The discovery of various protein/receptor targets from genomic research is expanding rapidly. Along with the automation of organic synthesis and biochemical screening, this is bringing a major change in the whole field of drug discovery research. In the traditional drug discovery process, the industry tests compounds in the thousands. With automated synthesis, the number of compounds to be tested could be in the millions. This two-dimensional expansion will lead to a major demand for resources, unless the chemical libraries are made wisely. The objective of this work is to provide both quantitative and qualitative characterization of known drugs which will help to generate "drug-like" libraries. In this work we analyzed the Comprehensive Medicinal Chemistry (CMC) database and seven different subsets belonging to different classes of drug molecules. These include some central nervous system active drugs and cardiovascular, cancer, inflammation, and infection disease states. A quantitative characterization based on computed physicochemical property profiles such as log P, molar refractivity, molecular weight, and number of atoms as well as a qualitative characterization based on the occurrence of functional groups and important substructures are developed here. For the CMC database, the qualifying range (covering more than 80% of the compounds) of the calculated log P is between -0.4 and 5.6, with an average value of 2.52. For molecular weight, the qualifying range is between 160 and 480, with an average value of 357. For molar refractivity, the qualifying range is between 40 and 130, with an average value of 97. For the total number of atoms, the qualifying range is between 20 and 70, with an average value of 48. Benzene is by far the most abundant substructure in this drug database, slightly more abundant than all the heterocyclic rings combined. Nonaromatic heterocyclic rings are twice as abundant as the aromatic heterocycles. Tertiary aliphatic amines, alcoholic OH and carboxamides are the most abundant functional groups in the drug database. The effective range of physicochemical properties presented here can be used in the design of drug-like combinatorial libraries as well as in developing a more efficient corporate medicinal chemistry library.
The high affinity of the noncovalent interaction between biotin and streptavidin forms the basis for many diagnostic assays that require the formation of an irreversible and specific linkage between biological macromolecules. Comparison of the refined crystal structures of apo and a streptavidin:biotin complex shows that the high affinity results from several factors. These factors include the formation of multiple hydrogen bonds and van der Waals interactions between biotin and the protein, together with the ordering of surface polypeptide loops that bury the biotin in the protein interior. Structural alterations at the biotin binding site produce quaternary changes in the streptavidin tetramer. These changes apparently propagate through cooperative deformations in the twisted beta sheets that link tetramer subunits.
Molecular hydrophobicity (lipophilicity), usually quantified as log P (the logarithm of 1-octanol/water partition coefficient), is an important molecular characteristic in drug discovery. ALOGP and CLOGP are two of the most widely used methods for the estimation of log P. This work describes an extensive reparametrization of the atomic log P values and a detailed comparison of the performance of ALOGP and CLOGP methods on the Pomona Medchem database. Only the “star list” compounds having precisely measured log P values were used in this analysis. While the overall results with both methods are similar, analysis shows that the CLOGP method is better for very small molecules in the range of 1−20 atoms. The two methods are almost comparable in the range of 21−45 atoms, while the ALOGP method has better accuracy for molecules with more than 45 atoms. Although the rms deviation and the correlation coefficient for CLOGP predictions were marginally better than those for corresponding ALOGP predictions, the latter showed a very stable performance for all classes of organic compounds analyzed. The ALOGP method can be used to compute estimates of most neutral organic compounds having C, H, O, N, S, Se, P, B, Si, and halogens. It also covers most zwitterionic compounds having amine and carboxylic acids and ammonium halide salts. The CLOGP method has improved considerably over the years to cover most neutral organic compounds, but it still has some undefined fragments. Finally, unlike CLOGP and other methods of predicting lipophilicity, the ALOGP method has multiple uses, such as the estimation of local hydrophobicity, the visualization of molecular hydrophobicity maps, and the evaluation of hydrophobic interactions in protein−ligand complexes.
Human erythropoietin is a haematopoietic cytokine required for the differentiation and proliferation of precursor cells into red blood cells. It activates cells by binding and orientating two cell-surface erythropoietin receptors (EPORs) which trigger an intracellular phosphorylation cascade. The half-maximal response in a cellular proliferation assay is evoked at an erythropoietin concentration of 10 pM, 10(-2) of its Kd value for erythropoietin-EPOR binding site 1 (Kd approximately equal to nM), and 10(-5) of the Kd for erythropoietin-EPOR binding site 2 (Kd approximately equal to 1 microM). Overall half-maximal binding (IC50) of cell-surface receptors is produced with approximately 0.18 nM erythropoietin, indicating that only approximately 6% of the receptors would be bound in the presence of 10 pM erythropoietin. Other effective erythropoietin-mimetic ligands that dimerize receptors can evoke the same cellular responses but much less efficiently, requiring concentrations close to their Kd values (approximately 0.1 microM). The crystal structure of erythropoietin complexed to the extracellular ligand-binding domains of the erythropoietin receptor, determined at 1.9 A from two crystal forms, shows that erythropoietin imposes a unique 120 degrees angular relationship and orientation that is responsible for optimal signalling through intracellular kinase pathways.
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