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Chemical language models enable de novo drug design without the requirement for explicit molecular construction rules. While such models have been applied to generate novel compounds with desired bioactivity, the actual prioritization and selection of the most promising computational designs remains challenging. Herein, we leveraged the probabilities learnt by chemical language models with the beam search algorithm as a model-intrinsic technique for automated molecule design and scoring. Prospective application of this method yielded novel inverse agonists of retinoic acid receptor-related orphan receptors (RORs). Each design was synthesizable in three reaction steps and presented low-micromolar to nanomolar potency towards RORγ. This model-intrinsic sampling technique eliminates the strict need for external compound scoring functions, thereby further extending the applicability of generative artificial intelligence to data-driven drug discovery.
Designed polypharmacology presents as an attractive strategy to increase therapeutic efficacy in multi-factorial diseases by a directed modulation of multiple involved targets with a single molecule. Such an approach appears particularly suitable in non-alcoholic steatohepatitis (NASH) which involves hepatic steatosis, inflammation and fibrosis as pathological hallmarks. Among various potential pharmacodynamic mechanisms, activation of the farnesoid X receptor (FXRa) and inhibition of leukotriene A4 hydrolase (LTA4Hi) hold promise to counteract NASH according to preclinical and clinical observations. We have developed dual FXR/LTA4H modulators as pharmacological tools, enabling evaluation of this polypharmacology concept to treat NASH and related pathologies. The optimized FXRa/LTA4Hi exhibits well-balanced dual activity on the intended targets with sub-micromolar potency and is highly selective over related nuclear receptors and enzymes rendering it suitable as tool to probe synergies of dual FXR/LTA4H targeting.
Non-alcoholic steatohepatitis (NASH) - a hepatic manifestation of the metabolic syndrome - is a multifactorial disease with alarming global prevalence. It involves steatosis, inflammation and fibrosis in the liver, thus demanding multiple modes of action for robust therapeutic efficacy. Aiming to fuse complementary validated anti-NASH strategies in a single molecule, we have designed and systematically optimized a scaffold for triple activation of farnesoid X receptor (FXR), peroxisome proliferator-activated receptor (PPAR) α and PPARδ. Pilot profiling of the resulting triple modulator demonstrated target engagement in native cellular settings and in mice, rendering it a suitable tool to probe the triple modulator concept in vivo. In DIO NASH in mice, the triple agonist counteracted hepatic inflammation and reversed hepatic fibrosis highlighting the potential of designed polypharmacology in NASH.