Mechanism of Action and Target Identification: A Matter of Timing in Drug Discovery

Machine Learning for Toxicity Prediction Using Chemical Structures: Pillars for Success in the Real World

Machine learning (ML) is increasingly valuable for predicting molecular properties and toxicity in drug discovery. However, toxicity-related end points have always been challenging to evaluate experimentally with respect to in vivo translation due to the required resources for human and animal studies; this has impacted data availability in the field. ML can augment or even potentially replace traditional experimental processes depending on the project phase and specific goals of the prediction. For instance, models can be used to select promising compounds for on-target effects or to deselect those with undesirable characteristics (e.g., off-target or ineffective due to unfavorable pharmacokinetics). However, reliance on ML is not without risks, due to biases stemming from nonrepresentative training data, incompatible choice of algorithm to represent the underlying data, or poor model building and validation approaches. This might lead to inaccurate predictions, misinterpretation of the confidence in ML predictions, and ultimately suboptimal decision-making. Hence, understanding the predictive validity of ML models is of utmost importance to enable faster drug development timelines while improving the quality of decisions. This perspective emphasizes the need to enhance the understanding and application of machine learning models in drug discovery, focusing on well-defined data sets for toxicity prediction based on small molecule structures. We focus on five crucial pillars for success with ML-driven molecular property and toxicity prediction: (1) data set selection, (2) structural representations, (3) model algorithm, (4) model validation, and (5) translation of predictions to decision-making. Understanding these key pillars will foster collaboration and coordination between ML researchers and toxicologists, which will help to advance drug discovery and development.

Total Synthesis and Pharmacological Evaluation of Phochrodines A-C

The first syntheses of the Phomopsis-isolated natural products phochrodines A-C are reported. Functional group manipulations on a key 5H-chromeno[4,3-b]pyridine intermediate, itself synthesized from intramolecular Suzuki-Miyaura coupling, enabled facile and high-yielding syntheses of all three natural products. Additionally, sufficient material was generated to enable detailed pharmacological profiling of each compound. Preliminary drug metabolism and pharmacokinetic (DMPK) experiments and ancillary pharmacology screening revealed phochrodine C (3) as an attractive scaffold for further modification, particularly for medicinal chemists working in the antidepressant space.

Comprehensive Characterization of Bruton's Tyrosine Kinase Inhibitor Specificity, Potency, and Biological Effects: Insights into Covalent and Noncovalent Mechanistic Signatures

Uncovering a drug's mechanism of action and possible adverse effects are critical components in drug discovery and development. Moreover, it provides evidence for why some drugs prove more effective than others and how to design better drugs altogether. Here, we demonstrate the utility of a high-throughput in vitro screening platform along with a comprehensive panel to aid in the characterization of 15 Bruton's tyrosine kinase (BTK) inhibitors that are either approved by the FDA or presently under clinical evaluation. To compare the potency of these drugs, we measured the binding affinity of each to wild-type BTK as well as a clinically relevant resistance mutant of BTK (BTK C481S). In doing so, we discovered a considerable difference in the selectivity and potency of these BTK inhibitors to the wild-type and mutant proteins. Some of this potentially contributes to the adverse effects experienced by patients undergoing therapy using these drugs. Overall, noncovalent BTK inhibitors showed stronger potency for both the wild-type and mutant BTK when compared with that of covalent inhibitors, with the majority demonstrating a higher specificity and less off-target modulation. Additionally, we compared biological outcomes for four of these inhibitors in human cell-based models. As expected, we found different phenotypic profiles for each inhibitor. However, the two noncovalent inhibitors had fewer off-target biological effects when compared with the two covalent inhibitors. This and similar in-depth preclinical characterization of drug candidates can provide critical insights into the efficacy and mechanism of action of a compound that may affect its safety in a clinical setting.

PregMedNet: Multifaceted Maternal Medication Impacts on Neonatal Complications

While medication intake is common among pregnant women, medication safety remains underexplored, leading to unclear guidance for patients and healthcare professionals. PregMedNet addresses this gap by providing a multifaceted maternal medication safety framework based on systematic analysis of 1.19 million mother-baby dyads from U.S. claims databases. A novel confounding adjustment pipeline was applied to systematically control confounders for multiple medication-disease pairs, robustly identifying both known and novel maternal medication effects. Notably, one of the newly discovered associations was experimentally validated, demonstrating the reliability of claims data and machine learning for perinatal medication safety studies. Additionally, potential biological mechanisms of newly identified associations were generated using a graph learning method. These findings highlight PregMedNet's value in promoting safer medication use during pregnancy and maternal-neonatal outcomes.

Local Antimicrobial Potential of Bupivacaine and Tolfenamic Acid-Loaded Ultra-High Molecular Weight Polyethylene (UHMWPE) for Orthopedic Infection

Peri-prosthetic joint infection (PJI) is a major post-arthroplasty complication that warrants alternative antibacterial approaches to improve prophylaxis and treatment outcomes. Local administration of analgesics post-surgery is common. Recent studies have demonstrated the antimicrobial potential of analgesics and the feasibility of dual drug-eluting ultra-high molecular weight polyethylene (UHMWPE) for local antibacterial applications. However, the antibacterial mechanism of action is poorly understood, and the translational value of antimicrobial dual drug-loaded UHMWPE has not been evaluated. In this study, we utilized the Laurdan assay and gene expression analysis to demonstrate the antibacterial action of bupivacaine hydrochloride (BP) and tolfenamic acid (TA) against Staphylococcus aureus. Furthermore, we incorporated BP and TA into UHMWPE at different weight concentrations and studied their longitudinal drug release and real-time antibacterial properties. The analgesics showed a significant effect on the bacterial membrane properties comparable to known antibiotics and regulated bacterial gene expression. For the dual drug-loaded UHMWPE, the drug release rate from BP/TA combinations was interestingly not a direct function of the loaded drug weight percent, potentially due to the hydrophobicity of TA and the interactions between the two drugs. Combinations of BP and TA at the higher total drug concentration (10 and 20%) showed a prolonged antibacterial effect against S. aureus, with great potential for prophylactic use.

Better understanding the phenotypic effects of drugs through shared targets in genetic disease networks

Introduction

Most drugs fail during development and there is a clear and unmet need for approaches to better understand mechanistically how drugs exert both their intended and adverse effects. Gaining traction in this field is the use of disease data linking genes with pathological phenotypes and combining this with drugtarget interaction data.

Methods

We introduce methodology to associate drugs with effects, both intended and adverse, using a tripartite network approach that combines drug-target and target-phenotype data, in which targets can be represented as proteins and protein domains.

Results

We were able to detect associations for over 140,000 ChEMBL drugs and 3,800 phenotypes, represented as Human Phenotype Ontology (HPO) terms. The overlap of these results with the SIDER databases of known drug side effects was up to 10 times higher than random, depending on the target type, disease database and score threshold used. In terms of overlap with drug-phenotype pairs extracted from the literature, the performance of our methodology was up to 17.47 times greater than random. The top results include phenotype-drug associations that represent intended effects, particularly for cancers such as chronic myelogenous leukemia, which was linked with nilotinib. They also include adverse side effects, such as blurred vision being linked with tetracaine.

Discussion

This work represents an important advance in our understanding of how drugs cause intended and adverse side effects through their action on disease causing genes and has potential applications for drug development and repositioning.

Uncovering the Mechanism of Action of Antiprotozoal Agents: A Survey on Photoaffinity Labeling Strategy

Plasmodium, Leishmania, and Trypanosoma parasites are responsible for infectious diseases threatening millions of people worldwide. Despite more recent efforts devoted to the search for new antiprotozoal agents, efficacy, safety, and resistance issues still hinder the development of suited therapeutic options. The lack of robustly validated targets and the complexity of parasite's diseases have made phenotypic screening a preferential drug discovery strategy for the identification of new chemical entities. However, via this approach, no information on biological target(s) and mechanisms of action of compounds are provided. Among the target deconvolution strategies useful to fill this gap, photoaffinity labeling (PAL) has emerged as one of most suited to enable investigation in a complex cellular environment. More recently, PAL has been exploited to unravel the molecular basis of bioactive compounds' function in live parasites, allowing elucidation of the mechanism of action of both approved drugs and new chemical entities. Besides highlighting new potential drug targets, PAL can provide valuable information on efficacy and liabilities of small molecules at the molecular level, which could be exploited to greatly facilitate the rational optimization of compounds in terms of potency and safety. In this review, we will report the most recent studies that have leveraged PAL to disclose the biological targets and mechanism of action of phenotypically active compounds targeting kinetoplastid diseases (i.e., human African trypanosomiasis, leishmaniasis, and Chagas disease) and malaria. Moreover, we will comment on potential perspectives that this innovative approach can provide in aiding the discovery and development of new antiprotozoal drugs.

Global Health Priority Box─Proactive Pandemic Preparedness

The coronavirus pandemic outbreak of 2019 highlighted the critical importance of preparedness for current and future public health threats (https://www.mmv.org/mmv-open/global-health-priority-box/about-global-health-priority-box). While the main attention for the past few years has been on COVID-19 research, this focus has reduced global resources on research in other areas, including malaria and neglected tropical diseases (NTDs). Such a shift in focus puts at risk the hard-earned progress in global health achieved over the past two decades (https://www.who.int/news-room/spotlight/10-global-health-issues-to-track-in-2021). To address the urgent need for new drugs to combat drug-resistant malaria, emerging zoonotic diseases, and vector control, Medicines for Malaria Venture (MMV) and Innovative Vector Control Consortium (IVCC) assembled a collection of 240 compounds and, in August 2022, launched the Global Health Priority Box (GHPB). This collection of compounds has confirmed activity against emerging pathogens or vectors and is available free of charge. This valuable tool enables researchers worldwide to build on each other's work and save precious time and resources by providing a starting point for the further development of treatments and insecticides. Furthermore, this open access box aligns with two of the many priorities outlined by the World Health Organization (WHO) (https://www.who.int/news-room/spotlight/10-global-health-issues-to-track-in-2021).

Common pitfalls in drug target Mendelian randomization and how to avoid them

BACKGROUND

Drug target Mendelian randomization describes the use of genetic variants as instrumental variables for studying the effects of pharmacological agents. The paradigm can be used to inform on all aspects of drug development and has become increasingly popular over the last decade, particularly given the time- and cost-efficiency with which it can be performed even before commencing clinical studies.

MAIN BODY

In this review, we describe the recent emergence of drug target Mendelian randomization, its common pitfalls, how best to address them, as well as potential future directions. Throughout, we offer advice based on our experiences on how to approach these types of studies, which we hope will be useful for both practitioners and those translating the findings from such work.

CONCLUSIONS

Drug target Mendelian randomization is nuanced and requires a combination of biological, statistical, genetic, epidemiological, clinical, and pharmaceutical expertise to be utilized to its full potential. Unfortunately, these skillsets are relatively infrequently combined in any given study.

Drug Mechanism: A bioinformatic update

A drug Mechanism of Action (MoA) is a complex biological phenomenon that describes how a bioactive compound produces a pharmacological effect. The complete knowledge of MoA is fundamental to fully understanding the drug activity. Over the years, many experimental methods have been developed and a huge quantity of data has been produced. Nowadays, considering the increasing omics data availability and the improvement of the accessible computational resources, the study of a drug MoA is conducted by integrating experimental and bioinformatics approaches. The development of new in silico solutions for this type of analysis is continuously ongoing; herein, an updating review on such bioinformatic methods is presented. The methodologies cited are based on multi-omics data integration in biochemical networks and Machine Learning (ML). The multiple types of usable input data and the advantages and disadvantages of each method have been analyzed, with a focus on their applications. Three specific research areas (i.e. cancer drug development, antibiotics discovery, and drug repurposing) have been chosen for their importance in the drug discovery fields in which the study of drug MoA, through novel bioinformatics approaches, is particularly productive.

What public health challenges and unmet medical needs would benefit from interdisciplinary collaboration in the EU? A survey and multi-stakeholder debate

In the past decade, significant European calls for research proposals have supported translational collaborative research on non-communicable and infectious diseases within the biomedical life sciences by bringing together interdisciplinary and multinational consortia. This research has advanced our understanding of disease pathophysiology, marking considerable scientific progress. Yet, it is crucial to retrospectively evaluate these efforts' societal impact. Research proposals should be thoughtfully designed to ensure that the research findings can be effectively translated into actionable policies. In addition, the choice of scientific methods plays a pivotal role in shaping the societal impact of research discoveries. Understanding the factors responsible for current unmet public health issues and medical needs is crucial for crafting innovative strategies for research policy interventions. A multistakeholder survey and a roundtable helped identify potential needs for consideration in the EU research and policy agenda. Based on survey findings, mental health disorders, metabolic syndrome, cancer, antimicrobial resistance, environmental pollution, and cardiovascular diseases were considered the public health challenges deserving prioritisation. In addition, early diagnosis, primary prevention, the impact of environmental pollution on disease onset and personalised medicine approaches were the most selected unmet medical needs. Survey findings enabled the formulation of some research-policies interventions (RPIs), which were further discussed during a multistakeholder online roundtable. The discussion underscored recent EU-level activities aligned with the survey-derived RPIs and facilitated an exchange of perspectives on public health and biomedical research topics ripe for interdisciplinary collaboration and warranting attention within the EU's research and policy agenda. Actionable recommendations aimed at facilitating the translation of knowledge into transformative, science-based policies are also provided.

The Millennia-Long Development of Drugs Associated with the 80-Year-Old Artificial Intelligence Story: The Therapeutic Big Bang?

The journey of drug discovery (DD) has evolved from ancient practices to modern technology-driven approaches, with Artificial Intelligence (AI) emerging as a pivotal force in streamlining and accelerating the process. Despite the vital importance of DD, it faces challenges such as high costs and lengthy timelines. This review examines the historical progression and current market of DD alongside the development and integration of AI technologies. We analyse the challenges encountered in applying AI to DD, focusing on drug design and protein-protein interactions. The discussion is enriched by presenting models that put forward the application of AI in DD. Three case studies are highlighted to demonstrate the successful application of AI in DD, including the discovery of a novel class of antibiotics and a small-molecule inhibitor that has progressed to phase II clinical trials. These cases underscore the potential of AI to identify new drug candidates and optimise the development process. The convergence of DD and AI embodies a transformative shift in the field, offering a path to overcome traditional obstacles. By leveraging AI, the future of DD promises enhanced efficiency and novel breakthroughs, heralding a new era of medical innovation even though there is still a long way to go.

Phenotypic drug discovery: a case for thymosin alpha-1

Phenotypic drug discovery (PDD) involves screening compounds for their effects on cells, tissues, or whole organisms without necessarily understanding the underlying molecular targets. PDD differs from target-based strategies as it does not require knowledge of a specific drug target or its role in the disease. This approach can lead to the discovery of drugs with unexpected therapeutic effects or applications and allows for the identification of drugs based on their functional effects, rather than through a predefined target-based approach. Ultimately, disease definitions are mostly symptom-based rather than mechanism-based, and the therapeutics should be likewise. In recent years, there has been a renewed interest in PDD due to its potential to address the complexity of human diseases, including the holistic picture of multiple metabolites engaging with multiple targets constituting the central hub of the metabolic host-microbe interactions. Although PDD presents challenges such as hit validation and target deconvolution, significant achievements have been reached in the era of big data. This article explores the experiences of researchers testing the effect of a thymic peptide hormone, thymosin alpha-1, in preclinical and clinical settings and discuss how its therapeutic utility in the precision medicine era can be accommodated within the PDD framework.

Spiro-Acridine Compound as a Pteridine Reductase 1 Inhibitor: in silico Target Fishing and in vitro Studies

Among the many neglected tropical diseases, leishmaniasis ranks second in mortality rate and prevalence. In a previous study, acridine derivatives were synthesized and tested for their antileishmanial activity against L. chagasi. The most active compound identified in that study (1) showed a single digit IC50 value against the parasite (1.10 μg/mL), but its macromolecular target remained unknown. Aiming to overcome this limitation, this work exploited inverse virtual screening to identify compound 1's putative molecular mechanism of action. In vitro assays confirmed that compound 1 binds to Leishmania chagasi pteridine reductase 1 (LcPTR1), with moderate affinity (Kd=33,1 μM), according to differential scanning fluorimetry assay. Molecular dynamics simulations confirm the stability of LcPTR1-compound 1 complex, supporting a competitive mechanism of action. Therefore, the workflow presented in this work successfully identified PTR1 as a macromolecular target for compound 1, allowing the designing of novel potent antileishmanial compounds.

Mechanism of action, potency and efficacy: considerations for cell therapies

One of the most challenging aspects of developing advanced cell therapy products (CTPs) is defining the mechanism of action (MOA), potency and efficacy of the product. This perspective examines these concepts and presents helpful ways to think about them through the lens of metrology. A logical framework for thinking about MOA, potency and efficacy is presented that is consistent with the existing regulatory guidelines, but also accommodates what has been learned from the 27 US FDA-approved CTPs. Available information regarding MOA, potency and efficacy for the 27 FDA-approved CTPs is reviewed to provide background and perspective. Potency process and efficacy process charts are introduced to clarify and illustrate the relationships between six key concepts: MOA, potency, potency test, efficacy, efficacy endpoint and efficacy endpoint test. Careful consideration of the meaning of these terms makes it easier to discuss the challenges of correlating potency test results with clinical outcomes and to understand how the relationships between the concepts can be misunderstood during development and clinical trials. Examples of how a product can be "potent but not efficacious" or "not potent but efficacious" are presented. Two example applications of the framework compare how MOA is assessed in cell cultures, animal models and human clinical trials and reveals the challenge of establishing MOA in humans. Lastly, important considerations for the development of potency tests for a CTP are discussed. These perspectives can help product developers set appropriate expectations for understanding a product's MOA and potency, avoid unrealistic assumptions and improve communication among team members during the development of CTPs.

Paradigm shift required for translational research on the brain

Biomedical research on the brain has led to many discoveries and developments, such as understanding human consciousness and the mind and overcoming brain diseases. However, historical biomedical research on the brain has unique characteristics that differ from those of conventional biomedical research. For example, there are different scientific interpretations due to the high complexity of the brain and insufficient intercommunication between researchers of different disciplines owing to the limited conceptual and technical overlap of distinct backgrounds. Therefore, the development of biomedical research on the brain has been slower than that in other areas. Brain biomedical research has recently undergone a paradigm shift, and conducting patient-centered, large-scale brain biomedical research has become possible using emerging high-throughput analysis tools. Neuroimaging, multiomics, and artificial intelligence technology are the main drivers of this new approach, foreshadowing dramatic advances in translational research. In addition, emerging interdisciplinary cooperative studies provide insights into how unresolved questions in biomedicine can be addressed. This review presents the in-depth aspects of conventional biomedical research and discusses the future of biomedical research on the brain.

Innovative strategies for measuring kinase activity to accelerate the next wave of novel kinase inhibitors

The development of protein kinase inhibitors (PKIs) has gained significance owing to their therapeutic potential for diseases like cancer. In addition, there has been a rise in refining kinase activity assays, each possessing unique biological and analytical characteristics crucial for PKI development. However, the PKI development pipeline experiences high attrition rates and approved PKIs exhibit unexploited potential because of variable patient responses. Enhancing PKI development efficiency involves addressing challenges related to understanding the PKI mechanism of action and employing biomarkers for precision medicine. Selecting appropriate kinase activity assays for these challenges can overcome these attrition rate issues. This review delves into the current obstacles in kinase inhibitor development and elucidates kinase activity assays that can provide solutions.

Drug development advances in human genetics-based targets

Drug development is a long and costly process, with a high degree of uncertainty from the identification of a drug target to its market launch. Targeted drugs supported by human genetic evidence are expected to enter phase II/III clinical trials or be approved for marketing more quickly, speeding up the drug development process. Currently, genetic data and technologies such as genome-wide association studies (GWAS), whole-exome sequencing (WES), and whole-genome sequencing (WGS) have identified and validated many potential molecular targets associated with diseases. This review describes the structure, molecular biology, and drug development of human genetics-based validated beneficial loss-of-function (LOF) mutation targets (target mutations that reduce disease incidence) over the past decade. The feasibility of eight beneficial LOF mutation targets (PCSK9, ANGPTL3, ASGR1, HSD17B13, KHK, CIDEB, GPR75, and INHBE) as targets for drug discovery is mainly emphasized, and their research prospects and challenges are discussed. In conclusion, we expect that this review will inspire more researchers to use human genetics and genomics to support the discovery of novel therapeutic drugs and the direction of clinical development, which will contribute to the development of new drug discovery and drug repurposing.

Progress interrogating TRPMPZQ as the target of praziquantel

The drug praziquantel (PZQ) has served as the long-standing drug therapy for treatment of infections caused by parasitic flatworms. These encompass diseases caused by parasitic blood, lung, and liver flukes, as well as various tapeworm infections. Despite a history of clinical usage spanning over 4 decades, the parasite target of PZQ has long resisted identification. However, a flatworm transient receptor potential ion channel from the melastatin subfamily (TRPMPZQ) was recently identified as a target for PZQ action. Here, recent experimental progress interrogating TRPMPZQ is evaluated, encompassing biochemical, pharmacological, genetic, and comparative phylogenetic data that highlight the properties of this ion channel. Various lines of evidence that support TRPMPZQ being the therapeutic target of PZQ are presented, together with additional priorities for further research into the mechanism of action of this important clinical drug.

Deciphering Drug Targets and Actions with Single-Cell and Spatial Resolution

Recent advances in chemical, molecular, and genetic approaches have provided us with an unprecedented capacity to identify drug-target interactions across the whole proteome and genome. Meanwhile, rapid developments of single-cell and spatial omics technologies are revolutionizing our understanding of the molecular architecture of biological systems. However, a significant gap remains in how we align our understanding of drug actions, traditionally based on molecular affinities, with the in vivo cellular and spatial tissue heterogeneity revealed by these newer techniques. Here, we review state-of-the-art methods for profiling drug-target interactions and emerging multiomics tools to delineate the tissue heterogeneity at single-cell resolution. Highlighting the recent technical advances enabling high-resolution, multiplexable in situ small-molecule drug imaging (clearing-assisted tissue click chemistry, or CATCH), we foresee the integration of single-cell and spatial omics platforms, data, and concepts into the future framework of defining and understanding in vivo drug-target interactions and mechanisms of actions.

The MSC-EV-microRNAome: A Perspective on Therapeutic Mechanisms of Action in Sepsis and ARDS

Mesenchymal stromal cells (MSCs) and MSC-derived extracellular vesicles (EVs) have emerged as innovative therapeutic agents for the treatment of sepsis and acute respiratory distress syndrome (ARDS). Although their potential remains undisputed in pre-clinical models, this has yet to be translated to the clinic. In this review, we focused on the role of microRNAs contained in MSC-derived EVs, the EV microRNAome, and their potential contribution to therapeutic mechanisms of action. The evidence that miRNA transfer in MSC-derived EVs has a role in the overall therapeutic effects is compelling. However, several questions remain regarding how to reconcile the stochiometric issue of the low copy numbers of the miRNAs present in the EV particles, how different miRNAs delivered simultaneously interact with their targets within recipient cells, and the best miRNA or combination of miRNAs to use as therapy, potency markers, and biomarkers of efficacy in the clinic. Here, we offer a molecular genetics and systems biology perspective on the function of EV microRNAs, their contribution to mechanisms of action, and their therapeutic potential.

Illuminating phenotypic drug responses of sarcoma cells to kinase inhibitors by phosphoproteomics

Kinase inhibitors (KIs) are important cancer drugs but often feature polypharmacology that is molecularly not understood. This disconnect is particularly apparent in cancer entities such as sarcomas for which the oncogenic drivers are often not clear. To investigate more systematically how the cellular proteotypes of sarcoma cells shape their response to molecularly targeted drugs, we profiled the proteomes and phosphoproteomes of 17 sarcoma cell lines and screened the same against 150 cancer drugs. The resulting 2550 phenotypic profiles revealed distinct drug responses and the cellular activity landscapes derived from deep (phospho)proteomes (9-10,000 proteins and 10-27,000 phosphorylation sites per cell line) enabled several lines of analysis. For instance, connecting the (phospho)proteomic data with drug responses revealed known and novel mechanisms of action (MoAs) of KIs and identified markers of drug sensitivity or resistance. All data is publicly accessible via an interactive web application that enables exploration of this rich molecular resource for a better understanding of active signalling pathways in sarcoma cells, identifying treatment response predictors and revealing novel MoA of clinical KIs.

Sildenafil as a Candidate Drug for Alzheimer's Disease: Real-World Patient Data Observation and Mechanistic Observations from Patient-Induced Pluripotent Stem Cell-Derived Neurons

Background

Alzheimer's disease (AD) is a chronic neurodegenerative disease needing effective therapeutics urgently. Sildenafil, one of the approved phosphodiesterase-5 inhibitors, has been implicated as having potential effect in AD.

Objective

To investigate the potential therapeutic benefit of sildenafil on AD.

Methods

We performed real-world patient data analysis using the MarketScan® Medicare Supplemental and the Clinformatics® databases. We conducted propensity score-stratified analyses after adjusting confounding factors (i.e., sex, age, race, and comorbidities). We used both familial and sporadic AD patient induced pluripotent stem cells (iPSC) derived neurons to evaluate the sildenafil's mechanism-of-action.

Results

We showed that sildenafil usage is associated with reduced likelihood of AD across four new drug compactor cohorts, including bumetanide, furosemide, spironolactone, and nifedipine. For instance, sildenafil usage is associated with a 54% reduced incidence of AD in MarketScan® (hazard ratio [HR] = 0.46, 95% CI 0.32- 0.66) and a 30% reduced prevalence of AD in Clinformatics® (HR = 0.70, 95% CI 0.49- 1.00) compared to spironolactone. We found that sildenafil treatment reduced tau hyperphosphorylation (pTau181 and pTau205) in a dose-dependent manner in both familial and sporadic AD patient iPSC-derived neurons. RNA-sequencing data analysis of sildenafil-treated AD patient iPSC-derived neurons reveals that sildenafil specifically target AD related genes and pathobiological pathways, mechanistically supporting the beneficial effect of sildenafil in AD.

Conclusions

These real-world patient data validation and mechanistic observations from patient iPSC-derived neurons further suggested that sildenafil is a potential repurposable drug for AD. Yet, randomized clinical trials are warranted to validate the causal treatment effects of sildenafil in AD.

Introducing the Automated Ligand Searcher

The Automated Ligand Searcher (ALISE) is designed as an automated computational drug discovery tool. To approximate the binding free energy of ligands to a receptor, ALISE includes a three-stage workflow, with each stage involving an increasingly sophisticated computational method: molecular docking, molecular dynamics, and free energy perturbation, respectively. To narrow the number of potential ligands, poorly performing ligands are gradually segregated out. The performance and usability of ALISE are benchmarked for a case study containing known active ligands and decoys for the HIV protease. The example illustrates that ALISE filters the decoys successfully and demonstrates that the automation, comprehensiveness, and user-friendliness of the software make it a valuable tool for improved and faster drug development workflows.

Virtual Screening and ADMET Prediction to Uncover the Potency of Flavonoids from Genus Erythrina as Antibacterial Agent through Inhibition of Bacterial ATPase DNA Gyrase B

The emergence of antimicrobial resistance due to the widespread and inappropriate use of antibiotics has now become the global health challenge. Flavonoids have long been reported to be a potent antimicrobial agent against a wide range of pathogenic microorganisms in vitro. Therefore, new antibiotics development based on flavonoid structures could be a potential strategy to fight against antibiotic-resistant infections. This research aims to screen the potency of flavonoids of the genus Erythrina as an inhibitor of bacterial ATPase DNA gyrase B. From the 378 flavonoids being screened, 49 flavonoids show potential as an inhibitor of ATPase DNA gyrase B due to their lower binding affinity compared to the inhibitor and ATP. Further screening for their toxicity, we identified 6 flavonoids from these 49 flavonoids, which are predicted to have low toxicity. Among these flavonoids, erystagallin B (334) is predicted to have the best pharmacokinetic properties, and therefore, could be further developed as new antibacterial agent.

Apoptosis mechanisms induced by 15d-PMJ2 in HCT116 colon cancer cells: insights into CHOP10/TRB3/Akt signaling

Agents that stimulate the endoplasmic reticulum (ER) stress pathway are being exploited pharmacologically to induce cancer cell death. Cytotoxic ER stress is typically regulated by the transcription factor, C/EBP homologous protein 10 (CHOP10). Products of CHOP10 transcription include the pro-apoptotic proteins: ER oxidoreductase 1α (ERO1α), death receptor-5 (DR5), and tribbles-related protein 3 (TRB3). Our previous findings showed cell death induced by 15-deoxy- Δ12,14 prostamide J2 (15d-PMJ2) occurred in an ER stress-dependent manner. However, the pathway by which 15d-PMJ2 regulates ER stress-mediated death downstream of CHOP10 has not been identified. Our results demonstrate 5 µM 15d-PMJ2 increased CHOP10 expression and apoptosis in HCT116 colon cancer cells. In cells treated with pharmacological inhibitors of ER stress, 15d-PMJ2-induced apoptosis was reliant upon the ER stress pathway. To investigate the role of CHOP10 and its transcriptional products in apoptosis, genetic deletion of CHOP10 (CHOP10-KO) was performed using the CRISPR/Cas9 system. The apoptotic action of 15d-PMJ2 was blunted in cells lacking CHOP10 expression. The deletion of CHOP10 reduced the expression of DR5, ERO1α, and TRB3 although only the expression of TRB3 was significantly reduced. Therefore, we overexpressed TRB3 in CHOP10-KO cells and observed that the activation of Akt was inhibited and 15d-PMJ2-induced apoptosis was restored. Thus, a mechanism of apoptosis elicited by 15d-PMJ2 includes the stimulation of CHOP10/TRB3/Akt inhibition. Given the important role these signaling molecules play in cancer cell fate, 15d-PMJ2 may be an effective inducer of apoptosis in cancer cells.

Sequence specificity defines the effectiveness of PPMOs targeting Pseudomonas aeruginosa

Development of new therapeutics against antibiotic resistant pathogenic bacteria is recognized as a priority across the globe. We have reported using peptide-conjugated phosphorodiamidate morpholino oligomers (PPMOs) as species-specific antibiotics. The oligo sequences, 11 bases are designed to be complementary to specific essential genes near the Shine-Dalgarno site and inhibit translation. Here, we analyzed target specificity and the impact of genetic mutations on lead PPMOs targeting the rpsJ or acpP gene of Pseudomonas aeruginosa. Mutants in P. aeruginosa PAO1 were generated with four, two, or one base-pair mutations within the 11-base target sequence of the rpsJ gene. All mutants exhibited increased MICs compared to wild-type PAO1 when treated with the RpsJ PPMO, and the increase in the MICs was proportional to the number of base-pair mutations. Among single base-pair mutants, mutations in the middle of the sequence were more impactful than mutations in 5' or 3' end of the sequence. The increased MICs shown by the rpsJ mutants could be reversed by PPMOs designed to target the mutated rpsJ sequence. BALB/c mice infected intratracheally with mutants demonstrated increased lung burden when treated with RpsJ PPMO compared to wild-type PAO1-infected mice treated with RpsJ PPMO. Treating mice with a PPMOs designed to specifically target the mutant sequence was more effective against these mutant strains. These experiments confirm target specificity of two lead P. aeruginosa PPMOs and illustrate one potential mechanism of resistance that could emerge from an antisense approach.

Ex Vivo Drug Screening Assay with Artificial Membranes: Characterizing Cholesterol Desorbing Competencies of Beta-Cyclodextrins

Despite advancements in contemporary therapies, cardiovascular disease from atherosclerosis remains a leading cause of mortality worldwide. Supported lipid bilayers (SLBs) are membrane interfaces that can be constructed with varying lipid compositions. Herein, we use a solvent-assisted lipid bilayer (SALB) construction method to build SLB membranes with varying cholesterol compositions to create a lipid-sterol interface atop a piezoelectric sensor. These cholesterol-laden SLBs were utilized to investigate the mechanisms of various cholesterol-lowering drug molecules. Within a flow-cell, membranes with varying cholesterol content were exposed to cyclodextrins 2-hydroxypropyl-beta-cyclodextrin (HPβCD) and methyl-beta-cyclodextrin (MβCD). Quartz-crystal microgravimetry with dissipation monitoring (QCM-D) enabled the collection of in vitro, real-time changes in relative areal mass and dissipation. We define the cholesterol desorbing competency of a cyclodextrin species via measures of the rate of cholesterol removal, the rate of the transfer of membrane-bound cholesterol to drug-complexed cholesterol, and the binding strength of the drug to the cholesterol-ladened membrane. Desorption data revealed distinct cholesterol removal kinetics for each cyclodextrin while also supporting a model for the lipid-cholesterol-drug interface. We report that MβCD removes a quantity of cholesterol 1.61 times greater, with a speed 2.12 times greater, binding affinity to DOPC lipid interfaces 1.97 times greater, and rate of internal cholesterol transfer 3.41 times greater than HPβCD.

μMap Photoproximity Labeling Enables Small Molecule Binding Site Mapping

The characterization of ligand binding modes is a crucial step in the drug discovery process and is especially important in campaigns arising from phenotypic screening, where the protein target and binding mode are unknown at the outset. Elucidation of target binding regions is typically achieved by X-ray crystallography or photoaffinity labeling (PAL) approaches; yet, these methods present significant challenges. X-ray crystallography is a mainstay technique that has revolutionized drug discovery, but in many cases structural characterization is challenging or impossible. PAL has also enabled binding site mapping with peptide- and amino-acid-level resolution; however, the stoichiometric activation mode can lead to poor signal and coverage of the resident binding pocket. Additionally, each PAL probe can have its own fragmentation pattern, complicating the analysis by mass spectrometry. Here, we establish a robust and general photocatalytic approach toward the mapping of protein binding sites, which we define as identification of residues proximal to the ligand binding pocket. By utilizing a catalytic mode of activation, we obtain sets of labeled amino acids in the proximity of the target protein binding site. We use this methodology to map, in vitro, the binding sites of six protein targets, including several kinases and molecular glue targets, and furthermore to investigate the binding site of the STAT3 inhibitor MM-206, a ligand with no known crystal structure. Finally, we demonstrate the successful mapping of drug binding sites in live cells. These results establish μMap as a powerful method for the generation of amino-acid- and peptide-level target engagement data.

Bioactive Lichen Secondary Metabolites and Their Presence in Species from Chile

Lichens are symbiotic organisms composed of at least one fungal and one algal species. They are found in different environments around the world, even in the poles and deserts. Some species can withstand extreme abiotic conditions, including radiation and the vacuum of space. Their chemistry is mainly due to the fungal metabolism and the production of several secondary metabolites with biological activity, which have been isolated due to an increasing interest from the pharmaceutical community. However, beyond the experimental data, little is known about their mechanisms of action and the potential pharmaceutical use of these kinds of molecules, especially the ones isolated from lesser-known species and/or lesser-studied countries. The main objective of this review is to analyze the bibliographical data of the biological activity of secondary metabolites from lichens, identifying the possible mechanisms of action and lichen species from Chile. We carried out a bibliographic revision of different scientific articles in order to collect all necessary information on the biological activity of the metabolites of these lichen species. For this, validated databases were used. We found the most recent reports where in vitro and in vivo studies have demonstrated the biological properties of these metabolites. The biological activity, namely anticancer, antioxidant, and anti-inflammatory activity, of 26 secondary metabolites are described, as well as their reported molecular mechanisms. The most notable metabolites found in this review were usnic acid, atranorin, protolichesterinic acid, and lobaric acid. Usnic acid was the most investigated metabolite, in addition to undergoing toxicological and pharmacological studies, where a hepatotoxicity effect was reported due to uncoupling oxidative phosphorylation. Additionally, no major studies have been made to validate the pharmacological application of these metabolites, and few advancements have been made in their artificial growth in bioreactors. Despite the described biological activities, there is little support to consider these metabolites in pharmaceutical formulations or to evaluate them in clinical trials. Nevertheless, it is important to carry out further studies regarding their possible human health effects. These lichen secondary metabolites present a promising research opportunity to find new pharmaceutical molecules due to their bioactive properties.

Rewiring Drug Research and Development through Human Data-Driven Discovery (HD3)

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and, as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry- and science-related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through the pursuit of a Human Data-driven Discovery (HD3) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather on the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD3, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, the rational design of combination therapies and the global response to the COVID-19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human-focused, systems-based approach to drug discovery and research.

What was old is new again: Phenotypic screening of a unique fungal library yields pyridoxatin, a promising lead against extensively resistant Acinetobacter baumannii (AB5075)

Due to the emergence of resistance, the World Health Organization considers Gram-negative pathogen Acinetobacter baumannii a top priority for therapeutic development. Using this priority pathogen and a phenotypic, agar plate-based assay, a unique library of extracts from 2,500 diverse fungi was screened for antimicrobial activity against a highly virulent, drug-resistant strain of A. baumannii (AB5075). The most potent hit from this screen was an extract from the fungus Tolypocladium sp., which was found to produce pyridoxatin. Another active extract from the fungi Trichoderma deliquescens was characterized and yielded trichokonin VII and trichokonin VIII. Evaluation of pyridoxatin against A. baumannii (AB5075) in a broth microdilution assay revealed a minimum inhibitory concentration (MIC) of 38 μM, compared to the known antibiotic levofloxacin with MIC of 28 μM. Mass spectrometry, Marfey's analysis and nuclear magnetic resonance spectroscopy analyses confirmed the structures of trichokonins VII and VIII to be consistent with previous reports. In an in vivo Galleria mellonella model, pyridoxatin tested at 150 mg/kg exhibited minimal toxicity (90% survival) and promising antimicrobial efficacy (50% survival) after 5 days. Trichokonins VII and VIII tested at 150 mg/kg were toxic to G. mellonella, with 20% survival and 40% survival after 5 days, respectively. The findings of this project suggest that pyridoxatin may serve as a lead compound for the development of antimicrobials against A. baumannii. They also demonstrate the value of the phenotypic screening approach employed herein.

Synthesis, molecular simulation studies, in vitro biological assessment of 2-substituted benzoxazole derivatives as promising antimicrobial agents

The 2-substituted benzoxazole derivatives are known to exhibit a wide spectrum of biological potential. Two series of novel benzoxazole derivatives containing 2-phenyl and 2-N-phenyl groups were synthesized, by following the green chemistry approach. All the newly synthesized derivatives were screened against gram-positive bacteria (Streptococcus pyogenes, Staphylococcus aureus), gram-negative bacteria (Pseudomonas aeruginosa, Escherichia coli) and the fungus (Aspergillus clavatus and Candida albicans). Most of these compounds have demonstrated potent antibacterial activities, especially against E. coli at 25 μg/mL, along with moderate antifungal activity. Among these, two compounds, 21 and 18, showed interesting antibacterial profile. Molecular docking studies suggested that the antibacterial activity can be linked to the inhibition of DNA gyrase. Overall, the study proposes that these biologically potent compounds can be considered for developing the next generation antimicrobial agents.

How Carvedilol activates β2-adrenoceptors

Carvedilol is among the most effective β-blockers for improving survival after myocardial infarction. Yet the mechanisms by which carvedilol achieves this superior clinical profile are still unclear. Beyond blockade of β1-adrenoceptors, arrestin-biased signalling via β2-adrenoceptors is a molecular mechanism proposed to explain the survival benefits. Here, we offer an alternative mechanism to rationalize carvedilol's cellular signalling. Using primary and immortalized cells genome-edited by CRISPR/Cas9 to lack either G proteins or arrestins; and combining biological, biochemical, and signalling assays with molecular dynamics simulations, we demonstrate that G proteins drive all detectable carvedilol signalling through β2ARs. Because a clear understanding of how drugs act is imperative to data interpretation in basic and clinical research, to the stratification of clinical trials or to the monitoring of drug effects on the target pathway, the mechanistic insight gained here provides a foundation for the rational development of signalling prototypes that target the β-adrenoceptor system.

Preclinical Characterization and Development on NAQ as a Mu Opioid Receptor Partial Agonist for Opioid Use Disorder Treatment

Mu opioid receptor (MOR) selective antagonists and partial agonists have clinical utility for the treatment of opioid use disorders (OUDs). However, the development of many has suffered due to their poor pharmacokinetic properties and/or rapid metabolism. Our recent efforts to identify MOR modulators have provided 17-cyclopropylmethyl-3,14β-dihydroxy-4,5α-epoxy-6α-(isoquinoline-3-carboxamido)morphinan (NAQ), a low-efficacy partial agonist, that showed sub-nanomolar binding affinity to the MOR (K i 0.6 nM) with selectivity over the delta opioid receptor (δ/μ 241) and the kappa opioid receptor (κ/μ 48). Its potent inhibition of the analgesic effect of morphine (AD50 0.46 mg/kg) and precipitation of significantly less withdrawal symptoms even at 100-fold greater dose than naloxone represents a promising molecule for further development as a novel OUD therapeutic agent. Therefore, further in vitro and in vivo characterization of its pharmacokinetics and pharmacodynamics properties was conducted to fully understand its pharmaceutical profile. NAQ showed favorable in vitro ADMET properties and no off-target binding to several classes of GPCRs, enzymes, and ion channels. Following intravenous administration, 1 mg/kg dose of NAQ showed a similar in vivo pharmacokinetic profile to naloxone; however, orally administered 10 mg/kg NAQ demonstrated significantly improved oral bioavailability over both naloxone and naltrexone. Abuse liability assessment of NAQ in rats demonstrated that NAQ functioned as a less potent reinforcer than heroin. Chronic 5 day NAQ pretreatment decreased heroin self-administration in a heroin-vs-food choice procedure similar to the clinically used MOR partial agonist buprenorphine. Taken together, these studies provide evidence supporting NAQ as a promising lead to develop novel OUD therapeutics.

Mitochondrial Imbalance of Trypanosoma cruzi Induced by the Marine Alkaloid 6-Bromo-2'-de-N-Methylaplysinopsin

Chagas disease, caused by Trypanosoma cruzi, affects seven million people worldwide and lacks effective treatments. Using bioactivity-guided fractionation, NMR, and electrospray ionization-high resolution mass spectrometry (ESI-HRMS) spectral analysis, the indole alkaloid 6-bromo-2'-de-N-methylaplysinopsin (BMA) was isolated and chemically characterized from the marine coral Tubastraea tagusensis. BMA was tested against trypomastigotes and intracellular amastigotes of T. cruzi, resulting in IC₅₀ values of 62 and 5.7 μM, respectively, with no mammalian cytotoxicity. The mechanism of action studies showed that BMA induced no alterations in the plasma membrane permeability but caused depolarization of the mitochondrial membrane potential, reducing ATP levels. Intracellular calcium levels were also reduced after the treatment, which was associated with pH alteration of acidocalcisomes. Using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF)/MS analysis, alterations of mass spectral signals were observed after treatment with BMA, suggesting a different mechanism from benznidazole. In silico pharmacokinetic-pharmacodynamic (PKPD) parameters suggested a drug-likeness property, supporting the promising usefulness of this compound as a new hit for optimizations.

Protein Binding in Translational Antimicrobial Development-Focus on Interspecies Differences

Background/Introduction: Plasma protein binding (PPB) continues to be a key aspect of antibiotic development and clinical use. PPB is essential to understand several properties of drug candidates, including antimicrobial activity, drug-drug interaction, drug clearance, volume of distribution, and therapeutic index. Focus areas of the review: In this review, we discuss the basics of PPB, including the main drug binding proteins i.e., Albumin and α-1-acid glycoprotein (AAG). Furthermore, we present the effects of PPB on the antimicrobial activity of antibiotics and the current role of PPB in in vitro pharmacodynamic (PD) models of antibiotics. Moreover, the effect of PPB on the PK/PD of antibiotics has been discussed in this review. A key aspect of this paper is a concise evaluation of PPB between animal species (dog, rat, mouse, rabbit and monkey) and humans. Our statistical analysis of the data available in the literature suggests a significant difference between antibiotic binding in humans and that of dogs or mice, with the majority of measurements from the pre-clinical species falling within five-fold of the human plasma value. Conversely, no significant difference in binding was found between humans and rats, rabbits, or monkeys. This information may be helpful for drug researchers to select the most relevant animal species in which the metabolism of a compound can be studied for extrapolating the results to humans. Furthermore, state-of-the-art methods for determining PPB such as equilibrium dialysis, ultracentrifugation, microdialysis, gel filtration, chromatographic methods and fluorescence spectroscopy are highlighted with their advantages and disadvantages.

Molecular targets for the development of new acaricides against Rhipicephalus microplus: a review

The cattle tick Rhipicephalus microplus is an ectoparasite with high economic importance to bovine culture, mainly in tropical and subtropical regions. The resistance of the tick from the commercial acaricides has hindered its control, thus motivating the search for new strategies. The purpose of this study was to perform a critical review about the main molecular targets of R. microplus that are useful for the discovery of new acaricides. Bibliographic search was conducted in the databases PubMed, ScienceDirect and CAB Direct, using the following descriptors: ‘Rhipicephalus microplus’, ‘Boophilus microplus’, ‘molecular targets’ and ‘action’, published between 2010 and 2021. Out of the 212 publications identified, 17 articles were selected for study inclusion. This review described 14 molecular targets and among these 4 are targets from commercial acaricides. Most of them are enzymes to catalyse important reactions to tick survival, related to energetic metabolism, mechanisms of biotransformation and neurotransmission. The data will be helpful in the development of new more effective and selective acaricides.

Design of SARS-CoV-2 Main Protease Inhibitors Using Artificial Intelligence and Molecular Dynamic Simulations

Drug design is a time-consuming and cumbersome process due to the vast search space of drug-like molecules and the difficulty of investigating atomic and electronic interactions. The present paper proposes a computational drug design workflow that combines artificial intelligence (AI) methods, i.e., an evolutionary algorithm and artificial neural network model, and molecular dynamics (MD) simulations to design and evaluate potential drug candidates. For the purpose of illustration, the proposed workflow was applied to design drug candidates against the main protease of severe acute respiratory syndrome coronavirus 2. From the ∼140,000 molecules designed using AI methods, MD analysis identified two molecules as potential drug candidates.

Measuring Protein Aggregation and Stability Using High-Throughput Biophysical Approaches

Structure-function relationships of biological macromolecules, in particular proteins, provide crucial insights for fundamental biochemistry, medical research and early drug discovery. However, production of recombinant proteins, either for structure determination, functional studies, or to be used as biopharmaceutical products, is often hampered by their instability and propensity to aggregate in solution in vitro. Protein samples of poor quality are often associated with reduced reproducibility as well as high research and production expenses. Several biophysical methods are available for measuring protein aggregation and stability. Yet, discovering and developing means to improve protein behaviour and structure-function integrity remains a demanding task. Here, we discuss workflows that are made possible by adapting established biophysical methods to high-throughput screening approaches. Rapid identification and optimisation of conditions that promote protein stability and reduce aggregation will support researchers and industry to maximise sample quality, stability and reproducibility, thereby reducing research and development time and costs.

Induction of Genes Implicated in Stress Response and Autophagy by a Novel Quinolin-8-yl-nicotinamide QN523 in Pancreatic Cancer

Using a cytotoxicity-based phenotypic screen of a highly diverse library of 20,000 small-molecule compounds, we identified a quinolin-8-yl-nicotinamide, QN519, as a promising lead. QN519 represents a novel scaffold with drug-like properties, showing potent in vitro cytotoxicity in a panel of 12 cancer cell lines. Subsequently, lead optimization campaign generated compounds with IC50 values < 1 μM. An optimized compound, QN523, shows significant in vivo efficacy in a pancreatic cancer xenograft model. QN523 treatment significantly increased the expression of HSPA5, DDIT3, TRIB3, and ATF3 genes, suggesting activation of the stress response pathway. We also observed a significant increase in the expression of WIPI1, HERPUD1, GABARAPL1, and MAP1LC3B, implicating autophagy as a major mechanism of action. Due to the lack of effective treatments for pancreatic cancer, discovery of novel agents such as the QN series of compounds with unique mechanism of action has the potential to fulfill a clear unmet medical need.

The cellular response to drug perturbation is limited: comparison of large-scale chemogenomic fitness signatures

Background

Chemogenomic profiling is a powerful approach for understanding the genome-wide cellular response to small molecules. First developed in Saccharomyces cerevisiae, chemogenomic screens provide direct, unbiased identification of drug target candidates as well as genes required for drug resistance. While many laboratories have performed chemogenomic fitness assays, few have been assessed for reproducibility and accuracy. Here we analyze the two largest independent yeast chemogenomic datasets comprising over 35 million gene-drug interactions and more than 6000 unique chemogenomic profiles; the first from our own academic laboratory (HIPLAB) and the second from the Novartis Institute of Biomedical Research (NIBR).

Results

Despite substantial differences in experimental and analytical pipelines, the combined datasets revealed robust chemogenomic response signatures, characterized by gene signatures, enrichment for biological processes and mechanisms of drug action. We previously reported that the cellular response to small molecules is limited and can be described by a network of 45 chemogenomic signatures. In the present study, we show that the majority of these signatures (66%) are also found in the companion dataset, providing further support for their biological relevance as conserved systems-level, small molecule response systems.

Conclusions

Our results demonstrate the robustness of chemogenomic fitness profiling in yeast, while offering guidelines for performing other high-dimensional comparisons including parallel CRISPR screens in mammalian cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08395-x.

Translational advances of melanocortin drugs: Integrating biology, chemistry and genetics

Melanocortin receptors have emerged as important targets with a very unusual versatility, as their widespread distribution on multiple tissues (e.g. skin, adrenal glands, brain, immune cells, exocrine glands) together with the variety of physiological processes they control (pigmentation, cortisol release, satiety mechanism, inflammation, secretions), place this family of receptors as genuine therapeutic targets for many disorders. This review focuses in the journey of the development of melanocortin receptors as therapeutic targets from the discovery of their existence in the early 1990 s to the approval of the first few drugs of this class. Two major areas of development characterise the current state of melanocortin drug development: their role in obesity, recently culminated with the approval of setmelanotide, and their potential for the treatment of chronic inflammatory and autoimmune diseases like rheumatoid arthritis, multiple sclerosis or fibrosis. The pro-resolving nature of these drugs offers the advantage of acting by mimicking the way our body naturally resolves inflammation, expecting fewer side effects and a more balanced (i.e. non-immunosuppressive) response from them. Here we also review the approaches followed for the design and development of novel compounds, the importance of the GPCR nature of these receptors in the process of drug development, therapeutic value, current challenges and successes, and the potential for the implementation of precision medicine approaches through the incorporation of genetics advances.

System-oriented optimization of multi-target 2,6-diaminopurine derivatives: Easily accessible broad-spectrum antivirals active against flaviviruses, influenza virus and SARS-CoV-2

The worldwide circulation of different viruses coupled with the increased frequency and diversity of new outbreaks, strongly highlight the need for new antiviral drugs to quickly react against potential pandemic pathogens. Broad-spectrum antiviral agents (BSAAs) represent the ideal option for a prompt response against multiple viruses, new and re-emerging. Starting from previously identified anti-flavivirus hits, we report herein the identification of promising BSAAs by submitting the multi-target 2,6-diaminopurine chemotype to a system-oriented optimization based on phenotypic screening on cell cultures infected with different viruses. Among the synthesized compounds, 6i showed low micromolar potency against Dengue, Zika, West Nile and Influenza A viruses (IC50 = 0.5-5.3 μM) with high selectivity index. Interestingly, 6i also inhibited SARS-CoV-2 replication in different cell lines, with higher potency on Calu-3 cells that better mimic the SARS-CoV-2 infection in vivo (IC50 = 0.5 μM, SI = 240). The multi-target effect of 6i on flavivirus replication was also analyzed in whole cell studies (in vitro selection and immunofluorescence) and against isolated host/viral targets.

Leveraging the Genetic Diversity of Human Stem Cells in Therapeutic Approaches

Since their discovery 15 years ago, human pluripotent stem cell (hPSC) technologies have begun to revolutionize science and medicine, rapidly expanding beyond investigative research to drug discovery and development. Efforts to leverage hPSCs over the last decade have focused on increasing both the complexity and in vivo fidelity of human cellular models through enhanced differentiation methods. While these evolutions have fostered novel insights into disease mechanisms and influenced clinical drug discovery and development, there are still several considerations that limit the utility of hPSC models. In this review, we highlight important, yet underexplored avenues to broaden their reach. We focus on (i) the importance of diversifying existing hPSC collections, and their utilization to investigate therapeutic strategies in individuals from different genetic backgrounds, ancestry and sex; (ii) considerations for the selection of therapeutically relevant hPSC-based models; (iii) strategies to adequately increase the scale of cell-based studies; and (iv) the advances and constraints of clinical trials in a dish. Moreover, we advocate for harnessing the translational capabilities of hPSC models along with the use of innovative, scalable approaches for understanding genetic biases and the impact of sex and ancestry on disease mechanisms and drug efficacy and response. The next decade of hPSC innovation is poised to provide vast insights into the genetic basis of human disease and enable rapid advances to develop, repurpose, and ensure the safety of the next generation of disease therapies across diverse human populations.

Discovery of pseudolaric acid A as a new Hsp90 inhibitor uncovers its potential anticancer mechanism

Pseudolaric acid A (PAA), one of the main bioactive ingredients in traditional medicine Pseudolarix cortex, exhibits remarkable anticancer activities. Yet its mechanism of action and molecular target have not been investigated and remain unclear. In this work, mechanistic study showed that PAA induced cell cycle arrest at G2/M phase and promoted cell death through caspase-8/caspase-3 pathway, demonstrating potent antiproliferation and anticancer activities. PAA was discovered to be a new Hsp90 inhibitor and multiple biophysical experiments confirmed that PAA directly bind to Hsp90. Active PAA-probe was designed, synthesized and biological evaluated. It was subsequently employed to verify the cellular interaction with Hsp90 in HeLa cells through photoaffinity labeling approach. Furthermore, NMR experiments showed that N-terminal domain of Hsp90 and essential groups in PAA are important for the protein-inhibitor recognition. Structure-activity relationship studies revealed the correlation between its Hsp90 inhibitory activity with anticancer activity. This work proposed a potential mechanism involved with the anticancer activity of PAA and will improve the appreciation of PAA as a potential cancer therapy candidate.