Molecular Fragments and Fingerprints - Design and Use of Relational Databases in Chemistry - page 97

Table 8.2 Atomic Weights for Some
Common Atoms and Associated SMARTS

SMARTS

Weight Symbol

[#1] 1.01 H

[#6] 12.01 C

[#7] 14.01 N

[#8] 16.00 O

[#9] 19.00 F

[#15] 30.97 P

[#16] 32.06 S

[#17] 35.45 Cl

[*;h1] 1.01 H1

[*;h2] 2.02 H2

[*;h3] 3.03 H3

[*;h4] 4.04 H4

[*;h5] 5.05 H5

[*;h6] 6.06 H6

buried in an external computer program, exposing them in a table makes
it easier to maintain, verify, and expand the parameter set.
The simplest molecular property is molecular weight. The obvious frag-
ments to use for this are atoms. It is a simple matter to define the SMARTS
fragments for any atom. Table 8.2 shows the definition for a few common
atoms. The full table for the first 103 atoms is shown in the Appendix.
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.

Create Function amw(character varying)
Returns Numeric As $EOSQL$
Select sum(weight*count_matches($1,smarts)) From amw;
$EOSQL$ Language SQL;

This function is not a very efficient method to compute molecular weight
compared with a compiled C program, for example. The advantage is that
the function is contained within the database and is expressed using a
relational table that exposes the important parameters of the computation.
The following function could be used when creating a table containing
SMILES, or used when necessary, for example, to compute the molecular
weight of phenol.

Select amw('c1ccccc1O');
Select amw(smiles) from structure;