首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献,搜索用时 31 毫秒
1.
Fragment screening offers an alternative to traditional screening for discovering new leads in drug discovery programs. This paper describes a fragment screening methodology based on high throughput X-ray crystallography. The method is illustrated against five proteins (p38 MAP kinase, CDK2, thrombin, ribonuclease A, and PTP1B). The fragments identified have weak potency (>100 microM) but are efficient binders relative to their size and may therefore represent suitable starting points for evolution to good quality lead compounds. The examples illustrate that a range of molecular interactions (i.e., lipophilic, charge-charge, neutral hydrogen bonds) can drive fragment binding and also that fragments can induce protein movement. We believe that the method has great potential for the discovery of novel lead compounds against a range of targets, and the companion paper illustrates how lead compounds have been identified for p38 MAP kinase starting from fragments such as those described in this paper.  相似文献   

2.
3.
A fragment-based drug design paradigm has been successfully applied in the discovery of lead series of ketohexokinase inhibitors. The paradigm consists of three iterations of design, synthesis, and X-ray crystallographic screening to progress low molecular weight fragments to leadlike compounds. Applying electron density of fragments within the protein binding site as defined by X-ray crystallography, one can generate target specific leads without the use of affinity data. Our approach contrasts with most fragment-based drug design methodology where solution activity is a main design guide. Herein we describe the discovery of submicromolar ketohexokinase inhibitors with promising druglike properties.  相似文献   

4.
Knowledge of the three-dimensional structures of protein targets now emerging from genomic data has the potential to accelerate drug discovery greatly. X-ray crystallography is the most widely used technique for protein structure determination, but technical challenges and time constraints have traditionally limited its use primarily to lead optimization. Here, we describe how significant advances in process automation and informatics have aided the development of high-throughput X-ray crystallography, and discuss the use of this technique for structure-based lead discovery.  相似文献   

5.
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.  相似文献   

6.
A pharmacophore represents a simple and intuitive concept that can be used in many different drug discovery applications. Ligand-based and structure-based pharmacophore models continue to play a pivotal role in hit discovery and may guide lead optimization. Moreover, owing to the versatility of the pharmacophore concept, pharmacophore modelling has been routinely used in combination with other molecular modelling techniques. The synergistic use of different tools in drug discovery workflows may allow to fully exploit the advantages, while compensating for some of the intrinsic limitations, of each methodology. This review will focus on the synergistic combination of pharmacophore modelling with other molecular modelling approaches such as the hot spot analysis of protein binding sites, molecular dynamics, and docking.  相似文献   

7.
The successful practice of medicinal chemistry is crucially dependent on the principles of molecular recognition: the first and "fundamental" requirement for a drug is to bind to its target; specificity, or at least selectivity, of binding is also a must. Subsequent optimization steps to develop a lead compound into a drug are a complex mixture of processes that are not yet fully understood or predictable. Fortunately, criteria exist to discard leads that would be intractable for optimization. The concepts of non-lead-likeness and lead-likeness, in respect to drug-likeness and non-drug-likeness, have prompted a rich discussion in the recent medicinal chemistry literature. The fragment approach is an emerging philosophy in the process of lead compound discovery. The basic interactions responsible for binding affinity are defined from the "protein interactions world" and key structural fragments are combined according to the criteria of three-dimensional diversity to find new leads. New techniques in screening are used for the detection of the weaker interactions of fragments with their targets that might be undetectable in classical biological assays.  相似文献   

8.
Fragment-based drug discovery has become a powerful method for the generation of drug leads against therapeutic targets. Beyond the identification of novel and effective starting points for drug design, fragments have emerged as reliable tools for assessing protein druggability and identifying protein hot spots. Here, we have examined fragments resulting from the deconstruction of known inhibitors from the glycogen phosphorylase enzyme, a therapeutic target against type 2 diabetes, with two motivations. First, we have analyzed the fragment binding to the multiple binding sites of the glycogen phosphorylase, and then we have investigated the use of fragments to study allosteric enzymes. The work we report illustrates the power of fragmentlike ligands not only for probing the various binding pockets of proteins, but also for uncovering cooperativity between these various binding sites.  相似文献   

9.
High-throughput structural biology in drug discovery: protein kinases   总被引:1,自引:0,他引:1  
Structural biology is an invaluable tool in modern drug discovery, providing key insights into the interactions of small-molecule drugs with their protein targets. As in many aspects of the drug discovery process, significant synergies can be realized in structural biology by the contemporaneous pursuit of many target proteins from a single structural and functional class. We will review some of those synergies here using the example of the protein kinases--an important class of drug targets that has recently been the subject of intensive study. We conclude by discussing some of the technical advances in X-ray crystallography that have enabled implementation of high-throughput structural biology as applied to drug lead optimization.  相似文献   

10.
Conventional bioassay-based screening remains a mainstream approach for lead discovery. However, its limitations have meant that other, more biophysical methods, such as X-ray crystallography and NMR, are now being developed as lead discovery tools. These methods are particularly effective at detecting the binding of low affinity, low molecular weight compounds and transforming them into novel potent leads using structure-guided chemistry. Here, we describe some of the technologies and approaches that are being developed in structure-based screening using X-ray crystallography, which promise to have a major impact on lead discovery.  相似文献   

11.
Finding novel compounds as starting points for optimization is a major challenge in drug discovery research. Fragment-based methods have emerged in the past ten years as an effective way to sample chemical diversity with a limited number of low molecular weight compounds. The structures of the fragments(s) binding to the protein can then be used to design new compounds with increased affinity, specificity and novelty. This article describes the Vernalis approach to fragment based drug discovery, called SeeDs (Structural exploitation of experimental Drug startpoints). The approach includes the design of a fragment library, identification of fragments that bind competitively to a target by ligand-based NMR techniques and protein crystal structures to characterize binding. Fragments that bind are then evolved to hits, either by growing the fragment or by combining structural features from a number of compounds. The process is illustrated with examples from recent medicinal chemistry programmes to discover compounds against the oncology targets Hsp90 and PDK1. In addition, we summarise our experience with using molecular docking calculations to predict fragment binding and anecdotes on the selectivity and binding modes for fragments seen against a range of targets.  相似文献   

12.
The ability to identify the sites of a protein that can bind with high affinity to small, drug-like compounds has been an important goal in drug design. Accurate prediction of druggable sites and the identification of small compounds binding in those sites have provided the input for fragment-based combinatorial approaches that allow for a more thorough exploration of the chemical space, and that have the potential to yield molecules that are more lead-like than those found using traditional high-throughput screening. Current progress in experimental and computational methods for identifying and characterizing druggable ligand binding sites on protein targets is reviewed herein, including a discussion of successful nuclear magnetic resonance, X-ray crystallography and tethering technologies. Classical geometric and energy-based computational methods are also discussed, with particular focus on two powerful technologies, that is, computational solvent mapping and grand canonical Monte Carlo simulations (as used by Locus Pharmaceuticals Inc). Both methods can be used to reliably identify druggable sites on proteins and to facilitate the design of novel, low-nanomolar-affinity ligands.  相似文献   

13.
Recently, fragment-based drug design has been established as a crucial strategy for hit identification and lead generation, which has strongly encouraged the development of approaches to specifically recognize and evaluate molecular fragments or structural scaffolds that preferentially interact with particular sites of important biological targets. In this context, fragment-based quantitative structure-activity relationship (FB-QSAR) has emerged as a versatile tool to explore the chemical and biological space of data sets of compounds. FB-QSAR approaches have evolved from a classical use in the generation of standard QSAR models into advanced drug design tools for database mining, pharmacokinetic property prediction and optimization of multiple parameters. This paper provides a brief perspective on the evolution and current status of FB-QSAR, highlighting new opportunities in drug design.  相似文献   

14.
Integrated bioinformatic approaches to drug discovery exploit computational techniques to examine the flow of information from genome to structure to function. Informatics is being be used to accelerate and rationalize the process of antimycobacterial drug discovery and design, with the immediate goals to identify viable drug targets and produce a set of critically evaluated protein target models and corresponding set of probable lead compounds. Bioinformatic approaches are being successfully applied in the selection and prioritization of putative mycobacterial drug target genes; computational modelling and x-ray structure validation of protein targets with drug lead compounds; simulated docking and virtual screening of potential lead compounds; and lead validation and optimization using structure-activity and structure-function relationships. By identifying active sites, characterizing patterns of conserved residues and, where relevant, predicting catalytic residues, bioinformatics provides information to aid the design of selective and efficacious pharmacophores. In this review, we describe selected recent progress in antimycobacterial drug design, illustrating the strengths and limitations of current structural bioinformatic approaches as tools in the fight against tuberculosis.  相似文献   

15.
Fragment-based lead discovery: leads by design   总被引:3,自引:0,他引:3  
Fragment-based lead discovery (also referred to as needles, shapes, binding elements, seed templates or scaffolds) is a new lead discovery approach in which much lower molecular weight (120-250 Da) compounds are screened relative to HTS campaigns. Fragment-based hits are typically weak inhibitors (10 microM-mM), and therefore need to be screened at higher concentration using very sensitive biophysical detection techniques such as protein crystallography and NMR as the primary screening techniques, rather than bioassays. Compared with HTS hits, these fragments are simpler, less functionalized compounds with correspondingly lower affinity. However, fragment hits typically possess high 'ligand efficiency' (binding affinity per heavy atom) and so are highly suitable for optimization into clinical candidates with good drug-like properties.  相似文献   

16.
Recently, fragment-based drug design has been established as a crucial strategy for hit identification and lead generation, which has strongly encouraged the development of approaches to specifically recognize and evaluate molecular fragments or structural scaffolds that preferentially interact with particular sites of important biological targets. In this context, fragment-based quantitative structure–activity relationship (FB-QSAR) has emerged as a versatile tool to explore the chemical and biological space of data sets of compounds. FB-QSAR approaches have evolved from a classical use in the generation of standard QSAR models into advanced drug design tools for database mining, pharmacokinetic property prediction and optimization of multiple parameters. This paper provides a brief perspective on the evolution and current status of FB-QSAR, highlighting new opportunities in drug design.  相似文献   

17.
18.
In recent years there has been a growing interest in computer-based screening. One of the driving forces has been the increased efficiency of protein crystallography leading to the real possibility of using structure-based design as a significant contributor to the discovery of novel ligands. In 1957 after 22 years of work the first protein structure, determined by x-ray crystallography was produced. Now the process has become increasingly automated and nearly 20,000 protein structures are available in the Protein Data Bank (PDB). Equally, progress in genomics will result in a great expansion of validated targets for cancer therapy. The understanding of the relationships between structure and function of gene products will be one of the key routes to new therapeutic advances. The challenge now is to use this data in the discovery of novel therapeutics. One approach is obviously to synthesize molecules and co-crystallize or soak them into the protein crystal and so determine the position and interaction of the molecule with the protein. The structural information obtained (where does the molecule bind; what are the ligand/protein/solvent interactions?) can be invaluable in the generation of novel molecules or in the re-design of existing molecules whose drug properties are not optimal. However, when dealing with large numbers (millions) of molecules, when crystallization is difficult or in testing hypotheses, a significant contribution can be made using computer based screening methods. In order to use the structural information derived from x-ray crystallography (or other sources, for example NMR or homology modelling) when evaluating the utility of a novel ligand, we need to understand where in the protein (or other macromolecule such as RNA) the ligand is likely to bind and also if possible, the strength of the binding interactions. This problem is known as the 'docking problem'. There have been many approaches to the solution of this problem over the last ten years. For example, some methods rely on complex molecular dynamics simulations while others use less costly graph matching approaches. There is generally a compromise between speed and accuracy, with some methods giving much more information and insight into the nature of the protein/ligand interactions and other methods optimised for speed of docking thousands of putative ligands. We will describe some of the more common methods and algorithms used to solve the docking problem and in particular, we will review recent applications in cancer research.  相似文献   

19.
Over the past decade, fragment-based drug discovery has developed significantly and has gained increasing popularity in the pharmaceutical industry as a powerful alternative and complement to traditional high-throughput screening approaches for hit identification. Fragment-based methods are capable of rapidly identifying starting points for structure-based drug design from relatively small libraries of low molecular weight compounds. The main constraints are the need for sensitive methods that can reliably detect the typically weak interactions between fragments and the target protein, and strategies for transforming fragments into higher molecular weight drug candidates. This approach has recently been validated as series of compounds from various programs have entered clinical trials.  相似文献   

20.
To address the problem of specificity in G-protein coupled receptor (GPCR) drug discovery, there has been tremendous recent interest in allosteric drugs that bind at sites topographically distinct from the orthosteric site. Unfortunately, structure-based drug design of allosteric GPCR ligands has been frustrated by the paucity of structural data for allosteric binding sites, making a strong case for predictive computational methods. In this work, we map the surfaces of the β11AR) and β22AR) adrenergic receptor structures to detect a series of five potentially druggable allosteric sites. We employ the FTMAP algorithm to identify ‘hot spots’ with affinity for a variety of organic probe molecules corresponding to drug fragments. Our work is distinguished by an ensemble-based approach, whereby we map diverse receptor conformations taken from molecular dynamics (MD) simulations totaling approximately 0.5 μs. Our results reveal distinct pockets formed at both solvent-exposed and lipid-exposed cavities, which we interpret in light of experimental data and which may constitute novel targets for GPCR drug discovery. This mapping data can now serve to drive a combination of fragment-based and virtual screening approaches for the discovery of small molecules that bind at these sites and which may offer highly selective therapies.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号