CompBio»SAAFEC-SEQ

About SAAFEC-SEQ

SAAFEC-SEQ predicts the stability change caused by point mutations in proteins using a sequence-based machine-learning workflow. It supports both single-mutation and multiple-mutation submission modes, and the server-side workflow will validate the submitted sequence and mutation information before running the predictor.

The standalone code and example dataset are available for local use: Dataset.zip and Code from our GitHub Repository. Install and configure the standalone code as described in README.md.

Please cite SAAFEC-SEQ when using the web server in published work:

Li, G.; Panday, S.K.; Alexov, E. SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability. Int. J. Mol. Sci. 2021, 22, 606. https://doi.org/10.3390/ijms22020606

NOTE » SAAFEC-SEQ currently uses the UniRef100 database instead of the full nr database to make searches faster and less computationally intensive. The results should generally be similar, but they may differ slightly from results generated using nr.

Submit SAAFEC-SEQ Job

Note: For single-mutation jobs, paste or upload one protein sequence and specify one mutation. For multiple-mutation jobs, paste or upload one protein sequence and provide a mutation-list file.

Submission mode

Single mutation

Multiple mutations

Protein Sequence

Paste protein sequence

Upload FASTA sequence file

Choose a FASTA file

The pasted sequence takes precedence if both text and file are provided.

Single Mutation

Position

Wildtype amino acid

Mutated amino acid

Multiple Mutations

Upload mutation list file

Choose mutation list file

Example format: A 42 V

SAAFEC-SEQ: an online application for calculating folding free energy changes in proteins caused by missense mutations

Professor Emil Alexov Group

Please correct the following errors before submitting: