this problem is crucial , for example , in early 
 stages of drug discovery .
withdrawing a launched drug from the market 
 due to adverse drug reactions ( adrs ) is the costliest failure of a 
 drug discovery program , frequently followed by years and years of 
 lawsuits and costly settlements .
thus , it is paramount for medicinal 
 chemists to be aware of potential structural features that may cause 
 adrs at efficacious doses .
another related field is the environmental 
 toxicology ( or ecotoxicology ) , which assesses the environmental risk 
 of industrially produced chemicals .
again , the studies to perform 
 such estimation are based on expensive and time - consuming experiments .
one approach to the toxicity assessment is using predictions provided 
 by the quantitative structure  activity relationship ( qsar ) 
 models , which use different machine learning methods to correlate 
 structural properties of chemicals ( or so - called molecular descriptors ) 
 to their toxicity .
although qsar modeling 
 is a powerful technique , the two major problems are the applicability 
 domain and interpretability of such models .
the models based on powerful 
 methods , such as artificial neural networks ( ann ) or support vector 
 machines ( svm ) , frequently use hundreds of descriptors and are particularly 
 difficult to interpret .
the lack of interpretability makes it difficult 
 for these models to be used in the design of new potential drugs and 
 to comply with the rules ( so - called oecd rules ) during the validation 
 step .
another approach that is a 
 lot easier to interpret is related to 
 molecular patterns that are associated with particular types of toxicity 
 or adrs either directly or after undergoing of a metabolic activation in vivo ( or bioactivation ) .
toxicophores  or  structural alerts  
 ( sas ) and represent a very simple and easily interpretable way to 
 flag compounds with potential toxicity .
well - known expert systems 
 based on sas are the multicase expert systems from multicase , inc . and
the studies performed in the past decade have shown that structural 
 alerts is an efficient technique to detect potentially toxic chemicals .
screening chemical compounds against known structural alerts can 
 be a good practice to complement the qsar models and to help interpret 
 their predictions . to make the wealth of knowledge of the structural 
 alerts that could 
 cause adrs and toxic chemicals , we have developed toxalerts ( http://ochem.eu/alerts ) , an open web - based platform for uploading 
 and storing structural alerts published in scientific literature in 
 a structured manner with a capability to virtually screen compound 
 libraries against these alerts to flag toxic chemicals and compounds 
 with potential adrs .
the major goal of the project was to develop 
 an open , community - driven , and expandable system .
toxalerts is a unique knowledge - based expert 
 web - based platform 
 for storing structural alerts for toxic chemicals and compounds that 
 could cause adverse drug reactions .
the platform allows virtual screening 
 of chemical compound libraries to flag potentially toxic chemicals , 
 reactive and potentially unstable compounds , and compounds with liabilities 
 that could form reactive metabolites upon bioactivation . currently , 
 the database contains more than 600 alerts from 12 publications for 
 carcinogenicity , mutagenicity , skin sensitization , acute aquatic toxicity , 
 and potential idiosyncratic drug toxicity .
the system is accessible 
 from any modern web - browser that supports 
 java .
the platform is designed to promote collaborations and facilitate 
 drug discovery efforts in the academic sector : registered users can 
 add their own structural alerts as well as take advantage of the alerts 
 that are already in the database to virtually screen their libraries . the toxalerts system is integrated with the online chemical modeling 
 environment ( ochem ) , which provides a 
 number of benefits such as a possibility to screen against structural 
 alerts , usage of already built and creation of new qsar models on 
 our parallel distributed computational environment .
toxalerts is publicly 
 accessible after a simple online registration procedure at http://ochem.eu/alerts or from a general ochem interface at http://ochem.eu .
in addition to the identification of potentially toxic compounds , 
 the structural alerts can be also used to define structurally similar 
 compounds that can be used for the development of  local  

a set of structural alerts can be used to define an applicability 
 domain of a given qsar model , which falls 
 well within the context of the european program on registration , evaluation , 
 authorisation and restriction of chemicals ( reach ) .
a big advantage 
 of the structural alerts approach featured by toxalerts 
 is the clear interpretability of results .
while the conventional qsar 
 models based on many molecular descriptors and nonlinear methods can 
 be superior for catching complex dependencies , the structural alerts 
 is an excellent technique to flag potentially toxic compounds and 
 provide easily interpretable results .
the interpretability of predictions 
 would also be advantageous for legislative purposes like the reach 
 initiative . at the moment
, the 
 coverage of structural alerts by toxalerts can not 
 compete with commercial software packages such as derek or multicase . 

however , this open collaborative platform has a great potential , proven 
 by the success of ochem , which already 
 contains more than 1 m data records , thousands of private models , 
 and dozens of publicly available qsar models .
both ochem and toxalerts 
 are inspired by the developments in bioinformatics and biocomputing 
 where the majority of the code and resources are publicly available 
 and used by hundreds thousands of users .
the development of open access 
 software , depositories of data and models , and availability online 
 resources are going to dramatically change to the way the academic 
 community will perform chemoinfomatics and computational chemistry 
 calculations in the future .
 the article presents a web - based platform for collecting 
 and storing 
 toxicological structural alerts from literature and for virtual screening 
 of chemical libraries to flag potentially toxic chemicals and compounds 
 that can cause adverse side effects . 
 an alert is uniquely identified 
 by a smarts template , a toxicological endpoint , and a publication 
 where the alert was described . 
 additionally , the system allows storing 
 complementary information such as name , comments , and mechanism of 
 action , as well as other data . 
 most importantly , the platform can 
 be easily used for fast virtual screening of large chemical datasets , 
 focused libraries , or newly designed compounds against the toxicological 
 alerts , providing a detailed profile of the chemicals grouped by structural 
 alerts and endpoints . 
 such a facility can be used for decision making 
 regarding whether a compound should be tested experimentally , validated 
 with available qsar models , or eliminated from consideration altogether . 
 
 the alert - based screening can also be helpful for an easier interpretation 
 of more complex qsar models . 
 the system is publicly accessible and 
 tightly integrated with the online chemical modeling environment ( ochem , http://ochem.eu ) . 
 the system is open and expandable : any registered 
 ochem user can introduce new alerts , browse , edit alerts introduced 
 by other users , and virtually screen his / her data sets against all 
 or selected alerts . 
 the user sets being passed through the structural 
 alerts can be used at ochem for other typical tasks : exporting in 
 a wide variety of formats , development of qsar models , additional 
 filtering by other criteria , etc . 
 the database already contains almost 
 600 structural alerts for such endpoints as mutagenicity , carcinogenicity , 
 skin sensitization , compounds that undergo metabolic activation , and 
 compounds that form reactive metabolites and , thus , can cause adverse 
 reactions . the toxalerts platform is accessible on the web at http://ochem.eu/alerts , and it is constantly growing . 
Introduction
Conclusions