Title:In Silico Assessment of Adverse Effects of a Large Set of 6-Fluoroquinolones Obtained from a Study of Tuberculosis Chemotherapy
VOLUME: 7 ISSUE: 4
Author(s):Marjan Tusar, Nikola Minovski, Natalja Fjodorova and Marjana Novic
Affiliation:National Institute of Chemistry, Hajdrihova 19, SI-1001 Ljubljana, Slovenia.
Keywords:Tuberculosis, antibacterial drugs, predictive models, new active molecules, assessment of toxicity, 6-Fluoroquinolones, Quinolone antibacterials, Vega platform, Caesar prediction models, Toxtree expert
Abstract:Among the different chemotherapeutic classes available today, the 6-fluoroquinolone (6-FQ) antibacterials are
still one of the most effective cures in fighting tuberculosis (TB). Nowadays, the development of novel 6-FQs for
treatment of TB mainly depends on understanding how the structural modifications of the main quinolone scaffold at
specific positions affect the anti-mycobacterial activity. Alongside the structure-activity relationship (SAR) studies of the
6-FQ antibacterials, which can be considered as a golden rule in the development of novel active antitubercular 6-FQs, the
structure side effects relationship (SSER) of these drugs must be also taken into account. In the present study we focus on
a proficient implementation of the existing knowledge-based expert systems for design of novel 6-FQ antibacterials with
possible enhanced biological activity against Mycobaterium tuberculosis as well as lower toxicity. Following the SAR in
silico studies of the quinolone antibacterials against M. tuberculosis performed in our laboratory, a large set of 6-FQs was
selected. Several new 6-FQ derivatives were proposed as drug candidates for further research and development. The 6-
FQs identified as potentially effective against M. tuberculosis were subjected to an additional SSER study for prediction
of their toxicological profile. The assessment of structurally-driven adverse effects which might hamper the potential of
new drug candidates is mandatory for an effective drug design. We applied publicly available knowledge-based (expert)
systems and Quantitative Structure-Activity Relationship (QSAR) models in order to prepare a priority list of active
compounds. A preferred order of drug candidates was obtained, so that the less harmful candidates were identified for
further testing.
TOXTREE expert system as well as some QSAR models developed in the framework of EC funded project CAESAR
were used to assess toxicity. CAESAR models were developed according to the OECD principles for the validation of
QSAR and they turn to be appropriate tools for in silico tests regarding five different toxicity endpoints. Those endpoints
with high relevance for REACH are: bioconcentration factor, skin sensitization, carcinogenicity, mutagenicity, and
developmental toxicity. We used the above-mentioned freely available models to select a set of less harmful active 6-FQs
as candidates for clinical studies.
