Motif Discovery in Protein Sequences

Mohamed, Sarajul Fikri; Elloumi, Mourad; Thompson, Julie

doi:10.5772/65441

Cited by 10 publications

(5 citation statements)

References 27 publications

(30 reference statements)

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“…We therefore set out to design a systematic computational method for discovering features in IDRs, that is unbiased by prior knowledge or interest. The problem of feature discovery runs closely parallel to the concept of motif discovery [28], [29]: given a set of functionally related sequences, motif discovery methods attempt to find overrepresented subsequences with the idea that these motifs may represent conserved binding, interaction, or regulatory sites informative of the function of proteins. Motif discovery approaches range from fully unsupervised to regression approaches where function is predicted from sequence.…”

Section: Introductionmentioning

confidence: 99%

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

Pritišanac

et al. 2021

Preprint

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A major challenge to the characterization of intrinsically disordered regions (IDRs), which are widespread in the proteome, but relatively poorly understood, is the identification of molecular features, such as short motifs, amino acid repeats and physicochemical properties that mediate the functions of these regions. Here, we introduce a proteome-scale feature discovery method for IDRs. Our method, which we call "reverse homology", exploits the principle that important functional features are conserved over evolution as a contrastive learning signal for deep learning: given a set of homologous IDRs, the neural network has to correctly choose a randomly held-out homologue from another set of IDRs sampled randomly from the proteome. We pair reverse homology with a simple architecture and interpretation techniques, and show that the network learns conserved features of IDRs that can be interpreted as motifs, repeats, and other features. We also show that our model can be used to produce specific predictions of what residues and regions are most important to the function, providing a computational strategy for designing mutagenesis experiments in uncharacterized IDRs. Our results suggest that feature discovery using neural networks is a promising avenue to gain systematic insight into poorly understood protein sequences.

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Section: Introductionmentioning

confidence: 99%

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

Pritišanac

et al. 2021

Preprint

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“…Finally, we identify the motifs using SeqPos motif analysis tool [20]. Biological sequence motifs are short conserved sequence pattern associated with distinct functions that usually represents important structural or functional features [21].…”

Section: Methodsmentioning

confidence: 99%

Epigenetic Regulations, Motif and Pathway Identification of Gabaergic Neurotransmitter’s Chip Sequence

Murthy,

Bagchi

2023

Advances in Health Sciences Research

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Background: The next generation techniques has revolutionalized the biology era. In this work we are using Chromatin immunoprecipitation (ChiP) technique on the ChIP-seq of Gamma-Amino Butyric Acid (GABA). GABA is a brain-made chemical. It also found in some foods. The effect of GABA in brain is anti-seizure and anti-anxiety. GABA blocks the brain signals, the neurotransmissions and hence there is interest in using GABA as a dietary supplement. But it is taken by mouth, it is able to cross the blood-brain barrier. Hence the effects of GABA supplements on the brain is unknown.Methodology: GABA is implicated in several neurological disorders like alzheimers, rett symdrome, schizophrenia, etc. In this work, the chip sequence of GABA is retrieved from SRA database, removed the PCR duplicates and finally identified the genome enriched region using the MAC2 call peak tool.Results: Peak table was annotated to identify the genes and the corresponding pathways was identified from the KEGG pathway. This annotated peak table was used to identify the motifs present in the chip-seq of GABA.

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“…Motifs are short patterns of sequences that usually impart significant structural or functional characteristic to proteins and are usually conserved in protein families or subfamilies ( Mohamed et al, 2016 ). MotifFinder 23 was used to detect the motifs present in 3p.AtFBP113 sequence.…”

Section: Methodsmentioning

confidence: 99%

Classification and Computational Analysis of Arabidopsis thaliana Sperm Cell-Specific F-Box Protein Gene 3p.AtFBP113

et al. 2020

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In plants, F-box proteins (FBPs) constitute one of the largest superfamilies of regulatory proteins. Most F-box proteins are shown to be an integral part of SCF complexes, which carry out the degradation of proteins and regulate diverse important biological processes. Anthers and pollen development have a huge importance in crop breeding. Despite the vast diversity of FBPs in Arabidopsis male reproductive organs, their role in anther and pollen development is not much explored. Moreover, a standard nomenclature for naming FBPs is also lacking. Here, we propose a standard nomenclature for naming the FBPs of Arabidopsis thaliana uniformly and carry out a systematic analysis of sperm cell-specific FBP gene, i.e., 3p.AtFBP113 due to its reported high and preferential expression, for detailed functional annotation. The results revealed that 3p.AtFBP113 is located on the small arm of chromosome and encodes 397 amino acid long soluble, stable, and hydrophilic protein with the possibility of localization in various cellular compartments. The presence of the C-terminal F-box associated domain (FBA) with immunoglobulin-like fold anticipated its role in protein binding. Gene ontology based functional annotation and tissue-specific gene co-expression analysis further strengthened its role in protein binding and ubiquitination. Moreover, various potential post/co-translational modifications were anticipated and the predicted tertiary structure also showed the presence of characteristic domains and fold. Thus, the outcomes of the study will be useful in developing a better understating of the function of 3p.AtFBP113 during the process of pollen development, which will be helpful for targeting the gene for manipulation of male fertility that has immense importance in hybrid breeding.

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Motif Discovery in Protein Sequences

Cited by 10 publications

References 27 publications

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

Epigenetic Regulations, Motif and Pathway Identification of Gabaergic Neurotransmitter’s Chip Sequence

Classification and Computational Analysis of Arabidopsis thaliana Sperm Cell-Specific F-Box Protein Gene 3p.AtFBP113

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