Modelling the enantiorecognition of structurally diverse pharmaceuticals on O-substituted polysaccharide-based stationary phases.

This study aims to develop models to predict the retention, separation and elution sequence of the enantiomers of structurally diverse pharmaceuticals. More specifically, Quantitative Structure Retention Relationships (QSRR) models are built that describe the relationship between molecular descriptors and retention. Eighteen structurally diverse chiral mixtures, each consisting of a pair of enantiomers, were analyzed on two polysaccharide chiral stationary phases, Chiralcel OD-RH (cellulose tris(3,5-dimethylphenylcarbamate)) and Lux amylose-2 (amylose tris(5-chloro-2-methylphenylcarbamate)), applying either a basic or an acidic mobile phase, and their retention factor and elution sequence were determined. Both achiral and, in-house defined, chiral descriptors were used as descriptive variables to build the models. Linear regression techniques, i.e. stepwise multiple linear regression (sMLR) and partial least squares (PLS) regression, were applied to model the retention or separation as a function of the descriptors. In a first step, models were built with only achiral descriptors to model the global retention of both enantiomers of a chiral molecule. Subsequently, models were built with only chiral descriptors to predict the enantioseparation and elution sequence, and finally, models were considered with both descriptor types to predict the retention, the separation and the elution sequence of the enantiomers. The global retention was predicted well by the sMLR models with only achiral descriptors. The models with only chiral descriptors were not found suitable to predict the enantioseparation and elution sequence. Finally, the models containing both chiral and achiral descriptors allowed predicting the retention well, but their ability to predict the elution sequence and separation of the enantiomers differed widely for the chromatographic systems considered.

Structural investigation of human cystine/glutamate antiporter system xc - (Sxc -) using homology modeling and molecular dynamics.

The cystine/glutamate antiporter system xc - (Sxc -) belongs to the SLC7 family of plasma membrane transporters. It exports intracellular glutamate along the latter's concentration gradient as a driving force for cellular uptake of cystine. Once imported, cystine is mainly used for the production of glutathione, a tripeptide thiol crucial in maintenance of redox homeostasis and protection of cells against oxidative stress. Overexpression of Sxc - has been found in several cancer cells, where it is thought to counteract the increased oxidative stress. In addition, Sxc - is important in the central nervous system, playing a complex role in regulating glutamatergic neurotransmission and glutamate toxicity. Accordingly, this transporter is considered a potential target for the treatment of cancer as well as neurodegenerative diseases. Till now, no specific inhibitors are available. We herein present four conformations of Sxc - along its transport pathway, obtained using multi-template homology modeling and refined by means of Molecular Dynamics. Comparison with a very recently released cryo-EM structure revealed an excellent agreement with our inward-open conformation. Intriguingly, our models contain a structured N-terminal domain that is unresolved in the experimental structures and is thought to play a gating role in the transport mechanism of other SLC7 family members. In contrast to the inward-open model, there is no direct experimental counterpart for the other three conformations we obtained, although they are in fair agreement with the other stages of the transport mechanism seen in other SLC7 transporters. Therefore, our models open the prospect for targeting alternative Sxc - conformations in structure-based drug design efforts.

Modelling approaches for chiral chromatography on polysaccharide-based and macrocyclic antibiotic chiral selectors: A review.

An overview of molecular modelling approaches, related to chiral separations on polysaccharide-based and macrocyclic antibiotic chiral selectors, is presented. Both atomistic calculations and empirical fitting procedures are discussed. Atomistic calculations, such as docking and molecular dynamics can be used to model the interactions between enantiomers and the chiral stationary phase. This may help obtaining information about the chiral recognition mechanism. Conversely, in empirical fitting procedures, mathematical models for relevant separation parameters are fitted to experimental observations. The latter use theoretical molecular descriptors, calculated from the molecular structure, which are combined into a model to predict a given response, for example, retention. Such relationships, when used in chiral separations, are often called quantitative structure enantioselective retention relationships (QSERR) and an increased interest in them can be observed in the literature. Different regression models are discussed, such as multiple linear regression and partial least squares.

Styrene-Maleic Acid Copolymer Nanodiscs to Determine the Shape of Membrane Proteins.

Lipid nanodiscs can be used to solubilize functional membrane proteins (MPs) in nativelike environments. Thus, they are promising reagents that have been proven useful to characterize MPs. Both protein and non-protein molecular belts have shown promise to maintain the structural integrity of MPs in lipid nanodiscs. Small-angle neutron scattering (SANS) can be used to determine low-resolution structures of proteins in solution, which can be enhanced through the use of contrast variation methods. We present theoretical contrast variation SANS results for protein and styrene-maleic acid copolymer (SMA) belt 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC) nanodiscs with and without additional bound or transmembrane proteins. The predicted scattering properties are derived from atomistic molecular dynamics simulations to account for conformational fluctuations, and we determine deuterium-labeling conditions such that SANS intensity profiles only include contributions from the scattering of the MP of interest. We propose strategies to tune the neutron scattering length densities (SLDs) of the SMA and DMPC using selective deuterium labeling such that the SLD of the nanodisc becomes homogeneous and its scattering can essentially be eliminated in solvents containing an appropriate amount of D2O. These finely tuned labeled polymer-based nanodiscs are expected to be useful to extract the size and molecular shape information of MPs using SANS-based contrast variation experiments, and they can be used with MPs of any molecular weight.

The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions.

Accurate potential energy models are necessary for reliable atomistic simulations of chemical phenomena. In the realm of biomolecular modeling, large systems like proteins comprise very many noncovalent interactions (NCIs) that can contribute to the protein's stability and structure. This work presents two high-quality chemical databases of common fragment interactions in biomolecular systems as extracted from high-resolution Protein DataBank crystal structures: 3380 sidechain-sidechain interactions and 100 backbone-backbone interactions that inaugurate the BioFragment Database (BFDb). Absolute interaction energies are generated with a computationally tractable explicitly correlated coupled cluster with perturbative triples [CCSD(T)-F12] "silver standard" (0.05 kcal/mol average error) for NCI that demands only a fraction of the cost of the conventional "gold standard," CCSD(T) at the complete basis set limit. By sampling extensively from biological environments, BFDb spans the natural diversity of protein NCI motifs and orientations. In addition to supplying a thorough assessment for lower scaling force-field (2), semi-empirical (3), density functional (244), and wavefunction (45) methods (comprising >1M interaction energies), BFDb provides interactive tools for running and manipulating the resulting large datasets and offers a valuable resource for potential energy model development and validation.

Rationally designed BCL6 inhibitors target activated B cell diffuse large B cell lymphoma.

Diffuse large B cell lymphomas (DLBCLs) arise from proliferating B cells transiting different stages of the germinal center reaction. In activated B cell DLBCLs (ABC-DLBCLs), a class of DLBCLs that respond poorly to current therapies, chromosomal translocations and amplification lead to constitutive expression of the B cell lymphoma 6 (BCL6) oncogene. The role of BCL6 in maintaining these lymphomas has not been investigated. Here, we designed small-molecule inhibitors that display higher affinity for BCL6 than its endogenous corepressor ligands to evaluate their therapeutic efficacy for targeting ABC-DLBCL. We used an in silico drug design functional-group mapping approach called SILCS to create a specific BCL6 inhibitor called FX1 that has 10-fold greater potency than endogenous corepressors and binds an essential region of the BCL6 lateral groove. FX1 disrupted formation of the BCL6 repression complex, reactivated BCL6 target genes, and mimicked the phenotype of mice engineered to express BCL6 with corepressor binding site mutations. Low doses of FX1 induced regression of established tumors in mice bearing DLBCL xenografts. Furthermore, FX1 suppressed ABC-DLBCL cells in vitro and in vivo, as well as primary human ABC-DLBCL specimens ex vivo. These findings indicate that ABC-DLBCL is a BCL6-dependent disease that can be targeted by rationally designed inhibitors that exceed the binding affinity of natural BCL6 ligands.

Parametrization of halogen bonds in the CHARMM general force field: Improved treatment of ligand-protein interactions.

A halogen bond is a highly directional, non-covalent interaction between a halogen atom and another electronegative atom. It arises due to the formation of a small region of positive electrostatic potential opposite the covalent bond to the halogen, called the 'sigma hole.' Empirical force fields in which the electrostatic interactions are represented by atom-centered point charges cannot capture this effect because halogen atoms usually carry a negative charge and therefore interact unfavorably with other electronegative atoms. A strategy to overcome this problem is to attach a positively charged virtual particle to the halogen. In this work, we extend the additive CHARMM General Force Field (CGenFF) to include such interactions in model systems of phenyl-X, with X being Cl, Br or I including di- and trihalogenated species. The charges, Lennard-Jones parameters, and halogen-virtual particle distances were optimized to reproduce the orientation dependence of quantum mechanical interaction energies with water, acetone, and N-methylacetamide as well as experimental pure liquid properties and relative hydration free energies with respect to benzene. The resulting parameters were validated in molecular dynamics simulations on small-molecule crystals and on solvated protein-ligand complexes containing halogenated compounds. The inclusion of positive virtual sites leads to better agreement across experimental observables, including preservation of ligand binding poses as a direct result of the improved representation of halogen bonding.

Additive CHARMM force field for naturally occurring modified ribonucleotides.

More than 100 naturally occurring modified nucleotides have been found in RNA molecules, in particular in tRNAs. We have determined molecular mechanics force field parameters compatible with the CHARMM36 all-atom additive force field for all these modifications using the CHARMM force field parametrization strategy. Emphasis was placed on fine tuning of the partial atomic charges and torsion angle parameters. Quantum mechanics calculations on model compounds provided the initial set of target data, and extensive molecular dynamics simulations of nucleotides and oligonucleotides in aqueous solutions were used for further refinement against experimental data. The presented parameters will allow for computational studies of a wide range of RNAs containing modified nucleotides, including the ribosome and transfer RNAs.

Quantifying the Binding Interaction between the Hypoxia-Inducible Transcription Factor and the von Hippel-Lindau Suppressor.

The hypoxia-inducible transcription factors (HIF) play a central role in the human oxygen sensing signaling pathway. The binding of the von Hippel-Lindau tumor suppressor protein (pVHL)-ElonginC-ElonginB complex (VCB) to HIF-1α is highly selective for the trans-4-hydroxylation form of when Pro564 in the C-terminal oxygen-dependent degradation domain (ODDD) of HIF-1α. The binding of HIFα for VCB is increased by ∼1000-fold upon addition of a single hydroxyl group to either of two conserved proline-residues. Here, we address how this addition governs selective recognition and characterizes the strength of the interaction of this "switch-like" signaling event. A new set of molecular mechanics parameters for 4-hydroxyproline has been developed following the CHARMM force field philosophy. Using the free energy perturbation (FEP) formalism, the difference in the binding free energies between HIF-1α in the nonhydroxylated and hydroxylated forms with the VCB complex was estimated using over 3 µs of MD trajectories. These results can favorably be compared to an experimental value of ∼4 kcal mol(-1). It is observed that the optimized hydrogen bonding network to the buried hydroxyprolyl group confers precise discrimination between hydroxylated and unmodified prolyl residues. These observations provide insight that will aid in developing therapeutic agents that block HIF-α recognition by pVHL.

Robustness in the fitting of molecular mechanics parameters.

Automated methods for force field parametrization have attracted renewed interest of the community, but the robustness issues associated with the often ill-conditioned nature of parameter optimization have been vastly underappreciated in the recent literature. For this reason, this article offers a detailed description of the origin and nature of these issues. This includes a discussion of the restrained electrostatic potential fit (RESP) charge model, which does contain explicit robustness-enhancing measures albeit not in the context of bonded parameters, and which forms an inspiration for the present work. It is also discussed how all the bonded parameters in a Class I force field can be simultaneously fit using the linear least squares (LLS) procedure, and a novel restraining strategy is presented that overcomes robustness issues in the LLS fitting of bonded parameters while minimally impacting the fitted values of well-behaved parameters. Two variants of this methodology are then validated through a number of case studies, including the fitting of bond-charge increments, which illustrates the method's potential for robustly solving general LLS problems beyond force field parametrization.

In silico identification of PAP-1 binding sites in the Kv1.2 potassium channel.

Voltage-gated potassium channels of the Kv1 family play a crucial role in the generation and transmission of electrical signals in excitable cells affecting neuronal and cardiac activities. Small-molecule blockage of these channels has been proposed to occur via a cooperative mechanism involving two main blocking sites: the inner-pore site located below the selectivity filter, and a side-pocket cavity located between the pore and the voltage sensor. Using 0.5 µs molecular dynamics simulation trajectories complemented by docking calculations, the potential binding sites of the PAP-1 (5-(4-phenoxybutoxy)psoralen) blocker to the crystal structure of Kv1.2 channel have been studied. The presence of both mentioned blocking sites at Kv1.2 is confirmed, adding evidence in favor of a cooperative channel blockage mechanism. These observations provide insight into drug modulation that will guide further developments of Kv inhibitors.

CHARMM-GUI PDB manipulator for advanced modeling and simulations of proteins containing nonstandard residues.

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface to prepare molecular simulation systems and input files to facilitate the usage of common and advanced simulation techniques. Since it is originally developed in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to setup a broad range of simulations including free energy calculation and large-scale coarse-grained representation. Here, we describe functionalities that have recently been integrated into CHARMM-GUI PDB Manipulator, such as ligand force field generation, incorporation of methanethiosulfonate spin labels and chemical modifiers, and substitution of amino acids with unnatural amino acids. These new features are expected to be useful in advanced biomolecular modeling and simulation of proteins.

Lipid-linked oligosaccharides in membranes sample conformations that facilitate binding to oligosaccharyltransferase.

Lipid-linked oligosaccharides (LLOs) are the substrates of oligosaccharyltransferase (OST), the enzyme that catalyzes the en bloc transfer of the oligosaccharide onto the acceptor asparagine of nascent proteins during the process of N-glycosylation. To explore LLOs' preferred location, orientation, structure, and dynamics in membrane bilayers of three different lipid types (dilauroylphosphatidylcholine, dimyristoylphosphatidylcholine, and dioleoylphosphatidylcholine), we have modeled and simulated both eukaryotic (Glc3-Man9-GlcNAc2-PP-Dolichol) and bacterial (Glc1-GalNAc5-Bac1-PP-Undecaprenol) LLOs, which are composed of an isoprenoid moiety and an oligosaccharide, linked by pyrophosphate. The simulations show no strong impact of different bilayer hydrophobic thicknesses on the overall orientation, structure, and dynamics of the isoprenoid moiety and the oligosaccharide. The pyrophosphate group stays in the bilayer head group region. The isoprenoid moiety shows high flexibility inside the bilayer hydrophobic core, suggesting its potential role as a tentacle to search for OST. The oligosaccharide conformation and dynamics are similar to those in solution, but there are preferred interactions between the oligosaccharide and the bilayer interface, which leads to LLO sugar orientations parallel to the bilayer surface. Molecular docking of the bacterial LLO to a bacterial OST suggests that such orientations can enhance binding of LLOs to OST.

Perturbation of long-range water dynamics as the mechanism for the antifreeze activity of antifreeze glycoprotein.

Very little is known about the mechanism of antifreeze action of antifreeze glycoproteins (AFGPs) present in Antarctic teleost fish. Recent NMR and CD studies assisted with total synthesis of synthetic AFGP variants have provided insight into the structure of short AFGP glycopeptides, though the observations did not yield information on the antifreeze mechanism of action. In this study, we use Hamiltonian replica exchange (HREX) molecular dynamics simulations to probe the structure and surrounding aqueous environments of both the natural (AFGP8) and synthetic (s-AFGP4) AFGPs. AFGPs can adopt both amphiphilic and pseudoamphiphilic conformations, the preference of which is related to the proline content of the peptide. The arrangement of carbohydrates allows the hydroxyl groups on terminal galactose units to form stable water bridges which in turn influence the hydrogen-bond network, structure, and dynamics of the surrounding solvent. Interestingly, these local effects lead to the perturbation of the tetrahedral environment for water molecules in hydration layers far (10.0-12.0 Å) from the AFGPs. This structure-induced alteration of long-range hydration dynamics is proposed to be the major contributor to antifreeze activity, a conclusion that is in line with terahertz spectroscopy experiments. The detailed structure-mechanism correlation provided in this study could lead to the design of better synthetic AFGP variants.

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.

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.

Amphipathic α-helix mimetics based on a 1,2-diphenylacetylene scaffold.

In order to mimic amphipathic α-helices, a novel scaffold based on a 1,2-diphenylacetylene was designed. NMR and computational modeling confirmed that an intramolecular hydrogen bond favors conformations of the 1,2-diphenylacetylene that allow for accurate mimicry of the i, i + 7 and i + 2, i + 5 side chains found on opposing faces of an α-helix.

The novel BH3 α-helix mimetic JY-1-106 induces apoptosis in a subset of cancer cells (lung cancer, colon cancer and mesothelioma) by disrupting Bcl-xL and Mcl-1 protein-protein interactions with Bak.

BACKGROUND: It has been shown in many solid tumors that the overexpression of the pro-survival Bcl-2 family members Bcl-2/Bcl-xL and Mcl-1 confers resistance to a variety of chemotherapeutic agents. We designed the BH3 α-helix mimetic JY-1-106 to engage the hydrophobic BH3-binding grooves on the surfaces of both Bcl-xL and Mcl-1. METHODS: JY-1-106-protein complexes were studied using molecular dynamics (MD) simulations and the SILCS methodology. We have evaluated the in vitro effects of JY-1-106 by using a fluorescence polarization (FP) assay, an XTT assay, apoptosis assays, and immunoprecipitation and western-blot assays. A preclinical human cancer xenograft model was used to test the efficacy of JY-1-106 in vivo. RESULTS: MD and SILCS simulations of the JY-1-106-protein complexes indicated the importance of the aliphatic side chains of JY-1-106 to binding and successfully predicted the improved affinity of the ligand for Bcl-xL over Mcl-1. Ligand binding affinities were measured via an FP assay using a fluorescently labeled Bak-BH3 peptide in vitro. Apoptosis induction via JY-1-106 was evidenced by TUNEL assay and PARP cleavage as well as by Bax-Bax dimerization. Release of multi-domain Bak from its inhibitory binding to Bcl-2/Bcl-xL and Mcl-1 using JY-1-106 was detected via immunoprecipitation (IP) western blotting.At the cellular level, we compared the growth proliferation IC50s of JY-1-106 and ABT-737 in multiple cancer cell lines with various Bcl-xL and Mcl-1 expression levels. JY-1-106 effectively induced cell death regardless of the Mcl-1 expression level in ABT-737 resistant solid tumor cells, whilst toxicity toward normal human endothelial cells was limited. Furthermore, synergistic effects were observed in A549 cells using a combination of JY-1-106 and multiple chemotherapeutic agents. We also observed that JY-1-106 was a very effective agent in inducing apoptosis in metabolically stressed tumors. Finally, JY-1-106 was evaluated in a tumor-bearing nude mouse model, and was found to effectively repress tumor growth. Strong TUNEL signals in the tumor cells demonstrated the effectiveness of JY-1-106 in this animal model. No significant side effects were observed in mouse organs after multiple injections. CONCLUSIONS: Taken together, these observations demonstrate that JY-1-106 is an effective pan-Bcl-2 inhibitor with very promising clinical potential.

Site-Specific Fragment Identification Guided by Single-Step Free Energy Perturbation Calculations.

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.

Extension of the CHARMM General Force Field to sulfonyl-containing compounds and its utility in biomolecular simulations.

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.