Destabilized adaptive influenza variants critical for innate immune system escape are potentiated by host chaperones.

The threat of viral pandemics demands a comprehensive understanding of evolution at the host-pathogen interface. Here, we show that the accessibility of adaptive mutations in influenza nucleoprotein at fever-like temperatures is mediated by host chaperones. Particularly noteworthy, we observe that the Pro283 nucleoprotein variant, which (1) is conserved across human influenza strains, (2) confers resistance to the Myxovirus resistance protein A (MxA) restriction factor, and (3) critically contributed to adaptation to humans in the 1918 pandemic influenza strain, is rendered unfit by heat shock factor 1 inhibition-mediated host chaperone depletion at febrile temperatures. This fitness loss is due to biophysical defects that chaperones are unavailable to address when heat shock factor 1 is inhibited. Thus, influenza subverts host chaperones to uncouple the biophysically deleterious consequences of viral protein variants from the benefits of immune escape. In summary, host proteostasis plays a central role in shaping influenza adaptation, with implications for the evolution of other viruses, for viral host switching, and for antiviral drug development.

ß-Branched Amino Acids Stabilize Specific Conformations of Cyclic Hexapeptides.

Cyclic peptides (CPs) are a promising class of molecules for drug development, particularly as inhibitors of protein-protein interactions. Predicting low-energy structures and global structural ensembles of individual CPs is critical for the design of bioactive molecules, but these are challenging to predict and difficult to verify experimentally. In our previous work, we used explicit-solvent molecular dynamics simulations with enhanced sampling methods to predict the global structural ensembles of cyclic hexapeptides containing different permutations of glycine, alanine, and valine. One peptide, cyclo-(VVGGVG) or P7, was predicted to be unusually well structured. In this work, we synthesized P7, along with a less well-structured control peptide, cyclo-(VVGVGG) or P6, and characterized their global structural ensembles in water using NMR spectroscopy. The NMR data revealed a structural ensemble similar to the prediction for P7 and showed that P6 was indeed much less well-structured than P7. We then simulated and experimentally characterized the global structural ensembles of several P7 analogs and discovered that ß-branching at one critical position within P7 is important for overall structural stability. The simulations allowed deconvolution of thermodynamic factors that underlie this structural stabilization. Overall, the excellent correlation between simulation and experimental data indicates that our simulation platform will be a promising approach for designing well-structured CPs and also for understanding the complex interactions that control the conformations of constrained peptides and other macrocycles.

Understanding and designing head-to-tail cyclic peptides.

Cyclic peptides (CPs) are an exciting class of molecules with a variety of applications. However, design strategies for CP therapeutics, for example, are generally limited by a poor understanding of their sequence-structure relationships. This knowledge gap often leads to a trial-and-error approach for designing CPs for a specific purpose, which is both costly and time-consuming. Herein, we describe the current experimental and computational efforts in understanding and designing head-to-tail CPs along with their respective challenges. In addition, we provide several future directions in the field of computational CP design to improve its accuracy, efficiency and applicability. These advances, combined with experimental techniques, shall ultimately provide a better understanding of these interesting molecules and a reliable working platform to rationally design CPs with desired characteristics.

Predictions for α-Helical Glycopeptide Design from Structural Bioinformatics Analysis.

Glycosylation not only impacts the functions of glycoproteins but can also improve glycoprotein stability and folding efficiency-characteristics that are desirable for protein engineering and therapeutic design. To further elucidate the effects of N-glycosylation on protein structure and to provide principles useful for the rational design of α-helical glycopeptides, we investigate stabilizing protein-sugar interactions in α-helical glycosylation sites using an integrated structural bioinformatics analysis and molecular dynamics simulation approach. We identify two glycan conformations with an Asn χ1 of 180° or 300° that are amenable to α-helical structure in natural α-helical glycosylation sites in the Protein Data Bank. A combination of sterics and favorable intraglycopeptide enthalpy explains the existence of only these two conformations. Furthermore, we catalog all known protein-sugar interactions that utilize these conformational modes. The most common interactions involve either a Glu residue at the -4 position interacting with the GlcNAc whose Asn has χ1 = 300° or a Glu residue at the +4 position interacting with the GlcNAc whose Asn has χ1 = 180°. Via metadynamics simulations of model α-helical glycopeptides with each of these two interactions, we find that both interactions are stabilizing as a result of favorable electrostatic intraglycopeptide interactions. Thus, we suggest that incorporating a Glu at either the -4 or +4 position relative to an N-linked glycan may be a useful strategy for engineering stable α-helical glycoproteins.

Toward accurately modeling N-methylated cyclic peptides.

Cyclic peptides have unique properties and can target protein surfaces specifically and potently. N-Methylation provides a promising way to further optimize the pharmacokinetic and structural profiles of cyclic peptides. The capability to accurately model structures adopted by N-methylated cyclic peptides would facilitate rational design of this interesting and useful class of molecules. We apply molecular dynamics simulations with advanced enhanced sampling methods to efficiently characterize the structural ensembles of N-methylated cyclic peptides, while simultaneously evaluating the overall performance of several simulation force fields. We find that one of the residue-specific force fields, RSFF2, is able to recapitulate experimental structures of the N-methylated cyclic peptide benchmarks tested here when the correct amide isomers are used as initial configurations and enforced during the simulations. Thus, using our simulation approach, it is possible to accurately and efficiently predict the structures of N-methylated cyclic peptides if sufficient information is available to determine the correct amide cis/trans configuration. Moreover, our results suggest that, upon further optimization of RSFF2 to more reliably predict cis/trans isomers, molecular dynamics simulations will be able to de novo predict N-methylated cyclic peptides in the near future, strongly motivating such continued optimization.

Mapping the sequence-structure relationships of simple cyclic hexapeptides.

Cyclic peptides are promising protein-protein interaction modulators with high binding affinities and specificities, as well as enhanced stabilities and oral availabilities over linear analogs. Despite their relatively small size and cyclic architecture, it is currently difficult to predict the favored conformation(s) of most classes of cyclic peptides. An improved understanding of the sequence-structure relationships for cyclic peptides will offer an avenue for the rational design of cyclic peptides as possible therapeutics. In this work, we systematically explored the sequence-structure relationships for two cyclic hexapeptide systems using molecular dynamics simulation techniques. Starting with an all-glycine cyclic hexapeptide, cyclo-G6, we systematically replaced glycine residues with alanines and characterized the structural ensembles of different variants. The same process was repeated with valines to investigate the effects of larger side chains. An analysis of the origin of structure preferences was performed using thermodynamics decomposition and several general observations are reported.

Designing Well-Structured Cyclic Pentapeptides Based on Sequence-Structure Relationships.

Cyclic peptides are a promising class of molecules for unique applications. Unfortunately, cyclic peptide design is severely limited by the difficulty in predicting the conformations they will adopt in solution. In this work, we use explicit-solvent molecular dynamics simulations to design well-structured cyclic peptides by studying their sequence-structure relationships. Critical to our approach is an enhanced sampling method that exploits the essential transitional motions of cyclic peptides to efficiently sample their conformational space. We simulated a range of cyclic pentapeptides from all-glycine to a library of cyclo-(X1X2AAA) peptides to map their conformational space and determine cooperative effects of neighboring residues. By combining the results from all cyclo-(X1X2AAA) peptides, we developed a scoring function to predict the structural preferences for X1-X2 residues within cyclic pentapeptides. Using this scoring function, we designed a cyclic pentapeptide, cyclo-(GNSRV), predicted to be well structured in aqueous solution. Subsequent circular dichroism and NMR spectroscopy revealed that this cyclic pentapeptide is indeed well structured in water, with a nuclear Overhauser effect and J-coupling values consistent with the predicted structure.

Host proteostasis modulates influenza evolution.

Predicting and constraining RNA virus evolution require understanding the molecular factors that define the mutational landscape accessible to these pathogens. RNA viruses typically have high mutation rates, resulting in frequent production of protein variants with compromised biophysical properties. Their evolution is necessarily constrained by the consequent challenge to protein folding and function. We hypothesized that host proteostasis mechanisms may be significant determinants of the fitness of viral protein variants, serving as a critical force shaping viral evolution. Here, we test that hypothesis by propagating influenza in host cells displaying chemically-controlled, divergent proteostasis environments. We find that both the nature of selection on the influenza genome and the accessibility of specific mutational trajectories are significantly impacted by host proteostasis. These findings provide new insights into features of host-pathogen interactions that shape viral evolution, and into the potential design of host proteostasis-targeted antiviral therapeutics that are refractory to resistance.

Insights into How Cyclic Peptides Switch Conformations.

Cyclic peptides have recently emerged as promising modulators of protein-protein interactions. However, it is currently highly difficult to predict the structures of cyclic peptides owing to their rugged conformational free energy landscape, which prevents sampling of all thermodynamically relevant conformations. In this article, we first investigate how a relatively flexible cyclic hexapeptide switches conformations. It is found that, although the circular geometry of small cyclic peptides of size 6-8 may require rare, coherent dihedral changes to sample a new conformation, the changes are rather local, involving simultaneous changes of ϕi and ψi or ψi and ϕi+1. The understanding of how these cyclic peptides switch conformations enables the use of metadynamics simulations with reaction coordinates specifically targeting such coupled two-dihedral changes to effectively sample cyclic peptide conformational space.

Computational methods to design cyclic peptides.

Cyclic peptides (CPs) are promising modulators of protein-protein interactions (PPIs), but their application remains challenging. It is currently difficult to predict the structures and bioavailability of CPs. The ability to design CPs using computer modeling would greatly facilitate the development of CPs as potent PPI modulators for fundamental studies and as potential therapeutics. Herein, we describe computational methods to generate CP libraries for virtual screening, as well as current efforts to accurately predict the conformations adopted by CPs. These advances are making it possible to envision robust computational design of active CPs. However, unique properties of CPs pose significant challenges associated with sampling CP conformational space and accurately describing CP energetics. These major obstacles to structure prediction likely must be solved before robust design of active CPs can be reliably achieved.