| Autor: |
V. Joachim Haupt, Florian Kaiser, Thomas Schubert, Maximilian G. Plach |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| DOI: |
10.1101/2020.04.22.021360 |
| Popis: |
Accelerated development of lead structures is of high interest to the pharmaceutical industry in order to decrease development times and costs. We showcase how an intelligent combination of AI-based drug screening with state-of-the-art biophysics drives the rapid identification of novel inhibitor structures with high chemical diversity for cGMP-dependent 3’,5’-cyclic phosphodiesterase (PDE2). The starting point was an off-the-shelve chemical library of two million drug-like compounds. In a single in silico reduction step, we short-listed 125 compounds – the focused library – as potential binders to PDE2 and tested their binding behavior in vitro using MicroScale Thermophoresis (MST). Of this focused library, seven compounds indicated binding to PDE2, translating to a hit rate of 6%. Three of these compounds have affinities in the lower micromolar range. The compound with the highest affinity showed a KD of 10 µM and is thus an excellent starting point for further medicinal chemistry optimization. The results show how innovative and structure-driven in silico approaches and biophysics can be used to accelerate drug discovery and to obtain new molecular scaffolds at a fraction of the costs and time – compared with standard high-throughput screening. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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