Metadynamics as a tool for mapping the conformational and free-energy space of peptides--the alanine dipeptide case study

Crystal structure of lipase from Pseudomonas aeruginosa reveals an unusual catalytic triad conformation

The Pseudomonas aeruginosa lipase PaL catalyzes the stereoselective hydrolysis of menthyl propionate to produce L-menthol. The lack of a three-dimensional structure of PaL has so far prevented a detailed understanding of its stereoselective reaction mechanism. Here, the crystal structure of PaL was determined at a resolution of 1.80 Å by single-wavelength anomalous diffraction. In the apo-PaL structure, the catalytic His302 is located in a long loop on the surface that is solvent exposed. His302 is distant from the other two catalytic residues, Asp274 and Ser164. This configuration of catalytic residues is unusual for lipases. Using metadynamics simulations, we observed that the enzyme undergoes a significant conformational change upon ligand binding. We also explored the catalytic and stereoselectivity mechanisms of PaL by all-atom molecular dynamics simulations. These findings could guide the engineering of PaL with an improved diastereoselectivity for L-menthol production.

Neighbor effect on conformational spaces of alanine residue in azapeptides

The conformational properties of Alanine (Ala) residue have been investigated to understand protein folding and develop force fields. In this work, we examined the neighbor effect on the conformational spaces of Ala residue using model azapeptides, Ac-Ala-azaGly-NHMe (3, AaG), and Ac-azaGly-Ala-NHMe (4, aGA1). Ramachandran energy maps were generated by scanning (φ, ψ) dihedral angles of the Ala residues in models with the fixed dihedral angles (φ = ±90°, ψ = ±0° or ±180°) of azaGly residue using LCgau-BOP and LCgau-BOP + LRD functionals in the gas and water phases. The integral-equation-formalism polarizable continuum model (IEF-PCM) and a solvation model density (SMD) were employed to mimic the solvation effect. The most favorable conformation of Ala residue in azapeptide models is found as the polyproline II (βP), inverse γ-turn (γ'), β-sheet (βS), right-handed helix (αR), or left-handed helix (αL) depending on the conformation of neighbor azaGly residue in isolated form. Solvation methods exhibit that the Ala residue favors the βP, δR, and αR conformations regardless of its position in azapeptides 3 and 4 in water. Azapeptide 5, Ac-azaGly-Ala-NH2 (aGA2), was synthesized to evaluate the theoretical results. The X-ray structure showed that azaGly residue adopts the polyproline II (βP) and Ala residue adopts the right-handed helical (αR) structure in aGA2. The conformational preferences of aGA2 and the dimer structure of aGA2 based on the X-ray structure were examined to assess the performance of DFT functionals. In addition, the local minima of azapeptide 6, Ac-Phe-azaGly-NH2 (FaG), were compared with the previous experimental results. SMD/LCgau-BOP + LRD methods agreed well with the reported experimental results. The results suggest the importance of weak dispersion interactions, neighbor effect, and solvent influence in the conformational preferences of Ala residue in model azapeptides.

One Descriptor to Fold Them All: Harnessing Intuition and Machine Learning to Identify Transferable Lasso Peptide Reaction Coordinates

Identifying optimal reaction coordinates for complex conformational changes and protein folding remains an outstanding challenge. This study combines collective variable (CV) discovery based on chemical intuition and machine learning with enhanced sampling to converge the folding free energy landscape of lasso peptides, a unique class of natural products with knot-like tertiary structures. This knotted scaffold imparts remarkable stability, making lasso peptides resistant to proteolytic degradation, thermal denaturation, and extreme pH conditions. Although their direct synthesis would enable therapeutic design, it has not yet been possible due to the improbable occurrence of spontaneous lasso folding. Thus, simulations characterizing the folding propensity are needed to identify strategies for increasing access to the lasso architecture by stabilizing the pre-lasso ensemble before isopeptide bond formation. Herein, harmonic linear discriminant analysis (HLDA) is combined with metadynamics-enhanced sampling to discover CVs capable of distinguishing the pre-lasso fold and converging the folding propensity. Intuitive CVs are compared to iterative rounds of HLDA to identify CVs that not only accomplish these goals for one lasso peptide but also seem to be transferable to others, establishing a protocol for the identification of folding reaction coordinates for lasso peptides.

Score Dynamics: Scaling Molecular Dynamics with Picoseconds Time Steps via Conditional Diffusion Model

We propose score dynamics (SD), a general framework for learning accelerated evolution operators with large timesteps from molecular dynamics (MD) simulations. SD is centered around scores or derivatives of the transition log-probability with respect to the dynamical degrees of freedom. The latter play the same role as force fields in MD but are used in denoising diffusion probability models to generate discrete transitions of the dynamical variables in an SD time step, which can be orders of magnitude larger than a typical MD time step. In this work, we construct graph neural network-based SD models of realistic molecular systems that are evolved with 10 ps timesteps. We demonstrate the efficacy of SD with case studies of the alanine dipeptide and short alkanes in aqueous solution. Both equilibrium predictions derived from the stationary distributions of the conditional probability and kinetic predictions for the transition rates and transition paths are in good agreement with MD. Our current SD implementation is about 2 orders of magnitude faster than the MD counterpart for the systems studied in this work. Open challenges and possible future remedies to improve SD are also discussed.

CREST-A program for the exploration of low-energy molecular chemical space

Conformer-rotamer sampling tool (CREST) is an open-source program for the efficient and automated exploration of molecular chemical space. Originally developed in Pracht et al. [Phys. Chem. Chem. Phys. 22, 7169 (2020)] as an automated driver for calculations at the extended tight-binding level (xTB), it offers a variety of molecular- and metadynamics simulations, geometry optimization, and molecular structure analysis capabilities. Implemented algorithms include automated procedures for conformational sampling, explicit solvation studies, the calculation of absolute molecular entropy, and the identification of molecular protonation and deprotonation sites. Calculations are set up to run concurrently, providing efficient single-node parallelization. CREST is designed to require minimal user input and comes with an implementation of the GFNn-xTB Hamiltonians and the GFN-FF force-field. Furthermore, interfaces to any quantum chemistry and force-field software can easily be created. In this article, we present recent developments in the CREST code and show a selection of applications for the most important features of the program. An important novelty is the refactored calculation backend, which provides significant speed-up for sampling of small or medium-sized drug molecules and allows for more sophisticated setups, for example, quantum mechanics/molecular mechanics and minimum energy crossing point calculations.

Minimum Free Energy Pathways of Reactive Processes with Nudged Elastic Bands

The determination of minimum free energy pathways (MFEP) is one of the most widely used strategies to study reactive processes. For chemical reactions in complex environments, the combination of quantum mechanics (QM) with a molecular mechanics (MM) representation is usually necessary in a hybrid QM/MM framework. However, even within the QM/MM approximation, the affordable sampling of the phase space is, in general, quite restricted. To reduce drastically the computational cost of the simulations, several methods such as umbrella sampling require performing a priori a selection of a reaction coordinate. The quality of the computed results, in an affordable computational time, is intimately related to the reaction coordinate election which is, in general, a nontrivial task. In this work, we provide an approach to model reactive processes in complex environments that does not require the a priori selection of a reaction coordinate. The proposed methodology combines QM/MM simulations with an extrapolation of the nudged elastic bands (NEB) method to the free energy surface (FENEB). We present and apply our own FENEB scheme to optimize MFEP in different reactive processes, using QM/MM frameworks at semiempirical and density functional theory levels. Our implementation is based on performing the FENEB optimization by uncoupling the optimization of the band in a perpendicular and tangential direction. In each step, a full optimization with the spring force is performed, which guarantees that the images remain evenly distributed. The robustness of the method and the influence of sampling on the quality of the optimized MFEP and its associated free energy barrier are studied. We show that the FENEB method provides a good estimation of the reaction barrier even with relatively short simulation times, supporting that its combination with QM/MM frameworks provides an adequate tool to study chemical processes in complex environments.

LINES: Log-Probability Estimation via Invertible Neural Networks for Enhanced Sampling

It is very challenging to sample a molecular process with large activation energies using molecular dynamics simulations. Current enhanced sampling methodologies, such as umbrella sampling and metadynamics, rely on the identification of appropriate reaction coordinates for a system. In this paper, we developed a method for log-probability estimation via invertible neural networks for enhanced sampling (LINES). This iterative scheme utilizes a normalizing flow machine learning model to learn the underlying free energy surface (FES) of a system as a function of molecular coordinates and then applies a gradient-based optimization method to the learned normalizing flow to identify reaction coordinates. A biasing potential is then evaluated over a tabulated grid of the reaction coordinate values, which can be applied to the next round of simulations for enhanced sampling, resulting in more efficient sampling. We tested the accuracy and efficiency of the LINES method in sampling the FES using the alanine dipeptide system. We also demonstrated the effectiveness of identification of reaction coordinates through simulation of cyclobutanol unbinding from β-cyclodextrin and the folding/unfolding of CLN025─a variant of the peptide Chignolin. The LINES method can be extended to the study of large-scale protein systems with complex nonlinear reaction pathways.

Application of molecular dynamics simulation in biomedicine

Molecular dynamics (MD) simulation has been widely used in the field of biomedicine to study the conformational transition of proteins caused by mutation or ligand binding/unbinding. It provides some perspectives those are difficult to find in traditional biochemical or pathological experiments, for example, detailed effects of mutations on protein structure and protein-protein/ligand interaction at the atomic level. In this review, a broad overview on conformation changes and drug discovery by MD simulation is given. We first discuss the preparation of protein structure for MD simulation, which is a key step that determines the accuracy of the simulation. Then, we summarize the applications of commonly used force fields and MD simulations in scientific research. Finally, enhanced sampling methods and common applications of these methods are introduced. In brief, MD simulation is a powerful tool and it can be used to guide experimental study. The combination of MD simulation and experimental techniques is an a priori means to solve the biomedical problems and give a deep understanding on the relationship between protein structure and function.

Property Map Collective Variable as a Useful Tool for a Force Field Correction

The accuracy of biomolecular simulations depends on the accuracy of an empirical molecular mechanics potential known as a force field: a set of parameters and expressions to estimate the potential from atomic coordinates. Accurate parametrization of force fields for small organic molecules is a challenge due to their high diversity. One of the possible approaches is to apply a correction to the existing force fields. Here, we propose an approach to estimate the density functional theory (DFT)-derived force field correction which is calculated during the run of molecular dynamics without significantly affecting its speed. Using the formula known as a property map collective variable, we approximate the force field correction by a weighted average of this force field correction calculated only for a small series of reference structures. To validate this method, we used seven AMBER force fields, and we show how it is possible to convert one force field to behave like the other one. We also present the force field correction for the important anticancer drug Imatinib as a use case example. Our method appears to be suitable for adjusting the force field for general drug-like molecules. We provide a pipeline that generates the correction; this pipeline is available at https://pmcvff-correction.cerit-sc.cz/.

Peptide Isomerization is Suppressed at the Air-Water Interface

We use molecular dynamics simulations to study the thermodynamics and kinetics of alanine dipeptide isomerization at the air-water interface. Thermodynamically, we find an affinity of the dipeptide to the interface. This affinity arises from stabilizing intramolecular interactions that become unshielded as the dipeptide is desolvated. Kinetically, we consider the rate of transitions between the α_L and β conformations of alanine dipeptide and evaluate it as a continuous function of the distance from the interface using a recent extension of transition path sampling, TPS+U. The rate of isomerization at the Gibbs dividing surface is suppressed relative to the bulk by a factor of 3. Examination of the ensemble of transition states elucidates the role of solvent degrees of freedom in mediating favorable intramolecular interactions along the reaction pathway of isomerization. Near the air-water interface, water is less effective at mediating these intramolecular interactions.

Transmembrane penetration mechanism of cyclic pollutants inspected by molecular dynamics and metadynamics: the case of morpholine, phenol, 1,4-dioxane and oxane

The presence of industrially produced chemicals in water is often not monitored, while their passive transport and accumulation can cause serious damage in living cells. Molecular dynamics simulations are an effective way to understand the mechanism of the action of these pollutants. In this paper, the passive membrane transport of 1,4-dioxane, phenol, oxane and morpholine was investigated and analyzed thoroughly from structural and energetic points of view. Free energy profiles for pollutant and water penetration into the bilayer were obtained from well-tempered metadynamics (WT-MD) simulations and a mass density-based approach. It was found that all four investigated compounds can penetrate biological membranes and affect the free energy profile of water penetration. Out of the investigated species, oxane has the thermodynamically most preferred position in the bilayer center, leading to a lower free energy barrier of water molecules by 3 kJ mol-1, resulting in 5 times more water molecules in the bilayer center. The concentration dependence of free energy was tested at two different phenol concentrations using WT-MD, and it was found that the higher phenol concentration lowers the main barrier by 3 kJ mol-1. Density-based free energy calculations were found to reproduce the results of WT-MD within the limits of chemical accuracy.

Temperature Dependence of Peptide Conformational Equilibria from Simulations at a Single Temperature

Understanding the structure of proteins is key to unraveling their function in biological processes. Thus, significant attention has been paid to the calculation of conformational free energies. In this paper, we demonstrate a simple extension of fluctuation theory that permits the calculation of the temperature derivative of the conformational free energy, and hence the internal energy and entropy, from single-temperature simulations. The method further enables the decomposition into the contribution of different interactions present in the system to the internal energy surface. We illustrate the method for the canonical test system of alanine dipeptide in aqueous solution, for which we examine the free energy as a function of two dihedral angles. This system, like many, is most effectively treated using accelerated sampling methods and we show how the present approach is compatible with an important class of these, those that introduce a bias potential, by implementing it within metadynamics.

Pressure dependence of vibrational optical activity of model biomolecules. A computational study

Change of molecular properties with pressure is an attracting means to regulate molecular reactivity or biological activity. However, the effect is usually small and so far explored rather scarcely. To obtain a deeper insight and estimate the sensitivity of vibrational optical activity spectra to pressure-induced conformational changes, we investigate small model molecules. The Ala-Ala dipeptide, isomaltose disaccharide and adenine-uracil dinucleotide were chosen to represent three different biomolecular classes. The pressure effects were modeled by molecular dynamics and density functional theory simulations. The dinucleotide was found to be the most sensitive to the pressure, whereas for the disaccharide the smallest changes are predicted. Pressure-induced relative intensity changes in vibrational circular dichroism and Raman optical activity spectra are predicted to be 2-3-times larger than for non-polarized IR and Raman techniques.

Unraveling the Molecular Mechanism of Prion H2 C-Terminus Misfolding by Metadynamics Simulations

Conformational transition from the normal cellular form of prion protein (PrP^C) to the pathogenic "scrapie" form (PrP^Sc) is considered to be a key event in the occurrence of prion disease. Additionally, the H2 C-terminus is widely considered to be a vital site for PrP conformational transition, which can be used as an important region to explore the potential mechanism of PrP misfolding. Therefore, to study the misfolding mechanism of PrP, 500 ns well-tempered metadynamics simulations were performed by focusing on the H2 C-terminus of PrP. For comparison, three systems were designed in total, including PrP in neutral and acidic conditions, as well as H187R mutant. The resulting free energy surfaces (FESs) obtained from metadynamics simulations reveal that acidic conditions and H187R mutation can facilitate PrP misfolding by decreasing free energy barriers for conformational transition and forming energy stable conformational states. Further analyses aimed at H2 C-terminus show that due to the increase of positive charge on residue 187 in both acidic and H187R systems, the electrostatic repulsion of residue 187 and R136/R156 increases greatly, which disrupts the electrostatic interaction network around H2 C-terminus and exposes the hydrophobic core to the solvent. Taken together, acidic conditions and H187R mutation can accelerate PrP misfolding mainly by forming more energetically stable metastable conformations with lower free energy barriers, and electrostatic network disruption involving residue 187 drives the initial misfolding of H2 C-terminus. This study provides quantitative insight into the related function of the H2 C-terminus in the PrP misfolding process, which may guide H2 C-terminus mediated drug design in the future.

Automated exploration of the low-energy chemical space with fast quantum chemical methods

We propose and discuss an efficient scheme for the in silico sampling for parts of the molecular chemical space by semiempirical tight-binding methods combined with a meta-dynamics driven search algorithm. The focus of this work is set on the generation of proper thermodynamic ensembles at a quantum chemical level for conformers, but similar procedures for protonation states, tautomerism and non-covalent complex geometries are also discussed. The conformational ensembles consisting of all significantly populated minimum energy structures normally form the basis of further, mostly DFT computational work, such as the calculation of spectra or macroscopic properties. By using basic quantum chemical methods, electronic effects or possible bond breaking/formation are accounted for and a very reasonable initial energetic ranking of the candidate structures is obtained. Due to the huge computational speedup gained by the fast low-cost quantum chemical methods, overall short computation times even for systems with hundreds of atoms (typically drug-sized molecules) are achieved. Furthermore, specialized applications, such as sampling with implicit solvation models or constrained conformational sampling for transition-states, metal-, surface-, or noncovalently bound complexes are discussed, opening many possible applications in modern computational chemistry and drug discovery. The procedures have been implemented in a freely available computer code called CREST, that makes use of the fast and reliable GFNn-xTB methods.

Quantum Mechanical and Molecular Mechanics Modeling of Membrane-Embedded Rhodopsins

Computational chemistry provides versatile methods for studying the properties and functioning of biological systems at different levels of precision and at different time scales. The aim of this article is to review the computational methodologies that are applicable to rhodopsins as archetypes for photoactive membrane proteins that are of great importance both in nature and in modern technologies. For each class of computational techniques, from methods that use quantum mechanics for simulating rhodopsin photophysics to less-accurate coarse-grained methodologies used for long-scale protein dynamics, we consider possible applications and the main directions for improvement.

Amino Acid Interaction (INTAA) web server

Large biomolecules-proteins and nucleic acids-are composed of building blocks which define their identity, properties and binding capabilities. In order to shed light on the energetic side of interactions of amino acids between themselves and with deoxyribonucleotides, we present the Amino Acid Interaction web server (http://bioinfo.uochb.cas.cz/INTAA/). INTAA offers the calculation of the residue Interaction Energy Matrix for any protein structure (deposited in Protein Data Bank or submitted by the user) and a comprehensive analysis of the interfaces in protein-DNA complexes. The Interaction Energy Matrix web application aims to identify key residues within protein structures which contribute significantly to the stability of the protein. The application provides an interactive user interface enhanced by 3D structure viewer for efficient visualization of pairwise and net interaction energies of individual amino acids, side chains and backbones. The protein-DNA interaction analysis part of the web server allows the user to view the relative abundance of various configurations of amino acid-deoxyribonucleotide pairs found at the protein-DNA interface and the interaction energies corresponding to these configurations calculated using a molecular mechanical force field. The effects of the sugar-phosphate moiety and of the dielectric properties of the solvent on the interaction energies can be studied for the various configurations.

Rotational Dynamics of Linkers in Metal⁻Organic Frameworks

Among the numerous fascinating properties of metal⁻organic frameworks (MOFs), their rotational dynamics is perhaps one of the most intriguing, with clear consequences for adsorption and separation of molecules, as well as for optical and mechanical properties. A closer look at the rotational mobility in MOF linkers reveals that it is not only a considerably widespread phenomenon, but also a fairly diverse one. Still, the impact of these dynamics is often understated. In this review, we address the various mechanisms of linker rotation reported in the growing collection of literature, followed by a highlight of the methods currently used in their study, and we conclude with the impacts that such dynamics have on existing and future applications.

Estimation of the infinitesimal generator by square-root approximation

In recent years, for the analysis of molecular processes, the estimation of time-scales and transition rates has become fundamental. Estimating the transition rates between molecular conformations is-from a mathematical point of view-an invariant subspace projection problem. We present a method to project the infinitesimal generator acting on function space to a low-dimensional rate matrix. This projection can be performed in two steps. First, we discretize the conformational space in a Voronoi tessellation, then the transition rates between adjacent cells is approximated by the geometric average of the Boltzmann weights of the Voronoi cells. This method demonstrates that there is a direct relation between the potential energy surface of molecular structures and the transition rates of conformational changes. We will show also that this approximation is correct and converges to the generator of the Smoluchowski equation in the limit of infinitely small Voronoi cells. We present results for a two dimensional diffusion process and alanine dipeptide as a high-dimensional system.

The influence of solvent on conformational properties of peptides with Aib residue-a DFT study

The conformational propensities of the Aib residue on the example of two model peptides Ac-Aib-NHMe (1) and Ac-Aib-NMe2 (2), were studied by B3LYP and M06-2X functionals, in the gas phase and in the polar solvents. To verify the reliability of selected functionals, we also performed MP2 calculations for the tested molecules in vacuum. Polarizable continuum models (PCM and SMD) were used to estimate the solvent effect. Ramachandran maps were calculated to find all energy minima. Noncovalent intramolecular interactions due to hydrogen-bonds and dipole attractions between carbonyl groups are responsible for the relative stabilities of the conformers. In order to verify the theoretical results, the available conformations of similar X-ray structures from the Cambridge Crystallographic Data Center (CCDC) were analyzed. The results of the calculations show that both derivatives with the Aib residue in the gas phase prefer structures stabilized by intramolecular N-H⋯O hydrogen bonds, i.e., C5 and C7 conformations, while polar solvent promotes helical conformation with φ, ψ values equal to +/-60°, +/-40°. In addition, in the case of molecule 2, the helical conformation is the only one available in the polar environment. This result is fully consistent with the X-ray data. Graphical abstract Effect of solvent on the Ramachandran maps of the model peptides with Aib residue.

The effects of replacing the water model while decoupling water-water and water-solute interactions on computed properties of simple salts

The effects of decoupling the water-water and water-solute interactions are studied with selected mono-valent ions as the solute. Using the ion-water cross terms developed for the BLYPSP-4F water model, we replaced the water potential with WAIL, TIP4P, and TIP3P without changing the ion-water parameters. When the adaptive force matching (AFM) derived BLYPSP-4F model is replaced by the other AFM derived WAIL model, the difference in ion properties, such as hydration free energies, radial distribution functions, relative diffusion constants, is negligible, demonstrating the feasibility for combining AFM parameters from different sources. Interestingly, when the AFM-derived ion-water cross-terms are used with a non-AFM based water model, only small changes in the ion properties are observed. The final combined models with TIP3P or TIP4P water reproduce the salt hydration free energies within 6% of experiments. The feasibility of combining AFM models with other non-AFM models is of significance since such combinations allow more complex systems to be studied without specific parameterization. In addition, the study suggests an interesting prospect of reusing the cross-terms when a part of a general force field is replaced with a different model. The prevailing practice, which is to re-derive all cross-terms with combining rules, may not have been optimal.

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.

Free Energy Landscapes of Alanine Oligopeptides in Rigid-Body and Hybrid Water Models

Replica exchange molecular dynamics is used to study the effect of different rigid-body (mTIP3P, TIP4P, SPC/E) and hybrid (H1.56, H3.00) water models on the conformational free energy landscape of the alanine oligopeptides (acAnme and acA5nme), in conjunction with the CHARMM22 force field. The free energy landscape is mapped out as a function of the Ramachandran angles. In addition, various secondary structure metrics, solvation shell properties, and the number of peptide-solvent hydrogen bonds are monitored. Alanine dipeptide is found to have similar free energy landscapes in different solvent models, an insensitivity which may be due to the absence of possibilities for forming i-(i + 4) or i-(i + 3) intrapeptide hydrogen bonds. The pentapeptide, acA5nme, where there are three intrapeptide backbone hydrogen bonds, shows a conformational free energy landscape with a much greater degree of sensitivity to the choice of solvent model, though the three rigid-body water models differ only quantitatively. The pentapeptide prefers nonhelical, non-native PPII and β-sheet populations as the solvent is changed from SPC/E to the less tetrahedral liquid (H1.56) to an LJ-like liquid (H3.00). The pentapeptide conformational order metrics indicate a preference for open, solvent-exposed, non-native structures in hybrid solvent models at all temperatures of study. The possible correlations between the properties of solvent models and secondary structure preferences of alanine oligopeptides are discussed, and the competition between intrapeptide, peptide-solvent, and solvent-solvent hydrogen bonding is shown to be crucial in the relative free energies of different conformers.

Solvent induced conformational fluctuation of alanine dipeptide studied by using vibrational probes

The solvation effect on the three dimensional structure and the vibrational feature of alanine dipeptide (ALAD) was evaluated by applying the implicit solvents from polarizable continuum solvent model (PCM) through ab initio calculations, by using molecular dynamic (MD) simulations with explicit solvents, and by combining these two approaches. The implicit solvent induced potential energy fluctuations of ALAD in CHCl3, DMSO and H2O are revealed by means of ab initio calculations, and a global view of conformational and solvation environmental dependence of amide I frequencies is achieved. The results from MD simulations with explicit solvents show that ALAD trends to form PPII, αL, αR, and C5 in water, PPII and C5 in DMSO, and C5 in CHCl3, ordered by population, and the demonstration of the solvated structure, the solute-solvent interaction and hydrogen bonding is therefore enhanced. Representative ALAD-solvent clusters were sampled from MD trajectories and undergone ab initio calculations. The explicit solvents reveal the hydrogen bonding between ALAD and solvents, and the correlation between amide I frequencies and the CO bond length is built. The implicit solvents applied to the ALAD-solvent clusters further compensate the solvation effect from the bulk, and thus enlarge the degree of structural distortion and the amide I frequency red shift. The combination of explicit solvent in the first hydration shell and implicit solvent in the bulk is helpful for our understanding about the conformational fluctuation of solvated polypeptides through vibrational probes.

The intrinsic conformational features of amino acids from a protein coil library and their applications in force field development

The local conformational (φ, ψ, χ) preferences of amino acid residues remain an active research area, which are important for the development of protein force fields. In this perspective article, we first summarize spectroscopic studies of alanine-based short peptides in aqueous solution. While most studies indicate a preference for the P(II) conformation in the unfolded state over α and β conformations, significant variations are also observed. A statistical analysis from various coil libraries of high-resolution protein structures is then summarized, which gives a more coherent view of the local conformational features. The φ, ψ, χ distributions of the 20 amino acids have been obtained from a protein coil library, considering both backbone and side-chain conformational preferences. The intrinsic side-chain χ(1) rotamer preference and χ(1)-dependent Ramachandran plot can be generally understood by combining the interaction of the side-chain Cγ/Oγ atom with two neighboring backbone peptide groups. Current all-atom force fields such as AMBER ff99sb-ILDN, ff03 and OPLS-AA/L do not reproduce these distributions well. A method has been developed by combining the φ, ψ plot of alanine with the influence of side-chain χ(1) rotamers to derive the local conformational features of various amino acids. It has been further applied to improve the OPLS-AA force field. The modified force field (OPLS-AA/C) reproduces experimental (3)J coupling constants for various short peptides quite well. It also better reproduces the temperature-dependence of the helix-coil transition for alanine-based peptides. The new force field can fold a series of peptides and proteins with various secondary structures to their experimental structures. MD simulations of several globular proteins using the improved force field give significantly less deviation (RMSD) to experimental structures. The results indicate that the local conformational features from coil libraries are valuable for the development of balanced protein force fields.

Ramachandran Plot for Alanine Dipeptide as Determined from Raman Optical Activity

Accessible values of the φ and ψ torsional angles determining peptide main chain conformation are traditionally displayed in the form of Ramachandran plots. The number of experimental methods making it possible to determine such conformational distribution is limited. In the present study, Raman optical activity (ROA) spectra of Ac-Ala-NHMe were measured and fit by theoretical curves. This revealed the most favored conformers and a large part of the potential energy surface (PES) of this model dipeptide. Such experimental PES compares well to quantum chemical computations, whereas molecular dynamics (MD) modeling reproduces it less faithfully. The surface shape is consistent with the temperature dependence of the spectra, as observed experimentally and predicted by MD. Despite errors associated with spectral modeling and the measurement, the results are likely to facilitate future applications of ROA spectroscopy.

Population based reweighting of scaled molecular dynamics

Molecular dynamics simulation using enhanced sampling methods is one of the powerful computational tools used to explore protein conformations and free energy landscapes. Enhanced sampling methods often employ either an increase in temperature or a flattening of the potential energy surface to rapidly sample phase space, and a corresponding reweighting algorithm is used to recover the Boltzmann statistics. However, potential energies of complex biomolecules usually involve large fluctuations on a magnitude of hundreds of kcal/mol despite minimal structural changes during simulation. This leads to noisy reweighting statistics and complicates the obtainment of accurate final results. To overcome this common issue in enhanced conformational sampling, we propose a scaled molecular dynamics method, which modifies the biomolecular potential energy surface and employs a reweighting scheme based on configurational populations. Statistical mechanical theory is applied to derive the reweighting formula, and the canonical ensemble of simulated structures is recovered accordingly. Test simulations on alanine dipeptide and the fast folding polypeptide Chignolin exhibit sufficiently enhanced conformational sampling and accurate recovery of free energy surfaces and thermodynamic properties. The results are comparable to long conventional molecular dynamics simulations and exhibit better recovery of canonical statistics over methods which employ a potential energy term in reweighting.

Reliable oligonucleotide conformational ensemble generation in explicit solvent for force field assessment using reservoir replica exchange molecular dynamics simulations

Molecular dynamics force field development and assessment requires a reliable means for obtaining a well-converged conformational ensemble of a molecule in both a time-efficient and cost-effective manner. This remains a challenge for RNA because its rugged energy landscape results in slow conformational sampling and accurate results typically require explicit solvent which increases computational cost. To address this, we performed both traditional and modified replica exchange molecular dynamics simulations on a test system (alanine dipeptide) and an RNA tetramer known to populate A-form-like conformations in solution (single-stranded rGACC). A key focus is on providing the means to demonstrate that convergence is obtained, for example, by investigating replica RMSD profiles and/or detailed ensemble analysis through clustering. We found that traditional replica exchange simulations still require prohibitive time and resource expenditures, even when using GPU accelerated hardware, and our results are not well converged even at 2 μs of simulation time per replica. In contrast, a modified version of replica exchange, reservoir replica exchange in explicit solvent, showed much better convergence and proved to be both a cost-effective and reliable alternative to the traditional approach. We expect this method will be attractive for future research that requires quantitative conformational analysis from explicitly solvated simulations.

Adsorption and friction behavior of amphiphilic polymers on hydrophobic surfaces

The ability of amphiphilic polymers to self-assemble and form a gel or gel-like layer has been investigated by means of both experimental and theoretical studies on alkylated derivatives of poly(acrylic acid). Experiments were performed to determine the relationship between amphiphilic polymer chemistry, structure, water retention, and friction in the presence of hydrophobic substrates. The results indicate that the amphiphilic polymer forms a water-enriched, friction-reducing adsorbed layer on hydrophobic surfaces. The shear moduli and viscosities of the adsorbed layers, as determined by fitting the Voigt model to QCM-D data, were consistent with the presence of a gel. Computational studies on HPAA-12 were performed and are consistent with the presence of adsorbed conformations, in which the lowest free energy in the model corresponded to a partially adsorbed molecule, with a small fraction of hydrophobic side chains being compelled, for configurational reasons, to point into the bulk water. This would support the possibility of the formation of either a gel-like layer or surface aggregation. However, because the adsorption experiments showed no evidence of aggregation, this strongly suggests the formation of a gel.

Critical Assessment of Current Force Fields. Short Peptide Test Case

The applicability of molecular dynamics simulations for studies of protein folding or intrinsically disordered proteins critically depends on quality of energetic functions-force fields. The four popular force fields for biomolecular simulations, CHARMM22/CMAP, AMBER FF03, AMBER FF99SB, and OPLS-AA/L, were compared in prediction of conformational propensities of all common proteinogenic amino acids. The minimalistic model of terminally block amino acids (dipeptides) was chosen for assessment of side chain effects on backbone propensities. The precise metadynamics simulations revealed striking inconsistency of trends in conformational preferences as manifested by investigated force fields for both backbone and side chains. To trace this disapproval between force fields, the two related AMBER force fields were studied more closely. In the cases of FF99SB and FF03, we uncovered that the distinct tends were driven by different charge models. Additionally, the effects of recent correction for side chain torsion (FF99SB-ILDN) were examined on affected amino acids and exposed significant coupling between free energy profiles and propensities of backbone and side chain conformers. These findings have important consequences for further force field development.

Assessment of the intrinsic conformational preferences of dipeptide amino acids in aqueous solution by combined umbrella sampling/MBAR statistics. A comparison with experimental results

The propensities of 19 amino acid dipeptides have been calculated by a distributed umbrella sampling molecular dynamics simulation procedure using the OPLS-AA force field. The potential of mean force maps was estimated with the multiple Bennett acceptance ratio statistics. The resulting propensities compare satisfactorily well with very recently published experimental data on equivalent systems. In particular, α conformation-probabilities for all of the dipeptides remain much lower than either β or P(II) propensities. This result is in agreement with most experimental data for dipeptides. However, it is also in contrast with most simulation studies performed so far with other force fields, where α conformations result even more probable than P(II) or β ones. We discuss the behavior of the OPLS-AA force field, which can be useful for the improvement of this model in reproducing the recent experimental observations on amino acid dipeptides.

Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations

Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations.

Quantitative Assessment of Force Fields on Both Low-Energy Conformational Basins and Transition-State Regions of the (ϕ-ψ) Space

The free energy surfaces (FESs) of alanine dipeptide are studied to illustrate a new strategy to assess the performance of classical molecular mechanics force field on the full range of the (ϕ-ψ) conformational space. The FES is obtained from metadynamics simulations with five commonly used force fields and from ab initio density functional theory calculations in both gas phase and aqueous solution. The FESs obtained at the B3LYP/6-311+G(2d,p)//B3LYP/6-31G(d,p) level of theory are validated by comparison with previously reported MP2 and LMP2 results as well as with experimentally obtained probability distribution between the C5-β (or β-PPII) and αR states. A quantitative assessment is made for each force field in three conformational basins, LeRI (C5-β-C7eq), LeRII (β2-αR), and LeRIII(αL-C7ax-αD) as well as three transition-state regions linking the above conformational basins. The performance of each force field is evaluated in terms of the average free energy of each region in comparison with that of the ab initio results. We quantify how well a force field FES matches the ab initio FES through the calculation of the standard deviation of a free energy difference map between the two FESs. The results indicate that the performance varies largely from region to region or from force field to force field. Although not one force field is able to outperform all others in all conformational areas, the OPLSAA/L force field gives the best performance overall, followed by OPLSAA and AMBER03. For the three top performers, the average free energies differ from the corresponding ab initio values from within the error range (<0.4 kcal/mol) to ∼1.5 kcal/mol for the low-energy regions and up to ∼2.0 kcal/mol for the transition-state regions. The strategy presented and the results obtained here should be useful for improving the parametrization of force fields targeting both accuracy in the energies of conformers and the transition-state barriers.