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Ab initio modeling is considered an especially difficult category of protein structure prediction, as it does not use information from structural homology and must rely on information from sequence homology and modeling physical interactions within the protein. Rosetta@home has been used in CASP since 2006, where it was among the top predictors ...
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.
An alpha-helix with hydrogen bonds (yellow dots) The α-helix is the most abundant type of secondary structure in proteins. The α-helix has 3.6 amino acids per turn with an H-bond formed between every fourth residue; the average length is 10 amino acids (3 turns) or 10 Å but varies from 5 to 40 (1.5 to 11 turns).
Namely, ESMFold is a newly developed large language model (LLM) for the prediction of protein structures based solely on their amino acid sequences. It can predict a 3D structure of a protein with atomic-level resolution with an input of a single amino acid sequence. [19]
This software can be used together with other molecular modeling protocols, such as docking to model protein oligomers. [6] In addition, CS-ROSETTA can be combined with chemical shift resonance assignment algorithms to create a fully automated NMR structure determination pipeline.
One highly successful method for ab initio modeling is the Rosetta program, which divides the protein into short segments and arranges short polypeptide chain into a low-energy local conformation. Rosetta is available for commercial use and for non-commercial use through its public program, Robetta.
Name Description Knots [Note 1]Links References trRosettaRNA: trRosettaRNA is an algorithm for automated prediction of RNA 3D structure. It builds the RNA structure by Rosetta energy minimization, with deep learning restraints from a transformer network (RNAformer). trRosettaRNA has been validated in blind tests, including CASP15 and RNA-Puzzles, which suggests that the automated predictions ...
This group of methods [11] [9] [12] [13] [14] makes use of known protein complex structures to predict and structurally model interactions between query protein sequences. The prediction process generally starts by employing a sequence based method (e.g. Interolog ) to search for protein complex structures that are homologous to the query ...