In Silico Approaches for Predicting Adme Properties

Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches

Neurotoxicology is the study of adverse effects on the structure or function of the developing or mature adult nervous system following exposure to chemical, biological, or physical agents. The development of more informative alternative methods to assess developmental (DNT) and adult (NT) neurotoxicity induced by xenobiotics is critically needed. The use of such alternative methods including in silico approaches that predict DNT or NT from chemical structure (e.g., statistical-based and expert rule-based systems) is ideally based on a comprehensive understanding of the relevant biological mechanisms. This paper discusses known mechanisms alongside the current state of the art in DNT/NT testing. In silico approaches available today that support the assessment of neurotoxicity based on knowledge of chemical structure are reviewed, and a conceptual framework for the integration of in silico methods with experimental information is presented. Establishing this framework is essential for the development of protocols, namely standardized approaches, to ensure that assessments of NT and DNT based on chemical structures are generated in a transparent, consistent, and defendable manner.

In silico approaches in organ toxicity hazard assessment: current status and future needs in predicting liver toxicity

Hepatotoxicity is one of the most frequently observed adverse effects resulting from exposure to a xenobiotic. For example, in pharmaceutical research and development it is one of the major reasons for drug withdrawals, clinical failures, and discontinuation of drug candidates. The development of faster and cheaper methods to assess hepatotoxicity that are both more sustainable and more informative is critically needed. The biological mechanisms and processes underpinning hepatotoxicity are summarized and experimental approaches to support the prediction of hepatotoxicity are described, including toxicokinetic considerations. The paper describes the increasingly important role of in silico approaches and highlights challenges to the adoption of these methods including the lack of a commonly agreed upon protocol for performing such an assessment and the need for in silico solutions that take dose into consideration. A proposed framework for the integration of in silico and experimental information is provided along with a case study describing how computational methods have been used to successfully respond to a regulatory question concerning non-genotoxic impurities in chemically synthesized pharmaceuticals.

In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs

Historically, identifying carcinogens has relied primarily on tumor studies in rodents, which require enormous resources in both money and time. In silico models have been developed for predicting rodent carcinogens but have not yet found general regulatory acceptance, in part due to the lack of a generally accepted protocol for performing such an assessment as well as limitations in predictive performance and scope. There remains a need for additional, improved in silico carcinogenicity models, especially ones that are more human-relevant, for use in research and regulatory decision-making. As part of an international effort to develop in silico toxicological protocols, a consortium of toxicologists, computational scientists, and regulatory scientists across several industries and governmental agencies evaluated the extent to which in silico models exist for each of the recently defined 10 key characteristics (KCs) of carcinogens. This position paper summarizes the current status of in silico tools for the assessment of each KC and identifies the data gaps that need to be addressed before a comprehensive in silico carcinogenicity protocol can be developed for regulatory use.

On the use of electronegativity and electron affinity based pseudo-molecular field descriptors in developing correlations for quantitative structure-activity relationship modeling of drug activities

For quantitative structure-activity relationship (QSAR) modeling in ligand-based drug discovery programs, pseudo-molecular field (PMF) descriptors using intrinsic atomic properties, namely, electronegativity and electron affinity are studied. In combination with partial least squares analysis and Procrustes transformation, these PMF descriptors were employed successfully to develop correlations that predict the activities of target protein inhibitors involved in various diseases (cancer, neurodegenerative disorders, HIV, and malaria). The results show that the present QSAR approach is competitive to existing QSAR models. In order to demonstrate the use of this algorithm, we present results of screening naturally occurring molecules with unknown bioactivities. The pIC₅₀ predictions can screen molecules that have desirable activity before assessment by docking studies.

Network pharmacology-based study on the mechanism of Yiganling capsule in hepatitis B treatment

Background

Yiganling (YGL) capsule is a traditional Chinese medicine preparation consisting of eight herbs that has been clinically proven to have a favorable treatment effect on Hepatitis B (HB). However, due to its multiple targets and multi-pharmacological effects, the mechanisms of YGL capsule in the treatment of HB are unknown.

Methods

First, the chemical constituents of YGL capsules were obtained from the Chinese medicine database, and YGL capsules were constructed. Second, active compounds were screened by the ADME model. The target fishing model was used to screen the corresponding targets of active compounds and to construct a compounds and compound targets network. Using human disease databases and literature mining, we systematically identified genes associated with HB, constructed disease-specific protein-protein interaction networks, and performed clustering and enrichment analyses of these networks. These networks were then merged to obtain a compound-disease target network, and cluster and enrichment analyses were performed on the compound-disease target network to acquire a compounds-disease targets-mechanism network and a clustering network.

Results

We successfully built eight pharmacological network diagrams, including four primary networks and other network maps. The four dominating network maps included a HB disease-associated protein-protein interaction network, a YGL capsule compounds-target network, a YGL capsule ingredient target-HB disease target network, and a YGL-HB disease mechanism network. Other networks included a pathway of HB disease targets, the HB disease protein-protein interaction cluster analysis network, and the YGL-HB target clustering network.

Conclusion

This study successfully forecasted, illuminated, and confirmed the synergistic effects of HB disease molecules and discovered the potential of HB relevant targets, clusters, and target-related biological processes and signaling pathways. Our research not only provides theoretical support for the molecular and pharmacological mechanisms of YGL capsule in HB treatment, but also provides new research methods for the study of the other traditional Chinese medicinal compounds.

Application and Impact of Human Dose Projection from Discovery to Early Drug Development

The application and impact of human dose projection (HDP) has been well recognized in the late drug development phase, with increasing appreciation earlier during discovery and early development. This commentary describes the perspective of pharmaceutical scientists on the evolving application and impact of HDP at various phases from discovery to early development, including lead generation, lead optimization, lead up to candidate nomination, and early drug development. The underlying fundamental concepts and key input parameters for HDP are briefly discussed. A broad overview of phase-specific tools and approaches commonly utilized for human dose projection in the pharmaceutical industry is provided. A discussion of phase-appropriate implementation strategies, associated limitations/assumptions and continuous refinement for HDP from discovery to early development is presented. The authors describe the phase-specific applications of human dose projection to facilitate key assessments and relative impact on decision points.

Network Pharmacology of Yougui Pill Combined with Buzhong Yiqi Decoction for the Treatment of Sexual Dysfunction

Purpose

We aimed to find the possible key targets of Yougui pill and Buzhong Yiqi decoction for the treatment of sexual dysfunction.

Materials and Methods

The composition of Yougui pill combined with Buzhong Yiqi decoction was obtained, and its effective components of medicine were screened using ADME; the component target proteins were predicted and screened based on the TCMSP and BATMAN databases. Target proteins were cross-validated using the CTD database. We performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses for target proteins using the Cytoscape plugin ClueGO + CluePedia and the R package clusterProfiler, respectively. Subsequently, protein-protein interaction (PPI) analyses were conducted using the STRING database. Finally, a pharmacological network was constructed.

Results

The pharmacological network contained 89 nodes and 176 relation pairs. Among these nodes, there were 12 for herbal medicines (orange peel, licorice, Eucommia, Aconite, Astragalus, Chinese wolfberry, yam, dodder seed, ginseng, Cornus officinalis, Rehmannia, and Angelica), 9 for chemical components (18-beta-glycyrrhetinic acid, carvacrol, glycyrrhetinic acid, higenamine, nobilin, quercetin, stigmasterol, synephrine, and thymol), 62 for target proteins (e.g., NR3C1, ESR1, PTGS2, CAT, TNF, INS, and TP53), and 6 for pathways (MAPK signaling pathway, proteoglycans in cancer, dopaminergic synapse, thyroid hormone signaling pathway, cAMP signaling pathway, and neuroactive ligand-receptor interaction).

Conclusion

NR3C1, ESR1, PTGS2, CAT, TNF, INS, and TP53 may be important targets for the key active elements in the decoction combining Yougui pill and Buzhong Yiqi. Furthermore, these target proteins are relevant to the treatment of sexual dysfunction, probably via pathways associated with cancer and signal transduction.

Systems pharmacology exploration of botanic drug pairs reveals the mechanism for treating different diseases

Multi-herb therapy has been widely used in Traditional Chinese medicine and tailored to meet the specific needs of each individual. However, the potential molecular or systems mechanisms of them to treat various diseases have not been fully elucidated. To address this question, a systems pharmacology approach, integrating pharmacokinetics, pharmacology and systems biology, is used to comprehensively identify the drug-target and drug-disease networks, exemplified by three representative Radix Salviae Miltiorrhizae herb pairs for treating various diseases (coronary heart disease, dysmenorrheal and nephrotic syndrome). First, the compounds evaluation and the multiple targeting technology screen the active ingredients and identify the specific targets for each herb of three pairs. Second, the herb feature mapping reveals the differences in chemistry and pharmacological synergy between pairs. Third, the constructed compound-target-disease network explains the mechanisms of treatment for various diseases from a systematic level. Finally, experimental verification is taken to confirm our strategy. Our work provides an integrated strategy for revealing the mechanism of synergistic herb pairs, and also a rational way for developing novel drug combinations for treatments of complex diseases.

Novel DOT1L ReceptorNatural Inhibitors Involved in Mixed Lineage Leukemia: a Virtual Screening, Molecular Docking and Dynamics Simulation Study

BACKGROUND

The human protein methyl-transferase DOT1L catalyzes the methylation of histone H3 on lysine 79 (H3K79) at homeobox genes and is also involved in a number of significant processes ranging from gene expression to DNA-damage response and cell cycle progression. Inhibition of DOT1L activity by shRNA or small-molecule inhibitors has been established to prevent proliferation of various MLL-rearranged leukemia cells in vitro, establishing DOT1L an attractive therapeutic target for mixed lineage leukemia (MLL). Most of the drugs currently in use for the MLL treatment are reported to have low efficacy, hence this study focused on various natural compounds which exhibit minimal toxic effects and high efficacy for the target receptor.

MATERIALS AND METHODS

Structures of human protein methyl-transferase DOT1L and natural compound databases were downloaded from various sources. Virtual screening, molecular docking, dynamics simulation and drug likeness studies were performed for those natural compounds to evaluate and analyze their anti-cancer activity.

RESULTS

The top five screened compounds possessing good binding affinity were identified as potential high affinity inhibitors against DOT1L's active site. The top ranking molecule amongst the screened ligands had a Glide g-score of -10.940 kcal/mol and Glide e-model score of -86.011 with 5 hydrogen bonds and 12 hydrophobic contacts. This ligand's behaviour also showed consistency during the simulation of protein-ligand complex for 20000 ps, which is indicative of its stability in the receptor pocket.

CONCLUSIONS

The ligand obtained out of this screening study can be considered as a potential inhibitor for DOT1L and further can be treated as a lead for the drug designing pipeline.

Identification of anti-cancer targets of eco-friendly waste Punica granatum peel by dual reverse virtual screening and binding analysis

BACKGROUND

Punica granatum (family: Lythraceae) is mainly found in Iran, which is considered to be its primary centre of origin. Studies on pomegranate peel have revealed antioxidant, anti-inflammatory, anti- angiogenesis activities, with prevention of premature aging and reducing inflammation. In addition to this it is also useful in treating various diseases like diabetes, maintaining blood pressure and treatment of neoplasms such as prostate and breast cancer.

OBJECTIVES

In this study we identified anti-cancer targets of active compounds like corilagin (tannins), quercetin (flavonoids) and pseudopelletierine (alkaloids) present in pomegranate peel by employing dual reverse screening and binding analysis.

MATERIALS AND METHODS

The potent targets of the pomegranate peel were annotated by the PharmMapper and ReverseScreen 3D, then compared with targets identified from different Bioassay databases (NPACT and HIT's). Docking was then further employed using AutoDock pyrx and validated through discovery studio for studying molecular interactions.

RESULTS

A number of potent anti-cancerous targets were attained from the PharmMapper server according to their fit score and from ReverseScreen 3D server according to decreasing 3D scores.

CONCLUSION

The identified targets now need to be further validated through in vitro and in vivo studies.

A novel systems pharmacology model for herbal medicine injection: a case using Reduning injection

BACKGROUND

Compared with the traditional oral administration form, injection administration is basically superior in terms of both biological availability and therapeutic effects. However, few researches have focused on the traditional Chinese medicinal injection due to the complicated constituents and the intricate mechanism of action.

METHODS

In the present work, a novel systems pharmacology model, integrating ADME (absorption, distribution, metabolism, and excretion) filtering such as half-life evaluation, network targeting, pathway and systems analyses, is specifically developed for the identification of active compounds and the study of the mechanism of action of TCM injection, which is exemplified by Reduning injection confronting the influenza.

RESULTS

The ADME filter successfully identifies 35 bioactive compounds (31 molecules and 4 metabolites) from the Reduning injection. The systems analysis and experimental validation further reveal a new way of confronting influenza disease of this injection: 1) stimulating the immunomodulatory agents for immune response activation, and 2) regulating the inflammatory agents for anti-inflammation.

CONCLUSIONS

The novel systems pharmacology method used in this study has the potential to advance the understanding of the molecular mechanisms of action of multicomponent herbal injections, and provide clues to discovering more effective drugs against complex diseases.

Strategies for the generation, validation and application of in silico ADMET models in lead generation and optimization

INTRODUCTION

The most desirable chemical starting point in drug discovery is a hit or lead with a good overall profile, and where there may be issues; a clear SAR strategy should be identifiable to minimize the issue. Filtering based on drug-likeness concepts are a first step, but more accurate theoretical methods are needed to i) estimate the biological profile of molecule in question and ii) based on the underlying structure-activity relationships used by the model, estimate whether it is likely that the molecule in question can be altered to remove these liabilities.

AREAS COVERED

In this paper, the authors discuss the generation of ADMET models and their practical use in decision making. They discuss the issues surrounding data collation, experimental errors, the model assessment and validation steps, as well as the different types of descriptors and statistical models that can be used. This is followed by a discussion on how the model accuracy will dictate when and where it can be used in the drug discovery process. The authors also discuss how models can be developed to more effectively enable multiple parameter optimization.

EXPERT OPINION

Models can be applied in lead generation and lead optimization steps to i) rank order a collection of hits, ii) prioritize the experimental assays needed for different hit series, iii) assess the likelihood of resolving a problem that might be present in a particular series in lead optimization and iv) screen a virtual library based on a hit or lead series to assess the impact of diverse structural changes on the predicted properties.

Repeatability analysis of the Tetrahymena pyriformis population growth impairment assay

Assessments necessary to ensure the safety of both humans and the environment are challenged by the sheer number of chemicals in use today. Chemical legislation, such as REACH, aims to use alternative methods to reduce the reliance on in vivo animal testing. Consequently, databases such as the TETRATOX database, containing data from the Tetrahymena pyriformis population growth impairment assay, have been used extensively to develop computational models which aid in priority setting and initial hazard assessments. To use any toxicological data, an assessment of quality is required. One important aspect of quality is the repeatability of the assay. This study considered TETRATOX assay data for 85 structurally and mechanistically diverse compounds. The repeatability of replicate determinations was assessed and factors relating to repeatability are discussed. Despite the majority of compounds demonstrating excellent repeatability, it was found that the mechanism of action is likely to be a modulating factor, with compounds acting via electrophilic mechanisms being more likely to exhibit reduced repeatability than those acting via narcotic mechanisms. It is evident from this study that the TETRATOX assay is a robust and highly repeatable assay, suitable for use in toxicological modelling studies and priority setting.

Alternative (non-animal) methods for cosmetics testing: current status and future prospects-2010

The 7th amendment to the EU Cosmetics Directive prohibits to put animal-tested cosmetics on the market in Europe after 2013. In that context, the European Commission invited stakeholder bodies (industry, non-governmental organisations, EU Member States, and the Commission's Scientific Committee on Consumer Safety) to identify scientific experts in five toxicological areas, i.e. toxicokinetics, repeated dose toxicity, carcinogenicity, skin sensitisation, and reproductive toxicity for which the Directive foresees that the 2013 deadline could be further extended in case alternative and validated methods would not be available in time. The selected experts were asked to analyse the status and prospects of alternative methods and to provide a scientifically sound estimate of the time necessary to achieve full replacement of animal testing. In summary, the experts confirmed that it will take at least another 7-9 years for the replacement of the current in vivo animal tests used for the safety assessment of cosmetic ingredients for skin sensitisation. However, the experts were also of the opinion that alternative methods may be able to give hazard information, i.e. to differentiate between sensitisers and non-sensitisers, ahead of 2017. This would, however, not provide the complete picture of what is a safe exposure because the relative potency of a sensitiser would not be known. For toxicokinetics, the timeframe was 5-7 years to develop the models still lacking to predict lung absorption and renal/biliary excretion, and even longer to integrate the methods to fully replace the animal toxicokinetic models. For the systemic toxicological endpoints of repeated dose toxicity, carcinogenicity and reproductive toxicity, the time horizon for full replacement could not be estimated.