scholarly journals Searching the optimal folding routes of a Complex Lasso protein

2018 ◽  
Author(s):  
Claudio Perego ◽  
Raffaello Potestio
Keyword(s):  
Protein Folding ◽  
Protein Structures ◽  
Test System ◽  
Coarse Grained ◽  
Evolutionary Strategy ◽  
Topological Descriptors ◽  
Structure Topology ◽  
Factor Modeling ◽  
Angular Potential ◽  
Macrophage Colony

ABSTRACTUnderstanding how polypeptides can efficiently and reproducibly attain a self-entangled conformation is a compelling biophysical challenge, which might shed new light on our general knowledge of protein folding. Complex Lassos, namely self-entangled protein structures characterized by a covalent loop sealed by a cysteine bridge, represent an ideal test system in the framework of entangled folding. Indeed, as cysteine bridges form in oxidizing conditions, they can be used as on/off switches of the structure topology, to investigate the role played by the backbone entanglement in the process.In the present work we have used molecular dynamics to simulate the folding of a complex lasso glycoprotein, Granulocyte-macrophage colony-stimulating factor, modeling both reducing and oxidizing conditions. Together with a well-established Go-like description, we have employed the elastic folder model, a Coarse-Grained, minimalistic representation of the polypeptide chain, driven by a structure-based angular potential. The purpose of this study is to assess the kinetically optimal pathways, in relation to the formation of the native topology. To this end we have implemented an evolutionary strategy that tunes the elastic folder model potentials to maximize the folding probability within the early stages of the dynamics. The resulting protein model is capable of folding with high success rate, avoiding the kinetic traps that hamper the efficient folding in the other tested models. Employing specifically designed topological descriptors, we could observe that the selected folding routes avoid the topological bottleneck by locking the cysteine bridge after the topology is formed.These results provide valuable insights on the selection of mechanisms in self-entangled protein folding while, at the same time, the proposed methodology can complement the usage of established minimalistic models, and draw useful guidelines for more detailed simulations.

scholarly journals Modeling of Disordered Protein Structures Using Monte Carlo Simulations and Knowledge-Based Statistical Force Fields

2018 ◽  
Author(s):  
Maciej Pawel Ciemny ◽  
Aleksandra Elzbieta Badaczewska-Dawid ◽  
Monika Pikuzinska ◽  
Andrzej Kolinski ◽  
Sebastian Kmiecik
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Protein Folding ◽  
Case Studies ◽  
Protein Structures ◽  
Coarse Grained ◽  
Computational Time ◽  
Modeling Tools ◽  
Disordered Protein ◽  
Knowledge Based

The description of protein disordered states is important for understanding protein folding mechanisms and their functions. In this short review, we briefly describe a simulation approach to modeling disordered protein interactions and unfolded states of globular proteins. It is based on the CABS coarse-grained protein model that uses a Monte Carlo (MC) sampling scheme and a knowledge-based statistical force field. We review several case studies showing that description of protein disordered states resulting from CABS simulations is consistent with experimental data. The case studies comprise investigations of protein-peptide binding and protein folding processes. The CABS model has been recently made available as the simulation engine of multiscale modeling tools enabling studies of protein-peptide docking and protein flexibility. Those tools offer customization of the modeling process, driving the conformational search using distance restraints, reconstruction of selected models to all-atom resolution and studies of large protein systems in a reasonable computational time. Therefore, CABS can be combined in integrative modeling pipelines incorporating experimental data and other modeling tools of various resolution.

scholarly journals Modeling of Disordered Protein Structures Using Monte Carlo Simulations and Knowledge-Based Statistical Force Fields

2019 ◽  
Vol 20 (3) ◽  
pp. 606 ◽  
Author(s):  
Maciej Ciemny ◽  
Aleksandra Badaczewska-Dawid ◽  
Monika Pikuzinska ◽  
Andrzej Kolinski ◽  
Sebastian Kmiecik
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Protein Folding ◽  
Case Studies ◽  
Protein Structures ◽  
Coarse Grained ◽  
Computational Time ◽  
Modeling Tools ◽  
Disordered Protein ◽  
Knowledge Based

The description of protein disordered states is important for understanding protein folding mechanisms and their functions. In this short review, we briefly describe a simulation approach to modeling protein interactions, which involve disordered peptide partners or intrinsically disordered protein regions, and unfolded states of globular proteins. It is based on the CABS coarse-grained protein model that uses a Monte Carlo (MC) sampling scheme and a knowledge-based statistical force field. We review several case studies showing that description of protein disordered states resulting from CABS simulations is consistent with experimental data. The case studies comprise investigations of protein–peptide binding and protein folding processes. The CABS model has been recently made available as the simulation engine of multiscale modeling tools enabling studies of protein–peptide docking and protein flexibility. Those tools offer customization of the modeling process, driving the conformational search using distance restraints, reconstruction of selected models to all-atom resolution, and simulation of large protein systems in a reasonable computational time. Therefore, CABS can be combined in integrative modeling pipelines incorporating experimental data and other modeling tools of various resolution.

T26248G-transversion mutation in exon7 of the putative methyltransferase Nsun7 gene causes a change in protein folding associated with reduced sperm motility in asthenospermic men

2015 ◽  
Vol 27 (3) ◽  
pp. 471 ◽  
Author(s):  
Nahid Khosronezhad ◽  
Abasalt Hosseinzadeh Colagar ◽  
Syed Golam Ali Jorsarayi
Keyword(s):  
Protein Folding ◽  
Sperm Motility ◽  
Protein Function ◽  
Direct Sequencing ◽  
Protein Structures ◽  
Single Strand Conformation Polymorphism ◽  
Extraction Methods ◽  
World Health ◽  
Transversion Mutation ◽  
Health Organization

The NOP2/Sun domain family, member 7 (Nsun7) gene, which encodes putative methyltransferase Nsun7, has a role in sperm motility in mice. In humans, this gene is located on chromosome 4 with 12 exons. The aim of the present study was to investigate mutations of exon 7 in the normospermic and asthenospermic men. Semen samples were collected from the Fatemezahra IVF centre (Babol, Iran) and analysed on the basis of World Health Organization (WHO) guidelines using general phenol–chloroform DNA extraction methods. Exon 7 was amplified using Sun7-F and Sun7-R primers. Bands on samples from asthenospermic men that exhibited different patterns of movement on single-strand conformation polymorphism gels compared with normal samples were identified and subjected to sequencing for further identification of possible mutations. Direct sequencing of polymerase chain reaction (PCR) products, along with their analysis, confirmed C26232T-transition and T26248G-transversion mutations in asthenospermic men. Comparison of normal and mutant protein structures of Nsun7 indicated that the amino acid serine was converted to alanine, the structure of the helix, coil and strand was changed, and the protein folding and ligand binding sites were changed in samples from asthenospermic men with a transversion mutation in exon 7, indicating impairment of protein function. Because Nsun7 gene products have a role in sperm motility, if an impairment occurs in exon 7 of this gene, it may lead to infertility. The transversion mutation in exon 7 of the Nsun7 gene can be used as an infertility marker in asthenospermic men.

scholarly journals Distributions of experimental protein structures on coarse-grained free energy landscapes

2015 ◽  
Vol 143 (24) ◽  
pp. 243153 ◽  
Author(s):  
Kannan Sankar ◽  
Jie Liu ◽  
Yuan Wang ◽  
Robert L. Jernigan
Keyword(s):  
Free Energy ◽  
Protein Structures ◽  
Coarse Grained ◽  
Energy Landscapes ◽  
Free Energy Landscapes

scholarly journals A Generic Force Field for Simulating Native Protein Structures Using Dissipative Particle Dynamics

Soft Matter ◽  
2021 ◽  
Author(s):  
Rakesh K Vaiwala ◽  
Ganapathy Ayappa
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Molecular Dynamics Simulations ◽  
Dissipative Particle Dynamics ◽  
Protein Structures ◽  
Particle Dynamics ◽  
Coarse Grained ◽  
Native Protein ◽  
Dynamics Simulations

A coarse-grained force field for molecular dynamics simulations of native structures of proteins in a dissipative particle dynamics (DPD) framework is developed. The parameters for bonded interactions are derived by...

Self-Similarity of Protein Folding Flows

2012 ◽  
Vol 7 (4) ◽  
pp. 136-141
Author(s):  
I. Kalgin ◽  
Sergey Chekmarev
Keyword(s):  
Protein Folding ◽  
Sh3 Domain ◽  
Atomic Level ◽  
The Self ◽  
Coarse Grained ◽  
Folding Kinetics ◽  
Native State ◽  
Self Similarity ◽  
Folding Dynamics ◽  
Fractal Character

The problem of how a protein folds into its functional (native) state is one of the central problems of molecular biology, which attracts the attention of researchers from biology, physics and chemistry for many years. Of particular interest are general properties of the folding process, because the mechanisms of folding of different proteins can be essentially different. Previously, in the study of folding of fyn SH3 domain, we found that despite all the diversity and complexity of individual folding trajectories, the folding flows possess a well pronounced property of self-similarity, with a fractal character of the flow distributions. In the present paper, we study this phenomenon for another protein – beta3s, which is essentially different from the SH3 domain in its structure and folding kinetics. Also, in contrast to the fyn SH3 domain, for which a coarse-grained representation was used, we perform simulations on the atomic level of resolution. We show that the self-similarity and fractality of folding flows are observed is this case too, which suggests that these properties are characteristic of the protein folding dynamics

3. Proteins

2021 ◽  
pp. 34-51
Author(s):  
Mark Lorch
Keyword(s):  
Amino Acids ◽  
Protein Folding ◽  
Protein Structure ◽  
Protein Structures ◽  
Structure And Function ◽  
Vast Array ◽  
A Cell ◽  
Cellular Machinery ◽  
And Function ◽  
The Relationship

This chapter examines proteins, the dominant proportion of cellular machinery, and the relationship between protein structure and function. The multitude of biological processes needed to keep cells functioning are managed in the organism or cell by a massive cohort of proteins, together known as the proteome. The twenty amino acids that make up the bulk of proteins produce the vast array of protein structures. However, amino acids alone do not provide quite enough chemical variety to complete all of the biochemical activity of a cell, so the chapter also explores post-translation modifications. It finishes by looking as some dynamic aspects of proteins, including enzyme kinetics and the protein folding problem.

scholarly journals ProSNEx: a web-based application for exploration and analysis of protein structures using network formalism

2019 ◽  
Vol 47 (W1) ◽  
pp. W471-W476 ◽  
Author(s):  
Rasim Murat Aydınkal ◽  
Onur Serçinoğlu ◽  
Pemra Ozbek
Keyword(s):  
Protein Structure ◽  
Normal Mode Analysis ◽  
Shortest Paths ◽  
Protein Structures ◽  
Interaction Strength ◽  
Biological Information ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Residue Interaction ◽  
Natural Variant

AbstractProSNEx (Protein Structure Network Explorer) is a web service for construction and analysis of Protein Structure Networks (PSNs) alongside amino acid flexibility, sequence conservation and annotation features. ProSNEx constructs a PSN by adding nodes to represent residues and edges between these nodes using user-specified interaction distance cutoffs for either carbon-alpha, carbon-beta or atom-pair contact networks. Different types of weighted networks can also be constructed by using either (i) the residue-residue interaction energies in the format returned by gRINN, resulting in a Protein Energy Network (PEN); (ii) the dynamical cross correlations from a coarse-grained Normal Mode Analysis (NMA) of the protein structure; (iii) interaction strength. Upon construction of the network, common network metrics (such as node centralities) as well as shortest paths between nodes and k-cliques are calculated. Moreover, additional features of each residue in the form of conservation scores and mutation/natural variant information are included in the analysis. By this way, tool offers an enhanced and direct comparison of network-based residue metrics with other types of biological information. ProSNEx is free and open to all users without login requirement at http://prosnex-tool.com.

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