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bioRxiv · 10.1101/2021.11.04.467289

ProDCoNN-server: a web server for protein sequence prediction and design from a three-dimensional structure

Zhang, Y.·Mandal, A.·Cui, K.·Liu, X.·Zhang, J.
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Abstract

We present ProDCoNN-server, a web server for protein sequence design and prediction from a given protein structure. The server is based on a previously developed deep learning model for protein design, ProDCoNN, which achieved state-of-the-art performance when tested on large numbers of test proteins and benchmark datasets. The prediction is very fast compared with other protein sequence prediction servers - it takes only a few minutes for a query protein on average. Two models could be selected for different purposes: BBO for full sequence prediction, extendable for multiple sequence generation, and BBS for single position prediction with the type of other residues known. ProDCoNN-server outputs the predicted sequence and the probability matrix for each amino acid at each predicted residue. The probability matrix can also be visualized as a sequence logos figure (BBO) or probability distribution plot (BBS). The server is available at: https://prodconn.stat.fsu.edu/.

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Zhang, Y., Mandal, A., Cui, K., Liu, X., Zhang, J.. 2021-11-05. ProDCoNN-server: a web server for protein sequence prediction and design from a three-dimensional structure. https://doi.org/10.1101/2021.11.04.467289

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