Successor Sequence Predictor (SSP)
| Authors | |
|---|---|
| Year of publication | 2024 |
| Type | Software |
| MU Faculty or unit | |
| web | https://github.com/loschmidt/successor-sequence-predictor |
| Description | Successor Sequence Predictor is an in silico method that mimics laboratory-based protein evolution by reconstructing a protein’s evolutionary history and suggesting future amino acid substitutions based on trends observed in that history through carefully selected physicochemical descriptors. This approach enhances specialised proteins by predicting mutations that improve desired properties, such as thermostability, activity, and solubility. Successor Sequence Predictor can thus be used as a general protein engineering tool to develop practically useful proteins. The code of the Successor Sequence Predictor is available on GitHub https://github.com/loschmidt/successor-sequence-predictor. |
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