Identification of anti-pathogenic activity among in silico predicted small-molecule inhibitors of Pseudomonas aeruginosa LasR or nitric oxide reductase (NOR)

Introduction: Antibiotic-resistant Pseudomonas aeruginosa strains cause considerable morbidity and mortality globally. Identification of novel targets in this notorious pathogen is urgently warranted to facilitate discovery of new anti-pathogenic agents against it. This study attempted to identify small-molecule inhibitors of two important proteins LasR and nitric oxide reductase (NOR) in P. aeruginosa. ‘Las’ system can be said to be the ‘master’ regulator of quorum sensing in P. aeruginosa, whose receptor protein is LasR. Similarly, NOR is crucial to detoxification of reactive nitrogen species. Methods: In silico identification of potential LasR or NOR inhibitors was attempted through a virtual screening platform AtomNet® to obtain a final subset of <100 top scoring compounds. These compounds were evaluated for their in vivo anti-pathogenic activity by challenging the model host Caenorhabditis elegans with P. aeruginosa in the presence or absence of test compounds. Survival of the worm population in 24-well assay plates was monitored over a period of 5 days microscopically. Results: Of the 96 predicted LasR inhibitors, 11 exhibited anti-Pseudomonas activity (23%-96% inhibition of bacterial virulence as per third-day end-point) at 25-50 µg/mL. Of the 85 predicted NOR inhibitors, 8 exhibited anti-Pseudomonas activity (40%-85% inhibition of bacterial virulence as per second-day end-point) at 25-50 µg/mL. Conclusion: Further investigation on molecular mode of action of compounds found active in this study is warranted. Virtual screening can be said to be a useful tool in narrowing down the list of compounds requiring actual wet-lab screening, saving considerable time and efforts for drug discovery

Prospectus, September 19, 1979

PARKLAND--A KING\u27S PALACE; Student elections lacks voters, candidates, and issues; Parkland College Results of Student Government Election Sept. 12, 13, 1979; Bad Co.: not much fantasy; No record for PC; U.S. productivity down; Sigma Theta Phi: the rush is on; Pro Kennedy group holds first meeting: Notice; WPCD: African affairs needed; Inventory Lists; Parkland Art Program sponsors St. Louis trip; PC offers music; Goldrush has new life; \u27Forum\u27 talks stugo and drinking age; All-Comers pulls surprises; Classifeds; Otrabanda comes to PC; Last Chance to Sign Up for Student Health Insurance; Seven fare well in Freddy; Fast Freddy Contest; Crowd at presentation; U.S. table tennis getting popular; Spikers hopes are high; Elam strides toward victory; Parkland Women\u27s Volleyball Rosterhttps://spark.parkland.edu/prospectus_1979/1012/thumbnail.jp

Neutrophil Elastase Promotes Interleukin-1 beta Secretion from Human Coronary Endothelium

The endothelium is critically involved in the pathogenesis of atherosclerosis by producing pro-inflammatory mediators, including IL-1β. Coronary arteries from patients with ischemic heart disease express large amounts of IL-1β in the endothelium. However, the mechanism by which endothelial cells (ECs) release IL-1β remains to be elucidated. We investigated neutrophil elastase (NE), a potent serine protease detected in vulnerable areas of human carotid plaques, as a potential “trigger” for IL-1β processing and release. This study tested the hypothesis that NE potentiates the processing and release of IL-1β from human coronary endothelium. We found that NE cleaves the pro-isoform of IL-1β in ECs and causes significant secretion of bioactive IL-1β via extracellular vesicles. This release was attenuated significantly by inhibition of neutrophil elastase but not caspase-1. Transient increases in intracellular Ca2+ levels were observed prior to secretion. Inside ECs, and after NE treatment only, IL-1β was detected within LAMP-1-positive multivesicular bodies. The released vesicles contained bioactive IL-1β. In vivo, in experimental atherosclerosis, NE was detected in mature atherosclerotic plaques, predominantly in the endothelium, alongside IL-1β. This study reveals a novel mechanistic link between NE expression in atherosclerotic plaques and concomitant pro-inflammatory bioactive IL-1β secretion from ECs. This could reveal additional potential anti-IL-1β therapeutic targets and provide further insights into the inflammatory process by which vascular disease develops

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Accounting for apparent deviations between calorimetric and van't Hoff enthalpies

BackgroundIn theory, binding enthalpies directly obtained from calorimetry (such as ITC) and the temperature dependence of the binding free energy (van't Hoff method) should agree. However, previous studies have often found them to be discrepant.MethodsExperimental binding enthalpies (both calorimetric and van't Hoff) are obtained for two host-guest pairs using ITC, and the discrepancy between the two enthalpies is examined. Modeling of artificial ITC data is also used to examine how different sources of error propagate to both types of binding enthalpies.ResultsFor the host-guest pairs examined here, good agreement, to within about 0.4kcal/mol, is obtained between the two enthalpies. Additionally, using artificial data, we find that different sources of error propagate to either enthalpy uniquely, with concentration error and heat error propagating primarily to calorimetric and van't Hoff enthalpies, respectively.ConclusionsWith modern calorimeters, good agreement between van't Hoff and calorimetric enthalpies should be achievable, barring issues due to non-ideality or unanticipated measurement pathologies. Indeed, disagreement between the two can serve as a flag for error-prone datasets. A review of the underlying theory supports the expectation that these two quantities should be in agreement.General significanceWe address and arguably resolve long-standing questions regarding the relationship between calorimetric and van't Hoff enthalpies. In addition, we show that comparison of these two quantities can be used as an internal consistency check of a calorimetry study

Evaluating Force Field Performance in Thermodynamic Calculations of Cyclodextrin Host–Guest Binding: Water Models, Partial Charges, and Host Force Field Parameters

Computational prediction of noncovalent binding free energies with methods based on molecular mechanical force fields has become increasingly routine in drug discovery projects, where they promise to speed the discovery of small molecule ligands to bind targeted proteins with high affinity. Because the reliability of free energy methods still has significant room for improvement, new force fields, or modifications of existing ones, are regularly introduced with the aim of improving the accuracy of molecular simulations. However, comparatively little work has been done to systematically assess how well force fields perform, particularly in relation to the calculation of binding affinities. Hardware advances have made these calculations feasible, but comprehensive force field assessments for protein–ligand sized systems still remain costly. Here, we turn to cyclodextrin host–guest systems, which feature many hallmarks of protein–ligand binding interactions but are generally much more tractable due to their small size. We present absolute binding free energy and enthalpy calculations, using the attach-pull-release (APR) approach, on a set of 43 cyclodextrin-guest pairs for which experimental ITC data are available. The test set comprises both α- and β-cyclodextrin hosts binding a series of small organic guests, each with one of three functional groups: ammonium, alcohol, or carboxylate. Four water models are considered (TIP3P, TIP4Pew, SPC/E, and OPC), along with two partial charge assignment procedures (RESP and AM1-BCC) and two cyclodextrin host force fields. The results suggest a complex set of considerations when choosing a force field for biomolecular simulations. For example, some force field combinations clearly outperform others at the binding enthalpy calculations but not for the binding free energy. Additionally, a force field combination which we expected to be the worst performer gave the most accurate binding free energies – but the least accurate binding enthalpies. The results have implications for the development of improved force fields, and we propose this test set, and potential future elaborations of it, as a powerful validation suite to evaluate new force fields and help guide future force field development

Sample calculation using protein APR

<p>Sample calculation using the protein attach-pull-release (APR) method on the BZT-7 ligand to the BRD4 first bromodomain, with the SPC/E water model. Instructions for the automatic creation of the system are included in the automated.bash script in the ./Base-SPC/ folder, and the ./BZT-7-SPC/ folder contains the sample calculation. To obtain the binding free energies from the simulations using MBAR, instructions can be found in the ./Base-SPC/analysis/get-results.bash script. </p

Predicting binding free energies: Frontiers and benchmarks (a perpetual review)

Binding free energy calculations based on molecular simulations provide predicted affinities for biomolecular complexes.These calculations begin with a detailed description of a system, including its chemical composition and the interactions between its components.Simulations of the system are then used to compute thermodynamic information, such as binding affinities.Because of their growing promise for guiding molecular design, these calculations have recently begun to see widespread applications in early stage drug discovery.However, many challenges remain to make them a robust and reliable tool.&nbsp;Here, we highlight key challenges facing these calculations, describe known examples of these challenges, and call for the designation of standard community benchmark test systems that will help the research community generate and evaluate progress.In our view, progress will require careful assessment and evaluation of new methods, force fields, and modeling innovations on well-characterized benchmark systems, and we lay out our vision for how this can be achieved.&nbsp; &nbsp;This repository relates to the perpetual review (definition) paper called "Predicting binding free energies: Frontiers and benchmarks" by David L. Mobley, Germano Heinzelmann and Michael K. Gilson. Its focus is benchmark sets for binding free energy calculations, including the perpetual review paper, but also all things relating to benchmark sets for free energy calculations. This includes discussion, datasets, and standards for datasets and data deposition.&nbsp; &nbsp;This work is posted with permission from the Annual Review of Biophysics, Volume 46 © 2017 by Annual Reviews. Only the Annual Reviews version of the work is peer reviewed; versions posted here are effectively preprints updated at the authors' discretion. The right to create derivative works (exercised here) is also exercised with permission from the Annual Review of Biophysics, Volume 46 © 2017 by Annual Reviews, http://www.annualreviews.org/ &nbsp; &nbsp;Updated versions of this work are maintained at github.com/mobleylab/benchmarksets and this eScholarship archive serves to archive release versions of the work

Bind3P: Optimization of a Water Model with Host-Guest Binding Data

We report a water model, Bind3P (Version 0.1), which was obtained by using sensitivity analysis to readjust the Lennard-Jones parameters of the TIP3P model against experimental binding free energies for six host-guest systems, along with pure liquid properties. Tests of Bind3P against >100 experimental binding free energies and enthalpies for host-guest systems distinct from the training set show a consistent drop in the mean signed error, relative to matched calculations with TIP3P. Importantly, Bind3P also yields some improvement in the hydration free energies of small organic molecules, and preserves the accuracy of bulk water properties, such as density and the heat of vaporization. The same approach can be applied to more sophisticated water models that can better represent pure water properties. These results lend further support to concept of integrating host-guest binding data into force field parameterization