Journal: bioRxiv

Article Title: High Content Screening and Proteomic Analysis Identify a Kinase Inhibitor that rescues pathological phenotypes in a Patient-Derived Model of Parkinson’s Disease

doi: 10.1101/2020.06.12.148031

Figure Lengend Snippet: a. Directed differentiation of Pax6+ (green)/ Nestin+ (red) neural precursor cells (NPCs; DIV 0, left) into TUJ1+ (red)/ TH+ (green) neurons (DIV 21, right). The differentiation protocol and timeline of analysis are shown in the drawing in the middle.. FG2 and FGF8, fibroblast growth factors 2 and 8; SHH, Sonic Hedgehog; AA, ascorbic acid; Scale bar represents BDNF, brain-derived neurotrophic factor; GDNF, glial cell-derived neurotrophic factor (GDNF); cAMP, cyclic AMP. Scale bars, 50 μm. b. Scatter plot showing the ratio of TH versus TUJ1 fluorescence intensity in duplicate upon treatment with 273 small molecule kinase inhibitors. The dots inside the green square correspond to the 4 hit compounds showing significant increase of TH versus TUJ1 fluorescence ratio as compared to the DMSO controls (blue dots). The red arrow indicates BX795. c. Representative images of patient-derived p.A53T-neurons immunolabelled for TH in 384-well plates. Upper micrograph shows control DMSO-treated cells while lower micrograph represents BX795-treated cells. Scale bar represents 150 μm. d. Tests of the four hit compounds in a dose-response format. Data are presented as mean ± SEM.(one-way ANOVA, *P<0.05, n=3 independent experiments).

Article Snippet: A collection of 273 small molecule kinase inhibitors from Selleck Chemicals was used.

Techniques: Derivative Assay, Fluorescence

Journal: Biochemistry

Article Title: The Rational Discovery of a Tau Aggregation Inhibitor

doi: 10.1021/acs.biochem.8b00581

Figure Lengend Snippet: Discovery of potentially active compounds through iterative machine learning. a) A pilot set of 1000 compounds randomly chosen from the CNS library was docked against the 10 most populated clusters from each of the 25 segments. The histogram of each compound’s most favored target illustrates that some segments of tau4RD are better able to accommodate small molecule binding. b) PLSR trained on 990 compounds from the pilot set was able to predict the docking scores of the remaining 10 compounds with reasonable accuracy. Pearson correlation coefficients are shown at the bottom of the panel. c) PLSR was used to select compounds from the diverse set of small molecules in the CNS library. Iteration 1 yielded 1000 compounds based on the results and fingerprints of the pilot set. Iteration 2, based on the docking scores and fingerprints of the 2000 compounds from the pilot set and Iteration 1, yielded primarily compounds that had already been examined and docked in Iteration 1. When these were excluded from the library, the next 1000 compounds (“Iter. 2 – new”) displayed worse docking scores on average. This indicated that the PLSR search had largely converged.

Article Snippet: Selected compounds were identified from the ChemBridge CNS small molecule collection, and dry samples were obtained through Hit2Lead (ChemBridge, San Diego, CA).

Techniques: Binding Assay