In the past few years awareness about disorder protein has been increased among researchers. The prediction of disordered regions in proteins is becoming an important aspect for understanding protein function. In this work, we are working an approach for enhancing the prediction accuracy of protein ...
As no clear definition of disorder exists, we have developed parameters based on several alternative definitions and introduced a new one based on the concept of "hot loops," i.e., coils with high temperature factors....
The prediction of disordered regions in proteins is becoming an important aspect for understanding protein function. In this work, we are working an approach for enhancing the prediction accuracy of protein disorder. This work combines sequence and structural information to train neural networks to ...
PROTEIN analysisCHEMICAL shift (Nuclear magnetic resonance)Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is,...
We present here DisEMBL, a computational tool for prediction of disordered/unstructured regions within a protein sequence. As no clear definition of disorder exists, we have developed parameters based on several alternative definitions and introduced a new one based on the concept of “hot loops,”...
摘要: Prediction of protein disorder is important as a part of the protein folding problem. In this paper, we investigate the possibility of multilayer perceptron (MLP) as the predictor of the protein disorder. The investigation includes single hidden layer MLP, multi-hidden...
of the protein databases and thus computational methods are used to close this gap and to investigate the disorder. MFDp2 is a novel webserver for accurate sequence-based prediction of protein disorder which also outputs well-described sequence-derived information that allows profiling the predicted ...
One popular method, IUPred provides a robust prediction of protein disorder based on an energy estimation approach that captures the fundamental difference between the biophysical properties of ordered and disordered regions. This paper reviews the energy estimation method underlying IUPred and the basic ...
Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high.
Recent breakthroughs in highly accurate protein structure prediction using deep neural networks have made considerable progress in solving the structure prediction component of the ‘protein folding problem’. However, predicting detailed mechanisms of how proteins fold into specific native structures remains ...