Biology subjects

Rube, H. T.

Publications and source records attributed to Rube, H. T..

5 recordsLinked to original sources

bioRxiv2024

Accurate sequence-to-affinity models for SH2 domains from multi-round peptide binding assays coupled with free-energy regression

Short linear peptide motifs play important roles in cell signaling. They can act as modification sites for enzymes and as recognition sites for peptide binding domains. SH2 domains bind specifically to tyrosine-phosphorylated proteins, with the affinity of the interaction depending strongly on the flanking sequence. Quantifying this sequence specificity is critical for deciphering phosphotyrosine-dependent signaling networks. In recent years, protein display technologies and deep sequencing have allowed researchers to profile SH2 domain binding across thousands of candidate ligands. Here, we present a concerted experimental and computational strategy that improves the predictive power of SH2 specificity profiling. Through multi-round affinity selection and deep sequencing with large randomized phosphopeptide libraries, we produce suitable data to train an additive binding free energy model that covers the full theoretical ligand sequence space. Our models can be used to predict signaling network connectivity and the impact of missense variants in phosphoproteins on SH2 binding.

systems biology↗

bioRxiv2022

Transcription factor paralogs orchestrate alternative gene regulatory networks by context-dependent cooperation with multiple cofactors

In eukaryotes, members of large transcription factor families often exhibit similar DNA binding properties in vitro, yet initiate paralog-specific gene regulatory networks in vivo. The serially homologous first (T1) and third (T3) thoracic legs of Drosophila, which result from alternative gene regulatory networks specified by the Hox proteins Scr and Ubx, respectively, offer a unique opportunity to address this paradox in vivo. Genome-wide analyses using epitope-tagged alleles of both Hox loci in the T1 and T3 leg imaginal discs, which are the precursors to the adult appendages and ventral body regions, show that [~]8% of Hox binding is paralog-specific. Binding specificity is mediated by interactions with distinct cofactors in different domains: the known Hox cofactor Exd acts in the proximal domain and is necessary for Scr to bind many of its paralog-specific targets, while in the distal leg domain, we identified the homeodomain protein Distal-less (Dll) as a novel Hox cofactor that enhances Scr binding to a different subset of genomic loci. Reporter genes confirm the in vivo roles of Scr+Dll and suggest that [~]1/3 of paralog-specific Hox binding in enhancers is functional. Together, these findings provide a genome-wide view of how Hox paralogs, and perhaps paralogs of other transcription factor families, orchestrate alternative downstream gene networks and suggest the importance of multiple, context-specific cofactors.

molecular biology↗

bioRxiv2021

Probing molecular specificity with deep sequencing and biophysically interpretable machine learning

Quantifying sequence-specific protein-ligand interactions is critical for understanding and exploiting numerous cellular processes, including gene regulation and signal transduction. Next-generation sequencing (NGS) based assays are increasingly being used to profile these interactions with high-throughput. However, these assays do not provide the biophysical parameters that have long been used to uncover the quantitative rules underlying sequence recognition. We developed a highly flexible machine learning framework, called ProBound, to define sequence recognition in terms of biophysical parameters based on NGS data. ProBound quantifies transcription factor (TF) behavior with models that accurately predict binding affinity over a range exceeding that of previous resources, captures the impact of DNA modifications and conformational flexibility of multi-TF complexes, and infers specificity directly from in vivo data such as ChIP-seq without peak calling. When coupled with a new assay called Kd-seq, it determines the absolute affinity of protein-ligand interactions. It can also profile the kinetics of kinase-substrate interactions. By constructing a biophysically robust foundation for profiling sequence recognition, ProBound opens up new avenues for decoding biological networks and rationally engineering protein-ligand interactions.

genomics↗

bioRxiv2017

SelexGLM differentiates androgen and glucocorticoid receptor DNA-binding preference over an extended binding site

The DNA-binding interfaces of the androgen (AR) and glucocorticoid (GR) receptors are virtually identical, yet these transcription factors share only about a third of their genomic binding sites and regulate similarly distinct sets of target genes. To address this paradox, we determined the intrinsic specificities of the AR and GR DNA binding domains using a refined version of SELEX-seq. We developed an algorithm, SelexGLM, that quantifies binding specificity over a large (31 bp) binding-site by iteratively fitting a feature-based generalized linear model to SELEX probe counts. This analysis revealed that the DNA binding preferences of AR and GR homodimers differ significantly, both within and outside the 15bp core binding site. The relative preference between the two factors can be tuned over a wide range by changing the DNA sequence, with AR more sensitive to sequence changes than GR. The specificity of AR extends to the regions flanking the core 15bp site, where isothermal calorimetry measurements reveal that affinity is augmented by enthalpy-driven readout of poly-A sequences associated with narrowed minor groove width. We conclude that the increased specificity of AR is correlated with more enthalpy-driven binding than GR. The binding models help explain differences in AR and GR genomic binding, and provide a biophysical rationale for how promiscuous binding by GR allows functional substitution for AR in some castration-resistant prostate cancers.

systems biology↗

bioRxiv2017

The effect of sequence mismatches on binding affinity and endonuclease activity are decoupled throughout the Cas9 binding site

The CRISPR-Cas9 system is a powerful genomic tool. Although targeted to complementary genomic sequences by a guide RNA (gRNA), Cas9 tolerates gRNA:DNA mismatches and cleaves off-target sites. How mismatches quantitatively affect Cas9 binding and cutting is not understood. Using SelexGLM to construct a comprehensive model for DNA-binding specificity, we observed that 13-bp of complementarity in the PAM-proximal DNA contributes to affinity. We then adapted Spec-seq and developed SEAM-seq to systematically compare the impact of gRNA:DNA mismatches on affinity and endonuclease activity, respectively. Though most often coupled, these simple and accessible experiments identified sometimes opposing effects for mismatches on DNA-binding and cutting. In the PAM-distal region mismatches decreased activity but not affinity, whereas in the PAM-proximal region some reduced-affinity mismatches enhanced activity. This mismatch-activation was particularly evident where the gRNA:DNA duplex bends. We developed integrative models from these measurements that estimate catalytic efficiency and can be used to predict off-target cleavage.

biochemistry↗