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The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and nearly 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16180. Catalytic receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, ion channels, nuclear hormone receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate., (© 2023 The Authors. British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of The British Pharmacological Society.)

Background: Machine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federated learning (FL) allows the training of distributed machine learning models without sharing sensitive data. In addition, the implementation is time-consuming and requires advanced programming skills and complex technical infrastructures., Objective: Various tools and frameworks have been developed to simplify the development of FL algorithms and provide the necessary technical infrastructure. Although there are many high-quality frameworks, most focus only on a single application case or method. To our knowledge, there are no generic frameworks, meaning that the existing solutions are restricted to a particular type of algorithm or application field. Furthermore, most of these frameworks provide an application programming interface that needs programming knowledge. There is no collection of ready-to-use FL algorithms that are extendable and allow users (eg, researchers) without programming knowledge to apply FL. A central FL platform for both FL algorithm developers and users does not exist. This study aimed to address this gap and make FL available to everyone by developing FeatureCloud, an all-in-one platform for FL in biomedicine and beyond., Methods: The FeatureCloud platform consists of 3 main components: a global frontend, a global backend, and a local controller. Our platform uses a Docker to separate the local acting components of the platform from the sensitive data systems. We evaluated our platform using 4 different algorithms on 5 data sets for both accuracy and runtime., Results: FeatureCloud removes the complexity of distributed systems for developers and end users by providing a comprehensive platform for executing multi-institutional FL analyses and implementing FL algorithms. Through its integrated artificial intelligence store, federated algorithms can easily be published and reused by the community. To secure sensitive raw data, FeatureCloud supports privacy-enhancing technologies to secure the shared local models and assures high standards in data privacy to comply with the strict General Data Protection Regulation. Our evaluation shows that applications developed in FeatureCloud can produce highly similar results compared with centralized approaches and scale well for an increasing number of participating sites., Conclusions: FeatureCloud provides a ready-to-use platform that integrates the development and execution of FL algorithms while reducing the complexity to a minimum and removing the hurdles of federated infrastructure. Thus, we believe that it has the potential to greatly increase the accessibility of privacy-preserving and distributed data analyses in biomedicine and beyond., (©Julian Matschinske, Julian Späth, Mohammad Bakhtiari, Niklas Probul, Mohammad Mahdi Kazemi Majdabadi, Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Anne Hartebrodt, Balazs-Attila Orban, Sándor-József Fejér, Olga Zolotareva, Supratim Das, Linda Baumbach, Josch K Pauling, Olivera Tomašević, Béla Bihari, Marcus Bloice, Nina C Donner, Walid Fdhila, Tobias Frisch, Anne-Christin Hauschild, Dominik Heider, Andreas Holzinger, Walter Hötzendorfer, Jan Hospes, Tim Kacprowski, Markus Kastelitz, Markus List, Rudolf Mayer, Mónika Moga, Heimo Müller, Anastasia Pustozerova, Richard Röttger, Christina C Saak, Anna Saranti, Harald H H W Schmidt, Christof Tschohl, Nina K Wenke, Jan Baumbach. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.07.2023.)

Alzheimer's disease (AD) and other forms of dementia are together a leading cause of disability and death in the aging global population, imposing a high personal, societal, and economic burden. They are also among the most prominent examples of failed drug developments. Indeed, after more than 40 AD trials of anti-amyloid interventions, reduction of amyloid-β (Aβ) has never translated into clinically relevant benefits, and in several cases yielded harm. The fundamental problem is the century-old, brain-centric phenotype-based definitions of diseases that ignore causal mechanisms and comorbidities. In this hypothesis article, we discuss how such current outdated nosology of dementia is a key roadblock to precision medicine and articulate how Network Medicine enables the substitution of clinicopathologic phenotypes with molecular endotypes and propose a new framework to achieve precision and curative medicine for patients with neurodegenerative disorders.

Soluble guanylate cyclase (sGC) - cyclic guanosine monophosphate (cGMP) signalling is important for healthy memory function and a healthy vascular system. Targeting sGC-cGMP signalling can therefore be a potential strategy to enhance memory processes. sGC can be targeted by using agonists, such as sGC stimulator riociguat. Therefore, this study aimed to target sGC using riociguat to investigate its acute effects on memory function and neuronal plasticity in mice. The effects of riociguat on long-term memory and a biperiden-induced memory deficit model for assessing short-term memory were tested in the object location task, and working memory was tested in the Y-maze continuous alternation task. Pharmacokinetic measurements were performed within brain tissue of mice, and hippocampal plasticity measures were assessed using western blotting. Acute oral administration with a low dose of 0.03 mg/kg riociguat was able to enhance working-, short-, and long-term spatial memory. Under cerebral vasoconstriction higher doses of riociguat were still effective on memory. Pharmacokinetic measurements revealed poor brain penetration of riociguat and its metabolite M-1. Increased activation of VASP was found, while no effects were found on other memory-related hippocampal plasticity measures. Memory enhancing effects of riociguat are most likely regulated by vascular peripheral effects on cGMP signalling. Yet, further research is needed to investigate the possible contribution of hemodynamic or metabolic effects of sGC stimulators on memory performance., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Mechanism-based therapy centred on the molecular understanding of disease-causing pathways in a given patient is still the exception rather than the rule in medicine, even in cardiology. However, recent successful drug developments centred around the second messenger cyclic guanosine-3'-5'-monophosphate (cGMP), which is regulating a number of cardiovascular disease modulating pathways, are about to provide novel targets for such a personalized cardiovascular therapy. Whether cGMP breakdown is inhibited or cGMP synthesis is stimulated via guanylyl cyclases or their upstream regulators in different cardiovascular disease phenotypes, the outcomes seem to be so far uniformly protective. Thus, a network of cGMP-modulating drugs has evolved that act in a mechanism-based, possibly causal manner in a number of cardiac conditions. What remains a challenge is the detection of cGMPopathy endotypes amongst cardiovascular disease phenotypes. Here, we review the growing clinical relevance of cGMP and provide a glimpse into the future on how drugs interfering with this pathway may change how we treat and diagnose cardiovascular diseases altogether., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Differential gene expression normalised to a single housekeeping (HK) is used to identify disease mechanisms and therapeutic targets. HK gene selection is often arbitrary, potentially introducing systematic error and discordant results. Here we examine these risks in a disease model of brain hypoxia. We first identified the eight most frequently used HK genes through a systematic review. However, we observe that in both ex-vivo and in vivo, their expression levels varied considerably between conditions. When applying these genes to normalise expression levels of the validated stroke target gene, inducible Nox4, we obtained opposing results. As an alternative tool for unbiased HK gene selection, software tools exist but are limited to individual datasets lacking genome-wide search capability and user-friendly interfaces. We, therefore, developed the HouseKeepR algorithm to rapidly analyse multiple gene expression datasets in a disease-specific manner and rank HK gene candidates according to stability in an unbiased manner. Using a panel of de novo top-ranked HK genes for brain hypoxia, but not single genes, Nox4 induction was consistently reproduced. Thus, differential gene expression analysis is best normalised against a HK gene panel selected in an unbiased manner. HouseKeepR is the first user-friendly, bias-free, and broadly applicable tool to automatically propose suitable HK genes in a tissue- and disease-dependent manner., (© 2022. The Author(s).)

Atherosclerosis and its complications are major causes of cardiovascular morbidity and death. Apart from risk factors such as hypercholesterolemia and inflammation, the causal molecular mechanisms are unknown. One proposed causal mechanism involves elevated levels of reactive oxygen species (ROS). Indeed, early expression of the ROS forming NADPH oxidase type 5 (Nox5) in vascular endothelial cells correlates with atherosclerosis and aortic aneurysm. Here we test the pro-atherogenic Nox5 hypothesis using mouse models. Because Nox5 is missing from the mouse genome, a knock-in mouse model expressing human Nox5 in its physiological location of endothelial cells (eNOX5 ki/ki ) was tested as a possible new humanised mouse atherosclerosis model. However, whether just on a high cholesterol diet or by crossing in aortic atherosclerosis-prone ApoE -/- mice with and without induction of diabetes, Nox5 neither induced on its own nor aggravated aortic atherosclerosis. Surprisingly, however, diabetic ApoE -/- x eNOX5 ki/ki mice developed aortic aneurysms more than twice as often correlating with lower vascular collagens, as assessed by trichrome staining, without changes in inflammatory gene expression, suggesting that endothelial Nox5 directly affects extracellular matrix remodelling associated with aneurysm formation in diabetes. Thus Nox5-derived reactive oxygen species are not a new independent mechanism of atherosclerosis but may enhance the frequency of abdominal aortic aneurysms in the context of diabetes. Together with similar clinical findings, our preclinical target validation opens up a first-in-class mechanism-based approach to treat or even prevent abdominal aortic aneurysms., (© 2022. The Author(s).)

Cancer is a heterogeneous disease characterized by unregulated cell growth and promoted by mutations in cancer driver genes some of which encode suitable drug targets. Since the distinct set of cancer driver genes can vary between and within cancer types, evidence-based selection of drugs is crucial for targeted therapy following the precision medicine paradigm. However, many putative cancer driver genes can not be targeted directly, suggesting an indirect approach that considers alternative functionally related targets in the gene interaction network. Once potential drug targets have been identified, it is essential to consider all available drugs. Since tools that offer support for systematic discovery of drug repurposing candidates in oncology are lacking, we developed CADDIE, a web application integrating six human gene-gene and four drug-gene interaction databases, information regarding cancer driver genes, cancer-type specific mutation frequencies, gene expression information, genetically related diseases, and anticancer drugs. CADDIE offers access to various network algorithms for identifying drug targets and drug repurposing candidates. It guides users from the selection of seed genes to the identification of therapeutic targets or drug candidates, making network medicine algorithms accessible for clinical research. CADDIE is available at https://exbio.wzw.tum.de/caddie/ and programmatically via a python package at https://pypi.org/project/caddiepy/., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Excessive production of renal reactive oxygen species (ROS) plays a major role in diabetic kidney disease (DKD). Here, we provide key findings demonstrating the predominant pathological role of the pro-oxidant enzyme NADPH oxidase 5 (NOX5) in DKD, independent of the previously characterized NOX4 pathway. In patients with diabetes, we found increased expression of renal NOX5 in association with enhanced ROS formation and upregulation of ROS-sensitive factors early growth response 1 (EGR-1), protein kinase C-α (PKC-α), and a key metabolic gene involved in redox balance, thioredoxin-interacting protein (TXNIP). In preclinical models of DKD, overexpression of NOX5 in Nox4-deficient mice enhances kidney damage by increasing albuminuria and augmenting renal fibrosis and inflammation via enhanced ROS formation and the modulation of EGR1, TXNIP, ERK1/2, PKC-α, and PKC-ε. In addition, the only first-in-class NOX inhibitor, GKT137831, appears to be ineffective in the presence of NOX5 expression in diabetes. In vitro, silencing of NOX5 in human mesangial cells attenuated upregulation of EGR1, PKC-α, and TXNIP induced by high glucose levels, as well as markers of inflammation (TLR4 and MCP-1) and fibrosis (CTGF and collagens I and III) via reduction in ROS formation. Collectively, these findings identify NOX5 as a superior target in human DKD compared with other NOX isoforms such as NOX4, which may have been overinterpreted in previous rodent studies., (© 2022 by the American Diabetes Association.)

For complex diseases, most drugs are highly ineffective, and the success rate of drug discovery is in constant decline. While low quality, reproducibility issues, and translational irrelevance of most basic and preclinical research have contributed to this, the current organ-centricity of medicine and the 'one disease-one target-one drug' dogma obstruct innovation in the most profound manner. Systems and network medicine and their therapeutic arm, network pharmacology, revolutionize how we define, diagnose, treat, and, ideally, cure diseases. Descriptive disease phenotypes are replaced by endotypes defined by causal, multitarget signaling modules that also explain respective comorbidities. Precise and effective therapeutic intervention is achieved by synergistic multicompound network pharmacology and drug repurposing, obviating the need for drug discovery and speeding up clinical translation., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Aggregates of the microtubule-associated protein tau are a common marker of neurodegenerative diseases collectively termed as tauopathies, such as Alzheimer's disease (AD) and frontotemporal dementia. Therapeutic strategies based on tau have failed in late stage clinical trials, suggesting that tauopathy may be the consequence of upstream causal mechanisms. As increasing levels of reactive oxygen species (ROS) may trigger protein aggregation or modulate protein degradation and, we had previously shown that the ROS producing enzyme NADPH oxidase 4 (NOX4) is a major contributor to cellular autotoxicity, this study was designed to evaluate if NOX4 is implicated in tauopathy. Our results show that NOX4 is upregulated in patients with frontotemporal lobar degeneration and AD patients and, in a humanized mouse model of tauopathy induced by AVV-Tau P301L brain delivery. Both, global knockout and neuronal knockdown of the Nox4 gene in mice, diminished the accumulation of pathological tau and positively modified established tauopathy by a mechanism that implicates modulation of the autophagy-lysosomal pathway (ALP) and, consequently, improving the macroautophagy flux. Moreover, neuronal-targeted NOX4 knockdown was sufficient to reduce neurotoxicity and prevent cognitive decline, even after induction of tauopathy, suggesting a direct and causal role for neuronal NOX4 in tauopathy. Thus, NOX4 is a previously unrecognized causative, mechanism-based target in tauopathies and blood-brain barrier permeable specific NOX4 inhibitors could have therapeutic potential even in established disease., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Traditional drug discovery faces a severe efficacy crisis. Repurposing of registered drugs provides an alternative with lower costs and faster drug development timelines. However, the data necessary for the identification of disease modules, i.e. pathways and sub-networks describing the mechanisms of complex diseases which contain potential drug targets, are scattered across independent databases. Moreover, existing studies are limited to predictions for specific diseases or non-translational algorithmic approaches. There is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their individual use cases. We close this gap with NeDRex, an integrative and interactive platform for network-based drug repurposing and disease module discovery. NeDRex integrates ten different data sources covering genes, drugs, drug targets, disease annotations, and their relationships. NeDRex allows for constructing heterogeneous biological networks, mining them for disease modules, prioritizing drugs targeting disease mechanisms, and statistical validation. We demonstrate the utility of NeDRex in five specific use-cases., (© 2021. The Author(s).)

The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15541. Catalytic receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, ion channels, nuclear hormone receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate., (© 2021 The Authors. British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of The British Pharmacological Society.)

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic., Competing Interests: No competing financial interests exist., (© Massimiliano Zanin et al., 2021; Published by Mary Ann Liebert, Inc.)

Despite the international guidelines on the containment of the coronavirus disease 2019 (COVID-19) pandemic, the European scientific community was not sufficiently prepared to coordinate scientific efforts. To improve preparedness for future pandemics, we have initiated a network of nine European-funded Cooperation in Science and Technology (COST) Actions that can help facilitate inter-, multi-, and trans-disciplinary communication and collaboration., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Most diseases are defined by a symptom, not a mechanism. Consequently, therapies remain symptomatic. In reverse, many potential disease mechanisms remain in arbitrary search for clinical relevance. Reactive oxygen species (ROS) are such an example. It is an attractive hypothesis that dysregulation of ROS can become a disease trigger. Indeed, elevated ROS levels of various biomarkers have been correlated with almost every disease, yet after decades of research without any therapeutic application. We here present a first systematic, non-hypothesis-based approach to transform this field as a proof of concept for biomedical research in general. We selected as seed proteins 9 families with 42 members of clinically researched ROS-generating enzymes, ROS-metabolizing enzymes or ROS targets. Applying an unbiased network medicine approach, their first neighbours were connected, and, based on a stringent subnet participation degree (SPD) of 0.4, hub nodes excluded. This resulted in 12 distinct human interactome-based ROS signalling modules, while 8 proteins remaining unconnected. This ROSome is in sharp contrast to commonly used highly curated and integrated KEGG, HMDB or WikiPathways. These latter serve more as mind maps of possible ROS signalling events but may lack important interactions and often do not take different cellular and subcellular localization into account. Moreover, novel non-ROS-related proteins were part of these forming functional hybrids, such as the NOX5/sGC, NOX1,2/NOS2, NRF2/ENC-1 and MPO/SP-A modules. Thus, ROS sources are not interchangeable but associated with distinct disease processes or not at all. Module members represent leads for precision diagnostics to stratify patients with specific ROSopathies for precision intervention. The upper panel shows the classical approach to generate hypotheses for a role of ROS in a given disease by focusing on ROS levels and to some degree the ROS type or metabolite. Low levels are considered physiological; higher amounts are thought to cause a redox imbalance, oxidative stress and eventually disease. The source of ROS is less relevant; there is also ROS-induced ROS formation, i.e. by secondary sources (see upwards arrow). The non-hypothesis-based network medicine approach uses genetically or otherwise validated risk genes to construct disease-relevant signalling modules, which will contain also ROS targets. Not all ROS sources will be relevant for a given disease; some may not be disease relevant at all. The three examples show (from left to right) the disease-relevant appearance of an unphysiological ROS modifier/toxifier protein, ROS target or ROS source.

The 1998 Nobel Prize in Medicine and Physiology for the discovery of nitric oxide, a nitrogen containing reactive oxygen species (also termed reactive nitrogen or reactive nitrogen/oxygen species) stirred great hopes. Clinical applications, however, have so far pertained exclusively to the downstream signaling of cGMP enhancing drugs such as phosphodiesterase inhibitors and soluble guanylate cyclase stimulators. All clinical attempts, so far, to inhibit NOS have failed even though preclinical models were strikingly positive and clinical biomarkers correlated perfectly. This rather casts doubt on our current way of target identification in drug discovery in general and our way of patient stratification based on correlating but not causal biomarkers or symptoms. The opposite, NO donors, nitrite and enhancing NO synthesis by eNOS/NOS3 recoupling in situations of NO deficiency, are rapidly declining in clinical relevance or hold promise but need yet to enter formal therapeutic guidelines, respectively. Nevertheless, NOS inhibition in situations of NO overproduction often jointly with enhanced superoxide (or hydrogen peroxide production) still holds promise, but most likely only in acute conditions such as neurotrauma (Stover et al., J Neurotrauma 31(19):1599-1606, 2014) and stroke (Kleinschnitz et al., J Cereb Blood Flow Metab 1508-1512, 2016; Casas et al., Proc Natl Acad Sci U S A 116(14):7129-7136, 2019). Conversely, in chronic conditions, long-term inhibition of NOS might be too risky because of off-target effects on eNOS/NOS3 in particular for patients with cardiovascular risks or metabolic and renal diseases. Nitric oxide synthases (NOS) and their role in health (green) and disease (red). Only neuronal/type 1 NOS (NOS1) has a high degree of clinical validation and is in late stage development for traumatic brain injury, followed by a phase II safety/efficacy trial in ischemic stroke. The pathophysiology of NOS1 (Kleinschnitz et al., J Cereb Blood Flow Metab 1508-1512, 2016) is likely to be related to parallel superoxide or hydrogen peroxide formation (Kleinschnitz et al., J Cereb Blood Flow Metab 1508-1512, 2016; Casas et al., Proc Natl Acad Sci U S A 114(46):12315-12320, 2017; Casas et al., Proc Natl Acad Sci U S A 116(14):7129-7136, 2019) leading to peroxynitrite and protein nitration, etc. Endothelial/type 3 NOS (NOS3) is considered protective only and its inhibition should be avoided. The preclinical evidence for a role of high-output inducible/type 2 NOS (NOS2) isoform in sepsis, asthma, rheumatic arthritis, etc. was high, but all clinical development trials in these indications were neutral despite target engagement being validated. This casts doubt on the role of NOS2 in humans in health and disease (hence the neutral, black coloring).

Reactive oxygen species (ROS) are ubiquitous metabolic products and important cellular signaling molecules that contribute to several biological functions. Pathophysiology arises when ROS are generated either in excess or in cell types or subcellular locations that normally do not produce ROS or when non-physiological types of ROS (e.g., superoxide instead of hydrogen peroxide) are formed. In the latter scenario, antioxidants were considered as the apparent remedy but, clinically, have consistently failed and even sometimes induced harm. The obvious reason for that is the non-selective ROS scavenging effects of antioxidants which interfere with both qualities of ROS, physiological and pathological. Therefore, it is essential to overcome this "antidote or neutralizer" strategy. We here review the most promising alternative approach by identifying the disease-relevant enzymatic sources of ROS, target these selectively, but leave physiological ROS signaling through other sources intact. Among all ROS sources, NADPH oxidases (NOX1-5 and DUOX1-2) stand out as their sole function is to produce ROS, whereas most other enzymatic sources only produce ROS as a by-product or upon biochemical uncoupling or damage. This qualifies NOXs as the main potential drug-target candidates in diseases associated with dysfunction in ROS signaling. As a reflection of this, the development of several NOX inhibitors has taken place. Recently, the WHO approved a new stem, "naxib," which refers to NADPH oxidase inhibitors, and thereby recognized NOX inhibitors as a new therapeutic class. This has been announced while clinical trials with the first-in-class compound, setanaxib (initially known as GKT137831) had been initiated. We also review the differences between the seven NOX family members in terms of structure and function in health and disease and then focus on the most advanced NOX inhibitors with an exclusive focus on clinically relevant validations and applications. Therapeutically relevant NADPH oxidase isoforms type 1, 2, 4, and 5 (NOX1, NOX2, NOX4, NOX5). Of note, NOX5 is not present in mice and rats and thus pre-clinically less studied. NOX2, formerly termed gp91 phox , has been correlated with many, too many, diseases and is rather relevant as genetic deficiency in chronic granulomatous disease (CGD), treated by gene therapy. Overproduction of ROS through NOX1, NOX4, and NOX5 leads to the indicated diseases states including atherosclerosis (red), a condition where NOX4 is surprisingly protective.

Hypertension is the most important cause of death and disability in the elderly. In 9 out of 10 cases, the molecular cause, however, is unknown. One mechanistic hypothesis involves impaired endothelium-dependent vasodilation through reactive oxygen species (ROS) formation. Indeed, ROS forming NADPH oxidase (Nox) genes associate with hypertension, yet target validation has been negative. We re-investigate this association by molecular network analysis and identify NOX5, not present in rodents, as a sole neighbor to human vasodilatory endothelial nitric oxide (NO) signaling. In hypertensive patients, endothelial microparticles indeed contained higher levels of NOX5-but not NOX1, NOX2, or NOX4-with a bimodal distribution correlating with disease severity. Mechanistically, mice expressing human Nox5 in endothelial cells developed-upon aging-severe systolic hypertension and impaired endothelium-dependent vasodilation due to uncoupled NO synthase (NOS). We conclude that NOX5-induced uncoupling of endothelial NOS is a causal mechanism and theragnostic target of an age-related hypertension endotype. Nox5 knock-in (KI) mice represent the first mechanism-based animal model of hypertension., Competing Interests: The authors have declared that no competing interests exist.

Network Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein-protein interaction networks, correlation-based networks, gene regulatory networks, and Bayesian networks. Network Medicine applies these integrated approaches to Omics Big Data (including genetics, epigenetics, transcriptomics, metabolomics, and proteomics) using computational biology tools and, thereby, has the potential to provide improvements in the diagnosis, prognosis, and treatment of complex diseases. We discuss briefly the types of molecular data that are used in molecular network analyses, survey the analytical methods for inferring molecular networks, and review efforts to validate and visualize molecular networks. Successful applications of molecular network analysis have been reported in pulmonary arterial hypertension, coronary heart disease, diabetes mellitus, chronic lung diseases, and drug development. Important knowledge gaps in Network Medicine include incompleteness of the molecular interactome, challenges in identifying key genes within genetic association regions, and limited applications to human diseases. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Translational, Genomic, and Systems Medicine > Translational Medicine Analytical and Computational Methods > Analytical Methods Analytical and Computational Methods > Computational Methods., (© 2020 Wiley Periodicals LLC.)

Reactive oxygen species (ROS) have been correlated with almost every human disease. Yet clinical exploitation of these hypotheses by pharmacological modulation of ROS has been scarce to nonexistent. Are ROS, thus, irrelevant for disease? No. One key misconception in the ROS field has been its consideration as a rather detrimental metabolic by-product of cell metabolism, and thus, any approach eliminating ROS to a certain tolerable level would be beneficial. We now know, instead, that ROS at every concentration, low or high, can serve many essential signaling and metabolic functions. This likely explains why systemic, nonspecific antioxidants have failed in the clinic, often with neutral and sometimes even detrimental outcomes. Recently, drug development has focused, instead, on identifying and selectively modulating ROS enzymatic sources that in a given constellation cause disease while leaving ROS physiologic signaling and metabolic functions intact. As sources, the family of NADPH oxidases stands out as the only enzyme family solely dedicated to ROS formation. Selectively targeting disease-relevant ROS-related proteins is already quite advanced, as evidenced by several phase II/III clinical trials and the first drugs having passed registration. The ROS field is expanding by including target enzymes and maturing to resemble more and more modern, big data-enhanced drug discovery and development, including network pharmacology. By defining a disease based on a distinct mechanism, in this case ROS dysregulation, and not by a symptom or phenotype anymore, ROS pharmacology is leaping forward from a clinical underperformer to a proof of concept within the new era of mechanism-based precision medicine. SIGNIFICANCE STATEMENT: Despite being correlated to almost every human disease, nearly no ROS modulator has been translated to the clinics yet. Here, we move far beyond the old-fashioned misconception of ROS as detrimental metabolic by-products and suggest 1) novel pharmacological targeting focused on selective modulation of ROS enzymatic sources, 2) mechanism-based redefinition of diseases, and 3) network pharmacology within the ROS field, altogether toward the new era of ROS pharmacology in precision medicine., (Copyright © 2020 by The Author(s).)

Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In this context, the Collaboration on Science and Technology Action on Open Multiscale Systems Medicine (OpenMultiMed) reviewed the available advanced technologies for multidimensional data generation and integration in an open-science approach as well as key clinical applications of network and systems medicine and the main issues and opportunities for the future. Results: The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales. Moreover, the application of findable, applicable, interoperable, and reusable principles and the adoption of standards increases data availability and sharing for multiscale integration and interpretation. These innovations have led to the first clinical applications of network and systems medicine, particularly in the field of personalized therapy and drug dosing. Enlarging network and systems medicine application would now imply to increase patient engagement and health care providers as well as to educate the novel generations of medical doctors and biomedical researchers to shift the current organ- and symptom-based medical concepts toward network- and systems-based ones for more precise diagnoses, interventions, and ideally prevention. Conclusion: In this dynamic setting, the health care system will also have to evolve, if not revolutionize, in terms of organization and management., Competing Interests: No competing financial interests exist., (© Blandine Comte et al. 2020; Published by Mary Ann Liebert, Inc.)

Nitric oxide (NO)-cyclic GMP (cGMP) signaling is a vasoprotective pathway therapeutically targeted, for example, in pulmonary hypertension. Its dysregulation in disease is incompletely understood. Here we show in pulmonary artery endothelial cells that feedback inhibition by NO of the NO receptor, the cGMP forming soluble guanylate cyclase (sGC), may contribute to this. Both endogenous NO from endothelial NO synthase and exogenous NO from NO donor compounds decreased sGC protein and activity. This effect was not mediated by cGMP as the NO-independent sGC stimulator, or direct activation of cGMP-dependent protein kinase did not mimic it. Thiol-sensitive mechanisms were also not involved as the thiol-reducing agent N-acetyl-L-cysteine did not prevent this feedback. Instead, both in-vitro and in-vivo and in health and acute respiratory lung disease, chronically elevated NO led to the inactivation and degradation of sGC while leaving the heme-free isoform, apo-sGC, intact or even increasing its levels. Thus, NO regulates sGC in a bimodal manner, acutely stimulating and chronically inhibiting, as part of self-limiting direct feedback that is cGMP independent. In high NO disease conditions, this is aggravated but can be functionally recovered in a mechanism-based manner by apo-sGC activators that re-establish cGMP formation.

The First International Conference in Systems and Network Medicine gathered together 200 global thought leaders, scientists, clinicians, academicians, industry and government experts, medical and graduate students, postdoctoral scholars and policymakers. Held at Georgetown University Conference Center in Washington D.C. on September 11-13, 2019, the event featured a day of pre-conference lectures and hands-on bioinformatic computational workshops followed by two days of deep and diverse scientific talks, panel discussions with eminent thought leaders, and scientific poster presentations. Topics ranged from: Systems and Network Medicine in Clinical Practice; the role of -omics technologies in Health Care; the role of Education and Ethics in Clinical Practice, Systems Thinking, and Rare Diseases; and the role of Artificial Intelligence in Medicine. The conference served as a unique nexus for interdisciplinary discovery and dialogue and fostered formation of new insights and possibilities for health care systems advances., Competing Interests: No competing financial interests exist., (© Emma Kurnat-Thoma et al. 2020 Published by Mary Ann Liebert, Inc.)

Dysfunctional reactive oxygen species (ROS) signaling is considered an important disease mechanism. Therapeutically, non-selective scavenging of ROS by antioxidants, however, has failed in multiple clinical trials to provide patient benefit. Instead, pharmacological modulation of disease-relevant, enzymatic sources of ROS appears to be an alternative, more promising and meanwhile successfully validated approach. With respect to targets, the family of NADPH oxidases (NOX) stands out as main and dedicated ROS sources. Validation of the different NOX isoforms has been mainly through genetically modified rodent models and is lagging behind in other species. It is unclear whether the different NOX isoforms are sufficiently distinct to allow selective pharmacological modulation. Here we show for five widely used NOX inhibitors that isoform selectivity can be achieved, although individual compound specificity is as yet insufficient. NOX1 was most potently (IC 50 ) targeted by ML171 (0.1 μM); NOX2, by VAS2870 (0.7 μM); NOX4, by M13 (0.01 μM) and NOX5, by ML090 (0.01 μM). In addition, some non-specific antioxidant and assay artefacts may limit the interpretation of data, which included, surprisingly, the clinically advanced NOX inhibitor, GKT136901. In a human ischemic blood-brain barrier hyperpermeability model where genetic target validation is not an option, we provide proof-of-principle that pharmacological target validation for different NOX isoforms is possible by applying an inhibitor panel at IC 50 concentrations. Moreover, our findings encourage further lead optimization and development efforts for isoform-selective NOX inhibitors in different indications., Competing Interests: Declaration of competing interest None to declare., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Reactive oxygen species (ROS) have been mainly viewed as unwanted by-products of cellular metabolism, oxidative stress, a sign of a cellular redox imbalance, and potential disease mechanisms, such as in diabetes mellitus (DM). Antioxidant therapies, however, have failed to provide clinical benefit. This paradox can be explained by recent discoveries that ROS have mainly essential signaling and metabolic functions and evolutionally conserved physiological enzymatic sources. Disease can occur when ROS accumulate in nonphysiological concentrations, locations, or forms. By focusing on disease-relevant sources and targets of ROS, and leaving ROS physiology intact, precise therapeutic interventions are now possible and are entering clinical trials. Their outcomes are likely to profoundly change our concepts of ROS in DM and in medicine in general., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Drug discovery faces an efficacy crisis to which ineffective mainly single-target and symptom-based rather than mechanistic approaches have contributed. We here explore a mechanism-based disease definition for network pharmacology. Beginning with a primary causal target, we extend this to a second using guilt-by-association analysis. We then validate our prediction and explore synergy using both cellular in vitro and mouse in vivo models. As a disease model we chose ischemic stroke, one of the highest unmet medical need indications in medicine, and reactive oxygen species forming NADPH oxidase type 4 ( Nox4 ) as a primary causal therapeutic target. For network analysis, we use classical protein-protein interactions but also metabolite-dependent interactions. Based on this protein-metabolite network, we conduct a gene ontology-based semantic similarity ranking to find suitable synergistic cotargets for network pharmacology. We identify the nitric oxide synthase ( Nos1 to 3 ) gene family as the closest target to Nox4 Indeed, when combining a NOS and a NOX inhibitor at subthreshold concentrations, we observe pharmacological synergy as evidenced by reduced cell death, reduced infarct size, stabilized blood-brain barrier, reduced reoxygenation-induced leakage, and preserved neuromotor function, all in a supraadditive manner. Thus, protein-metabolite network analysis, for example guilt by association, can predict and pair synergistic mechanistic disease targets for systems medicine-driven network pharmacology. Such approaches may in the future reduce the risk of failure in single-target and symptom-based drug discovery and therapy., Competing Interests: Conflict of interest statement: H.H.H.W.S. is a cofounder of a biotech company, Vasopharm, engaged in the development of small-molecule NOS inhibitors, currently in stage III clinical development. However, H.H.H.W.S. has no operative role in the company and holds less than 1% of shares., (Copyright © 2019 the Author(s). Published by PNAS.)

Introduction: Drug-resistant infections are becoming increasingly frequent worldwide, causing hundreds of thousands of deaths annually. This is partly due to the very limited set of protein drug targets known for human-infecting viral genomes. The eleven influenza virus proteins, for instance, exploit host cell factors for replication and suppression of the antiviral immune responses. A systems medicine approach to identify relevant and druggable host factors would dramatically expand therapeutic options. Therapeutic target identification, however, has hitherto relied on static molecular networks, whereas in reality the interactome, in particular during an infection, is subject to constant change. Methods: We developed time-course network enrichment (TiCoNE), an expert-centered approach for discovering temporal response pathways. In the first stage of TiCoNE, time-series expression data is clustered in a human-augmented manner to identify groups of biological entities with coherent temporal responses. Throughout this process, the expert can add, remove, merge, or split temporal patterns. The resulting groups can then be mapped to an interaction network to identify enriched pathways and to analyze cross-talk enrichments and depletions between groups. Finally, temporal response groups of two experiments can be intersected, to identify condition-variant response patterns that represent promising drug-target candidates. Results: We applied TiCoNE to human gene expression data for influenza A virus infection and rhino virus infection, respectively. We then identified coherent temporal response patterns and employed our cross-talk analysis to establish two potential timelines of systems-level host responses for either infection. Next, we compared the two phenotypes and unraveled condition-variant temporal groups interacting on a networks level. The highest-ranking ones we then validated via literature search and wet-lab experiments. This not only confirmed many of our candidates as previously known, but we also identified phospholipid scramblase 1 (encoded by PLSCR1 ) as a previously not recognized host factor that is essential for influenza A virus infection. Conclusion: With TiCoNE we developed a novel approach for conjointly analyzing molecular networks with time-series expression data and demonstrated its power by identifying temporal drug-targets. We provide proof-of-concept that not only novel targets can be identified using our approach, but also that anti-infective drug target discovery can be enhanced by investigating temporal molecular networks of the host in response to viral infection., Competing Interests: No competing financial interests exist.

Gene regulatory networks (GRNs) and gene expression data form a core element of systems biology-based phenotyping. Changes in the expression of transcription factors are commonly believed to have a causal effect on the expression of their targets. Here we evaluated in the best researched model organism, Escherichia coli, the consistency between a GRN and a large gene expression compendium. Surprisingly, a modest correlation was observed between the expression of transcription factors and their targets and, most noteworthy, both activating and repressing interactions were associated with positive correlation. When evaluated using a sign consistency model we found the regulatory network was not more consistent with measured expression than random network models. We conclude that, at least in E. coli, one cannot expect a causal relationship between the expression of transcription and factors their targets, and that the current static GRN does not adequately explain transcriptional regulation. The implications of this are profound as they question what we consider established knowledge of the systemic biology of cells and point to methodological limitations with respect to single omics analysis, static networks and temporality.

The past decades have witnessed a paradigm shift from the traditional drug discovery shaped around the idea of “one target, one disease” to polypharmacology (multiple targets, one disease). Given the lack of clear-cut boundaries across disease (endo)phenotypes and genetic heterogeneity across patients, a natural extension to the current polypharmacology paradigm is to target common biological pathways involved in diseases via endopharmacology (multiple targets, multiple diseases). In this study, we present proximal pathway enrichment analysis (PxEA) for pinpointing drugs that target common disease pathways towards network endopharmacology. PxEA uses the topology information of the network of interactions between disease genes, pathway genes, drug targets and other proteins to rank drugs by their interactome-based proximity to pathways shared across multiple diseases, providing unprecedented drug repurposing opportunities. Using PxEA, we show that many drugs indicated for autoimmune disorders are not necessarily specific to the condition of interest, but rather target the common biological pathways across these diseases. Finally, we provide high scoring drug repurposing candidates that can target common mechanisms involved in type 2 diabetes and Alzheimer’s disease, two conditions that have recently gained attention due to the increased comorbidity among patients.

Systems medicine has a mechanism-based rather than a symptom- or organ-based approach to disease and identifies therapeutic targets in a nonhypothesis-driven manner. In this work, we apply this to transcription factor nuclear factor (erythroid-derived 2)-like 2 (NRF2) by cross-validating its position in a protein-protein interaction network (the NRF2 interactome) functionally linked to cytoprotection in low-grade stress, chronic inflammation, metabolic alterations, and reactive oxygen species formation. Multiscale network analysis of these molecular profiles suggests alterations of NRF2 expression and activity as a common mechanism in a subnetwork of diseases (the NRF2 diseasome). This network joins apparently heterogeneous phenotypes such as autoimmune, respiratory, digestive, cardiovascular, metabolic, and neurodegenerative diseases, along with cancer. Importantly, this approach matches and confirms in silico several applications for NRF2-modulating drugs validated in vivo at different phases of clinical development. Pharmacologically, their profile is as diverse as electrophilic dimethyl fumarate, synthetic triterpenoids like bardoxolone methyl and sulforaphane, protein-protein or DNA-protein interaction inhibitors, and even registered drugs such as metformin and statins, which activate NRF2 and may be repurposed for indications within the NRF2 cluster of disease phenotypes. Thus, NRF2 represents one of the first targets fully embraced by classic and systems medicine approaches to facilitate both drug development and drug repurposing by focusing on a set of disease phenotypes that appear to be mechanistically linked. The resulting NRF2 drugome may therefore rapidly advance several surprising clinical options for this subset of chronic diseases., (Copyright © 2018 by The Author(s).)

Network medicine utilizes common genetic origins, markers and co-morbidities to uncover mechanistic links between diseases. These links can be summarized in the diseasome, a comprehensive network of disease-disease relationships and clusters. The diseasome has been influential during the past decade, although most of its links are not followed up experimentally. Here, we investigate a high prevalence unmet medical need cluster of disease phenotypes linked to cyclic GMP. Hitherto, the central cGMP-forming enzyme, soluble guanylate cyclase (sGC), has been targeted pharmacologically exclusively for smooth muscle modulation in cardiology and pulmonology. Here, we examine the disease associations of sGC in a non-hypothesis based manner in order to identify possibly previously unrecognized clinical indications. Surprisingly, we find that sGC, is closest linked to neurological disorders, an application that has so far not been explored clinically. Indeed, when investigating the neurological indication of this cluster with the highest unmet medical need, ischemic stroke, pre-clinically we find that sGC activity is virtually absent post-stroke. Conversely, a heme-free form of sGC, apo-sGC, was now the predominant isoform suggesting it may be a mechanism-based target in stroke. Indeed, this repurposing hypothesis could be validated experimentally in vivo as specific activators of apo-sGC were directly neuroprotective, reduced infarct size and increased survival. Thus, common mechanism clusters of the diseasome allow direct drug repurposing across previously unrelated disease phenotypes redefining them in a mechanism-based manner. Specifically, our example of repurposing apo-sGC activators for ischemic stroke should be urgently validated clinically as a possible first-in-class neuroprotective therapy., Competing Interests: H.H.H.W.S. receive a research grant from Bayer Healthcare, the patent owner of BAY58-2667 and BAY60-2770. The remaining authors declare no competing financial interests.