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- uptake type,
- sequence.
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2. Natural CPPs
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Represents a balanced dataset of CPPs and non-CPPs; often used for model benchmarking.
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3. Non-CPPs
Contains negative CPP samples in .txt format.
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Contains non-CPP sequences shown not to demonstrate activity experimentally.
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4. Non-Natural CPPs
Contains CPPs consisting of non-natural amino acids.
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Contains a list of abbreviations for modified amino acids in .txt format (ABBREVIATION: NAME; ...: ...).
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Useful tools :bookmark_tabs:
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Modelling of interaction with membrane
For CPPs from 7 to 24 amino acids you can use [PMIpred neural network model](https://pmipred.fkt.physik.tu-dortmund.de/curvature-sensing-peptide/) trained on Molecular Dynamics (MD) data to predict its interaction with the cellular membrane. Please use modelling on neutral membrane for better differentiation between CPPs and non-CPPs.
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Membrane permeability prediction
For so-called stapled peptides consisting of both natural and modified amino acids you can predict membrane permeability using [STAPEP package](https://github.com/dahuilangda/stapep_package) offering the full pipeline from data preprocessing to ML model development and use on novel samples.