Molecular dynamics simulations of highly crowded amino acid solutions: comparisons of eight different force field combinations with experiment and with each other

Retention of methicillin susceptibility in Staphylococcus aureus using natural adjuvant as an allosteric modifier of penicillin-binding protein 2a

The emergence of methicillin-resistant Staphylococcus aureus (MRSA) poses a significant global public health challenge due to its resistance to conventional antibiotics, primarily mediated by the mutated penicillin-binding protein, PBP2a. This study aims to investigate the potential of phytochemicals derived from medicinal plants in the Indian subcontinent to serve as adjuvants, enhancing the efficacy of methicillin against MRSA through allosteric modification of PBP2a using molecular docking and molecular dynamics (MD) simulation. After comprehensive Absorption, Distribution, Metabolism, and Excretion (ADME) profiling, along with AMES and hepatotoxicity tests, 9 compounds were shortlisted as suitable adjuvant candidates. Among them, nimbolide, quercetin, emodin, daidzein, eriodictyol, luteolin, and apigenin exhibited strong binding affinity to the allosteric site of PBP2a, with docking scores ranging from -8.7 to -7.3 kcal/mol. These phytochemicals facilitated enhanced methicillin binding, as evidenced by improved docking scores ranging from -6.1 to -6.8 kcal/mol, compared to -5.6 kcal/mol for methicillin alone. Molecular dynamics simulations confirmed the stability and favorable conformations of phytochemical-PBP2a complexes. Quercetin and daidzein were identified as the most promising adjuvant candidates, forming stable and energetically favorable complexes with PBP2a. Experimental validation showed that quercetin, at 30 mg/mL, effectively retained methicillin's antibacterial efficacy against MRSA. This study underscores the potential of natural compounds in overcoming antibiotic resistance and suggests that phytochemical-antibiotic synergism could be a viable strategy to combat multidrug-resistant bacterial infections.

An in silico molecular docking and simulation study to identify potential anticancer phytochemicals targeting the RAS signaling pathway

The dysregulation of the rat sarcoma (RAS) signaling pathway, particularly the MAPK/ERK cascade, is a hallmark of many cancers, leading to uncontrolled cellular proliferation and resistance to apoptosis-inducing treatments. Dysregulation of the MAPK/ERK pathway is common in various cancers including pancreatic, lung, and colon cancers, making it a critical target for therapeutic intervention. Natural compounds, especially phytochemicals, offer a promising avenue for developing new anticancer therapies due to their potential to interfere with these signaling pathways. This study investigates the potential of anticancer phytochemicals to inhibit the MAPK/ERK pathway through molecular docking and simulation techniques. A total of 26 phytochemicals were screened from an initial set of 340 phytochemicals which were retrieved from Dr. Duke's database using in silico methods for their binding affinity and stability. Molecular docking was performed to identify key interactions with ERK2, followed by molecular dynamics (MD) simulations to evaluate the stability of these interactions. The study identified several phytochemicals, including luteolin, hispidulin, and isorhamnetin with a binding score of -10.1±0 Kcal/mol, -9.86±0.15 Kcal/mol, -9.76±0.025 Kcal/mol, respectively as promising inhibitors of the ERK2 protein. These compounds demonstrated significant binding affinities and stable interactions with ERK2 in MD simulation studies up to 200ns, particularly at the active site. The radius of gyration analysis confirmed the stability of these phytochemical-protein complexes' compactness, indicating their potential to inhibit ERK activity. The stability and binding affinity of these compounds suggest that they can effectively inhibit ERK2 activity, potentially leading to more effective and less toxic cancer treatments. The findings underscore the therapeutic promise of these phytochemicals, which could serve as a basis for developing new cancer therapies.

Effective Inclusion of Electronic Polarization Improves the Description of Electrostatic Interactions: The prosECCo75 Biomolecular Force Field

prosECCo75 is an optimized force field effectively incorporating electronic polarization via charge scaling. It aims to enhance the accuracy of nominally nonpolarizable molecular dynamics simulations for interactions in biologically relevant systems involving water, ions, proteins, lipids, and saccharides. Recognizing the inherent limitations of nonpolarizable force fields in precisely modeling electrostatic interactions essential for various biological processes, we mitigate these shortcomings by accounting for electronic polarizability in a physically rigorous mean-field way that does not add to computational costs. With this scaling of (both integer and partial) charges within the CHARMM36 framework, prosECCo75 addresses overbinding artifacts. This improves agreement with experimental ion binding data across a broad spectrum of systems─lipid membranes, proteins (including peptides and amino acids), and saccharides─without compromising their biomolecular structures. prosECCo75 thus emerges as a computationally efficient tool providing enhanced accuracy and broader applicability in simulating the complex interplay of interactions between ions and biomolecules, pivotal for improving our understanding of many biological processes.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

Structure, energetics and dynamics in crowded amino acid solutions: a molecular dynamics study

A comprehensive understanding of crowding effects on biomolecular processes necessitates investigating the bulk thermodynamic and kinetic properties of the solutions with an accurate molecular representation of the crowded milieu. Recent studies have reparameterized the non-bonded dispersion interaction of solutes to precisely model intermolecular interactions, which would circumvent artificial aggregation as shown by the original force-fields. However, the performance of this reparameterization is yet to be assessed for concentrated crowded solutions in terms of investigating the hydration shell structure, energetics and dynamics. In this study, we perform molecular dynamics simulations of crowded aqueous solutions of five zwitterionic neutral amino acids (Gly, Ala, Thr, Pro, and Ser), mimicking the molecular crowding environment, using a modified AMBER ff99SB-ILDN force-field. We systematically examine and show that the reproducibility of the osmotic coefficients, density, viscosity and self-diffusivity of amino acids improves using the modified force-field in crowded concentrations. The modified force-field also improves the structuring of the solute solvation shells, solute interaction energy and convergence of tails of radial distribution functions, indicating reduction in the artificial aggregation. Our results also indicate that the hydrogen bonding network of water weakens and water molecules anomalously diffuse at small time scales in the crowded solutions. These results underscore the significance of examining the solution properties and anomalous hydration behaviour of water in crowded solutions, which have implications in shaping the structure and dynamics of biomolecules. The findings also illustrate the improvement in predicting bulk solution properties using the modified force-field, thereby providing an approach towards accurate modeling of crowded molecular solutions.

Phase separation in amino acid mixtures is governed by composition

Macromolecular phase separation has recently come to immense prominence as it is central to the formation of membraneless organelles, leading to a new paradigm of cellular organization. This type of phase transition, often termed liquid-liquid phase separation (LLPS), is mediated by molecular interactions between biomolecules, including nucleic acids and both ordered and disordered proteins. In the latter case, the separation between protein-dense and -dilute phases is often interpreted using models adapted from polymer theory. Specifically, the "stickers and spacers" model proposes that the formation of condensate-spanning networks in protein solutions originates from the interplay between two classes of residues and that the main determinants for phase separation are multivalency and sequence patterning. The duality of roles of stickers (aromatics like Phe and Tyr) and spacers (Gly and polar residues) may apply more broadly in protein-like mixtures, and the presence of these two types of components alone may suffice for LLPS to take place. In order to explore this hypothesis, we use atomistic molecular dynamics simulations of capped amino acid residues as a minimal model system. We study the behavior of pure amino acids in water for three types of residues corresponding to the spacer and sticker categories and of their multicomponent mixtures. In agreement with previous observations, we find that the spacer-type amino acids fail to phase separate on their own, while the sticker is prone to aggregation. However, ternary amino acid mixtures involving both types of amino acids phase separate into two phases that retain intermediate degrees of compaction and greater fluidity than sticker-only condensates. Our results suggest that LLPS is an emergent property of amino acid mixtures determined by composition.

Influence of Nonspecific Interactions on Protein Associations: Implications for Biochemistry In Vivo

The cellular interior is composed of a variety of microenvironments defined by distinct local compositions and composition-dependent intermolecular interactions. We review the various types of nonspecific interactions between proteins and between proteins and other macromolecules and supramolecular structures that influence the state of association and functional properties of a given protein existing within a particular microenvironment at a particular point in time. The present state of knowledge is summarized, and suggestions for fruitful directions of research are offered. Expected final online publication date for the Annual Review of Biochemistry, Volume 91 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Crowding effects on water-mediated hydrophobic interactions

Understanding the fundamental forces such as hydrophobic interactions in a crowded intracellular environment is necessary to comprehensively decipher the mechanisms of protein folding and biomolecular self-assemblies. The widely accepted entropic depletion view of crowding effects primarily attributes biomolecular compaction to the solvent excluded volume effects exerted by the "inert" crowders, neglecting their soft interactions with the biomolecule. In this study, we examine the effects of chemical nature and soft attractive energy of crowders on the water-mediated hydrophobic interaction between two non-polar neopentane solutes using molecular dynamics simulations. The crowded environment is modeled using dipeptides composed of polar and non-polar amino acids of varying sizes. The results show that amongst the non-polar crowders, Leu₂ strengthens the hydrophobic interactions significantly, whereas the polar and small-sized non-polar crowders do not show significant strengthening. Distinct underlying thermodynamic driving forces are illustrated where the small-sized crowders drive hydrophobic interaction via a classic entropic depletion effect and the bulky crowders strengthen it by preferential interaction with the solute. A crossover from energy-stabilized solvent-separated pair to entropy-stabilized contact pair state is observed in the case of bulky non-polar (Leu₂) and polar (Lys₂) crowders. The influence of solute-crowder energy in affecting the dehydration energy penalty is found to be crucial for determining the neopentane association. The findings demonstrate that along with the entropic (size) effects, the energetic effects also play a crucial role in determining hydrophobic association. The results can be extended and have implications in understanding the impact of protein crowding with varying chemistry in modulating the protein free energy landscapes.

Small crowder interactions can drive hydrophobic polymer collapse as well as unfolding

Biomolecules evolve and function in the intracellular crowded environment that is densely packed with macromolecules. Yet, a microscopic understanding of the effects of such an environment on the conformational preferences of biomolecules remains elusive. While prior investigations have attributed crowding effects mainly to the excluded volume (size) effects of the crowders, very little is known about the effects exerted due to their chemical interactions. In this study, crowding effects of tri-alanine peptides on the collapse equilibria of generic hydrophobic polymer are investigated using molecular dynamics simulations. The role of weak, non-specific, attractive polymer-crowder interactions in modulating the polymer collapse equilibria is examined. The results highlight that crowding effects can lead to polymer compaction as well as unfolding depending on the strength of polymer-crowder interaction energy. Strongly interacting crowders weaken hydrophobic collapse (or unfold the polymer) at high volume fractions and induce polymer collapse only under dilute conditions. Weakly interacting crowders induce polymer collapse at all crowder concentrations. Interestingly, the thermodynamic driving forces for polymer collapse are remarkably different in the two cases. Strongly and weakly interacting crowders induce collapse by preferential adsorption and preferential depletion respectively. The findings provide new insights into the possible effects of interplay of intermolecular interactions in a crowded environment. The results have implications in understanding the impact of crowding in altering free energy landscapes of proteins.

pH-Induced Changes in Polypeptide Conformation: Force-Field Comparison with Experimental Validation

Microsecond-long all-atom molecular dynamics (MD) simulations, circular dichroism, laser Doppler velocimetry, and dynamic light-scattering techniques have been used to investigate pH-induced changes in the secondary structure, charge, and conformation of poly l-lysine (PLL) and poly l-glutamic acid (PGA). The employed combination of the experimental methods reveals for both PLL and PGA a narrow pH range at which they are charged enough to form stable colloidal suspensions, maintaining their α-helix content above 60%; an elevated charge state of the peptides required for colloidal stability promotes the peptide solvation as a random coil. To obtain a more microscopic view on the conformations and to verify the modeling performance, peptide secondary structure and conformations rising in MD simulations are also examined using three different force fields, i.e., OPLS-AA, CHARMM27, and AMBER99SB*-ILDNP. Ramachandran plots reveal that in the examined setup the α-helix content is systematically overestimated in CHARMM27, while OPLS-AA overestimates the β-sheet fraction at lower ionization degrees. At high ionization degrees, the OPLS-AA force-field-predicted secondary structure fractions match the experimentally measured distribution most closely. However, the pH-induced changes in PLL and PGA secondary structure are reasonably captured only by the AMBER99SB*-ILDNP force field, with the exception of the fully charged PGA in which the α-helix content is overestimated. The comparison to simulations results shows that the examined force fields involve significant deviations in their predictions for charged homopolypeptides. The detailed mapping of secondary structure dependency on pH for the polypeptides, especially finding the stable colloidal α-helical regime for both examined peptides, has significant potential for practical applications of the charged homopolypeptides. The findings raise attention especially to the pH fine tuning as an underappreciated control factor in surface modification and self-assembly.

Towards capturing cellular complexity: combining encapsulation and macromolecular crowding in a reverse micelle

This paper studies the orientational structure and dynamics of multi-protein systems under confinement and discusses the implications on biological cells.

On the Applicability of Force Fields To Study the Aggregation of Amyloidogenic Peptides Using Molecular Dynamics Simulations

Molecular dynamics simulations play an essential role in understanding biomolecular processes such as protein aggregation at temporal and spatial resolutions which are not attainable by experimental methods. For a correct modeling of protein aggregation, force fields must accurately represent molecular interactions. Here, we study the effect of five different force fields on the oligomer formation of Alzheimer's Aβ_16-22 peptide and two of its mutants: Aβ_16-22(F19V,F20V), which does not form fibrils, and Aβ_16-22(F19L) which forms fibrils faster than the wild type. We observe that while oligomer formation kinetics depends strongly on the force field, structural properties, such as the most relevant protein-protein contacts, are similar between them. The oligomer formation kinetics obtained with different force fields differ more from each other than the kinetics between aggregating and nonaggregating peptides simulated with a single force field. We discuss the difficulties in comparing atomistic simulations of amyloid oligomer formation with experimental observables.

Discrete and Continuum Models for the Salt in Crowded Environments of Suspended Charged Particles

Electrostatic forces greatly affect the overall dynamics and diffusional activities of suspended charged particles in crowded environments. Accordingly, the concentration of counter- or co-ions in a fluid-''the salt"-determines the range, strength, and order of electrostatic interactions between particles. This environment fosters engineering routes for controlling directed assembly of particles at both the micro- and nanoscale. Here, we analyzed two computational modeling schemes that considered salt within suspensions of charged particles, or polyelectrolytes: discrete and continuum. Electrostatic interactions were included through a Green's function formalism, where the confined fundamental solution for Poisson's equation is resolved by the general geometry Ewald-like method. For the discrete model, the salt was considered as regularized point-charges with a specific valence and size, while concentration fields were defined for each ionic species for the continuum model. These considerations were evolved using Brownian dynamics of the suspended charged particles and the discrete salt ions, while a convection-diffusion transport equation, including the Nernst-Planck diffusion mechanism, accounted for the dynamics of the concentration fields. The salt/particle models were considered as suspensions under slit-confinement conditions for creating crowded "macro-ions", where density distributions and radial distribution functions were used to compare and differentiate computational models. Importantly, our analysis shows that disparate length scales or increased system size presented by the salt and suspended particles are best dealt with using concentration fields to model the ions. These findings were then validated by novel simulations of a semipermeable polyelectrolyte membrane, at the mesoscale, from which ionic channels emerged and enable ion conduction.

Macromolecular crowding and the importance of proper hydration for the structure and dynamics of protein solutions

Extensive computational studies of ubiquitin crowding with a special focus on protein hydration directly visible in dielectric spectra.

Crowding in Cellular Environments at an Atomistic Level from Computer Simulations

The effects of crowding in biological environments on biomolecular structure, dynamics, and function remain not well understood. Computer simulations of atomistic models of concentrated peptide and protein systems at different levels of complexity are beginning to provide new insights. Crowding, weak interactions with other macromolecules and metabolites, and altered solvent properties within cellular environments appear to remodel the energy landscape of peptides and proteins in significant ways including the possibility of native state destabilization. Crowding is also seen to affect dynamic properties, both conformational dynamics and diffusional properties of macromolecules. Recent simulations that address these questions are reviewed here and discussed in the context of relevant experiments.

Reparametrization of Protein Force Field Nonbonded Interactions Guided by Osmotic Coefficient Measurements from Molecular Dynamics Simulations

There is a small, but growing, body of literature describing the use of osmotic coefficient measurements to validate and reparametrize simulation force fields. Here we have investigated the ability of five very commonly used force field and water model combinations to reproduce the osmotic coefficients of seven neutral amino acids and five small molecules. The force fields tested include AMBER ff99SB-ILDN, CHARMM36, GROMOS54a7, and OPLS-AA, with the first of these tested in conjunction with the TIP3P and TIP4P-Ew water models. In general, for both the amino acids and the small molecules, the tested force fields produce computed osmotic coefficients that are lower than experiment; this is indicative of excessively favorable solute-solute interactions. The sole exception to this general trend is provided by GROMOS54a7 when applied to amino acids: in this case, the computed osmotic coefficients are consistently too high. Importantly, we show that all of the force fields tested can be made to accurately reproduce the experimental osmotic coefficients of the amino acids when minor modifications-some previously reported by others and some that are new to this study-are made to the van der Waals interactions of the charged terminal groups. Special care is required, however, when simulating Proline with a number of the force fields, and a hydroxyl-group specific modification is required in order to correct Serine and Threonine when simulated with AMBER ff99SB-ILDN. Interestingly, an alternative parametrization of the van der Waals interactions in the latter force field, proposed by the Nerenberg and Head-Gordon groups, is shown to immediately produce osmotic coefficients that are in excellent agreement with experiment. Overall, this study reinforces the idea that osmotic coefficient measurements can be used to identify general shortcomings in commonly used force fields' descriptions of solute-solute interactions and further demonstrates that modifications to van der Waals parameters provide a simple route to optimizing agreement with experiment.

Direct Comparison of Amino Acid and Salt Interactions with Double-Stranded and Single-Stranded DNA from Explicit-Solvent Molecular Dynamics Simulations

Given the ubiquitous nature of protein-DNA interactions, it is important to understand the interaction thermodynamics of individual amino acid side chains for DNA. One way to assess these preferences is to perform molecular dynamics (MD) simulations. Here we report MD simulations of 20 amino acid side chain analogs interacting simultaneously with both a 70-base-pair double-stranded DNA and with a 70-nucleotide single-stranded DNA. The relative preferences of the amino acid side chains for dsDNA and ssDNA match well with values deduced from crystallographic analyses of protein-DNA complexes. The estimated apparent free energies of interaction for ssDNA, on the other hand, correlate well with previous simulation values reported for interactions with isolated nucleobases, and with experimental values reported for interactions with guanosine. Comparisons of the interactions with dsDNA and ssDNA indicate that, with the exception of the positively charged side chains, all types of amino acid side chain interact more favorably with ssDNA, with intercalation of aromatic and aliphatic side chains being especially notable. Analysis of the data on a base-by-base basis indicates that positively charged side chains, as well as sodium ions, preferentially bind to cytosine in ssDNA, and that negatively charged side chains, and chloride ions, preferentially bind to guanine in ssDNA. These latter observations provide a novel explanation for the lower salt dependence of DNA duplex stability in GC-rich sequences relative to AT-rich sequences.

Molecular dynamics simulations of aqueous glycine solutions

Pre-nucleation clusters of glycine are strongly hydrated dynamic solutes, which change size and shape within hundreds of picoseconds.

The Differential Response of Proteins to Macromolecular Crowding

The habitat in which proteins exert their function contains up to 400 g/L of macromolecules, most of which are proteins. The repercussions of this dense environment on protein behavior are often overlooked or addressed using synthetic agents such as poly(ethylene glycol), whose ability to mimic protein crowders has not been demonstrated. Here we performed a comprehensive atomistic molecular dynamic analysis of the effect of protein crowders on the structure and dynamics of three proteins, namely an intrinsically disordered protein (ACTR), a molten globule conformation (NCBD), and a one-fold structure (IRF-3) protein. We found that crowding does not stabilize the native compact structure, and, in fact, often prevents structural collapse. Poly(ethylene glycol) PEG500 failed to reproduce many aspects of the physiologically-relevant protein crowders, thus indicating its unsuitability to mimic the cell interior. Instead, the impact of protein crowding on the structure and dynamics of a protein depends on its degree of disorder and results from two competing effects: the excluded volume, which favors compact states, and quinary interactions, which favor extended conformers. Such a viscous environment slows down protein flexibility and restricts the conformational landscape, often biasing it towards bioactive conformations but hindering biologically relevant protein-protein contacts. Overall, the protein crowders used here act as unspecific chaperons that modulate the protein conformational space, thus having relevant consequences for disordered proteins.

Most in vitro and in silico biophysical experiments generally study proteins in an isolated environment, overlooking that their natural environment—the cell cytoplasm—is a solution that is highly populated by proteins. To address this knowledge gap, here we explored how a crowded environment alters the conformational sampling of three proteins, each with a different degree of disorder and flexibility. We simulated a crowded system composed by the three proteins and reaching a cell-like concentration and compared the protein behavior observed with that induced by PEG500, a synthetic crowding agent. Despite some similarities between the environments, protein crowders showed a number of characteristics that raise concerns about the use of diluted solutions or synthetic agents when studying protein behavior.

Osmotic Pressure Simulations of Amino Acids and Peptides Highlight Potential Routes to Protein Force Field Parameterization

Recent molecular dynamics (MD) simulations of proteins have suggested that common force fields overestimate the strength of amino acid interactions in aqueous solution. In an attempt to determine the causes of these effects, we have measured the osmotic coefficients of a number of amino acids using the AMBER ff99SB-ILDN force field with two popular water models, and compared the results with available experimental data. With TIP4P-Ew water, interactions between aliphatic residues agree well with experiment, but interactions of the polar residues serine and threonine are found to be excessively attractive. For all tested amino acids, the osmotic coefficients are lower when the TIP3P water model is used. Additional simulations performed on charged amino acids indicate that the osmotic coefficients are strongly dependent on the parameters assigned to the salt ions, with a reparameterization of the sodium/carboxylate interaction reported by the Aksimentiev group significantly improving description of the osmotic coefficient for glutamate. For five neutral amino acids, we also demonstrate a decrease in solute-solute attractions using the recently reported TIP4P-D water model and using the KBFF force field. Finally, we show that for four two-residue peptides improved agreement with experiment can be achieved by rederiving the partial charges for each peptide.

On the slowdown mechanism of water dynamics around small amphiphiles

Partitioning the water molecules depending on their location with respect to the solute makes it possible to probe the cause of the orientational slowdown in aqueous tetramethylurea.

Diffusion within the cytoplasm: a mesoscale model of interacting macromolecules

Recent experiments carried out in the dense cytoplasm of living cells have highlighted the importance of proteome composition and nonspecific intermolecular interactions in regulating macromolecule diffusion and organization. Despite this, the dependence of diffusion-interaction on physicochemical properties such as the degree of poly-dispersity and the balance between steric repulsion and nonspecific attraction among macromolecules was not systematically addressed. In this work, we study the problem of diffusion-interaction in the bacterial cytoplasm, combining theory and experimental data to build a minimal coarse-grained representation of the cytoplasm, which also includes, for the first time to our knowledge, the nucleoid. With stochastic molecular-dynamics simulations of a virtual cytoplasm we are able to track the single biomolecule motion, sizing from 3 to 80 nm, on submillisecond-long trajectories. We demonstrate that the size dependence of diffusion coefficients, anomalous exponents, and the effective viscosity experienced by biomolecules in the cytoplasm is fine-tuned by the intermolecular interactions. Accounting only for excluded volume in these potentials gives a weaker size-dependence than that expected from experimental data. On the contrary, adding nonspecific attraction in the range of 1-10 thermal energy units produces a stronger variation of the transport properties at growing biopolymer sizes. Normal and anomalous diffusive regimes emerge straightforwardly from the combination of high macromolecular concentration, poly-dispersity, stochasticity, and weak nonspecific interactions. As a result, small biopolymers experience a viscous cytoplasm, while the motion of big ones is jammed because the entanglements produced by the network of interactions and the entropic effects caused by poly-dispersity are stronger.

A consistent force field parameter set for zwitterionic amino acid residues

Isolated amino acids play an important role in biochemistry and are therefore an interesting object of study. Atomistic molecular dynamics (MD) simulations can provide a high-resolution picture of the dynamic features of these species, especially in their biological environment. Unfortunately, most standard force field packages lack libraries for isolated amino acids in their zwitterionic form. Although several studies have used ad-hoc parameterizations for single amino acids, a consistent force-field parameter set for these molecules is still missing. Here, we present such a parameter library derived from the widely used parm99SB set from the AMBER program package. The parameter derivation for all 20 proteinogenic amino acids transparently followed established procedures with histidine treated in three different protonation states. All amino acids were subjected to MD simulations in four different forms for comparison: zwitterionic, N-teminally capped with acetyl, C-terminally capped with N-methyl, and capped at both termini. Simulation results show similarities between the different forms. Five zwitterionic amino acids-arginine, glutamate, glycine, phenylalanine, leucine-were simulated in a protein environment. Proteins and ligands generally retained their initial structure. The new parameter set will thus facilitate future atomistic simulations of these species.

COFFDROP: A Coarse-Grained Nonbonded Force Field for Proteins Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of Amino Acids

We describe the derivation of a set of bonded and nonbonded coarse-grained (CG) potential functions for use in implicit-solvent Brownian dynamics (BD) simulations of proteins derived from all-atom explicit-solvent molecular dynamics (MD) simulations of amino acids. Bonded potential functions were derived from 1 μs MD simulations of each of the 20 canonical amino acids, with histidine modeled in both its protonated and neutral forms; nonbonded potential functions were derived from 1 μs MD simulations of every possible pairing of the amino acids (231 different systems). The angle and dihedral probability distributions and radial distribution functions sampled during MD were used to optimize a set of CG potential functions through use of the iterative Boltzmann inversion (IBI) method. The optimized set of potential functions—which we term COFFDROP (COarse-grained Force Field for Dynamic Representation Of Proteins)—quantitatively reproduced all of the “target” MD distributions. In a first test of the force field, it was used to predict the clustering behavior of concentrated amino acid solutions; the predictions were directly compared with the results of corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement. In a second test, BD simulations of the small protein villin headpiece were carried out at concentrations that have recently been studied in all-atom explicit-solvent MD simulations by Petrov and Zagrovic (PLoS Comput. Biol.2014, 5, e1003638). The anomalously strong intermolecular interactions seen in the MD study were reproduced in the COFFDROP simulations; a simple scaling of COFFDROP’s nonbonded parameters, however, produced results in better accordance with experiment. Overall, our results suggest that potential functions derived from simulations of pairwise amino acid interactions might be of quite broad applicability, with COFFDROP likely to be especially useful for modeling unfolded or intrinsically disordered proteins.

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.

Are current atomistic force fields accurate enough to study proteins in crowded environments?

The high concentration of macromolecules in the crowded cellular interior influences different thermodynamic and kinetic properties of proteins, including their structural stabilities, intermolecular binding affinities and enzymatic rates. Moreover, various structural biology methods, such as NMR or different spectroscopies, typically involve samples with relatively high protein concentration. Due to large sampling requirements, however, the accuracy of classical molecular dynamics (MD) simulations in capturing protein behavior at high concentration still remains largely untested. Here, we use explicit-solvent MD simulations and a total of 6.4 µs of simulated time to study wild-type (folded) and oxidatively damaged (unfolded) forms of villin headpiece at 6 mM and 9.2 mM protein concentration. We first perform an exhaustive set of simulations with multiple protein molecules in the simulation box using GROMOS 45a3 and 54a7 force fields together with different types of electrostatics treatment and solution ionic strengths. Surprisingly, the two villin headpiece variants exhibit similar aggregation behavior, despite the fact that their estimated aggregation propensities markedly differ. Importantly, regardless of the simulation protocol applied, wild-type villin headpiece consistently aggregates even under conditions at which it is experimentally known to be soluble. We demonstrate that aggregation is accompanied by a large decrease in the total potential energy, with not only hydrophobic, but also polar residues and backbone contributing substantially. The same effect is directly observed for two other major atomistic force fields (AMBER99SB-ILDN and CHARMM22-CMAP) as well as indirectly shown for additional two (AMBER94, OPLS-AAL), and is possibly due to a general overestimation of the potential energy of protein-protein interactions at the expense of water-water and water-protein interactions. Overall, our results suggest that current MD force fields may distort the picture of protein behavior in biologically relevant crowded environments.

Protein behavior is strongly affected by highly crowded and interaction-rich environments, i.e., typical conditions in both biologically relevant systems, such as the cellular interior, and solution-based structural experiments, including NMR and different spectroscopies. On the other hand, primarily because of limited computational power, molecular dynamics (MD) simulations, a premier high-resolution method for analyzing structure, dynamics and interactions of proteins, have been predominantly used to study individual proteins at infinite dilution. To fill this gap, we use MD simulations to study the behavior of wild-type (aggregation-resistant) and oxidatively damaged (aggregation-prone) forms of villin headpiece at high concentration, and reveal unexpected limitations and inaccuracies of modern-day MD force fields when it comes to modeling proteins at physiologically or experimentally relevant concentrations.

Evaluating the strength of salt bridges: a comparison of current biomolecular force fields

Recent advances in computer hardware and software have made rigorous evaluation of current biomolecular force fields using microsecond-scale simulations possible. Force fields differ in their treatment of electrostatic interactions, including the formation of salt bridges in proteins. Here we conducted an extensive evaluation of salt bridge interactions in the latest AMBER, CHARMM, and OPLS force fields, using microsecond-scale molecular dynamics simulations of amino acid analogues in explicit solvent. We focused on salt bridges between three different pairs of oppositely charged amino acids: Arg/Asp, Lys/Asp, and His(+)/Asp. Our results reveal considerable variability in the predicted K_A values of the salt bridges for these force fields, as well as differences from experimental data: almost all of the force fields overestimate the strengths of the salt bridges. When amino acids are represented by side-chain analogues, the AMBER ff03 force field overestimates the K_A values the least, while for complete amino acids, the AMBER ff13α force field yields the lowest K_A value, most likely caused by an altered balance of side-chain/side-chain and side-chain/backbone contacts. These findings confirm the notion that the implicit incorporation of solvent polarization improves the accuracy of modeling salt bridge interactions.

Current and emerging opportunities for molecular simulations in structure-based drug design

An overview of the current capabilities and limitations of molecular simulation of biomolecular complexes in the context of computer-aided drug design is provided. Steady improvements in computer hardware coupled with more refined representations of energetics are leading to a new appreciation of the driving forces of molecular recognition. Molecular simulations are poised to more frequently guide the interpretation of biophysical measurements of biomolecular complexes. Ligand design strategies emerge from detailed analyses of computed structural ensembles. The feasibility of routine applications to ligand optimization problems hinges upon successful extensive large scale validation studies and the development of protocols to intelligently automate computations.