victor369basu/ProteinStructurePrediction
Protein structure prediction is the task of predicting the 3-dimensional structure (shape) of a protein given its amino acid sequence and any available supporting information. In this section, we will Install and inspect sidechainnet, a dataset with tools for predicting and inspecting protein structures, complete two simplified implementations of Attention based Networks for predicting protein angles from amino acid sequences, and visualize our predictions along the way.
This project helps biologists and biochemists predict the three-dimensional shape of a protein just from its amino acid sequence. You input an amino acid sequence, possibly with additional evolutionary information like PSSMs, and it outputs the predicted angles for each amino acid, which can then be visualized as a 3D protein structure. This is designed for researchers studying protein function, drug discovery, or protein engineering.
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Use this if you need a rapid, computational method to estimate protein structures from their amino acid sequences without the need for time-consuming and expensive experimental techniques.
Not ideal if you require the absolute highest atomic-level accuracy, as this is a simplified model not employing complex techniques like Multiple Sequence Alignment (MSA) or ESM embeddings, unlike systems such as AlphaFold.
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Python
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MIT
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Aug 04, 2022
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