In silico prediction of skin metabolism and its implication in toxicity assessment

Skin, being the largest organ of the body, represents an important route of exposure, not only for the abundance of chemicals present in the environment, but also for products designed for topical application such as drugs and personal care products. Determining whether such incidental or intentional exposure poses a risk to human health requires consideration of temporal concentration, both externally and internally, in addition to assessing the chemical’s intrinsic hazard. In order to elicit a toxic response in vivo the chemical must reach its site of action in sufficient concentration, as determined by its absorption, distribution, metabolism and elimination (ADME) profile. Whilst absorption and distribution into and through skin layers have been studied for decades, only more recently has skin metabolism become a subject of intense research, now recognised as playing a key role in both toxification and detoxification processes. The majority of information on metabolic processes, however, has generally been acquired via studies performed on the liver. This paper outlines strategies that may be used to leverage current knowledge, gained from liver metabolism studies, to inform predictions for skin metabolism through understanding the differences in the enzymatic landscapes between skin and liver. The strategies outlined demonstrate how an array of in silico tools may be used in concert to resolve a significant challenge in predicting toxicity following dermal exposure. The use of in vitro methods for determining skin metabolism, both to provide further experimental data for modelling and to verify predictions is also discussed. Herein, information on skin metabolism is placed within the context of toxicity prediction for risk assessment, which requires consideration of both exposure and hazard of parent chemicals and their metabolites

Predicting drug metabolism: experiment and/or computation?

Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.This is the accepted manuscript of a paper published in Nature Reviews Drug Discovery (Kirchmair J, Göller AH, Lang D, Kunze J, Testa B, Wilson ID, Glen RC, Schneider G, Nature Reviews Drug Discovery, 2015, 14, 387–404, doi:10.1038/nrd4581). The final version is available at http://dx.doi.org/10.1038/nrd458

Adaptation of High-Throughput Screening in Drug Discovery—Toxicological Screening Tests

High-throughput screening (HTS) is one of the newest techniques used in drug design and may be applied in biological and chemical sciences. This method, due to utilization of robots, detectors and software that regulate the whole process, enables a series of analyses of chemical compounds to be conducted in a short time and the affinity of biological structures which is often related to toxicity to be defined. Since 2008 we have implemented the automation of this technique and as a consequence, the possibility to examine 100,000 compounds per day. The HTS method is more frequently utilized in conjunction with analytical techniques such as NMR or coupled methods e.g., LC-MS/MS. Series of studies enable the establishment of the rate of affinity for targets or the level of toxicity. Moreover, researches are conducted concerning conjugation of nanoparticles with drugs and the determination of the toxicity of such structures. For these purposes there are frequently used cell lines. Due to the miniaturization of all systems, it is possible to examine the compound’s toxicity having only 1–3 mg of this compound. Determination of cytotoxicity in this way leads to a significant decrease in the expenditure and to a reduction in the length of the study

Integration of In Silico and In Vitro ADMET properties in lead identification and optimization of compounds for the treatment of parasitic diseases

Parasitic infections are the major causes of illness and death in tropical regions especially in Africa. The main parasitic diseases include leishmaniasis, filariasis, malaria, river blindness, Chagas disease and schistosomiasis. With the absence of vaccines, treatment relies mainly on chemotherapy hence the need for efficacious and safe medicines. Many of the medicines currently used have low efficacy and cause side effects. Some are also being lost to drug resistance. To address the inadequacy of treatment options for infectious diseases, a number of initiatives have been started to promote drug discovery and development in Africa. In parallel they have been collaboration between African institutions and leading pharmaceutical companies as well as other relevant R & D organizations. This has led to the need to modernize African approaches to drug discovery and development with respect to the integration of medicinal chemistry, pharmacology and pharmacokinetics as reflected in the processes of Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET). However, scientific and technological expertise in pharmacokinetics for drug discovery is under developed in Africa