Biology subjects

Plach, M. G.

Publications and source records attributed to Plach, M. G..

2 recordsLinked to original sources

bioRxiv2020

In Silico Driven Prediction of MAPK14 Off-Targets Reveals Unrelated Proteins with High Accuracy

During the discovery and development of new drugs, candidates with undesired and potentially harmful side-effects can arise at all stages, which poses significant scientific and economic risks. Most of such phenotypic side-effects can be attributed to binding of the drug candidate to unintended proteins, so-called off-targets. The early identification of potential off-targets is therefore of utmost importance to mitigate any downstream risks. We showcase how the combination of knowledge-based in silico off-target screening and state-of-the-art biophysics can be applied to rapidly identify off-targets for a MAPK14 inhibitor. Out of 13 predicted off-targets, six proteins were confirmed to interact with the inhibitor in vitro, which translates to an exceptional hit rate of 46%. For two proteins, affinities in the lower micromolar range were obtained: The kinase IRE1 and the Hematopoietic Prostaglandin D Synthase, which is entirely unrelated to MAPK14 and is involved in different cell-regulatory processes. The whole off-target identification/validation pipeline can be completed as fast as within two months, excluding delivery times of proteins. These results emphasize how computational off-target screening in combination with MicroScale Thermophoresis can effectively reduce downstream development risks in a very competitive time frame and at low cost.

bioinformatics↗

bioRxiv2020

Focus Your Screening Library: Rapid Identification of Novel PDE2 Inhibitors with in silico Driven Library Prioritization and MicroScale Thermophoresis

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 {micro}M 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.

bioinformatics↗