Force Field Modeling of Amino Acid Conformational Energies

Vibrational Circular Dichroism Spectroscopy with a Classical Polarizable Force Field: Alanine in the Gas and Condensed Phases

Polarizable force fields are an essential component for the chemically accurate modeling of complex molecular systems with a significant degree of fluxionality, beyond harmonic or perturbative approximations. In this contribution we examine the performance of such an approach for the vibrational spectroscopy of the alanine amino acid, in the gas and condensed phases, from the Fourier transform of appropriate time correlation functions generated along molecular dynamics (MD) trajectories. While the infrared (IR) spectrum only requires the electric dipole moment, the vibrational circular dichroism (VCD) spectrum further requires knowledge of the magnetic dipole moment, for which we provide relevant expressions to be used with polarizable force fields. The AMOEBA force field was employed here to model alanine in the neutral and zwitterionic isolated forms, solvated by water or nitrogen, and as a crystal. Within this framework, comparison of the electric and magnetic dipole moments to those obtained with nuclear velocity perturbation theory based on density-functional theory for the same MD trajectories are found to agree well with one another. The statistical convergence of the IR and VCD spectra is examined and found to be more demanding in the latter case. Comparisons with experimental frequencies are also provided for the condensed phases.

Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory

We selected 145 reference organic molecules that include model fragments used in computer-aided drug design. We calculated 158 conformational energies and barriers using force fields, with wide applicability in commercial and free softwares and extensive application on the calculation of conformational energies of organic molecules, e.g. the UFF and DREIDING force fields, the Allinger's force fields MM3-96, MM3-00, MM4-8, the MM2-91 clones MMX and MM+, the MMFF94 force field, MM4, ab initio Hartree-Fock (HF) theory with different basis sets, the standard density functional theory B3LYP, the second-order post-HF MP2 theory and the Domain-based Local Pair Natural Orbital Coupled Cluster DLPNO-CCSD(T) theory, with the latter used for accurate reference values. The data set of the organic molecules includes hydrocarbons, haloalkanes, conjugated compounds, and oxygen-, nitrogen-, phosphorus- and sulphur-containing compounds. We reviewed in detail the conformational aspects of these model organic molecules providing the current understanding of the steric and electronic factors that determine the stability of low energy conformers and the literature including previous experimental observations and calculated findings. While progress on the computer hardware allows the calculations of thousands of conformations for later use in drug design projects, this study is an update from previous classical studies that used, as reference values, experimental ones using a variety of methods and different environments. The lowest mean error against the DLPNO-CCSD(T) reference was calculated for MP2 (0.35 kcal mol-1), followed by B3LYP (0.69 kcal mol-1) and the HF theories (0.81-1.0 kcal mol-1). As regards the force fields, the lowest errors were observed for the Allinger's force fields MM3-00 (1.28 kcal mol-1), ΜΜ3-96 (1.40 kcal mol-1) and the Halgren's MMFF94 force field (1.30 kcal mol-1) and then for the MM2-91 clones MMX (1.77 kcal mol-1) and MM+ (2.01 kcal mol-1) and MM4 (2.05 kcal mol-1). The DREIDING (3.63 kcal mol-1) and UFF (3.77 kcal mol-1) force fields have the lowest performance. These model organic molecules we used are often present as fragments in drug-like molecules. The values calculated using DLPNO-CCSD(T) make up a valuable data set for further comparisons and for improved force field parameterization.

A General Picture of Cucurbit[8]uril Host–Guest Binding: Recalibrating Bonded Interactions

Atomic-level understanding of the dynamic feature of host–guest interactions remains a central challenge in supramolecular chemistry. The remarkable guest binding behavior of the Cucurbiturils family of supramolecular containers makes them promising drug carriers. Among Cucurbit[n]urils, Cucurbit[8]uril (CB8) has an intermediate portal size and cavity volume. It can exploit almost all host–guest recognition motifs formed by this host family. In our previous work, an extensive computational investigation of the binding of seven commonly abused and structurally diverse drugs to the CB8 host was performed, and a general dynamic binding picture of CB8-guest interactions was obtained. Further, two widely used fixed-charge models for drug-like molecules were investigated and compared in great detail, aiming at providing guidelines in choosing an appropriate charge scheme in host-guest modelling. Iterative refitting of atomic charges leads to improved binding thermodynamics and the best root-mean-squared deviation from the experimental reference is 2.6 kcal/mol. In this work, we focus on a thorough evaluation of the remaining parts of classical force fields, i.e., the bonded interactions. The widely used general Amber force fields are assessed and refitted with generalized force-matching to improve the intra-molecular conformational preference, and thus the description of inter-molecular host–guest interactions. The interaction pattern and binding thermodynamics show a significant dependence on the modelling parameters. The refitted system-specific parameter set improves the consistency of the modelling results and the experimental reference significantly. Finally, combining the previous charge-scheme comparison and the current force-field refitting, we provide general guidelines for the theoretical modelling of host–guest binding.

Side-Chain Polarity Modulates the Intrinsic Conformational Landscape of Model Dipeptides

The intrinsic conformational preferences of small peptides may provide additional insight into the thermodynamics and kinetics of protein folding. In this study, we explore the underlying energy landscapes of two model peptides, namely, Ac-Ala-NH₂ and Ac-Ser-NH₂, using geometry-optimization-based tools developed within the context of energy landscape theory. We analyze not only how side-chain polarity influences the structural preferences of the dipeptides, but also other emergent properties of the landscape, including heat capacity profiles, and kinetics of conformational rearrangements. The contrasting topographies of the free energy landscape agree with recent results from Fourier transform microwave spectroscopy experiments, where Ac-Ala-NH₂ was found to exist as a mixture of two conformers, while Ac-Ser-NH₂ remained structurally locked, despite exhibiting an apparently rich conformational landscape.

Experimental conformational energy maps of proteins and peptides

We have presented an extensive analysis of the peptide backbone dihedral angles in the PDB structures and computed experimental Ramachandran plots for their distributions seen under a various constraints on X-ray resolution, representativeness at different sequence identity percentages, and hydrogen bonding distances. These experimental distributions have been converted into isoenergy contour plots using the approach employed previously by F. M. Pohl. This has led to the identification of energetically favored minima in the Ramachandran (ϕ, ψ) plots in which global minima are predominantly observed either in the right-handed α-helical or the polyproline II regions. Further, we have identified low energy pathways for transitions between various minima in the (ϕ,ψ) plots. We have compared and presented the experimental plots with published theoretical plots obtained from both molecular mechanics and quantum mechanical approaches. In addition, we have developed and employed a root mean square deviation (RMSD) metric for isoenergy contours in various ranges, as a measure (in kcal.mol^-1 ) to compare any two plots and determine the extent of correlation and similarity between their isoenergy contours. In general, we observe a greater degree of compatibility with experimental plots for energy maps obtained from molecular mechanics methods compared to most quantum mechanical methods. The experimental energy plots we have investigated could be helpful in refining protein structures obtained from X-ray, NMR, and electron microscopy and in refining force field parameters to enable simulations of peptide and protein structures that have higher degree of consistency with experiments. Proteins 2017; 85:979-1001. © 2017 Wiley Periodicals, Inc.

Exploring short intramolecular interactions in alkylaromatic substrates

From proteins and peptides to semiconducting polymers, aliphatic chains on aromatic groups are recurring motifs in macromolecules from very diverse application fields. Fields in which molecular folding and packing determine the macroscopic physical properties that make such advanced materials appealing in the first place. Within each macromolecule, the intrinsic structure of each unit defines how it interacts with its neighbours, ultimately opening up or denying certain backbone conformations. This eventually also determines how macromolecules interact with each other. This account deals specifically with the conformational problem of many common alkylaromatic units, examining the features of an intramolecular interaction involving a side chain with as few as three methylene groups. A set of 23 model compounds featuring an intramolecular interaction between an aliphatic X-H (X = C, N, O, and S) bond and an aromatic ring was considered. Quantitative computational analysis was made possible, thanks to complete basis set extrapolated CCSD(T) calculations and NCI topological analysis, the latter of which revealed an elaborate network of dispersive and steric interactions leading to somewhat unintuitive and unexpected results, such as the higher energetic stability of certain twisted conformational isomers over those with extended side chains. Vicinal covalent effects from polarizing groups and various heteroatoms, along with the occurrence of non-dispersive phenomena, were also investigated. The conclusions drawn from the investigation include a comprehensive set of guidelines intended to aid in the prediction of the most stable conformation for this class of building blocks. Our findings affect a variety of different research fields, including the tailoring of functional materials for organic electronics and photovoltaics, with insights into a rational treatment of conformational disorder, and the study of protein- and peptide-folding preferences, putting an emphasis on peculiar interactions between the backbone and aromatic residues.

Conformational Interconversions of Amino Acid Derivatives

Exhaustive conformational interconversions including transition structure analyses of N-acetyl-l-glycine-N-methylamide as well as its alanine, serine, and cysteine analogues have been investigated at the MP2/6-31G** level, yielding a total of 142 transition states. Improved estimates of relative energies were obtained by separately extrapolating the Hartree-Fock and MP2 energies to the basis set limit and adding the difference between CCSD(T) and MP2 results with the cc-pVDZ basis set to the extrapolated MP2 results. The performance of eight empirical force fields (AMBER94, AMBER14SB, MM2, MM3, MMFFs, CHARMM22_CMAP, OPLS_2005, and AMOEBAPRO13) in reproducing ab initio energies of transition states was tested. Our results indicate that commonly used class I force fields employing a fixed partial charge model for the electrostatic interaction provide mean errors in the ∼10 kJ/mol range for energies of conformational transition states for amino acid conformers. Modern reparametrized versions, such as CHARMM22_CMAP, and polarizable force fields, such as AMOEBAPRO13, have slightly lower mean errors, but maximal errors are still in the 35 kJ/mol range. There are differences between the force fields in their ability for reproducing conformational transitions classified according to backbone/side-chain or regions in the Ramachandran angles, but the data set is likely too small to draw any general conclusions. Errors in conformational interconversion barriers by ∼10 kJ/mol suggest that the commonly used force field may bias certain types of transitions by several orders of magnitude in rate and thus lead to incorrect dynamics in simulations. It is therefore suggested that information for conformational transition states should be included in parametrizations of new force fields.

An Atomic Counterpoise Method for Estimating Inter- and Intramolecular Basis Set Superposition Errors

An atomic counterpoise method is proposed to calculate estimates of inter- and intramolecular basis set superposition errors. The method estimates the basis set superposition error as a sum of atomic contributions and can be applied for both independent particle and electron correlation models. It is shown that the atomic counterpoise method provides results very similar to the molecular counterpoise method for intermolecular basis set superposition errors at both the HF and MP2 levels of theory with a sequence of increasingly larger basis sets. The advantage of the atomic counterpoise method is that it can be applied with equal ease to estimate intramolecular basis set superposition errors, for which few other methods exist. The atomic counterpoise method is computationally quite efficient, requiring typically double the amount of computer time as required for calculating the uncorrected energy.

Microhydration of Protonated Nα-Acetylhistidine: A Theoretical Approach

Extensive exploration of the potential energy surfaces of protonated Nα-acetylhistidine hydrated by 0-3 molecules of water was performed. The methodology combined hierarchical and genealogical (Darwin family tree) approaches using polarizable AMOEBA force field and M06 functional. It is demonstrated that this mixed approach allows recovering a larger number of conformers than the number recovered by using any one of the two methods alone. Hydration enthalpies of protonated Nα-acetylhistidine and of model compounds have been computed using higher theoretical methods, up to the G4MP2 procedure. Excellent agreement with experiment is observed for successive hydration of methylamonium and imidazolium cations using MP2/6-311++G(2d,2p)//M06/6-311++G(d,p) and G4MP2 methods, thereby validating the theory levels used for hydrated protonated Nα-acetylhistidine. It is found that the first hydration enthalpy of protonated Nα-acetylhistidine is ca. 10 kJ mol(-1) lower than that of imidazolium, a result explained by the local environment of the positively charged imidazolium moiety.

On combining Thole's induced point dipole model with fixed charge distributions in molecular mechanics force fields

The Thole induced point dipole model is combined with three different point charge fitting methods, Merz-Kollman (MK), charges from electrostatic potentials using a grid (CHELPG), and restrained electrostatic potential (RESP), and two multipole algorithms, distributed multipole analysis (DMA) and Gaussian multipole model (GMM), which can be used to describe the electrostatic potential (ESP) around molecules in molecular mechanics force fields. This is done to study how the different methods perform when intramolecular polarizability contributions are self-consistently removed from the fitting done in the force field parametrization. It is demonstrated that the polarizable versions of the partial charge models provide a good compromise between accuracy and computational efficiency in describing the ESP of small organic molecules undergoing conformational changes. For the point charge models, the inclusion of polarizability reduced the the average root mean square error of ESP over the test set by 4-10%.

Tri-peptide reference structures for the calculation of relative solvent accessible surface area in protein amino acid residues

Relative amino acid residue solvent accessibility values allow the quantitative comparison of atomic solvent-accessible surface areas in different residue types and physical environments in proteins and in protein structural alignments. Geometry-optimised tri-peptide structures in extended solvent-exposed reference conformations have been obtained for 43 amino acid residue types at a high level of quantum chemical theory. Significant increases in side-chain solvent accessibility, offset by reductions in main-chain atom solvent exposure, were observed for standard residue types in partially geometry-optimised structures when compared to non-minimised models built from identical sets of proper dihedral angles abstracted from the literature. Optimisation of proper dihedral angles led most notably to marked increases of up to 54% in proline main-chain atom solvent accessibility compared to literature values. Similar effects were observed for fully-optimised tri-peptides in implicit solvent. The relief of internal strain energy was associated with systematic variation in N, C(α) and C(β) atom solvent accessibility across all standard residue types. The results underline the importance of optimisation of 'hard' degrees of freedom (bond lengths and valence bond angles) and improper dihedral angle values from force field or other context-independent reference values, and impact on the use of standardised fixed internal co-ordinate geometry in sampling approaches to the determination of absolute values of protein amino acid residue solvent accessibility. Quantum chemical methods provide a useful and accurate alternative to molecular mechanics methods to perform energy minimisation of peptides containing non-standard (chemically modified) amino acid residues frequently present in experimental protein structure data sets, for which force field parameters may not be available. Reference tri-peptide atomic co-ordinate sets including hydrogen atoms are made freely available.

Role of electrostatic interactions in binding of peptides and intrinsically disordered proteins to their folded targets. 1. NMR and MD characterization of the complex between the c-Crk N-SH3 domain and the peptide Sos

Intrinsically disordered proteins (IDPs) often rely on electrostatic interactions to bind their structured targets. To obtain insight into the mechanism of formation of the electrostatic encounter complex, we investigated the binding of the peptide Sos (PPPVPPRRRR), which serves as a minimal model for an IDP, to the c-Crk N-terminal SH3 domain. Initially, we measured ¹⁵N relaxation rates at two magnetic field strengths and determined the binding shifts for the complex of Sos with wild-type SH3. We have also recorded a 3 μs molecular dynamics (MD) trajectory of this complex using the Amber ff99SB*-ILDN force field. The comparison of the experimental and simulated data shows that MD simulation consistently overestimates the strength of salt bridge interactions at the binding interface. The series of simulations using other advanced force fields also failed to produce any satisfactory results. To address this issue, we have devised an empirical correction to the Amber ff99SB*-ILDN force field whereby the Lennard-Jones equilibrium distance for the nitrogen-oxygen pair across the Arg-to-Asp and Arg-to-Glu salt bridges has been increased by 3%. Implementing this correction resulted in a good agreement between the simulations and the experiment. Adjusting the strength of salt bridge interactions removed a certain amount of strain contained in the original MD model, thus improving the binding of the hydrophobic N-terminal portion of the peptide. The arginine-rich C-terminal portion of the peptide, freed from the effect of the overstabilized salt bridges, was found to interconvert more rapidly between its multiple conformational states. The modified MD protocol has also been successfully used to simulate the entire binding process. In doing so, the peptide was initially placed high above the protein surface. It then arrived at the correct bound pose within ∼2 Å of the crystallographic coordinates. This simulation allowed us to analyze the details of the dynamic binding intermediate, i.e., the electrostatic encounter complex. However, an experimental characterization of this transient, weakly populated state remains out of reach. To overcome this problem, we designed the double mutant of c-Crk N-SH3 in which mutations Y186L and W169F abrogate tight Sos binding and shift the equilibrium toward the intermediate state resembling the electrostatic encounter complex. The results of the combined NMR and MD study of this engineered system will be reported in the next part of this paper.

Comprehensive analysis of energy minima of the 20 natural amino acids

Energy minima of the 20 natural amino acids (capped by a peptide bond at both the N and the C termini, CH3-C(═O)-N(H)-(H)Cα(R)-C(═O)-N(H)-CH3), were obtained by ab initio geometry optimization. Starting with a large number of minima, quickly generated by MarvinView, geometry optimization at the HF/6-31G(d,p) level of theory reduced the number of minima, followed by further optimization at the B3LYP/apc-1 and MP2/cc-pVDZ levels, which caused some minima to disappear and some stable minima to migrate on the Ramachandran map. There is a relation between the number of minima and the size and the flexibility of the side chain. The energy minima of the 20 amino acids are mainly located in the regions of βL, γL, δL, and αL of the Ramachandran map. Multipole moments of atoms occurring in the fragment [-NH-Cα-C(═O)-] common to all 20 amino acids were calculated at the three levels of theory mentioned above. The near parallelism in behavior of these moments between levels of theory is beneficial toward estimating moments with the more expensive B3LYP and MP2 methods from data calculated with the cheaper HF method. Finally, we explored the transferability of properties between different amino acids: the bond length and angles of the common fragment [-NH-Cα(HαCβ)-C'(═O)-] in all amino acids except Gly and Pro. All bond lengths are highly transferable between different amino acids, and the standard deviations are small.

Performance of four different force fields for simulations of dipeptide conformations: GlyGly, GlyGly-, GlyGly · Cl-, GlyGly · Na+ and GlyGly · (H2O)2

Monte-Carlo conformational searches with four kinds of force fields (AMBER94, MM3*, MMFFs, and OPLS-2005) were performed on glycylglycine (GlyGly), deprotonated glycylglycine (GlyGly(-)), glycylglycine chloride anion complex (GlyGly · Cl(-)), glycylglycine sodium cation complex (GlyGly · Na(+)) and glycylglycine dihydrate [GlyGly · (H2O)2]. Combined with Hartree-Fock (HF) and second-order Møller-Plesset (MP2) optimizations, conformations within an energy of 20 kJ mol(-1) were predicted. After MP2 calculations, the geometries and relative energies of the predicted structures were the same regardless of the force field used. Therefore, the performance of different force fields reflects mainly the conformational search process. For GlyGly, there was practically no difference among the four force fields. Due to the complex hydrogen bonding network when involving water, the total number of resulting conformers for GlyGly · (H2O)2 increased drastically. Moreover, the MMFFs force field fared best in finding the global minimum compared to the remaining three force fields. In describing hydrogen bonded and inter-molecular complexes, we recommend application of the MMFFs and AMBER94 force fields. Furthermore, the MMFFs and OPLS-2005 force fields have a good description of electrostatic interactions. This work will contribute to helping the reader make an optimal choice of force field, taking into account the latter's strengths and limitations.

Three-Dimensional RISM Integral Equation Theory for Polarizable Solute Models

Modeling solute polarizability is a key ingredient for improving the description of solvation phenomena. In recent years, polarizable molecular mechanics force fields have emerged that circumvent the limitations of classical fixed charge force fields by the ability to adapt their electrostatic potential distribution to a polarizing environment. Solvation phenomena are characterized by the solute's excess chemical potential, which can be computed by expensive fully atomistic free energy simulations. The alternative is to employ an implicit solvent model, which poses a challenge to the formulation of the solute-solvent interaction term within a polarizable framework. Here, we adapt the three-dimensional reference interaction site model (3D RISM) integral equation theory as a solvent model, which analytically yields the chemical potential, to the polarizable AMOEBA force field using an embedding cluster (EC-RISM) strategy. The methodology is analogous to our earlier approach to the coupling of a quantum-chemical solute description with a classical 3D RISM solvent. We describe the conceptual physical and algorithmic basis as well as the performance for several benchmark cases as a proof of principle. The results consistently show reasonable agreement between AMOEBA and quantum-chemical free energies in solution in general and allow for separate assessment of energetic and solvation-related contributions. We find that, depending on the parametrization, AMOEBA reproduces the chemical potential in better agreement with reference quantum-chemical calculations than the intramolecular energies, which suggests possible routes toward systematic improvement of polarizable force fields.

Motional timescale predictions by molecular dynamics simulations: case study using proline and hydroxyproline sidechain dynamics

We propose a new approach for force field optimizations which aims at reproducing dynamics characteristics using biomolecular MD simulations, in addition to improved prediction of motionally averaged structural properties available from experiment. As the source of experimental data for dynamics fittings, we use ¹³C NMR spin-lattice relaxation times T₁ of backbone and sidechain carbons, which allow to determine correlation times of both overall molecular and intramolecular motions. For structural fittings, we use motionally averaged experimental values of NMR J couplings. The proline residue and its derivative 4-hydroxyproline with relatively simple cyclic structure and sidechain dynamics were chosen for the assessment of the new approach in this work. Initially, grid search and simplexed MD simulations identified large number of parameter sets which fit equally well experimental J couplings. Using the Arrhenius-type relationship between the force constant and the correlation time, the available MD data for a series of parameter sets were analyzed to predict the value of the force constant that best reproduces experimental timescale of the sidechain dynamics. Verification of the new force-field (termed as AMBER99SB-ILDNP) against NMR J couplings and correlation times showed consistent and significant improvements compared to the original force field in reproducing both structural and dynamics properties. The results suggest that matching experimental timescales of motions together with motionally averaged characteristics is the valid approach for force field parameter optimization. Such a comprehensive approach is not restricted to cyclic residues and can be extended to other amino acid residues, as well as to the backbone. Proteins 2014; 82:195–215. © 2013 Wiley Periodicals, Inc.

QM and QM/MM simulations of proteins

Molecular dynamics simulations of biomolecules have matured into powerful tools of structural biology. In addition to the commonly used empirical force field potentials, quantum mechanical descriptions are gaining popularity for structure optimization and dynamic simulations of peptides and proteins. In this chapter, we introduce methodological developments such as the QM/MM framework and linear-scaling QM that make efficient calculations on large biomolecules possible. We identify the most common scenarios in which quantum descriptions of peptides and proteins are employed, such as structural refinement, force field development, treatment of unusual residues, and predicting spectroscopic and exited state properties. The benefits and shortcomings of QM potentials, in comparison to classical force fields, are discussed, with special emphasis on the sampling problems of protein conformational space. Finally, recent examples of QM/MM calculations in light-sensitive membrane proteins illustrate typical applications of the reviewed methods.

Polarizable force fields

This chapter provides an overview of the most common methods for including an explicit description of electronic polarization in molecular mechanics force fields: the induced point dipole, shell, and fluctuating charge models. The importance of including polarization effects in biomolecular simulations is discussed, and some of the most important achievements in the development of polarizable biomolecular force fields to date are highlighted.

Modeling Structural Coordination and Ligand Binding in Zinc Proteins with a Polarizable Potential

As the second most abundant cation in human body, zinc is vital for the structures and functions of many proteins. Zinc-containing matrix metalloproteinases (MMPs) have been widely investigated as potential drug targets in a range of diseases ranging from cardiovascular disorders to cancers. However, it remains a challenge in theoretical studies to treat zinc in proteins with classical mechanics. In this study, we examined Zn(2+) coordination with organic compounds and protein side chains using a polarizable atomic multipole based electrostatic model. We find that polarization effect plays a determining role in Zn(2+) coordination geometry in both matrix metalloproteinase (MMP) complexes and in zinc-finger proteins. In addition, the relative binding free energies of selected inhibitors binding with MMP13 have been estimated and compared with experimental results. While not directly interacting with the small molecule inhibitors, the permanent and polarizing field of Zn(2+) exerts a strong influence on the relative affinities of the ligands. The simulation results also reveal the polarization effect on binding is ligand dependent and thus difficult to be incorporated into fixed-charge models implicitly.

The stability of Cα peptide radicals: why glycyl radical enzymes?

The conformational space of dipeptide models derived from glycine, alanine, phenylalanine, proline, tyrosine, and cysteine has been searched extensively and compared with the corresponding C(α) dipeptide radicals at the G3(MP2)-RAD level of theory. The results indicate that the (least-substituted) glycine dipeptide radical is the thermochemically most stable of these species. Analysis of the structural parameters indicates that this is due to repulsive interactions between the C(α) substituents and peptide units in the radical. A comparison of the conformational preferences of dipeptide radicals and their closed-shell parents also indicates that radical stability is a strongly conformation-dependent property.

Experimental verification of force fields for molecular dynamics simulations using Gly-Pro-Gly-Gly

Experimental NMR verification of MD simulations using 12 different force fields (AMBER, CHARMM, GROMOS, and OPLS-AA) and 5 different water models has been undertaken to identify reliable MD protocols for structure and dynamics elucidations of small open chain peptides containing Gly and Pro. A conformationally flexible tetrapeptide Gly-Pro-Gly-Gly was selected for NMR (3)J-coupling, chemical shift, and internuclear distance measurements, followed by their calculations using 2 μs long MD simulations in water. In addition, Ramachandran population maps for Pro-2 and Gly-3 residues of GPGG obtained from MD simulations were used for detailed comparisons with similar maps from the protein data bank (PDB) for large number of Gly and Pro residues in proteins. The MD simulations revealed strong dependence of the populations and geometries of preferred backbone and side chain conformations, as well as the time scales of the peptide torsional transitions on the force field used. On the basis of the analysis of the measured and calculated data, AMBER99SB is identified as the most reliable force field for reproducing NMR measured parameters, which are dependent on the peptide backbone and the Pro side chain geometries and dynamics. Ramachandran maps showing the dependence of conformational populations as a function of backbone ϕ/ψ angles for Pro-2 and Gly-3 residues of GPGG from MD simulations using AMBER99SB, AMBER03, and CHARMM were found to resemble similar maps for Gly and Pro residues from the PDB survey. Three force fields (AMBER99, AMBER99ϕ, and AMBER94) showed the least satisfactory agreement with both the solution NMR and the PDB survey data. The poor performance of these force fields is attributed to their propensity to overstabilize helical peptide backbone conformations at the Pro-2 and Gly-3 residues. On the basis of the similarity of the MD and PDB Ramachandran plots, the following sequence of transitions is suggested for the Gly backbone conformation: α(L) ⇆ β(PR) ⇆ β(S) ⇆ β(P) ⇆ α, where backbone secondary structures α(L) and α are associated with helices and turns, β(P) and β(PR) correspond to the left- and right-handed polyproline II structures and β(S) denotes the fully stretched backbone conformation. Compared to the force field dependence, less significant, but noteworthy, variations in the populations of the peptide backbone conformations were observed. For different solvent models considered, a correlation was noted between the number of torsional transitions in GPGG and the water self-diffusion coefficient on using TIP3P, TIP4P, and TIP5P models. In addition to MD results, we also report DFT derived Karplus relationships for Gly and Pro residues using B972 and B3LYP functionals.

A water potential based on multipole moments trained by machine learning — Reducing maximum energy errors

A potential that strives to represent the Coulomb interaction realistically must include polarization. In our approach, three decisions were made to accomplish this: (i) define an atom according to quantum chemical topology (QCT), (ii) express the interaction between atoms via their multipole moments, and (iii) use machine learning to capture the response of an atomic multipole moment to a change in this atom’s environment. This approach avoids explicit (distributed) polarizabilities and eliminates the problem of polarization catastrophe. Previously, we showed ( Phys. Chem. Chem. Phys. 2009, 11, 6365 ) that a machine learning method called kriging predicted atomic multipole moments more accurately than competing machine learning methods. This was established for the atoms of a central water molecule in water clusters, from the dimer to the hexamer. The prediction errors in all multipole moments were collectively assessed by errors in total interaction energy, for thousands of clusters configurations. Here, we target the maximum errors, with an eye on reducing the worst predictions that the potential may return. We demonstrate proof-of-principle for the water dimer using local kriging.

Computational investigation on the mechanism and the stereoselectivity of Morita-Baylis-Hillman reaction and the effect of the bifunctional catalyst N-methylprolinol

The mechanism of the Morita-Baylis-Hillman (MBH) reaction between formaldehyde and methyl vinyl ketone (MVK) catalyzed by N-methylprolinol was investigated using density functional theory (DFT) method. The overall reaction includes two steps: C-C bond formation and hydrogen migration. In the presence of water, the hydrogen migration occurs via a six-membered ring transition state and the corresponding energy barrier decreases dramatically, and therefore the RDS is the C-C bond formation step. The calculations indicate that the C-C bond formation step controls the stereochemistry of the reaction. In this step, the hydrogen bonding induces the direction of the attack of enamine to aldehyde from the -OH group side of N-methylprolinol. The energy-favored transition states are mainly stabilized by hydrogen bonding, while the chirality of the products is affected by the hydrogen bonding and the steric hindrance. The calculations correctly reproduce the major product in (R)-configuration, which is consistent with the experimental observation.

The SAAP force field: development of the single amino acid potentials for 20 proteinogenic amino acids and Monte Carlo molecular simulation for short peptides

Molecular simulation by using force field parameters has been widely applied in the fields of peptide and protein research for various purposes. We recently proposed a new all-atom protein force field, called the SAAP force field, which utilizes single amino acid potentials (SAAPs) as the fundamental elements. In this article, whole sets of the SAAP force field parameters in vacuo, in ether, and in water have been developed by ab initio calculation for all 20 proteinogenic amino acids and applied to Monte Carlo molecular simulation for two short peptides. The side-chain separation approximation method was employed to obtain the SAAP parameters for the amino acids with a long side chain. Monte Carlo simulation for Met-enkephalin (CHO-Tyr-Gly-Gly-Phe-Met-NH2) by using the SAAP force field revealed that the conformation in vacuo is mainly controlled by strong electrostatic interactions between the amino acid residues, while the SAAPs and the interamino acid Lennard-Jones potentials are predominant in water. In ether, the conformation would be determined by the combination of the three components. On the other hand, the SAAP simulation for chignolin (H-Gly-Tyr-Asp-Pro-Glu-Thr-Gly-Thr-Trp-Gly-OH) reasonably reproduced a native-like beta-hairpin structure in water although the C-terminal and side-chain conformations were different from the native ones. It was suggested that the SAAP force field is a useful tool for analyzing conformations of polypeptides in terms of intrinsic conformational propensities of the single amino acid units.