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There has recently been a resurgence of interest in psychedelic compounds based on studies demonstrating their potential therapeutic applications in treating posttraumatic stress disorder, substance abuse disorders, and treatment-resistant depression. Despite promising efficacy observed in some clinical trials, the full range of biological effects and mechanism(s) of action of these compounds have yet to be fully established. Indeed, most studies to date have focused on assessing the psychological mechanisms of psychedelics, often neglecting the nonpsychological modes of action. However, it is important to understand that psychedelics may mediate their therapeutic effects through multi-faceted mechanisms, such as the modulation of brain network activity, neuronal plasticity, neuroendocrine function, glial cell regulation, epigenetic processes, and the gut-brain axis. This review provides a framework supporting the implementation of a multi-faceted approach, incorporating in silico, in vitro and in vivo modeling, to aid in the comprehensive understanding of the physiological effects of psychedelics and their potential for clinical application beyond the treatment of psychiatric disorders. We also provide an overview of the literature supporting the potential utility of psychedelics for the treatment of brain injury (e.g., stroke and traumatic brain injury), neurodegenerative diseases (e.g., Parkinson's and Alzheimer's diseases), and gut-brain axis dysfunction associated with psychiatric disorders (e.g., generalized anxiety disorder and major depressive disorder). To move the field forward, we outline advantageous experimental frameworks to explore these and other novel applications for psychedelics. [ABSTRACT FROM AUTHOR]

There has recently been a resurgence of interest in psychedelic compounds based on studies demonstrating their potential therapeutic applications in treating post-traumatic stress disorder, substance abuse disorders, and treatment-resistant depression. Despite promising efficacy observed in some clinical trials, the full range of biological effects and mechanism(s) of action of these compounds have yet to be fully established. Indeed, most studies to date have focused on assessing the psychological mechanisms of psychedelics, often neglecting the non-psychological modes of action. However, it is important to understand that psychedelics may mediate their therapeutic effects through multi-faceted mechanisms, such as the modulation of brain network activity, neuronal plasticity, neuroendocrine function, glial cell regulation, epigenetic processes, and the gut-brain axis. This review provides a framework supporting the implementation of a multi-faceted approach, incorporating in silico, in vitro and in vivo modeling, to aid in the comprehensive understanding of the physiological effects of psychedelics and their potential for clinical application beyond the treatment of psychiatric disorders. We also provide an overview of the literature supporting the potential utility of psychedelics for the treatment of brain injury (e.g., stroke and traumatic brain injury), neurodegenerative diseases (e.g., Parkinson’s and Alzheimer’s diseases), and gut-brain axis dysfunction associated with psychiatric disorders (e.g., generalized anxiety disorder and major depressive disorder). To move the field forward, we outline advantageous experimental frameworks to explore these and other novel applications for psychedelics.

From the last two decades, phthalimide analogues received prime interest from scientists due to its potent inhibitory action on different cancer‐causing receptors. A variety of anticancer drugs are coming into the market but challenges of drug resistance, toxicities, and failure in therapy still remain. Cancer is a group of complex disorders it involves multiple receptors. So there is a need of targeting multiple receptors to get desired potent anticancer drugs with minimum harmful effects. Phthalimide scaffolds fit into these criteria as it is extensively reported for the inhibition of different cancer receptors such as VEGFR, HDAC, EGFR, TNF‐α, etc. The multi‐targeted mechanism of phthalimide derivatives plays a major role in anticancer therapy. Due to this advantage, there is the hope of developing some novel effective multi‐targeted anticancer agents. Consider structural features and pharmacological advancement of phthalimide analogues may fulfill the current need of cancer patients. In this review, we covered history, chemistry, SAR, anticancer mechanisms, and the current status of phthalimide derivatives reported till 2022. The article specifically focused on different cancer‐causing receptors inhibited by phthalimide derivatives and their mechanism of action in brief. Finally, we provided the future scope and role of phthalimide derivatives in multi‐targeted anticancer drug discovery. [ABSTRACT FROM AUTHOR]

Pioneering success of antibodies targeting immune checkpoints such as programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) has changed the outlook of cancer therapy. Although these antibodies show impressive durable clinical activity, low response rates and immune-related adverse events are becoming increasingly evident in antibody-based approaches. For further strides in cancer immunotherapy, novel treatment strategies including combination therapies and alternate therapeutic modalities are highly warranted. Towards this discovery and development of small molecule, checkpoint inhibitors are actively being pursued, and the efforts have culminated in the ongoing clinical testing of orally bioavailable checkpoint inhibitors. This review focuses on the small molecule agents targeting PD-1 checkpoint pathway for cancer immunotherapy and highlights various chemotypes/scaffolds and their characterization including binding and functionality along with reported mechanism of action. The learnings from the ongoing small molecule clinical trials and crucial points to be considered for their clinical development are also discussed. [ABSTRACT FROM AUTHOR]

Pioneering success of antibodies targeting immune checkpoints such as programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) has changed the outlook of cancer therapy. Although these antibodies show impressive durable clinical activity, low response rates and immune-related adverse events are becoming increasingly evident in antibody-based approaches. For further strides in cancer immunotherapy, novel treatment strategies including combination therapies and alternate therapeutic modalities are highly warranted. Towards this discovery and development of small molecule, checkpoint inhibitors are actively being pursued, and the efforts have culminated in the ongoing clinical testing of orally bioavailable checkpoint inhibitors. This review focuses on the small molecule agents targeting PD-1 checkpoint pathway for cancer immunotherapy and highlights various chemotypes/scaffolds and their characterization including binding and functionality along with reported mechanism of action. The learnings from the ongoing small molecule clinical trials and crucial points to be considered for their clinical development are also discussed.

Abstract. The development of monoclonal antibody (mAb) biosimilars is a complex process. The key to their successful development and commercialization is an in-depth understanding of the key product attributes that impact safety and efficacy and the strategies to control them. Functional assessment of mAb is a crucial part of the comparability of biopharmaceutical drugs. The development of a relevant and robust functional assay requires an interdisciplinary approach and sufficient flexibility to balance regulatory concerns as well as dynamics and variability during the manufacturing process. Although many advanced tools are available to study and compare the potency and bioactivity of the protein, most of these techniques suffer from major shortcomings that limit their routine use. These include the complexity of the task, establishment of the relevance of the chosen method with the mechanism of action (MOA) of the biosimilar, cost and extended time of analysis, and often the ambiguity in interpretation of the resulting data. To overcome or to address these challenges, the use of multiple orthogonal state-of-the-art techniques is a necessary prerequisite. [ABSTRACT FROM AUTHOR]

Abstract While the COVID-19 pandemic has spurred intense research and collaborative discovery worldwide, the development of a safe, effective, and targeted antiviral from the ground up is time intensive. Therefore, most antiviral discovery efforts are focused on the re-purposing of clinical stage or approved drugs. While emerging data on drugs undergoing COVID-19 repurpose are intriguing, there is an undeniable need to develop broad-spectrum antivirals to prevent future viral pandemics of unknown origin. The ideal drug to curtail rapid viral spread would be a broad-acting agent with activity against a wide range of viruses. Such a drug would work by modulating host-proteins that are often shared by multiple virus families thereby enabling preemptive drug development and therefore rapid deployment at the onset of an outbreak. Targeting host-pathways and cellular proteins that are hijacked by viruses can potentially offer broad-spectrum targets for the development of future antiviral drugs. Such host-directed antivirals are also likely to offer a higher barrier to the development and selection of drug resistant mutations. Given that most approved antivirals do not target host-proteins, we reinforce the need for the development of such antivirals that can be used in pre- and post-exposure populations.

T-cell-dependent bispecific antibodies (TDBs) are promising cancer immunotherapies that recruit patients’ T cells to kill cancer cells. There are many TDBs in clinical trials, demonstrating their widely recognized therapeutic potential. However, their complex, multi-step mechanism of action (MoA), which includes bispecific antigen binding, T-cell activation, and target-cell killing, presents unique challenges for biological characterization and potency assay selection. Here, we describe the development of a single reporter-gene potency assay for a TDB (TDB1) that is MoA reflective and sensitive to binding of both antigens. Our reporter-gene assay measures T-cell activation using Jurkat cells engineered to express luciferase under the control of an NFkB response element. The potencies of select samples were measured both by this assay and by a flow-cytometry-based cell-killing assay using human lymphocytes as effector cells. Correlating the two sets of potency results clearly establishes our reporter-gene assay as MoA reflective. Furthermore, correlating potencies for the same panel of samples against binding data measured by binding assays for each individual arm demonstrates that the reporter-gene potency assay reflects dual-antigen binding and can detect changes in affinity for either arm. This work demonstrates that one reporter-gene assay can be used to measure the potency of TDB1 while capturing key aspects of its MoA, thus serving as a useful case study of selection and justification of reporter-gene potency assays for TDBs. Furthermore, our strategy of correlating reporter-gene potency, target-cell killing, and antigen binding for each individual arm serves as a useful example of a thorough, holistic approach to biological characterization for TDBs that can be applied to other bispecific molecules.

Chronic stable angina (CSA) presents as a complication of coronary heart disease, leading to a high incidence and mortality rate worldwide. Dantonic® or Compound Danshen Dripping Pills (CDDP) is a well-known traditional Chinese medicine used for the treatment of myocardial ischemic diseases, such as angina pectoris (AP), myocardial infarction, and sudden death. Dantonic® has been extensively utilized in clinical practice in China for more than 14 years and has proved to be an effective therapy for the treatment of many myocardial ischemic diseases since its approval by CFDA in 1994. Clinical studies in China have shown that Dantonic® is an effective and safe drug for the treatment of angina pectoris manifested with ameliorating anginal symptoms and showing few adverse effects. Nevertheless, the mechanism of Dantonic® for the treatment of angina has been underestimated. Therefore, in this review, we mainly focus on discussing the pharmacological mechanism of action (MoA) of Dantonic® for the treatment of CSA, including the promotion of coronary microcirculation, the optimization of myocardial energy metabolism, and the inhibition of platelet aggregation.

The low rate of discovery and rapid spread of resistant pathogens have made antibiotic discovery a worldwide priority. In cell-based screening, the mechanism of action (MOA) is identified after antimicrobial activity. This increases rediscovery, impairs low potency candidate detection, and does not guide lead optimization. In this study, high-throughput Fourier-transform infrared (FTIR) spectroscopy was used to discriminate the MOA of 14 antibiotics at pathway, class, and individual antibiotic level. For that, the optimal combinations and parametrizations of spectral preprocessing were selected with cross-validated partial least squares discriminant analysis, to which various machine learning algorithms were applied. This coherently resulted in very good accuracies, independently of the algorithms, and at all levels of MOA. Particularly, an ensemble of subspace discriminants predicted the known pathway (98.6%), antibiotic classes (100%), and individual antibiotics (97.8%) with exceptional accuracy, and similar results were obtained for simulated novel MOA. Even at very low concentrations (1 μg/mL) and growth inhibition (15%), over 70% pathway and class accuracy was achieved, suggesting FTIR spectroscopy can probe the grey chemical matter. Prediction of inhibitory effect was also examined, for which a squared exponential Gaussian process regression yielded a root mean square error of 0.33 and a R2 of 0.92, indicating that metabolic alterations leading to growth inhibition are intrinsically reflected on FTIR spectra beyond cell density. Key points: • Antibiotic MOA and potency estimated with high-throughput FTIR spectroscopy • Sub-inhibitory MOA identification suggests ability to explore grey chemical matter • Data analysis optimization improved MOA identification at antibiotic level by 38% [ABSTRACT FROM AUTHOR]

Mesenchymal stromal cells (MSCs) have been widely investigated for regenerative medicine applications, from treating various inflammatory diseases as a cell therapy to generating engineered tissue constructs. Numerous studies have evaluated the potential effects of MSCs following therapeutic administration. By responding to their surrounding microenvironment, MSCs may mediate immunomodulatory effects through various mechanisms that directly (i.e., contact-dependent) or indirectly (i.e., paracrine activity) alter the physiology of endogenous cells in various disease pathologies. More specifically, a pivotal crosstalk between MSCs and tissue-resident macrophages and monocytes (TMφ) has been elucidated using in vitro and in vivo preclinical studies. An improved understanding of this crosstalk could help elucidate potential mechanisms of action (MOAs) of therapeutically administered MSCs. TMφ, by nature of their remarkable functional plasticity and prevalence within the body, are uniquely positioned as critical modulators of the immune system – not only in maintaining homeostasis but also during pathogenesis. This has prompted further exploration into the cellular and molecular alterations to TMφ mediated by MSCs. In vitro assays and in vivo preclinical trials have identified key interactions mediated by MSCs that polarize the responses of TMφ from a pro-inflammatory (i.e., classical activation) to a more anti-inflammatory/reparative (i.e., alternative activation) phenotype and function. In this review, we describe physiological and pathological TMφ functions in response to various stimuli and discuss the evidence that suggest specific mechanisms through which MSCs may modulate TMφ phenotypes and functions, including paracrine interactions (e.g., secretome and extracellular vesicles), nanotube-mediated intercellular exchange, bioenergetics, and engulfment by macrophages. Continued efforts to elucidate this pivotal crosstalk may offer an improved understanding of the immunomodulatory capacity of MSCs and inform the development and testing of potential MOAs to support the therapeutic use of MSCs and MSC-derived products in various diseases.

DrugMatrix is a valuable toxicogenomic dataset, which provides in vivo transcriptome data corresponding to hundreds of chemical drugs. However, the relationships between drugs and how those drugs affect the biological process are still unknown. The high dimensionality of the microarray data hinders its application. The aims of this study are to (1) represent the transcriptome data by lower-dimensional vectors, (2) compare drug similarity, (3) represent drug combinations by adding vectors and (4) infer drug mechanism of action (MoA) and genotoxicity features. We borrowed the latent semantic analysis (LSA) technique from natural language processing to represent treatments (drugs with multiple concentrations and time points) by dense vectors, each dimension of which is an orthogonal biological feature. The gProfiler enrichment tool was used for the 100-dimensional vector feature annotation. The similarity between treatments vectors was calculated by the cosine function. Adding vectors may represent drug combinations, treatment times or treatment doses that are not presented in the original data. Drug–drug interaction pairs had a higher similarity than random drug pairs in the hepatocyte data. The vector features helped to reveal the MoA. Differential feature expression was also implicated for genotoxic and non-genotoxic carcinogens. An easy-to-use Web tool was developed by Shiny Web application framework for the exploration of treatment similarities and drug combinations (https://bioinformatics.fafu.edu.cn/drugmatrix/). We represented treatments by vectors and provided a tool that is useful for hypothesis generation in toxicogenomic, such as drug similarity, drug repurposing, combination therapy and MoA. [ABSTRACT FROM AUTHOR]

The prediction of biological targets of bioactive molecules from machine-readable materials can be routinely performed by computational target prediction tools (CTPTs). However, the prediction of biological targets of bioactive molecules from non-digital materials (e.g., printed or handwritten documents) has not been possible due to the complex nature of bioactive molecules and impossibility of employing computations. Improving the target prediction accuracy is the most important challenge for computational target prediction. A minimum structure is identified for each group of neighbor molecules in the proposed method. Each group of neighbor molecules represents a distinct structural class of molecules with the same function in relation to the target. The minimum structure is employed as a query to search for molecules that perfectly satisfy the minimum structure of what is guessed crucial for the targeted activity. The proposed method is based on chemical similarity, but only molecules that perfectly satisfy the minimum structure are considered. Structurally related bioactive molecules found with the same minimum structure were considered as neighbor molecules of the query molecule. The known target of the neighbor molecule is used as a reference for predicting the target of the neighbor molecule with an unknown target. A lot of information is needed to identify the minimum structure, because it is necessary to know which part(s) of the bioactive molecule determines the precise target or targets responsible for the observed phenotype. Therefore, the predicted target based on the minimum structure without employing the statistical significance is considered as a reliable prediction. Since only molecules that perfectly (and not partly) satisfy the minimum structure are considered, the minimum structure can be used without similarity calculations in non-digital materials and with similarity calculations (perfect similarity) in machine-readable materials. Nine tools (PASS online, PPB, SEA, TargetHunter, PharmMapper, ChemProt, HitPick, SuperPred, and SPiDER), which can be used for computational target prediction, are compared with the proposed method for 550 target predictions. The proposed method, SEA, PPB, and PASS online, showed the best quality and quantity for the accurate predictions.

The prediction of biological targets of bioactive molecules from machine-readable materials can be routinely performed by computational target prediction tools (CTPTs). However, the prediction of biological targets of bioactive molecules from non-digital materials (e.g., printed or handwritten documents) has not been possible due to the complex nature of bioactive molecules and impossibility of employing computations. Improving the target prediction accuracy is the most important challenge for computational target prediction. A minimum structure is identified for each group of neighbor molecules in the proposed method. Each group of neighbor molecules represents a distinct structural class of molecules with the same function in relation to the target. The minimum structure is employed as a query to search for molecules that perfectly satisfy the minimum structure of what is guessed crucial for the targeted activity. The proposed method is based on chemical similarity, but only molecules that perfectly satisfy the minimum structure are considered. Structurally related bioactive molecules found with the same minimum structure were considered as neighbor molecules of the query molecule. The known target of the neighbor molecule is used as a reference for predicting the target of the neighbor molecule with an unknown target. A lot of information is needed to identify the minimum structure, because it is necessary to know which part(s) of the bioactive molecule determines the precise target or targets responsible for the observed phenotype. Therefore, the predicted target based on the minimum structure without employing the statistical significance is considered as a reliable prediction. Since only molecules that perfectly (and not partly) satisfy the minimum structure are considered, the minimum structure can be used without similarity calculations in non-digital materials and with similarity calculations (perfect similarity) in machine-readable materials. Nine tools (PASS online, PPB, SEA, TargetHunter, PharmMapper, ChemProt, HitPick, SuperPred, and SPiDER), which can be used for computational target prediction, are compared with the proposed method for 550 target predictions. The proposed method, SEA, PPB, and PASS online, showed the best quality and quantity for the accurate predictions. [ABSTRACT FROM AUTHOR]

Graphical abstract This review article mainly focuses on the mechanism of action (MoA) of Dantonic® for the treatment of chronic stable angina, which includes the promotion of coronary microcirculation, the optimization of myocardial energy metabolism and the inhibition of platelet aggregation. Highlights • Dantonic® is a currently used medicine for chronic stable angina (CSA) in China. • The mechanism of action (MoA) of Dantonic® for CSA mainly includes three aspects. • The MoA of Dantonic® for CSA includes promoting coronary microcirculation. • The MoA of Dantonic® for CSA includes optimizing myocardial energy metabolism. • The MoA of Dantonic® for CSA includes inhibiting platelet aggregation. Abstract Chronic stable angina (CSA) presents as a complication of coronary heart disease, leading to a high incidence and mortality rate worldwide. Dantonic® or Compound Danshen Dripping Pills (CDDP) is a well-known traditional Chinese medicine used for the treatment of myocardial ischemic diseases, such as angina pectoris (AP), myocardial infarction, and sudden death. Dantonic® has been extensively utilized in clinical practice in China for more than 14 years and has proved to be an effective therapy for the treatment of many myocardial ischemic diseases since its approval by CFDA in 1994. Clinical studies in China have shown that Dantonic® is an effective and safe drug for the treatment of angina pectoris manifested with ameliorating anginal symptoms and showing few adverse effects. Nevertheless, the mechanism of Dantonic® for the treatment of angina has been underestimated. Therefore, in this review, we mainly focus on discussing the pharmacological mechanism of action (MoA) of Dantonic® for the treatment of CSA, including the promotion of coronary microcirculation, the optimization of myocardial energy metabolism, and the inhibition of platelet aggregation. [ABSTRACT FROM AUTHOR]

Biological assays are essential tools in biomedical and pharmaceutical research. In simplest terms, such an assay is an analytical method used to measure or predict a response in a biological system in the presence of a given stimulus (e.g., drug). The inherent complexity involved in evaluating a biological system requires the use of rigorous and appropriate tools for data analysis. Linear and nonlinear regression models represent critically important statistical analyses used to define the relationships between variables of interest in biological systems. Recent challenges relating to the reproducibility of published data suggest the absence of standardized and routine use of statistics to support experimental results across a wide range of scientific disciplines. The current situation warrants an introductory review of basic regression concepts using current, practical examples, along with references to in-depth resources. The goal is to provide the necessary information to help standardize the analysis of biological assays in academic research and drug discovery and development, elevating their utility and increasing data transparency and reproducibility. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC., (© 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.)

Abstract: Due to evolutionary conservation of biology, experimental knowledge captured from genetic studies in eukaryotic model organisms provides insight into human cellular pathways and ultimately physiology. Yeast chemogenomic profiling is a powerful approach for annotating cellular responses to small molecules. Using an optimized platform, we provide the relative sensitivities of the heterozygous and homozygous deletion collections for nearly 1800 biologically active compounds. The data quality enables unique insights into pathways that are sensitive and resistant to a given perturbation, as demonstrated with both known and novel compounds. We present examples of novel compounds that inhibit the therapeutically relevant fatty acid synthase and desaturase (Fas1p and Ole1p), and demonstrate how the individual profiles facilitate hypothesis-driven experiments to delineate compound mechanism of action. Importantly, the scale and diversity of tested compounds yields a dataset where the number of modulated pathways approaches saturation. This resource can be used to map novel biological connections, and also identify functions for unannotated genes. We validated hypotheses generated by global two-way hierarchical clustering of profiles for (i) novel compounds with a similar mechanism of action acting upon microtubules or vacuolar ATPases, and (ii) an un-annotated ORF, YIL060w, that plays a role in respiration in the mitochondria. Finally, we identify and characterize background mutations in the widely used yeast deletion collection which should improve the interpretation of past and future screens throughout the community. This comprehensive resource of cellular responses enables the expansion of our understanding of eukaryotic pathway biology. [Copyright &y& Elsevier]

Highlights: [•] We analyzed selective response of compounds on diverse subset of cancer cell lines. [•] We used GI50 profile of >40,000 compounds on 60 cancer cell lines. [•] 3D shape-based similarity predicts the GI50 profile better than 2D chemical similarity. [•] Lineage- and genotype-specific compound response was identified. [Copyright &y& Elsevier]

The development of monoclonal antibody (mAb) biosimilars is a complex process. The key to their successful development and commercialization is an in-depth understanding of the key product attributes that impact safety and efficacy and the strategies to control them. Functional assessment of mAb is a crucial part of the comparability of biopharmaceutical drugs. The development of a relevant and robust functional assay requires an interdisciplinary approach and sufficient flexibility to balance regulatory concerns as well as dynamics and variability during the manufacturing process. Although many advanced tools are available to study and compare the potency and bioactivity of the protein, most of these techniques suffer from major shortcomings that limit their routine use. These include the complexity of the task, establishment of the relevance of the chosen method with the mechanism of action (MOA) of the biosimilar, cost and extended time of analysis, and often the ambiguity in interpretation of the resulting data. To overcome or to address these challenges, the use of multiple orthogonal state-of-the-art techniques is a necessary prerequisite., (© 2021. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

Aging is a natural biological progress accompanied by the gradual decline in physiological functions, manifested by its close association with an increased incidence of human diseases and higher vulnerability to death. Those diseases include neurological disorders, cardiovascular diseases, diabetes, and cancer, many of which are currently without effective cures. Even though aging is inevitable, there are still interventions that can be developed to prevent/delay the onset and progression of those aging-associated diseases and extend healthspan and/or lifespan. Here, we review decades of research that reveals the molecular pathways underlying aging and forms the biochemical basis for anti-aging drug development. Importantly, due to the vast chemical space of natural products and the rich history of herb medicines in treating human diseases documented in different cultures, natural products have played essential roles in aging research. Using several of the most promising natural products and their derivatives as examples, we discuss how natural products serve as an inspiration resource that helped the identification of key components/pathways underlying aging, their mechanisms of action inside the cell, and the functional scaffolds or targeting mechanisms that can be learned from natural products for drug engineering and optimization. We argue that natural products might eventually provide a solution to aging and aging-associated diseases. [ABSTRACT FROM AUTHOR]

Mesenchymal stromal cells (MSCs) have been widely investigated for regenerative medicine applications, from treating various inflammatory diseases as a cell therapy to generating engineered tissue constructs. Numerous studies have evaluated the potential effects of MSCs following therapeutic administration. By responding to their surrounding microenvironment, MSCs may mediate immunomodulatory effects through various mechanisms that directly (i.e., contact-dependent) or indirectly (i.e., paracrine activity) alter the physiology of endogenous cells in various disease pathologies. More specifically, a pivotal crosstalk between MSCs and tissue-resident macrophages and monocytes (TMφ) has been elucidated using in vitro and in vivo preclinical studies. An improved understanding of this crosstalk could help elucidate potential mechanisms of action (MOAs) of therapeutically administered MSCs. TMφ, by nature of their remarkable functional plasticity and prevalence within the body, are uniquely positioned as critical modulators of the immune system - not only in maintaining homeostasis but also during pathogenesis. This has prompted further exploration into the cellular and molecular alterations to TMφ mediated by MSCs. In vitro assays and in vivo preclinical trials have identified key interactions mediated by MSCs that polarize the responses of TMφ from a pro-inflammatory (i.e., classical activation) to a more anti-inflammatory/reparative (i.e., alternative activation) phenotype and function. In this review, we describe physiological and pathological TMφ functions in response to various stimuli and discuss the evidence that suggest specific mechanisms through which MSCs may modulate TMφ phenotypes and functions, including paracrine interactions (e.g., secretome and extracellular vesicles), nanotube-mediated intercellular exchange, bioenergetics, and engulfment by macrophages. Continued efforts to elucidate this pivotal crosstalk may offer an improved understanding of the immunomodulatory capacity of MSCs and inform the development and testing of potential MOAs to support the therapeutic use of MSCs and MSC-derived products in various diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Stevens, Bowles, Yeago and Roy.)

T-cell-dependent bispecific antibodies (TDBs) are promising cancer immunotherapies that recruit patients' T cells to kill cancer cells. There are many TDBs in clinical trials, demonstrating their widely recognized therapeutic potential. However, their complex, multi-step mechanism of action (MoA), which includes bispecific antigen binding, T-cell activation, and target-cell killing, presents unique challenges for biological characterization and potency assay selection. Here, we describe the development of a single reporter-gene potency assay for a TDB (TDB1) that is MoA reflective and sensitive to binding of both antigens. Our reporter-gene assay measures T-cell activation using Jurkat cells engineered to express luciferase under the control of an NFkB response element. The potencies of select samples were measured both by this assay and by a flow-cytometry-based cell-killing assay using human lymphocytes as effector cells. Correlating the two sets of potency results clearly establishes our reporter-gene assay as MoA reflective. Furthermore, correlating potencies for the same panel of samples against binding data measured by binding assays for each individual arm demonstrates that the reporter-gene potency assay reflects dual-antigen binding and can detect changes in affinity for either arm. This work demonstrates that one reporter-gene assay can be used to measure the potency of TDB1 while capturing key aspects of its MoA, thus serving as a useful case study of selection and justification of reporter-gene potency assays for TDBs. Furthermore, our strategy of correlating reporter-gene potency, target-cell killing, and antigen binding for each individual arm serves as a useful example of a thorough, holistic approach to biological characterization for TDBs that can be applied to other bispecific molecules.

Delta-5 desaturase (D5D) catalyzes the conversion from dihomo-gamma linoleic acid (DGLA) to arachidonic acid (AA). DGLA and AA are common precursors of anti- and pro-inflammatory eicosanoids, respectively, making D5D an attractive drug target for inflammatory-related diseases. Despite several reports on D5D inhibitors, their biochemical mechanisms of action (MOAs) remain poorly understood, primarily due to the difficulty in performing quantitative enzymatic analysis. Herein, we report a radioligand binding assay to overcome this challenge and characterized T-3364366, a thienopyrimidinone D5D inhibitor, by use of the assay. T-3364366 is a reversible, slow-binding inhibitor with a dissociation half-life in excess of 2.0 h. The long residence time was confirmed in cellular washout assays. Domain swapping experiments between D5D and D6D support [(3)H]T-3364366 binding to the desaturase domain of D5D. The present study is the first to demonstrate biochemical MOA of desaturase inhibitors, providing important insight into drug discovery of desaturase enzymes.