scholarly journals Computational Studies on Photolyase (Phr) Proteins of Cyanobacteria

2021 ◽  
Author(s):  
Rajneesh - ◽  
Soumila Mondal ◽  
Jainendra Pathak ◽  
Prashant R. Singh ◽  
Shailendra P. Singh ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Active Site ◽  
Binding Sites ◽  
Structural Information ◽  
Interaction Analysis ◽  
3D Structure ◽  
Length Distribution ◽  
Amino Acid Sequences ◽  
Ligand Interaction

Photolyases (Phrs) are enzymes that utilize blue/ultraviolet (UV-A) region of light for repairing UV-induced cyclopyramidine dimer. We have studied Phr groups by bioinformatic analyses as well as active-site and structural modeling. The analysis of 238 amino acid sequences from 85 completely sequenced cyanobacterial genomes revealed five classes of Phrs, i.e., CPD Gr I, 6-4 Phrs/cryptochrome, Cry-DASH, Fe-S bacteria Phrs, and a group having fewer number of amino acids (276-385) in length. Distribution of Phr groups in cyanobacteria belonging to the order Synechococcales was found to be influenced by the habitats of the organisms. Class V Phrs were exclusively present in cyanobacteria. Unique motif and binding sites were reported in Group II and III. Fe-S protein binding site was only present in Group V. Active site residues and putative CPD/6-4pp binding residues are charged amino acids which were present on the surface of the proteins. Majority of hydrophilic amino acid residues were present on surface of Phrs. Sequence analysis confirmed the diverse nature of Phrs, though, sequence diversity does not affect their overall 3D structure. Protein-ligand interaction analysis identified novel CPD/6-4PP binding sites on Phrs. This structural information of Phrs can be used for the preparation of efficient Phr based formulations.

scholarly journals The Extracellular Transport Signal of the Vibrio cholerae Endochitinase (ChiA) Is a Structural Motif Located between Amino Acids 75 and 555

2002 ◽  
Vol 184 (8) ◽  
pp. 2225-2234 ◽  
Author(s):  
Jason P. Folster ◽  
Terry D. Connell
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Vibrio Cholerae ◽  
Structural Information ◽  
Amino Acid Sequences ◽  
Structural Motif ◽  
Terminal Branch ◽  
C Terminus ◽  
N Terminus ◽  
Extracellular Transport

ABSTRACT ChiA, an 88-kDa endochitinase encoded by the chiA gene of the gram-negative enteropathogen Vibrio cholerae, is secreted via the eps-encoded main terminal branch of the general secretory pathway (GSP), a mechanism which also transports cholera toxin. To localize the extracellular transport signal of ChiA that initiates transport of the protein through the GSP, a chimera comprised of ChiA fused at the N terminus with the maltose-binding protein (MalE) of Escherichia coli and fused at the C terminus with a 13-amino-acid epitope tag (E-tag) was expressed in strain 569B(chiA::Kanr), a chiA-deficient but secretion-competent mutant of V. cholerae. Fractionation studies revealed that blockage of the natural N terminus and C terminus of ChiA did not prevent secretion of the MalE-ChiA-E-tag chimera. To locate the amino acid sequences which encoded the transport signal, a series of truncations of ChiA were engineered. Secretion of the mutant polypeptides was curtailed only when ChiA was deleted from the N terminus beyond amino acid position 75 or from the C terminus beyond amino acid 555. A mutant ChiA comprised of only those amino acids was secreted by wild-type V. cholerae but not by an epsD mutant, establishing that amino acids 75 to 555 independently harbored sufficient structural information to promote secretion by the GSP of V. cholerae. Cys77 and Cys537, two cysteines located just within the termini of ChiA(75-555), were not required for secretion, indicating that those residues were not essential for maintaining the functional activity of the ChiA extracellular transport signal.

PREDICTION OF THE THREE-DIMENSIONAL STRUCTURE OF THE ENZYMATIC PART OF T-PA

1987 ◽  
Author(s):  
A Heckel ◽  
K M Hasselbach
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Active Site ◽  
Serine Proteases ◽  
Three Dimensional ◽  
Amino Acid Sequences ◽  
Dimensional Structure ◽  
Salt Bridges ◽  
Three Dimensional Structure ◽  
Insertions And Deletions

Up to now the three-dimensional structure of t-PA or parts of this enzyme is unknown. Using computer graphical methods the spatial structure of the enzymatic part of t-PA is predicted on the hypothesis, the three-dimensional backbone structure of t-PA being similar to that of other serine proteases. The t-PA model was built up in three steps:1) Alignment of the t-PA sequence with other serine proteases. Comparison of enzyme structures available from Brookhaven Protein Data Bank proved elastase as a basis for modeling.2) Exchange of amino acids of elastase differing from the t-PA sequence. The replacement of amino acids was performed such that backbone atoms overlapp completely and side chains superpose as far as possible.3) Modeling of insertions and deletions. To determine the spatial arrangement of insertions and deletions parts of related enzymes such as chymotrypsin or trypsin were used whenever possible. Otherwise additional amino acid sequences were folded to a B-turn at the surface of the proteine, where all insertions or deletions are located. Finally the side chain torsion angles of amino acids were optimised to prevent close contacts of neigh bouring atoms and to improve hydrogen bonds and salt bridges.The resulting model was used to explain binding of arginine 560 of plasminogen to the active site of t-PA. Arginine 560 interacts with Asp 189, Gly 19 3, Ser 19 5 and Ser 214 of t-PA (chymotrypsin numbering). Furthermore interaction of chromo-genic substrate S 2288 with the active site of t-PA was studied. The need for D-configuration of the hydrophobic amino acid at the N-terminus of this tripeptide derivative could be easily explained.

Nucleotide and Amino Acid Sequences of the Metallo-β-Lactamase, ImiS, from Aeromonas veronii bv. sobria

1998 ◽  
Vol 42 (2) ◽  
pp. 436-439 ◽  
Author(s):  
T. R. Walsh ◽  
W. A. Neville ◽  
M. H. Haran ◽  
D. Tolson ◽  
D. J. Payne ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Active Site ◽  
Amino Acid Sequences ◽  
Open Reading Frame ◽  
Reading Frame ◽  
Aeromonas Veronii ◽  
Putative Active Site ◽  
Lactamase Gene ◽  
Active Site Sequence

ABSTRACT The Aeromonas veronii bv. sobria metallo-β-lactamase gene, imiS, was cloned. The imiS open reading frame extends for 762 bp and encodes a protein of 254 amino acids with a secreted modified protein of 227 amino acids and a predicted pI of 8.1. To confirm the predicted sequence, purified ImiS was digested and the resulting peptides were identified, yielding an identical sequence for ImiS, with 98% identity to CphA. Both possessed the putative active-site sequence Asn-Tyr-His-Thr-Asp at positions 88 to 92, which is unique to the Aeromonas metallo-β-lactamases.

scholarly journals miR-1322 Binding Sites in Paralogous and Orthologous Genes

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Raigul Niyazova ◽  
Olga Berillo ◽  
Shara Atambayeva ◽  
Anna Pyrkova ◽  
Aigul Alybayeva ◽  
...  
Keyword(s):  
Amino Acids ◽  
Transcription Factors ◽  
Amino Acid ◽  
Binding Site ◽  
Binding Sites ◽  
Target Genes ◽  
Amino Acid Sequences ◽  
Orthologous Genes ◽  
Start Position ◽  
Human Genes

We searched for 2,563 microRNA (miRNA) binding sites in 17,494 mRNA sequences of human genes. miR-1322 has more than 2,000 binding sites in 1,058 genes withΔG/ΔGmratio of 85% and more. miR-1322 has 1,889 binding sites in CDSs, 215 binding sites in 5′ UTRs, and 160 binding sites in 3′ UTRs. From two to 28 binding sites have arranged localization with the start position through three nucleotides of each following binding site. The nucleotide sequences of these sites in CDSs encode oligopeptides with the same and/or different amino acid sequences. We found that 33% of the target genes encoded transcription factors. miR-1322 has arranged binding sites in the CDSs of orthologousMAMLD1,MAML2, andMAML3genes. These sites encode a polyglutamine oligopeptide ranging from six to 47 amino acids in length. The properties of miR-1322 binding sites in orthologous and paralogous target genes are discussed.

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.

scholarly journals A sequence embedding method for enzyme optimal condition analysis

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiangjun Li ◽  
Zhixin Dou ◽  
Yuqing Sun ◽  
Lushan Wang ◽  
Bin Gong ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Optimal Condition ◽  
Tertiary Structure ◽  
Structural Information ◽  
Amino Acid Sequences ◽  
Computational Method ◽  
Embedding Method ◽  
Latent Space ◽  
Probabilistic Approximation

Abstract Background An enzyme activity is influenced by the external environment. It is important to have an enzyme remain high activity in a specific condition. A usual way is to first determine the optimal condition of an enzyme by either the gradient test or by tertiary structure, and then to use protein engineering to mutate a wild type enzyme for a higher activity in an expected condition. Results In this paper, we investigate the optimal condition of an enzyme by directly analyzing the sequence. We propose an embedding method to represent the amino acids and the structural information as vectors in the latent space. These vectors contain information about the correlations between amino acids and sites in the aligned amino acid sequences, as well as the correlation with the optimal condition. We crawled and processed the amino acid sequences in the glycoside hydrolase GH11 family, and got 125 amino acid sequences with optimal pH condition. We used probabilistic approximation method to implement the embedding learning method on these samples. Based on these embedding vectors, we design a computational score to determine which one has a better optimal condition for two given amino acid sequences and achieves the accuracy 80% on the test proteins in the same family. We also give the mutation suggestion such that it has a higher activity in an expected environment, which is consistent with the previously professional wet experiments and analysis. Conclusion A new computational method is proposed for the sequence based on the enzyme optimal condition analysis. Compared with the traditional process that involves a lot of wet experiments and requires multiple mutations, this method can give recommendations on the direction and location of amino acid substitution with reference significance for an expected condition in an efficient and effective way.

Amino acid sequence of penicillopepsin. II. Isolation and characterization of thermolytic peptides

1976 ◽  
Vol 54 (10) ◽  
pp. 885-894 ◽  
Author(s):  
Leticia Rao ◽  
Theo Hofmann
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Active Site ◽  
Amino Acid Sequences ◽  
Porcine Pepsin ◽  
Isolation And Characterization

The determination of the amino acid sequences of 70 peptides obtained from a thermoiytic digest of penicillopepsin (EC 3.4.23.7) is described. Fifty-six unique sequences ranging from 2 to 13 amino acids were compiled. Among these was a heptapeptide whose sequence is nearly identical with that of the epoxide-reactive active site peptide of porcine pepsin (EC 3.4.23.1). Considering unrecognized overlaps, a minimum of 272 and a maximum of 293 unique amino acids have been obtained. They account for about 90% of the amino acids of the enzyme.

scholarly journals Prediction of the Iron–Sulfur Binding Sites in Proteins Using the Highly Accurate Three-Dimensional Models Calculated by AlphaFold and RoseTTAFold

Inorganics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 2
Author(s):  
Béatrice Golinelli-Pimpaneau
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Conformational Changes ◽  
Binding Sites ◽  
Three Dimensional ◽  
Amino Acid Sequences ◽  
Iron Sulfur ◽  
Dimensional Models ◽  
Three Dimensional Models ◽  
Substrate Inhibitor

AlphaFold and RoseTTAFold are deep learning-based approaches that predict the structure of proteins from their amino acid sequences. Remarkable success has recently been achieved in the prediction accuracy of not only the fold of the target protein but also the position of its amino acid side chains. In this article, I question the accuracy of these methods to predict iron–sulfur binding sites. I analyze three-dimensional models calculated by AlphaFold and RoseTTAFold of Fe–S–dependent enzymes, for which no structure of a homologous protein has been solved experimentally. In all cases, the amino acids that presumably coordinate the cluster were gathered together and facing each other, which led to a quite accurate model of the Fe–S cluster binding site. Yet, cysteine candidates were often involved in intramolecular disulfide bonds, and the number and identity of the protein amino acids that should ligate the cluster were not always clear. The experimental structure determination of the protein with its Fe–S cluster and in complex with substrate/inhibitor/product is still needed to unambiguously visualize the coordination state of the cluster and understand the conformational changes occurring during catalysis.

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.

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