zinc ( zinc is not commercial ) 
 is a public access database and tool 
 set , initially developed to enable ready access to compounds for virtual 
 screening , that has become ever widely 
 used for virtual screening , ligand discovery , pharamcophore screens , benchmarking , and force field development .
increasingly , however , 
 investigators have tried to interrogate it for questions that it was 
 not designed to answer .
simple questions , such as how many endogenous 
 human metabolites are there , which of these are purchasable , or what 
 natural product or drug does a compound most closely resemble , were 
 surprisingly difficult to answer . with a target in mind ,
investigators 
 often wanted a focused library biased toward ligands for that target . 
 with new compounds discovered ,
they often wanted to find the most 
 similar ligands already known for that target . to optimize that ligand
, 
 they might look to the availability of starting products for synthesis , 
 asking , for instance , how many boronic acids that contain an indole 
 ring may be purchased in preparative quantities and how soon will 
 they arrive . for these and many related 
 questions , we wondered whether we could make a system that obviated 
 the need for a computer expert s assistance . here
, we describe 
 a new version of zinc designed to address these questions , while retaining 
 the ease of use of the original tool .
zinc15 is designed to bring 
 together biology and chemoinformatics with a tool that is easy to 
 use for nonexperts , while remaining fully programmable for chemoinformaticians 
 and computational biologists .
1 ) 
 to integrate and curate biological 
 activity , chemical property , and commercial availability data for 
 small molecules from public sources , supplemented by additional calculated 
 properties into a chemistry - aware relational database .
2 ) to build 
 a general query language and report generator that is web url compatible . 
 3 ) to design a graphical user interface that requires no programming 
 to interrogate the database using this query language .
4 ) to demonstrate 
 and document the use of this tool to answer previously difficult questions .
this effort has resulted in zinc 15 , a new research tool for ligand 
 discovery that connects biological activities by gene product , drugs , 
 and natural products with commercial availability .
we describe the 
 system and demonstrate its use to answer questions about biologically 
 active and purchasable chemical space that were previously not easy 
 for nonexperts .
previously in zinc , compounds stood 
 on their own and were both the subject of queries to zinc and the 
 answers to such queries .
an innovation of this version is to identify 
 those molecules that have known biological effects or are of biological 
 origin , such as drugs and natural products , and to link compounds 
 to the proteins and biological processes that they modulate .
correspondingly , 
 one can now interrogate zinc regarding the ligands that bind to a 
 particular protein or regarding the proteins that a particular molecule 
 is known to modulate . extending this
, one can also ask what biologically 
 active molecules are most like those that bind a particular protein 
 of interest and what proteins such a compound might be predicted to 
 bind , based on chemical similarity to known ligands . in this way , 
 the mission of zinc is expanded from purely compound - centric to one 
 that links molecules to biological targets , processes , and other bioactive 
 small molecules .
the biological annotations  the identification 
 of molecules as metabolites , drugs , and natural products and the identification 
 of molecules as ligands for particular proteins and processes  all 
 derived from other databases and libraries , such as hmdb , chembl , and drugbank , for which zinc is essentially a client and from 
 whose rapid development in the last several years zinc has benefited . 

what is new here is that zinc cross - references this information with 
 purchasability of reagents ; this much expands its ability to bring 
 readily available reagents to biological questions
. doing so 
 has demanded optimization of the mechanics of zinc and 
 its interface . some of these have obvious impacts on the user and 
 the questions they can ask , for instance , expanding the number of 
 molecules they can address by 2 orders of magnitude . for convenience , 

we divide the results into descriptions of the new associations with 
 which purchasable molecules are freighted and examples of their use .
zinc15 draws 
 upon third party databases such as chembl , hmdb , drugbank , and https://clinicaltrials.gov to annotate high information compounds 
 that are active in , or created by , nature .
these include biogenic 
 molecules , such as natural products , metabolites , and fda approved 
 drugs , among others ( figure 1a ) .
what zinc brings is not only 
 lists of these molecules , which after all are derived from other sources , 
 but their purchasability and , as we will see , their predicted as well 
 as known associations .
for instance , there are 70539 metabolites that 
 have been annotated , 15006 of which may 
 be purchased from vendors . restricting 
 this to endogenous human metabolites , there are 46941 molecules , of which 8271 are for sale
. properties of catalogs and , in turn , the molecules they 
 contains are ranked in three independent series , thus : biogenic : endogenous 
 human metabolites > nonhuman metabolites > natural products 
 > unknown 
 biogenicity .
drug - series : fda approved > world drugs > investigational 
 > in man > in vivo > in cells > in vitro > unknown 
 bioactivity .
purchasability : 
 in - stock > via agent > on - demand > boutique > annotated 
 ( not for sale ) . 
 within each series
, we classify each compound by the highest level 
 it attains by catalog membership .
molecules found in catalogs categorized 
 as containing only endogenous human metabolites such as oxedrine ( zinc733 ) , for instance , inherit that 
 property .
compounds are also annotated with molecular 
 properties that speak to their potential behavior and mechanism . for 
 instance
, 16485 compounds have appeared 
 in the literature and have been shown to aggregate , a mechanism that is the origin of the greatest number of 
 artifacts in early drug discovery . of 
 these , 15072 are purchasable .
interestingly , 53 metabolites have been observed to aggregate as have 23 world drugs , i.e. drugs approved 
 by major national regulatory agencies such as the fda . the zinc15 web interface .
a : selected 
 zinc 
 substance subsets showing the number of purchasable bioactive and 
 biogenic subsets .
click on the subset name ( 2 ) to browse or download a subset . 

( 3 ) estimates of the number of each subset . ( 4 ) inset of dropdown 
 menu providing access to other resources .
the page navigation tool ( 1 ) , the get total tool ( 2 ) , the breadcrumbs 
 ( 3 ) , the selection tool ( 4 ) , and the download tool ( 5 ) .
click on any 
 molecule s number ( 6 ) to view its detail page .
for instance , to answer the following question : how many endogenous 
 human metabolites are there .
the user would browse to http://zinc15.docking.org , click on substances in the navigation bar ( top ) , click on subsets 
 ( top , left ) , and select endogenous from the list ( bottom ) ( figure 1a ) .
the endogenous 
 human metabolites are displayed , as tiles , but often there are too 
 many to count immediately ( figure 1b ) . to count the number if it is not displayed , the 
 user clicks on the  get total  button ( top , left ) ( 47319 ) . 

the user selects 
  now  from the selection tool dropdown menu ( top , right ) 
 and clicks on the count button again ( now 7190 ) . to download these
, 
 the user would click on the download button ( top , right ) .
the same 
 procedure is applicable for drugs , investigational compounds , and 
 biogenic compounds , among others .
thus , the user may ask for drugs 
 that are also metabolites or natural products that have been investigated 
 in clinical trials . having 
 drawn on databases 
 such as chembl and drugbank to associate compounds with their individual 
 targets
for instance , in zinc15 there 
 are 2737 eukaryotic proteins that have compounds binding at 10 m 
 or better annotated to them . over 100,000 
 distinct compounds hit at least one eukaryotic target at 10 nm or 
 better , rising to over 1/3 of a million 
 at 10 m .
intriguingly , only 361 
 bacterial proteins have molecules annotated to them amounting to only 4283 compounds at 1 m or better ; the numbers for archael and viral targets are , 
 notwithstanding intense interest , lower still .
zinc may be used to acquire 
 focused libraries of ligands annotated to a particular gene .
for instance , 
 a user seeking new ligands for the ionotropic glutamate receptor grin1 
 might want the 59 known ligands as controls in 3d sdf format files of the usual relevant forms expected at physiological 
 ph . in the previous example
orthologous 
 genes were combined into gene symbols , but some questions require 
 a particular species be specified .
thus , 
 2025 compounds bind the human beta-2 adrenergic receptor at 10 m 
 or better , while 2050 distinct compounds 
 bind any of its orthologs , which includes 
 the 2025 above plus 25 additional compounds .
eight distinct uniprot 
 annotations are available for this gene , and 2021 distinct ligands bind either the rat or human form at 1 
 m or better
. the user may look for molecules either 
 one at a time or in bulk .
for a single molecule , the chemical drawing 
 may be seeded with a drug or chemical name , smiles string , smarts 
 pattern , inchi , inchikey , zinc i d , or even original catalog ids such 
 as chembl ids ( figure 2a ) .
four buttons below the chemical drawing tool allow for exact , 
 substructure , and two kinds of similarity searches , using either tanimoto or dice coefficients , 
 each based on 512 bit ecfp4 fingerprints .
to look up many compounds at once , the user may use the resolver ( figure 2b ) , specifying one molecule per line , again using smiles , 
 name , and i d but not smarts .
( 1 ) the user may seed the drawing with chemical 
 or drug names , zinc ids , inchi , inchikey , or original catalog numbers . 

the search options may be edited prior to search ( 2 ) , which is run 
 using one of four buttons below drawing ( 3 ) : exact match , substructure , 
 and two kinds of similarity .
specify one molecule per line 
 in a file ( 4 ) or by pasting ( 5 ) .
additional search options ( 6 ) . format 
 of results may be specified ( 7 , inset 8) prior to running the resolver . 

buttons to browse subsets or view subsets ( 9 ) as well as general free 
 text search .
there is no set limit 
 on the number of molecules that may be returned 
 in a single similarity search calculation . using the api
, it should 
 be possible to download 1 million or more compounds , in any format , 
 based on similarity and/or substructure . however
, these queries may 
 take a long time and would likely be run in batch mode .
zinc is a public resource , and occasionally 
 the most pragmatic solution may be to download a large portion of 
 zinc and run a chemical search locally .
we look forward 
 to discovering the practical limits of this new technology . in previous 
 versions of zinc , we supported similarity searches for multiple molecules , 
 apparently in parallel .
internally , they were run serially , and the 
 results concatenated . currently , there is no mechanism to run queries 
 with multiple query molecules .
2 ) use the resolver , which is limited to a minimum similarity of 0.7 
 ( ecfp4 ) .
when a hit is found in 
 a screening campaign , a common next step is to identify , possibly 
 model , and then purchase analogs , often called sar - by - catalog .
how 
 well explored is the annotated or purchasable chemical space around 
 a compound ? to investigate analogs of olaparib ( zinc 40430143 ) , a 
 recently approved parp inhibitor ,
the user clicks on substance in 
 the navigation bar and types olaparib in the input line above the 
 drawing tool ( figure 2a ) . at time of writing
there were 38885 analogs within a tanimoto 
 of 50% ( ecfp4 ) , 297 of which were in 
 stock for immediate delivery .
zinc 
 can answer questions about novelty of a newly discovered ligand for 
 a particular target .
for instance , the drug cariprazine is known to 
 hit drd2 , but what are the most similar ligands that hit drd3 or drd4 ? 
 to investigate this , the user would click on substances in the navigation 
 bar and enter cariprazine in the draw / search structure field above 
 the drawing tool ( the molecule appears ) ( figure 2a ) .
on the results page , the user selects the relations selector 
 ( the chain link icon ) , selects gene from the popup , types drd3 as 
 the resource name , and clicks on the blue chain link icon to apply 
 this constraint .
zinc supports full smarts 
 using rdkit , enabling complex chemical 
 patterns to be matched .
the same search tool used for similarity search 
 may be used , in conjunction with the substructure button .
smarts pattern 
 searching can be slow , and thus many of these queries will probably 
 end up being run in batch mode .
for instance , to find benzylamines , 
 the user would click on substances in the navigation bar , enter the 
 smarts c1ccccc1cn in the draw / search structure bar above the drawing 
 tool , and click on the substructure button below the drawing tool . 
 to select only compounds available in preparative quantities , the 
 users would click on the subsets popup ( the label icon ) and click 
 on bb ( building blocks ) . to only select 
 compounds available for immediate delivery , the user would select 
 now from the same popup . if the user needs to look 
 up more that a few molecules , a bulk facility can simplify this task . 
 to do this , the user selects substances from the navigation bar and 
 using the resolver ( figure 2b ) either selects a file containing molecules to look up or 
 specifies them in the paste smiles field .
in either case , there should 
 be one molecule per line , which may be smiles , cas number , name , zinc 
 i d , or an original catalog i d , such as chembl i d .
options include 
 allowing close matches , looking for analogs , and whether a single 
 or multiple matches should be returned per input line
. the output 
 may be to a web page or a downloadable file in 11 supported formats 
 ( figure 3a ) .
when ready , 
 the user clicks  resolve file  to start the process . 

if more than 300 molecules are specified , the job is automatically 
 run in batch mode .
a. 
 zinc results 
 may be accessed in 11 formats plus the web pages .
three line - oriented 
 formats are easy to parse for both people and computers .
three machine 
 readable formats provide for rich and flexible data interchange between 
 programs .
b. compounds are classified by how they may be purchased 
 based on their current catalog membership .
there are five primary 
 levels and three derived levels . c. we classify 
 substances into six levels by the most 
 reactive group they possess , based on smarts patterns.d .
3d representations 
 are associated progressively with the ph range at which they become 
 relevant for docking .
these patterns enable new features , such as computing 
 a  reactivity  attribute for each molecule , accelerating 
 substructure search , and providing a basis for new features .
we have 
 calculated patterns for 480 pains patterns using the rdkit version 
 of the guha translation of the original 
 sln format smarts .
we also include 40 
 filtering patterns used in the previous version of zinc for backward 
 compatibility .
we have calculated statistics on the prevalence of 
 these functional groups allowing the 
 most popular and the least popular to be easily identified .
we compute 
 a reactivity score ( figure 3c ) , which classifies each molecule by the  worst  

functionality it contains , enabling queries as well as subsets that 
 follow community opinion in the tranche browser .
for instance , which 
 pains patterns are most common among drugs ? to answer this , the user 
 would select patterns from the navigation bar , click browse , and then 
 click on the drugs column heading twice to sort it in descending order . 
 to find purchasable sulfonyl halides ,
the user would select patterns 
 from the more menu in the navigation bar and then click browse . in 
 the lookup field
, the user would type  sulfonyl halide  
 and click on the blue  go  button .
the user can see 
 that there are 85487 sulfonyl halides for sale and clicks on the number 
 to view the substances .
the user may further specify building block 
 or now subsets to further narrow the query .
the statistics of occurrence documents the popularity 
 of rings by subset . to browse these ,
the user would select rings from 
 the navigation bar followed by browse . rings may be ordered by their frequency of occurrence in drugs , 
 natural products , or purchasable subsets by clicking on the column 
 heading .
the interface allows the user to , for instance , rapidly identify 
 all compounds containing indole rings available in preparative quantities , all investigational compounds containing quinazoline 
 rings , or all compounds containing both 
 pyrimidine and morpholine rings .
the 
 latter is interpreted as  all substances containing a morpholine 
 ring , and among these , those where any ring in the compound is pyrimidine  .
interesting questions may be answered from the molecule detail 
 page alone ( figure 4 ) . to look up an individual drug by name or zinc i d , click on substances 
 in the navigation bar and
enter its name or code into the text input 
 field above the molecular drawing tool ( we will use the example for 
 isoniazid , zinc1590 ) and click exact ( below , left ) .
the molecule detail 
 page contains purchasing information , annotated catalog membership 
 ( figure 4a ) , biological 
 activity data derived from chembl , biological activity predictions 
 from sea and chembl , similar interesting molecules ( figure 4b ) , publications from chembl , 
 chemical patterns , rings , publications from chembl , clinical trial 
 information , and more .
molecules may be downloaded in either 2d or 
 3d in 11 formats ( figure 3a ) .
large subsets and slow - to - download ones will be queued 
 and run in batch mode when resources permit . a special class of downloads 

lead - like  
 and  fragment - like  subsets , for which we recommend 
 the tranche browser , accessed from the tranches button 
 in the navigation bar ( figure 5 ) .
the tranche browser divides physical property space into 
 121 tranches based on two properties in 11 bins each : the horizontal 
 axis is size ( molecular weight ) and the vertical axis is polarity 
 ( logp ) .
the tranche browser allows the user to select the characteristics 
 of the database subset required and then download it , in 2d ( smiles ) 
 for chemoinformatics or 3d formats for docking
. the user may select 
 or deselect individual tranches by clicking on them or use the presets selector ( top right ) to choose a popular subset . 
 for 2d databases ,
the user may also specify purchasability ( figure 3b ) and reactivity 
 ( figure 3c ) and two 
 downloading options , format ( figure 3a ) and download method .
in addition to purchasability 
 and reactivity , 3d users may specify restrictions on net molecular 
 charge and ph range ( figure 5 ) .
a. showing ( 1 ) zinc 
 i d , name if known , subset membership , ( 2 ) properties and 2d depiction , 
 ( 3 ) 3d representations if available , ( 4 ) purchasing information , and 
 ( 5 ) annotated catalog membership , ( 6 ) breadcrumbs indicating current 
 location , ( 7 ) selection tool for refinement of query , and ( 8) download 
 tool . b. interesting bioactive and biogenic 
 analogs section of molecule detail page : ( 1 ) similar biogenic compounds , 
 ( 2 ) similar bioactive compounds , ( 3 ) compounds with a shared scaffold , 
 ( 4 ) similar aggregators , and ( 5 ) similar purchasable compounds currently 
 too slow to calculate .
physical - chemical space has been divided into 11 bins of polarity - hydrophobicity 
 ( calculated logp , vertical ) ( 1 ) and size ( molecular weight , horizontal ) 
 ( 2 ) .
subsets of this space may be selected in 2d ( smiles ) or 3d ( figure 3a ) ( 3 ) .
purchasability 
 level ( figure 3b ) ( 4 ) 
 and reactivity ( figure 3c ) ( 5 ) may also be specified .
for 3d only , net molecular charge ( 6 ) 
 and ph range ( figure 3d ) ( 7 ) may also be specified .
presets ( 8) correspond to community 
 practice ( e.g. ,  lead - like  ,  fragment - like  ) , 
 and download ( 9 ) provides for five methods to access the selected 
 molecules . knowing that a 
 molecule resembles a drug or natural product can help generate hypotheses 
 of mechanism of action , while the absence of similar annotated compounds 
 might suggest biological novelty .
each substance detail page includes 
 an analogs section , in which the nearest endogenous 
 human metabolite , any metabolite , natural product , drug , in man compounds , 
 and bioactives are shown , if there is one within a tanimoto index 
 of 0.6 ( 512 bit ecfp4 fingerprints ) . a find more button 
 may be used to find more .
we have already seen earlier how the most 
 similar compounds annotated for an individual gene target , its major 
 target or subclass , or from a particular catalog may also be found . downloading a 3d screening 
 library for docking
subset for 
 docking , the user selects  tranches  from the navigation 
 bar and then clicks on 3d ( top left ) to switch to the 3d downloading 
 tool ( figure 5 ) . from 
 the preset popup ( top right ) the user chooses 
lead - like  , 
 which sets the molecular weight and logp range of tranches .
individual 
 tranches may be selected or deselected by clicking on them . by default , 
 the purchasability selector ( figure 3b )
is set to wait - ok , which includes both in stock 
 and on demand compounds .
the reactivity selector ( figure 3c ) is set to mild by default , 
 which includes pains and weakly reactive compounds . to download a 
 script to download the database , the user clicks on the download icon 
 ( top right ) , where two further choices are possible .
the user downloads the script , which 
 may then be run to download the database tranches .
target classes such as membrane 
 receptors , ion channels , transporters , and enzymes group proteins 
 by function .
we have adapted the top two classification tiers in chembl 
 to assign one of 15 major and 42 target 
 subclasses to all genes ( table 2 ) .
zinc may be used to select 
 compounds that are known or predicted to hit particular classes of 
 targets .
thus , for instance , there are 35080 commercially available 
 ligands for class a gcprs ( purchasable ) , and for epigenetic regulator 
 targets , there are 1286 purchasable annotated ligands .
the 
 number of genes total as 
 well as the number of genes for which one or more compounds active 
 at 10 m or better was for sale at the time of publication . 

the number of distinct compounds that are for sale and not for sale 
 for each target class .
zinc encompasses 
 more of the 
 purchasable and annotated chemical space as the catalogs it includes 
 grow in size and number , currently adding around 50 new vendor and 
 annotated catalogs each year .
the date 
 each catalog was last updated is available in tabular form and on the detail page of each catalog .
two - dimensional smiles have been decoupled from 
 3d models , allowing us to load molecules for which we do not build 
 noncovalent 3d docking models such as boronic acids , tin , and silicon 
 containing compounds .
zinc now includes molecules with molecular weight 
 of up to 1000 da , offering more complete coverage of commercially 
 available chemical space , currently with 220 million molecules , over 
 half of which are for sale .
zinc is now a good way to find molecules 
 even if they are too big to be practical for docking , as long as they 
 are available for purchase .
building blocks available in preparative 
 quantities are now included and are easier to find .
we now use chemaxon s 
 jchem to protonate and prepare biologically relevant tautomers , resulting in an average of 2.2 biologically 
 relevant forms per molecule at physiological ph .
zinc now uses the 
 latest version of omega ( openeye scientific software , http://eyesopen.com ) for improved 3d conformations for docking .
we have added pdbqt 
 to sdf , mol2 , and our own flexibase formats , for both dock37 and previous versions .
zinc15 will now generate 
 dude - style decoys for any molecule directly 
 from the database .
zinc 
 now provides iupac inchi and inchikeys for every molecule to allow 
 better interoperability with other resources such as wikipedia , chembl , pubchem , chemspider , and unichem .
the first 
 part of an inchikey , which specifies the framework without stereochemistry 
 or protonation , offers a reliable way to find stereoisomers ( e.g. , 
 for praziquantel ) .
the canonicalization 
 required by inchis has reduced molecule duplication in zinc so that 
 search results are better estimates of their true values .
the anatomical therapeutic 
 chemical classification system , curated by the world health organization , 
 organizes drugs by their therapeutic , pharmacological , and chemical 
 properties .
zinc acquires atc codes of drugs via chembl20 and drugbank , 
 allowing drugs to be selected by anatomical , therapeutic , and chemical 
 classes . for instance
, the user may find 
 all purchasable drugs for cancer , all 
 dermatologicals of biological origin , and opioid anesthetics such as fentanyl .
integration of atc codes also allows for more consistent identification 
 of who - assigned names for substances .
we load clinical trials information 
 from https://clinicaltrials.gov , enabling zinc to answer 
 questions about these important compounds .
for instance , to see the 
 current clinical trials , the user would click on clinical trials in 
 the navigation bar and select current from the selection tool ( top 
 right ) .
it is possible to ask to see which compounds are in clinical 
 trials that hit a eukaryotic target at 10 nm or better and also to ask to see compounds in clinical 
 trials for cancer that are sold by cayman chemicals .
publications information 
 from chembl 
 enables the literature to be browsed , active compounds for any paper 
 to be displayed , papers to be found based on which compounds they 
 report on , and many other questions .
the user need only enter the 
 pmid of a paper to retrieve all the active structures it reports .
suppose the user would like the active compounds 
 from a paper in 2d or 3d form .
2014 , 57 , 9 , the user would click on publication in the navigation bar and enter 
 either the pmid ( here 24684293 ) or select the journal , year , volume , 
 and page number from the selectors . the user clicks search to arrive 
 at the page where the two genes and the first five compounds that 
 bind them at 10 m or better as described in that paper are 
 shown . to download these compounds , use 
 the download selector ( top , center ) . to find out whether any of the 
 compounds reported in this paper can be purchased ,
the user would 
 click on purchasable in the selection tool ( top , right ) .
for example , 
 it turns out that the subnanomolar ligand for protein kinase c , zinc4096162 , 
 is available , in both screening and preparative quantities .
this compound , 
 in turn , is reported in 15 papers , which are summarized at the bottom 
 of its detail page or listed at the references 
 relation to zinc4096162 .
a new api that 
 is almost identical to the web page url structure allows zinc to be 
 scripted and integrated into third - party applications .
documentation 
 for both the web page and the api is available using the help and examples endpoints , 
 and the api ( url ) syntax is described on our wiki .
machine - readable formats such as json , xml , sdf , csv , and 
 txt may be read directly into third party client programs such as 
 knime , pipelinepilot , cytoscape , datawarrior , instantjchem , and ipython notebook via pandas . in many cases , 
 the content of the help pages
each resource supports up to ten endpoints , 
 including the relation endpoint , which intersects one relation with 
 another .
the subsets endpoint allows the curators to define popular 
 subsets of the resource , which can help simplify query syntax .
the 
 supported subsets for each resource are available at the respective 
 subsets endpoint .
three themes emerge from this work . first , a new research tool 
  zinc15  is now available .
it enables chemists and 
 biologists to answer questions that before would have required the 
 assistance of a chemoinformatician .
second , zinc has also been improved 
 for experts , enabling them to integrate its features into their applications 
 using the new api .
third , zinc has undergone a wide variety of improvements 
 for its original constituency , molecular docking .
this required the design of a new database , the use of new software 
 such as rdkit , a new url - compatible query language and report generator , 
 and new web pages designed to simplify complex tasks .
the data are 
 structured in 20 resources , which are further divided into subsets . 

questions may now be asked not only about molecules but also genes 
 and their target classes , catalogs , chemical patterns and rings , publications , 
 and clinical trials as well as individual activity data points .
orthologous 
 targets from chembl are now grouped by gene symbol and organized by 
 major and subclasses .
the system offers focused libraries of known 
 compounds , purchasable or otherwise , organized by gene , subclass , 
 or major target class .
zinc answers questions about chemical novelty 
 and similarity to known drugs , bioactives , and natural products .
chemoinformaticsts 
 may now embed zinc and its tools into their own applications . for 
 instance
, zinc has been integrated into cytoscape ( zincytoscape ) and 
 r ( spelter ) .
the new api offers a modular interface using industry - standard 
 formats like xml and json , and reports are flexible in format and 
 content .
resources and their attributes are fully documented and may 
 also be retrieved in a machine - readable format allowing the creation 
 of rich and dynamic tools . the interface accepts molecular queries 
 represented not only as smiles and smarts but also inchi , inchikey , 
 and even binary fingerprints . finally , the virtual screening 
 community can benefit from many 
 innovations and improvements here . among these are new vendors , new 
 annotated catalogs , improved 3d representations , tranches for more 
 efficient physical property subsets , less duplication , faster and 
 more comprehensive searches by similarity and substructure , annotations 
 grouped by gene and organism class , and search results that may be 
 hundreds or thousands of times larger than before .
zinc provides a 
 view of biologically precedented and commercially available chemical 
 space organized by genes and the major and subclasses to which they 
 belong . for over one - third of genes that have ligands reported in 
 the literature
not a single one of them is for sale , underscoring 
 an urgent need for synthesis to fill gaps in screening libraries .
it inherits errors and ambiguity 
 from the catalogs it incorporates , including stereochemical ambiguity , 
 an ongoing challenge with few solutions that are not labor intensive . 

whereas our goal is to make the interface capable of creating every 
 query without programming expertise , the zinc query and report language 
 ( api ) allow many options for which we have not yet been able to build 
 a point - and - click interface .
due to its size and to the generality 
 of questions supported , some queries will take a long time and must 
 be run in batch .
batch mode , meant to handle long - running queries , 
 will not be released until december 2015 .
, zinc allows compounds to be annotated for bioactivity 
 and biogenicity , adding value to their library .
synthetic organic 
 chemists may use zinc to identify neglected metabolites or drugs for 
 synthesis or other bioactives that are not currently purchasable , 
 as well as the building blocks with which to make them .
curators of 
 annotated libraries such as chembl and drugbank may use zinc to enhance 
 their offerings with supporting information such as purchasability 
 and biogenicity information .
dockers and chemoinformaticians may download 
 commercially available libraries for screening , in 2d or 3d , as well 
 as sets of known actives as controls .
medicinal chemists may use zinc 
 to compare their discoveries to what is known publically and then 
 to find purchasable analogs or building blocks to make new libraries . 

we expect the zinc tools and libraries to have broad utility in the 
 community .
new software was written for 
 loading , curating , and querying the database in python using the chemoinformatics 
 software system rdkit 2014_09_01 , the 
 python structured query language toolkit and object relational mapper 
 sqlalchemy version 0.9.8 , and the python 
 web framework flask version 0.10.1 .
some sources such as hmdb and 
 drugbank were loaded as several distinct catalogs in zinc allowing 
 us to leverage the curation of metabolite origin such as plant metabolites 
 in hmdb or drug status such as investigational drugs in drugbank . 

all catalogs in zinc are categorized by their biogenic and bioactivity 
 status , if any .
for instance , 
 the  approved  subset of drugbank was categorized as 
  world drugs  since it contains over 100 drugs approved 
 in other countries but not by fda , and the  endogenous  

these values are computed 
 and stored and are accessible in the interface as molecular features . 

there are four biogenic catalog levels : 1 ) endogenous human metabolites , 
 i.e. compounds that are synthesized in man .
interestingly , this may 
 include compounds produced by our bacterial flora ; 2 ) metabolites 
 of any species , i.e. small molecules that are involved in metabolism , 
 development , and reproduction but not metabolites of xenobiotics ; 
 3 ) biogenic compounds , often called natural products ; 4 ) unknown biogenic 
 status .
1 ) fda approved ; 2 ) world drugs ; 3 ) investigational , compounds 
 reported to be used in clinical trials ; 4 ) in man , which including 
 nutraceuticals , for instance ; 5 ) in vivo , which includes drugbank 
 experimental compounds that have been in animals ; 6 ) in cells , which 
 includes compounds reported active in cell based assays ; 7 ) in vitro , 
 compounds active or assumed active at 10 m or better in a direct 
 binding assay .
the categories are ordered to be progressively inclusive 
 within each series , thus all fda approved drugs are also world drugs 
 and all compounds active in cells are also active in vitro .
we annotate 
 as building blocks those catalogs of compounds available in preparative 
 quantities , typically 250 mg or more .
commercial vendors are categorized 
 by the speed and cost of compound acquisition , allowing the best purchasability 
 of every compound to be computed based on its current catalog membership . 

catalog categorizations are refined continually by purchasing experience 
 in our lab and reports from colleagues , as follows : 1 ) in stock , delivery in under 2 weeks , 95% typical acquisition 
 success rate ; 2 ) procurement agent , in stock , delivery in 2 weeks , 
 95% typical acquisition success rate ; 3 ) make - on - demand , delivery 
 typically within 8 to 10 weeks , 70% typical acquisition success rate ; 
 4 ) boutique , where the cost may be high but still likely cheaper than 
 making it yourself , 70% typical acquisition success rate .
source catalogs are processed and 
 loaded into the database ( 2d only ) as follows .
name and cas numbers are loaded into 
 a synonyms table , while selected bioactivity and other selected data 
 are stored in a provided_values table .
we convert sdf to smiles using rdkit and take the largest organic part 
 of the compound ( desalting ) , enumerating up to four stereoisomers 
 from stereochemically ambiguous smiles using oechem tk version 1.7 
 ( openeye scientific software , santa fe , nm ) . because of the combinatorial 
 problem of ambiguous stereocenters in sterols , we used smarts filters 
 to prioritize the most probable implied stereoisomers based on biosynthetic 
 pathways ( prof .
the smiles are neutralized with mitools ( http://molinspiration.com ) , which also filters out incorrectly coded molecules well .
molecules 
 are loaded using python / rdkit scripts by attempting to map them to 
 existing zinc ids or creating new zinc substances as necessary , as 
 well as any additional required datastructures .
inchi and inchikeys 
 are calculated on loading , and the inchikey is used as a unique constraint 
 in the database .
512 bit morgan fingerprints with radius 2 ( effectively 
 ecfp4 ) are calculated for each molecule using rdkit .
the 3d molecule processing 
 pipeline 
 is now disconnected from the 2d loading process , above .
we now use 
 chemaxon s package and the command line tool cxcalc to calculate 
 protonation states and tautomers at or near physiologically relevant 
 ph in three ph tranches .
these are physiological , 
 covering roughly ph 6.4 to 8.4 , high , roughly ph 8.4 to 9.0 , and low , 
 roughly ph 5.8 to 6.4 .
each protomer is rendered into 3d using jchem s 
 molconvert ( chemaxon , budapest , hungary ) and conformationally sampled 
 using omega ( openeye scientific software , 
 santa fe nm ) .
atomic charges and desolvation 
 penalties are calculated using amsol 7.1 and our previously published protocol .
files are formatted for docking as flexibase files , mol2 , sdf , and pdbqt .
we normalized pki , ic50 , ec50 , ac50 , and pic50 to a single 
 standard pki value , which we rounded to two decimal places .
we filtered out data flagged with the data_validity_comment 
 field indicating possible problems in the source document .
we associate 
 compounds annotated for protein complexes to each of the genes involved 
 in that complex .
two common areas of biology where multigene complexes 
 are observed is for the cell surface receptor integrins and the ligand - gated 
 ion channels such as the nicotinic acetylcholine receptor .
for instance , 
 integrin vla-1 is an alpha-1/beta-1 heterodimer of two genes , itga1 
 and itgb1 , respectively . likewise , nachrs such as ( alpha-3)2(beta-4)3 
 is a heteropentamer of two genes chrna3 and chrnb4 , respectively . 
 in such cases ,
for single proteins , we used uniprot 
 gene symbols based on the uniprot accession 
 codes in chembl .
orthologs in the trembl part of uniprot often did 
 not have assigned gene symbols , in which case we used the uniprot 
 accession code as a provisional gene name .
we assigned target classes 
 and subclasses based on the first two subfields of the protein_class 
 field of the protein_classification table of chembl .
in this version 
 of zinc there are 42 subclasses grouped into 15 major target classes : 
 membrane receptor , ion channel , transporter , transcription factor , 
 enzyme , epigenetic , and 9 other catch - all classes for the few cases 
 when none of these fit .
we computed 512 bit 
 fingerprints using 
 the morgan algorithm with radius 2 as implemented in rdkit .
stereoisomers 
 and some very near neighbors have identical fingerprints , resulting 
 in approximately 50% fewer fingerprints than substances , on average . 

we grouped fingerprints into three classes , interesting , current , 
 and benched for faster searching .
queries that limit their results 
 to annotated compounds need only search fingerprints in the interesting 
 subsets , while benched fingerprints , corresponding to compounds not 
 in any current catalog , are never searched .
we have implemented a very 
 general chemical search api that automatically parallelizes chemical 
 search queries using python green threads to search in parallel increments 
 of 1 million molecules at a time . executed on a 64-core computer , 

we often see full database smarts searches completing in 30 s or less , 
 although smarts can be of almost unlimited complexity , and some queries 
 will certainly take far longer . similarity searches
features label 
 molecules with computed 
 properties often derived from catalog membership that would be prohibitive 
 to calculate interactively .
there are four biogenic class annotations : 
 biogenic ( natural products ) , metabolites , endogenous human metabolites , 
 and unknown .
there are eight bioactivity classes , which includes drugs : 
 fda approved , world drugs , investigational , in man , in vivo , in cells , 
 in vitro , and unknown .
there has been considerable 
 interest in pan - assay interference ( pains ) smarts patterns recently .
we used the rdkit version of the guha translation of 
 the original 480 pains expressed in sybyl line notation ( sln ) .
all molecules in zinc have been annotated and 
 are searchable by pains and other smarts patterns .
the reactivity categories are a ) anodyne ; b ) clean 
 ( pains - ok ) ; c ) mild ( weakly reactive , typically as a nucleophile or 
 electrophile ) ; d ) reactive ; e ) unstable or irrelevant for screening . 
 for e
, we do not build molecular models for noncovalent docking ( e.g. , 
 boronic acids ) .
the web site and api were 
 coded in python 
 using rdkit , sqlalchemy , and flask .
a curator s tool ( zincmanage ) 
 is used to load , update , and curate the database .
a command line interface 
 ( zinccli ) provides a unix - shell like interface for additional 
 testing and curation .
the stereochemical 
 ambiguity problem is 
 particularly acute in sterol rings , but since these are almost always 
 biological in origin and are derived from the sterol biosynthetic 
 pathway , sensible guesses of stereochemistry are reasonable .
we have 
 therefore created a special sterol processing pipeline for loading 
 molecules into zinc .
leslie kuhn for drawing our attention 
 to this and for providing smarts patterns and advice .
we used mitools ( http://molinspiration.com ) to extract 
 ring systems from every zinc molecule and loaded them 
 into the database .
we calculate static counts of the number of molecules 
 that have biogenic or bioactivity annotations , allowing rapid reports 
 of approximate counts of numbers of qualifying compounds per ring .
we built an interface to the docs table 
 in chembl20 and integrated it into the docs resource on the molecule 
 detail , gene detail , and target detail pages .
we attempt to identify names for substances 
 in zinc from who - assigned names via the atc , chembl molecule names , 
 and synonyms extracted from hmdb , drugbank , ttd , and other catalogs .
all drug or dietary supplement interventions 
 are then queried using a free text search against substance names 
 to map the indications to the corresponding substances in zinc .
there are 
 five classes of endpoints , ten static and an almost unlimited number 
 of dynamic ones .
the five endpoint classes are list , detail , relation , 
 subsets , and special .
thus , for example , the substances help endpoint provides guidance on how to find substances 
 of interest and a table provides a list of available catalogs in zinc 
 and the time of their last update and 
 shows the available subsets of genes in zinc per chembl20 . the major classes home endpoint provides an overview of target classes in zinc 
 and gives examples of how to query and select individual observations 
 of compound - target affinities from chembl , with or without additional 
 purchasability constraints .
 many 
 questions about the biological activity and availability of 
 small molecules remain inaccessible to investigators who could most 
 benefit from their answers . to narrow the gap between chemoinformatics 
 and biology , we have developed a suite of ligand annotation , purchasability , 
 target , and biology association tools , incorporated into zinc and 
 meant for investigators who are not computer specialists . 
 the new 
 version contains over 120 million purchasable  drug - like  
 compounds  
 effectively all organic molecules that are for 
 sale  a quarter of which are available for immediate delivery . 
 
 zinc connects purchasable compounds to high - value ones such as metabolites , 
 drugs , natural products , and annotated compounds from the literature . 
 
 compounds may be accessed by the genes for which they are annotated 
 as well as the major and minor target classes to which those genes 
 belong . 
 it offers new analysis tools that are easy for nonspecialists 
 yet with few limitations for experts . 
 zinc retains its original 3d 
 roots  all molecules are available in biologically relevant , 
 ready - to - dock formats . 
 zinc is freely available at http://zinc15.docking.org . 
Introduction
Results
Discussion
Methods