text: Annotating and classifying chemical compounds using the semantics popularly accepted by researchers involved in drug design is crucial for the effective use of Biological and structural data for technological growth and drug development. Drug design is a collective and coordinated effort involving several disciplines such as structural biology and medicinal chemistry. The semantics, chemical taxonomies, used by these disciplines may differ from one another. Several semantic representations of the views commonly used by these disciplines are presented and their utilization in developing a chemical Semantic Web is illustrated.
  Further reading, downloads, and publications are available at: http://xpdb.nist.gov/hiv2_d/download.html. For further information, contact T.N. Bhat (bhat@nist.gov) or John Barkley (jbarkley@nist.gov). Inspiration and guidance in the preparation of this use case by Eric Neumann, Anne Plant, & Henry Rodriguez is greatly appreciated.
  3D structures of HIV protease inhibitors
  A structural biologist facilitates drug design by studying enzyme drug interactions using a computer generated model built using experimental X-ray or NMR data. The popular paradigm in drug discovery seeks to collect, compare, and test many chemically similar compounds built by linking several building blocks generally known as fragments. This approach to modern drug discovery[1] is rational and knowledge-based with a defined hypothesis on the functional role of individual fragments that make up a drug. The process of drug design, therefore, begins with a lead compound followed by a hypothesis as how different fragments of this compound interact with the amino acid residues of the target protein molecule[2]. Following this, database searches are performed to gather structural neighbors of the lead compounds using what is commonly known as 'mix and match method of building the functional fragments' of a lead compound. The suitability of these fragments that makeup a lead compound is established using fragment-based in silico modeling or X-ray crystallographic screening techniques[3,4] These fragments are reviewed based on complimentarity between the properties of the fragments and the enzyme residues. Charge – charge complimentarity (pairing of + & - charges), hydrogen-bond complimentarity (donar & acceptor pairing), space filling complimentarity (void and volume pairing) are a few of these properties.
  The above figure shows interactions between the amino acid residues of HIV protease (gold) and drug fragments (pink). Modelers usually divide drugs into fragments such as P1, P2, P3, P1', P2', and P3' by breaking the drugs at the peptidic bonds (marked by white arrows). Often these fragments are further classified based on the type of the atoms and/or the type of the ring structures they have. Additional such pictures may be viewed at http://xpdb.nist.gov/hivsdb/gallery.html or here.
  These URLs show the IUPAC names along with the schematic drawings of fragments that have been used to form potent AIDS drugs.
  What fragment of given drug has been used in other drugs?
  1: has-fragment
  2:  has-fragment
  3: has-fragment
  4: has-fragment
  5: has-fragment
  A full list of fragments of AIDS potent drugs may be found in the URLs: http://xpdb.nist.gov/hivsdb/hiv_ligands.pl http://xpdb.nist.gov/hiv2_d/hiv_ligands.pl http://xpdb.nist.gov/hiv2_d/hivsdb_fragment_search.pl http://xpdb.nist.gov/hivsdb/hivsdb_fragment_search.pl
  Often many questions are not elmentary. For this reason, we define "conjugated" statements. A conjugated statement is a statement formed by concatenating and/or intersecting more than one statement. For instance, the 'has common fragment' statement uses the intersection of two or more 'has a fragment' statements. For example: KNI-272 and Ritonavir has a common fragment shown by the schematic drawing:
  Which other drugs in the database are structurally related to a given structure?
  To facilitate the conjugation of multiple statements, a chemical data-tree formed by the elements of statements is used. In this data-tree, the subjects and objects of the statements are organized in successive layers as shown below.
  Each layer of the data-tree acts a subject for the object defined in the adjacent layers. The predicate that proceeds from top most layer to adjacent layer is 'has class', the predicates for the layers that follow the top most layers are 'has subgroup','has fragment' and 'is drug'.
  Give me all the drugs with a particular subgroup napthyl
  Statement: fragment of
  Response to the above question amounts to conjugating the desired 'is subgroup of' statement with 'fragment of' statement to obtain a list of drugs. Additional examples of this type of use cases may be found in the URLs http://xpdb.nist.gov/hivsdb/advanced_query_files/slide0002.htm and in http://xpdb.nist.gov/hiv2_d/advanced_query_files/slide0002.htm
  can be associated with a complete compound, such as, ATP (this molecule is source of energy for human body and an average body processes a huge amount of this compound every day):
  These concepts are then used to develop the chemical taxonomy. This step involves examination of all the concepts and their relationships and then classifying them into a hierarchy. For instance, the concept represented by Pyrimidine and Imidazole may be defined as instances at the same hierarchical level, since they both define concepts of similar nature. These concepts may be assumed to precede the concept of Purine. The concept of Pyrimidine may be assumed to precede the concept of Purine. The concept of Purine precede that of ATP.
  Advantages of chemical taxonomy for annotation
  A chemical taxonomy allows a database developer to accurately define and cross-index concepts within the resource. Using these indices search engines may be developed to facilitate gradual build of a user query starting from commonly used concepts in the field.
  How a user queries a chemical taxonomy based Webpage
  At this time, the chemical taxonomy based search engine exists only in the NIST database. Users perform their initial queries using the chemical taxonomy graphic (at http://bioinfo.nist.gov/SemanticWeb_hiv2d/chemblast.do and http://xpdb.nist.gov/hiv2_d/advanced_query_files/slide0002.htm) in order to access the 2500 compounds that are common to HIVSDB and PubChem.
  From this initial page, one may select the top leftmost 'Start here' to obtain the Web page shown below to query the class of compounds described in the OWL representation.
  Here, the user sees the first layer of the OWL representation. If users now select the second, third, or fourth layers, they will see the corresponding data elements. Each of these layers correspond to particular level of the taxonomy represented by chemical taxonomy. Adjacent layers of the taxonomy are connected by relationships defined in OWL statements.
  From the Web page shown above, a user may select a particular type of structure, for instance a double fused ring . Then the following Web page appears that has all the fused rings in the database and denoted by the OWL representation.
  Media:HCLS$$ChemicalTaxonomiesUseCase$fig-uc2-7.JPG
  Media:HCLS$$ChemicalTaxonomiesUseCase$fig-uc2-8.JPG
  From here, a user may select one of the fragments, for instance 45222_chain1_5. This will lead to the page shown below . This page has the structures that satisfy all the elements chosen in the previous selections.