Drug discovery

Virtual screening serves as a pivotal computational method within the realm of drug discovery, facilitating the exploration of vast compound libraries in search of those elusive molecular structures with the potential to form crucial interactions with a drug target. In most cases, this target is a protein receptor or enzyme intricately linked to specific diseases or conditions. The ultimate objective is to pinpoint and prioritize the most promising compounds, ones that warrant further labor-intensive experimental assessments. This strategic approach not only streamlines the drug discovery process but also offers the tantalizing prospect of significantly curtailing the associated time, financial resources, and the sheer volume of experiments necessary to identify medically active molecules.

Some drugs bind better than others

Within our research group, we are at the forefront of drug discovery through the pioneering application of virtual screening. This computational technique allows us to meticulously search vast compound libraries for those elusive structures with a high likelihood of binding to drug targets. These targets, often intricate protein receptors or enzymes intricately linked to various diseases, are the focal points of our research efforts. Our core mission involves identifying the most promising compounds that merit further experimental testing. This approach not only streamlines the drug discovery process but, significantly, dramatically reduces the time, cost, and sheer number of experiments required to unearth medically active molecules.\p>

Recent Publications

Different receptor models show differences in ligand binding strength and location: a computational drug screening for the tick-borne encephalitis virus, Felicitas Finke, Jonathan Hungerland, Ilia A. Solov'yov, Fabian Schuhmann, Molecular Diversity, https://doi.org/10.1007/s11030-024-10850-8, (2024)
Introducing the Automated Ligand Searcher, Luise Jacobsen, Jonathan Hungerland, Vladimir Bačić, Luca Gerhards, Fabian Schuhmann, Ilia A. Solov'yov, Journal of Chemical Information and Modeling, 63, 7518-7528, (2023)
Computergestütztes Screening potentiell pharmakologisch wirksamer Liganden gegen das Frühsommer-Meningoenzephalitis-Virus: Ein Vergleich verschiedener Rezeptorstrukturmodelle, Felicitas Finke, Carl von Ossietzky University, Germany, 1 — 102, Bachelor Thesis, Carl von Ossietzky University, (2023)
Design of SARS-CoV-2 Main Protease Inhibitors Using Artificial Intelligence and Molecular Dynamic Simulations, Lars Elend, Luise Jacobsen, Tim Cofala, Jonas Prellberg, Thomas Teusch, Oliver Kramer, Ilia A. Solov'yov, Molecules, 27, 4020-(1-25), (2022)
Inhibition Mechanism of Antimalarial Drugs Targeting the Cytochrome bc1 Complex, Luise Jacobsen, Peter Husen, Ilia A. Solov'yov, Journal of Chemical Information and Modeling, 61, 1334-1345, (2021)