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Biomedical subjects

W Graham Richards

Publications and source records attributed to W Graham Richards.

10 recordsLinked to original sources
PubMed2002

Ab initio QM/MM dynamics simulation of the tetrahedral intermediate of serine proteases: insights into the active site hydrogen-bonding network.

Ab initio QM/MM dynamics simulation is employed to examine the stability of the tetrahedral intermediate during the deacylation step in elastase-catalyzed hydrolysis of a simple peptide. An extended quantum region includes the catalytic triad, the tetrahedral structure, and the oxyanion hole. The calculations indicate that the tetrahedral intermediate of serine proteases is a stable species on the picosecond time scale. On the basis of geometrical and dynamical properties, and in agreement with many experimental and theoretical studies, it is suggested that the crucial hydrogen bonds involved in stabilizing this intermediate are between Asp-102 and His-57 and between the charged oxygen of the intermediate and the backbone N-H group of Gly-193 in the oxyanion hole. The mobility of the imidazolium ring between O(w) and O(gamma), two of the oxygens of the tetrahedral structure, shows how the intermediate could proceed toward the product state without a "ring-flip mechanism", proposed earlier on the basis of NMR data. In addition to the proposed C(epsilon)(1)-H.O hydrogen bond between the imidazolium ring and the backbone carbonyl of Ser-214, we observe an alternative C(epsilon)(1)-H.O hydrogen bond with the backbone carbonyl of Thr-213, that can stabilize the intermediate during the imidazolium movement. Proton hopping occurs between Asp-102 and His-57 during the simulation. The proton is, however, largely localized on the nitrogen, and hence it does not participate in a low-barrier hydrogen bond. The study also suggests factors that may be implicated in product release: breaking the hydrogen bond of the charged oxygen with the backbone of Ser-195 in the oxyanion hole and a loop opening between residues 216-225 that enables the breaking of a hydrogen bond in subsite S(3).

Animals↗
PubMed2002

Docking of flexible molecules using multiscale ligand representations.

Structural genomics will yield an immense number of protein three-dimensional structures in the near future. Automated theoretical methodologies are needed to exploit this information and are likely to play a pivotal role in drug discovery. Here, we present a fully automated, efficient docking methodology that does not require any a priori knowledge about the location of the binding site or function of the protein. The method relies on a multiscale concept where we deal with a hierarchy of models generated for the potential ligand. The models are created using the k-means clustering algorithm. The method was tested on seven protein-ligand complexes. In the largest complex, human immunodeficiency virus reverse transcriptase/nevirapin, the root mean square deviation value when comparing our results to the crystal structure was 0.29 A. We demonstrate on an additional 25 protein-ligand complexes that the methodology may be applicable to high throughput docking. This work reveals three striking results. First, a ligand can be docked using a very small number of feature points. Second, when using a multiscale concept, the number of conformers that require to be generated can be significantly reduced. Third, fully flexible ligands can be treated as a small set of rigid k-means clusters.

Algorithms↗
PubMed2002

The potential of Internet computing for drug discovery.

Large-scale, high precision drug discovery calculations, such as predicting protein folding or small-molecule protein inhibitors, have frustrated computational chemists because the supercomputers currently available are insufficiently powerful. The increasing power of PCs offers an alternative approach by harnessing 'idle time' from corporate and home computers that are connected to the Internet or an intranet. However, although the approach has the potential of offering hundreds or thousands of years of computer time per elapsed day, the architecture constraints require computational chemists to choose their methods and applications with care. Some algorithms, such as those for molecular simulations, are generally not appropriate, whereas virtual screening of molecules for protein inhibition works well.

Algorithms↗
PubMed2002

Molecular dynamics simulations of the acyl-enzyme and the tetrahedral intermediate in the deacylation step of serine proteases.

Despite the availability of many experimental data and some modeling studies, questions remain as to the precise mechanism of the serine proteases. Here we report molecular dynamics simulations on the acyl-enzyme complex and the tetrahedral intermediate during the deacylation step in elastase catalyzed hydrolysis of a simple peptide. The models are based on recent crystallographic data for an acyl-enzyme intermediate at pH 5 and a time-resolved study on the deacylation step. Simulations were carried out on the acyl enzyme complex with His-57 in protonated (as for the pH 5 crystallographic work) and deprotonated forms. In both cases, a water molecule that could provide the nucleophilic hydroxide ion to attack the ester carbonyl was located between the imidazole ring of His-57 and the carbonyl carbon, close to the hydrolytic position assigned in the crystal structure. In the "neutral pH" simulations of the acyl-enzyme complex, the hydrolytic water oxygen was hydrogen bonded to the imidazole ring and the side chain of Arg-61. Alternative stable locations for water in the active site were also observed. Movement of the His-57 side-chain from that observed in the crystal structure allowed more solvent waters to enter the active site, suggesting that an alternative hydrolytic process directly involving two water molecules may be possible. At the acyl-enzyme stage, the ester carbonyl was found to flip easily in and out of the oxyanion hole. In contrast, simulations on the tetrahedral intermediate showed no significant movement of His-57 and the ester carbonyl was constantly located in the oxyanion hole. A comparison between the simulated tetrahedral intermediate and a time-resolved crystallographic structure assigned as predominantly reflecting the tetrahedral intermediate suggests that the experimental structure may not precisely represent an optimal arrangement for catalysis in solution. Movement of loop residues 216-223 and P3 residue, seen both in the tetrahedral simulation and the experimental analysis, could be related to product release. Furthermore, an analysis of the geometric data obtained from the simulations and the pH 5 crystal structure of the acyl-enzyme suggests that since His-57 is protonated, in some aspects, this crystal structure resembles the tetrahedral intermediate.

Acylation↗
PubMed2002

Novel CD8+ T cell antagonists based on beta 2-microglobulin.

The CD8 coreceptor of cytotoxic T lymphocytes binds to a conserved region of major histocompatibility complex class I molecules during recognition of peptide-major histocompatibility complex (MHC) class I antigens on the surface of target cells. This event is central to the activation of cytotoxic T lymphocyte (CTL) effector functions. The contribution of the MHC complex class I light chain, beta(2)-microglobulin, to CD8alphaalpha binding is relatively small and is mediated mainly through the lysine residue at position 58. Despite this, using molecular modeling, we predict that its mutation should have a dramatic effect on CD8alphaalpha binding. The predictions are confirmed using surface plasmon resonance binding studies and human CTL activation assays. Surprisingly, the charge-reversing mutation, Lys(58) --> Glu, enhances beta(2)m-MHC class I heavy chain interactions. This mutation also significantly reduces CD8alphaalpha binding and is a potent antagonist of CTL activation. These results suggest a novel approach to CTL-specific therapeutic immunosuppression.

Amino Acid Sequence↗
PubMed2002

Identification of ligand binding sites on proteins using a multi-scale approach.

Identification of a ligand binding site on a protein is pivotal to drug discovery. To date, no reliable and computationally feasible general approach to this problem has been published. Here we present an automated efficient method for determining binding sites on proteins for potential ligands without any a priori knowledge. Our method is based upon the multiscale concept where we deal with a hierarchy of models generated using a k-means clustering algorithm for the potential ligand. This is done in a simple approach whereby a potential ligand is represented by a growing number of feature points. At each increasing level of detail, a pruning of potential binding site is performed. A nonbonding energy function is used to score the interactions between molecules at each step. The technique was successfully employed to seven protein-ligand complexes. In the current paper we show that the algorithm considerably reduces the computational effort required to solve this problem. This approach offers real opportunities for exploiting the large number of structures that will evolve from structural genomics.

Algorithms↗
PubMed2002

Pattern recognition and massively distributed computing.

A feature of Peter Kollman's research was his exploitation of the latest computational techniques to devise novel applications of the free energy perturbation method. He would certainly have seized upon the opportunities offered by massively distributed computing. Here we describe the use of over a million personal computers to perform virtual screening of 3.5 billion druglike molecules against protein targets by pharmacophore pattern matching, together with other applications of pattern recognition such as docking ligands without any a priori knowledge about the binding site location.

Algorithms↗
PubMedDate not supplied

Calculation of protein domain structural similarity using two-dimensional representations.

By reducing protein structures to two-dimensional representations, it is possible to speed up the alignment of the structures and hence calculate similarity indices faster that using three-dimensional representations. Using amino acid based representations gives much better discrimination between proteins and faster calculations. Taking into account the relative similarity of the amino acids involved allowed improved accuracy at very little time cost.

Amino Acids↗