Virtual screening

Virtual screening ("VS") has become an integral part of the drug discovery process in recent years. Related to the more general and long pursued concept of database searching, the term "virtual screening" is relatively new. Walters, et al. define virtual screening as "automatically evaluating very large libraries of compounds" using computer programs.^[1] As this definition suggests, VS has largely been a numbers game focusing on questions like how can we filter down the enormous chemical space of over 10⁶⁰ conceivable compounds^{[citation needed]} to a manageable number that can be synthesized, purchased, and tested. Although filtering the entire chemical universe might be a fascinating question, more practical VS scenarios focus on designing and optimizing targeted combinatorial libraries and enriching libraries of available compounds from in-house compound repositories or vendor offerings.

Additional recommended knowledge

Daily Visual Balance Check

Correct Test Weight Handling Guide: 12 Practical Tips

Essential Laboratory Skills Guide

The main goal of a virtual screen is to come up with hits of novel chemical structure that yield a unique pharmacological profile. Thus, success of a virtual screen is defined in terms of finding interesting new scaffolds rather than many hits. Interpretations of VS accuracy should therefore be considered with caution. Low hit rates of interesting scaffolds are clearly preferable over high hit rates of already known scaffolds.

See also

• Virtual high throughput screening
• Scoring functions

References

1. ^ Walters WP, Stahl MT, Murcko MA (1998). "Virtual screening – an overview". Drug Discov. Today 3 (4): 160-178. doi:10.1016/S1359-6446(97)01163-X.

Further reading

• Melagraki G, Afantitis A, Sarimveis H, Koutentis PA, Markopoulos J, Igglessi-Markopoulou O (2007). "Optimization of biaryl piperidine and 4-amino-2-biarylurea MCH1 receptor antagonists using QSAR modeling, classification techniques and virtual screening". J. Comput. Aided Mol. Des. 21 (5): 251–67. doi:10.1007/s10822-007-9112-4. PMID 17377847.
• Afantitis A, Melagraki G, Sarimveis H, Koutentis PA, Markopoulos J, Igglessi-Markopoulou O (2006). "Investigation of substituent effect of 1-(3,3-diphenylpropyl)-piperidinyl phenylacetamides on CCR5 binding affinity using QSAR and virtual screening techniques". J. Comput. Aided Mol. Des. 20 (2): 83–95. doi:10.1007/s10822-006-9038-2. PMID 16783600.
• Eckert H, Bajorath J (2007). "Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches". Drug Discov. Today 12 (5-6): 225–33. doi:10.1016/j.drudis.2007.01.011. PMID 17331887.
• Willett P (2006). "Similarity-based virtual screening using 2D fingerprints". Drug Discov. Today 11 (23-24): 1046–53. doi:10.1016/j.drudis.2006.10.005. PMID 17129822.
• Fara DC, Oprea TI, Prossnitz ER, Bologa CG, Edwards BS, Sklar LA (2006). "Integration of virtual and physical screening". Drug Discov. Today: Technologies 3 (4): 377-385. doi:doi:10.1016/j.ddtec.2006.11.003.
• Muegge I, Oloffa S (2006). "Advances in virtual screening". Drug Discov. Today: Technologies 3 (4): 405-411. doi:doi:10.1016/j.ddtec.2006.12.002.