Biology subjects

Jacobs, W. M.

Publications and source records attributed to Jacobs, W. M..

9 recordsLinked to original sources

bioRxiv2024

Interplay of condensation and chromatin binding underlies BRD4 targeting

Nuclear compartments form via biomolecular phase separation, mediated through multivalent properties of biomolecules concentrated within condensates. Certain compartments are associated with specific chromatin regions, including transcriptional initiation condensates, which are composed of transcription factors and transcriptional machinery, and form at acetylated regions including enhancer and promoter loci. While protein self-interactions, especially within low-complexity and intrinsically disordered regions, are known to mediate condensation, the role of substrate-binding interactions in regulating the formation and function of biomolecular condensates is under-explored. Here, utilizing live-cell experiments in parallel with coarse-grained simulations, we investigate how chromatin interaction of the transcription factor BRD4 modulates its condensate formation. We find that both kinetic and thermodynamic properties of BRD4 condensation are affected by chromatin binding: nucleation rate is sensitive to BRD4-chromatin interactions, providing an explanation for the selective formation of BRD4 condensates at acetylated chromatin regions, and thermodynamically, multivalent acetylated chromatin sites provide a platform for BRD4 clustering below the concentration required for off-chromatin condensation. This provides a molecular and physical explanation of the relationship between nuclear condensates and epigenetically modified chromatin that results in their mutual spatiotemporal regulation, suggesting that epigenetic modulation is an important mechanism by which the cell targets transcriptional condensates to specific chromatin loci.

molecular biology↗

bioRxiv2023

Emergence of multiphase condensates from a limited set of chemical building blocks

Biomolecules composed of a limited set of chemical building blocks can co-localize into distinct, spatially segregated compartments known as biomolecular condensates. Although recent studies of intracellular condensates have shown that coexisting, immiscible condensates can form spontaneously via phase separation, it has remained unclear how coexisting and multiphase condensates assemble from chemical building blocks with limited specificity. Here we establish a connection between the interdependencies among biomolecular interactions and the thermodynamic stability of multiphase condensates. We then introduce an inverse design approach for computing the minimum interaction specificity required to assemble condensates with prescribed molecular compositions in a multicomponent biomolecular mixture. As a proof of principle, we apply our theory to design mixtures of model heteropolymers using a minimal number of distinct monomer types, and we use molecular simulations to verify that our designs produce coexisting condensates with the target molecular compositions. Our theoretical approach explains how multiphase condensates arise in naturally occurring biomolecular mixtures and provides a rational algorithm for engineering complex artificial condensates from simple chemical building blocks.

biophysics↗

bioRxiv2023

Active learning of the thermodynamics-dynamics tradeoff in protein condensates

Phase-separated biomolecular condensates exhibit a wide range of dynamical properties, which depend on the sequences of the constituent proteins and RNAs. However, it is unclear to what extent condensate dynamics can be tuned without also changing the thermodynamic properties that govern phase separation. Using coarse-grained simulations of intrinsically disordered proteins, we show that the dynamics and thermodynamics of homopolymer condensates are strongly correlated, with increased condensate stability being coincident with low mobilities and high viscosities. We then apply an "active learning" strategy to identify heteropolymer sequences that break this correlation. This data-driven approach and accompanying analysis reveal how heterogeneous amino-acid compositions and non-uniform sequence patterning map to a range of independently tunable dynamical and thermodynamic properties of biomolecular condensates. Our results highlight key molecular determinants governing the physical properties of biomolecular condensates and establish design rules for the development of stimuli-responsive biomaterials.

biophysics↗

bioRxiv2020

DBFOLD: An efficient algorithm for computing folding pathways of complex proteins

Atomistic simulations can provide valuable, experimentally-verifiable insights into protein folding mechanisms, but existing ab initio simulation methods are restricted to only the smallest proteins due to severe computational speed limits. The folding of larger proteins has been studied using native-centric potential functions, but such models omit the potentially crucial role of non-native interactions.Here, we present an algorithm, entitled DBFOLD, which can predict folding pathways for a wide range of proteins while accounting for the effects of non-native contacts. In addition, DBFOLD can predict the relative rates of different transitions within a proteins folding pathway. To accomplish this, rather than directly simulating folding, our method combines equilibrium Monte-Carlo simulations, which deploy enhanced sampling, with unfolding simulations at high temperatures. We show that under certain conditions, trajectories from these two types of simulations can be jointly analyzed to compute unknown folding rates from detailed balance. This requires inferring free energies from the equilibrium simulations, and extrapolating transition rates from the unfolding simulations to lower, physiologically-reasonable temperatures at which the native state is marginally stable. As a proof of principle, we show that our method can accurately predict folding pathways and Monte-Carlo rates for the well-characterized Streptococcal protein G. We then show that our method significantly reduces the amount of computation time required to compute the folding pathways of large, misfolding-prone proteins that lie beyond the reach of existing direct simulation methods. Our algorithm, which is available online, can generate detailed atomistic models of protein folding mechanisms while shedding light on the role of non-native intermediates which may crucially affect organismal fitness and are frequently implicated in disease. Author summaryMany proteins must adopt a specific structure in order to function. Computational simulations have been used to shed light on the mechanisms of protein folding, but unfortunately, realistic simulations can typically only be run for small proteins, due to severe limits in computational speed. Here, we present a method to solve this problem, whereby instead of directly simulating folding from an unfolded state, we run simulations that allow for computation of equilibrium folding free energies, alongside high temperature simulations to compute unfolding rates. From these quantities, folding rates can be computed using detailed balance. Importantly, our method can account for the effects of nonnative contacts which transiently form during folding and must be broken prior to adoption of the native state. Such contacts, which are often excluded from simple models of folding, may crucially affect real protein folding pathways and are often observed in folding intermediates implicated in disease.

biophysics↗

bioRxiv2020

Effect of protein structure on evolution of cotranslational folding

Cotranslational folding is expected to occur when the folding speed of the nascent chain is faster than the translation speed of the ribosome, but it is difficult to predict which proteins cotranslationally fold. Here, we simulate evolution of model proteins to investigate how native structure influences evolution of cotranslational folding. We developed a model that connects protein folding during and after translation to cellular fitness. Model proteins evolved improved folding speed and stability, with proteins adopting one of two strategies for folding quickly. Low contact order proteins evolve to fold cotranslationally. Such proteins adopt native conformations early on during the translation process, with each subsequently translated residue establishing additional native contacts. On the other hand, high contact order proteins tend not to be stable in their native conformations until the full chain is nearly extruded. We also simulated evolution of slowly translating codons, finding that slowing translation at certain positions enhances cotranslational folding. Finally, we investigated real protein structures using a previously published dataset that identified evolutionarily conserved rare codons in E. coli genes and associated such codons with cotranslational folding intermediates. We found that protein substructures preceding conserved rare codons tend to have lower contact orders, in line with our finding that lower contact order proteins are more likely to fold cotranslationally. Our work shows how evolutionary selection pressure can cause proteins with local contact topologies to evolve cotranslational folding. Statement of significanceSubstantial evidence exists for proteins folding as they are translated by the ribosome. Here we developed a biologically intuitive evolutionary model to show that avoiding premature protein degradation can be a sufficient evolutionary force to drive evolution of cotranslational folding. Furthermore, we find that whether a proteins native fold consists of more local or more nonlocal contacts affects whether cotranslational folding evolves. Proteins with local contact topologies are more likely to evolve cotranslational folding through nonsynonymous mutations that strengthen native contacts as well as through synonymous mutations that provide sufficient time for cotranslational folding intermediates to form.

biophysics↗

bioRxiv2019

Co-translational folding allows misfolding-prone proteins to circumvent deep kinetic traps

Many large proteins suffer from slow or inefficient folding in vitro. Here, we provide evidence that this problem can be alleviated in vivo if proteins start folding co-translationally. Using an all-atom simulation-based algorithm, we compute the folding properties of various large protein domains as a function of nascent chain length, and find that for certain proteins, there exists a narrow window of lengths that confers both thermodynamic stability and fast folding kinetics. Beyond these lengths, folding is drastically slowed by non-native interactions involving C-terminal residues. Thus, co-translational folding is predicted to be beneficial because it allows proteins to take advantage of this optimal window of lengths and thus avoid kinetic traps. Interestingly, many of these proteins sequences contain conserved rare codons that may slow down synthesis at this optimal window, suggesting that synthesis rates may be evolutionarily tuned to optimize folding. Using kinetic modelling, we show that under certain conditions, such a slowdown indeed improves co-translational folding efficiency by giving these nascent chains more time to fold. In contrast, other proteins are predicted not to benefit from co-translational folding due to a lack of significant non-native interactions, and indeed these proteins sequences lack conserved C-terminal rare codons. Together, these results shed light on the factors that promote proper protein folding in the cell, and how biomolecular self-assembly may be optimized evolutionarily.\n\nSignificance StatementMany proteins must adopt a specific structure in order to perform their functions, and failure to do so has been linked to disease. Although small proteins often fold rapidly and spontaneously to their native conformations, larger proteins are less likely to fold correctly due to the myriad incorrect arrangements they can adopt. Here, we show that this problem can be alleviated if proteins start folding while they are being translated, namely, built one amino acid at a time on the ribosome. This process of co-translational folding biases certain proteins away from misfolded states that tend to hinder spontaneous refolding. Signatures of unusually slow translation suggest that some of these proteins have evolved to fold co-translationally.

biophysics↗

bioRxiv2018

Accurate protein-folding transition-path statistics from a simple free-energy landscape

A central goal of protein-folding theory is to predict the stochastic dynamics of transition paths -- the rare trajectories that transit between the folded and unfolded ensembles -- using only thermodynamic information, such as a low-dimensional equilibrium free-energy landscape. However, commonly used one-dimensional landscapes typically fall short of this aim, because an empirical coordinate-dependent diffusion coefficient has to be fit to transition-path trajectory data in order to reproduce the transition-path dynamics. We show that an alternative, first-principles free-energy landscape predicts transition-path statistics that agree well with simulations and single-molecule experiments without requiring dynamical data as an input. This topological configuration model assumes that distinct, native-like substructures assemble on a timescale that is slower than native-contact formation but faster than the folding of the entire protein. Using only equilibrium simulation data to determine the free energies of these coarse-grained intermediate states, we predict a broad distribution of transition-path transit times that agrees well with the transition-path durations observed in simulations. We further show that both the distribution of finite-time displacements on a one-dimensional order parameter and the ensemble of transition-path trajectories generated by the model are consistent with the simulated transition paths. These results indicate that a landscape based on transient folding intermediates, which are often hidden by one-dimensional projections, can form the basis of a predictive model of protein-folding transition-path dynamics.

biophysics↗

bioRxiv2017

Accessibility of the Shine-Dalgarno sequence dictates N-terminal codon bias in E. coli

Despite considerable efforts, no physical mechanism has been shown to explain N-terminal codon bias in prokaryotic genomes. Using a systematic study of synonymous substitutions in two endogenous E. coli genes, we show that interactions between the coding region and the upstream Shine-Dalgarno (SD) sequence modulate the efficiency of translation initiation, affecting both intracellular mRNA and protein levels due to the inherent coupling of transcription and translation in E. coli. We further demonstrate that far-downstream mutations can also modulate mRNA levels by occluding the SD sequence through the formation of non-equilibrium secondary structures. By contrast, a non-endogenous RNA polymerase that decouples transcription and translation largely alleviates the effects of synonymous substitutions on mRNA levels. Finally, a complementary statistical analysis of the E. coli genome specifically implicates avoidance of intra-molecular base-pairing with the SD sequence. Our results provide general physical insights into the coding-level features that optimize protein expression in prokaryotes.

biophysics↗

bioRxiv2017

Evidence of evolutionary selection for co-translational folding

Recent experiments and simulations have demonstrated that proteins can fold on the ribosome. However, the extent and generality of fitness effects resulting from co-translational folding remain open questions. Here we report a genome-wide analysis that uncovers evidence of evolutionary selection for co-translational folding. We describe a robust statistical approach to identify loci within genes that are both significantly enriched in slowly translated codons and evolutionarily conserved. Surprisingly, we find that domain boundaries can explain only a small fraction of these conserved loci. Instead, we propose that regions enriched in slowly translated codons are associated with co-translational folding intermediates, which may be smaller than a single domain. We show that the intermediates predicted by a native-centric model of co-translational folding account for the majority of these loci across more than 500 E. coli proteins. By making a direct connection to protein folding, this analysis provides strong evidence that many synonymous substitutions have been selected to optimize translation rates at specific locations within genes. More generally, our results indicate that kinetics, and not just thermodynamics, can significantly alter the efficiency of self-assembly in a biological context.

biophysics↗