Molecular details of μ opioid receptor activations were obtained using molecular dynamics simulations of the receptor in the presence of 3 agonists, 3 antagonists, a partial agonist and on the constitutively active T279K mutant. Agonists have a higher probability of direct interactions of their basic nitrogen (N) with Asp147 as compared to antagonists, indicating that direct ligand-Asp147 interactions modulate activation. Medium size substituents on the basic N of antagonists lead to steric interactions that perturb N-Asp147 interactions, while additional favorable interactions occur with larger basic N substituents, such as in N-phenethylnormorphine, restoring N-Asp147 interactions, leading to agonism. With the orvinols, the increased size of the C19 substituent in buprenorphine over diprenorphine leads increased interactions with residues adjacent to Asp147, partially overcoming the presence of the cyclopropyl N substituent, such that buprenorphine is a partial agonist. Results also indicate different conformational properties of the intracellular regions of the transmembrane helices in agonists versus antagonists.
Structure-activity relationship; molecular dynamics; binding orientations; agonists and antagonists
The structure of the O-methyl glycoside of the naturally
C10H18O8, has been determined by X-ray
crystallography at 100 K, supplementing the previously determined structure
obtained at 293 K (Acta Cryst., 1996, C52, 2285-2287). Molecular dynamics
simulations of this glycoside were performed in the crystal environment with
different numbers of units cells included in the primary simulation system at
both 100 K and 293 K. The calculated unit cell parameters and the
intra-molecular geometries (bonds, angles, and dihedrals) agree well with
experimental results. Atomic fluctuations, including B-factors and anisotropies,
are in good agreement with respect to the relative values on an atom-by-atom
basis. In addition, the fluctuations increase with increasing simulation system
size, with the simulated values converging to values lower than those observed
experimentally indicating that the simulation model is not accounting for all
possible contributions to the experimentally observed B-factors which may be
related to either the simulation time scale or size. In the simulations the
hydroxyl group of O7 is found to form bifurcated hydrogen bonds with O6 and O8
of an adjacent molecule, with the interactions dominated by the HO7-O6
interaction. Quantum mechanical calculations support this observation.
CHARMM force field; carbohydrates; molecular dynamics simulation; molecular modeling; monosaccharides
Group 1 metabotropic glutamate receptors (mGluR) are G-protein coupled receptors with a large bilobate extracellular ligand binding region (LBR) that resembles a Venus fly trap. Closing of this LBR in the presence of a ligand is associated with the activation of the receptor. From conformational sampling of the LBR-ligand complexes using all-atom molecular dynamics (MD) simulations, we characterized the conformational minima related to the hinge like motion associated with the LBR closing/opening in the presence of known agonists and antagonists. By applying a harmonic restraint on the LBR, we also determined the conformational forces generated by the different ligands. The change in the location of the minima and the conformational forces were used to quantify the efficacies of the ligands. This analysis shows that efficacies can be estimated from the forces of a single conformation of the receptor, indicating the potential of MD simulations as an efficient and useful technique to quantify efficacies thereby facilitating the rational design of mGluR agonists and antagonists.
metabotropic glutamate receptors; conformational sampling; molecular dynamics; conformational force; efficacy
2-Acetylaminofluorene (AAF) is a prototype arylamine carcinogen that forms C8-substituted dG-AAF and dG-AF as the major DNA lesions. The bulky N-acetylated dG-AAF lesion can induce various frameshift mutations depending on the base sequence around the lesion. We hypothesized that the thermodynamic stability of bulged-out slipped mutagenic intermediates (SMIs) is directly related to deletion mutations. The objective of the present study was to probe the structural/conformational basis of various dG-AAF–induced SMIs formed during a translesion synthesis. We performed spectroscopic, thermodynamic, and molecular dynamics studies of several AAF-modified 16-mer model DNA duplexes, including fully paired and −1, −2, and −3 deletion duplexes of the 5′-CTCTCGATG[FAAF]CCATCAC-3′ sequence and an additional −1 deletion duplex of the 5′-CTCTCGGCG[FAAF]CCATCAC-3′ NarI sequence. Modified deletion duplexes existed in a mixture of external B and stacked S conformers, with the population of the S conformer being ‘GC’ −1 (73%) > ‘AT’ −1 (72%) > full (60%) > −2 (55%) > −3 (37%). Thermodynamic stability was in the order of −1 deletion > −2 deletion > fully paired > −3 deletion duplexes. These results indicate that the stacked S-type conformer of SMIs are thermodynamically more stable than the conformationally flexible external B conformer. Results from the molecular dynamics simulations indicate perturbation of base stacking dominate the relative stability along with contributions from bending, duplex dynamics, solvation effects that are important in specific cases. Taken together, these results support a hypothesis that the conformational and thermodynamic stabilities of the SMIs are critical determinants for the induction of frameshift mutations.
Towards the development of potent and selective inhibitors of melanoma cells containing active ERK signaling, we herein report on the pharmacophore determination and optimization of the ERK docking domain inhibitor (Z)-3-(2-aminoethyl)-5-(4-ethoxybenzylidene)thiazolidine-2,4-dione.
The antiproliferative factor (APF) involved in interstitial cystitis is a glycosylated nonapeptide (TVPAAVVVA) containing a sialylated core α-O-disaccharide linked to the N-terminal threonine. The chemical structure of APF was deduced using spectroscopic techniques and confirmed using total synthesis. The synthetic APF provided a platform to study amino acid modifications and their effect on APF activity, based on which a structure-activity relationship (SAR) for APF activity was previously proposed. However, this SAR model could not explain the change in activity associated with minor alterations in the peptide sequence. Presented is computational analysis of 14 APF derivatives to identify structural trends from which a more detailed SAR is obtained. The APF activity is found to be dictated by the close interplay between carbohydrate-peptide and peptide-peptide interactions. The former involves hydrogen bond and hydrophobic interactions and the latter is dominated by hydrophobic interactions. The highly flexible hydrophobic peptide adopts collapsed conformations separated by low energy barriers. APF activity correlates with hydrophobic clustering associated with amino acids 4A, 6V and 8V. Peptide conformations are highly sensitive to single point mutations, which explain the experimental trends. The presented SAR will act as a guide for lead optimization of more potent APF analogues of potential therapeutic utility.
The in-silico Site Identification by Ligand Competitive Saturation (SILCS) approach identifies the binding sites of representative chemical entities on the entire protein surface, information that can be applied for computational fragment-based drug design. In this study, we report an efficient computational protocol that uses sampling of the protein-fragment conformational space obtained from the SILCS simulations and performs single step free energy perturbation (SSFEP) calculations to identify site-specific favorable chemical modifications of benzene involving substitutions of ring hydrogens with individual non-hydrogen atoms. The SSFEP method is able to capture the experimental trends in relative hydration free energies of benzene analogues and for two datasets of experimental relative binding free energies of congeneric series of ligands of the proteins α-thrombin and P38 MAP kinase. The approach includes a protocol in which data obtained from SILCS simulations of the proteins is first analyzed to identify favorable benzene binding sites following which an ensemble of benzene-protein conformations for that site is obtained. The SSFEP protocol applied to that ensemble results in good reproduction of experimental free energies of the α-thrombin ligands, but not for P38 MAP kinase ligands. Comparison with results from a P38 full-ligand simulation and analysis of conformations reveals the reason for the poor agreement being the connectivity with the remainder of the ligand, a limitation inherent in fragment-based methods. Since the SSFEP approach can identify favorable benzene modifications as well as identify the most favorable fragment conformations, the obtained information can be of value for fragment linking or structure-based optimization.
Amino acid side-chain fluctuations play an essential role in the structure and function of proteins. Accordingly, in theoretical studies of proteins it is important to have an accurate description of their conformational properties. Recently, new side-chain torsion parameters were introduced into the CHARMM and Amber additive force fields and evaluated based on the conformational properties of the individual side-chains using protein simulations in explicit solvent. While effective for validation, MD simulations of proteins must be extended into the microsecond regime to obtain full convergence of the side-chain conformations, limiting their use for force field optimization. To address this, we systematically test the utility of explicit solvent simulations of (Ala)4-X-(Ala)4 peptides, where X represents the amino acids, as model systems for the optimization of χ1 and χ2 side-chain parameters. The effect of (Ala)4-X-(Ala)4 backbone conformation was tested by constraining the backbone in the α-helical, C5, C7eq and PPII conformations and performing exhaustive sampling using Hamiltonian replica exchange simulations. Rotamer distributions from protein and the (Ala)4-X-(Ala)4 simulations showed the highest correlation for the C7eq and PPII conformations, though agreement was best for the α-helical conformation for Asn. Hydrogen bond analysis indicate the utility of the C7eq and PPII conformations to be due to specific side-chain-backbone hydrogen bonds not being oversampled, thereby allowing sampling of a range of side-chain conformations consistent with the distributions occurring in full proteins. It is anticipated that the (Ala)4-X-(Ala)4 model system will allow for iterative force field optimization targeting condensed phase conformational distributions of side-chains.
Bacteria require iron for survival and virulence and employ several mechanisms including utilization of the host heme containing proteins. The final step in releasing iron is the oxidative cleavage of heme by HemO. A recent computer aided drug design (CADD) study identified several inhibitors of the bacterial HemOs. Herein we report the near complete HN, N, CO Cα and Cβ chemical shift assignment of the P. aeruginosa HemO in the absence and presence of inhibitors (E)-3-(4-(Phenylamino)phenylcarbamoyl) acrylic acid (3) and (E)-N’-(4-(dimethylamino)benzylidene) diazenecarboximidhydrazide (5). The NMR data confirms the inhibitors bind within the heme pocket of HemO consistent with in silico molecular dynamic simulations. Both inhibitors and the phenoxy derivative of 3 have activity against P. aeruginosa clinical isolates. Furthermore 5 showed antimicrobial activity in the in vivo C. elegans curing assay. Thus targeting virulence mechanisms required within the host is a viable antimicrobial strategy for the development of novel antivirulants.
Human arginase is a binuclear manganese metalloenzyme that participates in the urea cycle. Arginase catalyses the hydrolysis of L-arginine into L-ornithine and urea and is linked to several disorders such as asthma and cancer. Currently, the protonation and tautomerization state of the substrate when bound to the active site, which contains two manganese ions, is not known. Knowledge of the charge dependent behavior of arginine in the arginase I environment would be of utility towards understanding the catalytic mechanism and designing inhibitors of this enzyme. The arginine+/0 species, including all possible neutral tautomers, were modeled using an aminoimidazole analog as template. All-atom molecular dynamics simulations were then performed on each of the charged and neutral species. In addition, a hydroxide ion was included in selected simulations to test its importance. Results show that the positively charged state of arginine is stable in the active site of arginase I, with that stabilization facilitated by the presence of hydroxide. Glu277 is indicated to play a role in stabilizing arginine in the active site and facilitating its ability to assume a catalytically competent conformation in the presence of hydroxide. The reported interactions and modeled arginine bound arginase I structures can be used as a tool for structure based inhibitor design as experimental data on the structure of the substrate-enzyme complex is lacking.
manganese; arginine; Molecular Dynamics; molecular modeling; CHARMM; hydroxide ion
Base stacking is known to make an important contribution to the stability of DNA and RNA and, accordingly, significant efforts are ongoing to calculate stacking energies using ab initio quantum mechanical methods. To date, impressive improvements have been made in the model chemistries used to perform stacking energy calculations, including extensions that include robust treatments of electron correlation with extended basis sets, as required to treat interactions where dispersion makes a significant contribution. However, those efforts typically use rigid monomer geometries when calculating the interaction energies. To overcome this, in the present work we describe a novel internal coordinate definition that allows the relative, intermolecular orientation of stacked base monomers to be constrained during geometry optimizations while allowing full optimization of the intramolecular degrees of freedom. Use of the novel reference frame to calculate the impact of full geometry optimization versus constraining the bases to be planar on base monomer stacking energies, combined with density-fitted, spin-component scaling MP2 treatment of electron correlation, shows that full optimization makes the average stacking energy more favorable by −3.4 and −1.5 kcal/mol for the canonical A and B conformations of the 16 5’ to 3’ base stacked monomers. Thus, treatment of geometry optimization impacts the stacking energies to an extent similar to or greater than the impact of current state of the art increases in the rigor of the model chemistry itself used to treat base stacking. Results also indicate that stacking favors the B form of DNA, though the average difference versus the A form decreases from −2.6 to −0.6 kcal/mol when the intramolecular geometry is allowed to fully relax. However, stacking involving cytosine is shown to favor the A form of DNA, with that contribution generally larger in the fully optimized bases. The present results show the importance of allowing geometry optimization, as well as properly treating the appropriate model chemistry, in studies of nucleic acid base stacking.
MP2; density-fitting; resolution of identity; oligonucleotide; base stacking
Cluster DNA damage refers to two or more lesions in a single turn of the DNA helix. Such clustering may occur with bulky DNA lesions, which may be responsible for their sequence dependent repair and mutational outcomes. Here we prepared three 16-mer cluster duplexes in which two fluoroacetylaminofluorene adducts (dG-FAAF) are separated by none, one and two nucleotides in the E. coli NarI mutational hot spot (5'-CTCTCG1G2CG3CCATCAC-3'): i.e. 5'-- CG1*G2*CG3CC--3', 5'--CG1G2*CG3*CC--3', and 5'--CG1*G2CG3*CC--3' [G*=dG-FAAF], respectively. We conducted spectroscopic, thermodynamic, and molecular dynamics studies of these di-FAAF duplexes and the results were compared with those of the corresponding mono- FAAF adducts in the same NarI sequence (Nucleic Acids Res. 2012, 3939–3951). Our nucleotide excision repair results showed greater reparability of the di-adducts in comparison to the corresponding mono-adducts. Moreover, we observed dramatic flanking base sequence effects on their repair efficiency in the order of NarI-G2G3 > -G1G3 > -G1G2. The NMR/CD/UV-melting and MD-simulation results revealed that in contrast to the mono-adducts, di-adducts produced synergistic effect on duplex destabilization. In addition, dG-FAAF at G2G3 and G1G3 destack the neighboring bases with greater destabilization occurring with the former. Overall, the results indicate the importance of base stacking and related thermal/thermodynamic destabilization in the repair of bulky cluster arylamine DNA adducts.
Amino acid side chain conformational properties influence the overall structural and dynamic properties of proteins and, therefore, their biological functions. In this study, quantum mechanical (QM) potential energy surfaces for the rotation of side chain χ1 and χ2 torsions in dipeptides in the alphaR, beta and alphaL backbone conformations were calculated. The QM energy surfaces provide a broad view of the intrinsic conformational properties of each amino acid side chain. The extent to which intrinsic energetics dictates side-chain orientation was studied through comparisons of the QM energy surfaces with χ1 and χ2 free energy surfaces from probability distributions obtained from a survey of high resolution crystal structures. In general, the survey probability maxima are centered in minima in the QM surfaces as expected for sp3 (or sp2 for χ2 of Asn, Phe, Trp, and Tyr) atom centers with strong variations between amino acids occurring in the energies of the minima indicating intrinsic differences in rotamer preferences. High correlations between the QM and survey data were found for hydrophobic side chains except Met, suggesting minimal influence of the protein and solution environments on their conformational distributions. Conversely, low correlations for polar or charged side-chains indicate a dominant role of the environment in stabilizing conformations that are not intrinsically favored. Data also link the presence of off-rotamers in His and Trp to favorable interactions with the backbone. Results also suggest that the intrinsic energetics of the side-chains of Phe and Tyr may play important roles in protein folding and stability. Analyses on whether intrinsic side chain energetics can influence backbone preference identified a strong correlation for residues in the AlphaL backbone conformation. It is suggested that this correlation reflects the intrinsic instability of the AlphaL backbone such that assumption of this backbone conformation is facilitated by intrinsically favorable side-chain conformations. Together our results offer a broad overview of the conformational properties of amino acid side-chains and the QM data may be used as target data for force field optimization.
The accuracy of the empirical force fields is critical for meaningful molecular dynamics simulations of concentrated ionic solutions. Current models are typically developed on the basis of single ion properties such as the monohydrate energy in the gas phase, or the absolute hydration free energy at infinite dilution. However, failure of these models to accurately represent the properties of concentrated solutions cannot be excluded. Here, these issues are illustrated for a polarizable potential based on classical Drude oscillators. To accurately model concentrated ionic solutions, the parameters of the potential functions are optimized to reproduce osmotic pressure data. The sodium-chloride potential of mean force in solution calculated from the empirically-adjusted model is consistent with the results from that calculated from ab initio CPMD simulations.
Osmotic pressure; Drude; force field; ions; sodium-chloride; molecular dynamics
Molecular Dynamics simulations of the pentamidine-S100B complex, where two molecules of pentamidine bind per monomer of S100B, were performed in an effort to determine what properties would be desirable in a pentamidine-derived compound as an inhibitor for S100B. These simulations predicted that increasing the linker length of the compound would allow a single molecule to span both pentamidine binding sites on the protein. The resulting compound, SBi4211 (also known as heptamidine), was synthesized and experiments to study its inhibition of S100B were performed. The 1.65 Å X-ray crystal structure was determined for Ca2+-S100B-heptamdine and gives high-resolution information about key contacts that facilitate the interaction between heptamidine and S100B. Additionally, NMR HSQC experiments with both compounds show that heptamidine interacts with the same region of S100B as pentamidine. Heptamidine is able to selectively kill melanoma cells with S100B over those without S100B, indicating that its binding to S100B has an inhibitory effect and that this compound may be useful in designing higher-affinity S100B inhibitors as a treatment for melanoma and other S100B-related cancers.
Molecular dynamics simulations of the pentamidine–S100B
complex, where two molecules of pentamidine bind per monomer of S100B,
were performed in an effort to determine what properties would be
desirable in a pentamidine-derived compound as an inhibitor for S100B.
These simulations predicted that increasing the linker length of the
compound would allow a single molecule to span both pentamidine binding
sites on the protein. The resulting compound, SBi4211 (also known
as heptamidine), was synthesized, and experiments to study its inhibition
of S100B were performed. The 1.65 Å X-ray crystal structure was
determined for Ca2+–S100B–heptamdine and
gives high-resolution information about key contacts that facilitate
the interaction between heptamidine and S100B. Additionally, NMR HSQC
experiments with both compounds show that heptamidine interacts with
the same region of S100B as pentamidine. Heptamidine is able to selectively
kill melanoma cells with S100B over those without S100B, indicating
that its binding to S100B has an inhibitory effect and that this compound
may be useful in designing higher affinity S100B inhibitors as a treatment
for melanoma and other S100B-related cancers.
structure-based discovery; pentamidine-related inhibitor; calcium-binding protein S100B
There is an urgent need for novel sources of antibiotics
the incessant and inevitable onset of bacterial resistance. To this
end, we have initiated a structure-based drug design program that
features a desmethylation strategy (i.e., replacing methyl groups
with hydrogens). Herein, we report the total synthesis, molecular
modeling, and biological evaluation of 4,8-didesmethyl telithromycin
(5), a novel desmethyl analogue of the third-generation
ketolide antibiotic telithromycin (2), which is an FDA-approved
semisynthetic derivative of erythromycin (1). We found 5 to be eight times more active than previously prepared 4,8,10-tridesmethyl
congener (3) and two times more active than 4,10-didesmethyl
regioisomer (4) in MIC assays. While less potent than
telithromycin (2) and paralleling the observations made
in the previous study of 4,10-didesmethyl analogue (4), the inclusion of a single methyl group improves biological activity,
thus supporting its role in antibiotic activity.
total synthesis; ketolide antibiotics; antibiotic
resistance; telithromycin; molecular modeling; desmethyl analogues
There is an urgent need for novel sources of antibiotics to address the incessant and inevitable onset of bacterial resistance. To this end, we have initiated a structure-based drug design program that features a desmethylation strategy (i.e., replacing methyl groups with hydrogens). Herein we report the total synthesis, molecular modeling and biological evaluation of 4,8-didesmethyl telithromycin (5), a novel desmethyl analogue of the third-generation ketolide antibiotic telithromycin (2), which is an FDA-approved semisynthetic derivative of erythromycin (1). We found 4,8-didesmethyl telithromycin (5) to be eight times more active than previously prepared 4,8,10-tridesmethyl congener (3) and two times more active than 4,10-didesmethyl regioisomer (4) in MIC assays. While less potent than telithromycin (2) and paralleling the observations made in the previous study of 4,10-didesmethyl analogue (4), the inclusion of a single methyl group improves biological activity thus supporting its role in antibiotic activity.
total synthesis; ketolide antibiotics; antibiotic resistance; telithromycin; molecular modeling; desmethyl analogues
Presented is an extension of the CHARMM General force field (CGenFF) to enable the modeling of sulfonyl-containing compounds. Model compounds containing chemical moieties such as sulfone, sulfonamide, sulfonate and sulfamate were used as the basis for the parameter optimization. Targeting high-level quantum mechanical and experimental crystal data, the new parameters were optimized in a hierarchical fashion designed to maintain compatibility with the remainder of the CHARMM additive force field. The optimized parameters satisfactorily reproduced equilibrium geometries, vibrational frequencies, interactions with water, gas phase dipole moments and dihedral potential energy scans. Validation involved both crystalline and liquid phase calculations showing the newly developed parameters to satisfactorily reproduce experimental unit cell geometries, crystal intramolecular geometries and pure solvent densities. The force field was subsequently applied to study conformational preference of a sulfonamide based peptide system. Good agreement with experimental IR/NMR data further validated the newly developed CGenFF parameters as a tool to investigate the dynamic behavior of sulfonyl groups in a biological environment. CGenFF now covers sulfonyl group containing moieties allowing for modeling and simulation of sulfonyl-containing compounds in the context of biomolecular systems including compounds of medicinal interest.
empirical force field; molecular mechanics; molecular dynamics; molecular modeling; potential energy function; sulfonamide; β-strand mimetic; peptidomimetic; medicinal chemistry; drug design
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.
While the quality of the current CHARMM22/CMAP additive force field for proteins has been demonstrated in a large number of applications, limitations in the model with respect to the equilibrium between the sampling of helical and extended conformations in folding simulations have been noted. To overcome this, as well as make other improvements in the model, we present a combination of refinements that should result in enhanced accuracy in simulations of proteins. The common (non Gly, Pro) backbone CMAP potential has been refined against experimental solution NMR data for weakly structured peptides, resulting in a rebalancing of the energies of the α-helix and extended regions of the Ramachandran map, correcting the α-helical bias of CHARMM22/CMAP. The Gly and Pro CMAPs have been refitted to more accurate quantum-mechanical energy surfaces. Side-chain torsion parameters have been optimized by fitting to backbone-dependent quantum-mechanical energy surfaces, followed by additional empirical optimization targeting NMR scalar couplings for unfolded proteins. A comprehensive validation of the revised force field was then performed against data not used to guide parametrization: (i) comparison of simulations of eight proteins in their crystal environments with crystal structures; (ii) comparison with backbone scalar couplings for weakly structured peptides; (iii) comparison with NMR residual dipolar couplings and scalar couplings for both backbone and side-chains in folded proteins; (iv) equilibrium folding of mini-proteins. The results indicate that the revised CHARMM 36 parameters represent an improved model for the modeling and simulation studies of proteins, including studies of protein folding, assembly and functionally relevant conformational changes.
Molecular dynamics simulation; NMR spectroscopy; empirical energy function; protein folding
Accounting for target flexibility and selecting “hot spots” most likely to be able to bind an inhibitor continue to be challenges in the field of structure-based drug design, especially in the case of protein-protein interactions. Computational fragment-based approaches employing molecular dynamics (MD) simulations are a promising emerging technology having the potential to address both of these challenges. However, the optimal MD conditions permitting sufficient target flexibility while also avoiding fragment-induced target denaturation remain ambiguous. Using one such technology (SILCS: Site Identification by Ligand Competitive Saturation), conditions were identified to either prevent denaturation or identify and exclude trajectories in which subtle but important denaturation was occurring. The target system employed was the well-characterized protein cytokine IL-2, which is involved in a protein-protein interface and, in its un-liganded crystallographic form, lacks surface pockets that can serve as small-molecule binding sites. Nonetheless, small-molecule inhibitors have previously been discovered that bind to two “cryptic” binding sites that emerge only in the presence of ligand binding, highlighting the important role of IL-2 flexibility. Using the above conditions, SILCS with hydrophobic fragments was able to identify both sites based on favorable fragment binding while avoiding IL-2 denaturation. An important additional finding was that acetonitrile, a water-miscible fragment, fails to identify either site yet can induce target denaturation, highlighting the importance of fragment choice.
interleukin-2; immunosuppression; computer-aided drug design; lead optimization; molecular dynamics simulations; protein-protein interactions
A series of phenylpropyloxyethylamines and cinnamyloxyethylamines were synthesized as deconstructed analogs of 14-phenylpropyloxymetopon and analyzed for opioid receptor binding affinity. Using the Conformationally Sampled Pharmacophore modeling approach, we discovered a series of compounds lacking a tyrosine mimetic, historically considered essential for μ opioid binding. Based on the binding studies, we have identified the optimal analogs to be N-methyl-N-phenylpropyl-2-(3-phenylpropoxy)ethanamine, with 1520 nM, and 2-(cinnamyloxy)-N-methyl-N-phenethylethanamine with 1680 nM affinity for the μ opioid receptor. These partial opioid structure analogs will serve as the novel lead compounds for future optimization studies.
Opioid; Phenylpropyloxyethylamine; Conformationally Sampled Pharmacophore
The applicability of a computational method, Site Identification by Ligand Competitive Saturation (SILCS), to identify regions on a protein surface with which different types of functional groups on low-molecular weight inhibitors interact is demonstrated. The method involves molecular dynamics (MD) simulations of a protein in an aqueous solution of chemically diverse small molecules from which probability distributions of fragments types, termed FragMaps, are obtained. In the present application, SILCS simulations are performed with an aqueous solution of 1 M benzene and propane to map the affinity pattern of the protein for aromatic and aliphatic functional groups. In addition, water hydrogen and oxygen atoms serve as probes for hydrogen bond donor and acceptor affinity, respectively. The method is tested using a set of 7 proteins for which crystal structures of complexes with several high affinity inhibitors are known. Good agreement is obtained between FragMaps and the positions of chemically similar functional groups in inhibitors as observed in the X-ray crystallographic structures. Quantitative capabilities of the SILCS approach are demonstrated by converting FragMaps to free energies, termed Grid Free Energies (GFE), and showing correlation between the GFE values and experimental binding affinities. For proteins for which ligand decoy sets are available, GFE values are shown to typically score the crystal conformation and conformations similar to it more favorable than decoys. Additionally, SILCS is tested for its ability to capture the subtle differences in ligand affinity across homologous proteins, information which may be of utility towards specificity-guided drug design. Taken together, our results show that SILCS can recapitulate the known location of functional groups of bound inhibitors for a number of proteins, suggesting that the method may be of utility for rational drug design.
Resistance to macrolide antibiotics is conferred by mutation of A2058 to G or methylation by Erm methyltransferases of the exocyclic N6 of A2058 (E. coli numbering) that forms the macrolide binding site in the 50S subunit of the ribosome. Ketolides such as telithromycin mitigate A2058G resistance yet remain susceptible to Erm-based resistance. Molecular details associated with macrolide resistance due to the A2058G mutation and methylation at N6 of A2058 by Erm methyltransferases were investigated using empirical force field-based simulations. To address the buried nature of the macrolide binding site, the number of waters within the pocket was allowed to fluctuate via the use of a Grand Canonical Monte Carlo (GCMC) methodology. The GCMC water insertion/deletion steps were alternated with Molecular Dynamics (MD) simulations to allow for relaxation of the entire system. From this GCMC/MD approach information on the interactions between telithromycin and the 50S ribosome was obtained. In the wild-type (WT) ribosome, the 2′-OH to A2058 N1 hydrogen bond samples short distances with a higher probability, while the effectiveness of telithromycin against the A2058G mutation is explained by a rearrangement of the hydrogen bonding pattern of the 2′-OH to 2058 that maintains the overall antibiotic-ribosome interactions. In both the WT and A2058G mutation there is significant flexibility in telithromycin's imidazole-pyridine side chain (ARM), indicating that entropic effects contribute to the binding affinity. Methylated ribosomes show lower sampling of short 2′-OH to 2058 distances and also demonstrate enhanced G2057-A2058 stacking leading to disrupted A752-U2609 Watson-Crick (WC) interactions as well as hydrogen bonding between telithromycin's ARM and U2609. This information will be of utility in the rational design of novel macrolide analogs with improved activity against methylated A2058 ribosomes.
Bacterial resistance to antibiotics is a serious public health problem that requires the continuous development of new antibiotics. Bacteria acquire resistance to macrolide antibiotics by (1) effluxing the drug from the cell, (2) modifying the drug, or (3) modifying the drug target (i.e., the 50S subunit of the ribosome) to abrogate or completely abolish binding. While newer antibiotics are able to avoid the first two mechanisms, they remain unable to overcome resistance due to ribosomal modification, particularly due to methyltransferase (i.e., erm) enzymes. We have applied computer-aided drug design methods designed explicitly for studies of the ribosome to better understand the relationship between modification of the ribosome by erms and the binding of telithromycin, a 3rd generation ketolide antibiotic derived from erythromycin. While we confirm that ribosomal modification leads to decreased binding due to disruption of key interactions with the drug, we find these modifications effect a structural rearrangement of the entire region of the ribosome responsible for binding macrolide antibiotics. This information will be useful in the design of novel antibiotics that are effective against resistant bacteria possessing modified ribosomes.