Assignment of polar states for protein amino acid residues using an interaction cluster decomposition algorithm and its application to high resolution protein structure modeling

2006 ◽  
Vol 66 (4) ◽  
pp. 824-837 ◽  
Author(s):  
Xin Li ◽  
Matthew P. Jacobson ◽  
Kai Zhu ◽  
Suwen Zhao ◽  
Richard A. Friesner
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
High Resolution ◽  
Decomposition Algorithm ◽  
Structure Modeling ◽  
Amino Acid Residues ◽  
Protein Amino Acid ◽  
Protein Structure Modeling

scholarly journals The VSGB 2.0 model: A next generation energy model for high resolution protein structure modeling

2011 ◽  
Vol 79 (10) ◽  
pp. 2794-2812 ◽  
Author(s):  
Jianing Li ◽  
Robert Abel ◽  
Kai Zhu ◽  
Yixiang Cao ◽  
Suwen Zhao ◽  
...  
Keyword(s):  
Protein Structure ◽  
High Resolution ◽  
Energy Model ◽  
Structure Modeling ◽  
Next Generation ◽  
Protein Structure Modeling

scholarly journals Localnet: A Simple Recurrent Neural Network Model for Protein Secondary Structure Prediction Using Local Amino Acid Sequences Only

2021 ◽  
Author(s):  
Shutong Yang ◽  
Yuhong Wang ◽  
Kennie Cruz-Gutierrez ◽  
Fangling Wu ◽  
Chuan-Fan Ding
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Protein Secondary Structure ◽  
Amino Acid Sequences ◽  
Evolutionary Information ◽  
Structure Modeling ◽  
Protein Structure Modeling

Abstract BackgroundProtein secondary structure prediction (PSSP) is important for protein structure modeling and design. Over the past a few years, deep learning models have shown promising results for PSSP. However, the current good performers for PSSP often require evolutionary information such as multiple sequence alignments and even real protein structures (templates), entire protein sequences, and amino acid property profiles. ResultsIn this study, we used a fixed-size window of adjacent residues and only amino acid sequences, without any evolutionary information, as inputs, and developed a very simple, yet accurate RNN model: LocalNet. The accuracy for three states of secondary structures is as high as 85.15%, indicating that the local amino acid sequence itself contains enough information for PSSP, a well-known classical view. By comparing to other predictors, we also achieve an state-of-art accuracy on dataset of CASP11, CASP12 and CASP13.ConclusionThe well-trained models are expected to have good applications in protein structure modeling and protein design. This model can be downloaded from https://github.com/lake-chao/protein-secondary-structure-prediction.

scholarly journals Comparative protein structure modeling by combining multiple templates and optimizing sequence-to-structure alignments

2007 ◽  
Vol 23 (19) ◽  
pp. 2558-2565 ◽  
Author(s):  
N. Fernandez-Fuentes ◽  
B. K. Rai ◽  
C. J. Madrid-Aliste ◽  
J. Eduardo Fajardo ◽  
A. Fiser
Keyword(s):  
Protein Structure ◽  
Structure Modeling ◽  
Protein Structure Modeling ◽  
Multiple Templates

scholarly journals RosettaBackrub--a web server for flexible backbone protein structure modeling and design

2010 ◽  
Vol 38 (Web Server) ◽  
pp. W569-W575 ◽  
Author(s):  
F. Lauck ◽  
C. A. Smith ◽  
G. F. Friedland ◽  
E. L. Humphris ◽  
T. Kortemme
Keyword(s):  
Protein Structure ◽  
Web Server ◽  
Structure Modeling ◽  
Protein Structure Modeling

scholarly journals AS2TS system for protein structure modeling and analysis

2005 ◽  
Vol 33 (Web Server) ◽  
pp. W111-W115 ◽  
Author(s):  
A. Zemla ◽  
C. E. Zhou ◽  
T. Slezak ◽  
T. Kuczmarski ◽  
D. Rama ◽  
...  
Keyword(s):  
Protein Structure ◽  
Structure Modeling ◽  
Modeling And Analysis ◽  
Protein Structure Modeling
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