arXiv subjects

Eugene I. Shakhnovich

Publications and source records attributed to Eugene I. Shakhnovich.

At least 19 recordsLinked to original sources

arXiv2023

Evaluating the roughness of structure-property relationships using pretrained molecular representations

Quantitative structure-property relationships (QSPRs) aid in understanding molecular properties as a function of molecular structure. When the correlation between structure and property weakens, a dataset is described as "rough," but this characteristic is partly a function of the chosen representation. Among possible molecular representations are those from recently-developed "foundation models" for chemistry which learn molecular representation from unlabeled samples via self-supervision. However, the performance of these pretrained representations on property prediction benchmarks is mixed when compared to baseline approaches. We sought to understand these trends in terms of the roughness of the underlying QSPR surfaces. We introduce a reformulation of the roughness index (ROGI), ROGI-XD, to enable comparison of ROGI values across representations and evaluate various pretrained representations and those constructed by simple fingerprints and descriptors. We show that pretrained representations do not produce smoother QSPR surfaces, in agreement with previous empirical results of model accuracy. Our findings suggest that imposing stronger assumptions of smoothness with respect to molecular structure during model pretraining can aid in the downstream generation of smoother QSPR surfaces.

q-bio.QM↗

arXiv2023

Systematic conformation-to-phenotype mapping via limited deep-sequencing of proteins

Non-native conformations drive protein misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well-suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.

physics.bio-ph↗

arXiv2020

Metabolic response to point mutations reveals principles of modulation of in vivo enzyme activity and phenotype

The relationship between sequence variation and phenotype is poorly understood. Here we use metabolomic analysis to elucidate the molecular mechanism underlying the filamentous phenotype of E. coli strains that carry destabilizing mutations in the Dihydrofolate Reductase (DHFR). We find that partial loss of DHFR activity causes SOS response indicative of DNA damage and cell filamentation. This phenotype is triggered by an imbalance in deoxy nucleotide levels, most prominently a disproportionate drop in the intracellular dTTP. We show that a highly cooperative (Hill coefficient 2.5) in vivo activity of Thymidylate Kinase (Tmk), a downstream enzyme that phosphorylates dTMP to dTDP, is the cause of suboptimal dTTP levels. dTMP supplementation in the media rescues filamentation and restores in vivo Tmk kinetics to almost perfect Michaelis-Menten, like its kinetics in vitro. Overall, this study highlights the important role of cellular environment in sculpting enzymatic kinetics with system level implications for bacterial phenotype.

q-bio.BM↗

arXiv2020

A native chemical chaperone in the human eye lens

Cataract is one of the most prevalent protein aggregation disorders and still the biggest cause of vision loss worldwide. The human lens, in its core region, lacks turnover of any cells or cellular components; it has therefore evolved remarkable mechanisms for resisting protein aggregation for a lifetime. We now report that one such mechanism relies on an unusually abundant metabolite, myo-inositol, to suppress light-scattering aggregation of lens proteins. We quantified aggregation suppression by in vitro turbidimetry and characterized both macroscopic and microscopic mechanisms of myo-inositol action using negative-stain electron microscopy, differential scanning fluorometry, and a thermal scanning Raman spectroscopy apparatus. Given recent metabolomic evidence that it is dramatically depleted in human cataractous lenses compared to age-matched controls, we suggest that maintaining or restoring healthy levels of myo-inositol in the lens may be a simple, safe, and widely available strategy for reducing the global burden of cataract.

q-bio.BM↗

arXiv2020

Accelerating high-throughput virtual screening through molecular pool-based active learning

Structure-based virtual screening is an important tool in early stage drug discovery that scores the interactions between a target protein and candidate ligands. As virtual libraries continue to grow (in excess of $10^8$ molecules), so too do the resources necessary to conduct exhaustive virtual screening campaigns on these libraries. However, Bayesian optimization techniques can aid in their exploration: a surrogate structure-property relationship model trained on the predicted affinities of a subset of the library can be applied to the remaining library members, allowing the least promising compounds to be excluded from evaluation. In this study, we assess various surrogate model architectures, acquisition functions, and acquisition batch sizes as applied to several protein-ligand docking datasets and observe significant reductions in computational costs, even when using a greedy acquisition strategy; for example, 87.9% of the top-50000 ligands can be found after testing only 2.4% of a 100M member library. Such model-guided searches mitigate the increasing computational costs of screening increasingly large virtual libraries and can accelerate high-throughput virtual screening campaigns with applications beyond docking.

q-bio.QM↗

arXiv2020

Effect of protein structure on evolution of cotranslational folding

Cotranslational folding depends on the folding speed and stability of the nascent protein. It remains difficult, however, 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 slower translation speeds 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.

q-bio.BM↗

arXiv2019

Improved fragment-based movement with LRFragLib for all-atom Ab initio protein folding

Fragment-based assembly has been widely used in Ab initio protein folding simulation which can effectively reduce the conformational space and thus accelerate sampling. The efficiency of fragment-based movement as well as the quality of fragment library determine whether the folding process can lead the free energy landscape to the global minimum and help the protein to reach near-native folded state. We designed an improved fragment-based movement, "fragmove", which substituted multiple backbone dihedral angles in every simulation step. This movement strategy was derived from the fragment library generated by LRFragLib, an effective fragment detection algorithm using logistic regression model. We show in replica exchange Monte Carlo (REMC) simulation that "fragmove", when compared with a set of existing movements in REMC, shows significant improved ability at increasing secondary and tertiary predicted model accuracy by 11.24% and 17.98%, respectively and reaching energy minima decreased by 5.72%. Our results demonstrate that this improved movement is more powerful to guide proteins faster to low energy regions of conformational space and promote folding efficiency and predicted model accuracy.

q-bio.QM↗

arXiv2019

Mutation rate variability as a driving force in adaptive evolution

Mutation rate is a key determinant of the pace as well as outcome of evolution, and variability in this rate has been shown in different scenarios to play a key role in evolutionary adaptation and resistance evolution under stress caused by selective pressure. Here we investigate the dynamics of resistance fixation in a bacterial population with variable mutation rates and show that evolutionary outcomes are most sensitive to mutation rate variations when the population is subject to environmental and demographic conditions that suppress the evolutionary advantage of high-fitness subpopulations. By directly mapping a biophysical fitness function to the system-level dynamics of the population we show that both low and very high, but not intermediate, levels of stress in the form of an antibiotic result in a disproportionate effect of hypermutation on resistance fixation. We demonstrate how this behavior is directly tied to the extent of genetic hitchhiking in the system, the propagation of high-mutation rate cells through association with high-fitness mutations. Our results indicate a substantial role for mutation rate flexibility in the evolution of antibiotic resistance under conditions that present a weak advantage over wildtype to resistant cells.

q-bio.PE↗

arXiv2018

Substrate inhibition imposes fitness penalty at high protein stability

Proteins are only moderately stable. It has long been debated whether this narrow range of stabilities is solely a result of neutral drift towards lower stability or purifying selection against excess stability is also at work - for which no experimental evidence was found so far. Here we show that mutations outside the active site in the essential E. coli enzyme adenylate kinase result in stability-dependent increase in substrate inhibition by AMP, thereby impairing overall enzyme activity at high stability. Such inhibition caused substantial fitness defects not only in the presence of excess substrate but also under physiological conditions. In the latter case, substrate inhibition caused differential accumulation of AMP in the stationary phase for the inhibition prone mutants. Further, we show that changes in flux through Adk could accurately describe the variation in fitness effects. Taken together, these data suggest that selection against substrate inhibition and hence excess stability may have resulted in a narrow range of optimal stability observed for modern proteins.

q-bio.BM↗

arXiv2018

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.

q-bio.BM↗

arXiv2018

Growth tradeoffs produce complex microbial communities on a single limiting resource

The relationship between the dynamics of a community and its constituent pairwise interactions is a fundamental problem in ecology. Higher-order ecological effects beyond pairwise interactions may be key to complex ecosystems, but mechanisms to produce these effects remain poorly understood. Here we show that higher-order effects can arise from variation in multiple microbial growth traits, such as lag times and growth rates, on a single limiting resource with no other interactions. These effects produce a range of ecological phenomena: an unlimited number of strains can exhibit multistability and neutral coexistence, potentially with a single keystone strain; strains that coexist in pairs do not coexist all together; and the champion of all pairwise competitions may not dominate in a mixed community. Since variation in multiple growth traits is ubiquitous in microbial populations due to pleiotropy and non-genetic variation, our results indicate these higher-order effects may also be widespread, especially in laboratory ecology and evolution experiments.

q-bio.PE↗

arXiv2018

Tradeoffs between microbial growth phases lead to frequency-dependent and non-transitive selection

Mutations in a microbial population can increase the frequency of a genotype not only by increasing its exponential growth rate, but also by decreasing its lag time or adjusting the yield (resource efficiency). The contribution of multiple life-history traits to selection is a critical question for evolutionary biology as we seek to predict the evolutionary fates of mutations. Here we use a model of microbial growth to show there are two distinct components of selection corresponding to the growth and lag phases, while the yield modulates their relative importance. The model predicts rich population dynamics when there are tradeoffs between phases: multiple strains can coexist or exhibit bistability due to frequency-dependent selection, and strains can engage in rock-paper-scissors interactions due to non-transitive selection. We characterize the environmental conditions and patterns of traits necessary to realize these phenomena, which we show to be readily accessible to experiments. Our results provide a theoretical framework for analyzing high-throughput measurements of microbial growth traits, especially interpreting the pleiotropy and correlations between traits across mutants. This work also highlights the need for more comprehensive measurements of selection in simple microbial systems, where the concept of an ordinary fitness landscape breaks down.

q-bio.PE↗

arXiv2017

Absence of selection for quantum coherence in the Fenna-Matthews-Olson complex: a combined evolutionary and excitonic study

We present a study on the evolution of the Fenna-Matthews-Olson bacterial photosynthetic pigment-protein complex. This protein complex functions as an antenna. It transports absorbed photons - excitons - to a reaction center where photosynthetic reactions initiate. The efficiency of exciton transport is therefore fundamental for the photosynthetic bacterium's survival. We have reconstructed an ancestor of the complex to establish whether coherence in the exciton transport was selected for or optimized over time. We have also investigated on the role of optimizing free energy variation upon folding in evolution. We studied whether mutations which connect the ancestor to current day species were stabilizing or destabilizing from a thermodynamic view point. From this study, we established that most of these mutations were thermodynamically neutral. Furthermore, we did not see a large change in exciton transport efficiency or coherence and thus our results predict that exciton coherence was not specifically selected for.

physics.bio-ph↗

arXiv2016

Graph's Topology and Free Energy of a Spin Model on the Graph

In this work we show that there is a direct relationship between a graph's topology and the free energy of a spin system on the graph. We develop a method of separating topological and enthalpic contributions to the free energy, and find that considering the topology is sufficient to qualitatively compare the free energies of different graph systems at high temperature, even when the energetics are not fully known. This method was applied to the metal lattice system with defects, and we found that it partially explains why point defects are more stable than high-dimensional defects. Given the energetics, we can even quantitatively compare free energies of different graph structures via a closed form of linear graph contributions. The closed form is applied to predict the sequence space free energy of lattice proteins, which is a key factor determining the designability of a protein structure.

cond-mat.stat-mech↗

arXiv2016

The role of evolutionary selection in the dynamics of protein structure evolution

Emergence of new protein structures has proved difficult to trace in nature and engineer in the laboratory. However, one aspect of structure evolution has proved immensely helpful for determining the three-dimensional structure of proteins from their sequences: in the vast majority of cases, proteins that share more than 30% sequence identity have similar structures. Below this mark is the "twilight zone" where proteins may have identical or very different structures. These observations form the foundational intuition behind structure homology modeling. Despite their importance, however, they have never received a comprehensive biophysical justification. Here we show that the onset of the twilight zone is more gradual for proteins with low contact density, a proxy for low thermodynamic stability, than proteins with high contact density. Then we present an analytical model that treats divergent fold evolution as an activated process, in analogy to chemical kinetics, where sequence evolution must overcome thermodynamically unstable evolutionary intermediates to discover new folds. This model explains the existence of a twilight zone and explains why its onset is more abrupt for some classes of proteins than for others. We test the assumptions of the model and characterize the dynamics of fold evolution using evolutionary simulations of model proteins and cell populations. Overall these results show how fundamental biophysical constraints directed evolutionary dynamics leading to the Universe of modern protein structures and sequences.

q-bio.PE↗

arXiv2016

Structure-based prediction of protein-folding transition paths

We propose a general theory to describe the distribution of protein-folding transition paths. We show that transition paths follow a predictable sequence of high-free-energy transient states that are separated by free-energy barriers. Each transient state corresponds to the assembly of one or more discrete, cooperative units, which are determined directly from the native structure. We show that the transition state on a folding pathway is reached when a small number of critical contacts are formed between a specific set of substructures, after which folding proceeds downhill in free energy. This approach suggests a natural resolution for distinguishing parallel folding pathways and provides a simple means to predict the rate-limiting step in a folding reaction. Our theory identifies a common folding mechanism for proteins with diverse native structures and establishes general principles for the self-assembly of polymers with specific interactions.

q-bio.BM↗

arXiv2016

An internal disulfide locks a misfolded aggregation-prone intermediate in cataract-linked mutants of human γD-crystallin

Considerable mechanistic insight has been gained into amyloid aggregation; however, a large class of non-amyloid protein aggregates are considered 'amorphous,' and in most cases little is known about their mechanisms. Amorphous aggregation of γ-crystallins in the eye lens causes a widespread disease of aging, cataract. We combined simulations and experiments to study the mechanism of aggregation of two γD-crystallin mutants, W42R and W42Q - the former a congenital cataract mutation, and the latter a mimic of age-related oxidative damage. We found that formation of an internal disulfide was necessary and sufficient for aggregation under physiological conditions. Two-chain all-atom simulations predicted that one non-native disulfide in particular, between Cys32 and Cys41, was likely to stabilize an unfolding intermediate prone to intermolecular interactions. Mass spectrometry and mutagenesis experiments confirmed the presence of this bond in the aggregates and its necessity for oxidative aggregation under physiological conditions in vitro. Mining the simulation data linked formation of this disulfide to extrusion of the N-terminal \b{eta}-hairpin and rearrangement of the native \b{eta}-sheet topology. Specific binding between the extruded hairpin and a distal \b{eta}-sheet, in an intermolecular chain reaction similar to domain swapping, is the most probable mechanism of aggregate propagation.

q-bio.BM↗

arXiv2012

Soluble oligomerization provides a beneficial fitness effect on destabilizing mutations

Mutations create the genetic diversity on which selective pressures can act, yet also create structural instability in proteins. How, then, is it possible for organisms to ameliorate mutation-induced perturbations of protein stability while maintaining biological fitness and gaining a selective advantage? Here we used a new technique of site-specific chromosomal mutagenesis to introduce a selected set of mostly destabilizing mutations into folA - an essential chromosomal gene of E. coli encoding dihydrofolate reductase (DHFR) - to determine how changes in protein stability, activity and abundance affect fitness. In total, 27 E.coli strains carrying mutant DHFR were created. We found no significant correlation between protein stability and its catalytic activity nor between catalytic activity and fitness in a limited range of variation of catalytic activity observed in mutants. The stability of these mutants is strongly correlated with their intracellular abundance; suggesting that protein homeostatic machinery plays an active role in maintaining intracellular concentrations of proteins. Fitness also shows a significant correlation with intracellular abundance of soluble DHFR in cells growing at 30oC. At 42oC, on the other hand, the picture was mixed, yet remarkable: a few strains carrying mutant DHFR proteins aggregated rendering them nonviable, but, intriguingly, the majority exhibited fitness higher than wild type. We found that mutational destabilization of DHFR proteins in E. coli is counterbalanced at 42oC by their soluble oligomerization, thereby restoring structural stability and protecting against aggregation.

q-bio.BM↗