An open-source software package for creating and operating web-based structure and/or reaction databases is presented. Besides standard search capabilities (text, structure/substructure/similarity), the system offers a fast additional search option, entirely based on binary pattern matching, which uses automatically assigned functional group descriptors.

P-Glycoprotein (P-gp, ABCB1) plays a significant role in determining the ADMET properties of drugs and drug candidates. Substrates of P-gp are not only subject to multidrug resistance (MDR) in tumor therapy, they are also associated with poor pharmacokinetic profiles. In contrast, inhibitors of P-gp have been advocated as modulators of MDR. However, due to the polyspecificity of P-gp, knowledge on the molecular basis of ligand-transporter interaction is still poor, which renders the prediction of whether a compound is a P-gp substrate/non-substrate or an inhibitor/non-inhibitor quite challenging. In the present investigation, we used a set of fingerprints representing the presence/absence of various functional groups for machine learning based classification of a set of 484 substrates/non-substrates and a set of 1935 inhibitors/non-inhibitors. Best models were obtained using a combination of a wrapper subset evaluator (WSE) with random forest (RF), kappa nearest neighbor (kNN) and support vector machine (SVM), showing accuracies >70%. Best P-gp substrate models were further validated with three sets of external P-gp substrate sources, which include Drug Bank (n = 134), TP Search (n = 90) and a set compiled from literature (n = 76). Association rule analysis explores the various structural feature requirements for P-gp substrates and inhibitors.

The article describes a classification system termed “extended functional groups” (EFG), which are an extension of a set previously used by the CheckMol software, that covers in addition heterocyclic compound classes and periodic table groups. The functional groups are defined as SMARTS patterns and are available as part of the ToxAlerts tool (http://ochem.eu/alerts) of the On-line CHEmical database and Modeling (OCHEM) environment platform. The article describes the motivation and the main ideas behind this extension and demonstrates that EFG can be efficiently used to develop and interpret structure-activity relationship models.

SSAO/VAP-1 is not only involved in the metabolism of biogenic and xenobiotic primary amines and in the production of metabolites with cytotoxic effects or certain physiological actions, but also plays a role, for example, as an adhesion molecule, in leukocyte trafficking, in regulating glucose uptake and in adipocyte homeostasis. Interest in the enzyme has been stimulated by the findings that the activities of the SSAOs are altered (mostly increased) in various human disorders, including diabetes, congestive heart failure, liver cirrhosis, Alzheimers disease and several inflammatory diseases, although the underlying causes are often unknown. On the basis of their insulin-mimicking effect, SSAO substrates are possibly capable of ameliorating metabolic changes in diabetes, while SSAO inhibitors (somewhat of a contradiction) are of potential benefit in preventing diabetes complications, atherosclerosis and oxidative stress contributing to several disorders or modulating inflammation, and hence may be of substantial therapeutic value. Great efforts have been made to develop novel compounds which may lead to future drugs useful in therapy, based on their effects on SSAO/VAP-1, and some of the results relating to novel substrates and inhibitors are surveyed in the present review.

Semicarbazide-sensitive amine-oxidase (SSAO) is present in various human tissues and in plasma. Oxidative deamination of short-chain aliphatic amines is catalyzed by this enzyme to afford the corresponding aldehydes, ammonia and hydrogen peroxide. Methylamine and aminoacetone have been recognized to be physiological substrates for SSAO. There are several pathological states where increased serum SSAO activity have been found, such as diabetes mellitus, congestive heart failure, multiple types of cerebral infarction, uraemia, and hepatic cirrhosis. The role of SSAO in pathophysiology of diabetes has been most extensively investigated. The elevated formation of the potentially cytotoxic products of the enzyme may contribute to the endothelial injury of blood vessels, resulting in the early development of severe atherosclerosis; it may also contribute to the pathogenesis of diabetic angiopathy. It is now suggested that SSAO inhibitors may prevent the development of atherosclerosis and diabetic complications as well. Inhibitors can be conveniently subdivided into the main groups of hydrazine derivatives, arylalkylamines, propenyl- and propargylamines, oxazolidinones, and haloalkylamines. Of them, aryl(alkyl)hydrazines, and 3-halo-2-phenylallylamines are generally very strong SSAO inhibitors. Most of these inhibitors of SSAO have been originally developed for other purposes, or they are simple chemical reagents with highly reactive structural element(s); these compounds have not been able to fulfil all criteria of high potency, selectivity, and acceptable toxicity. New potent compounds with selectivity and low toxicity are needed, which may prove useful tools for understanding the roles and function of SSAO, or they may even be valuable substances for treatment of various diseases.