Virtual screening in structure-based drug discovery

Recent advances in structure determination and computational methods have encouraged the development of structure-based virtual screening. Here we survey progress in the field and review the most recent methods, validation experiments and real applications, including an in-house example of hit identification for the oncology target Hsp90. These results provide a basis for discussing the current state of structure-based virtual screening and to outline the developments that are expected to have a major impact in the near future.     

High-throughput screening technologies for drug glucuronidation profiling

A significant number of endogenous and exogenous compounds, including many therapeutic agents, are metabolized in humans via glucuronidation, catalysed by uridine diphosphoglucuronosyltransferases (UGTs). The study of the UGTs is a growing field of research, with constantly accumulated and updated information regarding UGT structure, purification, substrate specificity and inhibition, including clinically relevant drug interactions. Development of reliable UGT assays for the assessment of individual isoform substrate specificity and for the discovery of novel isoform-specific substrates and inhibitors is crucial for understanding the function and regulation of the UGT enzyme family and its clinical and pharmacological relevance. High-throughput screening (HTS) is a powerful technology used to search for novel substrates and inhibitors for a wide variety of targets. However, application of HTS in the context of UGTs is complicated because of the poor stability, low levels of expression, low affinity and broad substrate specificity of the enzymes, combined with difficulties in obtaining individual UGT isoforms in purified format, and insufficient information regarding isoform-specific substrates and inhibitors. This review examines the current status of HTS assays used in the search for novel UGT substrates and inhibitors, emphasizing advancements and challenges in HTS technologies for drug glucuronidation profiling, and discusses possible avenues for future advancement of the field.     

High-throughput screening technologies for ion channel drug discovery

Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite their relevance in diseases and the variety of physiological functions they are involved in, ion channels still remain underexploited as drug targets. This, to a large extent, is attributed to the absence of screening technologies that ensure both the quality and the throughput of data. However, an increasing number of assays and technologies have evolved rapidly in the past decades. In this review, we summarized the currently available high-throughput screening technologies in ion channel drug discovery.     

Novel approaches to glioma drug design and drug screening

Introduction: Gliomas are considered the most malignant form of brain tumors, and ranked among the most aggressive human cancers. Despite advance standard therapy the prognosis for patients with gliomas remains poor. Chemotherapy has played an important role as an adjuvant in treating gliomas. The efficacy of the chemotherapeutic drug is limited due to poor drug delivery and the inherent chemo- and radio-resistance. Challenges of the brain cancer therapy in clinical settings are; i) to overcome the chemo- and radio-resistance, ii) to improve drug delivery to tumors and iii) the development of effective drug screening procedures.

Areas covered: In this review, the authors discuss clinically important chemotherapeutic agents used for treating malignant gliomas along with novel drug design approaches. The authors, furthermore, discuss the in vitro and in vivo drug screening procedures for the development of novel drug candidates.

Expert opinion: The development of novel and highly potent chemotherapeutic agents for both glioma and glioma stem cells (GSCs) is highly important for future brain cancer research. Thus, research efforts should be directed towards developing innovative molecularly targeted antiglioma agents in order to reduce the toxicity and drug resistance which are associated with current forms of therapy. Development of novel pre-clinical drug screening procedures is also very critical for the overall success of brain cancer therapies in clinical settings.     

Thermodynamic studies for drug design and screening

INTRODUCTION: A key part of drug design and development is the optimization of molecular interactions between an engineered drug candidate and its binding target. Thermodynamic characterization provides information about the balance of energetic forces driving binding interactions and is essential for understanding and optimizing molecular interactions. AREAS COVERED: This review discusses the information that can be obtained from thermodynamic measurements and how this can be applied to the drug development process. Current approaches for the measurement and optimization of thermodynamic parameters are presented, specifically higher throughput and calorimetric methods. Relevant literature for this review was identified in part by bibliographic searches for the period 2004 - 2011 using the Science Citation Index and PUBMED and the keywords listed below. EXPERT OPINION: The most effective drug design and development platform comes from an integrated process utilizing all available information from structural, thermodynamic and biological studies. Continuing evolution in our understanding of the energetic basis of molecular interactions and advances in thermodynamic methods for widespread application are essential to realize the goal of thermodynamically driven drug design. Comprehensive thermodynamic evaluation is vital early in the drug development process to speed drug development toward an optimal energetic interaction profile while retaining good pharmacological properties. Practical thermodynamic approaches, such as enthalpic optimization, thermodynamic optimization plots and the enthalpic efficiency index, have now matured to provide proven utility in the design process. Improved throughput in calorimetric methods remains essential for even greater integration of thermodynamics into drug design.     

ADME-Tox in drug discovery: integration of experimental and computational technologies

Over the past ten years, in vitro experimental tools to characterize ADME-Tox profiles of compounds have been applied in early stages of the drug discovery process to increase the success rate of discovery programmes and to progress better candidates into drug development. Application of in silico ADME-Tox models has further enhanced discovery support, enabling virtual screening of compounds and thus, application of ADME-Tox at every stage of the discovery process. Ultimately, effective and efficient ADME-Tox support of discovery will depend on a complementary and synergistic use of experimental and in silico ADME-Tox.     

Thermodynamic studies for drug design and screening

Introduction: A key part of drug design and development is the optimization of molecular interactions between an engineered drug candidate and its binding target. Thermodynamic characterization provides information about the balance of energetic forces driving binding interactions and is essential for understanding and optimizing molecular interactions.

Areas covered: This review discusses the information that can be obtained from thermodynamic measurements and how this can be applied to the drug development process. Current approaches for the measurement and optimization of thermodynamic parameters are presented, specifically higher throughput and calorimetric methods. Relevant literature for this review was identified in part by bibliographic searches for the period 2004 – 2011 using the Science Citation Index and PUBMED and the keywords listed below.

Expert opinion: The most effective drug design and development platform comes from an integrated process utilizing all available information from structural, thermodynamic and biological studies. Continuing evolution in our understanding of the energetic basis of molecular interactions and advances in thermodynamic methods for widespread application are essential to realize the goal of thermodynamically driven drug design. Comprehensive thermodynamic evaluation is vital early in the drug development process to speed drug development toward an optimal energetic interaction profile while retaining good pharmacological properties. Practical thermodynamic approaches, such as enthalpic optimization, thermodynamic optimization plots and the enthalpic efficiency index, have now matured to provide proven utility in the design process. Improved throughput in calorimetric methods remains essential for even greater integration of thermodynamics into drug design.     

Structure-based screening and design in drug discovery

Structure-based screening represents an integrated approach for the identification and optimization of hits by the combined use of nuclear magnetic resonance (NMR) spectroscopy, homology modeling and X-ray crystallography. A general feature of the methodology is the introduction of structure-based methods (NMR, modeling and X-ray) early in the drug discovery process to optimize hits in terms of their affinities and specificities. This approach promises to deliver leads with improved physicochemical properties as compared with leads generated from a traditional HTS program. This review presents examples of structure-based screening from published and in-house drug discovery projects.     

The impact of new technologies on drug design

The Cutting Edge Approaches to Drug Design symposium, held March 13, 2001, in London, U.K., was organized by the Royal Society of Chemistry's Molecular Modelling Group and the Structural Biology Group of the Biochemical Society. The symposium was aimed primarily at medicinal chemists keen to discover how cutting edge methods can accelerate drug design. The talks were aimed at the nonspecialist, and topics included target finding, virtual screening, informatics in lead optimization and in silico pharmacokinetic profiling. Several examples demonstrated the power of these methods.     

Structure-based approaches to drug design and virtual screening

Structure-based design has made an important contribution to drug discovery for many years. Recently, the increasing availability of structural data and the affordability of high-performance computing platforms have broadened the applicability of these methods. In particular, virtual screening has been adopted as an effective paradigm for lead discovery that fits in well alongside high-throughput screening programs. Structure-based virtual screening relies on fast and accurate computational methods for the prediction of receptor-ligand binding modes and binding affinities. In this paper, recent technical advances in the field of molecular docking and de novo design are reviewed, in particular, the development of flexible receptor models, docking of combinatorial libraries and novel scoring methods.     

Exploiting high-throughput ion channel screening technologies in integrated drug discovery

Ion channels are increasingly being implicated in disease. Although existing drugs that modulate channel function currently represent a key class of pharmaceutical agents, future ion channel drugs could help to treat an even wider variety of diseases. Despite their disease relevance, ion channels remain largely under exploited as drug targets, chiefly resulting from the absence of screening technologies that provide the throughput and quality of data required to support medicinal chemistry. Although some technical challenges still lie ahead, this historic bottleneck in drug discovery is now being bypassed by newer technologies that can be fully integrated into the early stages of drug discovery and will allow the discovery of novel therapeutic agents. Sequencing the human genome has greatly added to the number of potential drug targets but selecting suitable ion channels for drug discovery research should be based on the potential therapeutic relevance of the channel and not just the availability of suitable screens. Currently, ion channel drug discovery is focused on the need to identify compounds that can provide tractable starting points for medicinal chemistry. Advances in laboratory automation have brought significant opportunities to increase screening throughput for ion channel assays but careful assay configuration to model drug-target interactions in a physiological manner remains an essential consideration. Ion channel screening platforms are described in this review to provide some insight into the variety of technologies available for screening, together with some of their inherent advantages and limitations.     

高内涵药物筛选方法的研究及应用

高通量药物筛选 (high throughputscreening,HTS)是 20世纪 80年代中期产生的为寻找先导物针对大量样品进行药理活性评价分析的一种技术手段,在创新药物的研究和开发中发挥了重要作用。本室于 1998年在国内率先将其用于创新药物的研究,已发现一批具有潜在研究价值的化合物 [1, 2]。近年来在药物发现领域又出现了一个新概念———高内涵药物筛选 (high contentscreening,HCS)。本文就高内涵药物筛选目前的研究和应用情况作一讨论。1　高通量药物筛选与高内涵药物筛选高通量药物筛选是以药物发现的基本规律为基础,应用药理学、生物化学…     

药物研究的有效途径:组合化学与合理药物设计相结合

新药研究领域正孕育着一场以研究和应用分子多样性为核心的方法学革命，一方面它迅速吸收分子生物学、计算机科学和现代有机合成的最新研究成果，成为各种新技术、新方法荟萃的焦点；另一方面它又为各种新原理和新概念问世提供必要条件。最近出现的高通量筛选（ｈｉｇｈｔ...     

De novo drug design: integration of structure-based and ligand-based methods

Structure-based and ligand-based methods are used to derive predictive models in de novo drug design. Structure-based methods rely exclusively on prior knowledge of a protein structure to derive novel ligands, while ligand-based methods are traditionally used when no protein structure is available. Where there is sufficient information, these methods can be used in conjunction to increase the accuracy of simulation and enhance the drug design process. This review presents developments in the integration of these methods for de novo drug design, and recent results from both systems are highlighted.     

Virtual screening with solvation and ligand-induced complementarity

We present our database-screening tool SLIDE, which is capable of screening large data sets of organic compounds for potential ligands to a given binding site of a target protein. Its main feature is the modeling of induced complementarity by making adjustments in the protein side chains and ligand upon binding. Mean-field theory is used to balance the conformational changes in both molecules in order to generate a shape-complementary interface. Solvation is considered by prediction of water molecules likely to be conserved from the crystal structure of the ligand-free protein, and allowing them to mediate ligand interactions, if possible, or including a desolvation penalty when they are displaced by ligand atoms that do not replace the lost hydrogen bonds.A data set of over 175 000 organic molecules was screened for potential ligands to the progesterone receptor, dihydrofolate reductase, and a DNA-repair enzyme. In all cases the screening time was less than a day on a Pentium II processor, and known ligands as well as highly complementary new potential ligands were found. This revised version was published online in June 2006 with corrections to the Cover Date.