Biomedical subjects

D A Gschwend

Publications and source records attributed to D A Gschwend.

6 recordsLinked to original sources

PubMed2000

Molecular modeling of G-protein coupled receptor kinase 2: docking and biochemical evaluation of inhibitors.

G-protein coupled receptor kinase 2 (GRK2) regulates the activity of many receptors. Because potent inhibitors of GRK2 are thus far limited to polyanionic compounds like heparin, we searched for new inhibitors with the aid of a molecular model of GRK2. We used the available crystal structure of cAMP dependent protein kinase (cAPK) as a template to construct a 3D homology model of GRK2. Known cAPK and GRK2 inhibitors were docked into the active sites of GRK2 and cAPK using DOCK v3.5. H8 docked into the hydrophobic pocket of the adenosine 5'-triphosphate (ATP) binding site of cAPK, consistent with its known competitive cAPK inhibition relative to ATP. Similarly, 3 of 4 known GRK2 inhibitors docked into the ATP binding pocket of GRK2 with good scores. Screening the Fine Chemicals Directory (FCD, containing the 3D structures of 13,000 compounds) for docking into the active sites of GRK2 identified H8 and the known GRK2 inhibitor trifluoperazine as candidates. Whereas H8 indeed inhibited light-dependent phosphorylation of rhodopsin by GRK2, but with low potency, 3 additional FCD compounds with promising GRK2 scores failed to inhibit GRK2. This result demonstrates limitations of the GRK2 model in predicting activity among diverse chemical structures. Docking suramin, an inhibitor of protein kinase C (not present in FCD) yielded a good fit into the ATP binding site of GRK2 over cAPK. Suramin did inhibit GRK2 with IC50 32 microM (pA26.39 for competitive inhibition of ATP). Suramin congeners with fewer sulfonic acid residues (NF062, NF503 [IC50 14 microM]) or representing half of the suramin molecule (NF520) also inhibited GRK2 as predicted by docking. In conclusion, suramin and analogues are lead compounds in the development of more potent and selective inhibitors of GRK2.

Animals↗

PubMed1997

Specificity in structure-based drug design: identification of a novel, selective inhibitor of Pneumocystis carinii dihydrofolate reductase.

Specificity is an important aspect of structure-based drug design. Distinguishing between related targets in different organisms is often the key to therapeutic success. Pneumocystis carinii is a fungal opportunist which causes a crippling pneumonia in immunocompromised individuals. We report the identification of novel inhibitors of P. carinii dihydrofolate reductase (DHFR) that are selective versus inhibition of human DHFR using computational molecular docking techniques. The Fine Chemicals Directory, a database of commercially available compounds, was screened with the DOCK program suite to produce a list of potential P. carinii DHFR inhibitors. We then used a postdocking refinement directed at discerning subtle structural and chemical features that might reflect species specificity. Of 40 compounds predicted to exhibit anti-Pneumocystis DHFR activity, each of novel chemical framework, 13 (33%) show IC50 values better than 150 microM in an enzyme assay. These inhibitors were further assayed against human DHFR: 10 of the 13 (77%) bind preferentially to the fungal enzyme. The most potent compound identified is a 7 microM inhibitor of P. carinii DHFR with 25-fold selectivity. The ability of molecular docking methods to locate selective inhibitors reinforces our view of structure-based drug discovery as a valuable strategy, not only for identifying lead compounds, but also for addressing receptor specificity.

Antifungal Agents↗

PubMed1996

Orientational sampling and rigid-body minimization in molecular docking revisited: on-the-fly optimization and degeneracy removal.

Strategies for computational association of molecular components entail a compromise between configurational exploration and accurate evaluation. Following the work of Meng et al. [Proteins, 17 (1993) 266], we investigate issues related to sampling and optimization in molecular docking within the context of the DOCK program. An extensive analysis of diverse sampling conditions for six receptor-ligand complexes has enabled us to evaluate the tractability and utility of on-the-fly force-field score minimization, as well as the method for configurational exploration. We find that the sampling scheme in DOCK is extremely robust in its ability to produce configurations near to those experimentally observed. Furthermore, despite the heavy resource demands of refinement, the incorporation of a rigid-body, grid-based simplex minimizer directly into the docking process results in a docking strategy that is more efficient at retrieving experimentally observed configurations than docking in the absence of optimization. We investigate the capacity for further performance enhancement by implementing a degeneracy checking protocol aimed at circumventing redundant optimizations of geometrically similar orientations. Finally, we present methods that assist in the selection of sampling levels appropriate to desired result quality and available computational resources.

Algorithms↗

PubMed1995

New molecular shape descriptors: application in database screening.

Geometric descriptors are becoming popular tools for encoding molecular shape, for use in database screening and clustering calculations. They provide condensed representations of complex objects and, as a consequence, can usually be compared quite rapidly. Here we present a number of new descriptors and methods for the quantification of molecular shape similarity. The techniques are tested using two different biological systems, with particular emphasis on their potential utility as methods for prescreening shape-based database searches. Results are compared with data sets produced using the DOCK program. We find that such similarity evaluations are useful for finding molecules with complementary shape, and that they contain an enriched number of potential DOCK hits when compared to the original databases. Significant limitations in the utility of such DOCK prescreens are discussed, and potential solutions are considered.

Binding Sites↗

PubMed1993

Orientational sampling and rigid-body minimization in molecular docking.

The biological activities of proteins depend on specific molecular recognition and binding. Computational methods for predicting binding modes can facilitate the discovery and design of ligands and yield information on the factors governing complementarity. The DOCK suite of programs has been applied to several systems; here, the degree of orientational sampling required to reproduce and identify known binding modes, with and without rigid-body energy minimization, is investigated for four complexes. There is a tradeoff between sampling and minimization. The known binding modes can be identified with intensive sampling alone (10,000 to 20,000 orientations generated per system) or with moderate sampling combined with minimization. Optimization improves energies significantly, particularly when steric clashes are present, and brings many orientations closer to the experimentally observed position. Whether or not minimization is performed, however, sampling must be sufficient to find at least one structure in the vicinity of the presumed true binding mode. Hybrid approaches combining docking and minimization are promising and will become more viable with the use of faster algorithms and the judicious selection of fewer orientations for minimization.

Carboxypeptidases↗

PubMedDate not supplied

Molecular docking towards drug discovery.

Fueled by advances in molecular structure determination, tools for structure-based drug design are proliferating rapidly. Lead discovery through searching of ligand databases with molecular docking techniques represents an attractive alternative to high-throughout random screening. The size of commercial databases imposes severe computational constraints on molecular docking, compromising the level of calculational detail permitted for each putative ligand. We describe alternative philosophies for docking which effectively address this challenge. With respect to the dynamic aspects of molecular recognition, these strategies lie along a spectrum of models bounded by the Lock-and-Key and Induced-Fit theories for ligand binding. We explore the potential of a rigid model in exploiting species specificity and of a tolerant model in predicting absolute ligand binding affinity. Current molecular docking methods are limited primarily by their ability to rank docked complexes; we therefore place particular emphasis on this aspect of the problem throughout our validation of docking strategies.

Animals↗