Biology subjects

Berkeley, R. F.

Publications and source records attributed to Berkeley, R. F..

4 recordsLinked to original sources

bioRxiv2025

Tryptoline Stereoprobe Elaboration Identifies Inhibitors of the GRPEL1-HSPA9 Chaperone Complex

Activity-based protein profiling has identified hundreds of proteins from diverse classes that react at specific cysteine residues with stereochemically defined electrophilic compounds (stereoprobes) in human cells. The structure-activity relationships underlying these stereoprobe-protein interactions, however, remain poorly understood. Here we show that the protein interaction landscape of tryptoline acrylamide stereoprobes can be profoundly altered by structural modifications distal to the acrylamide reactive group. The majority of stereoprobe liganding events occurred at non-orthosteric sites and mostly evaded assignment by the machine learning-based co-folding model Boltz-2, which instead tended to misplace the stereoprobes in orthosteric pockets (an outcome we term "orthostery burnout"). We found that stereoprobes reacting with C124 in the nucleotide exchange factor GRPEL1 disrupt interactions with the mitochondrial HSP70 chaperone HSPA9/mortalin, leading to impairments in mitochondrial protein import and induction of mitophagy. Our results highlight tryptoline acrylamides as a versatile source of covalent ligands targeting non-orthosteric sites on proteins, including tool compounds that perturb the mitochondrial HSP70 chaperone system.

biochemistry↗

bioRxiv2025

ANTIDOTE: A Metadata-Driven Neural Network for Improving CryoEM 3-D Particle Sorting

Despite the maturation of cryogenic electron microscopy (cryoEM) methodologies, generating high-resolution three-dimensional (3-D) reconstructions from micrographs is a time-intensive process involving iterative rounds of subjective data curation and hyperparameter optimization. Current approaches to particle classification are often unable to remove all low-quality particles from particle stacks, largely due to the low signal-to-noise ratio, the high dimensionality of particle images, and the multiple degrees of freedom associated with each particles unknown rotation, orientation, and class assignment. The retention of low-quality particles negatively affects the overall quality of the final EM density and continued efforts to eliminate their deleterious contributions are warranted. Here, we present ANTIDOTE (A Neural network Trained In Deleterious Object deTection and Elimination), a neural network framework that discriminates between constructive and deleterious particles using per-particle metadata generated during 3-D classification in RELION. Using benchmark and real-world cryoEM datasets, we demonstrate that ANTIDOTE paired with RELION 3-D classification achieves higher particle classification accuracy than conventional data processing approaches alone, yielding improvements in reconstruction quality, global and local resolution, and map interpretability while reducing time-consuming hyperparameter optimization. We additionally detail practical use-case scenarios for ANTIDOTE and demonstrate its versatility in increasing particle curation accuracy for high-quality cryoEM reconstruction.

biophysics↗

bioRxiv2024

Capturing the Conformational Heterogeneity of HSPB1 Chaperone Oligomers at Atomic Resolution

Small heat shock proteins (sHSPs), including HSPB1, are essential regulators of cellular proteostasis that interact with unfolded and partially folded proteins to prevent aberrant misfolding and aggregation. These proteins fulfill a similar role in biological condensates, where they interact with intrinsically disordered proteins to modulate their liquid-liquid and liquid-to-solid phase transitions. Characterizing sHSP structure, dynamics, and client interactions is challenging due to their partially disordered nature, their tendency to form polydisperse oligomers, and their diverse range of clients. In this work, we leverage various biophysical methods, including fast 1H-based magic angle spinning (MAS) NMR spectroscopy, molecular dynamics (MD) simulations and modeling, to shed new light on the structure and dynamics of HSPB1 oligomers. Using split-intein mediated segmental labeling, we provide unambiguous evidence that in the oligomer context the N-terminal domain (NTD) of HSPB1 is rigid and adopts an ensemble of heterogenous conformations, the -crystallin domain (ACD) forms dimers and experiences multiple distinct local environments, while the C-terminal domain (CTD) remains highly dynamic. Our computational models suggest that the NTDs participate in extensive NTD-NTD and NTD-ACD interactions and are sequestered within the oligomer interior. We further demonstrate that HSPB1 higher order oligomers disassemble into smaller oligomeric species in the presence of a client protein and that an accessible NTD is essential for HSPB1 partitioning into condensates and interactions with client proteins. Our integrated approach provides a high-resolution view of the complex oligomeric landscape of HSPB1 and sheds light on the elusive network of interactions that underly HSPB1 function in biological condensates. Significance statementHSPB1 is a ubiquitous cellular chaperone that helps prevent the aberrant aggregation of intrinsically disordered proteins involved in biological condensates and neurodegenerative diseases. Despite its central role in this process, many aspects of HSPB1s structure and interactions with clients are not well understood due to its tendency to form polydisperse oligomeric structures and to function in heterogeneous condensate environments. Here, we present an integrated approach that includes segmental labeling, fast MAS NMR spectroscopy, and computational tools to characterize the structure and dynamics of HSPB1 in its oligomeric form and within client condensates at high resolution. Our approach, which is applicable to other complex biological systems, highlights the important role of HSPB1s N-terminal domain in oligomeric assembly and interactions with clients.

biophysics↗

bioRxiv2020

Real-Time Observation of Structure and Dynamics during the Liquid-to-Solid Transition of FUS LC

Many of the proteins found in pathological protein fibrils also exhibit tendencies for liquid-liquid phase separation (LLPS) both in vitro and in cells. The mechanisms underlying the connection between these phase transitions have been challenging to study due to the heterogeneous and dynamic nature of the states formed during the maturation of LLPS protein droplets into gels and solid aggregates. Here, we interrogate the liquid-to-solid transition of the low complexity domain of the RNA binding protein FUS (FUS LC), which has been shown to adopt LLPS, gel-like, and amyloid states. We employ magic-angle spinning (MAS) NMR spectroscopy which has allowed us to follow these transitions in real time and with residue specific resolution. We observe the development of {beta}-sheet structure through the maturation process and show that the final state of FUS LC fibrils produced through LLPS is distinct from that grown from fibrillar seeds. We also apply our methodology to FUS LC G156E, a clinically relevant FUS mutant that exhibits accelerated fibrillization rates. We observe significant changes in dynamics during the transformation of the FUS LC G156E construct and begin to unravel the sequence specific contributions to this phenomenon with computational studies of the phase separated state of FUS LC and FUS LC G156E. SignificanceThe presence of protein aggregates and plaques in the brain is a common pathological sign of neurodegenerative disease. Recent work has revealed that many of the proteins found in these aggregates can also form liquid-liquid droplets and gels. While the interconversion from one state to another can have vast implications for cell function and disease, the molecular mechanisms that underlie these processes are not well understood. Here, we combine MAS NMR spectroscopy with other biophysical and computational tools to follow the transitions of the stress response protein FUS. This approach has allowed us to observe real-time changes in structure and dynamics as the protein undergoes these transitions, and to reveal the intricate effects of disease-relevant mutations on the transformation process.

biophysics↗