An Efficient, Site-Selective and Spontaneous Peptide Macrocyclisation During in†vitro Translation.

Macrocyclisation provides a means of stabilising the conformation of peptides, often resulting in improved stability, selectivity, affinity, and cell permeability. In this work, a new approach to peptide macrocyclisation is reported, using a cyanobenzothiazole-containing amino acid that can be incorporated into peptides by both in vitro translation and solid phase peptide synthesis, meaning it should be applicable to peptide discovery by mRNA display. This cyclisation proceeds rapidly, with minimal by-products, is selective over other amino acids including non N-terminal cysteines, and is compatible with further peptide elaboration exploiting such an additional cysteine in bicyclisation and derivatisation reactions. Molecular dynamics simulations show that the new cyclisation group is likely to influence the peptide conformation as compared to previous thioether-based approaches, through rigidity and intramolecular aromatic interactions, illustrating their complementarity.

OFraMP: a fragment-based tool to facilitate the parametrization of large molecules.

An Online tool for Fragment-based Molecule Parametrization (OFraMP) is described. OFraMP is a web application for assigning atomic interaction parameters to large molecules by matching sub-fragments within the target molecule to equivalent sub-fragments within the Automated Topology Builder (ATB, atb.uq.edu.au) database. OFraMP identifies and compares alternative molecular fragments from the ATB database, which contains over 890,000 pre-parameterized molecules, using a novel hierarchical matching procedure. Atoms are considered within the context of an extended local environment (buffer region) with the degree of similarity between an atom in the target molecule and that in the proposed match controlled by varying the size of the buffer region. Adjacent matching atoms are combined into progressively larger matched sub-structures. The user then selects the most appropriate match. OFraMP also allows users to manually alter interaction parameters and automates the submission of missing substructures to the ATB in order to generate parameters for atoms in environments not represented in the existing database. The utility of OFraMP is illustrated using the anti-cancer agent paclitaxel and a dendrimer used in organic semiconductor devices. OFraMP applied to paclitaxel (ATB ID 35922).

Covalent Proteomimetic Inhibitor of the Bacterial FtsQB Divisome Complex.

The use of antibiotics is threatened by the emergence and spread of multidrug-resistant strains of bacteria. Thus, there is a need to develop antibiotics that address new targets. In this respect, the bacterial divisome, a multi-protein complex central to cell division, represents a potentially attractive target. Of particular interest is the FtsQB subcomplex that plays a decisive role in divisome assembly and peptidoglycan biogenesis in E. coli. Here, we report the structure-based design of a macrocyclic covalent inhibitor derived from a periplasmic region of FtsB that mediates its binding to FtsQ. The bioactive conformation of this motif was stabilized by a customized cross-link resulting in a tertiary structure mimetic with increased affinity for FtsQ. To increase activity, a covalent handle was incorporated, providing an inhibitor that impedes the interaction between FtsQ and FtsB irreversibly. The covalent inhibitor reduced the growth of an outer membrane-permeable E. coli strain, concurrent with the expected loss of FtsB localization, and also affected the infection of zebrafish larvae by a clinical E. coli strain. This first-in-class inhibitor of a divisome protein-protein interaction highlights the potential of proteomimetic molecules as inhibitors of challenging targets. In particular, the covalent mode-of-action can serve as an inspiration for future antibiotics that target protein-protein interactions.

C-X Bond Activation by Palladium: Steric Shielding versus Steric Attraction.

The C-X bond activation (X = H, C) of a series of substituted C(n°)-H and C(n°)-C(m°) bonds with C(n°) and C(m°) = H3 C- (methyl, 0°), CH3 H2 C- (primary, 1°), (CH3 )2 HC- (secondary, 2°), (CH3 )3 C- (tertiary, 3°) by palladium were investigated using relativistic dispersion-corrected density functional theory at ZORA-BLYP-D3(BJ)/TZ2P. The effect of the stepwise introduction of substituents was pinpointed at the C-X bond on the bond activation process. The C(n°)-X bonds become substantially weaker going from C(0°)-X, to C(1°)-X, to C(2°)-X, to C(3°)-X because of the increasing steric repulsion between the C(n°)- and X-group. Interestingly, this often does not lead to a lower barrier for the C(n°)-X bond activation. The C-H activation barrier, for example, decreases from C(0°)-X, to C(1°)-X, to C(2°)-X and then increases again for the very crowded C(3°)-X bond. For the more congested C-C bond, in contrast, the activation barrier always increases as the degree of substitution is increased. Our activation strain and matching energy decomposition analyses reveal that these differences in C-H and C-C bond activation can be traced back to the opposing interplay between steric repulsion across the C-X bond versus that between the catalyst and substrate.

A Modified Arrhenius Approach to Thermodynamically Study Regioselectivity in Cytochrome P450-Catalyzed Substrate Conversion.

The regio- (and stereo-)selectivity and specific activity of cytochrome P450s are determined by the accessibility of potential sites of metabolism (SOMs) of the bound substrate relative to the heme, and the activation barrier of the regioselective oxidation reaction(s). The accessibility of potential SOMs depends on the relative binding free energy (ΔΔGbind ) of the catalytically active substrate-binding poses, and the probability of the substrate to adopt a transition-state geometry. An established experimental method to measure activation energies of enzymatic reactions is the analysis of reaction rate constants at different temperatures and the construction of Arrhenius plots. This is a challenge for multistep P450-catalyzed processes that involve redox partners. We introduce a modified Arrhenius approach to overcome the limitations in studying P450 selectivity, which can be applied in multiproduct enzyme catalysis. Our approach gives combined information on relative activation energies, ΔΔGbind values, and collision entropies, yielding direct insight into the basis of selectivity in substrate conversion.

A Comparative Linear Interaction Energy and MM/PBSA Study on SIRT1-Ligand Binding Free Energy Calculation.

Binding free energy (ΔGbind) computation can play an important role in prioritizing compounds to be evaluated experimentally on their affinity for target proteins, yet fast and accurate ΔGbind calculation remains an elusive task. In this study, we compare the performance of two popular end-point methods, i.e., linear interaction energy (LIE) and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA), with respect to their ability to correlate calculated binding affinities of 27 thieno[3,2-d]pyrimidine-6-carboxamide-derived sirtuin 1 (SIRT1) inhibitors with experimental data. Compared with the standard single-trajectory setup of MM/PBSA, our study elucidates that LIE allows to obtain direct ("absolute") values for SIRT1 binding free energies with lower compute requirements, while the accuracy in calculating relative values for ΔGbind is comparable (Pearson's r = 0.72 and 0.64 for LIE and MM/PBSA, respectively). We also investigate the potential of combining multiple docking poses in iterative LIE models and find that Boltzmann-like weighting of outcomes of simulations starting from different poses can retrieve appropriate binding orientations. In addition, we find that in this particular case study the LIE and MM/PBSA models can be optimized by neglecting the contributions from electrostatic and polar interactions to the ΔGbind calculations.

Binding free energy predictions of farnesoid X receptor (FXR) agonists using a linear interaction energy (LIE) approach with reliability estimation: application to the D3R Grand Challenge 2.

Computational protein binding affinity prediction can play an important role in drug research but performing efficient and accurate binding free energy calculations is still challenging. In the context of phase 2 of the Drug Design Data Resource (D3R) Grand Challenge 2 we used our automated eTOX ALLIES approach to apply the (iterative) linear interaction energy (LIE) method and we evaluated its performance in predicting binding affinities for farnesoid X receptor (FXR) agonists. Efficiency was obtained by our pre-calibrated LIE models and molecular dynamics (MD) simulations at the nanosecond scale, while predictive accuracy was obtained for a small subset of compounds. Using our recently introduced reliability estimation metrics, we could classify predictions with higher confidence by featuring an applicability domain (AD) analysis in combination with protein-ligand interaction profiling. The outcomes of and agreement between our AD and interaction-profile analyses to distinguish and rationalize the performance of our predictions highlighted the relevance of sufficiently exploring protein-ligand interactions during training and it demonstrated the possibility to quantitatively and efficiently evaluate if this is achieved by using simulation data only.

A QM/MM Derived Polarizable Water Model for Molecular Simulation.

In this work, we propose an improved QM/MM-based strategy to determine condensed-phase polarizabilities and we use this approach to optimize a new and simple polarizable four-site water model for classical molecular simulation. For the determination of the model value for the polarizability from QM/MM, we show that our proposed consensus-fitting strategy significantly reduces the uncertainty in calculated polarizabilities in cases where the size of the local external electric field is small. By fitting electrostatic, polarization and dispersion properties of our water model based on quantum and/or combined QM/MM calculations, only a single model parameter (describing exchange repulsion) is left for empirical calibration. The resulting model performs well in describing relevant pure-liquid thermodynamic and transport properties, which illustrates the merit of our approach to minimize the number of free variables in our model.

A systematic approach to calibrate a transferable polarizable force field parameter set for primary alcohols.

In this work, parameters are optimized for a charge-on-spring based polarizable force field for linear alcohols. We show that parameter transferability can be obtained using a systematic approach in which the effects of parameter changes on physico-chemical properties calculated from simulation are predicted. Our previously described QM/MM calculations are used to attribute condensed-phase polarizabilities, and starting from the non-polarizable GROMOS 53A5/53A6 parameter set, van der Waals and Coulomb interaction parameters are optimized to reproduce pure-liquid (thermodynamic, dielectric, and transport) properties, as well as hydration free energies. For a large set of models, which were obtained by combining small perturbations of 10 distinct parameters, values for pure-liquid properties of the series methanol to butanol were close to experiment. From this large set of models, we selected 34 models without special repulsive van der Waals parameters to distinguish between hydrogen-bonding and non-hydrogen-bonding atom pairs, to make the force field simple and transparent. © 2017 Wiley Periodicals, Inc.

Comprehensive and Automated Linear Interaction Energy Based Binding-Affinity Prediction for Multifarious Cytochrome P450 Aromatase Inhibitors.

Cytochrome P450 aromatase (CYP19A1) plays a key role in the development of estrogen dependent breast cancer, and aromatase inhibitors have been at the front line of treatment for the past three decades. The development of potent, selective and safer inhibitors is ongoing with in silico screening methods playing a more prominent role in the search for promising lead compounds in bioactivity-relevant chemical space. Here we present a set of comprehensive binding affinity prediction models for CYP19A1 using our automated Linear Interaction Energy (LIE) based workflow on a set of 132 putative and structurally diverse aromatase inhibitors obtained from a typical industrial screening study. We extended the workflow with machine learning methods to automatically cluster training and test compounds in order to maximize the number of explained compounds in one or more predictive LIE models. The method uses protein-ligand interaction profiles obtained from Molecular Dynamics (MD) trajectories to help model search and define the applicability domain of the resolved models. Our method was successful in accounting for 86% of the data set in 3 robust models that show high correlation between calculated and observed values for ligand-binding free energies (RMSE < 2.5 kJ mol-1), with good cross-validation statistics.

Insights into regioselective metabolism of mefenamic acid by cytochrome P450 BM3 mutants through crystallography, docking, molecular dynamics, and free energy calculations.

Cytochrome P450 BM3 (CYP102A1) mutant M11 is able to metabolize a wide range of drugs and drug-like compounds. Among these, M11 was recently found to be able to catalyze formation of human metabolites of mefenamic acid and other nonsteroidal anti-inflammatory drugs (NSAIDs). Interestingly, single active-site mutations such as V87I were reported to invert regioselectivity in NSAID hydroxylation. In this work, we combine crystallography and molecular simulation to study the effect of single mutations on binding and regioselective metabolism of mefenamic acid by M11 mutants. The heme domain of the protein mutant M11 was expressed, purified, and crystallized, and its X-ray structure was used as template for modeling. A multistep approach was used that combines molecular docking, molecular dynamics (MD) simulation, and binding free-energy calculations to address protein flexibility. In this way, preferred binding modes that are consistent with oxidation at the experimentally observed sites of metabolism (SOMs) were identified. Whereas docking could not be used to retrospectively predict experimental trends in regioselectivity, we were able to rank binding modes in line with the preferred SOMs of mefenamic acid by M11 and its mutants by including protein flexibility and dynamics in free-energy computation. In addition, we could obtain structural insights into the change in regioselectivity of mefenamic acid hydroxylation due to single active-site mutations. Our findings confirm that use of MD and binding free-energy calculation is useful for studying biocatalysis in those cases in which enzyme binding is a critical event in determining the selective metabolism of a substrate.

Genetic Control and Evolution of Anthocyanin Methylation.

Anthocyanins are a chemically diverse class of secondary metabolites that color most flowers and fruits. They consist of three aromatic rings that can be substituted with hydroxyl, sugar, acyl, and methyl groups in a variety of patterns depending on the plant species. To understand how such chemical diversity evolved, we isolated and characterized METHYLATION AT THREE2 (MT2) and the two METHYLATION AT FIVE (MF) loci from Petunia spp., which direct anthocyanin methylation in petals. The proteins encoded by MT2 and the duplicated MF1 and MF2 genes and a putative grape (Vitis vinifera) homolog Anthocyanin O-Methyltransferase1 (VvAOMT1) are highly similar to and apparently evolved from caffeoyl-Coenzyme A O-methyltransferases by relatively small alterations in the active site. Transgenic experiments showed that the Petunia spp. and grape enzymes have remarkably different substrate specificities, which explains part of the structural anthocyanin diversity in both species. Most strikingly, VvAOMT1 expression resulted in the accumulation of novel anthocyanins that are normally not found in Petunia spp., revealing how alterations in the last reaction can reshuffle the pathway and affect (normally) preceding decoration steps in an unanticipated way. Our data show how variations in gene expression patterns, loss-of-function mutations, and alterations in substrate specificities all contributed to the anthocyanins' structural diversity.

Application of engineered cytochrome P450 mutants as biocatalysts for the synthesis of benzylic and aromatic metabolites of fenamic acid NSAIDs.

Cytochrome P450 BM3 mutants are promising biocatalysts for the production of drug metabolites. In the present study, the ability of cytochrome P450 BM3 mutants to produce oxidative metabolites of structurally related NSAIDs meclofenamic acid, mefenamic acid and tolfenamic acid was investigated. A library of engineered P450 BM3 mutants was screened with meclofenamic acid (1) to identify catalytically active and selective mutants. Three mono-hydroxylated metabolites were identified for 1. The hydroxylated products were confirmed by NMR analysis to be 3'-OH-methyl-meclofenamic acid (1a), 5-OH-meclofenamic acid (1b) and 4'-OH-meclofenamic acid (1c) which are human relevant metabolites. P450 BM3 variants containing V87I and V87F mutation showed high selectivity for benzylic and aromatic hydroxylation of 1 respectively. The applicability of these mutants to selectively hydroxylate structurally similar drugs such as mefenamic acid (2) and tolfenamic acid (3) was also investigated. The tested variants showed high total turnover numbers in the order of 4000-6000 and can be used as biocatalysts for preparative scale synthesis. Both 1 and 2 could undergo benzylic and aromatic hydroxylation by the P450 BM3 mutants, whereas 3 was hydroxylated only on aromatic rings. The P450 BM3 variant M11 V87F hydroxylated the aromatic ring at 4' position of all three drugs tested with high regioselectivity. Reference metabolites produced by P450 BM3 mutants allowed the characterisation of activity and regioselectivity of metabolism of all three NSAIDs by thirteen recombinant human P450s. In conclusion, engineered P450 BM3 mutants that are capable of benzylic or aromatic hydroxylation of fenamic acid containing NSAIDs, with high selectivity and turnover numbers have been identified. This shows their potential use as a greener alternative for the generation of drug metabolites.

A comparison between QM/MM and QM/QM based fitting of condensed-phase atomic polarizabilities.

Recently we reported a combined QM/MM approach to estimate condensed-phase values of atomic polarizabilities for use in (bio)molecular simulation. The setup relies on a MM treatment of the solvent when determining atomic polarizabilities to describe the response of a QM described solute to its external electric field. In this work, we study the effect of using alternative descriptions of the solvent molecules when evaluating atomic polarizabilities of a methanol solute. In a first step, we show that solute polarizabilities are not significantly affected upon substantially increasing the MM dipole moments towards values that are typically reported in literature for water solvent molecules. Subsequently, solute polarization is evaluated in the presence of a QM described solvent (using the frozen-density embedding method). In the latter case, lower oxygen polarizabilities were obtained than when using MM point charges to describe the solvent, due to introduction of Pauli-repulsion effects.

Towards automated binding affinity prediction using an iterative linear interaction energy approach.

Binding affinity prediction of potential drugs to target and off-target proteins is an essential asset in drug development. These predictions require the calculation of binding free energies. In such calculations, it is a major challenge to properly account for both the dynamic nature of the protein and the possible variety of ligand-binding orientations, while keeping computational costs tractable. Recently, an iterative Linear Interaction Energy (LIE) approach was introduced, in which results from multiple simulations of a protein-ligand complex are combined into a single binding free energy using a Boltzmann weighting-based scheme. This method was shown to reach experimental accuracy for flexible proteins while retaining the computational efficiency of the general LIE approach. Here, we show that the iterative LIE approach can be used to predict binding affinities in an automated way. A workflow was designed using preselected protein conformations, automated ligand docking and clustering, and a (semi-)automated molecular dynamics simulation setup. We show that using this workflow, binding affinities of aryloxypropanolamines to the malleable Cytochrome P450 2D6 enzyme can be predicted without a priori knowledge of dominant protein-ligand conformations. In addition, we provide an outlook for an approach to assess the quality of the LIE predictions, based on simulation outcomes only.

Minimally modified human blood coagulation factor X to bypass direct factor Xa inhibitors.

BACKGROUND: Direct oral factor (F)Xa inhibitors are widely used as alternatives to conventional vitamin K antagonists in managing venous thromboembolism and nonvalvular atrial fibrillation. Unfortunately, bleeding-related adverse events remain a major concern in clinical practice. In case of bleeding or emergency surgery, rapid-onset reversal agents may be required to counteract the anticoagulant activity. OBJECTIVES: The ability of FXa variants to bypass the direct oral FXa inhibitors was assessed. METHODS: Human FXa variants were generated through substitution of phenylalanine 174 (F174) for either alanine, isoleucine, or serine. FXa variants were stably expressed in HEK293 cells and purified to homogeneity using ion-exchange chromatography. RESULTS: F174-substituted human FX variants demonstrated efficacy in restoring thrombin generation in plasma containing direct FXa inhibitors (apixaban, rivaroxaban, edoxaban). Their ability to bypass the anticoagulant effects stems from a significantly reduced sensitivity for the direct FXa inhibitors due to a decrease in binding affinity determined using molecular dynamics simulations and free energy computation. Furthermore, F174 modification resulted in a partial loss of inhibition by tissue factor pathway inhibitor, enhancing the procoagulant effect of F174-substituted FX. Consequently, the F174A- and F174S-substituted FX variants effectively counteracted the effects of 2 widely used anticoagulants, apixaban and rivaroxaban, in plasma of atrial fibrillation and venous thromboembolism patients. CONCLUSION: These human FX variants have the potential to serve as a rescue reversal strategy to overcome the effect of direct FXa inhibitors in case of life-threatening bleeding events or emergency surgical interventions.

CYP 2D6 binding affinity predictions using multiple ligand and protein conformations.

Because of the large flexibility and malleability of Cytochrome P450 enzymes (CYPs), in silico prediction of CYP binding affinities to drugs and other xenobiotic compounds is a true challenge. In the current work, we use an iterative linear interaction energy (LIE) approach to compute CYP binding affinities from molecular dynamics (MD) simulation. In order to improve sampling of conformational space, we combine results from simulations starting with different relevant protein-ligand geometries. For calculated binding free energies of a set of thiourea compounds binding to the flexible CYP 2D6 isoform, improved correlation with experiment was obtained by combining results of MD runs starting from distinct protein conformations and ligand-binding orientations. This accuracy was obtained from relatively short MD simulations, which makes our approach computationally attractive for automated calculations of ligand-binding affinities to flexible proteins such as CYPs.

Distant sequence regions of JBP1 contribute to J-DNA binding.

Base-J (ß-D-glucopyranosyloxymethyluracil) is a modified DNA nucleotide that replaces 1% of thymine in kinetoplastid flagellates. The biosynthesis and maintenance of base-J depends on the base-J-binding protein 1 (JBP1) that has a thymidine hydroxylase domain and a J-DNA-binding domain (JDBD). How the thymidine hydroxylase domain synergizes with the JDBD to hydroxylate thymine in specific genomic sites, maintaining base-J during semi-conservative DNA replication, remains unclear. Here, we present a crystal structure of the JDBD including a previously disordered DNA-contacting loop and use it as starting point for molecular dynamics simulations and computational docking studies to propose recognition models for JDBD binding to J-DNA. These models guided mutagenesis experiments, providing additional data for docking, which reveals a binding mode for JDBD onto J-DNA. This model, together with the crystallographic structure of the TET2 JBP1-homologue in complex with DNA and the AlphaFold model of full-length JBP1, allowed us to hypothesize that the flexible JBP1 N-terminus contributes to DNA-binding, which we confirmed experimentally. Α high-resolution JBP1:J-DNA complex, which must involve conformational changes, would however need to be determined experimentally to further understand this unique underlying molecular mechanism that ensures replication of epigenetic information.

New functionalities in the GROMOS biomolecular simulation software.

Since the most recent description of the functionalities of the GROMOS software for biomolecular simulation in 2005 many new functions have been implemented. In this article, the new functionalities that involve modified forces in a molecular dynamics (MD) simulation are described: the treatment of electronic polarizability, an implicit surface area and internal volume solvation term to calculate interatomic forces, functions for the GROMOS coarse-grained supramolecular force field, a multiplicative switching function for nonbonded interactions, adiabatic decoupling of a number of degrees of freedom with temperature or force scaling to enhance sampling, and nonequilibrium MD to calculate the dielectric permittivity or viscosity. Examples that illustrate the use of these functionalities are given.

A single active site mutation inverts stereoselectivity of 16-hydroxylation of testosterone catalyzed by engineered cytochrome P450 BM3.

Inversion of stereoselectivity: screening of a minimal mutant library revealed a cytochrome P450 BM3 variant M01 A82W S72I capable of producing 16 α-OH-testosterone. Remarkably, a single active site mutation S72I in M01 A82W inverted the stereoselectivity of hydroxylation from 16 ß to 16 α. Introduction of S72I mutation in another 16 ß-OH-selective variant M11 V87I, also resulted in similar inversion of stereoselectivity.