However, molecular formula search implemented in some databases, including PubChem Chemical Structure Search, has an option to allow other elements in returned hits (e.g., C6H6O or C6H6N2O for the “C6H6” query).

The most common types of molecular fingerprints are structural keys, which encode structural information of a molecule into a binary string (that is, a string of 0’s and 1’s).  The position of each number in this string corresponds to a particular fragment.  If the molecule has a particular fragment, the corresponding bit position is set to 1, and otherwise to 0.  Note that there are many different ways to design molecular fingerprints, depending on what fragments are included in the fingerprint definition.  PubChem uses its own fingerprint called PubChem subgraph fingerprints.

PubChem provides two web-based tools that allow users to perform a cluster analysis of PubChem data:  the Structure Clustering tool and Structure-Activity Relationship (SAR) Analysis tool.

The Structure-Activity Relationship (SAR) Analysis tool

On the contrary, superstructure search returns molecules that comprise or make up the provided chemical structure query (that is, substructures that is contained in the query superstructure).  It should be noted that substructure search does not give you substructures of the query and that superstructure search does not return superstructures of the query.

FLink tool

However, some special filters, such as the "lipinski rule of 5" filter, or the “all” filter, are not link-based.

The Entrez Search and Retrieval System

aspirin[completesynonym] (1 hit, as of Feb. 26, 2017)https://www.ncbi.nlm.nih.gov/pccompound/?term=aspirin%5Bcompletesynonym%5D aspirin[synonym] (98 hits)https://www.ncbi.nlm.nih.gov/pccompound/?term=aspirin%5Bsynonym%5D aspirin (103 hits)

Alternatively, PubChemRDF data can also be loaded into RDF-aware graph databases such as Neo4j, and the graph traversal algorithms can be used to query the PubChem knowledge graphs.

In 2-D similarity search, the similarity between chemical structures is quantified using the Tanimoto equation (22–24) in conjunction with the PubChem substructure fingerprint

Therefore, some records in PubChem can persist with outdated (or incorrect) data.  To help identify such cases, we are introducing a “legacy” indication for contributors and their records.  Please note that this does not mean that data identified as “legacy” is without value.  Quite to the contrary, some legacy collections successfully collected valuable scientific data for the research community, and are simply no longer updating the information.

The distinction is important as PubChem is organized in three separate databases: Compound, Substance, and BioAssay. 

TOXNET (http://toxnet.nlm.nih.gov/)22-25, maintained by the National Library of Medicine (NLM) at NIH, is a group of databases covering toxicology, hazardous chemicals, toxic releases, environmental and occupational health, risk assessment. 

2.6. DrugBank: comprehensive information on drug molecules

all data on a computer must be represented in binary notation.

SPARQL which is the interestingly recursive acronym that stands for ‘SPARQL Protocol and RDF Query Language’.

Mass Spectrum

Safe Drinking Water Act: Consumer Confidence Reports

websites where you can obtain reliable spectral data, and software for viewing/simulating spectra.

Another extension of SMILES is SMIRKS28,29, which is a line notation for generic reactions. 

Actually, it is very common that there are a lot of SMILES strings that represent the same structure, whether it has a ring or not, because one can start with any atom in a molecule to derive a SMILES string.  Therefore, it is necessary to select a “unique SMILES” for a molecule among many possibilities.  Because this is done through a process called “canonicalization”, this unique SMILES string is also called the “canonical SMILES”.

All InChIs currently are prefixed with “INCHI=”. Following this, a designator of “1/” or “1S/” indicates whether the InChI is non-standard or standard (i.e. with fixed standardized options in the software)

the full stop (“.”) which overrides the implicit single bond between adjacent atoms we can make some exotic variants on SMILES:C1C.CC1ButaneC1CC1.C2CC2Cyclohexane

Chirality

Bonds Block

Resonance Run-of-the mill delocalization presents some of the same problems as aromaticity, but there is no conventional label for (non-aromatic) delocalized electrons, such as the delocalized negative charge and pi system in benzoate (VII and VIII). The connection tables will simply represent one resonance structure or another.

We would need to add an additional field to the atom and/or bond table to handle chirality (SCT VI, VII). We could do so either in a chemically sophisticated way, annotating the atom property, in a chemically-naive translation of a diagram feature, annotating the bond configuration, or both.

Of course, chemical structuresand topological graphs are not entirely equivalent: aconnection table is akin to a description of a singlevalence bond structure and does not take account,for example, of delocalized bonds.