RESUMO
Protein-protein interactions (PPIs) are ubiquitous biomolecular processes that are central to virtually all aspects of cellular function. Identifying small molecules that modulate specific disease-related PPIs is a strategy with enormous promise for drug discovery. The design of drugs to disrupt PPIs is challenging, however, because many potential drug-binding sites at PPI interfaces are "cryptic": When unoccupied by a ligand, cryptic sites are often flat and featureless, and thus not readily recognizable in crystal structures, with the geometric and chemical characteristics of typical small-molecule binding sites only emerging upon ligand binding. The rational design of small molecules to inhibit specific PPIs would benefit from a better understanding of how such molecules bind at PPI interfaces. To this end, we have conducted unbiased, all-atom MD simulations of the binding of four small-molecule inhibitors (SP4206 and three SP4206 analogs) to interleukin 2 (IL2)-which performs its function by forming a PPI with its receptor-without incorporating any prior structural information about the ligands' binding. In multiple binding events, a small molecule settled into a stable binding pose at the PPI interface of IL2, resulting in a protein-small-molecule binding site and pose virtually identical to that observed in an existing crystal structure of the IL2-SP4206 complex. Binding of the small molecule stabilized the IL2 binding groove, which when the small molecule was not bound emerged only transiently and incompletely. Moreover, free energy perturbation (FEP) calculations successfully distinguished between the native and non-native IL2-small-molecule binding poses found in the simulations, suggesting that binding simulations in combination with FEP may provide an effective tool for identifying cryptic binding sites and determining the binding poses of small molecules designed to disrupt PPI interfaces by binding to such sites.
Assuntos
Descoberta de Drogas , Interleucina-2 , Sítios de Ligação , Interleucina-2/química , Interleucina-2/metabolismo , Ligantes , Ligação ProteicaRESUMO
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.
RESUMO
The protein K-Ras functions as a molecular switch in signaling pathways regulating cell growth. In the human mitogen-activated protein kinase (MAPK) pathway, which is implicated in many cancers, multiple K-Ras proteins are thought to assemble at the cell membrane with Ras effector proteins from the Raf family. Here we propose an atomistic structural model for such an assembly. Our starting point was an asymmetric guanosine triphosphate-mediated K-Ras dimer model, which we generated using unbiased molecular dynamics simulations and verified with mutagenesis experiments. Adding further K-Ras monomers in a head-to-tail fashion led to a compact helical assembly, a model we validated using electron microscopy and cell-based experiments. This assembly stabilizes K-Ras in its active state and presents composite interfaces to facilitate Raf binding. Guided by existing experimental data, we then positioned C-Raf, the downstream kinase MEK1 and accessory proteins (Galectin-3 and 14-3-3σ) on and around the helical assembly. The resulting Ras-Raf signalosome model offers an explanation for a large body of data on MAPK signaling.
Assuntos
Proteínas Proto-Oncogênicas c-raf/química , Proteínas Proto-Oncogênicas c-raf/metabolismo , Proteínas Proto-Oncogênicas p21(ras)/química , Proteínas Proto-Oncogênicas p21(ras)/metabolismo , Proteínas Sanguíneas/química , Proteínas Sanguíneas/metabolismo , Proteínas de Ligação a DNA/química , Proteínas de Ligação a DNA/metabolismo , Transferência Ressonante de Energia de Fluorescência , Proteínas Ativadoras de GTPase/química , Proteínas Ativadoras de GTPase/metabolismo , Galectinas/química , Galectinas/metabolismo , Guanosina Trifosfato/química , Guanosina Trifosfato/metabolismo , Células HEK293 , Humanos , MAP Quinase Quinase 1/metabolismo , Microscopia Eletrônica , Microscopia Eletrônica de Transmissão , Simulação de Dinâmica Molecular , Complexos Multiproteicos/química , Complexos Multiproteicos/metabolismo , Mutagênese , Multimerização Proteica , Proteínas Proto-Oncogênicas c-raf/genética , Proteínas Proto-Oncogênicas p21(ras)/genética , Reprodutibilidade dos Testes , Transdução de Sinais , Fatores de Transcrição/química , Fatores de Transcrição/metabolismoRESUMO
MOTIVATION: Thousands of proteins are known to bind to DNA; for most of them the mechanism of action and the residues that bind to DNA, i.e. the binding sites, are yet unknown. Experimental identification of binding sites requires expensive and laborious methods such as mutagenesis and binding essays. Hence, such studies are not applicable on a large scale. If the 3D structure of a protein is known, it is often possible to predict DNA-binding sites in silico. However, for most proteins, such knowledge is not available. RESULTS: It has been shown that DNA-binding residues have distinct biophysical characteristics. Here we demonstrate that these characteristics are so distinct that they enable accurate prediction of the residues that bind DNA directly from amino acid sequence, without requiring any additional experimental or structural information. In a cross-validation based on the largest non-redundant dataset of high-resolution protein-DNA complexes available today, we found that 89% of our predictions are confirmed by experimental data. Thus, it is now possible to identify DNA-binding sites on a proteomic scale even in the absence of any experimental data or 3D-structural information. AVAILABILITY: http://cubic.bioc.columbia.edu/services/disis.
Assuntos
Aminoácidos/química , Proteínas de Ligação a DNA/química , Proteínas de Ligação a DNA/ultraestrutura , DNA/química , DNA/ultraestrutura , Modelos Químicos , Análise de Sequência de Proteína/métodos , Algoritmos , Sequência de Aminoácidos , Simulação por Computador , Modelos Moleculares , Dados de Sequência Molecular , Conformação ProteicaRESUMO
Epidermal growth factor receptor (EGFR) signalling is activated by ligand-induced receptor dimerization. Notably, ligand binding also induces EGFR oligomerization, but the structures and functions of the oligomers are poorly understood. Here, we use fluorophore localization imaging with photobleaching to probe the structure of EGFR oligomers. We find that at physiological epidermal growth factor (EGF) concentrations, EGFR assembles into oligomers, as indicated by pairwise distances of receptor-bound fluorophore-conjugated EGF ligands. The pairwise ligand distances correspond well with the predictions of our structural model of the oligomers constructed from molecular dynamics simulations. The model suggests that oligomerization is mediated extracellularly by unoccupied ligand-binding sites and that oligomerization organizes kinase-active dimers in ways optimal for auto-phosphorylation in trans between neighbouring dimers. We argue that ligand-induced oligomerization is essential to the regulation of EGFR signalling.
Assuntos
Receptores ErbB/química , Receptores ErbB/metabolismo , Animais , Artefatos , Sítios de Ligação , Células CHO , Cricetinae , Cricetulus , Fator de Crescimento Epidérmico/metabolismo , Transferência Ressonante de Energia de Fluorescência , Ligantes , Simulação de Dinâmica Molecular , Fosforilação , Domínios Proteicos , Multimerização Proteica , Transdução de SinaisRESUMO
The human epidermal growth factor receptor (HER) tyrosine kinases homo- and heterodimerize to activate downstream signaling pathways. HER3 is a catalytically impaired member of the HER family that contributes to the development of several human malignancies and is mutated in a subset of cancers. HER3 signaling depends on heterodimerization with a catalytically active partner, in particular epidermal growth factor receptor (EGFR) (the founding family member, also known as HER1) or HER2. The activity of homodimeric complexes of catalytically active HER family members depends on allosteric activation between the two kinase domains. To determine the structural basis for HER3 signaling through heterodimerization with a catalytically active HER family member, we solved the crystal structure of the heterodimeric complex formed by the isolated kinase domains of EGFR and HER3. The structure showed HER3 as an allosteric activator of EGFR and revealed a conserved role of the allosteric mechanism in activation of HER family members through heterodimerization. To understand the effects of cancer-associated HER3 mutations at the molecular level, we solved the structures of two kinase domains of HER3 mutants, each in a heterodimeric complex with the kinase domain of EGFR. These structures, combined with biochemical analysis and molecular dynamics simulations, indicated that the cancer-associated HER3 mutations enhanced the allosteric activator function of HER3 by redesigning local interactions at the dimerization interface.