Document text
Principal Investigator: Robert Best
Organization: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
Fiscal Year: 2020
Award: $866,673
Funding agency: National Institute of Diabetes and Digestive and Kidney Diseases
The project has addressed the following areas in the past year:
1. Studies of SARS-Cov2 Main Protease. In collaboration with John Louis (NIDDK), we have investigated the autoprocessing mechanism of the SARS-Cov2 Main Protease. A reaction coordinate was developed that can describe the conformational change between the native protease structure and a putative transient state required for protease autoprocessing, a key step for viral replication. Simulations show that this state is only slightly higher in free energy than the native state and should be populated on a microsecond to millisecond time scale, making the proposed autoprocessing mechanism extremely plausible. Future work will investigate this mechanism further and whether it can be exploited to design novel inhibitors for SARS proteases (R. Best).
2. Association of highly charged intrinsically disordered proteins. Recent work in collaboration with Ben Schuler's single molecule FRET group in Zurich has shown that high affinity disordered complexes of proteins or proteins and nucleic acids may be ubiquitous in cell nuclei. We are seeking to develop a predictive model for the affinity and structure of these complexes, initially via molecular simulation, but then via a semi-empirical theory fitted to experimental data collected in the Schuler lab (M. Ivanovic).
3. Development of coarse-grained models for complex coacervation of intrinsically disordered proteins with single- and double-stranded nucleic acids. Going beyond the 1:1 complexes studied in project 1, it is also possible for oppositely charged macromolecules such as proteins and DNA or RNA to undergo complex coacervation, forming a separate phase with high macromolecular density, under the correct conditions. Such a phenomenon may provide a physical basis for the formation of some of the membraneless organelles observed in the cell nucleus. We have developed a coarse-grained simulation model of protein-nucleic acid interactions, and used it to study the ordering induced on formation of the condensed phase. Future work will include improving the transferability of the model to different sequences and making it more sensitive to sequence-specific effects (K. Lebold).
4. Development of transferable sequence-specific models for liquid-liquid phase separation (LLPS) of intrinsically disordered proteins. We had previously shown that a simple coarse-grained model could be useful for modelling qualitative effects on protein liquid-liquid phase separation, the basis for formation of many membraneless organelles within cells. However, this model was not very predictive of which proteins would undergo phase separation. We have therefore undertaken a comprehensive refitting of the energy function in order to describe both the properties of isolated disordered chains and also those of proteins which are known to phase separate. The inclusion of the latter data set results in a great improvement of the overall accuracy of the model, owing to some of the effects which are important for driving LLPS not being well represented in the database of isolated (non phase-separating) proteins. This work is currently in preparation for publication (T. Dannenhoffer-Lafage).
5. All-atom simulations of protein phase separation and complex coacervation. Using time obtained on the Anton supercomputer, together with novel multiscale simulation methodology, we have performed the first all-atom simulations of a protein-rich phase representative of those obtained in protein LLPS. We have characterized the interactions driving formation of this phase, the partitioning of ions into the dense phase, and the dynamics of proteins within the phase - paper currently under review. We now intend to apply similar methodology to the more challenging problem of coacervation of oppositely charged proteins, in order to elucidate the interactions responsible for stabilizing these phases (M. Ivanovic).
6. Co-translational protein folding. In collaboration with Gunnar von Heijne, we have used our previously developed model for co-translational folding on the ribosome to investigate more directly the relationship between the forces arising from the folding nascent chain and the yield of full length protein obtained in arrest peptide experiments. We also devised a method for obtaining these forces directly from experiment by using a series of different arrest peptides with the same protein constructs (5). In a second collaboration with the group of Sander Tans, we are using our coarse-grained co-translational folding model to understand the effects of the ribosome on the folding and unfolding rates of ADR1a in the ribosome exit tunnel, as probed by single molecule force and fluorescence spectroscopy. We have recently started a new collaboration with Alexey Amunts in Stockholm to interpret their cryo-EM results on mitochondrial ribosomes (R. Best, P. Tian).
7. Using sequence-based energy functions to describe protein fitness landscapes and for protein design. Building on our success in describing the fitness landscape of a single fold using coevolutionary models, we are seeking to design sequences which can fold into two different structures as envisaged in our recent theoretical work (7). We are collaborating with Susan Marqusee's group to test some of these ideas (P. Tian). We are also looking to develop similar ideas to identify proteins which naturally switch folds (such as RfaH), using sequence information (L. Frechette).
8. Modelling sensitivity of single molecule experiments to protein folding transition paths using molecular simulations. Recent single molecule fluorescence experiments have been able to detect transition paths between folded and unfolded states of proteins by combining photon by photon detection with sophisticated maximum likelihood analysis algorithms. However, it is not clear how the inferred transition path durations relate to the actual folding transition path lengths, since they cannot be independently measured. We have used simulations as a model to generate coarse-grained folding trajectories for two proteins (alpha3D, protein G), in which we can unambiguously assign transition paths. We then generated synthetic photon trajectories from these simulations and analyzed them in the same way as the experimental data. We found that the experimentally inferred transition path durations are of the right magnitude, but systematically shorter than the true durations. Beyond current analysis methods, we are also testing the feasibility of obtaining information besides just the length of the transition path, i.e. transition path "shape", from this type of experiment, using synthetic data generated from our simulations (G. Taumoefolau).
9. Using transition-path sampling to study the mechanism and rate of assembly of transmembrane protein dimers, as represented by Glycophorin A. We have used our force field developed to best reproduce the stability of Glycophorin A in POPC membranes to study the dynamics of protein association using enhanced sampling methods (transition-path sampling) (4). We find that association occurs via an intermediate in which non-native interactions are initially formed between the helices, followed by a second step driven by native interactions. The same approach should be applicable to study oligomerization of other transmembrane domains. (J. Domanski).
Group members or jointly supervised external collaborators involved in each project are listed at the end of each section.
Terms: <2019 novel coronavirus><2019-nCoV><Address><Affinity><Algorithmic Analyses><Algorithmic Analysis><Analyses of Algorithms><Analysis of Algorithms><Area><Automobile Driving><Base Sequence><CD235A><Cell Body><Cell Nucleus><Cells><Charge><Collaborations><Complex><Cryo-electron Microscopy><Cryoelectron Microscopy><Cytoplasmic Granules><DNA><Data><Data Bases><Data Set><Databases><Dataset><Deoxyribonucleic Acid><Development><Disease><Disorder><Electron Cryomicroscopy><Esteroproteases><Evolution><Fluorescence><Fluorescence Spectroscopy><Free Energy><Future><G-substrate><GYPA><GYPA gene><Glycophorin A><Glycophorin A Protein><Goals><Grain><Integral Membrane Protein><Intrinsic Membrane Protein><Ions><Length><Liquid substance><Measures><Membrane><Membrane Protein Gene><Membrane Proteins><Membrane-Associated Proteins><Methodology><Methods><Mitochondria><Modeling><Molecular><Molecular Configuration><Molecular Conformation><Molecular Stereochemistry><Msec><NIDDK><National Institute of Diabetes and Digestive and Kidney Diseases><Non-Polyadenylated RNA><Nucleic Acids><Nucleotide Sequence><Nucleus><Organelles><Paper><Peptidases><Peptide Hydrolases><Peptides><Phase><Photons><Preparation><Property><Protease Gene><Proteases><Protein Dynamics><Protein Engineering><Proteinases><Proteins><Proteolytic Enzymes><Publications><RNA><RNA Gene Products><Reaction><Refit><Resolution><Ribonucleic Acid><Ribosomes><SARS><SARS coronavirus disease><SARS-CoV disease><SARS-CoV-2><SARS-CoV2><SARS-associated coronavirus 2><SARS-coronavirus-2><SARS-related coronavirus 2><Sampling><Scientific Publication><Series><Severe Acute Respiratory Syndrome><Severe Acute Respiratory Syndrome CoV disease><Severe Acute Respiratory Syndrome coronavirus disease><Severe acute respiratory syndrome coronavirus 2><Shapes><Structure><Supervision><Surface Proteins><TM Domain><Testing><Time><Transmembrane Domain><Transmembrane Protein><Transmembrane Protein Gene><Transmembrane Region><Virus Replication><Work><Wuhan coronavirus><aberrant protein folding><abnormal protein folding><amyloid fibril formation><cerebellum protein substrate for cGMP dependent protein kinase><computer based prediction><conformation><conformational state><cryo-EM><cryoEM><data base><density><design><designing><developmental><dimer><driving><experiment><experimental research><experimental study><fitness><fluid><genetic protein engineering><granule><improved><inhibitor><inhibitor/antagonist><insoluble aggregate><interest><liquid><macromolecule><member><membrane structure><millisecond><mitochondrial><model-based simulation><models and simulation><non-Native><nonnative><novel><nucleic acid sequence><pathologic protein folding><photon detection><photon-counting detector><prediction model><predictive modeling><prognostic model><protein G><protein aggregate><protein aggregation><protein complex><protein design><protein folding><protein function><protein mis-folding><protein misfolding><simulation><single molecule><single photon detector><single-molecule FRET><single-molecule fluorescence resonance energy transfer><smFRET><success><supercomputer><theories><time use><viral multiplication><viral replication><virus multiplication>