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1.
Proc Natl Acad Sci U S A ; 118(36)2021 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-34413211

RESUMO

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Traditional drug discovery methods have a >90% failure rate and can take 10 to 15 y from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious agents against SARS-CoV-2. From a library of 1,425 US Food and Drug Administration (FDA)-approved compounds and clinical candidates, we identified 17 hits that inhibited SARS-CoV-2 infection and analyzed their antiviral activity across multiple cell lines, including lymph node carcinoma of the prostate (LNCaP) cells and a physiologically relevant model of alveolar epithelial type 2 cells (iAEC2s). Additionally, we found that inhibitors of the Ras/Raf/MEK/ERK signaling pathway exacerbate SARS-CoV-2 infection in vitro. Notably, we discovered that lactoferrin, a glycoprotein found in secretory fluids including mammalian milk, inhibits SARS-CoV-2 infection in the nanomolar range in all cell models with multiple modes of action, including blockage of virus attachment to cellular heparan sulfate and enhancement of interferon responses. Given its safety profile, lactoferrin is a readily translatable therapeutic option for the management of COVID-19.


Assuntos
Antivirais/farmacologia , Fatores Imunológicos/farmacologia , Lactoferrina/farmacologia , SARS-CoV-2/efeitos dos fármacos , Internalização do Vírus/efeitos dos fármacos , Replicação Viral/efeitos dos fármacos , Animais , COVID-19/tratamento farmacológico , COVID-19/imunologia , COVID-19/prevenção & controle , COVID-19/virologia , Células CACO-2 , Linhagem Celular Tumoral , Chlorocebus aethiops , Relação Dose-Resposta a Droga , Descoberta de Drogas , Reposicionamento de Medicamentos/métodos , Células Epiteliais , Heparitina Sulfato/antagonistas & inibidores , Heparitina Sulfato/imunologia , Heparitina Sulfato/metabolismo , Hepatócitos , Ensaios de Triagem em Larga Escala , Humanos , SARS-CoV-2/crescimento & desenvolvimento , SARS-CoV-2/patogenicidade , Células Vero
2.
Science ; 373(6554): 541-547, 2021 07 30.
Artigo em Inglês | MEDLINE | ID: mdl-34326236

RESUMO

Repurposing drugs as treatments for COVID-19, the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has drawn much attention. Beginning with sigma receptor ligands and expanding to other drugs from screening in the field, we became concerned that phospholipidosis was a shared mechanism underlying the antiviral activity of many repurposed drugs. For all of the 23 cationic amphiphilic drugs we tested, including hydroxychloroquine, azithromycin, amiodarone, and four others already in clinical trials, phospholipidosis was monotonically correlated with antiviral efficacy. Conversely, drugs active against the same targets that did not induce phospholipidosis were not antiviral. Phospholipidosis depends on the physicochemical properties of drugs and does not reflect specific target-based activities-rather, it may be considered a toxic confound in early drug discovery. Early detection of phospholipidosis could eliminate these artifacts, enabling a focus on molecules with therapeutic potential.


Assuntos
Antivirais/farmacologia , COVID-19/tratamento farmacológico , Reposicionamento de Medicamentos , Lipidoses/induzido quimicamente , Fosfolipídeos/metabolismo , SARS-CoV-2/efeitos dos fármacos , Células A549 , Animais , Antivirais/química , Antivirais/uso terapêutico , Antivirais/toxicidade , COVID-19/virologia , Cátions , Chlorocebus aethiops , Relação Dose-Resposta a Droga , Feminino , Humanos , Camundongos , Testes de Sensibilidade Microbiana , SARS-CoV-2/fisiologia , Tensoativos/química , Tensoativos/farmacologia , Tensoativos/toxicidade , Células Vero , Replicação Viral/efeitos dos fármacos
3.
Mol Biol Cell ; 32(18): 1624-1633, 2021 08 19.
Artigo em Inglês | MEDLINE | ID: mdl-33909457

RESUMO

Histone deacetylase inhibitors, such as valproic acid (VPA), have important clinical therapeutic and cellular reprogramming applications. They induce chromatin reorganization that is associated with altered cellular morphology. However, there is a lack of comprehensive characterization of VPA-induced changes of nuclear size and shape. Here, we quantify 3D nuclear morphology of primary human astrocyte cells treated with VPA over time (hence, 4D). We compared volumetric and surface-based representations and identified seven features that jointly discriminate between normal and treated cells with 85% accuracy on day 7. From day 3, treated nuclei were more elongated and flattened and then continued to morphologically diverge from controls over time, becoming larger and more irregular. On day 7, most of the size and shape descriptors demonstrated significant differences between treated and untreated cells, including a 24% increase in volume and 6% reduction in extent (shape regularity) for treated nuclei. Overall, we show that 4D morphometry can capture how chromatin reorganization modulates the size and shape of the nucleus over time. These nuclear structural alterations may serve as a biomarker for histone (de-)acetylation events and provide insights into mechanisms of astrocytes-to-neurons reprogramming.

4.
bioRxiv ; 2021 Mar 24.
Artigo em Inglês | MEDLINE | ID: mdl-33791693

RESUMO

Repurposing drugs as treatments for COVID-19 has drawn much attention. A common strategy has been to screen for established drugs, typically developed for other indications, that are antiviral in cells or organisms. Intriguingly, most of the drugs that have emerged from these campaigns, though diverse in structure, share a common physical property: cationic amphiphilicity. Provoked by the similarity of these repurposed drugs to those inducing phospholipidosis, a well-known drug side effect, we investigated phospholipidosis as a mechanism for antiviral activity. We tested 23 cationic amphiphilic drugs-including those from phenotypic screens and others that we ourselves had found-for induction of phospholipidosis in cell culture. We found that most of the repurposed drugs, which included hydroxychloroquine, azithromycin, amiodarone, and four others that have already progressed to clinical trials, induced phospholipidosis in the same concentration range as their antiviral activity; indeed, there was a strong monotonic correlation between antiviral efficacy and the magnitude of the phospholipidosis. Conversely, drugs active against the same targets that did not induce phospholipidosis were not antiviral. Phospholipidosis depends on the gross physical properties of drugs, and does not reflect specific target-based activities, rather it may be considered a confound in early drug discovery. Understanding its role in infection, and detecting its effects rapidly, will allow the community to better distinguish between drugs and lead compounds that more directly impact COVID-19 from the large proportion of molecules that manifest this confounding effect, saving much time, effort and cost. One Sentence Summary: Drug-induced phospholipidosis is a single mechanism that may explain the in vitro efficacy of a wide-variety of therapeutics repurposed for COVID-19.

5.
mSphere ; 6(1)2021 01 20.
Artigo em Inglês | MEDLINE | ID: mdl-33472984

RESUMO

Functional characterization of open reading frames in nonmodel organisms, such as the common opportunistic fungal pathogen Candida albicans, can be labor-intensive. To meet this challenge, we built a comprehensive and unbiased coexpression network for C. albicans, which we call CalCEN, from data collected from 853 RNA sequencing runs from 18 large-scale studies deposited in the NCBI Sequence Read Archive. Retrospectively, CalCEN is highly predictive of known gene function annotations and can be synergistically combined with sequence similarity and interaction networks in Saccharomyces cerevisiae through orthology for additional accuracy in gene function prediction. To prospectively demonstrate the utility of the coexpression network in C. albicans, we predicted the function of underannotated open reading frames (ORFs) and identified CCJ1 as a novel cell cycle regulator in C. albicans This study provides a tool for future systems biology analyses of gene function in C. albicans We provide a computational pipeline for building and analyzing the coexpression network and CalCEN itself at http://github.com/momeara/CalCENIMPORTANCE Candida albicans is a common and deadly fungal pathogen of humans, yet the genome of this organism contains many genes of unknown function. By determining gene function, we can help identify essential genes, new virulence factors, or new regulators of drug resistance, and thereby give new targets for antifungal development. Here, we use information from large-scale RNA sequencing (RNAseq) studies and generate a C. albicans coexpression network (CalCEN) that is robust and able to predict gene function. We demonstrate the utility of this network in both retrospective and prospective testing and use CalCEN to predict a role for C4_06590W/CCJ1 in cell cycle. This tool will allow for a better characterization of underannotated genes in pathogenic yeasts.


Assuntos
Candida albicans/genética , Proteínas Fúngicas/genética , Expressão Gênica , Genes Fúngicos , Fases de Leitura Aberta , Candida albicans/patogenicidade , Ciclo Celular/genética , Genoma Fúngico , Estudos Prospectivos , Estudos Retrospectivos , Saccharomyces cerevisiae/genética , Análise de Sequência de RNA
6.
Science ; 370(6521)2020 12 04.
Artigo em Inglês | MEDLINE | ID: mdl-33060197

RESUMO

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a grave threat to public health and the global economy. SARS-CoV-2 is closely related to the more lethal but less transmissible coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Here, we have carried out comparative viral-human protein-protein interaction and viral protein localization analyses for all three viruses. Subsequent functional genetic screening identified host factors that functionally impinge on coronavirus proliferation, including Tom70, a mitochondrial chaperone protein that interacts with both SARS-CoV-1 and SARS-CoV-2 ORF9b, an interaction we structurally characterized using cryo-electron microscopy. Combining genetically validated host factors with both COVID-19 patient genetic data and medical billing records identified molecular mechanisms and potential drug treatments that merit further molecular and clinical study.


Assuntos
COVID-19/metabolismo , Proteínas do Nucleocapsídeo de Coronavírus/metabolismo , Interações entre Hospedeiro e Microrganismos , Proteínas de Transporte da Membrana Mitocondrial/metabolismo , Mapas de Interação de Proteínas , Vírus da SARS/metabolismo , SARS-CoV-2/metabolismo , Síndrome Respiratória Aguda Grave/metabolismo , Sequência Conservada , Proteínas do Nucleocapsídeo de Coronavírus/genética , Microscopia Crioeletrônica , Humanos , Proteínas de Transporte da Membrana Mitocondrial/genética , Fosfoproteínas/genética , Fosfoproteínas/metabolismo , Conformação Proteica
7.
Sci Adv ; 6(34): eabc6378, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32875119

RESUMO

Maintaining biocatalyst stability and activity is a critical challenge. Chondroitinase ABC (ChABC) has shown promise in central nervous system (CNS) regeneration, yet its therapeutic utility is severely limited by instability. We computationally reengineered ChABC by introducing 37, 55, and 92 amino acid changes using consensus design and forcefield-based optimization. All mutants were more stable than wild-type ChABC with increased aggregation temperatures between 4° and 8°C. Only ChABC with 37 mutations (ChABC-37) was more active and had a 6.5 times greater half-life than wild-type ChABC, increasing to 106 hours (4.4 days) from only 16.8 hours. ChABC-37, expressed as a fusion protein with Src homology 3 (ChABC-37-SH3), was active for 7 days when released from a hydrogel modified with SH3-binding peptides. This study demonstrates the broad opportunity to improve biocatalysts through computational engineering and sets the stage for future testing of this substantially improved protein in the treatment of debilitating CNS injuries.

8.
bioRxiv ; 2020 Jun 10.
Artigo em Inglês | MEDLINE | ID: mdl-32577649

RESUMO

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly translated to clinical care. Unfortunately, traditional drug discovery methods have a >90% failure rate and can take 10-15 years from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious single agents and combination therapies against SARS-CoV-2. Quantitative high-content morphological profiling was coupled with an AI-based machine learning strategy to classify features of cells for infection and stress. This assay detected multiple antiviral mechanisms of action (MOA), including inhibition of viral entry, propagation, and modulation of host cellular responses. From a library of 1,425 FDA-approved compounds and clinical candidates, we identified 16 dose-responsive compounds with antiviral effects. In particular, we discovered that lactoferrin is an effective inhibitor of SARS-CoV-2 infection with an IC50 of 308 nM and that it potentiates the efficacy of both remdesivir and hydroxychloroquine. Lactoferrin also stimulates an antiviral host cell response and retains inhibitory activity in iPSC-derived alveolar epithelial cells, a model for the primary site of infection. Given its safety profile in humans, these data suggest that lactoferrin is a readily translatable therapeutic adjunct for COVID-19. Additionally, several commonly prescribed drugs were found to exacerbate viral infection and warrant clinical investigation. We conclude that morphological profiling for drug repurposing is an effective strategy for the selection and optimization of drugs and drug combinations as viable therapeutic options for COVID-19 pandemic and other emerging infectious diseases.

9.
bioRxiv ; 2020 Mar 22.
Artigo em Inglês | MEDLINE | ID: mdl-32511329

RESUMO

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity- purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

10.
Nature ; 583(7816): 459-468, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32353859

RESUMO

A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein-protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.


Assuntos
Betacoronavirus/efeitos dos fármacos , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/metabolismo , Reposicionamento de Medicamentos , Terapia de Alvo Molecular , Pneumonia Viral/tratamento farmacológico , Pneumonia Viral/metabolismo , Mapas de Interação de Proteínas , Proteínas Virais/metabolismo , Animais , Antivirais/classificação , Antivirais/farmacologia , Betacoronavirus/genética , Betacoronavirus/metabolismo , Betacoronavirus/patogenicidade , COVID-19 , Chlorocebus aethiops , Clonagem Molecular , Infecções por Coronavirus/imunologia , Infecções por Coronavirus/virologia , Avaliação Pré-Clínica de Medicamentos , Células HEK293 , Interações Hospedeiro-Patógeno/efeitos dos fármacos , Humanos , Imunidade Inata , Espectrometria de Massas , Pandemias , Pneumonia Viral/imunologia , Pneumonia Viral/virologia , Ligação Proteica , Biossíntese de Proteínas/efeitos dos fármacos , Domínios Proteicos , Mapeamento de Interação de Proteínas , Receptores sigma/metabolismo , SARS-CoV-2 , Proteínas Ligases SKP Culina F-Box/metabolismo , Células Vero , Proteínas Virais/genética
11.
PLoS Biol ; 17(7): e3000358, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31283755

RESUMO

Hsp90 is a conserved molecular chaperone that assists in the folding and function of diverse cellular regulators, with a profound impact on biology, disease, and evolution. As a central hub of protein interaction networks, Hsp90 engages with hundreds of protein-protein interactions within eukaryotic cells. These interactions include client proteins, which physically interact with Hsp90 and depend on the chaperone for stability or function, as well as co-chaperones and partner proteins that modulate chaperone function. Currently, there are no methods to accurately predict Hsp90 interactors and there has been considerable network rewiring over evolutionary time, necessitating experimental approaches to define the Hsp90 network in the species of interest. This is a pressing challenge for fungal pathogens, for which Hsp90 is a key regulator of stress tolerance, drug resistance, and virulence traits. To address this challenge, we applied a novel biochemical fractionation and quantitative proteomic approach to examine alterations to the proteome upon perturbation of Hsp90 in a leading human fungal pathogen, Candida albicans. In parallel, we performed affinity purification coupled to mass spectrometry to define physical interacting partners for Hsp90 and the Hsp90 co-chaperones and identified 164 Hsp90-interacting proteins, including 111 that are specific to the pathogen. We performed the first analysis of the Hsp90 interactome upon antifungal drug stress and demonstrated that Hsp90 stabilizes processing body (P-body) and stress granule proteins that contribute to drug tolerance. We also describe novel roles for Hsp90 in regulating posttranslational modification of the Rvb1-Rvb2-Tah1-Pih1 (R2TP) complex and the formation of protein aggregates in response to thermal stress. This study provides a global view of the Hsp90 interactome in a fungal pathogen, demonstrates the dynamic role of Hsp90 in response to environmental perturbations, and highlights a novel connection between Hsp90 and the regulation of mRNA-associated protein granules.


Assuntos
Candida albicans/metabolismo , Proteínas Fúngicas/metabolismo , Proteínas de Choque Térmico HSP90/metabolismo , Chaperonas Moleculares/metabolismo , Proteômica/métodos , Candida albicans/genética , Candida albicans/patogenicidade , Candidíase/microbiologia , Proteínas Fúngicas/genética , Redes Reguladoras de Genes , Proteínas de Fluorescência Verde/genética , Proteínas de Fluorescência Verde/metabolismo , Proteínas de Choque Térmico HSP90/genética , Humanos , Microscopia Confocal , Chaperonas Moleculares/genética , Complexos Multiproteicos/genética , Complexos Multiproteicos/metabolismo , Ligação Proteica , Proteoma/genética , Proteoma/metabolismo , Virulência/genética
12.
Nature ; 566(7743): 224-229, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30728502

RESUMO

Despite intense interest in expanding chemical space, libraries containing hundreds-of-millions to billions of diverse molecules have remained inaccessible. Here we investigate structure-based docking of 170 million make-on-demand compounds from 130 well-characterized reactions. The resulting library is diverse, representing over 10.7 million scaffolds that are otherwise unavailable. For each compound in the library, docking against AmpC ß-lactamase (AmpC) and the D4 dopamine receptor were simulated. From the top-ranking molecules, 44 and 549 compounds were synthesized and tested for interactions with AmpC and the D4 dopamine receptor, respectively. We found a phenolate inhibitor of AmpC, which revealed a group of inhibitors without known precedent. This molecule was optimized to 77 nM, which places it among the most potent non-covalent AmpC inhibitors known. Crystal structures of this and other AmpC inhibitors confirmed the docking predictions. Against the D4 dopamine receptor, hit rates fell almost monotonically with docking score, and a hit-rate versus score curve predicted that the library contained 453,000 ligands for the D4 dopamine receptor. Of 81 new chemotypes discovered, 30 showed submicromolar activity, including a 180-pM subtype-selective agonist of the D4 dopamine receptor.


Assuntos
Agonistas de Dopamina/química , Agonistas de Dopamina/isolamento & purificação , Simulação de Acoplamento Molecular/métodos , Bibliotecas de Moléculas Pequenas/química , Bibliotecas de Moléculas Pequenas/isolamento & purificação , Inibidores de beta-Lactamases/química , Inibidores de beta-Lactamases/isolamento & purificação , Proteínas de Bactérias/antagonistas & inibidores , Proteínas de Bactérias/química , Cristalografia por Raios X , Humanos , Ligantes , Aprendizado de Máquina , Observação , Receptores de Dopamina D4/agonistas , Receptores de Dopamina D4/química , Receptores de Dopamina D4/metabolismo , beta-Lactamases/química
13.
J Control Release ; 297: 14-25, 2019 03 10.
Artigo em Inglês | MEDLINE | ID: mdl-30690102

RESUMO

Central nervous system (CNS) injuries, such as stroke and spinal cord injuries, result in the formation of a proteoglycan-rich glial scar, which acts as a barrier to axonal regrowth and limits the regenerative capacity of the CNS. Chondroitinase ABC (ChABC) is a potent bacterial enzyme that degrades the chondroitin sulfate proteoglycan (CSPG) component of the glial scar and promotes tissue recovery; however, its use is significantly limited by its inherent instability at physiological temperatures. Here, we demonstrate that ChABC can be stabilized using site-directed mutagenesis and covalent modification with poly(ethylene glycol) chains (i.e. PEGylation). Rosetta protein structure modeling was used to screen >20,000 single point mutations, and four potentially stabilizing mutations were tested in vitro. One of the mutations, N1000G (asparagine ➔ glycine at residue 1000), significantly improved the long-term activity of the protein, doubling its functional half-life. PEGylation of this ChABC mutant inhibited unfolding and aggregation and resulted in prolonged bioactivity with a 10-fold increase in activity compared to the unmodified protein after two days. Local, affinity-controlled release of the modified protein (PEG-N1000G-ChABC) was achieved by expressing it as a fusion protein with Src homology 3 (SH3) and delivering the protein from a methylcellulose hydrogel modified with SH3 binding peptides. This affinity-based release strategy provided sustained PEG-N1000G-ChABC-SH3 release over several days in vitro. Direct implantation of the hydrogel delivery vehicle containing stabilized PEG-N1000G-ChABC-SH3 onto the rat brain cortex in a sub-acute model of stroke resulted in significantly reduced CSPG levels in the penumbra of 49% at 14 and 40% at 28 days post-injury compared to animals treated with the vehicle alone.


Assuntos
Condroitina ABC Liase/química , Condroitina ABC Liase/metabolismo , Proteoglicanas de Sulfatos de Condroitina/metabolismo , Nanocápsulas/química , Regeneração Nervosa/efeitos dos fármacos , Polietilenoglicóis/química , Acidente Vascular Cerebral/metabolismo , Animais , Axônios/metabolismo , Encéfalo/efeitos dos fármacos , Condroitina ABC Liase/genética , Proteoglicanas de Sulfatos de Condroitina/efeitos dos fármacos , Liberação Controlada de Fármacos , Masculino , Mutagênese/efeitos dos fármacos , Proteínas Mutantes/genética , Proteínas Mutantes/metabolismo , Neuroglia/metabolismo , Proteus vulgaris/enzimologia , Ratos , Ratos Sprague-Dawley , Proteínas Recombinantes de Fusão/genética , Proteínas Recombinantes de Fusão/metabolismo , Domínios de Homologia de src
14.
mBio ; 9(4)2018 08 21.
Artigo em Inglês | MEDLINE | ID: mdl-30131363

RESUMO

The innate immune system is the first line of defense against invasive fungal infections. As a consequence, many successful fungal pathogens have evolved elegant strategies to interact with host immune cells. For example, Candida albicans undergoes a morphogenetic switch coupled to cell wall remodeling upon phagocytosis by macrophages and then induces macrophage pyroptosis, an inflammatory cell death program. To elucidate the genetic circuitry through which C. albicans orchestrates this host response, we performed the first large-scale analysis of C. albicans interactions with mammalian immune cells. We identified 98 C. albicans genes that enable macrophage pyroptosis without influencing fungal cell morphology in the macrophage, including specific determinants of cell wall biogenesis and the Hog1 signaling cascade. Using these mutated genes, we discovered that defects in the activation of pyroptosis affect immune cell recruitment during infection. Examining host circuitry required for pyroptosis in response to C. albicans infection, we discovered that inflammasome priming and activation can be decoupled. Finally, we observed that apoptosis-associated speck-like protein containing a CARD (ASC) oligomerization can occur prior to phagolysosomal rupture by C. albicans hyphae, demonstrating that phagolysosomal rupture is not the inflammasome activating signal. Taking the data together, this work defines genes that enable fungal cell wall remodeling and activation of macrophage pyroptosis independently of effects on morphogenesis and identifies macrophage signaling components that are required for pyroptosis in response to C. albicans infection.IMPORTANCECandida albicans is a natural member of the human mucosal microbiota that can also cause superficial infections and life-threatening systemic infections, both of which are characterized by inflammation. Host defense relies mainly on the ingestion and destruction of C. albicans by innate immune cells, such as macrophages and neutrophils. Although some C. albicans cells are killed by macrophages, most undergo a morphological change and escape by inducing macrophage pyroptosis. Here, we investigated the C. albicans genes and host factors that promote macrophage pyroptosis in response to intracellular fungi. This work provides a foundation for understanding how host immune cells interact with C. albicans and may lead to effective strategies to modulate inflammation induced by fungal infections.


Assuntos
Candida albicans/genética , Genes Fúngicos , Interações Hospedeiro-Patógeno , Macrófagos/microbiologia , Piroptose , Animais , Candida albicans/patogenicidade , Feminino , Ensaios de Triagem em Larga Escala , Evasão da Resposta Imune , Macrófagos/patologia , Camundongos , Camundongos Endogâmicos C57BL , Fagocitose
15.
Elife ; 72018 01 29.
Artigo em Inglês | MEDLINE | ID: mdl-29377793

RESUMO

The functions of most proteins are yet to be determined. The function of an enzyme is often defined by its interacting partners, including its substrate and product, and its role in larger metabolic networks. Here, we describe a computational method that predicts the functions of orphan enzymes by organizing them into a linear metabolic pathway. Given candidate enzyme and metabolite pathway members, this aim is achieved by finding those pathways that satisfy structural and network restraints implied by varied input information, including that from virtual screening, chemoinformatics, genomic context analysis, and ligand -binding experiments. We demonstrate this integrative pathway mapping method by predicting the L-gulonate catabolic pathway in Haemophilus influenzae Rd KW20. The prediction was subsequently validated experimentally by enzymology, crystallography, and metabolomics. Integrative pathway mapping by satisfaction of structural and network restraints is extensible to molecular networks in general and thus formally bridges the gap between structural biology and systems biology.


Assuntos
Biologia Computacional/métodos , Enzimas/genética , Enzimas/metabolismo , Haemophilus influenzae/genética , Haemophilus influenzae/metabolismo , Redes e Vias Metabólicas/genética , Biologia de Sistemas/métodos
16.
J Chem Theory Comput ; 13(6): 3031-3048, 2017 Jun 13.
Artigo em Inglês | MEDLINE | ID: mdl-28430426

RESUMO

Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta's success is the energy function: a model parametrized from small-molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, called the Rosetta Energy Function 2015 (REF15). Applying these concepts, we explain how to use Rosetta energies to identify and analyze the features of biomolecular models. Finally, we discuss the latest advances in the energy function that extend its capabilities from soluble proteins to also include membrane proteins, peptides containing noncanonical amino acids, small molecules, carbohydrates, nucleic acids, and other macromolecules.


Assuntos
Substâncias Macromoleculares/química , Simulação de Dinâmica Molecular , Protease de HIV/química , Protease de HIV/genética , Protease de HIV/metabolismo , Substâncias Macromoleculares/metabolismo , Mutação , Conformação Proteica , Eletricidade Estática , Termodinâmica
17.
PLoS One ; 11(7): e0160098, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27467773

RESUMO

The expansion of protein-ligand annotation databases has enabled large-scale networking of proteins by ligand similarity. These ligand-based protein networks, which implicitly predict the ability of neighboring proteins to bind related ligands, may complement biologically-oriented gene networks, which are used to predict functional or disease relevance. To quantify the degree to which such ligand-based protein associations might complement functional genomic associations, including sequence similarity, physical protein-protein interactions, co-expression, and disease gene annotations, we calculated a network based on the Similarity Ensemble Approach (SEA: sea.docking.org), where protein neighbors reflect the similarity of their ligands. We also measured the similarity with functional genomic networks over a common set of 1,131 genes, and found that the networks had only small overlaps, which were significant only due to the large scale of the data. Consistent with the view that the networks contain different information, combining them substantially improved Molecular Function prediction within GO (from AUROC~0.63-0.75 for the individual data modalities to AUROC~0.8 in the aggregate). We investigated the boost in guilt-by-association gene function prediction when the networks are combined and describe underlying properties that can be further exploited.


Assuntos
Bases de Dados de Proteínas , Redes Reguladoras de Genes , Ligantes
18.
ACS Chem Biol ; 10(12): 2772-84, 2015 Dec 18.
Artigo em Inglês | MEDLINE | ID: mdl-26421501

RESUMO

The binding of drugs and reagents to off-targets is well-known. Whereas many off-targets are related to the primary target by sequence and fold, many ligands bind to unrelated pairs of proteins, and these are harder to anticipate. If the binding site in the off-target can be related to that of the primary target, this challenge resolves into aligning the two pockets. However, other cases are possible: the ligand might interact with entirely different residues and environments in the off-target, or wholly different ligand atoms may be implicated in the two complexes. To investigate these scenarios at atomic resolution, the structures of 59 ligands in 116 complexes (62 pairs in total), where the protein pairs were unrelated by fold but bound an identical ligand, were examined. In almost half of the pairs, the ligand interacted with unrelated residues in the two proteins (29 pairs), and in 14 of the pairs wholly different ligand moieties were implicated in each complex. Even in those 19 pairs of complexes that presented similar environments to the ligand, ligand superposition rarely resulted in the overlap of related residues. There appears to be no single pattern-matching "code" for identifying binding sites in unrelated proteins that bind identical ligands, though modeling suggests that there might be a limited number of different patterns that suffice to recognize different ligand functional groups.


Assuntos
Proteínas/metabolismo , Sítios de Ligação , Complexos de Coordenação/metabolismo , Ligantes , Conformação Proteica , Dobramento de Proteína
19.
PLoS One ; 10(9): e0130433, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26335248

RESUMO

The development and validation of computational macromolecular modeling and design methods depend on suitable benchmark datasets and informative metrics for comparing protocols. In addition, if a method is intended to be adopted broadly in diverse biological applications, there needs to be information on appropriate parameters for each protocol, as well as metrics describing the expected accuracy compared to experimental data. In certain disciplines, there exist established benchmarks and public resources where experts in a particular methodology are encouraged to supply their most efficient implementation of each particular benchmark. We aim to provide such a resource for protocols in macromolecular modeling and design. We present a freely accessible web resource (https://kortemmelab.ucsf.edu/benchmarks) to guide the development of protocols for protein modeling and design. The site provides benchmark datasets and metrics to compare the performance of a variety of modeling protocols using different computational sampling methods and energy functions, providing a "best practice" set of parameters for each method. Each benchmark has an associated downloadable benchmark capture archive containing the input files, analysis scripts, and tutorials for running the benchmark. The captures may be run with any suitable modeling method; we supply command lines for running the benchmarks using the Rosetta software suite. We have compiled initial benchmarks for the resource spanning three key areas: prediction of energetic effects of mutations, protein design, and protein structure prediction, each with associated state-of-the-art modeling protocols. With the help of the wider macromolecular modeling community, we hope to expand the variety of benchmarks included on the website and continue to evaluate new iterations of current methods as they become available.


Assuntos
Benchmarking , Conjuntos de Dados como Assunto , Internet , Modelos Moleculares , Proteínas/química , Aminoácidos/química , Evolução Química , Mutação , Proteínas/genética , Termodinâmica
20.
J Chem Theory Comput ; 11(2): 609-22, 2015 Feb 10.
Artigo em Inglês | MEDLINE | ID: mdl-25866491

RESUMO

Interactions between polar atoms are challenging to model because at very short ranges they form hydrogen bonds (H-bonds) that are partially covalent in character and exhibit strong orientation preferences; at longer ranges the orientation preferences are lost, but significant electrostatic interactions between charged and partially charged atoms remain. To simultaneously model these two types of behavior, we refined an orientation dependent model of hydrogen bonds [Kortemme et al. J. Mol. Biol. 2003, 326, 1239] used by the molecular modeling program Rosetta and then combined it with a distance-dependent Coulomb model of electrostatics. The functional form of the H-bond potential is physically motivated and parameters are fit so that H-bond geometries that Rosetta generates closely resemble H-bond geometries in high-resolution crystal structures. The combined potentials improve performance in a variety of scientific benchmarks including decoy discrimination, side chain prediction, and native sequence recovery in protein design simulations and establishes a new standard energy function for Rosetta.


Assuntos
Modelos Químicos , Modelos Moleculares , Software , Eletricidade Estática , Ligação de Hidrogênio , Estrutura Molecular
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