Prediction of hydration free energies for the SAMPL4 diverse set of compounds using molecular dynamics simulations with the OPLS-AA force field

Neuroprotective efficacy of the glucocorticoid receptor modulator PT150 in the rotenone mouse model of Parkinson's disease

Parkinson's disease (PD) is the most common neurodegenerative movement disorder worldwide. Current treatments for PD largely center around dopamine replacement therapies and fail to prevent the progression of pathology, underscoring the need for neuroprotective interventions. Approaches that target neuroinflammation, which occurs prior to dopaminergic neuron (DAn) loss in the substantia nigra (SN), represent a promising therapeutic strategy. The glucocorticoid receptor (GR) has been implicated in the neuropathology of PD and modulates numerous neuroinflammatory signaling pathways in the brain. Therefore, we investigated the neuroprotective effects of the novel GR modulator, PT150, in the rotenone mouse model of PD, postulating that inhibition of glial inflammation would protect DAn and reduce accumulation of neurotoxic misfolded ⍺-synuclein protein. C57Bl/6 mice were exposed to 2.5 mg/kg/day rotenone by intraperitoneal injection for 14 days. Upon completion of rotenone dosing, mice were orally treated at day 15 with 30 mg/kg/day or 100 mg/kg/day PT150 in the 14-day post-lesioning incubation period, during which the majority of DAn loss and α-synuclein (α-syn) accumulation occurs. Our results indicate that treatment with PT150 reduced both loss of DAn and microgliosis in the nigrostriatal pathway. Although morphologic features of astrogliosis were not attenuated, PT150 treatment promoted potentially neuroprotective activity in these cells, including increased phagocytosis of hyperphosphorylated α-syn. Ultimately, PT150 treatment reduced the loss of DAn cell bodies in the SN, but not the striatum, and prohibited intra-neuronal accumulation of α-syn. Together, these data indicate that PT150 effectively reduced SN pathology in the rotenone mouse model of PD.

Neuroprotective Efficacy of the Glucocorticoid Receptor Modulator PT150 in the Rotenone Mouse Model of Parkinson's Disease

Parkinson's disease (PD) is the most common neurodegenerative movement disorder worldwide. Current treatments for PD largely center around dopamine replacement therapies and fail to prevent the progression of pathology, underscoring the need for neuroprotective interventions. Approaches that target neuroinflammation, which occurs prior to dopaminergic neuron (DAn) loss in the substantia nigra (SN), represent a promising therapeutic strategy. The glucocorticoid receptor (GR) has been implicated in the neuropathology of PD and modulates numerous neuroinflammatory signaling pathways in the brain. Therefore, we investigated the neuroprotective effects of the novel GR modulator, PT150, in the rotenone mouse model of PD, postulating that inhibition of glial inflammation would protect DAn and reduce accumulation of neurotoxic misfolded ⍺-synuclein protein. C57Bl/6 mice were exposed to 2.5 mg/kg/day rotenone by intraperitoneal injection for 14 days, immediately followed by oral treatment with 30 mg/kg/day or 100 mg/kg/day PT150 in the 14-day post-lesioning incubation period, during which the majority of DAn loss and α-synuclein (α-syn) accumulation occurs. Our results indicate that treatment with PT150 reduced both loss of DAn and microgliosis in the nigrostriatal pathway. Although morphologic features of astrogliosis were not attenuated, PT150 treatment promoted potentially neuroprotective activity in these cells, including increased phagocytosis of hyperphosphorylated α-syn. Ultimately, PT150 treatment reduced the loss of DAn cell bodies in the SN, but not the striatum, and prohibited intra-neuronal accumulation of α-syn. Together, these data indicate that PT150 effectively reduced SN pathology in the rotenone mouse model of PD.

The Giardia lamblia ribosome structure reveals divergence in several biological pathways and the mode of emetine function

Giardia lamblia is a deeply branching protist and a human pathogen. Its unusual biology presents the opportunity to explore conserved and fundamental molecular mechanisms. We determined the structure of the G. lamblia 80S ribosome bound to tRNA, mRNA, and the antibiotic emetine by cryo-electron microscopy, to an overall resolution of 2.49 Å. The structure reveals rapidly evolving protein and nucleotide regions, differences in the peptide exit tunnel, and likely altered ribosome quality control pathways. Examination of translation initiation factor binding sites suggests these interactions are conserved despite a divergent initiation mechanism. Highlighting the potential of G. lamblia to resolve conserved biological principles; our structure reveals the interactions of the translation inhibitor emetine with the ribosome and mRNA, thus providing insight into the mechanism of action for this widely used antibiotic. Our work defines key questions in G. lamblia and motivates future experiments to explore the diversity of eukaryotic gene regulation.

Identification of PARN nuclease activity inhibitors by computational-based docking and high-throughput screening

Poly(A)-specific ribonuclease (PARN) is a 3'-exoribonuclease that removes poly(A) tails from the 3' end of RNAs. PARN is known to deadenylate some ncRNAs, including hTR, Y RNAs, and some miRNAs and thereby enhance their stability by limiting the access of 3' to 5' exonucleases recruited by oligo(A) tails. Several PARN-regulated miRNAs target p53 mRNA, and PARN knockdown leads to an increase of p53 protein levels in human cells. Thus, PARN inhibitors might be used to induce p53 levels in some human tumors and act as a therapeutic strategy to treat cancers caused by repressed p53 protein. Herein, we used computational-based molecular docking and high-throughput screening (HTS) to identify small molecule inhibitors of PARN. Validation with in vitro and cell-based assays, identified 4 compounds, including 3 novel compounds and pyrimidopyrimidin-2-one GNF-7, previously shown to be a Bcr-Abl inhibitor, as PARN inhibitors. These inhibitors can be used as tool compounds and as lead compounds for the development of improved PARN inhibitors.

Nanoarchitecture factors of solid electrolyte interphase formation via 3D nano-rheology microscopy and surface force-distance spectroscopy

The solid electrolyte interphase in rechargeable Li-ion batteries, its dynamics and, significantly, its nanoscale structure and composition, hold clues to high-performing and safe energy storage. Unfortunately, knowledge of solid electrolyte interphase formation is limited due to the lack of in situ nano-characterization tools for probing solid-liquid interfaces. Here, we link electrochemical atomic force microscopy, three-dimensional nano-rheology microscopy and surface force-distance spectroscopy, to study, in situ and operando, the dynamic formation of the solid electrolyte interphase starting from a few 0.1 nm thick electrical double layer to the full three-dimensional nanostructured solid electrolyte interphase on the typical graphite basal and edge planes in a Li-ion battery negative electrode. By probing the arrangement of solvent molecules and ions within the electric double layer and quantifying the three-dimensional mechanical property distribution of organic and inorganic components in the as-formed solid electrolyte interphase layer, we reveal the nanoarchitecture factors and atomistic picture of initial solid electrolyte interphase formation on graphite-based negative electrodes in strongly and weakly solvating electrolytes.

A Novel Glucocorticoid and Androgen Receptor Modulator Reduces Viral Entry and Innate Immune Inflammatory Responses in the Syrian Hamster Model of SARS-CoV-2 Infection

Despite significant research efforts, treatment options for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain limited. This is due in part to a lack of therapeutics that increase host defense to the virus. Replication of SARS-CoV-2 in lung tissue is associated with marked infiltration of macrophages and activation of innate immune inflammatory responses that amplify tissue injury. Antagonists of the androgen (AR) and glucocorticoid (GR) receptors have shown efficacy in models of COVID-19 and in clinical studies because the cell surface proteins required for viral entry, angiotensin converting enzyme 2 (ACE2) and the transmembrane protease, serine 2 (TMPRSS2), are transcriptionally regulated by these receptors. We postulated that the GR and AR modulator, PT150, would reduce infectivity of SARS-CoV-2 and prevent inflammatory lung injury in the Syrian golden hamster model of COVID-19 by down-regulating expression of critical genes regulated through these receptors. Animals were infected intranasally with 2.5 × 104 TCID50/ml equivalents of SARS-CoV-2 (strain 2019-nCoV/USA-WA1/2020) and PT150 was administered by oral gavage at 30 and 100 mg/Kg/day for a total of 7 days. Animals were examined at 3, 5 and 7 days post-infection (DPI) for lung histopathology, viral load and production of proteins regulating the progression of SARS-CoV-2 infection. Results indicated that oral administration of PT150 caused a dose-dependent decrease in replication of SARS-CoV-2 in lung, as well as in expression of ACE2 and TMPRSS2. Lung hypercellularity and infiltration of macrophages and CD4+ T-cells were dramatically decreased in PT150-treated animals, as was tissue damage and expression of IL-6. Molecular docking studies suggest that PT150 binds to the co-activator interface of the ligand-binding domain of both AR and GR, thereby acting as an allosteric modulator and transcriptional repressor of these receptors. Phylogenetic analysis of AR and GR revealed a high degree of sequence identity maintained across multiple species, including humans, suggesting that the mechanism of action and therapeutic efficacy observed in Syrian hamsters would likely be predictive of positive outcomes in patients. PT150 is therefore a strong candidate for further clinical development for the treatment of COVID-19 across variants of SARS-CoV-2.

Substituted pteridinones, pyrimidines, pyrrolopyrimidines, and purines as p90 ribosomal S6 protein kinase-2 (RSK2) inhibitors: Pharmacophore modeling data

The RSK2 kinase is a downstream effector of the Ras/Raf/MEK/ERK pathway that is aberrantly active in a range of cancer types and has been recognized an anticancer target. The inhibition of RSK2 kinase activity would disrupt multiple pro-cancer processes; however, there are few RSK2 inhibitors. The data have been obtained for a series of pteridinone-, pyrimidine-, purine-, and pyrrolopyrimidine-based compounds, developed to establish a structure-activity relationship for RSK inhibition. The compounds were docked into the ATP-binding site of the N-terminal domain of the RSK2 kinase using Glide. The binding conformations of these molecules was then used to generate a set of pharmacophore models to determine the structural requirements for RSK2 inhibition. Through the combination of these models, common features (pharmacophores) can be identified that can inform the development of further small molecule RSK inhibitors. The synthesis and evaluation of the pteridinone- and pyrimidine-based compounds was reported in the related articles: Substituted pteridinones as p90 ribosomal S6 protein kinase (RSK) inhibitors: A structure-activity study (Casalvieri et al., 2020) and Molecular docking of substituted pteridinones and pyrimidines to the ATP-binding site of the N-terminal domain of RSK2 and associated MM/GBSA and molecular field datasets (Casalvieri et al., 2020). [1], [2]. The synthesis and evaluation of the purine- and pyrrolopyrimidine-based compounds was reported in the related research article: N-substituted pyrrolopyrimidines and purines as p90 ribosomal S6 protein kinase-2 (RSK2) inhibitors (Casalvieri et al., 2021) [3].

Systematic optimization of a fragment-based force field against experimental pure-liquid properties considering large compound families: application to oxygen and nitrogen compounds

The CombiFF approach is a workflow for the automated refinement of force-field parameters against experimental condensed-phase data, considering entire classes of organic molecules constructed using a fragment library via combinatorial isomer enumeration. One peculiarity of this approach is that it relies on an electronegativity-equalization scheme to account for induction effects within molecules, with values of the atomic hardness and electronegativity as electrostatic parameters, rather than the partial charges themselves. In a previous article [M. P. Oliveira, M. Andrey, S. R. Rieder, L. Kern, D. F. Hahn, S. Riniker, B. A. C. Horta and P. H. Hünenberger, J. Chem. Theory. Comput. 2020, 16, 7525], CombiFF was introduced and applied to calibrate a GROMOS-compatible united-atom force field for the saturated acyclic (halo-)alkane family. Here, this scheme is employed for the construction of a corresponding force field for saturated acyclic compounds encompassing eight common chemical functional groups involving oxygen and/or nitrogen atoms, namely: ether, aldehyde, ketone, ester, alcohol, carboxylic acid, amine, and amide. Monofunctional as well as homo-polyfunctional compounds are considered. A total of 1712 experimental liquid densities ρliq and vaporization enthalpies ΔHvap concerning 1175 molecules are used for the calibration (339 molecules) and validation (836 molecules) of the 102 non-bonded interaction parameters of the force field. Using initial parameter values based on the GROMOS 2016H66 parameter set, convergence is reached after five iterations. Given access to one processor per simulated system, this operation only requires a few days of wall-clock computing time. After optimization, the root-mean-square deviations from experiment are 29.9 (22.4) kg m-3 for ρliq and 4.1 (5.5) kJ mol-1 for ΔHvap for the calibration (validation) set. Thus, a very good level of agreement with experiment is achieved in terms of these two properties, although the errors are inhomogeneously distributed across the different chemical functional groups.

Precise force-field-based calculations of octanol-water partition coefficients for the SAMPL7 molecules

We predicted water-octanol partition coefficients for the molecules in the SAMPL7 challenge with explicit solvent classical molecular dynamics (MD) simulations. Water hydration free energies and octanol solvation free energies were calculated with a windowed alchemical free energy approach. Three commonly used force fields (AMBER GAFF, CHARMM CGenFF, OPLS-AA) were tested. Special emphasis was placed on converging all simulations, using a criterion developed for the SAMPL6 challenge. In aggregate, over 1000 [Formula: see text]s of simulations were performed, with some free energy windows remaining not fully converged even after 1 [Formula: see text]s of simulation time. Nevertheless, the amount of sampling produced [Formula: see text] estimates with a precision of 0.1 log units or better for converged simulations. Despite being probably as fully sampled as can expected and is feasible, the agreement with experiment remained modest for all force fields, with no force field performing better than 1.6 in root mean squared error. Overall, our results indicate that a large amount of sampling is necessary to produce precise [Formula: see text] predictions for the SAMPL7 compounds and that high precision does not necessarily lead to high accuracy. Thus, fundamental problems remain to be solved for physics-based [Formula: see text] predictions.

N-Substituted pyrrolopyrimidines and purines as p90 ribosomal S6 protein kinase-2 (RSK2) inhibitors

The RSK2 kinase is the downstream effector of the Ras/Raf/MEK/ERK pathway, that is often aberrantly activated in acute myeloid leukemia (AML). Recently, we reported a structure-activity study for BI-D1870, the pan-RSK inhibitor, and identified pteridinones that inhibited cellular RSK2 activity that did not result in concomitant cytotoxicity. In the current study, we developed a series of pyrrolopyrimidines and purines to replace the pteridinone ring of BI-D1870, with a range of N-substituents that extend to the substrate binding site to probe complementary interactions, while retaining the 2,6-difluorophenol-4-amino group to maintain interactions with the hinge domain and the DFG motif. Several compounds inhibited cellular RSK2 activity, and we identified compounds that uncoupled cellular RSK2 inhibition from potent cytotoxicity in the MOLM-13 AML cell line. These N-substituted probes have revealed an opportunity to further examine substituents that extend from the ATP- to the substrate-binding site may confer improved RSK potency and selectivity.

Substituted oxindol-3-ylidenes as AMP-activated protein kinase (AMPK) inhibitors

AMP-activated protein kinase (AMPK) is a central metabolic regulator that promotes cancer growth and survival under hypoxia and plays a role in the maintenance of cancer stem cells. A major challenge to interrogating the potential of targeting AMPK in cancer is the lack of potent and selective small molecule inhibitors. Compound C has been widely used as an AMPK inhibitor, but it lacks potency and has a poor selectivity profile. The multi-kinase inhibitor, sunitinib, has demonstrated potent nanomolar inhibition of AMPK activity and has scope for modification. Here, we have designed and synthesized several series of oxindoles to determine the structural requirements for AMPK inhibition and to improve selectivity. We identified two potent, novel oxindole-based AMPK inhibitors that were designed to interact with the DFG motif in the ATP-binding site of AMPK, this key feature evades interaction with the common recptor tyrosine kinase targets of sunitinib. Cellular engagement of AMPK by these oxindoles was confirmed by the inhibition of phosphorylation of acetyl-CoA carboxylase (ACC), a known substrate of AMPK, in myeloid leukemia cells. Interestingly, although AMPK is highly expressed and activated in K562 cells these oxindole-based AMPK inhibitors did not impact cell viability or result in significant cytotoxicity. Our studies serve as a platform for the further development of oxindole-based AMPK inhibitors with therapeutic potential.

Solvent similarity index

The Solvent Similarity Index (SSI) is a quantitative parameter we introduce for the comparison of the solvation properties of any solvent or solvent mixture. The Surface Site Interaction Model for Liquids at Equilibrium (SSIMPLE) was used to calculate the free energy of solvation of a single Surface Site Interaction Point (SSIP) on a solute. The SSIP representation of molecular surfaces was used to calculate the free energy of solvation for all possible solute polarities, generating a unique solvation profile for any solvent or solvent mixture. Quantitative comparison of the solvation profiles of two solvents was used as the basis for calculating the solvation similarity index. Values of SSI were calculated for all pairwise comparisons of 261 pure solvents at 298 K, and the results were used to classify solvents into groups according to their solvation properties. Applications to understanding the solvation properties of binary solvent mixtures and for identification of alternative solvents are illustrated.

Prediction of octanol-water partition coefficients for the SAMPL6-[Formula: see text] molecules using molecular dynamics simulations with OPLS-AA, AMBER and CHARMM force fields

All-atom molecular dynamics simulations with stratified alchemical free energy calculations were used to predict the octanol-water partition coefficient [Formula: see text] of eleven small molecules as part of the SAMPL6-[Formula: see text] blind prediction challenge using four different force field parametrizations: standard OPLS-AA with transferable charges, OPLS-AA with non-transferable CM1A charges, AMBER/GAFF, and CHARMM/CGenFF. Octanol parameters for OPLS-AA, GAFF and CHARMM were validated by comparing the density as a function of temperature, the chemical potential, and the hydration free energy to experimental values. The partition coefficients were calculated from the solvation free energy for the compounds in water and pure ("dry") octanol or "wet" octanol with 27 mol% water dissolved. Absolute solvation free energies were computed by thermodynamic integration (TI) and the multistate Bennett acceptance ratio with uncorrelated samples from data generated by an established protocol using 5-ns windowed alchemical free energy perturbation (FEP) calculations with the Gromacs molecular dynamics package. Equilibration of sets of FEP simulations was quantified by a new measure of convergence based on the analysis of forward and time-reversed trajectories. The accuracy of the [Formula: see text] predictions was assessed by descriptive statistical measures such as the root mean square error (RMSE) of the data set compared to the experimental values. Discarding the first 1 ns of each 5-ns window as an equilibration phase had a large effect on the GAFF data, where it improved the RMSE by up to 0.8 log units, while the effect for other data sets was smaller or marginally worsened the agreement. Overall, CGenFF gave the best prediction with RMSE 1.2 log units, although for only eight molecules because the current CGenFF workflow for Gromacs does not generate files for certain halogen-containing compounds. Over all eleven compounds, GAFF gave an RMSE of 1.5. The effect of using a mixed water/octanol solvent slightly decreased the accuracy for CGenFF and GAFF and slightly increased it for OPLS-AA. The GAFF and OPLS-AA results displayed a systematic error where molecules were too hydrophobic whereas CGenFF appeared to be more balanced, at least on this small data set.

Mixing states of imidazolium-based ionic liquid, [C4mim][TFSI], with cycloethers studied by SANS, IR, and NMR experiments and MD simulations

The mixing states of an imidazolium-based ionic liquid (IL), 1-butyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([C₄mim][TFSI]), with cycloethers, tetrahydrofuran (THF), 1,4-dioxane (1,4-DIO), and 1,3-dioxane (1,3-DIO), have been clarified on the meso- and microscopic scales using small-angle neutron scattering (SANS), IR, and NMR experiments and molecular dynamics (MD) simulations. SANS profiles of [C₄mim][TFSI]-THF-d₈ and -1,4-DIO-d₈ solutions at various mole fractions x_ML of molecular liquid (ML) have shown that [C₄mim][TFSI] is heterogeneously mixed with THF and 1,4-DIO on the mesoscopic scale, to a high extent in the case of the latter solution. In fact, [C₄mim][TFSI] and 1,4-DIO are not miscible with each other above the 1,4-DIO mole fraction x_1,4-DIO of 0.903, whereas the IL can be mixed with THF over the entire range of THF mole fraction x_THF. The results of IR and ¹H and ¹³C NMR measurements and MD simulations showed that cycloether molecules are more strongly hydrogen-bonded with the imidazolium ring H atoms in the order of THF > 1,3-DIO > 1,4-DIO. Although 1,4-DIO and 1,3-DIO molecules are structural isomers, our results point out that 1,4-DIO cannot be strongly hydrogen-bonded with the ring H atoms. The solvation of [TFSI]^- by cycloethers through the dipole-dipole interaction promotes hydrogen bonding between the ring H atoms and cycloethers. Thus, 1,4-DIO with the lowest dipole moment cannot easily eliminate [TFSI]^- from the imidazolium ring. This results in the weakest hydrogen bonds of 1,4-DIO with the ring H atoms. 2D-NMR of ¹H{¹H} rotating-frame nuclear Overhauser effect spectroscopy (ROESY) showed the interaction of the three cycloethers with the butyl group of [C₄mim]⁺. 1,4-DIO mainly interacts with the butyl group by the dispersion force, whereas THF interacts with the IL by both hydrogen bonding and dispersion force. This leads to the higher heterogeneity of the 1,4-DIO solutions compared to the THF solutions.

Molecular docking of substituted pteridinones and pyrimidines to the ATP-binding site of the N-terminal domain of RSK2 and associated MM/GBSA and molecular field datasets

The data have been obtained for a series of substituted pteridinones and pyrimidines that were developed based on BI-D1870 to establish a structure-activity relationship for RSK inhibition. The 19 compounds, 12 of these with R- and S-isomeric forms, were docked into the ATP-binding site of the N-terminal domain of the RSK2 kinase using Schrodinger Glide. The binding conformations of these molecules and their interactions with RSK2 may inform the development of further small molecule RSK inhibitors. The molecular mechanics energies combined with the generalized Born and surface area continuum solvation (MM-BGSA) method was used to estimate the free energy of binding of the small molecules with RSK2. The molecular field characteristics of the docked confirmations of the inhibitors was examined using Cresset Forge software. The synthesis and evaluation of these compounds was reported in the related research article: Substituted pteridinones as p90 ribosomal S6 protein kinase 2 (RSK2) inhibitors: a structure-activity study (Casalvieri et al., 2020).

Substituted pteridinones as p90 ribosomal S6 protein kinase (RSK) inhibitors: A structure-activity study

The activity of p90 ribosomal S6 kinase 2 (RSK2) has emerged as an attractive target for cancer therapy due to its role in the regulation of diverse cellular processes, such as cell transformation and proliferation. Several pan-RSK inhibitors have been identified with BI-D1870 and the pseudo-analogs LJH685 and LJI308 being the most selective, potent, and frequently used small molecule inhibitors. We designed and synthesized a series of pteridinones and pyrimidines to evaluate the structural features of BI-D1870 that are required for RSK2 inhibition. We have identified inhibitors of RSK2 activity, evaluated their target engagement in cells, and measured their effect on cell viability and cytotoxicity in the MOLM-13 acute myeloid leukemia (AML) cell line. The results of our studies support that RSK2 inhibition can be achieved in MOLM-13 cells without potent cytotoxicity. The structure-activity data from this study will be used as a platform to develop novel RSK2 inhibitors.

Comparison of the umbrella sampling and the double decoupling method in binding free energy predictions for SAMPL6 octa-acid host-guest challenges

We calculate the absolute binding free energies of tetra-methylated octa-acids host-guest systems as a part of the SAMPL6 blind challenge (receipt ID vq30p). We employed two different free energy simulation methods, i.e., the umbrella sampling (US) and double decoupling method (DDM). The US method was used with the weighted histogram analysis method (WHAM) (US-WHAM scheme). In the DDM scheme, Hamiltonian replica-exchange method (HREM) was combined with the Bennett acceptance ratio (BAR) (HREM-BAR scheme). We obtained initial binding poses via molecular docking using GalaxyDock-HG program, which is developed for the SAMPL challenge. The root mean square deviation (RMSD) and the mean absolute deviations (MAD) using US-WHAM scheme were 1.33 and 1.02 kcal/mol, respectively. The MAD was the top among all submissions, however the correlation with respect to experiment was unexceptional. While the RMSD and MAD via HREM-BAR scheme were greater than US-WHAM scheme, (i.e., 2.09 and 1.76 kcal/mol), their correlations were slightly better than US-WHAM. The correlation between the two methods was high. Further discussion on the DDM method can be found in a companion paper by Han et al. (receipt ID 3z83m) in the same issue.

SAMPL6: calculation of macroscopic pKa values from ab initio quantum mechanical free energies

Macroscopic pK_a values were calculated for all compounds in the SAMPL6 blind prediction challenge, based on quantum chemical calculations with a continuum solvation model and a linear correction derived from a small training set. Microscopic pK_a values were derived from the gas-phase free energy difference between protonated and deprotonated forms together with the Conductor-like Polarizable Continuum Solvation Model and the experimental solvation free energy of the proton. pH-dependent microstate free energies were obtained from the microscopic pK_as with a maximum likelihood estimator and appropriately summed to yield macroscopic pK_a values or microstate populations as function of pH. We assessed the accuracy of three approaches to calculate the microscopic pK_as: direct use of the quantum mechanical free energy differences and correction of the direct values for short-comings in the QM solvation model with two different linear models that we independently derived from a small training set of 38 compounds with known pK_a. The predictions that were corrected with the linear models had much better accuracy [root-mean-square error (RMSE) 2.04 and 1.95 pK_a units] than the direct calculation (RMSE 3.74). Statistical measures indicate that some systematic errors remain, likely due to differences in the SAMPL6 data set and the small training set with respect to their interactions with water. Overall, the current approach provides a viable physics-based route to estimate macroscopic pK_a values for novel compounds with reasonable accuracy.

Ligandbook: an online repository for small and drug-like molecule force field parameters

Summary

Ligandbook is a public database and archive for force field parameters of small and drug-like molecules. It is a repository for parameter sets that are part of published work but are not easily available to the community otherwise. Parameter sets can be downloaded and immediately used in molecular dynamics simulations. The sets of parameters are versioned with full histories and carry unique identifiers to facilitate reproducible research. Text-based search on rich metadata and chemical substructure search allow precise identification of desired compounds or functional groups. Ligandbook enables the rapid set up of reproducible molecular dynamics simulations of ligands and protein-ligand complexes.

Availability and Implementation

Ligandbook is available online at https://ligandbook.org and supports all modern browsers. Parameters can be searched and downloaded without registration, including access through a programmatic RESTful API. Deposition of files requires free user registration. Ligandbook is implemented in the PHP Symfony2 framework with TCL scripts using the CACTVS toolkit.

Supplementary information

Supplementary data are available at Bioinformatics online.

Bayesian Model Averaging for Ensemble-Based Estimates of Solvation-Free Energies

This paper applies the Bayesian Model Averaging statistical ensemble technique to estimate small molecule solvation free energies. There is a wide range of methods available for predicting solvation free energies, ranging from empirical statistical models to ab initio quantum mechanical approaches. Each of these methods is based on a set of conceptual assumptions that can affect predictive accuracy and transferability. Using an iterative statistical process, we have selected and combined solvation energy estimates using an ensemble of 17 diverse methods from the fourth Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) blind prediction study to form a single, aggregated solvation energy estimate. Methods that possess minimal or redundant information are pruned from the ensemble and the evaluation process repeats until aggregate predictive performance can no longer be improved. We show that this process results in a final aggregate estimate that outperforms all individual methods by reducing estimate errors by as much as 91% to 1.2 kcal mol^-1 accuracy. This work provides a new approach for accurate solvation free energy prediction and lays the foundation for future work on aggregate models that can balance computational cost with prediction accuracy.

Absolute binding free energies for octa-acids and guests in SAMPL5 : Evaluating binding free energies for octa-acid and guest complexes in the SAMPL5 blind challenge

As part of the SAMPL5 blind prediction challenge, we calculate the absolute binding free energies of six guest molecules to an octa-acid (OAH) and to a methylated octa-acid (OAMe). We use the double decoupling method via thermodynamic integration (TI) or Hamiltonian replica exchange in connection with the Bennett acceptance ratio (HREM-BAR). We produce the binding poses either through manual docking or by using GalaxyDock-HG, a docking software developed specifically for this study. The root mean square deviations for our most accurate predictions are 1.4 kcal mol-1 for OAH with TI and 1.9 kcal mol-1 for OAMe with HREM-BAR. Our best results for OAMe were obtained for systems with ionic concentrations corresponding to the ionic strength of the experimental solution. The most problematic system contains a halogenated guest. Our attempt to model the σ-hole of the bromine using a constrained off-site point charge, does not improve results. We use results from molecular dynamics simulations to argue that the distinct binding affinities of this guest to OAH and OAMe are due to a difference in the flexibility of the host. We believe that the results of this extensive analysis of host-guest complexes will help improve the protocol used in predicting binding affinities for larger systems, such as protein-substrate compounds.

Absolute binding free energy calculations of CBClip host-guest systems in the SAMPL5 blind challenge

Herein, we report the absolute binding free energy calculations of CBClip complexes in the SAMPL5 blind challenge. Initial conformations of CBClip complexes were obtained using docking and molecular dynamics simulations. Free energy calculations were performed using thermodynamic integration (TI) with soft-core potentials and Bennett's acceptance ratio (BAR) method based on a serial insertion scheme. We compared the results obtained with TI simulations with soft-core potentials and Hamiltonian replica exchange simulations with the serial insertion method combined with the BAR method. The results show that the difference between the two methods can be mainly attributed to the van der Waals free energies, suggesting that either the simulations used for TI or the simulations used for BAR, or both are not fully converged and the two sets of simulations may have sampled difference phase space regions. The penalty scores of force field parameters of the 10 guest molecules provided by CHARMM Generalized Force Field can be an indicator of the accuracy of binding free energy calculations. Among our submissions, the combination of docking and TI performed best, which yielded the root mean square deviation of 2.94 kcal/mol and an average unsigned error of 3.41 kcal/mol for the ten guest molecules. These values were best overall among all participants. However, our submissions had little correlation with experiments.

Prediction of cyclohexane-water distribution coefficients for the SAMPL5 data set using molecular dynamics simulations with the OPLS-AA force field

All-atom molecular dynamics simulations were used to predict water-cyclohexane distribution coefficients [Formula: see text] of a range of small molecules as part of the SAMPL5 blind prediction challenge. Molecules were parameterized with the transferable all-atom OPLS-AA force field, which required the derivation of new parameters for sulfamides and heterocycles and validation of cyclohexane parameters as a solvent. The distribution coefficient was calculated from the solvation free energies of the compound in water and cyclohexane. Absolute solvation free energies were computed by an established protocol using windowed alchemical free energy perturbation with thermodynamic integration. This protocol resulted in an overall root mean square error in [Formula: see text] of almost 4 log units and an overall signed error of -3 compared to experimental data. There was no substantial overall difference in accuracy between simulating in NVT and NPT ensembles. The signed error suggests a systematic error but the experimental [Formula: see text] data on their own are insufficient to uncover the source of this error. Preliminary work suggests that the major source of error lies in the hydration free energy calculations.

Blinded predictions of host-guest standard free energies of binding in the SAMPL5 challenge

In the context of the SAMPL5 blinded challenge standard free energies of binding were predicted for a dataset of 22 small guest molecules and three different host molecules octa-acids (OAH and OAMe) and a cucurbituril (CBC). Three sets of predictions were submitted, each based on different variations of classical molecular dynamics alchemical free energy calculation protocols based on the double annihilation method. The first model (model A) yields a free energy of binding based on computed free energy changes in solvated and host-guest complex phases; the second (model B) adds long range dispersion corrections to the previous result; the third (model C) uses an additional standard state correction term to account for the use of distance restraints during the molecular dynamics simulations. Model C performs the best in terms of mean unsigned error for all guests (MUE [Formula: see text]-95 % confidence interval) for the whole data set and in particular for the octa-acid systems (MUE [Formula: see text]). The overall correlation with experimental data for all models is encouraging ([Formula: see text]). The correlation between experimental and computational free energy of binding ranks as one of the highest with respect to other entries in the challenge. Nonetheless the large MUE for the best performing model highlights systematic errors, and submissions from other groups fared better with respect to this metric.

Mechanistic insights into mode of action of rice allene oxide synthase on hydroxyperoxides: An intermediate step in herbivory-induced jasmonate pathway

Various types of oxygenated fatty acids termed 'oxylipins' are involved in plant response to herbivory. Oxylipins like jasmonic acid (JA) and green leafy volatiles (GLVs) are formed by the action of enzymes like allene oxide synthase (AOS) and hydroxyperoxide lyase (HPL) respectively. In this study, we focus on AOS of Oryza sativa sb. Japonica, that interact with 9- and 13- hydroxyperoxides to produce intermediates of jasmonate pathway and compare it with rice HPL that yields GLVs. We attempt to elucidate the interaction pattern by computational docking protocols keeping the Arabidopsis AOS system as the reference model system. Both 9-hydroxyperoxide and 13-hydroxyperoxide fit into the active site of AOS completely with Phe347, Phe92, Ile463, Val345, and Asn278 being the common interacting residues. Phe347 and Phe92 were mutated with Leucine and docked again with the hydroxyperoxides. The Phe347→Leu347 mutant showed a different mode of action than AOS-hydroxyperoxide complex with Trp413 in direct bonding with the OOH group of 9-hydroxyperoxide. The loss of Lys88-OOH interaction in 13-hydroxyperoxide and loss-of-interaction of Leu347 indicated the importance of Phe347 residue in hydroxyperoxide catalysis. The second mutant Phe92→Leu92 also shows a very different interaction pattern with 13-hydroxyperoxide but not with 9-hydroxyperoxide.Therefore, it can be concluded that Phe347 is more crucial for AOS functionality than Phe92. The aromatic ring of a Phenylalanine residue is important for catalysis and its mutation affects the binding of the two ligands. Another important residue is Asn278 which is an important part of the AOS catalytic site for maintaining stability and can be compared with the Arabidopsis AOS residue Asn321. Lastly, the interaction of HPL with these two derivatives involves Leu363 residue instead of Phe347 and thus, validating the importance of Phe→Leu substitution to be the reason of different modes of action that result in completely different products from same substrates.

A WEE1 Inhibitor Analog of AZD1775 Maintains Synergy with Cisplatin and Demonstrates Reduced Single-Agent Cytotoxicity in Medulloblastoma Cells

The current treatment for medulloblastoma includes surgical resection, radiation, and cytotoxic chemotherapy. Although this approach has improved survival rates, the high doses of chemotherapy required for clinical efficacy often result in lasting neurocognitive defects and other adverse events. Therefore, the development of chemosensitizing agents that allow dose reductions of cytotoxic agents, limiting their adverse effects but maintaining their clinical efficacy, would be an attractive approach to treat medulloblastoma. We previously identified WEE1 kinase as a new molecular target for medulloblastoma from an integrated genomic analysis of gene expression and a kinome-wide siRNA screen of medulloblastoma cells and tissue. In addition, we demonstrated that WEE1 prevents DNA damage-induced cell death by cisplatin and that the WEE1 inhibitor AZD1775 displays synergistic activity with cisplatin. AZD1775 was developed as a WEE1 inhibitor from an initial hit from a high-throughput screen. However, given the lack of structure-activity data for AZD1775, we developed a small series of analogs to determine the requirements for WEE1 inhibition and further examine the effects of WEE1 inhibition in medulloblastoma. Interestingly, the compounds that inhibited WEE1 in the same nanomolar range as AZD1775 had significantly reduced single-agent cytotoxicity compared with AZD1775 and displayed synergistic activity with cisplatin in medulloblastoma cells. The potent cytotoxicity of AZD1775, unrelated to WEE1 inhibition, may result in dose-limiting toxicities and exacerbate adverse effects; therefore, WEE1 inhibitors that demonstrate low cytotoxicity could be dosed at higher concentrations to chemosensitize the tumor and potentiate the effect of DNA-damaging agents such as cisplatin.

Fragment based group QSAR and molecular dynamics mechanistic studies on arylthioindole derivatives targeting the α-β interfacial site of human tubulin

BACKGROUND

A number of microtubule disassembly blocking agents and inhibitors of tubulin polymerization have been elements of great interest in anti-cancer therapy, some of them even entering into the clinical trials. One such class of tubulin assembly inhibitors is of arylthioindole derivatives which results in effective microtubule disorganization responsible for cell apoptosis by interacting with the colchicine binding site of the β-unit of tubulin close to the interface with the α unit. We modelled the human tubulin β unit (chain D) protein and performed docking studies to elucidate the detailed binding mode of actions associated with their inhibition. The activity enhancing structural aspects were evaluated using a fragment-based Group QSAR (G-QSAR) model and was validated statistically to determine its robustness. A combinatorial library was generated keeping the arylthioindole moiety as the template and their activities were predicted.

RESULTS

The G-QSAR model obtained was statistically significant with r2 value of 0.85, cross validated correlation coefficient q2 value of 0.71 and pred_r2 (r2 value for test set) value of 0.89. A high F test value of 65.76 suggests robustness of the model. Screening of the combinatorial library on the basis of predicted activity values yielded two compounds HPI (predicted pIC50 = 6.042) and MSI (predicted pIC50 = 6.001) whose interactions with the D chain of modelled human tubulin protein were evaluated in detail. A toxicity evaluation resulted in MSI being less toxic in comparison to HPI.

CONCLUSIONS

The study provides an insight into the crucial structural requirements and the necessary chemical substitutions required for the arylthioindole moiety to exhibit enhanced inhibitory activity against human tubulin. The two reported compounds HPI and MSI showed promising anti cancer activities and thus can be considered as potent leads against cancer. The toxicity evaluation of these compounds suggests that MSI is a promising therapeutic candidate. This study provided another stepping stone in the direction of evaluating tubulin inhibition and microtubule disassembly degeneration as viable targets for development of novel therapeutics against cancer.