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Biomedical subjects

Meir Glick

Publications and source records attributed to Meir Glick.

8 recordsLinked to original sources
PubMed2003

The CD8 T cell coreceptor exhibits disproportionate biological activity at extremely low binding affinities.

T lymphocytes recognize peptides presented in the context of major histocompatibility complex (MHC) molecules on the surface of antigen presenting cells. Recognition specificity is determined by the alphabeta T cell receptor (TCR). The T lymphocyte surface glycoproteins CD8 and CD4 enhance T cell antigen recognition by binding to MHC class I and class II molecules, respectively. Biophysical measurements have determined that equilibrium binding of the TCR with natural agonist peptide-MHC (pMHC) complexes occurs with KD values of 1-50 microm. The pMHCI/CD8 and pMHCII/CD4 interactions are significantly weaker than this (KD >100 microm), and the relative roles of TCR/pMHC and pMHC/coreceptor affinity in T cell activation remain controversial. Here, we engineer mutations in the MHCI heavy chain and beta2-microglobulin that further reduce or abolish the pMHCI/CD8 interaction to probe the significance of pMHC/coreceptor affinity in T cell activation. We demonstrate that the pMHCI/CD8 coreceptor interaction retains the vast majority of its biological activity at affinities that are reduced by over 15-fold (KD > 2 mm). In contrast to previous reports, we observe that the weak interaction between HLA A68 and CD8, which falls within this spectrum of reduced affinities, retains substantial functional activity. These findings are discussed in the context of current concepts of coreceptor dependence and the mechanism by which TCR coreceptors facilitate T cell activation.

Antigen Presentation↗
PubMed2003

Refined structure of bovine carboxypeptidase A at 1.25 A resolution.

The crystal structure of the bovine zinc metalloproteinase carboxypeptidase A (CPA) has been refined to 1.25 A resolution based on room-temperature X-ray synchrotron data. The significantly improved structure of CPA at this resolution (anisotropic temperature factors, R factor = 10.4%, R(free) = 14.5%) allowed the modelling of conformational disorders of side chains, improved the description of the protein solvent network (375 water molecules) and provided a more accurate picture of the interactions between the active-site zinc and its ligands. The calculation of standard uncertainties in individual atom positions of the refined model of CPA allowed the deduction of the protonation state of some key residues in the active site and confirmed that Glu72 and Glu270 are negatively charged in the resting state of the enzyme at pH 7.5. These results were further validated by theoretical calculations that showed significant reduction of the pK(a) of these side chains relative to solution values. The distance between the zinc-bound solvent molecule and the metal ion is strongly suggestive of a neutral water molecule and not a hydroxide ion in the resting state of the enzyme. These findings could support both the general acid/general base mechanism, as well as the anhydride mechanism suggested for CPA.

Amino Acids↗
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

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

A stochastic algorithm for global optimization and for best populations: a test case of side chains in proteins.

The problem of global optimization is pivotal in a variety of scientific fields. Here, we present a robust stochastic search method that is able to find the global minimum for a given cost function, as well as, in most cases, any number of best solutions for very large combinatorial "explosive" systems. The algorithm iteratively eliminates variable values that contribute consistently to the highest end of a cost function's spectrum of values for the full system. Values that have not been eliminated are retained for a full, exhaustive search, allowing the creation of an ordered population of best solutions, which includes the global minimum. We demonstrate the ability of the algorithm to explore the conformational space of side chains in eight proteins, with 54 to 263 residues, to reproduce a population of their low energy conformations. The 1,000 lowest energy solutions are identical in the stochastic (with two different seed numbers) and full, exhaustive searches for six of eight proteins. The others retain the lowest 141 and 213 (of 1,000) conformations, depending on the seed number, and the maximal difference between stochastic and exhaustive is only about 0.15 Kcal/mol. The energy gap between the lowest and highest of the 1,000 low-energy conformers in eight proteins is between 0.55 and 3.64 Kcal/mol. This algorithm offers real opportunities for solving problems of high complexity in structural biology and in other fields of science and technology.

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↗