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Clusters of acidic and hydrophobic residues can predict acidic transcriptional activation domains from protein sequence.

ABSTRACT: Transcription factors activate gene expression in development, homeostasis, and stress with DNA binding domains and activation domains. Although there exist excellent computational models for predicting DNA binding domains from protein sequence, models for predicting activation domains from protein sequence have lagged, particularly in metazoans. We recently developed a simple and accurate predictor of acidic activation domains on human transcription factors. Here, we show how the accuracy of this human predictor arises from the clustering of aromatic, leucine, and acidic residues, which together are necessary for acidic activation domain function. When we combine our predictor with the predictions of convolutional neural network (CNN) models trained in yeast, the intersection is more accurate than individual models, emphasizing that each approach carries orthogonal information. We synthesize these findings into a new set of activation domain predictions on human transcription factors.

SUBMITTER: Kotha SR

PROVIDER: S-EPMC10550315 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Clusters of acidic and hydrophobic residues can predict acidic transcriptional activation domains from protein sequence.

Kotha Sanjana R SR Staller Max Valentín MV

Genetics 20231001 2

Transcription factors activate gene expression in development, homeostasis, and stress with DNA binding domains and activation domains. Although there exist excellent computational models for predicting DNA binding domains from protein sequence, models for predicting activation domains from protein sequence have lagged, particularly in metazoans. We recently developed a simple and accurate predictor of acidic activation domains on human transcription factors. Here, we show how the accuracy of th ...[more]

PMID: 37462277

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Project description:BackgroundLipocalins are widely distributed in nature and are found in bacteria, plants, arthropoda and vertebra. In hematophagous arthropods, they are implicated in the successful accomplishment of the blood meal, interfering with platelet aggregation, blood coagulation and inflammation and in the transmission of disease parasites such as Trypanosoma cruzi and Borrelia burgdorferi. The pairwise sequence identity is low among this family, often below 30%, despite a well conserved tertiary structure. Under the 30% identity threshold, alignment methods do not correctly assign and align proteins. The only safe way to assign a sequence to that family is by experimental determination. However, these procedures are long and costly and cannot always be applied. A way to circumvent the experimental approach is sequence and structure analyze. To further help in that task, the residues implicated in the stabilisation of the lipocalin fold were determined. This was done by analyzing the conserved interactions for ten lipocalins having a maximum pairwise identity of 28% and various functions.ResultsIt was determined that two hydrophobic clusters of residues are conserved by analysing the ten lipocalin structures and sequences. One cluster is internal to the barrel, involving all strands and the 310 helix. The other is external, involving four strands and the helix lying parallel to the barrel surface. These clusters are also present in RaHBP2, a unusual "outlier" lipocalin from tick Rhipicephalus appendiculatus. This information was used to assess assignment of LIR2 a protein from Ixodes ricinus and to build a 3D model that helps to predict function. FTIR data support the lipocalin fold for this protein.ConclusionBy sequence and structural analyzes, two conserved clusters of hydrophobic residues in interactions have been identified in lipocalins. Since the residues implicated are not conserved for function, they should provide the minimal subset necessary to confer the lipocalin fold. This information has been used to assign LIR2 to lipocalins and to investigate its structure/function relationship. This study could be applied to other protein families with low pairwise similarity, such as the structurally related fatty acid binding proteins or avidins.

Dataset Information

Clusters of acidic and hydrophobic residues can predict acidic transcriptional activation domains from protein sequence.

Publications

Clusters of acidic and hydrophobic residues can predict acidic transcriptional activation domains from protein sequence.

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