Naeglearia fowleri proline tRNA synthetase inhibitors

迄今为止发现的脯氨酸tRNA合成酶抑制剂都是基于知识的，并且在化学性质空间中采样的极小部分，以这种方式确定的化合物对传染病的临床影响可以忽略不计。在此期间，项目组对选定的小分子文库进行了定量高通量筛选（qHTS），并对命中的化合物进行了验证。

Proline tRNA synthetase inhibitors discovered to date have all been knowledge-based and sampled an extremely small portion of chemical property space and compounds identified this way have had negligible clinical impact against infectious diseases. During this period, the project team conducted quantitative high-throughput screening (qHTS) on select small molecule libraries, and hit compounds were validated. Machine learning approaches were utilized to construct in silico quantitative structure-activity relationship (QSAR) models to enable virtual screening of compounds against larger collections of NCATS molecules. Work is ongoing screening larger compound collections to identify compounds with increased potency and enable refinement of the QSAR model.