MolScore-Antibiotics discriminates between antibiotics and non-antibiotics. The MolScore-Antibiotics of a compound measures the probability of having antibiotic activity and is defined as a value between 0 and 1.

    MolScores-Antibiotics is able to detect and prioritise candidates for clinical development. The expert system has been validated with novel antibacterials which are now in clinical trials.

MolScore-Antibiotics near 0:                   => lowest predicted antibiotic activity

MolScore-Antibiotics near 1:                   => highest predicted antibiotic activity
       attractive ADME-profile




More than 95%
have been assigned correctly. Analysis based on
5000 compounds (independent validation data).

We supply
our results in
Results can be easily imported into other commercial software for selection of compounds with additional filters.

Further Links:
Drug design
Drug discovery
Drug development
Computational chemistry

Clinical trials


The expert system uses a number of different strategies to find novel antibiotics. Models, based on neural networks, pharmacophore models, structure-ADME-relations, decision-trees and affinity prediction to antibiotic drug targets have been included, see science & technology. It is complicated to calculate but easy to use!

    Our methods have been proven to predict the antibiotic activity with an extremely low error. The error rate, estimated with an independent validation data set, was less than 5 %. This shows the excellent generalisation ability of the models used.

    We have analysed whether MolScore-Antibiotics could select antibiotic drugs from the blockbusters of the last five years. All antibiotic blockbusters had MolScore-Antibiotics results higher than 0.996, see proof of principle for details. MolScore-Antibiotics has also detected future drugs, which are now in clinical trials.

    MolScore-Antibiotics can be used to guide the buying or selecting of compounds for focussed biological screening (prioritisation of compounds from large compound collections). Our expert system revealed that many compound databases from external suppliers only have a small amount of compounds with antibiotic activity. Interesting compounds can be easily cherry-picked, see our example (selection of antibiotics from an external database of 195.064 compounds).

    ==> Lead optimisation and drug-candidate selection


    Expert system for antibacterial research
                                                               ==> Hit detection & validation
                                                               ==> Lead selection & prioritisation

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