In silico research in drug discovery

Target and lead discovery constitute the main components of today's early pharmaceutical research. The aim of target discovery is the identification and validation of suitable drug targets for therapeutic intervention, whereas lead discovery identifies novel chemical molecules that act on those targets. With the near completion of the human genome sequencing, bioinformatics has established itself as an essential tool in target discovery and the in silico analysis of gene expression and gene function are now an integral part of it, facilitating the selection of the most relevant targets for a disease under study. In lead discovery, advances in chemoinformatics have led to the design of compound libraries in silico that can be screened virtually. Moreover, computational methods are being developed to predict the drug-likeness of compounds. Thus, drug discovery is already on the road towards electronic R&D.     

Predicting protein druggability

The ability to predict whether a particular protein can bind with high affinity and specificity to small, drug-like compounds based solely on its 3D structure has been a longstanding goal of structural biologists and computational scientists. The promise is that an accurate prediction of protein druggability can capitalize on the huge investments already made in structural genomics initiatives by identifying highly druggable proteins and using this information in target identification and validation campaigns. Here we discuss the potential utility of tools that characterize protein targets and describe strategies for the optimal integration of protein druggability data with bioinformatic approaches to target selection.     

Aptamers as tools for target prioritization and lead identification

The increasing number of potential drug target candidates has driven the development of novel technologies designed to identify functionally important targets and enhance the subsequent lead discovery process. Highly specific synthetic nucleic acid ligands – also known as aptamers – offer a new exciting route in the drug discovery process by linking target validation directly with HTS. Recently, aptamers have proven to be valuable tools for modulating the function of endogenous cellular proteins in their natural environment. A set of technologies has been developed to use these sophisticated ligands for the validation of potential drug targets in disease models. Moreover, aptamers that are specific antagonists of protein function can act as substitute interaction partners in HTS assays to facilitate the identification of small-molecule lead compounds.     

High-throughput X-ray crystallography for drug discovery

Knowledge of the three-dimensional structures of protein targets has the potential to greatly accelerate drug discovery, but technical challenges and time constraints have traditionally limited its use to lead optimization. Its application is now being extended beyond structure determination into new approaches for lead discovery. Structure-activity relationships by nuclear magnetic resonance have been widely used to detect ligand binding and to give some indication of the location of the binding site. X-ray crystallography has the advantage of defining ligand-binding sites with greater certainty. High-throughput approaches make this method applicable to screening to identify molecular fragments that bind protein targets, and to defining precisely their binding sites. X-ray crystallography can then be used as a rapid technique to guide the elaboration of the fragments into larger molecular weight compounds that might be useful leads for drug discovery.     

Microbial genomics - new targets,new drugs

Genomics has changed our view of the biological world in the past decade, providing both new information and new tools to characterise biological systems. Over 100 microbial genomes - including many of substantial clinical importance - have been fully or partially sequenced, pushing the search for novel antimicrobial compounds into the post-genomic era. Genomic information and associated new technologies have the potential to revolutionise the drug discovery process. Genomic methods have created a wealth of potential new antimicrobial targets; strategies are evolving to provide validation for these targets before chemical inhibitors are identified. The ability to obtain large amounts of purified target proteins and advances in X-ray crystallography have caused significant increases in available protein structures, which may foreshadow an increased effort in structure-based drug design. The post-genomics strategies used in antimicrobial drug discovery may have application for small molecule drug discovery in numerous therapeutic areas.     

Microbial genomics – new targets,new drugs

Genomics has changed our view of the biological world in the past decade, providing both new information and new tools to characterise biological systems. Over 100 microbial genomes – including many of substantial clinical importance – have been fully or partially sequenced, pushing the search for novel antimicrobial compounds into the post-genomic era. Genomic information and associated new technologies have the potential to revolutionise the drug discovery process. Genomic methods have created a wealth of potential new antimicrobial targets; strategies are evolving to provide validation for these targets before chemical inhibitors are identified. The ability to obtain large amounts of purified target proteins and advances in X-ray crystallography have caused significant increases in available protein structures, which may foreshadow an increased effort in structure-based drug design. The post-genomics strategies used in antimicrobial drug discovery may have application for small molecule drug discovery in numerous therapeutic areas.     

Chemogenomic approaches to rational drug design

Paradigms in drug design and discovery are changing at a significant pace. Concomitant to the sequencing of over 180 several genomes, the high-throughput miniaturization of chemical synthesis and biological evaluation of a multiple compounds on gene/protein expression and function opens the way to global drug-discovery approaches, no more focused on a single target but on an entire family of related proteins or on a full metabolic pathway. Chemogenomics is this emerging research field aimed at systematically studying the biological effect of a wide array of small molecular-weight ligands on a wide array of macromolecular targets. Since the quantity of existing data (compounds, targets and assays) and of produced information (gene/protein expression levels and binding constants) are too large for manual manipulation, information technologies play a crucial role in planning, analysing and predicting chemogenomic data. The present review will focus on predictive in silico chemogenomic approaches to foster rational drug design and derive information from the simultaneous biological evaluation of multiple compounds on multiple targets. State-of-the-art methods for navigating in either ligand or target space will be presented and concrete drug design applications will be mentioned.     

Toward Rational Fragment-Based Lead Design without 3D Structures

Fragment-based lead discovery (FBLD) has become a prime component of the armamentarium of modern drug design programs. FBLD identifies low molecular weight ligands that weakly bind to important biological targets. Three-dimensional structural information about the binding mode is provided by X-ray crystallography or NMR spectroscopy and is subsequently used to improve the lead compounds. Despite tremendous success rates, FBLD relies on the availability of high-resolution structural information, still a bottleneck in drug discovery programs. To overcome these limitations, we recently demonstrated that the meta-structure approach provides an alternative route to rational lead identification in cases where no 3D structure information about the biological target is available. Combined with information-rich NMR data, this strategy provides valuable information for lead development programs. We demonstrate with several examples the feasibility of the combined NMR and meta-structure approach to devise a rational strategy for fragment evolution without resorting to highly resolved protein complex structures.     

What to expect from rational drug design

For more than 20 years, rational methods of drug design have belonged to the methodological core of drug development. Rational drug design based on structural knowledge of protein targets and on computational modelling of drug–target interaction holds out the promise of a predictable development process for highly innovative drugs. Still, it remains a challenge to make the available structural information fruitful for lead design. As a consequence, rational design is becoming increasingly interwoven with high-throughput screening. In addition, the relationship to the emerging systems-oriented approaches has yet to be specified.     

Computational Advances for the Development of Allosteric Modulators and Bitopic Ligands in G Protein-Coupled Receptors

Allosteric modulators of G protein-coupled receptors (GPCRs), which target at allosteric sites, have significant advantages against the corresponding orthosteric compounds including higher selectivity, improved chemical tractability or physicochemical properties, and reduced risk of receptor oversensitization. Bitopic ligands of GPCRs target both orthosteric and allosteric sites. Bitopic ligands can improve binding affinity, enhance subtype selectivity, stabilize receptors, and reduce side effects. Discovering allosteric modulators or bitopic ligands for GPCRs has become an emerging research area, in which the design of allosteric modulators is a key step in the detection of bitopic ligands. Radioligand binding and functional assays ([³⁵S]GTPγS and ERK1/2 phosphorylation) are used to test the effects for potential modulators or bitopic ligands. High-throughput screening (HTS) in combination with disulfide trapping and fragment-based screening are used to aid the discovery of the allosteric modulators or bitopic ligands of GPCRs. When used alone, these methods are costly and can often result in too many potential drug targets, including false positives. Alternatively, low-cost and efficient computational approaches are useful in drug discovery of novel allosteric modulators and bitopic ligands to help refine the number of targets and reduce the false-positive rates. This review summarizes the state-of-the-art computational methods for the discovery of modulators and bitopic ligands. The challenges and opportunities for future drug discovery are also discussed.Key words: allosteric modulators, bitopic ligands, computational approaches, drug discovery, drug target discovery, G protein-coupled receptors     

Macromolecular crystallography as a tool for investigating drug, enzyme and receptor interactions

1. Protein crystallography is an essential tool for the discovery and investigation of pharmacological interactions at the molecular level. It allows investigators to directly visualize the three-dimensional structures of proteins, including enzymes, receptors and hormones. 2. Increasingly, knowledge of these interactions is being used in the drug-discovery process. This is popularly called structure-based drug design. The desired drug could be an enzyme inhibitor or an agonist that mimics endogenous transmitters or hormones. 3. Once the 3-D structure of a pharmacologically relevant target is known, computational processes can be used to search databases of compounds to identify ones that may interact strongly with the target. Lead compounds can be improved using the 3-D structure of the complex of the lead compound and its biological target. 4. The present review describes the processes involved in the determination of a structure by means of protein crystallography and the use of structures in the drug-discovery process. A number of successful examples of structure-based drug design are described. The limitations of the techniques are discussed.     

Molecular approaches to target discovery:--evaluating targets for anti-tuberculosis drug discovery programmes

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.     

When analoging is not enough: scaffold discovery in medicinal chemistry

Importance of the field: As an integral part of lead generation and optimization, scaffold discovery has broad implications in drug discovery. Currently available chemical scaffolds might be inadequate to provide drug-like ligands for new targets such as phosphatases and protein–protein interactions and therapeutically useful chemical space needs to be continuously explored. New scaffolds are often desired to overcome major hurdles (e.g., potency plateau, selectivity, pharmacokinetics, etc.) in lead generation and optimization. Timely discovery of proof-of-concept compounds facilitates target validation, diversifies clinical candidates and improves the overall success rate of drug discovery.

Areas covered in this review: This analysis discusses the strategies involved in finding new scaffolds (i.e., fragment-, ligand- and structure-based design) and their applications (e.g., improve potency/selectivity, multiple ligand design, protein–protein interactions, etc.) in drug discovery.

What the reader will gain: The readers will learn the strategies involved in scaffold design and the problems that they solve. They will also gain the understanding of the circumstances suitable for using scaffold design.

Take home message: Scaffold is defined by the authors as a biological target dependent concept. Therapeutically useful scaffolds are limited and the identification of new scaffolds is sometimes required to overcome major optimization hurdles. However, depending on the promiscuity of the binding pocket of the target and the validity of the optimization protocol, finding better scaffolds can be a challenging task. Several strategies in scaffold discovery have emerged or matured owing to recent trends such as pursuit of targets from new proteomic families, lack of validated targets, advances in synthesis and biological assays and adoption of in vitro activity-driven screening paradigms.     

Impact of recombinant DNA technology and protein engineering on structure-based drug design: case studies of HIV-1 and HCMV proteases

Structure-based drug design is an organized, multidisciplinary endeavor undertaken by scientists from many different scientific fields. The success of structure-based drug design was only made possible by advances in structure biology that provides the three-dimensional structure of the drug design target with which small molecular chemical ligands interact. Visualization of the conformation and interactions of a small molecule ligand bound to the protein target in the co-crystal structure of the protein:ligand complex enables the design of new chemical compounds with improved binding affinity and specificity. With the advances in molecular biology, lab automation, and computational science, genomic data have now become available for the human genome, as well as various other organisms. The pharmaceutical industry is currently putting forth tremendous effort in the area of functional genomics and structural genomics in attempts to decipher functions and structures of protein encoded by genes, with the ultimate goal of identifying novel targets for drug discovery and development. This chapter discusses the significant impact made by recombinant DNA technology and protein engineering on structural biology and, more specifically, on structure-based drug design.     

The role of structure based virtual screening in the early phase of drug discovery

Identification of a viable lead is a critical step in drug discovery. The qualities of the lead set the stage for subsequent efforts to ameliorate therapeutic efficacy through potency, selectivity, pharmacokinetics, toxicity and side effects. In a retrospective view of drug research the lead identification has been realised mainly by in vivo methodologies. However, limitations of in vivo models were found to be critical factors when analysing attrition rates that prompted research groups to introduce in vitro tests and rational approaches at the frontline of discovery programs. Virtual screening (VS) methods merge in vitro high-throughput (HTS) and rational approaches. The VS methods can be classified as ligand and structure based techniques. Structure based approaches depart from the structural information of the target to identify potential interactions between the ligands and the protein. The advantages and disadvantages and the applicability of the structure based virtual screening approaches constituted the main aim of my studies. The glycogen synthase kinase 3beta (GSK-3beta), the beta-secretase and the c-jun N-terminal kinase 3 (JNK-3) were selected as primary targets for virtual screening. The performance of virtual screens can only be validated in parallel with HTS, therefore a head to head comparative analysis was my next goal.     

The effect of plasma protein binding on in vivo efficacy: misconceptions in drug discovery

Data from in vitro plasma protein binding experiments that determine the fraction of protein-bound drug are frequently used in drug discovery to guide structure design and to prioritize compounds for in vivo studies. However, we consider that these practices are usually misleading, because in vivo efficacy is determined by the free (unbound) drug concentration surrounding the therapeutic target, not by the free drug fraction. These practices yield no enhancement of the in vivo free drug concentration. So, decisions based on free drug fraction could result in the wrong compounds being advanced through drug discovery programmes. This Perspective provides guidance on the application of plasma protein binding information in drug discovery.     

In silico Characterization of an Atypical MAPK Phosphatase of Plasmodium falciparum as a Suitable Target for Drug Discovery

Plasmodium falciparum, the causative agent of malaria, contributes to significant morbidity and mortality worldwide. Forward genetic analysis of the blood‐stage asexual cycle identified the putative phosphatase from PF3D7_1305500 as an important element of intraerythrocytic development expressed throughout the life cycle. Our preliminary evaluation identified it as an atypical mitogen‐activated protein kinase phosphatase. Additional bioinformatic analysis delineated a conserved signature motif and three residues with potential importance to functional activity of the atypical dual‐specificity phosphatase domain. A homology model of the dual‐specificity phosphatase domain was developed for use in high‐throughput in silico screening of the available library of antimalarial compounds from ChEMBL‐NTD. Seven compounds from this set with predicted affinity to the active site were tested against in vitro cultures, and three had reduced activity against a ?PF3D7_1305500 parasite, suggesting PF3D7_1305500 is a potential target of the selected compounds. Identification of these compounds provides a novel starting point for a structure‐based drug discovery strategy that moves us closer toward the discovery of new classes of clinical antimalarial drugs. These data suggest that mitogen‐activated protein kinase phosphatases represent a potentially new class of P. falciparum drug target.     

2-Phenylindole and Arylsulphonamide: Novel Scaffolds Bactericidal against Mycobacterium tuberculosis

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