Proteome-Wide Structural Computations Provide Insights into Empirical Amino Acid Substitution Matrices
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PROVIDER: S-EPMC9821064 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:Proteins evolve under a myriad of biophysical selection pressures that collectively control the patterns of amino acid substitutions. These evolutionary pressures are sufficiently consistent over time and across protein families to produce substitution patterns, summarized in global amino acid substitution matrices such as BLOSUM, JTT, WAG, and LG, which can be used to successfully detect homologs, infer phylogenies, and reconstruct ancestral sequences. Although the factors that govern the variation of amino acid substitution rates have received much attention, the influence of thermodynamic stability constraints remains unresolved. Here we develop a simple model to calculate amino acid substitution matrices from evolutionary dynamics controlled by a fitness function that reports on the thermodynamic effects of amino acid mutations in protein structures. This hybrid biophysical and evolutionary model accounts for nucleotide transition/transversion rate bias, multi-nucleotide codon changes, the number of codons per amino acid, and thermodynamic protein stability. We find that our theoretical model accurately recapitulates the complex yet universal pattern observed in common global amino acid substitution matrices used in phylogenetics. These results suggest that selection for thermodynamically stable proteins, coupled with nucleotide mutation bias filtered by the structure of the genetic code, is the primary driver behind the global amino acid substitution patterns observed in proteins throughout the tree of life.
| S-EPMC8442976 | biostudies-literature
Project description:Amino acid substitution matrices are central to protein-comparison methods. In most commonly used matrices, the substitution scores take a log-odds form, involving the ratio of "target" to "background" frequencies derived from large, carefully curated sets of protein alignments. However, such matrices often are used to compare protein sequences with amino acid compositions that differ markedly from the background frequencies used for the construction of the matrices. Of course, the target frequencies should be adjusted in such cases, but the lack of an appropriate way to do this has been a long-standing problem. This article shows that if one demands consistency between target and background frequencies, then a log-odds substitution matrix implies a unique set of target and background frequencies as well as a unique scale. Standard substitution matrices therefore are truly appropriate only for the comparison of proteins with standard amino acid composition. Accordingly, we present and evaluate a rationale for transforming the target frequencies implicit in a standard matrix to frequencies appropriate for a nonstandard context. This rationale yields asymmetric matrices for the comparison of proteins with divergent compositions. Earlier approaches are unable to deal with this case in a fully consistent manner. Composition-specific substitution matrix adjustment is shown to be of utility for comparing compositionally biased proteins, including those of organisms with nucleotide-biased, and therefore codon-biased, genomes or isochores.
| S-EPMC307629 | biostudies-literature
Project description:Human genetic variation in coding regions is fundamental to the study of protein structure and function. Most methods for interpreting missense variants consider substitution measures derived from homologous proteins across different species. In this study, we introduce human-specific amino acid (AA) substitution matrices that are based on genetic variations in the modern human population. We analyzed the frequencies of >4.8M single nucleotide variants (SNVs) at codon and AA resolution and compiled human-centric substitution matrices that are fundamentally different from classic cross-species matrices (e.g. BLOSUM, PAM). Our matrices are asymmetric, with some AA replacements showing significant directional preference. Moreover, these AA matrices are only partly predicted by nucleotide substitution rates. We further test the utility of our matrices in exposing functional signals of experimentally-validated protein annotations. A significant reduction in AA transition frequencies was observed across nine post-translational modification (PTM) types and four ion-binding sites. Our results propose a purifying selection signal in the human proteome across a diverse set of functional protein annotations and provide an empirical baseline for interpreting human genetic variation in coding regions.
| S-EPMC8445205 | biostudies-literature
Project description:An amino acid substitution scoring matrix encapsulates the rates at which various amino acid residues in proteins are substituted by other amino acid residues, over time. Database search methods make use of substitution scoring matrices to identify sequences with homologous relationships. However, widely used substitution scoring matrices, such as BLOSUM series, have been developed using aligned blocks that are mostly devoid of disordered regions in proteins. Hence, these substitution-scoring matrices are mostly inappropriate for homology searches involving proteins enriched with disordered regions as the disordered regions have distinct amino acid compositional bias, and therefore expected to have undergone amino acid substitutions that are distinct from those in the ordered regions. We, therefore, developed a novel series of substitution scoring matrices referred to as EDSSMat by exclusively considering the substitution frequencies of amino acids in the disordered regions of the eukaryotic proteins. The newly developed matrices were tested for their ability to detect homologs of proteins enriched with disordered regions by means of SSEARCH tool. The results unequivocally demonstrate that EDSSMat matrices detect more number of homologs than the widely used BLOSUM, PAM and other standard matrices, indicating their utility value for homology searches of intrinsically disordered proteins.
| S-EPMC6841959 | biostudies-literature
Project description:MOTIVATION: Although many amino acid substitution matrices have been developed, it has not been well understood which is the best for similarity searches, especially for remote homology detection. Therefore, we collected information related to existing matrices, condensed it and derived a novel matrix that can detect more remote homology than ever. RESULTS: Using principal component analysis with existing matrices and benchmarks, we developed a novel matrix, which we designate as MIQS. The detection performance of MIQS is validated and compared with that of existing general purpose matrices using SSEARCH with optimized gap penalties for each matrix. Results show that MIQS is able to detect more remote homology than the existing matrices on an independent dataset. In addition, the performance of our developed matrix was superior to that of CS-BLAST, which was a novel similarity search method with no amino acid matrix. We also evaluated the alignment quality of matrices and methods, which revealed that MIQS shows higher alignment sensitivity than that with the existing matrix series and CS-BLAST. Fundamentally, these results are expected to constitute good proof of the availability and/or importance of amino acid matrices in sequence analysis. Moreover, with our developed matrix, sophisticated similarity search methods such as sequence-profile and profile-profile comparison methods can be improved further. AVAILABILITY AND IMPLEMENTATION: Newly developed matrices and datasets used for this study are available at http://csas.cbrc.jp/Ssearch/.
| S-EPMC3904525 | biostudies-other
Project description:Microsatellites or simple sequence repeats (SSR) are abundant, highly diverse stretches of short DNA repeats present in all genomes. Tandem mono/tri/hexanucleotide repeats in the coding regions contribute to single amino acids repeats (SAARs) in the proteome. While SSRs in the coding region always result in amino acid repeats, a majority of SAARs arise due to a combination of various codons representing the same amino acid and not as a consequence of SSR events. Certain amino acids are abundant in repeat regions indicating a positive selection pressure behind the accumulation of SAARs. By analysing 22 proteomes including the human proteome, we explored the functional and structural relationship of amino acid repeats in an evolutionary context. Only ~15% of repeats are present in any known functional domain, while ~74% of repeats are present in the disordered regions, suggesting that SAARs add to the functionality of proteins by providing flexibility, stability and act as linker elements between domains. Comparison of SAAR containing proteins across species reveals that while shorter repeats are conserved among orthologs, proteins with longer repeats, >15 amino acids, are unique to the respective organism. Lysine repeats are well conserved among orthologs with respect to their length and number of occurrences in a protein. Other amino acids such as glutamic acid, proline, serine and alanine repeats are generally conserved among the orthologs with varying repeat lengths. These findings suggest that SAARs have accumulated in the proteome under positive selection pressure and that they provide flexibility for optimal folding of functional/structural domains of proteins. The insights gained from our observations can help in effective designing and engineering of proteins with novel features.
| S-EPMC5125637 | biostudies-literature
Project description:BackgroundSequence comparisons make use of a one-letter representation for amino acids, the necessary quantitative information being supplied by the substitution matrices. This paper deals with the problem of finding a representation that provides a comprehensive description of amino acid intrinsic properties consistent with the substitution matrices.ResultsWe present a Euclidian vector representation of the amino acids, obtained by the singular value decomposition of the substitution matrices. The substitution matrix entries correspond to the dot product of amino acid vectors. We apply this vector encoding to the study of the relative importance of various amino acid physicochemical properties upon the substitution matrices. We also characterize and compare the PAM and BLOSUM series substitution matrices.ConclusionsThis vector encoding introduces a Euclidian metric in the amino acid space, consistent with substitution matrices. Such a numerical description of the amino acid is useful when intrinsic properties of amino acids are necessary, for instance, building sequence profiles or finding consensus sequences, using machine learning algorithms such as Support Vector Machine and Neural Networks algorithms.
| S-EPMC3098074 | biostudies-literature
Project description:The genomic era has seen a remarkable increase in the number of genomes being sequenced and annotated. Nonetheless, annotation remains a serious challenge for compositionally biased genomes. For the preliminary annotation, popular nucleotide and protein comparison methods such as BLAST are widely employed. These methods make use of matrices to score alignments such as the amino acid substitution matrices. Since a nucleotide bias leads to an overall bias in the amino acid composition of proteins, it is possible that a genome with nucleotide bias may have introduced atypical amino acid substitutions in its proteome. Consequently, standard matrices fail to perform well in sequence analysis of these genomes. To address this issue, we examined the amino acid substitution in the AT-rich genome of Plasmodium falciparum, chosen as a reference and reconstituted a substitution matrix in the genome's context. The matrix was used to generate protein sequence alignments for the parasite proteins that improved across the functional regions. We attribute this to the consistency that may have been achieved amid the target and background frequencies calculated exclusively in our study. This study has important implications on annotation of proteins that are of experimental interest but give poor sequence alignments with standard conventional matrices.
| S-EPMC2588515 | biostudies-literature
Project description:The root-knot nematode Meloidogyne graminicola is an important pathogen in rice, causing huge yield losses annually worldwide. Details of the interaction between rice and M. graminicola and the resistance genes in rice still remain unclear. In this study, proteome-wide analyses of the compatible interaction of the japonica rice cultivar "Nipponbare" (NPB) with M. graminicola were performed. In total, 6072 proteins were identified in NPB roots with and without infection of M. graminicola by label-free quantitative mass spectrometry. Of these, 513 specifically or significantly differentially expressed proteins were identified to be uniquely caused by nematode infection. Among these unique proteins, 99 proteins were enriched on seven Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. By comparison of protein expression and gene transcription, LOC_Os01g06600 (ACX, a glutaryl-CoA dehydrogenase), LOC_Os09g23560 (CAD, a cinnamyl-alcohol dehydrogenase), LOC_Os03g39850 (GST, a glutathione S-transferase) and LOC_Os11g11960 (RPM1, a disease resistance protein) on the alpha-linolenic acid metabolism, phenylpropanoid biosynthesis, glutathione metabolism and plant-pathogen interaction pathways, respectively, were all associated with disease defense and identified to be significantly down-regulated in the compatible interaction of NPB with nematodes, while the corresponding genes were remarkably up-regulated in the roots of a resistant rice accession "Khao Pahk Maw" with infection of nematodes. These four genes likely played important roles in the compatible interaction of rice with M. graminicola. Conversely, these disease defense-related genes were hypothesized to be likely involved in the resistance of resistant rice lines to this nematode. The proteome-wide analyses provided many new insights into the interaction of rice with M. graminicola.
| S-EPMC7460654 | biostudies-literature
Project description:BACKGROUND:Amino acid substitution models play an important role in inferring phylogenies from proteins. Although different amino acid substitution models have been proposed, only a few were estimated from mitochondrial protein sequences for specific taxa such as the mtArt model for Arthropoda. The increasing of mitochondrial genome data from broad Orthoptera taxa provides an opportunity to estimate the Orthoptera-specific mitochondrial amino acid empirical model. RESULTS:We sequenced complete mitochondrial genomes of 54 Orthoptera species, and estimated an amino acid substitution model (named mtOrt) by maximum likelihood method based on the 283 complete mitochondrial genomes available currently. The results indicated that there are obvious differences between mtOrt and the existing models, and the new model can better fit the Orthoptera mitochondrial protein datasets. Moreover, topologies of trees constructed using mtOrt and existing models are frequently different. MtOrt does indeed have an impact on likelihood improvement as well as tree topologies. The comparisons between the topologies of trees constructed using mtOrt and existing models show that the new model outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein data. CONCLUSIONS:The new mitochondrial amino acid substitution model of Orthoptera shows obvious differences from the existing models, and outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein sequences.
| S-EPMC7236349 | biostudies-literature