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Background Quantitative structure-activity relationship (QSAR) is a computational modeling method for revealing relationships between structural properties of chemical compounds and biological activities. QSAR modeling is essential for drug discovery, but it has many constraints. Ensemble-based machine learning approaches have been used to overcome constraints and obtain reliable predictions. Ensemble learning builds a set of diversified models and combines them. However, the most prevalent approach random forest and other ensemble approaches in QSAR prediction limit their model diversity to a single subject. Results The proposed ensemble method consistently outperformed thirteen individual models on 19 bioassay datasets and demonstrated superiority over other ensemble approaches that are limited to a single subject. The comprehensive ensemble method is publicly available at http://data.snu.ac.kr/QSAR/ . Conclusions We propose a comprehensive ensemble method that builds multi-subject diversified models and combines them through second-level meta-learning. In addition, we propose an end-to-end neural network-based individual classifier that can automatically extract sequential features from a simplified molecular-input line-entry system (SMILES). The proposed individual models did not show impressive results as a single model, but it was considered the most important predictor when combined, according to the interpretation of the meta-learning.

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.

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

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.

The epidermal growth factor receptor (EGFR) plays a critical role in the tumorigenesis of various forms of cancer. Targeting the mutant forms of EGFR has been identified as an attractive therapeutic approach and led to the approval of three generations of inhibitors. The quinazoline core has emerged as a favorable scaffold for the development of novel EGFR inhibitors due to increased affinity for the active site of EGFR kinase. Currently, there are five first-generation (gefitinib, erlotinib, lapatinib, vandetanib, and icotinib) and two second-generation (afatinib and dacomitinib) quinazoline-based EGFR inhibitors approved for the treatment of various types of cancers. The aim of this review is to outline the structural modulations favorable for the inhibitory activity toward both common mutant (del19 and L858R) and resistance-conferring mutant (T790M and C797S) EGFR forms, and provide an overview of the newly synthesized quinazoline derivatives as potentially competitive, covalent or allosteric inhibitors of EGFR.

Curcumin, one of the major ingredients of turmeric (Curcuma longa), has been widely reported for its diverse bioactivities, including against malaria and inflammatory-related diseases. However, curcumin’s low bioavailability limits its potential as an antimalarial and anti-inflammatory agent. Therefore, research on the design and synthesis of novel curcumin derivatives is being actively pursued to improve the pharmacokinetic profile and efficacy of curcumin. This review discusses the antimalarial and anti-inflammatory activities and the structure–activity relationship (SAR), as well as the mechanisms of action of curcumin and its derivatives in malarial treatment. This review provides information on the identification of the methoxy phenyl group responsible for the antimalarial activity and the potential sites and functional groups of curcumin for structural modification to improve its antimalarial and anti-inflammatory actions, as well as potential molecular targets of curcumin derivatives in the context of malaria and inflammation.

Antibacterial resistance is one of the most important global threats to human health. Several studies have been performed to overcome this problem and infection-preventive approaches appear as promising solutions. Novel antimicrobial preventive molecules are needed and microbial biosurfactants have been explored in that scope. Considering their structure, these biomolecules can be divided into different classes, glycolipids and lipopeptides being the most studied. Besides their antimicrobial activity, biosurfactants have the advantage of being biocompatible, biodegradable, and non-toxic, which favor their application in several areas, including the health sector. Often, the most difficult infections to fight are associated with biofilm formation, particularly in medical devices. Strategies to overcome micro-organism attachment are thus emergent, and it is possible to take advantage of the antimicrobial/antibiofilm properties of biosurfactants to produce surfaces that are more resistant to the deposition/attachment of bacteria. Approaches such as the covalent bond of biosurfactants to the medical device surface leading to repulsive physical–chemical interactions or contact killing can be selected. Simpler strategies such as the absorption of biosurfactants on surfaces are also possible, eliminating micro-organisms in the vicinity. This review will focus on the physical and chemical characteristics of biosurfactants, their antimicrobial activity, antimicrobial/antibiofilm approaches, and finally on their structure–activity relationship.

A systematic structure–activity and computational modeling analysis of a series of glucagon-like peptide-1 receptor (GLP-1R) agonists based upon an ultra-short GLP-1 peptide, H-His-Aib-Glu-Gly-Thr-Phe-Thr-Ser-Asp-Bip-Bip-NH2, was conducted. This highly potent 11-mer peptide led to a deeper understanding of the α-helical bias of strategic α-methylation within the linear parent template as well as optimization of GLP-1R agonist potency by 1000-fold. These data were correlated with previously reported co-structures of both full-length GLP-1 analogs and progenitor N-terminal GLP-1 fragment analogs related to such ultra-short GLP-1R agonist peptides. Furthermore, the development of a quantitative structure–activity relationship (QSAR) model to analyze these findings is described in this study.

Increasing antibiotic resistance in Gram-negative bacteria, particularly in , and , presents a global medical challenge. No new antibiotics will be available for these 'superbugs in the near future due to the dry antibiotic discovery pipeline. Colistin and polymyxin B are increasingly used as the last-line therapeutic options for treatment of infections caused by multidrug-resistant Gram-negative bacteria. This article surveys the significant progress over the last decade in understanding polymyxin chemistry, mechanisms of antibacterial activity and resistance, structure-activity relationships and pharmacokinetics/pharmacodynamics. In the 'Bad Bugs, No Drugs era, we must pursue structure-activity relationship-based approaches to develop novel polymyxin-like lipopeptides targeting polymyxin-resistant Gram-negative 'superbugs . Before new antibiotics become available, we must optimize the clinical use of polymyxins through the application of pharmacokinetic/pharmacodynamic principles, thereby minimizing the development of resistance.