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 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.
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
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.
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.
Presented is an extension of the CHARMM additive carbohydrate all-atom force field to enable modeling of polysaccharides containing furanose sugars. The new force field parameters encompass 1 ↔ 2, 1 → 3, 1 → 4 and 1 → 6 pyranose-furanose linkages and 2 → 1 and 2 → 6 furanose-furanose linkages, building on existing hexopyranose and furanose monosaccharide parameters. The model compounds were chosen to be monomers or glycosidic-linked dimers of tetrahydropyran (THP) and tetrahydrofuran (THF) as to contain the key atoms in full carbohydrates. Target data for optimization included two-dimensional quantum mechanical (QM) potential energy scans of the Φ/Ψ glycosidic dihedral angles, with geometry optimization at the MP2/6-31G(d) level followed by MP2/cc-pVTZ single point energies. All possible chiralities of the model compounds at the linkage carbons were considered, and, for each geometry, the THF ring was constrained to the favorable South or North conformation. Target data also included QM vibrational frequencies and pair interaction energies and distances with water molecules. Force field validation included comparison of computed crystal properties, aqueous solution densities and NMR J-coupling constants to experimental reference values. Simulations of infinite crystals showed good agreement with experimental values for intramolecular geometries as well as for crystal unit cell parameters. Additionally, aqueous solution densities and available NMR data were reproduced to a high degree of accuracy, thus validating the hierarchically optimized parameters in both crystalline and aqueous condensed phases. The newly developed parameters allow for the modeling of linear, branched, and cyclic pyranose/furanose polysaccharides both alone and in heterogeneous systems including proteins, nucleic acids and/or lipids when combined with existing additive CHARMM biomolecular force fields.
Novel sources of antibiotics are required to keep pace with the inevitable onset of bacterial resistance. Continuing with our macrolide desmethylation strategy as a source of new antibiotics, we report the total synthesis, molecular modeling and biological evaluation of 4,10-didesmethyl telithromycin (4), a novel desmethyl analogue of the 3rd-generation drug telithromycin (2). Telithromycin is an FDA-approved ketolide antibiotic derived from erythromycin (1). We found 4,10-didesmethyl telithromycin (4) to be four times more active than previously prepared 4,8,10-tridesmethyl congener (3) in MIC assays. While less potent than telithromycin (2), the inclusion of the C-8 methyl group has improved biological activity suggesting it plays an important role in antibiotic function.
total synthesis; ketolide antibiotics; antibiotic resistance; telithromycin; molecular modeling; desmethyl analogues
Small ankyrin-1 is a splice variant of the ANK1 gene that binds to obscurin A. Previous studies have identified electrostatic interactions that contribute to this interaction. In addition, molecular dynamics (MD) simulations predict four hydrophobic residues in a ‘hot spot’ on the surface of the ankyrin-like repeats of sAnk1, near the charged residues involved in binding. We used site-directed mutagenesis, blot overlays and surface plasmon resonance assays to study the contribution of the hydrophobic residues, V70, F71, I102 and I103, to two different 30-mers of obscurin that bind sAnk1, Obsc6316–6345 and Obsc6231–6260. Alanine mutations of each of the hydrophobic residues disrupted binding to the high affinity binding site, Obsc6316–6345. In contrast, V70A and I102A mutations had no effect on binding to the lower affinity site, Obsc6231–6260. Alanine mutagenesis of the five hydrophobic residues present in Obsc6316–6345 showed that V6328, I6332, and V6334 were critical to sAnk1 binding. Individual alanine mutants of the six hydrophobic residues of Obsc6231–6260 had no effect on binding to sAnk1, although a triple alanine mutant of residues V6233/I6234/I6235 decreased binding. We also examined a model of the Obsc6316–6345-sAnk1 complex in MD simulations and found I102 of sAnk1 to be within 2.2Å of V6334 of Obsc6316–6345. In contrast to the I102A mutation, mutating I102 of sAnk1 to other hydrophobic amino acids such as phenylalanine or leucine did not disrupt binding to obscurin. Our results suggest that hydrophobic interactions contribute to the higher affinity of Obsc6316– 6345 for sAnk1 and to the dominant role exhibited by this sequence in binding.
Skeletal muscle; hydrophobic interactions; molecular dynamics
Thorough searches on the potential energy surfaces of five tripeptides, GGG, GYG, GWG, TGG and MGG, were performed by considering all possible combinations of the bond rotational degrees of freedom with a semi-empirical and ab initio combined computational approach. Structural characteristics of the obtained stable tripeptide conformers were carefully analyzed. Conformers of the five tripeptides were found to be closely connected with conformers of their constituting dipeptides and amino acids. A method for finding all important tripeptide conformers by optimizing a small number of trial structures generated by suitable superposition of the parent amino acid and dipeptide conformers is thus proposed. Applying the method to another five tripeptides, YGG, FGG, WGG, GFA and GGF, studied before shows that the new approach is both efficient and reliable by providing the most complete ensembles of tripeptide conformers. The method is further generalized for application to larger peptides by introducing the breeding and mutation concepts in a genetic algorithm way. The generalized method is verified to be capable of finding tetrapeptide conformers with secondary structures of strands, helices and turns which are highly populated in larger peptides. This show some promise for the proposed method to be applied for the structural determination of larger peptides.
amino acids; dipeptides; tripeptides; structure determination; genetic algorithm
Presented is an extension of the CHARMM additive all-atom carbohydrate force field to enable the modeling of phosphate and sulfate linked to carbohydrates. The parameters are developed in a hierarchical fashion using model compounds containing the key atoms in the full carbohydrates. Target data for parameter optimization included full two-dimensional energy surfaces defined by the glycosidic dihedral angle pairs in the phosphate/sulfate model compound analogs of hexopyranose monosaccharide phosphates and sulfates, as determined by quantum mechanical (QM) MP2/cc-pVTZ single point energies on MP2/6-31+G(d) optimized structures. In order to achieve balanced, transferable dihedral parameters for the dihedral angles, surfaces for all possible anomeric and conformational states were included during the parametrization process. In addition, to model physiologically relevant systems both the mono- and di-anionic charged states were studied for the phosphates. This resulted in over 7000 MP2/cc-pVTZ//MP2/6-31G+(d) model compound conformational energies which, supplemented with QM geometries, were the main target data for the parametrization. Parameters were validated against crystals of relevant monosaccharide derivatives obtained from the Cambridge Structural Database (CSD) and larger systems, namely inositol-(tri/tetra/penta) phosphates non-covalently bound to the pleckstrin homology (PH) domain and oligomeric chondroitin sulfate in solution and in complex with cathepsin K protein.
Canonical duplex RNA assumes only the A-form conformation at the secondary structure level while, in contrast, a wide range of non-canonical, tertiary conformations of RNA occur. Here, we show how the 2′-hydroxyl controls RNA conformational properties. Quantum mechanical (QM) calculations reveal that the orientation of the 2′-hydroxyl significantly alters the intrinsic flexibility of the phosphodiester backbone, favoring the A-form in duplex RNA when it is in the base orientation and facilitating sampling of a wide range of non-canonical, tertiary structures when it is in the O3′ orientation. Influencing the orientation of the 2′-hydroxyl are interactions with the environment as evidenced by crystallographic survey data, indicating the 2′-hydroxyl to sample more of the O3′ orientation in non-canonical RNA structures. These results indicate that the 2′-hydroxyl acts as a “switch” both limiting the conformation of RNA to the A-form at the secondary structure level, while allowing RNA to sample a wide range of non-canonical tertiary conformations.
The Diels – Alder reaction was applied to 4,5-epoxymorphinan opioids to generate a novel aromatic cycloadduct at C(7) – C(8): Thermolytic cleavage of sultine 8 produced the reactive diene o-quinodimethane 7 which condensed favorably with codeine (11), but not with codeinone (9) or 14- hydroxycodeinone (10), producing the desired tetrahydronaphtho adduct 12 with (7R,8R) geometry (Scheme). The configuration of the cycloadduct was determined by 1D- and 2D-NMR experiments. The unanticipated reactivity of these codeine derivatives was investigated by quantum-mechanical calculations, and it was determined that steric effects of the 6-keto and 14-hydroxy group likely precluded condensation by raising the molecular energy of their respective transition states.
The B-form of DNA can populate two different backbone conformations: BI and BII, defined by the difference between the torsion angles ε and ζ (BI = ε-ζ < 0 and BII = ε-ζ > 0). BI is the most populated state, but the population of the BII state, which is sequence dependent, is significant and accumulating evidence shows that BII affects the overall structure of DNA, and thus influences protein-DNA recognition. This work presents a reparametrization of the CHARMM27 additive nucleic acid force field to increase the sampling of the BII form in MD simulations of DNA. In addition, minor modifications of sugar puckering were introduced to facilitate sampling of the A form of DNA under the appropriate environmental conditions. Parameter optimization was guided by quantum mechanical data on model compounds, followed by calculations on several DNA duplexes in the condensed phase. The selected optimized parameters were then validated against a number of DNA duplexes, with the most extensive tests performed on the EcoRI dodecamer, including comparative calculations using the Amber Parm99bsc0 force field. The new CHARMM model better reproduces experimentally observed sampling of the BII conformation, including sampling as a function of sequence. In addition, the model reproduces the A form of the 1ZF1 duplex in 75 % ethanol, and yields a stable Z-DNA conformation of duplex (GTACGTAC) in its crystal environment. The resulting model, in combination with a recent reoptimization of the CHARMM27 force field for RNA, will be referred to as CHARMM36.
nucleic acids; RNA; empirical force field; quantum mechanics; EcorRI dodecamer; oligonucleotide; A-DNA; B-DNA; Z-DNA; crystal survey
Empirical force fields commonly used to describe the condensed phase properties of complex systems such as biological macromolecules are continuously being updated. Improvements in quantum mechanical (QM) methods used to generate target data, availability of new experimental target data, incorporation of new classes of compounds and new theoretical developments (eg. polarizable methods) make force-field development a dynamic domain of research. Accordingly, a number of improvements and extensions of the CHARMM force fields have occurred over the years. The objective of the present review is to provide an up-to-date overview of the CHARMM force fields. A limited presentation on the historical aspects of force fields will be given, including underlying methodologies and principles, along with a brief description of the strategies used for parameter development. This is followed by information on the CHARMM additive and polarizable force fields, including examples of recent applications of those force fields.
Poliovirus (PV) is a well-characterized RNA virus, and the RNA-dependent RNA polymerase (RdRp) from PV (3Dpol) has been widely employed as an important model for understanding the structure-function relationships of RNA and DNA polymerases. Many experimental studies of the kinetics of nucleotide incorporation by RNA and DNA polymerases suggest that each nucleotide incorporation cycle basically consists of six sequential steps: (1) an incoming nucleotide binds to the polymerase-primer/template complex; (2) the ternary complex (nucleotide-polymerase-primer/template) undergoes a conformational change; (3) phosphoryl transfer occurs (the chemistry step); (4) a post-chemistry conformational change occurs; (5) pyrophosphate is released; (6) RNA or DNA translocation. Recently, the importance of structural motif D in nucleotide incorporation has been recognized, but the functions of motif D are less well explored so far. In this work, we used two computational techniques, molecular dynamics (MD) simulation and quantum mechanics (QM) method, to explore the roles of motif D in nucleotide incorporation catalyzed by PV 3Dpol. We discovered that the motif D, exhibiting high flexibility in either the presence or the absence of RNA primer/template, might facilitate the transportation of incoming nucleotide or outgoing pyrophosphate. We observed that the dynamic behavior of motif A, which should be essential to the polymerase function, was greatly affected by the motions of motif D. In the end, through QM calculations, we attempted to investigate the proton transfer in enzyme catalysis associated with a few amino acid residues of motifs F and D.
The missing link between dynamics and structure or between dynamics and function of a protein has recently been paid much attention by many scientists since it has been recognized that a folded protein should be considered as an ensemble of conformations fluctuating in the neighborhood of its native state, instead of being pictured as a single static structure. Thus, to completely understand a protein and its functions, the dynamic features of the protein under a certain condition are required to be known. In this study, we performed atomistic MD simulations and QM calculations on the RNA-dependent RNA polymerase (RdRp) from poliovirus (PV), which is an important model system for gaining insight into the features of RNA and DNA polymerases. Through the computational studies of PV 3Dpol, we aim at finding out valuable information about the dynamic properties of the enzyme and exploring the molecular mechanism of the phosphoryl transfer in nucleotide incorporation.
We present an extension of the CHARMM hexopyranose monosaccharide additive all-atom force field to enable modeling of glycosidic-linked hexopyranose polysaccharides. The new force field parameters encompass 1→1, 1→2, 1→3, 1→4, and 1→6 hexopyranose glycosidic linkages, as well as O-methylation at the C1 anomeric carbon, and are developed to be consistent with the CHARMM all-atom biomolecular force fields for proteins, nucleic acids, and lipids. The parameters are developed in a hierarchical fashion using model compounds containing the key atoms in the full carbohydrates, in particular O-methyl-tetrahydropyran and glycosidic-linked dimers consisting of two molecules of tetrahyropyran or one of tetrahydropyran and one of cyclohexane. Target data for parameter optimization include full two-dimensional energy surfaces defined by the Φ/Ψ glycosidic dihedral angles in the disaccharide analogs as determined by quantum mechanical MP2/cc-pVTZ single point energies on MP2/6-31G(d) optimized structures (MP2/cc-pVTZ//MP2/6-31G(d)). In order to achieve balanced, transferable dihedral parameters for the Φ/Ψ glycosidic dihedral angles, surfaces for all possible chiralities at the ring carbon atoms involved in the glycosidic linkages are considered, resulting in over 5000 MP2/cc-pVTZ//MP2/6-31G(d) conformational energies. Also included as target data are vibrational frequencies, pair interaction energies and distances with water molecules, and intramolecular geometries including distortion of the glycosidic valence angle as a function of the glycosidic dihedral angles. The model-compound optimized force field parameters are validated on full disaccharides through comparison of molecular dynamics results to available experimental data. Good agreement is achieved with experiment for a variety of properties including crystal cell parameters and intramolecular geometries, aqueous densities, and aqueous NMR coupling constants associated with the glycosidic linkage. The newly-developed parameters allow for the modeling of linear, branched, and cyclic hexopyranose glycosides both alone and in heterogenous systems including proteins, nucleic acids and/or lipids when combined with existing CHARMM biomolecular force fields.
The small amyloid-forming GNNQQNY fragment of the prion sequence has been the subject of extensive experimental and numerical studies over the last few years. Using unbiased molecular dynamics with the OPEP coarse-grained potential, we focus here on the onset of aggregation in a 20-mer system. With a total of 16.9 of simulations at 280 K and 300 K, we show that the GNNQQNY aggregation follows the classical nucleation theory (CNT) in that the number of monomers in the aggregate is a very reliable descriptor of aggregation. We find that the critical nucleus size in this finite-size system is between 4 and 5 monomers at 280 K and 5 and 6 at 300 K, in overall agreement with experiment. The kinetics of growth cannot be fully accounted for by the CNT, however. For example, we observe considerable rearrangements after the nucleus is formed, as the system attempts to optimize its organization. We also clearly identify two large families of structures that are selected at the onset of aggregation demonstrating the presence of well-defined polymorphism, a signature of amyloid growth, already in the 20-mer aggregate.
Protein aggregation plays an important pathological role in numerous neurodegenerative diseases such as Alzheimer's, Parkinson's, Creutzfeldt-Jakob, the Prion disease and diabetes mellitus. In most cases, misfolded proteins are involved and aggregate irreversibly to form highly ordered insoluble macrostructures, called amyloid fibrils, which deposit in the brain. Studies have revealed that all proteins are capable of forming amyloid fibrils that all share common structural features and therefore aggregation mechanisms. The toxicity of amyloid aggregates is however not attributed to the fibrils themselves but rather to smaller more disordered aggregates, oligomers, forming parallel to or prior to fibrils. Understanding the assembly process of these amyloid oligomers is key to understanding their toxicity mechanism in order to devise a possible treatment strategy targeting these toxic aggregates. Our approach here is to computationally study the aggregation dynamics of a 20-mer of an amyloid peptide GNNQQNY from a prion protein. Our findings suggest that the assembly is a spontaneous process that can be described as a complex nucleation and growth mechanism and which can lead to two classes of morphologies for the aggregates, one of which resembles a protofibril-like structure. Such numerical studies are crucial to understanding the details of fast biological processes and complement well experimental studies.
G protein-coupled receptors form hetero-dimers and higher order hetero-oligomers, yet the significance of receptor heteromerization in cellular and behavioral responses is poorly understood. Atypical antipsychotic drugs, such as clozapine and risperidone all have in common a high affinity for the serotonin 5-HT2A receptor (2AR). However, closely related nonantipsychotic drugs, such as ritanserin and methysergide, while blocking 2AR function, lack comparable neuropsychological effects. Why some but not all drugs that inhibit 2AR-dependent signaling exhibit antipsychotic properties remains unresolved. We found that a heteromeric complex formed between the metabotropic glutamate 2 receptor (mGluR2) and the 2AR critically integrates the action of drugs affecting signaling and behavioral outcomes. Acting through the mGluR2/2AR heterocomplex, both glutamatergic and serotonergic drugs achieve a balance between Gi- and Gq-dependent signaling that predicts their psychoactive behavioral effects. These observations provide a novel mechanistic insight into antipsychotic action that may advance therapeutic strategies for schizophrenia.
The environmental arylamine mutagens are implicated in the etiology of various sporadic human cancers. Arylamine-modified dG lesions were studied in two fully paired 11-mer duplexes with a -G*CN- sequence context, in which G* is a C8-substituted dG adduct derived from fluorinated analogs of 4-aminobiphenyl (FABP), 2-aminofluorene (FAF) or 2-acetylaminofluorene (FAAF), and N is either dA or dT. The FABP and FAF lesions exist in a simple mixture of ‘stacked’ (S) and ‘B-type’ (B) conformers, whereas the N-acetylated FAAF also samples a ‘wedge’ (W) conformer. FAAF is repaired three to four times more efficiently than FABP and FAF. A simple A- to -T polarity swap in the G*CA/G*CT transition produced a dramatic increase in syn-conformation and resulted in 2- to 3-fold lower nucleotide excision repair (NER) efficiencies in Escherichia coli. These results indicate that lesion-induced DNA bending/thermodynamic destabilization is an important DNA damage recognition factor, more so than the local S/B-conformational heterogeneity that was observed previously for FAF and FAAF in certain sequence contexts. This work represents a novel 3′-next flanking sequence effect as a unique NER factor for bulky arylamine lesions in E. coli.
Understanding how glycosylation affects protein structure, dynamics, and function is an emerging and challenging problem in biology. As a first step toward glycan modeling in the context of structural glycobiology, we have developed Glycan Reader and integrated it into the CHARMM-GUI, http://www.charmm-gui.org/input/glycan. Glycan Reader greatly simplifies the reading of PDB structure files containing glycans through (i) detection of carbohydrate molecules, (ii) automatic annotation of carbohydrates based on their three-dimensional structures, (iii) recognition of glycosidic linkages between carbohydrates as well as N-/O-glycosidic linkages to proteins, and (iv) generation of inputs for the biomolecular simulation program CHARMM with the proper glycosidic linkage setup. In addition, Glycan Reader is linked to other functional modules in CHARMM-GUI, allowing users to easily generate carbohydrate or glycoprotein molecular simulation systems in solution or membrane environments and visualize the electrostatic potential on glycoprotein surfaces. These tools are useful for studying the impact of glycosylation on protein structure and dynamics.
Molecular Dynamics; Electrostatic Surface; Membrane; Visualization
Membrane-associated serine protease matriptase has been implicated in human diseases, and might be a drug target. In the present study, a novel class of matriptase inhibitors targeting zymogen activation is developed by a combination of the screening of compound library using a cell-based matriptase activation assay and a computer-aided search of commercially available analogs of a selected compound. Four structurally related compounds are identified that can inhibit matriptase activation with IC50 at low μM in both intact-cell and cell-free systems, suggesting that these inhibitors target the matriptase autoactivation machinery rather than the intracellular signaling pathways. These activation inhibitors can also inhibit prostasin activation, a downstream event that occurs in lockstep with matriptase activation. In contrast, the matriptase catalytic inhibitor CVS-3983 at a concentration 300-fold higher than its Ki fails to inhibit activation of either protease. Our results suggest that inhibiting matriptase activation is an efficient way to control matriptase function.
ERK; kinase inhibitor; small molecule; anti-cancer; protein-protein interaction
Monosaccharide derivatives such as xylose, fucose, N-acetylglucosamine (GlcNAc), N-acetylgalactosamine (GlaNAc), glucuronic acid, iduronic acid, and N-acetylneuraminic acid (Neu5Ac) are important components of eukaryotic glycans. The present work details development of force-field parameters for these monosaccharides and their covalent connections to proteins via O-linkages to serine or threonine sidechains and via N-linkages to asparagine sidechains. The force field development protocol was designed to explicitly yield parameters that are compatible with the existing CHARMM additive force field for proteins, nucleic acids, lipids, carbohydrates, and small molecules. Therefore, when combined with previously developed parameters for pyranose and furanose monosaccharides, for glycosidic linkages between monosaccharides, and for proteins, the present set of parameters enables the molecular simulation of a wide variety of biologically-important molecules such as complex carbohydrates and glycoproteins. Parametrization included fitting to quantum mechanical (QM) geometries and conformational energies of model compounds, as well as to QM pair interaction energies and distances of model compounds with water. Parameters were validated in the context of crystals of relevant monosaccharides, as well NMR and/or x-ray crystallographic data on larger systems including oligomeric hyaluronan, sialyl Lewis X, O- and N-linked glycopeptides, and a lectin:sucrose complex. As the validated parameters are an extension of the CHARMM all-atom additive biomolecular force field, they further broaden the types of heterogeneous systems accessible with a consistently-developed force-field model.
xylose; fucose; GlcNAc; GalNAc; glucuronic acid; sialic acid; Neu5Ac; O-linked; N-linked; glycoprotein; glycopeptide; glycan; peptidoglycan; glycosaminoglycan; force field; molecular dynamics; molecular mechanics; CHARMM