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HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing
Tianlong Chen · Chengyue Gong · Daniel Diaz · Xuxi Chen · Jordan Wells · Qiang Liu · Zhangyang Wang · Andrew Ellington · Alex Dimakis · Adam Klivans

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in AI for Science: Progress and Promises »
Event URL: https://openreview.net/forum?id=RtV_iEbWeGE »
The molecular basis of protein thermal stability is only partially understood and has major significance for drug and vaccine discovery. The lack of datasets and standardized benchmarks considerably limits learning-based discovery methods. We present $\texttt{HotProtein}$, a large-scale protein dataset with \textit{growth temperature} annotations of thermostability, containing $182$K amino acid sequences and $3$K folded structures from $230$ different species with a wide temperature range $-20^{\circ}\texttt{C}\sim 120^{\circ}\texttt{C}$. Due to functional domain differences and data scarcity within each species, existing methods fail to generalize well on our dataset. We address this problem through a novel learning framework, consisting of ($1$) Protein structure-aware pre-training (SAP) which leverages 3D information to enhance sequence-based pre-training; ($2$) Factorized sparse tuning (FST) that utilizes low-rank and sparse priors as an implicit regularization, together with feature augmentations. Extensive empirical studies demonstrate that our framework improves thermostability prediction compared to other deep learning models. Finally, we propose a novel editing algorithm to efficiently generate positive amino acid mutations that improve thermostability.
Keywords: dataset · Factorized Sparse Tuning · Protein Editing · Protein Thermostability · Structure-aware Pre-training

Author Information

Tianlong Chen (Unversity of Texas at Austin)
Chengyue Gong (University of Texas at Austin)
Daniel Diaz (University of Texas at Austin)
Xuxi Chen (University of Texas at Austin)
Jordan Wells (University of Texas at Austin)
Qiang Liu (Dartmouth College)
Zhangyang Wang (University of Texas at Austin)
Andrew Ellington (University of Texas at Austin)
Alex Dimakis (University of Texas, Austin)
Adam Klivans (UT Austin)

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