NMR structure-based drug design

Summary NMR is a useful tool for rapidly determining the conformations of receptor-bound ligands and identifying those protions of the ligand in contact with the receptor. In addition, the complete 3D structures of receptors and ligand/receptor complexes can be obtained using recently developed heteronuclear multi-dimensional NMR techniques. This NMR-derived structural information is potentially useful for aiding in the design of improved pharmaceutical agents. Approaches for utilizing the NMR-derived structural information along with the computational tools that facilitate this process are discussed.     

NMR spectroscopy in structure-based drug design

NMR methods for the study of motion in proteins continue to improve, and a number of studies of protein-ligand complexes relevant to drug design have been reported over the past year, for example, studies of fatty-acid-binding protein and SH2 and SH3 domains. These studies have begun to give a picture of the structural dynamics of protein-ligand complexes and to relate the changes in dynamics on ligand binding to the origins of specificity. NMR is also valuable in locating binding sites, both qualitatively from changes in chemical shift and more precisely from distances measured from relaxation effects. The conformation of the bound ligand can provide useful information for drug design, and over the past year improvements in methods have made it easier to obtain quantitative information from transferred nuclear Overhauser effect experiments.     

蛋白质磁共振——从结构生物学到结构基因组学

在后基因组时代,随着大量物种全基因组序列的获得,结构生物学家面临着结构基因组学的新机遇和挑战。与传统的结构生物学不同的是,结构基因组学的研究主要集中在结构和功能未知并且与从前研究的蛋白质相似性很小的蛋白质。准确的来讲,结构基因组学通过高通量蛋白质表达、结构解析来完成所有蛋白质家族的结构表征,从而能够通过结构预测功能。加州结构基因组学联合实验室发展了高度自动化的蛋白质合成、结晶、结构解析生产线。然而由于一些蛋白质不能被结晶,要想覆盖所有蛋白质结构域还有很大困难。Wuthrich的研究小组通过一些高通量的目的蛋白质筛选和NMR结构解析的方法解决了这一难题。与X射线晶体学解析蛋白质结构相比,NMR技术由于能够解析更接近生理状态的溶液结构而具有互补性。通过获得溶液中的蛋白质稳定性、动力学特征和相互作用信息,正如在朊蛋白和SARS相关蛋白的研究中所表现的那样,NMR技术从扩大已知的蛋白质结构数据库、新的蛋白质功能到化学生物学研究中都扮演着激动人心的角色。     

Solution NMR in structural genomics

Structural genomics (also known as structural proteomics) aims to generate accurate three-dimensional models for all folded, globular proteins and domains in the protein universe to understand the relationship between protein sequence, structure and function. NMR spectroscopy of small (<20 kDa) proteins has been used successfully within several large-scale structural genomics projects for more than six years now. Recent advances coming from traditional NMR structural biology laboratories as well as large scale centers and consortia using NMR for structural genomics promise to facilitate NMR analysis making it even a more efficient and increasingly automated procedure.     

Role for NMR in structural genomics

The 2nd EMSL Workshop on Structural Genomics was held on 28th and 29th July 2000 at the Environmental Molecular Sciences Laboratory at the Department of Energy's Pacific Northwest National Laboratory in Richland, WA. The workshop focused on four topics: 1. The role for NMR in structural and functional genomics; 2. The technical challenges NMR faces for structural and functional genomics; 3. The potential need for a national NMR center for structural and functional genomics in the United States; and 4. Organization of the NMR community. This report summarizes the workshop proceedings and conclusions reached regarding the role of NMR in the emerging fields of structural and functional genomics.     

Conformational control in structure-based drug design

In structure-based drug design, the basic goal is to design molecules that fit complementarily to a given binding pocket. Since such computationally modeled molecules may not adopt the intended bound conformation outside the binding pocket, one challenge is to ensure that the designed ligands adopt similar low energy conformations both inside and outside of the binding pocket. Computational chemistry methods and conformational preferences of small molecules from PDB and Cambridge Structural Database (CSD) can be used to predict the bound structures of the designed molecules. Herein, we review applications of conformational control in structure-based drug design using selected examples from the recent medicinal chemistry literature. The main purpose is to highlight some intriguing conformational features that can be applied to other drug discovery programs.     

Towards structure-based protein drug design

Structure-based drug design for chemical molecules has been widely used in drug discovery in the last 30 years. Many successful applications have been reported, especially in the field of virtual screening based on molecular docking. Recently, there has been much progress in fragment-based as well as de novo drug discovery. As many protein-protein interactions can be used as key targets for drug design, one of the solutions is to design protein drugs based directly on the protein complexes or the target structure. Compared with protein-ligand interactions, protein-protein interactions are more complicated and present more challenges for design. Over the last decade, both sampling efficiency and scoring accuracy of protein-protein docking have increased significantly. We have developed several strategies for structure-based protein drug design. A grafting strategy for key interaction residues has been developed and successfully applied in designing erythropoietin receptor-binding proteins. Similarly to small-molecule design, we also tested de novo protein-binder design and a virtual screen of protein binders using protein-protein docking calculations. In comparison with the development of structure-based small-molecule drug design, we believe that structure-based protein drug design has come of age.     

Recent advances in structure-based rational drug design

Two approaches to structure-based drug design, that is, the docking of known compounds into a target protein and molecular assembly in situ, are seen to be merging technologies. The need for structural information about drug-protein complexes is now fundamental for drug discovery.     

Unique opportunities for NMR methods in structural genomics

This Perspective, arising from a workshop held in July 2008 in Buffalo NY, provides an overview of the role NMR has played in the United States Protein Structure Initiative (PSI), and a vision of how NMR will contribute to the forthcoming PSI-Biology program. NMR has contributed in key ways to structure production by the PSI, and new methods have been developed which are impacting the broader protein NMR community.     

Applications of NMR in drug discovery

NMR, already some 50 years old, has long been an invaluable analytical method in industry for verification of chemical synthesis and compound characterisation. The range of molecular information accessible through NMR, however, offers a far larger horizon of applications. Of these, ligand screening by NMR has emerged as a very promising new method in drug discovery. Its unmatched screening sensitivity, combined with the abundance of available information on the structure and nature of molecular binding, justifies the growing interest in this dynamically expanding NMR application.     

Towards fully automated structure-based function prediction in structural genomics: a case study

As the global Structural Genomics projects have picked up pace, the number of structures annotated in the Protein Data Bank as hypothetical protein or unknown function has grown significantly. A major challenge now involves the development of computational methods to assign functions to these proteins accurately and automatically. As part of the Midwest Center for Structural Genomics (MCSG) we have developed a fully automated functional analysis server, ProFunc, which performs a battery of analyses on a submitted structure. The analyses combine a number of sequence-based and structure-based methods to identify functional clues. After the first stage of the Protein Structure Initiative (PSI), we review the success of the pipeline and the importance of structure-based function prediction. As a dataset, we have chosen all structures solved by the MCSG during the 5 years of the first PSI. Our analysis suggests that two of the structure-based methods are particularly successful and provide examples of local similarity that is difficult to identify using current sequence-based methods. No one method is successful in all cases, so, through the use of a number of complementary sequence and structural approaches, the ProFunc server increases the chances that at least one method will find a significant hit that can help elucidate function. Manual assessment of the results is a time-consuming process and subject to individual interpretation and human error. We present a method based on the Gene Ontology (GO) schema using GO-slims that can allow the automated assessment of hits with a success rate approaching that of expert manual assessment.     

A novel computational tool for automated structure-based drug design

The computer program LUDI for automated structure-based drug design is described. The program constructs possible new ligands for a given protein of known three-dimensional structure. This novel approach is based upon rules about energetically favourable non-bonded contact geometries between functional groups of the protein and the ligand which are derived from a statistical analysis of crystal packings of organic molecules. In a first step small fragments are docked into the protein binding site in such a way that hydrogen bonds and ionic interactions can be formed with the protein and hydrophobic pockets are filled with lipophilic groups of the ligands. The program can then append further fragments onto a previously positioned fragments or onto an already existing ligand (e.g., a lead structure that one seeks to improve). It is also possible to link several fragments together by bridge fragments to form a complete molecule. All putative ligands retrieved or constructed by LUDI are scored. We use a simple scoring function that was fitted to experimentally determined binding constants of protein–ligand complexes. LUCI is a very fast program with typical execution times of 1–5 min on a work station and is therefore suitable for interactive usage.     

High-throughput computational structure-based characterization of protein families: START domains and implications for structural genomics

SkyLine, a high-throughput homology modeling pipeline tool, detects and models true sequence homologs to a given protein structure. Structures and models are stored in SkyBase with links to computational function annotation, as calculated by MarkUs. The SkyLine/SkyBase/MarkUs technology represents a novel structure-based approach that is more objective and versatile than other protein classification resources. This structure-centric strategy provides a multi-dimensional organization and coverage of protein space at the levels of family, function, and genome. The concept of “modelability”, the ability to model sequences on related structures, provides a reliable criterion for membership in a protein family (“leverage”) and underlies the unique success of this approach. The overall procedure is illustrated by its application to START domains, which comprise a Biomedical Theme for the Northeast Structural Genomics Consortium as part of the Protein Structure Initiative. START domains are typically involved in the non-vesicular transport of lipids. While 19 experimentally determined structures are available, the family, whose evolutionary hierarchy is not well determined, is highly sequence diverse, and the ligand-binding potential of many family members is unknown. The SkyLine/SkyBase/MarkUs approach provides significant insights and predicts: (1) many more family members (~4,000) than any other resource; (2) the function for a large number of unannotated proteins; (3) instances of START domains in genomes from which they were thought to be absent; and (4) the existence of two types of novel proteins, those containing dual START domain and those containing N-terminal START domains.     

Residual dipolar couplings: Synergy between NMR and structural genomics

Structural genomics is on a quest for the structure and function of a significant fraction of gene products. Current efforts are focusing on structure determination of single-domain proteins, which can readily be targeted by X-ray crystallography, NMR spectroscopy and computational homology modeling. However, comprehensive association of gene products with functions also requires systematic determination of more complex protein structures and other biomolecules participating in cellular processes such as nucleic acids, and characterization of biomolecular interactions and dynamics relevant to function. Such NMR investigations are becoming more feasible, not only due to recent advances in NMR methodology, but also because structural genomics is providing valuable structural information and new experimental and computational tools. The measurement of residual dipolar couplings in partially oriented systems and other new NMR methods will play an important role in this synergistic relationship between NMR and structural genomics. Both an expansion in the domain of NMR application, and important contributions to future structural genomics efforts can be anticipated.     

Selection of an improved HDAC8 inhibitor through structure-based drug design

Histone deacetylases (HDACs) are enzymes, which catalyze the removal of acetyl moiety from acetyl-lysine within the histone proteins and promote gene repression and silencing resulting in several types of cancer. HDACs are important therapeutic targets for the treatment of cancer and related diseases. Hydroxamic acid inhibitors show promising results in clinical trials against carcinogenesis. 120 hydroxamic acid derivatives were designed as inhibitors based on hydrophobic pocket and the Zn (II) catalytic site of HDAC8 active site using Structure Based Drug Design (SBDD) approach. High Throughput Virtual screening (HTVs) was used to filter the effective inhibitors. Induced Fit Docking (IFD) studies were carried out for the screening of eight inhibitors using Glide software. Hydrogen bond, hydrophobic interactions and octahedral coordination geometry with Zn (II) were observed in the IFD complexes. Prime MM-GBSA calculation was carried out for the binding free energy, to observe the stability of docked complexes. The Lipinski's rule of five was analyzed for ADME/Tox drug likeliness using Qikprop simulation. These inhibitors have good inhibitory properties as they have favorable docking score, energy, emodel, hydrogen bond and hydrophobic interactions, binding free energy and ADME/Tox. However, one compound (Cmp22) successively satisfied all the studies among the eight compounds screened and seems to be a promising potent inhibitor against HDAC8.     

A three-dimensional model of CYP19 aromatase for structure-based drug design

Aromatase (CYP450_arom, CYP19) is an enzyme responsible for converting the aliphatic androgens androstenedione and testosterone to the aromatic estrogens estrone and estradiol, respectively. These endogenous hormones are a key factor in cancer tumor formation and proliferation through a cascade starting from estrogen binding to estrogen receptor. To interfere with the overproduction of estrogens especially in tumor tissue, it is possible to inhibit aromatase activity. This can be achieved using aromatase inhibitors. In order to design novel aromatase inhibitors, it is necessary to have an understanding of the active site of aromatase. As no crystal structure of the enzyme has yet been published, we built a homology model of aromatase using the first crystallized mammalian cytochrome enzyme, rabbit 21-progesterone hydroxylase 2C5, as a template structure. The initial model was validated with exhaustive molecular dynamics simulation with and without the natural substrate androstenedione. The resulting enzyme–substrate complex shows very good stability and only two of the residues are in disallowed regions in a Ramachandran plot.