scholarly journals MUFOLD: A new solution for protein 3D structure prediction

2009 ◽  
Vol 78 (5) ◽  
pp. 1137-1152 ◽  
Author(s):  
Jingfen Zhang ◽  
Qingguo Wang ◽  
Bogdan Barz ◽  
Zhiquan He ◽  
Ioan Kosztin ◽  
...  
Keyword(s):  
Structure Prediction ◽  
3D Structure ◽  
Protein 3D Structure ◽  
3D Structure Prediction

PSSRDBModel- Protein 3D structure prediction server based on the secondary structure informations

2019 ◽  
Vol 16 ◽  
pp. 1596-1602
Author(s):  
E. Loganathan ◽  
K. Dinakaran ◽  
P. Valarmathi ◽  
Gnanendra Shanmugam ◽  
Nagaraja Suryadevara
Keyword(s):  
Secondary Structure ◽  
Structure Prediction ◽  
3D Structure ◽  
Protein 3D Structure ◽  
Prediction Server ◽  
3D Structure Prediction

In silico 3D structure prediction and hydrogen peroxide binding study of wheat catalase

2013 ◽  
Vol 5 (1) ◽  
pp. 77-83 ◽  
Author(s):  
Gopal Krishna Sahu ◽  
Bibhuti Bhusan Sahoo ◽  
Sneha Bhandari ◽  
Shruti Pandey
Keyword(s):  
Hydrogen Peroxide ◽  
In Silico ◽  
Structure Prediction ◽  
3D Structure ◽  
Binding Study ◽  
3D Structure Prediction

scholarly journals Bioinformatics Tools and Benchmarks for Computational Docking and 3D Structure Prediction of RNA-Protein Complexes

Genes ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 432 ◽  
Author(s):  
Chandran Nithin ◽  
Pritha Ghosh ◽  
Janusz Bujnicki
Keyword(s):  
Rna Splicing ◽  
Structure Prediction ◽  
Protein Complexes ◽  
3D Structure ◽  
Structural Models ◽  
Computational Prediction ◽  
Computational Docking ◽  
3D Structure Prediction ◽  
Rna Protein Complexes

RNA-protein (RNP) interactions play essential roles in many biological processes, such as regulation of co-transcriptional and post-transcriptional gene expression, RNA splicing, transport, storage and stabilization, as well as protein synthesis. An increasing number of RNP structures would aid in a better understanding of these processes. However, due to the technical difficulties associated with experimental determination of macromolecular structures by high-resolution methods, studies on RNP recognition and complex formation present significant challenges. As an alternative, computational prediction of RNP interactions can be carried out. Structural models obtained by theoretical predictive methods are, in general, less reliable compared to models based on experimental measurements but they can be sufficiently accurate to be used as a basis for to formulating functional hypotheses. In this article, we present an overview of computational methods for 3D structure prediction of RNP complexes. We discuss currently available methods for macromolecular docking and for scoring 3D structural models of RNP complexes in particular. Additionally, we also review benchmarks that have been developed to assess the accuracy of these methods.

Automated RNA 3D Structure Prediction with RNAComposer

2016 ◽  
pp. 199-215 ◽  
Author(s):  
Marcin Biesiada ◽  
Katarzyna J. Purzycka ◽  
Marta Szachniuk ◽  
Jacek Blazewicz ◽  
Ryszard W. Adamiak
Keyword(s):  
Structure Prediction ◽  
3D Structure ◽  
3D Structure Prediction
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