Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation

Abstract Genome3D (https://www.genome3d.eu) is a freely available resource that provides consensus structural annotations for representative protein sequences taken from a selection of model organisms. Since the last NAR update in 2015, the method of data submission has been overhauled, with annotations now being ‘pushed’ to the database via an API. As a result, contributing groups are now able to manage their own structural annotations, making the resource more flexible and maintainable. The new submission protocol brings a number of additional benefits including: providing instant validation of data and avoiding the requirement to synchronise releases between resources. It also makes it possible to implement the submission of these structural annotations as an automated part of existing internal workflows. In turn, these improvements facilitate Genome3D being opened up to new prediction algorithms and groups. For the latest release of Genome3D (v2.1), the underlying dataset of sequences used as prediction targets has been updated using the latest reference proteomes available in UniProtKB. A number of new reference proteomes have also been added of particular interest to the wider scientific community: cow, pig, wheat and mycobacterium tuberculosis. These additions, along with improvements to the underlying predictions from contributing resources, has ensured that the number of annotations in Genome3D has nearly doubled since the last NAR update article. The new API has also been used to facilitate the dissemination of Genome3D data into InterPro, thereby widening the visibility of both the annotation data and annotation algorithms.

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DBP-PSSM: Combination of evolutionary profiles with the XGBoost algorithm to improve the identification of DNA-binding proteins

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207323999201124203531 ◽

2020 ◽

Vol 23 ◽

Author(s):

Yanping Zhang ◽

Pengcheng Chen ◽

Ya Gao ◽

Jianwei Ni ◽

Xiaosheng Wang

Keyword(s):

Logistic Regression ◽

Protein Structure ◽

Dna Binding ◽

Molecular Biology ◽

Binding Proteins ◽

Protein Sequences ◽

Low Complexity ◽

Dna Binding Proteins ◽

Position Information ◽

Position Representation

Aim and Objective:: Given the rapidly increasing number of molecular biology data available, computational methods of low complexity are necessary to infer protein structure, function, and evolution. Method:: In the work, we proposed a novel mthod, FermatS, which based on the global position information and local position representation from the curve and normalized moments of inertia, respectively, to extract features information of protein sequences. Furthermore, we use the generated features by FermatS method to analyze the similarity/dissimilarity of nine ND5 proteins and establish the prediction model of DNA-binding proteins based on logistic regression with 5-fold crossvalidation. Results:: In the similarity/dissimilarity analysis of nine ND5 proteins, the results are consistent with evolutionary theory. Moreover, this method can effectively predict the DNA-binding proteins in realistic situations. Conclusion:: The findings demonstrate that the proposed method is effective for comparing, recognizing and predicting protein sequences. The main code and datasets can download from https://github.com/GaoYa1122/FermatS.

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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

Malaria Journal ◽

10.1186/s12936-021-03664-8 ◽

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.

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High Throughput Phenotypic Selection of Mycobacterium tuberculosis Mutants with Impaired Resistance to Reactive Oxygen Species Identifies Genes Important for Intracellular Growth

PLoS ONE ◽

10.1371/journal.pone.0053486 ◽

2013 ◽

Vol 8 (1) ◽

pp. e53486 ◽

Cited By ~ 10

Author(s):

Olga Mestre ◽

Raquel Hurtado-Ortiz ◽

Tiago Dos Vultos ◽

Amine Namouchi ◽

Mena Cimino ◽

...

Keyword(s):

Reactive Oxygen Species ◽

Mycobacterium Tuberculosis ◽

High Throughput ◽

Reactive Oxygen ◽

Phenotypic Selection ◽

Oxygen Species ◽

Intracellular Growth ◽

Selection Of

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Influence of protein structure on selection of nitrous acid induced mutants of TMV

MGG Molecular & General Genetics ◽

10.1007/bf00426161 ◽

1967 ◽

Vol 99 (2) ◽

pp. 171-180 ◽

Cited By ~ 4

Author(s):

Peter V. Sengbusch

Keyword(s):

Protein Structure ◽

Nitrous Acid ◽

Induced Mutants ◽

Selection Of

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Selection of an Escherichia coli host that expresses mutant forms of Mycobacterium tuberculosis 2-trans enoyl-ACP(CoA) reductase and 3-ketoacyl-ACP(CoA) reductase enzymes

Protein Expression and Purification ◽

10.1016/j.pep.2003.10.009 ◽

2004 ◽

Vol 34 (1) ◽

pp. 118-125 ◽

Cited By ~ 4

Author(s):

Simone S Poletto ◽

Isabel O da Fonseca ◽

Luiz P.S de Carvalho ◽

Luiz A Basso ◽

Diógenes S Santos

Keyword(s):

Escherichia Coli ◽

Mycobacterium Tuberculosis ◽

Coa Reductase ◽

Mutant Forms ◽

Selection Of

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Selection of Medicinal Plants Suppressing Growth of Multidrug-Resistant Strain of Tuberculosis Causative Agent

Research Journal of Pharmacy and Technology ◽

10.52711/0974-360x.2021.00374 ◽

2021 ◽

pp. 2115-2118

Author(s):

Irina Alexandrovna Ratnikova ◽

Amankeldi Kurbanovich Sadanov ◽

Nina Nicolaevna Gavrilova ◽

Saltanat Emilkyzy Orazymbet ◽

Raushan Zhumabekkyzy Kaptagai

Keyword(s):

Mycobacterium Tuberculosis ◽

Medicinal Plants ◽

Aqueous Extract ◽

Causative Agent ◽

Resistant Strain ◽

Multidrug Resistant ◽

Alcohol Extract ◽

Selection Of ◽

Multidrug Resistant Strain

The article describes selection of medicinal plants active against multidrug-resistant strain of tuberculosis causative agent. It has been discovered that all tested extracts of medicinal plants in 1:20 dilutions were active regarding multidrug-resistant strain of Mycobacterium tuberculosis T-320 except for hackberry aqueous extract. The most active was alcohol extract of parmelia, which completely suppressed growth of mycobacteria in 1:100 dilution on the 21st day of cultivation.

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Astrometric Standard Fields for CCD Observations of Double Stars

Symposium - International Astronomical Union ◽

10.1017/s0074180900047501 ◽

1994 ◽

Vol 161 ◽

pp. 291-293

Author(s):

D. Sinachopoulos ◽

E. Oblak ◽

M. Geffert ◽

J. Colin ◽

J.-F. LeCampion ◽

...

Keyword(s):

Scientific Community ◽

Photometric Data ◽

Stellar Systems ◽

European Network ◽

Multiple Star ◽

Double Stars ◽

Visual Double Stars ◽

Ccd Observations ◽

Formation And Evolution ◽

Selection Of

The number of known double stars is steadily increasing, thanks to ground-based and space observations. Therefore the ratio of known double to single stars has to be revised upwards continuously. With the Hipparcos parallaxes it will be possible to get stellar statistics for precisely defined volumes of space. This will lead to strong constraints on all astrophysical calibrations of masses, spectral types and luminosities in the solar neighbourhood. A European network of laboratories was created in August 1990 in order to remedy the lack of photometric data for close visual double stars. This network intends to study all aspects of formation and evolution of double and multiple star systems. The immediate goal of the group is to provide the scientific community with a compilation of known photometric data on a large selection of close visual double stars and to significantly enlarge this information by new observations with modern devices. A photometric database of stellar systems is being compiled from most widely used photometric systems in collaboration with the ‘Centre de Données Stellaires’ of Strasbourg.

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Mouse Gut Microbiome-Encoded β-Glucuronidases Identified Using Metagenome Analysis Guided by Protein Structure

mSystems ◽

10.1128/msystems.00452-19 ◽

2019 ◽

Vol 4 (4) ◽

Cited By ~ 5

Author(s):

Benjamin C. Creekmore ◽

Josh H. Gray ◽

William G. Walton ◽

Kristen A. Biernat ◽

Michael S. Little ◽

...

Keyword(s):

Protein Structure ◽

Active Site ◽

Human Microbiome ◽

Drug Efficacy ◽

Human Microbiome Project ◽

Structural Features ◽

Model Organisms ◽

Mouse Strains ◽

Sequencing Data ◽

Metagenome Analysis

ABSTRACT Gut microbial β-glucuronidase (GUS) enzymes play important roles in drug efficacy and toxicity, intestinal carcinogenesis, and mammalian-microbial symbiosis. Recently, the first catalog of human gut GUS proteins was provided for the Human Microbiome Project stool sample database and revealed 279 unique GUS enzymes organized into six categories based on active-site structural features. Because mice represent a model biomedical research organism, here we provide an analogous catalog of mouse intestinal microbial GUS proteins—a mouse gut GUSome. Using metagenome analysis guided by protein structure, we examined 2.5 million unique proteins from a comprehensive mouse gut metagenome created from several mouse strains, providers, housing conditions, and diets. We identified 444 unique GUS proteins and organized them into six categories based on active-site features, similarly to the human GUSome analysis. GUS enzymes were encoded by the major gut microbial phyla, including Firmicutes (60%) and Bacteroidetes (21%), and there were nearly 20% for which taxonomy could not be assigned. No differences in gut microbial gus gene composition were observed for mice based on sex. However, mice exhibited gus differences based on active-site features associated with provider, location, strain, and diet. Furthermore, diet yielded the largest differences in gus composition. Biochemical analysis of two low-fat-associated GUS enzymes revealed that they are variable with respect to their efficacy of processing both sulfated and nonsulfated heparan nonasaccharides containing terminal glucuronides. IMPORTANCE Mice are commonly employed as model organisms of mammalian disease; as such, our understanding of the compositions of their gut microbiomes is critical to appreciating how the mouse and human gastrointestinal tracts mirror one another. GUS enzymes, with importance in normal physiology and disease, are an attractive set of proteins to use for such analyses. Here we show that while the specific GUS enzymes differ at the sequence level, a core GUSome functionality appears conserved between mouse and human gastrointestinal bacteria. Mouse strain, provider, housing location, and diet exhibit distinct GUSomes and gus gene compositions, but sex seems not to affect the GUSome. These data provide a basis for understanding the gut microbial GUS enzymes present in commonly used laboratory mice. Further, they demonstrate the utility of metagenome analysis guided by protein structure to provide specific sets of functionally related proteins from whole-genome metagenome sequencing data.

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