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 (ref. 3), 10−2 of its K d value for erythropoietin-EPOR binding site 1 (Kd 1 nM), and 10−5 of the K d for erythropoietin-EPOR binding site 2 (Kd 1 μM). Overall half-maximal binding (IC50) of cell-surface receptors is produced with ∼0.18 nM erythropoietin, indicating that only ∼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 K d values (∼0.1 μM). The crystal structure of erythropoietin complexed to the extracellular ligand-binding domains of the erythropoietin receptor, determined at 1.9 Å from two crystal forms, shows that erythropoietin imposes a unique 120° angular relationship and orientation that is responsible for optimal signalling through intracellular kinase pathways.
A virtual screen of a subsection of the AstraZeneca compound collection was performed for checkpoint kinase-1 (Chk-1 kinase) using a knowledge-based strategy. This involved initial filtering of the ...compound collection by application of generic physical properties followed by removal of compounds with undesirable chemical functionality. Subsequently, a 3-D pharmacophore screen for compounds with kinase binding motifs was applied. A database of approximately 200K compounds remained for docking into the active site of Chk-1 kinase, using the FlexX-Pharm program. For each compound that docked successfully into the binding site, up to 100 poses were saved. These poses were then postfiltered using a customized consensus scoring scheme for a kinase, followed by visual inspection of a selection of the docked compounds. This resulted in 103 compounds being ordered for testing in the project assay, and 36 of these (corresponding to four chemical classes) were found to inhibit the enzyme in a dose−response fashion with IC50 values ranging from 110 nM to 68 μM.
The X-ray crystal structure of a 19 kDa active fragment of human fibroblast collagenase has been determined by the multiple isomorphous replacement method and refined at 1.56 A resolution to an ...R-factor of 17.4%. The current structure includes a bound hydroxamate inhibitor, 88 waters and three metal atoms (two zincs and a calcium). The overall topology of the enzyme, comprised of a five stranded beta-sheet and three alpha-helices, is similar to the thermolysin-like metalloproteinases. There are some important differences between the collagenase and thermolysin families of enzymes. The active site zinc ligands are all histidines (His-218, His-222, and His-228). The presence of a second zinc ion in a structural role is a unique feature of the matrix metalloproteinases. The binding properties of the active site cleft are more dependent on the main chain conformation of the enzyme (and substrate) compared with thermolysin. A mechanism of action for peptide cleavage similar to that of thermolysin is proposed for fibroblast collagenase.
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.
Solvation free energy is an important molecular characteristic useful in drug discovery because it represents the desolvation cost of a ligand binding to a receptor. Most of the recent developments ...in the estimation of solvation free energy require the use of molecular mechanics and dynamics calculations. Group contribution methods have been rarely used in the past for calculating solvation free energy because automated prediction methods have not been developed in this regard. As an aid to combinatorial library design, we explored rapid and accurate means of computing solvation free energies from the covalent structures of organic molecules and compared the results on a test set with the GB/SA solvation model. Two independent additive-constitutive QSPR methods have been developed for the computation of solvation free energy. The first is a QSPR model (HLOGS) derived using a technique that uses the counts of distinct/similar fragments and substructures for each molecule as variables in a PLS regression. The second method (ALOGS) uses an extensive atom classification scheme developed earlier for the calculation of Log P. A database of 265 molecules with experimentally determined solvation free energies is used to derive the HLOGS (r = 0.97; rms = 0.58) and ALOGS (r = 0.98; rms = 0.38) models, which were then tested on 27 molecules not present in the training set. A detailed comparison of the HLOGS, ALOGS, GB/SA (with AMBER* and OPLSA* potentials) on the test set showed that the HLOGS and ALOGS models give better results than the GB/SA model. Among the three methods tested, the ALOGS method gives the best result on the test set (r = 0.96; rms = 0.86), though the parametrization for this method is incomplete as many atom types are undetermined due to their absence in the current training set. The HLOGS method appears to handle intramolecular interactions better than the ALOGS method.
Electrostatic calculations have been carried out on a number of structural conformers of tuna cytochrome c. Conformers were generated using molecular dynamics simulations with a range of solvent ...simulating, macroscopic dielectric formalisms, and one solvent model that explicitly included solvent water molecules. Structures generated using the lowest dielectric models were relatively tight, with side chains collapsed on the surface, while those from the higher dielectric models had more internal and external fluidity, with surface side chains exploring a fuller range of conformational space. The average structure generated with the explicitly solvated model corresponded most closely with the crystal structure. Individual pK values, overall titration curves, and electrostatic potential surfaces were calculated for average structures and structures along each simulation. Differences between structural conformers within each simulation give rise to substantial changes in calculated local electrostatic interactions, resulting in pK value fluctuations for individual sites in the protein that vary by 0.3-2.0 pK units from the calculated time average. These variations are due to the thermal side chain reorientations that produce fluctuations in charge site separations. Properties like overall titration curves and pH dependent stability are not as sensitive to side chain fluctuations within a simulation, but there are substantial effects between simulations due to marked differences in average side chain behavior. These findings underscore the importance of proper dielectric formalism in molecular dynamics simulations when used to generate alternate solution structures from a crystal structure, and suggest that conformers significantly removed from the average structure have altered electrostatic properties that may prove important in episodic protein properties such as catalysis.
Energy transfer in the "rapid diffusion" limit from electronically excited terbium(III) chelates in three different charge states to horse heart ferricytochrome c was measured as a function of ionic ...strength. Theoretical rate constants calculated by numerical integration of the Forster integral (containing the Poisson-Boltzmann-generated protein electrostatic potential) were compared with the experimental data to evaluate the accuracy of protein electrostatic field calculations at the protein/solvent interface. Two dielectric formalisms were used: a simple coulombic/Debye-Huckel procedure and a finite difference method Warwicker, J. \& Watson, H. C. (1982) J. Mol. Biol. 157, 671-679 that accounts for the low-dielectric protein interior and the irregular protein/solvent boundary. Good agreement with experiment was obtained and the ionic-strength dependence of the reaction was successfully reproduced. The sensitivity of theoretical rate constants to the choices of effective donor sphere size and the energy transfer distance criterion was analyzed. Electrostatic potential and rate-constant calculations were carried out on sets of structures collected along two molecular dynamics trajectories of cytochrome c. Protein conformational fluctuations were shown to produce large variations in the calculated energy transfer rate constant. We conclude that protein fluctuations and the resulting transient structures can play significant roles in biological or catalytic activities that are not apparent from examination of a static structure. For calculating protein electrostatics, large-scale low-frequency conformational fluctuations, such as charged side-chain reorientation, are established to be as important as the computational method for incorporating dielectric boundary effects.
The concept of pharmacophore modeling is one of the oldest yet most widely used concepts in today's drug discovery research. The essential substructural moieties of a molecule necessary for its ...pharmacological activity are called pharmacophores. This terminology was first introduced by Ehrlich, following the term chromophore, which was used to represent the functional groups responsible for the color of a compound. The interest in the idea of pharmacophores has grown enormously in recent years owing to the availability of various automated computerized software for identifying pharmacophores as well as their geometry. The pharmacophoric information as well as their three-dimensional structure can often be used to identify novel pharmacologically active lead compounds by searching various databases of known chemicals, like the Available Chemical Directory (ACD). Compounds having similar pharmacophoric groups often have similar biological activity. Understandably, the existence of similar or the same pharmacophoric groups does not guarantee that biological activity will be similar. The differentiating structural moieties may cause enough repulsive interaction with the target protein/receptor to diminish or abolish its binding affinity, or its chemical or physicochemical properties may be altered enough to prevent it from reaching the binding site.
PDF
