A quantitative systems pharmacology workflow toward optimal design and biomarker stratification of atopic dermatitis clinical trials

BACKGROUND

The development of atopic dermatitis (AD) drugs is challenged by many disease phenotypes and trial design options, which are hard to explore experimentally.

OBJECTIVE

We aimed to optimize AD trial design using simulations.

METHODS

We constructed a quantitative systems pharmacology model of AD and standard of care (SoC) treatments and generated a phenotypically diverse virtual population whose parameter distribution was derived from known relationships between AD biomarkers and disease severity and calibrated using disease severity evolution under SoC regimens.

RESULTS

We applied this workflow to the immunomodulator OM-85, currently being investigated for its potential use in AD, and calibrated the investigational treatment model with the efficacy profile of an existing trial (thereby enriching it with plausible marker levels and dynamics). We assessed the sensitivity of trial outcomes to trial protocol and found that for this particular example the choice of end point is more important than the choice of dosing regimen and patient selection by model-based responder enrichment could increase the expected effect size. A global sensitivity analysis revealed that only a limited subset of baseline biomarkers is needed to predict the drug response of the full virtual population.

CONCLUSIONS

This AD quantitative systems pharmacology workflow built around knowledge of marker-severity relationships as well as SoC efficacy can be tailored to specific development cases to optimize several trial protocol parameters and biomarker stratification and therefore has promise to become a powerful model-informed AD drug development and personalized medicine tool.

In Silico and Chromatographic Methods for Analysis of Biotransformation of Prospective Neuroprotective Pyrrole-Based Hydrazone in Isolated Rat Hepatocytes

In the current study, chromatographic and in silico techniques were applied to investigate the biotransformation of ethyl 5-(4-bromophenyl)-1-(2-(2-(2-hydroxybenzylidene) hydrazinyl)-2-oxoethyl)-2-methyl-1H-pyrrole-3-carboxylate (11b) in hepatocytic media. The initial chromatographic procedure was based on the employment of the conventional octadecyl stationary phase method for estimation of the chemical stability. Subsequently, a novel and rapid chromatographic approach based on a phenyl-hexyl column was developed, aiming to separate the possible metabolites. Both methods were performed on a Dionex 3000 ThermoScientific (ACM 2, Sofia, Bulgaria) device equipped with a diode array detector set up at 272 and 279 nm for analytes detection. An acetonitrile: phosphate buffer of pH 3.5: methanol (17:30:53 v/v/v) was eluted isocratically as a mobile phase with a 1 mL/min flow rate. A preliminary purification from the biological media was achieved by protein precipitation with methanol. A validation procedure was carried out, where the method was found to correspond to all ICH (Q2) and M10 set criteria. Additionally, an in silico-based approach with the online server BioTransformer 3.0 was applied in an attempt to predict the possible metabolites of the title compound 11b. It was hypothesized that four CYP450 isoforms (1A2, 2C9, 3A4, and 2C8) were involved in the phase I metabolism, resulting in the formation of 12 metabolites. Moreover, docking studies were conducted to evaluate the formation of stable complexes between 11b and the aforementioned isoforms. The obtained data indicated three metabolites as the most probable products, two of which (M9_11b and M10_11b) were synthesized by a classical approach for verification. Finally, liquid chromatography with a mass detector was implemented for comprehensive and summarized analysis, and the obtained results revealed that the metabolism of the 11b proceeds possibly with the formation of glucuronide and glycine conjugate of M11_11b.

Novel Lactone-Based Insecticides and Drosophila suzukii Management: Synthesis, Potential Action Mechanisms and Selectivity for Non-Target Parasitoids

Drosophila suzukii, an invasive insect pest, poses a significant threat to various fruit crops. The use of broad-spectrum insecticides to control this pest can reduce the effectiveness of biological control agents, such as the parasitoid Trichopria anastrephae. Here, we evaluated the toxicity of newly synthesized lactone derivatives on D. suzukii and their selectivity towards T. anastrephae. We used in silico approaches to identify potential targets from the most promising molecules in the D. suzukii nervous system and to understand potential differences in susceptibilities between D. suzukii and its parasitoid. Of the nine molecules tested, (rac)-8 and compound 4 demonstrated efficacy against the fly. Exposure to the estimated LC90 of (rac)-8 and compound 4 resulted in a mortality rate of less than 20% for T. anastrephae without impairing the parasitoid's functional parasitism. The in silico predictions suggest that (rac)-8 and compound 4 target gamma amino butyric acid (GABA) receptors and transient receptor potential (TRP) channels of D. suzukii. However, only the reduced interaction with TRP channels in T. anastrephae demonstrated a potential reason for the selectivity of these compounds on the parasitoid. Our findings suggest the potential for integrating (rac)-8 and compound 4 into D. suzukii management practices.

Investigating the adverse outcome pathways (AOP) of neurotoxicity induced by DBDPE with a combination of in vitro and in silico approaches

Current studies have shown an association between DBDPE and neurotoxicity. In this study, the adverse outcome pathway (AOP) and mechanistic analysis of DBDPE-induced neurotoxicity were explored by a combination of in vitro and in silico approaches in SK-N-SH cells. DBDPE-induced oxidative stress caused DNA strand breaks, resulting in the activation of poly (ADP-ribose) (PAR) polymerase-1 (PARP-1). Activation of PARP1 could cause toxic damage in various organ systems, especially in the nervous system. DBDPE-induced apoptosis via the caspase-dependent intrinsic mitochondrial pathway and the PARP1-dependent pathway. Activation of PARP1 by DBDPE was deemed the initiating event, thereby affecting the key downstream biochemical events (e.g., ROS production, DNA damage, membrane potential changes, and ATP reduction), which induced apoptosis. Furthermore, excessive activation of PARP1 was accompanied by the translocation of the apoptosis-inducing factor (AIF), which was associated with PARP1-dependent cell death. The inhibition of PARP1 by PJ34 reduced DBDPE-induced apoptosis and maintained cellular ATP levels. PJ34 also prevented the translocation of AIF from the mitochondria to the nucleus. These findings improve the understanding of the mechanism of DBDPE-induced neurotoxic effects and provide a theoretical basis for the ecological risk of DBDPE.

Recent Fabrication Methods to Produce Polymer-Based Drug Delivery Matrices (Experimental and In Silico Approaches)

The study of novel drug delivery systems represents one of the frontiers of the biomedical research area. Multi-disciplinary scientific approaches combining traditional or engineered technologies are used to provide major advances in improving drug bioavailability, rate of release, cell/tissue specificity and therapeutic index. Biodegradable and bio-absorbable polymers are usually the building blocks of these systems, and their copolymers are employed to create delivery components. For example, poly (lactic acid) or poly (glycolic acid) are often used as bricks for the production drug-based delivery systems as polymeric microparticles (MPs) or micron-scale needles. To avoid time-consuming empirical approaches for the optimization of these formulations, in silico-supported models have been developed. These methods can predict and tune the release of different drugs starting from designed combinations. Starting from these considerations, this review has the aim of investigating recent approaches to the production of polymeric carriers and the combination of in silico and experimental methods as promising platforms in the biomedical field.

A Revisit to the Research Updates of Drugs, Vaccines, and Bioinformatics Approaches in Combating COVID-19 Pandemic

A new strain of coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for the coronavirus disease 2019 (COVID-19) pandemic was first detected in the city of Wuhan in Hubei province, China in late December 2019. To date, more than 1 million deaths and nearly 57 million confirmed cases have been recorded across 220 countries due to COVID-19, which is the greatest threat to global public health in our time. Although SARS-CoV-2 is genetically similar to other coronaviruses, i.e., SARS and Middle East respiratory syndrome coronavirus (MERS-CoV), no confirmed therapeutics are yet available against COVID-19, and governments, scientists, and pharmaceutical companies worldwide are working together in search for effective drugs and vaccines. Repurposing of relevant therapies, developing vaccines, and using bioinformatics to identify potential drug targets are strongly in focus to combat COVID-19. This review deals with the pathogenesis of COVID-19 and its clinical symptoms in humans including the most recent updates on candidate drugs and vaccines. Potential drugs (remdesivir, hydroxychloroquine, azithromycin, dexamethasone) and vaccines [mRNA-1273; measles, mumps and rubella (MMR), bacille Calmette-Guérin (BCG)] in human clinical trials are discussed with their composition, dosage, mode of action, and possible release dates according to the trial register of US National Library of Medicines (clinicaltrials.gov), European Union (clinicaltrialsregister.eu), and Chinese Clinical Trial Registry (chictr.org.cn) website. Moreover, recent reports on in silico approaches like molecular docking, molecular dynamics simulations, network-based identification, and homology modeling are included, toward repurposing strategies for the use of already approved drugs against newly emerged pathogens. Limitations of effectiveness, side effects, and safety issues of each approach are also highlighted. This review should be useful for the researchers working to find out an effective strategy for defeating SARS-CoV-2.

In silico and in vitro approaches to evaluate the bioactivity of Cassia auriculata L extracts

The present study is an attempt to evaluate the in vitro anti-inflammatory and in silico anticancer potentials of the plant Cassia auriculata (CA). The aerial parts of CA were subjected to solvent extraction, and the extracts were fractionised by gas chromatography and mass spectrometry analysis for its phytochemical content. The antiinflammatory activity of the extracts were confirmed by the IC50 value of 125.02 µg/ml for red blood cell membrane stabilisation and 195.7 µg/ml for inhibition of protein denaturation activity. The interaction of bioactive compounds of CA ethanol extract with target protein was predicted through molecular docking studies, serine/threonine-protein kinase B (AKT1), responsible for development and progression of lung cancer using AutoDock tools. Extensive studies have been carried out on a range of kinase inhibitors targeting Akt, but obtaining promising results is a challenge yet due to its toxicity and resistance issues. Yohimbine, undecanoic acid 10-methyl-ethyl ester and chrysin significantly bind to the target protein with least binding energy. Hence, the present paper establishes the anti-inflammatory and anticancer capacities of CA ethanol extract as an alternative to the existing therapeutic approach to inflammation and cancer through a systematic in vitro and in silico approaches supplementing the findings.

Suramin could block the activity of Arabinono-1, 4-lactone oxidase enzyme from Leishmania donovani: structure-based screening and molecular dynamics analyses

BACKGROUND

Leishmania donovani, a parasitic protozoan causing visceral leishmaniasis, can lead to a dangerous and often fatal disease in humans. Current treatment for leishmaniasis may have severe side effects, low efficacy and high cost, hence an immediate need for new efficient drugs is essential. Arabinono-1, 4-lactone oxidase enzyme from Leishmania donovani (LdALO), which catalyzes the last step of the ascorbate biosynthesis pathway, has been considered as a potential target for antileishmanial drugs design.

METHODS

The current study was performed with an in silico approach to predict novel inhibitory molecules against the LdALO enzyme. Various modeling and refinement processes were employed to obtain a reliable 3D structure.

RESULTS

The best LdALO model with the highest qualitative model energy analysis score was predicted by the Robetta server and subsequently refined by 3D refine and ModLoop servers. The high quality of the final LdALO model was confirmed using model assessment software. Based on docking analysis results, we predicted 10 inhibitory molecules of a US Food and Drug Administration-approved library, with appropriate criteria regarding energy binding and interaction with the main functionally active sites of LdALO, indicating that they could be significant targets for further drug design investigations against L. donovani.

CONCLUSION

Suramin is used to treat the first stage of African sleeping sickness and its mechanism of action is unknown. Our results showed that suramin was the best-predicted inhibitor compound for LdALO enzyme activity.

Analysing the Structural Effect of Point Mutations of Cytotoxic Necrotizing Factor 1 (CNF1) on Lu/BCAM Adhesion Glycoprotein Association

Cytotoxic Necrotizing Factor 1 (CNF1) was identified in 1983 as a protein toxin produced by certain pathogenic strains of Escherichia coli. Since then, numerous studies have investigated its particularities. For instance, it is associated with the single chain AB-toxin family, and can be divided into different functional and structural domains, e.g., catalytic and transmembrane domain and interaction sites. A few years ago, the identification of the Lutheran (Lu) adhesion glycoprotein/basal cell adhesion molecule (BCAM) as a cellular receptor for CNF1 provided new insights into the adhesion process of CNF1. Very recently, the Ig-like domain 2 of Lu/BCAM was confirmed as the main interaction site using protein-protein interaction and competition studies with various different mutants. Here, I present in silico approaches that precisely explain the impact of these mutations, leading to a better explanation of these experimental studies. These results can be used in the development of future antitoxin strategies.

Emerging approaches in predictive toxicology

Predictive toxicology plays an important role in the assessment of toxicity of chemicals and the drug development process. While there are several well-established in vitro and in vivo assays that are suitable for predictive toxicology, recent advances in high-throughput analytical technologies and model systems are expected to have a major impact on the field of predictive toxicology. This commentary provides an overview of the state of the current science and a brief discussion on future perspectives for the field of predictive toxicology for human toxicity. Computational models for predictive toxicology, needs for further refinement and obstacles to expand computational models to include additional classes of chemical compounds are highlighted. Functional and comparative genomics approaches in predictive toxicology are discussed with an emphasis on successful utilization of recently developed model systems for high-throughput analysis. The advantages of three-dimensional model systems and stem cells and their use in predictive toxicology testing are also described.