Infectious Disorders - Drug Targets (Formerly Current Drug Targets - Infectious Disorders) - Volume 9, Issue 3, 2009

Coming from Crimea, the Black Death spread to Western Europe and North Africa during the 1340s. From 1346 to 1352, the plague killed an estimated 25-40% of Europeans of all age-groups [1], i.e. 30 to 60% of Europe population. One of the earliest and most widely accepted explanations was that God was punishing humanity for their sins. One remedy for the curse was to do penitence. Thus in 1348 there rapidly arose a mass movement of flagellation [2]. In fact flagellation could not really help against such threat. The Black Death or Bubonic plague is caused by Yersinia pestis, a Eubacteria discovered in 1894 by Alexandre Yersin. It is transmitted by the bite of the flea Xenopsylla cheopsis. This flea lives by feeding the blood of many species besides man but its most preferred relationship is with the black rat (Rattus rattus). Fossilized remains of the plague flea have been found in large numbers in Amarna, Egypt [3, 4] about 1350 BC, and thus could be directly linked to the events described in the Book of Samuel [5, 6]. During the epidemic of Bubonic plague in London in 1665-1666, the known treatments were made use of, e.g. the so-famous Theriac or Venice Treacle which is used from the time of ancient Rome as a remedy against poison [7]. Since then, more specialized and novel treatments have been developed. However, since the characterization of Yersinia pestis, numerous drugs have been developed against it, e.g. gentamicin or doxycycline [8]. These researches had been carried out using more elaborated biochemical, biophysical and biological approaches. However, with the explosion of genomic sequencing -815 complete genomes are made available for the scientific community (as of January 2009) [9]- complementing the experimental information with the increasing power of computational facilities has given new opportunities to fight against infectious diseases and to identify pertinent drug targets with novel methodologies. The in silico approaches have been playing a prominent role in this research area during the last decade. This special issue presents the various views about the different in silico approaches by some of the best international research teams. Pr. Sowdhamini's group has compared different genomes from a group of enterobacteric pathogens known to share similar genomic content but having diverse host specificities and distinct disease symptoms [10]. The detailed cross-genome analysis of these subspecies provides an understanding of the diversity and unique attributes defined in the individual Salmonella enterica genomes. Pr. Srinivasan's group develops new approaches dedicated to Plasmodium falciparum analysis, the most important causative agent of malaria [11]. The latter has a very specific genome and thus needs to be studied thoroughly and specifically. They present examples of protein-protein interactions across human and P. falciparum, potentially happening during pathogenesis. Pr. Deleage's work deals with Hepatitis C Virus (HCV). They have developed the European Hepatitis C Virus Database (euHCVdb, http://euhcvdb.ibcp.fr/), a collection of relevant structural models that can help in drug design , with strategies for combating resistance to drug treatment and to have a better understanding structural biology of the HCV [12]. They present some examples of the use of the database. Within this new research field, an important axis of research concerns the transmembrane proteins, they represent about ∼25% of proteins coded by genomes. Moreover, they serve as targets for about 2/3rd of the marketed drugs out of which 50% specifically target a GPCR [13]. As these proteins are embedded in a lipid membrane that constitutes a very specific environment, they represent only about ∼1% of all the available structures, owing to the difficulties associated with their crystallization [14]. Thus alternative approaches are required to obtain structural information. Consequently methods aiming at constructing 3D structural models are becoming an important area of research, for understanding biological mechanisms and interactions [15]. Wang and Duan summarizes the recent computational researches done on CCchemokine receptor 5 (CCR5), an essential co-receptor for HIV entry into the cells and show how the recently solved GPCR structures would provide new insights into the modeling of CCR5-inhibitor binding [16]. Pr. Etchebest's group work focus on an unorthodox chemokine receptor, named DARC, which binds chemokines of both CC and CXC classes and do not couple to G proteins and activate their signaling pathways. DARC had also been associated to cancer progression, numerous inflammatory diseases, and possibly to AIDS. We show our recent development of the construction and analyzes of structural models of DARC [17]. We underline the difficulty to propose pertinent structural models of transmembrane protein using comparative modeling process, and also highlight the use of other dedicated approaches like the analysis using Protein Blocks [18-20]. Finally, we present the recent development of protein - protein docking carried out between DARC structural models and CXCL-8 structures using an innovative hierarchal search procedure, based on both rigid and flexible docking [21].

Genome sequencing efforts of taxonomically proximate organisms successfully divulged proteomic diversity embedded within closely related organisms. The Salmonella enterica subspecies represents a group of enterobacteric pathogens known to share similar genomic content yet possess diverse host specificity and distinct disease symptoms. Study of Salmonella enterica subspecies proteomes reports an overestimation of the proximity among the subspecies. Interestingly, orthology comparison among Salmonella typhi and Salmonella typhimurium across the proteome suggested the metabolic proteins possessed the highest propensity of the divergence, while proteins involved in environment information processing and genetic information processing are least susceptible to evolution. Consistent with earlier reports, transporter proteins and transcription factors are the most populated protein families in the Salmonellae. Several of the unique domains present in Salmonella typhi and Salmonella typhimurium genomes were introduced into the genome through phage invasion and eventually selected. Redundancy and divergence is observed among the metabolic pathway proteins. Though complying with essentiality of their function, the metabolic proteins possess the highest propensity of sampling sequence space for imbibing new function. The detailed cross-genome analysis of the subspecies provides an understanding of diversity and unique attributes defined in the individual Salmonella enterica genomes.

In this article we review the organism-wide biological data available for Plasmodium falciparum (P. falciparum), a malarial parasite, in relation to the data available for other organisms. We provide comparisons at different levels such as amino acid sequences of proteins encoded in the genomes, protein-protein interaction features, metabolic and signaling pathways and processes. Our comparative analyses highlights that P. falciparum is highly diverged compared to most other eukaryotes at all these levels. Despite the extensive variation some of the physical associations between proteins, such as RNA polymerase complex and CDK-cyclin complex are expected to be conserved given their fundamental importance and ubiquitous nature. We also discuss examples of protein-protein interactions across human and P. falciparum potentially happening during pathogenesis.

Hepatitis C is a viral infection of the liver that results in acute hepatitis and chronic liver disease, including cirrhosis and liver cancer. An estimated 170 million persons are chronically infected worldwide. The Hepatitis C virus is the pathogen agent responsible for hepatitis C. HCV is an enveloped RNA-positive virus of the flaviviridae family. The HCV genome shows remarkable sequence variability. This variability leads to the classification of HCV into 6 genotypes, numerous subtypes and HCV exists in each infected patient as quasi-species. The genotype may be linked to the severity of the disease and to the efficiency of the combination treatment with interferon and ribavirin. To date, no vaccine to prevent or cure HCV exists. Numerous HCV specific inhibitors have been designed and some are currently under clinical trials. However, resistances of HCV against these inhibitors have been identified. We developed the European Hepatitis C Virus Database (euHCVdb, http://euhcvdb.ibcp.fr/), a collection of functionally and structurally (3D-models) annotated HCV sequences integrated with sequence and structure analysis tools. We show below how the euHCVdb database is a useful in silico tool that can help drug design, combating resistance to drug treatment and understand structural biology of the HCV.

The CC-chemokine receptor 5 (CCR5), a membrane protein belonging to the G-protein coupled receptor superfamily, has been identified as an essential co-receptor for HIV entry into the cells, and small molecules that inhibit HIV entry by targeting CCR5 have been in fast development as antiviral agents. This review focuses on computational studies of predicting the CCR5 structure and its interactions with known small molecule inhibitors and discusses how the recently solved GPCR structures would provide new insights into the modeling of CCR5-inhibitior binding. In addition, this review pays a particular attention to the design of the inhibitors that specifically interrupt the viral entry co-receptor activity of CCR5 while preserving its normal chemokine receptor function to minimize side effects and toxicity.

The Duffy Antigen/Receptor for Chemokine (DARC) is a seven segment transmembrane protein. It was firstly discovered as a blood group antigen and was the first specific gene locus assigned to a specific autosome in man. It became more famous as an erythrocyte receptor for malaria parasites (Plasmodium vivax and Plasmodium knowlesi), and finally for chemokines. DARC is an unorthodox chemokine receptor as (i) it binds chemokines of both CC and CXC classes and (ii) it lacks the Asp-Arg-Tyr consensus motif in its second cytoplasmic loop hence cannot couple to G proteins and activate their signaling pathways. DARC had also been associated to cancer progression, numerous inflammatory diseases, and possibly to AIDS. In this review, we will summarize important biological data on DARC. Then we shall focus on recent development of the elaboration and analyzes of structural models of DARC. We underline the difficulty to propose pertinent structural models of transmembrane protein using comparative modeling process, and other dedicated approaches as the Protein Blocks. The chosen structural models encompass most of the biochemical data known to date. Finally, we present recent development of protein - protein docking between DARC structural models and CXCL-8 structures. We propose a hierarchal search based on separated rigid and flexible docking.

Malaria remains one of the most burdensome human infectious diseases, with a high rate of resistance outbreaks and a constant need for the discovery of novel antimalarials and drug targets. For several reasons, Plasmodial proteins are difficult to characterise structurally using traditional physical approaches. However, these problems can be partially overcome using a number of in silico approaches. This review describes the peculiarities of malaria proteins and then details various in silico strategies to select and allow descriptions of the molecular structures of drug target candidates as well as subsequent rational approaches for drug design. Chiefly, homology modelling with specific focus on unique aspects of malaria proteins including low homology, large protein size and the presence of parasite-specific inserts is addressed and alternative strategies including multiple sequence and structure-based prediction methods, samplingbased approaches that aim to reveal likely global or shared features of a Plasmodial structure and the value of molecular dynamics understanding of unique features of Plasmodial proteins are discussed. Once a detailed description of the drug target is available, in silico approaches to the specific design of an inhibitory drug thereof becomes invaluable as an economic and rational alternative to chemical library screening.

The resurgence of drug resistant tuberculosis (TB) is a major global healthcare problem. Mycobacterium tuberculosis (MTB), TB's causative agent, evades the host immune system and drug regimes by entering prolonged periods of nonproliferation or dormancy. The identification of genes essential to the bacterium in its dormancy phase infections is a key strategy in the development of new anti-TB therapeutics. The rapid expansion of TB-related genomic data sources including DNA sequences, transcriptomic and proteomic profiles, and genome-wide essentiality data, present considerable opportunities to apply advanced computational analyses to predict potential drug targets. However, the translation of in silico predictions to effective clinical therapies remains a significant challenge.

Dengue virus (DENV), a member of the family Flaviviridae, presents a tremendous threat to global health since an estimated 2.5 billion people worldwide are at risk for epidemic transmission. DENV infections are primarily restricted to sub-tropical and tropical regions; however, there is concern that the virus will spread into new regions including the United States [1]. There are no approved antiviral drugs or vaccines to combat dengue infection, although DENV vaccines have entered Phase 3 clinical trials. Drug discovery and development efforts against DENV and other viral pathogens must overcome specificity, efficacy, safety, and resistance challenges before the shortage of licensed drugs to treat viral infections can be relieved. Current drug discovery methods are largely inefficient and thus relatively ineffective at tackling the growing threat to public health presented by emerging and remerging viral pathogens. This review discusses current and newly implemented structure-based computational efforts to discover antivirals that target the DENV NS3 protease, although it is clear that these computational tools can be applied to most disease targets.

Resolved three-dimensional protein structures are a major source of information for understanding protein functional properties. The current explosive growth of publicly available protein structures is producing large volumes of data for computational modelling and drug design methods. Target-based in silico drug design tools aid design and optimize compounds to bind to specific targets. MED-SuMo is a powerful technology for comparing local regions on protein surfaces, allowing similarities to be discovered and explored. This is a target-based tool that can exploit all available macromolecule structures. Its computational efficiency differentiates its approach from widely used methods such as docking and scoring, or map-based methods. As a result, MED-SuMo contributes to a large variety of real-world drug discovery applications. We review specific applications where MED-SuMo performed a significant role. These examples include functional annotation, pocket profiling, structural superposition, and functional binding site classification. We also review cases where MED-SuMo provided an innovative solution to frequent undertakings of the medicinal chemist and molecular modeller during lead discovery and lead optimization. These further cases include drug repurposing and fragment-based drug design.

The recent years have seen the emergence of diseases which have spread very quickly all around the world either through human travels like SARS or animal migration like avian flu. Among the biggest challenges raised by infectious emerging diseases, one is related to the constant mutation of the viruses which turns them into continuously moving targets for drug and vaccine discovery. Another challenge is related to the early detection and surveillance of the diseases as new cases can appear just anywhere due to the globalization of exchanges and the circulation of people and animals around the earth, as recently demonstrated by the avian flu epidemics. For 3 years now, a collaboration of teams in Europe and Asia has been exploring some innovative in silico approaches to better tackle avian flu taking advantage of the very large computing resources available on international grid infrastructures. Grids were used to study the impact of mutations on the effectiveness of existing drugs against H5N1 and to find potentially new leads active on mutated strains. Grids allow also the integration of distributed data in a completely secured way. The paper proposes new approaches for the integration of existing data sources towards a global surveillance network for molecular epidemiology and in silico drug discovery.

Text mining has become an integral part of all research in the medical field. Many text analysis software platforms support particular use cases and only those. We show an example of a bibliographic tool that can be used to support virtually any use case in an agile manner. Here we focus on a Pipeline Pilot web-based application that interactively analyzes and reports on PubMed search results. This will be of interest to any scientist to help identify the most relevant papers in a topical area more quickly and to evaluate the results of query refinement. Links with Entrez databases help both the biologist and the chemist alike. We illustrate this application with Leishmaniasis, a neglected tropical disease, as a case study.