Miguel Andrade

Computational investigation of the sequence context of arginine/glycine-rich motifs in the human proteome - BMC Genomics Arginine-glycine (RG)-rich motifs are among the most prevalent RNA-binding elements within intrinsically disordered regions (IDRs) of proteins and play crucial roles in RNA metabolism, gene regulation, and the formation of membraneless organelles via liquid phase separation (LLPS). Despite their biological relevance and implication in neurological disorders and cancer, the sequence features and context dependencies that define functional RG motifs remain poorly characterized owing to their disordered nature and sequence variability. In this study, we present a computational framework to dissect the sequence and structural context of RG motifs across the human proteome. By contrasting a functionally defined positive dataset—enriched for RNA-binding and phase-separating proteins—with a negative dataset of RG motif proteins lacking these annotations, we identified distinct compositional and contextual signatures. RG motifs in the functionally defined positive dataset show increased enrichment of phenylalanine, tyrosine, aspartic acid, and asparagine, both within and around the motif, as well as nonrandom spatial relationships with structured RNA-binding domains. Notably, phenylalanine and tyrosine exhibit divergent positional and functional profiles, suggesting distinct mechanistic roles. Our analysis highlights the potential of sequence-based approaches to uncover functional determinants in disordered protein regions and further advances our understanding of the properties of RG motifs, offering a transferable framework for the study of other low-complexity motifs.

We published / Computational investigation of the sequence context of arginine/glycine-rich motifs in the human proteome. / open access at bmcgenomics.biomedcentral.com/articles/10.... / read more about it at cbdm.uni-mainz.de/ma_motifs/

We published / Unraveling cooperative and competitive interactions within protein triplets in the human interactome. / open access at www.nature.com/articles/s41... / see also cbdm.uni-mainz.de/ma_ppi/

We published / Xsurvey: Web Tool to Query the Set of Homorepeats of all Reference Proteomes. / open access at ieeexplore.ieee.org/document/109... / see also cbdm.uni-mainz.de/ma_homorepea... / tool available here: cbdm-01.zdv.uni-mainz.de/~munoz/xsurv...

Apparent differences between human and chimp proteomes are reduced when considering human population: Human specific variants are enriched in disordered and compositionally biased regions Humans exhibit significant differences from other primates in anatomy, physiology, behavior, and culture, despite having similar genomes. Understanding the genetic basis of these unique human traits h...

We published / Apparent differences between human and chimp proteomes are reduced when considering human population: Human specific variants are enriched in disordered and compositionally biased regions. / open access at journals.plos.org/plosone/arti... / see also cbdm.uni-mainz.de/ma_intravar/

We published / Evaluating genetic regulators of microRNAs using machine learning models. / open access at www.mdpi.com/1422-0067/26... / read more about it at cbdm.uni-mainz.de/ma_transcrip...

Prediction of protein interactions with function in protein (de-)phosphorylation Protein–protein interactions (PPIs) form a complex network called “interactome” that regulates many functions in the cell. In recent years, there is an increasing accumulation of evidence supporting t...

We published / Prediction of protein interactions with a function in protein (de-)phosphorylation. / open access at journals.plos.org/plosone/arti... / read more about it at cbdm.uni-mainz.de/ma_ppi/

Batch Effects in High Dimensional Biological Data—Detection, Correction and Challenges Special Issue in journal Genes: Batch Effects in High Dimensional Biological Data—Detection, Correction and Challenges

We are editing a special issue of the journal Genes on Batch effects. www.mdpi.com/journal/gene...
Seeking submissions focusing on computational aspects of batch analysis and/or correction in multidimensional biological/biomedical data. Deadline 20 September 2025.