CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields

Computational Models for Predictive Cardiac Ion Channel Pharmacology

A wealth of experimental data exists describing the elementary building blocks of complex physiological systems. However, it is increasingly apparent in the biomedical sciences that mechanisms of biological function cannot be observed or readily predicted via study of constituent elements alone. This is especially clear in the longstanding failures in prediction of effects of drug treatment for heart rhythm disturbances. These failures stem in part from classical assumptions that have been made in cardiac antiarrhythmic drug development - that a drug operates by one mechanism via one target receptor that arises from one gene.

Star-shaped tetraspermine enhances cellular uptake and cytotoxicity of T-oligo in prostate cancer cells

PURPOSE

An oligonucleotide termed 'T-oligo' having sequence homology with telomere overhang has shown cytotoxicity in multiple cancers. We have demonstrated that T-oligo can induce apoptosis in androgen independent prostate cancer cell line DU-145. In this report, we evaluate the use of star-shaped tetraspermine (SSTS) for delivery of T-oligo.

METHODS

SSTS was synthesized from spermine and its intrinsic cytotoxicity towards DU-145 cells was compared with spermine and branched polyethyleneimine (bPEI). Atomistic molecular dynamic (MD) simulations were conducted to understand binding and complexation of spermine and SSTS with T-oligo. Complexation was also determined using gel electrophoresis and SYBR gold assay. Complexes were characterized for size, cellular uptake and antiproliferative effect.

RESULTS

SSTS exhibited significantly lower toxicity than spermine and bPEI. Its affinity towards T-oligo was significantly higher than spermine as determined by experimental studies and confirmed by MD simulations and it formed stable complexes (TONPs) with T-oligo. TONPs facilitated cellular uptake and nuclear accumulation of T-oligo and their cytotoxic potential was observed at concentration several folds lower than that required for T-oligo alone.

CONCLUSION

SSTS significantly enhanced therapeutic benefits associated with the use of T-oligo and can be developed as a delivery vehicle for its in-vivo therapeutic applications.

Web-based computational chemistry education with CHARMMing I: Lessons and tutorial

This article describes the development, implementation, and use of web-based “lessons” to introduce students and other newcomers to computer simulations of biological macromolecules. These lessons, i.e., interactive step-by-step instructions for performing common molecular simulation tasks, are integrated into the collaboratively developed CHARMM INterface and Graphics (CHARMMing) web user interface (http://www.charmming.org). Several lessons have already been developed with new ones easily added via a provided Python script. In addition to CHARMMing's new lessons functionality, web-based graphical capabilities have been overhauled and are fully compatible with modern mobile web browsers (e.g., phones and tablets), allowing easy integration of these advanced simulation techniques into coursework. Finally, one of the primary objections to web-based systems like CHARMMing has been that “point and click” simulation set-up does little to teach the user about the underlying physics, biology, and computational methods being applied. In response to this criticism, we have developed a freely available tutorial to bridge the gap between graphical simulation setup and the technical knowledge necessary to perform simulations without user interface assistance.

Web-based computational chemistry education with CHARMMing II: Coarse-grained protein folding

A lesson utilizing a coarse-grained (CG) G-like model has been implemented into the CHARMM INterface and Graphics (CHARMMing) web portal (www.charmming.org) to the Chemistry at HARvard Macromolecular Mechanics (CHARMM) molecular simulation package. While widely used to model various biophysical processes, such as protein folding and aggregation, CG models can also serve as an educational tool because they can provide qualitative descriptions of complex biophysical phenomena for a relatively cheap computational cost. As a proof of concept, this lesson demonstrates the construction of a CG model of a small globular protein, its simulation via Langevin dynamics, and the analysis of the resulting data. This lesson makes connections between modern molecular simulation techniques and topics commonly presented in an advanced undergraduate lecture on physical chemistry. It culminates in a straightforward analysis of a short dynamics trajectory of a small fast folding globular protein; we briefly describe the thermodynamic properties that can be calculated from this analysis. The assumptions inherent in the model and the data analysis are laid out in a clear, concise manner, and the techniques used are consistent with those employed by specialists in the field of CG modeling. One of the major tasks in building the G-like model is determining the relative strength of the nonbonded interactions between coarse-grained sites. New functionality has been added to CHARMMing to facilitate this process. The implementation of these features into CHARMMing helps automate many of the tedious aspects of constructing a CG G model. The CG model builder and its accompanying lesson should be a valuable tool to chemistry students, teachers, and modelers in the field.

Substrate-bound outward-open state of the betaine transporter BetP provides insights into Na+ coupling

The Na(+)-coupled betaine symporter BetP shares a highly conserved fold with other sequence unrelated secondary transporters, for example, with neurotransmitter symporters. Recently, we obtained atomic structures of BetP in distinct conformational states, which elucidated parts of its alternating-access mechanism. Here, we report a structure of BetP in a new outward-open state in complex with an anomalous scattering substrate, adding a fundamental piece to an unprecedented set of structural snapshots for a secondary transporter. In combination with molecular dynamics simulations these structural data highlight important features of the sequential formation of the substrate and sodium-binding sites, in which coordinating water molecules play a crucial role. We observe a strictly interdependent binding of betaine and sodium ions during the coupling process. All three sites undergo progressive reshaping and dehydration during the alternating-access cycle, with the most optimal coordination of all substrates found in the closed state.

Challenges, applications, and recent advances of protein-ligand docking in structure-based drug design

The docking methods used in structure-based virtual database screening offer the ability to quickly and cheaply estimate the affinity and binding mode of a ligand for the protein receptor of interest, such as a drug target. These methods can be used to enrich a database of compounds, so that more compounds that are subsequently experimentally tested are found to be pharmaceutically interesting. In addition, like all virtual screening methods used for drug design, structure-based virtual screening can focus on curated libraries of synthesizable compounds, helping to reduce the expense of subsequent experimental verification. In this review, we introduce the protein-ligand docking methods used for structure-based drug design and other biological applications. We discuss the fundamental challenges facing these methods and some of the current methodological topics of interest. We also discuss the main approaches for applying protein-ligand docking methods. We end with a discussion of the challenging aspects of evaluating or benchmarking the accuracy of docking methods for their improvement, and discuss future directions.

Evaluation of CM5 Charges for Condensed-Phase Modeling

The recently developed Charge Model 5 (CM5) is tested for its utility in condensed-phase simulations. The CM5 approach, which derives partial atomic charges from Hirshfeld population analyses, provides excellent results for gas-phase dipole moments and is applicable to all elements of the periodic table. Herein, the adequacy of scaled CM5 charges for use in modeling aqueous solutions has been evaluated by computing free energies of hydration (ΔGhyd) for 42 neutral organic molecules via Monte Carlo statistical mechanics. An optimal scaling factor for the CM5 charges was determined to be 1.27, resulting in a mean unsigned error (MUE) of 1.1 kcal/mol for the free energies of hydration. Testing for an additional 20 molecules gave an MUE of 1.3 kcal/mol. The high precision of the results is confirmed by free energy calculations using both sequential perturbations and complete molecular annihilation. Performance for specific functional groups is discussed; sulfur-containing molecules yield the largest errors. In addition, the scaling factor of 1.27 is shown to be appropriate for CM5 charges derived from a variety of density functional methods and basis sets. Though the average errors from the 1.27*CM5 results are only slightly lower than those using 1.14*CM1A charges, the broader applicability and easier access to CM5 charges via the Gaussian program are additional attractive features. The 1.27*CM5 charge model can be used for an enormous variety of applications in conjunction with many fixed-charge force fields and molecular modeling programs.

Base flip in DNA studied by molecular dynamics simulationsof differently-oxidized forms of methyl-Cytosine

Distortions in the DNA sequence, such as damage or mispairs, are specifically recognized and processed by DNA repair enzymes. Many repair proteins and, in particular, glycosylases flip the target base out of the DNA helix into the enzyme’s active site. Our molecular dynamics simulations of DNA with intact and damaged (oxidized) methyl-cytosine show that the probability of being flipped is similar for damaged and intact methyl-cytosine. However, the accessibility of the different 5-methyl groups allows direct discrimination of the oxidized forms. Hydrogen-bonded patterns that vary between methyl-cytosine forms carrying a carbonyl oxygen atom are likely to be detected by the repair enzymes and may thus help target site recognition.

Perspectives on the simulation of protein-surface interactions using empirical force field methods

Protein-surface interactions are of fundamental importance for a broad range of applications in the fields of biomaterials and biotechnology. Present experimental methods are limited in their ability to provide a comprehensive depiction of these interactions at the atomistic level. In contrast, empirical force field based simulation methods inherently provide the ability to predict and visualize protein-surface interactions with full atomistic detail. These methods, however, must be carefully developed, validated, and properly applied before confidence can be placed in results from the simulations. In this perspectives paper, I provide an overview of the critical aspects that I consider being of greatest importance for the development of these methods, with a focus on the research that my combined experimental and molecular simulation groups have conducted over the past decade to address these issues. These critical issues include the tuning of interfacial force field parameters to accurately represent the thermodynamics of interfacial behavior, adequate sampling of these types of complex molecular systems to generate results that can be comparable with experimental data, and the generation of experimental data that can be used for simulation results evaluation and validation.

Synthesis, biological, and biophysical studies of DAG-indololactones designed as selective activators of RasGRP

The development of selective agents capable of discriminating between protein kinase C (PKC) isoforms and other diacylglycerol (DAG)-responsive C1 domain-containing proteins represents an important challenge. Recent studies have highlighted the role that Ras guanine nucleotide-releasing protein (RasGRP) isoforms play both in immune responses as well as in the development of prostate cancer and melanoma, suggesting that the discovery of selective ligands could have potential therapeutic value. Thus far, the N-methyl-substituted indololactone 1 is the agonist with the highest reported potency and selectivity for RasGRP relative to PKC. Here we present the synthesis, binding studies, cellular assays and biophysical analysis of interactions with model membranes of a family of regioisomers of 1 (compounds 2-5) that differ in the position of the linkage between the indole ring and the lactone moiety. These structural variations were studied to explore the interaction of the active complex (C1 domain-ligand) with cellular membranes, which is believed to be an important factor for selectivity in the activation of DAG-responsive C1 domain containing signaling proteins. All compounds were potent and selective activators of RasGRP when compared to PKCα with selectivities ranging from 6 to 65 fold. However, the parent compound 1 was appreciably more selective than any of the other isomers. In intact cells, modest differences in the patterns of translocation of the C1 domain targets were observed. Biophysical studies using giant vesicles as model membranes did show substantial differences in terms of molecular interactions impacting lipid organization, dynamics and membrane insertion. However, these differences did not yield correspondingly large changes in patterns of biological response, at least for the parameters examined.

Derivation of coarse-grained potentials via multistate iterative Boltzmann inversion

In this work, an extension is proposed to the standard iterative Boltzmann inversion (IBI) method used to derive coarse-grained potentials. It is shown that the inclusion of target data from multiple states yields a less state-dependent potential, and is thus better suited to simulate systems over a range of thermodynamic states than the standard IBI method. The inclusion of target data from multiple states forces the algorithm to sample regions of potential phase space that match the radial distribution function at multiple state points, thus producing a derived potential that is more representative of the underlying interactions. It is shown that the algorithm is able to converge to the true potential for a system where the underlying potential is known. It is also shown that potentials derived via the proposed method better predict the behavior of n-alkane chains than those derived via the standard IBI method. Additionally, through the examination of alkane monolayers, it is shown that the relative weight given to each state in the fitting procedure can impact bulk system properties, allowing the potentials to be further tuned in order to match the properties of reference atomistic and/or experimental systems.

Sampling of Organic Solutes in Aqueous and Heterogeneous Environments Using Oscillating Excess Chemical Potentials in Grand Canonical-like Monte Carlo-Molecular Dynamics Simulations

Solute sampling of explicit bulk-phase aqueous environments in grand canonical (GC) ensemble simulations suffer from poor convergence due to low insertion probabilities of the solutes. To address this, we developed an iterative procedure involving Grand Canonical-like Monte Carlo (GCMC) and molecular dynamics (MD) simulations. Each iteration involves GCMC of both the solutes and water followed by MD, with the excess chemical potential (μex) of both the solute and the water oscillated to attain their target concentrations in the simulation system. By periodically varying the μex of the water and solutes over the GCMC-MD iterations, solute exchange probabilities and the spatial distributions of the solutes improved. The utility of the oscillating-μex GCMC-MD method is indicated by its ability to approximate the hydration free energy (HFE) of the individual solutes in aqueous solution as well as in dilute aqueous mixtures of multiple solutes. For seven organic solutes: benzene, propane, acetaldehyde, methanol, formamide, acetate, and methylammonium, the average μex of the solutes and the water converged close to their respective HFEs in both 1 M standard state and dilute aqueous mixture systems. The oscillating-μex GCMC methodology is also able to drive solute sampling in proteins in aqueous environments as shown using the occluded binding pocket of the T4 lysozyme L99A mutant as a model system. The approach was shown to satisfactorily reproduce the free energy of binding of benzene as well as sample the functional group requirements of the occluded pocket consistent with the crystal structures of known ligands bound to the L99A mutant as well as their relative binding affinities.

In vivo structure-activity relationship studies support allosteric targeting of a dual specificity phosphatase

Dual specificity phosphatase 6 (DUSP6) functions as a feedback attenuator of fibroblast growth factor signaling during development. In vitro high throughput chemical screening attempts to discover DUSP6 inhibitors have yielded limited success. However, in vivo whole-organism screens of zebrafish identified compound 1 (BCI) as an allosteric inhibitor of DUSP6. Here we designed and synthesized a panel of analogues to define the structure-activity relationship (SAR) of DUSP6 inhibition. In vivo high-content analysis in transgenic zebrafish, coupled with cell-based chemical complementation assays, identified structural features of the pharmacophore of 1 that were essential for biological activity. In vitro assays of DUSP hyperactivation corroborated the results from in vivo and cellular SAR. The results reinforce the notion that DUSPs are druggable through allosteric mechanisms and illustrate the utility of zebrafish as a model organism for in vivo SAR analyses.

Can molecular dynamics and QM/MM solve the penicillin binding protein protonation puzzle?

Benzylpenicillin, a member of the β-lactam antibiotic class, has been widely used to combat bacterial infections since 1947. The general mechanism is well-known: a serine protease enzyme (i.e., DD-peptidase) forms a long lasting intermediate with the lactam ring of the antibiotic known as acylation, effectively preventing biosynthesis of the bacterial cell wall. Despite this overall mechanistic understanding, many details of binding and catalysis are unclear. Specifically, there is ongoing debate about active site protonation states and the role of general acids/bases in the reaction. Herein, a unique combination of MD simulations, QM/MM minimizations, and QM/MM orbital analyses is combined with systematic variation of active site residue protonation states. Critical interactions that maximize the stability of the bound inhibitor are examined and used as metrics. This approach was validated by examining cefoxitin interactions in the CTX-M β-lactamase from E. coli and compared to an ultra high-resolution (0.88 Å) crystal structure. Upon confirming the approach used, an investigation of the preacylated Streptomyces R61 active site with bound benzylpenicillin was performed, varying the protonation states of His298 and Lys65. We concluded that protonated His298 and deprotonated Lys65 are most likely to exist in the R61 active site.

A fixed-charge model for alcohol polarization in the condensed phase, and its role in small molecule hydration

We present a simple optimization strategy for incorporating experimental dielectric response information on neat liquids in classical molecular models of alcohol. Using this strategy, we determine simple and transferable hydroxyl modulation rules that, when applied to an existing molecular parameter set, result in a newly dielectric corrected (DC) parameter set. We applied these rules to the general Amber force field (GAFF) to form an initial set of GAFF-DC parameters, and we found this to lead to significant improvement in the calculated dielectric constant and hydration free energy values for a wide variety of small molecule alcohol models. Tests of the GAFF-DC parameters in the SAMPL4 blind prediction event for hydration show these changes improve agreement with experiment. Surprisingly, these simple modifications also outperform detailed quantum mechanical electric field calculations using a self-consistent reaction field environment coupling term. This work provides a potential benchmark for future developments in methods for representing condensed-phase environments in electronic structure calculations.

Free energy landscape of G-protein coupled receptors, explored by accelerated molecular dynamics

G-protein coupled receptors (GPCRs) mediate cellular responses to various hormones and neurotransmitters and are important targets for treating a wide spectrum of diseases. They are known to adopt multiple conformational states (e.g., inactive, intermediate and active) during their modulation of various cell signaling pathways. Here, the free energy landscape of GPCRs is explored using accelerated molecular dynamics (aMD) simulations as demonstrated on the M2 muscarinic receptor, a key GPCR that regulates human heart rate and contractile forces of cardiomyocytes. Free energy profiles of important structural motifs that undergo conformational transitions upon GPCR activation and allosteric signaling are analyzed in detail, including the Arg(3.50)-Glu(6.30) ionic lock, the Trp(6.48) toggle switch and the hydrogen interactions between Tyr(5.58)-Tyr(7.53).

A Comparative Study of Transferable Aspherical Pseudoatom Databank and Classical Force Fields for Predicting Electrostatic Interactions in Molecular Dimers

Accurate and fast evaluation of electrostatic interactions in molecular systems is one of the most challenging tasks in the rapidly advancing field of macromolecular chemistry and drug design. Electrostatic interactions are of crucial importance in biological systems. They are well represented by quantum mechanical methods; however, such calculations are computationally expensive. In this study, we have evaluated the University of Buffalo Pseudoatom Databank (UBDB)1,2 approach for approximation of electrostatic properties of macromolecules and their complexes. We selected the S663 and JSCH-20054 data sets (208 molecular complexes in total) for this study. These complexes represent a wide range of chemical and biological systems for which hydrogen bonding, electrostatic, and van der Waals interactions play important roles. Reference electrostatic energies were obtained directly from wave functions at the B3LYP/aug-cc-pVTZ level of theory using the SAPT (Symmetry-Adapted Perturbation Theory) scheme for calculation of electrostatic contributions to total intermolecular interaction energies. Electrostatic energies calculated on the basis of the UBDB were compared with corresponding reference results. Results were also compared with energies computed using a point charge model from popular force fields (AM1-BCC and RESP used in AMBER and CGenFF from CHARMM family). The energy trends are quite consistent (R2 ≈ 0.98) for the UBDB method as compared to the AMBER5 and CHARMM force field methods6(R2 ≈ 0.93 on average). The RSMEs do not exceed 3.2 kcal mol-1 for the UBDB and are in the range of 3.7-7.6 kcal mol-1 for the point charge models. We also investigated the discrepancies in electrostatic potentials and magnitudes of dipole moments among the tested methods. This study shows that estimation of electrostatic interaction energies using the UBDB databank is accurate and reasonably fast when compared to other known methods, which opens potential new applications to macromolecules.

Functional mechanism of C-terminal tail in the enzymatic role of porcine testicular carbonyl reductase: a combined experiment and molecular dynamics simulation study of the C-terminal tail in the enzymatic role of PTCR

Porcine testicular carbonyl reductase, PTCR which is one of the short chain dehydrogenases/reductases (SDR) superfamily catalyzes the NADPH-dependent reduction of carbonyl compounds including steroids and prostaglandins. Previously we reported C- terminal tail of PTCR was deleted due to a nonsynonymous single nucleotide variation (nsSNV). Here we identified from kinetic studies that the enzymatic properties for 5α-dihydrotestosterone (5α-DHT) were different between wild-type and C-terminal-deleted PTCRs. Compared to wild-type PTCR, C-terminal-deleted PTCR has much higher reduction rate. To investigate structural difference between wild-type and C-terminal-deleted PTCRs upon 5α-DHT binding, we performed molecular dynamics simulations for two complexes. Using trajectories, molecular interactions including hydrogen bonding patterns, distance between 5α-DHT and catalytic Tyr193, and interaction energies are analyzed and compared. During the MD simulation time, the dynamic behavior of C-terminal tail in wild-type PTCR is also examined using essential dynamics analysis. The results of our simulations reveal that the binding conformation of 5α-DHT in C-terminal-deleted PTCR is more favorable for reduction reaction in PTCR, which shows strong agreement with kinetic data. These structural findings provide valuable information to understand substrate specificity of PTCR and further kinetic properties of enzymes belonging to the SDR superfamily.

Rehabilitating drug-induced long-QT promoters: in-silico design of hERG-neutral cisapride analogues with retained pharmacological activity

Background

The human ether-a-go-go related gene 1 (hERG1), which codes for a potassium ion channel, is a key element in the cardiac delayed rectified potassium current, I_Kr, and plays an important role in the normal repolarization of the heart’s action potential. Many approved drugs have been withdrawn from the market due to their prolongation of the QT interval. Most of these drugs have high potencies for their principal targets and are often irreplaceable, thus “rehabilitation” studies for decreasing their high hERG1 blocking affinities, while keeping them active at the binding sites of their targets, have been proposed to enable these drugs to re-enter the market.

Methods

In this proof-of-principle study, we focus on cisapride, a gastroprokinetic agent withdrawn from the market due to its high hERG1 blocking affinity. Here we tested an a priori strategy to predict a compound’s cardiotoxicity using de novo drug design with molecular docking and Molecular Dynamics (MD) simulations to generate a strategy for the rehabilitation of cisapride.

Results

We focused on two key receptors, a target interaction with the (adenosine) receptor and an off-target interaction with hERG1 channels. An analysis of the fragment interactions of cisapride at human A_2A adenosine receptors and hERG1 central cavities helped us to identify the key chemical groups responsible for the drug activity and hERG1 blockade. A set of cisapride derivatives with reduced cardiotoxicity was then proposed using an in-silico two-tier approach. This set was compared against a large dataset of commercially available cisapride analogs and derivatives.

Conclusions

An interaction decomposition of cisapride and cisapride derivatives allowed for the identification of key active scaffolds and functional groups that may be responsible for the unwanted blockade of hERG1.

Interaction between functionalized gold nanoparticles in physiological saline

The interactions between functionalized noble-metal particles in an aqueous solution are central to applications relying on controlled equilibrium association. Herein, we obtain the potentials of mean force (PMF) for pair-interactions between functionalized gold nanoparticles (AuNPs) in physiological saline. These results are based upon >1000 ns experiments in silico of all-atom model systems under equilibrium and non-equilibrium conditions. Four types of functionalization are built by coating each globular Au144 cluster with 60 thiolate groups: GS-AuNP (glutathionate), PhS-AuNP (thiophenol), CyS-AuNP (cysteinyl), and p-APhS-AuNP (para-amino-thiophenol), which are, respectively, negatively charged, hydrophobic (neutral-nonpolar), hydrophilic (neutral-polar), and positively charged at neutral pH. The results confirm the behavior expected of neutral (hydrophilic or hydrophobic) particles in a dilute aqueous environment, however the PMF curves demonstrate that the charged AuNPs interact with one another in a unique way-mediated by H2O molecules and an electrolyte (Na(+), Cl(-))-in a physiological environment. In the case of two GS-AuNPs, the excess, neutralizing Na(+) ions form a mobile (or 'dynamic') cloud of enhanced concentration between the like-charged GS-AuNPs, inducing a moderate attraction (∼25 kT) between them. Furthermore, to a lesser degree, for a pair of p-APhS-AuNPs, the excess, neutralizing Cl(-) ions (less mobile than Na(+)) also form a cloud of higher concentration between the two like-charged p-APhS-AuNPs, inducing weaker yet significant attractions (∼12 kT). On combining one GS- with one p-APhS-AuNP, the direct, attractive Coulombic force is completely screened out while the solvation effects give rise to moderate repulsion between the two unlike-charged AuNPs.

The SAMPL4 host-guest blind prediction challenge: an overview

Prospective validation of methods for computing binding affinities can help assess their predictive power and thus set reasonable expectations for their performance in drug design applications. Supramolecular host-guest systems are excellent model systems for testing such affinity prediction methods, because their small size and limited conformational flexibility, relative to proteins, allows higher throughput and better numerical convergence. The SAMPL4 prediction challenge therefore included a series of host-guest systems, based on two hosts, cucurbit[7]uril and octa-acid. Binding affinities in aqueous solution were measured experimentally for a total of 23 guest molecules. Participants submitted 35 sets of computational predictions for these host-guest systems, based on methods ranging from simple docking, to extensive free energy simulations, to quantum mechanical calculations. Over half of the predictions provided better correlations with experiment than two simple null models, but most methods underperformed the null models in terms of root mean squared error and linear regression slope. Interestingly, the overall performance across all SAMPL4 submissions was similar to that for the prior SAMPL3 host-guest challenge, although the experimentalists took steps to simplify the current challenge. While some methods performed fairly consistently across both hosts, no single approach emerged as consistent top performer, and the nonsystematic nature of the various submissions made it impossible to draw definitive conclusions regarding the best choices of energy models or sampling algorithms. Salt effects emerged as an issue in the calculation of absolute binding affinities of cucurbit[7]uril-guest systems, but were not expected to affect the relative affinities significantly. Useful directions for future rounds of the challenge might involve encouraging participants to carry out some calculations that replicate each others' studies, and to systematically explore parameter options.

The SAMPL4 hydration challenge: evaluation of partial charge sets with explicit-water molecular dynamics simulations

We used blind predictions of the 47 hydration free energies in the SAMPL4 challenge to test multiple partial charge models in the context of explicit solvent free energy simulations with the general AMBER force field. One of the partial charge models, IPolQ-Mod, is a fast continuum solvent-based implementation of the IPolQ approach. The AM1-BCC, restrained electrostatic potential (RESP) and IpolQ-Mod approaches all perform reasonably well (R(2) > 0.8), while VCharge, though faster, gives less accurate results (R(2) of 0.5). The AM1-BCC results are more accurate than those of RESP for tertiary amines and nitrates, but the overall difference in accuracy between these methods is not statistically significant. Interestingly, the IPolQ-Mod method is found to yield partial charges in very close agreement with RESP. This observation suggests that the success of RESP may be attributed to its fortuitously approximating the arguably more rigorous IPolQ approach.

Crystal structure of cindoxin, the P450cin redox partner

The crystal structure of the flavin mononucleotide (FMN)-containing redox partner to P450cin, cindoxin (Cdx), has been determined to 1.3 Å resolution. The overall structure is similar to that of the FMN domain of human cytochrome P450 reductase. A Brownian dynamics–molecular dynamics docking method was used to produce a model of Cdx with its redox partner, P450cin. This Cdx–P450cin model highlights the potential importance of Cdx Tyr96 in bridging the FMN and heme cofactors as well P450cin Arg102 and Arg346. Each of the single-site Ala mutants exhibits ∼10% of the wild-type activity, thus demonstrating the importance of these residues for binding and/or electron transfer. In the well-studied P450cam system, redox partner binding stabilizes the open low-spin conformation of P450cam and greatly decreases the stability of the oxy complex. In sharp contrast, Cdx does not shift P450cin to a low-spin state, although the stability of oxy-P450cin is decreased 10-fold in the presence of Cdx. This indicates that Cdx may have a modest effect on the open–closed equilibrium in P450cin compared to that in P450cam. It has been postulated that part of the effector role of Pdx on P450cam is to promote a significant structural change that makes available a proton relay network involving Asp251 required for O₂ activation. The structure around the corresponding Asp in P450cin, Asp241, provides a possible structural reason for why P450cin is less dependent on its redox partner for functionally important structural changes.

LIBSA--a method for the determination of ligand-binding preference to allosteric sites on receptor ensembles

Incorporation of receptor flexibility into computational drug discovery through the relaxed complex scheme is well suited for screening against a single binding site. In the absence of a known pocket or if there are multiple potential binding sites, it may be necessary to do docking against the entire surface of the target (global docking). However no suitable and easy-to-use tool is currently available to rank global docking results based on the preference of a ligand for a given binding site. We have developed a protocol, termed LIBSA for LIgand Binding Specificity Analysis, that analyzes multiple docked poses against a single or ensemble of receptor conformations and returns a metric for the relative binding to a specific region of interest. By using novel filtering algorithms and the signal-to-noise ratio (SNR), the relative ligand-binding frequency at different pockets can be calculated and compared quantitatively. Ligands can then be triaged by their tendency to bind to a site instead of ranking by affinity alone. The method thus facilitates screening libraries of ligand cores against a large library of receptor conformations without prior knowledge of specific pockets, which is especially useful to search for hits that selectively target a particular site. We demonstrate the utility of LIBSA by showing that it correctly identifies known ligand binding sites and predicts the relative preference of a set of related ligands for different pockets on the same receptor.

Escherichia coli peptidoglycan structure and mechanics as predicted by atomic-scale simulations

Bacteria face the challenging requirement to maintain their shape and avoid rupture due to the high internal turgor pressure, but simultaneously permit the import and export of nutrients, chemical signals, and virulence factors. The bacterial cell wall, a mesh-like structure composed of cross-linked strands of peptidoglycan, fulfills both needs by being semi-rigid, yet sufficiently porous to allow diffusion through it. How the mechanical properties of the cell wall are determined by the molecular features and the spatial arrangement of the relatively thin strands in the larger cellular-scale structure is not known. To examine this issue, we have developed and simulated atomic-scale models of Escherichia coli cell walls in a disordered circumferential arrangement. The cell-wall models are found to possess an anisotropic elasticity, as known experimentally, arising from the orthogonal orientation of the glycan strands and of the peptide cross-links. Other features such as thickness, pore size, and disorder are also found to generally agree with experiments, further supporting the disordered circumferential model of peptidoglycan. The validated constructs illustrate how mesoscopic structure and behavior emerge naturally from the underlying atomic-scale properties and, furthermore, demonstrate the ability of all-atom simulations to reproduce a range of macroscopic observables for extended polymer meshes.

The structure of the bacterial cell wall has been a point of controversy and contention since it was first discovered. Although the basic chemical composition of peptidoglycan, the key constituent of the cell wall, is now well established, its long-range organization is not. This dearth of information at the mesoscopic scale is a result of the inability of experimental imaging techniques to simultaneously visualize both the atomic-level detail of the peptidoglycan network and its macroscopic arrangement around the bacterium. Now, using molecular dynamics (MD) simulations, we have carefully constructed and validated models of sections of the Escherichia coli cell wall in full atomic detail. By comparing various properties of these models, including elasticity, pore size, and thickness with experiments, we can discriminate between them, resolving which best represents the native wall structure. In doing so, our study provides approaches for connecting measurements made in atomic-scale MD simulations with large-scale and even macroscopic properties.

Multiscale Free Energy Simulations: An Efficient Method for Connecting Classical MD Simulations to QM or QM/MM Free Energies Using Non-Boltzmann Bennett Reweighting Schemes

The reliability of free energy simulations (FES) is limited by two factors: (a) the need for correct sampling and (b) the accuracy of the computational method employed. Classical methods (e.g., force fields) are typically used for FES and present a myriad of challenges, with parametrization being a principle one. On the other hand, parameter-free quantum mechanical (QM) methods tend to be too computationally expensive for adequate sampling. One widely used approach is a combination of methods, where the free energy difference between the two end states is computed by, e.g., molecular mechanics (MM), and the end states are corrected by more accurate methods, such as QM or hybrid QM/MM techniques. Here we report two new approaches that significantly improve the aforementioned scheme; with a focus on how to compute corrections between, e.g., the MM and the more accurate QM calculations. First, a molecular dynamics trajectory that properly samples relevant conformational degrees of freedom is generated. Next, potential energies of each trajectory frame are generated with a QM or QM/MM Hamiltonian. Free energy differences are then calculated based on the QM or QM/MM energies using either a non-Boltzmann Bennett approach (QM-NBB) or non-Boltzmann free energy perturbation (NB-FEP). Both approaches are applied to calculate relative and absolute solvation free energies in explicit and implicit solvent environments. Solvation free energy differences (relative and absolute) between ethane and methanol in explicit solvent are used as the initial test case for QM-NBB. Next, implicit solvent methods are employed in conjunction with both QM-NBB and NB-FEP to compute absolute solvation free energies for 21 compounds. These compounds range from small molecules such as ethane and methanol to fairly large, flexible solutes, such as triacetyl glycerol. Several technical aspects were investigated. Ultimately some best practices are suggested for improving methods that seek to connect MM to QM (or QM/MM) levels of theory in FES.

Filling up the heme pocket stabilizes apomyoglobin and speeds up its folding

Wild type apomyoglobin folds in at least two steps: the ABGH core rapidly, followed much later by the heme-binding CDEF core. We hypothesize that the evolved heme-binding function of the CDEF core frustrates its folding: it has a smaller contact order and is no more complex topologically than ABGH, and thus, it should be able to fold faster. Therefore, filling up the empty heme cavity of apomyoglobin with larger, hydrophobic side chains should significantly stabilize the protein and increase its folding rate. Molecular dynamics simulations allowed us to design four different mutants with bulkier side chains that increase the native bias of the CDEF region. In vitro thermal denaturation shows that the mutations increase folding stability and bring the protein closer to two-state behavior, as judged by the difference of fluorescence- and circular dichroism-detected protein stability. Millisecond stopped flow measurements of the mutants exhibit refolding kinetics that are over 4 times faster than the wild type’s. We propose that myoglobin-like proteins not evolved to bind heme are equally stable, and find an example. Our results illustrate how evolution for function can force proteins to adapt frustrated folding mechanisms, despite having simple topologies.

Predicting hydration free energies with a hybrid QM/MM approach: an evaluation of implicit and explicit solvation models in SAMPL4

The correct representation of solute-water interactions is essential for the accurate simulation of most biological phenomena. Several highly accurate quantum methods are available to deal with solvation by using both implicit and explicit solvents. So far, however, most evaluations of those methods were based on a single conformation, which neglects solute entropy. Here, we present the first test of a novel approach to determine hydration free energies that uses molecular mechanics (MM) to sample phase space and quantum mechanics (QM) to evaluate the potential energies. Free energies are determined by using re-weighting with the Non-Boltzmann Bennett (NBB) method. In this context, the method is referred to as QM-NBB. Based on snapshots from MM sampling and accounting for their correct Boltzmann weight, it is possible to obtain hydration free energies that incorporate the effect of solute entropy. We evaluate the performance of several QM implicit solvent models, as well as explicit solvent QM/MM for the blind subset of the SAMPL4 hydration free energy challenge. While classical free energy simulations with molecular dynamics give root mean square deviations (RMSD) of 2.8 and 2.3 kcal/mol, the hybrid approach yields an improved RMSD of 1.6 kcal/mol. By selecting an appropriate functional and basis set, the RMSD can be reduced to 1 kcal/mol for calculations based on a single conformation. Results for a selected set of challenging molecules imply that this RMSD can be further reduced by using NBB to reweight MM trajectories with the SMD implicit solvent model.

Testing and validation of the Automated Topology Builder (ATB) version 2.0: prediction of hydration free enthalpies

To test and validate the Automated force field Topology Builder and Repository (ATB; http://compbio.biosci.uq.edu.au/atb/ ) the hydration free enthalpies for a set of 214 drug-like molecules, including 47 molecules that form part of the SAMPL4 challenge have been estimated using thermodynamic integration and compared to experiment. The calculations were performed using a fully automated protocol that incorporated a dynamic analysis of the convergence and integration error in the selection of intermediate points. The system has been designed and implemented such that hydration free enthalpies can be obtained without manual intervention following the submission of a molecule to the ATB. The overall average unsigned error (AUE) using ATB 2.0 topologies for the complete set of 214 molecules was 6.7 kJ/mol and for molecules within the SAMPL4 7.5 kJ/mol. The root mean square error (RMSE) was 9.5 and 10.0 kJ/mol respectively. However, for molecules containing functional groups that form part of the main GROMOS force field the AUE was 3.4 kJ/mol and the RMSE was 4.0 kJ/mol. This suggests it will be possible to further refine the parameters provided by the ATB based on hydration free enthalpies.

Partitioning of amino acids into a model membrane: capturing the interface

Energetics of protein side chain partitioning between aqueous solution and cellular membranes is of fundamental importance for correctly capturing the membrane binding and specific protein–lipid interactions of peripheral membrane proteins. We recently reported a highly mobile membrane mimetic (HMMM) model that accelerates lipid dynamics by modeling the membrane interior partially as a fluid organic solvent while retaining a literal description of the lipid head groups and the beginning of the tails. While the HMMM has been successfully applied to study spontaneous insertion of a number of peripheral proteins into membranes, a quantitative characterization of the energetics of membrane–protein interactions in HMMM membranes has not been performed. We report here the free energy profiles for partitioning of 10 protein side chain analogues into a HMMM membrane. In the interfacial and headgroup regions of the membrane, the side chain free energy profiles show excellent agreement with profiles previously reported for conventional membranes with full-tail lipids. In regions where the organic solvent is prevalent, the increased dipole and fluidity of the solvent generally result in a less accurate description, most notably overstabilization of aromatic and polar amino acids. As an additional measure of the ability of the HMMM model to describe membrane–protein interactions, the water-to-membrane interface transfer energies were analyzed and found to be in agreement with the previously reported experimental and computational hydrophobicity scales. We discuss strengths and weaknesses of HMMM in describing protein–membrane interactions as well as further development of model membranes.

Identification and Characterization of Noncovalent Interactions That Drive Binding and Specificity in DD-Peptidases and β-Lactamases

Bacterial resistance to standard (i.e., β-lactam-based) antibiotics has become a global pandemic. Simultaneously, research into the underlying causes of resistance has slowed substantially, although its importance is universally recognized. Key to unraveling critical details is characterization of the noncovalent interactions that govern binding and specificity (DD-peptidases, antibiotic targets, versus β-lactamases, the evolutionarily derived enzymes that play a major role in resistance) and ultimately resistance as a whole. Herein, we describe a detailed investigation that elicits new chemical insights into these underlying intermolecular interactions. Benzylpenicillin and a novel β-lactam peptidomimetic complexed to the Stremptomyces R61 peptidase are examined using an arsenal of computational techniques: MD simulations, QM/MM calculations, charge perturbation analysis, QM/MM orbital analysis, bioinformatics, flexible receptor/flexible ligand docking, and computational ADME predictions. Several key molecular level interactions are identified that not only shed light onto fundamental resistance mechanisms, but also offer explanations for observed specificity. Specifically, an extended π–π network is elucidated that suggests antibacterial resistance has evolved, in part, due to stabilizing aromatic interactions. Additionally, interactions between the protein and peptidomimetic substrate are identified and characterized. Of particular interest is a water-mediated salt bridge between Asp217 and the positively charged N-terminus of the peptidomimetic, revealing an interaction that may significantly contribute to β-lactam specificity. Finally, interaction information is used to suggest modifications to current β-lactam compounds that should both improve binding and specificity in DD-peptidases and their physiochemical properties.

Conopeptide Vt3.1 preferentially inhibits BK potassium channels containing β4 subunits via electrostatic interactions

BK channel β subunits (β1-β4) modulate the function of channels formed by slo1 subunits to produce tissue-specific phenotypes. The molecular mechanism of how the homologous β subunits differentially alter BK channel functions and the role of different BK channel functions in various physiologic processes remain unclear. By studying channels expressed in Xenopus laevis oocytes, we show a novel disulfide-cross-linked dimer conopeptide, Vt3.1 that preferentially inhibits BK channels containing the β4 subunit, which is most abundantly expressed in brain and important for neuronal functions. Vt3.1 inhibits the currents by a maximum of 71%, shifts the G-V relation by 45 mV approximately half-saturation concentrations, and alters both open and closed time of single channel activities, indicating that the toxin alters voltage dependence of the channel. Vt3.1 contains basic residues and inhibits voltage-dependent activation by electrostatic interactions with acidic residues in the extracellular loops of the slo1 and β4 subunits. These results suggest a large interaction surface between the slo1 subunit of BK channels and the β4 subunit, providing structural insight into the molecular interactions between slo1 and β4 subunits. The results also suggest that Vt3.1 is an excellent tool for studying β subunit modulation of BK channels and for understanding the physiological roles of BK channels in neurophysiology.

Anti-prion activity of a panel of aromatic chemical compounds: in vitro and in silico approaches

The prion protein (PrP) is implicated in the Transmissible Spongiform Encephalopathies (TSEs), which comprise a group of fatal neurodegenerative diseases affecting humans and other mammals. Conversion of cellular PrP (PrP(C)) into the scrapie form (PrP(Sc)) is the hallmark of TSEs. Once formed, PrP(Sc) aggregates and catalyzes PrP(C) misfolding into new PrP(Sc) molecules. Although many compounds have been shown to inhibit the conversion process, so far there is no effective therapy for TSEs. Besides, most of the previously evaluated compounds failed in vivo due to poor pharmacokinetic profiles. In this work we propose a combined in vitro/in silico approach to screen for active anti-prion compounds presenting acceptable drugability and pharmacokinetic parameters. A diverse panel of aromatic compounds was screened in neuroblastoma cells persistently infected with PrP(Sc) (ScN2a) for their ability to inhibit PK-resistant PrP (PrP(Res)) accumulation. From ∼200 compounds, 47 were effective in decreasing the accumulation of PrP(Res) in ScN2a cells. Pharmacokinetic and physicochemical properties were predicted in silico, allowing us to obtain estimates of relative blood brain barrier permeation and mutagenicity. MTT reduction assays showed that most of the active compounds were non cytotoxic. Compounds that cleared PrP(Res) from ScN2a cells, were non-toxic in the MTT assay, and presented a good pharmacokinetic profile were investigated for their ability to inhibit aggregation of an amyloidogenic PrP peptide fragment (PrP(109-149)). Molecular docking results provided structural models and binding affinities for the interaction between PrP and the most promising compounds. In summary, using this combined in vitro/in silico approach we have identified new small organic anti-scrapie compounds that decrease the accumulation of PrP(Res) in ScN2a cells, inhibit the aggregation of a PrP peptide, and possess pharmacokinetic characteristics that support their drugability. These compounds are attractive candidates for prion disease therapy.

Molecular mechanics

Molecular Mechanics (MM) force fields are the methods of choice for protein simulations, which are essential in the study of conformational flexibility. Given the importance of protein flexibility in drug binding, MM is involved in most if not all Computational Structure-Based Drug Discovery (CSBDD) projects. This paper introduces the reader to the fundamentals of MM, with a special emphasis on how the target data used in the parametrization of force fields determine their strengths and weaknesses. Variations and recent developments such as polarizable force fields are discussed. The paper ends with a brief overview of common force fields in CSBDD.

Multi-scale computational enzymology: enhancing our understanding of enzymatic catalysis

Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis.

Gas-phase ion isomer analysis reveals the mechanism of peptide sequence scrambling

Peptide sequence scrambling during mass spectrometry-based gas-phase fragmentation analysis causes misidentification of peptides and proteins. Thus, there is a need to develop an efficient approach to probing the gas-phase fragment ion isomers related to sequence scrambling and the underlying fragmentation mechanism, which will facilitate the development of bioinformatics algorithm for proteomics research. Herein, we report on the first use of electron transfer dissociation (ETD)-produced diagnostic fragment ions to probe the components of gas-phase peptide fragment ion isomers. In combination with ion mobility spectrometry (IMS) and formaldehyde labeling, this novel strategy enables qualitative and quantitative analysis of b-type fragment ion isomers. ETD fragmentation produced diagnostic fragment ions indicative of the precursor ion isomer components, and subsequent IMS analysis of b ion isomers provided their quantitative and structural information. The isomer components of three representative b ions (b9, b10, and b33 from three different peptides) were accurately profiled by this method. IMS analysis of the b9 ion isomers exhibited dynamic conversion among these structures. Furthermore, molecular dynamics simulation predicted theoretical drift time values, which were in good agreement with experimentally measured values. Our results strongly support the mechanism of peptide sequence scrambling via b ion cyclization, and provide the first experimental evidence to support that the conversion from molecular precursor ion to cyclic b ion (M → (c)b) pathway is less energetically (or kinetically) favored.

Inclusion of multiple fragment types in the site identification by ligand competitive saturation (SILCS) approach

The site identification by ligand competitive saturation (SILCS) method identifies the location and approximate affinities of small molecular fragments on a target macromolecular surface by performing molecular dynamics (MD) simulations of the target in an aqueous solution of small molecules representative of different chemical functional groups. In this study, we introduce a set of small molecules to map potential interactions made by neutral hydrogen bond donors and acceptors and charged donor and acceptor fragments in addition to nonpolar fragments. The affinity pattern is obtained in the form of discretized probability or, equivalently, free energy maps, called FragMaps, which can be visualized with the target surface. We performed SILCS simulations for four proteins for which structural and thermodynamic data is available for multiple diverse ligands. Good overlap is shown between high affinity regions identified by the FragMaps and the crystallographic positions of ligand functional groups with similar chemical functionality, thus demonstrating the validity of the qualitative information obtained from the simulations. To test the ability of FragMaps in providing quantitative predictions, we calculate the previously introduced ligand grid free energy (LGFE) metric and observe its correspondence with experimentally measured binding affinity. LGFE is computed for different conformational ensembles and improvement in prediction is shown with increasing ligand conformational sampling. Ensemble generation includes a Monte Carlo sampling approach that uses the GFE FragMaps directly as the energy function. The results show that some but not all experimental trends are predicted and warrant improvements in the scoring methodology. In addition, the potential utility of atom-based free energy contributions to the LGFE scores and the use of multiple ligands in SILCS to identify displaceable water molecules during ligand design are discussed.

Turning defense into offense: defensin mimetics as novel antibiotics targeting lipid II

We have previously reported on the functional interaction of Lipid II with human alpha-defensins, a class of antimicrobial peptides. Lipid II is an essential precursor for bacterial cell wall biosynthesis and an ideal and validated target for natural antibiotic compounds. Using a combination of structural, functional and in silico analyses, we present here the molecular basis for defensin-Lipid II binding. Based on the complex of Lipid II with Human Neutrophil peptide-1, we could identify and characterize chemically diverse low-molecular weight compounds that mimic the interactions between HNP-1 and Lipid II. Lead compound BAS00127538 was further characterized structurally and functionally; it specifically interacts with the N-acetyl muramic acid moiety and isoprenyl tail of Lipid II, targets cell wall synthesis and was protective in an in vivo model for sepsis. For the first time, we have identified and characterized low molecular weight synthetic compounds that target Lipid II with high specificity and affinity. Optimization of these compounds may allow for their development as novel, next generation therapeutic agents for the treatment of Gram-positive pathogenic infections.

Every year, an increasing number of people are at risk for bacterial infections that cannot be effectively treated. This is because many bacteria are becoming more resistant to antibiotics. Of particular concern is the rise in hospital-acquired infections. Infection caused by the methicillin-resistant Staphylococcus aureus bacterium or MRSA is the cause of many fatalities and puts a burden on health care systems in many countries. The antibiotic of choice for treatment of S. aureus infections is vancomycin, an antimicrobial peptide that kills bacteria by binding to the bacterial cell wall component Lipid II. Here, we have identified for the first time, small synthetic compounds that also bind Lipid II with the aim to develop new antibiotic drugs to fight against bacterial infections.

Effect of magnesium on calcium and oxalate ion binding

BACKGROUND AND PURPOSE

Magnesium (Mg(2+)) has been shown to be a kidney stone inhibitor; however, the exact mechanism of its effect is unknown. Using theoretical models, the interactions of calcium and oxalate were examined in the presence of Mg(2+).

METHODS

Molecular dynamics simulations were performed with NAMD and CHARMM27 force field. The interaction between calcium (Ca(2+)) and oxalate (Ox(2-)) ions was examined with and without magnesium. Concentrations of calcium and oxalate were 0.1 M and 0.03 M, respectively, and placed in a cubic box of length ~115 Angstrom. Na(+) and Cl(-) ions were inserted to meet system electroneutrality. Mg(2+) was then placed into the box at physiologic concentrations and the interaction between calcium and oxalate was observed. In addition, the effect of citrate and pH were examined in regard to the effect of Mg(2+) inhibition. Each system was allowed to run until a stable crystalline structure was formed.

RESULTS

The presence of Mg(2+) reduces the average size of the calcium oxalate and calcium phosphate aggregates. This effect is found to be Mg(2+) concentration-dependent. It is also found that Mg(2+) inhibition is synergistic with citrate and continues to be effective at acidic pH levels.

CONCLUSION

The presence of magnesium ions tends to destabilize calcium oxalate ion pairs and reduce the size of their aggregates. Mg(2+) inhibitory effect is synergistic with citrate and remains effective in acidic environments. Further studies are needed to see if this can be applied to in vivo models as well as extending this to other stone inhibitors and promoters.

Molecular dynamics simulations of DNA-free and DNA-bound TAL effectors

TAL (transcriptional activator-like) effectors (TALEs) are DNA-binding proteins, containing a modular central domain that recognizes specific DNA sequences. Recently, the crystallographic studies of TALEs revealed the structure of DNA-recognition domain. In this article, molecular dynamics (MD) simulations are employed to study two crystal structures of an 11.5-repeat TALE, in the presence and absence of DNA, respectively. The simulated results indicate that the specific binding of RVDs (repeat-variable diresidues) with DNA leads to the markedly reduced fluctuations of tandem repeats, especially at the two ends. In the DNA-bound TALE system, the base-specific interaction is formed mainly by the residue at position 13 within a TAL repeat. Tandem repeats with weak RVDs are unfavorable for the TALE-DNA binding. These observations are consistent with experimental studies. By using principal component analysis (PCA), the dominant motions are open-close movements between the two ends of the superhelical structure in both DNA-free and DNA-bound TALE systems. The open-close movements are found to be critical for the recognition and binding of TALE-DNA based on the analysis of free energy landscape (FEL). The conformational analysis of DNA indicates that the 5′ end of DNA target sequence has more remarkable structural deformability than the other sites. Meanwhile, the conformational change of DNA is likely associated with the specific interaction of TALE-DNA. We further suggest that the arrangement of N-terminal repeats with strong RVDs may help in the design of efficient TALEs. This study provides some new insights into the understanding of the TALE-DNA recognition mechanism.

S-adenosyl-homocysteine is a weakly bound inhibitor for a flaviviral methyltransferase

The methyltransferase enzyme (MTase), which catalyzes the transfer of a methyl group from S-adenosyl-methionine (AdoMet) to viral RNA, and generates S-adenosyl-homocysteine (AdoHcy) as a by-product, is essential for the life cycle of many significant human pathogen flaviviruses. Here we investigated inhibition of the flavivirus MTase by several AdoHcy-derivatives. Unexpectedly we found that AdoHcy itself barely inhibits the flavivirus MTase activities, even at high concentrations. AdoHcy was also shown to not inhibit virus growth in cell-culture. Binding studies confirmed that AdoHcy has a much lower binding affinity for the MTase than either the AdoMet co-factor, or the natural AdoMet analog inhibitor sinefungin (SIN). While AdoMet is a positively charged molecule, SIN is similar to AdoHcy in being uncharged, and only has an additional amine group that can make extra electrostatic contacts with the MTase. Molecular Mechanics Poisson-Boltzmann Sovation Area analysis on AdoHcy and SIN binding to the MTase suggests that the stronger binding of SIN may not be directly due to interactions of this amine group, but due to distributed differences in SIN binding resulting from its presence. The results suggest that better MTase inhibitors could be designed by using SIN as a scaffold rather than AdoHcy.

Optimized CGenFF force-field parameters for acylphosphate and N-phosphonosulfonimidoyl functional groups

We report an optimized set of CGenFF parameters that can be used to model small molecules containing acylphosphate and N-phosphonosulfonimidoyl functional groups in combination with the CHARMM force field. Standard CGenFF procedures were followed to obtain bonded interaction parameters, which were validated by geometry optimizations, comparison to the results of calculations at the MP2/6-31+G(d) level of theory, and molecular dynamics simulations. In addition, partial atomic charges were assigned so that the energy of hydrogen bonding of the model compounds with water was correctly reproduced. The availability of these parameters will facilitate computational studies of enzymes that generate acyladenylate intermediates during catalytic turnover. In addition, given that the N-phosphonosulfonimidoyl moiety is a stable transition state analog for the reaction of ammonia with an acyladenylate, the parameters developed in this study should find use in efforts to develop novel and potent inhibitors of various glutamine-dependent amidotransferases that have been validated as drug targets. Topology and parameter files for the model compounds used in this study, which can be combined with other CGenFF parameters in computational studies of more complicated acylphosphates and N-phosphonosulfonimidates are made available.

The molecular mechanism of ion-dependent gating in secondary transporters

LeuT-like fold Na-dependent secondary active transporters form a large family of integral membrane proteins that transport various substrates against their concentration gradient across lipid membranes, using the free energy stored in the downhill concentration gradient of sodium ions. These transporters play an active role in synaptic transmission, the delivery of key nutrients, and the maintenance of osmotic pressure inside the cell. It is generally believed that binding of an ion and/or a substrate drives the conformational dynamics of the transporter. However, the exact mechanism for converting ion binding into useful work has yet to be established. Using a multi-dimensional path sampling (string-method) followed by all-atom free energy simulations, we established the principal thermodynamic and kinetic components governing the ion-dependent conformational dynamics of a LeuT-like fold transporter, the sodium/benzyl-hydantoin symporter Mhp1, for an entire conformational cycle. We found that inward-facing and outward-facing states of Mhp1 display nearly the same free energies with an ion absent from the Na2 site conserved across the LeuT-like fold transporters. The barrier separating an apo-state from inward-facing or outward-facing states of the transporter is very low, suggesting stochastic gating in the absence of ion/substrate bound. In contrast, the binding of a Na2 ion shifts the free energy stabilizing the outward-facing state and promoting substrate binding. Our results indicate that ion binding to the Na2 site may also play a key role in the intracellular thin gate dynamics modulation by altering its interactions with the transmembrane helix 5 (TM5). The Potential of Mean Force (PMF) computations for a substrate entrance displays two energy minima that correspond to the locations of the main binding site S1 and proposed allosteric S2 binding site. However, it was found that substrate's binds to the site S1 ∼5 kcal/mol more favorable than that to the site S2 for all studied bound combinations of ions and a substrate.

Synthesis, modeling, and pharmacological evaluation of UMB 425, a mixed μ agonist/δ antagonist opioid analgesic with reduced tolerance liabilities

Opioid narcotics are used for the treatment of moderate-to-severe pain and primarily exert their analgesic effects through μ receptors. Although traditional μ agonists can cause undesired side effects, including tolerance, addition of δ antagonists can attenuate said side effects. Herein, we report 4a,9-dihydroxy-7a-(hydroxymethyl)-3-methyl-2,3,4,4a,5,6-hexahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7(7aH)-one (UMB 425) a 5,14-bridged morphinan-based orvinol precursor synthesized from thebaine. Although UMB 425 lacks δ-specific motifs, conformationally sampled pharmacophore models for μ and δ receptors predict it to have efficacy similar to morphine at μ receptors and similar to naltrexone at δ receptors, due to the compound sampling conformations in which the hydroxyl moiety interacts with the receptors similar to orvinols. As predicted, UMB 425 exhibits a mixed μ agonist/δ antagonist profile as determined in receptor binding and [(35)S]GTPγS functional assays in CHO cells. In vivo studies in mice show that UMB 425 displays potent antinociception in the hot plate and tail-flick assays. The antinociceptive effects of UMB 425 are blocked by naloxone, but not by the κ-selective antagonist norbinaltorphimine. During a 6-day tolerance paradigm, UMB 425 maintains significantly greater antinociception compared to morphine. These studies thus indicate that, even in the absence of δ-specific motifs fused to the C-ring, UMB 425 has mixed μ agonist/δ antagonist properties in vitro that translate to reduced tolerance liabilities in vivo.

A gating mechanism of pentameric ligand-gated ion channels

Pentameric ligand-gated ion channels (pLGICs) play a central role in intercellular communication in the nervous system and are involved in fundamental processes such as attention, learning, and memory. They are oligomeric protein assemblies that convert a chemical signal into an ion flux through the postsynaptic membrane, but the molecular mechanism of gating ions has remained elusive. Here, we present atomistic molecular dynamics simulations of the prokaryotic channels from Gloeobacter violaceus (GLIC) and Erwinia chrysanthemi (ELIC), whose crystal structures are thought to represent the active and the resting states of pLGICs, respectively, and of the eukaryotic glutamate-gated chloride channel from Caenorhabditis elegans (GluCl), whose open-channel structure was determined complexed with the positive allosteric modulator ivermectin. Structural observables extracted from the trajectories of GLIC and ELIC are used as progress variables to analyze the time evolution of GluCl, which was simulated in the absence of ivermectin starting from the structure with bound ivermectin. The trajectory of GluCl with ivermectin removed shows a sequence of structural events that couple agonist unbinding from the extracellular domain to ion-pore closing in the transmembrane domain. Based on these results, we propose a structural mechanism for the allosteric communication leading to deactivation/activation of the GluCl channel. This model of gating emphasizes the coupling between the quaternary twisting and the opening/closing of the ion pore and is likely to apply to other members of the pLGIC family.

Rapid parameterization of small molecules using the Force Field Toolkit

The inability to rapidly generate accurate and robust parameters for novel chemical matter continues to severely limit the application of molecular dynamics simulations to many biological systems of interest, especially in fields such as drug discovery. Although the release of generalized versions of common classical force fields, for example, General Amber Force Field and CHARMM General Force Field, have posited guidelines for parameterization of small molecules, many technical challenges remain that have hampered their wide-scale extension. The Force Field Toolkit (ffTK), described herein, minimizes common barriers to ligand parameterization through algorithm and method development, automation of tedious and error-prone tasks, and graphical user interface design. Distributed as a VMD plugin, ffTK facilitates the traversal of a clear and organized workflow resulting in a complete set of CHARMM-compatible parameters. A variety of tools are provided to generate quantum mechanical target data, setup multidimensional optimization routines, and analyze parameter performance. Parameters developed for a small test set of molecules using ffTK were comparable to existing CGenFF parameters in their ability to reproduce experimentally measured values for pure-solvent properties (<15% error from experiment) and free energy of solvation (±0.5 kcal/mol from experiment).

A comparative Kirkwood-Buff study of aqueous methanol solutions modeled by the CHARMM additive and Drude polarizable force fields

A comparative study on aqueous methanol solutions modeled by the CHARMM additive and Drude polarizable force fields was carried out by employing Kirkwood-Buff analysis. It was shown that both models reproduced the experimental Kirkwood-Buff integrals and excess coordination numbers adequately well over the entire concentration range. The Drude model showed significant improvement over the additive model in solution densities, partial molar volumes, excess molar volumes, concentration-dependent diffusion constants, and dielectric constants. However, the additive model performed somewhat better than the Drude model in reproducing the activity derivative, excess molar Gibbs energy, and excess molar enthalpy of mixing. This is due to the additive achieving a better balance among solute-solute, solute-solvent, and solvent-solvent interactions, indicating the potential for improvements in the Drude polarizable alcohol model.

Kirkwood-Buff analysis of aqueous N-methylacetamide and acetamide solutions modeled by the CHARMM additive and Drude polarizable force fields

Kirkwood-Buff analysis was performed on aqueous solutions of N-methylacetamide and acetamide using the Chemistry at HARvard Molecular Mechanics additive and Drude polarizable all-atom force fields. Comparison of a range of properties with experimental results, including Kirkwood-Buff integrals, excess coordination numbers, solution densities, partial molar values, molar enthalpy of mixing, showed both models to be well behaved at higher solute concentrations with the Drude model showing systematic improvement at lower solution concentrations. However, both models showed difficulties reproducing experimental activity derivatives and the excess Gibbs energy, with the Drude model performing slightly better. At the molecular level, the improved agreement of the Drude model at low solute concentrations is due to increased structure in the solute-solute and solute-solvent interactions. The present results indicate that the explicit inclusion of electronic polarization leads to improved modeling of dilute solutions even when those properties are not included as target data during force field optimization.