Replicated, replicable and relevant-target engagement and pharmacological experimentation in the 21st century

Biased signaling in drug discovery and precision medicine

Receptors are crucial for converting chemical and environmental signals into cellular responses, making them prime targets in drug discovery, with about 70% of drugs targeting these receptors. Biased signaling, or functional selectivity, has revolutionized drug development by enabling precise modulation of receptor signaling pathways. This concept is more firmly established in G protein-coupled receptor and has now been applied to other receptor types, including ion channels, receptor tyrosine kinases, and nuclear receptors. Advances in structural biology have further refined our understanding of biased signaling. This targeted approach enhances therapeutic efficacy and potentially reduces side effects. Numerous biased drugs have been developed and approved as therapeutics to treat various diseases, demonstrating their significant therapeutic potential. This review provides a comprehensive overview of biased signaling in drug discovery and disease treatment, highlighting recent advancements and exploring the therapeutic potential of these innovative modulators across various diseases.

In Silico Modeling Demonstrates that User Variability During Tumor Measurement Can Affect In Vivo Therapeutic Efficacy Outcomes

User measurement bias during subcutaneous tumor measurement is a source of variation in preclinical in vivo studies. We investigated whether this user variability could impact efficacy study outcomes, in the form of the false negative result rate when comparing treated and control groups. Two tumor measurement methods were compared; calipers which rely on manual measurement, and an automatic 3D and thermal imaging device. Tumor growth curve data were used to create an in silico efficacy study with control and treated groups. Before applying user variability, treatment group tumor volumes were statistically different to the control group. Utilizing data collected from 15 different users across 9 in vivo studies, user measurement variability was computed for both methods and simulation was used to investigate its impact on the in silico study outcome. User variability produced a false negative result in 0.7% to 18.5% of simulated studies when using calipers, depending on treatment efficacy. When using an imaging device with lower user variability this was reduced to 0.0% to 2.6%, demonstrating that user variability impacts study outcomes and the ability to detect treatment effect. Reducing variability in efficacy studies can increase confidence in efficacy study outcomes without altering group sizes. By using a measurement device with lower user variability, the chance of missing a therapeutic effect can be reduced and time and resources spent pursuing false results could be saved. This improvement in data quality is of particular interest in discovery and dosing studies, where being able to detect small differences between groups is crucial.

Detecting drug-target binding in cells using fluorescence-activated cell sorting coupled with mass spectrometry analysis

The assessment of drug-target engagement for determining the efficacy of a compound inside cells remains challenging, particularly for difficult target proteins. Existing techniques are more suited to soluble protein targets. Difficult target proteins include those with challenging in vitro solubility, stability or purification properties that preclude target isolation. Here, we report a novel technique that measures intracellular compound-target complex formation, as well as cellular permeability, specificity and cytotoxicity-the toxicity-affinity-permeability-selectivity (TAPS) technique. The TAPS assay is exemplified here using human kynurenine 3-monooxygenase (KMO), a challenging intracellular membrane protein target of significant current interest. TAPS confirmed target binding of known KMO inhibitors inside cells. We conclude that the TAPS assay can be used to facilitate intracellular hit validation on most, if not all intracellular drug targets.

Publication trends of study protocols in rehabilitation

INTRODUCTION

Growing evidence points for the need to publish study protocols in the health field. The aim of this paper was to observe whether the growing interest in publishing study protocols in the broader health field has been translated into increased publications of rehabilitation study protocols.

EVIDENCE ACQUISITION

PubMed was searched with appropriate combinations of Medical Subject Headings up to December 2014. The effective presence of study protocols was manually screened. Regression models analyzed the yearly growth of publications. Two-sample Z-tests analyzed whether the proportion of systematic reviews (SRs) and randomized controlled trials (RCTs) among study protocols differed from that of the same designs for the broader rehabilitation research.

EVIDENCE SYNTHESIS

Up to December 2014, 746 publications of rehabilitation study protocols were identified, with an exponential growth since 2005 (r2=0.981; P<0.001). RCT protocols were the most common among rehabilitation study protocols (83%), while RCTs were significantly more prevalent among study protocols than among the broader rehabilitation research (83% vs. 35.8%; P<0.001). For SRs, the picture was reversed: significantly less common among study protocols (2.8% vs. 9.3%; P<0.001). Funding was more often reported by rehabilitation study protocols than the broader rehabilitation research (90% vs. 53.1%; P<0.001). Rehabilitation journals published a significantly lower share of rehabilitation study protocols than they did for the broader rehabilitation research (1.8% vs.16.7%; P<0.001).

CONCLUSIONS

Identifying the reasons for these discrepancies and reverting unwarranted disparities (e.g. low rate of publication for rehabilitation SR protocols) are likely new avenues for rehabilitation research and its publication. SRs, particularly those aggregating RCT results, are considered the best standard of evidence to guide rehabilitation clinical practice; however, that standard can be improved in rigor and/or transparency if the publications of rehabilitation SRs protocols become more common.

Receptor-ligand interactions: Advanced biomedical applications

Receptor-ligand interactions (RLIs) are at the base of all biological events occurring in living cells. The understanding of interactions between complementary macromolecules in biological systems represents a high-priority research area in bionanotechnology to design the artificial systems mimicking natural processes. This review summarizes and analyzes RLIs in some cutting-edge biomedical fields, in particular, for the preparation of novel stationary phases to separate complex biological mixtures in medical diagnostics, for the design of ultrasensitive biosensors for identification of biomarkers of various diseases at early stages, as well as in the development of innovative biomaterials and approaches for regenerative medicine. All these biotechnological fields are closely related, because their success depends on a proper choice, combination and spatial disposition of the single components of ligand-receptor pairs on the surface of appropriately designed support.

Modulation of learning and memory by natural polyamines

Spermine and spermidine are natural polyamines that are produced mainly via decarboxylation of l-ornithine and the sequential transfer of aminopropyl groups from S-adenosylmethionine to putrescine by spermidine synthase and spermine synthase. Spermine and spermidine interact with intracellular and extracellular acidic residues of different nature, including nucleic acids, phospholipids, acidic proteins, carboxyl- and sulfate-containing polysaccharides. Therefore, multiple actions have been suggested for these polycations, including modulation of the activity of ionic channels, protein synthesis, protein kinases, and cell proliferation/death, within others. In this review we summarize these neurochemical/neurophysiological/morphological findings, particularly those that have been implicated in the improving and deleterious effects of spermine and spermidine on learning and memory of naïve animals in shock-motivated and nonshock-motivated tasks, from a historical perspective. The interaction with the opioid system, the facilitation and disruption of morphine-induced reward and the effect of polyamines and putative polyamine antagonists on animal models of cognitive diseases, such as Alzheimer's, Huntington, acute neuroinflammation and brain trauma are also reviewed and discussed. The increased production of polyamines in Alzheimer's disease and the biphasic nature of the effects of polyamines on memory and on the NMDA receptor are also considered. In light of the current literature on polyamines, which include the description of an inborn error of the metabolism characterized by mild-to moderate mental retardation and polyamine metabolism alterations in suicide completers, we can anticipate that polyamine targets may be important for the development of novel strategies and approaches for understanding the etiopathogenesis of important central disorders and their pharmacological treatment.

Guidelines for manuscript submission in the peer-reviewed pharmacological literature

Recent reports have highlighted studies in biomedical research that cannot be reproduced, tending to undermine the credibility, relevance and sustainability of the research process. To address this issue, a number of factors can be monitored to improve the overall probability of reproducibility. These include: (i) shortcomings in experimental design and execution that involve hypothesis conceptualization, statistical analysis, and data reporting; (ii) investigator bias and error; (iii) validation of reagents including cells and antibodies; and (iv) fraud. Historically, research data that have undergone peer review and are subsequently published are then subject to independent replication via the process of self-correction. This often leads to refutation of the original findings and retraction of the paper by which time considerable resources have been wasted in follow-on studies. New NIH guidelines focused on experimental conduct and manuscript submission are being widely adopted in the peer-reviewed literature. These, in their various iterations, are intended to improve the transparency and accuracy of data reporting via the use of checklists that are often accompanied by "best practice" guidelines that aid in validating the methodologies and reagents used in data generation. The present Editorial provides background and context to a newly developed checklist for submissions to Biochemical Pharmacology that is intended to be clear, logical, useful and unambiguous in assisting authors in preparing manuscripts and in facilitating the peer review process. While currently optional, development of this checklist based on user feedback will result in it being mandatory within the next 12 months.

Biased agonism at kappa opioid receptors: Implication in pain and mood disorders

The kappa opioid receptor (k receptor) and its endogenous ligand dynorphin have received significant attention due to their involvement in pathophysiology of mood disorders, drug addiction, psychotic disorders and pain. Multiple lines of evidences suggest that the k receptor modulates overlapping neurocircuits connecting brainstem monoaminergic nuclei with forebrain limbic structures and thereby regulates neurobiological effects of stress and psychostimulants. The emerging concept of "biased agonism" (also known as functional selectivity) for G Protein Coupled Receptor (GPCR) ligands have provided new insights into overall response generated by a ligand, which could be exploited for drug discovery. According to this concept, every ligand possesses the unique ability (coded in its structure) that dictates distinct signalling pattern, and consequently beneficial or adverse response. Although still a long way to comprehend the clinical potential of biased GPCR ligands, such ligand could be vital pharmacological probes. This article highlights various lines of evidence, which indicates different ligands of k receptor as "biased", and their potential implications in mood and pain disorders.

Experimental design and analysis and their reporting: new guidance for publication in BJP

Linked Editorials

This Editorial is part of a series. To view the other Editorials in this series, visit: http://onlinelibrary.wiley.com/doi/10.1111/bph.12956/abstract; http://onlinelibrary.wiley.com/doi/10.1111/bph.12954/abstract; http://onlinelibrary.wiley.com/doi/10.1111/bph.12955/abstract and http://onlinelibrary.wiley.com/doi/10.1111/bph.13112/abstract

Reproducibility in Science

Medical and scientific advances are predicated on new knowledge that is robust and reliable and that serves as a solid foundation on which further advances can be built. In biomedical research, we are in the midst of a revolution with the generation of new data and scientific publications at a previously unprecedented rate. However, unfortunately, there is compelling evidence that the majority of these discoveries will not stand the test of time. To a large extent, this reproducibility crisis in basic and preclinical research may be as a result of failure to adhere to good scientific practice and the desperation to publish or perish. This is a multifaceted, multistakeholder problem. No single party is solely responsible, and no single solution will suffice. Here we review the reproducibility problems in basic and preclinical biomedical research, highlight some of the complexities, and discuss potential solutions that may help improve research quality and reproducibility.

The future of drug discovery: enabling technologies for enhancing lead characterization and profiling therapeutic potential

Technology often serves as a handmaiden and catalyst of invention. The discovery of safe, effective medications depends critically upon experimental approaches capable of providing high-impact information on the biological effects of drug candidates early in the discovery pipeline. This information can enable reliable lead identification, pharmacological compound differentiation and successful translation of research output into clinically useful therapeutics. The shallow preclinical profiling of candidate compounds promulgates a minimalistic understanding of their biological effects and undermines the level of value creation necessary for finding quality leads worth moving forward within the development pipeline with efficiency and prognostic reliability sufficient to help remediate the current pharma-industry productivity drought. Three specific technologies discussed herein, in addition to experimental areas intimately associated with contemporary drug discovery, appear to hold particular promise for strengthening the preclinical valuation of drug candidates by deepening lead characterization. These are: i) hydrogen-deuterium exchange mass spectrometry for characterizing structural and ligand-interaction dynamics of disease-relevant proteins; ii) activity-based chemoproteomics for profiling the functional diversity of mammalian proteomes; and iii) nuclease-mediated precision gene editing for developing more translatable cellular and in vivo models of human diseases. When applied in an informed manner congruent with the clinical understanding of disease processes, technologies such as these that span levels of biological organization can serve as valuable enablers of drug discovery and potentially contribute to reducing the current, unacceptably high rates of compound clinical failure.

Translational paradigms in pharmacology and drug discovery

The translational sciences represent the core element in enabling and utilizing the output from the biomedical sciences and to improving drug discovery metrics by reducing the attrition rate as compounds move from preclinical research to clinical proof of concept. Key to understanding the basis of disease causality and to developing therapeutics is an ability to accurately diagnose the disease and to identify and develop safe and effective therapeutics for its treatment. The former requires validated biomarkers and the latter, qualified targets. Progress has been hampered by semantic issues, specifically those that define the end product, and by scientific issues that include data reliability, an overt reductionistic cultural focus and a lack of hierarchically integrated data gathering and systematic analysis. A necessary framework for these activities is represented by the discipline of pharmacology, efforts and training in which require recognition and revitalization.

Quantitative versus qualitative data: the numerical dimensions of drug action

The application of detailed quantitative analyses of the concentration dependence of the biological responses mediated by endogenous hormones and other mediators, drugs, and related compounds has been the foundation of pharmacology for the past century or more. This approach has been remarkably successful in identifying the specific molecular targets for these mediators and drugs, in establishing the mechanisms for those effects at both the cellular and whole organismal levels, and in the development of new chemical entities (NCEs) with great selectivity for individual molecular targets. The availability of such compounds has unfortunately led to a mindset that detailed quantitative analyses are no longer necessary to use such compounds in understanding biological system function and to draw valid conclusions in regard to the utility of NCEs selective for putative drug targets in the potential treatment of human disease states. This lack of appreciation for quantitative approaches has contributed significantly to the all-too-frequent failures of new drug candidates in early-stage clinical trials. The present article reviews basic drug/receptor concepts together with the mathematical relationships that underlie the quantitative analysis of dose-response and concentration-effect relationships for individual compounds and for more complex systems, such as the comparative analysis of multiple compounds at a single receptor. A thorough understanding of these concepts and their associated analyses, along with their proper and rigorous application in all pre-clinical drug development studies, is an essential component of an integrated approach toward improving drug development.