Amino acid distribution rules predict protein fold

2013 ◽  
Vol 41 (2) ◽  
pp. 616-619 ◽  
Author(s):  
Alexander E. Kister ◽  
Vladimir Potapov
Keyword(s):  
Amino Acid ◽  
Structure Prediction ◽  
Structural Characteristics ◽  
Protein Fold ◽  
Amino Acid Distribution ◽  
Distribution Rules ◽  
Residue Contacts ◽  
Rule Approach ◽  
Structure Relationship ◽  
Polypeptide Chains

In the present article, we provide a brief overview of the main approaches to analysing the sequence–structure relationship of proteins and outline a novel method of structure prediction. The proposed method involves finding a set of rules that describes a correlation between the distribution of residues in a sequence and the essential structural characteristics of a protein structure. The residue distribution rules specify the ‘favourable’ residues that are required in certain positions of a polypeptide chain in order for it to assume a particular protein fold, and the ‘unfavourable’ residues incompatible with the given fold. Identification of amino acid distribution rules derives from examination of inter-residue contacts. We describe residue distribution rules for a large group of β-sandwich-like proteins characterized by a specific arrangement of strands in their two β-sheets. It was shown that this method has very high accuracy (approximately 85%). The advantage of the residue rule approach is that it makes possible prediction of protein folding even in polypeptide chains that have very low global sequence similarities, as low as 18%. Another potential benefit is that a better understanding of which residues play essential roles in a given protein fold may facilitate rational protein engineering design.

scholarly journals Protein structure prediction and design in a biologically-realistic implicit membrane

2019 ◽  
Author(s):  
Rebecca F. Alford ◽  
Patrick J. Fleming ◽  
Karen G. Fleming ◽  
Jeffrey J. Gray
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
Membrane Proteins ◽  
Membrane Protein ◽  
Protein Structure Prediction ◽  
Protein Design ◽  
Structure Prediction ◽  
De Novo ◽  
Computational Design ◽  
Amino Acid Distribution

ABSTRACTProtein design is a powerful tool for elucidating mechanisms of function and engineering new therapeutics and nanotechnologies. While soluble protein design has advanced, membrane protein design remains challenging due to difficulties in modeling the lipid bilayer. In this work, we developed an implicit approach that captures the anisotropic structure, shape of water-filled pores, and nanoscale dimensions of membranes with different lipid compositions. The model improves performance in computational bench-marks against experimental targets including prediction of protein orientations in the bilayer, ΔΔG calculations, native structure dis-crimination, and native sequence recovery. When applied to de novo protein design, this approach designs sequences with an amino acid distribution near the native amino acid distribution in membrane proteins, overcoming a critical flaw in previous membrane models that were prone to generating leucine-rich designs. Further, the proteins designed in the new membrane model exhibit native-like features including interfacial aromatic side chains, hydrophobic lengths compatible with bilayer thickness, and polar pores. Our method advances high-resolution membrane protein structure prediction and design toward tackling key biological questions and engineering challenges.Significance StatementMembrane proteins participate in many life processes including transport, signaling, and catalysis. They constitute over 30% of all proteins and are targets for over 60% of pharmaceuticals. Computational design tools for membrane proteins will transform the interrogation of basic science questions such as membrane protein thermodynamics and the pipeline for engineering new therapeutics and nanotechnologies. Existing tools are either too expensive to compute or rely on manual design strategies. In this work, we developed a fast and accurate method for membrane protein design. The tool is available to the public and will accelerate the experimental design pipeline for membrane proteins.

Amino-Acid Sequence of the αD- and ß-Polypeptide Chains of the Japanese Quail Hemoglobin

1993 ◽  
Vol 374 (1-6) ◽  
pp. 111-116 ◽  
Author(s):  
Yukinori EGUCHI ◽  
Yasutugu NAKASHIMA ◽  
Hiroshi TAKEI
Keyword(s):  
Amino Acid ◽  
Amino Acid Sequence ◽  
Japanese Quail ◽  
Polypeptide Chains

SOME ASPECTS OF THE STRUCTURE OF HEMOGLOBIN

1964 ◽  
Vol 42 (6) ◽  
pp. 755-762 ◽  
Author(s):  
David B. Smith
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Partial Amino Acid Sequence ◽  
Heme Pocket ◽  
Terminal Amino ◽  
Polypeptide Chains ◽  
Kinetics Of ◽  
Β Chain

An outline of present ideas concerning the arrangement, folding, and chemistry of the polypeptide chains of hemoglobin is given with some references to present know ledge of myoglobin.New material includes a partial amino acid sequence of the β-chain of horse hemoglobin, details concerning the amino acids lining the heme pocket of horse hemoglobin, and the effects of carboxypeptidases A and B on horse oxy- and horse deoxy-hemoglobin. The kinetics of the latter reactions are not simple. The C-terminal amino acids are released more rapidly from the oxygenated form.

scholarly journals Number and activity of active ribosomes in bacterial polyribosomes

1977 ◽  
Vol 164 (3) ◽  
pp. 669-674 ◽  
Author(s):  
J Stenesh ◽  
P Y Shen
Keyword(s):  
Amino Acid ◽  
Bacillus Stearothermophilus ◽  
Polypeptide Chains ◽  
Active Ribosome

Polyribosomes were isolated from Baccillus licheniformis, grown at 37 and 46 degrees C, and from Bacillus stearothermophilus, grown at 46 and 55 degrees C. The polyribosomes were incubated with either [3H]puromycin or [14C]phenylalanine. The number of active ribosomes (i.e. those to which growing polypeptide chains are attached) was calculated from the amount of [3H]peptidyl-puromycin formed. The activity of an active ribosome (i.e. the total number of amino acid molecules incorporated/unit time per active ribosome) was calculated from the uptake of [14C]phenylalanine. The number of active ribosomes per migrogram of RNA was as follows: for B. licheniformis, 1.66 × 10(12) and 1.72 × 10(12) at 37 and 46 degrees C respectively; for B. stearothermophilus, 2.59 × 10(12) at 46 and 55 degreesC respectively. The activity per active ribosome was as follows: for B. licheniformis, 0.61 and 0.05 at 37 and 46 degrees C respectively; for B. stearothermophilus, 0.58 and 0.42 at 46 and 55 degrees C respectively.

scholarly journals In-silicoprediction and modeling of theEntamoeba histolyticaproteins: Serine-richEntamoeba histolyticaprotein and 29 kDa Cysteine-rich protease

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3160 ◽  
Author(s):  
Kumar Manochitra ◽  
Subhash Chandra Parija
Keyword(s):  
Amino Acid ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Amino Acid Sequences ◽  
Treatment Modalities ◽  
Bioinformatic Tools ◽  
Complex Protein ◽  
A Cell ◽  
Quaternary Structures

BackgroundAmoebiasis is the third most common parasitic cause of morbidity and mortality, particularly in countries with poor hygienic settings. There exists an ambiguity in the diagnosis of amoebiasis, and hence there arises a necessity for a better diagnostic approach. Serine-richEntamoeba histolyticaprotein (SREHP), peroxiredoxin and Gal/GalNAc lectin are pivotal inE. histolyticavirulence and are extensively studied as diagnostic and vaccine targets. For elucidating the cellular function of these proteins, details regarding their respective quaternary structures are essential. However, studies in this aspect are scant. Hence, this study was carried out to predict the structure of these target proteins and characterize them structurally as well as functionally using appropriatein-silicomethods.MethodsThe amino acid sequences of the proteins were retrieved from National Centre for Biotechnology Information database and aligned using ClustalW. Bioinformatic tools were employed in the secondary structure and tertiary structure prediction. The predicted structure was validated, and final refinement was carried out.ResultsThe protein structures predicted by i-TASSER were found to be more accurate than Phyre2 based on the validation using SAVES server. The prediction suggests SREHP to be an extracellular protein, peroxiredoxin a peripheral membrane protein while Gal/GalNAc lectin was found to be a cell-wall protein. Signal peptides were found in the amino-acid sequences of SREHP and Gal/GalNAc lectin, whereas they were not present in the peroxiredoxin sequence. Gal/GalNAc lectin showed better antigenicity than the other two proteins studied. All the three proteins exhibited similarity in their structures and were mostly composed of loops.DiscussionThe structures of SREHP and peroxiredoxin were predicted successfully, while the structure of Gal/GalNAc lectin could not be predicted as it was a complex protein composed of sub-units. Also, this protein showed less similarity with the available structural homologs. The quaternary structures of SREHP and peroxiredoxin predicted from this study would provide better structural and functional insights into these proteins and may aid in development of newer diagnostic assays or enhancement of the available treatment modalities.

scholarly journals FingerprintContacts: Predicting Alternative Conformations of Proteins from Coevolution

2020 ◽  
Author(s):  
Jiangyan Feng ◽  
Diwakar Shukla
Keyword(s):  
Ligand Binding ◽  
Structure Prediction ◽  
De Novo ◽  
Three Dimensional ◽  
Sequence Information ◽  
Structural Constraints ◽  
Complex Signals ◽  
Residue Contacts ◽  
Small Clusters ◽  
Functional Mechanisms

AbstractProteins are dynamic molecules which perform diverse molecular functions by adopting different three-dimensional structures. Recent progress in residue-residue contacts prediction opens up new avenues for the de novo protein structure prediction from sequence information. However, it is still difficult to predict more than one conformation from residue-residue contacts alone. This is due to the inability to deconvolve the complex signals of residue-residue contacts, i.e. spatial contacts relevant for protein folding, conformational diversity, and ligand binding. Here, we introduce a machine learning based method, called FingerprintContacts, for extending the capabilities of residue-residue contacts. This algorithm leverages the features of residue-residue contacts, that is, (1) a single conformation outperforms the others in the structural prediction using all the top ranking residue-residue contacts as structural constraints, and (2) conformation specific contacts rank lower and constitute a small fraction of residue-residue contacts. We demonstrate the capabilities of FingerprintContacts on eight ligand binding proteins with varying conformational motions. Furthermore, FingerprintContacts identifies small clusters of residue-residue contacts which are preferentially located in the dynamically fluctuating regions. With the rapid growth in protein sequence information, we expect FingerprintContacts to be a powerful first step in structural understanding of protein functional mechanisms.

scholarly journals The complete amino acid sequence of three alcohol dehydrogenase alleloenzymes (AdhN-11, AdhS and AdhUF) from the fruitfly Drosophila melanogaster

1980 ◽  
Vol 187 (3) ◽  
pp. 875-883 ◽  
Author(s):  
D R Thatcher
Keyword(s):  
Drosophila Melanogaster ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Alcohol Dehydrogenase ◽  
Aspartic Acid ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
British Library ◽  
Horse Liver ◽  
And Staphylococcus Aureus

The sequence of three alcohol dehydrogenase alleloenzymes from the fruitfly Drosophila melanogaster has been determined by the sequencing of peptides produced by trypsin, chymotrypsin, thermolysin, pepsin and Staphylococcus aureus-V8-proteinase digestion. The amino acid sequence shows no obvious homology with the published sequences of the horse liver and yeast enzymes, and secondary structure prediction suggests that the nucleotide-binding domain is located in the N-terminal half of the molecule. The amino acid substitutions between AdhN-11 (a point mutation of AdhF), AdhS and AdhUF alleloenzymes were identified. AdhN-11 alcohol dehydrogenase differed from the other two by a glycine-14-(AdhS and AdhUF)-to-aspartic acid substitution, the AdhS enzyme from AdhN-11 and AdhUF enzymes by a threonine-192-(AdhN-11 and AdhUF)-to-lysine (AdhS) substitution and the AdhUF enzyme was found to differ by an alanine-45-(AdhS and AdhN-11)-to-aspartic acid (AdhUF) charge substitution and a ‘silent’ asparagine-8-(AdhS and AdhN-11)-to-alanine (AdhUF) substitution. Detailed sequence evidence has been deposited as Supplementary Publication SUP 50107 (36 pages) at the British Library Lending Division, Boston Spa, Wetherby, West Yorkshire LS23 7BQ, U.K., from whom copies can be obtained on the terms indicated in Biochem. J. (1978) 169, 5.

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