Principles of carbopeptoid folding: a molecular dynamics simulation study

Peptide science: A "rule model" for new generations of peptidomimetics

Peptides have been heavily investigated for their biocompatible and bioactive properties. Though a wide array of functionalities can be introduced by varying the amino acid sequence or by structural constraints, properties such as proteolytic stability, catalytic activity, and phase behavior in solution are difficult or impossible to impart upon naturally occurring α-L-peptides. To this end, sequence-controlled peptidomimetics exhibit new folds, morphologies, and chemical modifications that create new structures and functions. The study of these new classes of polymers, especially α-peptoids, has been highly influenced by the analysis, computational, and design techniques developed for peptides. This review examines techniques to determine primary, secondary, and tertiary structure of peptides, and how they have been adapted to investigate peptoid structure. Computational models developed for peptides have been modified to predict the morphologies of peptoids and have increased in accuracy in recent years. The combination of in vitro and in silico techniques have led to secondary and tertiary structure design principles that mirror those for peptides. We then examine several important developments in peptoid applications inspired by peptides such as pharmaceuticals, catalysis, and protein-binding. A brief survey of alternative backbone structures and research investigating these peptidomimetics shows how the advancement of peptide and peptoid science has influenced the growth of numerous fields of study. As peptide, peptoid, and other peptidomimetic studies continue to advance, we will expect to see higher throughput structural analyses, greater computational accuracy and functionality, and wider application space that can improve human health, solve environmental challenges, and meet industrial needs. STATEMENT OF SIGNIFICANCE: Many historical, chemical, and functional relations draw a thread connecting peptides to their recent cognates, the "peptidomimetics". This review presents a comprehensive survey of this field by highlighting the width and relevance of these familial connections. In the first section, we examine the experimental and computational techniques originally developed for peptides and their morphing into a broader analytical and predictive toolbox. The second section presents an excursus of the structures and properties of prominent peptidomimetics, and how the expansion of the chemical and structural diversity has returned new exciting properties. The third section presents an overview of technological applications and new families of peptidomimetics. As the field grows, new compounds emerge with clear potential in medicine and advanced manufacturing.

Molecular dynamics simulations of structure-property relationships of Tween 80 surfactants in water and at interfaces

We build a united atom model for Tween 80 (polyoxyethylene sorbitan oleates), based on the GROMOS53A6(OXY+D) force field, and apply it to two stereoisomers, three constitutional isomers, and three structures with one, two, and three tails, to represent components in the Tween 80 commercial mixture. In a preassembled micelle containing 60 molecules, the distribution of Tween tail and ethylene oxide head groups is found to be insensitive to stereoisomerization but sensitive to changes in relative lengths of the four polyoxyethylene head groups. At the air-water and oil-water interfaces, the interfacial tension is significantly lower for the constitutional isomer with a shorter W headgroup, which attaches the tail to the sorbitan ring, and for Tween 80 isomers with more than one tail group. The results indicate the possible scope for improvement in the design of polyoxyethylene sorbitan oleates with improved surface tension reduction or better spreading at the oil-water interface. We also report surfactant component distribution profiles within preassembled micelles and at interfaces that can be used for validating coarse-grained surfactant models needed for simulation of self-assembly of Tween 80 surfactant mixtures.

Develop and test a solvent accessible surface area-based model in conformational entropy calculations

It is of great interest in modern drug design to accurately calculate the free energies of protein-ligand or nucleic acid-ligand binding. MM-PBSA (molecular mechanics Poisson-Boltzmann surface area) and MM-GBSA (molecular mechanics generalized Born surface area) have gained popularity in this field. For both methods, the conformational entropy, which is usually calculated through normal-mode analysis (NMA), is needed to calculate the absolute binding free energies. Unfortunately, NMA is computationally demanding and becomes a bottleneck of the MM-PB/GBSA-NMA methods. In this work, we have developed a fast approach to estimate the conformational entropy based upon solvent accessible surface area calculations. In our approach, the conformational entropy of a molecule, S, can be obtained by summing up the contributions of all atoms, no matter they are buried or exposed. Each atom has two types of surface areas, solvent accessible surface area (SAS) and buried SAS (BSAS). The two types of surface areas are weighted to estimate the contribution of an atom to S. Atoms having the same atom type share the same weight and a general parameter k is applied to balance the contributions of the two types of surface areas. This entropy model was parametrized using a large set of small molecules for which their conformational entropies were calculated at the B3LYP/6-31G* level taking the solvent effect into account. The weighted solvent accessible surface area (WSAS) model was extensively evaluated in three tests. For convenience, TS values, the product of temperature T and conformational entropy S, were calculated in those tests. T was always set to 298.15 K through the text. First of all, good correlations were achieved between WSAS TS and NMA TS for 44 protein or nucleic acid systems sampled with molecular dynamics simulations (10 snapshots were collected for postentropy calculations): the mean correlation coefficient squares (R²) was 0.56. As to the 20 complexes, the TS changes upon binding; TΔS values were also calculated, and the mean R² was 0.67 between NMA and WSAS. In the second test, TS values were calculated for 12 proteins decoy sets (each set has 31 conformations) generated by the Rosetta software package. Again, good correlations were achieved for all decoy sets: the mean, maximum, and minimum of R² were 0.73, 0.89, and 0.55, respectively. Finally, binding free energies were calculated for 6 protein systems (the numbers of inhibitors range from 4 to 18) using four scoring functions. Compared to the measured binding free energies, the mean R² of the six protein systems were 0.51, 0.47, 0.40, and 0.43 for MM-GBSA-WSAS, MM-GBSA-NMA, MM-PBSA-WSAS, and MM-PBSA-NMA, respectively. The mean rms errors of prediction were 1.19, 1.24, 1.41, 1.29 kcal/mol for the four scoring functions, correspondingly. Therefore, the two scoring functions employing WSAS achieved a comparable prediction performance to that of the scoring functions using NMA. It should be emphasized that no minimization was performed prior to the WSAS calculation in the last test. Although WSAS is not as rigorous as physical models such as quasi-harmonic analysis and thermodynamic integration (TI), it is computationally very efficient as only surface area calculation is involved and no structural minimization is required. Moreover, WSAS has achieved a comparable performance to normal-mode analysis. We expect that this model could find its applications in the fields like high throughput screening (HTS), molecular docking, and rational protein design. In those fields, efficiency is crucial since there are a large number of compounds, docking poses, or protein models to be evaluated. A list of acronyms and abbreviations used in this work is provided for quick reference.

Calculation of configurational entropy with a Boltzmann-quasiharmonic model: the origin of high-affinity protein-ligand binding

Accurate assessment of configurational entropy remains a large challenge in biology. While many methods exist to calculate configurational entropy, there is a balance between accuracy and computational demands. Here we calculate ligand and protein conformational entropies using the Boltzmann-quasiharmonic (BQH) method, which treats the first-order entropy term by the Boltzmann expression for entropy while determining correlations using the quasiharmonic model. This method is tested by comparison with the exact Clausius expression for entropy on a range of test molecules ranging from small ligands to a protein. Using the BQH method, we then analyze the rotational and translational (R/T) entropy change upon ligand binding for five protein complexes to explore the origins of extremely tight affinity. The results suggest that in these systems such affinity is achieved by a combination of simultaneously maintaining good protein-ligand contacts while allowing significant residual R/T motion of the ligand through suitable protein motions.

Independent-Trajectories Thermodynamic-Integration Free-Energy Changes for Biomolecular Systems: Determinants of H5N1 Avian Influenza Virus Neuraminidase Inhibition by Peramivir

Free-energy changes are essential physicochemical quantities for understanding most biochemical processes. Yet, the application of accurate thermodynamic-integration (TI) computation to biological and macromolecular systems is limited by finite-sampling artifacts. In this paper, we employ independent-trajectories thermodynamic-integration (IT-TI) computation to estimate improved free-energy changes and their uncertainties for (bio)molecular systems. IT-TI aids sampling statistics of the thermodynamic macrostates for flexible associating partners by ensemble averaging of multiple, independent simulation trajectories. We study peramivir (PVR) inhibition of the H5N1 avian influenza virus neuraminidase flexible receptor (N1). Binding site loops 150 and 119 are highly mobile, as revealed by N1-PVR 20-ns molecular dynamics. Due to such heterogeneous sampling, standard TI binding free-energy estimates span a rather large free-energy range, from a 19% underestimation to a 29% overestimation of the experimental reference value (−62.2 ± 1.8 kJ mol⁻¹). Remarkably, our IT-TI binding free-energy estimate (−61.1 ± 5.4 kJ mol⁻¹) agrees with a 2% relative difference. In addition, IT-TI runs provide a statistics-based free-energy uncertainty for the process of interest. Using ∼800 ns of overall sampling, we investigate N1-PVR binding determinants by IT-TI alchemical modifications of PVR moieties. These results emphasize the dominant electrostatic contribution, particularly through the N1 E277−PVR guanidinium interaction. Future drug development may be also guided by properly tuning ligand flexibility and hydrophobicity. IT-TI will allow estimation of relative free energies for systems of increasing size, with improved reliability by employing large-scale distributed computing.

An improved relaxed complex scheme for receptor flexibility in computer-aided drug design

The interactions among associating (macro)molecules are dynamic, which adds to the complexity of molecular recognition. While ligand flexibility is well accounted for in computational drug design, the effective inclusion of receptor flexibility remains an important challenge. The relaxed complex scheme (RCS) is a promising computational methodology that combines the advantages of docking algorithms with dynamic structural information provided by molecular dynamics (MD) simulations, therefore explicitly accounting for the flexibility of both the receptor and the docked ligands. Here, we briefly review the RCS and discuss new extensions and improvements of this methodology in the context of ligand binding to two example targets: kinetoplastid RNA editing ligase 1 and the W191G cavity mutant of cytochrome c peroxidase. The RCS improvements include its extension to virtual screening, more rigorous characterization of local and global binding effects, and methods to improve its computational efficiency by reducing the receptor ensemble to a representative set of configurations. The choice of receptor ensemble, its influence on the predictive power of RCS, and the current limitations for an accurate treatment of the solvent contributions are also briefly discussed. Finally, we outline potential methodological improvements that we anticipate will assist future development.

Dynamics, Hydration, and Motional Averaging of a Loop-Gated Artificial Protein Cavity: The W191G Mutant of Cytochrome c Peroxidase in Water as Revealed by Molecular Dynamics Simulations

Five molecular dynamics simulations of the W191G cavity mutant of cytochrome c peroxidase in explicit water reveal distinct dynamic and hydration behavior depending on the closed or open state of the flexible loop gating the cavity, the binding of (K+ or small molecule) cations, and the system temperature. The conformational spaces sampled by the loop region and by the cavity significantly reduce upon binding. The largest ordering factor on water dynamics is the presence of the K+ ion occupying the gated cavity. Considerable water exchange occurs for the open-gate cavity when no ligand or cation is bound. In all cases, good correspondence is found between the calculated (ensemble-averaged) location of water molecules and the water sites determined by X-ray crystallography experiments. However, our simulations suggest that these sites do not necessarily correspond to the presence of bound water molecules. In fact, individual water molecules may repeatedly exchange within the cavity volume yet occupy on average these water sites. Four major conclusions emerge. First, it seems misleading to interpret the conformation of protein loop regions in terms of single dominant structures. Second, our simulations support the general picture of Pro 190 cis-trans isomerization as a determinant of the loop-opening mechanism. Third, receptor flexibility is fundamental for ligand binding and molecular recognition, and our results suggest its importance for the docking of small compounds to the artificial cavity. Fourth, after validation against the available experimental data, molecular dynamics simulations can be used to characterize the dynamics and exchange of water molecules and ions, providing atomic level and time-dependent information otherwise inaccessible to experiments.

N-Glycoside neoglycotrimers from 2,3,4,6-tetra-O-acetyl-β-d-glucopyranosyl azide

2,3,4,6-Tetra-O-acetyl-beta-D-glucopyranosyl azide is available on large scale from D-glucose by means of a three-step sequence involving acetylation, activation as the glycosyl bromide, and stereospecific displacement with azide anion. The azide functionality then serves as a convenient anchor upon which to introduce new functionality, usually with retention of the beta-stereochemistry. Here we report the synthesis of an amide-linked N-glycosyl trimer, by employing a Staudinger-aza-Wittig process on the azide, as well as a hybrid N-glycosyl triazole-amide-linked trimer in which the sugars are separated by 1,2,3-triazole heterocycles. Both of these neoglycotrimers are isolated in good yield with high beta-selectivity in each case.

The GROMOS software for biomolecular simulation: GROMOS05

We present the latest version of the Groningen Molecular Simulation program package, GROMOS05. It has been developed for the dynamical modelling of (bio)molecules using the methods of molecular dynamics, stochastic dynamics, and energy minimization. An overview of GROMOS05 is given, highlighting features not present in the last major release, GROMOS96. The organization of the program package is outlined and the included analysis package GROMOS++ is described. Finally, some applications illustrating the various available functionalities are presented.