotyping. Moreover, the nucleotide usage of BVDV NS5A dominates the genotype-specific pattern of synonymous codon usage. There is an obvious relationship between synonymous codon usage bias and the spatial conformation of the in-plane membrane anchor. Furthermore, the overall tRNA abundance profiling displays that codon positions with a high level of tRNA abundance are more than ones with a low level of tRNA abundance in the in-plane membrane anchor, implying that high translation speed probably acts on the spatial conformation of in-plane membrane anchor of BVDV NS5A. These results give a new opinion on the effect of codon usage bias in the formation of the in-plane membrane anchor of BVDV NS5A.

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Background

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression.

Results

Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to prevous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding.

Conclusions

Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08635-0).

Network analysis of synonymous codon usage

MOTIVATION

Most amino acids are encoded by multiple synonymous codons, some of which are used more rarely than others. Analyses of positions of such rare codons in protein sequences revealed that rare codons can impact co-translational protein folding and that positions of some rare codons are evolutionarily conserved. Analyses of their positions in protein 3-dimensional structures, which are richer in biochemical information than sequences alone, might further explain the role of rare codons in protein folding.

RESULTS

We model protein structures as networks and use network centrality to measure the structural position of an amino acid. We first validate that amino acids buried within the structural core are network-central, and those on the surface are not. Then, we study potential differences between network centralities and thus structural positions of amino acids encoded by conserved rare, non-conserved rare and commonly used codons. We find that in 84% of proteins, the three codon categories occupy significantly different structural positions. We examine protein groups showing different codon centrality trends, i.e. different relationships between structural positions of the three codon categories. We see several cases of all proteins from our data with some structural or functional property being in the same group. Also, we see a case of all proteins in some group having the same property. Our work shows that codon usage is linked to the final protein structure and thus possibly to co-translational protein folding.

AVAILABILITY AND IMPLEMENTATION

https://nd.edu/∼cone/CodonUsage/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A Crosstalk on Codon Usage in Genes Associated with Leukemia

Leukemia is the outcome of aggregation of damaged white blood cells. Several genes were reported to be associated with the pathogenesis of leukemia. These genes were computationally analyzed to decipher their codon usage bias (CUB) and to identify the prime factors influencing the codon usage profile as no work was reported yet. The mean values of synonymous codon usage order (SCUO) parameter indicated low CUB of the genes. Significant positive association of SCUO with overall GC and positional GCs might signal the presence of mutational pressure. However, neutrality plot suggested the dominant role of natural selection across the genes. Along with natural selection, the role of mutation pressure was also prominent and that might be responsible for lower CUB (SCUO = 0.19) of genes. Low translational speed might permit accuracy in the process. A strong inverse relationship of translational rate was observed with CUB of genes and folding energy.

A deep attention network for predicting amino acid signals in the formation of [Formula: see text]-helices

The secondary and tertiary structure of a protein has a primary role in determining its function. Even though many folding prediction algorithms have been developed in the past decades - mainly based on the assumption that folding instructions are encoded within the protein sequence - experimental techniques remain the most reliable to establish protein structures. In this paper, we searched for signals related to the formation of [Formula: see text]-helices. We carried out a statistical analysis on a large dataset of experimentally characterized secondary structure elements to find over- or under-occurrences of specific amino acids defining the boundaries of helical moieties. To validate our hypothesis, we trained various Machine Learning models, each equipped with an attention mechanism, to predict the occurrence of [Formula: see text]-helices. The attention mechanism allows to interpret the model's decision, weighing the importance the predictor gives to each part of the input. The experimental results show that different models focus on the same subsequences, which can be seen as codes driving the secondary structure formation.

Physicochemical Foundations of Life that Direct Evolution: Chance and Natural Selection are not Evolutionary Driving Forces

The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made of complex multicellular organisms and, then, modified to fit a DNA-centric view. In this article, it is argued that based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that (i) natural selection plays a dominant role in evolution and (ii) the probability of mutations is independent of the generated phenotype. It is shown that the adaptation of a phenotype to an environment does not correspond to organism fitness, but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome, but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature, and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype in which the phenotype ensures the stability of its originating genome in a cellular and environmental physicochemical parameter-depending manner.

Genome scale analysis of Escherichia coli with a comprehensive prokaryotic sequence-based biophysical model of translation initiation and elongation

Translation initiation in prokaryotes is affected by the mRNA folding and interaction of the ribosome binding site with the ribosomal RNA. The elongation rate is affected, among other factors, by the local biophysical properties of the coding regions, the decoding rates of different codons, and the interactions among ribosomes. Currently, there is no comprehensive biophysical model of translation that enables the prediction of mRNA translation dynamics based only on the transcript sequence and while considering all of these fundamental aspects of translation. In this study, we provide, for the first time, a computational simulative biophysical model of both translation initiation and elongation with all aspects mentioned above. We demonstrate our model performance and advantages focusing on Escherichia coli genes. We further show that the model enables prediction of translation rate, protein levels, and ribosome densities. In addition, our model enables quantifying the effect of silent mutations on translation rate in different parts of the transcript, the relative effect of mutations on translation initiation and elongation, and the effect of mutations on ribosome traffic jams. Thus, unlike previous models, the proposed one provides comprehensive information, facilitating future research in disciplines such as molecular evolution, synthetic biology, and functional genomics. A toolkit to estimate translation dynamics of transcripts is available at: https://www.cs.tau.ac.il/∼tamirtul/transim.

Evidence of evolutionary selection for cotranslational folding

Recent experiments and simulations have demonstrated that proteins can fold on the ribosome. However, the extent and generality of fitness effects resulting from cotranslational folding remain open questions. Here we report a genome-wide analysis that uncovers evidence of evolutionary selection for cotranslational folding. We describe a robust statistical approach to identify loci within genes that are both significantly enriched in slowly translated codons and evolutionarily conserved. Surprisingly, we find that domain boundaries can explain only a small fraction of these conserved loci. Instead, we propose that regions enriched in slowly translated codons are associated with cotranslational folding intermediates, which may be smaller than a single domain. We show that the intermediates predicted by a native-centric model of cotranslational folding account for the majority of these loci across more than 500 Escherichia coli proteins. By making a direct connection to protein folding, this analysis provides strong evidence that many synonymous substitutions have been selected to optimize translation rates at specific locations within genes. More generally, our results indicate that kinetics, and not just thermodynamics, can significantly alter the efficiency of self-assembly in a biological context.

Role of mRNA structure in the control of protein folding

Specific structures in mRNA modulate translation rate and thus can affect protein folding. Using the protein structures from two eukaryotes and three prokaryotes, we explore the connections between the protein compactness, inferred from solvent accessibility, and mRNA structure, inferred from mRNA folding energy (ΔG). In both prokaryotes and eukaryotes, the ΔG value of the most stable 30 nucleotide segment of the mRNA (ΔGmin) strongly, positively correlates with protein solvent accessibility. Thus, mRNAs containing exceptionally stable secondary structure elements typically encode compact proteins. The correlations between ΔG and protein compactness are much more pronounced in predicted ordered parts of proteins compared to the predicted disordered parts, indicative of an important role of mRNA secondary structure elements in the control of protein folding. Additionally, ΔG correlates with the mRNA length and the evolutionary rate of synonymous positions. The correlations are partially independent and were used to construct multiple regression models which explain about half of the variance of protein solvent accessibility. These findings suggest a model in which the mRNA structure, particularly exceptionally stable RNA structural elements, act as gauges of protein co-translational folding by reducing ribosome speed when the nascent peptide needs time to form and optimize the core structure.

Nonoptimal codon usage influences protein structure in intrinsically disordered regions

Synonymous codons are not used with equal frequencies in most genomes. Codon usage has been proposed to play a role in regulating translation kinetics and co-translational protein folding. The relationship between codon usage and protein structures and the in vivo role of codon usage in eukaryotic protein folding is not clear. Here, we show that there is a strong codon usage bias in the filamentous fungus Neurospora. Importantly, we found genome-wide correlations between codon choices and predicted protein secondary structures: Nonoptimal codons are preferentially used in intrinsically disordered regions, and more optimal codons are used in structured domains. The functional importance of such correlations in vivo was confirmed by structure-based codon manipulation of codons in the Neurospora circadian clock gene frequency (frq). The codon optimization of the predicted disordered, but not well-structured regions of FRQ impairs clock function and altered FRQ structures. Furthermore, the correlations between codon usage and protein disorder tendency are conserved in other eukaryotes. Together, these results suggest that codon choices and protein structures co-evolve to ensure proper protein folding in eukaryotic organisms.

Prediction of protein structural features from sequence data based on Shannon entropy and Kolmogorov complexity

While the genome for a given organism stores the information necessary for the organism to function and flourish it is the proteins that are encoded by the genome that perhaps more than anything else characterize the phenotype for that organism. It is therefore not surprising that one of the many approaches to understanding and predicting protein folding and properties has come from genomics and more specifically from multiple sequence alignments. In this work I explore ways in which data derived from sequence alignment data can be used to investigate in a predictive way three different aspects of protein structure: secondary structures, inter-residue contacts and the dynamics of switching between different states of the protein. In particular the use of Kolmogorov complexity has identified a novel pathway towards achieving these goals.

Hysteresis as a Marker for Complex, Overlapping Landscapes in Proteins

Topologically complex proteins fold by multiple routes as a result of hard-to-fold regions of the proteins. Oftentimes these regions are introduced into the protein scaffold for function and increase frustration in the otherwise smooth-funneled landscape. Interestingly, while functional regions add complexity to folding landscapes, they may also contribute to a unique behavior referred to as hysteresis. While hysteresis is predicted to be rare, it is observed in various proteins, including proteins containing a unique peptide cyclization to form a fluorescent chromophore as well as proteins containing a knotted topology in their native fold. Here, hysteresis is demonstrated to be a consequence of the decoupling of unfolding events from the isomerization or hula-twist of a chromophore in one protein and the untying of the knot in a second protein system. The question now is- can hysteresis be a marker for the interplay of landscapes where complex folding and functional regions overlap?

Evolutionary conservation of codon optimality reveals hidden signatures of cotranslational folding

The choice of codons can influence local translation kinetics during protein synthesis. Whether codon preference is linked to co-translational regulation of polypeptide folding remains unclear. Here, we derive a revised translational efficiency scale that incorporates the competition between tRNA supply and demand. Applying this scale to ten closely related yeasts, we uncover the evolutionary conservation of codon optimality in eukaryotes. This analysis reveals universal patterns of conserved optimal and nonoptimal codons, often in clusters, which associate with the secondary structure of the translated polypeptides independent of the levels of expression. Our analysis suggests an evolved function for codon optimality in regulating the rhythm of elongation to facilitate co-translational polypeptide folding, beyond its previously proposed role of adapting to the cost of expression. These findings establish how mRNA sequences are generally under selection to optimize the co-translational folding of corresponding polypeptides.

Genetic code redundancy and its influence on the encoded polypeptides

The genetic code is said to be redundant in that the same amino acid residue can be encoded by multiple, so-called synonymous, codons. If all properties of synonymous codons were entirely equivalent, one would expect that they would be equally distributed along protein coding sequences. However, many studies over the last three decades have demonstrated that their distribution is not entirely random. It has been postulated that certain codons may be translated by the ribosome faster than others and thus their non-random distribution dictates how fast the ribosome moves along particular segments of the mRNA. The reasons behind such segmental variability in the rates of protein synthesis, and thus polypeptide emergence from the ribosome, have been explored by theoretical and experimental approaches. Predictions of the relative rates at which particular codons are translated and their impact on the nascent chain have not arrived at unequivocal conclusions. This is probably due, at least in part, to variation in the basis for classification of codons as “fast” or “slow”, as well as variability in the number and types of genes and proteins analyzed. Recent methodological advances have allowed nucleotide-resolution studies of ribosome residency times in entire transcriptomes, which confirm the non-uniform movement of ribosomes along mRNAs and shed light on the actual determinants of rate control. Moreover, experiments have begun to emerge that systematically examine the influence of variations in ribosomal movement and the fate of the emerging polypeptide chain.

Synonymous codon usage influences the local protein structure observed

Translation of mRNA into protein is a unidirectional information flow process. Analysing the input (mRNA) and output (protein) of translation, we find that local protein structure information is encoded in the mRNA nucleotide sequence. The Coding Sequence and Structure (CSandS) database developed in this work provides a detailed mapping between over 4000 solved protein structures and their mRNA. CSandS facilitates a comprehensive analysis of codon usage over many organisms. In assigning translation speed, we find that relative codon usage is less informative than tRNA concentration. For all speed measures, no evidence was found that domain boundaries are enriched with slow codons. In fact, genes seemingly avoid slow codons around structurally defined domain boundaries. Translation speed, however, does decrease at the transition into secondary structure. Codons are identified that have structural preferences significantly different from the amino acid they encode. However, each organism has its own set of ‘significant codons’. Our results support the premise that codons encode more information than merely amino acids and give insight into the role of translation in protein folding.

Electrostatics in the ribosomal tunnel modulate chain elongation rates

Electrostatic potentials along the ribosomal exit tunnel are nonuniform and negative. The significance of electrostatics in the tunnel remains relatively uninvestigated, yet they are likely to play a role in translation and secondary folding of nascent peptides. To probe the role of nascent peptide charges in ribosome function, we used a molecular tape measure that was engineered to contain different numbers of charged amino acids localized to known regions of the tunnel and measured chain elongation rates. Positively charged arginine or lysine sequences produce transient arrest (pausing) before the nascent peptide is fully elongated. The rate of conversion from transiently arrested to full-length nascent peptide is faster for peptides containing neutral or negatively charged residues than for those containing positively charged residues. We provide experimental evidence that extraribosomal mechanisms do not account for this charge-specific pausing. We conclude that pausing is due to charge-specific interactions between the tunnel and the nascent peptide.

The Proteomic Code: a molecular recognition code for proteins

Background

The Proteomic Code is a set of rules by which information in genetic material is transferred into the physico-chemical properties of amino acids. It determines how individual amino acids interact with each other during folding and in specific protein-protein interactions. The Proteomic Code is part of the redundant Genetic Code.

Review

The 25-year-old history of this concept is reviewed from the first independent suggestions by Biro and Mekler, through the works of Blalock, Root-Bernstein, Siemion, Miller and others, followed by the discovery of a Common Periodic Table of Codons and Nucleic Acids in 2003 and culminating in the recent conceptualization of partial complementary coding of interacting amino acids as well as the theory of the nucleic acid-assisted protein folding.

Methods and conclusions

A novel cloning method for the design and production of specific, high-affinity-reacting proteins (SHARP) is presented. This method is based on the concept of proteomic codes and is suitable for large-scale, industrial production of specifically interacting peptides.

A "silent" polymorphism in the MDR1 gene changes substrate specificity

Synonymous single-nucleotide polymorphisms (SNPs) do not produce altered coding sequences, and therefore they are not expected to change the function of the protein in which they occur. We report that a synonymous SNP in the Multidrug Resistance 1 (MDR1) gene, part of a haplotype previously linked to altered function of the MDR1 gene product P-glycoprotein (P-gp), nonetheless results in P-gp with altered drug and inhibitor interactions. Similar mRNA and protein levels, but altered conformations, were found for wild-type and polymorphic P-gp. We hypothesize that the presence of a rare codon, marked by the synonymous polymorphism, affects the timing of cotranslational folding and insertion of P-gp into the membrane, thereby altering the structure of substrate and inhibitor interaction sites.

Indications that "codon boundaries" are physico-chemically defined and that protein-folding information is contained in the redundant exon bases

Background

All the information necessary for protein folding is supposed to be present in the amino acid sequence. It is still not possible to provide specific ab initio structure predictions by bioinformatical methods. It is suspected that additional folding information is present in protein coding nucleic acid sequences, but this is not represented by the known genetic code.

Results

Nucleic acid subsequences comprising the 1st and/or 3rd codon residues in mRNAs express significantly higher free folding energy (FFE) than the subsequence containing only the 2nd residues (p < 0.0001, n = 81). This periodic FFE difference is not present in introns. It is therefore a specific physico-chemical characteristic of coding sequences and might contribute to unambiguous definition of codon boundaries during translation. The FFEs of the 1st and 3rd residues are additive, which suggests that these residues contain a significant number of complementary bases and that may contribute to selection for local RNA secondary structures in coding regions. This periodic, codon-related structure-formation of mRNAs indicates a connection between the structures of exons and the corresponding (translated) proteins. The folding energy dot plots of RNAs and the residue contact maps of the coded proteins are indeed similar. Residue contact statistics using 81 different protein structures confirmed that amino acids that are coded by partially reverse and complementary codons (Watson-Crick (WC) base pairs at the 1st and 3rd codon positions and translated in reverse orientation) are preferentially co-located in protein structures.

Conclusion

Exons are distinguished from introns, and codon boundaries are physico-chemically defined, by periodically distributed FFE differences between codon positions. There is a selection for local RNA secondary structures in coding regions and this nucleic acid structure resembles the folding profiles of the coded proteins. The preferentially (specifically) interacting amino acids are coded by partially complementary codons, which strongly supports the connection between mRNA and the corresponding protein structures and indicates that there is protein folding information in nucleic acids that is not present in the genetic code. This might suggest an additional explanation of codon redundancy.

Amino acid size, charge, hydropathy indices and matrices for protein structure analysis

BACKGROUND

Prediction of protein folding and specific interactions from only the sequence (ab initio) is a major challenge in bioinformatics. It is believed that such prediction will prove possible if Anfinsen's thermodynamic principle is correct for all kinds of proteins, and all the information necessary to form a concrete 3D structure is indeed present in the sequence.

RESULTS

We indexed the 200 possible amino acid pairs for their compatibility regarding the three major physicochemical properties--size, charge and hydrophobicity--and constructed Size, Charge and Hydropathy Compatibility Indices and Matrices (SCI & SCM, CCI & CCM, and HCI & HCM). Each index characterized the expected strength of interaction (compatibility) of two amino acids by numbers from 1 (not compatible) to 20 (highly compatible). We found statistically significant positive correlations between these indices and the propensity for amino acid co-locations in real protein structures (a sample containing total 34630 co-locations in 80 different protein structures): for HCI: p < 0.01, n = 400 in 10 subgroups; for SCI p < 1.3E-08, n = 400 in 10 subgroups; for CCI: p < 0.01, n = 175). Size compatibility between residues (well known to exist in nucleic acids) is a novel observation for proteins. Regression analyzes indicated at least 7 well distinguished clusters regarding size compatibility and 5 clusters of charge compatibility. We tried to predict or reconstruct simple 2D representations of 3D structures from the sequence using these matrices by applying a dot plot-like method. The location and pattern of the most compatible subsequences was very similar or identical when the three fundamentally different matrices were used, which indicates the consistency of physicochemical compatibility. However, it was not sufficient to choose one preferred configuration between the many possible predicted options.

CONCLUSION

Indexing of amino acids for major physico-chemical properties is a powerful approach to understanding and assisting protein design. However, it is probably insufficient itself for complete ab initio structure prediction.

Nucleic acid chaperons: a theory of an RNA-assisted protein folding

Background

Proteins are assumed to contain all the information necessary for unambiguous folding (Anfinsen's principle). However, ab initio structure prediction is often not successful because the amino acid sequence itself is not sufficient to guide between endless folding possibilities. It seems to be a logical to try to find the "missing" information in nucleic acids, in the redundant codon base.

Results

mRNA energy dot plots and protein residue contact maps were found to be rather similar. The structure of mRNA is also conserved if the protein structure is conserved, even if the sequence similarity is low. These observations led me to suppose that some similarity might exist between nucleic acid and protein folding. I found that amino acid pairs, which are co-located in the protein structure, are preferentially coded by complementary codons. This codon complementarity is not perfect; it is suboptimal where the 1st and 3rd codon residues are complementary to each other in reverse orientation, while the 2nd codon letters may be, but are not necessarily, complementary.

Conclusion

Partial complementary coding of co-locating amino acids in protein structures suggests that mRNA assists in protein folding and functions not only as a template but even as a chaperon during translation. This function explains the role of wobble bases and answers the mystery of why we have a redundant codon base.

Artificial neural networks for computer-based molecular design

The theory of artificial neural networks is briefly reviewed focusing on supervised and unsupervised techniques which have great impact on current chemical applications. An introduction to molecular descriptors and representation schemes is given. In addition, worked examples of recent advances in this field are highlighted and pioneering publications are discussed. Applications of several types of artificial neural networks to compound classification, modelling of structure-activity relationships, biological target identification, and feature extraction from biopolymers are presented and compared to other techniques. Advantages and limitations of neural networks for computer-aided molecular design and sequence analysis are discussed.

An Integrated Sequence-Structure Database incorporating matching mRNA sequence, amino acid sequence and protein three-dimensional structure data

We have constructed a non-homologous database, termed the Integrated Sequence-Structure Database (ISSD) which comprises the coding sequences of genes, amino acid sequences of the corresponding proteins, their secondary structure and straight phi,psi angles assignments, and polypeptide backbone coordinates. Each protein entry in the database holds the alignment of nucleotide sequence, amino acid sequence and the PDB three-dimensional structure data. The nucleotide and amino acid sequences for each entry are selected on the basis of exact matches of the source organism and cell environment. The current version 1.0 of ISSD is available on the WWW at http://www.protein.bio.msu.su/issd/ and includes 107 non-homologous mammalian proteins, of which 80 are human proteins. The database has been used by us for the analysis of synonymous codon usage patterns in mRNA sequences showing their correlation with the three-dimensional structure features in the encoded proteins. Possible ISSD applications include optimisation of protein expression, improvement of the protein structure prediction accuracy, and analysis of evolutionary aspects of the nucleotide sequence-protein structure relationship.