ReviewCurrent opinion in chemical biology2011
Large-scale integrated super-computing platform for next generation virtual drug discovery.
Review in Current opinion in chemical biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- An Improved Method for P2X7R Antagonist Screening.PloS one · 2015Article
- New insights for drug design from the X-ray crystallographic structures of G-protein-coupled receptors.Molecular pharmacology · 2012Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditional drug discovery starts by experimentally screening chemical libraries to find hit compounds that bind to protein targets, modulating their activity. Subsequent rounds of iterative chemical derivitization and rescreening are conducted to enhance the potency, selectivity, and pharmacological properties of hit compounds. Although computational docking of ligands to targets has been used to augment the empirical discovery process, its historical effectiveness has been limited because of the poor correlation of ligand dock scores and experimentally determined binding constants. Recent progress in super-computing, coupled to theoretical insights, allows the calculation of the Gibbs free energy, and therefore accurate binding constants, for usually large ligand-receptor systems. This advance extends the potential of virtual drug discovery. A specific embodiment of the technology, integrating de novo, abstract fragment based drug design, sophisticated molecular simulation, and the ability to calculate thermodynamic binding constants with unprecedented accuracy, are discussed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.