Quantitative analysis on the characteristics of targets with FDA approved drugs

Accumulated knowledge of genomic information, systems biology, and disease mechanisms provide an unprecedented opportunity to elucidate the genetic basis of diseases, and to discover new and novel therapeutic targets from the wealth of genomic data. With hundreds to a few thousand potential targets available in the human genome alone, target selection and validation has become a critical component of drug discovery process. The explorations on quantitative characteristics of the currently explored targets (those without any marketed drug) and successful targets (targeted by at least one marketed drug) could help discern simple rules for selecting a putative successful target. Here we use integrative in silico (computational) approaches to quantitatively analyze the characteristics of 133 targets with FDA approved drugs and 3120 human disease genes (therapeutic targets) not targeted by FDA approved drugs. This is the first attempt to comparatively analyze targets with FDA approved drugs and targets with no FDA approved drug or no drugs available for them. Our results show that proteins with 5 or fewer number of homologs outside their own family, proteins with single-exon gene architecture and proteins interacting with more than 3 partners are more likely to be targetable. These quantitative characteristics could serve as criteria to search for promising targetable disease genes.     

新的抗真菌药物靶点研究进展

近30年来,侵袭性真菌感染发病率持续上升,病死率居高不下,而治疗药物十分有限是造成其高致死率的重要因素之一。因此,发现新的抗真菌靶点和药物,已成为迫切需要。正在研究的新的抗真菌靶点如下：一是信号通路介导的抗真菌靶点,包括钙调神经磷酸酶及其分子伴侣Hsp90、3-磷酸肌醇依赖性蛋白激酶（PKH）以及参与Ras蛋白修饰的相关酶等,其拮抗剂包括传统免疫抑制剂的类似物以及Hsp90抗体、KP-372-1和PS77以及手霉素A等;二是GPI锚定蛋白合成通路的催化酶,其抑制剂有E1210和M720等化合物;三是分泌型天冬氨酸蛋白酶,肽类、逆转录病毒抑制剂,以及砜类的衍生物等均可以抑制这一靶点;四是海藻糖的合成的两个关键酶Tps1和Tps2。鉴于侵袭性真菌感染严重影响人类公共健康安全,而新型抗真菌药物的研发又依赖于新靶点的探索,因此,本文靶向这一核心真菌临床问题,系统介绍了当前新的抗真菌药物靶点发展概况,并在靶点选择可行性以及针对靶点的药物研发策略上提出见解。     

Predict potential drug targets from the ion channel proteins based on SVM

The identification of molecular targets is a critical step in the drug discovery and development process. Ion channel proteins represent highly attractive drug targets implicated in a diverse range of disorders, in particular in the cardiovascular and central nervous systems. Due to the limits of experimental technique and low-throughput nature of patch-clamp electrophysiology, they remain a target class waiting to be exploited. In our study, we combined three types of protein features, primary sequence, secondary structure and subcellular localization to predict potential drug targets from ion channel proteins applying classical support vector machine (SVM) method. In addition, our prediction comprised two stages. In stage 1, we predicted ion channel target proteins based on whole-genome target protein characteristics. Firstly, we performed feature selection by Mann-Whitney U test, then made predictions to identify potential ion channel targets by SVM and designed a new evaluating indicator Q to prioritize results. In stage 2, we made a prediction based on known ion channel target protein characteristics. Genetic algorithm was used to select features and SVM was used to predict ion channel targets. Then, we integrated results of two stages, and found that five ion channel proteins appeared in both prediction results including CGMP-gated cation channel beta subunit and Gamma-aminobutyric acid receptor subunit alpha-5, etc., and four of which were relative to some nerve diseases. It suggests that these five proteins are potential targets for drug discovery and our prediction strategies are effective.     

Validation of ion channel targets

A prerequisite for a successful target-based drug discovery program is a robust data set that increases confidence in the validation of the molecular target and the therapeutic approach. Given the significant time and resource investment required to carry a drug to market, early selection of targets that can be modulated safely and effectively forms the basis for a strong portfolio and pipeline. In this article we present some of the more useful scientific approaches that can be applied toward the validation of ion channel targets, a molecular family with a history of clinical success in therapeutic areas such as cardiovascular, respiratory, pain and neuroscience.     

Can medical genetics and evolutionary biology inspire drug target identification?

New strategies for target identification are urgently needed to tackle the current productivity challenges in drug discovery. By examining successful human drug targets, it can be seen that approximately 50% are associated with genetic disorders. Further analysis shows that these successfully targeted genes share some common evolutionary features, which strongly suggests that evolutionary information can help identify drug targets with the greatest potential for therapeutic development.     

In vivo drug target discovery: identifying the best targets from the genome

A vast number of genes of unknown function threaten to clog drug discovery pipelines. To develop therapeutic products from novel genomic targets, it will be necessary to correlate biology with gene sequence information. Industrialized mouse reverse genetics is being used to determine gene function in the context of mammalian physiology and to identify the best targets for drug development.     

Evolutionary patterning: a novel approach to the identification of potential drug target sites in Plasmodium falciparum

Malaria continues to be the most lethal protozoan disease of humans. Drug development programs exhibit a high attrition rate and parasite resistance to chemotherapeutic drugs exacerbates the problem. Strategies that limit the development of resistance and minimize host side-effects are therefore of major importance. In this study, a novel approach, termed evolutionary patterning (EP), was used to identify suitable drug target sites that would minimize the emergence of parasite resistance. EP uses the ratio of non-synonymous to synonymous substitutions (omega) to assess the patterns of evolutionary change at individual codons in a gene and to identify codons under the most intense purifying selection (omega < or = 0.1). The extreme evolutionary pressure to maintain these residues implies that resistance mutations are highly unlikely to develop, which makes them attractive chemotherapeutic targets. Method validation included a demonstration that none of the residues providing pyrimethamine resistance in the Plasmodium falciparum dihydrofolate reductase enzyme were under extreme purifying selection. To illustrate the EP approach, the putative P. falciparum glycerol kinase (PfGK) was used as an example. The gene was cloned and the recombinant protein was active in vitro, verifying the database annotation. Parasite and human GK gene sequences were analyzed separately as part of protozoan and metazoan clades, respectively, and key differences in the evolutionary patterns of the two molecules were identified. Potential drug target sites containing residues under extreme evolutionary constraints were selected. Structural modeling was used to evaluate the functional importance and drug accessibility of these sites, which narrowed down the number of candidates. The strategy of evolutionary patterning and refinement with structural modeling addresses the problem of targeting sites to minimize the development of drug resistance. This represents a significant advance for drug discovery programs in malaria and other infectious diseases.     

Mining predicted essential genes of Brugia malayi for nematode drug targets

We report results from the first genome-wide application of a rational drug target selection methodology to a metazoan pathogen genome, the completed draft sequence of Brugia malayi, a parasitic nematode responsible for human lymphatic filariasis. More than 1.5 billion people worldwide are at risk of contracting lymphatic filariasis and onchocerciasis, a related filarial disease. Drug treatments for filariasis have not changed significantly in over 20 years, and with the risk of resistance rising, there is an urgent need for the development of new anti-filarial drug therapies. The recent publication of the draft genomic sequence for B. malayi enables a genome-wide search for new drug targets. However, there is no functional genomics data in B. malayi to guide the selection of potential drug targets. To circumvent this problem, we have utilized the free-living model nematode Caenorhabditis elegans as a surrogate for B. malayi. Sequence comparisons between the two genomes allow us to map C. elegans orthologs to B. malayi genes. Using these orthology mappings and by incorporating the extensive genomic and functional genomic data, including genome-wide RNAi screens, that already exist for C. elegans, we identify potentially essential genes in B. malayi. Further incorporation of human host genome sequence data and a custom algorithm for prioritization enables us to collect and rank nearly 600 drug target candidates. Previously identified potential drug targets cluster near the top of our prioritized list, lending credibility to our methodology. Over-represented Gene Ontology terms, predicted InterPro domains, and RNAi phenotypes of C. elegans orthologs associated with the potential target pool are identified. By virtue of the selection procedure, the potential B. malayi drug targets highlight components of key processes in nematode biology such as central metabolism, molting and regulation of gene expression.     

Proteases as drug targets

The effective management of AIDS with HIV protease inhibitors, or the use of angiotensin-converting enzyme inhibitors to treat hypertension, indicates that proteases do make good drug targets. On the other hand, matrix metalloproteinase (MMP) inhibitors from several companies have failed in both cancer and rheumatoid arthritis clinical trials. Mindful of the MMP inhibitor experience, this chapter explores how tractable proteases are as drug targets from a chemistry perspective. It examines the recent success of other classes of drug for the treatment of rheumatoid arthritis, and highlights the need to consider where putative targets lie on pathophysiological pathways--regardless of what kind of therapeutic entity would be required to target them. With genome research yielding many possible new drug targets, it explores the likelihood of discovering proteolytic enzymes that are causally responsible for disease processes and that might therefore make better targets, especially if they lead to the development of drugs that can be administered orally. It also considers the impact that biologics are having on drug discovery, and in particular whether biologically derived therapeutics such as antibodies are likely to significantly alter the way we view proteases as targets and the methods used to discover therapeutic inhibitors.     

Cordycepin: A bioactive metabolite with therapeutic potential

Cytotoxic nucleoside analogues were the first chemotherapeutic agents for cancer treatment. Cordycepin, an active ingredient of the insect fungus Cordyceps militaris, is a category of compounds that exhibit significant therapeutic potential. Cordycepin has many intracellular targets, including nucleic acid (DNA/RNA), apoptosis and cell cycle, etc. Investigations of the mechanism of anti-cancer drugs have yielded important information for the design of novel drug targets in order to enhance anti-tumor activity with less toxicity to patients. This extensive review covers various molecular aspects of cordycepin interactions with its recognized cellular targets and proposes the development of novel therapeutic strategies for cancer treatment.     

Combinatorial selection of RNA ligands for complex cellular targets : the RNA liagands-based proteomics

This study explores the selection of high affinity RNA ligands for the complex cellular targets present in crude HeLa nuclear extract through directed evolution and deconvolution. RNA ligands for the mixed nuclear targets were selected from around 6 x 10(14) RNA sequences through an iterated enrichment process. RNA ligands for various gene products of the extract were simultaneously selected and were shown to specifically interact with their target molecules. The target molecules were isolated from the nuclear extract by affinity chromatography using columns tagged with the RNA ligands, resolved on two-dimensional gels, and identified by mass spectrometry. These RNA ligands may be useful in characterizing novel functions of cellular proteins and modulating complex molecular events.     

Exploration of Target Spaces in the Human Genome for Protein and Peptide Drugs

After decades of development, protein and peptide drugs have now grown into a major drug class in the marketplace. Target identification and validation are crucial for the discovery of protein and peptide drugs, and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection. However,owing to the developmental history in the pharmaceutical industry, previous systematic exploration of the target s...     

The sensitivity of gap analysis to conservation targets

A crucial stage in systematic conservation planning is the definition of explicit conservation targets to be achieved by a network of protected areas. A wide variety of targets have been employed, including overall percentage area, uniform representation of biodiversity features, and variable targets according to conservation interest. Despite the diversity of options, most studies adopt a particular set of targets without further explanation, and few have investigated the effect of target selection on their results. Here, using a data set on the distribution of plants and terrestrial vertebrates in southern France, we investigate how variation in targets can affect both stages of a gap analysis: the assessment of the completeness of an existing reserve network, and the prioritization of areas for its expansion. Target selection had a major impact on the gap analysis results, with uniform targets (50% of each species’ range) emphasizing the representation of common species, and contrasting targets (weighted according to species’ conservation interest) concentrating attention on high conservation interest species and the areas where they occur. Systematic conservation planning exercises should thus pay close attention to the definition and justification of the representation targets employed.