Showing papers by "Michael Feig published in 2021"

Charge-driven condensation of RNA and proteins suggests broad role of phase separation in cytoplasmic environments.

Abstract: Phase separation processes are increasingly being recognized as important organizing mechanisms of biological macromolecules in cellular environments. Well-established drivers of phase separation are multi-valency and intrinsic disorder. Here, we show that globular macromolecules may condense simply based on electrostatic complementarity. More specifically, phase separation of mixtures between RNA and positively charged proteins is described from a combination of multiscale computer simulations with microscopy and spectroscopy experiments. Phase diagrams were mapped out as a function of molecular concentrations in experiment and as a function of molecular size and temperature via simulations. The resulting condensates were found to retain at least some degree of internal dynamics varying as a function of the molecular composition. The results suggest a more general principle for phase separation that is based primarily on electrostatic complementarity without invoking polymer properties as in most previous studies. Simulation results furthermore suggest that such phase separation may occur widely in heterogenous cellular environment between nucleic acid and protein components.

New parallel computing algorithm of molecular dynamics for extremely huge scale biological systems

Abstract: In this paper, we address high performance extreme-scale molecular dynamics (MD) algorithm in the GENESIS software to perform cellular-scale molecular dynamics (MD) simulations with more than 100,000 CPU cores. It includes (1) the new algorithm of real-space nonbonded interactions maximizing the performance on ARM CPU architecture, (2) reciprocal-space nonbonded interactions minimizing communicational cost, (3) accurate temperature/pressure evaluations that allows a large time step, and (4) effective parallel file inputs/outputs (I/O) for MD simulations of extremely huge systems. The largest system that contains 1.6 billion atoms was simulated using MD with a performance of 8.30 ns/day on Fugaku supercomputer. It extends the available size and time of MD simulations to answer unresolved questions of biomacromolecules in a living cell.

Improved Sampling Strategies for Protein Model Refinement Based on Molecular Dynamics Simulation.

Abstract: Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict protein structures. These methods utilize protein structure databases for structure prediction via template-based modeling or for training machine-learning models to generate predictions. Structure prediction for proteins distant from proteins with known structures often results in lower accuracy with respect to the true physiological structures. Physics-based protein model refinement methods can be applied to improve model accuracy in the predicted models. Refinement methods rely on conformational sampling around the predicted structures, and if structures closer to the native states are sampled, improvements in the model quality become possible. Molecular dynamics simulations have been especially successful for improving model qualities but although consistent refinement can be achieved, the improvements in model qualities are still moderate. To extend the refinement performance of a simulation-based protocol, we explored new schemes that focus on optimized use of biasing functions and the application of increased simulation temperatures. In addition, we tested the use of alternative initial models so that the simulations can explore the conformational space more broadly. Based on the insights of this analysis, we are proposing a new refinement protocol that significantly outperformed previous state-of-the-art molecular dynamics simulation-based protocols in the benchmark tests described here.

Physics-based protein structure refinement in the era of artificial intelligence

Abstract: Protein structure refinement is the last step in protein structure prediction pipelines. Physics-based refinement via molecular dynamics (MD) simulations has made significant progress during recent years. During CASP14, we tested a new refinement protocol based on an improved sampling strategy via MD simulations. MD simulations were carried out at an elevated temperature (360 K). An optimized use of biasing restraints and the use of multiple starting models led to enhanced sampling. The new protocol generally improved the model quality. In comparison with our previous protocols, the CASP14 protocol showed clear improvements. Our approach was successful with most initial models, many based on deep learning methods. However, we found that our approach was not able to refine machine-learning models from the AlphaFold2 group, often decreasing already high initial qualities. To better understand the role of refinement given new types of models based on machine-learning, a detailed analysis via MD simulations and Markov state modeling is presented here. We continue to find that MD-based refinement has the potential to improve AI predictions. We also identified several practical issues that make it difficult to realize that potential. Increasingly important is the consideration of inter-domain and oligomeric contacts in simulations; the presence of large kinetic barriers in refinement pathways also continues to present challenges. Finally, we provide a perspective on how physics-based refinement could continue to play a role in the future for improving initial predictions based on machine learning-based methods.

Reduced efficacy of a Src kinase inhibitor in crowded protein solution.

Abstract: The inside of a cell is highly crowded with proteins and other biomolecules. How proteins express their specific functions together with many off-target proteins in crowded cellular environments is largely unknown. Here, we investigate an inhibitor binding with c-Src kinase using atomistic molecular dynamics (MD) simulations in dilute as well as crowded protein solution. The populations of the inhibitor, 4-amino-5-(4-methylphenyl)−7-(t-butyl)pyrazolo[3,4-d]pyrimidine (PP1), in bulk solution and on the surface of c-Src kinase are reduced as the concentration of crowder bovine serum albumins (BSAs) increases. This observation is consistent with the reduced PP1 inhibitor efficacy in experimental c-Src kinase assays in addition with BSAs. The crowded environment changes the major binding pathway of PP1 toward c-Src kinase compared to that in dilute solution. This change is explained based on the population shift mechanism of local conformations near the inhibitor binding site in c-Src kinase. The intracellular compartment is a crowded environment. Here, the authors use molecular dynamics (MD) simulations to assess inhibitor binding to c-Src kinase and show how ligand binding pathways differ in crowded and dilute protein solutions, highlighting the role of c-Src Tyr82 sidechain.

Inhibitory Proteins Block Substrate Access to the Active Site of Bacillus subtilis Intramembrane Metalloprotease SpoIVFB

Abstract: Intramembrane proteases of diverse signaling pathways use membrane-embedded active sites to cleave membrane-associated substrates. Interactions of intramembrane metalloproteases with modulators are poorly understood. Inhibition of Bacillus subtilis intramembrane metalloprotease SpoIVFB requires BofA and SpoIVFA, which transiently prevent cleavage of Pro-{sigma}K during endosporulation. Three conserved BofA residues (N48, N61, T64) in or near predicted transmembrane segment (TMS) 2 were found to be required for SpoIVFB inhibition. Disulfide cross-linking indicated that BofA TMS2 occupies the SpoIVFB active site region. BofA and SpoIVFA neither prevented SpoIVFB from interacting with Pro-{sigma}K in co-purification assays nor interfered with cross-linking between the C-terminal regions of Pro-{sigma}K and SpoIVFB. However, BofA and SpoIVFA did interfere with cross-linking between the N-terminal Proregion of Pro-{sigma}K and the SpoIVFB active site region and interdomain linker. A BofA variant lacking predicted TMS1, in combination with SpoIVFA, was less effective at interfering with some of the cross-links and slightly less effective at inhibiting cleavage of Pro-{sigma}K by SpoIVFB. A structural model was built of SpoIVFB in complex with BofA and parts of SpoIVFA and Pro-{sigma}K, using partial homology and constraints from cross-linking and co-evolutionary analyses. The model predicts that N48 in BofA TMS2 interacts with T64 (and possibly N61) of BofA to stabilize a membrane-embedded C-terminal region. SpoIVFA is predicted to bridge the BofA C-terminal region and SpoIVFB. Thus, the two inhibitory proteins block access of the Pro-{sigma}K N-terminal region to the SpoIVFB active site region. Our findings may inform efforts to develop selective inhibitors of intramembrane metalloproteases. SignificanceIntramembrane metalloproteases (IMMPs) function in numerous signaling processes that impact health. For example, IMMPs function in pathways regulating human cholesterol levels and bacterial pathogenesis. Knowledge of IMMP interactions with modulators could inform design of therapeutics, but structures of complexes have not been reported. We found that a transmembrane segment of BofA occupies the active site region to inhibit SpoIVFB, an IMMP crucial for endosporulation of Bacillus subtilis. Because endosporulation enhances persistence of related pathogenic bacteria, our structural model of SpoIVFB in complex with BofA and parts of its other inhibitory protein SpoIVFA and its substrate Pro-{sigma}K, may lead to strategies to control endosporulation. More broadly, insights from the SpoIVFB inhibition mechanism could guide efforts to develop inhibitors of other IMMPs.

Biosynthesis and trafficking of heme o and heme a: new structural insights and their implications for reaction mechanisms and prenylated heme transfer.

Abstract: Aerobic respiration is a key energy-producing pathway in many prokaryotes and virtually all eukaryotes. The final step of aerobic respiration is most commonly catalyzed by heme-copper oxidases embedded in the cytoplasmic or mitochondrial membrane. The majority of these terminal oxidases contain a prenylated heme (typically heme a or occasionally heme o) in the active site. In addition, many heme-copper oxidases, including mitochondrial cytochrome c oxidases, possess a second heme a cofactor. Despite the critical role of heme a in the electron transport chain, the details of the mechanism by which heme b, the prototypical cellular heme, is converted to heme o and then to heme a remain poorly understood. Recent structural investigations, however, have helped clarify some elements of heme a biosynthesis. In this review, we discuss the insight gained from these advances. In particular, we present a new structural model of heme o synthase (HOS) based on distance restraints from inferred coevolutionary relationships and refined by molecular dynamics simulations that are in good agreement with the experimentally determined structures of HOS homologs. We also analyze the two structures of heme a synthase (HAS) that have recently been solved by other groups. For both HOS and HAS, we discuss the proposed catalytic mechanisms and highlight how new insights into the heme-binding site locations shed light on previously obtained biochemical data. Finally, we explore the implications of the new structural data in the broader context of heme trafficking in the heme a biosynthetic pathway and heme-copper oxidase assembly.

Inhibitory proteins block substrate access to the membrane-embedded active site of Bacillus subtilis intramembrane protease SpoIVFB

Abstract: Intramembrane proteases function in numerous signaling pathways that impact health, but how their membrane-embedded active sites interact with modulators is poorly understood. We examined inhibition of intramembrane metalloprotease SpoIVFB by proteins BofA and SpoIVFA. We found that BofA residues in and near a predicted transmembrane segment are required for SpoIVFB inhibition, and cross-linking experiments indicated that this transmembrane segment occupies the SpoIVFB active site region. BofA and SpoIVFA neither prevented SpoIVFB from interacting with substrate in co-purification assays nor interfered with cross-linking between the C-terminal regions of substrate and SpoIVFB. However, the inhibitory proteins did interfere with cross-linking between the SpoIVFB active site region and the substrate N-terminal Proregion, which is normally cleaved. We conclude that BofA and SpoIVFA block substrate access to the membrane-embedded active site of SpoIVFB. A structural model was built of SpoIVFB in complex with BofA and parts of SpoIVFA and substrate, using partial homology and constraints from cross-linking and co-evolutionary analyses. The model predicts that conserved BofA residues interact to stabilize a transmembrane segment and a membrane-embedded C-terminal region. SpoIVFA is predicted to bridge the BofA C-terminal region and SpoIVFB, forming a membrane-embedded inhibitory complex. Implications for design of intramembrane metalloprotease inhibitors are discussed.

Inhibitory proteins block substrate access by occupying the active site cleft of Bacillus subtilis intramembrane protease SpoIVFB

Abstract: Intramembrane proteases function in numerous signaling pathways that impact health, but knowledge about regulation of intramembrane proteolysis is limited. We examined inhibition of intramembrane metalloprotease SpoIVFB by proteins BofA and SpoIVFA. We found that BofA residues in and near a predicted transmembrane segment are required for SpoIVFB inhibition, and cross-linking experiments indicated that this transmembrane segment occupies the SpoIVFB active site cleft. SpoIVFA is also required for SpoIVFB inhibition. The inhibitory proteins block access of the substrate N-terminal Proregion to the membrane-embedded SpoIVFB active site, based on additional cross-linking experiments; however, the inhibitory proteins did not prevent interaction between the substrate C-terminal region and the SpoIVFB soluble domain. A structural model was built of SpoIVFB in complex with BofA and parts of SpoIVFA and substrate, using partial homology and constraints from cross-linking and co-evolutionary analyses. The model predicts that conserved BofA residues interact to stabilize a transmembrane segment and a membrane-embedded C-terminal region. SpoIVFA is predicted to bridge the BofA C-terminal region and SpoIVFB, forming a membrane-embedded inhibition complex. Our results reveal a novel mechanism of intramembrane protease inhibition with clear implications for relief from inhibition in vivo and design of inhibitors as potential therapeutics.