scholarly journals Antiviral Resistance against Viral Mutation: Praxis and Policy for SARS-CoV-2

2021 ◽  
Vol 9 (1) ◽  
pp. 81-89
Author(s):  
Robert Penner
Keyword(s):  
Free Energy ◽  
Vaccine Development ◽  
A Priori ◽  
Structural Data ◽  
Medical Sciences ◽  
Spike Glycoprotein ◽  
Mutagenic Potential ◽  
Viral Mutation ◽  
Novel Method ◽  
Antiviral Targets

Abstract Tools developed by Moderna, BioNTech/Pfizer, and Oxford/Astrazeneca, among others, provide universal solutions to previously problematic aspects of drug or vaccine delivery, uptake and toxicity, portending new tools across the medical sciences. A novel method is presented based on estimating protein backbone free energy via geometry to predict effective antiviral targets, antigens and vaccine cargos that are resistant to viral mutation. This method is reviewed and reformulated in light of the recent proliferation of structural data on the SARS-CoV-2 spike glycoprotein and its mutations in multiple lineages. Key findings include: collections of mutagenic residues reoccur across strains, suggesting cooperative convergent evolution; most mutagenic residues do not participate in backbone hydrogen bonds; metastability of the glyco-protein limits the change of free energy through mutation thereby constraining selective pressure; and there are mRNA or virus-vector cargos targeting low free energy peptides proximal to conserved high free energy peptides providing specific recipes for vaccines with greater specificity than the full-spike approach. These results serve to limit peptides in the spike glycoprotein with high mutagenic potential and thereby provide a priori constraints on viral and attendant vaccine evolution. Scientific and regulatory challenges to nucleic acid therapeutic and vaccine development and deployment are finally discussed.

scholarly journals Antiviral Resistance against Viral Mutation: Praxis and Policy for SARS CoV-2

2021 ◽  
Author(s):  
Robert Penner
Keyword(s):  
Free Energy ◽  
Vaccine Development ◽  
Structural Data ◽  
Antiviral Resistance ◽  
Medical Sciences ◽  
Viral Mutation ◽  
Novel Method ◽  
Antiviral Targets ◽  
Universal Solutions ◽  
Regulatory Challenges

AbstractNew tools developed by Moderna, BioNTech/Pfizer and Oxford/Astrazeneca provide universal solutions to previously problematic aspects of drug or vaccine delivery, uptake and toxicity, portending new tools across the medical sciences. A novel method is presented based on estimating protein backbone free energy via geometry to predict effective antiviral targets, antigens and vaccine cargoes that are resistant to viral mutation. This method, partly described in earlier work of the author, is reviewed and reformulated here in light of the profusion of recent structural data on the SARS CoV-2 spike glycoprotein and its latest mutations. Scientific and regulatory challenges to nucleic acid therapeutic and vaccine development and deployment are also discussed.

scholarly journals Use of scaled-particle theory in the assessment of the Ph4As+/Ph4B− assumption for single ions

1979 ◽  
Vol 57 (1) ◽  
pp. 71-76 ◽  
Author(s):  
Michael H. Abraham ◽  
Asadollah Nasehzadeh
Keyword(s):  
Free Energy ◽  
Recent Work ◽  
Scaled Particle Theory ◽  
Cavity Formation ◽  
Energy Term ◽  
Free Energies ◽  
Particle Theory ◽  
Novel Method ◽  
Energy Of Interaction ◽  
Solvent Molecules

A novel method for the assessment of the Ph4As+/Ph4B− assumption for free energies of transfer of single ions has recently been suggested by Treiner, and used by him to deduce that the assumption is not valid for transfers between water, propylene carbonate, sulpholane, dimethylsulphoxide, N-methyl-2-pyrrolidone, and perhaps also dimethylformamide. The basis of the method is the estimation of the free energy of cavity formation by scaled-particle theory, together with the hypothesis that the free energy of interaction of Ph4As+ (or Ph4B−) with solvent molecules is the same in all solvents, ΔGt0(int) = 0. It is shown in the present paper that (a) whether or not the Ph4As+/Ph4B− assumption applies to transfer to a given solvent depends on which other solvent is taken as the reference solvent in Treiner's method, (b) the calculation of the cavity free energy term by scaled-particle theory and by the theory of Sinanoglu – Reisse – Moura Ramos (SRMR) yields values so different that the method cannot be considered reliable, (c) the calculation of cavity enthalpies and entropies for Ph4As+ or Ph4B− by scaled-particle theory yields results that are chemically not reasonable, (d) the hypothesis that ΔGt0(int) = 0 conflicts with SRMR theory, and (e) the conclusions reached by Treiner are not in accord with recent work that in general supports the Ph4As+/Ph4B− assumption for solvents that are rejected by Treiner.

Novel method for hyperspectral unmixing: fuzzy c-means unmixing

Sensor Review ◽  
2016 ◽  
Vol 36 (2) ◽  
pp. 184-192
Author(s):  
Mingyu Nie ◽  
Zhi Liu ◽  
Xiaomei Li ◽  
Qiang Wu ◽  
Bo Tang ◽  
...  
Keyword(s):  
Design Methodology ◽  
Hyperspectral Image ◽  
A Priori ◽  
Image Sensors ◽  
Spectral Unmixing ◽  
Content Type ◽  
Hyperspectral Unmixing ◽  
Fuzzy C Means ◽  
Novel Method ◽  
Iteration Analysis

Purpose This paper aims to effectively achieve endmembers and relative abundances simultaneously in hyperspectral image unmixing yield. Hyperspectral unmixing, which is an important step before image classification and recognition, is a challenging issue because of the limited resolution of image sensors and the complex diversity of nature. Unmixing can be performed using different methods, such as blind source separation and semi-supervised spectral unmixing. However, these methods have disadvantages such as inaccurate results or the need for the spectral library to be known a priori. Design/methodology/approach This paper proposes a novel method for hyperspectral unmixing called fuzzy c-means unmixing, which achieves endmembers and relative abundance through repeated iteration analysis at the same time. Findings Experimental results demonstrate that the proposed method can effectively implement hyperspectral unmixing with high accuracy. Originality/value The proposed method present an effective framework for the challenging field of hyperspectral image unmixing.

scholarly journals Energetics based epitope screening in SARS CoV-2 (COVID 19) spike glycoprotein by Immuno-informatic analysis aiming to a suitable vaccine development

2020 ◽  
Author(s):  
Amrita Banerjee ◽  
Dipannita Santra ◽  
Smarajit Maiti
Keyword(s):  
Vaccine Development ◽  
Spike Glycoprotein ◽  
Structure Quality ◽  
Angiotensin Converting Enzyme 2 ◽  
Mhc Ii ◽  
Good Target ◽  
Short Period ◽  
Recent Outbreak ◽  
Interpro Database

AbstractThe recent outbreak by SARS-CoV-2 has generated a chaos in global health and economy and claimed/infected a large number of lives. Closely resembling with SARS CoV, the present strain has manifested exceptionally higher degree of spreadability, virulence and stability possibly due to some unidentified mutations. The viral spike glycoprotein is very likely to interact with host Angiotensin-Converting Enzyme 2 (ACE2) and transmits its genetic materials and hijacks host machinery with extreme fidelity for self propagation. Few attempts have been made to develop a suitable vaccine or ACE2 blocker or virus-receptor inhibitor within this short period of time. Here, attempt was taken to develop some therapeutic and vaccination strategies with a comparison of spike glycoproteins among SARS-CoV, MERS-CoV and the SARS-CoV-2. We verified their structure quality (SWISS-MODEL, Phyre2, Pymol) topology (ProFunc), motifs (MEME Suite, GLAM2Scan), gene ontology based conserved domain (InterPro database) and screened several epitopes (SVMTrip) of SARS CoV-2 based on their energetics, IC50 and antigenicity with regard to their possible glycosylation and MHC/paratopic binding (Vaxigen v2.0, HawkDock, ZDOCK Server) effects. We screened here few pairs of spike protein epitopic regions and selected their energetic, IC50, MHC II reactivity and found some of those to be very good target for vaccination. A possible role of glycosylation on epitopic region showed profound effects on epitopic recognition. The present work might be helpful for the urgent development of a suitable vaccination regimen against SARS CoV-2.

scholarly journals Exploiting NoSQL Graph Databases and in Memory Architectures for Extracting Graph Structural Data Summaries

2017 ◽  
Vol 25 (01) ◽  
pp. 81-109 ◽  
Author(s):  
Arnaud Castelltort ◽  
Anne Laurent
Keyword(s):  
Relational Databases ◽  
Structural Data ◽  
Scientific Data ◽  
Graph Database ◽  
Graph Databases ◽  
Fuzzy Operators ◽  
Data Volume ◽  
Novel Method ◽  
Memory Architectures ◽  
Data Summaries

NoSQL graph databases have been introduced in recent years for dealing with large collections of graph-based data. Scientific data and social networks are among the best examples of the dramatic increase of the use of such structures. NoSQL repositories allow the management of large amounts of data in order to store and query them. Such data are not structured with a predefined schema as relational databases could be. They are rather composed by nodes and relationships of a certain type. For instance, a node can represent a Person and a relationship Friendship. Retrieving the structure of the graph database is thus of great help to users, for example when they must know how to query the data or to identify relevant data sources for recommender systems. For this reason, this paper introduces methods to retrieve structural summaries. Such structural summaries are extracted at different levels of information from the NoSQL graph database. The expression of the mining queries is facilitated by the use of two frame-works: Fuzzy4S allowing to define fuzzy operators and operations with Scala; Cypherf allowing the use of fuzzy operators and operations in the declarative queries over NoSQL graph databases. We show that extracting such summaries can be impossible with the NoSQL query engines because of the data volume and the complexity of the task of automatic knowledge extraction. A novel method based on in memory architectures is thus introduced. This paper provides the definitions of the summaries with the methods to automatically extract them from NoSQL graph databases only and with the help of in-memory architectures. The benefit of our proposition is demonstrated by experimental results.

scholarly journals Distributions of Hyper-Local Configuration Elements to Characterize, Compare, and Assess Landscape-Level Spatial Patterns

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 420
Author(s):  
Tarmo K. Remmel
Keyword(s):  
A Priori ◽  
Simulated Data ◽  
Generic Model ◽  
Regular Grid ◽  
First Order ◽  
Local Configuration ◽  
Leibler Divergence ◽  
Common Framework ◽  
Novel Method ◽  
The Many

Even with considerable attention in recent decades, measuring and working with patterns remains a complex task due to the underlying dynamic processes that form these patterns, the influence of scales, and the many further implications stemming from their representation. This work scrutinizes binary classes mapped onto regular grids and counts the relative frequencies of all first-order configuration components and then converts these measurements into empirical probabilities of occurrence for either of the two landscape classes. The approach takes into consideration configuration explicitly and composition implicitly (in a common framework), while the construction of a frequency distribution provides a generic model of landscape structure that can be used to simulate structurally similar landscapes or to compare divergence from other landscapes. The technique is first tested on simulated data to characterize a continuum of landscapes across a range of spatial autocorrelations and relative compositions. Subsequent assessments of boundary prominence are explored, where outcomes are known a priori, to demonstrate the utility of this novel method. For a binary map on a regular grid, there are 32 possible configurations of first-order orthogonal neighbours. The goal is to develop a workflow that permits patterns to be characterized in this way and to offer an approach that identifies how relatively divergent observed patterns are, using the well-known Kullback–Leibler divergence.

scholarly journals Термодинамическая модель зародышеобразования кристаллов n-терфенила с анизотропией поверхностной энергии на межфазной границе жидкость-воздух

2019 ◽  
Vol 61 (12) ◽  
pp. 2432
Author(s):  
В.А. Постников ◽  
А.А. Кулишов ◽  
А.А. Островская ◽  
А.С. Степко ◽  
П.В. Лебедев-Степанов
Keyword(s):  
Free Energy ◽  
Crystal Growth ◽  
Surface Energy ◽  
Force Field ◽  
Structural Data ◽  
Field Method ◽  
Experimental Information ◽  
Growth From Solutions ◽  
Atomic Force ◽  
Air Interface

An analysis of the change in the Gibbs free energy ∆G upon the formation of a flat nucleus of a p-terphenyl crystal at the liquid – air interface is presented, taking into account the anisotropy of the surface energy of the faces. The surface energy values of the p-terphenyl crystal faces were calculated by the atomic force field method OPLS, based on structural data. Experimental information on crystal growth from solutions and their surface properties was used to analyze the model.

scholarly journals A Pipeline for Making 31P NMR Accessible for Small- and Large-Scale Lipidomics Studies

2021 ◽  
Author(s):  
Samuel Furse ◽  
Huw Williams ◽  
Adam Watkins ◽  
Samuel Virtue ◽  
Antonio Vidal-Puig ◽  
...  
Keyword(s):  
Large Scale ◽  
31P Nmr ◽  
A Priori ◽  
Structural Data ◽  
Mass Spectrometry Data ◽  
Head Group ◽  
Sample Extraction ◽  
Tools And Techniques ◽  
Scientific Questions ◽  
Insight Into

Detailed molecular analysis is of increasing importance in research into the regulation of biochemical pathways, organismal growth and disease. Lipidomics in particular is increasingly sought after as it provides insight into molecular species involved in energy storage, signalling and fundamental cellular structures. This has led to the use of a range of tools and techniques to acquire lipidomics data. 31P NMR for lipidomics offers well-resolved head group/lipid class analysis, structural data that can be used to inform and strengthen interpretation of mass spectrometry data and part of structural determination a priori. In the present study, we codify the use of 31P NMR for lipidomics to make the technique more accessible to new users and more useful for a wider range of studies. We describe the process from sample extraction to data processing and analysis. This pipeline is important because it allows greater thoroughness in lipidomics studies and increases scope for answering scientific questions about lipid systems.

scholarly journals Franchise extension and fiscal structure in the UK 1820–1913: a new test of the Redistribution Hypothesis

Cliometrica ◽  
2021 ◽  
Author(s):  
Toke S. Aidt ◽  
Stanley L. Winer ◽  
Peng Zhang
Keyword(s):  
Experimental Data ◽  
Narrative Analysis ◽  
Structural Breaks ◽  
A Priori ◽  
Historical Narrative ◽  
Compelling Evidence ◽  
Novel Method ◽  
The Uk ◽  
The Relationship ◽  
Do So

AbstractThe Redistribution Hypothesis predicts that franchise extension causes an increase in state-sponsored redistribution. We test this hypothesis by considering the relationship between franchise extension and selected aspects of fiscal structure at both central and local government levels in the UK from 1820 to 1913. We do so without imposing a priori restrictions on the direction of causality using a novel method for causal investigation of non-experimental data proposed by Hoover (2001). This method is based on tests for structural breaks in the conditional and marginal distributions of the franchise and fiscal structure time series preceded by a detailed historical narrative analysis. We do not find compelling evidence supporting the Redistribution Hypothesis.

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