Introduction

Discovery of antiviral drugs has always been an opportunistic endeavor. Small molecules in general and nucleoside analogues in particular have led investigators to discover uncharacterized viral gene products that could be exploited for the purpose of antiviral chemotherapy. Great strides have also been made in understanding fundamental events in the viral replication cycle including the binding of viral glycoproteins to cellular receptors, viral regulatory proteins that control expression of viral and cellular gene expression, viral genes that affect the synthesis and packaging of the viral genome, and viral factors that subvert the host immune response (Whitley and Roizman, 2001). Many of the viral genes that contribute to these processes are known and for some of them, the precise function is understood at the molecular level. For these targets it is comparatively simple to reduce the essential function to a biochemical assay, such as a polymerase or protease assay for use in a high throughput screen in order to identify small molecule inhibitors of enzyme function (Liu and Roizman, 1993). This approach has facilitated the proactive and rational search for specific enzyme inhibitors and has led to the development of effective antiviral therapies. Although this approach is effective, it requires well-characterized targets with a defined biochemical function, and can be applied only to a very small proportion of the essential viral gene products. At present, the best targets for antiviral chemotherapy likely remain undescribed and unutilized.

The development of new classes of antiviral drugs is limited by our understanding of biology. More often than not, it is unclear which viral gene products contribute to essential functions. Less clear still is the precise function or functions that the constituent proteins perform such that the biochemical activity can not be modeled in vitro. Thus, the challenge and rate-limiting step in this process is to identify the functions of gene products that are required for viral replication and to define precisely the molecular mechanisms involved with these processes.

Advances in genomics and associated technologies are offering new opportunities to investigators to answer such questions. This endeavor is driving technological developments in bioinformatics, genetics and laboratory automation and promises to generate a host of new resources that can be brought to bear on all fields of biology (Collins et al., 2003). Advances in molecular virology will help drive this effort and will also benefit tremendously as virus–host interactions are defined in more detail and on a grander scale. Genomics, proteomics and related technologies can also be applied specifically to the discovery and development of antiviral therapies. Techniques and approaches that are particularly suited to this task are discussed and early experiments in this arena will be described.

Development of bioinformatics and computational tools

The emerging and evolving fields of genomics and proteomics are changing the way that biological research is conducted and technologies associated with these efforts can be applied effectively to the study of viral biology. The development of these fields is driven in part by the technological advances that produce genomic sequences more efficiently every year (Venter et al., 2003). Significant technological advances in chemistry, biotechnology, and bioinformatics are also major drivers in this field and each of these efforts has produced tremendous new resources and even greater quantities of raw data. Perhaps the most defining characteristic of these emerging fields of research is the tremendous size and complexity of the data sets they generate. Significant computational resources are required to manage the volumes of data, manipulate it, and parse it into databases that can be queried by researchers. This process requires training in computer science and mathematics. Investigators who specialize in these fields will contribute greatly to any future drug discovery projects using these new technologies. Bioinformatics resources are also required to analyze the data, identify patterns and display the patterns in a way that can be interpreted by investigators in the field. Data that is processed in this manner is designed to help investigators understand the problem at hand and can help them make hypotheses. Inferences drawn from these efforts need to be tested and confirmed in the laboratory, but the process helps to focus valuable research time on prioritized compounds or genes.

The application of computational methods to the study of herpesviruses biology is particularly intriguing. Large DNA viruses present a unique set of well characterized genomes that are comparatively well studied and characterized (Davison et al., 2002). New tools developed by scientists in bioinformatics can be applied to these genomes to test their ability to predict the organization of viral genes, their global coding capacity and the function of viral proteins (Novotny et al., 2001; Rigoutsos et al., 2003). Laboratory confirmation of transcriptional patterns and gene expression and gene function is essential to this process, particularly early on when the bioinformatics algorithms are being tested on these genomes. The genetic tractability of herpesviruses and availability of genome wide methods to test these hypotheses make this an ideal system to validate new approaches to study biological processes (Stingley et al., 2000). Communication and cooperation between the specialists in bioinformatics and bench level virologists is essential and will facilitate the incremental improvement of algorithms predictive of biological structure and function. The iterative process of algorithm refinement and biological confirmation will lead to computational approaches that are increasingly predictive of viral biology.

Studying new methods in bioinformatics in herpesviruses presents certain virus specific problems. Even within the alphaherpesviruses, the variation in G + C content will present a codon bias that must be taken into consideration. The genomic organization of 3′ coterminal transcription units as well as readthrough of certain stop codons will complicate the computational analysis as well as laboratory characterization of gene expression. Indeed, this is true in other viruses, such as SV40 where algorithms trained on mammalian genomes fail in many cased because of conservative assumptions about splicing sites and polyadenylation signals. Nevertheless, the genomics studies at the level of herpesviruses will be particularly instructive and will guide efforts to define and interpret sequences from more complex genomes, such as the human genome.

Data relevant to the discovery of new drugs tend to be concentrated at the intersection of large data sets. Databases that contain information related to biological function, chemical structure, and the biologic activity of small molecules all can contribute to the search for new lead compounds. The nature of this problem is inherently complex and databases will be required to handle the volumes of data. In the near term, computational methods can suggest aspects of viral replication that might be targeted specifically by small molecule inhibitors. Similarly, these methods may identify small molecules with well described biological effects that could be used to probe cellular functions that may be required by the virus. In the long term, computational approaches have the potential to link databases containing information on chemical structure, protein structure, biochemical activity, and biologic activity of small molecules. It may eventually be possible to mine existing data in a meaningful way to suggest chemical classes that might be used to inhibit known biochemical activities.

Impact of genomics and related fields on herpesvirus research

The scientific landscape has changed dramatically in the last 15 years with the completion of the DNA sequence for the genomes of all eight known human herpesviruses (Baer et al., 1984; Chee et al., 1990; Davison and Scott, 1986; Dolan et al., 1998; Gompels et al., 1995; McGeoch et al., 1988, 1991; Pfeiffer et al., 1995; Russo et al., 1996). This is a very significant step in the path towards understanding the biology of herpesvirus infections. These and other resources in the publicly available databases are tremendously valuable to scientists studying herpesvirus infections and provide a map and common reference points to help scientists describe precisely viral transcripts and open reading frames (ORFs). Genomic sequences can also be used to compare genomic organization among all the herpesviruses, and represents a starting point in the path towards the identifying evolutionary relationships in this virus family. Importantly, the nucleotide sequences in the databases are not static. Sequence data are inherently noisy and most genomic sequences in GenBank have mistakes that need to be corrected when they are identified, especially in information-dense viral genomes. Annotations of viral genomes are conducted with the best tools available at the time of submission, but they become outdated as gene prediction algorithms improve and as experiments in the laboratory identify new genes (Cha et al., 1996). Since the annotation process is evolving, scientists should expect to find inconsistencies among the annotations of different genomes, as the terminology used to describe gene function is continually evolving (Ashburner et al., 2000). Thus, prototype viral genomes will need to be updated and reannotated in an iterative process, particularly as new strains and viruses are sequenced (Davison et al., 2003). Versioning of genomes and annotations is becoming more important when comparing sequences and annotations due to the continual annotation process, analogous to the versioning of software and human genome release versions in NCBI.

Genomics studies in herpesviruses initially focused on defining the structure and coding capacity of each of the viral genomes and comparing them with annotated sequences of related viruses. The DNA sequence and structure of the genomes is comparatively simple to define, yet even for these simple organisms it is not possible to predict with any certainty which, if any genes will be expressed in the context of an infection. Depending on the algorithms used, different numbers of ORFs will identified and laboratory experimentation is required to confirm which ORFs are actually expressed in the context of a viral infection (Davison et al., 2003; Rigoutsos et al., 2003). As synthesized microarrays become less expensive, oligonucleotide probes which hybridize to putative exons and splice junctions can be used for confirming the expression of predicted transcripts and splice variants in a bulk fashion (Shoemaker et al., 2001). Continued experimentation and consistent reannotation among the submitted sequences will help define how these viruses, and indeed their human host use DNA to regulate and code for all the required functions. As this knowledge base expands, relationships among all the herpesviruses will crystallize and molecular evolutionary patterns will start to emerge.

The viral proteome represents all of the proteins expressed by the virus and reflects both the processing of RNA transcripts as well as the post-translational processing that occurs. Proteomics methods have the potential to be particularly powerful because it can distinguish the modification of viral gene products during the course of viral infection and can help characterize how proteolysis, glycosylation and phosphorylation impact viral replication. At one level, mass spectrometry and protein microsequencing can be used to identify sets of viral proteins involved in a particular biologic process (Greco et al., 2001). Genome wide searches using algorithms to predict protein structure or identify conserved motifs can also be used to generate hypotheses regarding protein function (Oien et al., 2002). Yeast two-hybrid studies provide an experimental approach for the study protein-protein interactions among viral and cellular proteins and will help to provide information about functional complexes in an infected cell. Efforts underway to construct protein-protein interaction maps have the potential to help understand which gene products cooperate in biological processes.

The emerging field of chemical genetics will also likely impact the discovery of antiviral therapies and could be one of the most useful tools (Strausberg and Schreiber, 2003). Genes can be classified in orthologous groups (Tatusov et al., 1997) and small molecules can be classified into families based on the chemical structure. Genetics can be used to characterize the phenotype associated with a particular gene, and in an analogous manner the biological effect of a drug, or chemotype, can be associated with small molecules. Relating chemotypes and genotypes can help identify the molecular targets and pathways affected by groups of compounds. This information can be used to infer the mechanism of action of candidate molecules by comparing the chemotype with existing phenotypes associated with viruses containing mutations in different pathways. This process might also be particularly useful in identifying cellular response patterns associated with drug toxicity that could be used to eliminate lead compounds early in the discovery process (Waring et al., 2002).

New resources for use in drug discovery

Genomics and proteomics are promising new fields with lofty goals, but can they provide immediate utility to efforts currently underway to identify new classes of antiviral drugs? At present, the impact of these fields is most apparent in the widespread use of data and tools provided by the publicly available databases. The GenBank, EMBL, and DDBJ nucleotide databases provided freely on the web are a tremendous resource to everyone and most researchers use the databases or related tools on a regular basis. The National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/) and the European Bioinformatics Institute (http://www.ebi.ac.uk/services/index.html) websites in particular provide access, to basic tools and services that are used in laboratories every day. These tools include nucleotide and protein database searching tools, genome maps, structural databases and pattern recognition tools. The STDGEN database provided by Los Alamos National Laboratories (http://www.stdgen.lanl.gov/) is a wonderful resource that provides specific genomic and proteomic information on herpesviruses and contains BLAST search results with links to other viral orthologues and conserved orthologous groups. Tools provided by these organizations are continually upgraded and new tools appear on a regular basis. Thus, a review of the available tools will be quickly outdated and can not substitute for a trip to the web sites listed in this text.

A number of new material resources have also been created through the automation of laboratory procedures. Microarrays of several different types are commercially available for characterizing changing transcription patterns in infected cells (Browne et al., 2001). Herpesvirus specific microarrays have also been constructed and can rapidly assess viral transcript changes in response to stimuli (Stingley et al., 2000). Expression clone libraries have been produced in efforts designed to assay gene function and virus knockout libraries have been assembled by a number of investigators. Each of the resources described here has the potential to be used in a genome wide search to identify viral genes that are important in the replication process.

Application of new technologies to cell-based antiviral assays

New tools and resources described herein, have the potential to be extremely useful in the drug discovery process and some strategies are currently in use. Many of the new strategies are unproven, and as such, are high risk activities that are used sparingly in the industrial setting. Nevertheless, high risk–high reward strategies have their place in the discovery process, particularly in the search for new classes of antivirals. The specific application of new technologies and resources to conventional screening and development activities has the potential to make an immediate and positive impact on the drug discovery process.

Cell-based screens for small molecules with antiviral activity have been utilized for all of the herpesviruses. Historically, most approved therapies for herpesvirus infections resulted from this approach to antiviral discovery, but continued screening of the same libraries with very similar assays is not likely to identify new lead compounds. It is possible to change the assays to bias the hit compounds away from molecules already identified in previous screens and towards molecules with different mechanisms of action. For example, screening recombinant viruses that lack the thymidine kinase (in herpes simplex virus (HSV)), or recombinant viruses lacking the UL97 kinase (in cytomegalovirus (CMV)) will identify small molecules and nucleosides that do not require phosphorylation to be active. Lead compounds identified in these particular screens would also be candidates for the treatment of drug resistant infections. Genetically sensitized viruses, like the recombinants described above, might react more strongly to weakly active compounds and could unmask these molecules in existing chemical libraries. Candidate molecules with unusual mechanisms of action or good pharmacologic properties could then be selected for chemical modification to improve the antiviral activity.

As an alternative to the conventional endpoint of cytopathic effect inhibition, the affect of small molecules on viral transcriptional patterns could be monitored to reveal molecules with unusual mechanisms of action. Microarray technologies would be particularly useful in this regard, but it limits the number of compounds that could be examined in detail. In essence, this approach has already been validated through the characterization of gamma or late viral transcripts by treatment with phosphonoacetic acid (Stingley et al., 2000). The cellular transcriptional response to small molecules could also be monitored simultaneously to measure changes in the host response to infection induced by the small molecules (Browne et al., 2001; Fruh et al., 2001). Microarrays can also help identify the mechanisms of transformation in infected cells and could potentially lead to better therapies for virus induced malignancies (Moses et al., 2002). Potential toxicities could also be identified at an early stage by monitoring the induction of cellular genes associated with the response to toxic compounds (Waring et al., 2002). Data generated by such an approach could also be queried at a later date using chemical genetics techniques to classify and cluster the chemotypes of molecules in the library.

Application of new technologies to biochemical assays

Biochemical screening assays will likely derive the greatest benefit from genomics and proteomics technologies. The increased characterization of viral gene products will likely identify additional biochemical activities that can be converted rapidly into small molecule screens. Homology searching algorithms also play a major role because of their ability to extend knowledge from one herpesvirus to related viruses. BLAST searches with a known gene can identify orthologues in other herpesviruses and related genes (paralogues) within the same virus in an effort to identify viral proteins with a similar biochemical activity (Davison et al., 2002). For example, an orthologue of the HSV protease was identified in CMV and a similar biochemical assay could be used for both to screen for inhibitors of this biochemical activity (Jarvest et al., 1999; Pinto et al., 1999).

Many viral gene products have no known function, yet possess characteristic motifs that could potentially be used in biochemical screens (Rigoutsos et al., 2003). Hypotheses generated by searches such as these could be tested in the laboratory and if confirmed could be used in a biochemical screen. For instance, nucleotide binding motifs in poorly characterized genes could be used to identify nucleosides that bind to these sites with high affinity. Similarly, a structural search revealed that UL57 in CMV appears to be related at a structural level to some endonucleases (Novotny et al., 2001). If this activity were confirmed in the laboratory, a biochemical screen could be used to identify specific inhibitors of this activity and might be effective in inhibiting viral replication given that this gene is known to be essential for viral replication.

Biochemical assays based on protein-protein interactions are capable of identifying molecules with antiviral activity. Information garnered from proteomics methods or yeast-two hybrids could be used to devise a rapid assay for protein–protein interactions that are presumed to be important for viral replication. Screening of small molecule libraries or peptide libraries could identify specific inhibitors that also possess antiviral activity (Liuzzi et al., 1994). This same strategy could be employed to identify inhibitors that disrupt the interaction of viral and cellular proteins that appear to be important viral replication. If fact, it may be possible to perform the high throughput screen directly in yeast if the interaction was originally defined in this system.

The best characterized molecular targets have had their crystal structures determined. Given these data, it is possible to recrystallize these molecules with known inhibitors to identify protein binding sites or to dock small molecules in silico to identify molecules in improved binding affinities to the active site (Stoll et al., 2003). This approach is particularly useful in lead optimization and medicinal chemistry efforts to increase potency. For any of the technologies discussed here, their greatest utility is generating testable hypotheses that could identify new and unexploited targets for antiviral therapy.

Application of new technologies to functional assays

Genetic approaches can identify gene products that are essential for viral replication, but without a biochemical assay, it is not possible to screen for inhibitors of these molecules. Functional genomics approaches can be employed to try to identify surrogate phenotypes for interesting genes. With these sorts of assays, the surrogate assays do not necessarily measure the relevant functional aspect of the gene in question. Any inhibitors identified from screens based on surrogate assays need to be validated in secondary assays (Tugendreich et al., 2001). Although surrogate approaches are high risk high reward propositions, they are particularly useful for screening ion channels or other molecules that require an intact membrane for activity (Hahnberger et al., 1996).

Application of new technologies to characterize mechanism of action and spectrum of activity

New technological developments also impact how researchers conduct preclinical studies on compounds with antiviral activity. Mechanism of action studies still involve the isolation of drug resistant viruses, but genomic sequencing of drug resistant viruses can be faster than conducting conventional marker transfer studies to identify the molecular targets of investigational drugs (S. W. Chou, pers. commun.). Direct sequencing is also cost effective in identifying resistance mutations in clinical isolates where the mechanisms of drug resistance are well characterized (Lurain et al., 2001).

Genomics approaches can also be used to help predict the spectrum of activity of a compound if the mechanism of action is known. Homology searches can be used to identify gene families common to a wide variety of organisms and are called clusters of orthologous groups (COGs) (Tatusov et al., 1997). This process was also conducted for all sequenced herpesviruses and a set of viral COGs was assembled (Montague and Hutchison, 2000). In addition to helping define orthologues in this group of viruses, the COGs can also be used to construct genome-wide phylogenetic trees, that closely match trees constructed using the highly conserved core genes (Davison et al., 2002). COGs can also be clustered based on the viruses in which they appear, and can help to define a theoretical spectrum of activity for antiviral drugs based on the conservation of the molecular targets. A comparison of the predicted drug efficacy (shaded area) is compared with antiviral activity reported in the literature (+ or −) in Table 67.1. A number of interesting disparities are immediately apparent. Penciclovir did not appear to be active against EBV, and neither acyclovir nor penciclovir exhibited significant antiviral activity against HHV8, despite the fact that they possess relatively well conserved thymidine kinases. These results are explained in part by apparent low activity of the HHV8 thymidine kinase and narrow substrate specificity (Gustafson et al., 2000). The activity of ganciclovir in viruses without TK orthologues can be explained by the alternative phosphorylation by UL97 protein kinase in cytomegalovirus and related orthologues in the other β herpesviruses (Littler et al., 1992; Sullivan et al., 1992). The high degree of conservation among the herpesviruses in the DNA polymerase is very predictive for broad efficacy of foscarnet, cidofovir, and the 4-oxoquinoline derivatives. The exception is the reduced susceptibility of HHV6A,B, that can be explained by an unusual V823A polymorphism in the active site of these viruses. Of interest, both of the benzimidazole analogs (maribavir and BDCRB) exhibit a very limited spectrum of activity, which is not predicted given the well conserved molecular target, particularly with BDCRB. Like other computational methods described herein, their greatest utility of this approach is generating a hypothesis to be tested in the laboratory. Future mechanism of action studies for this series of compounds will be needed to explain the limited spectrum of activity for this series of compounds.

Table 67.1

Predicted spectrum of activity based on molecular target conservation.

Conclusions

As genomics and related technologies develop, they will be applied to the study of herpesvirus biology and to the discovery of new antiviral drugs to treat these infections. Initial reports have provided indications that these strategies may be particularly useful in this family of viruses. These approaches hold promise and will likely make substantial contributions to the field as the technologies mature.

Acknowledgment

I thank David Shivak for his helpful comments and his critical reading of the manuscript.

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