The evolution of proteins from random amino acid sequences. I. Evidence from the lengthwise distribution of amino acids in modern protein sequences

1993 ◽  
Vol 36 (1) ◽  
pp. 79-95 ◽  
Author(s):  
Stephen H. White ◽  
Russell E. Jacobs
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Protein Sequences ◽  
Amino Acid Sequences ◽  
Evolution Of Proteins

scholarly journals BIOPEP-UWM Database of Bioactive Peptides: Current Opportunities

2019 ◽  
Vol 20 (23) ◽  
pp. 5978 ◽  
Author(s):  
Minkiewicz ◽  
Iwaniak ◽  
Darewicz
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Chronic Diseases ◽  
Bioactive Peptides ◽  
Protein Sequences ◽  
Batch Processing ◽  
Amino Acid Sequences ◽  
Quantitative Parameters ◽  
New Information

The BIOPEP-UWM™ database of bioactive peptides (formerly BIOPEP) has recently become a popular tool in the research on bioactive peptides, especially on these derived from foods and being constituents of diets that prevent development of chronic diseases. The database is continuously updated and modified. The addition of new peptides and the introduction of new information about the existing ones (e.g., chemical codes and references to other databases) is in progress. New opportunities include the possibility of annotating peptides containing D-enantiomers of amino acids, batch processing option, converting amino acid sequences into SMILES code, new quantitative parameters characterizing the presence of bioactive fragments in protein sequences, and finding proteinases that release particular peptides.

scholarly journals Analisis Pohon Filogenik dari Protein Non-Struktural 1 (NS1) Virus Dengue di Kawasan Asia Tenggara

2011 ◽  
Vol 1 (2) ◽  
pp. 69
Author(s):  
Vanny Narita ◽  
Asma Omar ◽  
Agus Masduki
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Dengue Virus ◽  
Protein Sequences ◽  
Amino Acid Sequences ◽  
South East Asia ◽  
Phylogenetic Relation ◽  
Phylogenetic Tree Analysis ◽  
Tree Analysis ◽  
Different Strains

<p style="text-align: justify;" align="center">Protein non-struktural 1 adalah protein Virus Dengue yang terkonservasi, tetapi protein non-struktural 1 dari Virus Dengue yang berbeda strain memiliki epitop berbeda yang dapat dikenali oleh sel-B. Epitop-epitop ini mungkin disusun oleh asam amino yang sama dalam urutan yang berbeda. Kemungkinan ini perlu dipertimbangkan dalam rangka memprediksi epitop sekuensial Virus Dengue. Tujuan penelitian kami adalah menganalisis hubungan kekerabatan dan susunan asam amino pada epitop spesifik yang telah dikonfirmasi dari sampel representatif gen protein NS1 dari Virus Dengue di kawasan Asia Tenggara. Hubungan kekerabatan protein non-struktural 1 dianalisis dengan perangkat lunak Lasergene<sup>®</sup>. Sekuen gen ditranslasi terlebih dahulu ke urutan asam amino, dan analisis pohon filogenetik kemudian dilakukan. Hasilnya menunjukkan bahwa hubungan kekerabatan protein non-struktural 1 berkisar antara 72-98%. Selanjutnya, epitop serospesifik dibandingkan berdasarkan hasil pengolahan data dnegan Lasergene. Perbandingan epitop serospesifik menunjukkan bahwa asam amino yang dominan dalam epitop adalah histidin, tirosin, glutamine dan serin</p><h6 style="text-align: center;"><em> </em><em> </em><strong>Abstract</strong></h6>Non-structural 1 protein is a conserved protein of dengue virus, but non-structural 1 proteins of dengue virus from different strains have different epitopes which can be recognized by B-cell. These epitopes may be constructed of similar amino acids in a different arrangement. This possibility  must be considered in order to predict the sequencial epitope of dengue virus. The objective of our study was to analyze the phylogenetic relation and the arrangment of confirmed specific epitopes of dengue strains  from representatives of South East Asia’s NS1 dengue gene samples. The phylogenetic relation of non-structural 1 protein sequences from South East Asia was analyzed with Lasergene<sup>®</sup> software. The gene sequences were translated to amino acid sequences, and phylogenetic tree analysis was performed. The results showed that the relatedness values among full sequences of non-structural 1 protein were 72-98%. Furthermore, the serospesific epitopes were compared according to the Lasergene results. The serospesific epitope comparation showed that the dominant   amino acids in these epitopes were histidine, tyrosine, glutamine and serine.

scholarly journals 13C-NMR sonification of human insulin: a method for conversion of amino-acid sequences to music notes

2019 ◽  
Vol 9 (4) ◽  
pp. 4077-4084
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Human Insulin ◽  
Chemical Shifts ◽  
Protein Sequences ◽  
Amino Acid Sequences ◽  
Time Duration ◽  
Resonant Frequencies ◽  
Chemical Systems ◽  
Nmr Data

The concept of molecular sonification comprises total steps of methods that convert the physical data derived from chemical systems into acousmatic music. NMR data of the 13C are especially well suited data sources for Insulin sonification. Even though their resonant frequencies are typically in the MHz region, the resonant frequencies span around kHz. The human insulin is consisting of 51 amino acids which can be divided into 7 series of amino acids for seven octaves of notes. During NMR calculation with ab-initio methods, these signals are routinely mixed down into the audible frequencies ranges, rendering the need for any additional frequencies transpositions unnecessary. By this work, insulin protein sequences into musical notes to reveal auditory algorithms have been converted. Calculation and optimization of 20 amino acids have been done and the total frequencies of each amino acid have been converted to 20 music notes and distinguishing those using variations of chemical shifts including pitch, time duration length of notes and even rhythm have been accomplished.

scholarly journals Annotating Gene Ontology terms for protein sequences with the Transformer model

2020 ◽  
Author(s):  
Dat Duong ◽  
Lisa Gai ◽  
Ankith Uppunda ◽  
Don Le ◽  
Eleazar Eskin ◽  
...  
Keyword(s):  
Neural Network ◽  
Amino Acids ◽  
Gene Ontology ◽  
Amino Acid ◽  
3D Structure ◽  
Protein Sequences ◽  
Amino Acid Sequences ◽  
Training Dataset ◽  
Go Annotation ◽  
Go Terms

AbstractPredicting functions for novel amino acid sequences is a long-standing research problem. The Uniprot database which contains protein sequences annotated with Gene Ontology (GO) terms, is one commonly used training dataset for this problem. Predicting protein functions can then be viewed as a multi-label classification problem where the input is an amino acid sequence and the output is a set of GO terms. Recently, deep convolutional neural network (CNN) models have been introduced to annotate GO terms for protein sequences. However, the CNN architecture can only model close-range interactions between amino acids in a sequence. In this paper, first, we build a novel GO annotation model based on the Transformer neural network. Unlike the CNN architecture, the Transformer models all pairwise interactions for the amino acids within a sequence, and so can capture more relevant information from the sequences. Indeed, we show that our adaptation of Transformer yields higher classification accuracy when compared to the recent CNN-based method DeepGO. Second, we modify our model to take motifs in the protein sequences found by BLAST as additional input features. Our strategy is different from other ensemble approaches that average the outcomes of BLAST-based and machine learning predictors. Third, we integrate into our Transformer the metadata about the protein sequences such as 3D structure and protein-protein interaction (PPI) data. We show that such information can greatly improve the prediction accuracy, especially for rare GO labels.

Computational Analysis of Therapeutic Enzyme Uricase from Different Source Organisms

2020 ◽  
Vol 17 (1) ◽  
pp. 59-77
Author(s):  
Anand Kumar Nelapati ◽  
JagadeeshBabu PonnanEttiyappan
Keyword(s):  
Uric Acid ◽  
Amino Acid ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Protein Sequences ◽  
Amino Acid Sequences ◽  
Amino Acid Residues ◽  
Multiple Sequence ◽  
Physiochemical Properties ◽  
Pharmaceutical Industries

Background:Hyperuricemia and gout are the conditions, which is a response of accumulation of uric acid in the blood and urine. Uric acid is the product of purine metabolic pathway in humans. Uricase is a therapeutic enzyme that can enzymatically reduces the concentration of uric acid in serum and urine into more a soluble allantoin. Uricases are widely available in several sources like bacteria, fungi, yeast, plants and animals.Objective:The present study is aimed at elucidating the structure and physiochemical properties of uricase by insilico analysis.Methods:A total number of sixty amino acid sequences of uricase belongs to different sources were obtained from NCBI and different analysis like Multiple Sequence Alignment (MSA), homology search, phylogenetic relation, motif search, domain architecture and physiochemical properties including pI, EC, Ai, Ii, and were performed.Results:Multiple sequence alignment of all the selected protein sequences has exhibited distinct difference between bacterial, fungal, plant and animal sources based on the position-specific existence of conserved amino acid residues. The maximum homology of all the selected protein sequences is between 51-388. In singular category, homology is between 16-337 for bacterial uricase, 14-339 for fungal uricase, 12-317 for plants uricase, and 37-361 for animals uricase. The phylogenetic tree constructed based on the amino acid sequences disclosed clusters indicating that uricase is from different source. The physiochemical features revealed that the uricase amino acid residues are in between 300- 338 with a molecular weight as 33-39kDa and theoretical pI ranging from 4.95-8.88. The amino acid composition results showed that valine amino acid has a high average frequency of 8.79 percentage compared to different amino acids in all analyzed species.Conclusion:In the area of bioinformatics field, this work might be informative and a stepping-stone to other researchers to get an idea about the physicochemical features, evolutionary history and structural motifs of uricase that can be widely used in biotechnological and pharmaceutical industries. Therefore, the proposed in silico analysis can be considered for protein engineering work, as well as for gout therapy.

scholarly journals Roles of the C-Terminal Amino Acids of Non-Hexameric Helicases: Insights from Escherichia coli UvrD

2021 ◽  
Vol 22 (3) ◽  
pp. 1018
Author(s):  
Hiroaki Yokota
Keyword(s):  
Escherichia Coli ◽  
Amino Acids ◽  
Amino Acid ◽  
Single Molecule ◽  
Underlying Mechanism ◽  
Amino Acid Sequences ◽  
E Coli ◽  
X Ray Crystallography ◽  
Terminal Amino

Helicases are nucleic acid-unwinding enzymes that are involved in the maintenance of genome integrity. Several parts of the amino acid sequences of helicases are very similar, and these quite well-conserved amino acid sequences are termed “helicase motifs”. Previous studies by X-ray crystallography and single-molecule measurements have suggested a common underlying mechanism for their function. These studies indicate the role of the helicase motifs in unwinding nucleic acids. In contrast, the sequence and length of the C-terminal amino acids of helicases are highly variable. In this paper, I review past and recent studies that proposed helicase mechanisms and studies that investigated the roles of the C-terminal amino acids on helicase and dimerization activities, primarily on the non-hexermeric Escherichia coli (E. coli) UvrD helicase. Then, I center on my recent study of single-molecule direct visualization of a UvrD mutant lacking the C-terminal 40 amino acids (UvrDΔ40C) used in studies proposing the monomer helicase model. The study demonstrated that multiple UvrDΔ40C molecules jointly participated in DNA unwinding, presumably by forming an oligomer. Thus, the single-molecule observation addressed how the C-terminal amino acids affect the number of helicases bound to DNA, oligomerization, and unwinding activity, which can be applied to other helicases.

scholarly journals The amino acid sequence of cytochromes c-551 from three species of Pseudomonas

1973 ◽  
Vol 131 (3) ◽  
pp. 485-498 ◽  
Author(s):  
R. P. Ambler ◽  
Margaret Wynn
Keyword(s):  
Amino Acids ◽  
Pseudomonas Aeruginosa ◽  
Amino Acid ◽  
Cytochrome C ◽  
Amino Acid Sequence ◽  
Amino Acid Sequences ◽  
Mitochondrial Cytochrome ◽  
Cytochromes C ◽  
Lending Library ◽  
Single Peptide

The amino acid sequences of the cytochromes c-551 from three species of Pseudomonas have been determined. Each resembles the protein from Pseudomonas strain P6009 (now known to be Pseudomonas aeruginosa, not Pseudomonas fluorescens) in containing 82 amino acids in a single peptide chain, with a haem group covalently attached to cysteine residues 12 and 15. In all four sequences 43 residues are identical. Although by bacteriological criteria the organisms are closely related, the differences between pairs of sequences range from 22% to 39%. These values should be compared with the differences in the sequence of mitochondrial cytochrome c between mammals and amphibians (about 18%) or between mammals and insects (about 33%). Detailed evidence for the amino acid sequences of the proteins has been deposited as Supplementary Publication SUP 50015 at the National Lending Library for Science and Technology, Boston Spa, Yorks. LS23 7BQ, U.K., from whom copies can be obtained on the terms indicated in Biochem. J. (1973), 131, 5.

scholarly journals Functional Analysis of PA Binding by Influenza A Virus PB1: Effects on Polymerase Activity and Viral Infectivity

2001 ◽  
Vol 75 (17) ◽  
pp. 8127-8136 ◽  
Author(s):  
Daniel R. Perez ◽  
Ruben O. Donis
Keyword(s):  
Amino Acids ◽  
Influenza Virus ◽  
Amino Acid ◽  
Viral Replication ◽  
Influenza A Virus ◽  
Influenza A ◽  
Amino Acid Sequences ◽  
Influenza Viruses ◽  
Virus Growth ◽  
Transcription And Replication

ABSTRACT Influenza A virus expresses three viral polymerase (P) subunits—PB1, PB2, and PA—all of which are essential for RNA and viral replication. The functions of P proteins in transcription and replication have been partially elucidated, yet some of these functions seem to be dependent on the formation of a heterotrimer for optimal viral RNA transcription and replication. Although it is conceivable that heterotrimer subunit interactions may allow a more efficient catalysis, direct evidence of their essentiality for viral replication is lacking. Biochemical studies addressing the molecular anatomy of the P complexes have revealed direct interactions between PB1 and PB2 as well as between PB1 and PA. Previous studies have shown that the N-terminal 48 amino acids of PB1, termed domain α, contain the residues required for binding PA. We report here the refined mapping of the amino acid sequences within this small region of PB1 that are indispensable for binding PA by deletion mutagenesis of PB1 in a two-hybrid assay. Subsequently, we used site-directed mutagenesis to identify the critical amino acid residues of PB1 for interaction with PA in vivo. The first 12 amino acids of PB1 were found to constitute the core of the interaction interface, thus narrowing the previous boundaries of domain α. The role of the minimal PB1 domain α in influenza virus gene expression and genome replication was subsequently analyzed by evaluating the activity of a set of PB1 mutants in a model reporter minigenome system. A strong correlation was observed between a functional PA binding site on PB1 and P activity. Influenza viruses bearing mutant PB1 genes were recovered using a plasmid-based influenza virus reverse genetics system. Interestingly, mutations that rendered PB1 unable to bind PA were either nonviable or severely growth impaired. These data are consistent with an essential role for the N terminus of PB1 in binding PA, P activity, and virus growth.

Sequence and expression of the dCMP deaminase gene (DCD1) of Saccharomyces cerevisiae

1986 ◽  
Vol 6 (5) ◽  
pp. 1711-1721
Author(s):  
E M McIntosh ◽  
R H Haynes
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Amino Acids ◽  
Amino Acid ◽  
Amino Acid Sequences ◽  
Open Reading Frame ◽  
Northern Analysis ◽  
Hindiii Site ◽  
Reading Frame ◽  
Hindiii Restriction Site ◽  
Cycle Dependent

The dCMP deaminase gene (DCD1) of Saccharomyces cerevisiae has been isolated by screening a Sau3A clone bank for complementation of the dUMP auxotrophy exhibited by dcd1 dmp1 haploids. Plasmid pDC3, containing a 7-kilobase (kb) Sau3A insert, restores dCMP deaminase activity to dcd1 mutants and leads to an average 17.5-fold overproduction of the enzyme in wild-type cells. The complementing activity of the plasmid was localized to a 4.2-kb PvuII restriction fragment within the Sau3A insert. Subcloning experiments demonstrated that a single HindIII restriction site within this fragment lies within the DCD1 gene. Subsequent DNA sequence analysis revealed a 936-nucleotide open reading frame encompassing this HindIII site. Disruption of the open reading frame by integrative transformation led to a loss of enzyme activity and confirmed that this region constitutes the dCMP deaminase gene. Northern analysis indicated that the DCD1 mRNA is a 1.15-kb poly(A)+ transcript. The 5' end of the transcript was mapped by primer extension and appears to exhibit heterogeneous termini. Comparison of the amino acid sequence of the T2 bacteriophage dCMP deaminase with that deduced for the yeast enzyme revealed a limited degree of homology which extends over the entire length of the phage polypeptide (188 amino acids) but is confined to the carboxy-terminal half of the yeast protein (312 amino acids). A potential dTTP-binding site in the yeast and phage enzymes was identified by comparison of homologous regions with the amino acid sequences of a variety of other dTTP-binding enzymes. Despite the role of dCMP deaminase in dTTP biosynthesis, Northern analysis revealed that the DCD1 gene is not subject to the same cell cycle-dependent pattern of transcription recently found for the yeast thymidylate synthetase gene (TMP1).

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