Reductionism and proxy failure: From neuroscience to target-based drug discovery

Reductionist methodologies reduce phenomena to some of their lower-level components. Researchers gradually shift their focus away from observing the actual object of study toward investigating and optimizing such lower-level proxies. Following reductionism, these proxies progressively diverge further from the original object of study. We vividly illustrate this in the evolution of target-based drug discovery from rational and phenotypic drug discovery.

Models and approaches to comprehend and address glial inflammation following spinal cord injury

Spinal cord injury (SCI) culminates in chronic inflammation and glial scar formation driven by the activation of microglia and astrocytes. Current anti-inflammatory strategies to treat glial activation associated with SCI have several limitations. Existing in vitro and ex vivo models studying molecular mechanisms associated with inflammation focus only on the acute phase. However, the progression of glial cell-derived inflammation over the acute-to-chronic phases has not been assessed. Understanding this progression will help establish a framework for evaluating therapeutic strategies. Additionally, new models could be useful as high-throughput screening (HTS) platforms. This review aims to highlight currently available models and future methods that could facilitate screening of novel therapeutics for SCI.

Deep learning in image-based phenotypic drug discovery

Modern drug discovery approaches often use high-content imaging to systematically study the effect on cells of large libraries of chemical compounds. By automatically screening thousands or millions of images to identify specific drug-induced cellular phenotypes, for example, altered cellular morphology, these approaches can reveal 'hit' compounds offering therapeutic promise. In the past few years, artificial intelligence (AI) methods based on deep learning (DL) [a family of machine learning (ML) techniques] have disrupted virtually all image analysis tasks, from image classification to segmentation. These powerful methods also promise to impact drug discovery by accelerating the identification of effective drugs and their modes of action. In this review, we highlight applications and adaptations of ML, especially DL methods for cell-based phenotypic drug discovery (PDD).

Compounds co-targeting kinases in axon regulatory pathways promote regeneration and behavioral recovery after spinal cord injury in mice

Recovery from spinal cord injury (SCI) and other central nervous system (CNS) trauma is hampered by limits on axonal regeneration in the CNS. Regeneration is restricted by the lack of neuron-intrinsic regenerative capacity and by the repressive microenvironment confronting damaged axons. To address this challenge, we have developed a therapeutic strategy that co-targets kinases involved in both extrinsic and intrinsic regulatory pathways. Prior work identified a kinase inhibitor (RO48) with advantageous polypharmacology (co-inhibition of targets including ROCK2 and S6K1), which promoted CNS axon growth in vitro and corticospinal tract (CST) sprouting in a mouse pyramidotomy model. We now show that RO48 promotes neurite growth from sensory neurons and a variety of CNS neurons in vitro, and promotes CST sprouting and/or regeneration in multiple mouse models of spinal cord injury. Notably, these in vivo effects of RO48 were seen in several independent experimental series performed in distinct laboratories at different times. Finally, in a cervical dorsal hemisection model, RO48 not only promoted growth of CST axons beyond the lesion, but also improved behavioral recovery in the rotarod, gridwalk, and pellet retrieval tasks. Our results provide strong evidence for RO48 as an effective compound to promote axon growth and regeneration. Further, they point to strategies for increasing robustness of interventions in pre-clinical models.

What are the challenges with multi-targeted drug design for complex diseases?

INTRODUCTION

Current findings on multifactorial diseases with a complex pathomechanism confirm that multi-target drugs are more efficient ways in treating them as opposed to single-target drugs. However, to design multi-target ligands, a number of factors and challenges must be taken into account.

AREAS COVERED

In this perspective, we summarize the concept of application of multi-target drugs for the treatment of complex diseases such as neurodegenerative diseases, schizophrenia, diabetes, and cancer. We discuss the aspects of target selection for multifunctional ligands and the application of in silico methods in their design and optimization. Furthermore, we highlight other challenges such as balancing affinities to different targets and drug-likeness of obtained compounds. Finally, we present success stories in the design of multi-target ligands for the treatment of common complex diseases.

EXPERT OPINION

Despite numerous challenges resulting from the design of multi-target ligands, these efforts are worth making. Appropriate target selection, activity balancing, and ligand drug-likeness belong to key aspects in the design of ligands acting on multiple targets. It should be emphasized that in silico methods, in particular inverse docking, pharmacophore modeling, machine learning methods and approaches derived from network pharmacology are valuable tools for the design of multi-target drugs.

Knowledge-based approaches to drug discovery for rare diseases

The conventional drug discovery pipeline has proven to be unsustainable for rare diseases. Herein, we discuss recent advances in biomedical knowledge mining applied to discovering therapeutics for rare diseases. We summarize current chemogenomics data of relevance to rare diseases and provide a perspective on the effectiveness of machine learning (ML) and biomedical knowledge graph mining in rare disease drug discovery. We illustrate the power of these methodologies using a chordoma case study. We expect that a broader application of knowledge graph mining and artificial intelligence (AI) approaches will expedite the discovery of viable drug candidates against both rare and common diseases.

Natural Products Are a Promising Source for Anthelmintic Drug Discovery

Parasitic nematodes infect almost all forms of life. In the human context, parasites are one of the major causative factors for physical and intellectual growth retardation in the developing world. In the agricultural setting, parasites have a great economic impact through a reduction in livestock performance or control cost. The main method of controlling these devastating conditions is the use of anthelmintic drugs. Unfortunately, there are only a few anthelmintic drug classes available in the market and significant resistance has developed in most of the parasitic species of livestock. Therefore, development of new anthelmintics with different modes of action is critical for sustainable parasitic control in the future. The drug development pipeline is broadly limited to two types of molecules, namely synthetic compounds and natural plant products. Compared to synthetic compounds, natural products are highly diverse, and many have historically proven valuable in folk medicine to treat various gastrointestinal ailments. This review focus on the use of traditional knowledge-based plant extracts in the development of new therapeutic leads, the approaches used as screening techniques, and common bottlenecks and opportunities in plant-based anthelmintic drug discovery.

Synthesis and Antiplasmodial Activity of Bisindolylcyclobutenediones

Malaria is one of the most dangerous infectious diseases. Because the causative Plasmodium parasites have developed resistances against virtually all established antimalarial drugs, novel antiplasmodial agents are required. In order to target plasmodial kinases, novel N-unsubstituted bisindolylcyclobutenediones were designed as analogs to the kinase inhibitory bisindolylmaleimides. Molecular docking experiments produced favorable poses of the unsubstituted bisindolylcyclobutenedione in the ATP binding pocket of various plasmodial protein kinases. The synthesis of the title compounds was accomplished by sequential Friedel-Crafts acylation procedures. In vitro screening of the new compounds against transgenic NF54-luc P. falciparum parasites revealed a set of derivatives with submicromolar activity, of which some displayed a reasonable selectivity profile against a human cell line. Although the molecular docking studies suggested the plasmodial protein kinase PfGSK-3 as the putative biological target, the title compounds failed to inhibit the isolated enzyme in vitro. As selective submicromolar antiplasmodial agents, the N-unsubstituted bisindolylcyclobutenediones are promising starting structures in the search for antimalarial drugs, albeit for a rational development, the biological target addressed by these compounds has yet to be identified.

SARs for the Antiparasitic Plant Metabolite Pulchrol. 3. Combinations of New Substituents in A/B-Rings and A/C-Rings

The natural products pulchrol and pulchral, isolated from the roots of the Mexican plant Bourreria pulchra, have previously been shown to possess antiparasitic activity towards Trypanosoma cruzi, Leishmania braziliensis and L. amazonensis, which are protozoa responsible for Chagas disease and leishmaniasis. These infections have been classified as neglected diseases, and still require the development of safer and more efficient alternatives to their current treatments. Recent SARs studies, based on the pulchrol scaffold, showed which effects exchanges of its substituents have on the antileishmanial and antitrypanosomal activity. Many of the analogues prepared were shown to be more potent than pulchrol and the current drugs used to treat leishmaniasis and Chagas disease (miltefosine and benznidazole, respectively), in vitro. Moreover, indications of some of the possible interactions that may take place in the binding sites were also identified. In this study, 12 analogues with modifications at two or three different positions in two of the three rings were prepared by synthetic and semi-synthetic procedures. The molecules were assayed in vitro towards T. cruzi epimastigotes, L. braziliensis promastigotes, and L. amazonensis promastigotes. Some compounds had higher antiparasitic activity than the parental compound pulchrol, and in some cases even benznidazole and miltefosine. The best combinations in this subset are with carbonyl functionalities in the A-ring and isopropyl groups in the C-ring, as well as with alkyl substituents in both the A- and C-rings combined with a hydroxyl group in position 1 (C-ring). The latter corresponds to cannabinol, which indeed was shown to be potent towards all the parasites.

Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence

Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor.

The right tools for the job: the central role for next generation chemical probes and chemistry-based target deconvolution methods in phenotypic drug discovery

The reconnection of the scientific community with phenotypic drug discovery has created exciting new possibilities to develop therapies for diseases with highly complex biology. It promises to revolutionise fields such as neurodegenerative disease and regenerative medicine, where the development of new drugs has consistently proved elusive. Arguably, the greatest challenge in readopting the phenotypic drug discovery approach exists in establishing a crucial chain of translatability between phenotype and benefit to patients in the clinic. This remains a key stumbling block for the field which needs to be overcome in order to fully realise the potential of phenotypic drug discovery. Excellent quality chemical probes and chemistry-based target deconvolution techniques will be a crucial part of this process. In this review, we discuss the current capabilities of chemical probes and chemistry-based target deconvolution methods and evaluate the next advances necessary in order to fully support phenotypic screening approaches in drug discovery.

High-Throughput Screening Platforms in the Discovery of Novel Drugs for Neurodegenerative Diseases

Neurodegenerative diseases (NDDs) are incurable and debilitating conditions that result in progressive degeneration and/or death of nerve cells in the central nervous system (CNS). Identification of viable therapeutic targets and new treatments for CNS disorders and in particular, for NDDs is a major challenge in the field of drug discovery. These difficulties can be attributed to the diversity of cells involved, extreme complexity of the neural circuits, the limited capacity for tissue regeneration, and our incomplete understanding of the underlying pathological processes. Drug discovery is a complex and multidisciplinary process. The screening attrition rate in current drug discovery protocols mean that only one viable drug may arise from millions of screened compounds resulting in the need to improve discovery technologies and protocols to address the multiple causes of attrition. This has identified the need to screen larger libraries where the use of efficient high-throughput screening (HTS) becomes key in the discovery process. HTS can investigate hundreds of thousands of compounds per day. However, if fewer compounds could be screened without compromising the probability of success, the cost and time would be largely reduced. To that end, recent advances in computer-aided design, in silico libraries, and molecular docking software combined with the upscaling of cell-based platforms have evolved to improve screening efficiency with higher predictability and clinical applicability. We review, here, the increasing role of HTS in contemporary drug discovery processes, in particular for NDDs, and evaluate the criteria underlying its successful application. We also discuss the requirement of HTS for novel NDD therapies and examine the major current challenges in validating new drug targets and developing new treatments for NDDs.

Integration of pharmacogenomics and theranostics with nanotechnology as quality by design (QbD) approach for formulation development of novel dosage forms for effective drug therapy

To cater to medication needs in the future healthcare system, we need to shift from the conventional system of drug delivery to modern molecular signature-based drug delivery systems. The current drug therapies are either less effective, ineffective, or produce numerous adverse reactions. One scientific principle or discipline cannot adequately address all the problems, so we need an innovative application of the current scientific principles. Here we are proposing a novel concept of nanoformulation based on pharmacogenomics and theranostics for personalized error-free and targeted therapeutic agent delivery. The addition of more knowledge about the human genome opens the new way to study disease-gene, gene-drug, and drug-effect interactions, which is the basis of future medicines. Pharmacogenomics provides information about the disease etiology, role in genes in disease pathophysiology, disease biomarkers, drug targets, drug effects, and the fate of drugs inside the body. Theranostics approach utilizes the above information in diagnosis, treatment, and monitoring of the disease on a real-time basis. Personalized dosage forms can be formulated into a nanoformulation that provides a better therapeutic effect and minimizes adverse drug reactions. The therapeutic system needs to be shifted from the principle of one drug fits all to one drug unique population. In the present manuscript, we tried to conceptualize a modern therapeutic system by combining the three approaches viz. pharmacogenomics, theranostics, and nanotechnology applied in the area of formulation development to produce a multifunctional single tiny entity.

The Resurrection of Phenotypic Drug Discovery

Prior to genetic mapping, the majority of drug discovery efforts involved phenotypic screening, wherein compounds were screened in either in vitro or in vivo models thought to mimic the disease state of interest. While never completely abandoning phenotypic approaches, the labor intensive nature of such tests encouraged the pharmaceutical industry to move away from them in favor of target-based drug discovery, which facilitated throughput and allowed for the efficient screening of large numbers of compounds. However, a consequence of reliance on target-based screening was an increased number of failures in clinical trials due to poor correlation between novel mechanistic targets and the actual disease state. As a result, the field has seen a recent resurrection in phenotypic drug discovery approaches. In this work, we highlight some recent phenotypic projects from our industrial past and in our current academic drug discovery environment that have provided encouraging results.

Phenotypic Screening in C. elegans as a Tool for the Discovery of New Geroprotective Drugs

Population aging is one of the largest challenges of the 21st century. As more people live to advanced ages, the prevalence of age-related diseases and disabilities will increase placing an ever larger burden on our healthcare system. A potential solution to this conundrum is to develop treatments that prevent, delay or reduce the severity of age-related diseases by decreasing the rate of the aging process. This ambition has been accomplished in model organisms through dietary, genetic and pharmacological interventions. The pharmacological approaches hold the greatest opportunity for successful translation to the clinic. The discovery of such pharmacological interventions in aging requires high-throughput screening strategies. However, the majority of screens performed for geroprotective drugs in C. elegans so far are rather low throughput. Therefore, the development of high-throughput screening strategies is of utmost importance.

Drug repurposing: a promising tool to accelerate the drug discovery process

Traditional drug discovery and development involves several stages for the discovery of a new drug and to obtain marketing approval. It is necessary to discover new strategies for reducing the drug discovery time frame. Today, drug repurposing has gained importance in identifying new therapeutic uses for already-available drugs. Typically, repurposing can be achieved serendipitously (unintentional fortunate observations) or through systematic approaches. Numerous strategies to discover new indications for FDA-approved drugs are discussed in this article. Drug repurposing has therefore become a productive approach for drug discovery because it provides a novel way to explore old drugs for new use but encounters several challenges. Some examples of different approaches are reviewed here.

Identifying the Antiproliferative Effect of Astragalus Polysaccharides on Breast Cancer: Coupling Network Pharmacology With Targetable Screening From the Cancer Genome Atlas

Background:Astragalus polysaccharides (APS), natural plant compounds, have recently emerged as a promising strategy for cancer treatment, but little is known concerning their effects on breast cancer (BC) tumorigenesis.

Methods: We obtained breast cancer genetic data from The Cancer Genome Atlas (TCGA) database, network pharmacology to further clarify its biological properties. Survival analysis and molecular docking techniques were implemented for the final screening to obtain key target information. Our experiments focused on the detection of intervention effects of APS on BC cells (MCF-7 and MDA-MB-231), and quantitative RT-PCR (qRT-PCR) was used to assess the expression of key targets.

Results: A total of 1,439 differentially expressed genes (DEGs) were identified by TCGA and used to build disease networks. Module analysis, gene ontology and pathway analysis revealed characteristic of the DEGs network. Topological properties were used to identify key targets, survival analysis and molecular docking finally found that the targets of APS regulation of BC cells may be CCNB1, CDC6, and p53. Through cell viability, migration and invasion assays, we found that APS interferes with the development of breast cancer in MCF7 and MDA-MB-231 cells in a dose-dependent manner. Furthermore, qRT-PCR verification suggested that the expression of CCNB1 and CDC6 in breast cancer cells was significantly downregulated in response to APS, while expression of the tumor suppressor gene P53 was significantly increased.

Conclusion: Results of this study suggest therapeutic potential for APS in BC treatment, possibly through interventions with CCNB1, CDC6, and P53. Furthermore, these findings illustrate the feasibility of using network pharmacology to connect large-scale target data as a way to discover the mechanism of natural products interfering with disease.

Scaffold Ranking and Positional Scanning Identify Novel Neurite Outgrowth Promoters with Nanomolar Potency

Central nervous system (CNS) neurons typically fail to regrow their axons after injury. Injuries or neuropathies that damage CNS axons and disrupt neuronal circuitry often result in permanent functional deficits. Axon regeneration is therefore an intensely pursued therapeutic strategy for numerous CNS disorders. Phenotypic screens utilizing primary neurons have proven successful at identifying agents that promote axon regeneration in vivo. Here, we report the screening of mixture-based combinatorial small molecule libraries in a phenotypic assay utilizing primary CNS neurons and the discovery of neurite outgrowth promoters with low nanomolar potency.

An automated high-throughput system for phenotypic screening of chemical libraries on C. elegans and parasitic nematodes

Parasitic nematodes infect hundreds of millions of people and farmed livestock. Further, plant parasitic nematodes result in major crop damage. The pipeline of therapeutic compounds is limited and parasite resistance to the existing anthelmintic compounds is a global threat. We have developed an INVertebrate Automated Phenotyping Platform (INVAPP) for high-throughput, plate-based chemical screening, and an algorithm (Paragon) which allows screening for compounds that have an effect on motility and development of parasitic worms. We have validated its utility by determining the efficacy of a panel of known anthelmintics against model and parasitic nematodes: Caenorhabditis elegans, Haemonchus contortus, Teladorsagia circumcincta, and Trichuris muris. We then applied the system to screen the Pathogen Box chemical library in a blinded fashion and identified compounds already known to have anthelmintic or anti-parasitic activity, including tolfenpyrad, auranofin, and mebendazole; and 14 compounds previously undescribed as anthelmintics, including benzoxaborole and isoxazole chemotypes. This system offers an effective, high-throughput system for the discovery of novel anthelmintics.

Effect of the Leaf Essential Oil from Cinnamosma madagascariensis Danguy on Pentylenetetrazol-induced Seizure in Rats

In the Malagasy traditional practices, the smoke from burning leaves of Cinnamosma madagascariensis Danguy is inhaled to treat brain disorders such as dementia, epilepsy, and headache. In the present work, we have evaluated the in vivo anticonvulsant effects of the essential oil from leaves of C. madagascariensis (CMEO). CMEO was isolated by steam distillation. The anticonvulsant activity of CMEO (0.4 and 0.8 ml/kg bw) administered subcutaneously was evaluated on pentylenetetrazol (PTZ)-induced seizures in Wistar rats; diazepam was used as positive control. Linalool, limonene, and myrcene were the major CMEO constituents. At the dose of 0.8 ml/kg, CMEO completely arrested the PTZ-induced convulsions with moderate sedative effects. The traditional anticonvulsant use of C. madagascariensis was confirmed allowing us to candidate molecules from CMEO as potential drugs to treat convulsions associated with strong agitation.

High content analysis of phagocytic activity and cell morphology with PuntoMorph

BACKGROUND

Phagocytosis is essential for maintenance of normal homeostasis and healthy tissue. As such, it is a therapeutic target for a wide range of clinical applications. The development of phenotypic screens targeting phagocytosis has lagged behind, however, due to the difficulties associated with image-based quantification of phagocytic activity.

NEW METHOD

We present a robust algorithm and cell-based assay system for high content analysis of phagocytic activity. The method utilizes fluorescently labeled beads as a phagocytic substrate with defined physical properties. The algorithm employs statistical modeling to determine the mean fluorescence of individual beads within each image, and uses the information to conduct an accurate count of phagocytosed beads. In addition, the algorithm conducts detailed and sophisticated analysis of cellular morphology, making it a standalone tool for high content screening.

RESULTS

We tested our assay system using microglial cultures. Our results recapitulated previous findings on the effects of microglial stimulation on cell morphology and phagocytic activity. Moreover, our cell-level analysis revealed that the two phenotypes associated with microglial activation, specifically cell body hypertrophy and increased phagocytic activity, are not highly correlated. This novel finding suggests the two phenotypes may be under the control of distinct signaling pathways.

COMPARISON WITH EXISTING METHODS

We demonstrate that our assay system outperforms preexisting methods for quantifying phagocytic activity in multiple dimensions including speed, accuracy, and resolution.

CONCLUSIONS

We provide a framework to facilitate the development of high content assays suitable for drug screening. For convenience, we implemented our algorithm in a standalone software package, PuntoMorph.

Identification of Breast Cancer Inhibitors Specific for G Protein-Coupled Estrogen Receptor (GPER)-Expressing Cells

Together with estrogen receptors ERα and ERβ, the G protein-coupled estrogen receptor (GPER) mediates important pathophysiological signaling pathways induced by estrogens and is currently regarded as a promising target for ER-negative (ER-) and triple-negative (TN) breast cancer. Only a few selective GPER modulators have been reported to date, and their use in cancer cell lines has often led to contradictory results. Herein we report the application of virtual screening and cell-based studies for the identification of new chemical scaffolds with a specific antiproliferative effect against GPER-expressing breast cancer cell lines. Out of the four different scaffolds identified, 8-chloro-4-(4-chlorophenyl)pyrrolo[1,2-a]quinoxaline 14 c was found to be the most promising compound able to induce: 1) antiproliferative activity in GPER-expressing cell lines (MCF7 and SKBR3), similarly to G15; 2) no effect on cells that do not express GPER (HEK293); 3) a decrease in cyclin D1 expression; and 4) a sustained induction of cell-cycle negative regulators p53 and p21.

Quality by design (QbD) approach of pharmacogenomics in drug designing and formulation development for optimization of drug delivery systems

Conventional approaches of drug discovery are very complex, costly and time consuming. But after the completion of human genome project, applications of pharmacogenomics in this area completely revolutionize the drug discovery and development process to produce a quality by design (QbD) approach based products. The applications of two areas of pharmacogenomics i.e. structural and functional pharmacogenomics excel the drug discovery process by employing genomic data in drug target identification and evaluation, lead optimization via high throughput screening, evaluation of drug metabolizing enzymes, drug transporters and drug receptors using computer aided technique and bioinformatics library data base. Pharmacogenomics also provides an important and reliable basis for evaluation and optimization of the dosage forms as well as repositioning of failed drugs for the treatment of new disease. Various dosage forms of category of drugs such as anticancer drugs, vaccines, gene and DNA delivery systems and immunological agents can be easily evaluated based on the genetic markers of the related disease. The effect of different formulation polymers on pharmacokinetic and pharmacodynamic properties of drugs can be assessed easily and therefore it plays an important role in formulation optimization. However, current applications of pharmacogenomics in drug discovery and formulation optimization are very limited because of costly and non accessible techniques for everyone, but in future, with the advancement in the technology; the application of genomic data in drug discovery will provide us with innovative, safer and more efficacious medicines.