Virtual screening approach

Table 10.4-5. Recent successes of structure-based virtual screening approaches.

Pirard B, Brendel J, Peukert S. The discovery of Kvl.5 blockers as a case study for the application of virtual screening approaches. J Chem Inf Model 2005 45 477-85. 

Fig. 4.5 Examples of successful virtual screening approaches. All structures (a-l) are active against different target proteins or receptors, they were discovered in prospective applications using a variety of virtual screening approaches and work flows. See text for details.

Every currently available virtual screening approach in structure- or ligand-based design is heuristic and thus will neither provide any quality guarantee nor an error bound on the obtained results. In every case, the fundamental model describing similarity or... 

Few reports are available for systematic approaches towards new selective inhibitors of DNMTs. The most prominent example is the tryptophan derivative RG108 (NSC401077) that was identified via a virtual screening approach [30, 82] and is active between 10 and 100 iM. In the same study, NSC 303530 was also identified as a somewhat weaker inhibitor (Figure 8.10). The analog of R108 that does not contain the carboxylic acid group was found to be inactive. 

Park, H., Bhattarai, B. R, Ham, S. W., Cho, H. (2009) Structure-based virtual screening approach to identify novel classes of PTP1B inhibitors. Eur JMed Chem 44, 3280-3284. 

Roy J, Kumar UC, Machiraju PK et al (2010) In silico studies on anthrax lethal factor inhibitors pharmacophore modeling and virtual screening approaches towards designing of novel inhibitors for a killer. J Mol Graph Model 29 256-265... 

Gopalakrishnan B, Aparna V, Jeevan J et al (2005) A virtual screening approach for thymidine monophosphate kinase inhibitors as... 

Discovering High-Affinity Ligands from the Computationally Predicted Structures and Affinities of Small Molecules Bound to a Target A Virtual Screening Approach. 

Figure 5.7 shows the major contributions of the local descriptors to activity and selectivity. As can be seen, the activity and selectivity maps are quite similar but also differ. Such fine distinctions are difficult to take into account to design new promising structures intuitively (especially if selectivity with respect to other receptor subtypes is also required). Thus, the automated virtual screening approach is preferred. 

Structure-based cheminformatics virtual screening approaches are probably closest in spirit to scoring functions. The scoring functions that are discussed below are judged either by their ability to correlate with experimental binding affinity or to recover known hits from compound collections. 

Summary and Conclusions Integration of Conventional and Cheminformatics Structure-based Virtual Screening Approaches... 

Simple descriptors as described above are quickly calculated and counted. Therefore, after typically removing compounds with atoms other than C, N, 0, S, H, P, Si, Cl, Br, F, and I, counting schemes present the first filter in virtual screening approaches. 

Once they are trained, neural networks and decision trees are very fast filter tools in virtual screening approaches. They are therefore applied early in the virtual screening filter cascade. 

Clark, D.E. Higgs, C. Wren, S.P. Dyke, H.J. Wong, M. Norman, D. Lockey, P.M. Roach, A.G. A virtual screening approach to finding novel and potent antagonists at... 

Structure-based virtual screening approaches (or high-throughput docking , HTD) are coming of age. " " These... 

---