Understanding metabolism related differences in ocular efficacy of MGV354

Predicting routes of phase I and II metabolism based on quantum mechanics and machine learning

Unexpected metabolism could lead to the failure of many late-stage drug candidates or even the withdrawal of approved drugs. Thus, it is critical to predict and study the dominant routes of metabolism in the early stages of research.We describe the development and validation of a 'WhichEnzyme' model that accurately predicts the enzyme families most likely to be responsible for a drug-like molecule's metabolism. Furthermore, we combine this model with our previously published regioselectivity models for Cytochromes P450, Aldehyde Oxidases, Flavin-containing Monooxygenases, UDP-glucuronosyltransferases and Sulfotransferases - the most important Phase I and Phase II drug metabolising enzymes - and a 'WhichP450' model that predicts the Cytochrome P450 isoform(s) responsible for a compound's metabolism.The regioselectivity models are based on a mechanistic understanding of these enzymes' actions and use quantum mechanical simulations with machine learning methods to accurately predict sites of metabolism and the resulting metabolites. We train heuristics based on the outputs of the 'WhichEnzyme', 'WhichP450', and regioselectivity models to determine the most likely routes of metabolism and metabolites to be observed experimentally.Finally, we demonstrate that this combination delivers high sensitivity in identifying experimentally reported metabolites and higher precision than other methods for predicting in vivo metabolite profiles.

Pharmacological Stimulation of Soluble Guanylate Cyclase Counteracts the Profibrotic Activation of Human Conjunctival Fibroblasts

Conjunctival fibrosis is a serious clinical concern implicated in a wide spectrum of eye diseases, including outcomes of surgery for pterygium and glaucoma. It is mainly driven by chronic inflammation that stimulates conjunctival fibroblasts to differentiate into myofibroblasts over time, leading to abnormal wound healing and scar formation. Soluble guanylate cyclase (sGC) stimulation was found to suppress transforming growth factor β (TGFβ)-induced myofibroblastic differentiation in various stromal cells such as skin and pulmonary fibroblasts, as well as corneal keratocytes. Here, we evaluated the in vitro effects of stimulation of the sGC enzyme with the cell-permeable pyrazolopyridinylpyrimidine compound BAY 41-2272 in modulating the TGFβ1-mediated profibrotic activation of human conjunctival fibroblasts. Cells were pretreated with the sGC stimulator before challenging with recombinant human TGFβ1, and subsequently assayed for viability, proliferation, migration, invasiveness, myofibroblast marker expression, and contractile properties. Stimulation of sGC significantly counteracted TGFβ1-induced cell proliferation, migration, invasiveness, and acquisition of a myofibroblast-like phenotype, as shown by a significant downregulation of FAP, ACTA2, COL1A1, COL1A2, FN1, MMP2, TIMP1, and TIMP2 mRNA levels, as well as by a significant reduction in α-smooth muscle actin, N-cadherin, COL1A1, and FN-EDA protein expression. In addition, pretreatment with the sGC stimulator was capable of significantly dampening TGFβ1-induced acquisition of a contractile phenotype by conjunctival fibroblasts, as well as phosphorylation of Smad3 and release of the proinflammatory cytokines IL-1β and IL-6. Taken together, our findings are the first to demonstrate the effectiveness of pharmacological sGC stimulation in counteracting conjunctival fibroblast-to-myofibroblast transition, thus providing a promising scientific background to further explore the feasibility of sGC stimulators as potential new adjuvant therapeutic compounds to treat conjunctival fibrotic conditions.