J Chem Inf Model - Target-independent prediction of drug synergies using only drug lipophilicity.

Tópicos

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Resumo

Physicochemical properties of compounds have been instrumental in selecting lead compounds with increased drug-likeness. However, the relationship between physicochemical properties of constituent drugs and the tendency to exhibit drug interaction has not been systematically studied. We assembled physicochemical descriptors for a set of antifungal compounds ("drugs") previously examined for interaction. Analyzing the relationship between molecular weight, lipophilicity, H-bond donor, and H-bond acceptor values for drugs and their propensity to show pairwise antifungal drug synergy, we found that combinations of two lipophilic drugs had a greater tendency to show drug synergy. We developed a more refined decision tree model that successfully predicted drug synergy in stringent cross-validation tests based on only lipophilicity of drugs. Our predictions achieved a precision of 63% and allowed successful prediction for 58% of synergistic drug pairs, suggesting that this phenomenon can extend our understanding for a substantial fraction of synergistic drug interactions. We also generated and analyzed a large-scale synergistic human toxicity network, in which we observed that combinations of lipophilic compounds show a tendency for increased toxicity. Thus, lipophilicity, a simple and easily determined molecular descriptor, is a powerful predictor of drug synergy. It is well established that lipophilic compounds (i) are promiscuous, having many targets in the cell, and (ii) often penetrate into the cell via the cellular membrane by passive diffusion. We discuss the positive relationship between drug lipophilicity and drug synergy in the context of potential drug synergy mechanisms.

Resumo Limpo

physicochem properti compound instrument select lead compound increas druglik howev relationship physicochem properti constitu drug tendenc exhibit drug interact systemat studi assembl physicochem descriptor set antifung compound drug previous examin interact analyz relationship molecular weight lipophil hbond donor hbond acceptor valu drug propens show pairwis antifung drug synergi found combin two lipophil drug greater tendenc show drug synergi develop refin decis tree model success predict drug synergi stringent crossvalid test base lipophil drug predict achiev precis allow success predict synergist drug pair suggest phenomenon can extend understand substanti fraction synergist drug interact also generat analyz largescal synergist human toxic network observ combin lipophil compound show tendenc increas toxic thus lipophil simpl easili determin molecular descriptor power predictor drug synergi well establish lipophil compound promiscu mani target cell ii often penetr cell via cellular membran passiv diffus discuss posit relationship drug lipophil drug synergi context potenti drug synergi mechan

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