Intrinsic backbone preferences are fully present in blocked amino acids

Intrinsic Conformational Dynamics of Glycine and Alanine in Polarizable Molecular Dynamics Force Fields: Comparison to Spectroscopic Data

Molecular dynamics (MD) is a great tool for elucidating conformational dynamics of proteins and peptides in water at the atomistic level that often surpasses the level of detail available experimentally. Structure predictions, however, are limited by the accuracy of the underlying MD force field. This limitation is particularly stark in the case of intrinsically disordered peptides and proteins, which are characterized by solvent-accessible and disordered peptide regions and domains. Recent studies show that most additive MD force fields, including CHARMM36m, do not reproduce the intrinsic conformational distributions of guest amino acid residues x in cationic GxG peptides in water in line with experimental data. Positing that a lack of polarizability in additive MD force fields may be the culprit for the reported discrepancies, we here examine the conformational dynamics of guest glycine and alanine residues in cationic GxG peptides in water using two polarizable MD force fields, CHARMM Drude and AMOEBA. Our results indicate that while AMOEBA captures the experimental data better than CHARMM Drude, neither of the two polarizable force fields offers an improvement of the Ramachandran distributions of glycine and alanine residues in cationic GGG and GAG peptides, respectively, over CHARMM36m.

Proteolytically Stable Diaza-Peptide Foldamers Mimic Helical Hot Spots of Protein-Protein Interactions and Act as Natural Chaperones

A novel class of peptidomimetic foldamers based on diaza-peptide units are reported. Circular dichroism, attenuated total reflection -Fourier transform infrared, NMR, and molecular dynamics studies demonstrate that unlike the natural parent nonapeptide, the specific incorporation of one diaza-peptide unit at the N-terminus allows helical folding in water, which is further reinforced by the introduction of a second unit at the C-terminus. The ability of these foldamers to resist proteolysis, to mimic the small helical hot spot of transthyretin-amyloid β (Aβ) cross-interaction, and to decrease pathological Aβ aggregation demonstrates that the introduction of diaza-peptide units is a valid approach for designing mimics or inhibitors of protein-protein interaction and other therapeutic peptidomimetics. This study also reveals that small peptide foldamers can play the same role as physiological chaperone proteins and opens a new way to design inhibitors of amyloid protein aggregation, a hallmark of more than 20 serious human diseases such as Alzheimer's disease.

Conformational Manifold Sampled by Two Short Linear Motif Segments Probed by Circular Dichroism, Vibrational, and Nuclear Magnetic Resonance Spectroscopy

Disordered protein segments called short linear motifs (SLiM) serve as recognition sites for a variety of biological processes and act as targeting signals, modification, and ligand binding sites. While SLiMs do not adopt one of the known regular secondary structures, the conformational distribution might still reflect the structural propensities of their amino acid residues and possible interactions between them. In the past, conformational analyses of short peptides provided compelling evidence for the notion that individual residues are less conformationally flexible than locally expected for a random coil. Here, we combined various spectroscopies (NMR, IR, vibrational, and UV circular dichroism) to determine the Ramachandran plots of two SLiM motifs, i.e., GRRDSG and GRRTSG. They are two representatives of RxxS motifs that are capable of being phosphorylated by protein kinase A, an enzyme that plays a fundamental role in a variety of biological processes. Our results reveal that the nearest and non-nearest interactions between residues cause redistributions between polyproline II and β-strand basins while concomitantly stabilizing extended relative to turn-forming and helical structures. They also cause shifts in basin positions. With increasing temperature, β-strand populations become more populated at the expense of polyproline II. While molecular dynamics simulations with Amber ff14SB and CHARMM 36m force fields indicate residue-residue interactions, they do not account for the observed structural changes.

The relevance of short peptides for an understanding of unfolded and intrinsically disordered proteins

Over the last thirty years the unfolded state of proteins has attracted considerable interest owing to the discovery of intrinsically disordered proteins which perform a plethora of functions despite resembling unfolded proteins to a significant extent. Research on both, unfolded and disordered proteins has revealed that their conformational properties can deviate locally from random coil behavior. In this context results from work on short oligopeptides suggest that individual amino acid residues sample the sterically allowed fraction of the Ramachandran plot to a different extent. Alanine has been found to exhibit a peculiarity in that it has a very high propensity for adopting polyproline II like conformations. This Perspectives article reviews work on short peptides aimed at exploring the Ramachandran distributions of amino acid residues in different contexts with experimental and computational means. Based on the thus provided overview the article discussed to what extent short peptides can serve as tools for exploring unfolded and disordered proteins and as benchmarks for the development of a molecular dynamics force field.

The influence of random-coil chemical shifts on the assessment of structural propensities in folded proteins and IDPs

In studying secondary structural propensities of proteins by nuclear magnetic resonance (NMR) spectroscopy, secondary chemical shifts (SCSs) serve as the primary atomic scale observables. For SCS calculation, the selection of an appropriate random coil chemical shift (RCCS) dataset is a crucial step, especially when investigating intrinsically disordered proteins (IDPs). The scientific literature is abundant in such datasets, however, the effect of choosing one over all the others in a concrete application has not yet been studied thoroughly and systematically. Hereby, we review the available RCCS prediction methods and to compare them, we conduct statistical inference by means of the nonparametric sum of ranking differences and comparison of ranks to random numbers (SRD-CRRN) method. We try to find the RCCS predictors best representing the general consensus regarding secondary structural propensities. The existence and the magnitude of resulting differences on secondary structure determination under varying sample conditions (temperature, pH) are demonstrated and discussed for globular proteins and especially IDPs.

A backbone-dependent rotamer library with high (ϕ, ψ) coverage using metadynamics simulations

Backbone-dependent rotamer libraries are commonly used to assign the side chain dihedral angles of amino acids when modeling protein structures. Most rotamer libraries are created by curating protein crystal structure data and using various methods to extrapolate the existing data to cover all possible backbone conformations. However, these rotamer libraries may not be suitable for modeling the structures of cyclic peptides and other constrained peptides because these molecules frequently sample backbone conformations rarely seen in the crystal structures of linear proteins. To provide backbone-dependent side chain information beyond the α-helix, β-sheet, and PPII regions, we used explicit-solvent metadynamics simulations of model dipeptides to create a new rotamer library that has high coverage in the (ϕ, ψ) space. Furthermore, this approach can be applied to build high-coverage rotamer libraries for noncanonical amino acids. The resulting Metadynamics of Dipeptides for Rotamer Distribution (MEDFORD) rotamer library predicts the side chain conformations of high-resolution protein crystal structures with similar accuracy (~80%) to a state-of-the-art rotamer library. Our ability to test the accuracy of MEDFORD at predicting the side chain dihedral angles of amino acids in noncanonical backbone conformation is restricted by the limited structural data available for cyclic peptides. For the cyclic peptide data that are currently available, MEDFORD and the state-of-the-art rotamer library perform comparably. However, the two rotamer libraries indeed make different rotamer predictions in noncanonical (ϕ, ψ) regions. For noncanonical amino acids, the MEDFORD rotamer library predicts the χ1 values with approximately 75% accuracy.

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.

Exploring Nearest Neighbor Interactions and Their Influence on the Gibbs Energy Landscape of Unfolded Proteins and Peptides

The Flory isolated pair hypothesis (IPH) is one of the corner stones of the random coil model, which is generally invoked to describe the conformational dynamics of unfolded and intrinsically disordered proteins (IDPs). It stipulates, that individual residues sample the entire sterically allowed space of the Ramachandran plot without exhibiting any correlations with the conformational dynamics of its neighbors. However, multiple lines of computational, bioinformatic and experimental evidence suggest that nearest neighbors have a significant influence on the conformational sampling of amino acid residues. This implies that the conformational entropy of unfolded polypeptides and proteins is much less than one would expect based on the Ramachandran plots of individual residues. A further implication is that the Gibbs energies of residues in unfolded proteins or polypeptides are not additive. This review provides an overview of what is currently known and what has yet to be explored regarding nearest neighbor interactions in unfolded proteins.

Development and Validation of AMBER-FB15-Compatible Force Field Parameters for Phosphorylated Amino Acids

Phosphorylation of select amino acid residues is one of the most common biological mechanisms for regulating protein structures and functions. While computational modeling can be used to explore the detailed structural changes associated with phosphorylation, most molecular mechanics force fields developed for the simulation of phosphoproteins have been noted to be inconsistent with experimental data. In this work, we parameterize force fields for the phosphorylated forms of the amino acids serine, threonine, and tyrosine using the ForceBalance software package with the goal of improving agreement with experiments for these residues. Our optimized force field, denoted as FB18, is parameterized using high-quality ab initio potential energy scans and is designed to be fully compatible with the AMBER-FB15 protein force field. When utilized in MD simulations together with the TIP3P-FB water model, we find that FB18 consistently enhances the prediction of experimental quantities such as ³J NMR couplings and intramolecular hydrogen-bonding propensities in comparison to previously published models. As was reported with AMBER-FB15, we also see improved agreement with the reference QM calculations in regions at and away from local minima. We thus believe that the FB18 parameter set provides a promising route for the further investigation of the varied effects of protein phosphorylation.

A comparison of three DFT exchange-correlation functionals and two basis sets for the prediction of the conformation distribution of hydrated polyglycine

The performance of three density functional theory (DFT) exchange-correlation functionals, namely, Perdew-Burke-Ernzerhof (PBE), BP86, and B3LYP, in predicting conformational distributions of a hydrated glycine peptide is tested with two different basis sets in the framework of adaptive force matching (AFM). The conformational distributions yielded the free energy profiles of the DFT functional and basis set combinations. Unlike traditional validations of potential energy and structural parameters, our approach allows the free energy of DFT to be validated. When compared to experimental distributions, the def2-TZVP basis set provides better agreement than a slightly trimmed aug-cc-pVDZ basis set. B3LYP is shown to be better than BP86 and PBE. The glycine model fitted against B3LYP-D3(BJ) with the def2-TZVP basis set is the most accurate and named the AFM2021 model for glycine. The AFM2021 glycine model provides better agreement with experimental J-coupling constants than C36m and ff14SB, although the margin is very small when compared to C36m. Our previously published alanine model is also refitted with the slightly simplified AFM2021 energy expression. This work shows good promise of AFM for developing force fields for a range of proteinogenic peptides using only DFT as reference.

Intrinsic Conformational Dynamics of Alanine in Water/Ethanol Mixtures: An Experiment-Driven Molecular Dynamics Study

In vitro, cationic glycylalanylglycine (GAG) forms a hydrogel in binary mixtures of water and ethanol. In water, alanine residue is known for its high polyproline II (pPII) content. Spectroscopic data, including three J-coupling constants and amide I' profiles, indicate that addition of 42% ethanol to water significantly reduces the pPII content of alanine residue in GAG. Here, experiment-based Gaussian Ramachandran distributions of alanine in GAG at different ethanol fractions are examined and three MD force fields are evaluated with respect to their ability to capture these ethanol-induced conformational changes. MD simulations on monomeric GAG in eight different water/ethanol mixtures within Amber ff14SB, OPLS-AA/M, and CHARMM36m reveal that only Amber ff14SB partially captures the ethanol-induced conformational changes of alanine residue in monomeric GAG when 42% ethanol is added to water. MD simulations of 200 mM GAG ensembles in pure water and in the aqueous solution with 42% ethanol showcase the ability of CHARMM36m to capture the effect of ethanol on the average pPII content of alanine in GAG and provide a plausible explanation for this effect, which may stem from an increased propensity of GAG to form oligomers in the presence of ethanol.

Glycine in Water Favors the Polyproline II State

Conformational preferences of amino acid residues in water are determined by the backbone and side-chain properties. Alanine is known for its high polyproline II (pPII) propensity. The question of relative contributions of the backbone and side chain to the conformational preferences of alanine and other amino acid residues in water is not fully resolved. Because glycine lacks a heavy-atom side chain, glycine-based peptides can be used to examine to which extent the backbone properties affect the conformational space. Here, we use published spectroscopic data for the central glycine residue of cationic triglycine in water to demonstrate that its conformational space is dominated by the pPII state. We assess three commonly used molecular dynamics (MD) force fields with respect to their ability to capture the conformational preferences of the central glycine residue in triglycine. We show that pPII is the mesostate that enables the functional backbone groups of the central residue to form the most hydrogen bonds with water. Our results indicate that the pPII propensity of the central glycine in GGG is comparable to that of alanine in GAG, implying that the water-backbone hydrogen bonding is responsible for the high pPII content of these residues.

Environment-Specific Force Field for Intrinsically Disordered and Ordered Proteins

The need for accurate and efficient force fields for modeling 3D structures of macrobiomolecules and in particular intrinsically disordered proteins (IDPs) has increased with recent findings to associate IDPs and human diseases. However, most conventional protein force fields and recent IDP-specific force fields are limited in reproducing accurate structural features of IDPs. Here, we present an environmental specific precise force field (ESFF1) based on CMAP corrections of 71 different sequence environments to improve the accuracy and efficiency of MD simulation for both IDPs and folded proteins. MD simulations of 84 different short peptides, IDPs, and structured proteins show that ESFF1 can accurately reproduce spectroscopic properties for different peptides and proteins whether they are disordered or ordered. The successful ab initio folding of five fast-folding proteins further supports the reliability of ESFF1. The extensive analysis documented here shows that ESFF1 is able to achieve a reasonable balance between ordered and disordered states in protein simulations.

Peptide-based short single β-strand mimics without hydrogen bonding or aggregation

Generation of short peptides with a single β-strand structure in solution is difficult. Herein, we design a new class of single β-strand peptidic mimics that are stable without self-aggregation in protic and non-protic solvents. Introduction of one present β-strand mimic can induce and propagate the β-strand structure for at least a penta-peptide sequence.

Hamiltonian Reweighing To Refine Protein Backbone Dihedral Angle Parameters in the GROMOS Force Field

Molecular dynamics simulations of proteins depend critically on the underlying force field, which may be parameterized against experimental data or high-quality quantum calculations. Here, we develop search algorithms based on Monte Carlo and steepest descent calculations to optimize the backbone dihedral angle parameters from a single reference simulation. We apply these tools to improve the agreement between simulations of single, capped amino acids and experimentally determined J values and secondary structure propensities of these molecules. The parameters are further refined based on simulations of a set of seven proteins and finally validated in simulations on a large set of 52 protein structures. Improvements in the dihedral angle distributions are observed, and structural propensities of the proteins are reproduced very well. Overall, the GROMOS 54A8_bb parameter set forms an improvement to previous parameter sets, both for small molecules and for protein simulations.

ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution

Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled φ/ψ parameters using 2D φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in aqueous solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, and to compare to results using other Amber models, we have performed a total of ∼5 ms MD simulations in explicit solvent. Our results show that after amino-acid-specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino-acid-specific Protein Data Bank (PDB) Ramachandran maps better but also shows significantly improved capability to differentiate amino-acid-dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated for by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. Of the explicit water models tested here, we recommend use of OPC with ff19SB.

Overall Shape Constraint of Alternating α/β-Hybrid Peptides Containing Bicyclic β-Proline

Our NMR, IR/Raman, CD spectroscopic, and X-ray crystallographic studies, as well as accelerated molecular dynamics simulations, showed that alternating hybrid α/β-peptides containing a bicyclic β-proline surrogate form unique extended curved folds, regardless of the peptide length and solvent environment. It is suggested that extended β/PPII structures are preferred in the insulating α-alanine moieties between the rigid bicyclic β-proline structures. These hybrid peptides inhibit p53-MDM2 and p53-MDMX protein-protein interactions.

Development and Validation of the Quantum Mechanical Bespoke Protein Force Field

Molecular mechanics force field parameters for macromolecules, such as proteins, are traditionally fit to reproduce experimental properties of small molecules, and thus, they neglect system-specific polarization. In this paper, we introduce a complete protein force field that is designed to be compatible with the quantum mechanical bespoke (QUBE) force field by deriving nonbonded parameters directly from the electron density of the specific protein under study. The main backbone and sidechain protein torsional parameters are rederived in this work by fitting to quantum mechanical dihedral scans for compatibility with QUBE nonbonded parameters. Software is provided for the preparation of QUBE input files. The accuracy of the new force field, and the derived torsional parameters, is tested by comparing the conformational preferences of a range of peptides and proteins with experimental measurements. Accurate backbone and sidechain conformations are obtained in molecular dynamics simulations of dipeptides, with NMR J coupling errors comparable to the widely used OPLS force field. In simulations of five folded proteins, the secondary structure is generally retained, and the NMR J coupling errors are similar to standard transferable force fields, although some loss of the experimental structure is observed in certain regions of the proteins. With several avenues for further development, the use of system-specific nonbonded force field parameters is a promising approach for next-generation simulations of biological molecules.

Homotrimerization Approach in the Design of Thrombospondin-1 Mimetic Peptides with Improved Potency in Triggering Regulated Cell Death of Cancer Cells

In order to optimize the potency of the first serum-stable peptide agonist of CD47 (PKHB1) in triggering regulated cell death of cancer cells, we designed a maturation process aimed to mimic the trimeric structure of the thrombospondin-1/CD47 binding epitope. For that purpose, an N-methylation scan of the PKHB1 sequence was realized to prevent peptide aggregation. Structural and pharmacological analyses were conducted in order to assess the conformational impact of these chemical modifications on the backbone structure and the biological activity. This structure-activity relationship study led to the discovery of a highly soluble N-methylated peptide that we termed PKT16. Afterward, this monomer was used for the design of a homotrimeric peptide mimic that we termed [PKT16]₃, which proved to be 10-fold more potent than its monomeric counterpart. A pharmacological evaluation of [PKT16]₃ in inducing cell death of adherent (A549) and nonadherent (MEC-1) cancer cell lines was also performed.

Structural Aspects of the O-glycosylation Linkage in Glycopeptides via MD Simulations and Comparison with NMR Experiments

A powerful conformational searching and enhanced sampling simulation method, and unbiased molecular dynamics simulations have been used along with NMR spectroscopic observables to provide a detailed structural view of O-glycosylation. For four model systems, the force-field parameters can accurately predict experimental NMR observables (J couplings and NOE's). This enables us to derive conclusions based on the generated ensembles, in which O-glycosylation affects the peptide backbone conformation by forcing it towards to an extended conformation. An exception is described for β-GalNAc-Thr where the α content is increased and stabilized via hydrogen bonding between the sugar and the peptide backbone, which was not observed in the rest of the studied systems. These observations might offer an explanation for the evolutionary preference of α-linked GalNAc glycosylation instead of a β link.

Amino acid conformations control the morphological and chiral features of the self-assembled peptide nanostructures: Young investigators perspective

HYPOTHESIS

A variety of nanostructures with different chiral features can be self-assembled from short peptides with highly similar sequences. We hypothesize that these supramolecular nanostructures are ruled by the constituent amino acid residues which adopt their conformations under the influence of intra-/inter-molecular interactions during peptide self-assembly.

APPROACH

Through reviewing recent advances in the self-assembly of short peptides and focusing on the relationship between amino acid conformations, peptide secondary structures and intra-/inter-molecular interactions within the supramolecular architectures, we aim to rationalize the complex interactive processes involved in the self-assembly of short, designed peptides.

RESULTS

Given the highly complexing interactive processes, the adoption of amino acid conformations and their control over peptide self-assembly consist of 4 main steps: (1) Each amino acid residue adopts its unique conformation in a specific sequence; (2) The sequence exhibits its own main chain geometry and determines the propensity of the intermolecular alignment within the building block; (3) The structural propensity of the building block and the packing mode between them determine the self-assembled structural features such as twisting, growth and chirality; (4) In addition to intra-/inter-molecular interactions, inter-sheet and inter-building block interactions could also affect the residue conformations and nanostructures, causing structural readjustment.

Experimentally Derived and Computationally Optimized Backbone Conformational Statistics for Blocked Amino Acids

Experimentally derived, amino acid specific backbone dihedral angle distributions are invaluable for modeling data-driven conformational equilibria of proteins and for enabling quantitative assessments of the accuracies of molecular mechanics force fields. The protein coil library that is extracted from analysis of high-resolution structures of proteins has served as a useful proxy for quantifying intrinsic and context-dependent conformational distributions of amino acids. However, data that go into coil libraries will have hidden biases, and ad hoc procedures must be used to remove these biases. Here, we combine high-resolution biased information from protein structural databases with unbiased low-resolution information from spectroscopic measurements of blocked amino acids to obtain experimentally derived and computationally optimized coil-library landscapes for each of the 20 naturally occurring amino acids. Quantitative descriptions of conformational distributions require parsing of data into conformational basins with defined envelopes, centers, and statistical weights. We develop and deploy a numerical method to extract conformational basins. The weights of conformational basins are optimized to reproduce quantitative inferences drawn from spectroscopic experiments for blocked amino acids. The optimized distributions serve as touchstones for assessments of intrinsic conformational preferences and for quantitative comparisons of molecular mechanics force fields.

Improvements to the ABSINTH Force Field for Proteins Based on Experimentally Derived Amino Acid Specific Backbone Conformational Statistics

We present an improved version of the ABSINTH implicit solvation model and force field paradigm (termed ABSINTH-C) by incorporating a grid-based term that bootstraps against experimentally derived and computationally optimized conformational statistics for blocked amino acids. These statistics provide high-resolution descriptions of the intrinsic backbone dihedral angle preferences for all 20 amino acids. The original ABSINTH model generates Ramachandran plots that are too shallow in terms of the basin structures and too permissive in terms of dihedral angle preferences. We bootstrap against the reference optimized landscapes and incorporate CMAP-like residue-specific terms that help us reproduce the intrinsic dihedral angle preferences of individual amino acids. These corrections that lead to ABSINTH-C are achieved by balancing the incorporation of the new residue-specific terms with the accuracies inherent to the original ABSINTH model. We demonstrate the robustness of ABSINTH-C through a series of examples to highlight the preservation of accuracies as well as examples that demonstrate the improvements. Our efforts show how the recent experimentally derived and computationally optimized coil-library landscapes can be used as a touchstone for quantifying errors and making improvements to molecular mechanics force fields.

AMBER and CHARMM Force Fields Inconsistently Portray the Microscopic Details of Phosphorylation

Phosphorylation of serine, threonine, and tyrosine is one of the most frequently occurring and crucial post-translational modifications of proteins often associated with important structural and functional changes. We investigated the direct effect of phosphorylation on the intrinsic conformational preferences of amino acids as a potential trigger of larger structural events. We conducted a comparative study of force fields on terminally capped amino acids (dipeptides) as the simplest model for phosphorylation. Our bias-exchange metadynamics simulations revealed that all model dipeptides sampled a great heterogeneity of ensembles affected by introduction of mono- and dianionic phosphate groups. However, the detected changes in populations of backbone conformers and side-chain rotamers did not reveal a strong discriminatory shift in preferences, as could be anticipated for the bulky, charged phosphate group. Furthermore, the AMBER and CHARMM force fields provided inconsistent populations of individual conformers as well as net structural trends upon phosphorylation. Detailed analysis of ensembles revealed competition between hydration and formation of internal hydrogen bonds involving amide hydrogens and the phosphate group. The observed difference in hydration free energy and potential for hydrogen bonding in individual force fields could be attributed to the different partial atomic charges used in each force field and, hence, the different parametrization strategies. Nevertheless, conformational propensities and net structural changes upon phosphorylation are difficult to extract from experimental measurements, and existing experimental data provide limited guidance for force field assessment and further development.

Tuning of protease resistance in oligopeptides through N-alkylation

N-Methylation of amino acids is an effective way to create protease resistance in both natural and synthetic peptides. However, alkyl substituents other than N-methyl have not been extensively studied. Here, we prepare and examine a series of N-substituted peptides in which the size and length of the alkyl group is modulated. These design insights provide a unique and modular handle for tuning proteolysis in oligopeptides.

Hydration effects on Leu's polyproline II population in AcLXPNH2

Hydration is important in many fundamental processes. To investigate hydration effects on peptide conformations, we examined neighboring-residue and side-chain blocking effects in AcLXPNH2. A correlation between two effects suggests that hydration stabilizes PII more than β-structures. Our results are important for understanding the hydration effects on peptide conformations and hydration-forces in general.

The use of 4,4,4-trifluorothreonine to stabilize extended peptide structures and mimic β-strands

Pentapeptides having the sequence R-HN-Ala-Val-X-Val-Leu-OMe, where the central residue X is L-serine, L-threonine, (2S,3R)-L-CF₃-threonine and (2S,3S)-L-CF₃-threonine were prepared. The capacity of (2S,3S)- and (2S,3R)-CF₃-threonine analogues to stabilize an extended structure when introduced in the central position of pentapeptides is demonstrated by NMR conformational studies and molecular dynamics simulations. CF₃-threonine containing pentapeptides are more prone to mimic β-strands than their natural Ser and Thr pentapeptide analogues. The proof of concept that these fluorinated β-strand mimics are able to disrupt protein–protein interactions involving β-sheet structures is provided. The CF₃-threonine containing pentapeptides interact with the amyloid peptide Aβ_1-42 in order to reduce the protein–protein interactions mediating its aggregation process.

Effect of the solvent on the conformational behavior of the alanine dipeptide deduced from MD simulations

In general, peptides do not exhibit a well-defined conformational profile in solution. However, despite the experimental blurred picture associated with their structure, compelling spectroscopic evidence shows that peptides exhibit local order. The conformational profile of a peptide is the result of a balance between intramolecular interactions between different atoms of the molecule and intermolecular interactions between atoms of the molecule and the solvent. Accordingly, the conformational profile of a peptide will change upon the properties of the solvent it is soaked. To get insight into the balance between intra- and intermolecular interactions on the conformational preferences of the peptide backbone we have studied the conformational profile of the alanine dipeptide in diverse solvents using molecular dynamics as sampling technique. Solvents studied include chloroform, methanol, dimethyl sulfoxide, water and N-methylacetamide. Different treatments of the solvent have been studied in the present work including explicit solvent molecules, a generalized Born model and using the bulk dielectric constant of the solvent. The diverse calculations identify four major conformations with different populations in the diverse solvents: the C₇^eq only sampled in chloroform; the C₅ or extended conformation; the polyproline (PII) conformation and the right-handed α-helix conformation (α_R). The results of present calculations permit to analyze how the balance between intra- and intermolecular interactions explains the populations of the diverse conformations observed.

Thrombospondin-1 Mimetic Agonist Peptides Induce Selective Death in Tumor Cells: Design, Synthesis, and Structure-Activity Relationship Studies

Thrombospondin-1 (TSP-1) is a glycoprotein considered as a key actor within the tumor microenvironment. Its binding to CD47, a cell surface receptor, triggers programmed cell death. Previous studies allowed the identification of 4N1K decapeptide derived from the TSP-1/CD47 binding epitope. Here, we demonstrate that this peptide is able to induce selective apoptosis of various cancer cell lines while sparing normal cells. A structure-activity relationship study led to the design of the first serum stable TSP-1 mimetic agonist peptide able to trigger selective programmed cell death (PCD) of at least lung, breast, and colorectal cancer cells. Altogether, these results will be of valuable interest for further investigation in the design of potent CD47 agonist peptides, opening new perspectives for the development of original anticancer therapies.

Optimization of Protein Backbone Dihedral Angles by Means of Hamiltonian Reweighting

Molecular dynamics simulations depend critically on the accuracy of the underlying force fields in properly representing biomolecules. Hence, it is crucial to validate the force-field parameter sets in this respect. In the context of the GROMOS force field, this is usually achieved by comparing simulation data to experimental observables for small molecules. In this study, we develop new amino acid backbone dihedral angle potential energy parameters based on the widely used 54A7 parameter set by matching to experimental J values and secondary structure propensity scales. In order to find the most appropriate backbone parameters, close to 100 000 different combinations of parameters have been screened. However, since the sheer number of combinations considered prohibits actual molecular dynamics simulations for each of them, we instead predicted the values for every combination using Hamiltonian reweighting. While the original 54A7 parameter set fails to reproduce the experimental data, we are able to provide parameters that match significantly better. However, to ensure applicability in the context of larger peptides and full proteins, further studies have to be undertaken.

Assessing backbone solvation effects in the conformational propensities of amino acid residues in unfolded peptides

Conformational ensembles of individual amino acid residues within model GxG peptides (x representing different amino acid residues) are dominated by a mixture of polyproline II (pPII) and β-strand like conformations. We recently discovered rather substantial differences between the enthalpic and entropic contributions to this equilibrium for different amino acid residues. Isoleucine and valine exceed all other amino acid residues in terms of their rather large enthalpic stabilization and entropic destabilization of polyproline II. In order to shed light on these underlying physical mechanisms, we performed high-level DFT calculations to explore the energetics of four representative GxG peptides where x = alanine (A), leucine (L), valine (V), and isoleucine (I) in explicit water (10 H2O molecules with a polarizable continuum water model) and in vacuo. We found that the large energetic contributions to the stabilization of pPII result, to a major extent, from peptide-water, water-water interactions, and changes of the solvent self-energy. Differences between the peptide-solvent interaction energies of hydration in pPII and β-strand peptides are particularly important for the pPII ⇌ β equilibria of the more aliphatic peptides GIG and GLG. Furthermore, we performed a vibrational analysis of the four peptides in both conformations and discovered a rather substantial mixing between water motions and peptide vibrations below 700 cm(-1). We found that the respective vibrational entropies are substantially different for the considered conformations, and their contributions to the Gibbs/Helmholtz energy stabilize β-strand conformations. Taken together, our results underscore the notion of the solvent being the predominant determinant of peptide (and protein) conformations in the unfolded state.

Molecular Dynamics Simulations of 441 Two-Residue Peptides in Aqueous Solution: Conformational Preferences and Neighboring Residue Effects with the Amber ff99SB-ildn-NMR Force Field

Understanding the intrinsic conformational preferences of amino acids and the extent to which they are modulated by neighboring residues is a key issue for developing predictive models of protein folding and stability. Here we present the results of 441 independent explicit-solvent MD simulations of all possible two-residue peptides that contain the 20 standard amino acids with histidine modeled in both its neutral and protonated states. (3)J(HNHα) coupling constants and δ(Hα) chemical shifts calculated from the MD simulations correlate quite well with recently published experimental measurements for a corresponding set of two-residue peptides. Neighboring residue effects (NREs) on the average (3)J(HNHα) and δ(Hα) values of adjacent residues are also reasonably well reproduced, with the large NREs exerted experimentally by aromatic residues, in particular, being accurately captured. NREs on the secondary structure preferences of adjacent amino acids have been computed and compared with corresponding effects observed in a coil library and the average β-turn preferences of all amino acid types have been determined. Finally, the intrinsic conformational preferences of histidine, and its NREs on the conformational preferences of adjacent residues, are both shown to be strongly affected by the protonation state of the imidazole ring.

The effect of chirality and steric hindrance on intrinsic backbone conformational propensities: tools for protein design

The conformational propensities of amino acids are an amalgamation of sequence effects, environmental effects and underlying intrinsic behavior. Many have attempted to investigate neighboring residue effects to aid in our understanding of protein folding and improve structure prediction efforts, especially with respect to difficult to characterize states, such as disordered or unfolded states. Host-guest peptide series are a useful tool in examining the propensities of the amino acids free from the surrounding protein structure. Here, we compare the distributions of the backbone dihedral angles (φ/ψ) of the 20 proteogenic amino acids in two different sequence contexts using the AAXAA and GGXGG host-guest pentapeptide series. We further examine their intrinsic behaviors across three environmental contexts: water at 298 K, water at 498 K, and 8 M urea at 298 K. The GGXGG systems provide the intrinsic amino acid propensities devoid of any conformational context. The alanine residues in the AAXAA series enforce backbone chirality, thereby providing a model of the intrinsic behavior of amino acids in a protein chain. Our results show modest differences in φ/ψ distributions due to the steric constraints of the Ala side chains, the magnitudes of which are dependent on the denaturing conditions. One of the strongest factors modulating φ/ψ distributions was the protonation of titratable side chains, and the largest differences observed were in the amino acid propensities for the rarely sampled αL region.

Populations of the Minor α-Conformation in AcGXGNH2 and the α-Helical Nucleation Propensities

Intrinsic backbone conformational preferences of different amino acids are important for understanding the local structure of unfolded protein chains. Recent evidence suggests α-structure is relatively minor among three major backbone conformations for unfolded proteins. The α-helices are the dominant structures in many proteins. For these proteins, how could the α-structures occur from the least in unfolded to the most in folded states? Populations of the minor α-conformation in model peptides provide vital information. Reliable determination of populations of the α-conformers in these peptides that exist in multiple equilibriums of different conformations remains a challenge. Combined analyses on data from AcGXPNH₂ and AcGXGNH₂ peptides allow us to derive the populations of PII, β and α in AcGXGNH₂. Our results show that on average residue X in AcGXGNH₂ adopt PII, β, and α 44.7%, 44.5% and 10.8% of time, respectively. The contents of α-conformations for different amino acids define an α-helix nucleation propensity scale. With derived PII, β and α-contents, we can construct a free energy-conformation diagram on each AcGXGNH₂ in aqueous solution for the three major backbone conformations. Our results would have broad implications on early-stage events of protein folding.

The amide III vibrational circular dichroism band as a probe to detect conformational preferences of alanine dipeptide in water

The conformational preferences of blocked alanine dipeptide (ADP), Ac-Ala-NHMe, in aqueous solution were studied using vibrational circular dichroism (VCD) together with density functional theory (DFT) calculations. DFT calculations of three most representative conformations of ADP surrounded by six explicit water molecules immersed in a dielectric continuum have proven high sensitivity of amide III VCD band shape that is characteristic for each conformation of the peptide backbone. The polyproline II (PII ) and αR conformation of ADP are associated with a positive VCD band while β conformation has a negative VCD band in amide III region. Knowing this spectral characteristic of each conformation allows us to assign the experimental amide III VCD spectrum of ADP. Moreover, the amide III region of the VCD spectrum was used to determine the relative populations of conformations of ADP in water. Based on the interpretation of the amide III region of VCD spectrum we have shown that dominant conformation of ADP in water is PII which is stabilized by hydrogen bonded water molecules between CO and NH groups on the peptide backbone.

Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications

Semiempirical (SE) methods can be derived from either Hartree-Fock or density functional theory by applying systematic approximations, leading to efficient computational schemes that are several orders of magnitude faster than ab initio calculations. Such numerical efficiency, in combination with modern computational facilities and linear scaling algorithms, allows application of SE methods to very large molecular systems with extensive conformational sampling. To reliably model the structure, dynamics, and reactivity of biological and other soft matter systems, however, good accuracy for the description of noncovalent interactions is required. In this review, we analyze popular SE approaches in terms of their ability to model noncovalent interactions, especially in the context of describing biomolecules, water solution, and organic materials. We discuss the most significant errors and proposed correction schemes, and we review their performance using standard test sets of molecular systems for quantum chemical methods and several recent applications. The general goal is to highlight both the value and limitations of SE methods and stimulate further developments that allow them to effectively complement ab initio methods in the analysis of complex molecular systems.

Dynamical Network of HIV-1 Protease Mutants Reveals the Mechanism of Drug Resistance and Unhindered Activity

HIV-1 protease variants resist drugs by active and non-active-site mutations. The active-site mutations, which are the primary or first set of mutations, hamper the stability of the enzyme and resist the drugs minimally. As a result, secondary mutations that not only increase protein stability for unhindered catalytic activity but also resist drugs very effectively arise. While the mechanism of drug resistance of the active-site mutations is through modulating the active-site pocket volume, the mechanism of drug resistance of the non-active-site mutations is unclear. Moreover, how these allosteric mutations, which are 8-21 Å distant, communicate to the active site for drug efflux is completely unexplored. Results from molecular dynamics simulations suggest that the primary mechanism of drug resistance of the secondary mutations involves opening of the flexible protease flaps. Results from both residue- and community-based network analyses reveal that this precise action of protease is accomplished by the presence of robust communication paths between the mutational sites and the functionally relevant regions: active site and flaps. While the communication is more direct in the wild type, it traverses across multiple intermediate residues in mutants, leading to weak signaling and unregulated motions of flaps. The global integrity of the protease network is, however, maintained through the neighboring residues, which exhibit high degrees of conservation, consistent with clinical data and mutagenesis studies.

New QM/MM implementation of the DFTB3 method in the gromacs package

The approximate density-functional tight-binding theory method DFTB3 has been implemented in the quantum mechanics/molecular mechanics (QM/MM) framework of the Gromacs molecular simulation package. We show that the efficient smooth particle-mesh Ewald implementation of Gromacs extends to the calculation of QM/MM electrostatic interactions. Further, we make use of the various free-energy functionalities provided by Gromacs and the PLUMED plugin. We exploit the versatility and performance of the current framework in three typical applications of QM/MM methods to solve biophysical problems: (i) ultrafast proton transfer in malonaldehyde, (ii) conformation of the alanine dipeptide, and (iii) electron-induced repair of a DNA lesion. Also discussed is the further development of the framework, regarding mostly the options for parallelization.

Improved Peptide and Protein Torsional Energetics with the OPLSAA Force Field

The development and validation of new peptide dihedral parameters are reported for the OPLS-AA force field. High accuracy quantum chemical methods were used to scan φ, ψ, χ1, and χ2 potential energy surfaces for blocked dipeptides. New Fourier coefficients for the dihedral angle terms of the OPLS-AA force field were fit to these surfaces, utilizing a Boltzmann-weighted error function and systematically examining the effects of weighting temperature. To prevent overfitting to the available data, a minimal number of new residue-specific and peptide-specific torsion terms were developed. Extensive experimental solution-phase and quantum chemical gas-phase benchmarks were used to assess the quality of the new parameters, named OPLS-AA/M, demonstrating significant improvement over previous OPLS-AA force fields. A Boltzmann weighting temperature of 2000 K was determined to be optimal for fitting the new Fourier coefficients for dihedral angle parameters. Conclusions are drawn from the results for best practices for developing new torsion parameters for protein force fields.

Correct folding of an α-helix and a β-hairpin using a polarized 2D torsional potential

A new modification to the AMBER force field that incorporates the coupled two-dimensional main chain torsion energy has been evaluated for the balanced representation of secondary structures. In this modified AMBER force field (AMBER03(2D)), the main chain torsion energy is represented by 2-dimensional Fourier expansions with parameters fitted to the potential energy surface generated by high-level quantum mechanical calculations of small peptides in solution. Molecular dynamics simulations are performed to study the folding of two model peptides adopting either α-helix or β-hairpin structures. Both peptides are successfully folded into their native structures using an AMBER03(2D) force field with the implementation of a polarization scheme (AMBER03(2D)p). For comparison, simulations using a standard AMBER03 force field with and without polarization, as well as AMBER03(2D) without polarization, fail to fold both peptides successfully. The correction to secondary structure propensity in the AMBER03 force field and the polarization effect are critical to folding Trpzip2; without these factors, a helical structure is obtained. This study strongly suggests that this new force field is capable of providing a more balanced preference for helical and extended conformations. The electrostatic polarization effect is shown to be indispensable to the growth of secondary structures.

Randomizing the unfolded state of peptides (and proteins) by nearest neighbor interactions between unlike residues

To explore the influence of nearest neighbors on conformational biases in unfolded peptides, we combined vibrational and 2D NMR spectroscopy to obtain the conformational distributions of selected "GxyG" host-guest peptides in aqueous solution: GDyG, GSyG, GxLG, GxVG, where x/y=A, K, L, V. Large changes of conformational propensities were observed due to nearest-neighbor interactions, at variance with the isolated pair hypothesis. We found that protonated aspartic acid and serine lose their above-the-average preference for turn-like structures in favor of polyproline II (pPII) populations in the presence of neighbors with bulky side chains. Such residues also decrease the above-the-average pPII preference of alanine. These observations suggest that the underlying mechanism involves a disruption of the hydration shell. Thermodynamic analysis of (3) J(H(N) ,H(α) ) (T) data for each x,y residue reveals that modest changes in the conformational ensemble masks larger changes of enthalpy and entropy governing the pPII↔β equilibrium indicating a significant residue dependent temperature dependence of the peptides' conformational ensembles. These results suggest that nearest-neighbor interactions between unlike residues act as conformational randomizers close to the enthalpy-entropy compensation temperature, eliminating intrinsic biases in favor of largely balanced pPII/β dominated ensembles at physiological temperatures.

Bayesian energy landscape tilting: towards concordant models of molecular ensembles

Predicting biological structure has remained challenging for systems such as disordered proteins that take on myriad conformations. Hybrid simulation/experiment strategies have been undermined by difficulties in evaluating errors from computational model inaccuracies and data uncertainties. Building on recent proposals from maximum entropy theory and nonequilibrium thermodynamics, we address these issues through a Bayesian energy landscape tilting (BELT) scheme for computing Bayesian hyperensembles over conformational ensembles. BELT uses Markov chain Monte Carlo to directly sample maximum-entropy conformational ensembles consistent with a set of input experimental observables. To test this framework, we apply BELT to model trialanine, starting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and OPLS-AA. BELT incorporation of limited chemical shift and (3)J measurements gives convergent values of the peptide's α, β, and PPII conformational populations in all cases. As a test of predictive power, all five BELT hyperensembles recover set-aside measurements not used in the fitting and report accurate errors, even when starting from highly inaccurate simulations. BELT's principled framework thus enables practical predictions for complex biomolecular systems from discordant simulations and sparse data.