SMARTS matches function

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. 

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 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... 

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 align function can be expanded in many ways. For example, instead of simply finding the center of each molecule, a substructure could be used. This might be defined as a SMARTS match that is expected in each of the molecules to be aligned. This would be a natural outcome of a substructure search. In order to create an array of coordinates for a subset of a molecule, the following function could be used. 

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. 

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 ... 

Protein sequences are structurally and functionally annotated at Bioverse (http // bioverse.compbio.washington.edu/). The annotations consist of three sections (McDermott and Samudrala, 2003). The sequence section lists similar sequences identified by searches using various methods, including PSI-BLAST. The structure section is composed of secondary and tertiary structure information. The function section combines PROSITE, BLOCK, PRINT, Pfam, ProDOM, SMART and TIGRFAM to match sequences to patterns, domains and famiUes. 

D knitted textiles have already been widely used as technical textiles in different fields. The future work should be on the development of new 3D knitted structures with more extra functions to meet the requirements of new application fields. For example, warp-knitted spacer fabrics have great structural variations. By using different structures and fibre materials, they have been developed to have various physical functions to be used in different fields, such as cushioning, sound absorption, smart textiles and thermal collection. New potential application fields should be identified first in the future, and then fabric stmctures can be designed to better match the specific applicatimis. 

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