Understanding protein folding, evolution and function via molecular simulation

National Institute Of Diabetes And Digestive And Kidney Diseases

Investigators

Linked publications, trials & patents

Abstract

The project has addressed the following areas in the past year: 1. Continued 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. In addition, we are now explicitly examining the coupling between dimerization of the protease and catalytic activity. (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 of opposite may be ubiquitous in cell nuclei. We have shown that this mode of association allows a competitive substitution mechanism that speeds unbinding 6. We are also seeking to develop a predictive model for the affinity and structure of these complexes. We have begun by refining the molecular simulation force fields to reproduce ion-ion and ion-protein interactions using new osmotic pressure 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. We are currently extending this model to include sequence-specific effects as well as back-mapping to atomistic simulations in a multiscale approach. (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, which has recently been published 1. We are now extending this model to capture specific structure formation (e.g. amyloid) to model possible aging processes in droplets. We are also developing models for cosolvent and Hofmeister effects which are sometimes of interest experimentally. (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 10. We are now applying 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 several experimental groups (Sander Tans, Gunnar von Heijne, Alex Katrinidis), we have investigated the effect of interactions with the ribosome on co-translational folding. We found that the effect of the ribosome on folding/unfolding kinetics measured via optical tweezers could not simply be described using via excluded volume, as in our previously developed model for co-translational folding on the ribosome. However, by adding a simple screened electrostatic potential we were able to reproduce the experimental trends, highlighting the importance of electrostatic interactions 9. In a new collaboration with Alexey Amunts in Stockholm, we have used coarse-grained simulations to interpret their cryo-EM results on mitochondrial ribosomes, showing that in some conformations it is possible for the nascent chain to form a helix 3 (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, and 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. Separately, we are exploring the use of machine learning to predict fitness landscapes for proteins of any given structure (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 8. 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. Modelling properties of extracellular matrix using coarse-grained models. We have recently started developing bottom up coarse-grained simulation models to describe the mechanical properties of the extracellular matrix and how they are related to its underlying molecular structure (G. Pantelopulos). 10. Inferring interactions between proteins and cosolutes using NMR data. In collaboration with Yusuke Okuno and Marius Clore, we have been using simulations in conjunction with experiments to analyze association of denaturant molecules with proteins using spin-labelled denaturants. For the first time we have shown directly that the denaturant mechanism involves primarily interactions with the unfolded state 4. We are now extending this work and developing all-atom models for the spin-labelled cosolutes. Group members or jointly supervised external collaborators involved in each project are listed at the end of each section.