scholarly journals LAHMA: structure analysis through local annotation of homology-matched amino acids

2021 ◽  
Vol 77 (1) ◽  
pp. 28-40
Author(s):  
Bart van Beusekom ◽  
George Damaskos ◽  
Maarten L. Hekkelman ◽  
Fernando Salgado-Polo ◽  
Yoshitaka Hiruma ◽  
...  
Keyword(s):  
Amino Acids ◽  
Protein Structure ◽  
3D Models ◽  
Structural Features ◽  
Structure Model ◽  
Ramachandran Plot ◽  
Structure Quality ◽  
Structural Superposition ◽  
Homologous Structure ◽  
Selection Of

Comparison of homologous structure models is a key step in analyzing protein structure. With a wealth of homologous structures, comparison becomes a tedious process, and often only a small (user-biased) selection of data is used. A multitude of structural superposition algorithms are then typically used to visualize the structures together in 3D and to compare them. Here, the Local Annotation of Homology-Matched Amino acids (LAHMA) website (https://lahma.pdb-redo.eu) is presented, which compares any structure model with all of its close homologs from the PDB-REDO databank. LAHMA displays structural features in sequence space, allowing users to uncover differences between homologous structure models that can be analyzed for their relevance to chemistry or biology. LAHMA visualizes numerous structural features, also allowing one-click comparison of structure-quality plots (for example the Ramachandran plot) and `in-browser' structural visualization of 3D models.

Sequence Specific Dihedral Angle Distribution: Application in Protein Structure Prediction and Evaluation

1970 ◽  
Vol 19 (2) ◽  
pp. 217-226
Author(s):  
S. M. Minhaz Ud-Dean ◽  
Mahdi Muhammad Moosa
Keyword(s):  
Protein Structure ◽  
Dihedral Angle ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Protein Structures ◽  
Angle Distribution ◽  
Ramachandran Plot ◽  
Specific Data ◽  
Specific Distribution ◽  
Structure Evaluation

Protein structure prediction and evaluation is one of the major fields of computational biology. Estimation of dihedral angle can provide information about the acceptability of both theoretically predicted and experimentally determined structures. Here we report on the sequence specific dihedral angle distribution of high resolution protein structures available in PDB and have developed Sasichandran, a tool for sequence specific dihedral angle prediction and structure evaluation. This tool will allow evaluation of a protein structure in pdb format from the sequence specific distribution of Ramachandran angles. Additionally, it will allow retrieval of the most probable Ramachandran angles for a given sequence along with the sequence specific data. Key words: Torsion angle, φ-ψ distribution, sequence specific ramachandran plot, Ramasekharan, protein structure appraisal D.O.I. 10.3329/ptcb.v19i2.5439 Plant Tissue Cult. & Biotech. 19(2): 217-226, 2009 (December)

Analysis of Oncogene Protein Structure Using Small World Network Concept

2020 ◽  
Vol 15 (7) ◽  
pp. 732-740
Author(s):  
Neetu Kumari ◽  
Anshul Verma
Keyword(s):  
Amino Acids ◽  
Protein Structure ◽  
Degree Distribution ◽  
Protein Structures ◽  
Small World ◽  
Extreme Condition ◽  
Centrality Measures ◽  
Small World Network ◽  
Network Concept ◽  
Oncogene Protein

Background: The basic building block of a body is protein which is a complex system whose structure plays a key role in activation, catalysis, messaging and disease states. Therefore, careful investigation of protein structure is necessary for the diagnosis of diseases and for the drug designing. Protein structures are described at their different levels of complexity: primary (chain), secondary (helical), tertiary (3D), and quaternary structure. Analyzing complex 3D structure of protein is a difficult task but it can be analyzed as a network of interconnection between its component, where amino acids are considered as nodes and interconnection between them are edges. Objective: Many literature works have proven that the small world network concept provides many new opportunities to investigate network of biological systems. The objective of this paper is analyzing the protein structure using small world concept. Methods: Protein is analyzed using small world network concept, specifically where extreme condition is having a degree distribution which follows power law. For the correct verification of the proposed approach, dataset of the Oncogene protein structure is analyzed using Python programming. Results: Protein structure is plotted as network of amino acids (Residue Interaction Graph (RIG)) using distance matrix of nodes with given threshold, then various centrality measures (i.e., degree distribution, Degree-Betweenness correlation, and Betweenness-Closeness correlation) are calculated for 1323 nodes and graphs are plotted. Conclusion: Ultimately, it is concluded that there exist hubs with higher centrality degree but less in number, and they are expected to be robust toward harmful effects of mutations with new functions.

scholarly journals Genetic diversity and natural selection on the thrombospondin-related adhesive protein (TRAP) gene of Plasmodium falciparum on Bioko Island, Equatorial Guinea and global comparative analysis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Li-Yun Lin ◽  
Hui-Ying Huang ◽  
Xue-Yan Liang ◽  
Dong-De Xie ◽  
Jiang-Tao Chen ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Plasmodium Falciparum ◽  
Natural Selection ◽  
Protein Structure ◽  
Transmembrane Protein ◽  
Fixation Index ◽  
Bioko Island ◽  
Adhesive Protein ◽  
Trap Gene ◽  
Selection Of

Abstract Background Thrombospondin-related adhesive protein (TRAP) is a transmembrane protein that plays a crucial role during the invasion of Plasmodium falciparum into liver cells. As a potential malaria vaccine candidate, the genetic diversity and natural selection of PfTRAP was assessed and the global PfTRAP polymorphism pattern was described. Methods 153 blood spot samples from Bioko malaria patients were collected during 2016–2018 and the target TRAP gene was amplified. Together with the sequences from database, nucleotide diversity and natural selection analysis, and the structural prediction were preformed using bioinformatical tools. Results A total of 119 Bioko PfTRAP sequences were amplified successfully. On Bioko Island, PfTRAP shows its high degree of genetic diversity and heterogeneity, with π value for 0.01046 and Hd for 0.99. The value of dN–dS (6.2231, p < 0.05) hinted at natural selection of PfTRAP on Bioko Island. Globally, the African PfTRAPs showed more diverse than the Asian ones, and significant genetic differentiation was discovered by the fixation index between African and Asian countries (Fst > 0.15, p < 0.05). 667 Asian isolates clustered in 136 haplotypes and 739 African isolates clustered in 528 haplotypes by network analysis. The mutations I116T, L221I, Y128F, G228V and P299S were predicted as probably damaging by PolyPhen online service, while mutations L49V, R285G, R285S, P299S and K421N would lead to a significant increase of free energy difference (ΔΔG > 1) indicated a destabilization of protein structure. Conclusions Evidences in the present investigation supported that PfTRAP gene from Bioko Island and other malaria endemic countries is highly polymorphic (especially at T cell epitopes), which provided the genetic information background for developing an PfTRAP-based universal effective vaccine. Moreover, some mutations have been shown to be detrimental to the protein structure or function and deserve further study and continuous monitoring.

A pair-to-pair amino acids substitution matrix and its applications for protein structure prediction

2007 ◽  
Vol 67 (1) ◽  
pp. 142-153 ◽  
Author(s):  
Eran Eyal ◽  
Milana Frenkel-Morgenstern ◽  
Vladimir Sobolev ◽  
Shmuel Pietrokovski
Keyword(s):  
Amino Acids ◽  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Substitution Matrix

MATHEMATICAL MODELS FOR THE SYNTHESIS OF PLANT-BASED COMPOSITIONS WITH IMPROVED AMINO ACID COMPOSITION

2021 ◽  
Author(s):  
Irina Gaivoronskaya ◽  
Valenitna Kolpakova
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Mathematical Models ◽  
Functional Properties ◽  
Amino Nitrogen ◽  
Essential Amino Acids ◽  
Major Allergen ◽  
Structural Features ◽  
Covalent Bonds ◽  
Pea Protein

The aim of the work was to optimize the process of obtaining multicomponent protein compositions with high biological value and higher functional properties than the original vegetable protein products. Was realized studies to obtain biocomposites on the base of pea protein-oat protein and pea protein-rice protein. Developed composites were enriched with all limited amino acids. For each of the essential amino acids, the amino acid score was 100% and higher. Protein products used in these compositions are not in major allergen list, which allows to use these compositions in allergen-free products and specialized nutrition. To determine biosynthesis parameters for compositions from pea protein and various protein concentrates with the use of transglutaminase enzyme, was studied effect of concentration and exposition time on the amount of amino nitrogen released during the reaction. Decreasing of amino nitrogen in the medium indicated the occurrence of a protein synthesis reaction with the formation of new covalent bonds. Were determined optimal parameters of reaction: the hydromodule, the exposure time, the concentration of EP of the preparation, were obtained mathematical models. Studies on the functional properties of composites, the physicochemical properties of the proteins that make up their composition, and structural features will make it possible to determine the uses in the manufacture of food products based on their ability to bind fat, water, form foam, gels, and etc.

Exploration of the forbidden regions of the Ramachandran plot (ϕ-ψ) with QTAIM

2017 ◽  
Vol 19 (38) ◽  
pp. 26423-26434 ◽  
Author(s):  
Roya Momen ◽  
Alireza Azizi ◽  
Lingling Wang ◽  
Yang Ping ◽  
Tianlv Xu ◽  
...  
Keyword(s):  
Amino Acids ◽  
Peptide Structure ◽  
Ramachandran Plot ◽  
Left Response ◽  
Forbidden Regions ◽  
Dark Green ◽  
Ramachandran Plots ◽  
Pale Green

Left: Response β is defined as: β = arccos(e̲2·y̲) with β* = arccos(e̲1·y̲). Right: QTAIM interpreted Ramachandran plots {(βϕ,βϕ*)-(βψ,βψ*)} ‘-’ is a hyphen and not a subtraction sign. Pale green and dark green crosses indicate the glycine, pink and red pluses represent the remaining amino acids (a.a.) in the magainin peptide structure.

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