scholarly journals AlloSigMA 2: paving the way to designing allosteric effectors and to exploring allosteric effects of mutations

2020 ◽  
Vol 48 (W1) ◽  
pp. W116-W124 ◽  
Author(s):  
Zhen Wah Tan ◽  
Enrico Guarnera ◽  
Wei-Ven Tee ◽  
Igor N Berezovsky
Keyword(s):  
Computational Design ◽  
Protein Activity ◽  
Antagonist Activity ◽  
Allosteric Control ◽  
Allosteric Effectors ◽  
Allosteric Sites ◽  
Statistical Mechanical Model ◽  
Statistical Mechanical ◽  
Allosteric Mechanisms ◽  
Potential Cancer

Abstract The AlloSigMA 2 server provides an interactive platform for exploring the allosteric signaling caused by ligand binding and/or mutations, for analyzing the allosteric effects of mutations and for detecting potential cancer drivers and pathogenic nsSNPs. It can also be used for searching latent allosteric sites and for computationally designing allosteric effectors for these sites with required agonist/antagonist activity. The server is based on the implementation of the Structure-Based Statistical Mechanical Model of Allostery (SBSMMA), which allows one to evaluate the allosteric free energy as a result of the perturbation at per-residue resolution. The Allosteric Signaling Map (ASM) providing a comprehensive residue-by-residue allosteric control over the protein activity can be obtained for any structure of interest. The Allosteric Probing Map (APM), in turn, allows one to perform the fragment-based-like computational design experiment aimed at finding leads for potential allosteric effectors. The server can be instrumental in elucidating of allosteric mechanisms and actions of allosteric mutations, and in the efforts on design of new elements of allosteric control. The server is freely available at: http://allosigma.bii.a-star.edu.sg

A statistical mechanical model for inverse melting

2003 ◽  
Vol 119 (8) ◽  
pp. 4582-4591 ◽  
Author(s):  
Melissa R. Feeney ◽  
Pablo G. Debenedetti ◽  
Frank H. Stillinger
Keyword(s):  
Mechanical Model ◽  
Statistical Mechanical Model ◽  
Statistical Mechanical

scholarly journals Cooperativity and modularity in protein folding

2016 ◽  
Author(s):  
Masaki Sasai ◽  
George Chikenji ◽  
Tomoki P. Terada
Keyword(s):  
Protein Folding ◽  
Mechanical Model ◽  
Energy Landscape ◽  
Native Conformation ◽  
Folding Nucleus ◽  
Modern Methods ◽  
Complex Topology ◽  
Statistical Mechanical Model ◽  
Statistical Mechanical ◽  
Dynamical Features

AbstractA simple statistical mechanical model proposed by Wako and Saitô has explained the aspects of protein folding surprisingly well. This model was systematically applied to multiple proteins by Muñoz and Eaton and has since been referred to as the Wako-Saitô-Muñoz-Eaton (WSME) model. The success of the WSME model in explaining the folding of many proteins has verified the hypothesis that the folding is dominated by native interactions, which makes the energy landscape globally biased toward native conformation. Using the WSME and other related models, Saitô emphasized the importance of the hierarchical pathway in protein folding; folding starts with the creation of contiguous segments having a native-like configuration and proceeds as growth and coalescence of these segments. The ϕ-values calculated for barnase with the WSME model suggested that segments contributing to the folding nucleus are similar to the structural modules defined by the pattern of native atomic contacts. The WSME model was extended to explain folding of multi-domain proteins having a complex topology, which opened the way to comprehensively understanding the folding process of multi-domain proteins. The WSME model was also extended to describe allosteric transitions, indicating that the allosteric structural movement does not occur as a deterministic sequential change between two conformations but as a stochastic diffusive motion over the dynamically changing energy landscape. Statistical mechanical viewpoint on folding, as highlighted by the WSME model, has been renovated in the context of modern methods and ideas, and will continue to provide insights on equilibrium and dynamical features of proteins.

scholarly journals Towards comprehensive allosteric control over protein activity

2018 ◽  
Author(s):  
Enrico Guarnera ◽  
Igor N. Berezovsky
Keyword(s):  
Ligand Binding ◽  
Molecular Mechanisms ◽  
Allosteric Regulation ◽  
Mode Switching ◽  
Contact Network ◽  
Protein Activity ◽  
Theoretical Understanding ◽  
Functional Sites ◽  
Allosteric Control ◽  
Allosteric Communication

AbstractOn the basis of the perturbation nature of allosteric communication, a computational framework is proposed for estimating the energetics of signaling caused by the ligand binding and mutations. The perturbations are modelled as alterations of the strenght of interactions in the protein contact network in the binding sites and neighborhoods of mutated residues. The combination of protein harmonic modelling with effect of perturbations and the estimate of local partition functions allow one to evaluate the energetics of allosteric communication at single residue level. The potential allosteric effect of a protein residue position, modulation range, is given by the difference between responses to stabilizing and destabilizing mutations. We show a versatility of the approach on three case studies of proteins with different mechanisms of allosteric regulation, testing it on their known regulatory and functional sites. Allosteric Signaling Maps (ASMs) obtained on the basis of residue-by-residue scanning are proposed as a comprehensive tool to explore a relationship between mutations allosterically modulating protein activity and those that mainly affect protein stability. Analysis of ASMs shows distance dependence of the mode switching in allosteric signaling, emphasizing the role of domains/subunits in protein allosteric communication as elements of a percolative system. Finally, ASMs can be used to complement and tune already existing signaling and to design new elements of allosteric regulation.SignificanceUniversality of allosteric signaling in proteins, molecular machines, and receptors and great advantages of prospected allosteric drugs in highly specific, non-competitive, and modulatory nature of their actions call for deeper theoretical understanding of allosteric communication. In the energy landscape paradigm underliying the molecular mechanisms of protein function, allosteric signalling is the result of any perturbation, such as ligand binding, mutations, intermolecular interactions etc. We present a computational model, allowing to tackle the problem of modulating the energetics of protein allosteric communication. Using this method, Allosteric Signaling Maps (ASMs) are proposed as an approach to exhaustively describe allosteric signaling in the protein, making it possible to take protein activity under allosteric control.

scholarly journals Statistical Mechanical Model of Gas Adsorption in a Metal-Organic Framework Harboring a Rotaxane Molecular Shuttle

2020 ◽  
Author(s):  
Jonathan Carney ◽  
David Roundy ◽  
Cory M. Simon
Keyword(s):  
Mechanical Model ◽  
Gas Adsorption ◽  
Adsorption Properties ◽  
Temperature Sensitive ◽  
Adsorption Model ◽  
Adsorption Sites ◽  
Statistical Mechanical Model ◽  
Metal Organic ◽  
Statistical Mechanical ◽  
Molecular Shuttle

Metal-organic frameworks (MOFs) are modular and tunable nano-porous materials with applications in gas storage, separations, and sensing. Flexible/dynamic components that respond to adsorbed gas can give MOFs unique or enhanced adsorption properties. Here, we explore the adsorption properties that could be imparted to a MOF by a rotaxane molecular shuttle (RMS) in its pores. In the unit cell of an RMS-MOF, a macrocyclic wheel is mechanically interlocked with a strut of the MOF scaffold. The wheel shuttles between stations on the strut that are also gas adsorption sites. At a level of abstraction similar to the seminal Langmuir adsorption model, we pose and analyze a simple statistical mechanical model of gas adsorption in an RMS-MOF that accounts for (i) wheel/gas competition for sites on the strut and (ii) gas-induced changes in the configurational entropy of the shuttling wheel. We determine how the amount of gas adsorbed, position of the wheel, and differential energy of adsorption depend on temperature, pressure, and the interactions of the gas/wheel with the stations. Our model reveals that, compared to a rigid, Langmuir material, the chemistry of the RMS-MOF can be tuned to render gas adsorption more or less temperature-sensitive and to release more or less heat upon adsorption. The model also uncovers a non-monotonic relationship between the temperature and the position of the wheel if gas out-competes the wheel for its preferable station.

DNA CURVATURE OF (CCTG)n · (CAGG)n AND (ATTCT)n · (AGAAT)n REPEATS SEQUENCES

2005 ◽  
Vol 19 (15n17) ◽  
pp. 2921-2926
Author(s):  
Lu CAI
Keyword(s):  
Experimental Data ◽  
Theoretical Prediction ◽  
Mechanical Model ◽  
Polyacrylamide Gel ◽  
Human Diseases ◽  
Dna Curvature ◽  
Statistical Mechanical Model ◽  
Statistical Mechanical

A statistical mechanical model was used to calculate the curvature of the 5 chemically synthesized DNAs which contain repeats sequences ( CCTG )n · ( CAGG )n and ( ATTCT )n · ( AGAAT )n associated with human diseases. 8% polyacrylamide gel analyses were also performed for these 5 DNAs. The results indicate the curvature of the sequences CCTG/bend and ATTCT/bend are larger than that of the sequences CCTG/straight and ATTCT/straight. The curvature of straight/bend is larger than that of CCTG/straight and ATTCT/straight, and smaller than that of CCTG/bend and ATTCT/bend. There exists good consistent between theoretical prediction and experimental data.

scholarly journals Structural Characterization and Statistical-Mechanical Model of Epidermal Patterns

2016 ◽  
Vol 111 (11) ◽  
pp. 2534-2545 ◽  
Author(s):  
Duyu Chen ◽  
Wen Yih Aw ◽  
Danelle Devenport ◽  
Salvatore Torquato
Keyword(s):  
Structural Characterization ◽  
Mechanical Model ◽  
Statistical Mechanical Model ◽  
Statistical Mechanical

Statistical mechanical model for the formation of octahedral silicon in phosphosilicate glasses

2021 ◽  
Author(s):  
Mikkel L. Bødker ◽  
Johan B. Pedersen ◽  
Francisco Muñoz ◽  
John C. Mauro ◽  
Morten M. Smedskjaer
Keyword(s):  
Mechanical Model ◽  
Statistical Mechanical Model ◽  
Statistical Mechanical
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