scholarly journals Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules

2021 ◽  
Author(s):  
Stefano Zamuner ◽  
Flavio Seno ◽  
Antonio Trovato
Keyword(s):  
Effective Interaction ◽  
Polymer Melt ◽  
Coarse Graining ◽  
Data Bank ◽  
Polymer Chains ◽  
Reference State ◽  
Protein Chain ◽  
Statistical Potentials ◽  
Knowledge Based ◽  
Wide Range

Knowledge-based approaches use the statistics collected from protein data-bank structures to estimate effective interaction potentials between amino acid pairs. Empirical relations are typically employed that are based on the crucial choice of a reference state associated to the null interaction case. Despite their significant effectiveness, the physical interpretation of knowledge-based potentials has been repeatedly questioned, with no consensus on the choice of the reference state. Here we use the fact that the Flory theorem, originally derived for chains in a dense polymer melt, holds also for chain fragments within the core of globular proteins, if the average over buried fragments collected from different non-redundant native structures is considered. After verifying that the ensuing Gaussian statistics, a hallmark of effectively non-interacting polymer chains, holds for a wide range of fragment lengths, we use it to define a `bona fide' reference state. Notably, despite the latter does depend on fragment length, deviations from it do not. This allows to estimate an effective interaction potential which is not biased by the presence of correlations due to the connectivity of the protein chain. We show how different sequence-independent effective statistical potentials can be derived using this approach by coarse-graining the protein representation at varying levels. The possibility of defining sequence-dependent potentials is explored.

scholarly journals Statistical Potentials from the Gaussian Scaling Behaviour of Chain Fragments Buried within Protein Globules

2021 ◽  
Author(s):  
Stefano Zamuner ◽  
Flavio Seno ◽  
Antonio Trovato
Keyword(s):  
Effective Interaction ◽  
Polymer Melt ◽  
Coarse Graining ◽  
Polymer Chains ◽  
Reference State ◽  
Protein Chain ◽  
Statistical Potentials ◽  
Knowledge Based ◽  
Wide Range ◽  
Bona Fide

Abstract Knowledge-based approaches use the statistics collected from protein databank structures to estimate effective interaction potentials between amino acid pairs. Empirical relations are typically employed that are based on the crucial choice of a reference state associated to the null interaction case. Despite their significant effectiveness, the physical interpretation of knowledge-based potentials has been repeatedly questioned, with no consensus on the choice of the reference state. Here we use the fact that the Flory theorem, originally derived for chains in a dense polymer melt, holds also for chain fragments within the core of globular proteins. After verifying that the ensuing Gaussian statistics, a hallmark of effectively non-interacting polymer chains, holds for a wide range of fragment lengths, we use it to define a ‘bona fide’ reference state. Notably, despite the latter does depend on fragment length, deviations from it do not. This allows to estimate an effective interaction potential which is not biased by the presence of correlations due to the connectivity of the protein chain. We show how different sequence-independent effective statistical potentials can be derived using this approach by coarse-graining the protein representation at varying levels. The possibility of defining sequence-dependent potentials is explored.

scholarly journals A Hybrid Knowledge-Based Recommender for Product-Service Systems Mass Customization

Information ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 296
Author(s):  
Laila Esheiba ◽  
Amal Elgammal ◽  
Iman M. A. Helal ◽  
Mohamed E. El-Sharkawi
Keyword(s):  
Recommender System ◽  
Mass Customization ◽  
Constraint Satisfaction Problem ◽  
Service Systems ◽  
Prototype System ◽  
Knowledge Based ◽  
Product Service ◽  
Wide Range ◽  
Hybrid Knowledge ◽  
Product Service Systems

Manufacturers today compete to offer not only products, but products accompanied by services, which are referred to as product-service systems (PSSs). PSS mass customization is defined as the production of products and services to meet the needs of individual customers with near-mass-production efficiency. In the context of the PSS mass customization environment, customers are overwhelmed by a plethora of previously customized PSS variants. As a result, finding a PSS variant that is precisely aligned with the customer’s needs is a cognitive task that customers will be unable to manage effectively. In this paper, we propose a hybrid knowledge-based recommender system that assists customers in selecting previously customized PSS variants from a wide range of available ones. The recommender system (RS) utilizes ontologies for capturing customer requirements, as well as product-service and production-related knowledge. The RS follows a hybrid recommendation approach, in which the problem of selecting previously customized PSS variants is encoded as a constraint satisfaction problem (CSP), to filter out PSS variants that do not satisfy customer needs, and then uses a weighted utility function to rank the remaining PSS variants. Finally, the RS offers a list of ranked PSS variants that can be scrutinized by the customer. In this study, the proposed recommendation approach was applied to a real-life large-scale case study in the domain of laser machines. To ensure the applicability of the proposed RS, a web-based prototype system has been developed, realizing all the modules of the proposed RS.

scholarly journals RuSseL: A Self-Consistent Field Theory Code for Inhomogeneous Polymer Interphases

Computation ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 57
Author(s):  
Constantinos J. Revelas ◽  
Aristotelis P. Sgouros ◽  
Apostolos T. Lakkas ◽  
Doros N. Theodorou
Keyword(s):  
Field Theory ◽  
Polymer Melt ◽  
Polymer Chains ◽  
Solid Polymer ◽  
One Dimensional ◽  
Consistent Field ◽  
Adsorbed Polymer ◽  
Self Consistent ◽  
Self Consistent Field ◽  
Self Consistent Field Theory

In this article, we publish the one-dimensional version of our in-house code, RuSseL, which has been developed to address polymeric interfaces through Self-Consistent Field calculations. RuSseL can be used for a wide variety of systems in planar and spherical geometries, such as free films, cavities, adsorbed polymer films, polymer-grafted surfaces, and nanoparticles in melt and vacuum phases. The code includes a wide variety of functional potentials for the description of solid–polymer interactions, allowing the user to tune the density profiles and the degree of wetting by the polymer melt. Based on the solution of the Edwards diffusion equation, the equilibrium structural properties and thermodynamics of polymer melts in contact with solid or gas surfaces can be described. We have extended the formulation of Schmid to investigate systems comprising polymer chains, which are chemically grafted on the solid surfaces. We present important details concerning the iterative scheme required to equilibrate the self-consistent field and provide a thorough description of the code. This article will serve as a technical reference for our works addressing one-dimensional polymer interphases with Self-Consistent Field theory. It has been prepared as a guide to anyone who wishes to reproduce our calculations. To this end, we discuss the current possibilities of the code, its performance, and some thoughts for future extensions.

scholarly journals Protein dynamics revealed by NMR relaxation methods

2018 ◽  
Vol 2 (1) ◽  
pp. 93-105 ◽  
Author(s):  
Fa-An Chao ◽  
R. Andrew Byrd
Keyword(s):  
Protein Dynamics ◽  
Structural Biology ◽  
Dynamic Models ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Data Bank ◽  
Biological Macromolecules ◽  
Relaxation Methods ◽  
Genomic Databases ◽  
Wide Range

Structural biology often focuses primarily on three-dimensional structures of biological macromolecules, deposited in the Protein Data Bank (PDB). This resource is a remarkable entity for the worldwide scientific and medical communities, as well as the general public, as it is a growing translation into three-dimensional space of the vast information in genomic databases, e.g. GENBANK. There is, however, significantly more to understanding biological function than the three-dimensional co-ordinate space for ground-state structures of biomolecules. The vast array of biomolecules experiences natural dynamics, interconversion between multiple conformational states, and molecular recognition and allosteric events that play out on timescales ranging from picoseconds to seconds. This wide range of timescales demands ingenious and sophisticated experimental tools to sample and interpret these motions, thus enabling clearer insights into functional annotation of the PDB. NMR spectroscopy is unique in its ability to sample this range of timescales at atomic resolution and in physiologically relevant conditions using spin relaxation methods. The field is constantly expanding to provide new creative experiments, to yield more detailed coverage of timescales, and to broaden the power of interpretation and analysis methods. This review highlights the current state of the methodology and examines the extension of analysis tools for more complex experiments and dynamic models. The future for understanding protein dynamics is bright, and these extended tools bring greater compatibility with developments in computational molecular dynamics, all of which will further our understanding of biological molecular functions. These facets place NMR as a key component in integrated structural biology.

scholarly journals Management activities in the field of wellness physical health activity of population in large cities of Europe: analysis of approaches

2020 ◽  
Vol 8 (6) ◽  
pp. 221-229
Author(s):  
Yevgeniy Borodin ◽  
Valerii Makashov
Keyword(s):  
Physical Activity ◽  
Local Governments ◽  
Effective Interaction ◽  
Public And Private ◽  
Large Cities ◽  
Increased Risk ◽  
Wide Range ◽  
Logical Method ◽  
Risk Of Disease ◽  
National Governments

Introduction. WHO has adopted a Strategy for Physical Activity and calls on national governments and local governments to update this area. The priority of this area is most obvious in large cities, whose population leads a predominantly sedentary lifestyle, resulting in an increased risk of disease and general deterioration in health both nationally and globally. The purpose of the study is to study the mechanisms of stimulating the population to develop physical activity, involvement in physical culture and mass sports in the activities of local authorities. Analysis of models of social interaction in order to form the commitment of the population to physical activity with the implementation of this value in all spheres of life. Material and methods - analysis of laws, comparative analysis, logical method. The results of the study - in some countries a network of healthy municipalities has been established and operates as part of the implementation of measures to support physical activity. In the EU, local governments have been paying close attention to this for several decades, accumulating a wide range of tools for effective interaction between government, the public and private sectors. Conclusion - this experience is extremely useful for Ukraine, namely in the study of the functions, forms and methods of physical activity management in large cities, especially in the context of the COVID19 pandemic.

scholarly journals System of criteria for effective interaction between the police and society in the interests of public security

2019 ◽  
pp. 66-72
Author(s):  
Сергей Ханин ◽  
Sergey Hanin
Keyword(s):  
Public Safety ◽  
Effective Interaction ◽  
Public Security ◽  
Personal Value ◽  
Constructive Dialogue ◽  
Wide Range

The article attempts to form a system of criteria to assess the effectiveness of the emerging partnership between the police and society, the purpose of which is to ensure public safety. Among the groups of criteria that determine the basis of interaction and their effectiveness, the author highlights the legal, organizational and personal value. The author comes to the conclusion that the emerging system of criteria for assessing the effectiveness of police and society interaction is designed to determine a wide range of prospects and features of a constructive dialogue that can eliminate the confrontation of interests and destructiveness both in relation to society and in relation to police.

scholarly journals A scaled MP-PIC method for bubbling fluidization

2021 ◽  
Author(s):  
Xing Zhao ◽  
Yong Jiang ◽  
Fei Li ◽  
Wei Wang
Keyword(s):  
Fluidized Beds ◽  
Volume Fraction ◽  
Phase Particle ◽  
Scaling Law ◽  
Coarse Graining ◽  
Coarse Grained ◽  
Particle In Cell ◽  
Wide Range ◽  
Pic Method ◽  
Multi Phase

Coarse-grained methods have been widely used in simulations of gas-solid fluidization. However, as a key parameter, the coarse-graining ratio, and its relevant scaling law is still far from reaching a consensus. In this work, a scaling law is developed based on a similarity analysis, and then it is used to scale the multi-phase particle-in-cell (MP-PIC) method, and validated in the simulation of two bubbling fluidized beds. The simulation result shows this scaled MP-PIC can reduce the errors of solids volume fraction and velocity distributions over a wide range of coarse-graining ratios. In future, we expect that a scaling law with consideration of the heterogeneity inside a parcel or numerical particle will further improve the performance of coarse-grained modeling in simulation of fluidized beds.

Improving Prediction Accuracy via Subspace Modeling in a Statistical Geometry Based Computational Protein Mutagenesis

2010 ◽  
Vol 1 (4) ◽  
pp. 54-68
Author(s):  
Majid Masso
Keyword(s):  
Bacteriophage T4 ◽  
Protein Structures ◽  
Dimensional Subspace ◽  
Sequence Length ◽  
Protein Chain ◽  
Contact Potential ◽  
Knowledge Based ◽  
Environmental Perturbations ◽  
Subspace Modeling ◽  
Residue Substitution

A computational mutagenesis is detailed whereby each single residue substitution in a protein chain of primary sequence length N is represented as a sparse N-dimensional feature vector, whose M << N nonzero components locally quantify environmental perturbations occurring at the mutated position and its neighbors in the protein structure. The methodology makes use of both the Delaunay tessellation algorithm for representing protein structures, as well as a four-body, knowledge based, statistical contact potential. Feature vectors for each subset of mutants due to all possible residue substitutions at a particular position cohabit the same M-dimensional subspace, where the value of M and the identities of the M nonzero components are similarly position dependent. The approach is used to characterize a large experimental dataset of single residue substitutions in bacteriophage T4 lysozyme, each categorized as either unaffected or affected based on the measured level of mutant activity relative to that of the native protein. Performance of a single classifier trained with the collective set of mutants in N-space is compared to that of an ensemble of position-specific classifiers trained using disjoint mutant subsets residing in significantly smaller subspaces. Results suggest that significant improvements can be achieved through subspace modeling.

Different folding models for 6Li+28Si elastic scattering

2020 ◽  
Vol 29 (09) ◽  
pp. 2050075
Author(s):  
Awad A. Ibraheem ◽  
M. El-Azab Farid ◽  
Eman Abd El-Rahman ◽  
Zakaria M. M. Mahmoud ◽  
Sherif R. Mokhtar
Keyword(s):  
Elastic Scattering ◽  
Optical Potential ◽  
Optical Model ◽  
Effective Interaction ◽  
Text Structure ◽  
Normalization Factor ◽  
Wide Range ◽  
Cluster Density ◽  
Double Folding ◽  
Good Agreement

In this work, the elastic scattering of 6Li+[Formula: see text]Si system at wide range energies from 76 to 318[Formula: see text]MeV is analyzed. The analysis is carried out in the framework of the optical model (OM). Two different methods are adopted for nuclear optical potential of this system. The first method is the double folding cluster (DFC) for the real part supplied with an imaginary part in the Woods–Saxon (WS) form. In the second one, the double folding (DF) model based upon São Paulo potential (SPP) is used as real and imaginary parts each multiplied by a corresponding normalization factor. For [Formula: see text]Si, the full [Formula: see text]-cluster density is considered while the [Formula: see text]-deuteron ([Formula: see text]–[Formula: see text]) structure is considered for 6Li. Therefore, the DFC real central part is calculated by folding both [Formula: see text]–[Formula: see text] and [Formula: see text]–[Formula: see text] effective interaction between target and nuclei over the cluster densities of the target and projectile. The derived renormalized potentials give a successful description of the data. The present results are in good agreement with the previous work. This agreement confirms the validity of the present methods to generate nucleus–nucleus optical potentials.

KORP: knowledge-based 6D potential for fast protein and loop modeling

2019 ◽  
Vol 35 (17) ◽  
pp. 3013-3019 ◽  
Author(s):  
José Ramón López-Blanco ◽  
Pablo Chacón
Keyword(s):  
Structure Prediction ◽  
Protein Structures ◽  
Joint Probability ◽  
Protein Modeling ◽  
Supplementary Information ◽  
Joint Probability Distribution ◽  
Loop Modeling ◽  
Statistical Potentials ◽  
Knowledge Based ◽  
Backbone Atoms

Abstract Motivation Knowledge-based statistical potentials constitute a simpler and easier alternative to physics-based potentials in many applications, including folding, docking and protein modeling. Here, to improve the effectiveness of the current approximations, we attempt to capture the six-dimensional nature of residue–residue interactions from known protein structures using a simple backbone-based representation. Results We have developed KORP, a knowledge-based pairwise potential for proteins that depends on the relative position and orientation between residues. Using a minimalist representation of only three backbone atoms per residue, KORP utilizes a six-dimensional joint probability distribution to outperform state-of-the-art statistical potentials for native structure recognition and best model selection in recent critical assessment of protein structure prediction and loop-modeling benchmarks. Compared with the existing methods, our side-chain independent potential has a lower complexity and better efficiency. The superior accuracy and robustness of KORP represent a promising advance for protein modeling and refinement applications that require a fast but highly discriminative energy function. Availability and implementation http://chaconlab.org/modeling/korp. Supplementary information Supplementary data are available at Bioinformatics online.

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