Biology subjects

Ginell, G. M.

Publications and source records attributed to Ginell, G. M..

6 recordsLinked to original sources

bioRxiv2024

Direct prediction of intermolecular interactions driven by disordered regions

Intrinsically disordered regions (IDRs) are critical for a wide variety of cellular functions, many of which involve interactions with partner proteins. Molecular recognition is typically considered through the lens of sequence-specific binding events. However, a growing body of work has shown that IDRs often interact with partners in a manner that does not depend on the precise order of the amino acid order, instead driven by complementary chemical interactions leading to disordered bound-state complexes. Despite this emerging paradigm, we lack tools to describe, quantify, predict, and interpret these types of structurally heterogeneous interactions from the underlying amino acid sequences. Here, we repurpose the chemical physics developed originally for molecular simulations to develop an approach for predicting intermolecular interactions between IDRs and partner proteins. Our approach enables the direct prediction of phase diagrams, the identification of chemically-specific interaction hotspots on IDRs, and a route to develop and test mechanistic hypotheses regarding IDR function in the context of molecular recognition. We use our approach to examine a range of systems and questions to highlight its versatility and applicability.

biophysics↗

bioRxiv2023

Labile assembly of a tardigrade protein induces biostasis

Tardigrades are microscopic animals that survive desiccation by inducing biostasis. To survive drying tardigrades rely on intrinsically disordered CAHS proteins that form gels. However, the sequence features and mechanisms underlying gel formation and the necessity of gelation for protection have not been demonstrated. Here we report a mechanism of gelation for CAHS D similar to that of intermediate filaments. We show that gelation restricts molecular motion, immobilizing and protecting labile material from the harmful effects of drying. In vivo, we observe that CAHS D forms fiber-like condensates during osmotic stress. Condensation of CAHS D improves survival of osmotically shocked cells through at least two mechanisms: reduction of cell volume change and reduction of metabolic activity. Importantly, condensation of CAHS D is reversible and metabolic rates return to control levels after CAHS condensates are resolved. This work provides insights into how tardigrades induce biostasis through the self-assembly of CAHS gels.

physiology↗

bioRxiv2023

Direct prediction of intrinsically disordered protein conformational properties from sequence

Intrinsically disordered regions (IDRs) are ubiquitous across all domains of life and play a range of functional roles. While folded domains are generally well-described by a single 3D structure, IDRs exist in a collection of interconverting states known as an ensemble. This structural heterogeneity means IDRs are largely absent from the PDB, contributing to a lack of computational approaches to predict ensemble conformational properties from sequence. Here we combine rational sequence design, large-scale molecular simulations, and deep learning to develop ALBATROSS, a deep learning model for predicting IDR ensemble dimensions from sequence. ALBATROSS enables the instantaneous prediction of ensemble average properties at proteome-wide scale. ALBATROSS is lightweight, easy-to-use, and accessible as both a locally installable software package and a point-and-click style interface in the cloud. We first demonstrate the applicability of our predictors by examining the generalizability of sequence-ensemble relationships in IDRs. Then, we leverage the high-throughput nature of ALBATROSS to characterize emergent biophysical behavior of IDRs within and between proteomes. Update from previous versionO_LIThis preprint reports an updated version of the ALBATROSS network weights trained on simulations of over 42,000 sequences. C_LIO_LIIn addition, we provide new colab notebooks that enable proteome-wide IDR prediction and annotation in minutes. C_LIO_LIAll conclusions and observations made in versions 1 and 2 of this manuscript remain true and robust. C_LI

biophysics↗

bioRxiv2023

Aberrant phase separation is a common killing strategy of positively charged peptides in biology and human disease

Positively charged repeat peptides are emerging as key players in neurodegenerative diseases. These peptides can perturb diverse cellular pathways but a unifying framework for how such promiscuous toxicity arises has remained elusive. We used mass-spectrometry-based proteomics to define the protein targets of these neurotoxic peptides and found that they all share similar sequence features that drive their aberrant condensation with these positively charged peptides. We trained a machine learning algorithm to detect such sequence features and unexpectedly discovered that this mode of toxicity is not limited to human repeat expansion disorders but has evolved countless times across the tree of life in the form of cationic antimicrobial and venom peptides. We demonstrate that an excess in positive charge is necessary and sufficient for this killer activity, which we name polycation poisoning. These findings reveal an ancient and conserved mechanism and inform ways to leverage its design rules for new generations of bioactive peptides.

cell biology↗

bioRxiv2022

SHEPHARD: a modular and extensible software architecture for analyzing and annotating large protein datasets

The emergence of high-throughput experiments and high-resolution computational predictions has led to an explosion in the quality and volume of protein sequence annotations at proteomic scales. Unfortunately, integrating and analyzing complex sequence annotations remains logistically challenging. Here we present SHEPHARD, a software package that makes large-scale integrative protein bioinformatics trivial. SHEPHARD is provided as a stand-alone package and with a pre-compiled set of human annotations in a Google Colab notebook.

bioinformatics↗

bioRxiv2022

The formation of a fuzzy complex in the negative arm regulates the robustness of the circadian clock.

The circadian clock times cellular processes to the day/night cycle via a Transcription-Translation negative Feedback Loop (TTFL). However, a mechanistic understanding of the negative arm in both the timing of the TTFL and its control of output is lacking. We posited that the formation of negative-arm protein complexes was fundamental to clock regulation stemming from the negative arm. Using a modified peptide microarray approach termed Linear motif discovery using rational design (LOCATE), we characterized the interaction of the disordered negative-arm clock protein FREQUENCY to its partner protein FREQUENCY-Interacting RNA helicase. LOCATE identified a specific Short Linear Motif (SLiM) and interaction "hotspot" as well as positively charged "islands" that mediate electrostatic interactions, suggesting a model where negative arm proteins form a "fuzzy" complex essential for clock timing and robustness. Further analysis revealed that the positively charged islands were an evolutionarily conserved feature in higher eukaryotes and contributed to proper clock function.

molecular biology↗