Tolcapone

Aggregated α-synuclein (α-SYN) proteins, encoded by the SNCA gene, are hallmarks of Lewy body disease (LBD), affecting multiple brain regions. However, the specific mechanisms underlying α-SYN pathology in cortical neurons, crucial for LBD-associated dementia, remain unclear. Here, we recapitulated α-SYN pathologies in human induced pluripotent stem cells (iPSCs)–derived cortical organoids generated from patients with LBD with SNCA gene triplication. Single-cell RNA sequencing, combined with functional and molecular validation, identified synaptic and mitochondrial dysfunction in excitatory neurons exhibiting high expression of the SNCA gene, aligning with observations in the cortex of autopsy-confirmed LBD human brains. Furthermore, we screened 1280 Food and Drug Administration–approved drugs and identified four candidates (entacapone, tolcapone, phenazopyridine hydrochloride, and zalcitabine) that inhibited α-SYN seeding activity in real-time quaking-induced conversion assays with human brains, reduced α-SYN aggregation, and alleviated mitochondrial dysfunction in SNCA triplication organoids and excitatory neurons. Our findings establish human cortical LBD models and suggest potential therapeutic drugs targeting α-SYN aggregation for LBD.

Flavonoids, especially their inhibitory effect on DPP-IV activity, have been widely recognized for their antidiabetic effects. However, the variety of natural flavonoid derivatives is very rich, and even subtle structural differences can lead to several orders of magnitude differences in their inhibitory activities against DPP-IV, which makes it challenging to find novel and potent anti-DPP-IV flavonoid derivatives experimentally. Therefore, there is an urgent need to develop an efficient screening pipeline that targets active natural products. Here, we propose a fusion strategy based on a QSAR model, and to simplify this process, it was applied to the discovery of flavonoid derivatives with potent anti-DPP-IV activity. First, the high-quality QSAR model (__-mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"-__Rtest2 = 0.816, MAE_test = 0.14, MSE_test = 0.026) was composed of seven key molecular property parameters, which were constructed with the genetic algorithm (GA) and passed the leave-one-out cross-validation evaluation. A total of 1,668 flavonoid derivatives were obtained from the natural product enriched by NPCD based on molecular fingerprint similarity (> 0.8). Further, the enriched flavonoid derivatives were further predicted and screened using the QED score combined with the QSAR model, and a total of 33 flavonoid derivatives (IC50_pre < 6.5 μM) were found. Subsequently, three flavonoid derivatives (5,7,3',5'-tetrahydroxyflavone, 3,7-dihydroxy-5,3',4'-trimethoxyflavone, and 5,7,2',5'-tetrahydroxyflavone) with highly effective anti-DPP-IV activity were obtained by ADMET analysis. Finally, the DPP-IV inhibitory potential of these three flavonoid derivatives was verified by 100 ns MD simulation and MM/PB(GB)SA.Communicated by Ramaswamy H. Sarma.