scholarly journals Computational modelling of Chromosomally Clustering Protein Domains In Bacteria

2021 ◽  
Author(s):  
Chiara E. Cotroneo ◽  
Isobel Claire Gormley ◽  
Denis C. Shields ◽  
Michael Salter-Townshend
Keyword(s):  
Gene Ontology ◽  
Mixture Model ◽  
Computational Modelling ◽  
Protein Domains ◽  
Gene Clusters ◽  
Protein Domain ◽  
Parameter Estimates ◽  
Bacterial Gene ◽  
Wide Range ◽  
The Stability

Abstract Background: In bacteria, genes with related functions - such as those involved in the metabolism of the same compound or in infection processes - are often physically close on the genome and form groups called clusters. The enrichment of such clusters over various distantly related bacteria can be used to predict the roles of genes of unknown function that cluster with characterised genes. There is no obvious rule to define a cluster, given their variability in size and intergenic distances, and the definition of what comprises a “gene”, since genes can gain and lose domains over time. Protein domains can cluster within a gene, or in adjacent genes of related function, and in both cases these are chromosomally clustered. Here, we model the distances between pairs of protein domain coding regions across a wide range of bacteria and archaea via a probabilistic two component mixture model, without imposing arbitrary thresholds in terms of gene numbers or distances. Results: We trained our model using matched Gene Ontology terms to label functionally related pairs and assess the stability of the parameters of the model across 14, 178 archaeal and bacterial strains. We found that the parameters of our mixture model are remarkably stable across bacteria and archaea, except for endosymbionts and obligate intracellular pathogens. Obligate pathogens have smaller genomes, and although they vary, on average do not show noticeably different clustering distances; the main difference in the parameter estimates is that a far greater proportion of the genes sharing ontology terms are clustered. This may reflect that these genomes are enriched for complexes encoded by clustered core housekeeping genes, as a proportion of the total genes. Given the overall stability of the parameter estimates, we then used the mean parameter estimates across the entire dataset to investigate which gene ontology terms are most frequently associated with clustered genes. Conclusions: Given the stability of the mixture model across species, it may be used to predict bacterial gene clusters that are shared across multiple species, in addition to giving insights into the evolutionary pressures on the chromosomal locations of genes in different species.

scholarly journals Computational modelling of chromosomally clustering protein domains in bacteria

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Chiara E. Cotroneo ◽  
Isobel Claire Gormley ◽  
Denis C. Shields ◽  
Michael Salter-Townshend
Keyword(s):  
Gene Ontology ◽  
Mixture Model ◽  
Computational Modelling ◽  
Protein Domains ◽  
Gene Clusters ◽  
Protein Domain ◽  
Parameter Estimates ◽  
Bacterial Gene ◽  
Wide Range ◽  
The Stability

Abstract Background In bacteria, genes with related functions—such as those involved in the metabolism of the same compound or in infection processes—are often physically close on the genome and form groups called clusters. The enrichment of such clusters over various distantly related bacteria can be used to predict the roles of genes of unknown function that cluster with characterised genes. There is no obvious rule to define a cluster, given their variability in size and intergenic distances, and the definition of what comprises a “gene”, since genes can gain and lose domains over time. Protein domains can cluster within a gene, or in adjacent genes of related function, and in both cases these are chromosomally clustered. Here, we model the distances between pairs of protein domain coding regions across a wide range of bacteria and archaea via a probabilistic two component mixture model, without imposing arbitrary thresholds in terms of gene numbers or distances. Results We trained our model using matched gene ontology terms to label functionally related pairs and assess the stability of the parameters of the model across 14,178 archaeal and bacterial strains. We found that the parameters of our mixture model are remarkably stable across bacteria and archaea, except for endosymbionts and obligate intracellular pathogens. Obligate pathogens have smaller genomes, and although they vary, on average do not show noticeably different clustering distances; the main difference in the parameter estimates is that a far greater proportion of the genes sharing ontology terms are clustered. This may reflect that these genomes are enriched for complexes encoded by clustered core housekeeping genes, as a proportion of the total genes. Given the overall stability of the parameter estimates, we then used the mean parameter estimates across the entire dataset to investigate which gene ontology terms are most frequently associated with clustered genes. Conclusions Given the stability of the mixture model across species, it may be used to predict bacterial gene clusters that are shared across multiple species, in addition to giving insights into the evolutionary pressures on the chromosomal locations of genes in different species.

scholarly journals Family-Specific Gains and Losses of Protein Domains in the Legume and Grass Plant Families

2020 ◽  
Vol 16 ◽  
pp. 117693432093994
Author(s):  
Akshay Yadav ◽  
David Fernández-Baca ◽  
Steven B Cannon
Keyword(s):  
Gene Ontology ◽  
Statistical Tests ◽  
Amino Acid Level ◽  
Protein Domains ◽  
Protein Sequences ◽  
Enrichment Analysis ◽  
Protein Domain ◽  
Data Matrix ◽  
Dna Crosslinks ◽  
Outgroup Species

Protein domains can be regarded as sections of protein sequences capable of folding independently and performing specific functions. In addition to amino-acid level changes, protein sequences can also evolve through domain shuffling events such as domain insertion, deletion, or duplication. The evolution of protein domains can be studied by tracking domain changes in a selected set of species with known phylogenetic relationships. Here, we conduct such an analysis by defining domains as “features” or “descriptors,” and considering the species (target + outgroup) as instances or data-points in a data matrix. We then look for features (domains) that are significantly different between the target species and the outgroup species. We study the domain changes in 2 large, distinct groups of plant species: legumes (Fabaceae) and grasses (Poaceae), with respect to selected outgroup species. We evaluate 4 types of domain feature matrices: domain content, domain duplication, domain abundance, and domain versatility. The 4 types of domain feature matrices attempt to capture different aspects of domain changes through which the protein sequences may evolve—that is, via gain or loss of domains, increase or decrease in the copy number of domains along the sequences, expansion or contraction of domains, or through changes in the number of adjacent domain partners. All the feature matrices were analyzed using feature selection techniques and statistical tests to select protein domains that have significant different feature values in legumes and grasses. We report the biological functions of the top selected domains from the analysis of all the feature matrices. In addition, we also perform domain-centric gene ontology (dcGO) enrichment analysis on all selected domains from all 4 feature matrices to study the gene ontology terms associated with the significantly evolving domains in legumes and grasses. Domain content analysis revealed a striking loss of protein domains from the Fanconi anemia (FA) pathway, the pathway responsible for the repair of interstrand DNA crosslinks. The abundance analysis of domains found in legumes revealed an increase in glutathione synthase enzyme, an antioxidant required from nitrogen fixation, and a decrease in xanthine oxidizing enzymes, a phenomenon confirmed by previous studies. In grasses, the abundance analysis showed increases in domains related to gene silencing which could be due to polyploidy or due to enhanced response to viral infection. We provide a docker container that can be used to perform this analysis workflow on any user-defined sets of species, available at https://cloud.docker.com/u/akshayayadav/repository/docker/akshayayadav/protein-domain-evolution-project .

scholarly journals Reconciling age-related changes in behavioural and neural indices of human perceptual decision making

2017 ◽  
Author(s):  
David P. McGovern ◽  
Aoife Hayes ◽  
Simon P. Kelly ◽  
Redmond O’Connell
Keyword(s):  
Decision Making ◽  
Change Detection ◽  
Computational Modelling ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Perceptual Decision Making ◽  
Neural Data ◽  
Motion Discrimination ◽  
Age Related ◽  
Wide Range

Ageing impacts on decision making behaviour across a wide range of cognitive tasks and scenarios. Computational modeling has proven highly valuable in providing mechanistic interpretations of these age-related differences; however, the extent to which model parameter differences accurately reflect changes to the underlying neural computations has yet to be tested. Here, we measured neural signatures of decision formation as younger and older participants performed motion discrimination and contrast-change detection tasks, and compared the dynamics of these signals to key parameter estimates from fits of a prominent accumulation-to-bound model (drift diffusion) to behavioural data. Our results indicate marked discrepancies between the age-related effects observed in the model output and the neural data. Most notably, while the model predicted a higher decision boundary in older age for both tasks, the neural data indicated no such differences. To reconcile the model and neural findings, we used our neurophysiological observations as a guide to constrain and adapt the model parameters. In addition to providing better fits to behaviour on both tasks, the resultant neurally-informed models furnished novel predictions regarding other features of the neural data which were empirically validated. These included a slower mean rate of evidence accumulation amongst older adults during motion discrimination and a beneficial reduction in between-trial variability in accumulation rates on the contrast-change detection task, which was linked to more consistent attentional engagement. Our findings serve to highlight how combining human brain signal measurements with computational modelling can yield unique insights into group differences in neural mechanisms for decision making.

Performance of Electronic Structure Methods for the Description of Hückel-Möbius Interconversions in Extended π-Systems

2019 ◽  
Author(s):  
Tatiana Woller ◽  
Ambar Banerjee ◽  
Nitai Sylvetsky ◽  
Xavier Deraet ◽  
Frank De Proft ◽  
...  
Keyword(s):  
Electronic Structure ◽  
Basis Set ◽  
Dft Methods ◽  
Molecular Switching ◽  
Wide Range ◽  
Electronic Structure Methods ◽  
Explicitly Correlated ◽  
Relative Errors ◽  
The Stability ◽  
Basis Set Expansion

<p>Expanded porphyrins provide a versatile route to molecular switching devices due to their ability to shift between several π-conjugation topologies encoding distinct properties. Taking into account its size and huge conformational flexibility, DFT remains the workhorse for modeling such extended macrocycles. Nevertheless, the stability of Hückel and Möbius conformers depends on a complex interplay of different factors, such as hydrogen bonding, p···p stacking, steric effects, ring strain and electron delocalization. As a consequence, the selection of an exchange-correlation functional for describing the energy profile of topological switches is very difficult. For these reasons, we have examined the performance of a variety of wavefunction methods and density functionals for describing the thermochemistry and kinetics of topology interconversions across a wide range of macrocycles. Especially for hexa- and heptaphyrins, the Möbius structures have a pronouncedly stronger degree of static correlation than the Hückel and figure-eight structures, and as a result the relative energies of singly-twisted structures are a challenging test for electronic structure methods. Comparison of limited orbital space full CI calculations with CCSD(T) calculations within the same active spaces shows that post-CCSD(T) correlation contributions to relative energies are very minor. At the same time, relative energies are weakly sensitive to further basis set expansion, as proven by the minor energy differences between MP2/cc-pVDZ and explicitly correlated MP2-F12/cc-pVDZ-F12 calculations. Hence, our CCSD(T) reference values are reasonably well-converged in both 1-particle and n-particle spaces. While conventional MP2 and MP3 yield very poor results, SCS-MP2 and particularly SOS-MP2 and SCS-MP3 agree to better than 1 kcal mol<sup>-1</sup> with the CCSD(T) relative energies. Regarding DFT methods, only M06-2X provides relative errors close to chemical accuracy with a RMSD of 1.2 kcal mol<sup>-1</sup>. While the original DSD-PBEP86 double hybrid performs fairly poorly for these extended p-systems, the errors drop down to 2 kcal mol<sup>-1</sup> for the revised revDSD-PBEP86-NL, again showing that same-spin MP2-like correlation has a detrimental impact on performance like the SOS-MP2 results. </p>

Insights into Potent Therapeutical Antileukemic Agent L-glutaminase Enzyme Under Solid-state Fermentation: A Review

2020 ◽  
Vol 21 (3) ◽  
pp. 211-220 ◽  
Author(s):  
Chandrasai Potla Durthi ◽  
Madhuri Pola ◽  
Satish Babu Rajulapati ◽  
Anand Kishore Kola
Keyword(s):  
Solid State ◽  
Solid State Fermentation ◽  
Food Industry ◽  
Energy Requirement ◽  
Production Studies ◽  
Wide Range ◽  
Hybridoma Technology ◽  
Bacteria And Fungi ◽  
The Stability ◽  
Glutaminase Activity

Aim & objective: To review the applications and production studies of reported antileukemic drug L-glutaminase under Solid-state Fermentation (SSF). Overview: An amidohydrolase that gained economic importance because of its wide range of applications in the pharmaceutical industry, as well as the food industry, is L-glutaminase. The medical applications utilized it as an anti-tumor agent as well as an antiretroviral agent. L-glutaminase is employed in the food industry as an acrylamide degradation agent, as a flavor enhancer and for the synthesis of theanine. Another application includes its use in hybridoma technology as a biosensing agent. Because of its diverse applications, scientists are now focusing on enhancing the production and optimization of L-glutaminase from various sources by both Solid-state Fermentation (SSF) and submerged fermentation studies. Of both types of fermentation processes, SSF has gained importance because of its minimal cost and energy requirement. L-glutaminase can be produced by SSF from both bacteria and fungi. Single-factor studies, as well as multi-level optimization studies, were employed to enhance L-glutaminase production. It was concluded that L-glutaminase activity achieved by SSF was 1690 U/g using wheat bran and Bengal gram husk by applying feed-forward artificial neural network and genetic algorithm. The highest L-glutaminase activity achieved under SSF was 3300 U/gds from Bacillus sp., by mixture design. Purification and kinetics studies were also reported to find the molecular weight as well as the stability of L-glutaminase. Conclusion: The current review is focused on the production of L-glutaminase by SSF from both bacteria and fungi. It was concluded from reported literature that optimization studies enhanced L-glutaminase production. Researchers have also confirmed antileukemic and anti-tumor properties of the purified L-glutaminase on various cell lines.

Recycling and Reuse in the Roman Economy

2020 ◽  
Keyword(s):  
Building Materials ◽  
Computational Modelling ◽  
Late Antique ◽  
Roman Economy ◽  
Wide Range ◽  
The Status ◽  
Recent Developments ◽  
Methodological Approaches ◽  
First Time ◽  
Site Types

The recycling and reuse of materials and objects were extensive in the past, but have rarely been embedded into models of the economy; even more rarely has any attempt been made to assess the scale of these practices. Recent developments, including the use of large datasets, computational modelling, and high-resolution analytical chemistry, are increasingly offering the means to reconstruct recycling and reuse, and even to approach the thorny matter of quantification. Growing scholarly interest in the topic has also led to an increasing recognition of these practices from those employing more traditional methodological approaches, which are sometimes coupled with innovative archaeological theory. Thanks to these efforts, it has been possible for the first time in this volume to draw together archaeological case studies on the recycling and reuse of a wide range of materials, from papyri and textiles, to amphorae, metals and glass, building materials and statuary. Recycling and reuse occur at a range of site types, and often in contexts which cross-cut material categories, or move from one object category to another. The volume focuses principally on the Roman Imperial and late antique world, over a broad geographical span ranging from Britain to North Africa and the East Mediterranean. Last, but not least, the volume is unique in focusing upon these activities as a part of the status quo, and not just as a response to crisis.

scholarly journals Polymer-Drug Conjugates as Nanotheranostic Agents

2021 ◽  
Vol 2 (1) ◽  
pp. 63-81
Author(s):  
Sajana Manandhar ◽  
Erica Sjöholm ◽  
Johan Bobacka ◽  
Jessica M. Rosenholm ◽  
Kuldeep K. Bansal
Keyword(s):  
Drug Delivery ◽  
Drug Release ◽  
Treatment Options ◽  
The Body ◽  
Drug Conjugates ◽  
Imaging Characteristics ◽  
Wide Range ◽  
Systemic Side Effects ◽  
Theranostic Agents ◽  
The Stability

Since the last decade, the polymer-drug conjugate (PDC) approach has emerged as one of the most promising drug-delivery technologies owing to several benefits like circumventing premature drug release, offering controlled and targeted drug delivery, improving the stability, safety, and kinetics of conjugated drugs, and so forth. In recent years, PDC technology has advanced with the objective to further enhance the treatment outcomes by integrating nanotechnology and multifunctional characteristics into these systems. One such development is the ability of PDCs to act as theranostic agents, permitting simultaneous diagnosis and treatment options. Theranostic nanocarriers offer the opportunity to track the distribution of PDCs within the body and help to localize the diseased site. This characteristic is of particular interest, especially among those therapeutic approaches where external stimuli are supposed to be applied for abrupt drug release at the target site for localized delivery to avoid systemic side effects (e.g., Visudyne®). Thus, with the help of this review article, we are presenting the most recent updates in the domain of PDCs as nanotheranostic agents. Different methodologies utilized to design PDCs along with imaging characteristics and their applicability in a wide range of diseases, have been summarized in this article.

scholarly journals Ligand-induced structural changes analysis of ribose-binding protein as studied by molecular dynamics simulations

2021 ◽  
pp. 1-12
Author(s):  
Haiyan Li ◽  
Zanxia Cao ◽  
Guodong Hu ◽  
Liling Zhao ◽  
Chunling Wang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Structural Changes ◽  
Binding Protein ◽  
Network Models ◽  
Md Simulations ◽  
Protein Domain ◽  
Opening Angle ◽  
Conformation Changes ◽  
Wide Range ◽  
Ribose Binding Protein

BACKGROUND: The ribose-binding protein (RBP) from Escherichia coli is one of the representative structures of periplasmic binding proteins. Binding of ribose at the cleft between two domains causes a conformational change corresponding to a closure of two domains around the ligand. The RBP has been crystallized in the open and closed conformations. OBJECTIVE: With the complex trajectory as a control, our goal was to study the conformation changes induced by the detachment of the ligand, and the results have been revealed from two computational tools, MD simulations and elastic network models. METHODS: Molecular dynamics (MD) simulations were performed to study the conformation changes of RBP starting from the open-apo, closed-holo and closed-apo conformations. RESULTS: The evolution of the domain opening angle θ clearly indicates large structural changes. The simulations indicate that the closed states in the absence of ribose are inclined to transition to the open states and that ribose-free RBP exists in a wide range of conformations. The first three dominant principal motions derived from the closed-apo trajectories, consisting of rotating, bending and twisting motions, account for the major rearrangement of the domains from the closed to the open conformation. CONCLUSIONS: The motions showed a strong one-to-one correspondence with the slowest modes from our previous study of RBP with the anisotropic network model (ANM). The results obtained for RBP contribute to the generalization of robustness for protein domain motion studies using either the ANM or PCA for trajectories obtained from MD.

scholarly journals No-z Model for Magnetic Fields of Different Astrophysical Objects and Stability of the Solutions

Data ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 4
Author(s):  
Evgeny Mikhailov ◽  
Daniela Boneva ◽  
Maria Pashentseva
Keyword(s):  
Magnetic Field ◽  
Magnetic Fields ◽  
Large Scale ◽  
Point Of View ◽  
Accretion Discs ◽  
Wide Range ◽  
Astrophysical Objects ◽  
Alpha Effect ◽  
The Stability ◽  
The Magnetic Field

A wide range of astrophysical objects, such as the Sun, galaxies, stars, planets, accretion discs etc., have large-scale magnetic fields. Their generation is often based on the dynamo mechanism, which is connected with joint action of the alpha-effect and differential rotation. They compete with the turbulent diffusion. If the dynamo is intensive enough, the magnetic field grows, else it decays. The magnetic field evolution is described by Steenbeck—Krause—Raedler equations, which are quite difficult to be solved. So, for different objects, specific two-dimensional models are used. As for thin discs (this shape corresponds to galaxies and accretion discs), usually, no-z approximation is used. Some of the partial derivatives are changed by the algebraic expressions, and the solenoidality condition is taken into account as well. The field generation is restricted by the equipartition value and saturates if the field becomes comparable with it. From the point of view of mathematical physics, they can be characterized as stable points of the equations. The field can come to these values monotonously or have oscillations. It depends on the type of the stability of these points, whether it is a node or focus. Here, we study the stability of such points and give examples for astrophysical applications.

scholarly journals Biodiversity of Secondary Metabolites Compounds Isolated from Phylum Actinobacteria and Its Therapeutic Applications

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4504
Author(s):  
Muhanna Al-shaibani ◽  
Radin Maya Saphira Radin Mohamed ◽  
Nik Sidik ◽  
Hesham Enshasy ◽  
Adel Al-Gheethi ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Bioactive Compounds ◽  
Extreme Environments ◽  
Software Tool ◽  
Gene Clusters ◽  
Well Being ◽  
Bioactive Substances ◽  
Diverse Range ◽  
Wide Range ◽  
Potential Applications

The current review aims to summarise the biodiversity and biosynthesis of novel secondary metabolites compounds, of the phylum Actinobacteria and the diverse range of secondary metabolites produced that vary depending on its ecological environments they inhabit. Actinobacteria creates a wide range of bioactive substances that can be of great value to public health and the pharmaceutical industry. The literature analysis process for this review was conducted using the VOSviewer software tool to visualise the bibliometric networks of the most relevant databases from the Scopus database in the period between 2010 and 22 March 2021. Screening and exploring the available literature relating to the extreme environments and ecosystems that Actinobacteria inhabit aims to identify new strains of this major microorganism class, producing unique novel bioactive compounds. The knowledge gained from these studies is intended to encourage scientists in the natural product discovery field to identify and characterise novel strains containing various bioactive gene clusters with potential clinical applications. It is evident that Actinobacteria adapted to survive in extreme environments represent an important source of a wide range of bioactive compounds. Actinobacteria have a large number of secondary metabolite biosynthetic gene clusters. They can synthesise thousands of subordinate metabolites with different biological actions such as anti-bacterial, anti-parasitic, anti-fungal, anti-virus, anti-cancer and growth-promoting compounds. These are highly significant economically due to their potential applications in the food, nutrition and health industries and thus support our communities’ well-being.

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