Protein Loop Structure Prediction Methods

2012 ◽  
Keyword(s):  
Structure Prediction ◽  
Prediction Methods ◽  
Loop Structure

Protein Loop Structure Prediction Methods

2008 ◽  
pp. 3100-3105
Author(s):  
Martin Mönnigmann ◽  
Christodoulos A. Floudas
Keyword(s):  
Structure Prediction ◽  
Prediction Methods ◽  
Loop Structure

In Silico Study of Secondary Structure of Hemoglobin Protein

2021 ◽  
pp. 6245-6249
Author(s):  
Roma Chandra
Keyword(s):  
Secondary Structure ◽  
Protein Sequence ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Secondary Structure Prediction ◽  
Three Dimensional ◽  
Protein Secondary Structure ◽  
Alpha Helix ◽  
Prediction Methods ◽  
Protein Secondary Structures

Protein structure prediction is one of the important goals in the area of bioinformatics and biotechnology. Prediction methods include structure prediction of both secondary and tertiary structures of protein. Protein secondary structure prediction infers knowledge related to presence of helixes, sheets and coils in a polypeptide chain whereas protein tertiary structure prediction infers knowledge related to three dimensional structures of proteins. Protein secondary structures represent the possible motifs or regular expressions represented as patterns that are predicted from primary protein sequence in the form of alpha helix, betastr and and coils. The secondary structure prediction is useful as it infers information related to the structure and function of unknown protein sequence. There are various secondary structure prediction methods used to predict about helixes, sheets and coils. Based on these methods there are various prediction tools under study. This study includes prediction of hemoglobin using various tools. The results produced inferred knowledge with reference to percentage of amino acids participating to produce helices, sheets and coils. PHD and DSC produced the best of the results out of all the tools used.

Protein Loop Structure Prediction Using Conformational Space Annealing

2017 ◽  
Vol 57 (5) ◽  
pp. 1068-1078 ◽  
Author(s):  
Seungryong Heo ◽  
Juyong Lee ◽  
Keehyoung Joo ◽  
Hang-Cheol Shin ◽  
Jooyoung Lee
Keyword(s):  
Structure Prediction ◽  
Conformational Space ◽  
Loop Structure

scholarly journals Advances inRosettastructure prediction for difficult molecular-replacement problems

2013 ◽  
Vol 69 (11) ◽  
pp. 2202-2208 ◽  
Author(s):  
Frank DiMaio
Keyword(s):  
Structure Prediction ◽  
Prediction Methods ◽  
Molecular Replacement ◽  
Improved Method ◽  
Model Quality ◽  
Future Directions ◽  
Protein Structure Modeling ◽  
Improve Model ◽  
Difficult Cases

Recent work has shown the effectiveness of structure-prediction methods in solving difficult molecular-replacement problems. TheRosettaprotein structure modeling suite can aid in the solution of difficult molecular-replacement problems using templates from 15 to 25% sequence identity;Rosettarefinement guided by noisy density has consistently led to solved structures where other methods fail. In this paper, an overview of the use ofRosettafor these difficult molecular-replacement problems is provided and new modeling developments that further improve model quality are described. Several variations to the method are introduced that significantly reduce the time needed to generate a model and the sampling required to improve the starting template. The improvements are benchmarked on a set of nine difficult cases and it is shown that this improved method obtains consistently better models in less running time. Finally, strategies for best usingRosettato solve difficult molecular-replacement problems are presented and future directions for the role of structure-prediction methods in crystallography are discussed.

Smotifs as structural local descriptors of supersecondary elements: classification, completeness and applications

2014 ◽  
Vol 10 (4) ◽  
Author(s):  
Jaume Bonet ◽  
Andras Fiser ◽  
Baldo Oliva ◽  
Narcis Fernandez-Fuentes
Keyword(s):  
Protein Design ◽  
Structure Prediction ◽  
Protein Structures ◽  
Regular Structure ◽  
Loop Structure ◽  
Apparent Lack ◽  
Knowledge Based ◽  
Limits Of Knowledge ◽  
Folding Dynamics ◽  
And Function

AbstractProtein structures are made up of periodic and aperiodic structural elements (i.e., α-helices, β-strands and loops). Despite the apparent lack of regular structure, loops have specific conformations and play a central role in the folding, dynamics, and function of proteins. In this article, we reviewed our previous works in the study of protein loops as local supersecondary structural motifs or Smotifs. We reexamined our works about the structural classification of loops (ArchDB) and its application to loop structure prediction (ArchPRED), including the assessment of the limits of knowledge-based loop structure prediction methods. We finalized this article by focusing on the modular nature of proteins and how the concept of Smotifs provides a convenient and practical approach to decompose proteins into strings of concatenated Smotifs and how can this be used in computational protein design and protein structure prediction.

Three-dimensional protein structure prediction: Methods and computational strategies

2014 ◽  
Vol 53 ◽  
pp. 251-276 ◽  
Author(s):  
Márcio Dorn ◽  
Mariel Barbachan e Silva ◽  
Luciana S. Buriol ◽  
Luis C. Lamb
Keyword(s):  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Three Dimensional ◽  
Prediction Methods

scholarly journals Report on the sixth blind test of organic crystal structure prediction methods

2016 ◽  
Vol 72 (4) ◽  
pp. 439-459 ◽  
Author(s):  
Anthony M. Reilly ◽  
Richard I. Cooper ◽  
Claire S. Adjiman ◽  
Saswata Bhattacharya ◽  
A. Daniel Boese ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Structure Prediction ◽  
Density Functional ◽  
Organic Crystal ◽  
Drug Candidate ◽  
Prediction Methods ◽  
Chloride Salt ◽  
Crystal Structure Prediction ◽  
Blind Test ◽  
Flexible Molecules

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disorderedZ′ = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.

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