Pharmacophore searches

The JME can also serve as a query input tool for structure databases by allowing creation of complex substructure queries (Figure 2-130), which are automatically translated into SMARTS [22]. With the help of simple HTML-format elements the creation of 3D structure queries is also possible, as were used in the 3D pharmacophore searches in the NCI database system [129]. Creation of reac-... 

D substructure search is usually known as pharmacophore searching in QSAR. Generally speaking, there are two major approaches to it topological and chemical function queries. These two techniques are based on a slighfly different philosophy and usually provide different results [31]. 

The 3D pharmacophore search with C(5)ROL in the Biochemical Pathways database provided 13 different molecules as hits. To further limit the number of hits, the additional restriction was imposed that the hits should have only two hydrogen... 

S Wang, DW Zaharevitz, R Sharma, VE Marquez, NE Lewm, L Du, PM Blumberg, GWA Milne. The discovery of novel, stnicturally diverse protein kinase C agonists through computer 3D-database pharmacophore search. I Med Chem 37 4479-4489, 1994. 

Today, 3D databases, which provide the means for storing and searching for 3D information of compounds, are proven to be useful tools in drug discovery programs. This is well exemplified with the recent discovery of novel nonpeptide HIV-1 protease inhibitors using pharmacophore searches of the National Cancer Institute 3D structural database [13-15]. 

Langer T, Hoffmann R. Pharmacophores and pharmacophore searches (Vol. 32 of Mannhold R, Kubinyi H, Foikers G, editors. Methods and Principles in Medicinal Chemistry). Weinheim Wiley-VCH, 2006. 

Hong H, Neamati N, Wang S, Nicklaus MC, Mazumder A, Zhao H, Burke Jr TR, Pommier Y, Milne GWA. Discovery of HIV-1 integrase inhibitors by pharmacophore searching. J Med Chem 1997 40 930-6. 

The final part is devoted to a survey of molecular properties of special interest to the medicinal chemist. The Theory of Atoms in Molecules by R. F.W. Bader et al., presented in Chapter 7, enables the quantitative use of chemical concepts, for example those of the functional group in organic chemistry or molecular similarity in medicinal chemistry, for prediction and understanding of chemical processes. This contribution also discusses possible applications of the theory to QSAR. Another important property that can be derived by use of QC calculations is the molecular electrostatic potential. J.S. Murray and P. Politzer describe the use of this property for description of noncovalent interactions between ligand and receptor, and the design of new compounds with specific features (Chapter 8). In Chapter 9, H.D. and M. Holtje describe the use of QC methods to parameterize force-field parameters, and applications to a pharmacophore search of enzyme inhibitors. The authors also show the use of QC methods for investigation of charge-transfer complexes. 

Chemical Information, Irvine CA Tripos, Inc. St. Louis MO), similarity searching can be carried out around a well-defined compound class using local descriptors such as atom pairs [46, 47] or topomeric shape [48, 49]. Also, ligand-based pharmacophore searches are able to identify follow-up compounds that are less obvious and more diverse than similarity searches [30, 50-54]. The problem with the latter methods is defining the molecular shape or pharmacophore specifically enough to be useful when there are few hits within a compound class and they cannot be reliably aligned (as is often the case for NMR hits in the absence of detailed structural information). 

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