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Of the thousands of novel compounds that a drug discovery project team invents and that bind to the therapeutic target, typically only a fraction of these have sufficient ADME/Tox properties to become a drug product. Understanding ADME/Tox is critical for all drug researchers, owing to its increasing importance in advancing high quality candidates to clinical studies and the processes of drug discovery. If the properties are weak, the candidate will have a high risk of failure or be less desirable as a drug product. This book is a tool and resource for scientists engaged in, or preparing for, the selection and optimization process. The authors describe how properties affect in vivo pharmacological activity and impact in vitro assays. Individual drug-like properties are discussed from a practical point of view, such as solubility, permeability and metabolic stability, with regard to fundamental understanding, applications of property data in drug discovery and examples of structural modifications that have achieved improved property performance. The authors also review various methods for the screening (high throughput), diagnosis (medium throughput) and in-depth (low throughput) analysis of drug properties. * Serves as an essential working handbook aimed at scientists and students in medicinal chemistry* Provides practical, step-by-step guidance on property fundamentals, effects, structure-property relationships, and structure modification strategies * Discusses improvements in pharmacokinetics from a practical chemist's standpoint

Stevioside, one of the natural sweeteners extracted from stevia leaves, and its derivatives are considered to have numerous beneficial pharmacological properties, including the inhibition of activated coagulation factor X (FXa). FXa-PAR signaling is a possible therapeutic target to enhance impaired metabolism and insulin resistance in obesity. Thus, the goal of the investigation was a QSAR analysis using multivariate adaptive regression splines (MARSplines) applied to a data set of 20 isosteviol derivatives bearing thiourea fragments with possible FXa inhibitory action. The best MARS submodel described a strong correlation between FXa inhibitory activity and molecular descriptors, such as: B01[C-Cl], E2m, L3v, Mor06i, RDF070i and HATS7s. Five out of six descriptors included in the model are geometrical descriptors quantifying three-dimensional aspects of molecular structure, which indicates that the molecular three-dimensional conformation is of high significance for the MARSplines modeling procedure and obviously for FXa inhibitory activity. High model performance was confirmed through an extensive validation protocol. The results of the study not only confirmed the enhancement in pharmacological activity by the presence of chlorine in a phenyl ring, but also, and primarily, may provide the basis for searching for new active isosteviol analogues, which may serve as drugs or health-beneficial food additives in patients suffering from obesity and comorbidities.

Fucoidans are marine sulfated biopolysaccharides that have heterogenous and complicated chemical structures. Various sugar monomers, glycosidic linkages, molecular masses, branching sites, and sulfate ester pattern and content are involved within their backbones. Additionally, sources, downstream processes, and geographical and seasonal factors show potential effects on fucoidan structural characteristics. These characteristics are documented to be highly related to fucoidan potential activities. Therefore, numerous chemical qualitative and quantitative determinations and structural elucidation methods are conducted to characterize fucoidans regarding their physicochemical and chemical features. Characterization of fucoidan polymers is considered a bottleneck for further biological and industrial applications. Consequently, the obtained results may be related to different activities, which could be improved afterward by further functional modifications. The current article highlights the different spectrometric and nonspectrometric methods applied for the characterization of native fucoidans, including degree of purity, sugar monomeric composition, sulfation pattern and content, molecular mass, and glycosidic linkages.

Chemotaxis is the directed motility by means of which microbes sense chemical cues and relocate towards more favorable environments. Methyl-accepting chemotaxis proteins (MCPs) are the most common receptors in bacteria and archaea. They are arranged as trimers of dimers that, in turn, form hexagonal arrays in the cytoplasmic membrane or in the cytoplasm. Several different classes of MCPs have been identified according to their ligand binding region and membrane topology. MCPs have been further classified based on the length and sequence conservation of their cytoplasmic domains. Clusters of membrane-embedded MCPs often localize to the poles of the cell, whereas cytoplasmic MCPs can be targeted to the poles or distributed throughout the cell body. MCPs play an important role in cell survival, pathogenesis, and biodegradation. Bacterial adaptation to diverse environmental conditions promotes diversity among the MCPs. This review summarizes structure, classification, and structure–activity relationship of the known MCP receptors, with a brief overview of the signal transduction mechanisms in bacteria and archaea.

The Freundlich isotherm parameters K and 1/n are typically regarded as empirical constants. However, the underlying theoretical basis for the widespread applicability of the Freundlich isotherm in describing adsorption processes for diverse organic compounds remains unclear. In this study, we successfully elucidated the reason by developing two optimal quantitative structure-activity relationship (QSAR) models: one correlating K with quantum chemical parameters and another linking 1/n to these parameters. The modeling results demonstrated that both K and 1/n exhibit strong correlations with specific quantum chemical descriptors, indicating that the empirical Freundlich isotherm’s applicability is fundamentally linked to the molecular structural characteristics of organic compounds. Key quantum parameters influencing K were identified as ∑q(O + N), q(CH+) max , ELUMO, Fukui(-) max , and Wiberg(C-C) min , suggesting that charge distribution, carbon bond energy, and active site energy are the primary factors governing adsorption efficiency on activated carbon. The QSAR model for 1/n yielded similarly novel and consistent insights, showing that the value of 1/n also correlated with molecular structural characteristics. Both models were rigorously validated and confirmed to be stable, robust, and accurate through standard statistical evaluations. These QSAR models can now be employed to identify whether an organic compound would conform to the Freundlich Isotherm and predict the adsorption efficiency of this compound by activated carbon based on their quantum chemical parameters. As to the practical implications, this study provides a convenient reference method for assessing the applicability of activated carbon adsorption in treating emerging organic pollutants in drinking water plants and a theoretical foundation for developing intelligent management systems in water treatment facilities.

In recent years, several strategies have been developed for the treatment of transthyretin-related amyloidosis, whose complex clinical manifestations involve cardiomyopathy and polyneuropathy. In view of this, transthyretin stabilizers represent a major cornerstone in treatment thanks to the introduction of tafamidis into therapy and the entry of acoramidis into clinical trials. However, the clinical treatment of transthyretin-related amyloidosis still presents several challenges, urging the development of new and improved therapeutics. Bearing this in mind, in this paper, the most promising among the recently published transthyretin stabilizers were reviewed. Their activity was described to provide some insights into their clinical potential, and crystallographic data were provided to explain their modes of action. Finally, structure–activity relationship studies were performed to give some guidance to future researchers aiming to synthesize new transthyretin stabilizers. Interestingly, some new details emerged with respect to the previously known general rules that guided the design of new compounds.

This handbook and ready reference presents a combination of statistical, information-theoretic, and data analysis methods to meet the challenge of designing empirical models involving molecular descriptors within bioinformatics.

Biofouling is the undesirable growth of micro- and macro-organisms on artificial water-immersed surfaces, which results in high costs for the prevention and maintenance of this process (billion €/year) for aquaculture, shipping and other industries that rely on coastal and off-shore infrastructure. To date, there are still no sustainable, economical and environmentally safe solutions to overcome this challenging phenomenon. A computer-aided drug design (CADD) approach comprising ligand- and structure-based methods was explored for predicting the antifouling activities of marine natural products (MNPs). In the CADD ligand-based method, 141 organic molecules extracted from the ChEMBL database and literature with antifouling screening data were used to build the quantitative structure–activity relationship (QSAR) classification model. An overall predictive accuracy score of up to 71% was achieved with the best QSAR model for external and internal validation using test and training sets. A virtual screening campaign of 14,492 MNPs from Encinar’s website and 14 MNPs that are currently in the clinical pipeline was also carried out using the best QSAR model developed. In the CADD structure-based approach, the 125 MNPs that were selected by the QSAR approach were used in molecular docking experiments against the acetylcholinesterase enzyme. Overall, 16 MNPs were proposed as the most promising marine drug-like leads as antifouling agents, e.g., macrocyclic lactam, macrocyclic alkaloids, indole and pyridine derivatives.

Pharmacology over the past 100 years has had a rich tradition of scientists with the ability to form qualitative or semi‐quantitative relations between molecular structure and activity in cerebro. To test these hypotheses they have consistently used traditional pharmacology tools such as in vivo and in vitro models. Increasingly over the last decade however we have seen that computational (in silico) methods have been developed and applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure‐activity relationships, pharmacophores, homology models and other molecular modeling approaches, machine learning, data mining, network analysis tools and data analysis tools that use a computer. In silico methods are primarily used alongside the generation of in vitro data both to create the model and to test it. Such models have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The aim of this review is to illustrate some of the in silico methods for pharmacology that are used in drug discovery. Further applications of these methods to specific targets and their limitations will be discussed in the second accompanying part of this review. British Journal of Pharmacology (2007) 152, 9–20; doi:10.1038/sj.bjp.0707305

Humic acid–based carbon dots (HACDs) have excellent properties and are widely used in environmental detection, bioimaging, and optoelectronic materials. Herein, we investigated the structure–activity relationship between the morphology and optical properties of HACDs, and reported on a novel strategy for metronidazole (MNZ) and ornidazole (ONZ) sensing in multiple real samples. It was found that the average particle size decreased from 3.28 to 2.44 nm, optimal emission wavelength was blue-shifted from 500 to 440 nm, and the quantum yield (QY) improved from 5 to 23% with the temperature increasing from 110 to 400 °C. Under the oxidation of hydrogen peroxide (H 2 O 2 ) and potassium permanganate (KMnO 4 ), the UV–vis spectra of HACD aqueous solution showed time-dependent behavior, and the fluorescence emission of HACDs achieved spectrally tunable multi-color luminescence in the temporal dimension. The surface of HACDs contained a large number of hydroxyl (–OH) and carboxyl (–COOH) fluorophores, resulting in excellent pH sensing. Meanwhile, the synthesized HACDs revealed sensitive response to MNZ and ONZ with the limit of detection (LOD) of 60 nM and 50 nM in aqueous solutions, which had also been successfully applied in various actual samples such as lake water, honey, eggs, and milk with satisfactory results because of the inner filter effect (IFE). Our research is advantageous to enhance the potential applications of HACDs in advanced analytical systems. Graphical abstract