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The American Society for Biochemistry and Molecular
Biology has this prescription for a periodic
table of proteins, organizing protein complexes based on simple rules,
tens of thousands of protein complexes each with their own 3-d structures, let
us recall the hypothetical smell network of all possible smells as they occur
to all people – the Lingua Anosmia.
There is a strong connection between olfaction and the
growing databases of bioinformatics, because smells are organic entities
themselves.
There is another database I envy, the human metabolome. It
contains 40,000 entries, all the metabolites that exist within and among the
human body. This one has even closer affinity with olfaction, because lots of
metabolites smell; and if they don't smell, they are the molecules that
eventually separate and combine to make something that does smell. Knowing the
relationships among the molecules associated with smelly activity can help to
organize the resulting smells of said metabolic activity. Your body odor does
not come from your body - unless we consider our microbiome to be part of our
body. Molecules that exit your body via sweat are deposited on the skin, a buffet
plate for the colonies of bacteria that live with us. They eat your sweat and
shit the body odor that you tend to consider yours. The smell of
the beach is a secondary metabolite of seaweed, which means the same thing –
sea bacteria eat the waste, or the metabolites, of seaweed.
Yes, that beautiful, intoxicating, deep and alluring
scent of the seashore is to the ocean what body odor is to our bodies.
In conclusion, metabolites, and many things biological,
and in their new supersized databasable format, are a step closer to the
realization of the hypothetical smell network, the Lingua Anosmia.
I’d like to ask the driven and capable reader to hook-up
this human metabolome with some smell data; I’d love to see it. Had I the time
and expertise, I'd like to hook it up myself, but alas; it's on my list.
“We’re bringing a lot of order into the messy world of
protein complexes”
-Sebastian Ahnert
Long form description of the Human Metabolomic Database:
The database is designed to contain or link three kinds
of data: 1) chemical data, 2) clinical data, and 3) molecular
biology/biochemistry data. The database contains 41,993 metabolite entries
including both water-soluble and lipid soluble metabolites as well as
metabolites that would be regarded as either abundant (> 1 uM) or relatively
rare (< 1 nM). Additionally, 5,701 protein sequences are linked to these
metabolite entries. Each MetaboCard entry contains more than 110 data fields
with 2/3 of the information being devoted to chemical/clinical data and the
other 1/3 devoted to enzymatic or biochemical data. Many data fields are
hyperlinked to other databases (KEGG, PubChem, MetaCyc, ChEBI, PDB, UniProt,
and GenBank) and a variety of structure and pathway viewing applets. The HMDB
database supports extensive text, sequence, chemical structure and relational
query searches. Four additional databases, DrugBank, T3DB, SMPDB andFooDB are
also part of the HMDB suite of databases. DrugBank contains equivalent
information on ~1600 drug and drug metabolites, T3DB contains information on
~3600 common toxins and environmental pollutants, SMPDB contains pathway
diagrams for ~700 human metabolic and disease pathways, whileFooDB contains
equivalent information on ~28,000 food components and food additives.
Citing the Human
Metabolome Database:
1. Wishart DS, Tzur D, Knox
C, et al., HMDB: the Human Metabolome Database. Nucleic Acids Res. 2007
Jan;35(Database issue):D521-6. 17202168
2. Wishart DS, Knox C, Guo
AC, et al., HMDB: a knowledgebase for the human metabolome.Nucleic Acids Res. 2009
37(Database issue):D603-610. 18953024
3. Wishart DS, Jewison T,
Guo AC, Wilson M, Knox C, et al., HMDB 3.0 — The Human Metabolome Database in
2013. Nucleic Acids Res. 2013. Jan 1;41(D1):D801-7. 23161693
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