Virtual screening: an endless staircase?

By Gisbert Schneider. 2010

515 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computational Theory and Mathematics, Molecular Biology, Computational Chemistry & Drug Discovery

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Citations in the corpus

Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules (2016, neutral): “However, even when accurate simulations are available, 7 computational molecular design is limited by the search strategy used to explore chemical space.”
Machine learning of molecular electronic properties in chemical compound space (2013, background): “While there is a wide variety of descriptors used in chem- and bio-informatics applications [23–27], they are conventionally based on”
PubChem3D: Diversity of shape (2011, background): “Virtual screening of large chemical databases is now a routine practice in modern drug discovery [1-8].”
Performance of machine-learning scoring functions in structure-based virtual screening (2017, background): “1) (1) per-target – in this approach, we generate 102 unique machine-learning SFs, each created independently for a single protein target (trained only on its active and decoys ligands); (2) horizontal split – both training and test sets contain data from all targets, i.”
ChemProt-3.0: a global chemical biology diseases mapping (2016, unknown): “These help to mine evaluate and ultimately distil this vast amount of protein–ligand interactions data, enabling the predictions of single ligands against a set of heterogeneous targets (16).”
Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review (2012, background): “It thus seems more appropriate in many applications to view DBVS from a problem-centric than a method-centric perspective (19).”
Structure-based drug discovery and protein targets in the CNS. (2011, methodology): “A recent commentary on the current state of the methods is provided by Schneider (2010).”