QAUST: Protein Function Prediction Using Structure Similarity, Protein Interaction, and Functional Motifs

Abstract

The number of available protein sequences in public databases is increasing exponentially. However, a significant percentage of these sequences lack functional annotation, which is essential for the understanding of how biological systems operate. Here, we propose a novel method, Quantitative Annotation of Unknown STructure (QAUST), to infer protein functions, specifically Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. QAUST uses three sources of information: structure information encoded by global and local structure similarity search, biological network information inferred by protein–protein interaction data, and sequence information extracted from functionally discriminative sequence motifs. These three pieces of information are combined by consensus averaging to make the final prediction. Our approach has been tested on 500 protein targets from the Critical Assessment of Functional Annotation (CAFA) benchmark set. The results show that our method provides accurate functional annotation and outperforms other prediction methods based on sequence similarity search or threading. We further demonstrate that a previously unknown function of human tripartite motif-containing 22 (TRIM22) protein predicted by QAUST can be experimentally validated.

Genome-Wide Identification and Analysis of NAC Transcription Factor Family in Two Diploid Wild Relatives of Cultivated Sweet Potato Uncovers Potential NAC Genes Related to Drought Tolerance

“…The results showed that ItfNAC62 had a similar spatial conformation with a paralogous A. thaliana gene ANAC019 . It is widely accepted that proteins with a similar spatial structure usually have analogical functions ( Najmanovich et al, 2005 ; Smaili et al, 2021 ), so we speculate that ItfNAC62 has similar functions to ANAC019 , which is involved in drought and biotic defense responses, which are dependent on the ABA or MeJA signaling pathway ( Bu et al, 2008 ; Jiang et al, 2014 ; Li et al, 2014 ; Sukiran et al, 2019 ). ABA and MeJA response CAEs were found in the ItfNAC62 promoter, suggesting that this gene participates in drought resistance, via the ABA or MeJA signaling pathway.…”

An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus

“… [34] ). Nonetheless, given the challenges associated with the annotation of “unknown” or “orphan” molecules, ML and structure-based tools (established recently; [89] , [90] , [91] , [92] ) appeared to provide a useful alternative to sequence-based methods, although often their performance had not been thoroughly evaluated individually or in combination [93] . To address this issue, we evaluated individual tools and optimised the cut-off values for select algorithms (cf.…”

Sequence vs. Structure: Delving Deep Into Data-Driven Protein Function Prediction

“…However, a simple similarity measure with a pre-set threshold is insufficient to assign high-confident protein function. DL-based PFP methods include function prediction from AA-sequence (Rao et al, 2019;Alley et al, 2019;Elnaggar et al, 2020;Dallago et al, 2021;Kulmanov & Hoehndorf, 2020;Meier et al, 2021;Biswas et al, 2021;Gelman et al, 2021;Yang et al, 2022a), 3-dimensional structure (Gligorijević et al, 2021;Smaili et al, 2021;Guo et al, 2022), evolutionary relationships and genomic context (Rao et al, 2021;Engelhardt et al, 2005), and their combinations Gligorijević et al, 2021). Here, we mainly restrict our scope to the sequence and structure.…”