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  1. Home
  2. Browse by Author

Browsing by Author "Morcos, Faruck"

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    A VDAC1-mediated NEET protein chain transfers [2Fe-2S] clusters between the mitochondria and the cytosol and impacts mitochondrial dynamics
    (National Academy of Sciences, 2022) Karmi, Ola; Marjault, Henri-Baptiste; Bai, Fang; Roy, Susmita; Sohn, Yang-Sung; Yahana, Merav Darash; Morcos, Faruck; Ioannidis, Konstantinos; Nahmias, Yaakov; Jennings, Patricia A.; Mittler, Ron; Onuchic, José N.; Nechushtai, Rachel; Center for Theoretical Biological Physics
    Mitochondrial inner NEET (MiNT) and the outer mitochondrial membrane (OMM) mitoNEET (mNT) proteins belong to the NEET protein family. This family plays a key role in mitochondrial labile iron and reactive oxygen species (ROS) homeostasis. NEET proteins contain labile [2Fe-2S] clusters which can be transferred to apo-acceptor proteins. In eukaryotes, the biogenesis of [2Fe-2S] clusters occurs within the mitochondria by the iron–sulfur cluster (ISC) system; the clusters are then transferred to [2Fe-2S] proteins within the mitochondria or exported to cytosolic proteins and the cytosolic iron–sulfur cluster assembly (CIA) system. The last step of export of the [2Fe-2S] is not yet fully characterized. Here we show that MiNT interacts with voltage-dependent anion channel 1 (VDAC1), a major OMM protein that connects the intermembrane space with the cytosol and participates in regulating the levels of different ions including mitochondrial labile iron (mLI). We further show that VDAC1 is mediating the interaction between MiNT and mNT, in which MiNT transfers its [2Fe-2S] clusters from inside the mitochondria to mNT that is facing the cytosol. This MiNT–VDAC1–mNT interaction is shown both experimentally and by computational calculations. Additionally, we show that modifying MiNT expression in breast cancer cells affects the dynamics of mitochondrial structure and morphology, mitochondrial function, and breast cancer tumor growth. Our findings reveal a pathway for the transfer of [2Fe-2S] clusters, which are assembled inside the mitochondria, to the cytosol.
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    CISD3/MiNT is required for complex I function, mitochondrial integrity, and skeletal muscle maintenance
    (National Academy of Sciences, 2024) Nechushtai, Rachel; Rowland, Linda; Karmi, Ola; Marjault, Henri-Baptiste; Nguyen, Thi Thao; Mittal, Shubham; Ahmed, Raheel S.; Grant, DeAna; Manrique-Acevedo, Camila; Morcos, Faruck; Onuchic, José N.; Mittler, Ron; Center for Theoretical Biological Physics
    Mitochondria play a central role in muscle metabolism and function. A unique family of iron–sulfur proteins, termed CDGSH Iron Sulfur Domain-containing (CISD/NEET) proteins, support mitochondrial function in skeletal muscles. The abundance of these proteins declines during aging leading to muscle degeneration. Although the function of the outer mitochondrial CISD/NEET proteins, CISD1/mitoNEET and CISD2/NAF-1, has been defined in skeletal muscle cells, the role of the inner mitochondrial CISD protein, CISD3/MiNT, is currently unknown. Here, we show that CISD3 deficiency in mice results in muscle atrophy that shares proteomic features with Duchenne muscular dystrophy. We further reveal that CISD3 deficiency impairs the function and structure of skeletal muscles, as well as their mitochondria, and that CISD3 interacts with, and donates its [2Fe-2S] clusters to, complex I respiratory chain subunit NADH Ubiquinone Oxidoreductase Core Subunit V2 (NDUFV2). Using coevolutionary and structural computational tools, we model a CISD3–NDUFV2 complex with proximal coevolving residue interactions conducive of [2Fe-2S] cluster transfer reactions, placing the clusters of the two proteins 10 to 16 Å apart. Taken together, our findings reveal that CISD3/MiNT is important for supporting the biogenesis and function of complex I, essential for muscle maintenance and function. Interventions that target CISD3 could therefore impact different muscle degeneration syndromes, aging, and related conditions.
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    Coevolutionary signals across protein lineages help capture multiple protein conformations
    (National Academy of Sciences, 2013) Morcos, Faruck; Jana, Biman; Hwa, Terence; Onuchic, José Nelson
    A long-standing problem in molecular biology is the determination of a complete functional conformational landscape of proteins. This includes not only proteins’ native structures, but also all their respective functional states, including functionally important intermediates. Here, we reveal a signature of functionally important states in several protein families, using direct coupling analysis, which detects residue pair coevolution of protein sequence composition. This signature is exploited in a protein structure-based model to uncover conformational diversity, including hidden functional configurations. We uncovered, with high resolution (mean ∼1.9 Å rmsd for nonapo structures), different functional structural states for medium to large proteins (200–450 aa) belonging to several distinct families. The combination of direct coupling analysis and the structure-based model also predicts several intermediates or hidden states that are of functional importance. This enhanced sampling is broadly applicable and has direct implications in protein structure determination and the design of ligands or drugs to trap intermediate states.
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    Designing bacterial signaling interactions with coevolutionary landscapes
    (Public Library of Science, 2018) Cheng, Ryan R.; Haglund, Ellinor; Tiee, Nicholas S.; Morcos, Faruck; Levine, Herbert; Adams, Joseph A.; Jennings, Patricia A.; Onuchic, José N.
    Selecting amino acids to design novel protein-protein interactions that facilitate catalysis is a daunting challenge. We propose that a computational coevolutionary landscape based on sequence analysis alone offers a major advantage over expensive, time-consuming brute-force approaches currently employed. Our coevolutionary landscape allows prediction of single amino acid substitutions that produce functional interactions between non-cognate, interspecies signaling partners. In addition, it can also predict mutations that maintain segregation of signaling pathways across species. Specifically, predictions of phosphotransfer activity between the Escherichia coli histidine kinase EnvZ to the non-cognate receiver Spo0F from Bacillus subtilis were compiled. Twelve mutations designed to enhance, suppress, or have a neutral effect on kinase phosphotransfer activity to a non-cognate partner were selected. We experimentally tested the ability of the kinase to relay phosphate to the respective designed Spo0F receiver proteins against the theoretical predictions. Our key finding is that the coevolutionary landscape theory, with limited structural data, can significantly reduce the search-space for successful prediction of single amino acid substitutions that modulate phosphotransfer between the two-component His-Asp relay partners in a predicted fashion. This combined approach offers significant improvements over large-scale mutations studies currently used for protein engineering and design.
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    Dimeric interactions and complex formation using direct coevolutionary couplings
    (Nature Publishing Group, 2015) dos Santos, Ricardo N.; Morcos, Faruck; Jana, Biman; Andricopulo, Adriano D.; Onuchic, José N.; Center for Theoretical Biological Physics
    We develop a procedure to characterize the association of protein structures into homodimers using coevolutionary couplings extracted from Direct Coupling Analysis (DCA) in combination with Structure Based Models (SBM). Identification of dimerization contacts using DCA is more challenging than intradomain contacts since direct couplings are mixed with monomeric contacts. Therefore a systematic way to extract dimerization signals has been elusive. We provide evidence that the prediction of homodimeric complexes is possible with high accuracy for all the cases we studied which have rich sequence information. For the most accurate conformations of the structurally diverse dimeric complexes studied the mean and interfacial RMSDs are 1.95Å and 1.44Å, respectively. This methodology is also able to identify distinct dimerization conformations as for the case of the family of response regulators, which dimerize upon activation. The identification of dimeric complexes can provide interesting molecular insights in the construction of large oligomeric complexes and be useful in the study of aggregation related diseases like Alzheimer’s or Parkinson’s.
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    Genomics-aided structure prediction
    (2012) Sulkowska, Joanna I.; Morcos, Faruck; Weigt, Martin; Hwa, Terence; Onuchic, José N.; National Science Foundation; Center for Theoretical Biological Physics
    We introduce a theoretical framework that exploits the everincreasing genomic sequence information for protein structure prediction. Structure-based models are modified to incorporate constraints by a large number of non-local contacts estimated from direct coupling analysis (DCA) of co-evolving genomic sequences. A simple hybrid method, called DCA-fold, integrating DCA contacts with an accurate knowledge of local information (e.g., the local secondary structure) is sufficient to fold proteins in the range of 1–3 Å resolution.
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    Integrated strategy reveals the protein interface between cancer targets Bcl-2 and NAF-1
    (PNAS, 2014) Tamir, Sagi; Rotem-Bamberger, Shahar; Katz, Chen; Morcos, Faruck; Hailey, Kendra L.; Zuris, John A.; Wang, Charles; Conlan, Andrea R.; Lipper, Colin H.; Paddock, Mark L.; Mittler, Ron; Onuchic, José Nelson; Jennings, Patricia A.; Friedler, Assaf; Nechushtai, Rachel; Center for Theoretical Biological Physics
    Life requires orchestrated control of cell proliferation, cell maintenance, and cell death. Involved in these decisions are protein complexes that assimilate a variety of inputs that report on the status of the cell and lead to an output response. Among the proteins involved in this response are nutrient-deprivation autophagy factor-1 (NAF-1)- and Bcl-2. NAF-1 is a homodimeric member of the novel Fe-S protein NEET family, which binds two 2Fe-2S clusters. NAF-1 is an important partner for Bcl-2 at the endoplasmic reticulum to functionally antagonize Beclin 1-dependent autophagy [Chang NC, Nguyen M, Germain M, Shore GC (2010) EMBO J 29 (3):606–618]. We used an integrated approach involving peptide array, deuterium exchange mass spectrometry (DXMS), and functional studies aided by the power of sufficient constraints from direct coupling analysis (DCA) to determine the dominant docked conformation of the NAF-1–Bcl-2 complex. NAF-1 binds to both the pro- and antiapoptotic regions (BH3 and BH4) of Bcl-2, as demonstrated by a nested protein fragment analysis in a peptide array and DXMS analysis. A combination of the solution studies together with a new application of DCA to the eukaryotic proteins NAF-1 and Bcl-2 provided sufficient constraints at amino acid resolution to predict the interaction surfaces and orientation of the protein–protein interactions involved in the docked structure. The specific integrated approach described in this paper provides the first structural information, to our knowledge, for future targeting of the NAF-1–Bcl-2 complex in the regulation of apoptosis/autophagy in cancer biology.
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    Interactions between mitoNEET and NAF-1 in cells
    (Public Library of Science, 2017) Karmi, Ola; Holt, Sarah H.; Song, Luhua; Tamir, Sagi; Luo, Yuting; Bai, Fang; Adenwalla, Ammar; Darash-Yahana, Merav; Sohn, Yang-Sung; Jennings, Patricia A.; Azad, Rajeev K.; Onuchic, José Nelson; Morcos, Faruck; Nechushtai, Rachel; Mittler, Ron; Center for Theoretical Biological Physics
    The NEET proteins mitoNEET (mNT) and nutrient-deprivation autophagy factor-1 (NAF-1) are required for cancer cell proliferation and resistance to oxidative stress. NAF-1 and mNT are also implicated in a number of other human pathologies including diabetes, neurodegeneration and cardiovascular disease, as well as in development, differentiation and aging. Previous studies suggested that mNT and NAF-1 could function in the same pathway in mammalian cells, preventing the over-accumulation of iron and reactive oxygen species (ROS) in mitochondria. Nevertheless, it is unknown whether these two proteins directly interact in cells, and how they mediate their function. Here we demonstrate, using yeast two-hybrid, in vivo bimolecular fluorescence complementation (BiFC), direct coupling analysis (DCA), RNA-sequencing, ROS and iron imaging, and single and double shRNA lines with suppressed mNT, NAF-1 and mNT/NAF-1 expression, that mNT and NAF-1 directly interact in mammalian cells and could function in the same cellular pathway. We further show using an in vitro cluster transfer assay that mNT can transfer its clusters to NAF-1. Our study highlights the possibility that mNT and NAF-1 function as part of an iron-sulfur (2Fe-2S) cluster relay to maintain the levels of iron and Fe-S clusters under control in the mitochondria of mammalian cells, thereby preventing the activation of apoptosis and/or autophagy and supporting cellular proliferation.
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    Machine learning in biological physics: From biomolecular prediction to design
    (National Academy of Sciences, 2024) Martin, Jonathan; Lequerica Mateos, Marcos; Onuchic, José N.; Coluzza, Ivan; Morcos, Faruck; Center for Theoretical Biological Physics
    Machine learning has been proposed as an alternative to theoretical modeling when dealing with complex problems in biological physics. However, in this perspective, we argue that a more successful approach is a proper combination of these two methodologies. We discuss how ideas coming from physical modeling neuronal processing led to early formulations of computational neural networks, e.g., Hopfield networks. We then show how modern learning approaches like Potts models, Boltzmann machines, and the transformer architecture are related to each other, specifically, through a shared energy representation. We summarize recent efforts to establish these connections and provide examples on how each of these formulations integrating physical modeling and machine learning have been successful in tackling recent problems in biomolecular structure, dynamics, function, evolution, and design. Instances include protein structure prediction; improvement in computational complexity and accuracy of molecular dynamics simulations; better inference of the effects of mutations in proteins leading to improved evolutionary modeling and finally how machine learning is revolutionizing protein engineering and design. Going beyond naturally existing protein sequences, a connection to protein design is discussed where synthetic sequences are able to fold to naturally occurring motifs driven by a model rooted in physical principles. We show that this model is “learnable” and propose its future use in the generation of unique sequences that can fold into a target structure.
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    The physical and evolutionary energy landscapes of devolved protein sequences corresponding to pseudogenes
    (National Academy of Sciences, 2024) Jaafari, Hana; Bueno, Carlos; Schafer, Nicholas P.; Martin, Jonathan; Morcos, Faruck; Wolynes, Peter G.; Center for Theoretical Biophysics
    Protein evolution is guided by structural, functional, and dynamical constraints ensuring organismal viability. Pseudogenes are genomic sequences identified in many eukaryotes that lack translational activity due to sequence degradation and thus over time have undergone “devolution.” Previously pseudogenized genes sometimes regain their protein-coding function, suggesting they may still encode robust folding energy landscapes despite multiple mutations. We study both the physical folding landscapes of protein sequences corresponding to human pseudogenes using the Associative Memory, Water Mediated, Structure and Energy Model, and the evolutionary energy landscapes obtained using direct coupling analysis (DCA) on their parent protein families. We found that generally mutations that have occurred in pseudogene sequences have disrupted their native global network of stabilizing residue interactions, making it harder for them to fold if they were translated. In some cases, however, energetic frustration has apparently decreased when the functional constraints were removed. We analyzed this unexpected situation for Cyclophilin A, Profilin-1, and Small Ubiquitin-like Modifier 2 Protein. Our analysis reveals that when such mutations in the pseudogene ultimately stabilize folding, at the same time, they likely alter the pseudogenes’ former biological activity, as estimated by DCA. We localize most of these stabilizing mutations generally to normally frustrated regions required for binding to other partners.
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