Matches function SMILES

Another SQL extension is needed that can understand the molecular structural nature of the SMILES string and treat it like more than just a text string. Suppose there is a function matches (A,B) that returns true when structure A contains structure B. Both these structures could be represented as SMILES and the matches function itself would understand the molecular nature properly. Then matches( C( N)S, C N ) would be true as would matchesCSC N, N C ), as intended. The matches function can be used to find all cyano-containing structures in a table using an SQL clause such as where matches (cansmi, C N )-... 

When searching a database, if an isomeric query is used, only structures with the identical stereochemistry will be found using either a direct lookup or the matches function. If a nonchiral query is used, the direct lookup will find matching nonchiral structures, including canonical SMILES. When a nonchiral query is used in the matches function, structures of all chirality will be found. There is no one best method for dealing with a database containing many chiral molecules. It is important to carefully consider how to design and search such a database. 

It is possible to specify the isotope of any atom in a SMILES string. This is generally not necessary because the most common isotope is simply assumed. But if, for example, a database contains information about 13C, this can be readily encoded into the SMILES using [13C] instead of simply C. The [13C] atom is considered different from the normal C atom in a SMILES. A direct lookup using canonical SMILES will not locate isotopes of the same structure. A substructure search using the matches function will locate isotopes. This is because the match function uses SMARTS to specify the desired substructure. 

Suppose it is decided that the valence 5, noncharge-separated representation of the nitro group is to be used throughout the database. The SMIRKS [0 2]=[N+ 1][0- 3] [0 2]=[N+0 1]=[0+0 3], when applied to any charge-separated nitro group will transform it into the proper form. This is accomplished by creating another new SQL function, xform(smiles, smarts). As with the cansmiles and matches functions, this is an extension to standard SQL. Some form of this transformation function is... 

This SQL statement can be expanded in many different ways to satisfy many different requirements. For example, an additional where clause in the subselect statements could limit selection of reactants by molecular weight, cost, availability, etc. The type of amine or acid chloride could also be selected by changing the SMARTS in the matches function. For example, aromatic amines could be selected by using matches (smiles, c[NHl] ). 

This function returns a length 166 fragment key. The input text string ( 1 in the function body) is a SMILES, as expected by the matches function. The table of fragments is based on the MACCS 166 public keys1 and is shown in Table A.5.3 of this Appendix. 

This function computes the average molecular weight of an input SMILES structure. It uses the table of atomic weights and SMARTS shown in Table A.2. It relies on the count matches function described in Chapter 7. 

Thematches(A, B) function is properly defined having A represent a structure using SMILES and B represent substructures using SMARTS. Of course, B may also be a SMILES. In this case, matches will be true when B is a substructure of A. All structures in a table for which CC(0)C is a substructure canbe found by using the SQL clause Where matches (cansmi,... 

The matches (A,B) function returns true when SMARTS B matches SMILES A. It is sometimes useful to know how many times B matches A. For this, a new function is defined count matches (A, B). It returns an integer, possibly 0. For example, count matches ( CC (0) C, C ) returns 3. The SQF clause where count matches(cansmi, [F,Cl,Br,I] ) > 2 will find all structures having more than 2 halogen atoms. In later chapters, examples will show how this function can be used to compute molecular properties and screen structures that conform to Lipinski s Rule of 5.11... 

Another useful SQF extension function is list matches (A,B). This returns an array of integers telling which atoms in SMILES A were matched by SMARTS B. For example, list matches( CC(O)C, C ) returns the array 1,2,4. This list can be used for additional processing of the matches SMITES, for example, to color the matched atoms in a drawing or viewing application. 

The following function is analogous to the fragment key function above. It uses a relational table to define fragments, a function to match SMILES and SMARTS (in this case count matches), and an aggregate SQL function to tally the results over all matched fragments. 

The CHORD6 chemical cartridge is a commercial product from gNova, Inc. It is written using C functions and the OEChem toolkit from OpenEye. It provides the core functions discussed in this book, such as cansmiles, matches, count matches, list matches, smiles to molfile, molfile to smiles, and xform. CHORD makes it possible to efficiently process RDBMS tables containing many millions of chemical structures. 

This function takes a SMILES and a SMiles ARbitrary Target Specifications (SMARTS). The SMARTS is used to locate a substructure within the SMILES and color the atoms that are matched. 

Table A.2 is a table of average molecular weights for each of the first 103 atoms in the periodic table. Because most SMILES do not contain explicit hydrogen atoms, an additional 6 rows are included to match atoms with 1-6 implicit hydrogen atoms. The function amw defined above uses this table to compute average molecular weight.

Create Or Replace Function count matches(text, text) Returns Integer As EOPERL use Chemistry File SMILES use Chemistry File SMARTS use Chemistry Ring 1aromatize mol1 ... 

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