Protein kinase biochemistry and drug discovery

Protein kinases are fascinating biological catalysts with a rapidly expanding knowledge base, a growing appreciation in cell regulatory control, and an ascendant role in successful therapeutic intervention. To better understand protein kinases, the molecular underpinnings of phosphoryl group transfer, protein phosphorylation, and inhibitor interactions are examined. This analysis begins with a survey of phosphate group and phosphoprotein properties which provide context to the evolutionary selection of phosphorylation as a central mechanism for biological regulation of most cellular processes. Next, the kinetic and catalytic mechanisms of protein kinases are examined with respect to model aqueous systems to define the elements of catalysis. A brief structural biology overview further delves into the molecular basis of catalysis and regulation of catalytic activity. Concomitant with a prominent role in normal physiology, protein kinases have important roles in the disease state. To facilitate effective kinase drug discovery, classic and emerging approaches for characterizing kinase inhibitors are evaluated including biochemical assay design, inhibitor mechanism of action analysis, and proper kinetic treatment of irreversible inhibitors. As the resulting protein kinase inhibitors can modulate intended and unintended targets, profiling methods are discussed which can illuminate a more complete range of an inhibitor's biological activities to enable more meaningful cellular studies and more effective clinical studies. Taken as a whole, a wealth of protein kinase biochemistry knowledge is available, yet it is clear that a substantial extent of our understanding in this field remains to be discovered which should yield many new opportunities for therapeutic intervention.     

RCSB Protein Data Bank: Enabling biomedical research and drug discovery

Analyses of publicly available structural data reveal interesting insights into the impact of the three‐dimensional (3D) structures of protein targets important for discovery of new drugs (e.g., G‐protein‐coupled receptors, voltage‐gated ion channels, ligand‐gated ion channels, transporters, and E3 ubiquitin ligases). The Protein Data Bank (PDB) archive currently holds > 155,000 atomic‐level 3D structures of biomolecules experimentally determined using crystallography, nuclear magnetic resonance spectroscopy, and electron microscopy. The PDB was established in 1971 as the first open‐access, digital‐data resource in biology, and is now managed by the Worldwide PDB partnership (wwPDB; wwPDB.org ). US PDB operations are the responsibility of the Research Collaboratory for Structural Bioinformatics PDB (RCSB PDB). The RCSB PDB serves millions of RCSB.org users worldwide by delivering PDB data integrated with ～40 external biodata resources, providing rich structural views of fundamental biology, biomedicine, and energy sciences. Recently published work showed that the PDB archival holdings facilitated discovery of ～90% of the 210 new drugs approved by the US Food and Drug Administration 2010–2016. We review user‐driven development of RCSB PDB services, examine growth of the PDB archive in terms of size and complexity, and present examples and opportunities for structure‐guided drug discovery for challenging targets (e.g., integral membrane proteins).     

Protein interactions in 3D: From interface evolution to drug discovery

Over the past 10years, much research has been dedicated to the understanding of protein interactions. Large-scale experiments to elucidate the global structure of protein interaction networks have been complemented by detailed studies of protein interaction interfaces. Understanding the evolution of interfaces allows one to identify convergently evolved interfaces which are evolutionary unrelated but share a few key residues and hence have common binding partners. Understanding interaction interfaces and their evolution is an important basis for pharmaceutical applications in drug discovery. Here, we review the algorithms and databases on 3D protein interactions and discuss in detail applications in interface evolution, drug discovery, and interface prediction.     

Adopting a practical statistical approach for evaluating assay agreement in drug discovery

The authors assess the equivalence of 2 assays and put forward a general approach for assay agreement analysis that can be applied during drug discovery. Data sets generated by different assays are routinely compared to each other during the process of drug discovery. For a given target, the assays used for high-throughput screening and structure-activity relationship studies will most likely differ in their assay reagents, assay conditions, and/or detection technology, which makes the interpretation of data between assays difficult, particularly as most assays are used to measure quantitative changes in compound potency against the target. To better quantify the relationship of data sets from different assays for the same target, the authors evaluated the agreement between results generated by 2 different assays that measure the activity of compounds against the same protein, ALK5. The authors show that the agreement between data sets can be quantified using correlation and Bland-Altman plots, and the precision of the assays can be used to define the expectations of agreement between 2 assays. They propose a scheme for addressing issues of assay data equivalence, which can be applied to address questions of how data sets compare during the lead identification and lead optimization processes in which assays are frequently added and changed.     

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.     

Fragonomics: fragment-based drug discovery

The use of smaller molecules (fragments) in the drug discovery process has led to success in delivering novel leads for many different targets. This process is a highly integrated process, starting from library design to screening and medicinal chemistry. An overview of this process is presented with particular emphasis placed on the NMR aspect of screening.     

Digital drug discovery

A report of the Cambridge Healthtech Institute conference 'Beyond Genome', San Franciso, USA, 13-16 June 2005.     

Dual-purpose drug discovery

A hot area in drug discovery focuses on developing small-molecule inhibitors of the epidermal growth factor receptor (EGFR) signaling pathway.     

Epigenetic drug discovery: targeting DNA methyltransferases

Epigenetic modification of DNA leads to changes in gene expression. DNA methyltransferases (DNMTs) comprise a family of nuclear enzymes that catalyze the methylation of CpG dinucleotides, resulting in an epigenetic methylome distinguished between normal cells and those in disease states such as cancer. Disrupting gene expression patterns through promoter methylation has been implicated in many malignancies and supports DNMTs as attractive therapeutic targets. This review focuses on the rationale of targeting DNMTs in cancer, the historical approach to DNMT inhibition, and current marketed hypomethylating therapeutics azacytidine and decitabine. In addition, we address novel DNMT inhibitory agents emerging in development, including CP-4200 and SGI-110, analogs of azacytidine and decitabine, respectively; the oligonucleotides MG98 and miR29a; and a number of reversible inhibitors, some of which appear to be selective against particular DNMT isoforms. Finally, we discuss future opportunities and challenges for next-generation therapeutics.     

Cyanobacteria: potential candidates for drug discovery

Cyanobacteria are a rich source of vast array of bioactive molecules including toxins with wide pharmaceutical importance. They show varied bioactivities like antitumor, antiviral, antibacterial, antifungal, antimalarial, antimycotics, antiproliferative, cytotoxicity, immunosuppressive agents and multi-drug resistance reversers. A number of techniques are now developed and standardized for the extraction, isolation, detection and purification of cyanobacterial bioactive molecules. Some of the compounds are showing interesting results and have successfully reached to phase II and phase III of clinical trials. These compounds also serve as lead compounds for the development of synthetic analogues with improved bioactivity. Cyanobacterial bioactive molecules hold a bright and promising future in scientific research and great opportunity for drug discovery. This review mainly focuses on anticancerous, antiviral and antibacterial compounds from cyanobacteria; their clinical status; extraction and detection techniques.     

Natural cannabinoids: templates for drug discovery

Recent studies have elucidated the biosynthetic pathway of cannabinoids and have highlighted the preference for a C-3 n-pentyl side chain in the most prominently represented cannabinoids from Cannabis sativa and their medicinally important decarboxylation products. The corresponding C-3 n-propyl side chain containing cannabinoids are also found, although in lesser quantities. Structure-activity relationship (SAR) studies performed on Delta(9)-tetrahydrocannabinol (Delta(9)-THC), the key psychoactive ingredient of Cannabis, and its synthetic analogues have identified the C-3 side chain as the key pharmacophore for ligand affinity and selectivity for the known cannabinoid receptors and for pharmacological potency. Interestingly, the terminal n-pentyl saturated hydrocarbon side chain of endocannabinoids also plays a corresponding crucial role in conferring similar properties. This review briefly summarizes the biosynthesis of cannabinoids and endocannabinoids and focuses on their side chain SAR.     

斑马鱼在新药发现中的应用

在过去20年里,斑马鱼已成为一种重要的模式脊椎动物,在发育、遗传、免疫、肿瘤和毒理等诸多研究领域中被广泛应用。近年来,斑马鱼作为活体模型越来越多地应用于某些生物学过程的药物筛选。通过斑马鱼初步筛选,在药物研发初期可确定化合物的生物学活性、毒性以及副作用等。最近的研究还发现,斑马鱼不仅用于新药筛选,还可用于药物结构的优化。本文重点介绍斑马鱼在新药发现中的应用。     

Bioinformatics and drug discovery

Bioinformatics involves both the automatic processing of large amounts of existing data and the creation of new types of information resource. Both will be required if the data are to be transformed into information and used to help in the discovery of drugs.