Biology subjects

Fraser, J. S.

Publications and source records attributed to Fraser, J. S..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

Fragment-Based Hit Discovery via Unsupervised Learning of Fragment-Protein Complexes

The process of finding molecules that bind to a target protein is a challenging first step in drug discovery. Crystallographic fragment screening is a strategy based on elucidating binding modes of small polar compounds and then building potency by expanding or merging them. Recent advances in high-throughput crystallography enable screening of large fragment libraries, reading out dense ensembles of fragments spanning the binding site. However, fragments typically have low affinity thus the road to potency is often long and fraught with false starts. Here, we take advantage of high-throughput crystallography to reframe fragment-based hit discovery as a denoising problem - identifying significant pharmacophore distributions from a fragment ensemble amid noise due to weak binders - and employ an unsupervised machine learning method to tackle this problem. Our method screens potential molecules by evaluating whether they recapitulate those fragment-derived pharmacophore distributions. We retrospectively validated our approach on an open science campaign against SARS-CoV-2 main protease (Mpro), showing that our method can distinguish active compounds from inactive ones using only structural data of fragment-protein complexes, without any activity data. Further, we prospectively found novel hits for Mpro and the Mac1 domain of SARS-CoV-2 non-structural protein 3. More broadly, our results demonstrate how unsupervised machine learning helps interpret high throughput crystallography data to rapidly discover of potent chemical modulators of protein function.

bioinformatics↗

bioRxiv2022

Molecular evidence of widespread benzimidazole drug resistance in Ancylostoma caninum from domestic dogs throughout the USA and discovery of a novel isotype-1 β-tubulin benzimidazole resistance mutation.

Ancylostoma caninum is an important zoonotic gastrointestinal nematode of dogs worldwide and a close relative of human hookworms. We recently reported that racing greyhounds in the USA are infected with A. caninum that are commonly resistant to multiple anthelmintics. Benzimidazole resistance in A. caninum in greyhounds was associated with a high frequency of the canonical F167Y(TTC>TAC) isotype-1 {beta}-tubulin mutation. In this work, we show that benzimidazole resistance is remarkably widespread in A. caninum from domestic dogs across the USA. First, we identified and showed the functional significance of a novel benzimidazole isotype-1 {beta}-tubulin resistance mutation, Q134H(CAA>CAT). Several benzimidazole resistant A. caninum isolates from greyhounds with a low frequency of the F167Y(TTC>TAC) mutation had a high frequency of a Q134H(CAA>CAT) mutation not previously reported from any eukaryotic pathogen in the field. Structural modeling predicted that the Q134 residue is directly involved in benzimidazole drug binding and that the 134H substitution would significantly reduce binding affinity. Introduction of the Q134H substitution into the C. elegans {beta}-tubulin gene ben-1, by CRISPR-Cas9 editing, conferred similar levels of resistance as a ben-1 null allele. Deep amplicon sequencing on A. caninum eggs from 685 hookworm positive pet dog fecal samples revealed that both mutations were widespread across the USA, often at high frequency, with prevalences of 49.7% (overall frequency 54.0%) and 31.1% (overall frequency 16.4%) for F167Y(TTC>TAC) and Q134H(CAA>CAT), respectively. Canonical codon 198 and 200 benzimidazole resistance mutations were absent. The F167Y(TTC>TAC) mutation had a significantly higher prevalence and frequency in Western USA than in other regions, which we hypothesize is due to differences in refugia. This work has important implications for companion animal parasite control and the potential emergence of drug resistance in human hookworms. Author SummaryAlthough increasingly common in livestock, no reports of widespread anthelmintic resistance are confirmed in any companion animal or human gastrointestinal nematode parasite to date. The canine hookworm is a common intestinal zoonotic parasite of dogs with severe clinical impacts in young dogs, and for which control is dependent on regular anthelmintic use. We recently reported multiple anthelmintic drug resistance in A. caninum isolates from greyhounds derived from multiple locations in the USA likely caused by long standing intensive treatment regimens in kennels. In this study, we investigated benzimidazole resistance in A. caninum in pet dogs across the USA. We also identified and showed the functional significance of a novel benzimidazole isotype-1 {beta}-tubulin resistance mutation in A. caninum from greyhounds that has not been previously reported in the field for any organism. We then determined that this novel mutation, as well as a previously characterized resistance mutation, were present, often at high frequency, in many A. caninum populations across the USA. This study reports the first evidence of widespread drug resistance for any parasitic nematode of companion animals and illustrates the power of molecular approaches to rapidly assess anthelmintic resistance in a region.

genomics↗

bioRxiv2022

Deep Insertion, Deletion, and Missense Mutation Libraries for Exploring Protein Variation in Evolution, Disease, and Biology

Insertions and deletions (indels) are a major source of genetic variation in evolution and the cause of nearly 30% of Mendelian disease. Despite their importance, indels are left out of nearly every systematic mutational scan to date due to technical challenges associated with making indel-containing libraries, limiting our understanding of indels in disease, biology, and evolution. Here we present a library generation method, DIMPLE, that generates deletions, insertions, and missense at similar frequencies within any gene. To benchmark DIMPLE, we generated libraries within four genes (Kir2.1, VatD, TRPV1, and OPRM1) of varying length and evolutionary origin. DIMPLE produces libraries that are near complete, low cost, and low bias. We measured how missense mutations and indels of varying length impact the potassium channel Kir2.1 surface expression. Across all Kir2.1s secondary structure, deletions are more disruptive than insertions, beta sheets are extremely sensitive to large deletions, and flexible loops allow insertions far more frequently than deletions. DIMPLEs low bias, ease of use, and low cost will enable high throughput probing of the importance of indels in disease and evolution.

genomics↗

bioRxiv2022

Structure-based inhibitor optimization for the Nsp3 Macrodomain of SARS-CoV-2

The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 152 Mac1-ligand complex crystal structures were determined, typically to 1 [A] resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated protein dynamics within the active site, and key inhibitor motifs that will template future drug development against Mac1. Significance StatementSARS-CoV-2 encodes a viral macrodomain protein (Mac1) that hydrolyzes ribo-adenylate marks on viral proteins, disrupting the innate immune response to the virus. Catalytic mutations in the enzyme make the related SARS-1 virus less pathogenic and non-lethal in animals, suggesting that Mac1 will be a good antiviral target. However, no potent inhibitors of this protein class have been described, and pharmacologically the enzyme remains an orphan. Here, we computationally designed potent inhibitors of Mac1, determining 150 inhibitor-enzyme structures to ultra-high resolution by crystallography. In silico fragment linking and molecular docking of > 450 million virtual compounds led to inhibitors with submicromolar activity. These molecules may template future drug discovery efforts against this crucial but understudied viral target.

biophysics↗

bioRxiv2022

Mapping Protein Dynamics at High-Resolution with Temperature-Jump X-ray Crystallography

Understanding and controlling protein motion at atomic resolution is a hallmark challenge for structural biologists and protein engineers because conformational dynamics are essential for complex functions such as enzyme catalysis and allosteric regulation. Time-resolved crystallography offers a window into protein motions, yet without a universal perturbation to initiate conformational changes the method has been limited in scope. Here we couple a solvent-based temperature jump with time-resolved crystallography to visualize structural motions in lysozyme, a dynamic enzyme. We observed widespread atomic vibrations on the nanosecond timescale, which evolve on the sub-millisecond timescale into localized structural fluctuations that are coupled to the active site. An orthogonal perturbation to the enzyme, inhibitor binding, altered these dynamics by blocking key motions that allow energy to dissipate from vibrations into functional movements linked to the catalytic cycle. Because temperature-jump is a universal method for perturbing molecular motion, the method demonstrated here is broadly applicable for studying protein dynamics.

biophysics↗

bioRxiv2022

Of Problems and Opportunities - How to Treat and How to not Treat Crystallographic Fragment-Screening Data

In their recent commentary in Protein Science, Jaskolski et al. analyze three randomly picked diffraction data sets from fragment-screening group depositions from the PDB and, based on that, claim that such data are principally problematic. We demonstrate here that if such data are treated properly, none of the proclaimed criticisms persist.

scientific communication and education↗

bioRxiv2022

Molecular-Dynamics Simulation Methods for Macromolecular Crystallography

To assess the potential benefits of molecular-dynamics (MD) simulations for macromolecular crystallography (MX), we performed room-temperature X-ray diffraction studies of the catalytic subunit of mouse protein kinase A (PKA-C). We then performed crystalline MD simulations of PKA-C, computed simulated electron densities from the water, protein, and ion components of the MD simulations, and carefully compared them to the initial crystal structure. The results led to the development of an MD-MX analysis procedure and several associated methods: 1) density comparison to evaluate consistency between the MD and the initial crystal structure model; 2) water building to generate alternative solvent models; and 3) protein remodeling to improve the crystal structure where interpretation of density is unclear. This procedure produced a revised structure of PKA with a new ordered water model and a modified protein structure. The revisions yield new insights into PKA mechanisms, including: a sensitivity of the His294 conformation to protonation state, with potential consequences for regulation of substrate binding; a remodeling of the Lys217 side chain along with a bound phosphate; an alternative conformation for Lys213 associated with binding to the regulatory subunit; and an alternative conformation for catalytic base Asp166 and nearby waters, suggesting a mechanism of progression of the phosphotransfer reaction via changes in Mg2+ coordination. Based on the benefits seen applying these methods to PKA, we recommend incorporating our MD-MX procedure into MX studies, to decide among ambiguous interpretations of electron density that occur, inevitably, as part of standard model refinement.

biophysics↗

bioRxiv2022

The mechanisms of catalysis and ligand binding for the SARS-CoV-2 NSP3 macrodomain from neutron and X-ray diffraction at room temperature

The NSP3 macrodomain of SARS CoV 2 (Mac1) removes ADP-ribosylation post-translational modifications, playing a key role in the immune evasion capabilities of the virus responsible for the COVID-19 pandemic. Here, we determined neutron and X-ray crystal structures of the SARS-CoV-2 NSP3 macrodomain using multiple crystal forms, temperatures, and pHs, across the apo and ADP-ribose-bound states. We characterize extensive solvation in the Mac1 active site, and visualize how water networks reorganize upon binding of ADP-ribose and non-native ligands, inspiring strategies for displacing waters to increase potency of Mac1 inhibitors. Determining the precise orientations of active site water molecules and the protonation states of key catalytic site residues by neutron crystallography suggests a catalytic mechanism for coronavirus macrodomains distinct from the substrate-assisted mechanism proposed for human MacroD2. These data provoke a re-evaluation of macrodomain catalytic mechanisms and will guide the optimization of Mac1 inhibitors.

biochemistry↗

bioRxiv2021

Ligand binding remodels protein side chain conformational heterogeneity

While protein conformational heterogeneity plays an important role in many aspects of biological function, including ligand binding, its impact has been difficult to quantify. Macromolecular X-ray diffraction is commonly interpreted with a static structure, but it can provide information on both the anharmonic and harmonic contributions to conformational heterogeneity. Here, through multiconformer modeling of time- and space-averaged electron density, we measure conformational heterogeneity of 743 stringently matched pairs of crystallographic datasets that reflect unbound/apo and ligand-bound/holo states. When comparing the conformational heterogeneity of side chains, we observe that when binding site residues become more rigid upon ligand binding, distant residues tend to become more flexible, especially in non-solvent exposed regions. Among ligand properties, we observe increased protein flexibility as the number of hydrogen bonds decrease and relative hydrophobicity increases. Across a series of 13 inhibitor bound structures of CDK2, we find that conformational heterogeneity is correlated with inhibitor features and identify how conformational changes propagate differences in conformational heterogeneity away from the binding site. Collectively, our findings agree with models emerging from NMR studies suggesting that residual side chain entropy can modulate affinity and point to the need to integrate both static conformational changes and conformational heterogeneity in models of ligand binding.

biophysics↗

bioRxiv2021

Structural basis for context-specific inhibition of translation by oxazolidinone antibiotics

The antibiotic linezolid, the first clinically approved member of the oxazolidinone class, inhibits translation of bacterial ribosomes by binding to the peptidyl transferase center. Recent work has demonstrated that linezolid does not inhibit peptide bond formation at all sequences but rather acts in a context-specific manner, namely when alanine occupies the penultimate position of the nascent chain. In this study, we determined that the second-generation oxazolidinone radezolid also induces stalling with alanine at the penultimate position. However, the molecular basis for context-specificity of these inhibitors has not been elucidated. In this study, we determined high-resolution cryo-EM structures of both linezolid and radezolid-stalled ribosome complexes. These structures reveal that the alanine side chain fits within a small hydrophobic crevice created by oxazolidinone, resulting in improved ribosome binding. Modification of the ribosome by the antibiotic resistance enzyme Cfr disrupts stalling by forcing the antibiotic to adopt a conformation that narrows the hydrophobic alanine pocket. Together, the structural and biochemical findings presented in this work provide molecular understanding of context-specific inhibition of translation by clinically important oxazolidinone antibiotics.

biophysics↗

bioRxiv2021

Deep neural language modeling enables functional protein generation across families

Bypassing natures evolutionary trajectory, de novo protein generation--defined as creating artificial protein sequences from scratch--could enable breakthrough solutions for biomedical and environmental challenges. Viewing amino acid sequences as a language, we demonstrate that a deep learning-based language model can generate functional artificial protein sequences across families, akin to generating grammatically and semantically correct natural language sentences on diverse topics. Our protein language model is trained by simply learning to predict the next amino acid for over 280 million protein sequences from thousands of protein families, without biophysical or coevolutionary modeling. We experimentally evaluate model-generated artificial proteins on five distinct antibacterial lysozyme families. Artificial proteins show similar activities and catalytic efficiencies as representative natural lysozymes, including hen egg white lysozyme, while reaching as low as 44% identity to any known naturally-evolved protein. The X-ray crystal structure of an enzymatically active artificial protein recapitulates the conserved fold and positioning of active site residues found in natural proteins. We demonstrate our language models ability to be adapted to different protein families by accurately predicting the functionality of artificial chorismate mutase and malate dehydrogenase proteins. These results indicate that neural language models successfully perform de novo protein generation across protein families and may prove to be a tool to shortcut evolution.

synthetic biology↗

bioRxiv2021

Accurately positioning functional residues with robotics-inspired computational protein design

Accurate positioning of functional residues is critical for the design of new protein functions, but has remained difficult because of the prevalence of irregular local geometries in active sites. Here we introduce two computational methods that build local protein geometries from sequence with atomic accuracy: fragment kinematic closure (FKIC) and loophash kinematic closure (LHKIC). FKIC and LHKIC integrate two approaches: robotics-inspired kinematics of protein backbones and insertion of peptide fragments, and show up to 140-fold improvements in native-like predictions over either approach alone. We then integrate these methods into a new design protocol, pull-into-place (PIP), to position functionally important sidechains via design of new structured loop conformations. We validate PIP by remodeling a sizeable active site region in an enzyme and confirming the engineered new conformations of two designs with crystal structures. The described methods can be applied broadly to the design of many new protein geometries and functions.

bioengineering↗

bioRxiv2021

A counter-enzyme complex regulates glutamate metabolism in Bacillus subtilis

Multi-enzyme assemblies composed of metabolic enzymes catalyzing sequential reactions are being increasingly studied. Here, we report the discovery of a 1.6 megadalton multi-enzyme complex from Bacillus subtilis composed of two enzymes catalyzing opposite rather than sequential reactions ("counter-enzymes"): glutamate synthase (GltAB), and glutamate dehydrogenase (GudB), that make and break glutamate, respectively. In vivo and in vitro studies show that the primary role of complex formation is to inhibit GudBs activity as this enzyme is constitutively expressed including in glutamate-limiting conditions. Using cryo-electron microscopy, we elucidated the structure of the complex and the basis of GudBs inhibition. Finally, we show that this complex that exhibits unusual oscillatory progress curves is a necessity for planktonic growth in glutamate-limiting conditions, but is also essential for biofilm growth in glutamate-rich media, suggesting a regulatory role at fluctuating glutamate concentrations.

biochemistry↗

bioRxiv2021

Type 2 innate immunity regulates hair follicle homeostasis to control Demodex pathosymbionts

Allergic skin diseases are common, but basal roles for type 2 immunity in cutaneous homeostasis are incompletely understood. Here, we show that skin group 2 innate lymphoid cells (ILC2s) are the predominant resident cells that secretes IL-13, which attenuates epithelial cell proliferation during anagen throughout the hair follicle (HF), including in HF stem cells. Although HF are normal in the absence of type 2 immunity, colonization with the commensal mite, Demodex musculi, results in epithelial proliferation and aberrant hair follicle morphology accompanied by loss of stable commensalism with massive infestation and expansion of inflammatory ILC2s and other immune cells. Topical anti-parasitic agents, but not broad-spectrum antibiotics, reversed the phenotype. Commensal Demodex colonization of mammalian hair follicles is ubiquitous, including in humans, revealing an unanticipated role for ILC2s and type 2 immunity for skin homeostasis in the normal environment. One Sentence SummaryDynamic regulation of skin physiology by Type 2 innate immunity regulates healthy commensalism by parasitic Demodex mites.

immunology↗

bioRxiv2021

Directed evolution of the rRNA methylating enzyme Cfr reveals molecular basis of antibiotic resistance

Alteration of antibiotic binding sites through modification of ribosomal RNA (rRNA) is a common form of resistance to ribosome-targeting antibiotics. The rRNA-modifying enzyme Cfr methylates an adenosine nucleotide within the peptidyl transferase center, resulting in the C-8 methylation of A2503 (m8A2503). Acquisition of cfr results in resistance to eight classes of ribosome-targeting antibiotics. Despite the prevalence of this resistance mechanism, it is poorly understood whether and how bacteria modulate Cfr methylation to adapt to antibiotic pressure. Moreover, direct evidence for how m8A2503 alters antibiotic binding sites within the ribosome is lacking. In this study, we performed directed evolution of Cfr under antibiotic selection to generate Cfr variants that confer increased resistance by enhancing methylation of A2503 in cells. Increased rRNA methylation is achieved by improved expression and stability of Cfr through transcriptional and post-transcriptional mechanisms, which may be exploited by pathogens under antibiotic stress as suggested by natural isolates. Using a variant which achieves near-stoichiometric methylation of rRNA, we determined a 2.2 [A] cryo-EM structure of the Cfr-modified ribosome. Our structure reveals the molecular basis for broad resistance to antibiotics and will inform the design of new antibiotics that overcome resistance mediated by Cfr.

biochemistry↗

bioRxiv2020

qFit 3: Protein and ligand multiconformer modeling for X-ray crystallographic and single-particle cryo-EM density maps

New X-ray crystallography and cryo-electron microscopy (cryo-EM) approaches yield vast amounts of structural data from dynamic proteins and their complexes. Modeling the full conformational ensemble can provide important biological insights, but identifying and modeling an internally consistent set of alternate conformations remains a formidable challenge. qFit efficiently automates this process by generating a parsimonious multiconformer model. We refactored qFit from a distributed application into software that runs efficiently on a small server, desktop, or laptop. We describe the new qFit 3 software and provide some examples. qFit 3 is open-source under the MIT license, and is available at https://github.com/ExcitedStates/qfit-3.0.

biophysics↗

bioRxiv2020

Outcomes of the 2019 EMDataResource model challenge: validation of cryo-EM models at near-atomic resolution

This paper describes outcomes of the 2019 Cryo-EM Map-based Model Metrics Challenge sponsored by EMDataResource (www.emdataresource.org). The goals of this challenge were (1) to assess the quality of models that can be produced using current modeling software, (2) to check the reproducibility of modeling results from different software developers and users, and (3) compare the performance of current metrics used for evaluation of models. The focus was on near-atomic resolution maps with an innovative twist: three of four target maps formed a resolution series (1.8 to 3.1 [A]) from the same specimen and imaging experiment. Tools developed in previous challenges were expanded for managing, visualizing and analyzing the 63 submitted coordinate models, and several novel metrics were introduced. The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual laboratory experiments and holdings of structure data archives such as the Protein Data Bank. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived from these benchmark maps by 13 participating teams, representing both widely used and novel modeling approaches. We also evaluate the pros and cons of the commonly used metrics to assess model quality and recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed density in the cryo-EM map.

biochemistry↗

bioRxiv2020

Expanding the space of protein geometries by computational design of de novo fold families

Naturally occurring proteins use a limited set of fold topologies, but vary the precise geometries of structural elements to create distinct shapes optimal for function. Here we present a computational design method termed LUCS that mimics natures ability to create families of proteins with the same overall fold but precisely tunable geometries. Through near-exhaustive sampling of loop-helix-loop elements, LUCS generates highly diverse geometries encompassing those found in nature but also surpassing known structure space. Biophysical characterization shows that 17 (38%) out of 45 tested LUCS designs were well folded, including 16 with designed non-native geometries. Four experimentally solved structures closely match the designs. LUCS greatly expands the designable structure space and provides a new paradigm for designing proteins with tunable geometries customizable for novel functions. One Sentence SummaryA computational method to systematically sample loop-helix-loop geometries expands the structure space of designer proteins.

bioengineering↗