Current industry perspective of how discovery is conducted seems to be fragmented and does not have a unified overall outlook of how discovery challenges are being addressed. Consequently, well-defined processes and drug-likeness criteria are being viewed as "broken" and will not maintain future R&D productivity. In this commentary, an analysis of existing practices for defining successful development candidates resulted in a 5 "must do" list to help advance Drug Discovery as presented from a Pharmaceutics perspective. The 5 "must do" list includes: what an ideal discovery team model should look like, what criteria should be considered for the desired development candidate profile, what the building blocks of the development candidate should look like, and how to assess the development risks of the candidate.
Gómez-Outes, Antonio; Suárez-Gea, Ma Luisa; Calvo-Rojas, Gonzalo; Lecumberri, Ramón; Rocha, Eduardo; Pozo-Hernández, Carmen; Terleira-Fernández, Ana Isabel; Vargas-Castrillón, Emilio
The history of the traditional anticoagulants is marked by both perseverance and serendipity. The anticoagulant effect of heparin was discovered by McLean in 1915, while he was searching for a procoagulant in dog liver. Link identified dicumarol from spoiled sweet clover hay in 1939 as the causal agent of the sweet clover disease, a hemorrhagic disorder in cattle. Hirudin extracts from the medicinal leech were first used for parenteral anticoagulation in the clinic in 1909, but their use was limited due to adverse effects and difficulties in achieving highly purified extracts. Heparins and coumarins (i.e.: warfarin, phenprocoumon, acenocoumarol) have been the mainstay of anticoagulant therapy for more than 60 years. Over the past decades, the drug discovery paradigm has shifted toward rational design following a target-based approach, in which specific proteins, or "targets", are chosen on current understandings of pathophysiology, small molecules that inhibit the target's activity may be identified by high-throughput screening and, in selected cases, these new molecules can be developed further as drugs. Despite the application of rational design, serendipity has still played a significant role in some of the new discoveries. This review will focus on the discovery of the main anticoagulant drugs in current clinical use, like unfractionated heparin, low-molecular-weight heparins, fondaparinux, coumarins (i.e.: warfarin, acenocoumarol, phenprocoumon), parenteral direct thrombin inhibitors (DTIs) (i.e.: argatroban, recombinant hirudins, bivalirudin), oral DTIs (i.e.: dabigatran) and oral direct factor Xa inhibitors (i.e.: rivaroxaban, apixaban).
Fujioka, Masahiko; Omori, Naoki
Therapeutic effects through G protein-coupled receptors (GPCRs) are promoted by a full agonist, partial agonist, neutral antagonist or inverse agonist. Dramatic change of function such as from a neutral antagonist to a full agonist with minimal variation of ligand structure is a phenomenon that medicinal chemists often encounter. This is also influenced by a change of assay format. The subtle nature of structure-function relationships is difficult to grasp unless carefully considered from both chemistry and assay perspectives. In this article we discuss the subtle aspects of GPCR drug discovery from the medicinal chemistry perspective.
Jordan, Allan M; Waddell, Ian D; Ogilvie, Donald J
The contraction in research within pharma has seen a renaissance in drug discovery within the academic setting. Often, groups grow organically from academic research laboratories, exploiting a particular area of novel biology or new technology. However, increasingly, new groups driven by industrial staff are emerging with demonstrable expertise in the delivery of medicines. As part of a strategic review by Cancer Research UK (CR-UK), the drug discovery team at the Manchester Institute was established to translate novel research from the Manchester cancer research community into drug discovery programmes. From a standing start, we have taken innovative approaches to solve key issues faced by similar groups, such as hit finding and target identification. Herein, we share our lessons learnt and successful strategies.
Mobley, David L.; Klimovich, Pavel V.
Computational techniques see widespread use in pharmaceutical drug discovery, but typically prove unreliable in predicting trends in protein-ligand binding. Alchemical free energy calculations seek to change that by providing rigorous binding free energies from molecular simulations. Given adequate sampling and an accurate enough force field, these techniques yield accurate free energy estimates. Recent innovations in alchemical techniques have sparked a resurgence of interest in these calculations. Still, many obstacles stand in the way of their routine application in a drug discovery context, including the one we focus on here, sampling. Sampling of binding modes poses a particular challenge as binding modes are often separated by large energy barriers, leading to slow transitions. Binding modes are difficult to predict, and in some cases multiple binding modes may contribute to binding. In view of these hurdles, we present a framework for dealing carefully with uncertainty in binding mode or conformation in the context of free energy calculations. With careful sampling, free energy techniques show considerable promise for aiding drug discovery. PMID:23267463
Mobley, David L.; Klimovich, Pavel V.
Computational techniques see widespread use in pharmaceutical drug discovery, but typically prove unreliable in predicting trends in protein-ligand binding. Alchemical free energy calculations seek to change that by providing rigorous binding free energies from molecular simulations. Given adequate sampling and an accurate enough force field, these techniques yield accurate free energy estimates. Recent innovations in alchemical techniques have sparked a resurgence of interest in these calculations. Still, many obstacles stand in the way of their routine application in a drug discovery context, including the one we focus on here, sampling. Sampling of binding modes poses a particular challenge as binding modes are often separated by large energy barriers, leading to slow transitions. Binding modes are difficult to predict, and in some cases multiple binding modes may contribute to binding. In view of these hurdles, we present a framework for dealing carefully with uncertainty in binding mode or conformation in the context of free energy calculations. With careful sampling, free energy techniques show considerable promise for aiding drug discovery.
Willumsen, Niels J; Bech, Morten; Olesen, Søren-Peter; Jensen, Bo Skaaning; Korsgaard, Mads P G; Christophersen, Palle
Proper function of ion channels is crucial for all living cells. Ion channel dysfunction may lead to a number of diseases, so-called channelopathies, and a number of common diseases, including epilepsy, arrhythmia, and type II diabetes, are primarily treated by drugs that modulate ion channels. A cornerstone in current drug discovery is high throughput screening assays which allow examination of the activity of specific ion channels though only to a limited extent. Conventional patch clamp remains the sole technique with sufficiently high time resolution and sensitivity required for precise and direct characterization of ion channel properties. However, patch clamp is a slow, labor-intensive, and thus expensive, technique. New techniques combining the reliability and high information content of patch clamping with the virtues of high throughput philosophy are emerging and predicted to make a number of ion channel targets accessible for drug screening. Specifically, genuine HTS parallel processing techniques based on arrays of planar silicon chips are being developed, but also lower throughput sequential techniques may be of value in compound screening, lead optimization, and safety screening. The introduction of new powerful HTS electrophysiological techniques is predicted to cause a revolution in ion channel drug discovery.
Vyas, V. K.; Ukawala, R. D.; Ghate, M.; Chintha, C.
Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery. PMID:23204616
Vyas, V K; Ukawala, R D; Ghate, M; Chintha, C
Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery.
Ntie-Kang, Fidele; Yong, Joseph N; Owono Owono, Luc C; Sippl, Wolfgang; Megnassan, Eugene
Based on the global burden of tuberculosis and resistant strains that have recently emerged, not responding to existing therapies, it has become urgent to search for new remedies against this global human plague that has been compounded by HIV co-infection. Thus, the search for new drugs against the disease-causing agent, Mycobacterium tuberculosis (MTB), is an ongoing effort. This review discusses the state-of-the-art in anti-tuberculosis pathogenesis and anti-TB drug research, identifying some of the challenges being faced by researchers in the field and sheds light on possible ways forward, particularly in low-income countries.
Jones, H M; Chen, Y; Gibson, C; Heimbach, T; Parrott, N; Peters, S A; Snoeys, J; Upreti, V V; Zheng, M; Hall, S D
The application of physiologically based pharmacokinetic (PBPK) modeling has developed rapidly within the pharmaceutical industry and is becoming an integral part of drug discovery and development. In this study, we provide a cross pharmaceutical industry position on "how PBPK modeling can be applied in industry" focusing on the strategies for application of PBPK at different stages, an associated perspective on the confidence and challenges, as well as guidance on interacting with regulatory agencies and internal best practices.
The challenge of controlling and eventually eradicating malaria means that new tools are urgently needed. South America’s role in this fight spans both ends of the research and development spectrum: both as a continent capable of discovering and developing new medicines, and also as a continent with significant numbers of malaria patients. This article reviews the contribution of groups in the South American continent to the research and development of new medicines over the last decade. Therefore, the current situation of research targeting malaria control and eradication is discussed, including endemicity, geographical distribution, treatment, drug-resistance and diagnosis. This sets the scene for a review of efforts within South America to discover and optimize compounds with anti-malarial activity. PMID:23706107
Garbaccio, Robert M; Parmee, Emma R
Chemical probes represent an important component of both academic and pharmaceutical drug discovery research. As a complement to prior reviews that have defined this scientific field, we aim to provide an industry perspective on the value of having high-quality chemical probes throughout the course of preclinical research. By studying examples from the internal Merck pipeline, we recognize that these probes require significant collaborative investment to realize their potential impact in clarifying the tractability and translation of a given therapeutic target. This perspective concludes with recommendations for chemical probe discovery aimed toward maximizing their potential to identify targets that result in the successful delivery of novel therapeutics. Copyright © 2016 Elsevier Ltd. All rights reserved.
Martínez-Rosell, Gerard; Giorgino, Toni; Harvey, Matt J; de Fabritiis, Gianni
Bio-molecular dynamics (MD) simulations based on graphical processing units (GPUs) were first released to the public in the early 2009 with the code ACEMD. Almost 8 years after, applications now encompass a broad range of molecular studies, while throughput improvements have opened the way to millisecond sampling timescales. Based on an extrapolation of the amount of sampling in published literature, the second timescale will be reached by the year 2022, and therefore we predict that molecular dynamics is going to become one of the main tools in drug discovery in both academia and industry. Here, we review successful applications in the drug discovery domain developed over these recent years of GPU-based MD. We also retrospectively analyse limitations that have been overcome over the years and give a perspective on challenges that remain to be addressed. Copyright© Bentham Science Publishers; For any queries, please email at email@example.com.
Tsaioun, Katya; Bottlaender, Michel; Mabondzo, Aloise
The advent of early absorption, distribution, metabolism, excretion, and toxicity (ADMET) screening has increased the attrition rate of weak drug candidates early in the drug-discovery process, and decreased the proportion of compounds failing in clinical trials for ADMET reasons. This paper reviews the history of ADMET screening and its place in pharmaceutical development, and central nervous system drug discovery in particular. Assays that have been developed in response to specific needs and improvements in technology that result in higher throughput and greater accuracy of prediction of human mechanisms of absorption and toxicity are discussed. The paper concludes with the authors' forecast of new models that will better predict human efficacy and toxicity. PMID:19534730
Manjunatha, Ujjini H; Smith, Paul W
Tuberculosis poses a major global health problem and multi-drug resistant strains are increasingly prevalent. Hence there is an urgent need to discover new TB drugs. Cell based phenotypic screening represents a powerful approach to identify anti-mycobacterial compounds and elucidate novel targets. Three high throughput phenotypic screens were performed at NITD against mycobacterium. Hits were identified and chemical series selected for optimisation. This produced compounds with good in vitro anti-mycobacterial activity and pharmacokinetic properties. Some compounds displayed oral activity in mouse efficacy models of TB. Herein, we review the TB discovery efforts at NITD and share experiences in optimisation of phenotypic hits, describing challenges encountered and lessons learned. We also offer perspectives to facilitate future selection and advancement of phenotypic hits.
Matthews, Holly; Hanison, James; Nirmalan, Niroshini
The pharmaceutical industry faces unsustainable program failure despite significant increases in investment. Dwindling discovery pipelines, rapidly expanding R&D budgets and increasing regulatory control, predict significant gaps in the future drug markets. The cumulative duration of discovery from concept to commercialisation is unacceptably lengthy, and adds to the deepening crisis. Existing animal models predicting clinical translations are simplistic, highly reductionist and, therefore, not fit for purpose. The catastrophic consequences of ever-increasing attrition rates are most likely to be felt in the developing world, where resistance acquisition by killer diseases like malaria, tuberculosis and HIV have paced far ahead of new drug discovery. The coming of age of Omics-based applications makes available a formidable technological resource to further expand our knowledge of the complexities of human disease. The standardisation, analysis and comprehensive collation of the “data-heavy” outputs of these sciences are indeed challenging. A renewed focus on increasing reproducibility by understanding inherent biological, methodological, technical and analytical variables is crucial if reliable and useful inferences with potential for translation are to be achieved. The individual Omics sciences—genomics, transcriptomics, proteomics and metabolomics—have the singular advantage of being complimentary for cross validation, and together could potentially enable a much-needed systems biology perspective of the perturbations underlying disease processes. If current adverse trends are to be reversed, it is imperative that a shift in the R&D focus from speed to quality is achieved. In this review, we discuss the potential implications of recent Omics-based advances for the drug development process. PMID:28248238
Srinivas, Nuggehally R; Mullangi, Ramesh
Bioanalysis is an important aspect of drug discovery process regardless of the chosen therapeutic area. There is a general misconception that bioanalysis is seldom important during the drug discovery process because there is no scrutiny of the data from a regulatory perspective. However, bioanalytical data gathered during the discovery stage enable several key decision(s) inclusive of termination of the program and/or creating adequate differentiation from the lead competitive molecules. The review covers various stage gate screens and experimental designs where bioanalytical data are extensively used for making an informed decision during the process of drug discovery.
Whiteside, Garth T; Pomonis, James D; Kennedy, Jeffrey D
In recent years, animal behavioral models, particularly those used in pain research, have been increasingly scrutinized and criticized for their role in the poor translation of novel pharmacotherapies for chronic pain. This article addresses the use of animal models of pain from the perspective of industrial drug discovery research. It highlights how, when, and why animal models of pain are used as one of the many experimental tools used to gain better understanding of target mechanisms and rank-order compounds in the iterative process of establishing structure-activity relationships (SAR). Together, these models help create an 'analgesic signature' for a compound and inform the indications most likely to yield success in clinical trials. In addition, the authors discuss some often under-appreciated aspects of currently used (traditional) animal models of pain, including how industry balances efficacy with side effect measures as part of the overall conclusion of efficacy. This is provided to add perspective regarding current efforts to develop new models and endpoints both in rodents and larger animal species as well as assess cognitive and/or affective aspects of pain. Finally, the authors suggest ways in which efficacy evaluation in animal models of pain, whether traditional or new, might better align with clinical standards of analysis, citing examples where applying effect size and NNT estimations to animal model data suggest that the efficacy bar often may be set too low preclinically to allow successful translation to the clinical setting. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Andreol, Federico; Barbosa, Arménio Jorge Moura; Daniele Parenti, Marco; Rio, Alberto Del
Research on cancer epigenetics has flourished in the last decade. Nevertheless growing evidence point on the importance to understand the mechanisms by which epigenetic changes regulate the genesis and progression of cancer growth. Several epigenetic targets have been discovered and are currently under validation for new anticancer therapies. Drug discovery approaches aiming to target these epigenetic enzymes with small-molecules inhibitors have produced the first pre-clinical and clinical outcomes and many other compounds are now entering the pipeline as new candidate epidrugs. The most studied targets can be ascribed to histone deacetylases and DNA methyltransferases, although several other classes of enzymes are able to operate post-translational modifications to histone tails are also likely to represent new frontiers for therapeutic interventions. By acknowledging that the field of cancer epigenetics is evolving with an impressive rate of new findings, with this review we aim to provide a current overview of pre-clinical applications of small-molecules for cancer pathologies, combining them with the current knowledge of epigenetic targets in terms of available structural data and drug design perspectives. PMID:23016851
Ou-Yang, Si-sheng; Lu, Jun-yan; Kong, Xiang-qian; Liang, Zhong-jie; Luo, Cheng; Jiang, Hualiang
Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process. Because of the dramatic increase in the availability of biological macromolecule and small molecule information, the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow, including target identification and validation, lead discovery and optimization and preclinical tests. Over the past decades, computational drug discovery methods such as molecular docking, pharmacophore modeling and mapping, de novo design, molecular similarity calculation and sequence-based virtual screening have been greatly improved. In this review, we present an overview of these important computational methods, platforms and successful applications in this field. PMID:22922346
Carlino, Luca; Rastelli, Giulio
Protein kinases play crucial roles in several cell transformation processes and are validated drug targets for many human diseases, including cancer. Nevertheless, most tumors have eluded the effects of inhibition of a single kinase by activating resistance mechanisms and/or alternative pathways and escape mechanisms. In recent years, multitarget approaches directed toward inhibition of kinases and targets of different families have received increasing attention. In particular, co-targeting kinases and bromodomain epigenetic reader proteins has rapidly emerged as a promising approach to cancer drug development. In this manuscript, we will review the recent discoveries that led to the identification and optimization of dual kinase/bromodomain inhibitors. We will analyze and compare the structural features required for dual inhibition and comment on the potential of this approach in anticancer drug discovery. Moreover, we will introduce computational approaches useful for the identification of dual kinase/bromodomain inhibitors and generate ad hoc pharmacophore and docking models.
Khurdayan, V; Davies, S
Sequences in Drug Discovery is a new series of distinct brief reports on breaking topics in the field of drug R&D. This month's Sequences in Drug Discovery contains the following reports: Spotlight on West Nile virus vaccines. p38alpha MAPK--a dynamic target in rheumatoid arthritis. The need for new contraceptives: targeting PDE3. Vasopeptidase inhibition with a triple mode of action. Current advances in the development of 5-HT(6) receptor antagonists.
Karawajczyk, Anna; Giordanetto, Fabrizio; Benningshof, Jorg; Hamza, Daniel; Kalliokoski, Tuomo; Pouwer, Kees; Morgentin, Remy; Nelson, Adam; Müller, Gerhard; Piechot, Alexander; Tzalis, Dimitrios
High-throughput screening (HTS) represents a major cornerstone of drug discovery. The availability of an innovative, relevant and high-quality compound collection to be screened often dictates the final fate of a drug discovery campaign. Given that the chemical space to be sampled in research programs is practically infinite and sparsely populated, significant efforts and resources need to be invested in the generation and maintenance of a competitive compound collection. The European Lead Factory (ELF) project is addressing this challenge by leveraging the diverse experience and know-how of academic groups and small and medium enterprises (SMEs) engaged in synthetic and/or medicinal chemistry. Here, we describe the novelty, diversity, structural complexity, physicochemical characteristics and overall attractiveness of this first batch of ELF compounds for HTS purposes.
Gromo, G.; Mann, J.; Fitzgerald, J.D.
The theme of this review is to summarize the evolving processes in cardiovascular drug discovery and development within a large pharmaceutical company. Emphasis is placed on the contrast between the academic and industrial research operating environments, which can influence the effectiveness of research collaboration between the two constituencies, but which plays such an important role in drug innovation. The strategic challenges that research directors face are also emphasized. The need for improved therapy in many cardiovascular indications remains high, but the feasibility in making progress, despite the advances in molecular biology and genomics, is also assessed. PMID:24890831
Balmith, Marissa; Faya, Mbuso; Soliman, Mahmoud E S
The Ebola virus, formally known as the Ebola hemorrhagic fever, is an acute viral syndrome causing sporadic outbreaks that have ravaged West Africa. Due to its extreme virulence and highly transmissible nature, Ebola has been classified as a category A bioweapon organism. Only recently have vaccine or drug regimens for the Ebola virus been developed, including Zmapp and peptides. In addition, existing drugs which have been repurposed toward anti-Ebola virus activity have been re-examined and are seen to be promising candidates toward combating Ebola. Drug development involving computational tools has been widely employed toward target-based drug design. Screening large libraries have greatly stimulated research toward effective anti-Ebola virus drug regimens. Current emphasis has been placed on the investigation of host proteins and druggable viral targets. There is a huge gap in the literature regarding guidelines in the discovery of Ebola virus inhibitors, which may be due to the lack of information on the Ebola drug targets, binding sites, and mechanism of action of the virus. This review focuses on Ebola virus inhibitors, drugs which could be repurposed to combat the Ebola virus, computational methods which study drug-target interactions as well as providing further insight into the mode of action of the Ebola virus. © 2016 John Wiley & Sons A/S.
Harvey, Alan L
Components from venoms have stimulated many drug discovery projects, with some notable successes. These are briefly reviewed, from captopril to ziconotide. However, there have been many more disappointments on the road from toxin discovery to approval of a new medicine. Drug discovery and development is an inherently risky business, and the main causes of failure during development programmes are outlined in order to highlight steps that might be taken to increase the chances of success with toxin-based drug discovery. These include having a clear focus on unmet therapeutic needs, concentrating on targets that are well-validated in terms of their relevance to the disease in question, making use of phenotypic screening rather than molecular-based assays, and working with development partners with the resources required for the long and expensive development process. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.
Arneric, Stephen P; Holladay, Mark; Williams, Michael
Neuronal nicotinic acetylcholine receptors (nAChRs) have been a target for drug discovery efforts, primarily for CNS indications, for the past two decades. While nicotine and related natural products have been used for smoking cessation in various formulations (e.g., gum, spray, patches), it was only in 2006 with the launch of varenicline (Chantix) by Pfizer for smoking cessation that a new chemical entity (NCE) originating from a rational medicinal chemistry effort targeting neuronal AChRs was approved. The current overview outlines the chronology of drug discovery efforts in nAChRs from the cloning of the receptor family in the 1980s, to initial research efforts at SIBIA, R.J. Reynolds and Abbott, to the current industry-wide interest in nAChR agonists as novel therapeutics for pain, schizophrenia and Alzheimer's Disease. Key events in the evolution of the nAChR field were the development of high throughput electrophysiological screening tools that provided the means to enable lead optimization efforts in medicinal chemistry and the discovery by John Daly at the NIH of the frog alkaloid, epibatidine, that provided the framework for the discovery of ABT-594, an alpha4beta2 agonist that is 200 times more potent than morphine as an analgesic. Over the next decade, it is anticipated that additional NCEs including antagonists and allosteric modulators (both positive and negative), interacting with various nAChR subtypes, will be advanced to the clinic in areas of high unmet medical need, e.g., pain, neurodegeneration, to provide novel medications with improved efficacy.
Marugán, Carlos; Torres, Raquel; Lallena, María José
Targeting mitotic regulators as a strategy to fight cancer implies the development of drugs against key proteins, such as Aurora-A and -B. Current drugs, which target mitosis through a general mechanism of action (stabilization/destabilization of microtubules), have several side effects (neutropenia, alopecia, and emesis). Pharmaceutical companies aim at avoiding these unwanted effects by generating improved and selective drugs that increase the quality of life of the patients. However, the development of these drugs is an ambitious task that involves testing thousands of compounds through biochemical and cell-based assays. In addition, molecules usually target complex biological processes, involving several proteins and different molecular pathways, further emphasizing the need for high-throughput screening techniques and multiplexing technologies in order to identify drugs with the desired phenotype. We will briefly describe two multiplexing technologies [high-content imaging (HCI) and flow cytometry] and two key processes for drug discovery research (assay development and validation) following our own published industry quality standards. We will further focus on HCI as a useful tool for phenotypic screening and will provide a concrete example of HCI assay to detect Aurora-A or -B selective inhibitors discriminating the off-target effects related to the inhibition of other cell cycle or non-cell cycle key regulators. Finally, we will describe other assays that can help to characterize the in vitro pharmacology of the inhibitors. PMID:26779442
Brian, William; Tremaine, Larry M; Arefayene, Million; de Kanter, Ruben; Evers, Raymond; Guo, Yingying; Kalabus, James; Lin, Wen; Loi, Cho-Ming; Xiao, Guangqing
Genetic variants of drug metabolism enzymes and transporters can result in high pharmacokinetic and pharmacodynamic variability, unwanted characteristics of efficacious and safe drugs. Ideally, the contributions of these enzymes and transporters to drug disposition can be predicted from in vitro experiments and in silico modeling in discovery or early development, and then be utilized during clinical development. Recently, regulatory agencies have provided guidance on the preclinical investigation of pharmacogenetics, for application to clinical drug development. This white paper summarizes the results of an industry survey conducted by the Industry Pharmacogenomics Working Group on current practice and challenges with using in vitro systems and in silico models to understand pharmacogenetic causes of variability in drug disposition.
Imbrici, Paola; Liantonio, Antonella; Camerino, Giulia M.; De Bellis, Michela; Camerino, Claudia; Mele, Antonietta; Giustino, Arcangela; Pierno, Sabata; De Luca, Annamaria; Tricarico, Domenico; Desaphy, Jean-Francois; Conte, Diana
In the human genome more than 400 genes encode ion channels, which are transmembrane proteins mediating ion fluxes across membranes. Being expressed in all cell types, they are involved in almost all physiological processes, including sense perception, neurotransmission, muscle contraction, secretion, immune response, cell proliferation, and differentiation. Due to the widespread tissue distribution of ion channels and their physiological functions, mutations in genes encoding ion channel subunits, or their interacting proteins, are responsible for inherited ion channelopathies. These diseases can range from common to very rare disorders and their severity can be mild, disabling, or life-threatening. In spite of this, ion channels are the primary target of only about 5% of the marketed drugs suggesting their potential in drug discovery. The current review summarizes the therapeutic management of the principal ion channelopathies of central and peripheral nervous system, heart, kidney, bone, skeletal muscle and pancreas, resulting from mutations in calcium, sodium, potassium, and chloride ion channels. For most channelopathies the therapy is mainly empirical and symptomatic, often limited by lack of efficacy and tolerability for a significant number of patients. Other channelopathies can exploit ion channel targeted drugs, such as marketed sodium channel blockers. Developing new and more specific therapeutic approaches is therefore required. To this aim, a major advancement in the pharmacotherapy of channelopathies has been the discovery that ion channel mutations lead to change in biophysics that can in turn specifically modify the sensitivity to drugs: this opens the way to a pharmacogenetics strategy, allowing the development of a personalized therapy with increased efficacy and reduced side effects. In addition, the identification of disease modifiers in ion channelopathies appears an alternative strategy to discover novel druggable targets. PMID:27242528
Despite striking advances in the biomedical sciences, the flow of new drugs has slowed to a trickle, impairing therapeutic advances as well as the commercial success of drug companies. Reduced productivity in the drug industry is caused mainly by corporate policies that discourage innovation. This is compounded by various consequences of mega-mergers, the obsession for blockbuster drugs, the shift of control of research from scientists to marketers, the need for fast sales growth, and the discontinuation of development compounds for nontechnical reasons. Lessons from the past indicate that these problems can be overcome, and herein, new and improved directions for drug discovery are suggested. PMID:17080187
Background Phosphoinositide lipid kinases (PIKs) generate specific phosphorylated variants of phosatidylinositols (PtdIns) that are critical for second messenger signaling and cellular membrane remodeling. Mammals have 19 PIK isoforms spread across three major families: the PtIns 3-kinases (PI3Ks), PtdIns 4-kinases (PI4Ks), and PtdIns-P (PIP) kinases (PIPKs). Other eukaryotes have fewer yet varying PIK complements. PIKs are also an important, emerging class of drug targets for many therapeutic areas including cancer, inflammatory and metabolic diseases and host-pathogen interactions. Here, we report the genomic occurrences and evolutionary relationships or phylogenomics of all three PIK families across major eukaryotic groups and suggest potential ramifications for drug discovery. Results Our analyses reveal four core eukaryotic PIKs which are type III PIK4A and PIK4B, and at least one homolog each from PI3K (possibly PIK3C3 as the ancestor) and PIP5K families. We also applied evolutionary analyses to PIK disease ontology and drug discovery. Mutated PIK3CA are known to be oncogenic and several inhibitors are in anti-cancer clinical trials. We found conservation of activating mutations of PIK3CA in paralogous isoforms suggesting specific functional constraints on these residues. By mapping published compound inhibition data (IC50s) onto a phylogeny of PI3Ks, type II PI4Ks and distantly related, MTOR, ATM, ATR and PRKDC kinases, we also show that compound polypharmacology corresponds to kinase evolutionary relationships. Finally, we extended the rationale for drugs targeting PIKs of malarial Plasmodium falciparum, and the parasites, Leishmania sp. and Trypanosoma sp. by identifying those PIKs highly divergent from human homologs. Conclusion Our phylogenomic analysis of PIKs provides new insights into the evolution of second messenger signaling. We postulate two waves of PIK diversification, the first in metazoans with a subsequent expansion in cold
Wohlleben, Wolfgang; Mast, Yvonne; Stegmann, Evi; Ziemert, Nadine
Due to the threat posed by the increase of highly resistant pathogenic bacteria, there is an urgent need for new antibiotics; all the more so since in the last 20 years, the approval for new antibacterial agents had decreased. The field of natural product discovery has undergone a tremendous development over the past few years. This has been the consequence of several new and revolutionizing drug discovery and development techniques, which is initiating a 'New Age of Antibiotic Discovery'. In this review, we concentrate on the most significant discovery approaches during the last and present years and comment on the challenges facing the community in the coming years. © 2016 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.
Kumalo, Hezekiel M; Bhakat, Soumendranath; Soliman, Mahmoud E
There are over 100 different types of cancer, and each is classified based on the type of cell that is initially affected. If left untreated, cancer can result in serious health problems and eventually death. Recently, the paradigm of cancer chemotherapy has evolved to use a combination approach, which involves the use of multiple drugs each of which targets an individual protein. Inhibition of heat-shock protein 90 (Hsp90) is one of the novel key cancer targets. Because of its ability to target several signaling pathways, Hsp90 inhibition emerged as a useful strategy to treat a wide variety of cancers. Molecular modeling approaches and methodologies have become 'close counterparts' to experiments in drug design and discovery workflows. A wide range of molecular modeling approaches have been developed, each of which has different objectives and outcomes. In this review, we provide an up-to-date systematic overview on the different computational models implemented toward the design of Hsp90 inhibitors as anticancer agents. Although this is the main emphasis of this review, different topics such as background and current statistics of cancer, different anticancer targets including Hsp90, and the structure and function of Hsp90 from an experimental perspective, for example, X-ray and NMR, are also addressed in this report. To the best of our knowledge, this review is the first account, which comprehensively outlines various molecular modeling efforts directed toward identification of anticancer drugs targeting Hsp90. We believe that the information, methods, and perspectives highlighted in this report would assist researchers in the discovery of potential anticancer agents. © 2015 John Wiley & Sons A/S.
Davies, Shelley L; Moral, Maria Angels; Bozzo, Jordi
Chronicles in Drug Discovery features special interest reports on advances in drug discovery. This month we highlight agents that target and deplete immunosuppressive regulatory T cells, which are produced by tumor cells to hinder innate immunity against, or chemotherapies targeting, tumor-associated antigens. Antiviral treatments for respiratory syncytial virus, a severe and prevalent infection in children, are limited due to their side effect profiles and cost. New strategies currently under clinical development include monoclonal antibodies, siRNAs, vaccines and oral small molecule inhibitors. Recent therapeutic lines for Huntington's disease include gene therapies that target the mutated human huntingtin gene or deliver neuroprotective growth factors and cellular transplantation in apoptotic regions of the brain. Finally, we highlight the antiinflammatory and antinociceptive properties of new compounds targeting the somatostatin receptor subtype sst4, which warrant further study for their potential application as clinical analgesics.
Khurdayan, V; Bozzo, J; Sorbera, L
Chronicles in Drug Discovery is a series of brief reports on timely topics in the field of drug R&D. This month's chronicles contain the following reports: Targeting DNA repair enzymes instead of viral proteins provides a great advantage in preventing the emergence of resistant mutants. A striking increase in therapeutic approaches for the treatment of IBD has been fueled by an improved understanding of the mechanisms that underlie its pathophysiology. Peptide deformylase inhibitors are under active investigation for bacterial infections and cancer treatment. Dopamine D3 receptors present an attractive target for alcoholism therapy since they are involved in the mechanisms of alcohol dependency and abuse.
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...
Guido, Rafael V C; Oliva, Glaucius; Andricopulo, Adriano D
The identification of promising hits and the generation of high quality leads are crucial steps in the early stages of drug discovery projects. The definition and assessment of both chemical and biological space have revitalized the screening process model and emphasized the importance of exploring the intrinsic complementary nature of classical and modern methods in drug research. In this context, the widespread use of combinatorial chemistry and sophisticated screening methods for the discovery of lead compounds has created a large demand for small organic molecules that act on specific drug targets. Modern drug discovery involves the employment of a wide variety of technologies and expertise in multidisciplinary research teams. The synergistic effects between experimental and computational approaches on the selection and optimization of bioactive compounds emphasize the importance of the integration of advanced technologies in drug discovery programs. These technologies (VS, HTS, SBDD, LBDD, QSAR, and so on) are complementary in the sense that they have mutual goals, thereby the combination of both empirical and in silico efforts is feasible at many different levels of lead optimization and new chemical entity (NCE) discovery. This paper provides a brief perspective on the evolution and use of key drug design technologies, highlighting opportunities and challenges.
Stern, Andrew M.; Schurdak, Mark E.; Bahar, Ivet; Berg, Jeremy M.; Taylor, D. Lansing
Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)–driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point. PMID:26962875
Hendriksen, Hendrikus; Groenink, Lucianne
Psychopharmacology has had some bad publicity lately. Frankly, there have been some major problems along the way in developing new effective drugs for psychiatric disorders. After a prolonged period of high investments but low success rates, big pharmaceutical companies seem to retract their activities in the psychopharmacology field. Yet, the burden of mental disorders is likely to keep on growing in the next decades. In this position paper, we focus on drug development for depression and anxiety disorders, to narrow the scope of the assay. We describe the current situation of the psychopharmacology field, and analyse some of the methods and paradigms that have brought us here, but which should perhaps change to bring us even further. In addition, some of the factors contributing to the current stagnation in psychopharmacology are discussed. Finally, we suggest a number of changes that could lead to a more rational strategy for central nervous system drug development and which may circumvent some of the pitfalls leading to "me too" approaches. Central to the suggested changes, is the notion that mental disorders do not lead to several symptoms, but a network of causally related symptoms convolutes into a mental disorder. We call upon academia to put these changes in the early phases of drug development into effect.
The RAS Drug Discovery group aims to develop assays that will reveal aspects of RAS biology upon which cancer cells depend. Successful assay formats are made available for high-throughput screening programs to yield potentially effective drug compounds.
Marya; Khan, Haroon; Ahmad, Izhar
Malaria remains one of the major public health problems worldwide and is responsible for a large number of morbidity and mortality. Especially, in the third world countries, it is still alarming. The development of drug-resistant to Plasmodium falciparum strains has further degraded the overall situation. However, a limited number of effective drugs available emphasizes how essential it is to establish new anti-malarial compounds. New antimalarial agents with distinctive structures and mechanism of action from the natural origin are thus immediately required to treat sensitive and drug-resistant strains of malaria. over the years, phytopharmaceuticals have provided numerous lead compounds. Similarly, the success rate of botanicals in terms of clinical significance is also very high. Of them, glycosides is one of the most widely distributed and emerging class of plant secondary metabolites. This review provides an outlook to recently isolated glycosides from plants with marked antimalarial effects in an in-vitro and in-vivo protocols and thus ideal candidates for clinical trials to ascertain their clinical utility and or led compounds.
Song, Chenchen; Knöpfel, Thomas
Optogenetics - the use of light and genetics to manipulate and monitor the activities of defined cell populations - has already had a transformative impact on basic neuroscience research. Now, the conceptual and methodological advances associated with optogenetic approaches are providing fresh momentum to neuroscience drug discovery, particularly in areas that are stalled on the concept of 'fixing the brain chemistry'. Optogenetics is beginning to translate and transit into drug discovery in several key domains, including target discovery, high-throughput screening and novel therapeutic approaches to disease states. Here, we discuss the exciting potential of optogenetic technologies to transform neuroscience drug discovery.
Leal, Miguel Costa; Sheridan, Christopher; Osinga, Ronald; Dionísio, Gisela; Rocha, Rui Jorge Miranda; Silva, Bruna; Rosa, Rui; Calado, Ricardo
The chemical diversity associated with marine natural products (MNP) is unanimously acknowledged as the “blue gold” in the urgent quest for new drugs. Consequently, a significant increase in the discovery of MNP published in the literature has been observed in the past decades, particularly from marine invertebrates. However, it remains unclear whether target metabolites originate from the marine invertebrates themselves or from their microbial symbionts. This issue underlines critical challenges associated with the lack of biomass required to supply the early stages of the drug discovery pipeline. The present review discusses potential solutions for such challenges, with particular emphasis on innovative approaches to culture invertebrate holobionts (microorganism-invertebrate assemblages) through in toto aquaculture, together with methods for the discovery and initial production of bioactive compounds from these microbial symbionts. PMID:24983638
Leal, Miguel Costa; Sheridan, Christopher; Osinga, Ronald; Dionísio, Gisela; Rocha, Rui Jorge Miranda; Silva, Bruna; Rosa, Rui; Calado, Ricardo
The chemical diversity associated with marine natural products (MNP) is unanimously acknowledged as the "blue gold" in the urgent quest for new drugs. Consequently, a significant increase in the discovery of MNP published in the literature has been observed in the past decades, particularly from marine invertebrates. However, it remains unclear whether target metabolites originate from the marine invertebrates themselves or from their microbial symbionts. This issue underlines critical challenges associated with the lack of biomass required to supply the early stages of the drug discovery pipeline. The present review discusses potential solutions for such challenges, with particular emphasis on innovative approaches to culture invertebrate holobionts (microorganism-invertebrate assemblages) through in toto aquaculture, together with methods for the discovery and initial production of bioactive compounds from these microbial symbionts.
Chichester, Christine; Digles, Daniela; Siebes, Ronald; Loizou, Antonis; Groth, Paul; Harland, Lee
Modern data-driven drug discovery requires integrated resources to support decision-making and enable new discoveries. The Open PHACTS Discovery Platform (http://dev.openphacts.org) was built to address this requirement by focusing on drug discovery questions that are of high priority to the pharmaceutical industry. Although complex, most of these frequently asked questions (FAQs) revolve around the combination of data concerning compounds, targets, pathways and diseases. Computational drug discovery using workflow tools and the integrated resources of Open PHACTS can deliver answers to most of these questions. Here, we report on a selection of workflows used for solving these use cases and discuss some of the research challenges. The workflows are accessible online from myExperiment (http://www.myexperiment.org) and are available for reuse by the scientific community.
Gawehn, Erik; Hiss, Jan A; Schneider, Gisbert
Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical research by borrowing from the field of "deep learning". Compared with some of the other life sciences, their application in drug discovery is still limited. Here, we provide an overview of this emerging field of molecular informatics, present the basic concepts of prominent deep learning methods and offer motivation to explore these techniques for their usefulness in computer-assisted drug discovery and design. We specifically emphasize deep neural networks, restricted Boltzmann machine networks and convolutional networks.
Slusher, Barbara S.; Conn, P. Jeffrey; Frye, Stephen; Glicksman, Marcie; Arkin, Michelle
The newly formed Academic Drug Discovery Consortium (ADDC) aims to support the growing numbers of university centres engaged in drug discovery that have emerged in response to recent changes in the drug discovery ecosystem. PMID:24172316
A common view within the pharmaceutical industry is that there is a problem with drug discovery and we should do something about it. There is much sympathy for this from academics, regulators and politicians. In this article I propose that lessons learnt from evolution help identify those factors that favour successful drug discovery. This personal view is influenced by a decade spent reviewing drug development programmes submitted for European regulatory approval. During the prolonged gestation of a new medicine few candidate molecules survive. This process of elimination of many variants and the survival of so few has much in common with evolution, an analogy that encourages discussion of the forces that favour, and those that hinder, successful drug discovery. Imagining a world without vaccines, anaesthetics, contraception and anti-infectives reveals how medicines revolutionized humanity. How to manipulate conditions that favour such discoveries is worth consideration. PMID:21395642
A common view within the pharmaceutical industry is that there is a problem with drug discovery and we should do something about it. There is much sympathy for this from academics, regulators and politicians. In this article I propose that lessons learnt from evolution help identify those factors that favour successful drug discovery. This personal view is influenced by a decade spent reviewing drug development programmes submitted for European regulatory approval. During the prolonged gestation of a new medicine few candidate molecules survive. This process of elimination of many variants and the survival of so few has much in common with evolution, an analogy that encourages discussion of the forces that favour, and those that hinder, successful drug discovery. Imagining a world without vaccines, anaesthetics, contraception and anti-infectives reveals how medicines revolutionized humanity. How to manipulate conditions that favour such discoveries is worth consideration. © 2011 The Author. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.
Leelananda, Sumudu P
The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed. PMID:28144341
Leelananda, Sumudu P; Lindert, Steffen
The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein-ligand docking, pharmacophore modeling and QSAR techniques are reviewed.
Zhou, Wei; Wang, Yonghua; Lu, Aiping; Zhang, Ge
Drug discovery is a risky, costly and time-consuming process depending on multidisciplinary methods to create safe and effective medicines. Although considerable progress has been made by high-throughput screening methods in drug design, the cost of developing contemporary approved drugs did not match that in the past decade. The major reason is the late-stage clinical failures in Phases II and III because of the complicated interactions between drug-specific, human body and environmental aspects affecting the safety and efficacy of a drug. There is a growing hope that systems-level consideration may provide a new perspective to overcome such current difficulties of drug discovery and development. The systems pharmacology method emerged as a holistic approach and has attracted more and more attention recently. The applications of systems pharmacology not only provide the pharmacodynamic evaluation and target identification of drug molecules, but also give a systems-level of understanding the interaction mechanism between drugs and complex disease. Therefore, the present review is an attempt to introduce how holistic systems pharmacology that integrated in silico ADME/T (i.e., absorption, distribution, metabolism, excretion and toxicity), target fishing and network pharmacology facilitates the discovery of small molecular drugs at the system level. PMID:26901192
Zhou, Wei; Wang, Yonghua; Lu, Aiping; Zhang, Ge
Drug discovery is a risky, costly and time-consuming process depending on multidisciplinary methods to create safe and effective medicines. Although considerable progress has been made by high-throughput screening methods in drug design, the cost of developing contemporary approved drugs did not match that in the past decade. The major reason is the late-stage clinical failures in Phases II and III because of the complicated interactions between drug-specific, human body and environmental aspects affecting the safety and efficacy of a drug. There is a growing hope that systems-level consideration may provide a new perspective to overcome such current difficulties of drug discovery and development. The systems pharmacology method emerged as a holistic approach and has attracted more and more attention recently. The applications of systems pharmacology not only provide the pharmacodynamic evaluation and target identification of drug molecules, but also give a systems-level of understanding the interaction mechanism between drugs and complex disease. Therefore, the present review is an attempt to introduce how holistic systems pharmacology that integrated in silico ADME/T (i.e., absorption, distribution, metabolism, excretion and toxicity), target fishing and network pharmacology facilitates the discovery of small molecular drugs at the system level.
Moroni, Elisabetta; Paladino, Antonella; Colombo, Giorgio
Proteins are not static objects. To carry out their functions in the cells and participate in biochemical interaction networks, proteins have to explore different conformational substates, which favor the adaptation to different partners and ultimately allow them to respond to changes in the environment. In this paper we discuss the implications of including the atomistic description of protein dynamics and flexibility in the context of drug discovery and design. The underlying idea is that a better understanding of the atomistic details of molecular recognition phenomena and conformational cross-talk between a ligand and a receptor can in fact translate in unexplored opportunities for the discovery of new drug like molecules. We will illustrate and discuss dynamics-based pharmacophores, the discovery of cryptic binding sites, the characterization and exploitation of allosteric regulation mechanisms and the definition of potential protein-protein interaction sites as potential sources of new bases for the rational design of small molecules endowed with specific biological functions. Overall, the inclusion of protein flexibility in the drug discovery process is starting to attract attention not only in the academic but also in the industrial community. This is supported by experimental tests that prove the actual feasibility of considering the explicit dynamics of drug-protein interactions at all relevant levels of resolution and the use of multiple receptor conformations in drug discovery, as affordable complements (if not an alternative) to classical High Throughput Screening (HTS) efforts based on static structures.
Eder, Jörg; Herrling, Paul L
Drugs discovered by the pharmaceutical industry over the past 100 years have dramatically changed the practice of medicine and impacted on many aspects of our culture. For many years, drug discovery was a target- and mechanism-agnostic approach that was based on ethnobotanical knowledge often fueled by serendipity. With the advent of modern molecular biology methods and based on knowledge of the human genome, drug discovery has now largely changed into a hypothesis-driven target-based approach, a development which was paralleled by significant environmental changes in the pharmaceutical industry. Laboratories became increasingly computerized and automated, and geographically dispersed research sites are now more and more clustered into large centers to capture technological and biological synergies. Today, academia, the regulatory agencies, and the pharmaceutical industry all contribute to drug discovery, and, in order to translate the basic science into new medical treatments for unmet medical needs, pharmaceutical companies have to have a critical mass of excellent scientists working in many therapeutic fields, disciplines, and technologies. The imperative for the pharmaceutical industry to discover breakthrough medicines is matched by the increasing numbers of first-in-class drugs approved in recent years and reflects the impact of modern drug discovery approaches, technologies, and genomics.
Haseltine, W A
Genomics, the systematic study of all the genes of an organism, offers a new and much-needed source of systematic productivity for the pharmaceutical industry. The isolation of the majority of human genes in their most useful form is leading to the creation of new drugs based on human proteins, antibodies, peptides, and genes. Human Genome Sciences, Inc, was the first company to use the systematic, genomics approach to discovering drugs, and we have placed 4 of these in clinical trials. Two are described: repifermin (keratinocyte growth factor-2, KGF-2) for wound healing and treatment of mucositis caused by cancer therapy, and B lymphocyte stimulator (BLyS) for stimulation of the immune system. An anti-BLyS antibody drug is in advanced preclinical development for treatment of autoimmune diseases.
Khurdayan, V K; Bozzo, J; Prous, J R
New brief reports this month include: Strategies for Duchenne Muscular Dystrophy: Various approaches are being explored to abate the dystrophic process including cellular therapies (transplanting stem cells or myogenic precursors into muscles), molecular approaches (delivering a functional or correcting the mutant dystrophin gene), such as MyoDys, Biostrophin(R) and antisense technology, and pharmacotherapeutics, which include calcium channel blockers, calpain inhibitors, phosphodiesterase inhibitors and monoclonal antibodies; Immunotherapy for Multiple Myeloma: Increasing numbers of antibodies and immunoconjugates with anticancer drugs are entering clinical development; Acute respiratory distress syndrome is among the most frequent reasons for intensive care. Current medications include antibiotics, diuretics, drugs to counteract low blood pressure caused by shock, anxiolytics and antiinflammatories, while there are eight potential drugs in active development; Pulmonary Hypertension: Drugs intervening at four signaling pathways (endothelin, prostacyclin, nitric oxide and platelet-derived growth factor), which are implicated in pulmonary hypertension, include readily available bosentan, sildenafil citrate and sitaxsentan sodium and investigational aviptadil and TBC-3711, among others.
Morrow, John Kenneth; Tian, Longzhang; Zhang, Shuxing
Despite the dramatic increase of global spending on drug discovery and development, the approval rate for new drugs is declining, due chiefly to toxicity and undesirable side effects. Simultaneously, the growth of available biomedical data in the post-genomic era has provided fresh insight into the nature of redundant and compensatory drug-target pathways. This stagnation in drug approval can be overcome by the novel concept of polypharmacology, which is built on the fundamental concept that drugs modulate multiple targets. Polypharmacology can be studied with molecular networks which integrate multidisciplinary concepts including cheminformatics, bioinformatics, and systems biology. In silico techniques such as structure and ligand-based approaches can be employed to study molecular networks and reduce costs by predicting adverse drug reactions and toxicity in the early stage of drug development. By amalgamating strides in this informatics-driven era, designing polypharmacological drugs with molecular network technology exemplifies the next generation of therapeutics with less off-target properties and toxicity. In this review, we will first describe the challenges in drug discovery, and showcase successes using multi-target drugs toward diseases such as cancer and mood disorders. We will then focus on recent development of in silico polypharmacology predictions. Finally, our technologies in molecular network analysis will be presented. PMID:20932236
Hughes, JP; Rees, S; Kalindjian, SB; Philpott, KL
Developing a new drug from original idea to the launch of a finished product is a complex process which can take 12–15 years and cost in excess of $1 billion. The idea for a target can come from a variety of sources including academic and clinical research and from the commercial sector. It may take many years to build up a body of supporting evidence before selecting a target for a costly drug discovery programme. Once a target has been chosen, the pharmaceutical industry and more recently some academic centres have streamlined a number of early processes to identify molecules which possess suitable characteristics to make acceptable drugs. This review will look at key preclinical stages of the drug discovery process, from initial target identification and validation, through assay development, high throughput screening, hit identification, lead optimization and finally the selection of a candidate molecule for clinical development. PMID:21091654
Hughes, J P; Rees, S; Kalindjian, S B; Philpott, K L
Developing a new drug from original idea to the launch of a finished product is a complex process which can take 12-15 years and cost in excess of $1 billion. The idea for a target can come from a variety of sources including academic and clinical research and from the commercial sector. It may take many years to build up a body of supporting evidence before selecting a target for a costly drug discovery programme. Once a target has been chosen, the pharmaceutical industry and more recently some academic centres have streamlined a number of early processes to identify molecules which possess suitable characteristics to make acceptable drugs. This review will look at key preclinical stages of the drug discovery process, from initial target identification and validation, through assay development, high throughput screening, hit identification, lead optimization and finally the selection of a candidate molecule for clinical development.
Liu, Ruiwu; Li, Xiaocen; Lam, Kit S
Several combinatorial methods have been developed to create focused or diverse chemical libraries with a wide range of linear or macrocyclic chemical molecules: peptides, non-peptide oligomers, peptidomimetics, small-molecules, and natural product-like organic molecules. Each combinatorial approach has its own unique high-throughput screening and encoding strategy. In this article, we provide a brief overview of combinatorial chemistry in drug discovery with emphasis on recently developed new technologies for design, synthesis, screening and decoding of combinatorial library. Examples of successful application of combinatorial chemistry in hit discovery and lead optimization are given. The limitations and strengths of combinatorial chemistry are also briefly discussed. We are now in a better position to truly leverage the power of combinatorial technologies for the discovery and development of next-generation drugs. Copyright © 2017 Elsevier Ltd. All rights reserved.
Khurdayan, V; Cullell-Young, M
New brief reports this month describe five timely topics: IDO inhibitors have demonstrated antitumor properties by increasing immune response to tumors and improving chemotherapy effectiveness. One of the current therapeutic efforts for Alzheimer's disease is directed towards blocking the gamma-secretase activity, thus reducing amyloid-beta production. Patients with premature ovarian failure (POF), at present mainly treated with hormone replacement therapy, are belated for novel treatment options. Selective ERbeta agonists are anticipated to emerge as therapeutics for the treatment of various diseases including inflammatory bowel syndrome, endometriosis, dementia and cognitive disorders. Phospholipase A2 inhibitors specific for enzyme isoforms are actively studied as potential antiallergic/antiasthmatic drugs, antiarthritic agents and therapeutics for atherosclerosis.
Hung, Che-Lun; Chen, Chi-Chun
Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.
Hong, Lin; Sklar, Larry A.
Neurological diseases have placed heavy social and financial burdens on modern society. As the life expectancy of humans is extended, neurological diseases, such as Parkinson’s disease, have become increasingly common among senior populations. Although the enigmas of Parkinson’s diseases await resolution, more vivid pictures on the cause, progression, and control of the illness are emerging after years of research. On the molecular level, GTPases are implicated in the etiology of Parkinson’s disease and are rational pharmaceutical targets for their control. However, targeting individual GTPases, which belong to a superfamily of proteins containing multiple members with a conserved guanine nucleotide binding domain, has proven to be challenging. In contrast, pharmaceutical pursuit of inhibition of kinases, which constitute another superfamily of proteins with more than 500 members, has been fairly successful. We reviewed the breakthroughs in the history of kinase drug discovery to provide guidance for the GTPase field. We summarize recent progress made in the regulation of GTPase activity. We also present an efficient and cost effective approach to drug screening, which uses multiplex flow cytometry and mixture-based positional scanning libraries. These methods allow simultaneous measurements of both the activity and the selectivity of the screened library. Several GTPase activator clusters were identified which showed selectivity against different GTPase subfamilies. While the clusters need to be further deconvoluted to identify individual active compounds, the method described here and the structure information gathered create a foundation for further developments to build upon. PMID:24926233
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Sliwoski, Gregory; Kothiwale, Sandeepkumar; Meiler, Jens
Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature. PMID:24381236
Tonge, Peter J
The development of therapies for the treatment of neurological cancer faces a number of major challenges including the synthesis of small molecule agents that can penetrate the blood-brain barrier (BBB). Given the likelihood that in many cases drug exposure will be lower in the CNS than in systemic circulation, it follows that strategies should be employed that can sustain target engagement at low drug concentration. Time dependent target occupancy is a function of both the drug and target concentration as well as the thermodynamic and kinetic parameters that describe the binding reaction coordinate, and sustained target occupancy can be achieved through structural modifications that increase target (re)binding and/or that decrease the rate of drug dissociation. The discovery and deployment of compounds with optimized kinetic effects requires information on the structure-kinetic relationships that modulate the kinetics of binding, and the molecular factors that control the translation of drug-target kinetics to time-dependent drug activity in the disease state. This Review first introduces the potential benefits of drug-target kinetics, such as the ability to delineate both thermodynamic and kinetic selectivity, and then describes factors, such as target vulnerability, that impact the utility of kinetic selectivity. The Review concludes with a description of a mechanistic PK/PD model that integrates drug-target kinetics into predictions of drug activity.
Morgnanesi, Dante; Heinrichs, Eric J; Mele, Anthony R; Wilkinson, Sean; Zhou, Suzanne; Kulp, John L
Computational chemical biology, applied to research on hepatitis B virus (HBV), has two major branches: bioinformatics (statistical models) and first-principle methods (molecular physics). While bioinformatics focuses on statistical tools and biological databases, molecular physics uses mathematics and chemical theory to study the interactions of biomolecules. Three computational techniques most commonly used in HBV research are homology modeling, molecular docking, and molecular dynamics. Homology modeling is a computational simulation to predict protein structure and has been used to construct conformers of the viral polymerase (reverse transcriptase domain and RNase H domain) and the HBV X protein. Molecular docking is used to predict the most likely orientation of a ligand when it is bound to a protein, as well as determining an energy score of the docked conformation. Molecular dynamics is a simulation that analyzes biomolecule motions and determines conformation and stability patterns. All of these modeling techniques have aided in the understanding of resistance mutations on HBV non-nucleos(t)ide reverse-transcriptase inhibitor binding. Finally, bioinformatics can be used to study the DNA and RNA protein sequences of viruses to both analyze drug resistance and to genotype the viral genomes. Overall, with these techniques, and others, computational chemical biology is becoming more and more necessary in hepatitis B research. This article forms part of a symposium in Antiviral Research on "An unfinished story: from the discovery of the Australia antigen to the development of new curative therapies for hepatitis B."
Dahlin, Jayme L; Inglese, James; Walters, Michael A
The number of academic drug discovery centres has grown considerably in recent years, providing new opportunities to couple the curiosity-driven research culture in academia with rigorous preclinical drug discovery practices used in industry. To fully realize the potential of these opportunities, it is important that academic researchers understand the risks inherent in preclinical drug discovery, and that translational research programmes are effectively organized and supported at an institutional level. In this article, we discuss strategies to mitigate risks in several key aspects of preclinical drug discovery at academic drug discovery centres, including organization, target selection, assay design, medicinal chemistry and preclinical pharmacology.
Hargrave-Thomas, Emily; Yu, Bo; Reynisson, Jóhannes
It was found that the discovery of 5.8% (84/1437) of all drugs on the market involved serendipity. Of these drugs, 31 (2.2%) were discovered following an incident in the laboratory and 53 (3.7%) were discovered in a clinical setting. In addition, 263 (18.3%) of the pharmaceuticals in clinical use today are chemical derivatives of the drugs discovered with the aid of serendipity. Therefore, in total, 24.1% (347/1437) of marketed drugs can be directly traced to serendipitous events confirming the importance of this elusive phenomenon. In the case of anticancer drugs, 35.2% (31/88) can be attributed to a serendipitous event, which is somewhat larger than for all drugs. The therapeutic field that has benefited the most from serendipity are central nervous system active drugs reflecting the difficulty in designing compounds to pass the blood-brain-barrier and the lack of laboratory-based assays for many of the diseases of the mind.
Hargrave-Thomas, Emily; Yu, Bo; Reynisson, Jóhannes
It was found that the discovery of 5.8% (84/1437) of all drugs on the market involved serendipity. Of these drugs, 31 (2.2%) were discovered following an incident in the laboratory and 53 (3.7%) were discovered in a clinical setting. In addition, 263 (18.3%) of the pharmaceuticals in clinical use today are chemical derivatives of the drugs discovered with the aid of serendipity. Therefore, in total, 24.1% (347/1437) of marketed drugs can be directly traced to serendipitous events confirming the importance of this elusive phenomenon. In the case of anticancer drugs, 35.2% (31/88) can be attributed to a serendipitous event, which is somewhat larger than for all drugs. The therapeutic field that has benefited the most from serendipity are central nervous system active drugs reflecting the difficulty in designing compounds to pass the blood-brain-barrier and the lack of laboratory-based assays for many of the diseases of the mind. PMID:22247822
Hao, Haiping; Zheng, Xiao; Wang, Guangji
Natural medicines (NMs) are indispensable sources for the development of modern drugs. However, the targets for most natural compounds are unknown and the current pharmacokinetic evaluation systems developed for target-defined drugs may not be directly applicable to NM-based drug discovery, which is a major hindrance in bringing natural compounds to the clinic. Here, we propose the concept of 'reverse pharmacokinetics' and discuss how a 'reverse pharmacokinetics' perspective could help clarify key questions in modern drug discovery from NMs with validated clinical benefits, thereby strengthening the translational potential. Reverse pharmacokinetics can provide physiologically relevant clues to the target identification and mechanistic study of NMs, which may also innovate drug discovery for complex diseases. We anticipate that an evolving deep understanding of the novel mode of action of natural compounds with a reverse pharmacokinetic insight may improve discovery of both single ingredient and multiple-component modern drugs from NMs.
Galan, M Carmen; Benito-Alifonso, David; Watt, Gregory M
The multitude of roles that carbohydrates and their glyco-conjugates play in biological processes has stimulated great interest in determining the nature of their interactions in both normal and diseased states. Manipulating such interactions will provide leads for drug discovery. Of the major classes of biomolecule, carbohydrates are the most structurally diverse. This hetereogeneity makes isolation of pure samples, and in sufficient amounts, from biological sources extremely difficult. Chemical synthesis offers the advantage of producing pure and structurally defined oligosaccharides for biological investigations. Although the complex nature of carbohydrates means that this is challenging, recent advances in the field have facilitated access to these molecules. The synthesis and isolation of oligosaccharides combined with progress in glycoarray technology have aided the identification of new carbohydrate-binding drug targets. This review aims to provide an overview of the latest advancements in carbohydrate chemistry and the role of these complex molecules in drug discovery, focusing particularly on synthetic methodologies, glycosaminoglycans, glycoprotein synthesis and vaccine development over the last few years.
Chien, Andrew; Foster, Ian; Goddette, Dean
Grid technologies enable flexible coupling and sharing of computers, instruments and storage. Grids can provide technical solutions to the volume of data and computational demands associated with drug discovery by delivering larger computing capability (flexible resource sharing), providing coordinated access to large data resources and enabling novel online exploration (coupling computing, data and instruments online). Here, we illustrate this potential by describing two applications: the use of desktop PC grid technologies for virtual screening, and distributed X-ray structure reconstruction and online visualization.
Gerwick, William H.; Fenner, Amanda M.
The marine environment has been a source of more than 20,000 inspirational natural products discovered over the past 50 years. From these efforts, 9 approved drugs and 12 current clinical trial agents have been discovered, either as natural products or molecules inspired from the natural product structure. To a significant degree, these have come from collections of marine invertebrates largely obtained from shallow water tropical ecosystems. However, there is a growing recognition that marine invertebrates are oftentimes populated with enormous quantities of ‘associated’ or symbiotic microorganisms, and that microorganisms are the true metabolic sources of these most valuable of marine natural products. Also, because of the inherently multidisciplinary nature of this field, a high degree of innovation is characteristic of marine natural product drug discovery efforts. PMID:23274881
Leonti, Marco; Stafford, Gary I; Cero, Maja Dal; Cabras, Stefano; Castellanos, Maria Eugenia; Casu, Laura; Weckerle, Caroline S
Ethnopharmacological investigations of traditional medicines have made significant contributions to plant-derived drugs, as well as the advancement of pharmacology. Drug discovery from medicinal flora is more complex than generally acknowledged because plants are applied for different therapeutic indications within and across cultures. Therefore we propose the concept of "reverse ethnopharmacology" and compare biomedical uses of plant taxa with their ethnomedicinal and popular uses and test the effect of these on the probability of finding biomedical and specifically anticancer drugs. For this analysis we use data on taxonomy and medical indications of plant derived biomedical drugs, clinical trial, and preclinical trial drug candidates published by Zhu et al. (2011) and compare their therapeutic indications with their ethnomedicinal and popular uses as reported in the NAPRALERT(®) database. Specifically, we test for increase or decrease of the probability of finding anticancer drugs based on ethnomedicinal and popular reports with Bayesian logistic regression analyses. Anticancer therapy resulted as the most frequent biomedicinal indication of the therapeutics derived from the 225 drug producing higher plant taxa and showed an association with ethnomedicinal and popular uses in women's medicine, which was also the most important popular use-category. Popular remedies for dysmenorrhoea, and uses as emmenagogues, abortifacients and contraceptives showed a positive effect on the probability of finding anticancer drugs. Another positive effect on the probability of discovering anticancer therapeutics was estimated for popular herbal drugs associated with the therapy of viral and bacterial infections, while the highest effect was found for popular remedies used to treat cancer symptoms. However, this latter effect seems to be influenced by the feedback loop and divulgence of biomedical knowledge on the popular level. We introduce the concept of reverse
Marder, Stephen R.; Roth, Bryan; Sullivan, Patrick F.; Scolnick, Edward M.; Nestler, Eric J.; Geyer, Mark A.; Welnberger, Daniel R.; Karayiorgou, Maria; Guidotti, Alessandro; Gingrich, Jay; Akbarian, Schahram; Buchanan, Robert W.; Lieberman, Jeffrey A.; Conn, P. Jeffrey; Haggarty, Stephen J.; Law, Amanda J.; Campbell, Brian; Krystal, John H.; Moghaddam, Bita; Saw, Akira; Caron, Marc G.; George, Susan R.; Allen, John A.; Solis, Michelle
Sponsored by the New York Academy of Sciences and with support from the National Institute of Mental Health, the Life Technologies Foundation, and the Josiah Macy Jr. Foundation, “Advancing Drug Discovery for Schizophrenia” was held March 9–11 at the New York Academy of Sciences in New York City. The meeting, comprising individual talks and panel discussions, highlighted basic, clinical, and translational research approaches, all of which contribute to the overarching goal of enhancing the pharmaceutical armamentarium for treating schizophrenia. This report surveys work by the vanguard of schizophrenia research in such topics as genetic and epigenetic approaches; small molecule therapeutics; and the relationships between target genes, neuronal function, and symptoms of schizophrenia. PMID:22032400
Toxicogenomics, drug discovery, and pathologist.
The field of toxicogenomics, which currently focuses on the application of large-scale differential gene expression (DGE) data to toxicology, is starting to influence drug discovery and development in the pharmaceutical indu...
Toxicogenomics, drug discovery, and pathologist.
The field of toxicogenomics, which currently focuses on the application of large-scale differential gene expression (DGE) data to toxicology, is starting to influence drug discovery and development in the pharmaceutical indu...
Lo Cicero, Alessandra; Nissan, Xavier
Progeria, or Hutchinson-Gilford progeria syndrome (HGPS), is a rare, fatal genetic disease characterized by an appearance of accelerated aging in children. This syndrome is typically caused by mutations in codon 608 (p.G608G) of the LMNA, leading to the production of a mutated form of lamin A precursor called progerin. In HGPS, progerin accumulates in cells causing progressive molecular defects, including nuclear shape abnormalities, chromatin disorganization, damage to DNA and delays in cell proliferation. Here we report how, over the past five years, pluripotent stem cells have provided new insights into the study of HGPS and opened new original therapeutic perspectives to treat the disease.
The global pharmaceutical industry is described as facing an 'innovation crisis' following the 'go-go-pharma' era; in other words, the problem is one of 'more money and fewer products'. Nevertheless, patients worldwide are awaiting innovative drugs. Therefore, the pharmaceutical industry has a duty to discover and develop novel drugs and medical technologies. Through universal coverage and reform of the patent system, the Japanese pharmaceutical industry has expanded greatly in line with the Japanese economy. However, in terms of scale and R&D investment, the Japanese pharmaceutical firms have lagged behind the foreign multinationals, which have undergone successive mergers and acquisitions. Meanwhile, it is true that several Japanese firms are playing an active role in overseas markets with their own blockbusters. This paper analyses and gives an overview of new trends in Japan's pharmaceutical industry within the global context.
The popularization of genomic high-throughput technologies is causing a revolution in biomedical research and, particularly, is transforming the field of drug discovery. Systems biology offers a framework to understand the extensive human genetic heterogeneity revealed by genomic sequencing in the context of the network of functional, regulatory and physical protein-drug interactions. Thus, approaches to find biomarkers and therapeutic targets will have to take into account the complex system nature of the relationships of the proteins with the disease. Pharmaceutical companies will have to reorient their drug discovery strategies considering the human genetic heterogeneity. Consequently, modeling and computational data analysis will have an increasingly important role in drug discovery.
Frearson, Julie; Wyatt, Paul
As the pharmaceutical industry continues to re-strategise and focus on low-risk, relatively short term gains for the sake of survival, we need to re-invigorate the early stages of drug discovery and rebalance efforts towards novel modes of action therapeutics and neglected genetic and tropical diseases. Academic drug discovery is one model which offers the promise of new approaches and an alternative organisational culture for drug discovery as it attempts to apply academic innovation and thought processes to the challenge of discovering drugs to address real unmet need. PMID:20922062
Learning from the failures of drug discovery in B-cell non-Hodgkin lymphomas and perspectives for the future: chronic lymphocytic leukemia and diffuse large B-cell lymphoma as two ends of a spectrum in drug development.
Kubuschok, Boris; Trepel, Martin
Despite substantial recent advances, there is still an unmet need for better therapies in B-cell non Hodgkin lymphomas (B-NHL), especially in relapsed or refractory disease. Many novel targeted drugs have been developed based on a better molecular understanding of B-NHL. Areas covered: This article focuses on chronic lymphocytic leukemia (CLL) as a representative for indolent lymphomas and paradigmatic for the tremendous progress in treating B-NHL on the one hand and diffuse large B-cell lymphoma (DLBCL) as a representative for aggressive lymphomas and paradigmatic for many unsolved problems in lymphoma treatment or the other hand. We highlight salient points in current therapies targeting genetic, epigenetic, immunological and microenvironmental alterations. Possible reasons for drug failure in clinical trials like tumor heterogeneity, clonal evolution and drug resistance mechanisms are discussed. Based thereon, some perspectives for further drug discovery are given. Expert opinion: In view of the pathogenetic complexity of lymphomas, therapies targeting exclusively a single alteration may fail because resistance mechanisms are present either initially or evolve during treatment. Therefore, future therapies in B-NHL may have to target the greatest possible number of genetic, immunological or epigenetic alterations still allowing tolerability and to monitor these alterations during therapy.
results provide us with a great perspective for designing novel GCS inhibitors. GCS is considered to be a critical enzyme implicated in cancer drug... Cytochrome P450 Inhibitors- A Study of Their Potency and Selectivity”, J. Sridhar, J. Liu, C.L.K. Stevens, and M. Foroozesh, Society of Toxicology...AD_________________ Award Number: W81XWH-11-1-0105 TITLE: A Drug Discovery Partnership for Personalized Breast Cancer Therapy
Shibayama, Sotaro; Tanikawa, Kunihiro; Fujimoto, Ryuhei; Kimura, Hiromichi
The pharmaceutical industry has experienced intermittent waves of mergers and acquisitions (M&As) since the 1980s and recently appeared to be in yet another wave. Previous studies indicated rather negative impacts of consolidation on research and development, suggesting that they do not necessarily lead to long-term reinforcement of research capabilities, although they may enrich the drug pipeline in the short term. However, recent studies have implied a positive side in terms of knowledge-base transfer. Further micro-organizational studies suggested that scientists learned new knowledge and approaches from partner scientists and improved their performance and innovation. These findings imply that measures for the scientist-level integration after M&As would reinforce fundamental research capabilities in the long term.
Zheng, Heping; Hou, Jing; Zimmerman, Matthew D; Wlodawer, Alexander; Minor, Wladek
Introduction X-ray crystallography plays an important role in structure-based drug design (SBDD), and accurate analysis of crystal structures of target macromolecules and macromolecule–ligand complexes is critical at all stages. However, whereas there has been significant progress in improving methods of structural biology, particularly in X-ray crystallography, corresponding progress in the development of computational methods (such as in silico high-throughput screening) is still on the horizon. Crystal structures can be overinterpreted and thus bias hypotheses and follow-up experiments. As in any experimental science, the models of macromolecular structures derived from X-ray diffraction data have their limitations, which need to be critically evaluated and well understood for structure-based drug discovery. Areas covered This review describes how the validity, accuracy and precision of a protein or nucleic acid structure determined by X-ray crystallography can be evaluated from three different perspectives: i) the nature of the diffraction experiment; ii) the interpretation of an electron density map; and iii) the interpretation of the structural model in terms of function and mechanism. The strategies to optimally exploit a macromolecular structure are also discussed in the context of ‘Big Data’ analysis, biochemical experimental design and structure-based drug discovery. Expert opinion Although X-ray crystallography is one of the most detailed ‘microscopes’ available today for examining macromolecular structures, the authors would like to re-emphasize that such structures are only simplified models of the target macromolecules. The authors also wish to reinforce the idea that a structure should not be thought of as a set of precise coordinates but rather as a framework for generating hypotheses to be explored. Numerous biochemical and biophysical experiments, including new diffraction experiments, can and should be performed to verify or falsify
Frearson, Julie A; Wyatt, Paul G; Gilbert, Ian H; Fairlamb, Alan H
Drug discovery is a high-risk, expensive and lengthy process taking at least 12 years and costing upwards of US$500 million per drug to reach the clinic. For neglected diseases, the drug discovery process is driven by medical need and guided by pre-defined target product profiles. Assessment and prioritisation of the most promising targets for entry into screening programmes is crucial for maximising the chances of success. Here, we describe criteria used in our drug discovery unit for target assessment and introduce the 'traffic-light' system as a prioritisation and management tool. We hope this brief review will stimulate basic scientists to acquire additional information necessary for drug discovery.
Erakovic Haber, Vesna; Spaventi, Radan
Drug discovery and development process is nowadays conducted in relatively standardised sequence of phases, starting with Discovery and being followed by Preclinical, Clinical and Non-Clinical Development. Discovery phase is divided in Hit Finding, Lead generation, Lead Optimisation and Candidate Identification Phase. Main drivers of the whole process are regulatory requirements and the aim to eliminate the unnecessary spending by early elimination of unlikely drug candidates. Marine products, once purified, isolated and produced in required quantities, follow the same route as any other synthetic drug.
Williams, Antony J; Harland, Lee; Groth, Paul; Pettifer, Stephen; Chichester, Christine; Willighagen, Egon L; Evelo, Chris T; Blomberg, Niklas; Ecker, Gerhard; Goble, Carole; Mons, Barend
Open PHACTS is a public-private partnership between academia, publishers, small and medium sized enterprises and pharmaceutical companies. The goal of the project is to deliver and sustain an 'open pharmacological space' using and enhancing state-of-the-art semantic web standards and technologies. It is focused on practical and robust applications to solve specific questions in drug discovery research. OPS is intended to facilitate improvements in drug discovery in academia and industry and to support open innovation and in-house non-public drug discovery research. This paper lays out the challenges and how the Open PHACTS project is hoping to address these challenges technically and socially.
Rosen, Jon; Marschke, Keith; Rungta, Deepa
Nuclear receptors (NRs) are a superfamily of ligand-dependent transcription factors that control diverse aspects of growth, development and homeostasis, making them exciting and important targets for drug discovery. In this review, some of the recent advances in our understanding of NRs, and their application to the discovery of new ligands, will be discussed.
Mitra, Partha P
Despite unquestionable success of the combination drug therapy, tuberculosis (TB) very recently has drawn major attention because of the global upsurge of MDR-TB, XDR -TB and HIV-TB co-infection cases. In the last four decades, only one compound is added to the treatment regimen leaving ample opportunities to find out a new generation of TB drugs. The modern concept of drug discovery utilizes the integrated knowledge of genomics, proteomics, molecular biology and systems biology to identify more specific targets. The purpose of this review is to revisit the field of tuberculosis drug discovery based on those new concepts to identify novel targets.
The Society for Medicines Research (SMR) held a one-day meeting on case histories in drug discovery on December 4, 2003, at the National Heart and Lung Institute in London. These meetings have been organized by the SMR biannually for many years, and this latest meeting proved extremely popular, attracting a capacity audience of more than 130 registrants. The purpose of these meetings is educational; they allow those interested in drug discovery to hear key learnings from recent successful drug discovery programs. There was no overall linking theme between the talks, other than each success story has led to the introduction of a new and improved product of therapeutic use. The drug discovery stories covered in the meeting were extremely varied and, put together, they emphasized that each successful story is unique and special. This meeting is also special for the SMR because it presents the "SMR Award for Drug Discovery" in recognition of outstanding achievement and contribution in the area. It should be remembered that drug discovery is an extremely risky business and an extremely costly and complicated process in which the success rate is, at best, low.
Chen, Haijun; Wu, Jianlei; Gao, Yu; Chen, Haiying; Zhou, Jia
As commented by the Nobelist James Black that "The most fruitful basis of the discovery of a new drug is to start with an old drug", drug repurposing represents an attractive drug discovery strategy. Despite the success of several repurposed drugs on the market, the ultimate therapeutic potential of a large number of non-cancer drugs is hindered during their repositioning due to various issues including the limited efficacy and intellectual property. With the increasing knowledge about the pharmacological properties and newly identified targets, the scaffolds of the old drugs emerge as a great treasure-trove towards new cancer drug discovery. In this review, we summarize the recent advances in the development of novel small molecules for cancer therapy by scaffold repurposing with highlighted examples. The relevant strategies, advantages, challenges and future research directions associated with this approach are also discussed.
Gilardoni, Francois; Arvanites, Anthony C
This editorial looks at how a fully integrated structure that performs all aspects in the drug discovery process, under one company, is slowly disappearing. The steps in the drug discovery paradigm have been slowly increasing toward virtuality or outsourcing at various phases of product development in a company's candidate pipeline. Each step in the process, such as target identification and validation and medicinal chemistry, can be managed by scientific teams within a 'virtual' company. Pharmaceutical companies to biotechnology start-ups have been quick in adopting this new research and development business strategy in order to gain flexibility, access the best technologies and technical expertise, and decrease product developmental costs. In today's financial climate, the term virtual drug discovery has an organizational meaning. It represents the next evolutionary step in outsourcing drug development.
Pandey, Saurabh; Pandey, Preeti; Tiwari, Gaurav; Tiwari, Ruchi
Recent years have witnessed the introduction of several high-quality review articles into the literature covering various scientific and technical aspects of bioanalysis. Now it is widely accepted that bioanalysis is an integral part of the pharmacokinetic/pharmacodynamic characterization of a novel chemical entity from the time of its discovery and during various stages of drug development, leading to its market authorization. In this compilation, the important bioanalytical parameters and its application to drug discovery and development approaches are discussed, which will help in the development of safe and more efficacious drugs with reduced development time and cost. It is intended to give some general thoughts in this area which will form basis of a general framework as to how one would approach bioanalysis from inception (i.e., discovery of a lead molecule) and progressing through various stages of drug development. PMID:23781412
In recent years, there has been unprecedented growth in compound activity data in the public domain. These compound data provide an indispensable resource for drug discovery in academic environments as well as in the pharmaceutical industry. To handle large volumes of heterogeneous and complex compound data and extract discovery-relevant knowledge from these data, advanced computational mining approaches are required. Herein, major public compound data repositories are introduced, data confidence criteria reviewed, and selected data mining approaches discussed.
Calderone, Richard; Sun, Nuo; Gay-Andrieu, Francoise; Groutas, William; Weerawarna, Pathum; Prasad, Sridhar; Alex, Deepu; Li, Dongmei
New data suggest that the global incidence of several types of fungal diseases have traditionally been under-documented. Of these, mortality caused by invasive fungal infections remains disturbingly high, equal to or exceeding deaths caused by drug-resistant tuberculosis and malaria. It is clear that basic research on new antifungal drugs, vaccines and diagnostic tools is needed. In this review, we focus upon antifungal drug discovery including in vitro assays, compound libraries and approaches to target identification. Genome mining has made it possible to identify fungal-specific targets; however, new compounds to these targets are apparently not in the antimicrobial pipeline. We suggest that ‘repurposing’ compounds (off patent) might be a more immediate starting point. Furthermore, we examine the dogma on antifungal discovery and suggest that a major thrust in technologies such as structural biology, homology modeling and virtual imaging is needed to drive discovery. PMID:25046525
Goodwin, R J A; Bunch, J; McGinnity, D F
Over the last decade mass spectrometry imaging (MSI) has been integrated in to many areas of drug discovery and development. It can have significant impact in oncology drug discovery as it allows efficacy and safety of compounds to be assessed against the backdrop of the complex tumour microenvironment. We will discuss the roles of MSI in investigating compound and metabolite biodistribution and defining pharmacokinetic -pharmacodynamic relationships, analysis that is applicable to all drug discovery projects. We will then look more specifically at how MSI can be used to understand tumour metabolism and other applications specific to oncology research. This will all be described alongside the challenges of applying MSI to industry research with increased use of metrology for MSI. © 2017 Elsevier Inc. All rights reserved.
Svennebring, Andreas M; Wikberg, Jarl Es
Three dedicated approaches to the calculation of the risk-adjusted net present value (rNPV) in drug discovery projects under different assumptions are suggested. The probability of finding a candidate drug suitable for clinical development and the time to the initiation of the clinical development is assumed to be flexible in contrast to the previously used models. The rNPV of the post-discovery cash flows is calculated as the probability weighted average of the rNPV at each potential time of initiation of clinical development. Practical considerations how to set probability rates, in particular during the initiation and termination of a project is discussed.
Bates, Susan E; Amiri-Kordestani, Laleh; Giaccone, Giuseppe
A British humorist said, "There is much to be said for failure. It is much more interesting than success." This CCR Focus section is aimed at identifying lessons to be learned from difficulties encountered in recent years during development of anticancer agents. Clearly, we have not found a silver bullet tyrosine kinase inhibitor against solid tumors comparable with imatinib in chronic myelogenous leukemia. Although vemurafenib for B-Raf-mutated melanoma and crizotinib for non-small cell lung cancers with echinoderm microtubule-associated protein-like 4 (EML4)-anaplastic lymphoma kinase (ALK) rearrangements were developed rapidly and offer hope for individualized targeted therapies, the development of agents targeting a number of other pathways has been slower and less successful. These agents include drugs for blocking the insulin-like growth factor I/insulin receptor pathways, mitotic kinase inhibitors, and Hsp90 antagonists. Several potentially useful, if not groundbreaking, agents have had setbacks in clinical development, including trastuzumab emtansine, gemtuzumab ozogamicin, and satraplatin. From experience, we have learned the following: (i) not every altered protein or pathway is a valid anticancer target; (ii) drugs must effectively engage the target; (iii) the biology of the systems we use must be very well understood; and (iv) clinical trials must be designed to assess whether the drug reached and impaired the target. It is also important that we improve the drug development enterprise to enhance enrollment, streamline clinical trials, reduce financial risk, and encourage the development of agents for niche indications. Such enormous challenges are offset by potentially tremendous gains in our understanding and treatment of cancer.
Eng-Chong, Tan; Yean-Kee, Lee; Chin-Fei, Chee; Choon-Han, Heh; Sher-Ming, Wong; Li-Ping, Christina Thio; Gen-Teck, Foo; Khalid, Norzulaani; Abd Rahman, Noorsaadah; Karsani, Saiful Anuar; Othman, Shatrah; Othman, Rozana; Yusof, Rohana
Boesenbergia rotunda is a herb from the Boesenbergia genera under the Zingiberaceae family. B. rotunda is widely found in Asian countries where it is commonly used as a food ingredient and in ethnomedicinal preparations. The popularity of its ethnomedicinal usage has drawn the attention of scientists worldwide to further investigate its medicinal properties. Advancement in drug design and discovery research has led to the development of synthetic drugs from B. rotunda metabolites via bioinformatics and medicinal chemistry studies. Furthermore, with the advent of genomics, transcriptomics, proteomics, and metabolomics, new insights on the biosynthetic pathways of B. rotunda metabolites can be elucidated, enabling researchers to predict the potential bioactive compounds responsible for the medicinal properties of the plant. The vast biological activities exhibited by the compounds obtained from B. rotunda warrant further investigation through studies such as drug discovery, polypharmacology, and drug delivery using nanotechnology. PMID:23243448
Eng-Chong, Tan; Yean-Kee, Lee; Chin-Fei, Chee; Choon-Han, Heh; Sher-Ming, Wong; Li-Ping, Christina Thio; Gen-Teck, Foo; Khalid, Norzulaani; Abd Rahman, Noorsaadah; Karsani, Saiful Anuar; Othman, Shatrah; Othman, Rozana; Yusof, Rohana
Boesenbergia rotunda is a herb from the Boesenbergia genera under the Zingiberaceae family. B. rotunda is widely found in Asian countries where it is commonly used as a food ingredient and in ethnomedicinal preparations. The popularity of its ethnomedicinal usage has drawn the attention of scientists worldwide to further investigate its medicinal properties. Advancement in drug design and discovery research has led to the development of synthetic drugs from B. rotunda metabolites via bioinformatics and medicinal chemistry studies. Furthermore, with the advent of genomics, transcriptomics, proteomics, and metabolomics, new insights on the biosynthetic pathways of B. rotunda metabolites can be elucidated, enabling researchers to predict the potential bioactive compounds responsible for the medicinal properties of the plant. The vast biological activities exhibited by the compounds obtained from B. rotunda warrant further investigation through studies such as drug discovery, polypharmacology, and drug delivery using nanotechnology.
In principal, drug discovery approaches can be grouped into target- and function-based, with the respective aims of developing either a target-selective drug or a drug that produces a specific biological effect irrespective of its mode of action. Most analyses of drug discovery approaches focus on productivity, whereas the strategic implications of the choice of drug discovery approach on market position and ability to maintain market exclusivity are rarely considered. However, a comparison of approaches from the perspective of market position indicates that the functional approach is superior for the development of novel, innovative treatments.
Brötz-Oesterhelt, Heike; Sass, Peter
During the last decade the field of antibacterial drug discovery has changed in many aspects including bacterial organisms of primary interest, discovery strategies applied and pharmaceutical companies involved. Target-based high-throughput screening had been disappointingly unsuccessful for antibiotic research. Understanding of this lack of success has increased substantially and the lessons learned refer to characteristics of targets, screening libraries and screening strategies. The 'genomics' approach was replaced by a diverse array of discovery strategies, for example, searching for new natural product leads among previously abandoned compounds or new microbial sources, screening for synthetic inhibitors by targeted approaches including structure-based design and analyses of focused libraries and designing resistance-breaking properties into antibiotics of established classes. Furthermore, alternative treatment options are being pursued including anti-virulence strategies and immunotherapeutic approaches. This article summarizes the lessons learned from the genomics era and describes discovery strategies resulting from that knowledge.
The increased use of drugs (and the concurrent increased risks of drug-induced illness) require definition of relevant research areas and strategy. For established marketed drugs, research needs depend on the magnitudes of risk of an illness from a drug and the base-line risk. With the drug risk high and the base-line risk low, the problem surfaces in premarketing studies or through the epidemic that develops after marketing. If the drug adds slightly to a high base-line risk, the effect is undetectable. When both risks are low, adverse effects can be discovered by chance, but systematic case-referent studies can speed discovery. If both risks are high, clinical trials and nonexperimental studies may be used. With both risks intermediate, systematic evaluations, especially case-referent studies are needed. Newly marketed drugs should be routinely evaluated through compulsory registration and follow-up study of the earliest users.
Liu, Fa; Mayer, John P
The discovery of novel therapeutics to combat human disease has traditionally been among the most important goals of research chemists. After a century of innovation, state-of-the-art chemical protein synthesis is now capable of efficiently assembling proteins of up to several hundred residues in length from individual amino acids. By virtue of its unique ability to incorporate non-native structural elements, chemical protein synthesis has been seminal in the recent development of several novel drug discovery technologies. In this chapter, we review the key advances in peptide and protein chemistry which have enabled our current synthetic capabilities. We also discuss the synthesis of D-proteins and their applications in mirror image phage-display and racemic protein crystallography, the synthesis of enzymes for structure-based drug discovery, and the direct synthesis of homogenous protein pharmaceuticals.
Kerns, Edward H; Di, Li; Carter, Guy T
The solubility of a compound depends on its structure and solution conditions. Structure determines the lipophilicity, hydrogen bonding, molecular volume, crystal energy and ionizability, which determine solubility. Solution conditions are affected by pH, co-solvents, additives, ionic strength, time and temperature. Many drug discovery experiments are conducted under "kinetic" solubility conditions. In drug discovery, solubility has a major impact on bioassays, formulation for in vivo dosing, and intestinal absorption. A good goal for the solubility of drug discovery compounds is >60 ug/mL. Equilibrium solubility assays can be conducted in moderate throughput, by incubating excess solid with buffer and agitating for several days, prior to filtration and HPLC quantitation. Kinetic solubility assays are performed in high throughput with shorter incubation times and high throughput analyses using plate readers. The most frequently used of these are the nephelometric assay and direct UV assay, which begin by adding a small volume of DMSO stock solution of each test compound to buffer. In nephelometry, this solution is serially diluted across a microtitre plate and undissolved particles are detected via light scattering. In direct UV, undissolved particles are separated by filtration, after which the dissolved material is quantitated using UV absorption. Equilibrium solubility is useful for preformulation. Kinetic solubility is useful for rapid compound assessment, guiding optimization via structure modification, and diagnosing bioassays. It is often useful to customize solubility experiments using conditions that answer specific research questions of drug discovery teams, such as compound selection and vehicle development for pharmacology and PK studies.
Ekins, Sean; Mietchen, Daniel; Coffee, Megan; Stratton, Thomas P; Freundlich, Joel S; Freitas-Junior, Lucio; Muratov, Eugene; Siqueira-Neto, Jair; Williams, Antony J; Andrade, Carolina
The Zika virus (ZIKV) outbreak in the Americas has caused global concern that we may be on the brink of a healthcare crisis. The lack of research on ZIKV in the over 60 years that we have known about it has left us with little in the way of starting points for drug discovery. Our response can build on previous efforts with virus outbreaks and lean heavily on work done on other flaviviruses such as dengue virus. We provide some suggestions of what might be possible and propose an open drug discovery effort that mobilizes global science efforts and provides leadership, which thus far has been lacking. We also provide a listing of potential resources and molecules that could be prioritized for testing as in vitro assays for ZIKV are developed. We propose also that in order to incentivize drug discovery, a neglected disease priority review voucher should be available to those who successfully develop an FDA approved treatment. Learning from the response to the ZIKV, the approaches to drug discovery used and the success and failures will be critical for future infectious disease outbreaks. PMID:27134728
Lesterhuis, W Joost; Bosco, Anthony; Lake, Richard A
The pathobiology-based approach to research and development has been the dominant paradigm for successful drug discovery over the last decades. We propose that the molecular and cellular events that govern a resolving, rather than an evolving, disease may reveal new druggable pathways.
Lowe, Derek B.
The generation of chemical libraries for screening is a key part of the drug discovery process. Now, two studies describe attempts to combine features of natural product biosynthesis into the creation of libraries with the aim of mimicking nature's success at the production of bioactive molecules.
Ross, Brian; Tran, Thao; Bhattacharya, Pratip; Watterson, D Martin; Sailasuta, Napapon
We describe the details of the magnetic resonance spectroscopy and chemical shift imaging techniques for the human brain which have been developed over the last two decades. With these non-invasive tools, it is now readily possible to repeatedly assay up to 20 common brain metabolites. From the perspective of drug discovery, each of these metabolites could fulfill a number of useful functions: disease biomarker, surrogate marker of drug delivery, surrogate marker of drug efficacy and so on. To facilitate the possible utility of clinical magnetic resonance spectroscopy in future drug discovery, the major portion of the review is devoted to a detailed description of the well-validated neurochemical profiles of many common human brain disorders, for which MRS data now exists. Beyond proton, MRS, the commonest tool provided by the manufacturers of clinical MRI equipment, lays the world of heteronuclear NMR more familiar to chemists. Here too, with relatively little effort it has been possible to define neurochemical profiles of human brain disorders using (13)C MRS in particular. The future for drug discovery scientists is discussed. Finally, recognizing that a known feature of MR is the lack of sensitivity, we describe new efforts to harness hyperpolarization, with its 50,000 signal amplification, to conventional MRS.
Carrara, Letizia; Lavezzi, Silvia Maria; Borella, Elisa; De Nicolao, Giuseppe; Magni, Paolo; Poggesi, Italo
Pharmacometric models represent the most comprehensive approaches for extracting, summarizing and integrating information obtained in the often sparse, limited, and less-than-optimally designed experiments performed in the early phases of oncology drug discovery. Whilst empirical methodologies may be enough for screening and ranking candidate drugs, modeling approaches are needed for optimizing and making economically viable the learn-confirm cycles within an oncology research program and anticipating the dose regimens to be investigated in the subsequent clinical development. Areas covered: Papers appearing in the literature of approximately the last decade reporting modeling approaches applicable to anticancer drug discovery have been listed and commented. Papers were selected based on the interest in the proposed methodology or in its application. Expert opinion: The number of modeling approaches used in the discovery of anticancer drugs is consistently increasing and new models are developed based on the current directions of research of new candidate drugs. These approaches have contributed to a better understanding of new oncological targets and have allowed for the exploitation of the relatively sparse information generated by preclinical experiments. In addition, they are used in translational approaches for guiding and supporting the choice of dosing regimens in early clinical development.
Kolb, V M
Selected works are discussed which clearly demonstrate that mimicking various aspects of the process by which natural products evolved is becoming a powerful tool in contemporary drug discovery. Natural products are an established and rich source of drugs. The term "natural product" is often used synonymously with "secondary metabolite." Knowledge of genetics and molecular evolution helps us understand how biosynthesis of many classes of secondary metabolites evolved. One proposed hypothesis is termed "inventive evolution." It invokes duplication of genes, and mutation of the gene copies, among other genetic events. The modified duplicate genes, per se or in conjunction with other genetic events, may give rise to new enzymes, which, in turn, may generate new products, some of which may be selected for. Steps of the inventive evolution can be mimicked in several ways for purpose of drug discovery. For example, libraries of chemical compounds of any imaginable structure may be produced by combinatorial synthesis. Out of these libraries new active compounds can be selected. In another example, genetic system can be manipulated to produce modified natural products ("unnatural natural products"), from which new drugs can be selected. In some instances, similar natural products turn up in species that are not direct descendants of each other. This is presumably due to a horizontal gene transfer. The mechanism of this inter-species gene transfer can be mimicked in therapeutic gene delivery. Mimicking specifics or principles of chemical evolution including experimental and test-tube evolution also provides leads for new drug discovery.
There is currently a crisis in drug discovery for neuropsychiatric disorders, with a profound, yet unexpected drought in new drug development across the spectrum. In this commentary, the sources of this dilemma and potential avenues to redress the issue are explored. These include a critical review of diagnostic issues and of selection of participants for clinical trials, and the mechanisms for identifying new drugs and new drug targets. Historically, the vast majority of agents have been discovered serendipitously or have been modifications of existing agents. Serendipitous discoveries, based on astute clinical observation or data mining, remain a valid option, as is illustrated by the suggestion in the paper by Wahlqvist and colleagues that treatment with sulfonylurea and metformin reduces the risk of affective disorder. However, the identification of agents targeting disorder-related biomarkers is currently proving particularly fruitful. There is considerable hope for genetics as a purist, pathophysiologically valid pathway to drug discovery; however, it is unclear whether the science is ready to meet this promise. Fruitful paradigms will require a break from the orthodoxy, and creativity and risk may well be the fingerprints of success.See related article http://www.biomedcentral.com/1741-7015/10/150.
There is currently a crisis in drug discovery for neuropsychiatric disorders, with a profound, yet unexpected drought in new drug development across the spectrum. In this commentary, the sources of this dilemma and potential avenues to redress the issue are explored. These include a critical review of diagnostic issues and of selection of participants for clinical trials, and the mechanisms for identifying new drugs and new drug targets. Historically, the vast majority of agents have been discovered serendipitously or have been modifications of existing agents. Serendipitous discoveries, based on astute clinical observation or data mining, remain a valid option, as is illustrated by the suggestion in the paper by Wahlqvist and colleagues that treatment with sulfonylurea and metformin reduces the risk of affective disorder. However, the identification of agents targeting disorder-related biomarkers is currently proving particularly fruitful. There is considerable hope for genetics as a purist, pathophysiologically valid pathway to drug discovery; however, it is unclear whether the science is ready to meet this promise. Fruitful paradigms will require a break from the orthodoxy, and creativity and risk may well be the fingerprints of success. See related article http://www.biomedcentral.com/1741-7015/10/150 PMID:23194414
Shah, Salim; Federoff, Howard J
Many parties contribute to discovery of new drugs - academic researchers, industry scientists, government agencies, and disease foundation helping to corral the resources necessary to sustain research efforts - but it has never been more apparent until now that these parties must work together to accomplish the shared goal of improving health. At a recent conference at the Georgetown University Medical Center, a group of prominent scientists from the academic, industry, government and disease advocacy communities came together to discuss new paths forward for stronger inter-institutional collaboration to establish a framework for translating new discoveries into drugs, improving proof of concept (PoC) studies, and reducing attrition at the clinical stage of drug development.
Sacan, Ahmet; Ekins, Sean; Kortagere, Sandhya
Drug discovery in the late twentieth and early twenty-first century has witnessed a myriad of changes that were adopted to predict whether a compound is likely to be successful, or conversely enable identification of molecules with liabilities as early as possible. These changes include integration of in silico strategies for lead design and optimization that perform complementary roles to that of the traditional in vitro and in vivo approaches. The in silico models are facilitated by the availability of large datasets associated with high-throughput screening, bioinformatics algorithms to mine and annotate the data from a target perspective, and chemoinformatics methods to integrate chemistry methods into lead design process. This chapter highlights the applications of some of these methods and their limitations. We hope this serves as an introduction to in silico drug discovery.
Edwards, Bruce S; Sklar, Larry A
Modern flow cytometers can make optical measurements of 10 or more parameters per cell at tens of thousands of cells per second and more than five orders of magnitude dynamic range. Although flow cytometry is used in most drug discovery stages, "sip-and-spit" sampling technology has restricted it to low-sample-throughput applications. The advent of HyperCyt sampling technology has recently made possible primary screening applications in which tens of thousands of compounds are analyzed per day. Target-multiplexing methodologies in combination with extended multiparameter analyses enable profiling of lead candidates early in the discovery process, when the greatest numbers of candidates are available for evaluation. The ability to sample small volumes with negligible waste reduces reagent costs, compound usage, and consumption of cells. Improved compound library formatting strategies can further extend primary screening opportunities when samples are scarce. Dozens of targets have been screened in 384- and 1536-well assay formats, predominantly in academic screening lab settings. In concert with commercial platform evolution and trending drug discovery strategies, HyperCyt-based systems are now finding their way into mainstream screening labs. Recent advances in flow-based imaging, mass spectrometry, and parallel sample processing promise dramatically expanded single-cell profiling capabilities to bolster systems-level approaches to drug discovery. © 2015 Society for Laboratory Automation and Screening.
Edwards, Bruce S.; Sklar, Larry A.
Summary Modern flow cytometers can make optical measurements of 10 or more parameters per cell at tens-of-thousands of cells per second and over five orders of magnitude dynamic range. Although flow cytometry is used in most drug discovery stages, “sip-and-spit” sampling technology has restricted it to low sample throughput applications. The advent of HyperCyt sampling technology has recently made possible primary screening applications in which tens-of-thousands of compounds are analyzed per day. Target-multiplexing methodologies in combination with extended multi-parameter analyses enable profiling of lead candidates early in the discovery process, when the greatest numbers of candidates are available for evaluation. The ability to sample small volumes with negligible waste reduces reagent costs, compound usage and consumption of cells. Improved compound library formatting strategies can further extend primary screening opportunities when samples are scarce. Dozens of targets have been screened in 384- and 1536-well assay formats, predominantly in academic screening lab settings. In concert with commercial platform evolution and trending drug discovery strategies, HyperCyt-based systems are now finding their way into mainstream screening labs. Recent advances in flow-based imaging, mass spectrometry and parallel sample processing promise dramatically expanded single cell profiling capabilities to bolster systems level approaches to drug discovery. PMID:25805180
Brown, Eric D; Wright, Gerard D
The looming antibiotic-resistance crisis has penetrated the consciousness of clinicians, researchers, policymakers, politicians and the public at large. The evolution and widespread distribution of antibiotic-resistance elements in bacterial pathogens has made diseases that were once easily treatable deadly again. Unfortunately, accompanying the rise in global resistance is a failure in antibacterial drug discovery. Lessons from the history of antibiotic discovery and fresh understanding of antibiotic action and the cell biology of microorganisms have the potential to deliver twenty-first century medicines that are able to control infection in the resistance era.
Wójcikowski, Maciej; Zielenkiewicz, Piotr; Siedlecki, Pawel
There has been huge progress in the open cheminformatics field in both methods and software development. Unfortunately, there has been little effort to unite those methods and software into one package. We here describe the Open Drug Discovery Toolkit (ODDT), which aims to fulfill the need for comprehensive and open source drug discovery software. The Open Drug Discovery Toolkit was developed as a free and open source tool for both computer aided drug discovery (CADD) developers and researchers. ODDT reimplements many state-of-the-art methods, such as machine learning scoring functions (RF-Score and NNScore) and wraps other external software to ease the process of developing CADD pipelines. ODDT is an out-of-the-box solution designed to be easily customizable and extensible. Therefore, users are strongly encouraged to extend it and develop new methods. We here present three use cases for ODDT in common tasks in computer-aided drug discovery. Open Drug Discovery Toolkit is released on a permissive 3-clause BSD license for both academic and industrial use. ODDT's source code, additional examples and documentation are available on GitHub (https://github.com/oddt/oddt).
Jacobson, Kenneth A.
G protein-coupled receptors (GPCRs) remain a major domain of pharmaceutical discovery. The discovery of GPCR lead compounds and their optimization are now structure-based, thanks to advances in X-ray crystallography, molecular modeling, protein engineering and biophysical techniques. In silico screening provides useful hit molecules. New pharmacological approaches to tuning the pleotropic action of GPCRs include: allosteric modulators, biased ligands, GPCR heterodimer-targeted compounds, manipulation of polypharmacology, receptor antibodies and tailoring of drug molecules to fit GPCR pharmacogenomics. Measurements of kinetics and drug efficacy are factors influencing clinical success. With the exception of inhibitors of GPCR kinases, targeting of intracellular GPCR signaling or receptor cycling for therapeutic purposes remains a futuristic concept. New assay approaches are more efficient and multidimensional: cell-based, label-free, fluorescence-based assays, and biosensors. Tailoring GPCR drugs to a patient’s genetic background is now being considered. Chemoinformatic tools can predict ADME-tox properties. New imaging technology visualizes drug action in vivo. Thus, there is reason to be optimistic that new technology for GPCR ligand discovery will help improve the current narrowing of the pharmaceutical pipeline. PMID:26265138
Albensi, B C
Scientific visualization has progressed significantly over the last century since the discovery of X-rays in 1895 and is used widely in many industries. In the pharmaceutical industry, there is a growing need for visualizing disease progression (or reversal) and for visualizing the effectiveness of a drug in animal models and in humans during clinical studies. Improvements in imaging technology could assist in decreasing the time from proof-of-concept to when a drug is finally launched. Many new drugs are entering the pipeline and progress in visualization technology should enhance the objective determination for predicting success or failure in a drug program. "A picture is worth a thousand words." Therefore, by collecting images, which provide information on molecular events, gene expression, biochemical subsystems, anatomical modifications and physiological perturbations, we positively and creatively alter our perception in our explorations of anatomy, disease mechanisms and drug interventions. (c) 2001 Prous Science. All rights reserved.
Bhar, Shanta; Ramana, Mucheli M V
With reference to challenges in developing varied and exceedingly complex scaffolds expeditiously through atom economy, domino reactions have assumed a significant role in several transformative endeavors towards established pharmaceuticals and new chemical entities across diverse therapeutic classes such as HIV integrase inhibitors, DPP4 [dipeptidyl peptidase IV] inhibitors, GSK- 3 (Glycogen Synthase Kinase 3) inhibitors, neoplastic drugs and microtubule antagonists. The very large chemical space of Domino Reactions can be leveraged for the design strategy of drugs and drug- like candidates with leading examples like Indinavir (Crixivan), Trandolapril (Mavik), Biyouyanagin A, endo pyrrolizidinone diastereomer [GSK] and several others. Domino reactions therefore constitute an integral part of both creative and functional aspects of drug design and discovery, contributing both enhanced efficiency as well as synthetic versatility to pharmaceutical drug design.
Trosset, Jean-Yves; Carbonell, Pablo
Synthetic biology (SB) is an emerging discipline, which is slowly reorienting the field of drug discovery. For thousands of years, living organisms such as plants were the major source of human medicines. The difficulty in resynthesizing natural products, however, often turned pharmaceutical industries away from this rich source for human medicine. More recently, progress on transformation through genetic manipulation of biosynthetic units in microorganisms has opened the possibility of in-depth exploration of the large chemical space of natural products derivatives. Success of SB in drug synthesis culminated with the bioproduction of artemisinin by microorganisms, a tour de force in protein and metabolic engineering. Today, synthetic cells are not only used as biofactories but also used as cell-based screening platforms for both target-based and phenotypic-based approaches. Engineered genetic circuits in synthetic cells are also used to decipher disease mechanisms or drug mechanism of actions and to study cell-cell communication within bacteria consortia. This review presents latest developments of SB in the field of drug discovery, including some challenging issues such as drug resistance and drug toxicity.
Zheng, Wei; Thorne, Natasha; McKew, John C.
The significant reduction in the number of newly approved drugs in past decade has been partially attributed to failures in discovery and validation of new targets. Evaluation of recently approved new drugs has revealed that the number of approved drugs discovered through phenotypic screens, an original drug screening paradigm, has exceeded those discovered through the molecular target-based approach. Phenotypic screening is thus gaining new momentum in drug discovery with the hope that this approach may revitalize drug discovery and improve the success rate of drug approval through the discovery of viable lead compounds and identification of novel drug targets. PMID:23850704
Kita, Kiyoshi; Shiomi, Kazuro; Omura, Satoshi
Japanese researchers continue to discover new means to combat parasites and make important contributions toward developing tools for global control of parasitic diseases. Streptomyces avermectinius, the source of ivermectin, was discovered in Japan in the early 1970s and renewed and vigorous screening of microbial metabolites in recent years has led to the discovery of new antiprotozoals and anthelminthics, including antimalarial drugs. Intensive studies of parasite energy metabolism, such as NADH-fumarate reductase systems and the synthetic pathways of nucleic acids and amino acids, also contribute to the identification of novel and unique drug targets.
Maiese, Kenneth; Chong, Zhao Zhong; Shang, Yan Chen; Wang, Shaohui
Introduction Diabetes mellitus impacts almost 200 million individuals worldwide and leads to debilitating complications. New avenues of drug discovery must target the underlying cellular processes of oxidative stress, apoptosis, autophagy, and inflammation that can mediate multi-system pathology during diabetes mellitus. Areas Covered We examine novel directions for drug discovery that involve the β-nicotinamide adenine dinucleotide (NAD+) precursor nicotinamide, the cytokine erythropoietin, the NAD+-dependent protein histone deacetylase SIRT1, the serine/threonine-protein kinase mammalian target of rapamycin (mTOR), and the wingless pathway. Implications for the targeting of these pathways that oversee gluconeogenic genes, insulin signaling and resistance, fatty acid beta-oxidation, inflammation, and cellular survival are presented. Expert Opinion Nicotinamide, erythropoietin, and the downstram pathways of SIRT1, mTOR, forkhead transcription factors, and wingless signaling offer exciting prospects for novel directions of drug discovery for the treatment of metabolic disorders. Future investigations must dissect the complex relationship and fine modulation of these pathways for the successful translation of robust reparative and regenerative strategies against diabetes mellitus and the complications of this disorder. PMID:23092114
Skora, Lukasz; Jahnke, Wolfgang
Drug discovery is a complex process, and a variety of technologies contribute to its success. Biophysical methods have gained widespread attention within the last decade, and in particular NMR spectroscopy as the most versatile biophysical method has seen numerous applications and significant impact to drug discovery. Here we summarize the potential of NMR to support drug discovery, and highlight a number of recent applications.
Jacobson, Kenneth A
G protein-coupled receptors (GPCRs) remain a major domain of pharmaceutical discovery. The identification of GPCR lead compounds and their optimization are now structure-based, thanks to advances in X-ray crystallography, molecular modeling, protein engineering and biophysical techniques. In silico screening provides useful hit molecules. New pharmacological approaches to tuning the pleotropic action of GPCRs include: allosteric modulators, biased ligands, GPCR heterodimer-targeted compounds, manipulation of polypharmacology, receptor antibodies and tailoring of drug molecules to fit GPCR pharmacogenomics. Measurements of kinetics and drug efficacy are factors influencing clinical success. With the exception of inhibitors of GPCR kinases, targeting of intracellular GPCR signaling or receptor cycling for therapeutic purposes remains a futuristic concept. New assay approaches are more efficient and multidimensional: cell-based, label-free, fluorescence-based assays, and biosensors. Tailoring GPCR drugs to a patient's genetic background is now being considered. Chemoinformatic tools can predict ADME-tox properties. New imaging technology visualizes drug action in vivo. Thus, there is reason to be optimistic that new technology for GPCR ligand discovery will help reverse the current narrowing of the pharmaceutical pipeline.
Recent advances in intravital bone imaging technology has enabled us to grasp the real cellular behaviors and functions in vivo , revolutionizing the field of drug discovery for novel therapeutics against intractable bone diseases. In this chapter, I introduce various updated information on pharmacological actions of several antibone resorptive agents, which could only be derived from advanced imaging techniques, and also discuss the future perspectives of this new trend in drug discovery.
Chow, Maggie; Boheler, Kenneth R; Li, Ronald A
Heart diseases remain a major cause of mortality and morbidity worldwide. However, terminally differentiated human adult cardiomyocytes (CMs) possess a very limited innate ability to regenerate. Directed differentiation of human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) into CMs has enabled clinicians and researchers to pursue the novel therapeutic paradigm of cell-based cardiac regeneration. In addition to tissue engineering and transplantation studies, the need for functional CMs has also prompted researchers to explore molecular pathways and develop strategies to improve the quality, purity and quantity of hESC-derived and iPSC-derived CMs. In this review, we describe various approaches in directed CM differentiation and driven maturation, and discuss potential limitations associated with hESCs and iPSCs, with an emphasis on the role of epigenetic regulation and chromatin remodeling, in the context of the potential and challenges of using hESC-CMs and iPSC-CMs for drug discovery and toxicity screening, disease modeling, and clinical applications.
Fagnan, David E; Gromatzky, Austin A; Stein, Roger M; Fernandez, Jose-Maria; Lo, Andrew W
Recently proposed 'megafund' financing methods for funding translational medicine and drug development require billions of dollars in capital per megafund to de-risk the drug discovery process enough to issue long-term bonds. Here, we demonstrate that the same financing methods can be applied to orphan drug development but, because of the unique nature of orphan diseases and therapeutics (lower development costs, faster FDA approval times, lower failure rates and lower correlation of failures among disease targets) the amount of capital needed to de-risk such portfolios is much lower in this field. Numerical simulations suggest that an orphan disease megafund of only US$575 million can yield double-digit expected rates of return with only 10-20 projects in the portfolio. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.
LaPlante, Steven R; Edwards, Paul J; Fader, Lee D; Jakalian, Araz; Hucke, Oliver
An often overlooked source of chirality is atropisomerism, which results from slow rotation along a bond axis due to steric hindrance and/or electronic factors. If undetected or not managed properly, this time-dependent chirality has the potential to lead to serious consequences, because atropisomers can be present as distinct enantiomers or diastereoisomers with their attendant different properties. Herein we introduce a strategy to reveal and classify compounds that have atropisomeric chirality. Energy barriers to axial rotation were calculated using quantum mechanics, from which predicted high barriers could be experimentally validated. A calculated rotational energy barrier of 20 kcal mol(-1) was established as a suitable threshold to distinguish between atropisomers and non-atropisomers with a prediction accuracy of 86%. This methodology was applied to subsets of drug databases in the course of which atropisomeric drugs were identified. In addition, some drugs were exposed that were not yet known to have this chiral attribute. The most valuable utility of this tool will be to predict atropisomerism along the drug discovery pathway. When used in concert with our compound classification scheme, decisions can be made during early discovery stages such as "hit-to-lead" and "lead optimization," to foresee and validate the presence of atropisomers and to exercise options of removing, further stabilizing, or rendering the chiral axis of interest more freely rotatable via SAR design, thereby decreasing this potential liability within a compound series. The strategy can also improve drug development plans, such as determining whether a drug or series should be developed as a racemic mixture or as an isolated single compound. Moreover, the work described herein can be extended to other chemical fields that require the assessment of potential chiral axes.
Jubb, Adrian M; Koeppen, Hartmut; Reis-Filho, Jorge S
The rapid pace of drug discovery and drug development in oncology, immunology and ophthalmology brings new challenges; the efficient and effective development of new targeted drugs will require more detailed molecular classifications of histologically homogeneous diseases that show heterogeneous clinical outcomes. To this end, single companion diagnostics for specific drugs will be replaced by multiplex diagnostics for entire therapeutic areas, preserving tissue and enabling rapid molecular taxonomy. The field will move away from the development of new molecular entities as single agents, to which resistance is common. Instead, a detailed understanding of the pathological mechanisms of resistance, in patients and in preclinical models, will be key to the validation of scientifically rational and clinically effective drug combinations. To remain at the heart of disease diagnosis and appropriate management, pathologists must evolve into translational biologists and biomarker scientists. Herein, we provide examples of where this metamorphosis has already taken place, in lung cancer and melanoma, where the transformation has yet to begin, in the use of immunotherapies for ophthalmology and oncology, and where there is fertile soil for a revolution in treatment, in efforts to classify glioblastoma and personalize treatment. The challenges of disease heterogeneity, the regulatory environment and adequate tissue are ever present, but these too are being overcome in dedicated academic centres. In summary, the tools necessary to overcome the 'whens' and 'ifs' of the molecular revolution are in the hands of pathologists today; it is a matter of standardization, training and leadership to bring these into routine practice and translate science into patient benefit. This Annual Review Issue of the Journal of Pathology highlights the central role for pathology in modern drug discovery and development.
Prasad, Sahdeo; Gupta, Subash C; Aggarwal, Bharat B
Novel drug development leading to final approval by the US FDA can cost as much as two billion dollars. Why the cost of novel drug discovery is so expensive is unclear, but high failure rates at the preclinical and clinical stages are major reasons. Although therapies targeting a given cell signaling pathway or a protein have become prominent in drug discovery, such treatments have done little in preventing or treating any disease alone because most chronic diseases have been found to be multigenic. A review of the discovery of numerous drugs currently being used for various diseases including cancer, diabetes, cardiovascular, pulmonary, and autoimmune diseases indicates that serendipity has played a major role in the discovery. In this review we provide evidence that rational drug discovery and targeted therapies have minimal roles in drug discovery, and that serendipity and coincidence have played and continue to play major roles. The primary focus in this review is on cancer-related drug discovery.
Blair, Wade; Cox, Christopher
Continued discovery and development of new antiviral medications are paramount for global human health, particularly as new pathogens emerge and old ones evolve to evade current therapeutic agents. Great success has been achieved in developing effective therapies to suppress human immunodeficiency virus (HIV) and hepatitis B virus (HBV); however, the therapies are not curative and therefore current efforts in HIV and HBV drug discovery are directed toward longer-acting therapies and/or developing new mechanisms of action that could potentially lead to cure, or eradication, of the virus. Recently, exciting early clinical data have been reported for novel antivirals targeting respiratory syncytial virus (RSV) and influenza (flu). Preclinical data suggest that these new approaches may be effective in treating high-risk patients afflicted with serious RSV or flu infections. In this review, we highlight new directions in antiviral approaches for HIV, HBV, and acute respiratory virus infections. PMID:26962437
Lu, Yunxiang; Liu, Yingtao; Xu, Zhijian; Li, Haiying; Liu, Honglai; Zhu, Weiliang
A large number of drugs and drug candidates in clinical development contain halogen substituents. For a long time, only the steric and lipophilic contributions of halogens were considered when trying to exploit their effects on ligand binding. However, the ability of halogens to form stabilizing interactions, such as halogen bonding, hydrogen bonding and multipolar interactions, in biomolecular systems was revealed recently. Halogen bonding, the non-covalent interaction in which covalently bound halogens interact with Lewis bases, has now been utilized in the context of rational drug design. The purpose of this review is to show how halogen bonding could be used in drug design, and in particular, to stimulate researchers to apply halogen bonding in lead optimization. This review article covers the recent advances relevant to halogen bonding in drug discovery and biological design over the past decade, including database survey of this interaction in protein-ligand complexes, molecular mechanical investigations of halogen bonding in drug discovery and applications of this interaction in the development of halogenated ligands as inhibitors and drugs for protein kinases, serine protease factor Xa, HIV reverse transcriptase and so on. Halogen bonding should intentionally be used as a powerful tool, comparable with hydrogen bonding, to enhance the binding affinity and also influence the binding selectivity. Rational design of new and potent inhibitors against therapeutic targets through halogen bonding continues to be an exciting area, which will be further elucidated with the combination of various experimental techniques and theoretical calculations in the forthcoming years.
Yan, Z; Caldwell, G W
To reduce the high attrition rates of NCEs in preclinical and clinical development uncovering pharmacokinetics, toxicokinetics, drug metabolism, and drug-drug interactions early in drug discovery would be highly valuable. There have been many in vitro screens developed for these areas that have higher sample throughput, which is consistent with the iterative cycle of a typical drug discovery research project. We have presented the present status and given detailed descriptions of biotransformation, metabolic stability assays, identification of drug metabolizing P450 enzymes, prediction of pharmacokinetic parameters from in vitro metabolism data, structure elucidation of metabolites, CYP450 inhibition assays and CYP450 induction assays from a drug discovery perspective. Strategies for the proper sequencing of primary and secondary assays employedfor drug metabolism and CYP450 inhibition & induction is discussed.
Mercola, Mark; Colas, Alexandre; Willems, Erik
The unexpected discovery that somatic cells can be reprogrammed to a pluripotent state yielding induced pluripotent stem cells (iPSCs) has made it possible to produce cardiovascular cells exhibiting inherited traits and disorders. Use of these cells in high throughput analyses should broaden our insight into fundamental disease mechanisms and provide many benefits for patients, including new therapeutics and individually tailored therapies. Here we review recent progress in generating iPSC-based models of cardiovascular disease and their multiple applications in drug development. PMID:23371902
Montazerhodjat, Vahid; Frishkopf, John J; Lo, Andrew W
We extend the megafund concept for funding drug discovery to enable dynamic leverage in which the portfolio of candidate therapeutic assets is predominantly financed initially by equity, and debt is introduced gradually as assets mature and begin generating cash flows. Leverage is adjusted so as to maintain an approximately constant level of default risk throughout the life of the fund. Numerical simulations show that applying dynamic leverage to a small portfolio of orphan drug candidates can boost the return on equity almost twofold compared with securitization with a static capital structure. Dynamic leverage can also add significant value to comparable all-equity-financed portfolios, enhancing the return on equity without jeopardizing debt performance or increasing risk to equity investors.
Wu, Hongjin; Wang, Charles; Wu, Shixiu
Next-generation sequencing (NGS), particularly single-cell sequencing, has revolutionized the scale and scope of genomic and biomedical research. Recent technological advances in NGS and single-cell studies have made the deep whole-genome (DNA-seq), whole epigenome and whole-transcriptome sequencing (RNA-seq) at single-cell level feasible. NGS at the single-cell level expands our view of genome, epigenome and transcriptome and allows the genome, epigenome and transcriptome of any organism to be explored without a priori assumptions and with unprecedented throughput. And it does so with single-nucleotide resolution. NGS is also a very powerful tool for drug discovery and drug development. In this review, we describe the current state of single-cell sequencing techniques, which can provide a new, more powerful and precise approach for analyzing effects of drugs on treated cells and tissues. Our review discusses single-cell whole genome/exome sequencing (scWGS/scWES), single-cell transcriptome sequencing (scRNA-seq), single-cell bisulfite sequencing (scBS), and multiple omics of single-cell sequencing. We also highlight the advantages and challenges of each of these approaches. Finally, we describe, elaborate and speculate the potential applications of single-cell sequencing for drug discovery and drug development.
Siegel, Marshall M
Electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) mass spectrometric methods useful for early discovery drug screening are reviewed. All methods described involve studies of non-covalent complexes between biopolymer receptors and small molecule ligands formed in the condensed phase. The complexes can be sprayed intact directly into the gas phase by ESI-MS using gentle experimental conditions. Gas phase screening applications are illustrated for drug ligand candidates non-covalently interacting with peptides, proteins, RNA, and DNA. In the condensed phase, the complexes can be also isolated, denatured and analyzed by ESI-MS to identify the small molecule ligands. Condensed phase drug screening examples are illustrated for the ESI-MS ancillary techniques of affinity chromatography, ultrafiltration, ultracentrifugation, gel permeation chromatography (GPC), reverse phase-high performance liquid chromatography (RP-HPLC) and capillary electrophoretic methods. Solid phase drug screening using MALDI-MS is illustrated for small molecule ligands bound to MALDI affinity probe tips and to beads. Since ESI and MALDI principally produce molecular ions, high throughput screening is achieved by analyzing mass indexed mixtures.
Honório, Kathia M; Moda, Tiago L; Andricopulo, Adriano D
The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME--absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.
Award Number: W81XWH-11-1-0105 TITLE: A Drug Discovery Partnership for Personalized Breast Cancer Therapy PRINCIPAL INVESTIGATOR: Maryam Foroozesh...W81XWH-11-1-0105 A Drug Discovery Partnership for Personalized Breast Cancer Therapy 5b. GRANT NUMBER BC102922 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR...drugs for breast cancer therapy. The Drug Design Team at Xavier consists of experts in computer-aided drug design methods and synthesis and has formed
Piel, Markus; Vernaleken, Ingo; Rösch, Frank
Molecular imaging methods such as positron emission tomography (PET) are increasingly involved in the development of new drugs. Using radioactive tracers as imaging probes, PET allows the determination of the pharmacokinetic and pharmacodynamic properties of a drug candidate, via recording target engagement, the pattern of distribution, and metabolism. Because of the noninvasive nature and quantitative end point obtainable by molecular imaging, it seems inherently suited for the examination of a pharmaceutical's behavior in the brain. Molecular imaging, most especially PET, can therefore be a valuable tool in CNS drug research. In this Perspective, we present the basic principles of PET, the importance of appropriate tracer selection, the impact of improved radiopharmaceutical chemistry in radiotracer development, and the different roles that PET can fulfill in CNS drug research.
Leal, Miguel C; Calado, Ricardo; Sheridan, Christopher; Alimonti, Andrea; Osinga, Ronald
Marine natural products (NP) are unanimously acknowledged as the 'blue gold' in the urgent quest for new pharmaceuticals. Although corals are among the marine organisms with the greatest diversity of secondary metabolites, growing evidence suggest that their symbiotic bacteria produce most of these bioactive metabolites. The ex hospite culture of coral symbiotic microbiota is extremely challenging and only limited examples of successful culture exist today. By contrast, in toto aquaculture of corals is a commonly applied technology to produce corals for aquaria. Here, we suggest that coral aquaculture could as well be a viable and economically feasible option to produce the biomass required to execute the first steps of the NP-based drug discovery pipeline.
Mullane, Kevin; Winquist, Raymond J; Williams, Michael
The translational sciences represent the core element in enabling and utilizing the output from the biomedical sciences and to improving drug discovery metrics by reducing the attrition rate as compounds move from preclinical research to clinical proof of concept. Key to understanding the basis of disease causality and to developing therapeutics is an ability to accurately diagnose the disease and to identify and develop safe and effective therapeutics for its treatment. The former requires validated biomarkers and the latter, qualified targets. Progress has been hampered by semantic issues, specifically those that define the end product, and by scientific issues that include data reliability, an overt reductionistic cultural focus and a lack of hierarchically integrated data gathering and systematic analysis. A necessary framework for these activities is represented by the discipline of pharmacology, efforts and training in which require recognition and revitalization. Copyright © 2013 Elsevier Inc. All rights reserved.
Tsvetanova, Billyana; Peng, Lansha; Liang, Xiquan; Li, Ke; Hammond, Linda; Peterson, Todd C; Katzen, Federico
Recombinant DNA technologies have had a fundamental impact on drug discovery. The continuous emergence of unique gene assembly techniques resulted in the generation of a variety of therapeutic reagents such as vaccines, cancer treatment molecules and regenerative medicine precursors. With the advent of synthetic biology there is a growing need for precise and concerted assembly of multiple DNA fragments of various sizes, including chromosomes. In this article, we summarize the highlights of the recombinant DNA technology since its inception in the early 1970s, emphasizing on the most recent advances, and underscoring their principles, advantages and shortcomings. Current and prior cloning trends are discussed in the context of sequence requirements and scars left behind. Our opinion is that despite the remarkable progress that has enabled the generation and manipulation of very large DNA sequences, a better understanding of the cell's natural circuits is needed in order to fully exploit the current state-of-the-art gene assembly technologies.
Ciura, Krzesimir; Dziomba, Szymon; Nowakowska, Joanna; Markuszewski, Michał J
The review is mainly focused on application of thin layer chromatography (TLC) as simple, rapid and inexpensive method for lipophilicity assessment. Among separation techniques, TLC is still one of the most popular for lipophilicity measurement. The principles and methodology of Quantitative Structure Retention Relationship (QSRR) employed to lipophilicity prediction from retention data are presented. Moreover, applications of TLC retention constants in Quantitative Structure Activity Relationship (QSAR) studies were critically overviewed. The paper concerns also bioautography as a TLC method complementary to QSAR studies. In the article, the advantages and limitations of well established and less common planar chromatography modes applied for drug discovery process were discussed. Copyright © 2017 Elsevier B.V. All rights reserved.
Pettit, Robin K
Natural products continue to play a major role in drug discovery and development. However, chemical redundancy is an ongoing problem. Genomic studies indicate that certain groups of bacteria and fungi have dozens of secondary metabolite pathways that are not expressed under standard laboratory growth conditions. One approach to more fully access the metabolic potential of cultivatable microbes is mixed fermentation, where the presence of neighboring microbes may induce secondary metabolite synthesis. Research to date indicates that mixed fermentation can result in increased antibiotic activity in crude extracts, increased yields of previously described metabolites, increased yields of previously undetected metabolites, analogues of known metabolites resulting from combined pathways and, importantly, induction of previously unexpressed pathways for bioactive constituents.
Singeç, Ilyas; Simeonov, Anton
Pluripotent stem cell research has made extraordinary progress over the last decade. The robustness of nuclear reprogramming of somatic cells into induced pluripotent stem cells (iPSCs) has created entirely novel opportunities for drug discovery and personalized regenerative medicine. Patient- and disease-specific iPSCs can be expanded indefinitely and differentiated into relevant cell types of different organ systems. As the utilization of iPSCs is becoming a key enabling technology across various scientific disciplines, there are still important challenges that need to be addressed. Here we review the current state and reflect on the issues that the stem cell and translational communities are facing in bringing iPSCs closer to clinical application. PMID:27774310
Litterman, Nadia K.; Rhee, Michele; Swinney, David C.; Ekins, Sean
Rare disease research has reached a tipping point, with the confluence of scientific and technologic developments that if appropriately harnessed, could lead to key breakthroughs and treatments for this set of devastating disorders. Industry-wide trends have revealed that the traditional drug discovery research and development (R&D) model is no longer viable, and drug companies are evolving their approach. Rather than only pursue blockbuster therapeutics for heterogeneous, common diseases, drug companies have increasingly begun to shift their focus to rare diseases. In academia, advances in genetics analyses and disease mechanisms have allowed scientific understanding to mature, but the lack of funding and translational capability severely limits the rare disease research that leads to clinical trials. Simultaneously, there is a movement towards increased research collaboration, more data sharing, and heightened engagement and active involvement by patients, advocates, and foundations. The growth in networks and social networking tools presents an opportunity to help reach other patients but also find researchers and build collaborations. The growth of collaborative software that can enable researchers to share their data could also enable rare disease patients and foundations to manage their portfolio of funded projects for developing new therapeutics and suggest drug repurposing opportunities. Still there are many thousands of diseases without treatments and with only fragmented research efforts. We will describe some recent progress in several rare diseases used as examples and propose how collaborations could be facilitated. We propose that the development of a center of excellence that integrates and shares informatics resources for rare diseases sponsored by all of the stakeholders would help foster these initiatives. PMID:25685324
Litterman, Nadia K; Rhee, Michele; Swinney, David C; Ekins, Sean
Rare disease research has reached a tipping point, with the confluence of scientific and technologic developments that if appropriately harnessed, could lead to key breakthroughs and treatments for this set of devastating disorders. Industry-wide trends have revealed that the traditional drug discovery research and development (R&D) model is no longer viable, and drug companies are evolving their approach. Rather than only pursue blockbuster therapeutics for heterogeneous, common diseases, drug companies have increasingly begun to shift their focus to rare diseases. In academia, advances in genetics analyses and disease mechanisms have allowed scientific understanding to mature, but the lack of funding and translational capability severely limits the rare disease research that leads to clinical trials. Simultaneously, there is a movement towards increased research collaboration, more data sharing, and heightened engagement and active involvement by patients, advocates, and foundations. The growth in networks and social networking tools presents an opportunity to help reach other patients but also find researchers and build collaborations. The growth of collaborative software that can enable researchers to share their data could also enable rare disease patients and foundations to manage their portfolio of funded projects for developing new therapeutics and suggest drug repurposing opportunities. Still there are many thousands of diseases without treatments and with only fragmented research efforts. We will describe some recent progress in several rare diseases used as examples and propose how collaborations could be facilitated. We propose that the development of a center of excellence that integrates and shares informatics resources for rare diseases sponsored by all of the stakeholders would help foster these initiatives.
Dudley, Joel T; Schadt, Eric; Sirota, Marina; Butte, Atul J; Ashley, Euan
Despite great strides in revealing and understanding the physiological and molecular bases of cardiovascular disease, efforts to translate this understanding into needed therapeutic interventions continue to lag far behind the initial discoveries. Although pharmaceutical companies continue to increase investments into research and development, the number of drugs gaining federal approval is in decline. Many factors underlie these trends, and a vast number of technological and scientific innovations are being sought through efforts to reinvigorate drug discovery pipelines. Recent advances in molecular profiling technologies and development of sophisticated computational approaches for analyzing these data are providing new, systems-oriented approaches towards drug discovery. Unlike the traditional approach to drug discovery which is typified by a one-drug-one-target mindset, systems-oriented approaches to drug discovery leverage the parallelism and high-dimensionality of the molecular data to construct more comprehensive molecular models that aim to model broader bimolecular systems. These models offer a means to explore complex molecular states (e.g., disease) where thousands to millions of molecular entities comprising multiple molecular data types (e.g., proteomics and gene expression) can be evaluated simultaneously as components of a cohesive biomolecular system. In this paper, we discuss emerging approaches towards systems-oriented drug discovery and contrast these efforts with the traditional, unidimensional approach to drug discovery. We also highlight several applications of these system-oriented approaches across various aspects of drug discovery, including target discovery, drug repositioning and drug toxicity. When available, specific applications to cardiovascular drug discovery are highlighted and discussed.
Orhan, Ilkay Erdogan
Pharmacognosy deals with the natural drugs obtained from organisms such as most plants, microbes, and animals. Up to date, many important drugs including morphine, atropine, galanthamine, etc. have originated from natural sources which continue to be good model molecules in drug discovery. Traditional medicine is also a part of pharmacognosy and most of the third world countries still depend on the use of herbal medicines. Consequently, pharmacognosy always keeps its popularity in pharmaceutical sciences and plays a critical role in drug discovery.
Geschwindner, Stefan; Ulander, Johan; Johansson, Patrik
The use of ligand binding thermodynamics has been proposed as a potential success factor to accelerate drug discovery. However, despite the intuitive appeal of optimizing binding enthalpy, a number of factors complicate routine use of thermodynamic data. On a macroscopic level, a range of experimental parameters including temperature and buffer choice significantly influence the observed thermodynamic signatures. On a microscopic level, solute effects, structural flexibility, and cooperativity lead to nonlinear changes in enthalpy. This multifactorial character hides essential enthalpy contributions of intermolecular contacts, making them experimentally nonobservable. In this perspective, we present three case studies, reflect on some key factors affecting thermodynamic signatures, and investigate their relation to the hydrophobic effect, enthalpy-entropy compensation, lipophilic ligand efficiency, and promiscuity. The studies highlight that enthalpy and entropy cannot be used as direct end points but can together with calculations increase our understanding of ligand binding and identify interesting outliers that do not behave as expected.
Scott, Latanya. M.; Lawrence, Harshani. R.; Sebti, Saïd. M.; Lawrence, Nicholas. J.; Wu, Jie.
Protein tyrosine phosphatases (PTPs) are a diverse family of enzymes encoded by 107 genes in the human genome. Together with protein tyrosine kinases (PTKs), PTPs regulate various cellular activities essential for the initiation and maintenance of malignant phenotypes. While PTK inhibitors are now used routinely for cancer treatment, the PTP inhibitor development field is still in the discovery phase. In this article, the suitability of targeting PTPs for novel anticancer drug discovery is discussed. Examples are presented for PTPs that have been targeted for anticancer drug discovery as well as potential new PTP targets for novel anticancer drug discovery. PMID:20337577
Gant, Thomas G
Deuterium, the stable isotope of hydrogen, is known to medicinal chemists for its utility in mechanistic, spectroscopic, and tracer studies. In fact, well-known applications utilizing deuterium exist within every subdiscipline in pharmaceutical discovery and development. Recent emphasis on incorporation of deuterium into the active pharmaceutical ingredient has come about as a result of inquiries into the potential for substantial benefits of the deuterium kinetic isotope effect on the safety and disposition of the drug substance. This Perspective traces the author's experience in reviving and expanding this potential utility, first suggested many decades prior by the discoverer of this, the simplest of all isotopes.
Jiménez-Díaz, María Belén; Viera, Sara; Fernández-Alvaro, Elena; Angulo-Barturen, Iñigo
The emergence of resistance to artemisinins and the renewed efforts to eradicate malaria demand the urgent development of new drugs. In this endeavour, the evaluation of efficacy in animal models is often a go/no go decision assay in drug discovery. This important role relies on the capability of animal models to assess the disposition, toxicology and efficacy of drugs in a single test. Although the relative merits of each efficacy model of malaria as human surrogate have been extensively discussed, there are no critical analyses on the use of such models in current drug discovery. In this article, we intend to analyse how efficacy models are used to discover new antimalarial drugs. Our analysis indicates that testing drug efficacy is often the last assay in each discovery stage and the experimental designs utilized are not optimized to expedite decision-making and inform clinical development. In light of this analysis, we propose new ways to accelerate drug discovery using efficacy models.
Marsden, Catherine J; Eckersley, Sonia; Hebditch, Max; Kvist, Alexander J; Milner, Roy; Mitchell, Danielle; Warwicker, Juli; Marley, Anna E
Antibodies are powerful research tools that can be used in many areas of biology to probe, measure, and perturb various biological structures. Successful drug discovery is dependent on the correct identification of a target implicated in disease, coupled with the successful selection, optimization, and development of a candidate drug. Because of their specific binding characteristics, with regard to specificity, affinity, and avidity, coupled with their amenability to protein engineering, antibodies have become a key tool in drug discovery, enabling the quantification, localization, and modulation of proteins of interest. This review summarizes the application of antibodies and other protein affinity reagents as specific research tools within the drug discovery process.
Russo, Patrizia; Del Bufalo, Alessandra; Fini, Massimo
The deep-sea habitat is a source of very potent marine-derived agents that may inhibit the growth of human cancer cells “in vitro” and “in vivo”. Salinosporamide-A, Marizomib, by Salinispora species is a proteasome inhibitor with promising anticancer activity (Phase I/II trials). Different deep-sea-derived drugs are under preclinical evaluation. Cancer is a complex disease that may be represented by network medicine. A simple consequence is the change of the concept of target entity from a single protein to a whole molecular pathway and or cellular network. Deep-sea-derived drugs fit well to this new concept. PMID:26600744
Chen, G; Jayawickreme, C; Way, J; Armour, S; Queen, K; Watson, C; Ignar, D; Chen, W J; Kenakin, T
This paper discusses the use of constitutively active G-protein-coupled receptor systems for drug discovery. Specifically, the ternary complex model is used to define the two major theoretical advantages of constitutive receptor screening-namely, the ability to detect antagonists as well as agonists directly and the fact that constitutive systems are more sensitive to agonists. In experimental studies, transient transfection of Chinese hamster ovary cyclic AMP response element (CRE) luciferase reporter cells with cDNA for human parathyroid hormone receptor, glucagon receptor, and glucagon-like peptide (GLP-1) receptor showed cDNA concentration-dependent constitutive activity with parathyroid hormone (PTH-1) and glucagon. In contrast, no constitutive activity was observed for GLP-1 receptor, yet responses to GLP-1 indicated that receptor expression had taken place. In another functional system, Xenopus laevi melanophores transfected with cDNA for human calcitonin receptor showed constitutive activity. Nine ligands for the calcitonin receptor either increased or decreased constitutive activity in this assay. The sensitivity of the system to human calcitonin increased with increasing constitutive activity. These data indicate that, for those receptors which naturally produce constitutive activity, screening in this mode could be advantageous over other methods.
Rogawski, M A
Levetiracetam, the α-ethyl analogue of the nootropic piracetam, is a widely used antiepileptic drug (AED) that provides protection against partial seizures and is also effective in the treatment of primary generalized seizure syndromes including juvenile myoclonic epilepsy. Levetiracetam was discovered in 1992 through screening in audiogenic seizure susceptible mice and, 3 years later, was reported to exhibit saturable, stereospecific binding in brain to a ∼90 kDa protein, later identified as the ubiquitous synaptic vesicle glycoprotein SV2A. A large-scale screening effort to optimize binding affinity identified the 4-n-propyl analogue, brivaracetam, as having greater potency and a broadened spectrum of activity in animal seizure models. Recent phase II clinical trials demonstrating that brivaracetam is efficacious and well tolerated in the treatment of partial onset seizures have validated the strategy of the discovery programme. Brivaracetam is among the first clinically effective AEDs to be discovered by optimization of pharmacodynamic activity at a molecular target. PMID:18552880
Petroski, Matthew D
The ubiquitin system of protein modification has emerged as a crucial mechanism involved in the regulation of a wide array of cellular processes. As our knowledge of the pathways in this system has grown, so have the ties between the protein ubiquitin and human disease. The power of the ubiquitin system for therapeutic benefit blossomed with the approval of the proteasome inhibitor Velcade in 2003 by the FDA. Current drug discovery activities in the ubiquitin system seek to (i) expand the development of new proteasome inhibitors with distinct mechanisms of action and improved bioavailability, and (ii) validate new targets. This review summarizes our current understanding of the role of the ubiquitin system in various human diseases ranging from cancer, viral infection and neurodegenerative disorders to muscle wasting, diabetes and inflammation. I provide an introduction to the ubiquitin system, highlight some emerging relationships between the ubiquitin system and disease, and discuss current and future efforts to harness aspects of this potentially powerful system for improving human health. Republished from Current BioData's Targeted Proteins database (TPdb; ). PMID:19007437
Kufahl, Peter R.; Watterson, Lucas R.
Introduction Globally, alcohol abuse and dependence are significant contributors to chronic disease and injury and are responsible for nearly 4% of all deaths annually. Acamprosate (Campral), one of only three pharmacological treatments approved for the treatment of alcohol dependence, has shown mixed efficacy in clinical trials in maintaining abstinence of detoxified alcoholics since studies began in the 1980’s. Yielding inconsistent results, these studies have prompted skepticism. Areas Covered Herein, the authors review the preclinical studies which have assessed the efficacy of acamprosate in various animal models of alcohol dependence and discuss the disparate findings from the major clinical trials. Moreover, the authors discuss the major limitations of these preclinical and clinical studies and offer explanations for the often contradictory findings. The article also looks at the importance of the calcium moiety that accompanies the salt form of acamprosate and its relevance to its activity. Expert opinion The recent discovery that large doses of calcium largely duplicate the effects of acamprosate in animal models has introduced a serious challenge to the widely-held functional association between this drug and the glutamate neurotransmission system. Future research on acamprosate or newer pharmacotherapeutics should consider assessing plasma and/or brain levels of calcium as a correlate or mediating factor in anti-relapse efficacy. Furthermore, preclinical research on acamprosate has thus far lacked animal models of chemical dependence on alcohol, and the testing of rodents with histories of alcohol intoxication and withdrawal is suggested. PMID:25258174
Schwartz, Phillip A; Murray, Brion W
Protein kinases are fascinating biological catalysts with a rapidly expanding knowledge base, a growing appreciation in cell regulatory control, and an ascendant role in successful therapeutic intervention. To better understand protein kinases, the molecular underpinnings of phosphoryl group transfer, protein phosphorylation, and inhibitor interactions are examined. This analysis begins with a survey of phosphate group and phosphoprotein properties which provide context to the evolutionary selection of phosphorylation as a central mechanism for biological regulation of most cellular processes. Next, the kinetic and catalytic mechanisms of protein kinases are examined with respect to model aqueous systems to define the elements of catalysis. A brief structural biology overview further delves into the molecular basis of catalysis and regulation of catalytic activity. Concomitant with a prominent role in normal physiology, protein kinases have important roles in the disease state. To facilitate effective kinase drug discovery, classic and emerging approaches for characterizing kinase inhibitors are evaluated including biochemical assay design, inhibitor mechanism of action analysis, and proper kinetic treatment of irreversible inhibitors. As the resulting protein kinase inhibitors can modulate intended and unintended targets, profiling methods are discussed which can illuminate a more complete range of an inhibitor's biological activities to enable more meaningful cellular studies and more effective clinical studies. Taken as a whole, a wealth of protein kinase biochemistry knowledge is available, yet it is clear that a substantial extent of our understanding in this field remains to be discovered which should yield many new opportunities for therapeutic intervention.
Frigeri, Antonio; Nicchia, Grazia Paola; Svelto, Maria
The intracellular hydric balance is an essential process of mammalian cells. The water movement across cell membranes is driven by osmotic and hydrostatic forces and the speed of this process is dependent on the presence of specific aquaporin water channels. Since the molecular identification of the first water channel, AQP1, by Peter Agre's group, 13 homologous members have been found in mammals with varying degree of homology. The fundamental importance of these proteins in all living cells is suggested by their genetic conservation in eukaryotic organisms through plants to mammals. A number of recent studies have revealed the importance of mammalian AQPs in both physiology and pathophysiology and have suggested that pharmacological modulation of aquaporins expression and activity may provide new tools for the treatment of variety of human disorders, such as brain edema, glaucoma, tumour growth, congestive heart failure and obesity in which water and small solute transport may be involved. This review will highlight the physiological role and the pathological involvement of AQPs in mammals and the potential use of some recent therapeutic approaches, such as RNAi and immunotherapy, for AQP-related diseases. Furthermore, strategies that can be developed for the discovery of selective AQP-drugs will be introduced and discussed.
Rocke, John; Lees, Julie; Packham, Ian; Chico, Timothy
The zebrafish is a well established model of vertebrate development, but has recently emerged as a powerful tool for cardiovascular research and in vivo cardiovascular drug discovery. The zebrafish embryo's low cost, small size and permeability to small molecules coupled with the ability to generate thousands of embryos per week, and improved automation of assays of cardiovascular development and performance allow drug screening for a number of cardiovascular effects. Such studies have already led to discovery of novel cardiovascular drugs with potentially clinically beneficial effects. In this review we summarise the advantages and disadvantages of the zebrafish for drug discovery using some patents, previous literature on zebrafish-based drug screening and assess where the zebrafish will fit into existing drug discovery programmes.
Three-dimensional (3D) in vitro systems that can mimic organ and tissue structure and function in vivo, will be of great benefit for a variety of biological applications from basic biology to toxicity testing and drug discovery. There have been several attempts to generate 3D tissue models but most of these models require costly equipment, and the most serious disadvantage in them is that they are too far from the mature human organs in vivo. Because of these problems, research and development in drug discovery, toxicity testing and biotech industries are highly expensive, and involve sacrifice of countless animals and it takes several years to bring a single drug/product to the market or to find the toxicity or otherwise of chemical entities. Our group has been actively working on several alternative models by merging biomaterials science, nanotechnology and biological principles to generate 3D in vitro living organs, to be called "Human Organs-on-Chip", to mimic natural organ/tissues, in order to reduce animal testing and clinical trials. We have fabricated a novel type of mechanically and biologically bio-mimicking collagen-based hydrogel that would provide for interconnected mini-wells in which 3D cell/organ culture of human samples in a manner similar to human organs with extracellular matrix (ECM) molecules would be possible. These products mimic the physical, chemical, and biological properties of natural organs and tissues at different scales. This paper will review the outcome of our several experiments so far in this direction and the future perspectives.
Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.
Di, Li; Feng, Bo; Goosen, Theunis C; Lai, Yurong; Steyn, Stefanus J; Varma, Manthena V; Obach, R Scott
Prediction of human pharmacokinetics of new drugs, as well as other disposition attributes, has become a routine practice in drug research and development. Prior to the 1990s, drug disposition science was used in a mostly descriptive manner in the drug development phase. With the advent of in vitro methods and availability of human-derived reagents for in vitro studies, drug-disposition scientists became engaged in the compound design phase of drug discovery to optimize and predict human disposition properties prior to nomination of candidate compounds into the drug development phase. This has reaped benefits in that the attrition rate of new drug candidates in drug development for reasons of unacceptable pharmacokinetics has greatly decreased. Attributes that are predicted include clearance, volume of distribution, half-life, absorption, and drug-drug interactions. In this article, we offer our experience-based perspectives on the tools and methods of predicting human drug disposition using in vitro and animal data.
Nicolaou, K C
Admirable as it is, the drug discovery and development process is continuously undergoing changes and adjustments in search of further improvements in efficiency, productivity, and profitability. Recent trends in academic-industrial partnerships promise to provide new opportunities for advancements of this process through transdisciplinary collaborations along the entire spectrum of activities involved in this complex process. This perspective discusses ways to promote the emerging academic paradigm of the chemistry-biology-medicine continuum as a means to advance the drug discovery and development process.
Choi, Hyukjae; Oh, Dong-Chan
Conventional approaches to natural product drug discovery rely mainly on random searches for bioactive compounds using bioassays. These traditional approaches do not incorporate a chemical biology perspective. Searching for bioactive molecules using a chemical and biological rationale constitutes a powerful search paradigm. Here, the authors review recent examples of the discovery of bioactive natural products based on chemical and biological interactions between hosts and symbionts, and propose this method provides a more effective means of exploring natural chemical diversity and eventually of discovering new drugs.
Natural products provide a successful supply of new chemical entities (NCEs) for drug discovery to treat human diseases. Approximately half of the NCEs are based on natural products and their derivatives. Notably, marine natural products, a largely untapped resource, have contributed to drug discovery and development with eight drugs or cosmeceuticals approved by the U.S. Food and Drug Administration and European Medicines Agency, and ten candidates undergoing clinical trials. Collaborative efforts from drug developers, biologists, organic, medicinal, and natural product chemists have elevated drug discoveries to new levels. These efforts are expected to continue to improve the efficiency of natural product-based drugs. Marinopyrroles are examined here as a case study for potential anticancer and antibiotic agents. © 2015 Wiley Periodicals, Inc.
The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. Recent open data initiatives in basic and clinical research have dramatically increased the types of data available to the public. The past few years have witnessed successful use of big data in many sectors across the whole drug discovery pipeline. In this review, we will highlight the state of the art in leveraging big data to identify new targets, drug indications, and drug response biomarkers in this era of precision medicine. PMID:26659699
Lodén, Henrik; Shariatgorji, Mohammadreza; Nilsson, Anna; Andrén, Per E
A vital process in drug discovery and development is to assess the absorption, distribution, metabolism, excretion and toxicology of potentially therapeutic compounds in the body. The potential utility of MS imaging has been demonstrated in many studies focusing on molecules including peptides, proteins and lipids. However, MS imaging also permits the direct analysis of drugs and drug metabolites in tissue samples without requiring the use of target-specific labels or reagents. Here, a brief technical description of the technique is presented along with examples of its usefulness at different stages of the drug discovery and development process including absorption, distribution, metabolism, excretion and toxicology, and blood-brain barrier drug penetration investigations.
Sucher, Nikolaus J
The apparent productivity crisis in the pharmaceutical industry and the economic and political rise of China have contributed to renewed interest in the application of Chinese medicine for drug discovery. The author presents an overview of the historical development and basic principles of theory and practice of Chinese herbal medicine, its materia medica and prescription formulas, and discusses the motivation for and rationale of its application to drug discovery. Furthermore, the author distinguishes the five main approaches to drug discovery from Chinese herbal medicine, based on the decreasing amount and detail of historical and clinical Chinese medicine knowledge that informed the research effort. Many compounds that have been isolated from the Chinese materia medica exhibit pharmacological activities comparable to pharmaceutical drugs. With the exception of the antimalarial drug artemisinin, however, this knowledge has not led to the successful development of new drugs outside of China. The chance of success in a Chinese medicine-based drug discovery effort will be increased by consideration of the empirical knowledge that has been documented over many centuries in the historical materia medica and prescription literature. Most Chinese medicine-derived compounds affect more than one target and do not correspond to the one compound/one-target drug discovery paradigm. A new frontier is opening up with the development of drugs consisting of combinations of multiple compounds acting on multiple targets under the paradigm of network pharmacology. The ancient practice of combining multiple drugs in prescription formulas can serve as inspirational analogy and a practical guide.
1Clinical pharmacology is a key activity in drug discovery and drug development with much to contribute to drug innovation. 2However, very few clinical pharmacologists choose the pharmaceutical industry as their ultimate career. 3Medical alumni of the RPMS clinical pharmacology department illustrate this; only four industrial careers vs thirty professors of clinical pharmacology or medicine. PMID:8807154
Bhardwaj, Anshu; Scaria, Vinod; Raghava, Gajendra Pal Singh; Lynn, Andrew Michael; Chandra, Nagasuma; Banerjee, Sulagna; Raghunandanan, Muthukurussi V; Pandey, Vikas; Taneja, Bhupesh; Yadav, Jyoti; Dash, Debasis; Bhattacharya, Jaijit; Misra, Amit; Kumar, Anil; Ramachandran, Srinivasan; Thomas, Zakir; Brahmachari, Samir K
It is being realized that the traditional closed-door and market driven approaches for drug discovery may not be the best suited model for the diseases of the developing world such as tuberculosis and malaria, because most patients suffering from these diseases have poor paying capacity. To ensure that new drugs are created for patients suffering from these diseases, it is necessary to formulate an alternate paradigm of drug discovery process. The current model constrained by limitations for collaboration and for sharing of resources with confidentiality hampers the opportunities for bringing expertise from diverse fields. These limitations hinder the possibilities of lowering the cost of drug discovery. The Open Source Drug Discovery project initiated by Council of Scientific and Industrial Research, India has adopted an open source model to power wide participation across geographical borders. Open Source Drug Discovery emphasizes integrative science through collaboration, open-sharing, taking up multi-faceted approaches and accruing benefits from advances on different fronts of new drug discovery. Because the open source model is based on community participation, it has the potential to self-sustain continuous development by generating a storehouse of alternatives towards continued pursuit for new drug discovery. Since the inventions are community generated, the new chemical entities developed by Open Source Drug Discovery will be taken up for clinical trial in a non-exclusive manner by participation of multiple companies with majority funding from Open Source Drug Discovery. This will ensure availability of drugs through a lower cost community driven drug discovery process for diseases afflicting people with poor paying capacity. Hopefully what LINUX the World Wide Web have done for the information technology, Open Source Drug Discovery will do for drug discovery. Copyright © 2011 Elsevier Ltd. All rights reserved.
Levin, Victor A.; Tonge, Peter J.; Gallo, James M.; Birtwistle, Marc R.; Dar, Arvin C.; Iavarone, Antonio; Paddison, Patrick J.; Heffron, Timothy P.; Elmquist, William F.; Lachowicz, Jean E.; Johnson, Ted W.; White, Forest M.; Sul, Joohee; Smith, Quentin R.; Shen, Wang; Sarkaria, Jann N.; Samala, Ramakrishna; Wen, Patrick Y.; Berry, Donald A.; Petter, Russell C.
Following the first CNS Anticancer Drug Discovery and Development Conference, the speakers from the first 4 sessions and organizers of the conference created this White Paper hoping to stimulate more and better CNS anticancer drug discovery and development. The first part of the White Paper reviews, comments, and, in some cases, expands on the 4 session areas critical to new drug development: pharmacological challenges, recent drug approaches, drug targets and discovery, and clinical paths. Following this concise review of the science and clinical aspects of new CNS anticancer drug discovery and development, we discuss, under the rubric “Accelerating Drug Discovery and Development for Brain Tumors,” further reasons why the pharmaceutical industry and academia have failed to develop new anticancer drugs for CNS malignancies and what it will take to change the current status quo and develop the drugs so desperately needed by our patients with malignant CNS tumors. While this White Paper is not a formal roadmap to that end, it should be an educational guide to clinicians and scientists to help move a stagnant field forward. PMID:26403167
Levin, Victor A; Tonge, Peter J; Gallo, James M; Birtwistle, Marc R; Dar, Arvin C; Iavarone, Antonio; Paddison, Patrick J; Heffron, Timothy P; Elmquist, William F; Lachowicz, Jean E; Johnson, Ted W; White, Forest M; Sul, Joohee; Smith, Quentin R; Shen, Wang; Sarkaria, Jann N; Samala, Ramakrishna; Wen, Patrick Y; Berry, Donald A; Petter, Russell C
Following the first CNS Anticancer Drug Discovery and Development Conference, the speakers from the first 4 sessions and organizers of the conference created this White Paper hoping to stimulate more and better CNS anticancer drug discovery and development. The first part of the White Paper reviews, comments, and, in some cases, expands on the 4 session areas critical to new drug development: pharmacological challenges, recent drug approaches, drug targets and discovery, and clinical paths. Following this concise review of the science and clinical aspects of new CNS anticancer drug discovery and development, we discuss, under the rubric "Accelerating Drug Discovery and Development for Brain Tumors," further reasons why the pharmaceutical industry and academia have failed to develop new anticancer drugs for CNS malignancies and what it will take to change the current status quo and develop the drugs so desperately needed by our patients with malignant CNS tumors. While this White Paper is not a formal roadmap to that end, it should be an educational guide to clinicians and scientists to help move a stagnant field forward.
The 2015 Nobel Prize in Physiology or Medicine has been awarded to William C. Campbell and Satoshi Omura, and Youyou Tu for the discovery of avermectins and artemisinin, respectively, therapies that revolutionized the treatment of devastating parasite diseases. With the recent technological advances, a New Golden Age of natural products drug discovery is dawning. PMID:26638061
The 2015 Nobel Prize in Physiology or Medicine has been awarded to William C. Campbell, Satoshi Omura, and Youyou Tu for the discovery of avermectins and artemisinin, respectively, therapies that revolutionized the treatment of devastating parasite diseases. With the recent technological advances, a New Golden Age of natural products drug discovery is dawning. Copyright © 2015 Elsevier Inc. All rights reserved.
Drug discovery today is impossible without sophisticated modeling and computation. In this review we touch on previous advances in computational biology and by tracing the steps involved in pharmaceutical development, we explore a range of novel, high value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry ties for scientific and human benefit. Attention to these opportunities could promise punctuated advance, and will complement the well-established computational work on which drug discovery currently relies. PMID:19674801
Yao, Lixia; Evans, James A; Rzhetsky, Andrey
Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.
Yao, Lixia; Evans, James A; Rzhetsky, Andrey
Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development,explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery.These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use.Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.
Patten, Shunmoogum A; Parker, J Alex; Wen, Xiao-Yan; Drapeau, Pierre
Simple animal models have enabled great progress in uncovering the disease mechanisms of amyotrophic lateral sclerosis (ALS) and are helping in the selection of therapeutic compounds through chemical genetic approaches. Within this article, the authors provide a concise overview of simple model organisms, C. elegans, Drosophila and zebrafish, which have been employed to study ALS and discuss their value to ALS drug discovery. In particular, the authors focus on innovative chemical screens that have established simple organisms as important models for ALS drug discovery. There are several advantages of using simple animal model organisms to accelerate drug discovery for ALS. It is the authors' particular belief that the amenability of simple animal models to various genetic manipulations, the availability of a wide range of transgenic strains for labelling motoneurons and other cell types, combined with live imaging and chemical screens should allow for new detailed studies elucidating early pathological processes in ALS and subsequent drug and target discovery.
Wild, David J
Increasingly, effective drug discovery involves the searching and data mining of large volumes of information from many sources covering the domains of chemistry, biology and pharmacology amongst others. This has led to a proliferation of databases and data sources relevant to drug discovery. This paper provides a review of the publicly-available large-scale databases relevant to drug discovery, describes the kinds of data mining approaches that can be applied to them and discusses recent work in integrative data mining that looks for associations that pan multiple sources, including the use of Semantic Web techniques. The future of mining large data sets for drug discovery requires intelligent, semantic aggregation of information from all of the data sources described in this review, along with the application of advanced methods such as intelligent agents and inference engines in client applications.
Jensen, Janne; Hyllner, Johan; Björquist, Petter
Development of new drugs is costly and takes huge resources into consideration. The big pharmaceutical companies are currently facing increasing developmental costs and a lower success-rate of bringing new compounds to the market. Therefore, it is now of outmost importance that the drug-hunting companies minimize late attritions due to sub-optimal pharmacokinetic properties or unexpected toxicity when entering the clinical programs. To achieve this, a strong need to test new candidate drugs in assays of high human relevance in vitro as early as possible has been identified. The traditionally used cell systems are however remarkably limited in this sense, and new improved technologies are of greatest importance. The human embryonic stem cells (hESC) is one of the most powerful cell types known. They have not only the possibility to divide indefinitely; these cells can also differentiate into all mature cell types of the human body. This makes them potentially very valuable for pharmaceutical development, spanning from use as tools in early target studies, DMPK or safety assessment, as screening models to find new chemical entities modulating adult stem cell fate, or as the direct use in cell therapies. This review illustrates the use of hESC in the drug discovery process, today, as well as in a future perspective. This will specifically be exemplified with the most important cell type for pharmaceutical development-the hepatocyte. We discuss how hESC-derived hepatocyte-like cells could improve this process, and how these cells should be cultured if optimized functionality and usefulness should be achieved. J. Cell. Physiol. 219: 513-519, 2009. (c) 2009 Wiley-Liss, Inc.
Rotella, David P
Small molecules remain the backbone for modern drug discovery. They are conceived and synthesized by medicinal chemists, many of whom were originally trained as organic chemists. Support from government and industry to provide training and personnel for continued development of this critical skill set has been declining for many years. This Viewpoint highlights the value of organic chemistry and organic medicinal chemists in the complex journey of drug discovery as a reminder that basic science support must be restored.
Baskin, Igor I; Winkler, David; Tetko, Igor V
Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to choose the most appropriate approach. In this review, the authors discuss traditional and newly emerging neural network approaches to drug discovery. Their focus is on backpropagation neural networks and their variants, self-organizing maps and associated methods, and a relatively new technique, deep learning. The most important technical issues are discussed including overfitting and its prevention through regularization, ensemble and multitask modeling, model interpretation, and estimation of applicability domain. Different aspects of using neural networks in drug discovery are considered: building structure-activity models with respect to various targets; predicting drug selectivity, toxicity profiles, ADMET and physicochemical properties; characteristics of drug-delivery systems and virtual screening. Neural networks continue to grow in importance for drug discovery. Recent developments in deep learning suggests further improvements may be gained in the analysis of large chemical data sets. It's anticipated that neural networks will be more widely used in drug discovery in the future, and applied in non-traditional areas such as drug delivery systems, biologically compatible materials, and regenerative medicine.
Nettleton, David O; Einolf, Heidi J
Evaluation of the potential of a drug candidate to inhibit or inactivate cytochrome P450 (CYP) enzymes remains an important part of pharmaceutical drug Discovery and Development programs. CYP enzymes are considered to be one of the most important enzyme families involved in the metabolic clearance of the vast majority of prescribed drugs. Clinical drug-drug interactions (DDI) involving inhibition or time-dependent inactivation of these enzymes can result in dangerous side effects resulting from reduced clearance/increased exposure of the drug being affected (the 'victim' drug). In this regard, pharmaceutical companies have become quite vigilant in mitigating CYP inhibition/inactivation liabilities of drug candidates early in Discovery including continued risk assessment throughout Development. In this review, common strategies and decision making processes for the assessment of DDI risk in the different stages of pharmaceutical development are discussed. In addition, in vitro study designs, analysis, and interpretation of CYP inhibition and inactivation data are described in stage appropriate context. The in vitro tools and knowledge available now enable the Discovery Chemist to place the potential CYP DDI liability of a drug candidate into perspective and to aid in the optimization of chemical drug design to further mitigate this risk.
Balganesh, T S; Furr, B J A
Selection of appropriate targets for launching antituberculosis drug discovery programmes is challenging. This challenge is magnified by the limited repertoire of 'validated targets' and the paucity of clinically successful drugs. However, continued understanding of the biology of the microbe and its interaction with the host has enabled detailed evaluation of several interesting pathways and novel targets. The value of a target that is suitable for antituberculosis drug discovery needs to be defined not only in the context of its 'essentiality' for survival in vitro but also against a variety of properties relevant to activities in the drug discovery process, e.g.; selectivity, vulnerability, suitability for structural studies, ability to monitor inhibition in whole cells etc. It is also rarely feasible to obtain all the relevant information on the target prior to the launch of a discovery programme. Thus, there is a continuous confidence-building exercise on the validity of a target. Several novel approaches have enabled exploitation of the mycobacterial genome and prioritisation of putative targets; the concept of 'sterilisation' is now being evaluated not only through the availability of structurally diverse probe compounds but also by the ability to characterise metabolic pathways in vivo. The impact of the current knowledge base on the different facets of 'target validation' relevant to antituberculosis drug discovery is discussed in this article with emphasis on developing appropriate matrix systems to prioritise them. The article also discusses the influence of lead generation approaches with specific reference to antibacterial drug discovery.
Small molecule drug discovery critically depends on the availability of meaningful in vitro assays to guide medicinal chemistry programs that are aimed at optimizing drug potency and selectivity. As it becomes increasingly evident, most disease relevant drug targets do not act as a single protein. In the body, they are instead generally found in complex with protein cofactors that are highly relevant for their correct function and regulation. This review highlights selected examples of the increasing trend to use biologically relevant protein complexes for rational drug discovery to reduce costly late phase attritions due to lack of efficacy or toxicity.
Smithsonian Institution, Washington, DC. National Air And Space Museum.
This material presents the historical perspectives of flight and student activities for grades K-3 prepared by the National Air and Space Museum (NASM) and National Aeronautics and Space Administration (NASA). Sections included are: (1) "Historical Perspective of Flight"; (2) "Discovery Vocabulary" (listing the terms found in the first section);…
Neglected tropical diseases (NTDs) are an extremely important issue facing global health care. To improve "access to health" where people are unable to access adequate medical care due to poverty and weak healthcare systems, we have established two consortiums: the NTD drug discovery research consortium, and the pediatric praziquantel consortium. The NTD drug discovery research consortium, which involves six institutions from industry, government, and academia, as well as an international non-profit organization, is committed to developing anti-protozoan active compounds for three NTDs (Leishmaniasis, Chagas disease, and African sleeping sickness). Each participating institute will contribute their efforts to accomplish the following: selection of drug targets based on information technology, and drug discovery by three different approaches (in silico drug discovery, "fragment evolution" which is a unique drug designing method of Astellas Pharma, and phenotypic screening with Astellas' compound library). The consortium has established a brand new database (Integrated Neglected Tropical Disease Database; iNTRODB), and has selected target proteins for the in silico and fragment evolution drug discovery approaches. Thus far, we have identified a number of promising compounds that inhibit the target protein, and we are currently trying to improve the anti-protozoan activity of these compounds. The pediatric praziquantel consortium was founded in July 2012 to develop and register a new praziquantel pediatric formulation for the treatment of schistosomiasis. Astellas Pharma has been a core member in this consortium since its establishment, and has provided expertise and technology in the area of pediatric formulation development and clinical development.
von Korff, Modest; Rufener, Christian; Stritt, Manuel; Freyss, Joel; Bär, Roman; Sander, Thomas
Grid computing offers an opportunity to gain massive computing power at low costs. We give a short introduction into the drug discovery process and exemplify the use of grid computing for image processing, docking and 3D pharmacophore descriptor calculations. The principle of a grid and its architecture are briefly explained. More emphasis is laid on the issues related to a company-wide grid installation and embedding the grid into the research process. The future of grid computing in drug discovery is discussed in the expert opinion section. Most needed, besides reliable algorithms to predict compound properties, is embedding the grid seamlessly into the discovery process. User friendly access to powerful algorithms without any restrictions, that is, by a limited number of licenses, has to be the goal of grid computing in drug discovery.
Ekins, Sean; Waller, Chris L; Bradley, Mary P; Clark, Alex M; Williams, Antony J
Drug discovery is shifting focus from industry to outside partners and, in the process, creating new bottlenecks. Technologies like high throughput screening (HTS) have moved to a larger number of academic and institutional laboratories in the USA, with little coordination or consideration of the outputs and creating a translational gap. Although there have been collaborative public-private partnerships in Europe to share pharmaceutical data, the USA has seemingly lagged behind and this may hold it back. Sharing precompetitive data and models may accelerate discovery across the board, while finding the best collaborators, mining social media and mobile approaches to open drug discovery should be evaluated in our efforts to remove drug discovery bottlenecks. We describe four strategies to rectify the current unsustainable situation.
Kumar, Ashutosh; Zhang, Kam Y J
Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery.
Background Drug discovery is a complex and unpredictable endeavor with a high failure rate. Current trends in the pharmaceutical industry have exasperated these challenges and are contributing to the dramatic decline in productivity observed over the last decade. The industrialization of science by forcing the drug discovery process to adhere to assembly-line protocols is imposing unnecessary restrictions, such as short project time-lines. Recent advances in nuclear magnetic resonance are responding to these self-imposed limitations and are providing opportunities to increase the success rate of drug discovery. Objective/Method A review of recent advancements in NMR technology that have the potential of significantly impacting and benefiting the drug discovery process will be presented. These include fast NMR data collection protocols and high-throughput protein structure determination, rapid protein-ligand co-structure determination, lead discovery using fragment-based NMR affinity screens, NMR metabolomics to monitor in vivo efficacy and toxicity for lead compounds, and the identification of new therapeutic targets through the functional annotation of proteins by FAST-NMR. Conclusion NMR is a critical component of the drug discovery process, where the versatility of the technique enables it to continually expand and evolve its role. NMR is expected to maintain this growth over the next decade with advancements in automation, speed of structure calculation, in-cell imaging techniques, and the expansion of NMR amenable targets. PMID:20333269
Sun, Ying; Zhou, Hong; Yang, Bao-xue
In polycystic kidney disease (PKD), a most common human genetic diseases, fluid-filled cysts displace normal renal tubules and cause end-stage renal failure. PKD is a serious and costly disorder. There is no available therapy that prevents or slows down the cystogenesis and cyst expansion in PKD. Numerous efforts have been made to find drug targets and the candidate drugs to treat PKD. Recent studies have defined the mechanisms underlying PKD and new therapies directed toward them. In this review article, we summarize the pathogenesis of PKD, possible drug targets, available PKD models for screening and evaluating new drugs as well as candidate drugs that are being developed. PMID:21642949
Shim, Joong Sup; Liu, Jun O.
Drug repositioning (also referred to as drug repurposing), the process of finding new uses of existing drugs, has been gaining popularity in recent years. The availability of several established clinical drug libraries and rapid advances in disease biology, genomics and bioinformatics has accelerated the pace of both activity-based and in silico drug repositioning. Drug repositioning has attracted particular attention from the communities engaged in anticancer drug discovery due to the combination of great demand for new anticancer drugs and the availability of a wide variety of cell- and target-based screening assays. With the successful clinical introduction of a number of non-cancer drugs for cancer treatment, drug repositioning now became a powerful alternative strategy to discover and develop novel anticancer drug candidates from the existing drug space. In this review, recent successful examples of drug repositioning for anticancer drug discovery from non-cancer drugs will be discussed. PMID:25013375
Shim, Joong Sup; Liu, Jun O
Drug repositioning (also referred to as drug repurposing), the process of finding new uses of existing drugs, has been gaining popularity in recent years. The availability of several established clinical drug libraries and rapid advances in disease biology, genomics and bioinformatics has accelerated the pace of both activity-based and in silico drug repositioning. Drug repositioning has attracted particular attention from the communities engaged in anticancer drug discovery due to the combination of great demand for new anticancer drugs and the availability of a wide variety of cell- and target-based screening assays. With the successful clinical introduction of a number of non-cancer drugs for cancer treatment, drug repositioning now became a powerful alternative strategy to discover and develop novel anticancer drug candidates from the existing drug space. In this review, recent successful examples of drug repositioning for anticancer drug discovery from non-cancer drugs will be discussed.
Medina-Franco, José L; Martinez-Mayorga, Karina; Meurice, Nathalie
The concept of chemical space has broad applications in drug discovery. In response to the needs of drug discovery campaigns, different approaches are followed to efficiently populate, mine and select relevant chemical spaces that overlap with biologically relevant chemical spaces. This paper reviews major trends in current drug discovery and their impact on the mining and population of chemical space. We also survey different approaches to develop screening libraries with confined chemical spaces balancing physicochemical properties. In this context, the confinement is guided by criteria that can be divided in two broad categories: i) library design focused on a relevant therapeutic target or disease and ii) library design focused on the chemistry or a desired molecular function. The design and development of chemical libraries should be associated with the specific purpose of the library and the project goals. The high complexity of drug discovery and the inherent imperfection of individual experimental and computational technologies prompt the integration of complementary library design and screening approaches to expedite the identification of new and better drugs. Library design approaches including diversity-oriented synthesis, biological-oriented synthesis or combinatorial library design, to name a few, and the design of focused libraries driven by target/disease, chemical structure or molecular function are more efficient if they are guided by multi-parameter optimization. In this context, consideration of pharmaceutically relevant properties is essential for balancing novelty with chemical space in drug discovery.
Zhu, Xiangcheng; Zheng, Qiang; Yang, Hu; Cai, Jin; Huang, Lei; Duan, Yanwen; Xu, Zhinan; Cen, Peilin
Inkjet dispensing technology is a promising fabrication methodology widely applied in drug discovery. The automated programmable characteristics and high-throughput efficiency makes this approach potentially very useful in miniaturizing the design patterns for assays and drug screening. Various custom-made inkjet dispensing systems as well as specialized bio-ink and substrates have been developed and applied to fulfill the increasing demands of basic drug discovery studies. The incorporation of other modern technologies has further exploited the potential of inkjet dispensing technology in drug discovery and development. This paper reviews and discusses the recent developments and practical applications of inkjet dispensing technology in several areas of drug discovery and development including fundamental assays of cells and proteins, microarrays, biosensors, tissue engineering, basic biological and pharmaceutical studies. Progression in a number of areas of research including biomaterials, inkjet mechanical systems and modern analytical techniques as well as the exploration and accumulation of profound biological knowledge has enabled different inkjet dispensing technologies to be developed and adapted for high-throughput pattern fabrication and miniaturization. This in turn presents a great opportunity to propel inkjet dispensing technology into drug discovery.
Kang, Byoung Heon; Altieri, Dario C.
There is a plethora of attractive drug targets in cancer, but their therapeutic exploitation proved more difficult than expected, and only rarely truly successful. One possibility not often considered in drug discovery is that cancer signaling pathways are not randomly arranged in cells, but orchestrated in specialized subcellular compartments. The identification of Heat Shock Protein-90 (Hsp90) chaperones in mitochondria of tumors, but not most normal tissues, provides an example of a compartmentalized network of cell survival, opening fresh prospects for novel, subcellularly-targeted cancer drug discovery. PMID:19648961
Heath, James R.; Ribas, Antoni; Mischel, Paul S.
The genetic, functional, or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development.1-3 In cancers, heterogeneity may be essential for tumor stability,4 but its precise role in tumor biology is poorly resolved. This challenges the design of accurate disease models for use in drug development, and can confound the interpretation of biomarker levels, and of patient responses to specific therapies. The complex nature of heterogeneous tissues has motivated the development of tools for single cell genomic, transcriptomic, and multiplex proteomic analysis. We review these tools, assess their advantages and limitations, and explore their potential applications in drug discovery and development. PMID:26669673
Tian, Hai-Feng; Chen, Bing; Wen, Jian-Fan
Giardiasis is a worldwide parasitic disease caused by the protozoan Giardia lamblia in humans and other animals, especially live stocks. Here, we briefly review the current state of therapeutic availability for giardiasis, including chemical drugs and vaccines, and the dilemma in the prevention and treatment of this disease, including the emergence of drug resistance and the shortage of vaccine (especially for humans). Future efforts and progress in controlling giardiasis are expected in three aspects: clarification of the drug resistance mechanisms, development of efficient vaccines, and identification of more targets for new drugs and vaccines.
Jin, Ping; Chen, Xiaofei
In recent years, there has been an expansion of the understanding of how epigenetic dysregulation plays a role in tumorigenesis, progression, metastasis and treatment resistance. Evidence has focused on two common and well-studied "epigenetic codes", i.e., DNA methylation and histone posttranslational modification, which regulate the transcriptional status in various types of cancer and the corresponding target agents. Aside from "writers" and "erasers", which refer to enzymes that catalyze and remove posttranslational modifications, respectively, "readers" bind to target proteins and recruit "writers" and "erasers" for regulating gene expression. A number of selective and potent anticancer compounds have been reported, some of which are in preclinical or clinical trials that have shown promising results, primarily against malignant neoplasms such as hematologic malignancies, with the subsequent emerging development of both monotherapy and co-administration with traditional cytotoxic medicines against solid tumors. Second-generation epigenetic agents such as EZH2 and BET inhibitors have greatly progressed. Epigenetic dysregulation has also provided feasibility for the diagnosis and treatment of cancer. In this review, we summarize the progress in epigenetics and drug discovery for cancer and certain clinical trials that may provide a perspective for future development.
Pharmaceutical discovery and development is expensive and highly risky, even for multinational corporations. As a developing country with limited financial resources, China has been seeking the most cost-effective means to reach the same level of innovation and productivity as Western countries in the pharmaceutical industry sector. After more than 50 years of building up talent and experience, the time for China to become a powerhouse in pharmaceutical innovation is finally approaching. Returnee scientists to China are one of the reasons for the wave of new discovery and commercialization occurring within the country. The consolidation of local Chinese pharmaceutical companies and foreign investment is also providing an agreeable environment for the evolution of a new generation of biotechnology. The opportunity for pharmaceutical innovation is also being expedited by the entry of multinational companies into the Chinese pharmaceutical market, and by the outsourcing of research from these companies to China.
Smith, Peter M
This paper reviews the characteristics of a new model of computing that has been spurred on by the Internet, known as Netcentric computing. Developments in this model led to distributed component architectures, which, although not new ideas, are now realizable with modern tools such as Enterprise Java. The application of this approach to scientific computing, particularly in pharmaceutical discovery research, is discussed and highlighted by a particular case involving the management of biological assay data.
Hosoya, Masaki; Czysz, Katherine
Despite continuous efforts to improve the process of drug discovery and development, achieving success at the clinical stage remains challenging because of a persistent translational gap between the preclinical and clinical settings. Under these circumstances, the discovery of human induced pluripotent stem (iPS) cells has brought new hope to the drug discovery field because they enable scientists to humanize a variety of pharmacological and toxicological models in vitro. The availability of human iPS cell-derived cells, particularly as an alternative for difficult-to-access tissues and organs, is increasing steadily; however, their use in the field of translational medicine remains challenging. Biomarkers are an essential part of the translational effort to shift new discoveries from bench to bedside as they provide a measurable indicator with which to evaluate pharmacological and toxicological effects in both the preclinical and clinical settings. In general, during the preclinical stage of the drug development process, in vitro models that are established to recapitulate human diseases are validated by using a set of biomarkers; however, their translatability to a clinical setting remains problematic. This review provides an overview of current strategies for human iPS cell-based drug discovery from the perspective of translational research, and discusses the importance of early consideration of clinically relevant biomarkers. PMID:28009813
Hosoya, Masaki; Czysz, Katherine
Despite continuous efforts to improve the process of drug discovery and development, achieving success at the clinical stage remains challenging because of a persistent translational gap between the preclinical and clinical settings. Under these circumstances, the discovery of human induced pluripotent stem (iPS) cells has brought new hope to the drug discovery field because they enable scientists to humanize a variety of pharmacological and toxicological models in vitro. The availability of human iPS cell-derived cells, particularly as an alternative for difficult-to-access tissues and organs, is increasing steadily; however, their use in the field of translational medicine remains challenging. Biomarkers are an essential part of the translational effort to shift new discoveries from bench to bedside as they provide a measurable indicator with which to evaluate pharmacological and toxicological effects in both the preclinical and clinical settings. In general, during the preclinical stage of the drug development process, in vitro models that are established to recapitulate human diseases are validated by using a set of biomarkers; however, their translatability to a clinical setting remains problematic. This review provides an overview of current strategies for human iPS cell-based drug discovery from the perspective of translational research, and discusses the importance of early consideration of clinically relevant biomarkers.
Kulakova, Liudmila; Galkin, Andrey; Chen, Catherine Z.; Southall, Noel; Marugan, Juan J.; Zheng, Wei
Giardiasis is a severe intestinal parasitic disease caused by Giardia lamblia, which inflicts many people in poor regions and is the most common parasitic infection in the United States. Current standard care drugs are associated with undesirable side effects, treatment failures, and an increasing incidence of drug resistance. As follow-up to a high-throughput screening of an approved drug library, which identified compounds lethal to G. lamblia trophozoites, we have determined the minimum lethal concentrations of 28 drugs and advanced 10 of them to in vivo studies in mice. The results were compared to treatment with the standard care drug, metronidazole, in order to identify drugs with equal or better anti-Giardia activities. Three drugs, fumagillin, carbadox, and tioxidazole, were identified. These compounds were also potent against metronidazole-resistant human G. lamblia isolates (assemblages A and B), as determined in in vitro assays. Of these three compounds, fumagillin is currently an orphan drug used within the European Union to treat microsporidiosis in immunocompromised individuals, whereas carbadox and tioxidazole are used in veterinary medicine. A dose-dependent study of fumagillin in a giardiasis mouse model revealed that the effective dose of fumagillin was ∼100-fold lower than the metronidazole dose. Therefore, fumagillin may be advanced to further studies as an alternative treatment for giardiasis when metronidazole fails. PMID:25267663
Alexandrov, Vadim; Brunner, Dani; Hanania, Taleen; Leahy, Emer
Drug testing with traditional behavioral assays constitutes a major bottleneck in the development of novel therapies. PsychoGenics developed three comprehensive highthroughtput systems, SmartCube®, NeuroCube® and PhenoCube® systems, to increase the efficiency of the drug screening and phenotyping in rodents. These three systems capture different domains of behavior, namely, cognitive, motor, circadian, social, anxiety-like, gait and others, using custom-built computer vision software and machine learning algorithms for analysis. This review exemplifies the use of the three systems and explains how they can advance drug screening with their applications to phenotyping of disease models, drug screening, selection of lead candidates, behavior-driven lead optimization, and drug repurposing. PMID:25592319
Zuniga, Edison S; Early, Julie; Parish, Tanya
There is an urgent need for new and better drugs to treat tuberculosis due to lengthy and complex treatment regimens and a rising problem of drug resistance. Drug discovery efforts have increased over the past few years, with a larger focus on modern high-throughput screening technologies. A combination of target-based approaches, with the traditional empirical means of drug identification, has been complemented by the use of target-based phenotypic screens only recently made possibly with newer genetic tools. Using these approaches, a number of promising compound series have been discovered. However, significant problems remain in developing these into drugs. This review highlights recent advances in TB drug discovery, including an overview of screening campaigns, lessons learned and future directions. PMID:25689534
Manallack, David T.; Prankerd, Richard J.; Yuriev, Elizabeth; Oprea, Tudor I.; Chalmers, David K.
While drug discovery scientists take heed of various guidelines concerning drug-like character, the influence of acid/base properties often remains under-scrutinised. Ionisation constants (pKa values) are fundamental to the variability of the biopharmaceutical characteristics of drugs and to underlying parameters such as logD and solubility. pKa values affect physicochemical properties such as aqueous solubility, which in turn influences drug formulation approaches. More importantly, absorption, distribution, metabolism, excretion and toxicity (ADMET) are profoundly affected by the charge state of compounds under varying pH conditions. Consideration of pKa values in conjunction with other molecular properties is of great significance and has the potential to be used to further improve the efficiency of drug discovery. Given the recent low annual output of new drugs from pharmaceutical companies, this review will provide a timely reminder of an important molecular property that influences clinical success. PMID:23099561
Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco
There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.
FitzGerald, Garret A
The rate of new drug approvals in the US has remained essentially constant since 1950, while the costs of drug development have soared. Many commentators question the sustainability of the current model of drug development, in which large pharmaceutical companies incur markedly escalating costs to deliver the same number of products to market. This Issue Brief summarizes the problem, describes ongoing governmental efforts to influence the process, and suggests changes in regulatory science and translational medicine that may promote more successful development of safe and effective therapeutics
Ochs, Christopher; Zheng, Ling; Gu, Huanying; Perl, Yehoshua; Geller, James; Kapusnik-Uner, Joan; Zakharchenko, Aleksandr
The National Drug File - Reference Terminology (NDF-RT) is a large and complex drug terminology. NDF-RT provides important information about clinical drugs, e.g., their chemical ingredients, mechanisms of action, dosage form and physiological effects. Within NDF-RT such information is represented using tens of thousands of roles. It is difficult to comprehend large, complex terminologies like NDF-RT. In previous studies, we introduced abstraction networks to summarize the content and structure of terminologies. In this paper, we introduce the Ingredient Abstraction Network to summarize NDF-RT's Chemical Ingredients and their associated drugs. Additionally, we introduce the Aggregate Ingredient Abstraction Network, for controlling the granularity of summarization provided by the Ingredient Abstraction Network. The Ingredient Abstraction Network is used to support the discovery of new candidate drug-drug interactions (DDIs) not appearing in First Databank, Inc.'s DDI knowledgebase.
Yan, Ming; Baran, Phil S.
A synthetic strategy has been developed that provides easy access to structurally diverse analogues of naturally occurring antibiotics, providing a fresh means of attack in the war against drug-resistant bacteria. See Article p.338
Harrigan, Jeanine A; Jacq, Xavier; Martin, Niall M; Jackson, Stephen P
More than a decade after a Nobel Prize was awarded for the discovery of the ubiquitin-proteasome system and clinical approval of proteasome and ubiquitin E3 ligase inhibitors, first-generation deubiquitylating enzyme (DUB) inhibitors are now approaching clinical trials. However, although our knowledge of the physiological and pathophysiological roles of DUBs has evolved tremendously, the clinical development of selective DUB inhibitors has been challenging. In this Review, we discuss these issues and highlight recent advances in our understanding of DUB enzymology and biology as well as technological improvements that have contributed to the current interest in DUBs as therapeutic targets in diseases ranging from oncology to neurodegeneration.
Geary, Timothy G; Conder, George A; Bishop, Bernard
Changes in economic imperatives in the pharmaceutical industry have led to a wave of consolidation, which has had the unintended side effect of shrinking the resource devoted to antiparasitic drug discovery in animal health companies. Scientific changes have altered the way in which drugs could be discovered in the future. New science and business models will need to be implemented to address the demand for innovative antiparasitic drugs in veterinary medicine. Novel drugs are needed to combat drug resistance and for currently non-addressed problems. At the center of the future for this field, however, lies the need for more support into the basic research on the biology of parasites.
Wu, Wan-Ying; Hou, Jin-Jun; Long, Hua-Li; Yang, Wen-Zhi; Liang, Jian; Guo, De-An
Over the past 30 years, China has significantly improved the drug development environment by establishing a series of policies for the regulation of new drug approval. The regulatory system for new drug evaluation and registration in China was gradually developed in accordance with international standards. The approval and registration of TCM in China became as strict as those of chemical drugs and biological products. In this review, TCM-based new drug discovery and development are introduced according to the TCM classification of nine categories.
Bauer, Renato A
Drugs that covalently bond to their biological targets have a long history in drug discovery. A look at drug approvals in recent years suggests that covalent drugs will continue to make impacts on human health for years to come. Although fraught with concerns about toxicity, the high potencies and prolonged effects achievable with covalent drugs may result in less-frequent drug dosing and in wide therapeutic margins for patients. Covalent inhibition can also dissociate drug pharmacodynamics (PD) from pharmacokinetics (PK), which can result in desired drug efficacy for inhibitors that have short systemic exposure. Evidence suggests that there is a reduced risk for the development of resistance against covalent drugs, which is a major challenge in areas such as oncology and infectious disease.
Tralau-Stewart, Cathy J; Wyatt, Colin A; Kleyn, Dominique E; Ayad, Alex
The re-focusing of pharmaceutical industry research away from early discovery activities is stimulating the development of novel models of drug discovery, notably involving academia as a 'front end'. In this article the authors explore the drivers of change, the role of new entrants (universities with specialised core facilities) and novel partnership models. If they are to be sustainable and deliver, these new models must be flexible and properly funded by industry or public funding, rewarding all partners for contributions. The introduction of an industry-like process and experienced management teams signals a revolution in discovery that benefits society by improving the value gained from publicly funded research.
Grabowski, M.; Chruszcz, M; Zimmerman, M; Kirillova, O; Minor, W
While three dimensional structures have long been used to search for new drug targets, only a fraction of new drugs coming to the market has been developed with the use of a structure-based drug discovery approach. However, the recent years have brought not only an avalanche of new macromolecular structures, but also significant advances in the protein structure determination methodology only now making their way into structure-based drug discovery. In this paper, we review recent developments resulting from the Structural Genomics (SG) programs, focusing on the methods and results most likely to improve our understanding of the molecular foundation of human diseases. SG programs have been around for almost a decade, and in that time, have contributed a significant part of the structural coverage of both the genomes of pathogens causing infectious diseases and structurally uncharacterized biological processes in general. Perhaps most importantly, SG programs have developed new methodology at all steps of the structure determination process, not only to determine new structures highly efficiently, but also to screen protein/ligand interactions. We describe the methodologies, experience and technologies developed by SG, which range from improvements to cloning protocols to improved procedures for crystallographic structure solution that may be applied in 'traditional' structural biology laboratories particularly those performing drug discovery. We also discuss the conditions that must be met to convert the present high-throughput structure determination pipeline into a high-output structure-based drug discovery system.
Grabowski, Marek; Chruszcz, Maksymilian; Zimmerman, Matthew D.; Kirillova, Olga; Minor, Wladek
While three dimensional structures have long been used to search for new drug targets, only a fraction of new drugs coming to the market has been developed with the use of a structure-based drug discovery approach. However, the recent years have brought not only an avalanche of new macromolecular structures, but also significant advances in the protein structure determination methodology only now making their way into structure-based drug discovery. In this paper, we review recent developments resulting from the Structural Genomics (SG) programs, focusing on the methods and results most likely to improve our understanding of the molecular foundation of human diseases. SG programs have been around for almost a decade, and in that time, have contributed a significant part of the structural coverage of both the genomes of pathogens causing infectious diseases and structurally uncharacterized biological processes in general. Perhaps most importantly, SG programs have developed new methodology at all steps of the structure determination process, not only to determine new structures highly efficiently, but also to screen protein/ligand interactions. We describe the methodologies, experience and technologies developed by SG, which range from improvements to cloning protocols to improved procedures for crystallographic structure solution that may be applied in “traditional” structural biology laboratories particularly those performing drug discovery. We also discuss the conditions that must be met to convert the present high-throughput structure determination pipeline into a high-output structure-based drug discovery system. PMID:19594422
Sugano, Kiyohiko; Okazaki, Arimichi; Sugimoto, Shohei; Tavornvipas, Sumitra; Omura, Atsushi; Mano, Takashi
The purposes of the review are to: a) Provide a comprehensible introduction of the-state-of-the-art sciences of solubility and dissolution, b) introduce typical technologies to assess solubility and dissolution, and c) propose the best practice strategy. The theories of solubility and dissolution required in drug discovery were reviewed especially from the view point of oral absorption. The physiological conditions in the gastrointestinal fluid in humans and animals were then briefly summarized. Technologies to assess solubility and dissolution in drug discovery were then introduced. Recently, these technologies have been improved by the laboratory automation and computational technologies. Finally, the strategies to apply these technologies for a drug discovery project were discussed.
Zheng, Mingyue; Liu, Xian; Xu, Yuan; Li, Honglin; Luo, Cheng; Jiang, Hualiang
In the past decades, China's computational drug design and discovery research has experienced fast development through various novel methodologies. Application of these methods spans a wide range, from drug target identification to hit discovery and lead optimization. In this review, we firstly provide an overview of China's status in this field and briefly analyze the possible reasons for this rapid advancement. The methodology development is then outlined. For each selected method, a short background precedes an assessment of the method with respect to the needs of drug discovery, and, in particular, work from China is highlighted. Furthermore, several successful applications of these methods are illustrated. Finally, we conclude with a discussion of current major challenges and future directions of the field.
Renaud, Jean-Paul; Chung, Chun-Wa; Danielson, U Helena; Egner, Ursula; Hennig, Michael; Hubbard, Roderick E; Nar, Herbert
Over the past 25 years, biophysical technologies such as X-ray crystallography, nuclear magnetic resonance spectroscopy, surface plasmon resonance spectroscopy and isothermal titration calorimetry have become key components of drug discovery platforms in many pharmaceutical companies and academic laboratories. There have been great improvements in the speed, sensitivity and range of possible measurements, providing high-resolution mechanistic, kinetic, thermodynamic and structural information on compound-target interactions. This Review provides a framework to understand this evolution by describing the key biophysical methods, the information they can provide and the ways in which they can be applied at different stages of the drug discovery process. We also discuss the challenges for current technologies and future opportunities to use biophysical methods to solve drug discovery problems.
Jones, Lyn H; Bunnage, Mark E
The allure of phenotypic screening, combined with the industry preference for target-based approaches, has prompted the development of innovative chemical biology technologies that facilitate the identification of new therapeutic targets for accelerated drug discovery. A chemogenomic library is a collection of selective small-molecule pharmacological agents, and a hit from such a set in a phenotypic screen suggests that the annotated target or targets of that pharmacological agent may be involved in perturbing the observable phenotype. In this Review, we describe opportunities for chemogenomic screening to considerably expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Other applications are explored, including drug repositioning, predictive toxicology and the discovery of novel pharmacological modalities.
Field, Mark C.; Horn, David; Fairlamb, Alan H.; Ferguson, Michael A. J.; Gray, David W.; Read, Kevin D.; De Rycker, Manu; Torrie, Leah S.; Wyatt, Paul G.; Wyllie, Susan; Gilbert, Ian H.
The World Health Organization recognizes human African trypanosomiasis, Chagas’ disease and the leishmaniases as neglected tropical diseases. These diseases are caused by parasitic trypanosomatids and range in severity from mild and self-curing to near invariably fatal. Public health advances have substantially decreased the impact of these diseases in recent decades, but alone will not eliminate these diseases. Here we discuss why new drugs against trypanosomatids are needed, approaches that are under investigation to develop new drugs and why the drug discovery pipeline remains essentially unfilled. Additionally, we consider the important challenges to drug discovery strategies and the new technologies that can address them. The combination of new drugs, new technologies and public health initiatives are essential for the management and hopefully eventual elimination of trypanosomatid diseases from the human population. PMID:28239154
Richette, Pascal; Garay, Ricardo
The increasing prevalence of gout has been accompanied by a growing number of patients intolerant to or with disease refractory to available urate-lowering therapies. These difficult-to-treat patients currently represent about 3 - 5% of people with gout in Europe and the United States, which highlights the need for emerging treatments to effectively lower urate levels. In this review, the authors describe the putative pharmacological targets to lower urate levels. Furthermore, the authors discuss various strategies used to discover novel molecules or to improve available drugs used to treat gout. Major advances in our understanding of urate renal transport from in vitro, animal and genetic studies could lead to the development of novel uricosuric drugs. Targeting one or several urate transporters such as urate transporter 1, organic anion transporter 4 and 10 and glucose transporter 9 is promising. Moreover, design of small molecules capable of blocking the site activity of enzymes other than xanthine oxidase and involved in the purine pathway could generate novel hypouricemic drugs. Finally, polyethylene glycol (PEGylation) can significantly extend the biological half-life of drugs and reduce antigenicity and immunogenicity of proteins. The technology has been successfully applied to an uricase (pegloticase), but the drug was immunogenic in some patients. Strategies to decrease the immunogenicity of a PEG-uricase are important for developing next-generation uricase.
Skinner, Gary M; Visscher, Koen
Single-molecule techniques offer a number of key benefits over conventional in vitro assay methods for drug screening, as they use less material and unlock the ability to observe transient states. By observing such states, it should be possible to screen for chemical compounds that isolate these steps. The benefit of this is twofold: (a) inhibitors can be found that target key phases in biochemical processes, e.g., transcription initiation; and (b) the total number of drug targets increases as many biochemical processes consist of many transient steps, e.g., transcription promoter binding, initiation, elongation, and termination. Although single-molecule methods offer exciting opportunities for new ways of discovering drugs, there are a number of obstacles to their adoption for drug screening. The main hurdle is to develop robust apparatus that will allow many thousands of individual single molecule experiments to be performed in parallel. By using recently developed integrated microfluidics technology, this hurdle may be overcome. Here, a number of potential single-molecule approaches to drug screening are presented along with a discussion of the benefits and technical obstacles that must be overcome.
Janero, David R
Research universities continue to produce new scientists capable of generating knowledge with the potential to inform disease etiology and treatment. Mounting interest of doctoral-level experimental science students in therapeutics-related research careers is discordant with the widespread lack of direct drug-discovery and development experience, let alone commercialization success, among university faculty and administrators. Likewise, the archetypical publication- and grant-fueled, principal investigator (PI)-focused academic system ("PI-stan") risks commoditization of science students pursuing their doctorates as a labor source, rendering them ill-prepared for career options related to therapeutics innovation by marginalizing their development of "beyond-the-bench" professional skills foundational to modern drug-discovery campaigns and career fluency. To militate against professionalization deficits in doctoral drug-discovery researchers, the author--a scientist-administrator-consultant with decades of discovery research and development (R&D), business, and educator experience in commercial and university settings--posits a critical need for pluridimensionality in graduate education and mentorship that extends well beyond thesis-related scientific domains/laboratory techniques to instill transferable operational-intelligence, project/people-management, and communication competencies. Specific initiatives are advocated to help enhance the doctoral science student's market competitiveness, adaptability, and navigation of the significant research, commercial, and occupational challenges associated with contemporary preclinical drug-discovery R&D.
Itoh, Yukihiro; Suzuki, Takayoshi
The first step in "drug" discovery is to find compounds binding to a potential drug target. In modern medicinal chemistry, the screening of a chemical library, structure-based drug design, and ligand-based drug design, or a combination of these methods, are generally used for identifying the desired compounds. However, they do not necessarily lead to success and there is no infallible method for drug discovery. Therefore, it is important to explore medicinal chemistry based on not only the conventional methods but also new ideas. So far, we have found various compounds as drug candidates. In these studies, some strategies based on organic chemistry have allowed us to find drug candidates, through 1) construction of a focused library using organic reactions and 2) rational design of enzyme inhibitors based on chemical reactions catalyzed by the target enzyme. Medicinal chemistry based on organic chemical reactions could be expected to supplement the conventional methods. In this review, we present drug discovery with the help of organic chemistry showing examples of our explorative studies on histone deacetylase inhibitors and lysine-specific demethylase 1 inhibitors.
Zhan, Peng; Pannecouque, Christophe; De Clercq, Erik; Liu, Xinyong
The early effectiveness of combinatorial antiretroviral therapy (cART) in the treatment of HIV infection has been compromised to some extent by rapid development of multidrug-resistant HIV strains, poor bioavailability, and cumulative toxicities, and so there is a need for alternative strategies of antiretroviral drug discovery and additional therapeutic agents with novel action modes or targets. From this perspective, we first review current strategies of antiretroviral drug discovery and optimization, with the aid of selected examples from the recent literature. We highlight the development of phosphate ester-based prodrugs as a means to improve the aqueous solubility of HIV inhibitors, and the introduction of the substrate envelope hypothesis as a new approach for overcoming HIV drug resistance. Finally, we discuss future directions for research, including opportunities for exploitation of novel antiretroviral targets, and the strategy of activation of latent HIV reservoirs as a means to eradicate the virus.
Qi, Da; King, Ross D; Hopkins, Andrew L; Bickerton, G Richard J; Soldatova, Larisa N
The paper presents an ontology for the description of Drug Discovery Investigation (DDI).This has been developed through the use of a Robot Scientist "Eve", and in consultation with industry. DDI aims to define the principle entities and the relations in the research and development phase of the drug discovery pipeline. DDI is highly transferable and extendable due to its adherence to accepted standards, and compliance with existing ontology resources. This enables DDI to be integrated with such related ontologies as the Vaccine Ontology, the Advancing Clinico-Genomic Trials on Cancer Master Ontology, etc. DDI is available at http://purl.org/ddi/wikipedia or http://purl.org/ddi/home.
Fang, Ye; Eglen, Richard M.
The past decades have witnessed significant efforts toward the development of three-dimensional (3D) cell cultures as systems that better mimic in vivo physiology. Today, 3D cell cultures are emerging, not only as a new tool in early drug discovery but also as potential therapeutics to treat disease. In this review, we assess leading 3D cell culture technologies and their impact on drug discovery, including spheroids, organoids, scaffolds, hydrogels, organs-on-chips, and 3D bioprinting. We also discuss the implementation of these technologies in compound identification, screening, and development, ranging from disease modeling to assessment of efficacy and safety profiles. PMID:28520521
Méndez-Lucio, Oscar; Medina-Franco, José L
Molecular complexity is becoming a crucial concept in drug discovery. It has been associated with target selectivity, success in progressing into clinical development and compound safety, among other factors. Multiple metrics have been developed to quantify molecular complexity and explore complexity-property relationships. However, there is no general agreement regarding how to measure this molecular feature. Herein, we have surveyed the many roles of molecular complexity in drug discovery discussing in a critical manner different quantification methods. Through the analysis of various reference compound databases, common pitfalls and workarounds of the quantification of molecular complexity are discussed.
Rodrigues, Tiago; Reker, Daniel; Welin, Martin; Caldera, Michael; Brunner, Cyrill; Gabernet, Gisela; Schneider, Petra; Walse, Björn; Schneider, Gisbert
Automated molecular de novo design led to the discovery of an innovative inhibitor of death-associated protein kinase 3 (DAPK3). An unprecedented crystal structure of the inactive DAPK3 homodimer shows the fragment-like hit bound to the ATP pocket. Target prediction software based on machine learning models correctly identified additional macromolecular targets of the computationally designed compound and the structurally related marketed drug azosemide. The study validates computational de novo design as a prime method for generating chemical probes and starting points for drug discovery.
Heath, James R; Ribas, Antoni; Mischel, Paul S
The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed.
Wild, David J; Wiggins, Gary D
Chemoinformatics is rapidly becoming a core part of drug design informatics, yet the educational opportunities in the field are currently limited. This article reviews the academic and commercial educational programs that are available in chemoinformatics, considers the current challenges and takes a look at emerging trends, such as distance education and intensive short courses.
Lovitt, Carrie J; Shelper, Todd B; Avery, Vicky M
Cell culture models have been at the heart of anti-cancer drug discovery programs for over half a century. Advancements in cell culture techniques have seen the rapid evolution of more complex in vitro cell culture models investigated for use in drug discovery. Three-dimensional (3D) cell culture research has become a strong focal point, as this technique permits the recapitulation of the tumor microenvironment. Biologically relevant 3D cellular models have demonstrated significant promise in advancing cancer drug discovery, and will continue to play an increasing role in the future. In this review, recent advances in 3D cell culture techniques and their application in tumor modeling and anti-cancer drug discovery programs are discussed. The topics include selection of cancer cells, 3D cell culture assays (associated endpoint measurements and analysis), 3D microfluidic systems and 3D bio-printing. Although advanced cancer cell culture models and techniques are becoming commonplace in many research groups, the use of these approaches has yet to be fully embraced in anti-cancer drug applications. Furthermore, limitations associated with analyzing information-rich biological data remain unaddressed.
Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong
Motivation: Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. Results: To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e−4) and 81.3% (P < e−12) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn’s disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn’s disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn’s disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. Availability and implementation: nlp
Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong
Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e(-4)) and 81.3% (P < e(-12)) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn's disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn's disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn's disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. nlp. edu/public/data/DMN © The Author 2015. Published by Oxford University Press.
Lin, Guimiao; Yin, Feng; Yong, Ken-Tye
The rapid development of drug discovery today is inseparable from the interaction of advanced particle technologies and new drug synthesis protocols. Quantum dots (QDs) are regarded as a unique class of fluorescent labels, with unique optical properties such as high brightness and long-term colloidal and optical stability; these are suitable for optical imaging, drug delivery and optical tracking, fluorescence immunoassay and other medicinal applications. More importantly, QD possesses a rich surface chemistry property that is useful for incorporating various drug molecules, targeting ligands, and additional contrast agents (e.g., MRI, PET, etc.) onto the nanoparticle surface for achieving targeted and traceable drug delivery therapy at both cellular and systemic levels. In recent times, the advancement of QD technology has promoted the use of functionalized nanocrystals for in vivo applications. Such research is paving the way for drug discovery using various bioconjugated QD formulations. In this editorial, the authors highlight the current research progress and future applications of QDs in drug discovery.
Zhang, Ming-Qiang; Wilkinson, Barrie
Although a very useful guideline for orally bioavailable small-molecule drug design, the 'rule-of-five' (also known as 'Lipinski's rule of drug-likeness') has to some extent been overemphasized. Firstly, only 51% of all FDA-approved small-molecule drugs are both used orally and comply with the 'rule-of-five'. This does not even include the increasing number of biologicals of which several have reached 'blockbuster' status. Secondly, it does not cover natural product and semisynthetic natural product drugs, which constitute over one-third of all marketed small-molecule drugs. A more balanced and programmatic approach to drug discovery should be more productive than to rely on an overemphasis of 'rule-of-five' compliance. Rather it should consider proactively the development of parenteral drugs in parallel to oral drugs and to consider the development of therapeutic antibodies in parallel to small-molecule drugs. These are particularly relevant for efforts against 'first-in-class' and/or particularly challenging targets such as proteases and those involving protein-protein interactions. In addition, more effort should be invested in natural product research. Emerging novel technologies such as synthetic biology (genetic engineering of living organisms to produce small-molecule therapeutics) may address several challenging issues of natural product-based drug discovery including synthetic feasibility and ligand efficiency.
Pettit, Robin K
Soil has the largest population of microbes of any habitat, but only about 0.3% of soil microbes are cultivable with current techniques. Cultured soil microbes have been an incredibly productive source of drugs, for example the cancer chemotherapeutics doxorubicin hydrochloride, bleomycin, daunorubicin and mitomycin. Unfortunately, the current yield of new drugs from soil microbes is low due to repeated cultivation of the same small fraction of cultivable microbes. Uncultured soil species represent a tremendous untapped resource of new antineoplastic agents. Methods have recently been developed to access the diversity of secondary metabolites from uncultured soil microbes. Briefly, total DNA is extracted from soil samples, purified, partially digested, and fragments inserted into vectors for expression in readily fermented microbes such as Escherichia coli. Clones expressing enzymatic and antibiotic activities that are encoded by novel sequences have been reported.
Poeta, Maurizio Del
This Special Issue is designed to highlight the latest research and development on new antifungal compounds with mechanisms of action different from the ones of polyenes, azoles, and echinocandins. The papers presented here highlight new pathways and targets that could be exploited for the future development of new antifungal agents to be used alone or in combination with existing antifungals. A computational model for better predicting antifungal drug resistance is also presented. PMID:28058254
Minie, Mark; Chopra, Gaurav; Sethi, Geetika; Horst, Jeremy; White, George; Roy, Ambrish; Hatti, Kaushik; Samudrala, Ram
The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound–proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12–25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 ‘high value’ predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering. PMID:24980786
Cain, Ricky; Narramore, Sarah; McPhillie, Martin; Simmons, Katie; Fishwick, Colin W G
In recent years bacterial resistance has been observed against many of our current antibiotics, for instance most worryingly against the cephalosporins which are typically the last line of defence against many bacterial infections. Additionally the failure of high throughput screening in the discovery of new antibacterial drug leads has led to a decline in the number of antibacterial agents reaching the market. Alternative methods of drug discovery including structure based drug design are needed to meet the threats caused by the emergence of resistance. In this review we explore the latest advancements in the identification of new antibacterial agents through the use of a number of structure based drug design programs. Copyright © 2014 Elsevier Inc. All rights reserved.
Among the fields of expertise required to develop drugs successfully, biochemistry holds a key position in drug discovery at the interface between chemistry, structural biology and cell biology. However, taking the example of protein kinases, it appears that biochemical assays are mostly used in the pharmaceutical industry to measure compound potency and/or selectivity. This limited use of biochemistry is surprising, given that detailed biochemical analyses are commonly used in academia to unravel molecular recognition processes. In this article, I show that biochemistry can provide invaluable information on the dynamics and energetics of compound-target interactions that cannot be obtained on the basis of potency measurements and structural data. Therefore, an extensive use of biochemistry in drug discovery could facilitate the identification and/or development of new drugs.
Selimović, Seila; Dokmeci, Mehmet R; Khademhosseini, Ali
The current drug discovery process is arduous and costly, and a majority of the drug candidates entering clinical trials fail to make it to the marketplace. The standard static well culture approaches, although useful, do not fully capture the intricate in vivo environment. By merging the advances in microfluidics with microfabrication technologies, novel platforms are being introduced that lead to the creation of organ functions on a single chip. Within these platforms, microengineering enables precise control over the cellular microenvironment, whereas microfluidics provides an ability to perfuse the constructs on a chip and to connect individual sections with each other. This approach results in microsystems that may better represent the in vivo environment. These organ-on-a-chip platforms can be utilized for developing disease models as well as for conducting drug testing studies. In this article, we highlight several key developments in these microscale platforms for drug discovery applications. Copyright © 2013 Elsevier Ltd. All rights reserved.
Richon, Victoria M
Over the past decade, the number of new therapies developed for the treatment of rare diseases continues to increase. The most rapid growth has been in the development of new drugs for oncology indications. One focus in drug discovery for oncology indications is the development of targeted therapies for select patient subgroups characterized by genetic alterations. The identification of these patient subgroups has increased in the past decade and has resulted in a corresponding increase in the development of new drugs for genetically defined patient subgroups. As an example of the development of new therapeutics for rare indications, I describe here the drug discovery efforts leading to the development of DOT1L inhibitors for the treatment of MLL-rearranged leukemia.
Van Eldik, Linda J; Koppal, Tanuja; Watterson, D Martin
The drug discovery and the drug development processes represent a continuum of recursive activities that range from initial drug target identification to final Food and Drug Administration approval and marketing of a new therapeutic. Drug discovery, as its name implies, is more exploratory and less focused in many cases, whereas drug development has a clinically defined endpoint and a specific disease goal. Academia has historically made major contributions to this process at the early discovery phases. However, current trends in the organization of the pharmaceutical industry suggest an expanded role for academia in the near future. Megamergers among major pharmaceutical corporations indicate their movement toward a focus on end-stage clinical trials, manufacturing, and marketing. There has been a parallel increase in outsourcing of intermediate steps to specialty small pharmaceutical, biotechnology, and contract service companies. The new paradigm suggests that academia will play an increasingly important role at the proof-of-principle stage of basic and clinical drug discovery research, in training the future skilled work force, and in close partnerships with small pharmaceutical and biotechnology companies. However, academic drug discovery research faces a set of barriers to progress, the relative importance of which varies with the home institution and the details of the research area. These barriers fall into four general categories: (1) the historical administrative structure and environment of academia; (2) the structure and emphasis of peer review panels that control research funding by government and private agencies; (3) the organization and operation of the academic infrastructure; and (4) the structure and availability of specialized resources and information management. Selected examples of barriers to drug discovery and drug development research and training in academia are presented, as are some specific recommendations designed to minimize or
Hoelder, Swen; Clarke, Paul A.; Workman, Paul
The discovery and development of small molecule cancer drugs has been revolutionised over the last decade. Most notably, we have moved from a one-size-fits-all approach that emphasized cytotoxic chemotherapy to a personalised medicine strategy that focuses on the discovery and development of molecularly targeted drugs that exploit the particular genetic addictions, dependencies and vulnerabilities of cancer cells. These exploitable characteristics are increasingly being revealed by our expanding understanding of the abnormal biology and genetics of cancer cells, accelerated by cancer genome sequencing and other high-throughput genome-wide campaigns, including functional screens using RNA interference. In this review we provide an overview of contemporary approaches to the discovery of small molecule cancer drugs, highlighting successes, current challenges and future opportunities. We focus in particular on four key steps: Target validation and selection; chemical hit and lead generation; lead optimization to identify a clinical drug candidate; and finally hypothesis-driven, biomarker-led clinical trials. Although all of these steps are critical, we view target validation and selection and the conduct of biology-directed clinical trials as especially important areas upon which to focus to speed progress from gene to drug and to reduce the unacceptably high attrition rate during clinical development. Other challenges include expanding the envelope of druggability for less tractable targets, understanding and overcoming drug resistance, and designing intelligent and effective drug combinations. We discuss not only scientific and technical challenges, but also the assessment and mitigation of risks as well as organizational, cultural and funding problems for cancer drug discovery and development, together with solutions to overcome the ‘Valley of Death’ between basic research and approved medicines. We envisage a future in which addressing these challenges will
McCammon, J. Andrew
This lecture will provide a general introduction to some of the ways that modern computational physics is contributing to the discovery of new pharmaceuticals, with special emphasis on drugs for infectious diseases. The basic sciences and computing technologies involved have advanced to the point that physics-based simulations of drug targets are now yielding truly valuable suggestions for new compounds. Supported in part by NSF, NIH, HHMI, CTBP, NBCR, and SDSC.
Potterat, Olivier; Hamburger, Matthias
An overview is given on current efforts in drug development based on plant-derived natural products. Emphasis is on projects which have advanced to clinical development. Therapeutic areas covered include cancer, viral infections including HIV, malaria, inflammatory diseases, nociception and vaccine adjuvants, metabolic disorders, and neurodegenerative diseases. Aspects which are specific to plant-based drug discovery and development are also addressed, such as supply issues in the commercial development, and the Convention on Biological Diversity.
Hoelder, Swen; Clarke, Paul A; Workman, Paul
The discovery and development of small molecule cancer drugs has been revolutionised over the last decade. Most notably, we have moved from a one-size-fits-all approach that emphasized cytotoxic chemotherapy to a personalised medicine strategy that focuses on the discovery and development of molecularly targeted drugs that exploit the particular genetic addictions, dependencies and vulnerabilities of cancer cells. These exploitable characteristics are increasingly being revealed by our expanding understanding of the abnormal biology and genetics of cancer cells, accelerated by cancer genome sequencing and other high-throughput genome-wide campaigns, including functional screens using RNA interference. In this review we provide an overview of contemporary approaches to the discovery of small molecule cancer drugs, highlighting successes, current challenges and future opportunities. We focus in particular on four key steps: Target validation and selection; chemical hit and lead generation; lead optimization to identify a clinical drug candidate; and finally hypothesis-driven, biomarker-led clinical trials. Although all of these steps are critical, we view target validation and selection and the conduct of biology-directed clinical trials as especially important areas upon which to focus to speed progress from gene to drug and to reduce the unacceptably high attrition rate during clinical development. Other challenges include expanding the envelope of druggability for less tractable targets, understanding and overcoming drug resistance, and designing intelligent and effective drug combinations. We discuss not only scientific and technical challenges, but also the assessment and mitigation of risks as well as organizational, cultural and funding problems for cancer drug discovery and development, together with solutions to overcome the 'Valley of Death' between basic research and approved medicines. We envisage a future in which addressing these challenges will enhance
Drinkwater, Nyssa; McGowan, Sheena
Despite a century of control and eradication campaigns, malaria remains one of the world's most devastating diseases. Our once-powerful therapeutic weapons are losing the war against the Plasmodium parasite, whose ability to rapidly develop and spread drug resistance hamper past and present malaria-control efforts. Finding new and effective treatments for malaria is now a top global health priority, fuelling an increase in funding and promoting open-source collaborations between researchers and pharmaceutical consortia around the world. The result of this is rapid advances in drug discovery approaches and technologies, with three major methods for antimalarial drug development emerging: (i) chemistry-based, (ii) target-based, and (iii) cell-based. Common to all three of these approaches is the unique ability of structural biology to inform and accelerate drug development. Where possible, SBDD (structure-based drug discovery) is a foundation for antimalarial drug development programmes, and has been invaluable to the development of a number of current pre-clinical and clinical candidates. However, as we expand our understanding of the malarial life cycle and mechanisms of resistance development, SBDD as a field must continue to evolve in order to develop compounds that adhere to the ideal characteristics for novel antimalarial therapeutics and to avoid high attrition rates pre- and post-clinic. In the present review, we aim to examine the contribution that SBDD has made to current antimalarial drug development efforts, covering hit discovery to lead optimization and prevention of parasite resistance. Finally, the potential for structural biology, particularly high-throughput structural genomics programmes, to identify future targets for drug discovery are discussed.
Shon, John; Ohkawa, Hitomi; Hammer, Juergen
Large pharmaceutical companies annually invest tens to hundreds of millions of US dollars in research informatics to support their early drug discovery processes. Traditionally, most of these investments are designed to increase the efficiency of drug discovery. The introduction of do-it-yourself scientific workflow platforms has enabled research informatics organizations to shift their efforts toward scientific innovation, ultimately resulting in a possible increase in return on their investments. Unlike the handling of most scientific data and application integration approaches, researchers apply scientific workflows to in silico experimentation and exploration, leading to scientific discoveries that lie beyond automation and integration. This review highlights some key requirements for scientific workflow environments in the pharmaceutical industry that are necessary for increasing research productivity. Examples of the application of scientific workflows in research and a summary of recent platform advances are also provided.
Breyer, Matthew D.; Look, A. Thomas; Cifra, Alessandra
ABSTRACT Model systems, including laboratory animals, microorganisms, and cell- and tissue-based systems, are central to the discovery and development of new and better drugs for the treatment of human disease. In this issue, Disease Models & Mechanisms launches a Special Collection that illustrates the contribution of model systems to drug discovery and optimisation across multiple disease areas. This collection includes reviews, Editorials, interviews with leading scientists with a foot in both academia and industry, and original research articles reporting new and important insights into disease therapeutics. This Editorial provides a summary of the collection's current contents, highlighting the impact of multiple model systems in moving new discoveries from the laboratory bench to the patients' bedsides. PMID:26438689
Yuan, William; Jiang, Dadi; Nambiar, Dhanya K; Liew, Lydia P; Hay, Michael Patrick; Bloomstein, Joshua; Lu, Peter; Turner, Brandon; Le, Quynh-The; Tibshirani, Robert; Khatri, Purvesh; Moloney, Mark Gerard; Koong, Albert C
We describe a new library generation method, Machine-based Identification of Molecules Inside Characterized Space (MIMICS) that generates sets of molecules inspired by a text-based input. MIMICS-generated libraries were found to preserve distributions of properties while simultaneously increasing structural diversity. Newly identified MIMICS-generated compounds were found to be bioactive as inhibitors of specific components of the unfolded protein response (UPR) and the VEGFR2 pathway in cell-based assays, thus confirming that applicability of this methodology towards drug design applications. Wider application of MIMICS could facilitate the efficient utilization of chemical space.
Tan, Yuxiang; Hu, Yong; Liu, Xiaoxiao; Yin, Zhinan; Chen, Xue-Wen; Liu, Mei
Adverse drug reactions (ADRs) are a major public health concern, causing over 100,000 fatalities in the United States every year with an annual cost of $136 billion. Early detection and accurate prediction of ADRs is thus vital for drug development and patient safety. Multiple scientific disciplines, namely pharmacology, pharmacovigilance, and pharmacoinformatics, have been addressing the ADR problem from different perspectives. With the same goal of improving drug safety, this article summarizes and links the research efforts in the multiple disciplines into a single framework from comprehensive understanding of the interactions between drugs and biological system and the identification of genetic and phenotypic predispositions of patients susceptible to higher ADR risks and finally to the current state of implementation of medication-related decision support systems. We start by describing available computational resources for building drug-target interaction networks with biological annotations, which provides a fundamental knowledge for ADR prediction. Databases are classified by functions to help users in selection. Post-marketing surveillance is then introduced where data-driven approach can not only enhance the prediction accuracy of ADRs but also enables the discovery of genetic and phenotypic risk factors of ADRs. Understanding genetic risk factors for ADR requires well organized patient genetics information and analysis by pharmacogenomic approaches. Finally, current state of clinical decision support systems is presented and described how clinicians can be assisted with the integrated knowledgebase to minimize the risk of ADR. This review ends with a discussion of existing challenges in each of disciplines with potential solutions and future directions.
Introduction There is an immediate need for functional and molecular studies to decipher differences between disease and “normal” settings to identify large quantities of validated targets with the highest therapeutic utilities. Furthermore, drug mechanism of action and biomarkers to predict drug efficacy and safety need to be identified for effective design of clinical trials, decreasing attrition rates, regulatory agency approval process and drug repositioning. By expanding the power of genetics and pharmacogenetics studies, next generation nucleic acid sequencing technologies have started to play an important role in all stages of drug discovery. Areas covered This article reviews the first and second generation sequencing technologies (SGSTs) and challenges they pose to biomedicine. The article then focuses on the emerging third generation sequencing technologies (TGSTs), their technological foundations and potential contributions to drug discovery. Expert Opinion Despite the scientific and commercial success of SGSTs, the goal of rapid, comprehensive and unbiased sequencing of nucleic acids has not been achieved. TGSTs promise to increase sequencing throughput and read lengths, decrease costs, run times and error rates, eliminate biases inherent in SGSTs, and offer capabilities beyond nucleic acid sequencing. Such changes will have positive impact in all sequencing applications to drug discovery. PMID:22468954
Chatelain, Eric; Ioset, Jean-Robert
New models of drug discovery have been developed to overcome the lack of modern and effective drugs for neglected diseases such as human African trypanosomiasis (HAT; sleeping sickness), leishmaniasis, and Chagas disease, which have no financial viability for the pharmaceutical industry. With the purpose of combining the skills and research capacity in academia, pharmaceutical industry, and contract researchers, public-private partnerships or product development partnerships aim to create focused research consortia that address all aspects of drug discovery and development. These consortia not only emulate the projects within pharmaceutical and biotechnology industries, eg, identification and screening of libraries, medicinal chemistry, pharmacology and pharmacodynamics, formulation development, and manufacturing, but also use and strengthen existing capacity in disease-endemic countries, particularly for the conduct of clinical trials. The Drugs for Neglected Diseases initiative (DNDi) has adopted a model closely related to that of a virtual biotechnology company for the identification and optimization of drug leads. The application of this model to the development of drug candidates for the kinetoplastid infections of HAT, Chagas disease, and leishmaniasis has already led to the identification of new candidates issued from DNDi's own discovery pipeline. This demonstrates that the model DNDi has been implementing is working but its DNDi, neglected diseases sustainability remains to be proven.
Wells, Timothy N C; Willis, Paul; Burrows, Jeremy N; Hooft van Huijsduijnen, Rob
There is a growing consensus that drug discovery thrives in an open environment. Here, we describe how the malaria community has embraced four levels of open data - open science, open innovation, open access and open source - to catalyse the development of new medicines, and consider principles that could enable open data approaches to be applied to other disease areas.
Guo, Dong; Heitman, Laura H; IJzerman, Adriaan P
Traditionally structure-activity/affinity relationships (SAR) have dominated research in medicinal chemistry. However, structure-kinetics relationships (SKR) can be very informative too. In this viewpoint we explore the molecular determinants of binding kinetics and discuss challenges for future binding kinetics studies. A scheme for future kinetics-directed drug design and discovery is also proposed.
Magedov, I. V.; Kornienko, A.
Multicomponent reactions are emerging as a powerful tool in alkaloid-based drug discovery. This Highlight describes several recent (all published in 2011) examples of the employment of multicomponent reactions for the synthesis of biologically active alkaloids and their medicinally relevant analogues. PMID:27917001
Brady, Linda S; Potter, William Z
Precompetitive public-private partnerships (PPPs) have the potential to improve psychiatric drug discovery by addressing gaps in the research and development pipeline such as the identification and validation of new targets, models, biomarkers and disease phenotyping. PPPs are a model to strategically bring together expertise, in-kind support and funding from multiple public and private sector partners. This editorial describes selected case examples of established and emerging public-private consortia in the United States and Europe that provide tools, methods or resources to accelerate central nervous system (CNS) drug discovery. The authors provides a listing of public-private consortia projects that focus on the CNS, the stage of the drug discovery pipeline that they address, diseases, deliverables provided and current consortia partners. Some of the projects undertaken by PPPs in the area of CNS drug discovery and development are beginning to make tools, resources and data publicly available. Only a few PPPs have delivered enough to extract lessons learned. These include building alignment across a wide group of stakeholders, engaging advocacy groups and funding commitments for a minimum of 5 years.
Andrei, Sebastian A; Sijbesma, Eline; Hann, Michael; Davis, Jeremy; O'Mahony, Gavin; Perry, Matthew W D; Karawajczyk, Anna; Eickhoff, Jan; Brunsveld, Luc; Doveston, Richard G; Milroy, Lech-Gustav; Ottmann, Christian
PPIs are involved in every disease and specific modulation of these PPIs with small molecules would significantly improve our prospects of developing therapeutic agents. Both industry and academia have engaged in the identification and use of PPI inhibitors. However in comparison, the opposite strategy of employing small-molecule stabilizers of PPIs is underrepresented in drug discovery. Areas covered: PPI stabilization has not been exploited in a systematic manner. Rather, this concept validated by a number of therapeutically used natural products like rapamycin and paclitaxel has been shown retrospectively to be the basis of the activity of synthetic molecules originating from drug discovery projects among them lenalidomide and tafamidis. Here, the authors cover the growing number of synthetic small-molecule PPI stabilizers to advocate for a stronger consideration of this as a drug discovery approach. Expert opinion: Both the natural products and the growing number of synthetic molecules show that PPI stabilization is a viable strategy for drug discovery. There is certainly a significant challenge to adapt compound libraries, screening techniques and downstream methodologies to identify, characterize and optimize PPI stabilizers, but the examples of molecules reviewed here in our opinion justify these efforts.
Rylova, Gabriela; Ozdian, Tomas; Varanasi, Lakshman; Soural, Miroslav; Hlavac, Jan; Holub, Dusan; Dzubak, Petr; Hajduch, Marian
Target discovery using the molecular approach, as opposed to the more traditional systems approach requires the study of the cellular or biological process underlying a condition or disease. The approaches that are employed by the "bench" scientist may be genetic, genomic or proteomic and each has its rightful place in the drug-target discovery process. Affinity-based proteomic techniques currently used in drug-discovery draw upon several disciplines, synthetic chemistry, cell-biology, biochemistry and mass spectrometry. An important component of such techniques is the probe that is specifically designed to pick out a protein or set of proteins from amongst the varied thousands in a cell lysate. A second component, that is just as important, is liquid-chromatography tandem massspectrometry (LC-MS/MS). LC-MS/MS and the supporting theoretical framework has come of age and is the tool of choice for protein identification and quantification. These proteomic tools are critical to maintaining the drug-candidate supply, in the larger context of drug discovery.
Grandjean, Nicolas; Charpiot, Brigitte; Pena, Carlos Andres; Peitsch, Manuel C
Patents are a major source of information in drug discovery and, when properly processed and analyzed, can yield a wealth of information on competitors activities, R&D trends, emerging fields, collaborations, among others. This review discusses the current state-of-the-art in textual data analysis and exploration methods as applied to patent analysis.:
Oz, Helieh S.
Toxoplasmosis, an infectious and inflammatory syndrome, is one of the most important foodborne diseases causing hospitalization and death in U.S.A. Toxoplasma infects nucleated cells including pancreatic and destroys the β cells. Toxoplasma is a Category B classified infection by CDC and NIH, which once infected the organisms reside in tissues in cysts form for the host’s lifelong awaiting reactivation. Congenital toxoplasmosis occurs by transplacental transmission during maternal infection or reactivation of organisms and manifests with spontaneous abortion, or severe physical and mental defects. Currently, there is no safe and effective therapeutic modality against congenital toxoplasmosis or the persistent chronic infection. Here, toxoplasmosis and possible involvement of infection in induction of pancreatitis, and an experimental drug efficacy is discussed. PMID:25530920
Tsopelas, Fotios; Giaginis, Constantinos; Tsantili-Kakoulidou, Anna
Lipophilicity, expressed as the octanol-water partition coefficient, constitutes the most important property in drug action, influencing both pharmacokinetic and pharmacodynamics processes as well as drug toxicity. On the other hand, biomimetic properties defined as the retention outcome on HPLC columns containing a biological relevant agent, provide a considerable advance for rapid experimental - based estimation of ADME properties in early drug discovery stages. Areas covered: This review highlights the paramount importance of lipophilicity in almost all aspects of drug action and safety. It outlines problems brought about by high lipophilicity and provides an overview of the drug-like metrics which incorporate lower limits or ranges of logP. The fundamental factors governing lipophilicity are compared to those involved in phospholipophilicity, assessed by Immobilized Artificial Membrane Chromatography (IAM). Finally, the contribution of biomimetic properties to assess plasma protein binding is evaluated. Expert opinion: Lipophilicity and biomimetic properties have important distinct and overlapping roles in supporting the drug discovery process. Lipophilicity is unique in early drug design for library screening and for the identification of the most promising compounds to start with, while biomimetic properties are useful for the experimentally-based evaluation of ADME properties for the synthesized novel compounds, supporting the prioritization of drug candidates and guiding further synthesis.
Zou, Jun; Zheng, Ming-Wu; Li, Gen; Su, Zhi-Guang
Systems biology is in an exponential development stage in recent years and has been widely utilized in biomedicine to better understand the molecular basis of human disease and the mechanism of drug action. Here, we discuss the fundamental concept of systems biology and its two computational methods that have been commonly used, that is, network analysis and dynamical modeling. The applications of systems biology in elucidating human disease are highlighted, consisting of human disease networks, treatment response prediction, investigation of disease mechanisms, and disease-associated gene prediction. In addition, important advances in drug discovery, to which systems biology makes significant contributions, are discussed, including drug-target networks, prediction of drug-target interactions, investigation of drug adverse effects, drug repositioning, and drug combination prediction. The systems biology methods and applications covered in this review provide a framework for addressing disease mechanism and approaching drug discovery, which will facilitate the translation of research findings into clinical benefits such as novel biomarkers and promising therapies.
Harris, Claire L
The complement system is best known for its role in innate immunity, providing a first line of defence against infection, maintaining tissue homeostasis by flagging apoptotic cells and debris for removal, and orchestrating crosstalk between adaptive and innate immunity. In a growing number of diseases, complement is known to drive pathogenesis or to contribute as an inflammatory amplifier of a disease trigger. Association of complement with common and devastating diseases has driven an upsurge in complement drug discovery, but despite a wealth of knowledge in the complexities of the cascade, and many decades of effort, very few drugs have progressed to late-stage clinical studies. The reasons for this are becoming clear with difficulties including high target concentration and turnover, lack of clarity around disease mechanism and unwanted side effects. Lessons learnt from drugs which are either approved, or are currently in late-stage development, or have failed and dropped off the drug development landscape, have been invaluable to drive a new generation of innovative drugs which are progressing through clinical development. In this review, the challenges associated with complement drug discovery are discussed and the current drug development landscape is reviewed. The latest approaches to improve drug characteristics are explored and those agents which employ these technologies to improve accessibility to patients are highlighted.
Brown, David G; Shotton, Elizabeth J
Structure-based drug design has become a key tool for the development of novel drugs. The process involves elucidating the three-dimensional structure of the potential drug molecule bound to the target protein that has been identified as playing a key role in the disease state. Using this three-dimensional information facilitates the process of making improvements to the potential drug molecule by highlighting existing and possible new interactions within the binding site. This knowledge is used to inform increases in potency and selectivity of the molecules as well as to help improve other drug-like properties. The speed and numbers of samples that can be studied, combined with the improved resolution of the structures that can be obtained using synchrotron radiation, have had a significant impact on the utilization of crystallography in the drug discovery process.
Alonso-Padilla, Julio; Rodríguez, Ana
The discovery of new therapeutic options against Trypanosoma cruzi, the causative agent of Chagas disease, stands as a fundamental need. Currently, there are only two drugs available to treat this neglected disease, which represents a major public health problem in Latin America. Both available therapies, benznidazole and nifurtimox, have significant toxic side effects and their efficacy against the life-threatening symptomatic chronic stage of the disease is variable. Thus, there is an urgent need for new, improved anti-T. cruzi drugs. With the objective to reliably accelerate the drug discovery process against Chagas disease, several advances have been made in the last few years. Availability of engineered reporter gene expressing parasites triggered the development of phenotypic in vitro assays suitable for high throughput screening (HTS) as well as the establishment of new in vivo protocols that allow faster experimental outcomes. Recently, automated high content microscopy approaches have also been used to identify new parasitic inhibitors. These in vitro and in vivo early drug discovery approaches, which hopefully will contribute to bring better anti-T. cruzi drug entities in the near future, are reviewed here.
Batra, Ankita S; Greenwood, Wendy
Despite remarkable advances in our understanding of the drivers of human malignancies, new targeted therapies often fail to show sufficient efficacy in clinical trials. Indeed, the cost of bringing a new agent to market has risen substantially in the last several decades, in part fuelled by extensive reliance on preclinical models that fail to accurately reflect tumour heterogeneity. To halt unsustainable rates of attrition in the drug discovery process, we must develop a new generation of preclinical models capable of reflecting the heterogeneity of varying degrees of complexity found in human cancers. Patient-derived tumour xenograft (PDTX) models prevail as arguably the most powerful in this regard because they capture cancer’s heterogeneous nature. Herein, we review current breast cancer models and their use in the drug discovery process, before discussing best practices for developing a highly annotated cohort of PDTX models. We describe the importance of extensive multidimensional molecular and functional characterisation of models and combination drug–drug screens to identify complex biomarkers of drug resistance and response. We reflect on our own experiences and propose the use of a cost-effective intermediate pharmacogenomic platform (the PDTX-PDTC platform) for breast cancer drug and biomarker discovery. We discuss the limitations and unanswered questions of PDTX models; yet, still strongly envision that their use in basic and translational research will dramatically change our understanding of breast cancer biology and how to more effectively treat it. PMID:27702751
De Backer, Marianne D; Van Dijck, Patrick
Antifungal drug discovery is starting to benefit from the enormous advances in the genomics field, which have occurred in the past decade. As traditional drug screening on existing targets is not delivering the long-awaited potent antifungals, efforts to use novel genetics and genomics-based strategies to aid in the discovery of novel drug targets are gaining increased importance. The current paradigm in antifungal drug target discovery focuses on basically two main classes of targets to evaluate: genes essential for viability and virulence or pathogenicity factors. Here we report on recent advances in genetics and genomics-based technologies that will allow us not only to identify and validate novel fungal drug targets, but hopefully in the longer run also to discover potent novel therapeutic agents. Fungal pathogens have typically presented significant obstacles when subjected to genetics, but the creativity of scientists in the anti-infectives field and the cross-talk with scientists in other areas is now yielding exciting new tools and technologies to tackle the problem of finding potent, specific and non-toxic antifungal therapeutics.
Alonso-Padilla, Julio; Rodríguez, Ana
The discovery of new therapeutic options against Trypanosoma cruzi, the causative agent of Chagas disease, stands as a fundamental need. Currently, there are only two drugs available to treat this neglected disease, which represents a major public health problem in Latin America. Both available therapies, benznidazole and nifurtimox, have significant toxic side effects and their efficacy against the life-threatening symptomatic chronic stage of the disease is variable. Thus, there is an urgent need for new, improved anti–T. cruzi drugs. With the objective to reliably accelerate the drug discovery process against Chagas disease, several advances have been made in the last few years. Availability of engineered reporter gene expressing parasites triggered the development of phenotypic in vitro assays suitable for high throughput screening (HTS) as well as the establishment of new in vivo protocols that allow faster experimental outcomes. Recently, automated high content microscopy approaches have also been used to identify new parasitic inhibitors. These in vitro and in vivo early drug discovery approaches, which hopefully will contribute to bring better anti–T. cruzi drug entities in the near future, are reviewed here. PMID:25474364
Ortega, Santiago Schiaffino; Cara, Luisa Carlota López; Salvador, María Kimatrai
The process of bringing new and innovative drugs, from conception and synthesis through to approval on the market can take the pharmaceutical industry 8-15 years and cost approximately $1.8 billion. Two key technologies are improving the hit-to-drug timeline: high-throughput screening (HTS) and rational drug design. In the latter case, starting from some known ligand-based or target-based information, a lead structure will be rationally designed to be tested in vitro or in vivo. Computational methods are part of many drug discovery programs, including the assessment of ADME (absorption-distribution-metabolism-excretion) and toxicity (ADMET) properties of compounds at the early stages of discovery/development with impressive results. The aim of this paper is to review, in a simple way, some of the most popular strategies used by modelers and some successful applications on computational chemistry to raise awareness of its importance and potential for an actual multidisciplinary drug discovery process.
A decline in the productivity of the pharmaceutical industry research and development (R&D) pipeline has highlighted the need to reconsider the classical strategies of drug discovery and development, which are based on internal resources, and to identify new means to improve the drug discovery process. Accepting that the combination of internal and external ideas can improve innovation, ways to access external innovation, that is, opening projects to external contributions, have recently been sought. In this review, the authors look at a number of external innovation opportunities. These include increased interactions with academia via academic centers of excellence/innovation centers, better communication on projects using crowdsourcing or social media and new models centered on external providers such as built-to-buy startups or virtual pharmaceutical companies. The buzz for accessing external innovation relies on the pharmaceutical industry's major challenge to improve R&D productivity, a conjuncture favorable to increase interactions with academia and new business models supporting access to external innovation. So far, access to external innovation has mostly been considered during early stages of drug development, and there is room for enhancement. First outcomes suggest that external innovation should become part of drug development in the long term. However, the balance between internal and external developments in drug discovery can vary largely depending on the company strategies.
Thiazolidinedione (TZD) is a powerful insulin sensitizer in the treatment of type 2 diabetes. It acts as a ligand to the nuclear receptor PPARγ (peroxisome proliferator-activated receptor-gamma) and induces transcription of PPARγ responsive genes. TZD controls lipid synthesis and storage in adipose tissue, liver and many other tissues through PPARγ. Derivatives of TZD, such as rosiglitazone (Avandia) and pioglitazone (Actos), are more powerful than metformin or berberine in insulin sensitization. Although they have common side effects such as weight gain and edema, these did not influence the side effects in general. However, recent findings of risk for congestive heart failure and bladder cancer have indeed significantly impaired their future in many countries. European countries have prohibited those drugs and in 2011, US will terminate application of rosiglitazone in clinics and hospitals. The multiple country actions may mark the end of TZD era. As a result, there is a strong demand for identification of TZD substitute in the treatment of type 2 diabetes. In this regard, literature about PPARγ ligands and potential TZD substitute are reviewed in this article. Histone deacetylase (HDAC) inhibitor is emphasized as a new class of insulin sensitizer here. Regulators of SIRT1, CREB, NO, p38, ERK and Cdk5 are discussed in the activation of PPARγ.
Esch, Eric W.; Bahinski, Anthony; Huh, Dongeun
Improving the effectiveness of preclinical predictions of human drug responses is critical to reducing costly failures in clinical trials. Recent advances in cell biology, microfabrication and microfluidics have enabled the development of microengineered models of the functional units of human organs — known as organs-on-chips — that could provide the basis for preclinical assays with greater predictive power. Here, we examine the new opportunities for the application of organ-on-chip technologies in a range of areas in preclinical drug discovery, such as target identification and validation, target-based screening, and phenotypic screening. We also discuss emerging drug discovery opportunities enabled by organs-on-chips, as well as important challenges in realizing the full potential of this technology. PMID:25792263
Cromie, Karen D; Van Heeke, Gino; Boutton, Carlo
Nanobodies are therapeutic proteins derived from the variable domain (VHH) of naturally occurring heavy-chain antibodies. These VHH domains are the smallest functional fragments derived from a naturally occurring immunoglobulin. Nanobodies can be easily produced in prokaryotic or eukaryotic host organisms and their unique biophysical characteristics render these molecules ideal candidates for drug development. They are also emerging as an interesting new class of potential therapeutics for targets such as GPCRs, which have historically been challenging for small molecule drug discovery and even more difficult for biologics discovery. The ability to easily combine Nanobodies with different binding sites and different modes of action can be used to generate highly selective and highly potent drug candidates with very attractive pharmacological profiles. In addition, Nanobodies have been used as crystallization chaperones to enable or facilitate the structural determination of an active GPCR conformation.
Nakamura, Shigeo; Mashino, Tadahiko
Fullerenes (represented by buckminsterfullerene, C(60)) are a new kind of organic compound with a cage-like structure. A great deal of attention has been focused on their unique properties. From the viewpoint of drug discovery, fullerenes could be novel lead compounds for drug discovery. However, fullerenes are poorly soluble in aqueous media. Incorporation of water-soluble groups into the fullerene core enables investigation of its biological activities. Certain fullerene derivatives show inhibitory activity against human immunodeficiency virus reverse transcriptase. Hepatitis C virus RNA polymerase is also inhibited by fullerene derivatives. Therefore, fullerene derivatives are candidate antiviral agents. In addition, fullerene derivatives exhibit antiproliferative activity by inducing apoptosis related to the generation of reactive oxygen species. Fullerene derivatives also have the potential to be anticancer drugs.
Awasthi, Divya; Freundlich, Joel S
Bacteria are capable of performing a number of biotransformations that may activate or deactivate xenobiotics. Recent efforts have utilized metabolomics techniques to study the fate of small-molecule antibacterials within the targeted organism. Examples involving Mycobacterium tuberculosis are reviewed and analyzed with regard to the insights they provide as to both activation and deactivation of the antibacterial. The studies, in particular, shed light on biosynthetic transformations performed by M. tuberculosis while suggesting avenues for the evolution of chemical tools, highlighting potential areas for drug discovery, and mechanisms of approved drugs. A two-pronged approach investigating the metabolism of antibacterials within both the host and bacterium is outlined and will be of value to both the chemical biology and drug discovery fields. Copyright © 2017 Elsevier Ltd. All rights reserved.
Weaver, Ian N; Weaver, Donald F
Drug design and discovery is an innovation process that translates the outcomes of fundamental biomedical research into therapeutics that are ultimately made available to people with medical disorders in many countries throughout the world. To identify which nations succeed, exceed, or fail at the drug design/discovery endeavor--more specifically, which countries, within the context of their national size and wealth, are "pulling their weight" when it comes to developing medications targeting the myriad of diseases that afflict humankind--we compiled and analyzed a comprehensive survey of all new drugs (small molecular entities and biologics) approved annually throughout the world over the 20-year period from 1991 to 2010. Based upon this analysis, we have devised prediction algorithms to ascertain which countries are successful (or not) in contributing to the worldwide need for effective new therapeutics.
Ekins, Sean; Reynolds, Robert C.; Kim, Hiyun; Koo, Mi-Sun; Ekonomidis, Marilyn; Talaue, Meliza; Paget, Steve D.; Woolhiser, Lisa K.; Lenaerts, Anne J.; Bunin, Barry A.; Connell, Nancy; Freundlich, Joel S.
SUMMARY Identification of unique leads represents a significant challenge in drug discovery. This hurdle is magnified in neglected diseases such as tuberculosis. We have leveraged public high-throughput screening (HTS) data, to experimentally validate virtual screening approach employing Bayesian models built with bioactivity information (single-event model) as well as bioactivity and cytotoxicity information (dual-event model). We virtually screen a commercial library and experimentally confirm actives with hit rates exceeding typical HTS results by 1-2 orders of magnitude. The first dual-event Bayesian model identified compounds with antitubercular whole-cell activity and low mammalian cell cytotoxicity from a published set of antimalarials. The most potent hit exhibits the in vitro activity and in vitro/in vivo safety profile of a drug lead. These Bayesian models offer significant economies in time and cost to drug discovery. PMID:23521795
Low productivity, rising R&D costs, dissipating proprietary products and dwindling pipelines are driving the pharmaceutical industry to unprecedented challenges and scrutiny. In this article I reflect on the current status of the pharmaceutical industry and reasons for continued low productivity. An emerging 'symbiotic model of innovation', that addresses underlying issues in drug failure and attempts to narrow gaps in current drug discovery processes, is discussed to boost productivity. The model emphasizes partnerships in innovation to deliver quality products in a cost-effective system. I also discuss diverse options to build a balanced research portfolio with higher potential for persistent delivery of drug molecules.
Myung, Kyung; Klittich, Carla J R
Twelve drugs from four chemical classes are currently available for treatment of systemic fungal infections in humans. By contrast, more than 100 structurally distinct compounds from over 30 chemical classes have been developed as agricultural fungicides, and these fungicides target many modes of action not represented among human antifungal drugs. In this article we introduce the diverse aspects of agricultural fungicides and compare them with human antifungal drugs. We propose that the information gained from the development of agricultural fungicides can be applied to the discovery of new mechanisms of action and new antifungal agents for the management of human fungal infections.
Santos, Zenildo; Avci, Pinar; Hamblin, Michael R
Introduction Hair loss or alopecia affects the majority of the population at some time in their life, and increasingly, sufferers are demanding treatment. Three main types of alopecia (androgenic [AGA], areata [AA] and chemotherapy-induced [CIA]) are very different, and have their own laboratory models and separate drug-discovery efforts. Areas covered In this article, the authors review the biology of hair, hair follicle (HF) cycling, stem cells and signaling pathways. AGA, due to dihydrotesterone, is treated by 5-α reductase inhibitors, androgen receptor blockers and ATP-sensitive potassium channel-openers. AA, which involves attack by CD8+NK group 2D-positive (NKG2D+) T cells, is treated with immunosuppressives, biologics and JAK inhibitors. Meanwhile, CIA is treated by apoptosis inhibitors, cytokines and topical immunotherapy. Expert opinion The desire to treat alopecia with an easy topical preparation is expected to grow with time, particularly with an increasing aging population. The discovery of epidermal stem cells in the HF has given new life to the search for a cure for baldness. Drug discovery efforts are being increasingly centered on these stem cells, boosting the hair cycle and reversing miniaturization of HF. Better understanding of the molecular mechanisms underlying the immune attack in AA will yield new drugs. New discoveries in HF neogenesis and low-level light therapy will undoubtedly have a role to play. PMID:25662177
Garg, Vibhav; Arora, Suchir; Gupta, Chitra
Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.
Santos, Zenildo; Avci, Pinar; Hamblin, Michael R
Hair loss or alopecia affects the majority of the population at some time in their life, and increasingly, sufferers are demanding treatment. Three main types of alopecia (androgenic [AGA], areata [AA] and chemotherapy-induced [CIA]) are very different, and have their own laboratory models and separate drug-discovery efforts. In this article, the authors review the biology of hair, hair follicle (HF) cycling, stem cells and signaling pathways. AGA, due to dihydrotesterone, is treated by 5-α reductase inhibitors, androgen receptor blockers and ATP-sensitive potassium channel-openers. AA, which involves attack by CD8(+)NK group 2D-positive (NKG2D(+)) T cells, is treated with immunosuppressives, biologics and JAK inhibitors. Meanwhile, CIA is treated by apoptosis inhibitors, cytokines and topical immunotherapy. The desire to treat alopecia with an easy topical preparation is expected to grow with time, particularly with an increasing aging population. The discovery of epidermal stem cells in the HF has given new life to the search for a cure for baldness. Drug discovery efforts are being increasingly centered on these stem cells, boosting the hair cycle and reversing miniaturization of HF. Better understanding of the molecular mechanisms underlying the immune attack in AA will yield new drugs. New discoveries in HF neogenesis and low-level light therapy will undoubtedly have a role to play.
Macalino, Stephani Joy Y; Gosu, Vijayakumar; Hong, Sunhye; Choi, Sun
Drug discovery utilizes chemical biology and computational drug design approaches for the efficient identification and optimization of lead compounds. Chemical biology is mostly involved in the elucidation of the biological function of a target and the mechanism of action of a chemical modulator. On the other hand, computer-aided drug design makes use of the structural knowledge of either the target (structure-based) or known ligands with bioactivity (ligand-based) to facilitate the determination of promising candidate drugs. Various virtual screening techniques are now being used by both pharmaceutical companies and academic research groups to reduce the cost and time required for the discovery of a potent drug. Despite the rapid advances in these methods, continuous improvements are critical for future drug discovery tools. Advantages presented by structure-based and ligand-based drug design suggest that their complementary use, as well as their integration with experimental routines, has a powerful impact on rational drug design. In this article, we give an overview of the current computational drug design and their application in integrated rational drug development to aid in the progress of drug discovery research.
Mdluli, Khisimuzi; Kaneko, Takushi; Upton, Anna
The recent accelerated approval for use in extensively drug-resistant and multidrug-resistant-tuberculosis (MDR-TB) of two first-in-class TB drugs, bedaquiline and delamanid, has reinvigorated the TB drug discovery and development field. However, although several promising clinical development programs are ongoing to evaluate new TB drugs and regimens, the number of novel series represented is few. The global early-development pipeline is also woefully thin. To have a chance of achieving the goal of better, shorter, safer TB drug regimens with utility against drug-sensitive and drug-resistant disease, a robust and diverse global TB drug discovery pipeline is key, including innovative approaches that make use of recently acquired knowledge on the biology of TB. Fortunately, drug discovery for TB has resurged in recent years, generating compounds with varying potential for progression into developable leads. In parallel, advances have been made in understanding TB pathogenesis. It is now possible to apply the lessons learned from recent TB hit generation efforts and newly validated TB drug targets to generate the next wave of TB drug leads. Use of currently underexploited sources of chemical matter and lead-optimization strategies may also improve the efficiency of future TB drug discovery. Novel TB drug regimens with shorter treatment durations must target all subpopulations of Mycobacterium tuberculosis existing in an infection, including those responsible for the protracted TB treatment duration. This review summarizes the current TB drug development pipeline and proposes strategies for generating improved hits and leads in the discovery phase that could help achieve this goal.
Qin, Chu; Tao, Lin; Liu, Xin; Shi, Zhe; Zhang, Cun Long; Tan, Chun Yan; Chen, Yu Zong; Jiang, Yu Yang
Due to extensive bioprospecting efforts of the past and technology factors, there have been questions about drug discovery prospect from untapped species. We analyzed recent trends of approved drugs derived from previously untapped species, which show no sign of untapped drug-productive species being near extinction and suggest high probability of deriving new drugs from new species in existing drug-productive species families and clusters. Case histories of recently approved drugs reveal useful strategies for deriving new drugs from the scaffolds and pharmacophores of the natural product leads of these untapped species. New technologies such as cryptic gene-cluster exploration may generate novel natural products with highly anticipated potential impact on drug discovery. PMID:22808057
Neves, Bruno J; Andrade, Carolina H; Cravo, Pedro V L
Schistosomiasis is a neglected parasitic tropical disease that claims around 200,000 human lives every year. Praziquantel (PZQ), the only drug recommended by the World Health Organization for the treatment and control of human schistosomiasis, is now facing the threat of drug resistance, indicating the urgent need for new effective compounds to treat this disease. Therefore, globally, there is renewed interest in natural products (NPs) as a starting point for drug discovery and development for schistosomiasis. Recent advances in genomics, proteomics, bioinformatics, and cheminformatics have brought about unprecedented opportunities for the rapid and more cost-effective discovery of new bioactive compounds against neglected tropical diseases. This review highlights the main contributions that NP drug discovery and development have made in the treatment of schistosomiasis and it discusses how integration with virtual screening (VS) strategies may contribute to accelerating the development of new schistosomidal leads, especially through the identification of unexplored, biologically active chemical scaffolds and structural optimization of NPs with previously established activity.
Claveria-Gimeno, Rafael; Vega, Sonia; Abian, Olga; Velazquez-Campoy, Adrian
Drug discovery is a challenging endeavor requiring the interplay of many different research areas. Gathering information on ligand binding thermodynamics may help considerably in reducing the risk within a high uncertainty scenario, allowing early rejection of flawed compounds and pushing forward optimal candidates. In particular, the free energy, the enthalpy, and the entropy of binding provide fundamental information on the intermolecular forces driving such interaction. Areas covered: The authors review the current status and recent developments in the application of ligand binding thermodynamics in drug discovery. The thermodynamic binding profile (Gibbs energy, enthalpy, and entropy of binding) can be used for lead selection and optimization (binding enthalpy, selectivity, and adaptability). Expert opinion: Binding thermodynamics provides fundamental information on the forces driving the formation of the drug-target complex. It has been widely accepted that binding thermodynamics may be used as a decision criterion along the ligand optimization process in drug discovery and development. In particular, the binding enthalpy may be used as a guide when selecting and optimizing compounds over a set of potential candidates. However, this has been recently called into question by arguing certain difficulties and in the light of certain experimental examples.
Wolf, Antje; Shahid, Mohammad; Kasam, Vinod; Ziegler, Wolfgang; Hofmann-Apitius, Martin
The first step in finding a "drug" is screening chemical compound databases against a protein target. In silico approaches like virtual screening by molecular docking are well established in modern drug discovery. As molecular databases of compounds and target structures are becoming larger and more and more computational screening approaches are available, there is an increased need in compute power and more complex workflows. In this regard, computational Grids are predestined and offer seamless compute and storage capacity. In recent projects related to pharmaceutical research, the high computational and data storage demands of large-scale in silico drug discovery approaches have been addressed by using Grid computing infrastructures, in both; pharmaceutical industry as well as academic research. Grid infrastructures are part of the so-called eScience paradigm, where a digital infrastructure supports collaborative processes by providing relevant resources and tools for data- and compute-intensive applications. Substantial computing resources, large data collections and services for data analysis are shared on the Grid infrastructure and can be mobilized on demand. This review gives an overview on the use of Grid computing for in silico drug discovery and tries to provide a vision of future development of more complex and integrated workflows on Grids, spanning from target identification and target validation via protein-structure and ligand dependent screenings to advanced mining of large scale in silico experiments.
Joachimiak, M P; Chang, C; Rosenthal, P J; Cohen, F E
associated with the activity of mechanistic inhibitors of cysteine proteases like the epoxide E64. Using plasmodial falcipain proteases, we show how a protein family perspective can influence target discovery and inhibitor design. We suspect that parallel drug discovery programs where a family of targets is considered, rather than serial programs built on a single therapeutic focus, will become the dominant industrial paradigm. Economies of scale in assay development and in compound synthesis are expected owing to the functional and structural features of individual family members. One of the remaining challenges in post-genomic drug discovery is that inhibitors of one target are likely to show some activity against other family members. This lack of specificity may lead to difficulties in functional assignments and target validation as well as a complex side effect profile.
Ekins, Sean; Freundlich, Joel S.; Choi, Inhee; Sarker, Malabika; Talcott, Carolyn
We are witnessing the growing menace of both increasing cases of drug-sensitive and drug-resistant Mycobacterium tuberculosis strains and the challenge to produce the first new tuberculosis (TB) drug in well over 40 years. The TB community, having invested in extensive high-throughput screening efforts, is faced with the question of how to optimally leverage this data in order to move from a hit to a lead to a clinical candidate and potentially a new drug. Complementing this approach, yet conducted on a much smaller scale, cheminformatic techniques have been leveraged and are herein reviewed. We suggest these computational approaches should be more optimally integrated in a workflow with experimental approaches to accelerate TB drug discovery. PMID:21129975
Heilker, Ralf; Traub, Stefanie; Reinhardt, Peter; Schöler, Hans R; Sterneckert, Jared
Owing to the inherent disconnect between drug pharmacology in heterologous cellular models and drug efficacy in vivo, the quest for more predictive in vitro systems is one of the most urgent challenges of modern drug discovery. An improved pharmacological in vitro profiling would employ primary samples of the proper drug-targeted human tissue or the bona fide human disease-relevant cells. With the advent of induced pluripotent stem (iPS) cell technology the facilitated access to a variety of disease-relevant target cells is now held out in prospect. In this review, we focus on the use of human iPS cell derived neurons for high throughput pharmaceutical drug screening, employing detection technologies that are sufficiently sensitive to measure signaling in cells with physiological target protein expression levels. Copyright © 2014 Elsevier Ltd. All rights reserved.
McLachlan, Andrew J.; Quinn, Ronald J.; Simpson, Stephen J.; de Cabo, Rafael
Despite remarkable technological advances in genetics and drug screening, the discovery of new pharmacotherapies has slowed and new approaches to drug development are needed. Research into the biology of aging is generating many novel targets for drug development that may delay all age-related diseases and be used long term by the entire population. Drugs that successfully delay the aging process will clearly become “blockbusters.” To date, the most promising leads have come from studies of the cellular pathways mediating the longevity effects of caloric restriction (CR), particularly target of rapamycin and the sirtuins. Similar research into pathways governing other hormetic responses that influence aging is likely to yield even more targets. As aging becomes a more attractive target for drug development, there will be increasing demand to develop biomarkers of aging as surrogate outcomes for the testing of the effects of new agents on the aging process. PMID:21693687
Bueters, Tjerk; Gibson, Christopher; Visser, Sandra A G
In this perspective article, we explain how quantitative and translational pharmacology, when well-implemented, is believed to lead to improved clinical candidates and drug targets that are differentiated from current treatment options. Quantitative and translational pharmacology aims to build and continuously improve the quantitative relationship between drug exposure, target engagement, efficacy, safety and its interspecies relationship at every phase of drug discovery. Drug hunters should consider and apply these concepts to develop compounds with a higher probability of interrogating the clinical biological hypothesis. We offer different approaches to set an initial effective concentration or pharmacokinetic-pharmacodynamic target in man and to predict human pharmacokinetics that determine together the predicted human dose and dose schedule. All concepts are illustrated with ample literature examples.
Abel, Robert; Wang, Lingle; Harder, Edward D; Berne, B J; Friesner, Richard A
A principal goal of drug discovery project is to design molecules that can tightly and selectively bind to the target protein receptor. Accurate prediction of protein-ligand binding free energies is therefore of central importance in computational chemistry and computer aided drug design. Multiple recent improvements in computing power, classical force field accuracy, enhanced sampling methods, and simulation setup have enabled accurate and reliable calculations of protein-ligands binding free energies, and position free energy calculations to play a guiding role in small molecule drug discovery. In this Account, we outline the relevant methodological advances, including the REST2 (Replica Exchange with Solute Temperting) enhanced sampling, the incorporation of REST2 sampling with convential FEP (Free Energy Perturbation) through FEP/REST, the OPLS3 force field, and the advanced simulation setup that constitute our FEP+ approach, followed by the presentation of extensive comparisons with experiment, demonstrating sufficient accuracy in potency prediction (better than 1 kcal/mol) to substantially impact lead optimization campaigns. The limitations of the current FEP+ implementation and best practices in drug discovery applications are also discussed followed by the future methodology development plans to address those limitations. We then report results from a recent drug discovery project, in which several thousand FEP+ calculations were successfully deployed to simultaneously optimize potency, selectivity, and solubility, illustrating the power of the approach to solve challenging drug design problems. The capabilities of free energy calculations to accurately predict potency and selectivity have led to the advance of ongoing drug discovery projects, in challenging situations where alternative approaches would have great difficulties. The ability to effectively carry out projects evaluating tens of thousands, or hundreds of thousands, of proposed drug candidates
Zheng, Chunli; Guo, Zihu; Huang, Chao; Wu, Ziyin; Li, Yan; Chen, Xuetong; Fu, Yingxue; Ru, Jinlong; Ali Shar, Piar; Wang, Yuan; Wang, Yonghua
A system-level identification of drug-target direct interactions is vital to drug repositioning and discovery. However, the biological means on a large scale remains challenging and expensive even nowadays. The available computational models mainly focus on predicting indirect interactions or direct interactions on a small scale. To address these problems, in this work, a novel algorithm termed weighted ensemble similarity (WES) has been developed to identify drug direct targets based on a large-scale of 98,327 drug-target relationships. WES includes: (1) identifying the key ligand structural features that are highly-related to the pharmacological properties in a framework of ensemble; (2) determining a drug’s affiliation of a target by evaluation of the overall similarity (ensemble) rather than a single ligand judgment; and (3) integrating the standardized ensemble similarities (Z score) by Bayesian network and multi-variate kernel approach to make predictions. All these lead WES to predict drug direct targets with external and experimental test accuracies of 70% and 71%, respectively. This shows that the WES method provides a potential in silico model for drug repositioning and discovery. PMID:26155766
Decher, Niels; Netter, Michael F; Streit, Anne K
Virtually all organisms use RNA editing as a powerful post-transcriptional mechanism to recode genomic information and to increase functional protein diversity. The enzymatic editing of pre-mRNA by ADARs and CDARs is known to change the functional properties of neuronal receptors and ion channels regulating cellular excitability. However, RNA editing is also an important mechanism for genes expressed outside the brain. The fact that RNA editing breaks the 'one gene encodes one protein' hypothesis is daunting for scientists and a probable drawback for drug development, as scientists might search for drugs targeting the 'wrong' protein. This possible difficulty for drug discovery and development became more evident from recent publications, describing that RNA editing events have profound impact on the pharmacology of some common drug targets. These recent studies highlight that RNA editing can cause massive discrepancies between the in vitro and in vivo pharmacology. Here, we review the putative impact of RNA editing on drug discovery, as RNA editing has to be considered before using high-throughput screens, rational drug design or choosing the right model organism for target validation.
The following article reports on the results and the outcome of a meeting organised at the Aptuit Auditorium in Verona (Italy), which highlighted the current applications of state-of-the-art computational science to drug design in Italy. The meeting, which had > 100 people in attendance, consisted of over 40 presentations and included keynote lectures given by world-renowned speakers. The topics included in the meeting are areas related to ligand and structure-based ligand design and library design and screening; it also provided discussion pertaining to chemometrics. The meeting also stressed the importance of public-private collaboration and reviewed the different approaches to computationally driven drug discovery taken within academia and industry. The meeting helped define the current position of state-of-the-art computational drug discovery in Italy, pointing out criticalities and assets. This kind of focused meeting is important in the sense that it lends the opportunity of a restricted yet representative community of fellow professionals to deeply discuss the current methodological approaches and provide future perspectives for computationally driven drug discovery.
Rowntree, Rebecca K; McNeish, John D
Pluripotent embryonic stem cells (ESCs), when compared with transformed, primary or engineered cells, have unique characteristics and advantages that have resulted in the development of important cell-based tools in modern drug discovery. However, a key limitation has been the availability of human ESCs from patients with specific medical needs and the broad range of genetic variation represented worldwide. Induced pluripotent stem (iPS) cells are derived from somatic cells that are reprogrammed to a pluripotent stem cell state and have functional characteristics similar to ESCs. The demonstration that human iPS cells can be derived, with relative ease, through the introduction of transcription factor combinations has allowed the generation of disease-specific iPS cell lines. Therefore, iPS cell technology may deliver robust, human pluripotent cell lines from a wide range of clinical phenotypes and genotypes. Although human iPS cell technology is still a new tool in drug discovery, the promise that this technology will impact the discovery of new therapies can be projected based on the uptake of stem cell applications in biopharmaceutical sciences. Here, the near-term opportunities that iPS cells may deliver to drug discoverers to generate and test hypotheses will be discussed, with a focus on the specific strengths and weaknesses of iPS cell technology. Finally, the future perspective will address novel opportunities iPS cells could uniquely deliver to the preclinical development of new drug therapies.
Durrant, Russil; Adamson, Simon; Todd, Fraser; Sellman, Doug
Drug use creates a significant amount of harm in modern societies. From an evolutionary perspective, the pervasive use of drugs and the ongoing risk of drug addiction can be explained in terms of the action of drugs on evolved motivational-emotional systems. Addiction arises through interaction of these evolutionarily ancient systems, designed to promote the pursuit of natural rewards, and contemporary environments where purified and potent forms of drugs are readily available. This evolutionary analysis is extended to account for developmental patterns in problem drug use, and to explain the existence of behavioural addictions, such as problem gambling. The paper concludes by considering some of the clinical and public policy implications of the evolutionary perspective presented.
Yokley, Brian H; Hartman, Matthew; Slusher, Barbara S
There was a greater than 50% decline in central nervous system (CNS) drug discovery and development programs by major pharmaceutical companies from 2009 to 2014. This decline was paralleled by a rise in the number of university led drug discovery centers, many in the CNS area, and a growth in the number of public-private drug discovery partnerships. Diverse operating models have emerged as the academic drug discovery centers adapt to this changing ecosystem.
López-Vallejo, Fabian; Caulfield, Thomas; Martínez-Mayorga, Karina; Giulianotti, Marc A; Nefzi, Adel; Houghten, Richard A; Medina-Franco, Jose L
Virtual screening is increasingly being used in drug discovery programs with a growing number of successful applications. Experimental methodologies developed to speed up the drug discovery processes include high-throughput screening and combinatorial chemistry. The complementarities between computational and experimental screenings have been recognized and reviewed in the literature. Computational methods have also been used in the combinatorial chemistry field, in particular in library design. However, the integration of computational and combinatorial chemistry screenings has been attempted only recently. Combinatorial libraries (experimental or virtual) represent a notable source of chemically related compounds. Advances in combinatorial chemistry and deconvolution strategies, have enabled the rapid exploration of novel and dense regions in the chemical space. The present review is focused on the integration of virtual and experimental screening of combinatorial libraries. Applications of virtual screening to discover novel anticancer agents and our ongoing efforts towards the integration of virtual screening and combinatorial chemistry are also discussed.
Wright, Peter M.; Seiple, Ian B.; Myers, Andrew G.
The discovery and implementation of antibiotics in the early twentieth century transformed human health and wellbeing. Chemical synthesis enabled the development of the first antibacterial substances, organoarsenicals and sulfa drugs, but these were soon outshone by a host of more powerful and vastly more complex antibiotics from nature: penicillin, streptomycin, tetracycline, and erythromycin, among others. These primary defences are now significantly less effective as an unavoidable consequence of rapid evolution of resistance within pathogenic bacteria, made worse by widespread misuse of antibiotics. For decades medicinal chemists replenished the arsenal of antibiotics by semisynthetic and to a lesser degree fully synthetic routes, but economic factors have led to a subsidence of this effort, which places society on the precipice of a disaster. We believe that the strategic application of modern chemical synthesis to antibacterial drug discovery must play a critical role if a crisis of global proportions is to be averted. PMID:24990531
Loging, William; Harland, Lee; Williams-Jones, Bryn
The vast range of in silico resources that are available in life sciences research hold much promise towards aiding the drug discovery process. To fully realize this opportunity, computational scientists must consider the practical issues of data integration and identify how best to apply these resources scientifically. In this article we describe in silico approaches that are driven towards the identification of testable laboratory hypotheses; we also address common challenges in the field. We focus on flexible, high-throughput techniques, which may be initiated independently of 'wet-lab' experimentation, and which may be applied to multiple disease areas. The utility of these approaches in drug discovery highlights the contribution that in silico techniques can make and emphasizes the need for collaboration between the areas of disease research and computational science.
Blat, Yuval; Blat, Shachar
Duchenne muscular dystrophy (DMD) is a genetic, lethal, muscle disorder caused by the loss of the muscle protein, dystrophin, leading to progressive loss of muscle fibers and muscle weakness. Drug discovery efforts targeting DMD have used two main approaches: (1) the restoration of dystrophin expression or the expression of a compensatory protein, and (2) the mitigation of downstream pathological mechanisms, including dysregulated calcium homeostasis, oxidative stress, inflammation, fibrosis, and muscle ischemia. The aim of this review is to introduce the disease, its pathophysiology, and the available research tools to a drug discovery audience. This review will also detail the most promising therapies that are currently being tested in clinical trials or in advanced preclinical models.
Blair, Wade; Perros, Manos
The 5th Antiviral Drug Discovery and Development Summit provided an up-to-date snapshot of the ongoing developments in the area. The topics covered ranged from updates on recently launched drugs (Kaletra), Fuzeon) and new investigational inhibitors (T-1249, Reverset, UK-427857, L-870810, PA-457, remofovir, VX-950), to the discovery of new antiviral targets and advances in technologies that may provide the substrate for the next generation of therapeutics. It is apparent from the range of presentations that much of today's efforts are focused on developing new classes of HIV inhibitors (gp41, integrase), while there is also considerable progress in hepatitis C, where a number of inhibitors have or should reach proof-of-concept studies in the coming months. Here we provide the highlights of this meeting, with particular emphasis on the new developments in HIV and hepatitis C virus.
Dias, Daniel A.; Urban, Sylvia; Roessner, Ute
Historically, natural products have been used since ancient times and in folklore for the treatment of many diseases and illnesses. Classical natural product chemistry methodologies enabled a vast array of bioactive secondary metabolites from terrestrial and marine sources to be discovered. Many of these natural products have gone on to become current drug candidates. This brief review aims to highlight historically significant bioactive marine and terrestrial natural products, their use in folklore and dereplication techniques to rapidly facilitate their discovery. Furthermore a discussion of how natural product chemistry has resulted in the identification of many drug candidates; the application of advanced hyphenated spectroscopic techniques to aid in their discovery, the future of natural product chemistry and finally adopting metabolomic profiling and dereplication approaches for the comprehensive study of natural product extracts will be discussed. PMID:24957513
Chang, Cheng; Ekins, Sean; Bahadduri, Praveen; Swaan, Peter W.
The ability to identify ligands for drug transporters is an important step in drug discovery and development. It can both improve accurate profiling of lead pharmacokinetic properties and assist in the discovery of new chemical entities targeting transporters. In silico approaches, especially pharmacophore-based database screening methods have great potential in improving the throughput of current transporter ligand identification assays, leading to a higher hit rate by focusing in vitro testing to the most promising hits. In this review, the potential of different in silico methods in transporter ligand identification studies are compared and summarized with an emphasis on pharmacophore modeling. Various implementations of pharmacophore model generation, database compilation and flexible screening algorithms are also introduced. Recent successful utilization of database searching with pharmacophores to identify novel ligands for the pharmaceutically significant transporters hPepT1, P-gp, BCRP, MRP1 and DAT are reviewed and challenges encountered with current approaches are discussed. PMID:17097188
Cromm, Philipp M; Crews, Craig M
Traditional pharmaceutical drug discovery is almost exclusively focused on directly controlling protein activity to cure diseases. Modulators of protein activity, especially inhibitors, are developed and applied at high concentration to achieve maximal effects. Thereby, reduced bioavailability and off-target effects can hamper compound efficacy. Nucleic acid-based strategies that control protein function by affecting expression have emerged as an alternative. However, metabolic stability and broad bioavailability represent development hurdles that remain to be overcome for these approaches. More recently, utilizing the cell's own protein destruction machinery for selective degradation of essential drivers of human disorders has opened up a new and exciting area of drug discovery. Small-molecule-induced proteolysis of selected substrates offers the potential of reaching beyond the limitations of the current pharmaceutical paradigm to expand the druggable target space. Copyright © 2017 Elsevier Ltd. All rights reserved.
Wright, Peter M; Seiple, Ian B; Myers, Andrew G
The discovery and implementation of antibiotics in the early twentieth century transformed human health and wellbeing. Chemical synthesis enabled the development of the first antibacterial substances, organoarsenicals and sulfa drugs, but these were soon outshone by a host of more powerful and vastly more complex antibiotics from nature: penicillin, streptomycin, tetracycline, and erythromycin, among others. These primary defences are now significantly less effective as an unavoidable consequence of rapid evolution of resistance within pathogenic bacteria, made worse by widespread misuse of antibiotics. For decades medicinal chemists replenished the arsenal of antibiotics by semisynthetic and to a lesser degree fully synthetic routes, but economic factors have led to a subsidence of this effort, which places society on the precipice of a disaster. We believe that the strategic application of modern chemical synthesis to antibacterial drug discovery must play a critical role if a crisis of global proportions is to be averted.
Herold, J. Martin; Ingerman, Lindsey A; Gao, Cen; Frye, Stephen V
The recognition of methyl-lysine and -arginine residues on both histone and other proteins by specific “reader” elements is important for chromatin regulation, gene expression, and control of cell-cycle progression. Recently the crucial role of these reader proteins in cancer development and dedifferentiation has emerged, owing to the increased interest among the scientific community. The methyl-lysine and -arginine readers are a large and very diverse set of effector proteins and targeting them with small molecule probes in drug discovery will inevitably require a detailed understanding of their structural biology and mechanism of binding. In the following review, the critical elements of methyl-lysine and -arginine recognition will be summarized with respect to each protein family and initial results in assay development, probe design, and drug discovery will be highlighted. PMID:22145013
Donev, Alexander N; Tobias, Randall D
Dose-response studies are an essential part of the drug discovery process. They are typically carried out on a large number of chemical compounds using serial dilution experimental designs. This paper proposes a method of selecting the key parameters of these designs (maximum dose, dilution factor, number of concentrations and number of replicated observations for each concentration) depending on the stage of the drug discovery process where the study takes place. This is achieved by employing and extending results from optimal design theory. Population D- and D(S)-optimality are defined and used to evaluate the precision of estimating the potency of the tested compounds. The proposed methodology is easy to use and creates opportunities to reduce the cost of the experiments without compromising the quality of the data obtained in them.
Williams, Antony J; Ekins, Sean; Clark, Alex M; Jack, J James; Apodaca, Richard L
Mobile hardware and software technology continues to evolve very rapidly and presents drug discovery scientists with new platforms for accessing data and performing data analysis. Smartphones and tablet computers can now be used to perform many of the operations previously addressed by laptops or desktop computers. Although the smaller screen sizes and requirements for touch-screen manipulation can present user-interface design challenges, especially with chemistry-related applications, these limitations are driving innovative solutions. In this early review of the topic, we collectively present our diverse experiences as software developer, chemistry database expert and naïve user, in terms of what mobile platforms could provide to the drug discovery chemist in the way of applications in the future as this disruptive technology takes off.
The isolation and extraction of novel bioactive secondary metabolites from marine microorganisms have a biomedical potential for future drug discovery as the oceans cover 70% of the planet's surface and life on earth originates from sea. Wide range of novel bioactive secondary metabolites exhibiting pharmacodynamic properties has been isolated from marine microorganisms and many to be discovered. The compounds isolated from marine organisms (macro and micro) are important in their natural form and also as templates for synthetic modifications for the treatments for variety of deadly to minor diseases. Many technical issues are yet to overcome before wide-scale bioprospecting of marine microorganisms becomes a reality. This chapter focuses on some novel secondary metabolites having antitumor, antivirus, enzyme inhibitor, and other bioactive properties identified and isolated from marine microorganisms including bacteria, actinomycetes, fungi, and cyanobacteria, which could serve as potentials for drug discovery after their clinical trials.
Frei, Priska; Navarra, Giulio; Sager, Christoph P; Silbermann, Marleen; Varga, Norbert; Wamhoff, Eike-Christian
A summit amongst the summits: The 11(th) Swiss Course on Medicinal Chemistry was held in October 2014, again in the scenic setting of the Alps in Leysin, Switzerland. One hundred participants, mostly from industry, experienced a week of expert talks about numerous aspects of drug discovery and medicinal chemistry. In this conference report, we briefly summarize the essential topics of this event, while the most inspiring lectures are described in greater detail.
Mendez, Lois; Henriquez, Gabriela; Sirimulla, Suman; Narayan, Mahesh
Halogen bonding has emerged at the forefront of advances in improving ligand: receptor interactions. In particular the newfound ability of this extant non-covalent-bonding phenomena has revolutionized computational approaches to drug discovery while simultaneously reenergizing synthetic approaches to the field. Here we survey, via examples of classical applications involving halogen atoms in pharmaceutical compounds and their biological hosts, the unique advantages that halogen atoms offer as both Lewis acids and Lewis bases.
Johnston, Jennifer A
The Ubiquitin Drug Discovery and Diagnostics Conference, held in Philadelphia, included topics covering the role of E3 ligases in disease. This conference report highlights selected presentations on E3-E2 ligase interactions, the SCF cyclin F ubiquitin ligase complex, and targeting HectH9 and KF-1 E3 ligases. Pharmaceutical research discussed includes E3 programs from Progenra and efforts to modulate the Parkin ligase at Elan Pharmaceuticals.
Redinbo, M R; Bencharit, S; Potter, P M
Human carboxylesterase 1 (hCE1) is a serine esterase involved in both drug metabolism and activation, as well as other biological processes. hCE1 catalyses the hydrolysis of heroin and cocaine, and the transesterification of cocaine in the presence of ethanol to the toxic metabolite cocaethylene. We have determined the crystal structures of hCE1 in complex with either the cocaine analogue homatropine or the heroin analogue naloxone. These are the first structures of a human carboxylesterase, and they provide details about narcotic metabolism in humans. hCE1's active site contains rigid and flexible pockets, explaining the enzyme's ability to act both specifically and promiscuously. hCE1 has also been reported to contain cholesteryl ester hydrolase, fatty acyl-CoA hydrolase and acyl-CoA:cholesterol acyltransferase activities, and thus appears to be involved in cholesterol metabolism. Since the enzyme may be useful as a treatment for cocaine overdose, and may afford protection against chemical weapons like Sarin, Soman and VX gas, hCE1 could serve as both a drug and a drug target. Selective hCE1 inhibitors targeted to several sites on the enzyme may also pave the way for novel clinical tools to manage cholesterol homoeostasis in humans.
Yap, Timothy A; Smith, Alan D; Ferraldeschi, Roberta; Al-Lazikani, Bissan; Workman, Paul; de Bono, Johann S
Castration-resistant prostate cancer (CRPC) is associated with a poor prognosis and poses considerable therapeutic challenges. Recent genetic and technological advances have provided insights into prostate cancer biology and have enabled the identification of novel drug targets and potent molecularly targeted therapeutics for this disease. In this article, we review recent advances in prostate cancer target identification for drug discovery and discuss their promise and associated challenges. We review the evolving therapeutic landscape of CRPC and discuss issues associated with precision medicine as well as challenges encountered with immunotherapy for this disease. Finally, we envision the future management of CRPC, highlighting the use of circulating biomarkers and modern clinical trial designs.
Chodera, John D.; Mobley, David L.; Shirts, Michael R.; Dixon, Richard W.; Branson, Kim; Pande, Vijay S.
Improved rational drug design methods are needed to lower the cost and increase the success rate of drug discovery and development. Alchemical binding free energy calculations, one potential tool for rational design, have progressed rapidly over the last decade, but still fall short of providing robust tools for pharmaceutical engineering. Recent studies, especially on model receptor systems, have clarified many of the challenges that must be overcome for robust predictions of binding affnity to be useful in rational design. In this review, inspired by a recent joint academic/industry meeting organized by the authors, we discuss these challenges and suggest a number of promising approaches for overcoming them. PMID:21349700
Davies-Coleman, Michael T; Veale, Clinton G L
Recent developments in marine drug discovery from three South African marine invertebrates, the tube worm Cephalodiscus gilchristi, the ascidian Lissoclinum sp. and the sponge Topsentia pachastrelloides, are presented. Recent reports of the bioactivity and synthesis of the anti-cancer secondary metabolites cephalostatin and mandelalides (from C. gilchristi and Lissoclinum sp., respectively) and various analogues are presented. The threat of drug-resistant pathogens, e.g., methicillin-resistant Staphylococcus aureus (MRSA), is assuming greater global significance, and medicinal chemistry strategies to exploit the potent MRSA PK inhibition, first revealed by two marine secondary metabolites, cis-3,4-dihydrohamacanthin B and bromodeoxytopsentin from T. pachastrelloides, are compared.
Mah, Robert; Thomas, Jason R; Shafer, Cynthia M
In recent years, the number of drug candidates with a covalent mechanism of action progressing through clinical trials or being approved by the FDA has increased significantly. And as interest in covalent inhibitors has increased, the technical challenges for characterizing and optimizing these inhibitors have become evident. A number of new tools have been developed to aid this process, but these have not gained wide-spread use. This review will highlight a number of methods and tools useful for prosecuting covalent inhibitor drug discovery programs.
drug design and development. The biological focus of our research addresses estrogen biosynthesis and on estrogen- induced gene expression in hormone-dependent breast cancer. Identification of critical small molecule-protein and protein-protein interactions during gene expression and signal transduction in the areas of steroidogenesis and estrogen-induced responses will result in new molecular targets for drug discovery and design for the treatment of hormone-dependent breast cancer. The Sabbatical Training Grant provided an enhancement of our research endeavors by
Beutler, John A.
Natural products have contributed to the development of many drugs for diverse indications. While most U.S. pharmaceutical companies have reduced or eliminated their in-house natural product groups, new paradigms and new enterprises have evolved to carry on a role for natural products in the pharmaceutical industry. Many of the reasons for the decline in popularity of natural products are being addressed by the development of new techniques for screening and production. This overview aims to inform pharmacologists of current strategies and techniques that make natural products a viable strategic choice for inclusion in drug discovery programs. PMID:20161632
Davies-Coleman, Michael T.; Veale, Clinton G. L.
Recent developments in marine drug discovery from three South African marine invertebrates, the tube worm Cephalodiscus gilchristi, the ascidian Lissoclinum sp. and the sponge Topsentia pachastrelloides, are presented. Recent reports of the bioactivity and synthesis of the anti-cancer secondary metabolites cephalostatin and mandelalides (from C. gilchristi and Lissoclinum sp., respectively) and various analogues are presented. The threat of drug-resistant pathogens, e.g., methicillin-resistant Staphylococcus aureus (MRSA), is assuming greater global significance, and medicinal chemistry strategies to exploit the potent MRSA PK inhibition, first revealed by two marine secondary metabolites, cis-3,4-dihydrohamacanthin B and bromodeoxytopsentin from T. pachastrelloides, are compared. PMID:26473891
Huang, Wei-Hsuan; Tseng, Chao-Neng; Tang, Jen-Yang; Yang, Cheng-Hong; Liang, Shih-Shin; Chang, Hsueh-Wei
RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently, RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA editing may be a potential target for therapeutic natural products. In this review, we provide a literature overview of the biological functions of RNA editing on gene expression, diseases, cancers, and drugs. The bioinformatics resources of RNA editing were also summarized.
Grant, Marianne A.
Pharmaceutical researchers must evaluate vast numbers of protein sequences and formulate innovative strategies for identifying valid targets and discovering leads against them as a way of accelerating drug discovery. The ever increasing number and diversity of novel protein sequences identified by genomic sequencing projects and the success of worldwide structural genomics initiatives have spurred great interest and impetus in the development of methods for accurate, computationally empowered protein function prediction and active site identification. Previously, in the absence of direct experimental evidence, homology-based protein function annotation remained the gold-standard for in silico analysis and prediction of protein function. However, with the continued exponential expansion of sequence databases, this approach is not always applicable, as fewer query protein sequences demonstrate significant homology to protein gene products of known function. As a result, several non-homology based methods for protein function prediction that are based on sequence features, structure, evolution, biochemical and genetic knowledge have emerged. Herein, we review current bioinformatic programs and approaches for protein function prediction/annotation and discuss their integration into drug discovery initiatives. The development of such methods to annotate protein functional sites and their application to large protein functional families is crucial to successfully utilizing the vast amounts of genomic sequence information available to drug discovery and development processes. PMID:25530654
Barbault, Florent; Maurel, François
Biological macromolecules, such as proteins or nucleic acids, are (still) molecules and thus they follow the same chemical rules that any simple molecule follows, even if their size generally renders accurate studies unhelpful. However, in the context of drug discovery, a detailed analysis of ligand association is required for understanding or predicting their interactions and hybrid quantum mechanics/molecular mechanics (QM/MM) computations are relevant tools to help elucidate this process. In this review, the authors explore the use of QM/MM for drug discovery. After a brief description of the molecular mechanics (MM) technique, the authors describe the subtractive and additive techniques for QM/MM computations. The authors then present several application cases in topics involved in drug discovery. QM/MM have been widely employed during the last decades to study chemical processes such as enzyme-inhibitor interactions. However, despite the enthusiasm around this area, plain MM simulations may be more meaningful than QM/MM. To obtain reliable results, the authors suggest fixing several keystone parameters according to the underlying chemistry of each studied system.
Barbault, Florent; Maurel, François
Biological macromolecules, such as proteins or nucleic acids, are (still) molecules and thus they follow the same chemical rules that any simple molecule follows, even if their size generally renders accurate studies unhelpful. However, in the context of drug discovery, a detailed analysis of ligand association is required for understanding or predicting their interactions and hybrid quantum mechanics/molecular mechanics (QM/MM) computations are relevant tools to help elucidate this process. Areas covered: In this review, the authors explore the use of QM/MM for drug discovery. After a brief description of the molecular mechanics (MM) technique, the authors describe the subtractive and additive techniques for QM/MM computations. The authors then present several application cases in topics involved in drug discovery. Expert opinion: QM/MM have been widely employed during the last decades to study chemical processes such as enzyme-inhibitor interactions. However, despite the enthusiasm around this area, plain MM simulations may be more meaningful than QM/MM. To obtain reliable results, the authors suggest fixing several keystone parameters according to the underlying chemistry of each studied system.
Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu
In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown ‘chemical space’ to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for ‘chemical space’, which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. PMID:27150808
Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu
In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown 'chemical space' to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for 'chemical space', which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Recent advances in machine learning have made significant contributions to drug discovery. Deep neural networks in particular have been demonstrated to provide significant boosts in predictive power when inferring the properties and activities of small-molecule compounds (Ma, J. et al. J. Chem. Inf. Model.2015, 55, 263–27425635324). However, the applicability of these techniques has been limited by the requirement for large amounts of training data. In this work, we demonstrate how one-shot learning can be used to significantly lower the amounts of data required to make meaningful predictions in drug discovery applications. We introduce a new architecture, the iterative refinement long short-term memory, that, when combined with graph convolutional neural networks, significantly improves learning of meaningful distance metrics over small-molecules. We open source all models introduced in this work as part of DeepChem, an open-source framework for deep-learning in drug discovery (Ramsundar, B. deepchem.io. https://github.com/deepchem/deepchem, 2016). PMID:28470045
Holdgate, Geoffrey; Geschwindner, Stefan; Breeze, Alex; Davies, Gareth; Colclough, Nicola; Temesi, David; Ward, Lara
Biophysical methods have become established in many areas of drug discovery. Application of these methods was once restricted to a relatively small number of scientists using specialized, low throughput technologies and methods. Now, automated high-throughput instruments are to be found in a growing number of laboratories. Many biophysical methods are capable of measuring the equilibrium binding constants between pairs of molecules crucial for molecular recognition processes, encompassing protein-protein, protein-small molecule, and protein-nucleic acid interactions, and several can be used to measure the kinetic or thermodynamic components controlling these biological processes. For a full characterization of a binding process, determinations of stoichiometry, binding mode, and any conformational changes associated with such interactions are also required. The suite of biophysical methods that are now available represents a powerful toolbox of techniques which can effectively deliver this full characterization.The aim of this chapter is to provide the reader with an overview of the drug discovery process and how biophysical methods, such as surface plasmon resonance (SPR), isothermal titration calorimetry (ITC), nuclear magnetic resonance, mass spectrometry (MS), and thermal unfolding methods can answer specific questions in order to influence project progression and outcomes. The selection of these examples is based upon the experiences of the authors at AstraZeneca, and relevant approaches are highlighted where they have utility in a particular drug discovery scenario.
Park, Soo-Jin; Im, Dong-Soon
Initial discovery on sphingosine 1-phosphate (S1P) as an intracellular second messenger was faced unexpectedly with roles of S1P as a first messenger, which subsequently resulted in cloning of its G protein-coupled receptors, S1P1–5. The molecular identification of S1P receptors opened up a new avenue for pathophysiological research on this lipid mediator. Cellular and molecular in vitro studies and in vivo studies on gene deficient mice have elucidated cellular signaling pathways and the pathophysiological meanings of S1P receptors. Another unexpected finding that fingolimod (FTY720) modulates S1P receptors accelerated drug discovery in this field. Fingolimod was approved as a first-in-class, orally active drug for relapsing multiple sclerosis in 2010, and its applications in other disease conditions are currently under clinical trials. In addition, more selective S1P receptor modulators with better pharmacokinetic profiles and fewer side effects are under development. Some of them are being clinically tested in the contexts of multiple sclerosis and other autoimmune and inflammatory disorders, such as, psoriasis, Crohn’s disease, ulcerative colitis, polymyositis, dermatomyositis, liver failure, renal failure, acute stroke, and transplant rejection. In this review, the authors discuss the state of the art regarding the status of drug discovery efforts targeting S1P receptors and place emphasis on potential clinical applications. PMID:28035084
Matsumoto, Mitsuyuki; Walton, Noah M; Yamada, Hiroshi; Kondo, Yuji; Marek, Gerard J; Tajinda, Katsunori
Failures of investigational new drugs (INDs) for schizophrenia have left huge unmet medical needs for patients. Given the recent lackluster results, it is imperative that new drug discovery approaches (and resultant drug candidates) target pathophysiological alterations that are shared in specific, stratified patient populations that are selected based on pre-identified biological signatures. One path to implementing this paradigm is achievable by leveraging recent advances in genetic information and technologies. Genome-wide exome sequencing and meta-analysis of single nucleotide polymorphism (SNP)-based association studies have already revealed rare deleterious variants and SNPs in patient populations. Areas covered: Herein, the authors review the impact that genetics have on the future of schizophrenia drug discovery. The high polygenicity of schizophrenia strongly indicates that this disease is biologically heterogeneous so the identification of unique subgroups (by patient stratification) is becoming increasingly necessary for future investigational new drugs. Expert opinion: The authors propose a pathophysiology-based stratification of genetically-defined subgroups that share deficits in particular biological pathways. Existing tools, including lower-cost genomic sequencing and advanced gene-editing technology render this strategy ever more feasible. Genetically complex psychiatric disorders such as schizophrenia may also benefit from synergistic research with simpler monogenic disorders that share perturbations in similar biological pathways.
Shu, Chih-Wen; Liu, Pei-Feng; Huang, Chun-Ming
Autophagy is an evolutionally conserved process in cells for cleaning abnormal proteins and organelles in a lysosome dependent manner. Growing studies have shown that defects or induced autophagy contributes to many diseases including aging, neurodegeneration, pathogen infection, and cancer. However, the precise involvement of autophagy in health and disease remains controversial because the theories are built on limited assays and chemical modulators, indicating that the role of autophagy in diseases may require further verification. Many food and drug administration (FDA) approved drugs modulate autophagy signaling, suggesting that modulation of autophagy with pharmacological agonists or antagonists provides a potential therapy for autophagy-related diseases. This suggestion raises an attractive issue on drug discovery for exploring chemical modulators of autophagy. High throughput screening (HTS) is becoming a powerful tool for drug discovery that may accelerate screening specific autophagy modulators to clarify the role of autophagy in diseases. Herein, this review lays out current autophagy assays to specifically measure autophagy components such as LC3 (mammalian homologue of yeast Atg8) and Atg4. These assays are feasible or successful for HTS with certain chemical libraries, which might be informative for this intensively growing field as research tools and hopefully developing new drugs for autophagy-related diseases.
Okuno, Yasushi; Yang, Jiyoon; Taneishi, Kei; Yabuuchi, Hiroaki; Tsujimoto, Gozoh
G-protein coupled receptors (GPCRs) represent one of the most important families of drug targets in pharmaceutical development. GPCR-LIgand DAtabase (GLIDA) is a novel public GPCR-related chemical genomic database that is primarily focused on the correlation of information between GPCRs and their ligands. It provides correlation data between GPCRs and their ligands, along with chemical information on the ligands, as well as access information to the various web databases regarding GPCRs. These data are connected with each other in a relational database, allowing users in the field of GPCR-related drug discovery to easily retrieve such information from either biological or chemical starting points. GLIDA includes structure similarity search functions for the GPCRs and for their ligands. Thus, GLIDA can provide correlation maps linking the searched homologous GPCRs (or ligands) with their ligands (or GPCRs). By analyzing the correlation patterns between GPCRs and ligands, we can gain more detailed knowledge about their interactions and improve drug design efforts by focusing on inferred candidates for GPCR-specific drugs. GLIDA is publicly available at . We hope that it will prove very useful for chemical genomic research and GPCR-related drug discovery. PMID:16381956
Oprea, Tudor I.; Bauman, Julie E.; Bologa, Cristian G.; Buranda, Tione; Chigaev, Alexandre; Edwards, Bruce S.; Jarvik, Jonathan W.; Gresham, Hattie D.; Haynes, Mark K.; Hjelle, Brian; Hromas, Robert; Hudson, Laurie; Mackenzie, Debra A.; Muller, Carolyn Y.; Reed, John C.; Simons, Peter C.; Smagley, Yelena; Strouse, Juan; Surviladze, Zurab; Thompson, Todd; Ursu, Oleg; Waller, Anna; Wandinger-Ness, Angela; Winter, Stuart S.; Wu, Yang; Young, Susan M.; Larson, Richard S.; Willman, Cheryl; Sklar, Larry A.
Academia and small business research units are poised to play an increasing role in drug discovery, with drug repurposing as one of the major areas of activity. Here we summarize project status for a number of drugs or classes of drugs: raltegravir, cyclobenzaprine, benzbromarone, mometasone furoate, astemizole, R-naproxen, ketorolac, tolfenamic acid, phenothiazines, methylergonovine maleate and beta-adrenergic receptor drugs, respectively. Based on this multi-year, multi-project experience we discuss strengths and weaknesses of academic-based drug repurposing research. Translational, target and disease foci are strategic advantages fostered by close proximity and frequent interactions between basic and clinical scientists, which often result in discovering new modes of action for approved drugs. On the other hand, lack of integration with pharmaceutical sciences and toxicology, lack of appropriate intellectual coverage and issues related to dosing and safety may lead to significant drawbacks. The development of a more streamlined regulatory process world-wide, and the development of pre-competitive knowledge transfer systems such as a global healthcare database focused on regulatory and scientific information for drugs world-wide, are among the ideas proposed to improve the process of academic drug discovery and repurposing, and to overcome the “valley of death” by bridging basic to clinical sciences. PMID:22368688
Hristovski, Dimitar; Kastrin, Andrej; Dinevski, Dejan; Burgun, Anita; Žiberna, Lovro; Rindflesch, Thomas C
We report on our research in using literature-based discovery (LBD) to provide pharmacological and/or pharmacogenomic explanations for reported adverse drug effects. The goal of LBD is to generate novel and potentially useful hypotheses by analyzing the scientific literature and optionally some additional resources. Our assumption is that drugs have effects on some genes or proteins and that these genes or proteins are associated with the observed adverse effects. Therefore, by using LBD we try to find genes or proteins that link the drugs with the reported adverse effects. These genes or proteins can be used to provide insight into the processes causing the adverse effects. Initial results show that our method has the potential to assist in explaining reported adverse drug effects.
There is a neat distinction between general purpose statistical techniques and quantitative models developed for specific problems. Principal Component Analysis (PCA) blurs this distinction: while being a general purpose statistical technique, it implies a peculiar style of reasoning. PCA is a 'hypothesis generating' tool creating a statistical mechanics frame for biological systems modeling without the need for strong a priori theoretical assumptions. This makes PCA of utmost importance for approaching drug discovery by a systemic perspective overcoming too narrow reductionist approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.
Chaudhari, Rajan; Tan, Zhi; Huang, Beibei; Zhang, Shuxing
Over the past couple of years, the cost of drug development has sharply increased along with the high rate of clinical trial failures. Such increase in expenses is partially due to the inability of the "one drug - one target" approach to predict drug side effects and toxicities. To tackle this issue, an alternative approach, known as polypharmacology, is being adopted to study small molecule interactions with multiple targets. Apart from developing more potent and effective drugs, this approach allows for studies of off-target activities and the facilitation of drug repositioning. Although exhaustive polypharmacology studies in-vitro or in-vivo are not practical, computational methods of predicting unknown targets or side effects are being developed. Areas covered: This article describes various computational approaches that have been developed to study polypharmacology profiles of small molecules. It also provides a brief description of the algorithms used in these state-of-the-art methods. Expert opinion: Recent success in computational prediction of multi-targeting drugs has established polypharmacology as a promising alternative approach to tackle some of the daunting complications in drug discovery. This will not only help discover more effective agents, but also present tremendous opportunities to study novel target pharmacology and facilitate drug repositioning efforts in the pharmaceutical industry.
Pérez-Nueno, Violeta I
Over the past three decades, the predominant paradigm in drug discovery was designing selective ligands for a specific target to avoid unwanted side effects. However, in the last 5 years, the aim has shifted to take into account the biological network in which they interact. Quantitative and Systems Pharmacology (QSP) is a new paradigm that aims to understand how drugs modulate cellular networks in space and time, in order to predict drug targets and their role in human pathophysiology. This review discusses existing computational and experimental QSP approaches such as polypharmacology techniques combined with systems biology information and considers the use of new tools and ideas in a wider 'systems-level' context in order to design new drugs with improved efficacy and fewer unwanted off-target effects. The use of network biology produces valuable information such as new indications for approved drugs, drug-drug interactions, proteins-drug side effects and pathways-gene associations. However, we are still far from the aim of QSP, both because of the huge effort needed to model precisely biological network models and the limited accuracy that we are able to reach with those. Hence, moving from 'one molecule for one target to give one therapeutic effect' to the 'big systems-based picture' seems obvious moving forward although whether our current tools are sufficient for such a step is still under debate.
Khalid, Nauman; Kobayashi, Isao; Nakajima, Mitsutoshi
Microelectromechanical systems (MEMS) and micro total analysis systems (μTAS) revolutionized the biochemical and electronic industries, and this miniaturization process became a key driver for many markets. Now, it is a driving force for innovations in life sciences, diagnostics, analytical sciences, and chemistry, which are called 'lab-on-a-chip, (LOC)' devices. The use of these devices allows the development of fast, portable, and easy-to-use systems with a high level of functional integration for applications such as point-of-care diagnostics, forensics, the analysis of biomolecules, environmental or food analysis, and drug development. In this review, we report on the latest developments in fabrication methods and production methodologies to tailor LOC devices. A brief overview of scale-up strategies is also presented together with their potential applications in drug delivery and discovery. The impact of LOC devices on drug development and discovery has been extensively reviewed in the past. The current research focuses on fast and accurate detection of genomics, cell mutations and analysis, drug delivery, and discovery. The current research also differentiates the LOC devices into new terminology of microengineering, like organ-on-a-chip, stem cells-on-a-chip, human-on-a-chip, and body-on-a-chip. Key challenges will be the transfer of fabricated LOC devices from lab-scale to industrial large-scale production. Moreover, extensive toxicological studies are needed to justify the use of microfabricated drug delivery vehicles in biological systems. It will also be challenging to transfer the in vitro findings to suitable and promising in vivo models. WIREs Syst Biol Med 2017, 9:e1381. doi: 10.1002/wsbm.1381 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.
Swaminathan, Soumya; Sundaramurthi, Jagadish Chandrabose; Palaniappan, Alangudi Natarajan; Narayanan, Sujatha
Emergence of drug-resistant tuberculosis (DR-TB) is a big challenge in TB control. The delay in diagnosis of DR-TB leads to its increased transmission, and therefore prevalence. Recent developments in genomics have enabled whole genome sequencing (WGS) of Mycobacterium tuberculosis (M. tuberculosis) from 3-day-old liquid culture and directly from uncultured sputa, while new bioinformatics tools facilitate to determine DR mutations rapidly from the resulting sequences. The present drug discovery and development pipeline is filled with candidate drugs which have shown efficacy against DR-TB. Furthermore, some of the FDA-approved drugs are being evaluated for repurposing, and this approach appears promising as several drugs are reported to enhance efficacy of the standard TB drugs, reduce drug tolerance, or modulate the host immune response to control the growth of intracellular M. tuberculosis. Recent developments in genomics and bioinformatics along with new drug discovery collectively have the potential to result in synergistic impact leading to the development of a rapid protocol to determine the drug resistance profile of the infecting strain so as to provide personalized medicine. Hence, in this review, we discuss recent developments in WGS, bioinformatics and drug discovery to perceive how they would transform the management of tuberculosis in a timely manner.
Sun, Yishan; Dolmetsch, Ricardo E
Compared with other medical fields, psychiatry is particularly challenging for rational drug discovery. The therapeutic endpoints are abstract measures of cognitive and behavioral performance, for which we have a very limited understanding of the underlying biological mechanisms. Existing preclinical disease models are also limited in their translational fidelity. Recently, there have been active discussions on the use of human induced pluripotent stem cells (iPSCs) as a catalyzing research tool in psychiatry, but very few review articles in the field have given specific considerations to their use at the interface between psychiatric research and drug discovery. Here, we discuss recent perspectives emerging from this interface. For physicians and researchers on the clinical side, we explain how iPSC-based experimental approaches are placed at the crossroads with psychiatric genetics and how representative studies in the field are addressing biological mechanisms underlying psychiatric disorders. For researchers who directly work with iPSCs and aspire to develop new research techniques, we direct their attention to the utility of this approach for unmet needs in drug discovery workflows.
Tsopelas, Fotios; Vallianatou, Theodosia; Tsantili-Kakoulidou, Anna
The development of immobilized artificial membrane (IAM) chromatography has unfolded new perspectives for the use of chromatographic techniques in drug discovery, combining simulation of the environment of cell membranes with rapid measurements. The present review describes the characteristics of phosphatidylcholine-based stationary phases and analyses the molecular factors governing IAM retention in comparison to n-octanol-water and liposomes partitioning systems as well as to reversed phase chromatography. Other biomimetic stationary phases are also briefly discussed. The potential of IAM chromatography to model permeability through the main physiological barriers and drug membrane interactions is outlined. Further applications to calculate complex pharmacokinetic properties, related to tissue binding, and to screen drug candidates for phospholipidosis, as well as to estimate cell accumulation/retention are surveyed. The ambivalent nature of IAM chromatography, as a border case between passive diffusion and binding, defines its multiple potential applications. However, despite its successful performance in many permeability and drug-membrane interactions studies, IAM chromatography is still used as a supportive and not a stand-alone technique. Further studies looking at IAM chromatography in different biological processes are still required if this technique is to have a more focused and consistent application in drug discovery.
Lim, William K
G protein-coupled receptors (GPCRs) are the largest class of cell surface receptors in humans. They convey extracellular signals into the cell interior by activating intracellular processes such as heterotrimeric G protein-dependent signaling pathways. They are widely distributed in the nervous system, and mediate key physiological processes including cognition, mood, appetite, pain and synaptic transmission. With at least 30% of marketed drugs being GPCR modulators, they are a major therapeutic target in the pharmaceutical industry's drug discovery programs. This review will survey recently patented ligands for GPCRs implicated in CNS disorders, in particular the metabotropic glutamate, adenosine and cannabinoid receptors. Metabotropic glutamate receptors regulate signaling by glutamate, the major excitatory brain neurotransmitter, while adenosine is a ubiquitous neuromodulater mediating diverse physiological effects. Recent patents for ligands of these receptors include mGluR5 antagonists and adenosine A(1) receptor agonists. Cannabinoid receptors remain one of the most important GPCR drug discovery target due to the intense interest in CB(1) receptor antagonists for treating obesity and metabolic syndrome. Such small molecule ligands are the outcome of the continuing focus of many pharmaceutical companies to identify novel GPCR agonist, antagonist or allosteric modulators useful for CNS disorders, for which more effective drugs are eagerly awaited.
The application of structural genomics methods and approaches to proteins from organisms causing infectious diseases is making available the three dimensional structures of many proteins that are potential drug targets and laying the groundwork for structure aided drug discovery efforts. There are a number of structural genomics projects with a focus on pathogens that have been initiated worldwide. The Center for Structural Genomics of Infectious Diseases (CSGID) was recently established to apply state-of-the-art high throughput structural biology technologies to the characterization of proteins from the National Institute for Allergy and Infectious Diseases (NIAID) category A-C pathogens and organisms causing emerging, or re-emerging infectious diseases. The target selection process emphasizes potential biomedical benefits. Selected proteins include known drug targets and their homologs, essential enzymes, virulence factors and vaccine candidates. The Center also provides a structure determination service for the infectious disease scientific community. The ultimate goal is to generate a library of structures that are available to the scientific community and can serve as a starting point for further research and structure aided drug discovery for infectious diseases. To achieve this goal, the CSGID will determine protein crystal structures of 400 proteins and protein-ligand complexes using proven, rapid, highly integrated, and cost-effective methods for such determination, primarily by X-ray crystallography. High throughput crystallographic structure determination is greatly aided by frequent, convenient access to high-performance beamlines at third-generation synchrotron X-ray sources.
Quan, Yuan; Xiong, Le; Chen, Jing; Zhang, Hong-Yu
Mycobacterium tuberculosis (Mtb), the pathogen of tuberculosis (TB), is one of the most infectious bacteria in the world. The traditional strategy to combat TB involves targeting the pathogen directly; however, the rapid evolution of drug resistance lessens the efficiency of this anti-TB method. Therefore, in recent years, some researchers have turned to an alternative anti-TB strategy, which hinders Mtb infection through targeting host genes. In this work, using a theoretical genetic analysis, we identified 170 Mtb infection-associated genes from human genetic variations related to Mtb infection. Then, the agents targeting these genes were identified to have high potential as anti-TB drugs. In particular, the agents that can target multiple Mtb infection-associated genes are more druggable than the single-target counterparts. These potential anti-TB agents were further screened by gene expression data derived from connectivity map. As a result, some agents were revealed to have high interest for experimental evaluation. This study not only has important implications for anti-TB drug discovery, but also provides inspirations for streamlining the pipeline of modern drug discovery.
Recently, ab initio quantum mechanical calculations have been applied to large molecules, including biomolecular systems. The fragment molecular orbital (FMO) method is one of the most efficient approaches for the quantum mechanical investigation of such molecules. In the FMO method, dividing a target molecule into small fragments reduces computational effort. The clear definition of inter-fragment interaction energy (IFIE) as an expression of total energy is another valuable feature of the FMO method because it provides the ability to analyze interactions in biomolecules. Thus, the FMO method is expected to be useful for drug discovery. This study demonstrates applications of the FMO method related to drug discovery. First, IFIE, according to FMO calculations, was used in the optimization of drug candidates for the development of anti-prion compounds. The second example involved interaction analysis of the human immunodeficiency virus type 1 (HIV-1) protease and a drug compound that used a novel analytical method for dispersion interaction, i.e., fragment interaction analysis based on LMP2 (FILM).
Taylor, Alexandria P; Robinson, Ralph P; Fobian, Yvette M; Blakemore, David C; Jones, Lyn H; Fadeyi, Olugbeminiyi
New advances in synthetic methodologies that allow rapid access to a wide variety of functionalized heterocyclic compounds are of critical importance to the medicinal chemist as it provides the ability to expand the available drug-like chemical space and drive more efficient delivery of drug discovery programs. Furthermore, the development of robust synthetic routes that can readily generate bulk quantities of a desired compound help to accelerate the drug development process. While established synthetic methodologies are commonly utilized during the course of a drug discovery program, the development of innovative heterocyclic syntheses that allow for different bond forming strategies are having a significant impact in the pharmaceutical industry. This review will focus on recent applications of new methodologies in C-H activation, photoredox chemistry, borrowing hydrogen catalysis, multicomponent reactions, regio- and stereoselective syntheses, as well as other new, innovative general syntheses for the formation and functionalization of heterocycles that have helped drive project delivery. Additionally, the importance and value of collaborations between industry and academia in shaping the development of innovative synthetic approaches to functionalized heterocycles that are of greatest interest to the pharmaceutical industry will be highlighted.
Griebel, Guy; Holmes, Andrew
Anxiety disorders are the most prevalent group of psychiatric diseases, and have high personal and societal costs. The search for novel pharmacological treatments for these conditions is driven by the growing medical need to improve on the effectiveness and the side effect profile of existing drugs. A huge volume of data has been generated by anxiolytic drug discovery studies, which has led to the progression of numerous new molecules into clinical trials. However, the clinical outcome of these efforts has been disappointing, as promising results with novel agents in rodent studies have very rarely translated into effectiveness in humans. Here, we analyse the major trends from preclinical studies over the past 50 years conducted in the search for new drugs beyond those that target the prototypical anxiety-associated GABA (γ-aminobutyric acid)–benzodiazepine system, which have focused most intensively on the serotonin, neuropeptide, glutamate and endocannabinoid systems. We highlight various key issues that may have hampered progress in the field, and offer recommendations for how anxiolytic drug discovery can be more effective in the future. PMID:23989795
Gong, Zhen; Hu, Guoping; Li, Qiang; Liu, Zhiguo; Wang, Fei; Zhang, Xuejin; Xiong, Jian; Li, Peng; Xu, Yan; Ma, Rujian; Chen, Shuhui; Li, Jian
Hit identification is the starting point of small-molecule drug discovery and is therefore very important to the pharmaceutical industry. One of the most important approaches to identify a new hit is to screen a compound library using an in vitro assay. High-throughput screening has made great contributions to drug discovery since the 1990s but requires expensive equipment and facilities, and its success depends on the size of the compound library. Recent progress in the development of compound libraries has provided more efficient ways to identify new hits for novel drug targets, thereby helping to promote the development of the pharmaceutical industry, especially for first-in-class drugs. In this review, the sources and classification of compound libraries are summarized. The progress made in combinatorial libraries and DNA-encoded libraries is reviewed. Library design methods, especially for focused libraries, are introduced in detail. In the final part, the status of the compound libraries at WuXi is reported. Copyright© Bentham Science Publishers; For any queries, please email at firstname.lastname@example.org.
Frey, Jeremy G; Bird, Colin L
Reviews of the development of drug discovery through the 20(th) century recognised the importance of chemistry and increasingly bioinformatics, but had relatively little to say about the importance of computing and networked computing in particular. However, the design and discovery of new drugs is arguably the most significant single application of bioinformatics and cheminformatics to have benefitted from the increases in the range and power of the computational techniques since the emergence of the World Wide Web, commonly now referred to as simply 'the Web'. Web services have enabled researchers to access shared resources and to deploy standardized calculations in their search for new drugs. This article first considers the fundamental principles of Web services and workflows, and then explores the facilities and resources that have evolved to meet the specific needs of chem- and bio-informatics. This strategy leads to a more detailed examination of the basic components that characterise molecules and the essential predictive techniques, followed by a discussion of the emerging networked services that transcend the basic provisions, and the growing trend towards embracing modern techniques, in particular the Semantic Web. In the opinion of the authors, the issues that require community action are: increasing the amount of chemical data available for open access; validating the data as provided; and developing more efficient links between the worlds of cheminformatics and bioinformatics. The goal is to create ever better drug design services.
Mol, Peter G M; Arnardottir, Arna H; Straus, Sabine M J; de Graeff, Pieter A; Haaijer-Ruskamp, Flora M; Quik, Elise H; Krabbe, Paul F M; Denig, Petra
Aims To compare the values regulators attach to different drug effects of oral antidiabetic drugs with those of doctors and patients. Methods We administered a ‘discrete choice’ survey to regulators, doctors and patients with type 2 diabetes in The Netherlands. Eighteen choice sets comparing two hypothetical oral antidiabetic drugs were constructed with varying drug effects on glycated haemoglobin, cardiovascular risk, bodyweight, duration of gastrointestinal complaints, frequency of hypoglycaemia and risk of bladder cancer. Responders were asked each time which drug they preferred. Results Fifty-two regulators, 175 doctors and 226 patients returned the survey. Multinomial conditional logit analyses showed that cardiovascular risk reduction was valued by regulators positively (odds ratio 1.98, 95% confidence interval 1.11–3.53), whereas drug choices were negatively affected by persistent gastrointestinal problems (odds ratio 0.24, 95% confidence interval 0.14–0.41) and cardiovascular risk increase (odds ratio 0.49, 95% confidence interval 0.27–0.87). Doctors and patients valued these effects in a similar manner to regulators. The values that doctors attached to large changes in glycated haemoglobin and that both doctors and patients attached to hypoglycaemia and weight gain also reached statistical significance. No group's drug choice was affected by a small absolute change in risk of bladder cancer when presented in the context of other drug effects. When comparing the groups, the value attached by regulators to less frequent hypoglycaemic episodes was significantly smaller than by patients (P = 0.044). Conclusions Regulators may value major benefits and risks of drugs for an individual diabetes patient mostly in the same way as doctors and patients, but differences may exist regarding the value of minor or short-term drug effects. PMID:25469876
Background The early drug discovery phase in pharmaceutical research and development marks the beginning of a long, complex and costly process of bringing a new molecular entity to market. As such, it plays a critical role in helping to maintain a robust downstream clinical development pipeline. Despite its importance, however, to our knowledge there are no published in silico models to simulate the progression of discrete virtual projects through a discovery milestone system. Results Multiple variables were tested and their impact on productivity metrics examined. Simulations predict that there is an optimum number of scientists for a given drug discovery portfolio, beyond which output in the form of preclinical candidates per year will remain flat. The model further predicts that the frequency of compounds to successfully pass the candidate selection milestone as a function of time will be irregular, with projects entering preclinical development in clusters marked by periods of low apparent productivity. Conclusions The model may be useful as a tool to facilitate analysis of historical growth and achievement over time, help gauge current working group progress against future performance expectations, and provide the basis for dialogue regarding working group best practices and resource deployment strategies. PMID:23186040
Elmer, Greg I; Kafkafi, Neri
The discovery of truly efficacious treatments that lead to full recovery is a daunting task in psychiatric illness. A systems-based orientation to in vivo pharmacology has been suggested as a way to transform psychiatric drug discovery and development. A critical catalyst in the success of recent systems biology efforts has been the incorporation of data mining strategies. Our approach to the drug discovery problem has been to utilize the whole animal to provide a systems response that is subsequently mined for predictive attributes with known psychopharmacological value. Our in vivo data mining approach, termed Pattern Array, establishes a framework for screening novel chemical entities based upon a response that represents the net pharmacological effect on the system of interest, namely the central nervous system (CNS). Large scale screening of small molecules by non-conventional approaches such as this at a systems level may improve the identification of novel chemical entities with psychiatric utility. This type of approach will compliment the more labor-intensive models based upon construct validity. It will take the collective effort of many disciplines and numerous strategies in close association with clinical colleagues to address quality of life issues and breakthrough treatment barriers in psychiatric illness.
Wang, Lingle; Deng, Yuqing; Wu, Yujie; Kim, Byungchan; LeBard, David N; Wandschneider, Dan; Beachy, Mike; Friesner, Richard A; Abel, Robert
The accurate prediction of protein-ligand binding free energies remains a significant challenge of central importance in computational biophysics and structure-based drug design. Multiple recent advances including the development of greatly improved protein and ligand molecular mechanics force fields, more efficient enhanced sampling methods, and low-cost powerful GPU computing clusters have enabled accurate and reliable predictions of relative protein-ligand binding free energies through the free energy perturbation (FEP) methods. However, the existing FEP methods can only be used to calculate the relative binding free energies for R-group modifications or single-atom modifications and cannot be used to efficiently evaluate scaffold hopping modifications to a lead molecule. Scaffold hopping or core hopping, a very common design strategy in drug discovery projects, is critical not only in the early stages of a discovery campaign where novel active matter must be identified but also in lead optimization where the resolution of a variety of ADME/Tox problems may require identification of a novel core structure. In this paper, we introduce a method that enables theoretically rigorous, yet computationally tractable, relative protein-ligand binding free energy calculations to be pursued for scaffold hopping modifications. We apply the method to six pharmaceutically interesting cases where diverse types of scaffold hopping modifications were required to identify the drug molecules ultimately sent into the clinic. For these six diverse cases, the predicted binding affinities were in close agreement with experiment, demonstrating the wide applicability and the significant impact Core Hopping FEP may provide in drug discovery projects.
Bortolato, Andrea; Doré, Andrew S; Hollenstein, Kaspar; Tehan, Benjamin G; Mason, Jonathan S; Marshall, Fiona H
Class B GPCRs of the secretin family are important drug targets in many human diseases including diabetes, neurodegeneration, cardiovascular disease and psychiatric disorders. X-ray crystal structures for the glucagon receptor and corticotropin-releasing factor receptor 1 have now been published. In this review, we analyse the new structures and how they compare with each other and with Class A and F receptors. We also consider the differences in druggability and possible similarity in the activation mechanisms. Finally, we discuss the potential for the design of small-molecule modulators for these important targets in drug discovery. This new structural insight allows, for the first time, structure-based drug design methods to be applied to Class B GPCRs. PMID:24628305
We report the discovery of a series of new drug leads that have potent activity against Mycobacterium tuberculosis as well as against other bacteria, fungi, and a malaria parasite. The compounds are analogues of the new tuberculosis (TB) drug SQ109 (1), which has been reported to act by inhibiting a transporter called MmpL3, involved in cell wall biosynthesis. We show that 1 and the new compounds also target enzymes involved in menaquinone biosynthesis and electron transport, inhibiting respiration and ATP biosynthesis, and are uncouplers, collapsing the pH gradient and membrane potential used to power transporters. The result of such multitarget inhibition is potent inhibition of TB cell growth, as well as very low rates of spontaneous drug resistance. Several targets are absent in humans but are present in other bacteria, as well as in malaria parasites, whose growth is also inhibited. PMID:24568559
Embryonic stem cells provide a potential resource for research and drug screening. To make such a resource feasible, it is necessary to generate cells of sufficient quality and quantity. The challenge is to expand cell numbers while maintaining the fidelity of phenotype and to control and direct differentiation to produce the cell type of interest in a format that is suitable for drug screening. At present, large-scale culturing of human ES cell lines is problematic and provides substantial challenges. This article provides an overview of current bioprocessing techniques that could be used to generate cells for drug discovery applications. This will generate further technical expertise that can be applied in the production of cells for potential therapeutic applications.
Doweyko, Arthur M; Doweyko, Lidia M
Humankind has been in the business of discovering drugs for thousands of years. At present, small-molecule drug design is based on specific macromolecular receptors as targets for inhibition or modulation. To this end, a number of clever approaches have evolved over time: computer-aided techniques including structure-activity relationships and synthesis, high-throughput screening, quantitative structure-activity relationships, hypotheses derived from ligand- and/or structure-based information and focused library approaches. In recent years, several alternative strategies have appeared in the form of the emerging paradigms of polypharmacology, systems biology and personalized medicine. These innovations point to key challenges and breakthroughs likely to affect the future of small-molecule drug discovery.
Xu, Rong; Wang, QuanQiu
Schizophrenia (SCZ) is a common complex disorder with poorly understood mechanisms and no effective drug treatments. Despite the high prevalence and vast unmet medical need represented by the disease, many drug companies have moved away from the development of drugs for SCZ. Therefore, alternative strategies are needed for the discovery of truly innovative drug treatments for SCZ. Here, we present a disease phenome-driven computational drug repositioning approach for SCZ. We developed a novel drug repositioning system, PhenoPredict, by inferring drug treatments for SCZ from diseases that are phenotypically related to SCZ. The key to PhenoPredict is the availability of a comprehensive drug treatment knowledge base that we recently constructed. PhenoPredict retrieved all 18 FDA-approved SCZ drugs and ranked them highly (recall = 1.0, and average ranking of 8.49%). When compared to PREDICT, one of the most comprehensive drug repositioning systems currently available, in novel predictions, PhenoPredict represented clear improvements over PREDICT in Precision-Recall (PR) curves, with a significant 98.8% improvement in the area under curve (AUC) of the PR curves. In addition, we discovered many drug candidates with mechanisms of action fundamentally different from traditional antipsychotics, some of which had published literature evidence indicating their treatment benefits in SCZ patients. In summary, although the fundamental pathophysiological mechanisms of SCZ remain unknown, integrated systems approaches to studying phenotypic connections among diseases may facilitate the discovery of innovative SCZ drugs. PMID:26151312
Darvesh, Altaf S.; Carroll, Richard T.; Geldenhuys, Werner J.; Gudelsky, Gary A.; Klein, Jochen; Meshul, Charles K.; Van der Schyf, Cornelis J.
Introduction Microdialysis is an important in vivo sampling technique, useful in the assay of extracellular tissue fluid. The technique has both pre-clinical and clinical applications but is most widely used in neuroscience. The in vivo microdialysis technique allows measurement of neurotransmitters such as acetycholine (ACh), the biogenic amines including dopamine (DA), norepinephrine (NE) and serotonin (5-HT), amino acids such as glutamate (Glu) and gamma aminobutyric acid (GABA), as well as the metabolites of the aforementioned neurotransmitters, and neuropeptides in neuronal extracellular fluid in discrete brain regions of laboratory animals such as rodents and non-human primates. Areas covered In this review we present a brief overview of the principles and procedures related to in vivo microdialysis and detail the use of this technique in the pre-clinical measurement of drugs designed to be used in the treatment of chemical addiction, neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD) and as well as psychiatric disorders such as attention-deficit/hyperactivity disorder (ADHD) and schizophrenia. This review offers insight into the tremendous utility and versatility of this technique in pursuing neuropharmacological investigations as well its significant potential in rational drug discovery. Expert opinion In vivo microdialysis is an extremely versatile technique, routinely used in the neuropharmacological investigation of drugs used for the treatment of neurological disorders. This technique has been a boon in the elucidation of the neurochemical profile and mechanism of action of several classes of drugs especially their effects on neurotransmitter systems. The exploitation and development of this technique for drug discovery in the near future will enable investigational new drug candidates to be rapidly moved into the clinical trial stages and to market thus providing new successful therapies for neurological diseases
Wang, Zhiyun; Du, Jian; Che, Pao-Lin; Meledeo, M Adam; Yarema, Kevin J
Metabolic glycoengineering, a technique pioneered almost two decades ago wherein monosaccharide analogs are utilized to install non-natural sugars into the glycocalyx of mammalian cells, has undergone a recent flurry of advances spurred by efforts to make the methodology more efficient. This article describes the versatility of metabolic glycoengineering, which is a prime example of 'chemical glycobiology,' and gives an overview of its capability to endow complex carbohydrates in living cells and animals with interesting (and useful!) functionalities. Then an overview is provided describing how acylated monosaccharides, a class of molecules originally intended to be efficiently-used, membrane-permeable metabolic intermediates, have led to the discovery that a subset of these compounds (e.g. tributanoylated hexosamines) display unanticipated 'scaffold-dependent' activities; this finding establishes these molecules as a versatile platform for drug discovery.
Walker, Stephen M; Davies, Barry J
In addressing the challenges facing pharmaceutical R&D one question is frequently asked: how can continuous improvement (CI), delivered through a Lean Sigma approach, be applied in a research environment to deliver overall benefit? We show that taking a value chain approach to improvement projects in a discovery research organization, initially focusing on the drug discovery project delivery level (i.e. middle layer of the value chain), provides the foundation for an effective CI programme. The adaptation of Lean Sigma principles and methodology, combined with the tenacity and creativity of scientists, enabled the delivery of significant improvements in challenging areas, including target selection, project decision making and the compound design-make-test-analyse (DMTA) cycle. Copyright © 2011 Elsevier Ltd. All rights reserved.
Wang, Zhiyun; Du, Jian; Che, Pao-Lin; Meledeo, M Adam; Yarema, Kevin J
Metabolic glycoengineering, a technique pioneered almost two decades ago wherein monosaccharide analogs are utilized to install non-natural sugars into the glycocalyx of mammalian cells, has undergone a recent flurry of advances spurred by efforts to make the methodology more efficient. This article describes the versatility of metabolic glycoengineering, which is a prime example of ‘chemical glycobiology,’ and gives an overview of its capability to endow complex carbohydrates in living cells and animals with interesting (and useful!) functionalities. Then an overview is provided describing how acylated monosaccharides, a class of molecules originally intended to be efficiently-used, membrane-permeable metabolic intermediates, have led to the discovery that a subset of these compounds (e.g. tributanoylated hexosamines) display unanticipated ‘scaffold-dependent’ activities; this finding establishes these molecules as a versatile platform for drug discovery. PMID:19747874
Cha, Y; Erez, T; Reynolds, I J; Kumar, D; Ross, J; Koytiger, G; Kusko, R; Zeskind, B; Risso, S; Kagan, E; Papapetropoulos, S; Grossman, I; Laifenfeld, D
Drug repurposing holds the potential to bring medications with known safety profiles to new patient populations. Numerous examples exist for the identification of new indications for existing molecules, most stemming from serendipitous findings or focused recent efforts specifically limited to the mode of action of a specific drug. In recent years, the need for new approaches to drug R&D, combined with the advent of big-data repositories and associated analytics has generated interest in developing systematic approaches to drug repurposing. A variety of innovative computational methods to enable systematic repurposing screens, experimental as well as through in-silico approaches, have emerged. An efficient drug repurposing pipeline requires the combination of access to molecule data, appropriate analytical expertise to enable robust insights, expertise and experimental set up for validation, and clinical development know-how. In this review we describe some of the main approaches to systematic repurposing, discuss the various players in this field and the need for strategic collaborations to increase likelihood of success in bringing existing molecules to new indications, as well as the current advantages, considerations and challenges in repurposing as a drug-development strategy pursued by pharmaceutical companies.
Bertucci, Carlo; Pistolozzi, Marco; De Simone, Angela
Chirality plays a fundamental role in determining the pharmacodynamic and pharmacokinetic properties of drugs, and contributes significantly to our understanding of the mechanisms that lie behind biorecognition phenomena. Circular dichroism spectroscopy is the technique of choice for determining the stereochemistry of chiral drugs and proteins, and for monitoring and characterizing molecular recognition phenomena in solution. The role of chirality in our understanding of recognition phenomena at the molecular level is discussed here via several selected systems of interest in the drug discovery and development area. The examples were selected in order to underline the utility of circular dichroism in emerging studies of protein-protein interactions in biological context. In particular, the following aspects are discussed here: the relationship between stereochemistry and pharmacological activity--stereochemical characterization of new leads and drugs; stereoselective binding of leads and drugs to target proteins--the binding of drugs to serum albumins; conformational transitions of peptides and proteins of physiological relevance, and the stereochemical characterization of therapeutic peptides.
Cheng, Feng; Theodorescu, Dan; Schulman, Ira G.; Lee, Jae K.
Liver toxicity (hepatotoxicity) is a critical issue in drug discovery and development. Standard preclinical evaluation of drug hepatotoxicity is generally performed using in vivo animal systems. However, only a small number of preselected compounds can be examined in vivo due to high experimental costs. A more efficient yet accurate screening technique which can identify potentially hepatotoxic compounds in the early stages of drug development would thus be valuable. Here, we develop and apply a novel genomic prediction technique for screening hepatotoxic compounds based on in vitro human liver cell tests. Using a training set of in vivo rodent experiments for drug hepatotoxicity evaluation, we discovered common biomarkers of drug-induced liver toxicity among six heterogeneous compounds. This gene set was further triaged to a subset of 32 genes that can be used as a multi-gene expression signature to predict hepatotoxicity. This multi-gene predictor was independently validated and showed consistently high prediction performance on five test sets of in vitro human liver cell and in vivo animal toxicity experiments. The predictor also demonstrated utility in evaluating different degrees of toxicity in response to drug concentrations which may be useful not only for discerning a compound’s general hepatotoxicity but also for determining its toxic concentration. PMID:21884709
Tipping, W. J.; Lee, M.; Serrels, A.; Brunton, V. G.
Optical microscopy techniques have emerged as a cornerstone of biomedical research, capable of probing the cellular functions of a vast range of substrates, whilst being minimally invasive to the cells or tissues of interest. Incorporating biological imaging into the early stages of the drug discovery process can provide invaluable information about drug activity within complex disease models. Spontaneous Raman spectroscopy has been widely used as a platform for the study of cells and their components based on chemical composition; but slow acquisition rates, poor resolution and a lack of sensitivity have hampered further development. A new generation of stimulated Raman techniques is emerging which allows the imaging of cells, tissues and organisms at faster acquisition speeds, and with greater resolution and sensitivity than previously possible. This review focuses on the development of stimulated Raman scattering (SRS), and covers the use of bioorthogonal tags to enhance sample detection, and recent applications of both spontaneous Raman and SRS as novel imaging platforms to facilitate the drug discovery process. PMID:26839248
Maiese, Kenneth; Chong, Zhao Zhong; Shang, Yan Chen; Hou, Jinling
Globally, developed nations spend a significant amount of their resources on healthcare initiatives that poorly translate into increased population life expectancy. As an example, the United States devotes sixteen percent of its gross domestic product to healthcare, the highest level in the world, but falls behind other nations that enjoy greater individual life expectancy. These observations point to the need for pioneering avenues of drug discovery to increase lifespan with controlled costs. In particular, innovative drug development for metabolic disorders such as diabetes mellitus (DM) becomes increasingly critical given that the number of diabetic individuals will increase exponentially over the next twenty years. Here we discuss the elucidation and targeting of novel cellular pathways that are intimately tied to oxidative stress in DM for new treatment strategies. Pathways that involve wingless, NAD+ precursors, and cytokines govern complex biological pathways that determine both cell survival and longevity during DM and its complications. Furthermore, the role of these entities as biomarkers for disease can further enhance their utility irrespective of their treatment potential. Greater understanding of the intricacies of these unique cellular mechanisms will shape future drug discovery for DM to provide focused clinical care with limited or absent long-term complications. PMID:20220043
Lovitt, Carrie J; Shelper, Todd B; Avery, Vicky M
Human cancer cell lines are an integral part of drug discovery practices. However, modeling the complexity of cancer utilizing these cell lines on standard plastic substrata, does not accurately represent the tumor microenvironment. Research into developing advanced tumor cell culture models in a three-dimensional (3D) architecture that more prescisely characterizes the disease state have been undertaken by a number of laboratories around the world. These 3D cell culture models are particularly beneficial for investigating mechanistic processes and drug resistance in tumor cells. In addition, a range of molecular mechanisms deconstructed by studying cancer cells in 3D models suggest that tumor cells cultured in two-dimensional monolayer conditions do not respond to cancer therapeutics/compounds in a similar manner. Recent studies have demonstrated the potential of utilizing 3D cell culture models in drug discovery programs; however, it is evident that further research is required for the development of more complex models that incorporate the majority of the cellular and physical properties of a tumor.
França, Tanos Celmar Costa
In the last decades, homology modeling has become a popular tool to access theoretical three-dimensional (3D) structures of molecular targets. So far several 3D models of proteins have been built by this technique and used in a great diversity of structural biology studies. But are those models consistent enough with experimental structures to make this technique an effective and reliable tool for drug discovery? Here we present, briefly, the fundamentals and current state-of-the-art of the homology modeling techniques used to build 3D structures of molecular targets, which experimental structures are not available in databases, and list some of the more important works, using this technique, available in literature today. In many cases those studies have afforded successful models for the drug design of more selective agonists/antagonists to the molecular targets in focus and guided promising experimental works, proving that, when the appropriate templates are available, useful models can be built using some of the several software available today for this purpose. Limitations of the experimental techniques used to solve 3D structures allied to constant improvements in the homology modeling software will maintain the need for theoretical models, establishing the homology modeling as a fundamental tool for the drug discovery.
Khachaturian, Zaven S
The rapid pace of neurobiology research has increased the prospects of developing drugs to prevent neurodegenerative disorders. Although the goal of delaying the onset of brain disorders may be within the grasp of modern medicine, there are several critical barriers to progress. Among these is the lack of appropriate models and modeling systems for specific neurodegenerative diseases. Traditionally, in drug discovery, testing, and development, a combination of models is used. These include in vitro, in vivo, transgenic, and other animal models. However, each of these models has limitations. In this article, the author advocates the use of "in silico" modeling systems, which could complement currently available models and enable investigators to simulate alternative strategies to modulate neural function in a dynamic interactive mode. Advances in computer technology, including increasing speed and memory, and ready access to parallel processing systems have made it easier for investigators to develop databases for computer abstractions of neural function and dysfunction and to begin to develop prototypes for use in complex systems modeling environments. Multimodeling systems have been widely used in other areas of science to study emergent behavior of complex systems, such as the impact of atmospheric changes on weather, flight patterns of birds in a flock, and the behavior of traders in a commodities market. Adoption of such approaches should increase understanding of the complexities of signal transduction pathways in neural networks and accelerate the drug discovery process.
Smith, Thomas J.
Green tea is made from unfermented dried leaves from Camellia sinensis and has been consumed by humans for thousands of years. For nearly as long, it has been used as a folk remedy for a wide array of diseases. More recently, a large number of in-vitro and in-vivo scientific studies have supported this ancient contention that the polyphenols from green tea can provide a number of health benefits. Since these compounds are clearly safe for human consumption and ubiquitous in the food supply, they are highly attractive as lead compounds for drug discovery programs. However, as drugs, they are far from optimum. They are relatively unstable, poorly absorbed, and readily undergo a number of metabolic transformations by intestinal microbiota and human enzymes. Further, since these compounds target a wide array of biological systems, in-vivo testing is rather difficult since effects on alternative pathways need to be carefully eliminated. The purpose of this review is to discuss some of the challenges and benefits of pursuing this family of compounds for drug discovery. PMID:21731575
Lovitt, Carrie J.; Shelper, Todd B.; Avery, Vicky M.
Human cancer cell lines are an integral part of drug discovery practices. However, modeling the complexity of cancer utilizing these cell lines on standard plastic substrata, does not accurately represent the tumor microenvironment. Research into developing advanced tumor cell culture models in a three-dimensional (3D) architecture that more prescisely characterizes the disease state have been undertaken by a number of laboratories around the world. These 3D cell culture models are particularly beneficial for investigating mechanistic processes and drug resistance in tumor cells. In addition, a range of molecular mechanisms deconstructed by studying cancer cells in 3D models suggest that tumor cells cultured in two-dimensional monolayer conditions do not respond to cancer therapeutics/compounds in a similar manner. Recent studies have demonstrated the potential of utilizing 3D cell culture models in drug discovery programs; however, it is evident that further research is required for the development of more complex models that incorporate the majority of the cellular and physical properties of a tumor. PMID:24887773
Maiese, Kenneth; Chong, Zhao Zhong; Shang, Yan Chen; Hou, Jinling
Globally, developed nations spend a significant amount of their resources on health care initiatives that poorly translate into increased population life expectancy. As an example, the United States devotes 16% of its gross domestic product to health care, the highest level in the world, but falls behind other nations that enjoy greater individual life expectancy. These observations point to the need for pioneering avenues of drug discovery to increase life span with controlled costs. In particular, innovative drug development for metabolic disorders such as diabetes mellitus becomes increasingly critical given that the number of diabetic people will increase exponentially over the next 20 years. This article discusses the elucidation and targeting of novel cellular pathways that are intimately tied to oxidative stress in diabetes mellitus for new treatment strategies. Pathways that involve wingless, β-nicotinamide adenine dinucleotide (NAD(+)) precursors, and cytokines govern complex biological pathways that determine both cell survival and longevity during diabetes mellitus and its complications. Furthermore, the role of these entities as biomarkers for disease can further enhance their utility irrespective of their treatment potential. Greater understanding of the intricacies of these unique cellular mechanisms will shape future drug discovery for diabetes mellitus to provide focused clinical care with limited or absent long-term complications.
Several diseases are characterized by alterations in the molecular distribution of vascular structures, presenting the opportunity to use monoclonal antibodies for clinical therapies. This pharmaceutical strategy, often referred to as "vascular targeting", has promise in promoting the discovery and development of selective biological drugs to regulate angiogenesis-related diseases such as cancer. Various experimental approaches have been utilized to discover accessible vascular markers of health and disease at the protein level. Our group has developed a new chemical proteomics technology to identify and quantify accessible vascular proteins in normal organs and at disease sites. Our developed methodology relies on the perfusion of animal models with suitable ester derivatives of biotin, which react with the primary amine groups of proteins as soon as the molecules are attached. This presentation reports biomedical applications based on vascular targeting strategies, as well as methodologies that have been used to discover new vascular targets. The identification of antigens located in the stromal tissue of pathological blood vessels may provide attractive targets for the development of antibody drugs. This method will also provide an efficient discovery target that could lead to the development of novel antibody drugs.
Okada, Yukinori; Wu, Di; Trynka, Gosia; Raj, Towfique; Terao, Chikashi; Ikari, Katsunori; Kochi, Yuta; Ohmura, Koichiro; Suzuki, Akari; Yoshida, Shinji; Graham, Robert R; Manoharan, Arun; Ortmann, Ward; Bhangale, Tushar; Denny, Joshua C; Carroll, Robert J; Eyler, Anne E; Greenberg, Jeffrey D; Kremer, Joel M; Pappas, Dimitrios A; Jiang, Lei; Yin, Jian; Ye, Lingying; Su, Ding-Feng; Yang, Jian; Xie, Gang; Keystone, Ed; Westra, Harm-Jan; Esko, Tõnu; Metspalu, Andres; Zhou, Xuezhong; Gupta, Namrata; Mirel, Daniel; Stahl, Eli A; Diogo, Dorothée; Cui, Jing; Liao, Katherine; Guo, Michael H; Myouzen, Keiko; Kawaguchi, Takahisa; Coenen, Marieke J H; van Riel, Piet L C M; van de Laar, Mart A F J; Guchelaar, Henk-Jan; Huizinga, Tom W J; Dieudé, Philippe; Mariette, Xavier; Bridges, S Louis; Zhernakova, Alexandra; Toes, Rene E M; Tak, Paul P; Miceli-Richard, Corinne; Bang, So-Young; Lee, Hye-Soon; Martin, Javier; Gonzalez-Gay, Miguel A; Rodriguez-Rodriguez, Luis; Rantapää-Dahlqvist, Solbritt; Arlestig, Lisbeth; Choi, Hyon K; Kamatani, Yoichiro; Galan, Pilar; Lathrop, Mark; Eyre, Steve; Bowes, John; Barton, Anne; de Vries, Niek; Moreland, Larry W; Criswell, Lindsey A; Karlson, Elizabeth W; Taniguchi, Atsuo; Yamada, Ryo; Kubo, Michiaki; Liu, Jun S; Bae, Sang-Cheol; Worthington, Jane; Padyukov, Leonid; Klareskog, Lars; Gregersen, Peter K; Raychaudhuri, Soumya; Stranger, Barbara E; De Jager, Philip L; Franke, Lude; Visscher, Peter M; Brown, Matthew A; Yamanaka, Hisashi; Mimori, Tsuneyo; Takahashi, Atsushi; Xu, Huji; Behrens, Timothy W; Siminovitch, Katherine A; Momohara, Shigeki; Matsuda, Fumihiko; Yamamoto, Kazuhiko; Plenge, Robert M
A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses--as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes--to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.
Schreyer, Adrian; Blundell, Tom
Harnessing data from the growing number of protein-ligand complexes in the Protein Data Bank is an important task in drug discovery. In order to benefit from the abundance of three-dimensional structures, structural data must be integrated with sequence as well as chemical data and the protein-small molecule interactions characterized structurally at the inter-atomic level. In this study, we present CREDO, a new publicly available database of protein-ligand interactions, which represents contacts as structural interaction fingerprints, implements novel features and is completely scriptable through its application programming interface. Features of CREDO include implementation of molecular shape descriptors with ultrafast shape recognition, fragmentation of ligands in the Protein Data Bank, sequence-to-structure mapping and the identification of approved drugs. Selected analyses of these key features are presented to highlight a range of potential applications of CREDO. The CREDO dataset has been released into the public domain together with the application programming interface under a Creative Commons license at http://www-cryst.bioc.cam.ac.uk/credo. We believe that the free availability and numerous features of CREDO database will be useful not only for commercial but also for academia-driven drug discovery programmes.
Lushington, Gerald H.; Dong, Yinghua; Theertham, Bhargav
The magnitude of the challenges in preclinical drug discovery is evident in the large amount of capital invested in such efforts in pursuit of a small static number of eventually successful marketable therapeutics. An explosion in the availability of potentially drug-like compounds and chemical biology data on these molecules can provide us with the means to improve the eventual success rates for compounds being considered at the preclinical level, but only if the community is able to access available information in an efficient and meaningful way. Thus, chemical database resources are critical to any serious drug discovery effort. This paper explores the basic principles underlying the development and implementation of chemical databases, and examines key issues of how molecular information may be encoded within these databases so as to enhance the likelihood that users will be able to extract meaningful information from data queries. In addition to a broad survey of conventional data representation and query strategies, key enabling technologies such as new context-sensitive chemical similarity measures and chemical cartridges are examined, with recommendations on how such resources may be integrated into a practical database environment. PMID:23782037
Elson, Elliot L.; Genin, Guy M.
The functions, form and mechanical properties of cells are inextricably linked to their extracellular environment. Cells from solid tissues change fundamentally when, isolated from this environment, they are cultured on rigid two-dimensional substrata. These changes limit the significance of mechanical measurements on cells in two-dimensional culture and motivate the development of constructs with cells embedded in three-dimensional matrices that mimic the natural tissue. While measurements of cell mechanics are difficult in natural tissues, they have proven effective in engineered tissue constructs, especially constructs that emphasize specific cell types and their functions, e.g. engineered heart tissues. Tissue constructs developed as models of disease also have been useful as platforms for drug discovery. Underlying the use of tissue constructs as platforms for basic research and drug discovery is integration of multiscale biomaterials measurement and computational modelling to dissect the distinguishable mechanical responses separately of cells and extracellular matrix from measurements on tissue constructs and to quantify the effects of drug treatment on these responses. These methods and their application are the main subjects of this review. PMID:26855763
This work postulates the thesis that the development of the contemporary psychopharmacology, which began with the chemical changes imposed to molecules with antihistaminergic properties, modelled the current ethiopatogenic theories of mental diseases. The development of chlorpromazine and imipramine was coincident with the beginning of the research about neurotransmission. This coincidence contributed for the construction of the dopaminergic theory of schizophrenia and in the monoaminergic theory of depression. Limitations of the effectivity of current drugs, as observed in the trials CATIE and STAR-D may justify a change of perspective in the search for new molecular targets for the treatment of both diseases. Historical data are provided to illustrate the above mentioned thesis, in the perspective of two epistemological concepts: the context of discovery proposed by Hans Reichenbach and the epistemological obstacle, proposed by Gaston Bachelard.
DeLano, Warren L
Widespread adoption of open-source software for network infrastructure, web servers, code development, and operating systems leads one to ask how far it can go. Will "open source" spread broadly, or will it be restricted to niches frequented by hopeful hobbyists and midnight hackers? Here we identify reasons for the success of open-source software and predict how consumers in drug discovery will benefit from new open-source products that address their needs with increased flexibility and in ways complementary to proprietary options.
Hulkower, Keren I; Herber, Renee L
Cell migration and invasion are processes that offer rich targets for intervention in key physiologic and pathologic phenomena such as wound healing and cancer metastasis. With the advent of high-throughput and high content imaging systems, there has been a movement towards the use of physiologically relevant cell-based assays earlier in the testing paradigm. This allows more effective identification of lead compounds and recognition of undesirable effects sooner in the drug discovery screening process. This article will review the effective use of several principle formats for studying cell motility: scratch assays, transmembrane assays, microfluidic devices and cell exclusion zone assays.
Kinch, Michael S; Flath, Richard
The way in which new medicines are discovered has irreversibly changed and the future sustainability of the enterprise is characterized by an unprecedented period of uncertainty. Herein, we convey that these changes provide unprecedented opportunities for many different players within the private and public sectors to work together and develop new models that ensure the sustainability of activities that have had an extraordinary impact; in terms of promoting public health and driving economic value. Specific examples of experiments are provided to demonstrate some of the new thinking that will be needed to ensure continuation of new drug discovery.
Mercola, Mark; Colas, Alexandre; Willems, Erik
The unexpected discovery that somatic cells can be reprogrammed to a pluripotent state yielding induced pluripotent stem cells has made it possible to produce cardiovascular cells exhibiting inherited traits and disorders. Use of these cells in high throughput analyses should broaden our insight into fundamental disease mechanisms and provide many benefits for patients, including new therapeutics and individually tailored therapies. Here we review recent progress in generating induced pluripotent stem cell-based models of cardiovascular disease and their multiple applications in drug development.
Bouvard, Claire; Barefield, Colleen; Zhu, Shoutian
Cancer stem cells (CSCs) have been identified in a growing list of malignancies and are believed to be responsible for cancer initiation, metastasis and relapse following certain therapies, even though they may only represent a small fraction of the cells in a given cancer. Like somatic stem cells and embryonic stem cells, CSCs are capable of self-renewal and differentiation into more mature, less tumorigenic cells that make up the bulk populations of cancer cells. Elimination of CSCs promises intriguing therapeutic potential and this concept has been adopted in preclinical drug discovery programs. Herein we will discuss the progress of these efforts, general considerations in practice, major challenges and possible solutions.
Alexandre, François-René; Domon, Lisianne; Frère, Stéphane; Testard, Alexandra; Thiéry, Valérie; Besson, Thierry
The interest of microwaves in drug discovery and multi-step synthesis is exposed with the aim of describing our strategy. These studies are connected with our work on the synthesis of original heterocyclic compounds with potential pharmaceutical value. Reactions in the presence of solvent and solvent-free synthesis can be realised under a variety of conditions; for some of these selected results are given, and where available, results from comparison with the same solvent-free conditions but with classical heating are given.
Sakurada, Kazuhiro; McDonald, Fiona M; Shimada, Fumiki
As William Shakespeare beautifully described, increasing age often causes loss of tissue and organ function. The increase in average life expectancy in many countries is generating an aging society and an increase in age-related health problems. Regenerative medicine is expected to be a powerful actor in this drama, and stem cell technology may hold the key to the development of innovative treatments for acute and chronic degenerative conditions. This Review surveys the present situation and some future prospects for regenerative medicine and stem cell based drug discovery.
Kappe, C Oliver; Dallinger, Doris
In the past few years, using microwave energy to heat and drive chemical reactions has become increasingly popular in the medicinal chemistry community. First described 20 years ago, this non-classical heating method has matured from a laboratory curiosity to an established technique that is heavily used in academia and industry. One of the many advantages of using rapid 'microwave flash heating' for chemical synthesis is the dramatic reduction in reaction times--from days and hours to minutes and seconds. As will be discussed here, there are good reasons why many pharmaceutical companies are incorporating microwave chemistry into their drug discovery efforts.
Schreyer, Adrian M; Blundell, Tom L
CREDO is a unique relational database storing all pairwise atomic interactions of inter- as well as intra-molecular contacts between small molecules and macromolecules found in experimentally determined structures from the Protein Data Bank. These interactions are integrated with further chemical and biological data. The database implements useful data structures and algorithms such as cheminformatics routines to create a comprehensive analysis platform for drug discovery. The database can be accessed through a web-based interface, downloads of data sets and web services at http://www-cryst.bioc.cam.ac.uk/credo. Database URL: http://www-cryst.bioc.cam.ac.uk/credo.
Spyrakis, Francesca; Ahmed, Mostafa H; Bayden, Alexander S; Cozzini, Pietro; Mozzarelli, Andrea; Kellogg, Glen E
The value of thoroughly understanding the thermodynamics specific to a drug discovery/design study is well known. Over the past decade, the crucial roles of water molecules in protein structure, function, and dynamics have also become increasingly appreciated. This Perspective explores water in the biological environment by adopting its point of view in such phenomena. The prevailing thermodynamic models of the past, where water was seen largely in terms of an entropic gain after its displacement by a ligand, are now known to be much too simplistic. We adopt a set of terminology that describes water molecules as being "hot" and "cold", which we have defined as being easy and difficult to displace, respectively. The basis of these designations, which involve both enthalpic and entropic water contributions, are explored in several classes of biomolecules and structural motifs. The hallmarks for characterizing water molecules are examined, and computational tools for evaluating water-centric thermodynamics are reviewed. This Perspective's summary features guidelines for exploiting water molecules in drug discovery.
Ortí, Leticia; Carbajo, Rodrigo J.; Pieper, Ursula; Eswar, Narayanan; Maurer, Stephen M.; Rai, Arti K.; Taylor, Ginger; Todd, Matthew H.; Pineda-Lucena, Antonio; Sali, Andrej; Marti-Renom, Marc A.
Background Conventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R&D institutions ranging from private–public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues—open source drug discovery—has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such “kernels”. Methodology/Principal Findings Here, we use a computational pipeline for: (i) comparative structure modeling of target proteins, (ii) predicting the localization of ligand binding sites on their surfaces, and (iii) assessing the similarity of the predicted ligands to known drugs. Our kernel currently contains 143 and 297 protein targets from ten pathogen genomes that are predicted to bind a known drug or a molecule similar to a known drug, respectively. The kernel provides a source of potential drug targets and drug candidates around which an online open source community can nucleate. Using NMR spectroscopy, we have experimentally tested our predictions for two of these targets, confirming one and invalidating the other. Conclusions/Significance The TDI kernel, which is being offered under the Creative Commons attribution share-alike license for free and unrestricted use, can be accessed on the World Wide Web at http://www.tropicaldisease.org. We hope that the kernel will facilitate collaborative efforts towards the discovery of new drugs against parasites that cause tropical diseases. PMID:19381286
BIT's Seventh Annual International Drug Discovery Science and Technology Congress, held in Shanghai, included topics covering new therapeutic and technological developments in the field of drug discovery. This conference report highlights selected presentations on open-access approaches to R&D, novel and multifactorial targets, and technologies that assist drug discovery. Investigational drugs discussed include the anticancer agents astuprotimut-r (GlaxoSmithKline plc) and AS-1411 (Antisoma plc).
Abdelraheem, Eman M. M.; Camacho, Carlos; Dömling, Alexander
Introduction Protein–protein interactions (PPIs) are important targets for understanding fundamental biology and for the development of therapeutic agents. Based on different physicochemical properties, numerous pieces of software (e.g PocketQuery, Anchor and FTMap) have been reported to find pockets on protein surfaces and have applications in facilitating the design and discovery of small molecular weight compounds which bind to these pockets. Areas covered The authors discuss a pocket-centric method of analyzing protein-protein interaction interfaces, which prioritize their pockets for small molecule drug discovery and the importance of multicomponent reaction (MCR) chemistry as starting points for undruggable targets. The authors also provide their perspectives on the field Expert opinion Only the tight interplay of efficient computational methods capable of screening a large chemical space and fast synthetic chemistry will lead to progress in the rational design of PPI antagonists in the future. Early drug discovery platforms will also benefit from efficient rapid feedback loops from early clinical research back to molecular design and the medicinal chemistry bench. PMID:26296101
Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves
We propose a new computational method for discovery of possible adverse drug reactions. The method consists of two key steps. First we use openly available resources to semi-automatically compile a consolidated data set describing drugs and their features (e.g., chemical structure, related targets, indications or known adverse reaction). The data set is represented as a graph, which allows for definition of graph-based similarity metrics. The metrics can then be used for propagating known adverse reactions between similar drugs, which leads to weighted (i.e., ranked) predictions of previously unknown links between drugs and their possible side effects. We implemented the proposed method in the form of a software prototype and evaluated our approach by discarding known drug-side effect links from our data and checking whether our prototype is able to re-discover them. As this is an evaluation methodology used by several recent state of the art approaches, we could compare our results with them. Our approach scored best in all widely used metrics like precision, recall or the ratio of relevant predictions present among the top ranked results. The improvement was as much as 125.79% over the next best approach. For instance, the F1 score was 0.5606 (66.35% better than the next best method). Most importantly, in 95.32% of cases, the top five results contain at least one, but typically three correctly predicted side effect (36.05% better than the second best approach). PMID:28269889
Hoagland, Daniel; Zhao, Ying; Lee, Richard
Pediatric tuberculosis is an underappreciated global epidemic estimated to afflict around half a million children worldwide. This problem has historically been overlooked, due in part to their low social status and the difficulty in diagnosis of tuberculosis in children. Children are more susceptible to tuberculosis infection and disease progression, including rapid dissemination into extra-pulmonary infection sites. Treatment of pediatric tuberculosis infections has been traditionally built around agents used to treat the adult disease, but the disease pathology, drug pharmacokinetics and the safety window in children differs from the adult disease. This produces additional concerns for drug discovery and development of new agents. This review examines: (i) the safety concerns for current front and second line agents used to treat complex drug resistant infections and how this knowledge can be used to identify, prioritize and dose agents that may be better tolerated in pediatric populations; (ii) the chemistry and suitability of new drugs in the clinical development pipeline for tuberculosis for the treatment of pediatric infections indicating several new agents may offer significant improvements for the treatment of multi-drug resistant tuberculosis in children. PMID:26202201
Jones, Alan Wayne
Studies in the field of forensic pharmacology and toxicology would not be complete without some knowledge of the history of drug discovery, the various personalities involved, and the events leading to the development and introduction of new therapeutic agents. The first medicinal drugs came from natural sources and existed in the form of herbs, plants, roots, vines and fungi. Until the mid-nineteenth century nature's pharmaceuticals were all that were available to relieve man's pain and suffering. The first synthetic drug, chloral hydrate, was discovered in 1869 and introduced as a sedative-hypnotic; it is still available today in some countries. The first pharmaceutical companies were spin-offs from the textiles and synthetic dye industry and owe much to the rich source of organic chemicals derived from the distillation of coal (coal-tar). The first analgesics and antipyretics, exemplified by phenacetin and acetanilide, were simple chemical derivatives of aniline and p-nitrophenol, both of which were byproducts from coal-tar. An extract from the bark of the white willow tree had been used for centuries to treat various fevers and inflammation. The active principle in white willow, salicin or salicylic acid, had a bitter taste and irritated the gastric mucosa, but a simple chemical modification was much more palatable. This was acetylsalicylic acid, better known as Aspirin®, the first blockbuster drug. At the start of the twentieth century, the first of the barbiturate family of drugs entered the pharmacopoeia and the rest, as they say, is history.
Hon, Kam Lun; Lee, Vivian W Y
The drug development industry is restructuring worldwide in terms of the research and development process. As with pharmaceuticals in the west, China faces major challenges for drug discovery and development. Areas covered: In this review, the authors discuss anti-cancer, anti-allergy, anti-infectious, and proprietary Chinese Medicines (pCM) for various chronic diseases (such as the allergic diseases: eczema, asthma and allergic rhinitis), which remain the contemporary therapeutic strategies that are being explored and developed. Drug transporters, disease specific biomarkers, pharmacophores, bioactive natural products and pharmacogenetics are some aspects of research technologies. Proprietary Chinese medicine remains one of the most popular strategies. There is however the issue of good research documentation of efficacy versus adverse effects. China has a complex healthcare system involving a large patient pool. Expert opinion: Various factors can impact drug development in China including the concurrent use of both western and Chinese medicines, pharmacogenetic variances, lack of multidisciplinary team impact on disease management and drug safety. China may adopt the current development of big data analysis in other countries such as UK and US to build and centralize a nationwide database for better monitoring and clinical evaluation to provide more efficient care at a lower cost.
Stitziel, Nathan O; Kathiresan, Sekar
Identifying appropriate molecular targets is a critical step in drug development. Despite many advantages, the traditional tools of observational epidemiology and cellular or animal models of disease can be misleading in identifying causal pathways likely to lead to successful therapeutics. Here, we review some favorable aspects of human genetics studies that have the potential to accelerate drug target discovery. These include using genetic studies to identify pathways relevant to human disease, leveraging human genetics to discern causal relationships between biomarkers and disease, and studying genetic variation in humans to predict the potential efficacy and safety of inhibitory compounds aimed at molecular targets. We present some examples taken from studies of plasma lipids and coronary artery disease to highlight how human genetics can accelerate therapeutics development. Copyright © 2017 Elsevier Inc. All rights reserved.
Li, Qingliang; Cheng, Tiejun; Wang, Yanli; Bryant, Stephen H
PubChem is a public repository of small molecules and their biological properties. Currently, it contains more than 25 million unique chemical structures and 90 million bioactivity outcomes associated with several thousand macromolecular targets. To address the potential utility of this public resource for drug discovery, we systematically summarized the protein targets in PubChem by function, 3D structure and biological pathway. Moreover, we analyzed the potency, selectivity and promiscuity of the bioactive compounds identified for these biological targets, including the chemical probes generated by the NIH Molecular Libraries Program. As a public resource, PubChem lowers the barrier for researchers to advance the development of chemical tools for modulating biological processes and drug candidates for disease treatments. Published by Elsevier Ltd.
Chan, Chung Yu; Huang, Po-Hsun; Guo, Feng; Ding, Xiaoyun; Kapur, Vivek; Mai, John D; Yuen, Po Ki; Huang, Tony Jun
Considerable advances have been made in the development of micro-physiological systems that seek to faithfully replicate the complexity and functionality of animal and human physiology in research laboratories. Sometimes referred to as "organs-on-chips", these systems provide key insights into physiological or pathological processes associated with health maintenance and disease control, and serve as powerful platforms for new drug development and toxicity screening. In this Focus article, we review the state-of-the-art designs and examples for developing multiple "organs-on-chips", and discuss the potential of this emerging technology to enhance our understanding of human physiology, and to transform and accelerate the drug discovery and preclinical testing process. This Focus article highlights some of the recent technological advances in this field, along with the challenges that must be addressed for these technologies to fully realize their potential.
Davis, Andrew M; Plowright, Alleyn T; Valeur, Eric
The strong biological rationale to pursue challenging drug targets such as protein-protein interactions has stimulated the development of novel screening strategies, such as DNA-encoded libraries, to allow broader areas of chemical space to be searched. There has also been renewed interest in screening natural products, which are the result of evolutionary selection for a function, such as interference with a key signalling pathway of a competing organism. However, recent advances in several areas, such as understanding of the biosynthetic pathways for natural products, synthetic biology and the development of biosensors to detect target molecules, are now providing new opportunities to directly harness evolutionary pressure to identify and optimize compounds with desired bioactivities. Here, we describe innovations in the key components of such strategies and highlight pioneering examples that indicate the potential of the directed-evolution concept. We also discuss the scientific gaps and challenges that remain to be addressed to realize this potential more broadly in drug discovery.
Cheng, Tiejun; Pan, Yongmei; Hao, Ming; Wang, Yanli; Bryant, Stephen H
A bibliometric analysis of PubChem applications is presented by reviewing 1132 research articles. The massive volume of chemical structure and bioactivity data in PubChem and its online services have been used globally in various fields including chemical biology, medicinal chemistry and informatics research. PubChem supports drug discovery in many aspects such as lead identification and optimization, compound-target profiling, polypharmacology studies and unknown chemical identity elucidation. PubChem has also become a valuable resource for developing secondary databases, informatics tools and web services. The growing PubChem resource with its public availability offers support and great opportunities for the interrogation of pharmacological mechanisms and the genetic basis of diseases, which are vital for drug innovation and repurposing.
Zdrazil, Barbara; Chichester, Christine; Zander Balderud, Linda; Engkvist, Ola; Gaulton, Anna; Overington, John P
Transport proteins represent an eminent class of drug targets and ADMET (absorption, distribution, metabolism, excretion, toxicity) associated genes. There exists a large number of distinct activity assays for transport proteins, depending on not only the measurement needed (e.g. transport activity, strength of ligand–protein interaction), but also due to heterogeneous assay setups used by different research groups. Efforts to systematically organize this (divergent) bioassay data have large potential impact in Public-Private partnership and conventional commercial drug discovery. In this short review, we highlight some of the frequently used high-throughput assays for transport proteins, and we discuss emerging assay ontologies and their application to this field. Focusing on human P-glycoprotein (Multidrug resistance protein 1; gene name: ABCB1, MDR1), we exemplify how annotation of bioassay data per target class could improve and add to existing ontologies, and we propose to include an additional layer of metadata supporting data fusion across different bioassays.
Durrant, Jacob D; Amaro, Rommie E
The emergence of drug-resistant bacteria threatens to revert humanity back to the preantibiotic era. Even now, multidrug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the pipeline. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug-discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics, leading to improved hit rates and faster transitions to preclinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field. © 2015 John Wiley & Sons A/S.
Secondary metabolites from plants, animals and microorganisms have been proven to be an outstanding source for new and innovative drugs and show a striking structural diversity that supplements chemically synthesized compounds or libraries in drug discovery programs. Unfortunately, extracts from natural sources are usually complex mixtures of compounds:: often generated in time consuming and for the most part manual processes. As quality and quantity of the provided samples play a pivotal role in the success of high-throughput screening programs this poses serious problems. In order to make samples of natural origin competitive with synthetic compound libraries, we devised a novel, automated sample preparation procedure based on solid-phase extraction (SPE). By making use of a modified Zymark RapidTrace® SPE workstation an easy-to-handle and effective fractionation method has been developed which allows the generation of highquality samples from natural origin, fulfilling the requirements of an integration into high-throughput screening programs. PMID:18924703
Cheng, Tiejun; Pan, Yongmei; Hao, Ming; Wang, Yanli; Bryant, Stephen H.
A bibliometric analysis of PubChem applications is presented by reviewing 1132 research articles. The massive volume of chemical structure and bioactivity data in PubChem and its online services has been used globally in various fields including chemical biology, medicinal chemistry and informatics research. PubChem supports drug discovery in many aspects such as lead identification and optimization, compound–target profiling, polypharmacology studies and unknown chemical identity elucidation. PubChem has also become a valuable resource for developing secondary databases, informatics tools and web services. The growing PubChem resource with its public availability offers support and great opportunities for the interrogation of pharmacological mechanisms and the genetic basis of diseases, which are vital for drug innovation and repurposing. PMID:25168772
Hurko, Orest; Ryan, John L.
Summary: Of all the therapeutic areas, diseases of the CNS provide the biggest challenges to translational research in this era of increased productivity and novel targets. Risk reduction by translational research incorporates the “learn” phase of the “learn and confirm” paradigm proposed over a decade ago. Like traditional drug discovery in vitro and in laboratory animals, it precedes the traditional phase 1–3 studies of drug development. The focus is on ameliorating the current failure rate in phase 2 and the delays resulting from suboptimal choices in four key areas: initial test subjects, dosing, sensitive and early detection of therapeutic effect, and recognition of differences between animal models and human disease. Implementation of new technologies is the key to success in this emerging endeavor. PMID:16489374
Chan, Chung Yu; Huang, Po-Hsun; Guo, Feng; Ding, Xiaoyun; Kapur, Vivek; Mai, John D.
Considerable advances have been made in the development of micro-physiological systems that seek to faithfully replicate the complexity and functionality of animal and human physiology in research laboratories. Sometimes referred to as “organs-on-chips”, these systems provide key insights into physiological or pathological processes associated with health maintenance and disease control, and serve as powerful platforms for new drug development and toxicity screening. In this Focus article, we review the state-of-the-art designs and examples for developing multiple “organs-on-chips”, and discuss the potential of this emerging technology to enhance our understanding of human physiology, and to transform and accelerate the drug discovery and pre-clinical testing process. This Focus article highlights some of the recent technological advances in this field, along with the challenges that must be addressed for these technologies to fully realize their potential. PMID:24193241
Gao, Lixia; Teng, Yong
Electrochemistry has emerged as a powerful analytical technique for chemical analysis of living cells, biologically active molecules and metabolites. Electrochemical biosensor, microfluidics and mass spectrometry are the most frequently used methods for electrochemical detection and monitory, which comprise a collection of extremely useful measurement tools for various fields of biology and medicine. Most recently, electrochemistry has been shown to be coupled with nanotechnology and genetic engineering to generate new enabling technologies, providing rapid, selective, and sensitive detection and diagnosis platforms. The primary focus of this review is to highlight the utility of electrochemical strategies and their conjunction with other approaches for drug metabolism and discovery. Current challenges and possible future developments and applications of electrochemistry in drug studies are also discussed.
The drug development process in the pharmaceutical industry has evolved from separate programs, specific for each country, into one coordinated, global development scheme. As a result, such a development program must meet regulatory requirements for all countries in which approval for the new drug will be sought. Barriers to Alzheimer disease (AD) drug discovery and development in the pharmaceutical industry can be categorized as (1) regulatory, (2) logistical, and (3) drug development issues. Some of the regulatory barriers could be overcome by international harmonization of guidelines for the development of antidementia drugs. The logistical issues can be reduced through international collaboration in the conduct of clinical studies, and the developmental issues can be addressed by using an expedited drug development plan that not only can reduce the time but also the resources required to develop the drug.
Wuitschik, Georg; Carreira, Erick M; Wagner, Björn; Fischer, Holger; Parrilla, Isabelle; Schuler, Franz; Rogers-Evans, Mark; Müller, Klaus
An oxetane can trigger profound changes in aqueous solubility, lipophilicity, metabolic stability, and conformational preference when replacing commonly employed functionalities such as gem-dimethyl or carbonyl groups. The magnitude of these changes depends on the structural context. Thus, by substitution of a gem-dimethyl group with an oxetane, aqueous solubility may increase by a factor of 4 to more than 4000 while reducing the rate of metabolic degradation in most cases. The incorporation of an oxetane into an aliphatic chain can cause conformational changes favoring synclinal rather than antiplanar arrangements of the chain. Additionally spirocyclic oxetanes (e.g., 2-oxa-6-aza-spiro[3.3]heptane) bear remarkable analogies to commonly used fragments in drug discovery, such as morpholine, and are even able to supplant the latter in its solubilizing ability. A rich chemistry of oxetan-3-one and derived Michael acceptors provide venues for the preparation of a broad variety of novel oxetanes not previously documented, thus providing the foundation for their broad use in chemistry and drug discovery.
Thakkar, Balmukund Sureshkumar; Albrigtsen, Marte; Svendsen, John Sigurd; Andersen, Jeanette H; Engh, Richard Alan
Drug discovery strategies include from broad random screening to focussed target-based approaches. Structure and substrate information greatly enables target-based design, but this is limited to relatively few targets; cell-based screening can identify new targets but often suffers from low hit rates and difficult hit optimization. Thus, newer approaches are needed that can improve the efficiency of screening and hit optimization. Here, we describe an efficient approach for hit generation, which may be called "biofocussed chemoprospecting." With bio-likeness and ease of synthesis as priority criteria, libraries may be constructed with good optimization potential, physicochemical diversity, drug likeness and low cost. Following this approach, two libraries based on linear and cyclic dipeptide scaffolds were designed, first as virtual libraries comprising of more than 30000 compounds, and after subsequent filtering, as a small library of a total of 51 compounds. These provided good diversity at low cost, and were tested for bioactivities. The discovery of six active compounds demonstrates a hit rate greater than 10%. This is comparable to target-based approaches, but the "chemoprospecting" method described here has the additional potential to identify new targets and mechanisms. © 2017 John Wiley & Sons A/S.
Pastor, Manuel; Benedetti, Paolo; Carotti, Angelo; Carrieri, Antonio; Díaz, Carlos; Herráiz, Cristina; Höltje, Hans-Dieter; Loza, M. Isabel; Oprea, Tudor; Padín, Fernando; Pubill, Francesc; Sanz, Ferran; Stoll, Friederike; the LINK3D Consortium
The work describes the development of novel software supporting synchronous distant collaboration between scientists involved in drug discovery and development projects. The program allows to visualize and share data as well as to interact in real time using standard intranets and Internet resources. Direct visualization of 2D and 3D molecular structures is supported and original tools for facilitating remote discussion have been integrated. The software is multiplatform (MS-Windows, SGI-IRIX, Linux), allowing for a seamless integration of heterogeneous working environments. The project aims to support collaboration both within and between academic and industrial institutions. Since confidentiality is very important in some scenarios, special attention has been paid to security aspects. The article presents the research carried out to gather the requirements of collaborative software in the field of drug discovery and development and describes the features of the first fully functional prototype obtained. Real-world testing activities carried out on this prototype in order to guarantee its adequacy in diverse environments are also described and discussed.
Picones, Arturo; Loza-Huerta, Arlet; Segura-Chama, Pedro; Lara-Figueroa, Cesar O
Automated technologies are now resolving the historical relegation that ion channels have endured as targets for the new drug discovery and development global efforts. The richness and adequacy of functional assay methodologies, remarkably fluorescence-based detection of ions fluxes and patch-clamp electrophysiology recording of ionic currents, are now automated and increasingly employed for the analysis of ion channel activity. While the former is currently the most commonly applied, the latter is finally reaching the throughput capacity to be engaged in the primary screening of chemical libraries conformed by hundreds of thousands of compounds. The use of automated instrumentation for the study of ion channel functionality (and dysfunctionality), particularly in the search for novel pharmacological agents with therapeutic purposes, has now reached out beyond the industrial setting, its original natural enclave, and is making its way into a growing number of academic labs and core facilities. The present chapter reviews the increasing contributions accomplished by a variety of different key automated technologies which have revolutionized the strategies to approach the discovery and development of new drugs targeting ion channels. © 2016 Elsevier Inc. All rights reserved.
Laustriat, Delphine; Gide, Jacqueline; Peschanski, Marc
Human pluripotent stem cells are a biological resource most commonly considered for their potential in cell therapy or, as it is now called, 'regenerative medicine'. However, in the near future, their most important application for human health may well be totally different, as they are more and more envisioned as opening new routes for pharmacological research. Pluripotent stem cells indeed possess the main attributes that make them theoretically fully equipped for the development of cell-based assays in the fields of drug discovery and predictive toxicology. These cells are characterized by: (i) an unlimited self-renewal capacity, which make them an inexhaustible source of cells; (ii) the potential to differentiate into any cell phenotype of the body at any stage of differentiation, with probably the notable exception, however, of the most mature forms of many lineages; and (iii) the ability to express genotypes of interest via the selection of donors, whether they be of embryonic origin, through pre-implantation genetic diagnosis, or adults, by genetic reprogramming of somatic cells, so-called iPSCs (induced pluripotent stem cells). In the present review, we provide diverse illustrations of the use of pluripotent stem cells in drug discovery and predictive toxicology, using either human embryonic stem cell lines or iPSC lines.
The term "high-content screening" has become synonymous with imaging screens using automated microscopes and automated image analysis. The term was coined a little over 10 years ago. Since then the technology has evolved considerably and has established itself firmly in the drug discovery and development industry. Both the instruments and the software controlling the instruments and analyzing the data have come to maturity, so the full benefits of high-content screening can now be realized. Those benefits are the capability of carrying out phenotypic multiparametric cellular assays in an unbiased, fully automated, and quantitative fashion. Automated microscopes and automated image analysis are being applied at all stages of the drug discovery and development pipeline. All major pharmaceutical companies have adopted the technology and it is in the process of being embraced broadly by the academic community. This review aims at describing the current capabilities and limits of the technology as well as highlighting necessary developments that are required to exploit fully the potential of high-content screening and analysis.
Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages. PMID:27074285
Whitehead, Kathryn; Karr, Natalie; Mitragotri, Samir
Oral drug delivery offers an attractive method of needle-free drug administration. Unfortunately, oral delivery is often hampered by the poor permeability of drugs across the intestinal epithelium. Although several single chemical permeation enhancers have been shown to alleviate permeability difficulties, this often occurs at the expense of safety. This in vitro study demonstrates the use of binary and ternary combinations of permeation enhancers to create synergistic enhancer formulations (SEFs) that offer a high level of potency while inducing very little toxicity in Caco-2 cells. Although relatively rare in the explored formulation space, SEFs were abundant enough to significantly increase the repertoire of permeation enhancers that are safe and effective in vitro. The most promising enhancers from the binary study led to easily identifiable ternary SEFs, thus increasing the efficiency of the discovery process. Some of the best performers of the study included binary combinations of hexylamine and chembetaine and ternary combinations of sodium laureth sulfate, decyltrimethyl ammonium bromide, and chembetaine, all at a total concentration of 0.1% (w/v). Furthermore, several SEFs were shown to be capable of increasing mannitol and 70 kDa dextran permeability across Caco-2 monolayers 15- and 8-fold, respectively. These results encourage further exploration of several leading formulations for in vivo applications in oral drug delivery.
Tan, MH Eileen; Li, Jun; Xu, H Eric; Melcher, Karsten; Yong, Eu-leong
Androgens and androgen receptors (AR) play a pivotal role in expression of the male phenotype. Several diseases, such as androgen insensitivity syndrome (AIS) and prostate cancer, are associated with alterations in AR functions. Indeed, androgen blockade by drugs that prevent the production of androgens and/or block the action of the AR inhibits prostate cancer growth. However, resistance to these drugs often occurs after 2–3 years as the patients develop castration-resistant prostate cancer (CRPC). In CRPC, a functional AR remains a key regulator. Early studies focused on the functional domains of the AR and its crucial role in the pathology. The elucidation of the structures of the AR DNA binding domain (DBD) and ligand binding domain (LBD) provides a new framework for understanding the functions of this receptor and leads to the development of rational drug design for the treatment of prostate cancer. An overview of androgen receptor structure and activity, its actions in prostate cancer, and how structural information and high-throughput screening have been or can be used for drug discovery are provided herein. PMID:24909511
Tan, M H Eileen; Li, Jun; Xu, H Eric; Melcher, Karsten; Yong, Eu-leong
Androgens and androgen receptors (AR) play a pivotal role in expression of the male phenotype. Several diseases, such as androgen insensitivity syndrome (AIS) and prostate cancer, are associated with alterations in AR functions. Indeed, androgen blockade by drugs that prevent the production of androgens and/or block the action of the AR inhibits prostate cancer growth. However, resistance to these drugs often occurs after 2-3 years as the patients develop castration-resistant prostate cancer (CRPC). In CRPC, a functional AR remains a key regulator. Early studies focused on the functional domains of the AR and its crucial role in the pathology. The elucidation of the structures of the AR DNA binding domain (DBD) and ligand binding domain (LBD) provides a new framework for understanding the functions of this receptor and leads to the development of rational drug design for the treatment of prostate cancer. An overview of androgen receptor structure and activity, its actions in prostate cancer, and how structural information and high-throughput screening have been or can be used for drug discovery are provided herein.
Sotgia, Federica; Martinez-Outschoorn, Ubaldo E; Lisanti, Michael P
Recent studies in cancer metabolism directly implicate catabolic fibroblasts as a new rich source of i) energy and ii) biomass, for the growth and survival of anabolic cancer cells. Conversely, anabolic cancer cells upregulate oxidative mitochondrial metabolism, to take advantage of the abundant fibroblast fuel supply. This simple model of "metabolic-symbiosis" has now been independently validated in several different types of human cancers, including breast, ovarian, and prostate tumors. Biomarkers of metabolic-symbiosis are excellent predictors of tumor recurrence, metastasis, and drug resistance, as well as poor patient survival. New pre-clinical models of metabolic-symbiosis have been generated and they genetically validate that catabolic fibroblasts promote tumor growth and metastasis. Over 30 different stable lines of catabolic fibroblasts and >10 different lines of anabolic cancer cells have been created and are well-characterized. For example, catabolic fibroblasts harboring ATG16L1 increase tumor cell metastasis by >11.5-fold, despite the fact that genetically identical cancer cells were used. Taken together, these studies provide >40 novel validated targets, for new drug discovery and anti-cancer therapy. Since anabolic cancer cells amplify their capacity for oxidative mitochondrial metabolism, we should consider therapeutically targeting mitochondrial biogenesis and OXPHOS in epithelial cancer cells. As metabolic-symbiosis promotes drug-resistance and may represent the escape mechanism during anti-angiogenic therapy, new drugs targeting metabolic-symbiosis may also be effective in cancer patients with recurrent and advanced metastatic disease.
Sotgia, Federica; Martinez-Outschoorn, Ubaldo E.; Lisanti, Michael P.
Recent studies in cancer metabolism directly implicate catabolic fibroblasts as a new rich source of i) energy and ii) biomass, for the growth and survival of anabolic cancer cells. Conversely, anabolic cancer cells upregulate oxidative mitochondrial metabolism, to take advantage of the abundant fibroblast fuel supply. This simple model of “metabolic-symbiosis” has now been independently validated in several different types of human cancers, including breast, ovarian, and prostate tumors. Biomarkers of metabolic-symbiosis are excellent predictors of tumor recurrence, metastasis, and drug resistance, as well as poor patient survival. New pre-clinical models of metabolic-symbiosis have been generated and they genetically validate that catabolic fibroblasts promote tumor growth and metastasis. Over 30 different stable lines of catabolic fibroblasts and >10 different lines of anabolic cancer cells have been created and are well-characterized. For example, catabolic fibroblasts harboring ATG16L1 increase tumor cell metastasis by >11.5-fold, despite the fact that genetically identical cancer cells were used. Taken together, these studies provide >40 novel validated targets, for new drug discovery and anti-cancer therapy. Since anabolic cancer cells amplify their capacity for oxidative mitochondrial metabolism, we should consider therapeutically targeting mitochondrial biogenesis and OXPHOS in epithelial cancer cells. As metabolic-symbiosis promotes drug-resistance and may represent the escape mechanism during anti-angiogenic therapy, new drugs targeting metabolic-symbiosis may also be effective in cancer patients with recurrent and advanced metastatic disease. PMID:23896568
Lai, Ashton C; Crews, Craig M
Small-molecule drug discovery has traditionally focused on occupancy of a binding site that directly affects protein function, and this approach typically precludes targeting proteins that lack such amenable sites. Furthermore, high systemic drug exposures may be needed to maintain sufficient target inhibition in vivo, increasing the risk of undesirable off-target effects. Induced protein degradation is an alternative approach that is event-driven: upon drug binding, the target protein is tagged for elimination. Emerging technologies based on proteolysis-targeting chimaeras (PROTACs) that exploit cellular quality control machinery to selectively degrade target proteins are attracting considerable attention in the pharmaceutical industry owing to the advantages they could offer over traditional small-molecule strategies. These advantages include the potential to reduce systemic drug exposure, the ability to counteract increased target protein expression that often accompanies inhibition of protein function and the potential ability to target proteins that are not currently therapeutically tractable, such as transcription factors, scaffolding and regulatory proteins.
Smith, Nadine Barrie
The use of needles for multiple injection of drugs, such as insulin for diabetes, can be painful. As a result, prescribed drug noncompliance can result in severe medical complications. Several noninvasive methods exist for transdermal drug delivery. These include chemical mediation using liposomes and chemical enhancers or physical mechanisms such as microneedles, iontophoresis, electroporation, and ultrasound. Ultrasound enhanced transdermal drug delivery offers advantages over traditional drug delivery methods which are often invasive and painful. A broad review of the transdermal ultrasound drug delivery literature has shown that this technology offers promising potential for noninvasive drug administration. From a clinical perspective, few drugs, proteins or peptides have been successfully administered transdermally because of the low skin permeability to these relatively large molecules, although much work is underway to resolve this problem. The proposed mechanism of ultrasound has been suggested to be the result of cavitation, which is discussed along with the bioeffects from therapeutic ultrasound. For low frequencies, potential transducers which can be used for drug delivery are discussed, along with cautions regarding ultrasound safety versus efficacy. PMID:18203426
Płocinska, Renata; Korycka-Machala, Malgorzata; Plocinski, Przemyslaw; Dziadek, Jaroslaw
Mycobacterium tuberculosis (M. tuberculosis), the causative agent of tuberculosis, is a leading infectious disease organism, causing millions of deaths each year. This serious pathogen has been greatly spread worldwide and recent years have observed an increase in the number of multi-drug resistant and totally drug resistant M. tuberculosis strains (WHO report, 2014). The danger of tuberculosis becoming an incurable disease has emphasized the need for the discovery of a new generation of antimicrobial agents. The development of novel alternative medical strategies, new drugs and the search for optimal drug targets are top priority areas of tuberculosis research. Key characteristics of mycobacteria include: slow growth, the ability to transform into a metabolically silent - latent state, intrinsic drug resistance and the relatively rapid development of acquired drug resistance. These factors make finding an ideal antituberculosis drug enormously challenging, even if it is designed to treat drug sensitive tuberculosis strains. A vast majority of canonical antibiotics including antituberculosis agents target bacterial cell wall biosynthesis or DNA/RNA processing. Novel therapeutic approaches are being tested to target mycobacterial cell division, twocomponent regulatory factors, lipid synthesis and the transition between the latent and actively growing states. This review discusses the choice of cellular targets for an antituberculosis therapy, describes putative drug targets evaluated in the recent literature and summarizes potential candidates under clinical and pre-clinical development. We focus on the key cellular process of DNA replication, as a prominent target for future antituberculosis therapy. We describe two main pathways: the biosynthesis of nucleic acids precursors - the nucleotides, and the synthesis of DNA molecules. We summarize data regarding replication associated proteins that are critical for nucleotide synthesis, initiation, unwinding and
Hallenbeck, Kenneth K; Turner, David M; Renslo, Adam R; Arkin, Michelle R
The targeting of non-catalytic cysteine residues with small molecules is drawing increased attention from drug discovery scientists and chemical biologists. From a biological perspective, genomic and proteomic studies have revealed the presence of cysteine mutations in several oncogenic proteins, suggesting both a functional role for these residues and also a strategy for targeting them in an 'allele specific' manner. For the medicinal chemist, the structure-guided design of cysteine- reactive molecules is an appealing strategy to realize improved selectivity and pharmacodynamic properties in drug leads. Finally, for chemical biologists, the modification of cysteine residues provides a unique means to probe protein structure and allosteric regulation. Here, we review three applications of cysteinemodifying small molecules: 1) the optimization of existing drug leads, 2) the discovery of new lead compounds, and 3) the use of cysteine-reactive molecules as probes of protein dynamics. In each case, structure-guided design plays a key role in determining which cysteine residue(s) to target and in designing compounds with the proper geometry to enable both covalent interaction with the targeted cysteine and productive non-covalent interactions with nearby protein residues.
It is suggested in this article that patient engagement should occur further upstream during the drug discovery stage. 'Lead patients', namely those patients who are proactive with respect to their health, possess knowledge of their disease and resulting symptoms. They are also well informed about the conventional as well as non-conventional treatments for disease management; and so can provide a nuanced perspective to drug design. Understanding how patients view the management of their diseases and how they view the use of conventional versus non-conventional interventions is of imperative importance to researchers. Indeed, this can provide insight into how conventional treatments might be designed from the outset to encourage compliance and positive health outcomes. Consequently, a continuum of lead patient engagement is employed that focuses on drug discovery processes ranging from participative, informative to collaborative engagement. This article looks at a variety of open innovation models that are currently employed across this engagement spectrum. It is no longer sufficient for industry stakeholders to consider conventional therapies as the only mechanisms being sought after by patients. Without patient engagement, the industry risks being re-prioritized in terms of its role in the patient journey towards not only recovery of health, but also sustained health and wellness before disease onset.
Hallenbeck, Kenneth K.; Turner, David M.; Renslo, Adam R.; Arkin, Michelle R.
The targeting of non-catalytic cysteine residues with small molecules is drawing increased attention from drug discovery scientists and chemical biologists. From a biological perspective, genomic and proteomic studies have revealed the presence of cysteine mutations in several oncogenic proteins, suggesting both a functional role for these residues and also a strategy for targeting them in an ‘allele specific’ manner. For the medicinal chemist, the structure-guided design of cysteine-reactive molecules is an appealing strategy to realize improved selectivity and pharmacodynamic properties in drug leads. Finally, for chemical biologists, the modification of cysteine residues provides a unique means to probe protein structure and allosteric regulation. Here, we review three applications of cysteine-modifying small molecules: 1) the optimization of existing drug leads, 2) the discovery of new lead compounds, and 3) the use of cysteine-reactive molecules as probes of protein dynamics. In each case, structure-guided design plays a key role in determining which cysteine residue(s) to target and in designing compounds with the proper geometry to enable both covalent interaction with the targeted cysteine and productive non-covalent interactions with nearby protein residues. PMID:27449257
Bashari, O; Redko, B; Cohen, A; Luboshits, G; Gellerman, G; Firer, M A
Metastatic castration-resistant prostate cancer (mCRPC) remains essentially incurable. Targeted Drug Delivery (TDD) systems may overcome the limitations of current mCRPC therapies. We describe the use of strict criteria to isolate novel prostate cancer cell targeting peptides that specifically deliver drugs into target cells. Phage from a libraries displaying 7mer peptides were exposed to PC-3 cells and only internalized phage were recovered. The ability of these phage to internalize into other prostate cancer cells (LNCaP, DU-145) was validated. The displayed peptides of selected phage clones were synthesized and their specificity for target cells was validated in vitro and in vivo. One peptide (P12) which specifically targeted PC-3 tumors in vivo was incorporated into mono-drug (Chlorambucil, Combretastatin or Camptothecin) and dual-drug (Chlorambucil/Combretastatin or Chlorambucil/Camptothecin) PDCs and the cytotoxic efficacy of these conjugates for target cells was tested. Conjugation of P12 into dual-drug PDCs allowed discovery of new drug combinations with synergistic effects. The use of strict selection criteria can lead to discovery of novel peptides for use as drug carriers for TDD. PDCs represent an effective alternative to current modes of free drug chemotherapy for prostate cancer. Copyright © 2017. Published by Elsevier B.V.
Ong, Voon S.; Cook, Kevin L.; Kosara, Christine M.; Brubaker, William F.
An integrated approach to quantitative bioanalysis, incorporating turbulent flow chromatography (TFC) with mass spectrometric detection, was developed to support in-house drug discovery and development efforts. Activities such as metabolic stability screening and pharmacokinetic characterization support are carried out on a single unified platform. Two different TFC column-switching configurations, parallel and serial, are presented. The first, a parallel TFC column configuration, is capable of high-throughput analysis but carryover can reach as high as 0.24%. The characteristics of the instrument operating in the parallel configuration are provided for analysis of samples generated during in vitro metabolic stability assessments, a key screen during the lead optimization phase of drug discovery. Operating in this configuration, the system has the capability of performing on-line solid phase extraction and analysis of approximately 400 samples containing phosphate-buffered saline in approximately 14 h. The second, a serial TFC column configuration, was used to perform direct plasma injection analysis. The advantage of the serial configuration is the relatively low carryover (<0.040%) observed due to increased number of valve washes; however these extra washes lead to increased injection cycle times. A method developed using the serial TFC column configuration for the determination of dihydropyridines in plasma samples is given as an example. Analytical performance criteria examined during method development and validation included linearity, accuracy, precision, and recovery. The robustness of the technique was demonstrated by applying the method in the analysis of over 2500 plasma samples generated during preclinical drug development studies. Further, combined analysis of plasma and brain tissue was performed using acetonitrile precipitation as sample pretreatment for both matrices.
Årdal, Christine; Røttingen, John-Arne
Open source drug discovery offers potential for developing new and inexpensive drugs to combat diseases that disproportionally affect the poor. The concept borrows two principle aspects from open source computing (i.e., collaboration and open access) and applies them to pharmaceutical innovation. By opening a project to external contributors, its research capacity may increase significantly. To date there are only a handful of open source R&D projects focusing on neglected diseases. We wanted to learn from these first movers, their successes and failures, in order to generate a better understanding of how a much-discussed theoretical concept works in practice and may be implemented. A descriptive case study was performed, evaluating two specific R&D projects focused on neglected diseases. CSIR Team India Consortium's Open Source Drug Discovery project (CSIR OSDD) and The Synaptic Leap's Schistosomiasis project (TSLS). Data were gathered from four sources: interviews of participating members (n = 14), a survey of potential members (n = 61), an analysis of the websites and a literature review. Both cases have made significant achievements; however, they have done so in very different ways. CSIR OSDD encourages international collaboration, but its process facilitates contributions from mostly Indian researchers and students. Its processes are formal with each task being reviewed by a mentor (almost always offline) before a result is made public. TSLS, on the other hand, has attracted contributors internationally, albeit significantly fewer than CSIR OSDD. Both have obtained funding used to pay for access to facilities, physical resources and, at times, labor costs. TSLS releases its results into the public domain, whereas CSIR OSDD asserts ownership over its results. Technically TSLS is an open source project, whereas CSIR OSDD is a crowdsourced project. However, both have enabled high quality research at low cost. The critical success factors appear to be clearly
Årdal, Christine; Røttingen, John-Arne
Background Open source drug discovery offers potential for developing new and inexpensive drugs to combat diseases that disproportionally affect the poor. The concept borrows two principle aspects from open source computing (i.e., collaboration and open access) and applies them to pharmaceutical innovation. By opening a project to external contributors, its research capacity may increase significantly. To date there are only a handful of open source R&D projects focusing on neglected diseases. We wanted to learn from these first movers, their successes and failures, in order to generate a better understanding of how a much-discussed theoretical concept works in practice and may be implemented. Methodology/Principal Findings A descriptive case study was performed, evaluating two specific R&D projects focused on neglected diseases. CSIR Team India Consortium's Open Source Drug Discovery project (CSIR OSDD) and The Synaptic Leap's Schistosomiasis project (TSLS). Data were gathered from four sources: interviews of participating members (n = 14), a survey of potential members (n = 61), an analysis of the websites and a literature review. Both cases have made significant achievements; however, they have done so in very different ways. CSIR OSDD encourages international collaboration, but its process facilitates contributions from mostly Indian researchers and students. Its processes are formal with each task being reviewed by a mentor (almost always offline) before a result is made public. TSLS, on the other hand, has attracted contributors internationally, albeit significantly fewer than CSIR OSDD. Both have obtained funding used to pay for access to facilities, physical resources and, at times, labor costs. TSLS releases its results into the public domain, whereas CSIR OSDD asserts ownership over its results. Conclusions/Significance Technically TSLS is an open source project, whereas CSIR OSDD is a crowdsourced project. However, both have enabled high quality
Scott, William L.; Denton, Ryan E.; Marrs, Kathleen A.; Durrant, Jacob D.; Samaritoni, J. Geno; Abraham, Milata M.; Brown, Stephen P.; Carnahan, Jon M.; Fischer, Lindsey G.; Glos, Courtney E.; Sempsrott, Peter J.; O'Donnell, Martin J.
The Distributed Drug Discovery (D3) program trains students in three drug discovery disciplines (synthesis, computational analysis, and biological screening) while addressing the important challenge of discovering drug leads for neglected diseases. This article focuses on implementation of the synthesis component in the second-semester…
Scott, William L.; Denton, Ryan E.; Marrs, Kathleen A.; Durrant, Jacob D.; Samaritoni, J. Geno; Abraham, Milata M.; Brown, Stephen P.; Carnahan, Jon M.; Fischer, Lindsey G.; Glos, Courtney E.; Sempsrott, Peter J.; O'Donnell, Martin J.
The Distributed Drug Discovery (D3) program trains students in three drug discovery disciplines (synthesis, computational analysis, and biological screening) while addressing the important challenge of discovering drug leads for neglected diseases. This article focuses on implementation of the synthesis component in the second-semester…
White, R E
The application of rapid methods currently used for screening discovery drug candidates for metabolism and pharmacokinetic characteristics is discussed. General considerations are given for screening in this context, including the criteria for good screens, the use of counterscreens, the proper sequencing of screens, ambiguity in the interpretation of results, strategies for false positives and negatives, and the special difficulties encountered in drug metabolism and pharmacokinetic screening. Detailed descriptions of the present status of screening are provided for absorption potential, blood-brain barrier penetration, inhibition and induction of cytochrome P450, pharmacokinetics, biotransformation, and computer modeling. Although none of the systems currently employed for drug metabolism and pharmacokinetic screening can be considered truly high-throughput, several of them are rapid enough to be a practical part of the screening paradigm for modern, fast-moving discovery programs.
Kang, Lifeng; Chung, Bong Geun; Langer, Robert; Khademhosseini, Ali
Microfluidic technologies' ability to miniaturize assays and increase experimental throughput have generated significant interest in the drug discovery and development domain. These characteristics make microfluidic systems a potentially valuable tool for many drug discovery and development applications. Here, we review the recent advances of microfluidic devices for drug discovery and development and highlight their applications in different stages of the process, including target selection, lead identification, preclinical tests, clinical trials, chemical synthesis, formulations studies and product management.
Kang, Lifeng; Chung, Bong Geun; Langer, Robert; Khademhosseini, Ali
Microfluidic technologies’ ability to miniaturize assays and increase experimental throughput have generated significant interest in the drug discovery and development domain. These characteristics make microfluidic systems a potentially valuable tool for many drug discovery and development applications. Here, we review the recent advances of microfluidic devices for drug discovery and development and highlight their applications in different stages of the process, including target selection, lead identification, preclinical tests, clinical trials, chemical synthesis, formulations studies, and product management. PMID:18190858
Tsai, Yingssu; McPhillips, Scott E.; González, Ana; McPhillips, Timothy M.; Zinn, Daniel; Cohen, Aina E.; Feese, Michael D.; Bushnell, David; Tiefenbrunn, Theresa; Stout, C. David; Ludaescher, Bertram; Hedman, Britt; Hodgson, Keith O.; Soltis, S. Michael
AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully demonstrated. This workflow was run once on the same 96 samples that the group had examined manually and the workflow cycled successfully through all of the samples, collected data from the same samples that were selected manually and located the same peaks of unmodeled density in the resulting difference
Sun, Huihua; Liu, Zihe; Zhao, Huimin; Ang, Ee Lui
Because of extraordinary structural diversity and broad biological activities, natural products have played a significant role in drug discovery. These therapeutically important secondary metabolites are assembled and modified by dedicated biosynthetic pathways in their host living organisms. Traditionally, chemists have attempted to synthesize natural product analogs that are important sources of new drugs. However, the extraordinary structural complexity of natural products sometimes makes it challenging for traditional chemical synthesis, which usually involves multiple steps, harsh conditions, toxic organic solvents, and byproduct wastes. In contrast, combinatorial biosynthesis exploits substrate promiscuity and employs engineered enzymes and pathways to produce novel “unnatural” natural products, substantially expanding the structural diversity of natural products with potential pharmaceutical value. Thus, combinatorial biosynthesis provides an environmentally friendly way to produce natural product analogs. Efficient expression of the combinatorial biosynthetic pathway in genetically tractable heterologous hosts can increase the titer of the compound, eventually resulting in less expensive drugs. In this review, we will discuss three major strategies for combinatorial biosynthesis: 1) precursor-directed biosynthesis; 2) enzyme-level modification, which includes swapping of the entire domains, modules and subunits, site-specific mutagenesis, and directed evolution; 3) pathway-level recombination. Recent examples of combinatorial biosynthesis employing these strategies will also be highlighted in this review. PMID:25709407
Wager, Travis T; Hou, Xinjun; Verhoest, Patrick R; Villalobos, Anabella
Significant progress has been made in prospectively designing molecules using the central nervous system multiparameter optimization (CNS MPO) desirability tool, as evidenced by the analysis reported herein of a second wave of drug candidates that originated after the development and implementation of this tool. This simple-to-use design algorithm has expanded design space for CNS candidates and has further demonstrated the advantages of utilizing a flexible, multiparameter approach in drug discovery rather than individual parameters and hard cutoffs of physicochemical properties. The CNS MPO tool has helped to increase the percentage of compounds nominated for clinical development that exhibit alignment of ADME attributes, cross the blood-brain barrier, and reside in lower-risk safety space (low ClogP and high TPSA). The use of this tool has played a role in reducing the number of compounds submitted to exploratory toxicity studies and increasing the survival of our drug candidates through regulatory toxicology into First in Human studies. Overall, the CNS MPO algorithm has helped to improve the prioritization of design ideas and the quality of the compounds nominated for clinical development.
Roguska, Michael; Kaymakcalan, Zehra; Salfeld, Jochen
The number of therapeutic antibodies approved by regulatory agencies as novel drugs and the number of antibodies in development has increased significantly. The modular nature of antibody structure has enabled researchers to more predictably design therapeutic antibodies by choosing appropriate functional features most appropriate for a given antibody target and clinical indication. Advances in recombinant antibody technologies have allowed the routine generation of antibodies that can satisfy stringent drug design criteria, such as low immunogenicity, high affinity, target specificity, and commercially viable manufacturing methods. Engineering design opportunities exist for both the variable and the constant regions that encompass, in addition to antigen specificity and affinity, effector functions that mediate immune complex clearance or pharmacokinetics. These are discussed in the context of relevant in vivo and in vitro technologies, such as human IgG transgenic mice, phage display, and biologics manufacturing. Finally, therapeutic antibodies are compared with traditional drugs with respect to target class, selectivity, route of administration, intellectual property issues, and lead discovery and optimization.
Winchester, Catherine L; Pratt, Judith A; Morris, Brian J
Despite intensive research over many years, the treatment of schizophrenia remains a major health issue. Current and emerging treatments for schizophrenia are based upon the classical dopamine and glutamate hypotheses of disease. Existing first and second generation antipsychotic drugs based upon the dopamine hypothesis are limited by their inability to treat all symptom domains and their undesirable side effect profiles. Third generation drugs based upon the glutamate hypothesis of disease are currently under evaluation but are more likely to be used as add on treatments. Hence there is a large unmet clinical need. A major challenge in neuropsychiatric disease research is the relatively limited knowledge of disease mechanisms. However, as our understanding of the genetic causes of the disease evolves, novel strategies for the development of improved therapeutic agents will become apparent. In this review we consider the current status of knowledge of the genetic basis of schizophrenia, including methods for identifying genetic variants associated with the disorder and how they impact on gene function. Although the genetic architecture of schizophrenia is complex, some targets amenable to pharmacological intervention can be discerned. We conclude that many challenges lie ahead but the stratification of patients according to biobehavioural constructs that cross existing disease classifications but with common genetic and neurobiological bases, offer opportunities for new approaches to effective drug discovery.
Waterman, Carrie; Calcul, Laurent; Beau, Jeremy; Ma, Wai Sheung; Lebar, Matthew D; von Salm, Jacqueline L; Harter, Charles; Mutka, Tina; Morton, Lindsay C; Maignan, Patrick; Barisic, Betty; van Olphen, Alberto; Kyle, Dennis E; Vrijmoed, Lilian; Pang, Ka-Lai; Pearce, Cedric J; Baker, Bill J
The ongoing search for effective antiplasmodial agents remains essential in the fight against malaria worldwide. Emerging parasitic drug resistance places an urgent need to explore chemotherapies with novel structures and mechanisms of action. Natural products have historically provided effective antimalarial drug scaffolds. In an effort to search nature's chemical potential for antiplasmodial agents, unconventionally sourced organisms coupled with innovative cultivation techniques were utilized. Approximately 60,000 niche microbes from various habitats (slow-growing terrestrial fungi, Antarctic microbes, and mangrove endophytes) were cultivated on a small-scale, extracted, and used in high-throughput screening to determine antimalarial activity. About 1% of crude extracts were considered active and 6% partially active (≥ 67% inhibition at 5 and 50 μg/mL, respectively). Active extracts (685) were cultivated on a large-scale, fractionated, and screened for both antimalarial activity and cytotoxicity. High interest fractions (397) with an IC50 < 1.11 μg/mL were identified and subjected to chromatographic separation for compound characterization and dereplication. Identifying active compounds with nanomolar antimalarial activity coupled with a selectivity index tenfold higher was accomplished with two of the 52 compounds isolated. This microscale, high-throughput screening project for antiplasmodial agents is discussed in the context of current natural product drug discovery efforts.
Van Dam, Debby; De Deyn, Peter Paul
With increasing feasibility of predicting conversion of mild cognitive impairment to dementia based on biomarker profiling, the urgent need for efficacious disease-modifying compounds has become even more critical. Despite intensive research, underlying pathophysiological mechanisms remain insufficiently documented for purposeful target discovery. Translational research based on valid animal models may aid in alleviating some of the unmet needs in the current Alzheimer's disease pharmaceutical market, which includes disease-modification, increased efficacy and safety, reduction of the number of treatment unresponsive patients and patient compliance. The development and phenotyping of animal models is indeed essential in Alzheimer's disease-related research as valid models enable the appraisal of early pathological processes – which are often not accessible in patients, and subsequent target discovery and evaluation. This review paper summarizes and critically evaluates currently available animal models, and discusses their value to the Alzheimer drug discovery pipeline. Models dealt with include spontaneous models in various species, including senescence-accelerated mice, chemical and lesion-induced rodent models, and genetically modified models developed in Drosophila melanogaster, Caenorhabditis elegans, Danio rerio and rodents. Although highly valid animal models exist, none of the currently available models recapitulates all aspects of human Alzheimer's disease, and one should always be aware of the potential dangers of uncritical extrapolating from model organisms to a human condition that takes decades to develop and mainly involves higher cognitive functions. LINKED ARTICLES This article is part of a themed issue on Translational Neuropharmacology. To view the other articles in this issue visit http://dx.doi.org/10.1111/bph.2011.164.issue-4 PMID:21371009
Peetla, Chiranjeevi; Stine, Andrew; Labhasetwar, Vinod
The transport of drugs or drug delivery systems across the cell membrane is a complex biological process, often difficult to understand because of its dynamic nature. In this regard, model lipid membranes, which mimic many aspects of cell-membrane lipids, have been very useful in helping investigators to discern the roles of lipids in cellular interactions. One can use drug-lipid interactions to predict pharmacokinetic properties of drugs, such as their transport, biodistribution, accumulation, and hence efficacy. These interactions can also be used to study the mechanisms of transport, based on the structure and hydrophilicity/hydrophobicity of drug molecules. In recent years, model lipid membranes have also been explored to understand their mechanisms of interactions with peptides, polymers, and nanocarriers. These interaction studies can be used to design and develop efficient drug delivery systems. Changes in the lipid composition of cells and tissue in certain disease conditions may alter biophysical interactions, which could be explored to develop target-specific drugs and drug delivery systems. In this review, we discuss different model membranes, drug-lipid interactions and their significance, studies of model membrane interactions with nanocarriers, and how biophysical interaction studies with lipid model membranes could play an important role in drug discovery and drug delivery. PMID:19432455
Buller, Fabian; Mannocci, Luca; Scheuermann, Jörg; Neri, Dario
DNA-encoded chemical libraries represent a novel avenue for the facile discovery of small molecule ligands against target proteins of biological or pharmaceutical importance. Library members consist of small molecules covalently attached to unique DNA fragments that serve as amplifiable identification barcodes. This encoding allows the in vitro selection of ligands at subpicomolar concentrations from large library populations by affinity capture on a target protein of interest, in analogy to established technologies for the selection of binding polypeptides (e.g., antibodies). Different library formats have been explored by various groups, allowing the construction of chemical libraries comprising up to millions of DNA-encoded compounds. Libraries before and after selection have been characterized by PCR amplification of the DNA codes and subsequent relative quantification of library members using high-throughput sequencing. The most enriched compounds have then been further analyzed in biological assays, in the presence or in the absence of linked DNA. This article reviews experimental strategies used for the construction of DNA-encoded chemical libraries, revealing how selection, decoding, and hit validation technologies have been used for drug discovery programs.
Jubb, Harry; Higueruelo, Alicia P; Winter, Anja; Blundell, Tom L
Although targeting protein-protein interfaces of regulatory multiprotein complexes has become a significant focus in drug discovery, it continues to pose major challenges. Most interfaces would be classed as 'undruggable' by conventional analyses, as they tend to be large, flat and featureless. Over the past decade, encouragement has come from the discovery of hotspots that contribute much of the free energy of interaction, and this has led to the development of tethering methods that target small molecules to these sites, often inducing adaptive changes. Equally important has been the recognition that many protein-protein interactions involve a continuous epitope of one partner and a well-defined groove or series of specific small pockets. These observations have stimulated the development of stapled α-helical peptides and other proteomimetic approaches. They have also led to the realisation that fragments might gain low-affinity 'footholds' on some protein-protein interfaces, and that these fragments might be elaborated to useful modulators of the interactions.
Terricabras, Emma; Benjamim, Claudia; Godessart, Nuria
The blockade of leukocyte migration has been demonstrated to be a valid option for the treatment of several autoimmune diseases. Chemokines play an active role in regulating cell infiltration into inflammatory sites and disrupting chemokine-receptor interactions has emerged as an alternative therapeutic approach. Pharmaceutical companies have developed an intense activity in the drug discovery of chemokine receptor antagonists in the last 10 years. Potent and selective compounds have been obtained and some of them are currently being evaluated in the clinic. The success of these trials will demonstrate whether the blockade of a single receptor is of therapeutic benefit. Alternative approaches, such as pan-receptor antagonists or inhibitors of the signalling pathways evoked by chemokines, are also being explored. In the meantime, new relationships between chemokines and receptors will be revealed, increasing our knowledge of such a fascinating field.
Dressler, Oliver J; Maceiczyk, Richard M; Chang, Soo-Ik; deMello, Andrew J
Over the past two decades, the application of microengineered systems in the chemical and biological sciences has transformed the way in which high-throughput experimentation is performed. The ability to fabricate complex microfluidic architectures has allowed scientists to create new experimental formats for processing ultra-small analytical volumes in short periods and with high efficiency. The development of such microfluidic systems has been driven by a range of fundamental features that accompany miniaturization. These include the ability to handle small sample volumes, ultra-low fabrication costs, reduced analysis times, enhanced operational flexibility, facile automation, and the ability to integrate functional components within complex analytical schemes. Herein we discuss the impact of microfluidics in the area of high-throughput screening and drug discovery and highlight some of the most pertinent studies in the recent literature.
Plant natural products have been intensively investigated during the past decades with a considerable amount of generated data. Databases are subsequently developed to facilitate the management and analysis of accumulated information including plant species, chemical compounds, structures and bioactivities. With the support of databases, the screening of novel bioactivities for plant natural products can benefit from advanced computational methods to accelerate the progress of drug discovery. This overview describes the contents of publicly available databases useful for computational research of plant natural products. Based on the databases, quantitative structure-activity relationship models and protein-ligand docking methods can be developed and applied to analyze and screen bioactive compounds. More public and structured databases with unique contents, search functions and links to major databases are needed for efficiently exploring the chemical space of plant natural products.
G protein-coupled receptors (GPCRs) transmit extracellular signals into the intracellular space, and play key roles in the physiological regulation of virtually every cell and tissue. Characteristic for the GPCR superfamily of cell surface receptors are their seven transmembrane-spanning alpha-helices, an extracellular N terminus and intracellular C-terminal tail. Besides transmission of extracellular signals, their activity is modulated by cellular signals in an auto- or transregulatory fashion. The molecular complexity of GPCRs and their regulated signaling networks triggered the interest in academic research groups to explore them further, and their drugability and role in pathophysiology triggers pharmaceutical research towards small molecular weight ligands and therapeutic antibodies. About 30% of marketed drugs target GPCRs, which underlines the importance of this target class. This review describes current and emerging cellular assays for the ligand discovery of GPCRs.
Hansen, Kasper B; Bräuner-Osborne, Hans
Fluorescent dyes sensitive to changes in intracellular calcium have become increasingly popular in G protein-coupled receptor (GPCR) drug discovery for several reasons. First of all, the assays using the dyes are easy to perform and are of low cost compared to other assays. Second, most non-Galpha(q)-coupled GPCRs can be tweaked to modulate intracellular calcium by co-transfection with promiscuous or chimeric/mutated G proteins making the calcium assays broadly applicable in GPCR research. Third, the price of instruments capable of measuring fluorescent-based calcium indicators has become significantly less making them obtainable even for academic groups. Here, we present a protocol for measuring changes in intracellular calcium levels in living mammalian cells based on the fluorescent calcium binding dye, fluo-4.
Fray, M Jonathan; Macdonald, Simon J F; Baldwin, Ian R; Barton, Nick; Brown, Jack; Campbell, Ian B; Churcher, Ian; Coe, Diane M; Cooper, Anthony W J; Craven, Andrew P; Fisher, Gail; Inglis, Graham G A; Kelly, Henry A; Liddle, John; Maxwell, Aoife C; Patel, Vipulkumar K; Swanson, Stephen; Wellaway, Natalie
In this article, we describe a practical drug discovery project for third-year undergraduates. No previous knowledge of medicinal chemistry is assumed. Initial lecture workshops cover the basic principles; then students, in teams, seek to improve the profile of a weakly potent, insoluble phosphatidylinositide 3-kinase delta (PI3Kδ) inhibitor (1) through compound array design, molecular modelling, screening data analysis and the synthesis of target compounds in the laboratory. The project benefits from significant industrial support, including lectures, student mentoring and consumables. The aim is to make the learning experience as close as possible to real-life industrial situations. In total, 48 target compounds were prepared, the best of which (5b, 5j, 6b and 6ap) improved the potency and aqueous solubility of the lead compound (1) by 100-1000 fold and ≥tenfold, respectively.
Li, Xin; Xu, Huai-long; Liu, Yong-xi; An, Na; Zhao, Si; Bao, Jin-ku
Autophagy, an evolutionarily conserved catabolic process involving the engulfment and degradation of non-essential or abnormal cellular organelles and proteins, is crucial for homeostatic maintenance in living cells. This highly regulated, multi-step process has been implicated in diverse diseases including cancer. Autophagy can function as either a promoter or a suppressor of cancer, which makes it a promising and challenging therapeutic target. Herein, we overview the regulatory mechanisms and dual roles of autophagy in cancer. We also describe some of the representative agents that exert their anticancer effects by regulating autophagy. Additionally, some emerging strategies aimed at modulating autophagy are discussed as having the potential for future anticancer drug discovery. In summary, these findings will provide valuable information to better utilize autophagy in the future development of anticancer therapeutics that meet clinical requirements. PMID:23564085
Karathanasis, Sotirios K.
Despite the explosion of knowledge in basic biological processes controlling tissue regeneration and the growing interest in repairing/replacing diseased tissues and organs through various approaches (e.g., small and large molecule therapeutics, stem cell injection, tissue engineering), the pharmaceutical industry (pharma) has been reluctant to fully adopt these technologies into the traditional drug discovery and research and development (R&D) process. In this article, I discuss knowledge-base gaps and other possible factors that may delay full incorporation of these innovations in pharma R&D. I hope that this discussion will illuminate key issues that currently limit synergistic relationships between pharma and academic institutions and may even stimulate initiation of such collaborative research. PMID:25085955
Long, Daniel D; Aggen, James B; Christensen, Burton G; Judice, J Kevin; Hegde, Sharath S; Kaniga, Koné; Krause, Kevin M; Linsell, Martin S; Moran, Edmund J; Pace, John L
The design, synthesis and antibacterial activity of novel glycopeptide/beta-lactam heterodimers is reported. Employing a multivalent approach to drug discovery, vancomycin and cephalosporin synthons, A and B respectively, were chemically linked to yield heterodimer antibiotics. These novel compounds were designed to inhibit Gram-positive bacterial cell wall biosynthesis by simultaneously targeting the principal cellular targets of both glycopeptides and beta-lactams. The antibiotics 8a-f displayed remarkable potency against a wide range of Gram-positive organisms including methicillin-resistant Staphylococcus aureus (MRSA). Compound 8e demonstrated excellent bactericidal activity against MRSA (ATCC 33591) and initial evidence supports a multivalent mechanism of action for this important new class of antibiotic.
Comer, Eamon; Duvall, Jeremy R; duPont Lee, Maurice
The development of resistance to existing antimicrobials has created a threat to human health that is not being addressed through our current drug pipeline. Limitations with the use of commercial vendor libraries and natural products have created a need for new types of small molecules to be screened in antimicrobial assays. Diversity oriented synthesis (DOS) is a strategy for the efficient generation of compound collections with a high degree of structural diversity. Diversity-oriented synthesis molecules occupy the middle ground of both complexity and efficiency of synthesis between natural products and commercial libraries. In this review we focus upon the use of diversity-oriented synthesis compound collections for the discovery of new antimicrobial agents.
Cruz-Monteagudo, Maykel; Medina-Franco, José L; Pérez-Castillo, Yunierkis; Nicolotti, Orazio; Cordeiro, M Natália D S; Borges, Fernanda
The impact activity cliffs have on drug discovery is double-edged. For instance, whereas medicinal chemists can take advantage of regions in chemical space rich in activity cliffs, QSAR practitioners need to escape from such regions. The influence of activity cliffs in medicinal chemistry applications is extensively documented. However, the 'dark side' of activity cliffs (i.e. their detrimental effect on the development of predictive machine learning algorithms) has been understudied. Similarly, limited amounts of work have been devoted to propose potential solutions to the drawbacks of activity cliffs in similarity-based approaches. In this review, the duality of activity cliffs in medicinal chemistry and computational approaches is addressed, with emphasis on the rationale and potential solutions for handling the 'ugly face' of activity cliffs. Copyright © 2014 Elsevier Ltd. All rights reserved.
Anastassopoulou, Cleo G.; Fuchs, Beth Burgwyn; Mylonakis, Eleftherios
The substantial morbidity and mortality associated with invasive fungal infections constitute undisputed tokens of their severity. The continued expansion of susceptible population groups (such as immunocompromised individuals, patients undergoing extensive surgery, and those hospitalized with serious underlying diseases especially in the intensive care unit) and the limitations of current antifungal agents due to toxicity issues or to the development of resistance, mandate the development of novel antifungal drugs. Currently, drug discovery is transitioning from the traditional in vitro large-scale screens of chemical libraries to more complex bioassays, including in vivo studies on whole animals; invertebrates, such as Caenorhabditis elegans, are thus gaining momentum as screening tools. Key pathogenesis features of fungal infections, including filament formation, are expressed in certain invertebrate and mammalian hosts; among the various potential hosts, C. elegans provides an attractive platform both for the study of host-pathogen interactions and the identification of new antifungal agents. Advantages of compound screening in this facile, relatively inexpensive and not as ethically challenged whole-animal context, include the simultaneous assessment of antifungal efficacy and toxicity that could result in the identification of compounds with distinct mechanisms of action, for example by promoting host immune responses or by impeding fungal virulence factors. With the recent advent of using predictive models to screen for compounds with improved chances of bioavailability in the nematode a priori, high-throughput screening of chemical libraries using the C. elegans-c. albicans antifungal discovery assay holds even greater promise for the identification of novel antifungal agents in the near future. PMID:21470110
Lv, Junfang; Shim, Joong Sup
Despite standard cancer therapies such as chemotherapy and targeted therapy have shown some efficacies, the cancer in many cases eventually relapses and metastasizes upon stopping the treatment. There is a small subpopulation of cancer cells within tumor, with specific characters similar to those found in stem cells. This group of cancer cells is known as tumor-initiating or cancer stem cells (CSCs), which have an ability to self-renew and give rise to cancer cell progeny. CSCs are related with drug resistance, metastasis and relapse of cancer, hence emerging as a crucial drug target for eliminating cancer. Rapid advancement of CSC biology has enabled researchers to isolate and culture CSCs in vitro, making the cells amenable to high-throughput drug screening. Recently, drug repositioning, which utilizes existing drugs to develop potential new indications, has been gaining popularity as an alternative approach for the drug discovery. As existing drugs have favorable bioavailability and safety profiles, drug repositioning is now actively exploited for prompt development of therapeutics for many serious diseases, such as cancer. In this review, we will introduce latest examples of attempted drug repositioning targeting CSCs and discuss potential use of the repositioned drugs for cancer therapy.
Galizzi, Jean-Pierre; Lockhart, Brian Paul; Bril, Antoine
Translational research is a continuum between clinical and basic research where the patient is the center of the research process. It brings clinical research to a starting point for the drug discovery process, permitting the generation of a more robust pathophysiological hypothesis essential for a better selection of drug targets and candidate optimization. It also establishes the basis of early proof for clinical concept studies, preferably in phase I, for which biomarkers and surrogate endpoints can often be used. Systems biology is a prerequisite approach to translational research where technologies and expertise are integrated and articulated to support efficient and productive realization of this concept. The first component of systems biology relies on omics-based technologies and integrates the changes in variables, such as genes, proteins and metabolites, into networks that are responsible for an organism's normal and diseased state. The second component of systems biology is in the domain of computational methods, where simulation and modeling create hypotheses of signaling pathways, transcription networks, physiological processes or even cell- or organism-based models. The simulations aim to show the origin of perturbations of the system that lead to pathological states and what treatment could be achieved to ameliorate or normalize the system. This review discusses how translational research and systems biology together could improve global understanding of drug targets, suggest new targets and approaches for therapeutics, and provide a deeper understanding of drug effects. Taken together, these types of analyses can lead to new therapeutic options while improving the safety and efficacy of new and existing medications.
Tsai, Yingssu; McPhillips, Scott E.; González, Ana; McPhillips, Timothy M.; Zinn, Daniel; Cohen, Aina E.; Feese, Michael D.; Bushnell, David; Tiefenbrunn, Theresa; Stout, C. David; Ludaescher, Bertram; Hedman, Britt; Hodgson, Keith O.; Soltis, S. Michael
New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully
Baumrind, D; Moselle, K A
Adolescent drug use is placed in an historical and developmental perspective. Existing evidence concerning causes and consequences of adolescent drug use is inconclusive. In the absence of conclusive empirical evidence and cogent theories, we present a prima facie case against early adolescent drug use by defending six propositions which posit specific cognitive, conative, and affective negative consequences including impairment of attention and memory; developmental lag imposing categorical limitations on the level of maximum functioning available to the user in cognitive, moral and psychosocial domains; amotivational syndrome; consolidation of diffuse or negative identity; and social alienation and estrangement. We call for a program of research which could provide credible evidence to support or rebut these propositions, and thus address the factual claims underlying the sociomoral concerns of social policy planners.
Lindsley, Craig W
The identification of sites on receptors topographically distinct from the orthosteric sites, so-called allosteric sites, has heralded novel approaches and modes of pharmacology for target modulation. Over the past 20 years, our understanding of allosteric modulation has grown significantly, and numerous advantages, as well as caveats (e.g., flat structure-activity relationships, species differences, "molecular switches"), have been identified. For multiple receptors and proteins, numerous examples have been described where unprecedented levels of selectivity are achieved along with improved physiochemical properties. While not a panacea, these novel approaches represent exciting opportunities for tool compound development to probe the pharmacology and therapeutic potential of discrete molecular targets, as well as new medicines. In this Perspective, in commemoration of the 2013 Philip S. Portoghese Medicinal Chemistry Lectureship ( Lindsley , C. W. Adventures in allosteric drug discovery . Presented at the 246th National Meeting of the American Chemical Society, Indianapolis, IN, September 10, 2013 ; The 2013 Portoghese Lectureship ), several vignettes of drug discovery campaigns targeting novel allosteric mechanisms will be recounted, along with lessons learned and guidelines that have emerged for successful lead optimization.
The identification of sites on receptors topographically distinct from the orthosteric sites, so-called allosteric sites, has heralded novel approaches and modes of pharmacology for target modulation. Over the past 20 years, our understanding of allosteric modulation has grown significantly, and numerous advantages, as well as caveats (e.g., flat structure–activity relationships, species differences, “molecular switches”), have been identified. For multiple receptors and proteins, numerous examples have been described where unprecedented levels of selectivity are achieved along with improved physiochemical properties. While not a panacea, these novel approaches represent exciting opportunities for tool compound development to probe the pharmacology and therapeutic potential of discrete molecular targets, as well as new medicines. In this Perspective, in commemoration of the 2013 Philip S. Portoghese Medicinal Chemistry Lectureship (LindsleyC. W.Adventures in allosteric drug discovery. Presented at the 246th National Meeting of the American Chemical Society, Indianapolis, IN, September 10, 2013; The 2013 Portoghese Lectureship), several vignettes of drug discovery campaigns targeting novel allosteric mechanisms will be recounted, along with lessons learned and guidelines that have emerged for successful lead optimization. PMID:25180768
Quinn, Robert A; Nothias, Louis-Felix; Vining, Oliver; Meehan, Michael; Esquenazi, Eduardo; Dorrestein, Pieter C
Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine. Copyright © 2016. Published by Elsevier Ltd.
Once viewed solely as a tool for low throughput and kinetic analysis of biomolecular interactions, optical biosensors are gaining widespread uses in drug discovery because of recent advances in instrumentation and experimental design. These advances have expanded the capabilities of optical biosensors to meet the needs at many points in the drug discovery process. Concurrent shifts in drug discovery paradigms have seen the growing use of whole cell systems for drug screens, thus creating both a need in drug discovery and a solution in optical biosensors. This article reviews important advances in optical biosensor instrumentation, and highlights the potential of optical biosensors for drug discovery with an emphasis on whole cell sensing in both high throughput and high content fashions.
Yasgar, Adam; Simeonov, Anton
Introduction Much has been presented and debated on the topic of drug abuse and its multidimensional nature, including the role of society and its customs and laws, economical factors, and the magnitude and nature of the burden. Given the complex nature of the receptors and pathways implicated in regulation of the cognitive and behavioral processes associated with addiction, a large number of molecular targets have been interrogated during recent years to discover starting points for development of small molecule interventions. Areas covered This review describes recent developments in the field of early drug discovery for drug abuse interventions, with a special emphasis on advances published during the 2012-2014 period. Expert Opinion Technologically, the processes/platforms utilized in drug abuse drug discovery are nearly identical to those used in the other disease areas. A key complicating factor in drug abuse research is the enormous biological complexity surrounding the brain processes involved and the associated difficulty in finding “good” targets and achieving exquisite selectivity of treatment agents. While tremendous progress has been made during recent years to use the power of high-throughput technologies to discover proof-of-principle molecules for many new targets, next-generation models will be especially important in this field; examples include seeking advantageous drug-drug combinations, use of automated whole-animal behavioral screening systems, advancing our understanding of the role of epigenetics in drug addiction, and the employment of organoid-level 3D test platforms (also referred to as tissue-chip or organs-on-chip). PMID:25251069
Coleman, Robert A
Today's drug discovery and development paradigm is not working, and something needs to be done about it. There is good reason to believe that a move away from reliance on animal surrogates for human subjects in the Pharma Industry's R&D programmes could provide an important step forward. However, no serious move will be made in that direction until there is some hard evidence that it will be rewarded with improved productivity outcomes. The Safer Medicines Trust are proposing that a study be undertaken, involving a range of drugs that have been approved for human use, but have subsequently proved to have limitations in terms of safety and/or efficacy. The aim is to determine the efficiency of a battery of human-based test methods to identify a compound's safety and efficacy profiles, and to compare this with that of the more traditional, largely animal-based methods that were employed in their original development. Should such an approach prove more reliable, the authorities will be faced with important decisions relating to the role of human biological test data in regulatory submissions, while the Pharma Industry will be faced with the key logistical issue of how to acquire the human biomaterials necessary to make possible the routine application of such test methods. 2009 FRAME.
Reid, Terry-Elinor; Fortunak, Joseph M.; Wutoh, Anthony; Wang, Xiang Simon
Receptor Tyrosine Kinases (RTKs) are essential components for regulating cell-cell signaling and communication events in cell growth, proliferation, differentiation, survival and metabolism. Deregulation of RTKs and their associated signaling pathways can lead to a wide variety of human diseases such as immunodeficiency, diabetes, arterosclerosis, psoriasis and cancer. Thus RTKs have become one of the most important drug targets families in recent decade. Pharmaceutical companies have dedicated their research efforts towards the discovery of small-molecule inhibitors of RTKs, many of which had been approved by the U.S. Food and Drug Administration (US FDA) or are currently in clinical trials. The great successes in the development of small-molecule inhibitors of RTKs are largely attributed to the use of modern cheminformatic approaches to identifying lead scaffolds. Those include the quantitative structure-activity relationship (QSAR) modeling, as well as the structure-, and ligand-based pharmacophore modeling techniques in this case. Herein we inspected the literature thoroughly in an effort to conduct a comparative analysis of major findings regarding the essential structure-activity relationships (SARs)/pharmacophore features of known active RTK inhibitors, most of which were collected from cheminformatic modeling approaches. PMID:26369823
Jacobs, Robert T.; Nare, Bakela; Phillips, Margaret A.
African sleeping sickness is endemic in sub-Saharan Africa where the WHO estimates that 60 million people are at risk for the disease. Human African trypanosomiasis (HAT) is 100% fatal if untreated and the current drug therapies have significant limitations due to toxicity and difficult treatment regimes. No new chemical agents have been approved since eflornithine in 1990. The pentamidine analog DB289, which was in late stage clinical trials for the treatment of early stage HAT recently failed due to toxicity issues. A new protocol for the treatment of late-stage T. brucei gambiense that uses combination nifurtomox/eflornithine (NECT) was recently shown to have better safety and efficacy than eflornithine alone, while being easier to administer. This breakthrough represents the only new therapy for HAT since the approval of eflornithine. A number of research programs are on going to exploit the unusual biochemical pathways in the parasite to identify new targets for target based drug discovery programs. HTS efforts are also underway to discover new chemical entities through whole organism screening approaches. A number of inhibitors with anti-trypanosomal activity have been identified by both approaches, but none of the programs are yet at the stage of identifying a preclinical candidate. This dire situation underscores the need for continued effort to identify new chemical agents for the treatment of HAT. PMID:21401507
Taylor, Christina M.; Wang, Qi; Rosa, Bruce A.; Huang, Stanley Ching-Cheng; Powell, Kerrie; Schedl, Tim; Pearce, Edward J.; Abubucker, Sahar; Mitreva, Makedonka
Parasitic roundworm infections plague more than 2 billion people (1/3 of humanity) and cause drastic losses in crops and livestock. New anthelmintic drugs are urgently needed as new drug resistance and environmental concerns arise. A “chokepoint reaction” is defined as a reaction that either consumes a unique substrate or produces a unique product. A chokepoint analysis provides a systematic method of identifying novel potential drug targets. Chokepoint enzymes were identified in the genomes of 10 nematode species, and the intersection and union of all chokepoint enzymes were found. By studying and experimentally testing available compounds known to target proteins orthologous to nematode chokepoint proteins in public databases, this study uncovers features of chokepoints that make them successful drug targets. Chemogenomic screening was performed on drug-like compounds from public drug databases to find existing compounds that target homologs of nematode chokepoints. The compounds were prioritized based on chemical properties frequently found in successful drugs and were experimentally tested using Caenorhabditis elegans. Several drugs that are already known anthelmintic drugs and novel candidate targets were identified. Seven of the compounds were tested in Caenorhabditis elegans and three yielded a detrimental phenotype. One of these three drug-like compounds, Perhexiline, also yielded a deleterious effect in Haemonchus contortus and Onchocerca lienalis, two nematodes with divergent forms of parasitism. Perhexiline, known to affect the fatty acid oxidation pathway in mammals, caused a reduction in oxygen consumption rates in C. elegans and genome-wide gene expression profiles provided an additional confirmation of its mode of action. Computational modeling of Perhexiline and its target provided structural insights regarding its binding mode and specificity. Our lists of prioritized drug targets and drug-like compounds have potential to expedite the discovery
Clematis, Andrea; Quarati, Alfonso; Cesini, Daniele; Milanesi, Luciano; Merelli, Ivan
Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements. PMID:24106693
Eustache, Stéphanie; Leprince, Jérôme; Tufféry, Pierre
Peptides have gained renewed interest as candidate therapeutics. However, to bring them to a broader clinical use, challenges such as the rational optimization of their pharmacological properties remain. Peptide scanning techniques offer a systematic framework to gain information on the functional role of individual amino acids of a peptide. Due to progress in mastering new chemical synthesis routes targeting amino acid backbone, they are currently diversified. Structure-activity relationship (SAR) analyses such as alanine- or enantioneric- scanning can now be supplemented by N-substitution, lactam cyclisation- or aza-amino scanning procedures addressing not only SAR considerations but also the peptide pharmacological properties. This review highlights the different scanning techniques currently available and illustrates how they can impact drug discovery. Progress in peptide scanning techniques opens new perspectives for peptide drug development. It comes with the promise of a paradigm change in peptide drug design in which peptide drugs will be closer to the parent peptides. However, scanning still remains assimilable to a trial and error strategy that could benefit from being combined with specific in silico approaches that start reaching maturity.
Kumalo, Hezekiel Mathambo; Bhakat, Soumendranath; Soliman, Mahmoud E S
he present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed some significant advantages over non-covalent inhibitors such as covalent warheads can target rare, non-conserved residue of a particular target protein and thus led to development of highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with shallow binding cleavage which will led to development of novel inhibitors with increased potency than non-covalent inhibitors. Several computational approaches have been developed to simulate covalent interactions; however, this is still a challenging area to explore. Covalent molecular docking has been recently implemented in the computer-aided drug design workflows to describe covalent interactions between inhibitors and biological targets. In this review we highlight: (i) covalent interactions in biomolecular systems; (ii) the mathematical framework of covalent molecular docking; (iii) implementation of covalent docking protocol in drug design workflows; (iv) applications covalent docking: case studies and (v) shortcomings and future perspectives of covalent docking. To the best of our knowledge; this review is the first account that highlights different aspects of covalent docking with its merits and pitfalls. We believe that the method and applications highlighted in this study will help future efforts towards the design of irreversible inhibitors.
Pearson, Lesley-Anne; Foley, David William
The complexities of modern drug discovery-an interdisciplinary process that often takes years and costs billions-can be extremely challenging to explain to a public audience. We present details of a 30 minute demonstrative lecture that uses well-known experiments to illustrate key concepts in drug discovery including synthesis, assay and metabolism.
Progesterone A-Form as a Target for New Drug Discovery in Human Breast Cancer PRINCIPAL INVESTIGATOR: James Voltz Paloma Giangrande Donald McDonnell, Ph.D...SUBTITLE 5. FUNDING NUMBERS Human Progesterone A-Form as a Target for New Drug DAMD17-98-1-8070 Discovery in Human Breast Cancer 6. AUTHOR(S) James