Structural proteomics in drug discovery

High-throughput, automated or semiautomated methodologies implemented by companies and structural genomics initiatives have accelerated the process of acquiring structural information for proteins via x-ray crystallography. This has enabled the application of structure-based drug design technologies to a variety of new structures that have potential pharmacologic relevance. Although there remain major challenges to applying these approaches more broadly to all classes of drug discovery targets, clearly the continued development and implementation of these structure-based drug design methodologies by the scientific community at large will help to address and provide solutions to these hurdles. The result will be a growing number of protein structures of important pharmacologic targets that will help to streamline the process of identification and optimization of lead compounds for drug development. These lead agonist and antagonist pharmacophores should, in turn, help to alleviate one of the current critical bottlenecks in the drug discovery process; that is, defining the functional relevance of potential novel targets to disease modification. The prospect of generating an increasing number of potential drug candidates will serve to highlight perhaps the most significant future bottleneck for drug development, the cost and complexity of the drug approval process.     

Structure-directed combinatorial library design

In recent years pharmaceutical companies have utilized structure-based drug design and combinatorial library design techniques to speed up their drug discovery efforts. Both approaches are routinely used in the lead discovery and lead optimization stages of the drug discovery process. Fragment-based drug design, a new power tool in the drug design toolbox, is also gaining acceptance across the pharmaceutical industry. This review will focus on the interplay between these three design techniques and recent developments in computational methodologies that enhance their integration. Examples of successful synergistic applications of these three techniques will be highlighted. Opinion regarding possible future directions of the field will be given.     

Pharmacologically relevant proteins

The emergence of structure-based drug design as a tool for drug discovery and development has focused increased attention on pharmacologically relevant proteins and the use of their three-dimensional structures to design novel pharmaceutical agents. This review describes recent structural studies of selected macromolecules that have been identified as targets for drug development. Several examples of the successful application of structure-based drug design techniques are also described.     

The progress made in determining the Mycobacterium tuberculosis structural proteome

Mycobacterium tuberculosis is a highly infectious pathogen that is still responsible for millions of deaths annually. Effectively treating this disease typically requires a course of antibiotics, most of which were developed decades ago. These drugs are, however, not effective against persistent tubercle bacilli and the emergence of drug-resistant stains threatens to make many of them obsolete. The identification of new drug targets, allowing the development of new potential drugs, is therefore imperative. Both proteomics and structural biology have important roles to play in this process, the former as a means of identifying promising drug targets and the latter allowing understanding of protein function and protein-drug interactions at atomic resolution. The determination of M. tuberculosis protein structures has been a goal of the scientific community for the last decade, who have aimed to supply a large amount of structural data that can be used in structure-based approaches for drug discovery and design. Only since the genome sequence of M. tuberculosis has been available has the determination of large numbers of tuberculosis protein structures been possible. Currently, the molecular structures of 8.5% of all the pathogen's protein-encoding ORFs have been determined. In this review, we look at the progress made in determining the M. tuberculosis structural proteome and the impact this has had on the development of potential new drugs, as well as the discovery of the function of crucial mycobaterial proteins.     

Structural genomics

Structural genomics can be defined as structural biology on a large number of target proteins in parallel. This approach plays an important role in modern structure-based drug design. Although a number of structural genomics initiatives have been initiated, relatively few are associated with integral membrane proteins. This indicates the difficulties in expression, purification, and crystallization of membrane proteins, which has also been confirmed by the existence of some 100 high-resolution structures of membrane proteins among the more than 30,000 entries in public databases. Paradoxically, membrane proteins represent 60–70% of current drug targets and structural knowledge could both improve and speed up the drug discovery process. In order to improve the sucess rate for structure resolution of membrane proteins structural genomics networks have been established.     

Novel computational biology methods and their applications to drug discovery

Computational biology methods are now firmly entrenched in the drug discovery process. These methods focus on modeling and simulations of biological systems to complement and direct conventional experimental approaches. Two important branches of computational biology include protein homology modeling and the computational biophysics method of molecular dynamics. Protein modeling methods attempt to accurately predict three-dimensional (3D) structures of uncrystallized proteins for subsequent structure-based drug design applications. Molecular dynamics methods aim to elucidate the molecular motions of the static representations of crystallized protein structures. In this review we highlight recent novel methodologies in the field of homology modeling and molecular dynamics. Selected drug discovery applications using these methods conclude the review.     

The genesis of high-throughput structure-based drug discovery using protein crystallography

Over the past 12 years, drugs have been developed using structure-based drug design relying upon traditional crystallographic methods. Established successes, such as the drugs designed against HIV-1 protease and neuraminidase, demonstrate the utility of a structure-based approach in the drug-discovery process. However, the approach has historically lacked throughput and reliability capabilities; these bottlenecks are being overcome by breakthroughs in high-throughput structural biology. Recent technological innovations such as submicroliter high-throughput crystallization, high-performance synchrotron beamlines and rapid binding-site analysis of de novo targets using virtual ligand screening and small molecule co-crystallization have resulted in a significant advance in structure-based drug discovery.     

From G Protein-coupled Receptor Structure Resolution to Rational Drug Design

A number of recent technical solutions have led to significant advances in G protein-coupled receptor (GPCR) structural biology. Apart from a detailed mechanistic view of receptor activation, the new structures have revealed novel ligand binding sites. Together, these insights provide avenues for rational drug design to modulate the activities of these important drug targets. The application of structural data to GPCR drug discovery ushers in an exciting era with the potential to improve existing drugs and discover new ones. In this review, we focus on technical solutions that have accelerated GPCR crystallography as well as some of the salient findings from structures that are relevant to drug discovery. Finally, we outline some of the approaches used in GPCR structure based drug design.     

Protein targets for structure-based anti-Mycobacterium tuberculosis drug discovery

Mycobacterium tuberculosis, which belongs to the genus Mycobacterium, is the pathogenic agent for most tuberculosis (TB). As TB remains one of the most rampant infectious diseases, causing morbidity and death with emergence of multi-drug-resistant and extensively-drug-resistant forms, it is urgent to identify new drugs with novel targets to ensure future therapeutic success. In this regards, the structural genomics of M. tuberculosis provides important information to identify potential targets, perform biochemical assays, determine crystal structures in complex with potential inhibitor(s), reveal the key sites/residues for biological activity, and thus validate drug targets and discover novel drugs. In this review, we will discuss the recent progress on novel targets for structure-based anti-M. tuberculosis drug discovery.     

The impact of cryo-EM on determining allosteric modulator-bound structures of G protein-coupled receptors

G-protein coupled receptors (GPCRs) are important therapeutic targets for the treatment of human disease. Although GPCRs are highly successful drug targets, there are many challenges associated with the discovery and translation of small molecule ligands that target the endogenous ligand-binding site for GPCRs. Allosteric modulators are a class of ligands that target alternative binding sites known as allosteric sites and offer fresh opportunities for the development of new therapeutics. However, only a few allosteric modulators have been approved as drugs. Advances in GPCR structural biology enabled by the cryogenic electron microscopy (cryo-EM) revolution have provided new insights into the molecular mechanism and binding location of small molecule allosteric modulators. This review highlights the latest findings from allosteric modulator-bound structures of Class A, B, and C GPCRs with a focus on small molecule ligands. Emerging methods that will facilitate cryo-EM structures of more difficult ligand-bound GPCR complexes are also discussed. The results of these studies are anticipated to aid future structure-based drug discovery efforts across many different GPCRs.     

Structural genomics and drug discovery

Structure determination has already proven useful for lead optimization and direct drug design. The number of high-resolution structures available in public databases today exceeds 30,000 and will definitely aid in structure-based drug design. Structural genomics approaches covering whole genomes, topologically similar proteins or gene families are great assets for further progress in the development of new drugs. However, membrane proteins representing 70% of current drug targets are poorly characterized structurally. The problems have been related to difficulties in obtaining large amount of recombinant membrane proteins as well as their purification and structure determination. Structural genomics has proven successful in developing new methods in areas from expression to structure determination by studying a large number of target proteins in parallel.     

Applications of NMR to structure-based drug design in structural genomics

Structural genomics is poised to have a tremendous impact on traditional structure-based drug design programs. As a result, there is a growing need to obtain rapid structural information in a reliable form that is amenable to rational drug design. In this manner, NMR has been expanding and evolving its role in aiding the design process. A variety of NMR methodologies that cover a range of inherent resolution are described in the context of structure-based drug design in the era of structural genomics.     

Structural genomics and drug discovery: all in the family

Structural genomics is starting to have an impact on the early stages of drug discovery and target validation through the contribution of new structures of known and potential drug targets, their complexes with ligands and protocols and reagents for additional structural work within a drug discovery program. Recent progress includes structures of targets from bacterial, viral and protozoan human pathogens, and human targets from known or potential druggable protein families such as, kinases, phosphatases, dehydrogenases/oxidoreductases, sulfo-, acetyl- and methyl-transferases, and a number of other key metabolic enzymes. Importantly, many of these structures contained ligands in the active sites, including for example, the first structures of target-bound therapeutics. Structural genomics of protein families combined with ligand discovery holds particular promise for advancing early stage discovery programs.     

Trends in application of advancing computational approaches in GPCR ligand discovery

G protein-coupled receptors (GPCRs) comprise the most important superfamily of protein targets in current ligand discovery and drug development. GPCRs are integral membrane proteins that play key roles in various cellular signaling processes. Therefore, GPCR signaling pathways are closely associated with numerous diseases, including cancer and several neurological, immunological, and hematological disorders. Computer-aided drug design (CADD) can expedite the process of GPCR drug discovery and potentially reduce the actual cost of research and development. Increasing knowledge of biological structures, as well as improvements on computer power and algorithms, have led to unprecedented use of CADD for the discovery of novel GPCR modulators. Similarly, machine learning approaches are now widely applied in various fields of drug target research. This review briefly summarizes the application of rising CADD methodologies, as well as novel machine learning techniques, in GPCR structural studies and bioligand discovery in the past few years. Recent novel computational strategies and feasible workflows are updated, and representative cases addressing challenging issues on olfactory receptors, biased agonism, and drug-induced cardiotoxic effects are highlighted to provide insights into future GPCR drug discovery.     

NMR techniques for characterization of ligand binding: utility for lead generation and optimization in drug discovery.

Over the last ten years, nmr spectroscopy has evolved into an important discipline in drug discovery. Initially, nmr was most useful as a technique to provide structural information regarding protein drug targets and target-ligand interactions. More recently, it has been shown that nmr may be used as an alternative method for identification of small molecule ligands that bind to protein drug targets. High throughput implementation of these experiments to screen small molecule libraries may lead to identification of potent and novel lead compounds. In this review, we will use examples from our own research to illustrate how nmr experiments to characterize ligand binding may be used to both screen for novel compounds during the process of lead generation, as well as provide structural information useful for lead optimization during the latter stages of a discovery program.     

Structural adaptation of extreme halophilic proteins through decrease of conserved hydrophobic contact surface

Background

Disrupting protein-protein interactions by small organic molecules is nowadays a promising strategy employed to block protein targets involved in different pathologies. However, structural changes occurring at the binding interfaces make difficult drug discovery processes using structure-based drug design/virtual screening approaches. Here we focused on two homologous calcium binding proteins, calmodulin and human centrin 2, involved in different cellular functions via protein-protein interactions, and known to undergo important conformational changes upon ligand binding.

Results

In order to find suitable protein conformations of calmodulin and centrin for further structure-based drug design/virtual screening, we performed in silico structural/energetic analysis and molecular docking of terphenyl (a mimicking alpha-helical molecule known to inhibit protein-protein interactions of calmodulin) into X-ray and NMR ensembles of calmodulin and centrin. We employed several scoring methods in order to find the best protein conformations. Our results show that docking on NMR structures of calmodulin and centrin can be very helpful to take into account conformational changes occurring at protein-protein interfaces.

Conclusions

NMR structures of protein-protein complexes nowadays available could efficiently be exploited for further structure-based drug design/virtual screening processes employed to design small molecule inhibitors of protein-protein interactions.     

Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach

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 3D 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.     

Structural chemoproteomics and drug discovery

Our laboratories have developed several technologies to accelerate drug discovery process on the basis of structural chemoproteomics. They include SPS technology for the efficient determination of protein structures, SCP technology for the rapid lead generation and SDF technology for the productive lead optimization. Using these technologies, we could determine many 3D structures of target proteins bound with biologically active chemicals including the structure of phosphodiesterase 5/Viagra complex and obtain highly potent compounds in animal models of obesity, diabetes, cancer and inflammation. In this paper, we will discuss concepts and applications of structural chemoproteomics for drug discovery.     

药物靶点的选择和验证

药物靶点的选择和验证是药物开发研究中一个重要的环节.随着现代分子生物学技术的发展和人类基因组计划的完成,出现了大量可供治疗干预的新型分子靶点,对这些新型分子靶点进行验证成为药物开发科学家所面临的重要任务.为此,就药物靶点及其选择、验证所需的分子技术基础作一简要综述.     

Exploring c-Met kinase flexibility by sampling and clustering its conformational space

It is now widely recognized that the flexibility of both partners has to be considered in molecular docking studies. However, the question how to handle the best the huge computational complexity of exploring the protein binding site landscape is still a matter of debate. Here we investigate the flexibility of c-Met kinase as a test case for comparing several simulation methods. The c-Met kinase catalytic site is an interesting target for anticancer drug design. In particular, it harbors an unusual plasticity compared with other kinases ATP binding sites. Exploiting this feature may eventually lead to the discovery of new anticancer agents with exquisite specificity. We present in this article an extensive investigation of c-Met kinase conformational space using large-scale computational simulations in order to extend the knowledge already gathered from available X-ray structures. In the process, we compare the relevance of different strategies for modeling and injecting receptor flexibility information into early stage in silico structure-based drug discovery pipeline. The results presented here are currently being exploited in on-going virtual screening investigations on c-Met.