Efficient Drug Discovery Research Articles

Targeting α-synuclein oligomers by protein-fragment complementation for drug discovery in synucleinopathies

Objective: Reducing the burden of α-synuclein oligomeric species represents a promising approach for disease-modifying therapies against synucleinopathies such as Parkinson’s disease and dementia with Lewy bodies. However, the lack of efficient drug discovery strategies that specifically target α-synuclein oligomers has been a limitation to drug discovery programs.Research design and methods: Here we describe an innovative strategy that harnesses the power of bimolecular protein-fragment complementation to monitor synuclein–synuclein interactions. We have developed two robust models to monitor α-synuclein oligomerization by generating novel stable cell lines expressing α-synuclein fusion proteins for either fluorescent or bioluminescent protein-fragment complementation under the tetracycline-controlled transcriptional activation system.Main outcome measures: A pilot screen was performed resulting in the identification of two potential hits, a p38 MAPK inhibitor and a casein kinase 2 inhibitor, thereby demonstrating the suitability of our protein-fragment complementation assay for the measurement of α-synuclein oligomerization in living cells at high throughput.Conclusions: The application of the strategy described herein to monitor α-synuclein oligomer formation in living cells with high throughput will facilitate drug discovery efforts for disease-modifying therapies against synucleinopathies and other proteinopathies.

A simple and reliable approach for assessing anticancer activity in vitro.

Cancer patients need better anticancer drugs, and medicinal chemistry can play a critical role in the discovery of these drugs. For an efficient drug discovery process, chemists working on the synthesis of potential anticancer agents need to use reliable screening methods. These methods should not only detect the compounds with the highest therapeutic potential, but should also predict whether such potential is high enough to deserve additional attention. Unfortunately, the current strategies for assessing anticancer activity in vitro are unable to do this reliably. This review article analyzes these strategies and describes an alternative screening approach. It is based on establishing suitable experimental conditions to detect compounds that improve the selective cytotoxicity of the drugs used in cancer therapy. This patient-oriented approach is easy to implement and may help medicinal chemists, and other researchers involved in cancer drug discovery, assess in vitro anticancer activity more reliably.

Label-free measurements of reaction kinetics using a droplet-based optofluidic device.

Label-free measurements of the reaction kinetics of a small sample volume are essential for efficient drug discovery, requiring methods and systems that are rapid, accurate, and cost-effective. Herein, we present an integrated optofluidic system for label-free characterization of reactions in a nanoliter reagent volume. This system contains a droplet-based microfluidic sampling section and an optical fiber-based spectroscopy detection section. By manipulating droplets containing reagents at certain concentrations at different times, quantifiable measurements via absorption spectroscopy can be made in a simple, sensitive, and high-throughput manner. We have demonstrated our system's capability by performing potency (IC50) assays of an inhibitor in a TEM-1 β-lactamase (enzyme) and nitrocefin (substrate) system. This integrated platform can potentially provide an automated, label-free, and low-cost method for many other assays of reaction kinetics.

Advantages of crystallographic fragment screening: Functional and mechanistic insights from a powerful platform for efficient drug discovery

X-ray crystallography has been an under-appreciated screening tool for fragment-based drug discovery due to the perception of low throughput and technical difficulty. Investigators in industry and academia have overcome these challenges by taking advantage of key factors that contribute to a successful crystallographic screening campaign. Efficient cocktail design and soaking methodologies have evolved to maximize throughput while minimizing false positives/negatives. In addition, technical improvements at synchrotron beamlines have dramatically increased data collection rates thus enabling screening on a timescale comparable to other techniques. The combination of available resources and efficient experimental design has resulted in many successful crystallographic screening campaigns. The three-dimensional crystal structure of the bound fragment complexed to its target, a direct result of the screening effort, enables structure-based drug design while revealing insights regarding protein dynamics and function not readily obtained through other experimental approaches. Furthermore, this “chemical interrogation” of the target protein crystals can lead to the identification of useful reagents for improving diffraction resolution or compound solubility.

Drug discovery in renal disease—towards a more efficient framework

The time and cost involved in bringing new drugs to the market hamper their approval. This problem is especially apparent in the case of renal diseases. Efficient drug research requires an a priori understanding of disease pathophysiology, target validation, rational and efficient drug discovery strategies and early testing of the physiological and pharmacological effects of the new agent in humans. Drug development initiated by academia benefits from international research networks and relies on internationally acceptable high-quality nonclinical data packages and bulk investigational drugs. Academics should, therefore, better understand pharmaceutical practice regulations and novel, efficient drug-development strategies. Many researchers remain unfamiliar with these areas and should collaborate with regulatory authorities to discover and validate surrogate markers for use in drug development, and to efficiently and effectively maximize the benefits and minimize the adverse effects of new drugs. The Japanese government and regulatory authorities have implemented a framework to encourage such collaborations; extension of this framework beyond its current reach is envisaged.

Seamless Integration of Dose‐Response Screening and Flow Chemistry: Efficient Generation of Structure–Activity Relationship Data of β‐Secretase (BACE1) Inhibitors

Drug discovery is a multifaceted endeavor encompassing as its core element thegeneration of structure-activity relationship (SAR) data by repeated chemical synthesis and biological testing of tailored molecules.Herein, we report on the developmentof a flow-based biochemical assay and its seamless integration into a fully automated system comprising flow chemical synthesis, purification and in-line quantification of compound concentration. This novel synthesis-screening platform enables to obtain SAR data onb-secretase (BACE1) inhibitors at an unprecedented cycle time of only 1 h instead of several days. Full integration and automation ofindustrial processes have always led to productivity gains and cost reductions, and this work demonstrates how applying these concepts to SAR generation may lead to a more efficient drug discovery process.

High-Throughput Screening Normalized to Biological Response: Application to Antiviral Drug Discovery

The process of conducting cell-based phenotypic screens can result in data sets from small libraries or portions of large libraries, making accurate hit picking from multiple data sets important for efficient drug discovery. Here, we describe a screen design and data analysis approach that allow for normalization not only between quadrants and plates but also between screens or batches in a robust, quantitative fashion, enabling hit selection from multiple data sets. We independently screened the MicroSource Spectrum and NCI Diversity Set II libraries using a cell-based phenotypic high-throughput screening (HTS) assay that uses an interferon-stimulated response element (ISRE)–driven luciferase-reporter assay to identify interferon (IFN) signal enhancers. Inclusion of a per-plate, per-quadrant IFN dose-response standard curve enabled conversion of ISRE activity to effective IFN concentrations. We identified 45 hits based on a combined z score ≥2.5 from the two libraries, and 25 of 35 available hits were validated in a compound concentration-response assay when tested using fresh compound. The results provide a basis for further analysis of chemical structure in relation to biological function. Together, the results establish an HTS method that can be extended to screening for any class of compounds that influence a quantifiable biological response for which a standard is available.

Multitarget strategy of traditional Chinese medicine in treatment of Alzheimer's disease

critical brain regions is considered to be a causative factor in the cognitive decline and neuronal degeneration associated with Alzheimer’s disease (AD). Thus, reducing levels of toxic A b species by inhibiting BACE may be a viable therapeutic strategy for the treatment of AD. Effectively selecting BACE inhibitors for in vivo profiling requires high confidence in the translatability of in vitro potency. Human iPS-derived neurons, which more closely represent human neurons, have been proposed to be a superior cellular model for translating in vitro potency to in vivo (and later clinical) efficacy. Methods: BACE inhibitors representing 3 chemical series were chosen for profiling in a soluble enzyme assay, an APP over-expressing human H4 neuroglioma cell line, a rodent primary neuronal culture, and in human iPS-derived neurons. Our human iPS line was derived from adult non-diseased fibroblasts that were reprogrammed into GABAergic neurons. IC50 correlations for A b lowering were built to compare potency across these assays. Additionally, wild-type 129/SVEmicewere dosed with several of these BACE inhibitors to establish the in vivo brain IC50 for A b. For all assays, in vitro -toin vivo correlations (IVIVCs) of in vitro IC50 values and in vivo IC50 values were generated.Results:We report a high correlation in BACE inhibitor potency between all the in vitro assays examined, including the iPS-derived neurons. Additionally, IVIVCs for the various in vitro assays described translate well to in vivo rodent efficacy. Conclusions: Selecting appropriate chemical matter for in vivo profiling is essential for efficient drug discovery. While the non-diseased human iPS-derived neurons that we tested are more representative of human neurons than the other assay models examined, they do not provide any distinct advantage in translating in vitro potency to in vivo efficacy and thus do not appear to represent a superior translatable cellular model for screening. It remains to be seen if iPSderived neurons from AD patients offer any advantage in screening for Alzheimer’s disease therapeutics.

A Toolbox of Fluorescence Microscopic Approaches Reveals Dynamics and Assembly of a Membrane-Associated Protein

A Toolbox of Fluorescence Microscopic Approaches Reveals Dynamics and Assembly of a Membrane-Associated Protein

Abstract 5526: Mass-action law algorithm-based computer simulation for efficient and econo-green cancer drug discovery and development.

Abstract Physico-chemical principle of the mass-action law algorithm (MALA) is the basis for systematic pharmacodynamics (PD) that leads to general median-effect equation (MEE) for single entity effect and the combination index equation (CIE) for multiple entity interactions (Chou TC, Pharmacol. Rev. 58: 621-681, 2006; Free web access: http://pharmrev.aspetjournals.org/content/58/3/621). “Median” is the common-link and universal reference point for single and multiple entities and for 1st-order and higher-order dynamics. Median is also the harmonic mean of kinetic constants where the harmony is the state of pure non-competitiveness [Chou, Nature Precedings (npre.2008.2064-2). Available free at http://precedings.nature.com/documents/2064/version/2]. Based on MEE, all dose-effect curves whether hyperbolic or sigmoidal, weak or strong, 1st-order or higher-order, in vitro or in vivo, can be linearlized by the median-effect plot with small number of data points in small size experiments (Chou, J. Theor. Biol. 59: 253-276, 1976; Pharmacol. Rev. .ibid). Based on CIE, CI<1, =1, and >1 quantitatively indicates synergism, additive effect, and antagonism, respectively (Chou & Talalay, Adv. Enz. Regul. 22: 27-55, 1984; Cancer Res. 70: 440-446, 2011). Thus. MEE is the common denominator for simple and complex bio-systems in vitro, in animal and in clinics. Computerized simulation of MEE or CIE can take <1 second, and the graphics can be drawn automatically (CompuSyn, www.combosyn.com, Free download). Applying this theory in this author's laboratory (personnel < 5 for decades) has published 253 articles that have been cited 13,749 times in over 523 different biomedical journals with h-index of 55 (Thomson Reuters Web of Science, www.researcherid.com/rid/B-4111-2009) along with 30 US patents. Thus, MALA-PD theory is the common denominator for integrating complex bio-systems and its computerized simulation have proven to lead to efficient, quantitative and econo-green bio-research and new drug discovery and development as illustrated in Chou, Integr. Biol. 3: 548-559, 2011; DOI: 10.1039/c0ib00130a and in Am. J. Cancer Res. 1(7): 925-954, 2011, Free web access: www.ajcr.us. Citation Format: Ting-Chao Chou. Mass-action law algorithm-based computer simulation for efficient and econo-green cancer drug discovery and development. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5526. doi:10.1158/1538-7445.AM2013-5526 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.

Introducing the 2013 JALA Ten.

Introducing the 2013 JALA Ten.

NIMH Tries to Jumpstart Drug Innovations

NIMH Tries to Jumpstart Drug Innovations

Strategy and Collaboration between Medicinal Chemists and Pharmaceutical Scientists for Drug Delivery Systems

In order to successfully apply drug delivery systems (DDS) to new chemical entities (NCEs), collaboration between medicinal chemists and formulation scientists is critical for efficient drug discovery. Formulation scientists have to use 'language' that medicinal chemists understand to help promote mutual understanding, and medicinal chemists and formulation scientists have to set up strategies to use suitable DDS technologies at the discovery phase of the programmes to ensure successful transfer into the development phase. In this review, strategies of solubilisation formulation for oral delivery, inhalation delivery, nasal delivery and bioconjugation are all discussed. For example, for oral drug delivery, multiple initiatives can be proposed to improve the process to select an optimal delivery option for an NCE. From a technical perspective, formulation scientists have to explain the scope and limitations of formulations as some DDS technologies might be applicable only to limited chemical spaces. Other limitations could be the administered dose and, cost, time and resources for formulation development and manufacturing. Since DDS selection is best placed as part of lead-optimisation, formulation scientists need to be involved in discovery projects at lead selection and optimisation stages. The key to success in their collaboration is to facilitate communication between these two areas of expertise at both a strategic and scientific level. Also, it would be beneficial for medicinal chemists and formulation scientists to set common goals to improve the process of collaboration and build long term partnerships to improve DDS.

FDA approved drugs complexed to their targets: evaluating pose prediction accuracy of docking protocols

Efficient drug discovery programs can be designed by utilizing existing pools of knowledge from the already approved drugs. This can be achieved in one way by repositioning of drugs approved for some indications to newer indications. Complex of drug to its target gives fundamental insight into molecular recognition and a clear understanding of putative binding site. Five popular docking protocols, Glide, Gold, FlexX, Cdocker and LigandFit have been evaluated on a dataset of 199 FDA approved drug-target complexes for their accuracy in predicting the experimental pose. Performance for all the protocols is assessed at default settings, with root mean square deviation (RMSD) between the experimental ligand pose and the docked pose of less than 2.0Å as the success criteria in predicting the pose. Glide (38.7%) is found to be the most accurate in top ranked pose and Cdocker (58.8%) in top RMSD pose. Ligand flexibility is a major bottleneck in failure of docking protocols to correctly predict the pose. Resolution of the crystal structure shows an inverse relationship with the performance of docking protocol. All the protocols perform optimally when a balanced type of hydrophilic and hydrophobic interaction or dominant hydrophilic interaction exists. Overall in 16 different target classes, hydrophobic interactions dominate in the binding site and maximum success is achieved for all the docking protocols in nuclear hormone receptor class while performance for the rest of the classes varied based on individual protocol.

Using Novel Descriptor Accounting for Ligand–Receptor Interactions To Define and Visually Explore Biologically Relevant Chemical Space

The definition and pragmatic implementation of biologically relevant chemical space is critical in addressing navigation strategies in the overlapping regions where chemistry and therapeutically relevant targets reside and, therefore, also key to performing an efficient drug discovery project. Here, we describe the development and implementation of a simple and robust method for representing biologically relevant chemical space as a general reference according to current knowledge, independently of any reference space, and analyzing chemical structures accordingly. Underlying our method is the generation of a novel descriptor (LiRIf) that converts structural information into a one-dimensional string accounting for the plausible ligand-receptor interactions as well as for topological information. Capitalizing on ligand-receptor interactions as a descriptor enables the clustering, profiling, and comparison of libraries of compounds from a chemical biology and medicinal chemistry perspective. In addition, as a case study, R-groups analysis is performed to identify the most populated ligand-receptor interactions according to different target families (GPCR, kinases, etc.), as well as to evaluate the coverage of biologically relevant chemical space by structures annotated in different databases (ChEMBL, Glida, etc.).

Induced pluripotent stem cell research: A revolutionary approach to face the challenges in drug screening

Discovery of induced pluripotent stem (iPS) cells in 2006 provided a new path for cell transplantation and drug screening. The iPS cells are stem cells derived from somatic cells that have been genetically reprogrammed into a pluripotent state. Similar to embryonic stem (ES) cells, iPS cells are capable of differentiating into three germ layers, eliminating some of the hurdles in ES cell technology. Further progress and advances in iPS cell technology, from viral to non-viral systems and from integrating to non-integrating approaches of foreign genes into the host genome, have enhanced the existing technology, making it more feasible for clinical applications. In particular, advances in iPS cell technology should enable autologous transplantation and more efficient drug discovery. Cell transplantation may lead to improved treatments for various diseases, including neurological, endocrine, and hepatic diseases. In studies on drug discovery, iPS cells generated from patient-derived somatic cells could be differentiated into specific cells expressing specific phenotypes, which could then be used as disease models. Thus, iPS cells can be helpful in understanding the mechanisms of disease progression and in cell-based efficient drug screening. Here, we summarize the history and progress of iPS cell technology, provide support for the growing interest in iPS cell applications with emphasis on practical uses in cell-based drug screening, and discuss some challenges faced in the use of this technology.

Functional characterization of drug-protein interactions network

Understanding the molecular mechanism that govern drug protein interactions is essential for efficient drug design. The progress in drug development is very slow compared to the rising variation in human genomes and the discovery of new diseases. Thus the need to have more efficient and effective drug discovery pipelines is becoming essential. In this paper, we study and analyze the relationships between drugs and proteins that they target. We consider some properties of the proteins that can be used to give weight to protein-protein relationships. We aim to identify protein properties that might guide the drug to proteins. Amino acid enrichment in target clusters is analyzed to assess if certain drugs prefer particular amino acids. The correlation between the net charge of the drug with the amino acids in the target protein is studies as well. Moreover, characterizing the functional components in drug target clusters is necessary to find drug preference. Sequence motifs and domains, post-translational modification and biological pathways of target proteins are analyzed to understand drug preference. This characterizes the drug target proteins from sequence and functional angles. Finally, we realized the importance of the social network model in analyzing any problem that can be modeled as a network. Fortunately, the problem tackled in this paper fits well the network requirement of the social network model. Hence, we analyze the correlations using the social network model where actors are drugs and proteins; our aim is to analyze the relations between drugs and proteins by benefiting from the rich metrics developed to analyze social networks. In this paper, we briefly mention the social network technique in order to demonstrate its applicability which will be detailed in a future publication.

In VivoChemical Screening for Modulators of Hematopoiesis and Hematological Diseases

In vivo chemical screening is a broadly applicable approach not only for dissecting genetic pathways governing hematopoiesis and hematological diseases, but also for finding critical components in those pathways that may be pharmacologically modulated. Both high-throughput chemical screening and facile detection of blood-cell-related phenotypes are feasible in embryonic/larval zebrafish. Two recent studies utilizing phenotypic chemical screens in zebrafish have identified several compounds that promote hematopoietic stem cell formation and reverse the hematopoietic phenotypes of a leukemia oncogene, respectively. These studies illustrate efficient drug discovery processes in zebrafish and reveal novel biological roles of prostaglandin E2 in hematopoietic and leukemia stem cells. Furthermore, the compounds discovered in zebrafish screens have become promising therapeutic candidates against leukemia and included in a clinical trial for enhancing hematopoietic stem cells during hematopoietic cell transplantation.

Editorial [Hot Topic: The Challenge of Viral Encephalitis: From Etiological Diagnosis to Efficient Antiviral Drug Discovery (Guest Editor: Laurent Dacheux)

Editorial [Hot Topic: The Challenge of Viral Encephalitis: From Etiological Diagnosis to Efficient Antiviral Drug Discovery (Guest Editor: Laurent Dacheux)

Profiling and Trend Analysis of Food Effects on Oral Drug Absorption Considering Micelle Interaction and Solubilization by Bile Micelles

Correlation analysis between food effects on oral drug absorption (food effect) and physicochemical properties is important for efficient drug discovery and contributes to drug design. This study focused on micelle binding and solubilization considering bile micelles in the intestinal fluid. Profiling using about 40 launched drugs demonstrated that those in a high solubilization area (area 1) tended to have a positive food effect, and that drugs exhibiting negative/no food effect tended to coexist in a no/low solubilization area (area 2). In area 1, the solubilization effect by bile micelles was demonstrated quantitatively as an important factor that indicates a positive food effect. In area 2, the relative and quantitative relationships among the membrane permeation rate, dissolution rate, micelle binding and food effect could be clarified by simulation. The improvement of membrane permeability and the suppression of micelle binding are considered to be required to avoid a negative food effect. In conclusion, important factors contributing to the food effect were clarified relatively and quantitatively. Data generated from this profiling may be beneficial to find a solution for negative food effects. Furthermore, this risk assessment of food effects is considered to be a useful tool in rational drug design for drug discovery.