**2. The use of genomics, proteomics and bioinformatics in fungicide design**

During decades, prior to the development of functional genomics, target discovery was relied on the "observation based" approach. That is, the target strategy involved screening of large numbers of small molecules against particular and desired phenotypes. From this approach, libraries of compounds were constructed with biologically derived or chemically synthesized agents who were used in a systematic manner. However, the result of this approach produced a low number of drugs (Ferrer-Alcon *et al.,* 2009, Steffens *et al.,* 1996). It can be stated that the pace of natural product research and the level of global interest in the particular area of our environment as risen dramatically in the past few years. This period is projected to continue for the future as the interface between biology and chemistry becomes even more blurred and public demand rises for the cost effective medications and biological agents from sustainable resources. The research approach should focus on how to discover novel plant derived natural products through molecular docking as new lead compounds for potential agents and to modify these compounds to find still more potent agents with focus being on the application of homology modeling (Singh & Sharma, 2011). Significant improvements in the era of genomics and proteomics and concurrent progresses in bioinformatics techniques, have given rise to the expectation that the three dimensional structure or reliable homology modeling of target proteins can be achieve in a reasonably short time. Traditionally, the medical plants have provided lead for antifungal compound. Most of fungicides available today were discovered from the screening of synthetic or natural product libraries. Natural products, either as pure compounds or as standardized plant extracts, provide unlimited opportunities for new fungicides leads because of the unmatched availability of chemical diversity. Newer molecular structures as isolated from

through specific binding of the β-tubulin subunit of fungal tubulin, which consequently interferes with microtubules assembly, which in turn is essential for numerous cellular processes, such as mitosis and cytoskeleton formation. Metal ions such copper and silver have been proposed to interact strongly with thiol groups in fungal enzymes and proteins. The inhibitory activity of these compounds may be caused by enzyme damage through binding to key functional groups, particularly sulphydril groups in plasma membrane and cytosol. Flucytosine (pyrimidine analog) the sites of action are nucleic acids, this agent is taken up by fungal cells via the enzyme cytosine permease. Biocides exhibit a multiplicity of antifungal mechanisms. The knowledge of their mechanism of action, combined with an understanding of quantitative structure activity relationships, provides an important platform from which novel biocides may emerge, offering enhanced activity and

Nowadays, new approaches based on graph-theoretical descriptors have emerged as powerful tools for the design of bioactive agents (Marrero –Ponce et al., 2008). The purpose of these approaches is to perform a massive screening of databases of heterogeneous series of compounds and to extract as much structural information as possible at different levels of chemical diversity. So, the use of methodologies and promising approaches may enable the discovery and identification of new candidates as potential fungicides. The new agrochemicals that can be designed will have a wide range of action against different species. Also, they will be able to act by different mechanisms of action and thus avoid the

**2. The use of genomics, proteomics and bioinformatics in fungicide design**  During decades, prior to the development of functional genomics, target discovery was relied on the "observation based" approach. That is, the target strategy involved screening of large numbers of small molecules against particular and desired phenotypes. From this approach, libraries of compounds were constructed with biologically derived or chemically synthesized agents who were used in a systematic manner. However, the result of this approach produced a low number of drugs (Ferrer-Alcon *et al.,* 2009, Steffens *et al.,* 1996). It can be stated that the pace of natural product research and the level of global interest in the particular area of our environment as risen dramatically in the past few years. This period is projected to continue for the future as the interface between biology and chemistry becomes even more blurred and public demand rises for the cost effective medications and biological agents from sustainable resources. The research approach should focus on how to discover novel plant derived natural products through molecular docking as new lead compounds for potential agents and to modify these compounds to find still more potent agents with focus being on the application of homology modeling (Singh & Sharma, 2011). Significant improvements in the era of genomics and proteomics and concurrent progresses in bioinformatics techniques, have given rise to the expectation that the three dimensional structure or reliable homology modeling of target proteins can be achieve in a reasonably short time. Traditionally, the medical plants have provided lead for antifungal compound. Most of fungicides available today were discovered from the screening of synthetic or natural product libraries. Natural products, either as pure compounds or as standardized plant extracts, provide unlimited opportunities for new fungicides leads because of the unmatched availability of chemical diversity. Newer molecular structures as isolated from

environmental acceptability (Fernandez- Acero *et al.,* 2011).

problems of cross-resistance (Speck-Planche *et al,* 2011).

natural products may be suitably modified to obtain designer molecules for fungicide. Pharmacological testing, modifying, derivatising and research on these natural products represent a good strategy for discovering and developing new fungicides. The combinatorial chemistry has helped in the development of a series of similar but homologous structural compounds for testing (Singh & Sharma, 2011).

At present, structure based-drug design and ligand-based drug design are two great strategies that can be applied for the discovery and/or development of new fungicides. Structure based-drug design relies on a knowledge of the three dimensional structure of the biological receptor, obtained through experimental methods such as X-ray crystallography or NMR spectroscopy. When the experimental structure of a target is not available, it may be possible to create a homology model of the biological receptor on the basis of the experimental structure of another known material (mostly a related protein). The use of various tools like automated computational procedures has provided a means of suggesting new drug candidates and optimizing time and resources. Sometimes the information about the three dimensional structure of the receptor is not available. In this sense, ligand-based drug design is focused on the knowleage of other molecules can be used to derive the minimum necessary structural characteristics that a molecule must present in order to bind to the receptor. Ligand-based drugs design can be applied in cases where the structure of the receptors is uknown but a series of compouds have been identified that exert the fungicide activity. It is necessary to have several compounds structurally similar with high activity, with no activity and with a range of intermediate activities. These other compounds that bind to the biological receptor of interest provides us information the minimum necessary structural characteristics that a molecule must present in order to bind to the receptor (Speck-Planche *et al.,* 2011). Both strategies of drug discovery can be extended to and applied in the design of more effective agrochemicals, and specifically fungicides. Example of applying new technologies towards the rational design of fungicides to control phytopathogenic fungi of commercial crops was used by Fernández-Acero *et al*, (2006). They found substrates with antifungal properties against oomycetes, they screened compounds analogous to various phytoalexins and to flavanes derivatives which display antifungal activity against *Phytophthora* fungi.

The use of bioinformatics techniques to biological systems was demonstrated in the Structural Proteomics In Europe (SPINE) project, which was established to develop new methods and technology for high throughput structural biology. Developments covers target selection, target registration, wet and dry laboratory data management and structure annotation as they pertain to high throughput study (Albeck *et al.,* 2006). How this program, there are now many databases which is constantly being updated with the latest data of groups to seek new targets, new fungicides and relevant information like new virulence factors of some fungi, some of these pages are: (www.broadinstitute.org/science/projects/fungal-genomeinitiative, http://cogeme.ex.ac.uk. www.phi-base.org, http://www.expasy.org/ and http://bioinformatics.charite.de/supernatural2/.

In the post-genomic era, new terms related with chemical "-omics" have appeared. The term "genetic chemical" describes the use of small molecules to selectively perturb gene function. When this concept is applied on a genome-wide scale it is named "chemogenomics". The application of chemogenomics to protein targets is named "chemoproteomics"; although a more explicit definition is TRAP (targeted related affinity profiling) defined as the use of

Target-Site-Specific Screening System for Antifungal Compounds 185

enzymes involved in the synthesis of toxins are included. These virulence factors are typically involved in evolutionary arms races between plants and pathogens (Gonzalez

Knowledge of the pathogenic cycle and virulence factors of the fungus is crucial for designing effective crop protection strategies, including the development of resistant plant genotypes through classical plant breeding or genetic engineering, fungicides or the use of biological control strategies (Gonzalez-Fernandez *et al.,* 2010). The determination of a specific factor as virulence or pathogenicity has been achieved by constructing defective mutants in the specific genes. The infection power of the analyzed mutants should at least decrease or disappear compared to the wild type, if the deflections of these genes in mutants produce a loss of vegetative lesion, it is logical to assume that the inhibition of this enzyme or set of enzymes by targeted strategies, should produce new fungicides. In this context, the use of natural products or related compounds as specific enzymes inhibitors is an archetype, as they would be species specific and the environmental impact would be reduced to a

A diversity of fungi, oomycetes secrete proteins and other molecules to different cellular compartments of their hosts to modulate plant defense circuitry and enable parasitic colonization, these molecules have been called "effectors". The usage of the term "effector" became popular in the field of plant-microbe interactions with the discovery that plant pathogenic gram-negative bacteria utilize a specialized machinery to deliver proteins inside host cells. More recently, a broader range of plant microbiologists have adopted the term effector and its associated concepts (Abramovitch et al., 2006). This term is now also routinely used in the fungal and oomycete literature and is becoming increasingly popular in nematology to describe secreted proteins that exert some effect on plant cells (Hogenhout

Some effectors are avirulence proteins and have a 'gene-for gene' relationship with resistance proteins in the host. When a fungal avirulence gene is mutated, hosts with the corresponding resistance gene no longer detect the pathogen; this leads to a compatible interaction. Host-specific proteinaceous toxins that have an 'inverse' gene-for-gene relationship with the host, whereby the interaction leads to disease such genes would be classified as pathogenicity genes (Oliver & Solomon, 2010). Small proteins encoded by fungal genes involved at various stage of infection, alter host cell structure and function

Fungi use signaling cascades to respond to changes in the environment by altering their gene expression. The interruption of these signaling genes results in the loss and/ or reduction in pathogenicity, as well as pleiotrophic effects on cellular processes, including mating, conidiation, growth rate and toxin production. Therefore, it is difficult to determine which aspect of fungal physiology is responsible for the loss of pathogenicity. The components of these signal transduction cascades may represent targets for the development of fungicides (Van De Wouw & Howlett, 2011). *Phytophtora infestans,* one of the most destructive pathogen of potato in the history, have a remarkable speed of adaptation to control strategies such as genetically resistant cultivars, comparison with two other *Phytophthora* genomes showed rapid turnover and extensive expansion of specific families of secreted disease effector proteins, including many genes that are induced during infection

facilitate infection. These proteins are often cysteine rich (hogenhout *et al*., 2009).

Fernandez *et al*., 2010).

et al., 2009).

minimum (Fernandez-Acero *et al.,* 2011).

biology to inform chemistry (Xu *et al*., 2007). The accumulation of proteomic information of fungal plant pathogens may be an incentive to the development of new and environmentally friendly fungicides. Particularly, Proteomics is another is a highthroughput technology that allows an in depth study of the sets of proteins synthesized in a specific sample at any specific moment. By protein profile comparison between samples, the proteins involved in specific biological processes may be revealed. One of the most interesting applications of the proteomics is its use in discovering new protein targets for drug design including fungicides (Fernandez-Acero *et al.,* 2010; Ferrer-Alarcon *et al.;* 2009). It involves the identification and early validation of disease-associated targets.

The accumulation of information over the last decades, relating to a) fungal molecular genetic data, b) pathogenicity/virulence factors and c) proteomic approaches, has led to the appearance of several web-accessible databases which contribute to the fungal scientific community's development in this field. More than 50 genomes of pathogenic fungi are published in the Broad Institute Database for public perusal (www.broadinstitute.org/science/projects/fungal-genomeinitiative); and further data in the Phytopathogenic Fungi and Oomycete EST Database, COGEME, http://cogeme.ex.ac.uk/). In spite of the incredible amount of biological information about fungal plant pathogens, there is no commercial fungicide developed from a molecular approach.
