Small Molecule Drug Development Research Articles

Development of small molecule drugs targeting immune checkpoints.

Immune checkpoint inhibitors (ICIs) are used to relieve and refuel anti-tumor immunity by blocking the interaction, transcription, and translation of co-inhibitory immune checkpoints or degrading co-inhibitory immune checkpoints. Thousands of small molecule drugs or biological materials, especially antibody-based ICIs, are actively being studied and antibodies are currently widely used. Limitations, such as anti-tumor efficacy, poor membrane permeability, and unneglected tolerance issues of antibody-based ICIs, remain evident but are thought to be overcome by small molecule drugs. Recent structural studies have broadened the scope of candidate immune checkpoint molecules, as well as innovative chemical inhibitors. By way of comparison, small molecule drug-based ICIs represent superior oral bioavailability and favorable pharmacokinetic features. Several ongoing clinical trials are exploring the synergetic effect of ICIs and other therapeutic strategies based on multiple ICI functions, including immune regulation, anti-angiogenesis, and cell cycle regulation. In this review we summarized the current progression of small molecule ICIs and the mechanism underlying immune checkpoint proteins, which will lay the foundation for further exploration.

AttSiOff: a self-attention-based approach on siRNA design with inhibition and off-target effect prediction

Small interfering RNA (siRNA) is often used for function study and expression regulation of specific genes, as well as the development of small molecule drugs. Selecting siRNAs with high inhibition and low off-target effects from massive candidates is always a great challenge. Increasing experimentally-validated samples can prompt the development of machine-learning-based algorithms, including Support Vector Machine (SVM), Convolutional Neural Network (CNN), and Graph Neural Network (GNN). However, these methods still suffer from limited accuracy and poor generalization in designing potent and specific siRNAs.In this study, we propose a novel approach for siRNA inhibition and off-target effect prediction, named AttSiOff. It combines a self-attention-based siRNA inhibition predictor with an mRNA searching package and an off-target filter. The predictor gives the inhibition score via analyzing the embedding of siRNA and local mRNA sequences, generated from the pre-trained RNA-FM model, as well as other meaningful prior-knowledge-based features. Self-attention mechanism can detect potentially decisive features, which may determine the inhibition of siRNA. It captures global and local dependencies more efficiently than normal convolutions. The tenfold cross-validation results indicate that our model outperforms all existing methods, achieving PCC of 0.81, SPCC of 0.84, and AUC of 0.886. It also reaches better performance of generalization and robustness on cross-dataset validation. In addition, the mRNA searching package could find all mature mRNAs for a given gene name from the GENOMES database, and the off-target filter can calculate the amount of unwanted off-target binding sites, which affects the specificity of siRNA. Experiments on five mature siRNA drugs, as well as a new target gene (AGT), show that AttSioff has excellent convenience and operability in practical applications.Graphical

Gaussian accelerated molecular dynamics simulations facilitate prediction of the permeability of cyclic peptides.

Despite their widespread use as therapeutics, clinical development of small molecule drugs remains challenging. Among the many parameters that undergo optimization during the drug development process, increasing passive cell permeability (i.e., log(P)) can have some of the largest impact on potency. Cyclic peptides (CPs) have emerged as a viable alternative to small molecules, as they retain many of the advantages of small molecules (oral availability, target specificity) while being highly effective at traversing the plasma membrane. However, the relationship between the dominant conformations that typify CPs in an aqueous versus a membrane environment and cell permeability remain poorly characterized. In this study, we have used Gaussian accelerated molecular dynamics (GaMD) simulations to characterize the effect of solvent on the free energy landscape of lariat peptides, a subset of CPs that have recently shown potential for drug development (Kelly et al., JACS 2021). Differences in the free energy of lariat peptides as a function of solvent can be used to predict permeability of these molecules, and our results show that permeability is most greatly influenced by N-methylation and exposure to solvent. Our approach lays the groundwork for using GaMD as a way to virtually screen large libraries of CPs and drive forward development of CP-based therapeutics.

Abstract 1352: Computational design of a cyclic peptide that inhibits the CTLA4 in T cells and the growth of lung carcinoma in mice

Abstract Proteins involved in immune checkpoint pathways, such as CTLA4, PD-1, and PD-L1, have become important targets for cancer immunotherapy; however, the development of small molecule drugs targeting these pathways has proven difficult due to the nature of their protein-protein interfaces. Here, using a hierarchy of computational techniques, we designed a cyclic peptide that binds CTLA4 and follow this with experimental verification of binding and biological activity, using bio-layer interferometry, cell culture, and a lung cancer mouse model in immunocompetent mice. Beginning from a template excised from the x-ray structure of the CTLA4:B7-2 complex, we generate several peptide sequences using Rosetta, a protein modelling program. These peptides are cyclized head-to-tail to improve structural and proteolytic stability and screened using molecular dynamics simulation and MM-GBSA calculation. The standard binding free energies for shortlisted peptides are then calculated in explicit-solvent simulation using a rigorous multistep Binding Free Energy Estimator (BFEE). The most promising peptide, cyc-EIDTVLTPTGWVAKRYS (hereafter CTLA4-ip), yields the standard free energy -6.6 ± 3.5 kcal/mol, which corresponds to a dissociation constant of 15 μmol/L. The binding affinity of this peptide for CTLA4 is measured experimentally (31 ± 4 μmol/L) using bio-layer interferometry. Pharmacokinetics of CTLA4-ip in a cell culture with Lewis lung carcinoma (LLC) cells and in mice revealed that this peptide is significantly more stable in both cell culture and in mice as compared to a control non-cyclic scrambled-sequence. Treatment with CTLA4-ip inhibited cancer cell growth in a co-culture of LLC cells and LLC cell-antigen primed murine T cells. Intraperitoneal administration of the CTLA4-ip (10mg/kg/day, every other day totaling 4 doses) markedly inhibited lung tumor growth in mice with an orthotropic LLC allograft model. Efficacy of the tumor growth inhibition by the CTLA4-ip was similar to that by an anti-PD-L1 antibody (10mg/kg/day, every two days totaling 3 doses). These results strongly suggest that this novel CTLA4-ip works as an immune checkpoint inhibitor to CTLA4 and is usable for lung cancer treatment. This research was supported by Kansas State University Johnson Cancer Research center (MT), Midwest Biomedical Accelerator Consortium (MT, JC), National Cancer Institute MT, JC) and the National Science Foundation (JC). Citation Format: Ravindra Thakkar, Deepa Upreti, Susumu Ishiguro, Geraldine Magnin, Keshari Sudasinghe, Anabelle Hall, Sarah DeVader, Masaaki Tamura, Jeffrey Comer. Computational design of a cyclic peptide that inhibits the CTLA4 in T cells and the growth of lung carcinoma in mice [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1352.

BMP2-ERK-ATF4 Axis-Based 6-methoxybenzofuran Compound I-9 Acts as Candidate Drug for Bone Formation and Anti-Osteoporosis.

As the global population ages, the number of patients with osteoporosis is rapidly rising. The existing first-line clinical drugs are bone resorption inhibitors that have difficulty restoring the bone mass of elderly patients to the safe range. The range and period of use of existing peptides and monoclonal antibodies are limited, and small-molecule bone formation-promoting drugs are urgently required. We established an I-9 synthesis route with high yield, simple operation, and low cost that was suitable for future large-scale production. I-9 administration promoted bone formation and increased bone mass in mice with low bone mass in an aged C57 mouse model. Our findings revealed a hitherto undescribed pathway involving the BMP2-ERK-ATF4 axis that promotes osteoblast differentiation; I-9 has favorable biosafety in mice. This study systematically investigated the efficacy, safety, and mechanism of I-9 for treating osteoporosis and positions this drug for preclinical research in the future. Thus, this study has promoted the development of small-molecule bone-promoting drugs.

Mining the Metabolic Capacity of Clostridium sporogenes Aided by Machine Learning.

Anaerobes dominate the microbiota of the gastrointestinal (GI) tract, where a significant portion of small molecules can be degraded or modified. However, the enormous metabolic capacity of gut anaerobes remains largely elusive in contrast to aerobic bacteria, mainly due to the requirement of sophisticated laboratory settings. In this study, we employed an in silico machine learning platform, MoleculeX, to predict the metabolic capacity of a gut anaerobe, Clostridium sporogenes, against small molecules. Experiments revealed that among the top seven candidates predicted as unstable, six indeed exhibited instability in C. sporogenes culture. We further identified several metabolites resulting from the supplementation of everolimus in the bacterial culture for the first time. By utilizing bioinformatics and in vitro biochemical assays, we successfully identified an enzyme encoded in the genome of C. sporogenes responsible for everolimus transformation. Our framework thus can potentially facilitate future understanding of small molecules metabolism in the gut, further improve patient care through personalized medicine, and guide the development of new small molecule drugs and therapeutic approaches.

Recent Advances in Real-Time Label-Free Detection of Small Molecules.

The detection and analysis of small molecules, typically defined as molecules under 1000 Da, is of growing interest ranging from the development of small-molecule drugs and inhibitors to the sensing of toxins and biomarkers. However, due to challenges such as their small size and low mass, many biosensing technologies struggle to have the sensitivity and selectivity for the detection of small molecules. Notably, their small size limits the usage of labeled techniques that can change the properties of small-molecule analytes. Furthermore, the capability of real-time detection is highly desired for small-molecule biosensors' application in diagnostics or screening. This review highlights recent advances in label-free real-time biosensing technologies utilizing different types of transducers to meet the growing demand for small-molecule detection.

Enhancing Predictions of Drug Solubility through Multidimensional Structural Characterization Exploitation.

Solubility is not only a significant physical property of molecules but also a vital factor in smallmolecule drug development. Determining drug solubility demands stringent equipment, controlled environments, and substantial human and material resources. The accurate prediction of drug solubility using computational methods has long been a goal for researchers. In this study, we introduce MSCSol, a solubility prediction model that integrates multidimensional molecular structure information. We incorporate a graph neural network with geometric vector perceptrons (GVP-GNN) to encode 3D molecular structures, representing spatial arrangement and orientation of atoms, as well as atomic sequences and interactions. We also employ Selective Kernel Convolution combined with Global and Local attention mechanisms to capture molecular features context at different scales. Additionally, various descriptors are calculated to enrich the molecular representation. For the 2D and 3D structural data of molecules, we design different data augmentation strategies to enhance generalization ability and prevent the model from learning irrelevant information. Extensive experiments on benchmark and independent datasets demonstrate MSCSol's superior performance. Ablation studies further confirm the effectiveness of different modules. Interpretability analysis highlights the importance of various atomic groups and substructures for solubility and verifies that our model effectively captures functional molecular structures and higher-order knowledge. The source code and datasets are freely available at https://github.com/ZiyuFanCSU/MSCSol.

In situ visualization of the cellular uptake and sub-cellular distribution of mussel oligosaccharides

Unlike chemosynthetic drugs designed for specific molecular and disease targets, active small-molecule natural products typically have a wide range of bioactivities and multiple targets, necessitating extensive screening and development. To address this issue, we propose a strategy for the direct in situ microdynamic examination of potential drug candidates to rapidly identify their effects and mechanisms of action. As a proof-of-concept, we investigated the behavior of mussel oligosaccharide (MOS-1) by tracking the subcellular dynamics of fluorescently labeled MOS-1 in cultured cells. We recorded the entire dynamic process of the localization of fluorescein isothiocyanate (FITC)-mussel oligosaccharide (MOS-1) to the lysosomes and visualized the distribution of the drug within the cell. Remarkably, lysosomes containing FITC-MOS-1 actively recruited lipid droplets, leading to fusion events and increased cellular lipid consumption. These drug behaviors confirmed MOS-1 is a candidate for the treatment of lipid-related diseases. Furthermore, in a high-fat HepG2 cell model and in high-fat diet-fed ApoE−/− mice, MOS-1 significantly promoted triglyceride degradation, reduced lipid droplet accumulation, lowered serum triglyceride levels, and mitigated liver damage and steatosis. Overall, our work supports the prioritization of in situ visual monitoring of drug location and distribution in subcellular compartments during the drug development phase as this methodology contributes to the rapid identification of drug indications. Collectively, this methodology is significant for the screening and development of selective small-molecule drugs, and is expected to expedite the identification of candidate molecules with medicinal effects.

Animal-sourced model of human norovirus infection predicted using environmental DNA metabarcoding analysis

Human noroviruses (HNVs) are one of the major causes of food poisoning and severe gastroenteritis. However, prevention and medical treatment of HNV disease is underdeveloped due to the lack of ecological understanding of the HNVs including their host organisms. We address the potential source animals of HNVs based on the environmental DNA metabarcoding analysis. By focusing on the HNV-epidemic area in Japan, we found several bird species of ducks, pochards, carrion crow, and swan showing significant cross-correlation with the HNV detection from cultured oysters. Humans and livestock mammals do not exhibit correlation with HNVs. These results suggest an avian-sourced, non-human- or sewage-mediated model of HNV infection. Unraveling the unknown host animals of pathogens like HNV facilitates artificial propagation of the pathogen, leading to vaccine and small molecule drug development.

Intrinsic Solubility of Ionizable Compounds from pKa Shift.

Aqueous solubility of pharmaceutical substances plays an important role in small molecule drug discovery and development, with ionizable groups often employed to enhance solubility. Drug candidate compounds often contain ionizable groups to increase their solubility. Recognizing that the electrostatically charged form of the compound is much more soluble than the uncharged form, this work proposes a model to explore the relationship between the pKa shift of the ionizable group and dissolution equilibria. The model considers three forms of a compound: dissolved-charged, dissolved-uncharged, and aggregated-uncharged. It analyzes two linked equilibria: the protonation of the ionizable group and the dissolution-aggregation of the uncharged form, with the observed pKa shift depending on the total concentration of the compound. The active concentration of the aggregates determines this shift. The model was explored through the determination of the pKa shift and intrinsic solubility of specific compounds, such as ICPD47, a high-affinity inhibitor of the Hsp90 chaperone protein and anticancer target, as well as benzoic acid and benzydamine. The model holds the potential for a more nuanced understanding of intrinsic solubility and may lead to advancements in drug discovery and development.

Identification of 2,4-Diaminoquinazoline Derivative as a Potential Small-Molecule Inhibitor against Chikungunya and Ross River Viruses

Alphaviruses are serious zoonotic threats responsible for significant morbidity, causing arthritis or encephalitis. So far, no licensed drugs or vaccines are available to combat alphaviral infections. About 300,000 chikungunya virus (CHIKV) infections have been reported in 2023, with more than 300 deaths, including reports of a few cases in the USA as well. The discovery and development of small-molecule drugs have been revolutionized over the last decade. Here, we employed a cell-based screening approach using a series of in-house small-molecule libraries to test for their ability to inhibit CHIKV replication. DCR 137, a quinazoline derivative, was found to be the most potent inhibitor of CHIKV replication in our screening assay. Both, the cytopathic effect, and immunofluorescence of infected cells were reduced in a dose-dependent manner with DCR 137 post-treatment. Most importantly, DCR 137 was more protective than the traditional ribavirin drug and reduced CHIKV plaque-forming units by several log units. CHIKV-E2 protein levels were also reduced in a dose-dependent manner. Further, DCR 137 was probed for its antiviral activity against another alphavirus, the Ross River virus, which revealed effective inhibition of viral replication. These results led to the identification of a potential quinazoline candidate for future optimization that might act as a pan-alphavirus inhibitor.

Small-Molecule Antibiotic Drug Development: Need and Challenges.

The need for new antibiotics is urgent. Antimicrobial resistance is rising, although currently, many more people die from drug-sensitive bacterial infections. The continued evolution of drug resistance is inevitable, fueled by pathogen population size and exposure to antibiotics. Additionally, opportunistic pathogens will always pose a threat to vulnerable patients whose immune systems cannot efficiently fight them even if they are sensitive to available antibiotics, according to clinical microbiology tests. These problems are intertwined and will worsen as human populations age, increase in density, and experience disruptions such as war, extreme weather events, or declines in standard of living. The development of appropriate drugs to treat all the world's bacterial infections should be a priority, and future success will likely require combinations of multiple approaches. However, the highest burden of bacterial infection is in Low- and Middle-Income Countries, where limited medical infrastructure is a major challenge. For effectively managing infections in these contexts, small-molecule-based treatments offer significant advantages. Unfortunately, support for ongoing small-molecule antibiotic discovery has recently suffered from significant challenges related both to the scientific difficulties in treating bacterial infections and to market barriers. Nevertheless, small-molecule antibiotics remain essential and irreplaceable tools for fighting infections, and efforts to develop novel and improved versions deserve ongoing investment. Here, we first describe the global historical context of antibiotic treatment and then highlight some of the challenges surrounding small-molecule development and potential solutions. Many of these challenges are likely to be common to all modalities of antibacterial treatment and should be addressed directly.

Roles of Nuclear Receptors in Esophageal Cancer.

Esophageal cancer (EC), including esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC), is a highly prevalent malignancy that occurs predominantly in the Asian region and is related to ethnicity, genetics, diet, and lifestyle. The nuclear receptor (NR) superfamily consists of 48 members of the human body. It is a collection of a large class of transcription factors, including Peroxisome proliferator-activated receptors (PPARs), Farnesol X receptor (FXR), Vitamin D receptor (VDR), Retinoic acid receptor (RAR), Pregnane X receptor (PXR), Androgen receptor (AR) and so on. Several NRs have been detected as oncogenes or tumor suppressors in EC progression. NRs are associated with the progression of many cancers, including EC. Some NRs, such as PPARs and FXR, play an important role in EC. Studying the molecular mechanism of NRs in EC is helpful for further understanding the development of EC. Preclinical research and development of small molecule compound drugs targeting NRs have provided new ideas for the potential targeted therapy of EC. This review summarizes the studies on NRs in EC in recent years, mainly including in vitro cell experiments and in vivo animal experiments. NRs influence EC progress in a variety of ways. They mainly affect the proliferation, migration and drug resistance of EC cells by affecting key cancer cell signaling pathways. Activation or inhibition of NRs inhibits or promotes EC progression, depending on EC types and tumor stages. Preclinical studies mainly focus on the development of small molecule drugs for targeting NRs (such as PPARγ agonists, PPARδ inhibitors, and FXR agonists), and agonists or inhibitors of NRs will become a potential therapeutic regimen for EC. The studies on the roles of NRs in EC have provided a theoretical basis for us to further understand the pathogenesis of EC and develop potential therapeutic drugs targeting NRs for the treatment of different diseases.

The Magic Methyl and Its Tricks in Drug Discovery and Development.

One of the key scientific aspects of small-molecule drug discovery and development is the analysis of the relationship between its chemical structure and biological activity. Understanding the effects that lead to significant changes in biological activity is of paramount importance for the rational design and optimization of bioactive molecules. The "methylation effect", or the "magic methyl" effect, is a factor that stands out due to the number of examples that demonstrate profound changes in either pharmacodynamic or pharmacokinetic properties. In many cases, this has been carried out rationally, but in others it has been the product of serendipitous observations. This paper summarizes recent examples that provide an overview of the current state of the art and contribute to a better understanding of the methylation effect in bioactive small-molecule drug candidates.

In Silico Evaluation of HN-N07 Small Molecule as an Inhibitor of Angiogenesis and Lymphangiogenesis Oncogenic Signatures in Non-Small Cell Lung Cancer.

Tumor angiogenesis and lymphangiogenesis pathways have been identified as important therapeutic targets in non-small cell lung cancer (NSCLC). Bevacizumab, which is a monoclonal antibody, was the initial inhibitor of angiogenesis and lymphangiogenesis that received approval for use in the treatment of advanced non-small cell lung cancer (NSCLC) in combination with chemotherapy. Despite its usage, patients may still develop resistance to the treatment, which can be attributed to various histological subtypes and the initiation of treatment at advanced stages of cancer. Due to their better specificity, selectivity, and safety compared to chemotherapy, small molecules have been approved for treating advanced NSCLC. Based on the development of multiple small-molecule antiangiogenic drugs either in house and abroad or in other laboratories to treat NSCLC, we used a quinoline-derived small molecule-HN-N07-as a potential target drug for NSCLC. Accordingly, we used computational simulation tools and evaluated the drug-likeness properties of HN-N07. Moreover, we identified target genes, resulting in the discovery of the target BIRC5/HIF1A/FLT4 pro-angiogenic genes. Furthermore, we used in silico molecular docking analysis to determine whether HN-N07 could potentially inhibit BIRC5/HIF1A/FLT4. Interestingly, the results of docking HN-N07 with the BIRC5, FLT4, and HIF1A oncogenes revealed unique binding affinities, which were significantly higher than those of standard inhibitors. In summary, these results indicate that HN-N07 shows promise as a potential inhibitor of oncogenic signaling pathways in NSCLC. Ongoing studies that involve in vitro experiments and in vivo investigations using tumor-bearing mice are in progress, aiming to evaluate the therapeutic effectiveness of the HN-N07 small molecule.

Considerations regarding the use of nonhuman primates in assessing safety endpoints for pharmaceuticals

Nonhuman primates (NHP) have become a commonly used nonrodent species for general toxicity testing for pharmaceuticals reviewed by CDER. Their increased use in pharmaceutical testing appears to have been driven by both increased use in small molecule drug development programs as well as a trend for biologics making up a greater percentage of pharmaceutical development programs. While always in limited supply, the COVID-19 pandemic acutely impaired the availability of NHPs for pharmaceutical testing due to disruptions in the supply and an increased demand to support COVID-19-directed research programs. Because this disruption in the NHP supply had the potential to significantly delay the development of new medications for the treatment of diseases currently without effective treatment options, FDA issued guidance in February of 2022, under its COVID-19 Public Health Emergency authority, that was intended to help mitigate the NHP supply issue by reducing the demand for NHPs. This guidance has been withdrawn with the expiration of the public health emergency. Here we discuss what impact we expect that the withdrawal of this guidance will have on efforts to minimize NHP use.

Cage-shaped silsesquioxane with multiactive sites for impeding aggregation of small insoluble organic molecule

Organic drug small molecules with rigid π-electron conjugated structures have relatively strong dipole–dipole and π-π stacking interactions causing the drug aggregation in solution, the efficacy of which is limited. In this study, molecular aggregation was inhibited by increasing the spacing of organic molecules to more than 7 Å. Thiol-polyhedral olisesquioxane (POSS-SH) with eight active sites was selected as a stabilizer to increase the molecular spacing through a large number of density functional theory (DFT). After non-pharmacologically acting amino/hydroxyl groups in poorly soluble drugs was double-bonded with acryloyl chloride. The drugs were modified by POSS-SH through “click chemistry” to increase molecular spacing, so as to prevent π - π stacking and charge transfer. DFT and spectroscopic property studies showed that the molecular spacing of the drug modified by POSS-SH exceeded 8.063 Å, the increased spacing effectively inhibited the H- or J-aggregation then increasing the solubility of poorly soluble molecules to greater than 6.24 g/100 g (H2O). The introduction of POSS-SH improved the solubility of insoluble molecules and so the therapeutic effects exerted by POSS-SH-modified hybrid molecules on cells were superior to the unmodified drug. Improving the solubility of insoluble drugs through POSS-SH may represent an important breakthrough in small-molecule drug research and development.

Role of Conserved Tyrosine Lid Residues in the Activation of the M2 Muscarinic Acetylcholine Receptor.

The development of subtype selective small molecule drugs for the muscarinic acetylcholine receptor (mAChR) family has been challenging. The design of more selective ligands can be improved by understanding the structure and function of key amino acid residues that line ligand binding sites. Here we study the role of three conserved key tyrosine residues [Y1043.33, Y4036.51, and Y4267.39 (Ballesteros and Weinstein numbers in superscript)] at the human M2 mAChR, located at the interface between the orthosteric and allosteric binding sites of the receptor. We specifically focused on the role of the three tyrosine hydroxyl groups in the transition between the inactive and active conformations of the receptor by making phenylalanine point mutants. Single-point mutation at either of the three positions was sufficient to reduce the affinity of agonists by ∼100-fold for the M2 mAChR, whereas the affinity of antagonists remained largely unaffected. In contrast, neither of the mutations affected the efficacy of orthosteric agonists. When mutations were combined into double and triple M2 mAChR mutants, the affinity of antagonists was reduced by more than 100-fold compared with the wild-type M2 receptor. In contrast, the affinity of allosteric modulators, either negative or positive, was retained at all single and multiple mutations, but the degree of allosteric effect exerted on the endogenous ligand acetylcholine was affected at all mutants containing Y4267.39F. These findings will provide insights to consider when designing future mAChR ligands. SIGNIFICANCE STATEMENT: Structural studies demonstrated that three tyrosine residues between the orthosteric and allosteric sites of the M2 muscarinic acetylcholine receptor (mAChR) had different hydrogen bonding networks in the inactive and active conformations. The role of hydroxyl groups of the tyrosine residues on orthosteric and allosteric ligand pharmacology was unknown. We found that hydroxyl groups of the tyrosine residues differentially affected the molecular pharmacology of orthosteric and allosteric ligands. These results provide insights to consider when designing future mAChR ligands.

Recent Developments in Ultralarge and Structure-Based Virtual Screening Approaches.

Drug development is a wide scientific field that faces many challenges these days. Among them are extremely high development costs, long development times, and a small number of new drugs that are approved each year. New and innovative technologies are needed to solve these problems that make the drug discovery process of small molecules more time and cost efficient, and that allow previously undruggable receptor classes to be targeted, such as protein-protein interactions. Structure-based virtual screenings (SBVSs) have become a leading contender in this context. In this review, we give an introduction to the foundations of SBVSs and survey their progress in the past few years with a focus on ultralarge virtual screenings (ULVSs). We outline key principles of SBVSs, recent success stories, new screening techniques, available deep learning-based docking methods, and promising future research directions. ULVSs have an enormous potential for the development of new small-molecule drugs and are already starting to transform early-stage drug discovery.