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Computational Biophysics & Bioinformatics - Dr. Emil Alexov Group
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SAAMBE-SEQ Web Server

SAAMBE-SEQ is a sequence-based machine learning algorithm to predict the binding energy changes upon single mutation in protein-protein complexes. Unlike other existing methods, SAAMBE-SEQ does not require a 3D complex structure as input. This method can be applied to protein complexes without known structure. The accuracy of SAAMBE-SEQ is comparable to existing structure-based methods. This method can be used to provide understanding the effect of mutation in protein complexes using sequence alone.

Reference: Gen Li, Swagata Pahari, Adithya Krishna Murthy, Siqi Liang, Robert Fragoza, Haiyuan Yu, Emil Alexov, SAAMBE-SEQ: A Sequence-based Method for Predicting Mutation Effect on Protein-protein Binding Affinity, Bioinformatics, btaa761. available here





Sequence Selection

Predicting the effect of one mutation only for this protein complex

OR,
Upload the sequence in FASTA format
Click here to Download a sample FASTA format

Upload the Muatated Chain Sequence

Upload the Interaction Chain Sequence


Mutation Details
Position:
Original Amino Acid:
Mutated Amino Acid:

Sequence Selection

Predicting the effect of multiple single mutations within the same protein complex - requires text file with mutations list

OR,
Upload the sequence in FASTA format
Click here to Download a sample FASTA format

Upload the Mutated Chain Sequence

Upload the Interaction Chain Sequence


Mutation Details

Upload a plain text file with one mutation per line,click here to view an example for reference


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