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Biology subjects

Heiden, S.

Publications and source records attributed to Heiden, S..

2 recordsLinked to original sources

Discovery of Membrane Channel Modulators via DNA-Encoded Library Screening Using Native-Like Membrane Protein Nanoparticles

Developing novel drugs against membrane proteins is a major challenge in drug discovery due to the difficulty of stabilizing these targets for high-throughput screenings. Pannexin 1 (PANX1) is a membrane channel protein involved in various physiological and pathological processes, making it a promising target for drug discovery. However, efforts to develop PANX1-targeting therapeutics have been hindered by the inherent challenges of stabilizing the protein channel and conducting effective pharmacological screening. Here, we report a proof-of-concept workflow that integrates the Salipro lipid nanoparticle platform with DNA-Encoded Library screenings in a detergent-free format. In this case study, the Salipro DirectMX method was used to generate functional PANX1 nanoparticles for drug discovery and characterisation. Using a high-stringency selection strategy and computational approaches, we identified a specific set of candidate compounds with selective PANX1 enrichment. Surface Plasmon Resonance analysis confirmed the identification of hit compounds. Cryo-Electron Microscopy of the Salipro-PANX1-Compound complex provided structural insights into a potential compound binding site. Electrophysiological recordings in PANX1-expressing Xenopus laevis oocytes demonstrated dose-dependent inhibition of PANX1-mediated ion conductance by the compounds. These findings establish a robust workflow for ligand discovery against challenging membrane protein targets and provide novel chemical starting points for the development of PANX1 modulators.

biochemistry↗

Winner(s)-take-all: nonlinear amplification of DNA-encoded library

Information processing functions are essential for biological organisms to perceive and react to their complex enviornment, as well as for human to analyze and rationalize them. While our brain has an extraordinary power to process complex information, winner(s)-take-all computation is one of the simplest models of lateral inhibition and competition among biological neurons. It has been implemented as DNA-based neural networks, for example, to mimic pattern recognition. However, the utility of DNA-based computation in information processing for real biotechnological applications remains to be demonstrated. In this paper, we developed a winner(s)-take-all method for non-linear amplification of mixtures of DNA sequences. Unlike conventional biological experiments, selected species were not directly subjected to analysis. Instead, parallel computation among myriad of different DNA sequences was carried out with a neural network-inspired winner-take-all function, to reduce the information complexity. The method could be used for various oligonucleotide-encoded libraries, as we have demonstrated its application in decoding and data analysis for selection experiment with DNA-encoded chemical library against protein target.

bioengineering↗