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.
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
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.
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.
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.
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.
Leek, Hanna; Andersson, Shalini
The provision of pure enantiomers is of increasing importance not only for the pharmaceutical industry but also for agro-chemistry and biotechnology. In drug discovery and development, the enantiomers of a chiral drug depict unique chemical and pharmacological behaviors in a chiral environment, such as the human body, in which the stereochemistry of the chiral drugs determines their pharmacokinetic, pharmacodynamic and toxicological properties. We present a number of challenging case studies of up-to-kilogram separations of racemic or enriched isomer mixtures using preparative liquid chromatography and super critical fluid chromatography to generate individual enantiomers that have enabled the development of new candidate drugs within AstraZeneca. The combination of chromatography and racemization as well as strategies on when to apply preparative chiral chromatography of enantiomers in a multi-step synthesis of a drug compound can further facilitate accelerated drug discovery and the early clinical evaluation of the drug candidates.
Lee, Wen Hwa
There is a scarcity of novel treatments to address many unmet medical needs. Industry and academia are finally coming to terms with the fact that the prevalent models and incentives for innovation in early stage drug discovery are failing to promote progress quickly enough. Here we will examine how an open model of precompetitive public–private research partnership is enabling efficient derisking and acceleration in the early stages of drug discovery, whilst also widening the range of communities participating in the process, such as patient and disease foundations. PMID:26042736
Feinstein, Wei; Brylinski, Michal
Computer-aided design is one of the critical components of modern drug discovery. Drug development is routinely streamlined using computational approaches to improve hit identification and lead selection, enhance bioavailability, and reduce toxicity. A mounting body of genomic knowledge accumulated during the last decade or so presents great opportunities for pharmaceutical research. However, new challenges also arose because processing this large volume of data demands unprecedented computing resources. On the other hand, the state-of-the-art heterogeneous systems deliver petaflops of peak performance to accelerate scientific discovery. In this communication, we review modern parallel accelerator architectures, mainly focusing on Intel Xeon Phi many-core devices. Xeon Phi is a relatively new platform that features tens of computing cores with hundreds of threads offering massively parallel capabilities for a broad range of application. We also discuss common parallel programming frameworks targeted to this accelerator, including OpenMP, OpenCL, MPI and HPX. Recent advances in code development for many-core devices are described to demonstrate the advantages of heterogeneous implementations over the traditional, serial computing. Finally, we highlight selected algorithms, eFindSite, a ligand binding site predictor, a force field for bio-molecular simulations, and BUDE, a structure-based virtual screening engine, to demonstrate how modern drug discovery is accelerated by heterogeneous systems equipped with parallel computing devices.
Perryman, Alexander L.; Horta Andrade, Carolina
The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses. PMID:27764115
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
Hagiwara, Yohsuke; Ohno, Kazuki; Orita, Masaya; Koga, Ryota; Endo, Toshio; Akiyama, Yutaka; Sekijima, Masakazu
The growing power of central processing units (CPU) has made it possible to use quantum mechanical (QM) calculations for in silico drug discovery. However, limited CPU power makes large-scale in silico screening such as virtual screening with QM calculations a challenge. Recently, general-purpose computing on graphics processing units (GPGPU) has offered an alternative, because of its significantly accelerated computational time over CPU. Here, we review a GPGPU-based supercomputer, TSUBAME2.0, and its promise for next generation in silico drug discovery, in high-density (HD) silico drug discovery.
Ge, Hu; Wang, Yu; Li, Chanjuan; Chen, Nanhao; Xie, Yufang; Xu, Mengyan; He, Yingyan; Gu, Xinchun; Wu, Ruibo; Gu, Qiong; Zeng, Liang; Xu, Jun
High-performance computing (HPC) has become a state strategic technology in a number of countries. One hypothesis is that HPC can accelerate biopharmaceutical innovation. Our experimental data demonstrate that HPC can significantly accelerate biopharmaceutical innovation by employing molecular dynamics-based virtual screening (MDVS). Without using HPC, MDVS for a 10K compound library with tens of nanoseconds of MD simulations requires years of computer time. In contrast, a state of the art HPC can be 600 times faster than an eight-core PC server is in screening a typical drug target (which contains about 40K atoms). Also, careful design of the GPU/CPU architecture can reduce the HPC costs. However, the communication cost of parallel computing is a bottleneck that acts as the main limit of further virtual screening improvements for drug innovations.
Do, Quoc-Tuan; Bernard, Philippe
Combinatorial chemistry and high-throughput screening (HTS) have led to the identification of numerous agents that are active and selective in vitro. Identifying drugs that are active in vivo, however, remains a challenge. Traditional medicinal cures based on natural materials have proven useful for many populations worldwide, representing huge and disperse tracts of knowledge that are sometimes neglected in Western research due to differences in the concepts of illness. In this review we introduce a new approach, termed 'reverse pharmacognosy' (from diverse molecules to plants), which can be coupled with pharmacognosy (from biodiverse plants to molecules). Reverse pharmacognosy utilizes new techniques, such as HTS, virtual screening and a knowledge database containing the traditional uses of plants. Integrating pharmacognosy and reverse pharmacognosy in the research process may provide an efficient and rapid tool for natural drug discovery.
Jiménez-Díaz, María Belén; Viera, Sara; Ibáñez, Javier; Mulet, Teresa; Magán-Marchal, Noemí; Garuti, Helen; Gómez, Vanessa; Cortés-Gil, Lorena; Martínez, Antonio; Ferrer, Santiago; Fraile, María Teresa; Calderón, Félix; Fernández, Esther; Shultz, Leonard D.; Leroy, Didier; Wilson, David M.; García-Bustos, José Francisco; Gamo, Francisco Javier; Angulo-Barturen, Iñigo
The emergence of resistance to available antimalarials requires the urgent development of new medicines. The recent disclosure of several thousand compounds active in vitro against the erythrocyte stage of Plasmodium falciparum has been a major breakthrough, though converting these hits into new medicines challenges current strategies. A new in vivo screening concept was evaluated as a strategy to increase the speed and efficiency of drug discovery projects in malaria. The new in vivo screening concept was developed based on human disease parameters, i.e. parasitemia in the peripheral blood of patients on hospital admission and parasite reduction ratio (PRR), which were allometrically down-scaled into P. berghei-infected mice. Mice with an initial parasitemia (P0) of 1.5% were treated orally for two consecutive days and parasitemia measured 24 h after the second dose. The assay was optimized for detection of compounds able to stop parasite replication (PRR = 1) or induce parasite clearance (PRR >1) with statistical power >99% using only two mice per experimental group. In the P. berghei in vivo screening assay, the PRR of a set of eleven antimalarials with different mechanisms of action correlated with human-equivalent data. Subsequently, 590 compounds from the Tres Cantos Antimalarial Set with activity in vitro against P. falciparum were tested at 50 mg/kg (orally) in an assay format that allowed the evaluation of hundreds of compounds per month. The rate of compounds with detectable efficacy was 11.2% and about one third of active compounds showed in vivo efficacy comparable with the most potent antimalarials used clinically. High-throughput, high-content in vivo screening could rapidly select new compounds, dramatically speeding up the discovery of new antimalarial medicines. A global multilateral collaborative project aimed at screening the significant chemical diversity within the antimalarial in vitro hits described in the literature is a feasible task
This highly interactive meeting effectively covered critical issues on every transaction from drug discovery through to development and commercialization. The program included company-specific descriptions of new discovery products, together with seminars by clinical research and site management organizations on the acceleration of development, pharmaco-economics, branding of products, direct-to-consumer advertising, global marketing, management, information technology and business strategy. There were approximately 50 sessions covered by 70 speakers.
Phillips, Anthony George; Hongaard-Andersen, Peter; Moscicki, Richard A; Sahakian, Barbara; Quirion, Rémi; Krishnan, K Ranga Rama; Race, Tim
Central nervous system (CNS) diseases and, in particular, mental health disorders, are becoming recognized as the health challenge of the 21(st) century. Currently, at least 10% of the global population is affected by a mental health disorder, a figure that is set to increase year on year. Meanwhile, the rate of development of new CNS drugs has not increased for many years, despite unprecedented levels of investment. In response to this state of affairs, the Collegium Internationale Neuro-Psychopharmacologicum (CINP) convened a summit to discuss ways to reverse this disturbing trend through new partnerships to accelerate CNS drug discovery. The objectives of the Summit were to explore the issues affecting the value chain (i.e. the chain of activities or stakeholders that a company engages in/with to deliver a product to market) in brain research, thereby gaining insights from key stakeholders and developing actions to address unmet needs; to identify achievable objectives to address the issues; to develop action plans to bring about measurable improvements across the value chain and accelerate CNS drug discovery; and finally, to communicate recommendations to governments, the research and development community, and other relevant stakeholders. Summit outputs include the following action plans, aligned to the pressure points within the brain research-drug development value chain: Code of conduct dealing with conflict of interest issues, Prevention, early diagnosis, and treatment, Linking science and regulation, Patient involvement in trial design, definition of endpoints, etc., Novel trial design, Reproduction and confirmation of data, Update of intellectual property (IP) laws to facilitate repurposing and combination therapy (low priority), Large-scale, global patient registries, Editorials on nomenclature, biomarkers, and diagnostic tools, and Public awareness, with brain disease advocates to attend G8 meetings and World Economic Forum (WEF) Annual meetings in
Hongaard-Andersen, Peter; Moscicki, Richard A.; Sahakian, Barbara; Quirion, Rémi; Krishnan, K. Ranga Rama; Race, Tim
Central nervous system (CNS) diseases and, in particular, mental health disorders, are becoming recognized as the health challenge of the 21st century. Currently, at least 10% of the global population is affected by a mental health disorder, a figure that is set to increase year on year. Meanwhile, the rate of development of new CNS drugs has not increased for many years, despite unprecedented levels of investment. In response to this state of affairs, the Collegium Internationale Neuro-Psychopharmacologicum (CINP) convened a summit to discuss ways to reverse this disturbing trend through new partnerships to accelerate CNS drug discovery. The objectives of the Summit were to explore the issues affecting the value chain (i.e. the chain of activities or stakeholders that a company engages in/with to deliver a product to market) in brain research, thereby gaining insights from key stakeholders and developing actions to address unmet needs; to identify achievable objectives to address the issues; to develop action plans to bring about measurable improvements across the value chain and accelerate CNS drug discovery; and finally, to communicate recommendations to governments, the research and development community, and other relevant stakeholders. Summit outputs include the following action plans, aligned to the pressure points within the brain research-drug development value chain: Code of conduct dealing with conflict of interest issues,Prevention, early diagnosis, and treatment,Linking science and regulation,Patient involvement in trial design, definition of endpoints, etc.,Novel trial design,Reproduction and confirmation of data,Update of intellectual property (IP) laws to facilitate repurposing and combination therapy (low priority),Large-scale, global patient registries,Editorials on nomenclature, biomarkers, and diagnostic tools, andPublic awareness, with brain disease advocates to attend G8 meetings and World Economic Forum (WEF) Annual meetings in Davos
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.
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
Doty, F. Patrick; Yang, Pin; Zhou, Xiaowang
Elpasolite scintillators are a large family of halides which includes compounds reported to meet the NA22 program goals of <3% energy resolution at 662 keV1. This work investigated the potential to produce quality elpasolite compounds and alloys of useful sizes at reasonable cost, through systematic experimental and computational investigation of crystal structure and properties across the composition space. Discovery was accelerated by computational methods and models developed previously to efficiently identify cubic members of the elpasolite halides, and to evaluate stability of anion and cation exchange alloys.
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 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.
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.
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.
Todd, A. M. M.; Bluem, H. P.; Jarvis, J. D.; Park, J. H.; Rathke, J. W.; Schultheiss, T. J.
Several Advanced Energy Systems (AES) accelerator projects that span applications in Discovery Science and Security are described. The design and performance of the IR and THz free electron laser (FEL) at the Fritz-Haber-Institut der Max-Planck-Gesellschaft in Berlin that is now an operating user facility for physical chemistry research in molecular and cluster spectroscopy as well as surface science, is highlighted. The device was designed to meet challenging specifications, including a final energy adjustable in the range of 15-50 MeV, low longitudinal emittance (<50 keV-psec) and transverse emittance (<20 π mm-mrad), at more than 200 pC bunch charge with a micropulse repetition rate of 1 GHz and a macropulse length of up to 15 μs. Secondly, we will describe an ongoing effort to develop an ultrafast electron diffraction (UED) source that is scheduled for completion in 2015 with prototype testing taking place at the Brookhaven National Laboratory (BNL) Accelerator Test Facility (ATF). This tabletop X-band system will find application in time-resolved chemical imaging and as a resource for drug-cell interaction analysis. A third active area at AES is accelerators for security applications where we will cover some top-level aspects of THz and X-ray systems that are under development and in testing for stand-off and portal detection.
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.
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
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.
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
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.
Temesi, David G; Martin, Scott; Smith, Robin; Jones, Christopher; Middleton, Brian
Screening assays capable of performing quantitative analysis on hundreds of compounds per week are used to measure metabolic stability during early drug discovery. Modern orthogonal acceleration time-of-flight (OATOF) mass spectrometers equipped with analogue-to-digital signal capture (ADC) now offer performance levels suitable for many applications normally supported by triple quadruple instruments operated in multiple reaction monitoring (MRM) mode. Herein the merits of MRM and OATOF with ADC detection are compared for more than 1000 compounds screened in rat and/or cryopreserved human hepatocytes over a period of 3 months. Statistical comparison of a structurally diverse subset indicated good agreement for the two detection methods. The overall success rate was higher using OATOF detection and data acquisition time was reduced by around 20%. Targeted metabolites of diazepam were detected in samples from a CLint determination performed at 1 microM. Data acquisition by positive and negative ion mode switching can be achieved on high-performance liquid chromatography (HPLC) peak widths as narrow as 0.2 min (at base), thus enabling a more comprehensive first pass analysis with fast HPLC gradients. Unfortunately, most existing OATOF instruments lack the software tools necessary to rapidly convert the huge amounts of raw data into quantified results. Software with functionality similar to open access triple quadrupole systems is needed for OATOF to truly compete in a high-throughput screening environment.
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.
Yang, Xianjin; Debonneuil, Edouard; Zhavoronkov, Alex; Mishra, Bud
Advances in financial engineering are radically reshaping the biomedical marketplace. For instance, new methods of pooling diversified drug development programs by placing them in a special purpose vehicle (SPV) have been proposed to create a securitized cancer megafund allowing for debt and equity participation. In this study, we perform theoretical and numerical simulations that highlight the role of empirical validation of the projects comprising a cancer megafund. We quantify the degree to which the deliberately designed structure of derivatives and investments is key to its liquidity. Research megafunds with comprehensive in silico and laboratory validation protocols and ability to issue both debt, and equity as well as hybrid financial products may enable conservative investors including pension funds and sovereign government funds to profit from unique securitization opportunities. Thus, while hedging investor's longevity risk, such well-validated megafunds will contribute to health, wellbeing and longevity of the global population. PMID:27275544
Yang, Xianjin; Debonneuil, Edouard; Zhavoronkov, Alex; Mishra, Bud
Advances in financial engineering are radically reshaping the biomedical marketplace. For instance, new methods of pooling diversified drug development programs by placing them in a special purpose vehicle (SPV) have been proposed to create a securitized cancer megafund allowing for debt and equity participation. In this study, we perform theoretical and numerical simulations that highlight the role of empirical validation of the projects comprising a cancer megafund. We quantify the degree to which the deliberately designed structure of derivatives and investments is key to its liquidity. Research megafunds with comprehensive in silico and laboratory validation protocols and ability to issue both debt, and equity as well as hybrid financial products may enable conservative investors including pension funds and sovereign government funds to profit from unique securitization opportunities. Thus, while hedging investor's longevity risk, such well-validated megafunds will contribute to health, well being and longevity of the global population.
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.
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.
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.
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
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. PMID:22247822
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.
Rzhetsky, Andrey; Foster, Jacob G.; Foster, Ian T.; Evans, James A.
Scientists perform a tiny subset of all possible experiments. What characterizes the experiments they choose? What are the consequences of those choices for the pace of scientific discovery? We model scientific knowledge as a network and science as a sequence of experiments designed to gradually uncover it. By analyzing millions of biomedical articles published over 30 y, we find that biomedical scientists pursue conservative research strategies exploring the local neighborhood of central, important molecules. Although such strategies probably serve scientific careers, we show that they slow scientific advance, especially in mature fields, where more risk and less redundant experimentation would accelerate discovery of the network. Lastly, we also consider institutional arrangements that could help science pursue these more efficient strategies.
Rzhetsky, Andrey; Foster, Jacob G.; Foster, Ian T.; ...
Scientists perform a tiny subset of all possible experiments. What characterizes the experiments they choose? What are the consequences of those choices for the pace of scientific discovery? We model scientific knowledge as a network and science as a sequence of experiments designed to gradually uncover it. By analyzing millions of biomedical articles published over 30 y, we find that biomedical scientists pursue conservative research strategies exploring the local neighborhood of central, important molecules. Although such strategies probably serve scientific careers, we show that they slow scientific advance, especially in mature fields, where more risk and less redundant experimentation wouldmore » accelerate discovery of the network. Lastly, we also consider institutional arrangements that could help science pursue these more efficient strategies.« less
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
Sims, James S.; Hagedorn, John G.; Ketcham, Peter M.; Satterfield, Steven G.; Griffin, Terence J.; George, William L.; Fowler, Howland A.; am Ende, Barbara A.; Hung, Howard K.; Bohn, Robert B.; Koontz, John E.; Martys, Nicos S.; Bouldin, Charles E.; Warren, James A.; Feder, David L.; Clark, Charles W.; Filla, B. James; Devaney, Judith E.
The rate of scientific discovery can be accelerated through computation and visualization. This acceleration results from the synergy of expertise, computing tools, and hardware for enabling high-performance computation, information science, and visualization that is provided by a team of computation and visualization scientists collaborating in a peer-to-peer effort with the research scientists. In the context of this discussion, high performance refers to capabilities beyond the current state of the art in desktop computing. To be effective in this arena, a team comprising a critical mass of talent, parallel computing techniques, visualization algorithms, advanced visualization hardware, and a recurring investment is required to stay beyond the desktop capabilities. This article describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing and visualization to accelerate condensate modeling, (2) fluid flow in porous materials and in other complex geometries, (3) flows in suspensions, (4) x-ray absorption, (5) dielectric breakdown modeling, and (6) dendritic growth in alloys. PMID:27551642
Sims, J S; Hagedorn, J G; Ketcham, P M; Satterfield, S G; Griffin, T J; George, W L; Fowler, H A; Am Ende, B A; Hung, H K; Bohn, R B; Koontz, J E; Martys, N S; Bouldin, C E; Warren, J A; Feder, D L; Clark, C W; Filla, B J; Devaney, J E
The rate of scientific discovery can be accelerated through computation and visualization. This acceleration results from the synergy of expertise, computing tools, and hardware for enabling high-performance computation, information science, and visualization that is provided by a team of computation and visualization scientists collaborating in a peer-to-peer effort with the research scientists. In the context of this discussion, high performance refers to capabilities beyond the current state of the art in desktop computing. To be effective in this arena, a team comprising a critical mass of talent, parallel computing techniques, visualization algorithms, advanced visualization hardware, and a recurring investment is required to stay beyond the desktop capabilities. This article describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing and visualization to accelerate condensate modeling, (2) fluid flow in porous materials and in other complex geometries, (3) flows in suspensions, (4) x-ray absorption, (5) dielectric breakdown modeling, and (6) dendritic growth in alloys.
Mortishire-Smith, Russell J; O'Connor, Desmond; Castro-Perez, Jose M; Kirby, Jane
The resource investment required to characterise the metabolic fate of a compound is relatively large, meaning that within a drug discovery environment relatively few compounds are characterised in depth. Rate-limiting steps include the setting up of a complex array of mass spectrometry experiments and the subsequent analysis of the large data sets produced. We describe here a strategy for the evaluation of metabolic routes using full-scan high-resolution liquid chromatography/quadrupole time-of-flight mass spectrometry (LC/QToFMS) with automated data analysis using Metabolynx, a commercially available software package. Data from several structurally diverse compounds taken from the literature illustrate that, with careful setting of key parameters, this approach is able to indicate the presence of a wide range of metabolites with only a limited requirement for manual intervention.
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.
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...
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.
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.
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.
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.
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.
... Matters NIH Research Matters January 13, 2014 Arthritis Genetics Analysis Aids Drug Discovery An international research team ... may play a role in triggering the disease. Genetic factors are also thought to play a role. ...
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.
Beckman, P.; Dave, P.; Drugan, C.
As a gateway for scientific discovery, the Argonne Leadership Computing Facility (ALCF) works hand in hand with the world's best computational scientists to advance research in a diverse span of scientific domains, ranging from chemistry, applied mathematics, and materials science to engineering physics and life sciences. Sponsored by the U.S. Department of Energy's (DOE) Office of Science, researchers are using the IBM Blue Gene/L supercomputer at the ALCF to study and explore key scientific problems that underlie important challenges facing our society. For instance, a research team at the University of California-San Diego/ SDSC is studying the molecular basis of Parkinson's disease. The researchers plan to use the knowledge they gain to discover new drugs to treat the disease and to identify risk factors for other diseases that are equally prevalent. Likewise, scientists from Pratt & Whitney are using the Blue Gene to understand the complex processes within aircraft engines. Expanding our understanding of jet engine combustors is the secret to improved fuel efficiency and reduced emissions. Lessons learned from the scientific simulations of jet engine combustors have already led Pratt & Whitney to newer designs with unprecedented reductions in emissions, noise, and cost of ownership. ALCF staff members provide in-depth expertise and assistance to those using the Blue Gene/L and optimizing user applications. Both the Catalyst and Applications Performance Engineering and Data Analytics (APEDA) teams support the users projects. In addition to working with scientists running experiments on the Blue Gene/L, we have become a nexus for the broader global community. In partnership with the Mathematics and Computer Science Division at Argonne National Laboratory, we have created an environment where the world's most challenging computational science problems can be addressed. Our expertise in high-end scientific computing enables us to provide guidance for applications
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
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.
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.
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
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.
Rzhetsky, Andrey; Foster, Jacob G; Foster, Ian T; Evans, James A
A scientist's choice of research problem affects his or her personal career trajectory. Scientists' combined choices affect the direction and efficiency of scientific discovery as a whole. In this paper, we infer preferences that shape problem selection from patterns of published findings and then quantify their efficiency. We represent research problems as links between scientific entities in a knowledge network. We then build a generative model of discovery informed by qualitative research on scientific problem selection. We map salient features from this literature to key network properties: an entity's importance corresponds to its degree centrality, and a problem's difficulty corresponds to the network distance it spans. Drawing on millions of papers and patents published over 30 years, we use this model to infer the typical research strategy used to explore chemical relationships in biomedicine. This strategy generates conservative research choices focused on building up knowledge around important molecules. These choices become more conservative over time. The observed strategy is efficient for initial exploration of the network and supports scientific careers that require steady output, but is inefficient for science as a whole. Through supercomputer experiments on a sample of the network, we study thousands of alternatives and identify strategies much more efficient at exploring mature knowledge networks. We find that increased risk-taking and the publication of experimental failures would substantially improve the speed of discovery. We consider institutional shifts in grant making, evaluation, and publication that would help realize these efficiencies.
Rzhetsky, Andrey; Foster, Jacob G.; Foster, Ian T.
A scientist’s choice of research problem affects his or her personal career trajectory. Scientists’ combined choices affect the direction and efficiency of scientific discovery as a whole. In this paper, we infer preferences that shape problem selection from patterns of published findings and then quantify their efficiency. We represent research problems as links between scientific entities in a knowledge network. We then build a generative model of discovery informed by qualitative research on scientific problem selection. We map salient features from this literature to key network properties: an entity’s importance corresponds to its degree centrality, and a problem’s difficulty corresponds to the network distance it spans. Drawing on millions of papers and patents published over 30 years, we use this model to infer the typical research strategy used to explore chemical relationships in biomedicine. This strategy generates conservative research choices focused on building up knowledge around important molecules. These choices become more conservative over time. The observed strategy is efficient for initial exploration of the network and supports scientific careers that require steady output, but is inefficient for science as a whole. Through supercomputer experiments on a sample of the network, we study thousands of alternatives and identify strategies much more efficient at exploring mature knowledge networks. We find that increased risk-taking and the publication of experimental failures would substantially improve the speed of discovery. We consider institutional shifts in grant making, evaluation, and publication that would help realize these efficiencies. PMID:26554009
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.
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
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.
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.
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.
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
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
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.
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.
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.
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
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.
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.
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
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.
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
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.
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).
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
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.
Prabhu, Vidya; Xu, Han
Site specific genome editing has been gradually employed in drug discovery and development process over the past few decades. Recent development of CRISPR technology has significantly accelerated the incorporation of genome editing in the bench side to bedside process. In this review, we summarize examples of applications of genome editing in the drug discovery and development process. We also discuss current hurdles and solutions of genome editing.
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.
Bailey, David S; Zanders, Edward D
Social networking is beginning to make an impact on the drug discovery process. While bioinformatics and chemoinformatics underpin research at a scientific level, rapid communication between individual researchers across continents now allows the global exchange of ideas, tools and technologies. Networking at this level of speed and reach is quite a recent phenomenon. It facilitates the development of common interests, accelerates technology transfer and increases cooperative and competitive behaviour. In this review, we critically evaluate different web based networking approaches as effective resources for the drug discovery scientist. We also ask whether social networking sites will evolve into serious and credible resources for the drug discovery community.
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.
Riera, Andres Ricardo Perez; Barros, Raimundo Barbosa; de Sousa, Francisco Daniel; Baranchuk, Adrian
Accelerated Idioventricular Rhythm (AIVR) is a ventricular rhythm consisting of three or more consecutive monomorphic beats, with gradual onset and gradual termination. It can rarely manifest in patients with completely normal hearts or with structural heart disease. It is usually seen during acute myocardial infarction reperfusion. This manuscript aims to review the history of the main discoveries that lead to the identification and comprehension of this fascinating arrhythmia. PMID:20084194
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.
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
The progress made in genome research raises the question whether the new knowledge bases that have emerged may also lead to better antidepressants. The past has seen many remarkable improvements over traditional drugs, but not a real breakthrough. More recently hypothesis-driven research in depression has focussed upon stress-hormone regulation as a possible target, but validation of new drugs is not yet in sight. In parallel, we see an upsurge of systematic unbiased research in a biotechnology-driven drug discovery effort. This research can only lead to results if clinical research adapts to these new demands by phenotyping depressed patients not only according to psychopathological characteristics but also by utilising functional (e.g. neuroendocrine, neuropsychological, neurophysiological, neuroimaging and clinical drug response) data that are to be correlated with data from genotyping. To achieve the goal of genotype/phenotype-based differential therapy, large-scale efforts with regards to both patient samples and genotyping capacities are needed. In the long term, increasingly detailed patient information, if translated into specific pharmacological treatments, will lead to customized drugs and thus to a partial fragmentation of the antidepressant market. Concurrently, the improved genotyping/phenotyping efforts will also lead to more widely applicable drugs that promise to avoid side effects and refractoriness and also to hasten the time to onset of action. Once these goals are achieved notorious undertreatment of depression may come to an end.
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.
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.
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
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.
Norris, Ray P.
Special Session 5 on Accelerating the Rate of Astronomical Discovery addressed a range of potential limits to progress: paradigmatic, technological, organizational, and political. It examined each issue both from modern and historical perspectives, and drew lessons to guide future progress. A number of issues were identified which may regulate the flow of discoveries, such as the balance between large strongly-focussed projects and instruments, designed to answer the most fundamental questions confronting us, and the need to maintain a creative environment with room for unorthodox thinkers and bold, high risk, projects. Also important is the need to maintain historical and cultural perspectives, and the need to engage the minds of the most brilliant young people on the planet, regardless of their background, ethnicity, gender, or geography.
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.
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.
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.
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.
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
The chapter reviews the historical phases of cosmic ray research from the very beginning around 1900 until the 1940s when first particle accelerators replaced cosmic particles as source for elementary particle interactions. In opposite to the discovery of X-rays or the ionising α-, β- and γ-rays, it was an arduous path to the definite acceptance of the new radiation. The starting point was the explanation that air becomes conductive by the ionising radiation of radioactive elements in the surroundings. In the following years the penetration power of the radiation was studied with the result, that there seems be a component harder than the known γ-rays. Victor F. Hess did in 1912 the key experiment with a hydrogen balloon. He measured with three detectors an increase of ionisation up to altitudes of 5 300 m and discovered the extraterrestrial penetrating radiation. The next phase is characterised by W. Kolhörster's confirmation in 1914, doubts by R.A. Millikan and others as well as the spectacular re-discovery of cosmic rays by Millikan in 1926. With the invention of new detectors as the cloud chamber and the Geiger-Müller counter and of the coincidence method the properties of cosmic rays could be investigated. One of the striking results was the discovery that cosmic rays are of corpuscular nature. The broad research activities starting end of the 1920s were the begin of a scientific success story, which nobody of the early protagonists might have imagined. In 1932 C.D. Anderson discovered the antiparticle of the electron. It was the birth of elementary particle physics. Four years later the muon was discovered which was for many years wrongly assumed to be the carrier of the short range nuclear force predicted by H. Yukawa. One of the last high-lights before the particle accelerators took over this field of fundamental research was the discovery of the Yukawa particle. In photographic emulsions exposed by cosmic particles the pion was found in 1947. This
Giardiello, Marco; Liptrott, Neill J.; McDonald, Tom O.; Moss, Darren; Siccardi, Marco; Martin, Phil; Smith, Darren; Gurjar, Rohan; Rannard, Steve P.; Owen, Andrew
Considerable scope exists to vary the physical and chemical properties of nanoparticles, with subsequent impact on biological interactions; however, no accelerated process to access large nanoparticle material space is currently available, hampering the development of new nanomedicines. In particular, no clinically available nanotherapies exist for HIV populations and conventional paediatric HIV medicines are poorly available; one current paediatric formulation utilizes high ethanol concentrations to solubilize lopinavir, a poorly soluble antiretroviral. Here we apply accelerated nanomedicine discovery to generate a potential aqueous paediatric HIV nanotherapy, with clinical translation and regulatory approval for human evaluation. Our rapid small-scale screening approach yields large libraries of solid drug nanoparticles (160 individual components) targeting oral dose. Screening uses 1 mg of drug compound per library member and iterative pharmacological and chemical evaluation establishes potential candidates for progression through to clinical manufacture. The wide applicability of our strategy has implications for multiple therapy development programmes. PMID:27767027
Giardiello, Marco; Liptrott, Neill J.; McDonald, Tom O.; Moss, Darren; Siccardi, Marco; Martin, Phil; Smith, Darren; Gurjar, Rohan; Rannard, Steve P.; Owen, Andrew
Considerable scope exists to vary the physical and chemical properties of nanoparticles, with subsequent impact on biological interactions; however, no accelerated process to access large nanoparticle material space is currently available, hampering the development of new nanomedicines. In particular, no clinically available nanotherapies exist for HIV populations and conventional paediatric HIV medicines are poorly available; one current paediatric formulation utilizes high ethanol concentrations to solubilize lopinavir, a poorly soluble antiretroviral. Here we apply accelerated nanomedicine discovery to generate a potential aqueous paediatric HIV nanotherapy, with clinical translation and regulatory approval for human evaluation. Our rapid small-scale screening approach yields large libraries of solid drug nanoparticles (160 individual components) targeting oral dose. Screening uses 1 mg of drug compound per library member and iterative pharmacological and chemical evaluation establishes potential candidates for progression through to clinical manufacture. The wide applicability of our strategy has implications for multiple therapy development programmes.
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.
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.
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
Bachi, Keren; Sierra, Salvador; Volkow, Nora D; Goldstein, Rita Z; Alia-Klein, Nelly
Drug-addiction may trigger early onset of age-related disease, due to drug-induced multi-system toxicity and perilous lifestyle, which remains mostly undetected and untreated. We present the literature on pathophysiological processes that may hasten aging and its relevance to addiction, including: oxidative stress and cellular aging, inflammation in periphery and brain, decline in brain volume and function, and early onset of cardiac, cerebrovascular, kidney, and liver disease. Timely detection of accelerated aging in addiction is crucial for the prevention of premature morbidity and mortality.
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.
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.
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
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.
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.
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.
Pankevich, Diana E.; Altevogt, Bruce M.; Dunlop, John; Gage, Fred H.; Hyman, Steve E.
Advances in the neurosciences have placed the field in the position where it is poised to significantly reduce the burden of nervous system disorders. However, drug discovery, development and translation for nervous system disorders still pose many unique challenges. The key scientific challenges can be summarized as follows: mechanisms of disease, target identification and validation, predictive models, biomarkers for patient stratification and as endpoints for clinical trials, clear regulatory pathways, reliability and reproducibility of published data, and data sharing and collaboration. To accelerate nervous system drug development the Institute of Medicine’s Forum on Neuroscience and Nervous System Disorders has hosted a series of public workshops that brought together representatives of industry, government (including both research funding and regulatory agencies), academia, and patient groups to discuss these challenges and offer potential strategies to improve the translational neuroscience. PMID:25442933
antifungal drugs against the highly protective structured popula- tion of C. albicans. We have fabricated a cellular microarray sys- tem consisting of...is a robust and effi- cient tool for accelerating the drug discovery process: (i) combinatorial screening against a collection of 28 antifungal com... against the NCI challenge set small-molecule library identified three heretofore-unknown hits. This cell-based microarray platform allows for
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.
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.
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
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.
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.
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
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.
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
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.
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.
Mitrovic, Slobodan; Cornell, Earl; Gregoire, John; Haber, Joel; Kan, Kevin; Lin, Sean; Liu, Xiaonao; Marcin, Martin; Soedarmadji, Edward; Suram, Santosh; Xiang, Chengxiang; Jin, Jian
High-Throughput Experimentation group at the Joint Center for Artificial Photosynthesis has a formidable mission: provide accelerated discovery of new photon absorbers and heterogeneous (photo)catalysts for solar fuel cells at the rate far beyond anything attempted in material science to date. The HTE pipeline includes material synthesis, screening and characterization. Within the first year of operations, our fabrication capabilities have risen to 100,000 samples per day using combinatorial inkjet-printing. Such high rate of sample production is setting daunting requirements on screening methods. We are developing and testing methods for fast bandgap measurements, using colorimetry and uv-vis spectroscopy. Material thickness and roughness is determined by confocal chromatic spectroscopy. Catalytic activity is screen through a massively parallel bubble screen and a fast scanning droplet (photo)electrochemical cell. Concurrently, we are developing protocols for high-throughput determination of phase and structure (XRD), surface composition and chemistry (XPS), surface area measurement, etc. on the characterization side of the pipeline. This work was performed at Joint Center for Artificial Photosynthesis, a DOE Energy Innovation Hub, supported through the Office of Science of the U.S. Department of Energy under Award No. DE-SC0004993
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.
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.
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.
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.
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
Low, Eric; Bountra, Chas; Lee, Wen Hwa
We are experiencing a new era enabled by unencumbered access to high quality data through the emergence of open science initiatives in the historically challenging area of early stage drug discovery. At the same time, many patient-centric organisations are taking matters into their own hands by participating in, enabling and funding research. Here we present the rationale behind the innovative partnership between the Structural Genomics Consortium (SGC)—an open, pre-competitive pre-clinical research consortium and the research-focused patient organisation Myeloma UK to create a new, comprehensive platform to accelerate the discovery and development of new treatments for multiple myeloma. PMID:27594912
Low, Eric; Bountra, Chas; Lee, Wen Hwa
We are experiencing a new era enabled by unencumbered access to high quality data through the emergence of open science initiatives in the historically challenging area of early stage drug discovery. At the same time, many patient-centric organisations are taking matters into their own hands by participating in, enabling and funding research. Here we present the rationale behind the innovative partnership between the Structural Genomics Consortium (SGC)-an open, pre-competitive pre-clinical research consortium and the research-focused patient organisation Myeloma UK to create a new, comprehensive platform to accelerate the discovery and development of new treatments for multiple myeloma.
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.
Blundell, Tom L; Sibanda, Bancinyane L; Montalvão, Rinaldo Wander; Brewerton, Suzanne; Chelliah, Vijayalakshmi; Worth, Catherine L; Harmer, Nicholas J; Davies, Owen; Burke, David
Impressive progress in genome sequencing, protein expression and high-throughput crystallography and NMR has radically transformed the opportunities to use protein three-dimensional structures to accelerate drug discovery, but the quantity and complexity of the data have ensured a central place for informatics. Structural biology and bioinformatics have assisted in lead optimization and target identification where they have well established roles; they can now contribute to lead discovery, exploiting high-throughput methods of structure determination that provide powerful approaches to screening of fragment binding. PMID:16524830
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
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
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.
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
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.
Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa
In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042
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.
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
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, 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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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
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.
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.
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.
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
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.
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.:
Leung, Elaine L; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua; Liu, Liang
Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple '-omics' databases. The newly developed algorithm- or network-based computational models can tightly integrate '-omics' databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various '-omics' platforms and computational tools would accelerate development of network-based drug discovery and network medicine.
Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua
Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768
Michelson, S; Joho, K
Drug development is a very expensive and inefficient process. Currently, it takes on average 15 years and costs approximately US $500 million to bring a new drug to market, with the pharmaceutical industry spending more than US $20 billion in identifying and developing drugs in 1998. Twenty-two percent of this total was spent on screening assays and toxicity testing. Yet the rapidly accelerating advances in high-throughput technologies, including screening and robotics, combinatorial chemistry, and genomics makes this an extremely data-rich environment. Add to that the new paradigms of pharmacogenomics and 'customized medicine', and the question is, are we helping or hurting our cause? Clearly, interpreting this flood of data and turning it into useful information is our next great hurdle. By extending the pharmacogenomic paradigm to the drug discovery process, this paper intends to put the scope of the problem into context.
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.
Milhas, Sabine; Raux, Brigitt; Betzi, Stéphane; Derviaux, Carine; Roche, Philippe; Restouin, Audrey; Basse, Marie-Jeanne; Rebuffet, Etienne; Lugari, Adrien; Badol, Marion; Kashyap, Rudra; Lissitzky, Jean-Claude; Eydoux, Cécilia; Hamon, Véronique; Gourdel, Marie-Edith; Combes, Sébastien; Zimmermann, Pascale; Aurrand-Lions, Michel; Roux, Thomas; Rogers, Catherine; Müller, Susanne; Knapp, Stefan; Trinquet, Eric; Collette, Yves; Guillemot, Jean-Claude; Morelli, Xavier
Protein-protein interactions (PPIs) represent an enormous source of opportunity for therapeutic intervention. We and others have recently pinpointed key rules that will help in identifying the next generation of innovative drugs to tackle this challenging class of targets within the next decade. We used these rules to design an oriented chemical library corresponding to a set of diverse "PPI-like" modulators with cores identified as privileged structures in therapeutics. In this work, we purchased the resulting 1664 structurally diverse compounds and evaluated them on a series of representative protein-protein interfaces with distinct "druggability" potential using homogeneous time-resolved fluorescence (HTRF) technology. For certain PPI classes, analysis of the hit rates revealed up to 100 enrichment factors compared with nonoriented chemical libraries. This observation correlates with the predicted "druggability" of the targets. A specific focus on selectivity profiles, the three-dimensional (3D) molecular modes of action resolved by X-ray crystallography, and the biological activities of identified hits targeting the well-defined "druggable" bromodomains of the bromo and extraterminal (BET) family are presented as a proof-of-concept. Overall, our present study illustrates the potency of machine learning-based oriented chemical libraries to accelerate the identification of hits targeting PPIs. A generalization of this method to a larger set of compounds will accelerate the discovery of original and potent probes for this challenging class of targets.
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.
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
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.
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.
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.
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.
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.
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.
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
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.
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
Garner, R. C.; Leong, D.
Accelerator mass spectrometry (AMS) is the most sensitive analytical method yet developed for elemental isotope analysis and has a broad range of applications. The measurement of 14C is of most interest to biomedical researchers but few studies have been reported using AMS in drug discovery and development. For biomedical use, 14C is incorporated into organic molecules by either radiosynthesis or biosynthetically and the isotope is used as a surrogate for the distribution of the radiolabelled molecule either in animal or human studies. The majority of users of 14C quantitate the radioactivity using decay counting usually with a liquid scintillation counter (LSC). Our Centre over the past 12 months has been evaluating and validating the use of AMS as an alternative detection method. In vitro spiking studies of human plasma with 14C-Fluconazole, a prescription antifungal drug has demonstrated an excellent correlation between AMS and LSC (correlation coefficient 0.999). Human Phase I clinical studies have been conducted with radioactive doses ranging from 120 Bq (7000 dpm) to 11 kBq (300 nCi) to provide mass balance, plasma concentration and radioactive metabolite profiling data. Limits of detection of 0.00022 Bq 14C-labelled drug/ml plasma have been accurately quantitated in a plasma background of 0.0078 Bq/ml (0.013 dpm/ml in a plasma background of 0.47 dpm/ml or 2.72 pMC in a background of 90.19 pMC).
Prashanth, Jutty Rajan; Lewis, Richard J; Dutertre, Sébastien
Conopeptides and conotoxins are small peptides produced by cone snails as a part of their predatory/defense strategies that target key ion channels and receptors in the nervous system. Some of these peptides also potently target mammalian ion channels involved in pain pathways. As a result, these venoms are a source of valuable pharmacological and therapeutic agents. The traditional approach towards conopeptide discovery relied on activity-guided fractionation, which is time consuming and resource-intensive. In this review, we discuss the advances in the fields of transcriptomics, proteomics and bioinformatics that now allow researchers to integrate these three platforms towards a more efficient discovery strategy. In this review, we also highlight the challenges associated with the wealth of data generated with this integrated approach and briefly discuss the impact these methods could have on the field of toxinology.
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.
Van Weeren, Reinout J.; Andrade-Santos, Felipe; Dawson, William; Golovich, Nathan; Lal, Dharam V.; Kang, Hyesung; Ryu, Dongsu; Brüggen, Marcus; Ogrean, Georgiana; Forman, William R.; Jones, Christine; Placco, Vinicius; Santucci, Rafael; Wittman, David M.; Lee, M. James; Kraft, Ralph P.; Sobral, David; Stroe, Andra; Fogarty, Kevin
In a growing number of galaxy clusters elongated Mpc-size radio sources, so-called radio relics, have been found. These relics trace relativistic electrons in the intracluster medium accelerated by collisionless shocks, generated by cluster-cluster merger events. However, cluster merger shocks typically have low Mach numbers and it is therefore unclear how these weak shocks are able to accelerate particles so efficiently, as inferred from the radio luminosity of these relics. A proposed solution to resolve this apparent discrepancy is that cluster shocks re-accelerate a population of fossil relativistic electrons, instead of thermal electrons.Here we present deep radio and Chandra X-ray observations of the merging cluster A3411-3412. This cluster is known to host a complex-shaped Mpc-size radio relic. In our new GMRT and VLA radio images of the cluster, we find a direct connection between the radio relic and a cluster radio galaxy. From the radio galaxy’s nucleus, a tail of radio emission "feeds" into the radio relic located about 90 kpc to its south. At the location of the relic, we find evidence for an X-ray surface brightness edge, consistent with the presence of a weak shock. Therefore, these observations show evidence that fossil relativistic electrons from active galactic nuclei are re-accelerated by weak cluster shocks.Our study indicates that in order to understand the non-thermal component of the intracluster medium, the presence and distribution of radio galaxies needs to be taken into account, in addition to particle acceleration at shocks. Observations at low radio frequencies, in particular with LOFAR, will be key to unveiling the connections between radio relics and radio AGN, because low-frequency observations are sensitive to synchrotron emission from older fossil radio plasma.
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.
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.
Salon, John A.; Lodowski, David T.
Crucial as molecular sensors for many vital physiological processes, seven-transmembrane domain G protein-coupled receptors (GPCRs) comprise the largest family of proteins targeted by drug discovery. Together with structures of the prototypical GPCR rhodopsin, solved structures of other liganded GPCRs promise to provide insights into the structural basis of the superfamily's biochemical functions and assist in the development of new therapeutic modalities and drugs. One of the greatest technical and theoretical challenges to elucidating and exploiting structure-function relationships in these systems is the emerging concept of GPCR conformational flexibility and its cause-effect relationship for receptor-receptor and receptor-effector interactions. Such conformational changes can be subtle and triggered by relatively small binding energy effects, leading to full or partial efficacy in the activation or inactivation of the receptor system at large. Pharmacological dogma generally dictates that these changes manifest themselves through kinetic modulation of the receptor's G protein partners. Atomic resolution information derived from increasingly available receptor structures provides an entrée to the understanding of these events and practically applying it to drug design. Supported by structure-activity relationship information arising from empirical screening, a unified structural model of GPCR activation/inactivation promises to both accelerate drug discovery in this field and improve our fundamental understanding of structure-based drug design in general. This review discusses fundamental problems that persist in drug design and GPCR structural determination. PMID:21969326
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.
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
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.
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.
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
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.
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.
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.
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
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
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.
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.
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.
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
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.
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
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.
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
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.
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.
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.
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.
Altstiel, L D
The major barrier to Alzheimer disease (AD) drug discovery and development in the biotechnology industry is scale. Most biotechnology companies do not have the personnel or expertise to carry a drug from the bench to the market. Much effort in the industry has been directed toward the elucidation of molecular mechanisms of AD and the identification of new targets. Advances in biotechnology have generated new insights into disease mechanisms, increased the number of lead compounds, and accelerated biologic screening. The majority of costs associated with drug development are in clinical testing and development activities, many of which are driven by regulatory issues. For most biotechnology companies, the costs of such trials and the infrastructure necessary to support them are prohibitive. Another significant barrier is the definition of therapeutic benefit for AD drugs; Food and Drug Administration (FDA) precedent has established that a drug must show superiority to placebo on a performance-based test of cognition and a measure of global clinical function. This restrictive definition is biased toward drugs that enhance performance on memory-based tests. Newer AD drugs are targeted toward slowing disease progression; however, there is currently no accepted definition of what constitutes efficacy in disease progression. Despite these obstacles, the biotechnology industry has much to offer AD drug discovery and development. Biotechnology firms have already developed essential technology for AD drug development and will continue to do so. Biotechnology companies can move more quickly; of course, the trick is to move quickly in the right direction. Speed may offset some of the problems associated with lack of scale. Additionally, biotechnology companies can afford to address markets that may be too restricted for larger pharmaceutical companies. This advantage will have increasing importance, as therapies are developed to address subtypes of AD.
Sims, James S.; George, William L.; Satterfield, Steven G.; Hung, Howard K.; Hagedorn, John G.; Ketcham, Peter M.; Griffin, Terence J.; Hagstrom, Stanley A.; Franiatte, Julien C.; Bryant, Garnett W.; Jaskólski, W.; Martys, Nicos S.; Bouldin, Charles E.; Simmons, Vernon; Nicolas, Oliver P.; Warren, James A.; am Ende, Barbara A.; Koontz, John E.; Filla, B. James; Pourprix, Vital G.; Copley, Stefanie R.; Bohn, Robert B.; Peskin, Adele P.; Parker, Yolanda M.; Devaney, Judith E.
This is the second in a series of articles describing a wide variety of projects at NIST that synergistically combine physical science and information science. It describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to accelerate research. The examples include scientific collaborations in the following areas: (1) High Precision Energies for few electron atomic systems, (2) Flows of suspensions, (3) X-ray absorption, (4) Molecular dynamics of fluids, (5) Nanostructures, (6) Dendritic growth in alloys, (7) Screen saver science, (8) genetic programming. PMID:27446728
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.
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. For further resources related to this article, please visit the WIREs website.
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.
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.
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
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).
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.
Papac, D I; Shahrokh, Z
This review highlights the many roles mass spectrometry plays in the discovery and development of new therapeutics by both the pharmaceutical and the biotechnology industries. Innovations in mass spectrometer source design, improvements to mass accuracy, and implementation of computer-controlled automation have accelerated the purification and characterization of compounds derived from combinatorial libraries, as well as the throughput of pharmacokinetics studies. The use of accelerator mass spectrometry, chemical reaction interface-mass spectrometry and continuous flow-isotope ratio mass spectrometry are promising alternatives for conducting mass balance studies in man. To meet the technical challenges of proteomics, discovery groups in biotechnology companies have led the way to development of instruments with greater sensitivity and mass accuracy (e.g., MALDI-TOF, ESI-Q-TOF, Ion Trap), the miniaturization of separation techniques and ion sources (e.g., capillary HPLC and nanospray), and the utilization of bioinformatics. Affinity-based methods coupled to mass spectrometry are allowing rapid and selective identification of both synthetic and biological molecules. With decreasing instrument cost and size and increasing reliability, mass spectrometers are penetrating both the manufacturing and the quality control arenas. The next generation of technologies to simplify the investigation of the complex fate of novel pharmaceutical entities in vitro and in vivo will be chip-based approaches coupled with mass spectrometry.
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.
Sims, James S; George, William L; Griffin, Terence J; Hagedorn, John G; Hung, Howard K; Kelso, John T; Olano, Marc; Peskin, Adele P; Satterfield, Steven G; Terrill, Judith Devaney; Bryant, Garnett W; Diaz, Jose G
This is the third in a series of articles that describe, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to accelerate scientific discovery. In this article we focus on the use of high performance computing and visualization for simulations of nanotechnology.
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.
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.
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
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.
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.
Ramoni, Rachel B; Mulvihill, John J; Adams, David R; Allard, Patrick; Ashley, Euan A; Bernstein, Jonathan A; Gahl, William A; Hamid, Rizwan; Loscalzo, Joseph; McCray, Alexa T; Shashi, Vandana; Tifft, Cynthia J; Wise, Anastasia L
Diagnosis at the edges of our knowledge calls upon clinicians to be data driven, cross-disciplinary, and collaborative in unprecedented ways. Exact disease recognition, an element of the concept of precision in medicine, requires new infrastructure that spans geography, institutional boundaries, and the divide between clinical care and research. The National Institutes of Health (NIH) Common Fund supports the Undiagnosed Diseases Network (UDN) as an exemplar of this model of precise diagnosis. Its goals are to forge a strategy to accelerate the diagnosis of rare or previously unrecognized diseases, to improve recommendations for clinical management, and to advance research, especially into disease mechanisms. The network will achieve these objectives by evaluating patients with undiagnosed diseases, fostering a breadth of expert collaborations, determining best practices for translating the strategy into medical centers nationwide, and sharing findings, data, specimens, and approaches with the scientific and medical communities. Building the UDN has already brought insights to human and medical geneticists. The initial focus has been on data sharing, establishing common protocols for institutional review boards and data sharing, creating protocols for referring and evaluating patients, and providing DNA sequencing, metabolomic analysis, and functional studies in model organisms. By extending this precision diagnostic model nationally, we strive to meld clinical and research objectives, improve patient outcomes, and contribute to medical science.
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
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.
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
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
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.
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
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
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.
Kellett, B.; Bingham, R.; Davies, J. A.; Bewsher, D.; Harrison, R. A.; Davis, C. J.; Eyles, C. J.; Crothers, S. R.
Comet 2P/Encke was the second comet to have its return correctly predicted (in 1819). Encke is a Jupiter-family comet with a period of 3.30 years and a perihelion distance of 0.338 AU. The interaction between cometary plasma and the solar wind plasma provides the potential for remote monitoring of the solar wind. In this regard comet Encke is potentially a very useful probe of the solar wind because of its very short orbital period and therefore large number of close approaches to the Sun. However, for this reason it is likely to have exhausted most of its reserves of ice and therefore possess a less dense plasma tail. The comet could therefore respond faster and more dynamically to solar wind variations than the tail of a more active or higher gas production comet. The Heliospheric Imager (HI) of STEREO-A (HI-1A), observed comet 2P/Encke during April, 2007. The comet was predicted to have reached perihelion on April 19th 0 UT. This paper will only consider the observations obtained by HI-1A on April 25th to 27th, 2007. At this time the comet was around 0.63 AU from Earth and 0.39 AU from the Sun. The comet was seen to exhibit a distinct "flick" of its plasma tail on April 26th and a series of "whiplash" events. However, the most interest phenomena seen was a whole series of "plasmoids" that were observed to break off from the brighter part of the tail near the nucleus and accelerate along the tail for 4-5 million kilometres down-wind of the nucleus.
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.
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.
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.
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.
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.
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.
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.
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.
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).
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
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.
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
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.
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.
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
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
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
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.
Haiech, Jacques; Ranjeva, Raoul; Kilhoffer, Marie-Claude
Life Sciences are built on observations. Right now, a more systemic approach allowing to integrate the different organizational levels in Biology is emerging. Such an approach uses a set of technologies and strategies allowing to build models that appear to be more and more predictive (omics, bioinformatics, integrative biology, computational biology…). Those models accelerate the rational development of new therapies avoiding an engineering based only on trials and errors. This approach both holistic and predictive radically modifies the discovery and development modalities used today in health industries. Moreover, because of the apparition of new jobs at the interface of disciplines, of private and public sectors and of life sciences and engineering sciences, this implies to rethink the training programs in both their contents and their pedagogical tools.
He, X-P; Xie, J; Tang, Y; Li, J; Chen, G-R
Protein tyrosine phosphatases (PTPs) are crucial regulators for numerous biological processes in nature. The dysfunction and overexpression of many PTP members have been demonstrated to cause fatal human diseases such as cancers, diabetes, obesity, neurodegenerative diseases and autoimmune disorders. In the past decade, considerable efforts have been devoted to the production of PTPs inhibitors by both academia and the pharmaceutical industry. However, there are only limited drug candidates in clinical trials and no commercial drugs have been approved, implying that further efficient discovery of novel chemical entities competent for inhibition of the specific PTP target in vivo remains yet a challenge. In light of the click-chemistry paradigm which advocates the utilization of concise and selective carbon-heteroatom ligation reactions for the modular construction of useful compound libraries, the Cu(I)-catalyzed azidealkyne 1,3-dipolar cycloaddition reaction (CuAAC) has fueled enormous energy into the modern drug discovery. Recently, this ingenious chemical ligation tool has also revealed efficacious and expeditious in establishing large combinatorial libraries for the acquisition of novel PTPs inhibitors with promising pharmacological profiles. We thus offer here a comprehensive review highlighting the development of PTPs inhibitors accelerated by the CuAAC click chemistry.
Peltier, John M.; Askovic, Srdjan; Becklin, Robert R.; Chepanoske, Cindy Lou; Ho, Yew-Seng J.; Kery, Vladimir; Lai, Shuping; Mujtaba, Tahmina; Pyne, Mike; Robbins, Paul B.; Rechenberg, Moritz Von; Richardson, Bonnie; Savage, Justin; Sheffield, Peter; Thompson, Sam; Weir, Lawrence; Widjaja, Kartika; Xu, Nafei; Zhen, Yuejun; Boniface, J. Jay
Proteomics-based technologies have the potential to accelerate the development of drugs, but such technologies must be well integrated in order to have a positive impact. We describe, herein, a multi-step process for the discovery of protein-protein interactions. It is shown that process stages are interdependent and can influence, either positively or negatively, subsequent steps. Optimization of each step, in the context of the full process, is essential for the overall success of the experiment.
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.
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.
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.
Van Voorhis, Wesley C; Adams, John H; Adelfio, Roberto; Ahyong, Vida; Akabas, Myles H; Alano, Pietro; Alday, Aintzane; Alemán Resto, Yesmalie; Alsibaee, Aishah; Alzualde, Ainhoa; Andrews, Katherine T; Avery, Simon V; Avery, Vicky M; Ayong, Lawrence; Baker, Mark; Baker, Stephen; Ben Mamoun, Choukri; Bhatia, Sangeeta; Bickle, Quentin; Bounaadja, Lotfi; Bowling, Tana; Bosch, Jürgen; Boucher, Lauren E; Boyom, Fabrice F; Brea, Jose; Brennan, Marian; Burton, Audrey; Caffrey, Conor R; Camarda, Grazia; Carrasquilla, Manuela; Carter, Dee; Belen Cassera, Maria; Chih-Chien Cheng, Ken; Chindaudomsate, Worathad; Chubb, Anthony; Colon, Beatrice L; Colón-López, Daisy D; Corbett, Yolanda; Crowther, Gregory J; Cowan, Noemi; D'Alessandro, Sarah; Le Dang, Na; Delves, Michael; DeRisi, Joseph L; Du, Alan Y; Duffy, Sandra; Abd El-Salam El-Sayed, Shimaa; Ferdig, Michael T; Fernández Robledo, José A; Fidock, David A; Florent, Isabelle; Fokou, Patrick V T; Galstian, Ani; Gamo, Francisco Javier; Gokool, Suzanne; Gold, Ben; Golub, Todd; Goldgof, Gregory M; Guha, Rajarshi; Guiguemde, W Armand; Gural, Nil; Guy, R Kiplin; Hansen, Michael A E; Hanson, Kirsten K; Hemphill, Andrew; Hooft van Huijsduijnen, Rob; Horii, Takaaki; Horrocks, Paul; Hughes, Tyler B; Huston, Christopher; Igarashi, Ikuo; Ingram-Sieber, Katrin; Itoe, Maurice A; Jadhav, Ajit; Naranuntarat Jensen, Amornrat; Jensen, Laran T; Jiang, Rays H Y; Kaiser, Annette; Keiser, Jennifer; Ketas, Thomas; Kicka, Sebastien; Kim, Sunyoung; Kirk, Kiaran; Kumar, Vidya P; Kyle, Dennis E; Lafuente, Maria Jose; Landfear, Scott; Lee, Nathan; Lee, Sukjun; Lehane, Adele M; Li, Fengwu; Little, David; Liu, Liqiong; Llinás, Manuel; Loza, Maria I; Lubar, Aristea; Lucantoni, Leonardo; Lucet, Isabelle; Maes, Louis; Mancama, Dalu; Mansour, Nuha R; March, Sandra; McGowan, Sheena; Medina Vera, Iset; Meister, Stephan; Mercer, Luke; Mestres, Jordi; Mfopa, Alvine N; Misra, Raj N; Moon, Seunghyun; Moore, John P; Morais Rodrigues da Costa, Francielly; Müller, Joachim; Muriana, Arantza; Nakazawa Hewitt, Stephen; Nare, Bakela; Nathan, Carl; Narraidoo, Nathalie; Nawaratna, Sujeevi; Ojo, Kayode K; Ortiz, Diana; Panic, Gordana; Papadatos, George; Parapini, Silvia; Patra, Kailash; Pham, Ngoc; Prats, Sarah; Plouffe, David M; Poulsen, Sally-Ann; Pradhan, Anupam; Quevedo, Celia; Quinn, Ronald J; Rice, Christopher A; Abdo Rizk, Mohamed; Ruecker, Andrea; St Onge, Robert; Salgado Ferreira, Rafaela; Samra, Jasmeet; Robinett, Natalie G; Schlecht, Ulrich; Schmitt, Marjorie; Silva Villela, Filipe; Silvestrini, Francesco; Sinden, Robert; Smith, Dennis A; Soldati, Thierry; Spitzmüller, Andreas; Stamm, Serge Maximilian; Sullivan, David J; Sullivan, William; Suresh, Sundari; Suzuki, Brian M; Suzuki, Yo; Swamidass, S Joshua; Taramelli, Donatella; Tchokouaha, Lauve R Y; Theron, Anjo; Thomas, David; Tonissen, Kathryn F; Townson, Simon; Tripathi, Abhai K; Trofimov, Valentin; Udenze, Kenneth O; Ullah, Imran; Vallieres, Cindy; Vigil, Edgar; Vinetz, Joseph M; Voong Vinh, Phat; Vu, Hoan; Watanabe, Nao-Aki; Weatherby, Kate; White, Pamela M; Wilks, Andrew F; Winzeler, Elizabeth A; Wojcik, Edward; Wree, Melanie; Wu, Wesley; Yokoyama, Naoaki; Zollo, Paul H A; Abla, Nada; Blasco, Benjamin; Burrows, Jeremy; Laleu, Benoît; Leroy, Didier; Spangenberg, Thomas; Wells, Timothy; Willis, Paul A
A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal
Van Voorhis, Wesley C.; Adams, John H.; Adelfio, Roberto; Ahyong, Vida; Akabas, Myles H.; Alano, Pietro; Alday, Aintzane; Alemán Resto, Yesmalie; Alsibaee, Aishah; Alzualde, Ainhoa; Andrews, Katherine T.; Avery, Simon V.; Avery, Vicky M.; Ayong, Lawrence; Baker, Mark; Baker, Stephen; Ben Mamoun, Choukri; Bhatia, Sangeeta; Bickle, Quentin; Bounaadja, Lotfi; Bowling, Tana; Bosch, Jürgen; Boucher, Lauren E.; Boyom, Fabrice F.; Brea, Jose; Brennan, Marian; Burton, Audrey; Caffrey, Conor R.; Camarda, Grazia; Carrasquilla, Manuela; Carter, Dee; Belen Cassera, Maria; Chih-Chien Cheng, Ken; Chindaudomsate, Worathad; Chubb, Anthony; Colon, Beatrice L.; Colón-López, Daisy D.; Corbett, Yolanda; Crowther, Gregory J.; Cowan, Noemi; D’Alessandro, Sarah; Le Dang, Na; Delves, Michael; Du, Alan Y.; Duffy, Sandra; Abd El-Salam El-Sayed, Shimaa; Ferdig, Michael T.; Fernández Robledo, José A.; Fidock, David A.; Florent, Isabelle; Fokou, Patrick V. T.; Galstian, Ani; Gamo, Francisco Javier; Gold, Ben; Golub, Todd; Goldgof, Gregory M.; Guha, Rajarshi; Guiguemde, W. Armand; Gural, Nil; Guy, R. Kiplin; Hansen, Michael A. E.; Hanson, Kirsten K.; Hemphill, Andrew; Hooft van Huijsduijnen, Rob; Horii, Takaaki; Horrocks, Paul; Hughes, Tyler B.; Huston, Christopher; Igarashi, Ikuo; Ingram-Sieber, Katrin; Itoe, Maurice A.; Jadhav, Ajit; Naranuntarat Jensen, Amornrat; Jensen, Laran T.; Jiang, Rays H. Y.; Kaiser, Annette; Keiser, Jennifer; Ketas, Thomas; Kicka, Sebastien; Kim, Sunyoung; Kirk, Kiaran; Kumar, Vidya P.; Kyle, Dennis E.; Lafuente, Maria Jose; Landfear, Scott; Lee, Nathan; Lee, Sukjun; Lehane, Adele M.; Li, Fengwu; Little, David; Liu, Liqiong; Llinás, Manuel; Loza, Maria I.; Lubar, Aristea; Lucantoni, Leonardo; Lucet, Isabelle; Maes, Louis; Mancama, Dalu; Mansour, Nuha R.; March, Sandra; McGowan, Sheena; Medina Vera, Iset; Meister, Stephan; Mercer, Luke; Mestres, Jordi; Mfopa, Alvine N.; Misra, Raj N.; Moon, Seunghyun; Moore, John P.; Morais Rodrigues da Costa, Francielly; Müller, Joachim; Muriana, Arantza; Nakazawa Hewitt, Stephen; Nare, Bakela; Nathan, Carl; Narraidoo, Nathalie; Nawaratna, Sujeevi; Ojo, Kayode K.; Ortiz, Diana; Panic, Gordana; Papadatos, George; Parapini, Silvia; Patra, Kailash; Pham, Ngoc; Prats, Sarah; Plouffe, David M.; Poulsen, Sally-Ann; Pradhan, Anupam; Quevedo, Celia; Quinn, Ronald J.; Rice, Christopher A.; Abdo Rizk, Mohamed; Ruecker, Andrea; St. Onge, Robert; Salgado Ferreira, Rafaela; Samra, Jasmeet; Robinett, Natalie G.; Schlecht, Ulrich; Schmitt, Marjorie; Silva Villela, Filipe; Silvestrini, Francesco; Sinden, Robert; Smith, Dennis A.; Soldati, Thierry; Spitzmüller, Andreas; Stamm, Serge Maximilian; Sullivan, David J.; Sullivan, William; Suresh, Sundari; Suzuki, Brian M.; Suzuki, Yo; Swamidass, S. Joshua; Taramelli, Donatella; Tchokouaha, Lauve R. Y.; Theron, Anjo; Thomas, David; Tonissen, Kathryn F.; Townson, Simon; Tripathi, Abhai K.; Trofimov, Valentin; Udenze, Kenneth O.; Ullah, Imran; Vallieres, Cindy; Vigil, Edgar; Vinetz, Joseph M.; Voong Vinh, Phat; Vu, Hoan; Watanabe, Nao-aki; Weatherby, Kate; White, Pamela M.; Wilks, Andrew F.; Winzeler, Elizabeth A.; Wojcik, Edward; Wree, Melanie; Wu, Wesley; Yokoyama, Naoaki; Zollo, Paul H. A.; Abla, Nada; Blasco, Benjamin; Burrows, Jeremy; Laleu, Benoît; Leroy, Didier; Spangenberg, Thomas; Wells, Timothy; Willis, Paul A.
A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal
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
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.
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.
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.
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.
Eglen, Richard; Reisine, Terry
Many drug discovery screening programs employ immortalized cells, recombinantly engineered to express a defined molecular target. Several technologies are now emerging that render it feasible to employ more physiologically, and clinically relevant, cell phenotypes. Consequently, numerous approaches use primary cells, which retain many functions seen in vivo, as well as endogenously expressing the target of interest. Furthermore, stem cells, of either embryonic or adult origin, as well as those derived from differentiated cells, are now finding a place in drug discovery. Collectively, these cells are expanding the utility of authentic human cells, either as screening tools or as therapeutics, as well as providing cells derived directly from patients. Nonetheless, the growing use of phenotypically relevant cells (including primary cells or stem cells) is not without technical difficulties, particularly when their envisioned use lies in high-throughput screening (HTS) protocols. In particular, the limited availability of homogeneous primary or stem cell populations for HTS mandates that novel technologies be developed to accelerate their adoption. These technologies include detection of responses with very few cells as well as protocols to generate cell lines in abundant, homogeneous populations. In parallel, the growing use of changes in cell phenotype as the assay readout is driving greater use of high-throughput imaging techniques in screening. Taken together, the greater availability of novel primary and stem cell phenotypes as well as new detection technologies is heralding a new era of cellular screening. This convergence offers unique opportunities to identify drug candidates for disorders at which few therapeutics are presently available.
Płocińska, Renata; Korycka-Machała, Małgorzata; Płociński, Przemysław; Dziadek, Jarosław
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, two-component 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
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…
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
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.
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.
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.
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
Hopkinson, Matthew N; Gómez-Suárez, Adrián; Teders, Michael; Sahoo, Basudev; Glorius, Frank
Herein, we report a conceptually novel mechanism-based screening approach to accelerate discovery in photocatalysis. In contrast to most screening methods, which consider reactions as discrete entities, this approach instead focuses on a single constituent mechanistic step of a catalytic reaction. Using luminescence spectroscopy to investigate the key quenching step in photocatalytic reactions, an initial screen of 100 compounds led to the discovery of two promising substrate classes. Moreover, a second, more focused screen provided mechanistic insights useful in developing proof-of-concept reactions. Overall, this fast and straightforward approach both facilitated the discovery and aided the development of new light-promoted reactions and suggests that mechanism-based screening strategies could become useful tools in the hunt for new reactivity.
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
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
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.
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.
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.
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.
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.
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
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.
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.
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.
Davies, E Keith; Richards, W Graham
Large-scale, high precision drug discovery calculations, such as predicting protein folding or small-molecule protein inhibitors, have frustrated computational chemists because the supercomputers currently available are insufficiently powerful. The increasing power of PCs offers an alternative approach by harnessing 'idle time' from corporate and home computers that are connected to the Internet or an intranet. However, although the approach has the potential of offering hundreds or thousands of years of computer time per elapsed day, the architecture constraints require computational chemists to choose their methods and applications with care. Some algorithms, such as those for molecular simulations, are generally not appropriate, whereas virtual screening of molecules for protein inhibition works well.
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.
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.
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
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.
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
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.
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
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. PMID:26958234
The biopharmaceutics classification system (BCS) and biopharmaceutics drug distribution classification system (BDDCS) are complementary classification systems that can improve, simplify, and accelerate drug discovery, development, and regulatory processes. Drug permeability has been widely accepted as a screening tool for determining intestinal absorption via the BCS during the drug development and regulatory approval processes. Currently, predicting clinically significant drug interactions during drug development is a known challenge for industry and regulatory agencies. The BDDCS, a modification of BCS that utilizes drug metabolism instead of intestinal permeability, predicts drug disposition and potential drug–drug interactions in the intestine, the liver, and most recently the brain. Although correlations between BCS and BDDCS have been observed with drug permeability rates, discrepancies have been noted in drug classifications between the two systems utilizing different permeability models, which are accepted as surrogate models for demonstrating human intestinal permeability by the FDA. Here, we recommend the most applicable permeability models for improving the prediction of BCS and BDDCS classifications. We demonstrate that the passive transcellular permeability rate, characterized by means of permeability models that are deficient in transporter expression and paracellular junctions (e.g., PAMPA and Caco-2), will most accurately predict BDDCS metabolism. These systems will inaccurately predict BCS classifications for drugs that particularly are substrates of highly expressed intestinal transporters. Moreover, in this latter case, a system more representative of complete human intestinal permeability is needed to accurately predict BCS absorption. PMID:24628254
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.
Chellan, Prinessa; Sadler, Peter J; Land, Kirkwood M
Apicomplexan parasites cause some of the most devastating human diseases, including malaria, toxoplasmosis, and cryptosporidiosis. New drug discovery is imperative in light of increased resistance. In this digest article, we briefly explore some of the recent and promising developments in new drug discovery against two apicomplexan parasites, Cryptosporidium and Toxoplasma.
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
Kelloff, Gary J; Sigman, Caroline C
Although several new oncology drugs have reached the market, more than 80% of drugs for all indications entering clinical development do not get marketing approval, with many failing late in development often in Phase III trials, because of unexpected safety issues or difficulty determining efficacy, including confounded outcomes. These factors contribute to the high costs of oncology drug development and clearly show the need for faster, more cost-effective strategies for evaluating oncology drugs and better definition of patients who will benefit from treatment. Remarkable advances in the understanding of neoplastic progression at the cellular and molecular levels have spurred the discovery of molecularly targeted drugs. This progress along with advances in imaging and bioassay technologies are the basis for describing and evaluating new biomarker endpoints as well as for defining other biomarkers for identifying patient populations, potential toxicity, and providing evidence of drug effect and efficacy. Definitions and classifications of these biomarkers for use in oncology drug development are presented in this paper. Science-based and practical criteria for validating biomarkers have been developed including considerations of mechanistic plausibility, available methods and technology, and clinical feasibility. New promising tools for measuring biomarkers have also been developed and are based on genomics and proteomics, direct visualisation by microscopy (e.g., confocal microscopy and computer-assisted image analysis of cellular features), nanotechnologies, and direct and remote imaging (e.g., fluorescence endoscopy and anatomical, functional and molecular imaging techniques). The identification and evaluation of potential surrogate endpoints and other biomarkers require access to and analysis of large amounts of data, new technologies and extensive research resources. Further, there is a requirement for a convergence of research, regulatory and drug developer
Kong, De-Xin; Li, Xue-Juan; Zhang, Hong-Yu
For drug discovery, historical experience is always of significance. Through examining the history of traditional medicines, we find that these medicines have more implications for drug discovery than just providing new chemical entities. The history of traditional medicines indicates that they depended more on the combination of natural agents than on screening new agents to find new remedies. This phenomenon suggests that shifting the current drug discovery paradigm from 'finding new-entity drugs' to 'combining existing agents' may be helpful for overcoming the 'more investment, fewer drugs' challenge. We show that clues to finding antidementia combinatorial drugs can be derived from traditional medicine formulae. It seems that to create a brighter future of drug discovery, we would better go back to history.
Cabrera-Pardo, Jaime R.; Chai, David I.; Liu, Song; Mrksich, Milan; Kozmin, Sergey A.
Identification of new reactions expands our knowledge of chemical reactivity and enables new synthetic applications. Accelerating the pace of this discovery process remains challenging. We describe a highly effective and simple platform for screening a large number of potential chemical reactions in order to discover and optimize previously unknown catalytic transformations thereby revealing new chemical reactivity. Our strategy is based on labeling one of the reactants with a polyaromatic chemical tag, which selectively undergoes photoionization-desorption process upon laser irradiation without the assistance of an external matrix and enables rapid mass spectrometric detection of any products originating from such labeled reactants in complex reaction mixtures without any chromatographic separation. This method was successfully employed for high-throughput discovery and subsequent optimization of two previously unknown benzannulation reactions. PMID:23609094
De novo experimental drug discovery is an expensive and time-consuming task. It requires the identification of drug-target interactions (DTIs) towards targets of biological interest, either to inhibit or enhance a specific molecular function. Dedicated computational models for protein simulation and DTI prediction are crucial for speed and to reduce the costs associated with DTI identification. In this paper we present a computational pipeline that enables the discovery of putative leads for drug repositioning that can be applied to any microbial proteome, as long as the interactome of interest is at least partially known. Network metrics calculated for the interactome of the bacterial organism of interest were used to identify putative drug-targets. Then, a random forest classification model for DTI prediction was constructed using known DTI data from publicly available databases, resulting in an area under the ROC curve of 0.91 for classification of out-of-sampling data. A drug-target network was created by combining 3,081 unique ligands and the expected ten best drug targets. This network was used to predict new DTIs and to calculate the probability of the positive class, allowing the scoring of the predicted instances. Molecular docking experiments were performed on the best scoring DTI pairs and the results were compared with those of the same ligands with their original targets. The results obtained suggest that the proposed pipeline can be used in the identification of new leads for drug repositioning. The proposed classification model is available at http://bioinformatics.ua.pt/software/dtipred/. PMID:27893735
Dunlop, John; Brandon, Nicholas J
Current therapeutics for schizophrenia, the typical and atypical antipsychotic class of drugs, derive their therapeutic benefit predominantly by antagonism of the dopamine D2 receptor subtype and have robust clinical benefit on positive symptoms of the disease with limited to no impact on negative symptoms and cognitive impairment. Driven by these therapeutic limitations of current treatments and the recognition that transmitter systems beyond the dopaminergic system in particular glutamatergic transmission contribute to the etiology of schizophrenia significant recent efforts have focused on the discovery and development of novel treatments for schizophrenia with mechanisms of action that are distinct from current drugs. Specifically, compounds selectively targeting the metabotropic glutamate receptor 2/3 subtype, phosphodiesterase subtype 10, glycine transporter subtype 1 and the alpha7 nicotinic acetylcholine receptor have been the subject of intense drug discovery and development efforts. Here we review recent clinical experience with the most advanced drug candidates targeting each of these novel mechanisms and discuss whether these new agents are living up to expectations.
Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way.
Alavijeh, Mohammad S.; Chishty, Mansoor; Qaiser, M. Zeeshan; Palmer, Alan M.
Summary: The worldwide market for therapies for CNS disorders is worth more than $50 billion and is set to grow substantially in the years ahead. This is because: 1) the incidence of many CNS disorders (e.g., Alzheimer’s disease, stroke, and Parkinson’s disease) increase exponentially after age 65 and 2) the number of people in the world over 65 is about to increase sharply because of a marked rise in fertility after World War II. However, CNS research and development are associated with significant challenges: it takes longer to get a CNS drug to market (12–16 years) compared with a non-CNS drug (10–12 years) and there is a higher attrition rate for CNS drug candidates than for non-CNS drug candidates. This is attributable to a variety of factors, including the complexity of the brain, the liability of CNS drugs to cause CNS side effects, and the requirement of CNS drugs to cross the blood-brain barrier (BBB). This review focuses on BBB penetration, along with pharmacokinetics and drug metabolism, in the process of the discovery and development of safe and effective medicines for CNS disorders. PMID:16489365
The aim of this study was to make a scientometric assessment of drug discovery efforts centered on pain-related molecular targets. The following scientometric indices were used: the popularity index, representing the share of articles (or patents) on a specific topic among all articles (or patents) on pain over the same 5-year period; the index of change, representing the change in the number of articles (or patents) on a topic from one 5-year period to the next; the index of expectations, representing the ratio of the number of all types of articles on a topic in the top 20 journals relative to the number of articles in all (>5,000) biomedical journals covered by PubMed over a 5-year period; the total number of articles representing Phase I-III trials of investigational drugs over a 5-year period; and the trial balance index, a ratio of Phase I-II publications to Phase III publications. Articles (PubMed database) and patents (US Patent and Trademark Office database) on 17 topics related to pain mechanisms were assessed during six 5-year periods from 1984 to 2013. During the most recent 5-year period (2009-2013), seven of 17 topics have demonstrated high research activity (purinergic receptors, serotonin, transient receptor potential channels, cytokines, gamma aminobutyric acid, glutamate, and protein kinases). However, even with these seven topics, the index of expectations decreased or did not change compared with the 2004-2008 period. In addition, publications representing Phase I-III trials of investigational drugs (2009-2013) did not indicate great enthusiasm on the part of the pharmaceutical industry regarding drugs specifically designed for treatment of pain. A promising development related to the new tool of molecular targeting, ie, monoclonal antibodies, for pain treatment has not yet resulted in real success. This approach has not yet demonstrated clinical effectiveness (at least with nerve growth factor) much beyond conventional analgesics, when its
The aim of this study was to make a scientometric assessment of drug discovery efforts centered on pain-related molecular targets. The following scientometric indices were used: the popularity index, representing the share of articles (or patents) on a specific topic among all articles (or patents) on pain over the same 5-year period; the index of change, representing the change in the number of articles (or patents) on a topic from one 5-year period to the next; the index of expectations, representing the ratio of the number of all types of articles on a topic in the top 20 journals relative to the number of articles in all (>5,000) biomedical journals covered by PubMed over a 5-year period; the total number of articles representing Phase I–III trials of investigational drugs over a 5-year period; and the trial balance index, a ratio of Phase I–II publications to Phase III publications. Articles (PubMed database) and patents (US Patent and Trademark Office database) on 17 topics related to pain mechanisms were assessed during six 5-year periods from 1984 to 2013. During the most recent 5-year period (2009–2013), seven of 17 topics have demonstrated high research activity (purinergic receptors, serotonin, transient receptor potential channels, cytokines, gamma aminobutyric acid, glutamate, and protein kinases). However, even with these seven topics, the index of expectations decreased or did not change compared with the 2004–2008 period. In addition, publications representing Phase I–III trials of investigational drugs (2009–2013) did not indicate great enthusiasm on the part of the pharmaceutical industry regarding drugs specifically designed for treatment of pain. A promising development related to the new tool of molecular targeting, ie, monoclonal antibodies, for pain treatment has not yet resulted in real success. This approach has not yet demonstrated clinical effectiveness (at least with nerve growth factor) much beyond conventional analgesics
Zingales, Bianca; Miles, Michael A; Moraes, Carolina B; Luquetti, Alejandro; Guhl, Felipe; Schijman, Alejandro G; Ribeiro, Isabela
This opinion piece presents an approach to standardisation of an important aspect of Chagas disease drug discovery and development: selecting Trypanosoma cruzi strains for in vitro screening. We discuss the rationale for strain selection representing T. cruzi diversity and provide recommendations on the preferred parasite stage for drug discovery, T. cruzi discrete typing units to include in the panel of strains and the number of strains/clones for primary screens and lead compounds. We also consider experimental approaches for in vitro drug assays. The Figure illustrates the current Chagas disease drug-discovery and development landscape. PMID:25317712
Zingales, Bianca; Miles, Michael A; Moraes, Carolina B; Luquetti, Alejandro; Guhl, Felipe; Schijman, Alejandro G; Ribeiro, Isabela
This opinion piece presents an approach to standardisation of an important aspect of Chagas disease drug discovery and development: selecting Trypanosoma cruzi strains for in vitro screening. We discuss the rationale for strain selection representing T. cruzi diversity and provide recommendations on the preferred parasite stage for drug discovery, T. cruzi discrete typing units to include in the panel of strains and the number of strains/clones for primary screens and lead compounds. We also consider experimental approaches for in vitro drug assays. The Figure illustrates the current Chagas disease drug-discovery and development landscape.
Gao, Qingzhi; Yang, Lulu; Zhu, Yongqiang
This review summarizes the background and updated progress of pharmacophore based drug design and provides the fundamental approach strategies on both structure based and ligand based pharmacophore approaches. The different programs and methodologies enable the implementation of more accurate and sophisticated pharmacophore model generation and application in drug discovery. This review will discuss and illustrate their advantages in pharmacophore based virtual screening and exemplify the detailed application workflow, which can be easily utilized by pharmaceutical bench work medicinal chemists. Pharmacophore based drug design process includes pharmacophore modeling and validation; pharmacophore based virtual screening, virtual hits profiling and lead identification. Strategies and proven methodologies for pharmacophore modeling are described including common feature and 3D QSAR based pharmacophore generation as well as structure based pharmacophore development. Different virtual screening strategies will be described in this review with detailed case studies for supporting practical applications. Representative success examples of pharmacophore based virtual screening for lead generation will be collected to demonstrate capabilities.
Kumari, Shraddha; Kumar, Awanish; Samant, Mukesh; Singh, Neeloo; Dube, Anuradha
Among the three clinical forms (cutaneous, mucosal and visceral) of leishmaniasis visceral (VL) one is the most devastating type caused by the invasion of the reticuloendothelial system of human by Leishmania donovani, L. infantum and L. chagasi. India and Sudan account for about half the world's burden of VL. Current control strategy is based on chemotherapy, which is difficult to administer, expensive and becoming ineffective due to the emergence of drug resistance. An understanding of resistance mechanism(s) operating in clinical isolates might provide additional leads for the development of new drugs. Further, due to the lack of fully effective treatment the search for novel immune targets is also needed. So far, no vaccine exists for VL despite indications of naturally developing immunity. Therefore, an urgent need for new and effective leishmanicidal agents and for this identification of novel drug and vaccine targets is imperative. The availability of the complete genome sequence of Leishmania has revolutionised many areas of leishmanial research and facilitated functional genomic studies as well as provided a wide range of novel targets for drug designing. Most notably, proteomics and transcriptomics have become important tools in gaining increased understanding of the biology of Leishmania to be explored on a global scale, thus accelerating the pace of discovery of vaccine/drug targets. In addition, these approaches provide the information regarding genes and proteins that are expressed and under which conditions. This review provides a comprehensive view about those proteins/genes identified using proteomics and transcriptomic tools for the development of vaccine/drug against VL.
Buckner, Frederick S
In the 100 years since the discovery of Chagas disease, only two drugs have been developed and introduced into clinical practice, and these drugs were introduced over 40 years ago. The tools of drug discovery have improved dramatically in the interim; however, this has not translated into new drugs for Chagas disease. This has been largely because the main practitioners of drug discovery are pharmaceutical companies who are not financially motivated to invest in Chagas disease and other "orphan" diseases. As a result, it has largely been up to academic groups to bring drug candidates through the discovery pipeline and to clinical trials. The difficulty with drug discovery in academia has been the challenge of bringing together the diverse expertise in biology, chemistry, and pharmacology in concerted efforts towards a common goal of developing therapeutics. Funding is often inadequate, but lack of coordination amongst academic investigators with different expertise has also contributed to the slow progress. The purpose of this chapter is to provide an overview of approaches that can be accomplished in academic settings for preclinical drug discovery for Chagas disease. The chapter addresses methods of drug screening against Trypanosoma cruzi cultures and in animal models and includes general topics on compound selection, testing for drug-like properties (including oral bioavailability), investigating the pharmacokinetics and toxicity of compounds, and finally providing parameters to help with triaging compounds.
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.
Following the success of small-molecule high-throughput screening (HTS) in drug discovery, other large-scale screening techniques are currently revolutionizing the biological sciences. Powerful new statistical tools have been developed to analyze the vast amounts of data in DNA chip studies, but have not yet found their way into compound screening. In HTS, characterization of single-point hit lists is often done only in retrospect after the results of confirmation experiments are available. However, for prioritization, for optimal use of resources, for quality control, and for comparison of screens it would be extremely valuable to predict the rates of false positives and false negatives directly from the primary screening results. Making full use of the available information about compounds and controls contained in HTS results and replicated pilot runs, the Z score and from it the p value can be estimated for each measurement. Based on this consideration, we have applied the concept of p-value distribution analysis (PVDA), which was originally developed for gene expression studies, to HTS data. PVDA allowed prediction of all relevant error rates as well as the rate of true inactives, and excellent agreement with confirmation experiments was found.
Avci, Pinar; Sadasivam, Magesh; Gupta, Asheesh; De Melo, Wanessa CMA; Huang, Ying-Ying; Yin, Rui; Rakkiyappan, Chandran; Kumar, Raj; Otufowora, Ayodeji; Nyame, Theodore; Hamblin, Michael R
Introduction Discovery of novel drugs, treatments, and testing of consumer products in the field of dermatology is a multi-billion dollar business. Due to the distressing nature of many dermatological diseases, and the enormous consumer demand for products to reverse the effects of skin photodamage, aging, and hair loss, this is a very active field. Areas covered In this paper, we will cover the use of animal models that have been reported to recapitulate to a greater or lesser extent the features of human dermatological disease. There has been a remarkable increase in the number and variety of transgenic mouse models in recent years, and the basic strategy for constructing them is outlined. Expert opinion Inflammatory and autoimmune skin diseases are all represented by a range of mouse models both transgenic and normal. Skin cancer is mainly studied in mice and fish. Wound healing is studied in a wider range of animal species, and skin infections such as acne and leprosy also have been studied in animal models. Moving to the more consumer-oriented area of dermatology, there are models for studying the harmful effect of sunlight on the skin, and testing of sunscreens, and several different animal models of hair loss or alopecia. PMID:23293893
Chautard, E; Thierry-Mieg, N; Ricard-Blum, S
Most genes, proteins and other components carry out their functions within a complex network of interactions and a single molecule can affect a wide range of other cell components. A global, integrative, approach has been developed for several years, including protein-protein interaction networks (interactomes). In this review, we describe the high-throughput methods used to identify new interactions and to build large interaction datasets. The minimum information required for reporting a molecular interaction experiment (MIMIx) has been defined as a standard for storing data in publicly available interaction databases. Several examples of interaction networks from molecular machines (proteasome) or organelles (phagosome, mitochondrion) to whole organisms (viruses, bacteria, yeast, fly, and worm) are given and attempts to cover the entire human interaction network are discussed. The methods used to perform the topological analysis of interaction networks and to extract biological information from them are presented. These investigations have provided clues on protein functions, signalling and metabolic pathways, and physiological processes, unraveled the molecular basis of some diseases (cancer, infectious diseases), and will be very useful to identify new therapeutic targets and for drug discovery. A major challenge is now to integrate data from different sources (interactome, transcriptome, phenome, localization) to switch from static to dynamic interaction networks. The merging of a viral interactome and the human interactome has been used to simulate viral infection, paving the way for future studies aiming at providing molecular basis of human diseases.
Geldenhuys, Werner J; Gaasch, Kevin E; Watson, Mark; Allen, David D; Van der Schyf, Cornelis J
Drug discovery is a time consuming and costly process. Recently, a trend towards the use of in silico computational chemistry and molecular modeling for computer-aided drug design has gained significant momentum. This review investigates the application of free and/or open-source software in the drug discovery process. Among the reviewed software programs are applications programmed in JAVA, Perl and Python, as well as resources including software libraries. These programs might be useful for cheminformatics approaches to drug discovery, including QSAR studies, energy minimization and docking studies in drug design endeavors. Furthermore, this review explores options for integrating available computer modeling open-source software applications in drug discovery programs.
Martin, Eric S.; Belmont, Peter J.; Sinnamon, Mark J.; Richard, Larissa Georgeon; Yuan, Jing; Coffee, Erin M.; Roper, Jatin; Lee, Lydia; Heidari, Pedram; Lunt, Sophia Y.; Goel, Gautam; Ji, Christy; Xie, Julie; Xie, Tao; Lamb, John; Weinrich, Scott; VanArsdale, Todd; Bronson, Roderick T.; Xavier, Ramnik J.; Vander Heiden, Matthew G.; Kan, Julie L. C.; Mahmood, Umar; Hung, Kenneth E.
Purpose Effective therapies for KRAS mutant colorectal cancer (CRC) are a critical unmet clinical need. Previously, we described GEMMs for sporadic Kras mutant and non-mutant CRC suitable for preclinical evaluation of experimental therapeutics. To accelerate drug discovery and validation, we sought to derive low-passage cell lines from GEMM Kras mutant and wild-type tumors for in vitro screening and transplantation into the native colonic environment of immunocompetent mice for in vivo validation. Experimental Design Cell lines were derived from Kras mutant and non-mutant GEMM tumors under defined media conditions. Growth kinetics, phosphoproteomes, transcriptomes, drug sensitivity, and metabolism were examined. Cell lines were implanted in mice and monitored for in vivo tumor analysis. Results Kras mutant cell lines displayed increased proliferation, MAPK signaling, and PI3K signaling. Microarray analysis identified significant overlap with human CRC-related gene signatures, including KRAS mutant and metastatic CRC. Further analyses revealed enrichment for numerous disease-relevant biological pathways, including glucose metabolism. Functional assessment in vitro and in vivo validated this finding and highlighted the dependence of Kras mutant CRC on oncogenic signaling and on aerobic glycolysis. Conclusions We have successfully characterized a novel GEMM-derived orthotopic transplant model of human KRAS mutant CRC. This approach combines in vitro screening capability using low-passage cell lines that recapitulate human CRC and potential for rapid in vivo validation using cell line-derived tumors that develop in the colonic microenvironment of immunocompetent animals. Taken together, this platform is a clear advancement in preclinical CRC models for comprehensive drug discovery and validation efforts. PMID:23403635
Patel, Gautam; Karver, Caitlin E.; Behera, Ranjan; Guyett, Paul; Sullenberger, Catherine; Edwards, Peter; Roncal, Norma E.; Mensa-Wilmot, Kojo; Pollastri, Michael P.
Human African trypanosomiasis (HAT) is a neglected tropical disease caused by the protozoan parasite Trypanosoma brucei. Since drugs in use against HAT are toxic and require intravenous dosing, new drugs are needed. Initiating lead discovery campaigns by using chemical scaffolds from drugs approved for other indications can speed up drug discovery for neglected diseases. We demonstrated recently that the 4-anilinoquinazolines lapatinib (GW572016, 1) and canertinib (CI-1033) kill T. brucei with low micromolar EC50 values. We now report promising activity of analogs of 1, which provided an excellent starting point for optimization of the chemotype. We report our compound optimization that has led to synthesis of several potent 4-anilinoquinazolines, including NEU621, 23a, a highly potent, orally bioavailable inhibitor of trypanosome replication. At the cellular level, 23a blocks duplication of the kinetoplast and arrests cytokinesis, making it a new tool for studying regulation of the trypanosome cell cycle. PMID:23597080
Patel, Gautam; Karver, Caitlin E; Behera, Ranjan; Guyett, Paul J; Sullenberger, Catherine; Edwards, Peter; Roncal, Norma E; Mensa-Wilmot, Kojo; Pollastri, Michael P
Human African trypanosomiasis (HAT) is a neglected tropical disease caused by the protozoan parasite Trypanosoma brucei . Because drugs in use against HAT are toxic and require intravenous dosing, new drugs are needed. Initiating lead discovery campaigns by using chemical scaffolds from drugs approved for other indications can speed up drug discovery for neglected diseases. We demonstrated recently that the 4-anilinoquinazolines lapatinib (GW572016, 1) and canertinib (CI-1033) kill T. brucei with low micromolar EC50 values. We now report promising activity of analogues of 1, which provided an excellent starting point for optimization of the chemotype. Our compound optimization that has led to synthesis of several potent 4-anilinoquinazolines, including NEU617, 23a, a highly potent, orally bioavailable inhibitor of trypanosome replication. At the cellular level, 23a blocks duplication of the kinetoplast and arrests cytokinesis, making it a new chemical tool for studying regulation of the trypanosome cell cycle.
Pors, Klaus; Goldberg, Frederick W; Leamon, Christopher P; Rigby, Alan C; Snyder, Scott A; Falconer, Robert A
Since the development of the first cytotoxic agents, synthetic organic chemistry has advanced enormously. The synthetic and medicinal chemists of today are at the centre of drug development and are involved in most, if not all, processes of drug discovery. Recent decreases in government funding and reformed educational policies could, however, seriously impact on drug discovery initiatives worldwide. Not only could these changes result in fewer scientific breakthroughs, but they could also negatively affect the training of our next generation of medicinal chemists.
Djuric, Stevan W.; Hutchins, Charles W.; Talaty, Nari N.
This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of “dangerous” reagents. Also featured are advances in the “computer-assisted drug design” area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities. PMID:27781094
Djuric, Stevan W; Hutchins, Charles W; Talaty, Nari N
This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of "dangerous" reagents. Also featured are advances in the "computer-assisted drug design" area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities.
Taylor, Richard D; MacCoss, Malcolm; Lawson, Alastair D G
We have enumerated all linear combinations of ring systems from FDA approved drugs, up to three rings in length and up to four bonds linkers to give an in silico database of approximately 14 million molecules. This virtual library was compared with molecular databases of published and commercially available compounds to assess the prevalence of drug ring combinations in modern medicinal chemistry and to identify areas of under-represented, but clinically validated, chemical space. From the 10 trillion molecular comparisons, we found that less than 1% of the possible combinations of drug ring systems appear in commercially available libraries. This key observation highlights significant opportunities to design new fragment-like and lead-like libraries aimed at improving success rates and reducing risk in small molecule drug discovery, as, based on our previous analysis ( Taylor J. Med. Chem. 2014 , 57 , 5845 - 5849 ), approximately 70% of all new drugs are made up of only ring systems that have been used in existing drugs.
Zhang, Aihua; Sun, Hui; Wang, Xijun
Herbal medicine (HM) has made a major contribution to the drug discovery process with regard to identifying products compounds. Currently, more attention has been focused on drug discovery from natural compounds of HM. Despite the rapid advancement of modern analytical techniques, drug discovery is still a difficult and lengthy process. Fortunately, mass spectrometry (MS) can provide us with useful structural information for drug discovery, has been recognized as a sensitive, rapid, and high-throughput technology for advancing drug discovery from HM in the post-genomic era. It is essential to develop an efficient, high-quality, high-throughput screening method integrated with an MS platform for early screening of candidate drug molecules from natural products. We have developed a new chinmedomics strategy reliant on MS that is capable of capturing the candidate molecules, facilitating their identification of novel chemical structures in the early phase; chinmedomics-guided natural product discovery based on MS may provide an effective tool that addresses challenges in early screening of effective constituents of herbs against disease. This critical review covers the use of MS with related techniques and methodologies for natural product discovery, biomarker identification, and determination of mechanisms of action. It also highlights high-throughput chinmedomics screening methods suitable for lead compound discovery illustrated by recent successes.
Radoshitzky, Sheli R.; Kuhn, Jens H.; de Kok-Mercado, Fabian; Jahrling, Peter B.; Bavari, Sina
Introduction Seven arenaviruses cause viral hemorrhagic fever in humans: the Old World arenaviruses Lassa and Lujo, and the New World Clade B arenaviruses Machupo (MACV), Junín (JUNV), Guanarito (GTOV), Sabiá (SABV), and Chapare (CHPV). All of these viruses are Risk Group 4 biosafety pathogens. MACV causes human disease outbreak with high case-fatality rates. To date, at least 1,200 cases with ≈200 fatalities have been recorded 1, 2. Areas covered This review summarizes available systems and technologies for the identification of antivirals against MACV, animal models for in vivo evaluation of novel inhibitors, present treatment of arenaviral diseases, overview of efficacious small molecules and other therapeutics reported to date, and strategies to identify novel inhibitors for anti-arenaviral therapy. Expert opinion New high-throughput approaches to quantitate infection rates of areaviruses, as well as viruses modified to carry reporter genes, will accelerate compound screens and drug discovery efforts. RNAi, gene expression profiling and proteomics studies will identify host targets for therapeutic intervention. New discoveries in the cell entry mechanism of MACV and other arenaviruses as well as extensive structural studies of arenaviral L and NP could facilitate the rational design of antivirals effective against all pathogenic New World arenaviruses. PMID:22607481
The tumor microenvironment, characterized by regions of hypoxia, low nutrition, and acidosis due to incomplete blood vessel networks, has been recognized as a major factor that influences not only the response to conventional anti-cancer therapies but also malignant progression and metastasis. However, exploiting such a cumbersome tumor microenvironment for cancer treatment could provide tumor-specific therapeutic approaches. In particular, hypoxia is now considered a fundamentally important characteristic of the tumor microenvironment in which hypoxia inducible factor (HIF)-1-mediated gene regulation is considered essential for angiogenesis and tumor development. Additional oxygen sensitive signaling pathways including mammalian target of rapamycin (mTOR) signaling and signaling through activation of the unfolded protein response (UPR) also contribute to the adaptation in the tumor microenvironment. This in turn has led to the current extensive interest in the signal molecules related to adaptive responses in the tumor microenvironment as potential molecular targets for cancer therapy against refractory cancer and recurrence in preparation for the aging society. Therefore, we should focus on the drug discovery for targeting the tumor microenvironment to develop tumor-specific cytostatic agents including angiogenesis inhibitors. In this paper, the development of hypoxia-selective prodrugs, HIF-1 inhibitors, and modulators of the tumor microenvironment will be discussed.
Fellmann, Christof; Gowen, Benjamin G; Lin, Pei-Chun; Doudna, Jennifer A; Corn, Jacob E
The recent development of CRISPR-Cas systems as easily accessible and programmable tools for genome editing and regulation is spurring a revolution in biology. Paired with the rapid expansion of reference and personalized genomic sequence information, technologies based on CRISPR-Cas are enabling nearly unlimited genetic manipulation, even in previously difficult contexts, including human cells. Although much attention has focused on the potential of CRISPR-Cas to cure Mendelian diseases, the technology also holds promise to transform the development of therapies to treat complex heritable and somatic disorders. In this Review, we discuss how CRISPR-Cas can affect the next generation of drugs by accelerating the identification and validation of high-value targets, uncovering high-confidence biomarkers and developing differentiated breakthrough therapies. We focus on the promises, pitfalls and hurdles of this revolutionary gene-editing technology, discuss key aspects of different CRISPR-Cas screening platforms and offer our perspectives on the best practices in genome engineering.
Chakraborty, Chiranjib; Doss C, George Priya; Chen, Luonan; Zhu, Hailong
In silico pharmacology is a promising field in the current state-of drug discovery. This area exploits "protein-protein Interaction (PPI) network analysis for drug discovery using the drug "target class". To document the current status, we have discussed in this article how this an integrated system of PPI networks contribute to understand the disease pathways, present state-of-the-art drug target discovery and drug discovery process. This review article enhances our knowledge on conventional drug discovery and current drug discovery using in silico techniques, best "target class", universal architecture of PPI networks, the present scenario of disease pathways and protein-protein interaction networks as well as the method to comprehend the PPI networks. Taken all together, ultimately a snapshot has been discussed to be familiar with how PPI network architecture can used to validate a drug target. At the conclusion, we have illustrated the future directions of PPI in target discovery and drug-design.
Liu, Yang; Zhai, Hua-Qiang; Xiang, Jia-Mei; Wang, Jing-Juan; Zhao, Bao-Sheng; Wang, Gang; Dong, Hong-Huan; Ouyang, Guo-Qing
With the kernel of efficacy, "Xiaohe Silian" was a pattern and method for new drug discovery which was constituted with "metabolism-efficacy, toxicity-efficacy, quality-efficacy and structure-efficacy". Its connotation was in keeping with traditional Chinese medicine (TCM) clinical pharmacy. This paper systematically summarized the research method of new drug discovery practice process for TCM. To avoid western drug like in TCM new drug discovery, we carried out combination analysis with TCM clinical pharmacy. The correlation analysis between basic elements of "Xiaohe Silian(n) and TCM clinical pharmacy was studied to guarantee this method could integrate closely with TCM clinic from all angles. Hence, this method aimed to provide a new method for TCM new drug discovery on the basis of TCM clinical pharmacy with insisting on holistic view of multicomponent study, kinetic view of metabolic process when the curative effect occurred and molecular material view of quality control and structure-activity exposition.
Menezes, V.; Takayama, K.; Ohki, T.; Gopalan, J.
Localized drug delivery with minimal tissue damage is desired in some of the clinical procedures such as gene therapy, treatment of cancer cells, treatment of thrombosis, etc. We present an effective method for delivering drug-coated microparticles using laser ablation on a thin metal foil containing particles. A thin metal foil, with a deposition of a layer of microparticles is subjected to laser ablation on its backface such that a shock wave propagates through the foil. Due to shock wave loading, the surface of the foil containing microparticles is accelerated to very high speeds, ejecting the deposited particles at hypersonic speeds. The ejected particles have sufficient momentum to penetrate soft body tissues, and the penetration depth observed is sufficient for most of the pharmacological treatments. We have tried delivering 1μm tungsten particles into gelatin models that represent soft tissues, and liver tissues of an experimental rat. Sufficient penetration depths have been observed in these experiments with minimum target damage.
Ekins, Sean; Clark, Alex M; Williams, Antony J
Abstract The Open Drug Discovery Teams (ODDT) project provides a mobile app primarily intended as a research topic aggregator of predominantly open science data collected from various sources on the internet. It exists to facilitate interdisciplinary teamwork and to relieve the user from data overload, delivering access to information that is highly relevant and focused on their topic areas of interest. Research topics include areas of chemistry and adjacent molecule-oriented biomedical sciences, with an emphasis on those which are most amenable to open research at present. These include rare and neglected diseases, and precompetitive and public-good initiatives such as green chemistry. The ODDT project uses a free mobile app as user entry point. The app has a magazine-like interface, and server-side infrastructure for hosting chemistry-related data as well as value added services. The project is open to participation from anyone and provides the ability for users to make annotations and assertions, thereby contributing to the collective value of the data to the engaged community. Much of the content is derived from public sources, but the platform is also amenable to commercial data input. The technology could also be readily used in-house by organizations as a research aggregator that could integrate internal and external science and discussion. The infrastructure for the app is currently based upon the Twitter API as a useful proof of concept for a real time source of publicly generated content. This could be extended further by accessing other APIs providing news and data feeds of relevance to a particular area of interest. As the project evolves, social networking features will be developed for organizing participants into teams, with various forms of communication and content management possible. PMID:23198003
Ojima, Iwao; Kumar, Kunal; Awasthi, Divya; Vineberg, Jacob G
Eukaryotic cell division or cytokinesis has been a major target for anticancer drug discovery. After the huge success of paclitaxel and docetaxel, microtubule-stabilizing agents (MSAs) appear to have gained a premier status in the discovery of next-generation anticancer agents. However, the drug resistance caused by MDR, point mutations, and overexpression of tubulin subtypes, etc., is a serious issue associated with these agents. Accordingly, the discovery and development of new-generation MSAs that can obviate various drug resistances has a significant meaning. In sharp contrast, prokaryotic cell division has been largely unexploited for the discovery and development of antibacterial drugs. However, recent studies on the mechanism of bacterial cytokinesis revealed that the most abundant and highly conserved cell division protein, FtsZ, would be an excellent new target for the drug discovery of next-generation antibacterial agents that can circumvent drug-resistances to the commonly used drugs for tuberculosis, MRSA and other infections. This review describes an account of our research on these two fronts in drug discovery, targeting eukaryotic as well as prokaryotic cell division.
Shakespeare, William C; Metcalf, Chester A; Wang, Yihan; Sundaramoorthi, Raji; Keenan, Terence; Weigele, Manfred; Bohacek, Regine S; Dalgarno, David C; Sawyer, Tomi K
Bone-targeted Src tyrosine kinase (STK) inhibitors have recently been developed for the treatment of osteoporosis and cancer-related bone diseases. The concept of bone targeting derives from bisphosphonates, and from the evolution of such molecules in terms of therapeutic efficacy for the treatment of bone disorders. Interestingly, some of the earliest bisphosphonates were recognized for their ability to inhibit calcium carbonate precipitation (scaling) by virtue of their affinity to chelate calcium. This chelating property was subsequently exploited in the development of bisphosphonate analogs as inhibitors of the bone-resorbing cells known as osteoclasts, giving rise to breakthrough medicines, such as Fosamax (for the treatment of osteoporosis) and Zometa (for the treatment of osteoporosis and bone metastases). Relative to these milestone achievements, there is a tremendous opportunity to explore beyond the limited chemical space (functional group diversity) of such bisphosphonates to design novel bone-targeting moieties, which may be used to develop other classes of promising small-molecule drugs affecting different biological pathways. Here, we review studies focused on bone-targeted inhibitors of STK, a key enzyme in osteoclast-dependent bone resorption. Two strategies are described relative to bone-targeted STK inhibitor drug discovery: (i) the development of novel Src homology (SH)-2 inhibitors incorporating non-hydrolyzable phosphotyrosine mimics and exhibiting molecular recognition and bone-targeting properties, leading to the in vivo-effective lead compound AP-22408; and (ii) the development of novel ATP-based Src kinase inhibitors incorporating bone-targeting moieties, leading to the in vivo-effective lead compound AP-23236. In summary, AP-22408 and AP-23236, which differ mechanistically by virtue of blocking Src-dependent non-catalytic or catalytic activities in osteoclasts, exemplify ARIAD Pharmaceuticals' structure-based design of novel bone
Felciano, Ramon M; Bavari, Sina; Richards, Daniel R; Billaud, Jean-Noel; Warren, Travis; Panchal, Rekha; Krämer, Andreas
Knowledge of immune system and host-pathogen pathways can inform development of targeted therapies and molecular diagnostics based on a mechanistic understanding of disease pathogenesis and the host response. We investigated the feasibility of rapid target discovery for novel broad-spectrum molecular therapeutics through comprehensive systems biology modeling and analysis of pathogen and host-response pathways and mechanisms. We developed a system to identify and prioritize candidate host targets based on strength of mechanistic evidence characterizing the role of the target in pathogenesis and tractability desiderata that include optimal delivery of new indications through potential repurposing of existing compounds or therapeutics. Empirical validation of predicted targets in cellular and mouse model systems documented an effective target prediction rate of 34%, suggesting that such computational discovery approaches should be part of target discovery efforts in operational clinical or biodefense research initiatives. We describe our target discovery methodology, technical implementation, and experimental results. Our work demonstrates the potential for in silico pathway models to enable rapid, systematic identification and prioritization of novel targets against existing or emerging biological threats, thus accelerating drug discovery and medical countermeasures research.
Xu, Zhijian; Yang, Zhuo; Liu, Yingtao; Lu, Yunxiang; Chen, Kaixian; Zhu, Weiliang
Halogen bond has attracted a great deal of attention in the past years for hit-to-lead-to-candidate optimization aiming at improving drug-target binding affinity. In general, heavy organohalogens (i.e., organochlorines, organobromines, and organoiodines) are capable of forming halogen bonds while organofluorines are not. In order to explore the possible roles that halogen bonds could play beyond improving binding affinity, we performed a detailed database survey and quantum chemistry calculation with close attention paid to (1) the change of the ratio of heavy organohalogens to organofluorines along the drug discovery and development process and (2) the halogen bonds between organohalogens and nonbiopolymers or nontarget biopolymers. Our database survey revealed that (1) an obviously increasing trend of the ratio of heavy organohalogens to organofluorines was observed along the drug discovery and development process, illustrating that more organofluorines are worn and eliminated than heavy organohalogens during the process, suggesting that heavy halogens with the capability of forming halogen bonds should have priority for lead optimization; and (2) more than 16% of the halogen bonds in PDB are formed between organohalogens and water, and nearly 20% of the halogen bonds are formed with the proteins that are involved in the ADME/T process. Our QM/MM calculations validated the contribution of the halogen bond to the binding between organohalogens and plasma transport proteins. Thus, halogen bonds could play roles not only in improving drug-target binding affinity but also in tuning ADME/T property. Therefore, we suggest that albeit halogenation is a valuable approach for improving ligand bioactivity, more attention should be paid in the future to the application of the halogen bond for ligand ADME/T property optimization.
potential drug target enzymes. The yeast expression system should allow rapid screening of new drugs , greatly increasing the rate at which new...medication yet the world faces a crisis--drug resistance is emerging and spreading faster than drugs are being developed and the flow in the pipeline of new ... drugs has all but stopped. This represents a particular threat to the U.S. Military. A new strategy for drug development is urgently needed. Current
He, Yan; Ho, Chris
Amorphous solid dispersion (ASD) can accelerate a project by improving dissolution rate and solubility, offering dose escalation flexibility and excipient acceptance for toxicology studies, as well as providing adequate preclinical and clinical exposure. The prerequisite physicochemical properties for a compound to form a stable ASD are glass-forming ability and low-crystallization tendency, which can be assessed using computational tools and experimental methods. Polymer excipient screening by in silico miscibility prediction and experimental screening techniques is discussed. Improved technologies for polymer screening with minimal quantity of drug substance, and the scalability of ASD from bench to commercial are reviewed. Considerations of in vitro evaluations, preclinical animal selection, and the translation of the preclinical results to clinical studies are also discussed. Better understanding of how polymers improve the stability of the amorphous phase in the solid state and how ASD improves bioavailability have facilitated the applications of ASD ranging from discovery research to preclinical development and further to commercialization. With the understanding of how ASDs are currently used in the pharmaceutical industry and what challenges remain to be solved, ASD can be applied to solve drug formulation problems at given research and development stages.
Lounnas, Valère; Ritschel, Tina; Kelder, Jan; McGuire, Ross; Bywater, Robert P.; Foloppe, Nicolas
The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented. PMID:24688704
Andersen, Peter Høngaard; Moscicki, Richard; Sahakian, Barbara; Quirion, Rémi; Krishnan, Ranga; Race, Tim; Phillips, Anthony
Innovative partnerships among researchers, patients, regulators, payors and industry are needed to reinvigorate drug discovery for central nervous system disorders. Here, we summarize plans of the Collegium Internationale Neuro-Psychopharmacologicum (CINP) to achieve this goal.
Weller, Harold N; Nirschl, David S; Petrillo, Edward W; Poss, Michael A; Andres, Charles J; Cavallaro, Cullen L; Echols, Martin M; Grant-Young, Katherine A; Houston, John G; Miller, Arthur V; Swann, R Thomas
The application of parallel synthesis to lead optimization programs in drug discovery has been an ongoing challenge since the first reports of library synthesis. A number of approaches to the application of parallel array synthesis to lead optimization have been attempted over the years, ranging from widespread deployment by (and support of) individual medicinal chemists to centralization as a service by an expert core team. This manuscript describes our experience with the latter approach, which was undertaken as part of a larger initiative to optimize drug discovery. In particular, we highlight how concepts taken from the manufacturing sector can be applied to drug discovery and parallel synthesis to improve the timeliness and thus the impact of arrays on drug discovery.
Murakami, Yoichi; Tripathi, Lokesh P; Prathipati, Philip; Mizuguchi, Kenji
Protein-protein interactions (PPIs) are vital to maintaining cellular homeostasis. Several PPI dysregulations have been implicated in the etiology of various diseases and hence PPIs have emerged as promising targets for drug discovery. Surface residues and hotspot residues at the interface of PPIs form the core regions, which play a key role in modulating cellular processes such as signal transduction and are used as starting points for drug design. In this review, we briefly discuss how PPI networks (PPINs) inferred from experimentally characterized PPI data have been utilized for knowledge discovery and how in silico approaches to PPI characterization can contribute to PPIN-based biological research. Next, we describe the principles of in silico PPI prediction and survey the existing PPI and PPI site prediction servers that are useful for drug discovery. Finally, we discuss the potential of in silico PPI prediction in drug discovery.
Müller, Gerhard; Ernst, Beat
Alpine fresh! Aimed at instructing young scientists at the beginning of their careers in industry, this medicinal chemistry course provides an overview of the state of the art techniques and current approaches to drug discovery and development.
Campbell, Robert M; Tummino, Peter J
Over the past several years, there has been rapidly expanding evidence of epigenetic dysregulation in cancer, in which histone and DNA modification play a critical role in tumor growth and survival. These findings have gained the attention of the drug discovery and development community, and offer the potential for a second generation of cancer epigenetic agents for patients following the approved "first generation" of DNA methylation (e.g., Dacogen, Vidaza) and broad-spectrum HDAC inhibitors (e.g., Vorinostat, Romidepsin). This Review provides an analysis of prospects for discovery and development of novel cancer agents that target epigenetic proteins. We will examine key examples of epigenetic dysregulation in tumors as well as challenges to epigenetic drug discovery with emerging biology and novel classes of drug targets. We will also highlight recent successes in cancer epigenetics drug discovery and consider important factors for clinical success in this burgeoning area.
Roy, Anuradha; McDonald, Peter R.; Sittampalam, Sitta; Chaguturu, Rathnam
High throughput screening (HTS) facilitates screening large numbers of compounds against a biochemical target of interest using validated biological or biophysical assays. In recent years, a significant number of drugs in clinical trails originated from HTS campaigns, validating HTS as a bona fide mechanism for hit finding. In the current drug discovery landscape, the pharmaceutical industry is embracing open innovation strategies with academia to maximize their research capabilities and to feed their drug discovery pipeline. The goals of academic research have therefore expanded from target identification and validation to probe discovery, chemical genomics, and compound library screening. This trend is reflected in the emergence of HTS centers in the public domain over the past decade, ranging in size from modestly equipped academic screening centers to well endowed Molecular Libraries Probe Centers Network (MLPCN) centers funded by the NIH Roadmap initiative. These centers facilitate a comprehensive approach to probe discovery in academia and utilize both classical and cutting-edge assay technologies for executing primary and secondary screening campaigns. The various facets of academic HTS centers as well as their implications on technology transfer and drug discovery are discussed, and a roadmap for successful drug discovery in the public domain is presented. New lead discovery against therapeutic targets, especially those involving the rare and neglected diseases, is indeed a Mount Everestonian size task, and requires diligent implementation of pharmaceutical industry’s best practices for a successful outcome. PMID:20809896
Roy, Anuradha; McDonald, Peter R; Sittampalam, Sitta; Chaguturu, Rathnam
High throughput screening (HTS) facilitates screening large numbers of compounds against a biochemical target of interest using validated biological or biophysical assays. In recent years, a significant number of drugs in clinical trails originated from HTS campaigns, validating HTS as a bona fide mechanism for hit finding. In the current drug discovery landscape, the pharmaceutical industry is embracing open innovation strategies with academia to maximize their research capabilities and to feed their drug discovery pipeline. The goals of academic research have therefore expanded from target identification and validation to probe discovery, chemical genomics, and compound library screening. This trend is reflected in the emergence of HTS centers in the public domain over the past decade, ranging in size from modestly equipped academic screening centers to well endowed Molecular Libraries Probe Centers Network (MLPCN) centers funded by the NIH Roadmap initiative. These centers facilitate a comprehensive approach to probe discovery in academia and utilize both classical and cutting-edge assay technologies for executing primary and secondary screening campaigns. The various facets of academic HTS centers as well as their implications on technology transfer and drug discovery are discussed, and a roadmap for successful drug discovery in the public domain is presented. New lead discovery against therapeutic targets, especially those involving the rare and neglected diseases, is indeed a Mount Everestonian size task, and requires diligent implementation of pharmaceutical industry's best practices for a successful outcome.
Buscher, Brigitte; Laakso, Sirpa; Mascher, Hermann; Pusecker, Klaus; Doig, Mira; Dillen, Lieve; Wagner-Redeker, Winfried; Pfeifer, Thomas; Delrat, Pascal; Timmerman, Philip
Plasma protein binding (PPB) is an important parameter for a drug's efficacy and safety that needs to be investigated during each drug-development program. Even though regulatory guidance exists to study the extent of PPB before initiating clinical studies, there are no detailed instructions on how to perform and validate such studies. To explore how PPB studies involving bioanalysis are currently executed in the industry, the European Bioanalysis Forum (EBF) has conducted three surveys among their member companies: PPB studies in drug discovery (Part I); in vitro PPB studies in drug development (Part II); and in vivo PPB studies in drug development. This paper reflects the outcome of the three surveys, which, together with the team discussions, formed the basis of the EBF recommendation. The EBF recommends a tiered approach to the design of PPB studies and the bioanalysis of PPB samples: 'PPB screening' experiments in (early) drug discovery versus qualified/validated procedures in drug development.
Gullo, Vincent P; Hughes, Dallas E
In recent years, large pharmaceutical companies have significantly reduced or eliminated the search for new therapeutic agents from natural sources. In spite of the many successes from natural product drug discovery, these companies have chosen to focus on compound libraries as the source of new lead compounds. Smaller biotechnology companies are continuing the search for novel natural products by developing and employing new and innovative approaches. This paper will describe some of these recent approaches to natural product drug discovery.:
Trifiletti, Daniel M.; Showalter, Timothy N.
Several advances in large data set collection and processing have the potential to provide a wave of new insights and improvements in the use of radiation therapy for cancer treatment. The era of electronic health records, genomics, and improving information technology resources creates the opportunity to leverage these developments to create a learning healthcare system that can rapidly deliver informative clinical evidence. By merging concepts from comparative effectiveness research with the tools and analytic approaches of “big data,” it is hoped that this union will accelerate discovery, improve evidence for decision making, and increase the availability of highly relevant, personalized information. This combination offers the potential to provide data and analysis that can be leveraged for ultra-personalized medicine and high-quality, cutting-edge radiation therapy. PMID:26697409
Patel, Hershna; Kukol, Andreas
Sequence variations in the binding sites of influenza A proteins are known to limit the effectiveness of current antiviral drugs. Clinically, this leads to increased rates of virus transmission and pathogenicity. Potential influenza A inhibitors are continually being discovered as a result of high-throughput cell based screening studies, whereas the application of computational tools to aid drug discovery has further increased the number of predicted inhibitors reported. This review brings together the aspects that relate to the identification of influenza A drug target sites and the findings from recent antiviral drug discovery strategies.
Background Innovation through an open source model has proven to be successful for software development. This success has led many to speculate if open source can be applied to other industries with similar success. We attempt to provide an understanding of open source software development characteristics for researchers, business leaders and government officials who may be interested in utilizing open source innovation in other contexts and with an emphasis on drug discovery. Methods A systematic review was performed by searching relevant, multidisciplinary databases to extract empirical research regarding the common characteristics and barriers of initiating and maintaining an open source software development project. Results Common characteristics to open source software development pertinent to open source drug discovery were extracted. The characteristics were then grouped into the areas of participant attraction, management of volunteers, control mechanisms, legal framework and physical constraints. Lastly, their applicability to drug discovery was examined. Conclusions We believe that the open source model is viable for drug discovery, although it is unlikely that it will exactly follow the form used in software development. Hybrids will likely develop that suit the unique characteristics of drug discovery. We suggest potential motivations for organizations to join an open source drug discovery project. We also examine specific differences between software and medicines, specifically how the need for laboratories and physical goods will impact the model as well as the effect of patents. PMID:21955914
Despite the scientific consensus on climate change, drastic uncertainties remain. The climate system is characterized by complex phenomena that are imperfectly observed and even more imperfectly simulated. Climate data is Big Data, yet the magnitude of data and climate model output increasingly overwhelms the tools currently used to analyze them. Computational innovation is therefore needed. Machine learning is a cutting-edge research area at the intersection of computer science and statistics, focused on developing algorithms for big data analytics. Machine learning has revolutionized scientific discovery (e.g. Bioinformatics), and spawned new technologies (e.g. Web search). The impact of machine learning on climate science promises to be similarly profound. The goal of the novel interdisciplinary field of Climate Informatics is to accelerate discovery in climate science with machine learning, in order to shed light on urgent questions about climate change. In this talk, I will survey my research group's progress in the emerging field of climate informatics. Our work includes algorithms to improve the combined predictions of the IPCC multi-model ensemble, applications to seasonal and subseasonal prediction, and a data-driven technique to detect and define extreme events.
Tu, Peng-fei; Jiang, Yong; Guo, Xiao-yu
Referring to the rapid developed life science and the higher requirements for the approval of innovative Chinese drugs in recent years, this paper described systematically the discovery, research and development (R&D) approaches for the innovative Chinese drugs under the new situation from the following five aspects, i. e., active components discovered from TCMs, the discovery of effective fractions of TCMs and their formulae, the R&D of TCM innovative drugs based on famous classic prescriptions and famous Chinese patent drugs, and the transformation of clinical effective prescriptions, on the basis of analysing the advantages of innovative drugs derived from natural products based on TCM theories and the problems existed in current R&D of new TCM drugs. Moreover, five suggestions are also given for the rapid development of TCM innovative drugs in China. All these will provide reference for the R&D of TCM innovative drugs.
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.
Campbell, James B
Key methodologies such as HTS and combinatorial chemistry have allowed pharmaceutical discovery to focus on identifying promising drug candidates through the use of statistics. Thus, amassing large data sets from large-scale screening campaigns of ever-increasing corporate compound collections was expected to deliver unprecedented success for the pharmaceutical industry. This feature review explores aspects of how the reliance on using numbers to drive discovery has gone awry. Building knowledge equity from the integration of multiple parallel screening assays, workstreams and data sources provides an alternative to driving discovery through statistics. Thus, a more rational approach to creating and inventing new leads and drug opportunities may be pursued.
Gao, Guangxun; Chen, Liang; Huang, Chuanshu
Discovery of novel cancer chemotherapeutics focuses on screening and identifying compounds that can target 'cancer-specific' biological processes while causing minimal toxicity to non-tumor cells. Alternatively, model organisms with highly conserved cancer-related cellular processes relative to human cells may offer new opportunities for anticancer drug discovery when combined with chemical screening. Some organisms used for chemotherapeutic discovery include yeast, Drosophila, and zebrafish which are similar in important ways relevant to cancer study but offer distinct advantages as well. Here, we describe these model attributes and the rationale for using them in cancer drug screening research.
Kitchen, Douglas B.
Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.
Kitchen, Douglas B
Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.
Gao, Guangxun; Chen, Liang; Huang, Chuanshu
Discovery of novel cancer chemotherapeutics focuses on screening and identifying compounds that can target ‘cancer-specific’ biological processes while causing minimal toxicity to non-tumor cells. Alternatively, model organisms with highly conserved cancer-related cellular processes relative to human cells may offer new opportunities for anticancer drug discovery when combined with chemical screening. Some organisms used for chemotherapeutic discovery include yeast, Drosophila, and zebrafish which are similar in important ways relevant to cancer study but offer distinct advantages as well. Here, we describe these model attributes and the rationale for using them in cancer drug screening research. PMID:24993385
Li, Xiangyi; Qin, Guangrong; Yang, Qingmin
Drug combination is a powerful and promising approach for complex disease therapy such as cancer and cardiovascular disease. However, the number of synergistic drug combinations approved by the Food and Drug Administration is very small. To bridge the gap between urgent need and low yield, researchers have constructed various models to identify synergistic drug combinations. Among these models, biomolecular network-based model is outstanding because of its ability to reflect and illustrate the relationships among drugs, disease-related genes, therapeutic targets, and disease-specific signaling pathways as a system. In this review, we analyzed and classified models for synergistic drug combination prediction in recent decade according to their respective algorithms. Besides, we collected useful resources including databases and analysis tools for synergistic drug combination prediction. It should provide a quick resource for computational biologists who work with network medicine or synergistic drug combination designing. PMID:27891522
Huang, Wenkang; Nussinov, Ruth; Zhang, Jian
Allostery is an intrinsic phenomenon of biological macromolecules involving regulation and/or signal transduction induced by a ligand binding to an allosteric site distinct from a molecule's active site. Allosteric drugs are currently receiving increased attention in drug discovery because drugs that target allosteric sites can provide important advantages over the corresponding orthosteric drugs including specific subtype selectivity within receptor families. Consequently, targeting allosteric sites, instead of orthosteric sites, can reduce drug-related side effects and toxicity. On the down side, allosteric drug discovery can be more challenging than traditional orthosteric drug discovery due to difficulties associated with determining the locations of allosteric sites and designing drugs based on these sites and the need for the allosteric effects to propagate through the structure, reach the ligand binding site and elicit a conformational change. In this study, we present computational tools ranging from the identification of potential allosteric sites to the design of "allosteric-like" modulator libraries. These tools may be particularly useful for allosteric drug discovery.
research working in concert with one another. The goal of this work is to use a molecular genetic approach both in the identification of new drug targets...analysis of critical genes in the Plasmodium falciparum for their role in drug resistance and as potential new drug targets using both the homologous P. falciparum system and the heterologous yeast system.
research working in concert with one another. The goal of this work is to use a molecular genetic approach both in the identification of new drug targets and...Plasmodium falciparum for their role in drug resistance and as potential new drug targets, including the analysis of gene expression in response to
a productive partnership with the Cancer Drug Validation Team at the Tulane Cancer Center. This inter-university collaboration involves training ...Identification of compounds with the potential for estrogen receptor activity. 15. SUBJECT TERMS Breast cancer, Partnership, Training 16. SECURITY...University involves training of Xavier researchers and students in drug target validation, biological assays of drug efficacy, evaluation of resistance
Camacho, Kathryn Militar
Chemotherapy combinations for cancer treatments harbor immense therapeutic potentials which have largely been untapped. Of all diseases, clinical studies of drug combinations are the most prevalent in oncology, yet their effectiveness is disputable, as complete tumor regressions are rare. Our research has been devoted towards developing delivery vehicles for combinations of chemotherapy drugs which elicit significant tumor reduction yet limit toxicity in healthy tissue. Current administration methods assume that chemotherapy combinations at maximum tolerable doses will provide the greatest therapeutic effect -- a presumption which often leads to unprecedented side effects. Contrary to traditional administration, we have found that drug ratios rather than total cumulative doses govern combination therapeutic efficacy. In this thesis, we have developed nanoparticles to incorporate synergistic ratios of chemotherapy combinations which significantly inhibit cancer cell growth at lower doses than would be required for their single drug counterparts. The advantages of multi-drug incorporation in nano-vehicles are many: improved accumulation in tumor tissue via the enhanced permeation and retention effect, limited uptake in healthy tissue, and controlled exposure of tumor tissue to optimal synergistic drug ratios. To exploit these advantages for polychemotherapy delivery, two prominent nanoparticles were investigated: liposomes and polymer-drug conjugates. Liposomes represent the oldest class of nanoparticles, with high drug loading capacities and excellent biocompatibility. Polymer-drug conjugates offer controlled drug incorporations through reaction stoichiometry, and potentially allow for delivery of precise ratios. Here, we show that both vehicles, when armed with synergistic ratios of chemotherapy drugs, significantly inhibit tumor growth in an aggressive mouse breast carcinoma model. Furthermore, versatile drug incorporation methods investigated here can be broadly
Crabtree, George; Glotzer, Sharon; McCurdy, Bill; Roberto, Jim
This report is based on a SC Workshop on Computational Materials Science and Chemistry for Innovation on July 26-27, 2010, to assess the potential of state-of-the-art computer simulations to accelerate understanding and discovery in materials science and chemistry, with a focus on potential impacts in energy technologies and innovation. The urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. To convert sunlight to fuel, efficiently store energy, or enable a new generation of energy production and utilization technologies requires the development of new materials and processes of unprecedented functionality and performance. New materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. Over the past two decades, the United States has developed and deployed the world's most powerful collection of tools for the synthesis, processing, characterization, and simulation and modeling of materials and chemical systems at the nanoscale, dimensions of a few atoms to a few hundred atoms across. These tools, which include world-leading x-ray and neutron sources, nanoscale science facilities, and high-performance computers, provide an unprecedented view of the atomic-scale structure and dynamics of materials and the molecular-scale basis of chemical processes. For the first time in history, we are able to synthesize, characterize, and model materials and chemical behavior at the length scale where this behavior is controlled. This ability is transformational for the discovery process and, as a result, confers a significant competitive advantage. Perhaps the most spectacular increase in capability has been demonstrated in high performance computing. Over the past decade, computational power has increased by a factor of a million due to advances in hardware and software. This rate of improvement, which shows no sign of abating, has
Cao, Shugeng; Kingston, David G. I.
The approach to new drugs through natural products has proved to be the single most successful strategy for the discovery of new drugs, but in recent years its use has been deemphasized by many pharmaceutical companies in favor of approaches based on combinatorial chemistry and genomics, among others. Drug discovery from natural sources requires continued access to plant, marine, and microbial biomass, and so the preservation of tropical rainforests is an important part of our drug discovery program. Sadly, many of the tropical forests of the world are under severe environmental pressure, and deforestation is a serious problem in most tropical countries. One way to combat this loss is to demonstrate their value as potential sources of new pharmaceutical or agrochemical products. As part of an effort to integrate biodiversity conservation and drug discovery with economic development, we initiated an International Cooperative biodiversity Group (ICBG) to discover potential pharmaceuticals from the plant biodiversity of Suriname and Madagascar. The Group, established with funding from agencies of the United States government, involved participants from the USA, Suriname, and Madagascar. The basic approach was to search for bioactive plants in the Suriname and Malagasy flora, and to isolate their bioactive constituents by the best available methods, but the work included capacity building as well as research. Progress on this project will be reported, drawing on results obtained from the isolation of bioactive natural products from Suriname and Madagascar. The benefits of this general approach to biodiversity and drug discovery will also be discussed. PMID:20161050
Banda, Juan M.; Evans, Lee; Vanguri, Rami S.; Tatonetti, Nicholas P.; Ryan, Patrick B.; Shah, Nigam H.
Identification of adverse drug reactions (ADRs) during the post-marketing phase is one of the most important goals of drug safety surveillance. Spontaneous reporting systems (SRS) data, which are the mainstay of traditional drug safety surveillance, are used for hypothesis generation and to validate the newer approaches. The publicly available US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) data requires substantial curation before they can be used appropriately, and applying different strategies for data cleaning and normalization can have material impact on analysis results. We provide a curated and standardized version of FAERS removing duplicate case records, applying standardized vocabularies with drug names mapped to RxNorm concepts and outcomes mapped to SNOMED-CT concepts, and pre-computed summary statistics about drug-outcome relationships for general consumption. This publicly available resource, along with the source code, will accelerate drug safety research by reducing the amount of time spent performing data management on the source FAERS reports, improving the quality of the underlying data, and enabling standardized analyses using common vocabularies. PMID:27193236
Banda, Juan M; Evans, Lee; Vanguri, Rami S; Tatonetti, Nicholas P; Ryan, Patrick B; Shah, Nigam H
Identification of adverse drug reactions (ADRs) during the post-marketing phase is one of the most important goals of drug safety surveillance. Spontaneous reporting systems (SRS) data, which are the mainstay of traditional drug safety surveillance, are used for hypothesis generation and to validate the newer approaches. The publicly available US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) data requires substantial curation before they can be used appropriately, and applying different strategies for data cleaning and normalization can have material impact on analysis results. We provide a curated and standardized version of FAERS removing duplicate case records, applying standardized vocabularies with drug names mapped to RxNorm concepts and outcomes mapped to SNOMED-CT concepts, and pre-computed summary statistics about drug-outcome relationships for general consumption. This publicly available resource, along with the source code, will accelerate drug safety research by reducing the amount of time spent performing data management on the source FAERS reports, improving the quality of the underlying data, and enabling standardized analyses using common vocabularies.
Tym, Joseph E; Mitsopoulos, Costas; Coker, Elizabeth A; Razaz, Parisa; Schierz, Amanda C; Antolin, Albert A; Al-Lazikani, Bissan
canSAR (http://cansar.icr.ac.uk) is a publicly available, multidisciplinary, cancer-focused knowledgebase developed to support cancer translational research and drug discovery. canSAR integrates genomic, protein, pharmacological, drug and chemical data with structural biology, protein networks and druggability data. canSAR is widely used to rapidly access information and help interpret experimental data in a translational and drug discovery context. Here we describe major enhancements to canSAR including new data, improved search and browsing capabilities, new disease and cancer cell line summaries and new and enhanced batch analysis tools.
Liu, Ke; Liu, Yanli; Lau, Johnathan L; Min, Jinrong
Chromatin structure is dynamically modulated by various chromatin modifications, such as histone/DNA methylation and demethylation. We have reviewed histone methyltransferases and methyllysine binders in terms of small molecule screening and drug discovery in the first part of this review series. In this part, we will summarize recent progress in chemical probe and drug discovery of histone demethylases and DNA methyltransferases. Histone demethylation and DNA methylation have attracted a lot of attention regarding their biology and disease implications. Correspondingly, many small molecule compounds have been designed to modulate the activity of histone demethylases and DNA methyltransferases, and some of them have been developed into therapeutic drugs or put into clinical trials.
Stewart, Adam Michael; Gerlai, Robert; Kalueff, Allan V
The high prevalence of brain disorders and the lack of their efficient treatments necessitate improved in-vivo pre-clinical models and tests. The zebrafish (Danio rerio), a vertebrate species with high genetic and physiological homology to humans, is an excellent organism for innovative central nervous system (CNS) drug discovery and small molecule screening. Here, we outline new strategies for developing higher-throughput zebrafish screens to test neuroactive drugs and predict their pharmacological mechanisms. With the growing application of automated 3D phenotyping, machine learning algorithms, movement pattern- and behavior recognition, and multi-animal video-tracking, zebrafish screens are expected to markedly improve CNS drug discovery.
Malhotra, Sony; Thomas, Sherine E; Ochoa Montano, Bernardo; Blundell, Tom L
The use of protein crystallography in structure-guided drug discovery allows identification of potential inhibitor-binding sites and optimisation of interactions of hits and lead compounds with a target protein. An early example of this approach was the use of the structure of HIV protease in designing AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design. Here, we discuss the use of structure-guided target identification and lead optimisation using fragment-based approaches in the development of new antimicrobials for mycobacterial infections.
Stoilova-McPhie, Svetla; Ali, Syed; Laezza, Fernanda
Protein-protein interactions (PPI) are key molecular elements that provide the basis of signaling in virtually all cellular processes. The precision and specificity of these molecular interactions have ignited a strong interest in pursuing PPI surfaces as new targets for drug discovery, especially against ion channels in the central nervous system (CNS) where selectivity and specificity are vital for developing drugs with limited side effects. Ion channels are large transmembrane domain proteins assembled with multiple regulatory proteins binding to the intracellular portion of channels. These macromolecular complexes are difficult to isolate, purify and reconstitute, posing a significant barrier in targeting these PPI for drug discovery purposes. Here, we will provide a short overview of salient features of PPI and discuss successful studies focusing on protein-channel interactions that could inspire new drug discovery campaigns targeting ion channel complexes. PMID:25485305
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.
Neelapu, Nageswara R R; Srimath-Tirumala-Peddinti, Ravi C P K; Nammi, Deepthi; Pasupuleti, Amita C M
The discovery and exploitation of new drug targets is a key focus for both the pharmaceutical industry and academic research. To provide an insight into trends in the exploitation of new drug targets, we have analysed different methods during the past six decades and advances made in drug target discovery. A special focus remains on different methods used for drug target discovery on infectious diseases such as Tuberculosis, Gastritis, Malaria, Trypanosomiasis and Leishmaniasis. We herewith provide a paradigm that is can be used for drug target discovery in the near future.
Vandamme, Drieke; Minke, Benedikt A; Fitzmaurice, William; Kholodenko, Boris N; Kolch, Walter
The pharmaceutical industry is faced with a range of challenges with the ever-escalating costs of drug development and a drying out of drug pipelines. By harnessing advances in -omics technologies and moving away from the standard, reductionist model of drug discovery, there is significant potential to reduce costs and improve efficacy. Embedding systems biology approaches in drug discovery, which seek to investigate underlying molecular mechanisms of potential drug targets in a network context, will reduce attrition rates by earlier target validation and the introduction of novel targets into the currently stagnant market. Systems biology approaches also have the potential to assist in the design of multidrug treatments and repositioning of existing drugs, while stratifying patients to give a greater personalization of medical treatment.
Walker, Michael J A
James Black has many claims to pharmacological fame as the creator of two new classes of drugs (beta-blockers and H2 antihistamines) and as a tireless innovator in drug discovery strategies and analytical procedures. The latter attributes in particular assisted Black in the invention of the prototypes for the two major classes of drugs for which he is best known, propranolol and cimetidine. The clinical impact of these drugs on both morbidity and mortality has been profound. In addition, the application of his analytical approach to drug discovery and pharmacology led others in the field to create many other new classes of drugs. Shortly before he died in 2010, Black wrote a retrospective review of his research career that provides insight into his innovative thinking and career success. This overview affords readers a very personal picture of the man, his ideas and his contributions.
Greggs, Willie M; Clouser, Christine L; Patterson, Steven E; Mansky, Louis M
Feline leukemia virus (FeLV) is a gammaretrovirus that is a significant cause of neoplastic-related disorders affecting cats worldwide. Treatment options for FeLV are limited, associated with serious side effects, and can be cost-prohibitive. The development of drugs used to treat a related retrovirus, human immunodeficiency virus type 1 (HIV-1), has been rapid, leading to the approval of five drug classes. Although structural differences affect the susceptibility of gammaretroviruses to anti-HIV drugs, the similarities in mechanism of replication suggest that some anti-HIV-1 drugs may also inhibit FeLV. This study demonstrates the anti-FeLV activity of four drugs approved by the US FDA (Food and Drug Administration) at non-toxic concentrations. Of these, tenofovir and raltegravir are anti-HIV-1 drugs, while decitabine and gemcitabine are approved to treat myelodysplastic syndromes and pancreatic cancer, respectively, but also have anti-HIV-1 activity in cell culture. Our results indicate that these drugs may be useful for FeLV treatment and should be investigated for mechanism of action and suitability for veterinary use.
Tzvetkov, Mladen V.
Variation in the human genome is a most important cause of variable response to drugs and other xenobiotics. Susceptibility to almost all diseases is determined to some extent by genetic variation. Driven by the advances in molecular biology, pharmacogenetics has evolved within the past 40 years from a niche discipline to a major driving force of clinical pharmacology, and it is currently one of the most actively pursued disciplines in applied biomedical research in general. Nowadays we can assess more than 1,000,000 polymorphisms or the expression of more than 25,000 genes in each participant of a clinical study – at affordable costs. This has not yet significantly changed common therapeutic practices, but a number of physicians are starting to consider polymorphisms, such as those in CYP2C9, CYP2C19, CYP2D6, TPMT and VKORC1, in daily medical practice. More obviously, pharmacogenetics has changed the practices and requirements in preclinical and clinical drug research; large clinical trials without a pharmacogenomic add-on appear to have become the minority. This review is about how the discipline of pharmacogenetics has evolved from the analysis of single proteins to current approaches involving the broad analyses of the entire genome and of all mRNA species or all metabolites and other approaches aimed at trying to understand the entire biological system. Pharmacogenetics and genomics are becoming substantially integrated fields of the profession of clinical pharmacology, and education in the relevant methods, knowledge and concepts form an indispensable part of the clinical pharmacology curriculum and the professional life of pharmacologists from early drug discovery to pharmacovigilance. PMID:18224312
Kathiravan, Muthu K; Khilare, Madhavi M; Nikoomanesh, Kiana; Chothe, Aparna S; Jain, Kishor S
DNA topoisomerases comprise a major aspect of basic cellular biology and are molecular targets for a variety of drugs like antibiotics, antibacterials and anticancer drugs. They act by inhibiting the topoisomerase molecule from relegating DNA strands after cleavage and convert the topoisomerases molecule into a DNA damaging agent. Though drugs of various categories acting through different mechanisms are available for the treatment, there are still problems associated with the currently available drugs. Therefore, Structural biologists, Structural chemists and Medicinal chemists all around the world have been identifying, designing, synthesizing and evaluating a variety of novel bioactive molecules targeting topoisomerase. This review summarizes types of topoisomerase and drug treating each class along with their structural requirement and activity. The emphasis has been laid in particular on the new potential heterocyles and the possible treatments as well as the current ongoing research status in the field of topoisomerase as dual targeting.
Feixas, Ferran; Lindert, Steffen; Sinko, William; McCammon, J. Andrew
The proper understanding of biomolecular recognition mechanisms that take place in a drug target is of paramount importance to improve the efficiency of drug discovery and development. The intrinsic dynamic character of proteins has a strong influence on biomolecular recognition mechanisms and models such as conformational selection have been widely used to account for this dynamic association process. However, conformational changes occurring in the receptor prior and upon association with other molecules are diverse and not obvious to predict when only a few structures of the receptor are available. In view of the prominent role of protein flexibility in ligand binding and its implications for drug discovery, it is of great interest to identify receptor conformations that play a major role in biomolecular recognition before starting rational drug design efforts. In this review, we discuss a number of recent advances in computer-aided drug discovery techniques that have been proposed to incorporate receptor flexibility into structure-based drug design. The allowance for receptor flexibility provided by computational techniques such as molecular dynamics simulations or enhanced sampling techniques helps to improve the accuracy of methods used to estimate binding affinities and, thus, such methods can contribute to the discovery of novel drug leads. PMID:24332165
Hart, Thomas; Xie, Lei
Introduction The conventional one-drug-one-target-one-disease drug discovery process has been less successful in tracking multi-genic, multi-faceted complex diseases. Systems pharmacology has emerged as a new discipline to tackle the current challenges in drug discovery. The goal of systems pharmacology is to transform huge, heterogeneous, and dynamic biological and clinical data into interpretable and actionable mechanistic models for decision making in drug discovery and patient treatment. Thus, big data technology and data science will play an essential role in systems pharmacology. Areas covered This paper critically reviews the impact of three fundamental concepts of data science on systems pharmacology: similarity inference, overfitting avoidance, and disentangling causality from correlation. The authors then discuss recent advances and future directions in applying the three concepts of data science to drug discovery, with a focus on proteome-wide context-specific quantitative drug target deconvolution and personalized adverse drug reaction prediction. Expert opinion Data science will facilitate reducing the complexity of systems pharmacology modeling, detecting hidden correlations between complex data sets, and distinguishing causation from correlation. The power of data science can only be fully realized when integrated with mechanism-based multi-scale modeling that explicitly takes into account the hierarchical organization of biological systems from nucleic acid to proteins, to molecular interaction networks, to cells, to tissues, to patients, and to populations. PMID:26689499
Gilbert, Ian H
Target-based approaches for human African trypanosomiasis (HAT) and related parasites can be a valuable route for drug discovery for these diseases. However, care needs to be taken in selection of both the actual drug target and the chemical matter that is developed. In this article, potential criteria to aid target selection are described. Then the physiochemical properties of typical oral drugs are discussed and compared to those of known anti-parasitics.
Mignani, Serge; Huber, Scot; Tomás, Helena; Rodrigues, João; Majoral, Jean-Pierre
In the pharmaceutical industry the long-term challenge of drug innovation is the key phrase throughout R&D that refers to increasing the output of original drug candidate molecules. To increase R&D productivity, implementation of new and strategic R&D orientations to develop new approaches or systems to identify hits and leads efficiently has taken place and enabled all scientists working in the drug discovery domain to develop innovative medicines for the 21st century.
Vleeshouwers, Vivianne G A A; Rietman, Hendrik; Krenek, Pavel; Champouret, Nicolas; Young, Carolyn; Oh, Sang-Keun; Wang, Miqia; Bouwmeester, Klaas; Vosman, Ben; Visser, Richard G F; Jacobsen, Evert; Govers, Francine; Kamoun, Sophien; Van der Vossen, Edwin A G
Potato is the world's fourth largest food crop yet it continues to endure late blight, a devastating disease caused by the Irish famine pathogen Phytophthora infestans. Breeding broad-spectrum disease resistance (R) genes into potato (Solanum tuberosum) is the best strategy for genetically managing late blight but current approaches are slow and inefficient. We used a repertoire of effector genes predicted computationally from the P. infestans genome to accelerate the identification, functional characterization, and cloning of potentially broad-spectrum R genes. An initial set of 54 effectors containing a signal peptide and a RXLR motif was profiled for activation of innate immunity (avirulence or Avr activity) on wild Solanum species and tentative Avr candidates were identified. The RXLR effector family IpiO induced hypersensitive responses (HR) in S. stoloniferum, S. papita and the more distantly related S. bulbocastanum, the source of the R gene Rpi-blb1. Genetic studies with S. stoloniferum showed cosegregation of resistance to P. infestans and response to IpiO. Transient co-expression of IpiO with Rpi-blb1 in a heterologous Nicotiana benthamiana system identified IpiO as Avr-blb1. A candidate gene approach led to the rapid cloning of S. stoloniferum Rpi-sto1 and S. papita Rpi-pta1, which are functionally equivalent to Rpi-blb1. Our findings indicate that effector genomics enables discovery and functional profiling of late blight R genes and Avr genes at an unprecedented rate and promises to accelerate the engineering of late blight resistant potato varieties.
Vleeshouwers, Vivianne G. A. A.; Rietman, Hendrik; Krenek, Pavel; Champouret, Nicolas; Young, Carolyn; Oh, Sang-Keun; Wang, Miqia; Bouwmeester, Klaas; Vosman, Ben; Visser, Richard G. F.; Jacobsen, Evert; Govers, Francine; Kamoun, Sophien; Van der Vossen, Edwin A. G.
Potato is the world's fourth largest food crop yet it continues to endure late blight, a devastating disease caused by the Irish famine pathogen Phytophthora infestans. Breeding broad-spectrum disease resistance (R) genes into potato (Solanum tuberosum) is the best strategy for genetically managing late blight but current approaches are slow and inefficient. We used a repertoire of effector genes predicted computationally from the P. infestans genome to accelerate the identification, functional characterization, and cloning of potentially broad-spectrum R genes. An initial set of 54 effectors containing a signal peptide and a RXLR motif was profiled for activation of innate immunity (avirulence or Avr activity) on wild Solanum species and tentative Avr candidates were identified. The RXLR effector family IpiO induced hypersensitive responses (HR) in S. stoloniferum, S. papita and the more distantly related S. bulbocastanum, the source of the R gene Rpi-blb1. Genetic studies with S. stoloniferum showed cosegregation of resistance to P. infestans and response to IpiO. Transient co-expression of IpiO with Rpi-blb1 in a heterologous Nicotiana benthamiana system identified IpiO as Avr-blb1. A candidate gene approach led to the rapid cloning of S. stoloniferum Rpi-sto1 and S. papita Rpi-pta1, which are functionally equivalent to Rpi-blb1. Our findings indicate that effector genomics enables discovery and functional profiling of late blight R genes and Avr genes at an unprecedented rate and promises to accelerate the engineering of late blight resistant potato varieties. PMID:18682852
San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul
Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA.
Brown, Jillian R; Crawford, Brett E; Esko, Jeffrey D
Glycans, the carbohydrate chains of glycoproteins, proteoglycans, and glycolipids, represent a relatively unexploited area for drug development compared with other macromolecules. This review describes the major classes of glycans synthesized by animal cells, their mode of assembly, and available inhibitors for blocking their biosynthesis and function. Many of these agents have proven useful for studying the biological activities of glycans in isolated cells, during embryological development, and in physiology. Some are being used to develop drugs for treating metabolic disorders, cancer, and infection, suggesting that glycans are excellent targets for future drug development.
Felder, Christian C
The Strategic Research Institute provided a well-organised 2-day summit that offered presentations and posters on new assay technology, structure-based small-molecule discovery and examples of clinical candidates targeted to G-protein-coupled receptor (GPCR) targets. A wide variety of topics were presented providing recent advances in GPCR target selection, bioassay-enabling technology and medicinal chemistry targeted to GPCR-relevant chemical libraries. GPCRs continue to be an attractive platform for drug discovery.
Harpaz, Rave; DuMouchel, William; Shah, Nigam H.; Madigan, David; Ryan, Patrick; Friedman, Carol
Introduction Discovery of new adverse drug events (ADEs) in the post-approval period is an important goal of the health system. Data mining methods that can transform data into meaningful knowledge to inform patient safety have proven to be essential. New opportunities have emerged to harness data sources that have not been used within the traditional framework. This article provides an overview of recent methodological innovations and data sources used in support of ADE discovery and analysis. PMID:22549283
Gledhill, Robert; Kent, Sarah; Hudson, Brian; Richards, W Graham; Essex, Jonathan W; Frey, Jeremy G
The Schools Malaria Project (http://emalaria.soton.ac.uk/) brings together school students with university researchers in the hunt for a new antimalaria drug. The design challenge being offered to students is to use a distributed drug search and selection system to design potential antimalaria drugs. The system is accessed via a Web interface. This e-science project displays the results of the trials in an accessible manner, giving students an opportunity for discussion and debate both with peers and with the university contacts. The project has been implemented by using distributed computing techniques, spreading computer load over a network of machines that cross institutional boundaries, forming a grid. This provides access to greater computing power and allows a much more complex and detailed formulation of the drug design problem to be tackled for research, teaching, and learning.
Meador, K J
The cognitive effects of antiepileptic drugs (AEDs) are of particular concern to clinicians because these drugs are the primary therapeutic modality for managing epilepsy. In general, the cognitive effects of most AEDs are modest and offset by their benefit in reducing seizures. Nonetheless, the cognitive effects of a particular AED may be clinically significant when treating specific patient populations, such as children and the elderly.
Basavaraj, S; Betageri, Guru V.
Drug discovery and development has become longer and costlier process. The fear of failure and stringent regulatory review process is driving pharmaceutical companies towards “me too” drugs and improved generics (505(b) (2)) fillings. The discontinuance of molecules at late stage clinical trials is common these years. The molecules are withdrawn at various stages of discovery and development process for reasons such as poor ADME properties, lack of efficacy and safety reasons. Hence this review focuses on possible applications of formulation and drug delivery to salvage molecules and improve the drugability. The formulation and drug delivery technologies are suitable for addressing various issues contributing to attrition are discussed in detail. PMID:26579359
Sakakibara, Noriko; Yoshioka, Ryuzo; Matsumoto, Kazuo
In 1970s, the material patent system was introduced in Japan. Since then, many Japanese pharmaceutical companies have endeavored to create original in-house products. From 1980s, many of the innovative products were small molecular drugs and were developed using powerful medicinal-chemical technologies. Among them were antibiotics and effective remedies for the digestive organs and circulatory organs. During this period, Japanese companies were able to launch some blockbuster drugs. At the same time, the pharmaceutical market, which had grown rapidly for two decades, was beginning to level off. From the late 1990s, drug development was slowing down due to the lack of expertise in biotechnology such as genetic engineering. In response to the circumstances, the research and development on biotechnology-based drugs such as antibody drugs have become more dynamic and popular at companies than small molecule drugs. In this paper, the writers reviewed in detail the transitions in drug discovery and development between 1980 and 2010.
Kingston, David G. I.
Natural products continue to provide a diverse and unique source of bioactive lead compounds for drug discovery, but maintaining their continued eminence as source compounds is challenging in the face of the changing face of the pharmaceutical industry and the changing nature of biodiversity prospecting brought about by the Convention of Biodiversity. This review provides an overview of some of these challenges, and suggests ways in which they can be addressed so that natural products research can remain a viable and productive route to drug discovery. Results from International Cooperative Biodiversity Groups (ICBGs) working in Madagascar, Panama, and Suriname are used as examples of what can be achieved when biodiversity conservation is linked to drug discovery. PMID:21138324
Arvidsson, Per I; Sandberg, Kristian; Forsberg-Nilsson, Karin
The Science for Life Laboratory Drug Discovery and Development (SciLifeLab DDD) platform reaches out to Swedish academia with an industry-standard infrastructure for academic drug discovery, supported by earmarked funds from the Swedish government. In this review, we describe the build-up and operation of the platform, and reflect on our first two years of operation, with the ambition to share learnings and best practice with academic drug discovery centers globally. We also discuss how the Swedish Teacher Exemption Law, an internationally unique aspect of the innovation system, has shaped the operation. Furthermore, we address how this investment in infrastructure and expertise can be utilized to facilitate international collaboration between academia and industry in the best interest of those ultimately benefiting the most from translational pharmaceutical research - the patients.
Li, Linfeng; Zhou, Qiong; Voss, Ty C; Quick, Kevin L; LaBarbera, Daniel V
3D organotypic culture models such as organoids and multicellular tumor spheroids (MCTS) are becoming more widely used for drug discovery and toxicology screening. As a result, 3D culture technologies adapted for high-throughput screening formats are prevalent. While a multitude of assays have been reported and validated for high-throughput imaging (HTI) and high-content screening (HCS) for novel drug discovery and toxicology, limited HTI/HCS with large compound libraries have been reported. Nonetheless, 3D HTI instrumentation technology is advancing and this technology is now on the verge of allowing for 3D HCS of thousands of samples. This review focuses on the state-of-the-art high-throughput imaging systems, including hardware and software, and recent literature examples of 3D organotypic culture models employing this technology for drug discovery and toxicology screening.
Subramaniam, Swaminathan; Dugar, Sundeep
Global pharmaceutical companies face an increasingly harsh environment for their primary business of selling medicines. They have to contend with a spiraling decline in the productivity of their R&D programs that is guaranteed to severely diminish their growth prospects. Outsourcing of drug discovery activities to low-cost locations is a growing response to this crisis. However, the upsides to outsourcing are capped by the failure of global pharmaceutical companies to take advantage of the full range of possibilities that this model provides. Companies that radically rethink and transform the way they conduct R&D, such as seeking the benefits of low-cost locations in India and China will be the ones that thrive in this environment. In this article we present our views on how the outsourcing model in drug discovery should go beyond increasing the efficiency of existing drug discovery processes to a fundamental rethink and re-engineering of these processes.
Manallack, David T.; Prankerd, Richard J.; Nassta, Gemma C.; Ursu, Oleg; Oprea, Tudor I.; Chalmers, David K.
Chemogenomics methods seek to characterize the interaction between drugs and biological systems and are an important guide for the selection of screening compounds. The acid/base character of drugs has a profound influence on their affinity for the receptor, on their absorption, distribution, metabolism, excretion and toxicity (ADMET) profile and the way the drug can be formulated. In particular, the charge state of a molecule greatly influences its lipophilicity and biopharmaceutical characteristics. This study investigates the acid/base profile of human small molecule drugs, chemogenomics datasets and screening compounds including a natural products set. We estimate the ionization constants (pKa values) of these compounds and determine the identity of the ionizable functional groups in each set. We find substantial differences in acid/base profiles of the chemogenomic classes. In many cases, these differences can be linked to the nature of the target binding site and the corresponding functional groups needed for recognition of the ligand. Clear differences are also observed between the acid/base characteristics of drugs and screening compounds. For example, the proportion of drugs containing a carboxylic acid was 20%, in stark contrast to a value of 2.4% for the screening set sample. The proportion of aliphatic amines was 27% for drugs and only 3.4% for screening compounds. This suggests that there is a mismatch between commercially available screening compounds and the compounds that are likely to interact with a given chemogenomic target family. Our analysis provides a guide for the selection of screening compounds to better target specific chemogenomic families with regard to the overall balance of acids, bases and pKa distributions. PMID:23303535
Frijters, Raoul; van Vugt, Marianne; Smeets, Ruben; van Schaik, René; de Vlieg, Jacob; Alkema, Wynand
The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs.
Frijters, Raoul; van Vugt, Marianne; Smeets, Ruben; van Schaik, René; de Vlieg, Jacob; Alkema, Wynand
The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs. PMID:20885778
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
Amirkia, Vafa; Heinrich, Michael
Context: In recent decades, natural products have undisputedly played a leading role in the development of novel medicines. Yet, trends in the pharmaceutical industry at the level of research investments indicate that natural product research is neither prioritized nor perceived as fruitful in drug discovery programmes as compared with incremental structural modifications and large volume HTS screening of synthetics. Aim: We seek to understand this phenomenon through insights from highly experienced natural product experts in industry and academia. Method: We conducted a survey including a series of qualitative and quantitative questions related to current insights and prospective developments in natural product drug development. The survey was completed by a cross-section of 52 respondents in industry and academia. Results: One recurrent theme is the dissonance between the perceived high potential of NP as drug leads among individuals and the survey participants' assessment of the overall industry and/or company level strategies and their success. The study's industry and academic respondents did not perceive current discovery efforts as more effective as compared with previous decades, yet industry contacts perceived higher hit rates in HTS efforts as compared with academic respondents. Surprisingly, many industry contacts were highly critical to prevalent company and industry-wide drug discovery strategies indicating a high level of dissatisfaction within the industry. Conclusions: These findings support the notion that there is an increasing gap in perception between the effectiveness of well established, commercially widespread drug discovery strategies between those working in industry and academic experts. This research seeks to shed light on this gap and aid in furthering natural product discovery endeavors through an analysis of current bottlenecks in industry drug discovery programmes. PMID:26578954
Beutler, John A
Natural products have provided chemical leads for the development of many drugs for diverse indications. While most U.S. pharmaceutical firms have reduced or eliminated their in-house natural product groups, there is a renewed interest in this source of new chemical entities. Many of the reasons for the past decline in popularity of natural products are being addressed by the development of new techniques for screening and production. The aim of this unit is to review current strategies and techniques that increase the value of natural products as a source for novel drug candidates.
Flannery, Erika L.; Chatterjee, Arnab K.; Winzeler, Elizabeth A.
Malaria elimination has recently been reinstated as a global health priority but current therapies seem to be insufficient for the task. Elimination efforts require new drug classes that alleviate symptoms, prevent transmission and provide a radical cure. To develop these next generation medicines, public-private partnerships are funding innovative approaches to identify compounds that target multiple parasite species at multiple stages of the parasite lifecycle. Here, we review the cell-, chemistry- and target-based approaches used to discover new drug candidates that are currently in clinical trials or undergoing preclinical testing. PMID:24217412
Poulev, Alexander; O'Neal, Joseph M; Logendra, Sithes; Pouleva, Reneta B; Timeva, Vesa; Garvey, Alison S; Gleba, Doloressa; Jenkins, Ivan S; Halpern, Barbara T; Kneer, Ralf; Cragg, Gordon M; Raskin, Ilya
Plant extracts collected from the wild are important sources for drug discovery. However, these extracts suffer from a lack of reproducible bioactivity and chemical composition caused by the highly inducible, variable, and transitory nature of plant secondary metabolism. Here, we demonstrate that exposing roots of hydroponically grown plants to chemical elicitors selectively and reproducibly induced the production of bioactive compounds, dramatically increased the hit rate, and more than doubled the number of plant species showing in vitro activity against bacteria, fungi, or cancer. Elicitation performed under controlled conditions dramatically improves reliability and efficiency of plant extracts in drug discovery while preserving wild species and their habitats.
Fernandes, Tiago G.; Diogo, Maria Margarida; Clark, Douglas S.; Dordick, Jonathan S.; Cabral, Joaquim M.S.
Cellular microarrays are powerful experimental tools for high-throughput screening of large numbers of test samples. Miniaturization increases assay throughput while reducing reagent consumption and the number of cells required, making these systems attractive for a wide range of assays in drug discovery, toxicology, stem cell research and potentially therapy. Here, we provide an overview of the emerging technologies that can be used to generate cellular microarrays, and we highlight recent significant advances in the field. This emerging and multidisciplinary approach offers new opportunities for the design and control of stem cells in tissue engineering and cellular therapies and promises to expedite drug discovery in the biotechnology and pharmaceutical industries. PMID:19398140
Imperatore, Concetta; Aiello, Anna; D'Aniello, Filomena; Senese, Maria; Menna, Marialuisa
The present review describes research on novel natural antitumor alkaloids isolated from marine invertebrates. The structure, origin, and confirmed cytotoxic activity of more than 130 novel alkaloids belonging to several structural families (indoles, pyrroles, pyrazines, quinolines, and pyridoacridines), together with some of their synthetic analogs, are illustrated. Recent discoveries concerning the current state of the potential and/or development of some of them as new drugs, as well as the current knowledge regarding their modes of action, are also summarized. A special emphasis is given to the role of marine invertebrate alkaloids as an important source of leads for anticancer drug discovery.
Tsui, Vickie; Ortwine, Daniel F; Blaney, Jeffrey M
Computational chemistry/informatics scientists and software engineers in Genentech Small Molecule Drug Discovery collaborate with experimental scientists in a therapeutic project-centric environment. Our mission is to enable and improve pre-clinical drug discovery design and decisions. Our goal is to deliver timely data, analysis, and modeling to our therapeutic project teams using best-in-class software tools. We describe our strategy, the organization of our group, and our approaches to reach this goal. We conclude with a summary of the interdisciplinary skills required for computational scientists and recommendations for their training.
Tsui, Vickie; Ortwine, Daniel F.; Blaney, Jeffrey M.
Computational chemistry/informatics scientists and software engineers in Genentech Small Molecule Drug Discovery collaborate with experimental scientists in a therapeutic project-centric environment. Our mission is to enable and improve pre-clinical drug discovery design and decisions. Our goal is to deliver timely data, analysis, and modeling to our therapeutic project teams using best-in-class software tools. We describe our strategy, the organization of our group, and our approaches to reach this goal. We conclude with a summary of the interdisciplinary skills required for computational scientists and recommendations for their training.
Campo, Brice; Vandal, Omar; Wesche, David L.; Burrows, Jeremy N.
The eradication of malaria will only be possible if effective, well-tolerated medicines kill hypnozoites in vivax and ovale malaria, and thus prevent relapses in patients. Despite progress in the 8-aminoquinoline series, with tafenoquine in Phase III showing clear benefits over primaquine, the drug discovery challenge to identify hypnozoiticidal or hypnozoite-activating compounds has been hampered by the dearth of biological tools and assays, which in turn has been limited by the immense scientific and logistical challenges associated with accessing relevant human tissue and sporozoites. This review summarises the existing drug discovery series and approaches concerning the goal to block relapse. PMID:25891812
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.
The term discovery applies herein to the successful outcome of inquiry in which a significant personal, professional or scholarly breakthrough or insight occurs, and which is individually or socially acknowledged as a key contribution to knowledge. Since discoveries culminate at fixed points in time, discoveries can serve as an outcome metric for…
Liu, Fangkun; Huang, Jing; Ning, Bo; Liu, Zhixiong; Chen, Shen; Zhao, Wei
Patient-derived cell lines and animal models have proven invaluable for the understanding of human intestinal diseases and for drug development although both inherently comprise disadvantages and caveats. Many genetically determined intestinal diseases occur in specific tissue microenvironments that are not adequately modeled by monolayer cell culture. Likewise, animal models incompletely recapitulate the complex pathologies of intestinal diseases of humans and fall short in predicting the effects of candidate drugs. Patient-derived stem cell organoids are new and effective models for the development of novel targeted therapies. With the use of intestinal organoids from patients with inherited diseases, the potency and toxicity of drug candidates can be evaluated better. Moreover, owing to the novel clustered regularly interspaced short palindromic repeats/CRISPR-associated protein-9 genome-editing technologies, researchers can use organoids to precisely modulate human genetic status and identify pathogenesis-related genes of intestinal diseases. Therefore, here we discuss how patient-derived organoids should be grown and how advanced genome-editing tools may be applied to research on modeling of cancer and infectious diseases. We also highlight practical applications of organoids ranging from basic studies to drug screening and precision medicine. PMID:27713700
Brown, Dean G; Lister, Troy; May-Dracka, Tricia L
Natural products have been a rich source of antibacterial drugs for many decades, but investments in this area have declined over the past two decades. The purpose of this review article is to provide a recent survey of new natural product classes and the mechanisms by which they work.
Hanson, C; Cairns, J; Wang, L; Sinha, S
This study integrates gene expression, genotype and drug response data in lymphoblastoid cell lines with transcription factor (TF)-binding sites from ENCODE (Encyclopedia of Genomic Elements) in a novel methodology that elucidates regulatory contexts associated with cytotoxicity. The method, GENMi (Gene Expression iN the Middle), postulates that single-nucleotide polymorphisms within TF-binding sites putatively modulate its regulatory activity, and the resulting variation in gene expression leads to variation in drug response. Analysis of 161 TFs and 24 treatments revealed 334 significantly associated TF–treatment pairs. Investigation of 20 selected pairs yielded literature support for 13 of these associations, often from studies where perturbation of the TF expression changes drug response. Experimental validation of significant GENMi associations in taxanes and anthracyclines across two triple-negative breast cancer cell lines corroborates our findings. The method is shown to be more sensitive than an alternative, genome-wide association study-based approach that does not use gene expression. These results demonstrate the utility of GENMi in identifying TFs that influence drug response and provide a number of candidates for further testing. PMID:26503816
Liu, Fangkun; Huang, Jing; Ning, Bo; Liu, Zhixiong; Chen, Shen; Zhao, Wei
Patient-derived cell lines and animal models have proven invaluable for the understanding of human intestinal diseases and for drug development although both inherently comprise disadvantages and caveats. Many genetically determined intestinal diseases occur in specific tissue microenvironments that are not adequately modeled by monolayer cell culture. Likewise, animal models incompletely recapitulate the complex pathologies of intestinal diseases of humans and fall short in predicting the effects of candidate drugs. Patient-derived stem cell organoids are new and effective models for the development of novel targeted therapies. With the use of intestinal organoids from patients with inherited diseases, the potency and toxicity of drug candidates can be evaluated better. Moreover, owing to the novel clustered regularly interspaced short palindromic repeats/CRISPR-associated protein-9 genome-editing technologies, researchers can use organoids to precisely modulate human genetic status and identify pathogenesis-related genes of intestinal diseases. Therefore, here we discuss how patient-derived organoids should be grown and how advanced genome-editing tools may be applied to research on modeling of cancer and infectious diseases. We also highlight practical applications of organoids ranging from basic studies to drug screening and precision medicine.
Cohen, Philip; Alessi, Dario R
Over the past 15 years protein kinases have become the pharmaceutical industry's most important class of drug target in the field of cancer. Some 20 drugs that target kinases have been approved for clinical use over the past decade, and hundreds more are undergoing clinical trials. However, the recent approval of the first protein kinase inhibitors for the treatment of inflammatory diseases, coupled with an enhanced understanding of the signaling networks that control the immune system, suggests that there will be a surge of interest in this area over the next 10 years. In this connection, we discuss opportunities for targeting protein kinases in the MyD88 signaling network for the development of drugs to treat chronic inflammatory and autoimmune diseases. Activating mutations in protein kinases underlie many other diseases and conditions, and we also discuss why the protein kinases SPAK/OSR1 and LRRK2 have recently become interesting targets for the treatment of hypertension and Parkinson's disease, respectively, and the progress that has been made in developing LRRK2 inhibitors. Finally we suggest that more focus on the identification of inhibitors of kinase activation, rather than kinase activity, may pay dividends in identifying exquisitely specific inhibitors of signal transduction cascades, and we also highlight "pseudo-kinases" as an attractive and unexplored area for drug development that merits much more attention in the years to come.
Prado-Prado, Francisco; Garcia-Mera, Xerardo; Rodriguez-Borges, Jose Enrique; Concu, Riccardo; Perez-Montoto, Lazaro Guillermo; Gonzalez-Diaz, Humberto; Duardo-Sanchez, Aliuska
In recent times, there has been an increased use of Computer-Aided Drug Discovery (CADD) techniques in Medicinal Chemistry as auxiliary tools in drug discovery. Whilst the ultimate goal of Medicinal Chemistry research is for the discovery of new drug candidates, a secondary yet important outcome that results is in the creation of new computational tools. This process is often accompanied by a lack of understanding of the legal aspects related to software and model use, that is, the copyright protection of new medicinal chemistry software and software-mediated discovered products. In the center of picture, which lies in the frontiers of legal, chemistry, and biosciences, we found computational modeling-based drug discovery patents. This article aims to review prominent cases of patents of bio-active organic compounds that involved/protect also computational techniques. We put special emphasis on patents based on Quantitative Structure-Activity Relationships (QSAR) models but we include other techniques too. An overview of relevant international issues on drug patenting is also presented.
Bauer, Armin; Brönstrup, Mark
Covering: up to March 2013. In addition to their prominent role in basic biological and chemical research, natural products are a rich source of commercial products for the pharmaceutical and other industries. Industrial natural product chemistry is of fundamental importance for successful product development, as the vast majority (ca. 80%) of commercial drugs derived from natural products require synthetic efforts, either to enable economical access to bulk material, and/or to optimize drug properties through structural modifications. This review aims to illustrate issues on the pathway from lead to product, and how they have been successfully addressed by modern natural product chemistry. It is focused on natural products of current relevance that are, or are intended to be, used as pharmaceuticals.
Ferrins, Lori; Rahmani, Raphaël; Baell, Jonathan B
Human African trypanosomiasis (HAT) has been neglected for a long time. The most recent drug to treat this disease, eflornithine, was approved by the US FDA in 2000. Current treatments exhibit numerous problematic side effects and are often ineffective against the debilitating CNS resident stage of the disease. Fortunately, several partnerships and initiatives have been formed over the last 20 years in an effort to eradicate HAT, along with a number of other neglected diseases. This has led to an increasing number of foundations and research institutions that are currently working on the development of new drugs for HAT and tools with which to diagnose and treat patients. New biochemical pathways as therapeutic targets are emerging, accompanied by increasing numbers of new antitrypanosomal compound classes. The future looks promising that this collaborative approach will facilitate eagerly awaited breakthroughs in the treatment of HAT.
Sarkar, Aurijit; Kellogg, Glen E.
Hydrophobic interactions are some of the most important interactions in nature. They are the primary driving force in a number of phenomena. This is mostly an entropic effect and can account for a number of biophysical events such as protein-protein or protein-ligand binding that are of immense importance in drug design. The earliest studies on this phenomenon can be dated back to the end of the 19th century when Meyer and Overton independently correlated the hydrophobic nature of gases to their anesthetic potency. Since then, significant progress has been made in this realm of science. This review briefly traces the history of hydrophobicity research along with the theoretical estimation of partition coefficients. Finally, the application of hydrophobicity estimation methods in the field of drug design and protein folding is discussed. PMID:19929828
Ebner, David C; Bialek, Peter; El-Kattan, Ayman F; Ambler, Catherine M; Tu, Meihua
The targeting of drugs to skeletal muscle is an emerging area of research. Driven by the need for new therapies to treat a range of muscle-associated diseases, these strategies aim to provide improved drug exposure at the site of action in skeletal muscle with reduced concentration in other tissues where unwanted side effects could occur. By interacting with muscle-specific cell surface recognition elements, both tissue localization and selective uptake into skeletal muscle cells can be achieved. The design of molecules that are substrates for muscle uptake transporters can provide concentration in m uscle tissue. For example, drug conjugates with carnitine can provide improved muscle uptake via OCTN2 transport. Binding to muscle surface recognition elements followed by endocytosis can allow even large molecules such as antibodies to enter muscle cells. Monoclonal antibody 3E10 demonstrated selective uptake into skeletal muscle in vivo. Hybrid adeno-associated viral vectors have recently shown promise for high skeletal muscle selectivity in gene transfer applications. Delivery technology methods, including electroporation of DNA plasmids, have also been investigated for selective muscle uptake. This review discusses challenges and opportunities for skeletal muscle targeting, highlighting specific examples and areas in need of additional research.
Glicksman, Marcie A.
Introduction Amyotrophic Lateral Sclerosis, also referred to as Lou Gehrig’s disease is characterized by the progressive loss of cells in the brain and spinal cord that leads to debilitation and death in 3–5 years. Only one therapeutic drug, Riluzole, has been approved for ALS and that drug improves survival by 2–3 months. The need for new therapeutics, either that can postpone or slow the progression of the motor deficits and prolong survival, is still a strong unmet medical need. Areas Covered Although there are a number of drugs currently in clinical trials for ALS, this review provides an overview of the most promising biological targets and preclinical strategies that are currently being developed and deployed. The list of targets for ALS was compiled from a variety of websites including: individual companies that have ALS programs, and the author’s experience. Expert Opinion Progress is being made in the identification of possible new therapeutics for ALS with recent efforts in: understanding the genetic causes of the disease, susceptibility factors, and the development of additional preclinical animal models. However, many challenges remain in the identification of new ALS therapeutics including: the use of relevant biomarkers, the need for earlier diagnosis of the disease, and additional animal models. Multiple strategies need to be tested, in the clinic, in order to determine what will be effective in patients. PMID:22646982
Moynie, Lucille; Schnell, Robert; McMahon, Stephen A.; Sandalova, Tatyana; Boulkerou, Wassila Abdelli; Schmidberger, Jason W.; Alphey, Magnus; Cukier, Cyprian; Duthie, Fraser; Kopec, Jolanta; Liu, Huanting; Jacewicz, Agata; Hunter, William N.; Naismith, James H.; Schneider, Gunter
Bacterial infections are increasingly difficult to treat owing to the spread of antibiotic resistance. A major concern is Gram-negative bacteria, for which the discovery of new antimicrobial drugs has been particularly scarce. In an effort to accelerate early steps in drug discovery, the EU-funded AEROPATH project aims to identify novel targets in the opportunistic pathogen Pseudomonas aeruginosa by applying a multidisciplinary approach encompassing target validation, structural characterization, assay development and hit identification from small-molecule libraries. Here, the strategies used for target selection are described and progress in protein production and structure analysis is reported. Of the 102 selected targets, 84 could be produced in soluble form and the de novo structures of 39 proteins have been determined. The crystal structures of eight of these targets, ranging from hypothetical unknown proteins to metabolic enzymes from different functional classes (PA1645, PA1648, PA2169, PA3770, PA4098, PA4485, PA4992 and PA5259), are reported here. The structural information is expected to provide a firm basis for the improvement of hit compounds identified from fragment-based and high-throughput screening campaigns. PMID:23295481
Moynie, Lucille; Schnell, Robert; McMahon, Stephen A; Sandalova, Tatyana; Boulkerou, Wassila Abdelli; Schmidberger, Jason W; Alphey, Magnus; Cukier, Cyprian; Duthie, Fraser; Kopec, Jolanta; Liu, Huanting; Jacewicz, Agata; Hunter, William N; Naismith, James H; Schneider, Gunter
Bacterial infections are increasingly difficult to treat owing to the spread of antibiotic resistance. A major concern is Gram-negative bacteria, for which the discovery of new antimicrobial drugs has been particularly scarce. In an effort to accelerate early steps in drug discovery, the EU-funded AEROPATH project aims to identify novel targets in the opportunistic pathogen Pseudomonas aeruginosa by applying a multidisciplinary approach encompassing target validation, structural characterization, assay development and hit identification from small-molecule libraries. Here, the strategies used for target selection are described and progress in protein production and structure analysis is reported. Of the 102 selected targets, 84 could be produced in soluble form and the de novo structures of 39 proteins have been determined. The crystal structures of eight of these targets, ranging from hypothetical unknown proteins to metabolic enzymes from different functional classes (PA1645, PA1648, PA2169, PA3770, PA4098, PA4485, PA4992 and PA5259), are reported here. The structural information is expected to provide a firm basis for the improvement of hit compounds identified from fragment-based and high-throughput screening campaigns.
Williams, Glyn; Ferenczy, György G; Ulander, Johan; Keserű, György M
Small is beautiful - reducing the size and complexity of chemical starting points for drug design allows better sampling of chemical space, reveals the most energetically important interactions within protein-binding sites and can lead to improvements in the physicochemical properties of the final drug. The impact of fragment-based drug discovery (FBDD) on recent drug discovery projects and our improved knowledge of the structural and thermodynamic details of ligand binding has prompted us to explore the relationships between ligand-binding thermodynamics and FBDD. Information on binding thermodynamics can give insights into the contributions to protein-ligand interactions and could therefore be used to prioritise compounds with a high degree of specificity in forming key interactions.
von Korff, Modest; Sander, Thomas
A new method is introduced to calculate the complexity of organic molecules in drug discovery. The complexity is calculated by taking the number of unique connected subgraphs u as basis c = f(a, b, p, u). With a and b are the number of atoms and bonds, respectively and p is the ratio of covered bonds by redundant fragments. A set of five datasets with 50 molecules each was analyzed. The datasets were compiled from bioactive natural products, approved drugs, highly bioactive molecules, commercially available compounds for high throughput screening and artificial generated molecules. Comparing the median of c for the five datasets showed a significant increase in the following order: commercially available compounds < bioactive molecules < approved drugs < natural products < artificial molecules. With the introduced complexity value c a meaningful figure of merit was developed to assess automatically the complexity of single compounds and compound libraries in drug discovery.
Zhao, Ying; Mu, Xin; Du, Guanhua
Microtubule-stabilizing agents (MSAs) have been highly successful in the treatment of cancer in the past 20years. To date, three classes of MSAs have entered the clinical trial stage or have been approved for clinical anticancer chemotherapy, and more than 10 classes of novel structural MSAs have been derived from natural resources. The microtubule typically contains two MSA-binding sites: the taxoid site and the laulimalide/peloruside site. All defined MSAs are known to bind at either of these sites, with subtle but significant differences. MSAs with different binding sites may produce a synergistic effect. Although having been extensively applied in the clinical setting, paclitaxel and other approved MSAs still pose many challenges such as multidrug resistance, low bioavailability, poor solubility, high toxicity, and low passage through the blood-brain barrier. A variety of studies focus on the structure-activity relationship in order to improve the pharmaceutical properties of these agents. Here, the mechanisms of action, advancements in pharmacological research, and clinical developments of defined MSAs during the past decade are discussed. The latest discovered MSAs are also briefly introduced in this review. The increasing number of natural MSAs indicates the potential discovery of more novel, natural MSAs with different structural bases, which will further promote the development of anticancer chemotherapy.
Evans, William J.
The prevention and treatment of late-life dysfunction are the goals of most geriatricians and should be the primary target for discovery and development of new medicines for elderly people. However, the development of new medicines for elderly people will face a number of challenges that are not seen for other patient populations. The burdens of multiple chronic diseases, low physiological reserve and polypharmacy must result in new clinical trials in frail older people with a high expectation of safety and efficacy. The etiology of functional limitations in elderly people is complex and often ascribed to conditions that escape the traditional definition of disease. While our society urgently needs new treatments that can reduce the burden of physical decline among older persons, guidelines on how these treatments should be developed and tested are currently lacking, in part because a consensus has not yet been achieved regarding the identifiable target diseases. New potential indications included sarcopaenia, anorexia of ageing, frailty, mobility disability and reduced functional capacity secondary to hospitalization. The challenges to conducting clinical trials in the elderly should not offset the great opportunity for the development of new medicines to prevent or reverse age-associated changes in body composition and poor functional capacity in the elderly. PMID:21115538
de Mooij-van Malsen, Annetrude J G; Pjetri, Eneda; Kas, Martien J
Animal studies play a central role in the identification and testing of novel drugs for CNS disorders. In his longstanding career, Berend Olivier has significantly contributed to CNS drug discovery by applying and supporting novel views and methodologies in the fields of behavioral neuroscience, pharmacology, and (epi-) genetics. Here we review and put forward some of these integrated approaches that have led to a productive collaboration and new insights into the genetic and epigenetic regulation of neurobehavioural traits related to psychiatric disorders.
de Mestre, Neville
All common fractions can be written in decimal form. In this Discovery article, the author suggests that teachers ask their students to calculate the decimals by actually doing the divisions themselves, and later on they can use a calculator to check their answers. This article presents a lesson based on the research of Bolt (1982).
Lavé, Thierry; Caruso, Antonello; Parrott, Neil; Walz, Antje
In this review we present ways in which translational PK/PD modeling can address opportunities to enhance probability of success in drug discovery and early development. This is achieved by impacting efficacy and safety-driven attrition rates, through increased focus on the quantitative understanding and modeling of translational PK/PD. Application of the proposed principles early in the discovery and development phases is anticipated to bolster confidence of successfully evaluating proof of mechanism in humans and ultimately improve Phase II success. The present review is centered on the application of predictive modeling and simulation approaches during drug discovery and early development, and more specifically of mechanism-based PK/PD modeling. Case studies are presented, focused on the relevance of M&S contributions to real-world questions and the impact on decision making.
Bald, Dirk; Villellas, Cristina; Lu, Ping; Koul, Anil
Drug-resistant mycobacterial infections are a serious global health challenge, leading to high mortality and socioeconomic burdens in developing countries worldwide. New innovative approaches, from identification of new targets to discovery of novel chemical scaffolds, are urgently needed. Recently, energy metabolism in mycobacteria, in particular the oxidative phosphorylation pathway, has emerged as an object of intense microbiological investigation and as a novel target pathway in drug discovery. New classes of antibacterials interfering with elements of the oxidative phosphorylation pathway are highly active in combating dormant or latent mycobacterial infections, with a promise of shortening tuberculosis chemotherapy. The regulatory approval of the ATP synthase inhibitor bedaquiline and the discovery of Q203, a candidate drug targeting the cytochrome bc1 complex, have highlighted the central importance of this new target pathway. In this review, we discuss key features and potential applications of inhibiting energy metabolism in our quest for discovering potent novel and sterilizing drug combinations for combating tuberculosis. We believe that the combination of drugs targeting elements of the oxidative phosphorylation pathway can lead to a completely new regimen for drug-susceptible and multidrug-resistant tuberculosis.
Haefliger, Benjamin; Prochazka, Laura; Angelici, Bartolomeo; Benenson, Yaakov
Development of drug discovery assays that combine high content with throughput is challenging. Information-processing gene networks can address this challenge by integrating multiple potential targets of drug candidates' activities into a small number of informative readouts, reporting simultaneously on specific and non-specific effects. Here we show a family of networks implementing this concept in a cell-based drug discovery assay for miRNA drug targets. The networks comprise multiple modules reporting on specific effects towards an intended miRNA target, together with non-specific effects on gene expression, off-target miRNAs and RNA interference pathway. We validate the assays using known perturbations of on- and off-target miRNAs, and evaluate an ∼700 compound library in an automated screen with a follow-up on specific and non-specific hits. We further customize and validate assays for additional drug targets and non-specific inputs. Our study offers a novel framework for precision drug discovery assays applicable to diverse target families. PMID:26880188
Jana, S; Mandlekar, S; Marathe, P
The prodrug design is a versatile, powerful method that can be applied to a wide range of parent drug molecules, administration routes, and formulations. Clinically, the majority of prodrugs are used with the aim of enhancing drug permeation by increasing lipophilicity, or by improving aqueous solubility. Prodrug design may improve the bioavailability of parent molecule, and thus can be integrated into the iterative process of lead optimization, rather than employing it as a post-hoc approach. The purpose of this review is to provide an update of advances and progress in the knowledge of current strategic approaches of prodrug design, along with their real-world utility in drug discovery and development. The review covers the type of prodrugs and functional groups that are amenable to prodrug design. Various prodrug approaches for improving oral drug delivery are discussed, with numerous examples of marketed prodrugs, including improved aqueous solubility, improved lipophilicity, transporter-mediated absorption, and prodrug design to achieve site-specific delivery. Tools employed for prodrug screening, and specific challenges in prodrug research and development are also elaborated. This article is intended to encourage discovery scientists to be creative and consider a rationally designed prodrug approach during the lead optimization phase of drug discovery programs, when the structure activity relationship (SAR) for the drug target is incompatible with pharmacokinetic or biopharmaceutical objectives.
It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415
Villellas, Cristina; Lu, Ping
ABSTRACT Drug-resistant mycobacterial infections are a serious global health challenge, leading to high mortality and socioeconomic burdens in developing countries worldwide. New innovative approaches, from identification of new targets to discovery of novel chemical scaffolds, are urgently needed. Recently, energy metabolism in mycobacteria, in particular the oxidative phosphorylation pathway, has emerged as an object of intense microbiological investigation and as a novel target pathway in drug discovery. New classes of antibacterials interfering with elements of the oxidative phosphorylation pathway are highly active in combating dormant or latent mycobacterial infections, with a promise of shortening tuberculosis chemotherapy. The regulatory approval of the ATP synthase inhibitor bedaquiline and the discovery of Q203, a candidate drug targeting the cytochrome bc1 complex, have highlighted the central importance of this new target pathway. In this review, we discuss key features and potential applications of inhibiting energy metabolism in our quest for discovering potent novel and sterilizing drug combinations for combating tuberculosis. We believe that the combination of drugs targeting elements of the oxidative phosphorylation pathway can lead to a completely new regimen for drug-susceptible and multidrug-resistant tuberculosis.
Saeidnia, Soodabeh; Gohari, Ahmad R; Manayi, Azadeh
Pharmacognosy is a science, which study natural products as a source of new drug leads and effective drug development. Rational and economic search for novel lead structures could maximize the speed of drug discovery by using powerful high technology methods. Reverse pharmacognosy, a complementary to pharmacognosy, couples the high throughput screening (HTS), virtual screening and databases along with the knowledge of traditional medicines. These strategies lead to identification of numerous in vitro active and selective hits enhancing the speed of drug discovery from natural sources. Besides, reverse pharmacology is a target base drug discovery approach; in the first step, a hypothesis is made that the alteration of specific protein activity will produce beneficial curative effects. Both, reverse pharmacognosy and reverse pharmacology take advantages of high technology methods to accomplish their particular purposes. Moreover, reverse pharmacognosy effectively utilize traditional medicines and natural products as promising sources to provide new drug leads as well as promote the rational use of them by using valuable information like protein structure databases and chemical libraries which prepare pharmacological profile of traditional medicine, plant extract or natural compounds.
Qian Cutrone, Jingfang Jenny; Huang, Xiaohua Stella; Kozlowski, Edward S; Bao, Ye; Wang, Yingzi; Poronsky, Christopher S; Drexler, Dieter M; Tymiak, Adrienne A
Synthetic macrocyclic peptides with natural and unnatural amino acids have gained considerable attention from a number of pharmaceutical/biopharmaceutical companies in recent years as a promising approach to drug discovery, particularly for targets involving protein-protein or protein-peptide interactions. Analytical scientists charged with characterizing these leads face multiple challenges including dealing with a class of complex molecules with the potential for multiple isomers and variable charge states and no established standards for acceptable analytical characterization of materials used in drug discovery. In addition, due to the lack of intermediate purification during solid phase peptide synthesis, the final products usually contain a complex profile of impurities. In this paper, practical analytical strategies and methodologies were developed to address these challenges, including a tiered approach to assessing the purity of macrocyclic peptides at different stages of drug discovery. Our results also showed that successful progression and characterization of a new drug discovery modality benefited from active analytical engagement, focusing on fit-for-purpose analyses and leveraging a broad palette of analytical technologies and resources.
Cold Spring Harbor Laboratory Scholarship ($1500), Cold Spring Harbor Laboratory...Yeast Genetics Course, Cold Spring Harbor , New York, July 22-Aug. 11, 2003 Keystone Symposia travel scholarship ($1000), New Advances in Drug Discovery...Chemotherapeutics, Geneva, Switzerland, Sept. 28-Oct. 1, 2004 Courses Cold Spring Harbor Laboratory Yeast Genetics Course, Cold Spring Harbor , New
Schenk, Dale; Carrillo, Maria C; Trojanowski, John Q
The Alzheimer's Association Research Roundtable, a consortium of Association senior scientists and leaders from pharmaceutical, biotech, and imaging companies, met to discuss strategies for developing novel therapeutics for the treatment of Alzheimer's disease (AD). The goal of the meeting was to address, primarily, strategies that do not hinge on directly modulating levels of beta-amyloid. The identification of beta-amyloid as the major constituent of senile plaques and the subsequent discovery that familial AD can be caused by mutations in either the beta-amyloid precursor protein or presenilins, proteases that cleaves beta-amyloid from its precursor, has spawned numerous therapeutic strategies for treating AD. These include passive and active vaccines for clearing beta-amyloid from the brain and the development of small molecule inhibitors of beta- and gamma-secretases that can attenuate the production of beta-amyloid. But the field recognizes that there is more to AD than beta-amyloid alone. What role do neurofibrillary tangles play in the disease, for example, and how are they influenced by beta-amyloid? What lies upstream of beta-amyloid production in the sporadic AD brain, and how do apolipoproteins and cholesterol influence disease progression? Are there environmental or behavioral factors that contribute to the initiation or progression of sporadic AD? Because of the complexity of AD, the field is continually looking to other therapeutic strategies that may complement or substitute for therapies that target beta-amyloid. This roundtable meeting was charged with discussing and evaluating some of those strategies.