Boltzmann's principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures

1993 ◽  
Vol 7 (4) ◽  
pp. 473-501 ◽  
Author(s):  
Manfred J. Sippl
Keyword(s):  
Protein Folding ◽  
Protein Structures ◽  
Knowledge Based ◽  
Mean Fields

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.

scholarly journals Efficient conformational space exploration in ab initio protein folding simulation

2015 ◽  
Vol 2 (8) ◽  
pp. 150238 ◽  
Author(s):  
Ahammed Ullah ◽  
Nasif Ahmed ◽  
Subrata Dey Pappu ◽  
Swakkhar Shatabda ◽  
A. Z. M. Dayem Ullah ◽  
...  
Keyword(s):  
Protein Folding ◽  
Ab Initio ◽  
Energy Function ◽  
Hydrophobic Interactions ◽  
Protein Structures ◽  
Search Algorithms ◽  
Conformational Space ◽  
Energy Functions ◽  
Knowledge Based ◽  
Folding Simulation

Ab initio protein folding simulation largely depends on knowledge-based energy functions that are derived from known protein structures using statistical methods. These knowledge-based energy functions provide us with a good approximation of real protein energetics. However, these energy functions are not very informative for search algorithms and fail to distinguish the types of amino acid interactions that contribute largely to the energy function from those that do not. As a result, search algorithms frequently get trapped into the local minima. On the other hand, the hydrophobic–polar (HP) model considers hydrophobic interactions only. The simplified nature of HP energy function makes it limited only to a low-resolution model. In this paper, we present a strategy to derive a non-uniform scaled version of the real 20×20 pairwise energy function. The non-uniform scaling helps tackle the difficulty faced by a real energy function, whereas the integration of 20×20 pairwise information overcomes the limitations faced by the HP energy function. Here, we have applied a derived energy function with a genetic algorithm on discrete lattices. On a standard set of benchmark protein sequences, our approach significantly outperforms the state-of-the-art methods for similar models. Our approach has been able to explore regions of the conformational space which all the previous methods have failed to explore. Effectiveness of the derived energy function is presented by showing qualitative differences and similarities of the sampled structures to the native structures. Number of objective function evaluation in a single run of the algorithm is used as a comparison metric to demonstrate efficiency.

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.

Midlatitude Cyclone Compositing to Constrain Climate Model Behavior Using Satellite Observations

2008 ◽  
Vol 21 (22) ◽  
pp. 5887-5903 ◽  
Author(s):  
P. R. Field ◽  
A. Gettelman ◽  
R. B. Neale ◽  
R. Wood ◽  
P. J. Rasch ◽  
...  
Keyword(s):  
Climate Model ◽  
Model Output ◽  
Liquid Water Path ◽  
Temperature Dependent ◽  
Community Atmosphere Model ◽  
Mean Wind Speed ◽  
Mean Fields ◽  
Microphysical Processes ◽  
Midlatitude Cyclones

Abstract Identical composite analysis of midlatitude cyclones over oceanic regions has been carried out on both output from the NCAR Community Atmosphere Model, version 3 (CAM3) and multisensor satellite data. By focusing on mean fields associated with a single phenomenon, the ability of the CAM3 to reproduce realistic midlatitude cyclones is critically appraised. A number of perturbations to the control model were tested against observations, including a candidate new microphysics package for the CAM. The new microphysics removes the temperature-dependent phase determination of the old scheme and introduces representations of microphysical processes to convert from one phase to another and from cloud to precipitation species. By subsampling composite cyclones based on systemwide mean strength (mean wind speed) and systemwide mean moisture the authors believe they are able to make meaningful like-with-like comparisons between observations and model output. All variations of the CAM tested overestimate the optical thickness of high-topped clouds in regions of precipitation. Over a system as a whole, the model can both over- and underestimate total high-topped cloud amounts. However, systemwide mean rainfall rates and composite structure appear to be in broad agreement with satellite estimates. When cyclone strength is taken into account, changes in moisture and rainfall rates from both satellite-derived observations and model output as a function of changes in sea surface temperature are in accordance with the Clausius–Clapeyron equation. The authors find that the proposed new microphysics package shows improvement to composite liquid water path fields and cloud amounts.

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