scholarly journals Evolution of the SARS-CoV-2 proteome in three dimensions (3D) during the first six months of the COVID-19 pandemic

2020 ◽  
Author(s):  
Joseph H. Lubin ◽  
Christine Zardecki ◽  
Elliott M. Dolan ◽  
Changpeng Lu ◽  
Zhuofan Shen ◽  
...  
Keyword(s):  
Amino Acid ◽  
Drug Discovery ◽  
Boundary Layers ◽  
Protein Function ◽  
Active Sites ◽  
Chemical Properties ◽  
Data Bank ◽  
Three Dimensions ◽  
Sequence Variant ◽  
The Impact

AbstractThree-dimensional structures of SARS-CoV-2 and other coronaviral proteins archived in the Protein Data Bank were used to analyze viral proteome evolution during the first six months of the COVID-19 pandemic. Analyses of spatial locations, chemical properties, and structural and energetic impacts of the observed amino acid changes in >48,000 viral proteome sequences showed how each one of the 29 viral study proteins have undergone amino acid changes. Structural models computed for every unique sequence variant revealed that most substitutions map to protein surfaces and boundary layers with a minority affecting hydrophobic cores. Conservative changes were observed more frequently in cores versus boundary layers/surfaces. Active sites and protein-protein interfaces showed modest numbers of substitutions. Energetics calculations showed that the impact of substitutions on the thermodynamic stability of the proteome follows a universal bi-Gaussian distribution. Detailed results are presented for six drug discovery targets and four structural proteins comprising the virion, highlighting substitutions with the potential to impact protein structure, enzyme activity, and functional interfaces. Characterizing the evolution of the virus in three dimensions provides testable insights into viral protein function and should aid in structure-based drug discovery efforts as well as the prospective identification of amino acid substitutions with potential for drug resistance.

scholarly journals EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4750 ◽  
Author(s):  
Afshine Amidi ◽  
Shervine Amidi ◽  
Dimitrios Vlachakis ◽  
Vasileios Megalooikonomou ◽  
Nikos Paragios ◽  
...  
Keyword(s):  
Neural Networks ◽  
Amino Acid ◽  
Convolutional Neural Networks ◽  
Protein Function ◽  
Enzyme Commission Number ◽  
Data Bank ◽  
Biochemical Properties ◽  
Data Availability ◽  
Binary Representation ◽  
Enzymatic Function

During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems. The size of the Protein Data Bank (PDB) has increased more than 15-fold since 1999, which enabled the expansion of models that aim at predicting enzymatic function via their amino acid composition. Amino acid sequence, however, is less conserved in nature than protein structure and therefore considered a less reliable predictor of protein function. This paper presents EnzyNet, a novel 3D convolutional neural networks classifier that predicts the Enzyme Commission number of enzymes based only on their voxel-based spatial structure. The spatial distribution of biochemical properties was also examined as complementary information. The two-layer architecture was investigated on a large dataset of 63,558 enzymes from the PDB and achieved an accuracy of 78.4% by exploiting only the binary representation of the protein shape. Code and datasets are available at https://github.com/shervinea/enzynet.

RECOGNIZING COMPLEX, ASYMMETRIC FUNCTIONAL SITES IN PROTEIN STRUCTURES USING A BAYESIAN SCORING FUNCTION

2003 ◽  
Vol 01 (01) ◽  
pp. 119-138 ◽  
Author(s):  
LIPING WEI ◽  
RUSS B. ALTMAN
Keyword(s):  
Binding Sites ◽  
Calcium Binding ◽  
Active Sites ◽  
Large Scale ◽  
Protein Structures ◽  
Scoring Function ◽  
Chemical Properties ◽  
Data Bank ◽  
Functional Sites ◽  
Calcium Binding Sites

The increase in known three-dimensional protein structures enables us to build statistical profiles of important functional sites in protein molecules. These profiles can then be used to recognize sites in large-scale automated annotations of new protein structures. We report an improved FEATURE system which recognizes functional sites in protein structures. FEATURE defines multi-level physico-chemical properties and recognizes sites based on the spatial distribution of these properties in the sites' microenvironments. It uses a Bayesian scoring function to compare a query region with the statistical profile built from known examples of sites and control nonsites. We have previously shown that FEATURE can accurately recognize calcium-binding sites and have reported interesting results scanning for calcium-binding sites in the entire Protein Data Bank. Here we report the ability of the improved FEATURE to characterize and recognize geometrically complex and asymmetric sites such as ATP-binding sites and disulfide bond-forming sites. FEATURE does not rely on conserved residues or conserved residue geometry of the sites. We also demonstrate that, in the absence of a statistical profile of the sites, FEATURE can use an artificially constructed profile based on a priori knowledge to recognize the sites in new structures, using redoxin active sites as an example.

The impact of biotechnology and molecular biology on the pharmaceutical industry

1992 ◽  
Vol 99 (1-2) ◽  
pp. 37-45
Author(s):  
A. N. Hobden ◽  
T. J. R. Harris
Keyword(s):  
Drug Discovery ◽  
Pharmaceutical Industry ◽  
Protein Function ◽  
High Throughput Screening ◽  
Mammalian Cells ◽  
Recombinant Dna ◽  
Hiv Protease ◽  
Baculovirus Infection ◽  
Recombinant Dna Techniques ◽  
The Impact

Synopsis:Biotechnology had its initial impact on the pharmaceutical industry well before the perceived time. The use of fermentation technology to produce antibiotics was a cornerstone for the development of the industry. This event was both before cloning (BC) and before DNA (rather than after DNA – AD). Even now the antibiotic market, which is worth over 10 billion U.S. dollars a year, is the most valuable segment of the total market, (c.200 billion dollars per year). Nevertheless the impact of biotechnology in drug discovery was until recently perceived solely to be the use of recombinant DNA techniques to produce therapeutic proteins and modified versions of them by protein engineering.There are several other places where genetic engineering is influencing drug discovery. The expression of recombinant proteins in surrogate systems (e.g. in E. coli, yeast or via baculovirus infection or in mammalian cells) provides materials for structure determination (e.g. HIV protease) and structure/function studies (e.g. various receptors). Recombinant DNA techniques are influencing assay technology by allowing access to proteins in sufficient quantity for high throughput screening.In addition, screening organisms can be constructed where a particular protein function can be measured in a microorganism by complementation or via reporter gene expression.Transgenic animals also illustrate the power of the technology for drug discovery. Not only will transgenic rats and mice be used as models of disease but also for efficacy and toxicological profiling. What is learned in transgenic rodents may well set the scene for somatic cell gene therapy in humans.

scholarly journals The impact of protein architecture on adaptive evolution

2019 ◽  
Author(s):  
Ana Filipa Moutinho ◽  
Fernanda Fontes Trancoso ◽  
Julien Yann Dutheil
Keyword(s):  
Amino Acid ◽  
Adaptive Evolution ◽  
Protein Function ◽  
Population Genomics ◽  
Solvent Accessibility ◽  
Protein Biosynthesis ◽  
Relative Solvent Accessibility ◽  
Adaptive Mutations ◽  
Protein Architecture ◽  
The Impact

AbstractAdaptive mutations play an important role in molecular evolution. However, the frequency and nature of these mutations at the intra-molecular level is poorly understood. To address this, we analysed the impact of protein architecture on the rate of adaptive substitutions, aiming to understand how protein biophysics influences fitness and adaptation. Using Drosophila melanogaster and Arabidopsis thaliana population genomics data, we fitted models of distribution of fitness effects and estimated the rate of adaptive amino-acid substitutions both at the protein and amino-acid residue level. We performed a comprehensive analysis covering genome, gene and protein structure, by exploring a multitude of factors with a plausible impact on the rate of adaptive evolution, such as intron number, protein length, secondary structure, relative solvent accessibility, intrinsic protein disorder, chaperone affinity, gene expression, protein function and protein-protein interactions. We found that the relative solvent accessibility is a major driver of adaptive evolution, with most adaptive mutations occurring at the surface of proteins. Moreover, we observe that the rate of adaptive substitutions differs between protein functional classes, with genes encoding for protein biosynthesis and degradation signalling exhibiting the fastest rates of protein adaptation. Overall, our results suggest that adaptive evolution in proteins is mainly driven by inter-molecular interactions, with host-pathogen coevolution likely playing a major role.

scholarly journals The Impact of Protein Architecture on Adaptive Evolution

2019 ◽  
Vol 36 (9) ◽  
pp. 2013-2028 ◽  
Author(s):  
Ana Filipa Moutinho ◽  
Fernanda Fontes Trancoso ◽  
Julien Yann Dutheil
Keyword(s):  
Amino Acid ◽  
Adaptive Evolution ◽  
Protein Function ◽  
Population Genomics ◽  
Solvent Accessibility ◽  
Protein Biosynthesis ◽  
Relative Solvent Accessibility ◽  
Adaptive Mutations ◽  
Protein Architecture ◽  
The Impact

Abstract Adaptive mutations play an important role in molecular evolution. However, the frequency and nature of these mutations at the intramolecular level are poorly understood. To address this, we analyzed the impact of protein architecture on the rate of adaptive substitutions, aiming to understand how protein biophysics influences fitness and adaptation. Using Drosophila melanogaster and Arabidopsis thaliana population genomics data, we fitted models of distribution of fitness effects and estimated the rate of adaptive amino-acid substitutions both at the protein and amino-acid residue level. We performed a comprehensive analysis covering genome, gene, and protein structure, by exploring a multitude of factors with a plausible impact on the rate of adaptive evolution, such as intron number, protein length, secondary structure, relative solvent accessibility, intrinsic protein disorder, chaperone affinity, gene expression, protein function, and protein–protein interactions. We found that the relative solvent accessibility is a major determinant of adaptive evolution, with most adaptive mutations occurring at the surface of proteins. Moreover, we observe that the rate of adaptive substitutions differs between protein functional classes, with genes encoding for protein biosynthesis and degradation signaling exhibiting the fastest rates of protein adaptation. Overall, our results suggest that adaptive evolution in proteins is mainly driven by intermolecular interactions, with host–pathogen coevolution likely playing a major role.

scholarly journals An Inquiry into Protein Structure and Genetic Disease: Introducing Undergraduates to Bioinformatics in a Large Introductory Course

2005 ◽  
Vol 4 (3) ◽  
pp. 207-220 ◽  
Author(s):  
April E. Bednarski ◽  
Sarah C.R. Elgin ◽  
Himadri B. Pakrasi
Keyword(s):  
Protein Structure ◽  
Genetic Disease ◽  
Protein Function ◽  
Genetic Diseases ◽  
Data Bank ◽  
Mendelian Inheritance ◽  
Single Mutation ◽  
Introductory Course ◽  
And Function ◽  
The Impact

This inquiry-based lab is designed around genetic diseases with a focus on protein structure and function. To allow students to work on their own investigatory projects, 10 projects on 10 different proteins were developed. Students are grouped in sections of 20 and work in pairs on each of the projects. To begin their investigation, students are given a cDNA sequence that translates into a human protein with a single mutation. Each case results in a genetic disease that has been studied and recorded in the Online Mendelian Inheritance in Man (OMIM) database. Students use bioinformatics tools to investigate their proteins and form a hypothesis for the effect of the mutation on protein function. They are also asked to predict the impact of the mutation on human physiology and present their findings in the form of an oral report. Over five laboratory sessions, students use tools on the National Center for Biotechnology Information (NCBI) Web site (BLAST, LocusLink, OMIM, GenBank, and PubMed) as well as ExPasy, Protein Data Bank, ClustalW, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and the structure-viewing program DeepView. Assessment results showed that students gained an understanding of the Web-based databases and tools and enjoyed the investigatory nature of the lab.

scholarly journals Genetic Variability of the Functional Domains of Chromodomains Helicase DNA-Binding (CHD) Proteins

Genes ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1827
Author(s):  
Ana R. Cardoso ◽  
Mónica Lopes-Marques ◽  
Manuela Oliveira ◽  
António Amorim ◽  
Maria J. Prata ◽  
...  
Keyword(s):  
Amino Acid ◽  
Dna Binding ◽  
Protein Function ◽  
Species Conservation ◽  
Functional Domains ◽  
Gene Duplications ◽  
Amino Acid Residues ◽  
The Past ◽  
The Impact ◽  
Paralogous Proteins

In the past few years, there has been an increasing neuroscientific interest in understanding the function of mammalian chromodomains helicase DNA-binding (CHD) proteins due to their association with severe developmental syndromes. Mammalian CHDs include nine members (CHD1 to CHD9), grouped into subfamilies according to the presence of specific functional domains, generally highly conserved in evolutionary terms. Mutations affecting these domains hold great potential to disrupt protein function, leading to meaningful pathogenic scenarios, such as embryonic defects incompatible with life. Here, we analysed the evolution of CHD proteins by performing a comparative study of the functional domains of CHD proteins between orthologous and paralogous protein sequences. Our findings show that the highest degree of inter-species conservation was observed at Group II (CHD3, CHD4, and CHD5) and that most of the pathological variations documented in humans involve amino acid residues that are conserved not only between species but also between paralogs. The parallel analysis of both orthologous and paralogous proteins, in cases where gene duplications have occurred, provided extra information showing patterns of flexibility as well as interchangeability between amino acid positions. This added complexity needs to be considered when the impact of novel mutations is assessed in terms of evolutionary conservation.

scholarly journals Improvement of growth, productivity and some chemical properties of hot pepper by foliar application of amino acids and yeast extract

10.5219/1160 ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 831-839
Author(s):  
Amina Aly ◽  
Noha Eliwa ◽  
Mohamed Hassan Abd El Megid
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Phenolic Compounds ◽  
Yeast Extract ◽  
Foliar Application ◽  
Chemical Properties ◽  
Ethanolic Extract ◽  
Hot Pepper ◽  
Maximum Increase ◽  
The Impact

A greenhouse experiment was conducted during the seasons of 2016 – 2017 to compare the impact of foliar amino acids binding (0.5, 1 and 2 g.L-1) and yeast extract ( 2.5, 5 and 10 g.L-1) on certain development and physiological parameters of hot pepper (Capsicum annuum L.). The results cleared that foliar application of amino acid (2 g.L-1) or yeast (10 g.L-1) increased development parameters of hot pepper compared to control in both first and second seasons. Amino acids foliar implementation with (2 g.L-1) gave higher content of anthocyanins, ascorbic acid, lycopene and ß- carotene contents as compared with the control. Also, 10 g.L-1 foliar application of yeast extract showed the best results as compared to control in both first and second seasons. Foliar application of amino acids contents increased phenol and flavonoid contents of hot pepper fruits. Maximum increase was observed at 2 g.L-1 amino acids in both seasons. While 1,1-Diphenyl-2-picrylhydrazyl (DPPH) and lipid peroxidation contents increased with 2 g.L-1 amino acids and 10 g.L-1 yeast foliar application. The HPLC analysis of ethanolic extract of hot pepper fruits has shown fifteen phenolic compounds. Phenolic compounds were increased by increasing the concentration of amino acid and yeast extract foliar application in the both two seasons. In conclusion it is recommended to use amino acid (2 g.L-1) and yeast extract (10 g.L-1) foliar application as they play a key role in productivity , also in protecting the environment as eco-friendly and cost-effective inputs for the farmers.

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