Current Drug Discovery Research Articles

Backtranslating clinical knowledge for use in cheminformatics—What is the potential?

‘From bench to bedside’ is seeing a very strong focus in current Drug Discovery. However, often overlooked are the advantages that turn out if data is used ‘from bedside to bench’, the fact one can also make beneficial use of clinical information in early Drug Discovery. By leveraging the wealth of clinical data carried by each marketed drug, down to the level of a single person, one can gain a deep insight that can be leveraged in conjunction with chemical structure information and therefore within all kinds of cheminformatics analyses. This supports the design of drugs that better fit the requirements of a well-defined subpopulation.Within this contribution I am going to focus on the realm of cheminformatics applications and how this data can thereby used to better impact the decisions of medicinal chemists.

What is the most important approach in current drug discovery: doing the right things or doing things right?

Doing the right things or doing things right: what is the most important focus for current drug discovery to secure delivery of new drugs of sustainable value to patients, healthcare professionals and healthcare providers? Some of the challenges faced today in drug discovery are addressed here: the relationship between R&D speed, cost and quality; how selection of performance metrics can affect the quality of the R&D output; the importance of leadership and management; how process orientation can affect, for example, creativity and innovation; the importance of selecting the right pharmacologic target and the right chemical lead; and why the use of drug-target kinetic and thermodynamic data to drive lead selection and lead optimization could increase success rates.

Abstract 3748: NVP-BYL719, a novel PI3Kalpha selective inhibitor with all the characteristics required for clinical development as an anti-cancer agent

Abstract Most of the current oncology drug discovery and development work has shifted towards molecularly targeted therapies. A key focus has been on identifying inhibitors against components of pathways that drive tumor cell proliferation, survival, and metastasis such as the PI3K/mTOR pathway, reported to be implicated in many human cancers through various mechanisms, such as, somatic PIK3CA missense mutations that occur at high frequency. These mutations are largely point mutations predominantly clustered within three hotspots in the helical and kinase domains of p110α: E542K, E545K and H1047R, which represent about 80% of the mutations observed, and confirmed to be oncogenic gain-of-function mutations. Based on these findings cancer-specific mutants of p110α appear to be ideal targets for drug development and p110α specific inhibitors, such as NVP-BYL719, could then have potential anti-cancer activity without causing the potential side effects that could be expected from interference with other Class I PI3K isoforms or other members of the PIKK family. NVP-BYL719 is best described as a PI3Kalpha inhibitor as in biochemical assays, it inhibits p110α as well as p110α most common somatic mutations (IC50=5 nM) much more potently than p110α and ≤ and has weak or no activity against p110α, Vps34 and mTOR and is selective against a wide range of protein kinases (> 50-fold). The potency and selectivity profile of NVP-BYL719 is confirmed at the cellular level, is correlated with inhibition of various PI3K/Akt downstream signaling pathway components and is associated with anti-proliferation of breast cancer cell lines harboring PIK3CA mutations. In vivo, NVP-BYL719 shows dose and time-dependent inhibition of the PI3K/Akt pathway which correlates with compound exposure and is associated with good tolerability and significant dose-dependent anti-tumor efficacy in PIK3CA mutant tumor xenograft models in rodents. Moreover, plasma insulin levels are significantly increased while blood glucose levels remained normal at all tested doses and time points indicating on-target effects of NVP-BYL719 on the regulation of metabolism. Overall, as a PI3Kalpha inhibitor, NVP-BYL719 has good drug-like and pharmacological properties and presents all the characteristics required for its ongoing Phase I clinical development in adult patients with advanced solid malignancies whose tumors have an alteration of the PIK3CA gene. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3748. doi:1538-7445.AM2012-3748

Drug repositioning for personalized medicine

Human diseases can be caused by complex mechanisms involving aberrations in numerous proteins and pathways. With recent advances in genomics, elucidating the molecular basis of disease on a personalized level has become an attainable goal. In many cases, relevant molecular targets will be identified for which approved drugs already exist, and the potential repositioning of these drugs to a new indication can be investigated. Repositioning is an accelerated route for drug discovery because existing drugs have established clinical and pharmacokinetic data. Personalized medicine and repositioning both aim to improve the productivity of current drug discovery pipelines, which expend enormous time and cost to develop new drugs, only to have them fail in clinical trials because of lack of efficacy or toxicity. Here, we discuss the current state of research in these two fields, focusing on recent large-scale efforts to systematically find repositioning candidates and elucidate individual disease mechanisms in cancer. We also discuss scenarios in which personalized drug repositioning could be particularly rewarding, such as for diseases that are rare or have specific mutations, as well as current challenges in this field. With an increasing number of drugs being approved for rare cancer subtypes, personalized medicine and repositioning approaches are poised to significantly alter the way we diagnose diseases, infer treatments and develop new drugs.

Amyloid-Binding Aptamer Conjugated Curcumin–PLGA Nanoparticle for Potential Use in Alzheimer’s Disease

Alzheimer’s disease is becoming a serious concern in the medical field due to its severity and prevalence. This multifactorial disease manifested by various genetic and nongenetic factors makes its treatment very difficult. Due to the inefficacy of the currently available drugs, newer therapeutic strategies are increasingly in demand. Most of the current drug discovery initiatives are pivoted around amyloid pathology which is considered to be central to the disease progression. In this work, we propose the use of amyloid-binding aptamer conjugated to poly(lactic-co-glycolic acid) (PLGA)-coated curcumin nanoparticles to bind to the amyloid plaques. Curcumin is a plant-derived compound with reported anti-amyloid activity. Recent reports reveal the importance of plasma amyloid in Alzheimer development. We propose that the amyloid-binding aptamer attached curcumin–PLGA nanoparticles can be used as a potential tool in targeting the plasma amyloid and thus helps in Alzheimer therapy.

The allosteric vestibule of a seven transmembrane helical receptor controls G-protein coupling

Seven transmembrane helical receptors (7TMRs) modulate cell function via different types of G proteins, often in a ligand-specific manner. Class A 7TMRs harbour allosteric vestibules in the entrance of their ligand-binding cavities, which are in the focus of current drug discovery. However, their biological function remains enigmatic. Here we present a new strategy for probing and manipulating conformational transitions in the allosteric vestibule of label-free 7TMRs using the M2 acetylcholine receptor as a paradigm. We designed dualsteric agonists as 'tailor-made' chemical probes to trigger graded receptor activation from the acetylcholine-binding site while simultaneously restricting spatial flexibility of the receptor's allosteric vestibule. Our findings reveal for the first time that a 7TMR's allosteric vestibule controls the extent of receptor movement to govern a hierarchical order of G-protein coupling. This is a new concept assigning a biological role to the allosteric vestibule for controlling fidelity of 7TMR signalling.

Recent Trends in Collaborative, Open Source Drug Discovery

The pharmaceutical sector has traditionally played a predominant role in screening compounds against a molecular target and optimizing chemistry to develop drugs. The basic research studies in the academic sector have provided the pharmaceutical companies with many biological targets with potential impact on therapeutics. These well- defined contributions of the pharmaceutical and academic sectors in drug discovery field are being redefined to meet the fiscal and innovation challenges in the current drug discovery landscape. There is an increased capital and personnel investment in academia in the areas of highthroughput screening and technology transfer. The pharma has adopted an open innovation paradigm which seeks to complement internal intellect with external global talent and expertise, with the overall goal of expediting complex data interpretation and introduction of more effective and safe drugs. The pharma- academia sectors are collaborating on several mutually beneficial alliances and the changing landscape at pharma- academiainterface necessitates an urgent need for a better understanding of the role of academia in translational research and suitable technology transfer terms to sustain collaborative opportunities.The collaborative partnership between pharma and academia is expected to provide the required boost to identify novel targets and develop new and effective drugs.

Role of Serotonin in Alzheimerʼs Disease

Mounting evidence accumulated over the past few years indicates that the neurotransmitter serotonin plays a significant role in cognition. As a drug target, serotonin receptors have received notable attention due in particular to the role of several serotonin-receptor subclasses in cognition and memory. The intimate anatomical and neurochemical association of the serotonergic system with brain areas that regulate memory and learning has directed current drug discovery programmes to focus on this system as a major therapeutic drug target. Thus far, none of these programmes has yielded unambiguous data that suggest that any of the new drug entities possesses disease-modifying properties, and significantly more research in this promising area of investigation is required. Compounds are currently being investigated for activity against serotonin 5-HT(1), 5-HT(4) and 5-HT(6) receptors. This review concludes that most work done in the development of selective serotonin receptor ligands is in the pre-clinical or early clinical phase. Also, while many of these compounds will likely find application as adjuvant therapy in the symptomatic treatment of Alzheimer's disease, there are currently only a few drug entities with activity against serotonin receptors that may offer the potential to alter the progression of the disease.

Current drug discovery strategies for treatment of hepatitis C virus infection

Hepatitis C virus (HCV) infection represents a major worldwide-health problem. The current standard of care is combination therapy with pegylated interferon and ribavirin, which achieves a successful response in only approximately 40% of genotype I patients. The biology of HCV infection has been under intensive research and important progress has been made in understanding the replication cycle of the virus. Several therapeutic targets have been under investigation, such as NS3 protease, NS4A replicase and NS5B polymerase. New potential targets, such as NS2 protease, as well as CD-81 and claudin-1 entry co-receptors, have also been identified. Clinical evaluations of drug candidates targeting NS3 protease, NS4A cofactor, and NS5B polymerase have demonstrated the potential of developing small molecules that interfere with the replication of the virus. Additional issues, including genotype coverage, resistant mutations, and combination therapy represent major challenges for future drug discovery efforts.

The plant-based immunomodulator curcumin as a potential candidate for the development of an adjunctive therapy for cerebral malaria

The clinical manifestations of cerebral malaria (CM) are well correlated with underlying major pathophysiological events occurring during an acute malaria infection, the most important of which, is the adherence of parasitized erythrocytes to endothelial cells ultimately leading to sequestration and obstruction of brain capillaries. The consequent reduction in blood flow, leads to cerebral hypoxia, localized inflammation and release of neurotoxic molecules and inflammatory cytokines by the endothelium. The pharmacological regulation of these immunopathological processes by immunomodulatory molecules may potentially benefit the management of this severe complication. Adjunctive therapy of CM patients with an appropriate immunomodulatory compound possessing even moderate anti-malarial activity with the capacity to down regulate excess production of proinflammatory cytokines and expression of adhesion molecules, could potentially reverse cytoadherence, improve survival and prevent neurological sequelae. Current major drug discovery programmes are mainly focused on novel parasite targets and mechanisms of action. However, the discovery of compounds targeting the host remains a largely unexplored but attractive area of drug discovery research for the treatment of CM. This review discusses the properties of the plant immune-modifier curcumin and its potential as an adjunctive therapy for the management of this complication.

Probing the links between in vitro potency, ADMET and physicochemical parameters

A common underlying assumption in current drug discovery strategies is that compounds with higher in vitro potency at their target(s) have greater potential to translate into successful, low-dose therapeutics. This has led to the development of screening cascades with in vitro potency embedded as an early filter. However, this approach is beginning to be questioned, given the bias in physicochemical properties that it can introduce early in lead generation and optimization, which is due to the often diametrically opposed relationship between physicochemical parameters associated with high in vitro potency and those associated with desirable absorption, distribution, metabolism, excretion and toxicity (ADMET) characteristics. Here, we describe analyses that probe these issues further using the ChEMBL database, which includes more than 500,000 drug discovery and marketed oral drug compounds. Key findings include: first, that oral drugs seldom possess nanomolar potency (50 nM on average); second, that many oral drugs have considerable off-target activity; and third, that in vitro potency does not correlate strongly with the therapeutic dose. These findings suggest that the perceived benefit of high in vitro potency may be negated by poorer ADMET properties.

Homology Model Versus X-ray Structure in Receptor-based Drug Design: A Retrospective Analysis with the Dopamine D3 Receptor.

Structure-based design methods commonly used in medicinal chemistry rely on a three-dimensional representation of the receptor. However, few crystal structures are solved in comparison with the huge number of pharmaceutical targets. This often renders homology models the only information available. It is particularly true for G protein-coupled receptors (GPCRs), one of the most important targets for approved medicines and current drug discovery projects. However, very few studies have tested their validity in comparison with corresponding crystal structures, especially in a lead optimization perspective. The recent solving of dopamine D3 receptor crystal structure allowed us to assess our historical homology model. We performed a statistical analysis, by docking our in-house lead optimization library of 1500 molecules. We demonstrate here that the refined homology model suits at least as well as the X-ray structure. It is concluded that when the crystal structure of a given GPCR is not available, homology modeling can be an excellent surrogate to support drug discovery efforts.

Open Access High Throughput Drug Discovery in the Public Domain: A Mount Everest in the Making

High throughput screening (HTS) facilitates screening large numbers of compounds against a biochemical target of interest using validated biological or biophysical assays. In recent years, a significant number of drugs in clinical trails originated from HTS campaigns, validating HTS as a bona fide mechanism for hit finding. In the current drug discovery landscape, the pharmaceutical industry is embracing open innovation strategies with academia to maximize their research capabilities and to feed their drug discovery pipeline. The goals of academic research have therefore expanded from target identification and validation to probe discovery, chemical genomics, and compound library screening. This trend is reflected in the emergence of HTS centers in the public domain over the past decade, ranging in size from modestly equipped academic screening centers to well endowed Molecular Libraries Probe Centers Network (MLPCN) centers funded by the NIH Roadmap initiative. These centers facilitate a comprehensive approach to probe discovery in academia and utilize both classical and cutting-edge assay technologies for executing primary and secondary screening campaigns. The various facets of academic HTS centers as well as their implications on technology transfer and drug discovery are discussed, and a roadmap for successful drug discovery in the public domain is presented. New lead discovery against therapeutic targets, especially those involving the rare and neglected diseases, is indeed a Mount Everestonian size task, and requires diligent implementation of pharmaceutical industry's best practices for a successful outcome.

Anaplastic Lymphoma Kinase: Role in specific tumours, and development of small molecule inhibitors for cancer therapy

The Anaplastic Lymphoma Kinase (ALK) is a receptor tyrosine kinase first identified as the product of a gene rearrangement in Anaplastic Large Cell Lymphoma. ALK has subsequently been found to be rearranged, mutated, or amplified in a further series of tumours including neuroblastoma, and Non-Small Cell Lung Cancer. There is strong preclinical evidence that ALK is a driving force for oncogenesis in these cases, and that inhibition of ALK kinase activity results in anti-tumoural efficacy. These observations have sparked the development of small molecule kinase inhibitors, the most advanced of which is currently in clinical testing and which has shown promising preliminary activity in the subset of lung cancer patients whose tumours harbour activated ALK. In this review, we describe the various oncogenic forms of ALK, relevant clinical settings, and give a detailed overview of current drug discovery efforts in the field.

Ranking effects of candidate drugs on biological process by integrating network analysis and Gene Ontology

There are high preclinical attrition rates in current drug discovery. The efficient assessment approach in the high throughout candidate drugs screening still needs great improvement. We propose two hypotheses. First, both drug action process and biological process can be converted to a common space of gene or gene product profiling. Second, the strength of drug action on biological process can be realized in the context of biological network. Based on the above hypotheses, we establish an algorithm termed Network-based Assessment for Drug Action (NADA) to assess the action strength of candidate drugs on certain biological processes. Then NADA is used to prioritize the effects of six compounds from traditional Chinese medicine on endothelial cell migration, a simple process defined by Gene Ontology, in the biological network specific for a given pathological process, angiogenesis. The computational results are subsequently tested by the experiment on the migration of Human Umbilical Vein Endothelial Cells in vitro. The experimental ranks for six compounds generally agree with the predicted output of NADA. NADA also outperforms the DAVID and meet/min methods in terms of the experimental orders, suggesting that the network topological features may have a key role in catching the mechanistic relationship between drug action and biological process. Hopefully, the progress of network biology approaches for deciphering complex diseases will further expedite the preclinical screening and accelerate the development of treatment modalities.

Identifying the Cellular Targets of Bioactive Small Molecules with Activity-Based Probes

The renaissance of cell- or organism-based phenotypic assays has made subsequent target identification for bioactive small organic molecules an important aspect of current drug discovery. Among the many strategies available for target identification, derivatizing bioactive small molecules into activity-based probes has the main advantage of determining small molecule-protein interactions directly in the native environment where the target proteins maintain their three-dimensional structures, including all the post-translational modifications, as the discrete small molecular probes usually have better access to intracellular compartments. Thus this chemical platform will not only afford a more precise means of understanding the mechanisms of action for bioactive molecules, but shed light onto the specificity of the bioactive small molecules. Here we will provide an overview of the strategies for the design of activity-based small molecular probes and review their applications for target identification using case studies. Special emphasis is placed on logistic concerns for probe's design as well as recent developments in this field.

Evolutionary inspirations for drug discovery

Conceptual innovations are needed to address the challenge of 'more investments, fewer drugs' in the pharmaceutical industry. Since the publication of The Origin of Species by Charles Darwin 150 years ago, evolution has been a central concept in biology. In this article, we show that evolutionary concepts are also helpful to streamline the drug-discovery pipeline through facilitating the discovery of targets and drug candidates. Furthermore, the antioxidant paradox can be addressed by an evolutionary methodology. Through examining the evolved biological roles of natural polyphenols (which dominate current antioxidant drug discovery), we reveal that polyphenols (particularly flavonoids) are not evolved for scavenging free radicals. This finding provides new clues to understanding why the strong in vitro antioxidant activities of polyphenols cannot be translated into in vivo effects. Polyphenols have evolved a superior ability to bind various proteins, so we also argue that they are good starting points for multi-target drugs.

Anticipating drug side effects by comparative pharmacology

Importance of the field: Anticipating the likely side effect profile of drugs is an aspect of key importance in current drug discovery, development and marketing. It was recently shown that drug pairs having similar side effect profiles had also affinity for a common target. Acknowledging that most drugs have a rich polypharmacology, we provide proof that drugs related by side effect similarity have in fact affinities for multiple common targets beyond their primary targets and set the basis for the use of comparative pharmacology to anticipate drug side effects.Areas covered in this review: Nomenclature issues to be able to identify and properly store drugs, targets and side effects from multiple public sources; the construction of drug networks from side effect similarity and the inference of common targets among them; polypharmacology and data completeness; methods for in silico target profiling; and comparative pharmacology and inference of common side effects.What the reader will gain: The reader is provided with a detailed step-by-step analysis of the entire process from predicting the target profile of a compound to anticipating its side effect profile, and a discussion on the particular needs and limitations found at each stage of the process through illustrative examples.Take home message: Comparing preclinical pharmacology data obtained in vitro but also predicted in silico using modern virtual screening methods represents an attractive strategy to anticipate clinical drug side effects.

Database on pharmacophore analysis of active principles, from medicinal plants

Plants continue to be a major source of medicines, as they have been throughout human history. In the present days, drug discovery from plants involves a multidisciplinary approach combining ethnobotanical, phytochemical and biological techniques to provide us new chemical compounds (lead molecules) for the development of drugs against various pharmacological targets, including cancer, diabetes and its secondary complications. In view of this need in current drug discovery from medicinal plants, here we describe another web database containing the information of pharmacophore analysis of active principles possessing antidiabetic, antimicrobial, anticancerous and antioxidant properties from medicinal plants. The database provides the botanical, taxonomic classification, biochemical as well as pharmacological properties of medicinal plants. Data on antidiabetic, antimicrobial, anti oxidative, anti tumor and anti inflammatory compounds, and their physicochemical properties, SMILES Notation, Lipinski's properties are included in our database. One of the proposed features in the database is the predicted ADMET values and the interaction of bioactive compounds to the target protein. The database alphabetically lists the compound name and also provides tabs separating for anti microbial, antitumor, antidiabetic, and antioxidative compounds. http://www.hccbif.info /

From Systems Biology to Systems Pathology: A New Subspecialty in Diagnostic and Personalized Medicine

There has been a fundamental shift in biopharmaceutical research from a linear, systematic investigation to a more whole organism, systems-oriented analysis program. The impetus behind this change is an acknowledgment that the current novel target and drug discovery model was flawed due in part to an overly simplified view of disease biology, i.e., a unidirectional path from one gene to one protein to one mechanism of action. Fortunately, recent technological advancements in whole genome analysis, DNA, RNA, proteome sequencing and mathematical modeling have permanently altered the target discovery landscape. These improvements in high throughput knowledge-creation have facilitated the multi-dimensional interrogation of disease in the context of the whole organism. One of the recently described mechanisms for helping to bridge these investigational studies with clinical medicine has been through the introduction of an analytic modeling platform known as “systems pathology”. The derived systems-based pathology models use the patients own clinical data and intact tissue specimens to construct a baseline phenotype for defining a clinical risk state. These biologic-quantitative models also provide a biomarker profile which can be linked to treatment and health outcomes. This paper presents the rationale and implementation of systems biology in the area of translational medicine and a practical clinical application, i.e., systems pathology. By incorporating high dimensional genome analysis and disease modeling efforts such as systems pathology, we illustrate how such advancements have helped bring systems biology to the clinic but have also served to make the medical decision and treatment algorithms a more patient-specific paradigm.