Search results
Results from the WOW.Com Content Network
The protein structure prediction remains an extremely difficult and unresolved undertaking. The two main problems are the calculation of protein free energy and finding the global minimum of this energy. A protein structure prediction method must explore the space of possible protein structures which is astronomically large.
AlphaFold is an artificial intelligence (AI) program developed by DeepMind, a subsidiary of Alphabet, which performs predictions of protein structure. [1] It is designed using deep learning techniques. [2] AlphaFold 1 (2018) placed first in the overall rankings of the 13th Critical Assessment of Structure Prediction (CASP) in
This list of protein subcellular localisation prediction tools includes software, databases, and web services that are used for protein subcellular localization prediction. Some tools are included that are commonly used to infer location through predicted structural properties, such as signal peptide or transmembrane helices , and these tools ...
Constituent amino-acids can be analyzed to predict secondary, tertiary and quaternary protein structure. This list of protein structure prediction software summarizes notable used software tools in protein structure prediction, including homology modeling, protein threading, ab initio methods, secondary structure prediction, and transmembrane helix and signal peptide prediction.
Protein threading treats the template in an alignment as a structure, and both sequence and structure information extracted from the alignment are used for prediction. When there is no significant homology found, protein threading can make a prediction based on the structure information.
The HH-suite comes with a number of pre-built profile HMMs that can be searched using HHblits and HHsearch, among them a clustered version of the UniProt database, of the Protein Data Bank of proteins with known structures, of Pfam protein family alignments, of SCOP structural protein domains, and many more.
De novo protein structure prediction methods attempt to predict tertiary structures from sequences based on general principles that govern protein folding energetics and/or statistical tendencies of conformational features that native structures acquire, without the use of explicit templates. Research into de novo structure prediction has been ...
Levinthal's paradox is a thought experiment in the field of computational protein structure prediction; protein folding seeks a stable energy configuration. An algorithmic search through all possible conformations to identify the minimum energy configuration (the native state) would take an immense duration; however in reality protein folding happens very quickly, even in the case of the most ...