A critical assessment of force field accuracy against NMR data for cyclic peptides containing β-amino acids

Polarizable Force Field of Intrinsically Disordered Proteins with CMAP and Reweighting Optimization

Intrinsically disordered proteins (IDPs) are highly structurally heterogeneous without a specific tertiary structure under physiology conditions and play key roles in the development of human diseases. Due to the characteristics of diverse conformations, as one of the important methods, molecular dynamics simulation can complement information for experimental methods. Because of the enrichment for charged amino acids for IDPs, polarizable force fields should be a good choice for the simulation of IDPs. However, current polarizable force fields are limited in sampling conformer features of IDPs. Therefore, a polarizable force field was released and named Drude2019IDP based on Drude2019 with reweighting and grid-based potential energy correction map optimization. In order to evaluate the performance of Drude2019IDP, 16 dipeptides, 18 short peptides, 3 representative IDPs, and 5 structural proteins were simulated. The results show that the NMR observables driven by Drude2019IDP are in better agreement with the experiment data than those by Drude2019 on short peptides and IDPs. Drude2019IDP can sample more diverse conformations than Drude2019. Furthermore, the performances of the two force fields are similar to the sample ordered proteins. These results confirm that the developed Drude2019IDP can improve the reproduction of conformers for intrinsically disordered proteins and can be used to gain insight into the paradigm of sequence-disorder for IDPs.

Molecular Dynamics Simulations of Transmembrane Cyclic Peptide Nanotubes Using Classical Force Fields, Hydrogen Mass Repartitioning, and Hydrogen Isotope Exchange Methods: A Critical Comparison

Self-assembled cyclic peptide nanotubes with alternating D- and L-amino acid residues in the sequence of each subunit have attracted a great deal of attention due to their potential for new nanotechnology and biomedical applications, mainly in the field of antimicrobial peptides. Molecular dynamics simulations can be used to characterize these systems with atomic resolution at different time scales, providing information that is difficult to obtain via wet lab experiments. However, the performance of classical force fields typically employed in the simulation of biomolecules has not yet been extensively tested with this kind of highly constrained peptide. Four different classical force fields (AMBER, CHARMM, OPLS, and GROMOS), using a nanotube formed by eight D,L-α-cyclic peptides inserted into a lipid bilayer as a model system, were employed here to fill this gap. Significant differences in the pseudo-cylindrical cavities formed by the nanotubes were observed, the most important being the diameter of the nanopores, the number and location of confined water molecules, and the density distribution of the solvent molecules. Furthermore, several modifications were performed on GROMOS54a7, aiming to explore acceleration strategies of the MD simulations. The hydrogen mass repartitioning (HMR) and hydrogen isotope exchange (HIE) methods were tested to slow down the fastest degrees of freedom. These approaches allowed a significant increase in the time step employed in the equation of the motion integration algorithm, from 2 fs up to 5–7 fs, with no serious changes in the structural and dynamical properties of the nanopores. Subtle differences with respect to the simulations with the unmodified force fields were observed in the concerted movements of the cyclic peptides, as well as in the lifetime of several H-bonds. All together, these results are expected to contribute to better understanding of the behavior of self-assembled cyclic peptide nanotubes, as well as to support the methods tested to speed up general MD simulations; additionally, they do provide a number of quantitative descriptors that are expected to be used as a reference to design new experiments intended to validate and complement computational studies of antimicrobial cyclic peptides.

Extensive evaluation of environment-specific force field for ordered and disordered proteins

Intrinsically disordered proteins (IDPs) have no fixed tertiary structure under physiological conditions and are associated with many human diseases. Because IDPs have the characteristic of possessing diverse conformations, current experimental methods cannot capture all the conformations of IDPs. However, molecular dynamics simulation can sample these atomistically diverse conformations as a valuable complement to experimental data. To accurately describe the properties of IDPs, the environment-specific precise force field (ESFF1) was successfully released to reproduce the conformer character of ordered and disordered proteins. Here, three typical IDPs and thirteen folded proteins were used to further evaluate the performance of this force field. The results indicate that the NMR observables of ESFF1 better approach experimental data than do those of ff14SB for IDPs. The sampling conformations by ESFF1 are more diverse than those of ff14SB. For folded proteins, these force fields have comparable performances for reproducing conformers. Therefore, ESFF1 can be used to reveal the model of sequence-disorder-function for IDPs.

Glycan-Induced Protein Dynamics in Human Norovirus P Dimers Depend on Virus Strain and Deamidation Status

Noroviruses are the major cause of viral gastroenteritis and re-emerge worldwide every year, with GII.4 currently being the most frequent human genotype. The norovirus capsid protein VP1 is essential for host immune response. The P domain mediates cell attachment via histo blood-group antigens (HBGAs) in a strain-dependent manner but how these glycan-interactions actually relate to cell entry remains unclear. Here, hydrogen/deuterium exchange mass spectrometry (HDX-MS) is used to investigate glycan-induced protein dynamics in P dimers of different strains, which exhibit high structural similarity but different prevalence in humans. While the almost identical strains GII.4 Saga and GII.4 MI001 share glycan-induced dynamics, the dynamics differ in the emerging GII.17 Kawasaki 308 and rare GII.10 Vietnam 026 strain. The structural aspects of glycan binding to fully deamidated GII.4 P dimers have been investigated before. However, considering the high specificity and half-life of N373D under physiological conditions, large fractions of partially deamidated virions with potentially altered dynamics in their P domains are likely to occur. Therefore, we also examined glycan binding to partially deamidated GII.4 Saga and GII.4 MI001 P dimers. Such mixed species exhibit increased exposure to solvent in the P dimer upon glycan binding as opposed to pure wildtype. Furthermore, deamidated P dimers display increased flexibility and a monomeric subpopulation. Our results indicate that glycan binding induces strain-dependent structural dynamics, which are further altered by N373 deamidation, and hence hint at a complex role of deamidation in modulating glycan-mediated cell attachment in GII.4 strains.

Elucidating Solution Structures of Cyclic Peptides Using Molecular Dynamics Simulations

Protein-protein interactions are vital to biological processes, but the shape and size of their interfaces make them hard to target using small molecules. Cyclic peptides have shown promise as protein-protein interaction modulators, as they can bind protein surfaces with high affinity and specificity. Dozens of cyclic peptides are already FDA approved, and many more are in various stages of development as immunosuppressants, antibiotics, antivirals, or anticancer drugs. However, most cyclic peptide drugs so far have been natural products or derivatives thereof, with de novo design having proven challenging. A key obstacle is structural characterization: cyclic peptides frequently adopt multiple conformations in solution, which are difficult to resolve using techniques like NMR spectroscopy. The lack of solution structural information prevents a thorough understanding of cyclic peptides' sequence-structure-function relationship. Here we review recent development and application of molecular dynamics simulations with enhanced sampling to studying the solution structures of cyclic peptides. We describe novel computational methods capable of sampling cyclic peptides' conformational space and provide examples of computational studies that relate peptides' sequence and structure to biological activity. We demonstrate that molecular dynamics simulations have grown from an explanatory technique to a full-fledged tool for systematic studies at the forefront of cyclic peptide therapeutic design.

Rotational Profiler: A Fast, Automated, and Interactive Server to Derive Torsional Dihedral Potentials for Classical Molecular Simulations

Rotational Profiler provides an analytical algorithm to compute sets of classical torsional dihedral parameters by fitting an empirical energy profile to a reference one that can be obtained experimentally or by quantum-mechanical methods. The resulting profiles are compatible with the functional forms in the most widely used biomolecular force fields (e.g., GROMOS, AMBER, OPLS, and CHARMM). The linear least-squares regression method is used to generate sets of parameters that best satisfy the fitting. Rotational Profiler is free to use, analytical, and force field/package independent. The formalism is herein described, and its usage, in an interactive and automated manner, is made available as a Web server at http://rotprof.lncc.br.

Applications of Molecular Dynamics Simulation in Structure Prediction of Peptides and Proteins

Compared with rapid accumulation of protein sequences from high-throughput DNA sequencing, obtaining experimental 3D structures of proteins is still much more difficult, making protein structure prediction (PSP) potentially very useful. Currently, a vast majority of PSP efforts are based on data mining of known sequences, structures and their relationships (informatics-based). However, if closely related template is not available, these methods are usually much less reliable than experiments. They may also be problematic in predicting the structures of naturally occurring or designed peptides. On the other hand, physics-based methods including molecular dynamics (MD) can utilize our understanding of detailed atomic interactions determining biomolecular structures. In this mini-review, we show that all-atom MD can predict structures of cyclic peptides and other peptide foldamers with accuracy similar to experiments. Then, some notable successes in reproducing experimental 3D structures of small proteins through MD simulations (some with replica-exchange) of the folding were summarized. We also describe advancements of MD-based refinement of structure models, and the integration of limited experimental or bioinformatics data into MD-based structure modeling.