Docking & Chemoinformatic Screens for New Ligands and Targets

By Peter Kolb, Rafaela Salgado Ferreira, John J. Irwin, Brian K. Shoichet. 2009

176 citations recorded by the source corpus.

Computer-based docking screens are now widely used to discover new ligands for targets of known structure; in the last two years alone, the discovery of ligands for over 20 proteins have been reported. Recently, investigators have also turned to predicting new substrates and for enzymes of unknown function, taking docking in a wholly new direction. Increasingly, the hit-rates, the true- and the false-positives from the docking screens are being compared to those from empirical, high-throughput screens, revealing the strengths, weaknesses and complementarities of both techniques. The recent efflorescence of GPCR structures has made these quintessential drug targets available to structure-based approaches. Consistent with their “druggability”, the docking screens have returned high hit-rates and potent molecules. Finally, in the last several years, an approach almost exactly opposite to docking has also appeared; this pharmacological network approach begins not with the structure of the target but rather those of drug molecules and asks, given a pattern of chemistry in the ligands, what targets may a particular drug bind to? This method, which returns to an older, pharmacology logic, has been surprisingly successful in predicting new “off-targets” for established drugs.

Subfields: Computational Theory and Mathematics, Molecular Biology, Radiology, Nuclear Medicine and Imaging

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Citations in the corpus

The enumeration of chemical space (2012, methodology): “29 , 30 Because virtual screening relies on the implementation of theoretical models, the method is very similar to rational design, but is better described as rational choosing.”
Visualisation and subsets of the chemical universe database GDB-13 for virtual screening (2011, background): “GDB-13 is far too large for applying advanced virtual screening tools such as docking or shape-based analyses, which are too resource intensive to perform on more than a few million structures [ 33 ].”
How accurately can one predict drug binding modes using AlphaFold models? (2023, background): “The vast majority of drug targets are proteins, and structures play a critical role in rational drug design (Anderson, 2003; Kolb et al., 2009).”
Virtual Screening with AutoDock: Theory and Practice (2010, background): “Today, virtual screening is widely used to predict the binding of a large database of ligands to a particular target, with the goal of identifying the most promising compounds from the database for further study [10,14-20].”
Advances and Challenges in Protein-Ligand Docking (2010, background): “Among them, protein-ligand docking is a particularly vibrant research area because of its importance to structure-based drug design [2–8] and will be the subject of the present review.”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, methodology): “The pharmacological network approach asks, given a pattern of chemistry in the ligands, which targets a particular drug may bind (Kolb et al., 2009)?”
Challenges and advances in computational docking: 2009 in review (2011, background): “Their importance is due to them being targeted by a very large number of drugs (146).”