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A unified interface for: Tertiary structure prediction/3D modelling, 3D model quality assessment, Intrinsic disorder prediction, Domain prediction, Prediction of protein-ligand binding residues Automated webserver and some downloadable programs RaptorX: remote homology detection, protein 3D modeling, binding site prediction
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 ...
RaptorX is a software and web server for protein structure and function prediction that is free for non-commercial use. RaptorX is among the most popular methods for protein structure prediction. RaptorX is among the most popular methods for protein structure prediction.
Swiss-model (stylized as SWISS-MODEL) is a structural bioinformatics web-server dedicated to homology modeling of 3D protein structures. [1] [2] As of 2024, homology modeling is the most accurate method to generate reliable three-dimensional protein structure models and is routinely used in many practical applications.
DeepMind is known to have trained the program on over 170,000 proteins from the Protein Data Bank, a public repository of protein sequences and structures.The program uses a form of attention network, a deep learning technique that focuses on having the AI identify parts of a larger problem, then piece it together to obtain the overall solution. [2]
I-TASSER is a template-based method for protein structure and function prediction. [1] The pipeline consists of six consecutive steps: 1, Secondary structure prediction by PSSpred; 2, Template detection by LOMETS [6] 3, Fragment structure assembly using replica-exchange Monte Carlo simulation [7]
Secondary structure-related Method that uses the distribution of hydrophobic and electrostatic patches on the surface of the protein, factoring in the intensity and relative orientation of the respective surface patches into an aggregation propensity function that has been trained on a benchmark set of 31 adnectin proteins.
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.