Overview of computational methods employed in early-stage drug discovery

Patient-derived organoids in human cancer: a platform for fundamental research and precision medicine

Cancer is associated with a high degree of heterogeneity, encompassing both inter- and intra-tumor heterogeneity, along with considerable variability in clinical response to common treatments across patients. Conventional models for tumor research, such as in vitro cell cultures and in vivo animal models, demonstrate significant limitations that fall short of satisfying the research requisites. Patient-derived tumor organoids, which recapitulate the structures, specific functions, molecular characteristics, genomics alterations and expression profiles of primary tumors. They have been efficaciously implemented in illness portrayal, mechanism exploration, high-throughput drug screening and assessment, discovery of innovative therapeutic targets and potential compounds, and customized treatment regimen for cancer patients. In contrast to conventional models, tumor organoids offer an intuitive, dependable, and efficient in vitro research model by conserving the phenotypic, genetic diversity, and mutational attributes of the originating tumor. Nevertheless, the organoid technology also confronts the bottlenecks and challenges, such as how to comprehensively reflect intra-tumor heterogeneity, tumor microenvironment, tumor angiogenesis, reduce research costs, and establish standardized construction processes while retaining reliability. This review extensively examines the use of tumor organoid techniques in fundamental research and precision medicine. It emphasizes the importance of patient-derived tumor organoid biobanks for drug development, screening, safety evaluation, and personalized medicine. Additionally, it evaluates the application of organoid technology as an experimental tumor model to better understand the molecular mechanisms of tumor. The intent of this review is to explicate the significance of tumor organoids in cancer research and to present new avenues for the future of tumor research.

Putative histidine kinase inhibitors with antibacterial effect against multi-drug resistant clinical isolates identified by in vitro and in silico screens

Novel antibacterials are urgently needed to address the growing problem of bacterial resistance to conventional antibiotics. Two-component systems (TCS) are widely used by bacteria to regulate gene expression in response to various environmental stimuli and physiological stress and have been previously proposed as promising antibacterial targets. TCS consist of a sensor histidine kinase (HK) and an effector response regulator. The HK component contains a highly conserved ATP-binding site that is considered to be a promising target for broad-spectrum antibacterial drugs. Here, we describe the identification of putative HK autophosphorylation inhibitors following two independent experimental approaches: in vitro fragment-based screen via differential scanning fluorimetry and in silico structure-based screening, each followed up by the exploration of analogue compounds as identified by ligand-based similarity searches. Nine of the tested compounds showed antibacterial effect against multi-drug resistant clinical isolates of bacterial pathogens and include three novel scaffolds, which have not been explored so far in other antibacterial compounds. Overall, putative HK autophosphorylation inhibitors were found that together provide a promising starting point for further optimization as antibacterials.

NMR in drug discovery on membrane proteins

Drug discovery on membrane proteins is still a difficult task, despite the recognized importance of membrane proteins as drug targets. Here, we present an overview of NMR methods available for structure-based drug design on membrane proteins. NMR spectroscopy is capable of identifying potential binders in screening and defining their relative binding constants, binding stoichiometry, conformation in the binding pocket and the relative binding orientation for binders of different series. Examples are given in the review highlighting the potential of NMR spectroscopy for future progress in drug discovery on membrane proteins.

Phenylalanine hydroxylase misfolding and pharmacological chaperones

Phenylketonuria (PKU) is a loss-of-function inborn error of metabolism. As many other inherited diseases the main pathologic mechanism in PKU is an enhanced tendency of the mutant phenylalanine hydroxylase (PAH) to misfold and undergo ubiquitin-dependent degradation. Recent alternative approaches with therapeutic potential for PKU aim at correcting the PAH misfolding, and in this respect pharmacological chaperones are the focus of increasing interest. These compounds, which often resemble the natural ligands and show mild competitive inhibition, can rescue the misfolded proteins by stimulating their renaturation in vivo. For PKU, a few studies have proven the stabilization of PKU-mutants in vitro, in cells, and in mice by pharmacological chaperones, which have been found either by using the tetrahydrobiopterin (BH(4)) cofactor as query structure for shape-focused virtual screening or by high-throughput screening of small compound libraries. Both approaches have revealed a number of compounds, most of which bind at the iron-binding site, competitively with respect to BH(4). Furthermore, PAH shares a number of ligands, such as BH(4), amino acid substrates and inhibitors, with the other aromatic amino acid hydroxylases: the neuronal/neuroendocrine enzymes tyrosine hydroxylase (TH) and the tryptophan hydroxylases (TPHs). Recent results indicate that the PAH-targeted pharmacological chaperones should also be tested on TH and the TPHs, and eventually be derivatized to avoid unwanted interactions with these other enzymes. After derivatization and validation in animal models, the PAH-chaperoning compounds represent novel possibilities in the treatment of PKU.

Allosteric inhibition of the hepatitis C virus NS5B polymerase: in silico strategies for drug discovery and development

Chronic infection by hepatitis C virus (HCV) often leads to severe liver disease including cirrhosis, hepatocellular carcinoma and liver failure. Despite it being more than 20 years since the identification of HCV, the current standard of care for treating the infection is based on aspecific therapy often associated with severe side effects and low-sustained virological response. Research is ongoing to develop new and better medications, including a broad range of allosteric NS5B polymerase inhibitors. This article reviews traditional computational methodologies and more recently developed in silico strategies aimed at identifying and optimizing non-nucleoside inhibitors targeting allosteric sites of HCV NS5B polymerase. The drug-discovery approaches reviewed could provide take-home lessons for general computer-aided research projects.

Computer tools in the discovery of HIV-1 integrase inhibitors

Computer-aided drug design (CADD) methodologies have made great advances and contributed significantly to the discovery and/or optimization of many clinically used drugs in recent years. CADD tools have likewise been applied to the discovery of inhibitors of HIV-1 integrase, a difficult and worthwhile target for the development of efficient anti-HIV drugs. This article reviews the application of CADD tools, including pharmacophore search, quantitative structure-activity relationships, model building of integrase complexed with viral DNA and quantum-chemical studies in the discovery of HIV-1 integrase inhibitors. Different structurally diverse integrase inhibitors have been identified by, or with significant help from, various CADD tools.