Biomedical subjects

Sándor Szalma

Publications and source records attributed to Sándor Szalma.

6 recordsLinked to original sources

PubMed2005

Three-dimensional models of histamine H3 receptor antagonist complexes and their pharmacophore.

Molecular modeling was used to analyze the binding mode and activities of histamine H3 receptor antagonists. A model of the H3 receptor was constructed through homology modeling methods based on the crystal structure of bovine rhodopsin. Known H3 antagonists were interactively docked into the putative antagonist binding pocket and the resultant model was subjected to molecular mechanics energy minimization and molecular dynamics simulations which included a continuum model of the lipid bilayer and intra- and extracellular aqueous environments surrounding the transmembrane helices. The transmembrane helices stayed well embedded in the dielectric slab representing the lipid bilayer and the intra- and extracellular loops remain situated in the aqueous solvent region of the model during molecular dynamics simulations of up to 200 ps in duration. A pharmacophore model was calculated by mapping the features common to three active compounds three-dimensionally in space. The 3D pharmacophore model complements our atomistic receptor/ligand modeling. The H3 antagonist pharmacophore consists of two protonation sites (i.e. basic centers) connected by a central aromatic ring or hydrophobic region. These two basic sites can simultaneously interact with Asp 114 (3.32) in helix III and a Glu 206 (5.46) in helix V which are believed to be the key residues that histamine interacts with to stabilize the receptor in the active state. The interaction with Glu 206 is consistent with the enhanced activity resulting from the additional basic site. In addition to these two salt bridging interactions, the central region of these antagonists contains a lipophilic group, usually an aromatic ring, that is found to interact with several nearby hydrophobic side chains. The picture of antagonist binding provided by these models is consistent with earlier pharmacophore models for H3 antagonists with some exceptions.

Amino Acid Sequence↗

PubMed2004

A hidden Markov model with molecular mechanics energy-scoring function for transmembrane helix prediction.

A range of methods has been developed to predict transmembrane helices and their topologies. Although most of these algorithms give good predictions, no single method consistently outperforms the others. However, combining different algorithms is one approach that can potentially improve the accuracy of the prediction. We developed a new method that initially uses a hidden Markov model to predict alternative models for membrane spanning helices in proteins. The algorithm subsequently identifies the best among models by ranking them using a novel scoring function based on the folding energy of transmembrane helical fragments. This folding of helical fragments and the incorporation into membrane is modeled using CHARMm, extended with the Generalized Born surface area solvent model (GBSA/IM) with implicit membrane. The combined method reported here, TMHGB significantly increases the accuracy of the original hidden Markov model-based algorithm.

Algorithms↗

PubMed2004

Automated evaluation of chemical shift perturbation spectra: New approaches to quantitative analysis of receptor-ligand interaction NMR spectra.

This paper presents new methods designed for quantitative analysis of chemical shift perturbation NMR spectra. The methods automatically trace the displacements of cross peaks between a perturbed test spectrum and the reference spectrum (or among a series of titration spectra), and measure the changes of chemical shifts, heights, and widths of the altered peaks. The methods are primary aimed at the (1)H-(15)N HSQC spectra of relatively small proteins (<15 kDa) assuming fast exchange between free and ligand-bound states on the chemical shift time scale, or for comparing spectra of free and fully bound states in the slow exchange situation. Using the (1)H-(15)N HSQC spectra from a titration experiment of the 74-residue Pex13p SH3 domain with a Pex14p peptide ligand (14 residues, K (d)= approximately 40 microM), we demonstrate the scope and limits of our automatic peak tracing (APET) algorithm for efficient scoring of high-throughput SAR by NMR type HSQC spectra, and progressive peak tracing (PROPET) algorithm for detailed analysis of ligand titration spectra. Simulated spectra with low signal-to-noise ratios (S/N ranged from 20 to 1) were used to demonstrate the reliability and reproducibility of the results when dealing with poor quality spectra. These algorithms have been implemented in a new software module, FELIX-Autoscreen, for streamlined processing, analysis and visualization of SAR by NMR and other high-throughput receptor/ligand interaction experiments.

Algorithms↗

PubMed2003

Assessment of putative protein targets derived from the SARS genome.

The ability to rapidly and reliably develop hypotheses on the function of newly discovered protein sequences requires systematic and comprehensive analysis. Such an analysis, embodied within the DS GeneAtlas pipeline, has been used to critically evaluate the severe acute respiratory syndrome (SARS) genome with the goal of identifying new potential targets for viral therapeutic intervention. This paper discusses several new functional hypotheses on the roles played by the constituent gene products of SARS, and will serve as an example of how such assignments can be developed or extended on other systems of interest.

Amino Acid Sequence↗

PubMed2003

Common Structural Cliques: a tool for protein structure and function analysis.

Proposed is a method for locating functionally relevant atoms in protein structures and a representation of spatial arrangements of these atoms allowing for a flexible description of active sites in proteins. The search method is based on comparison of local structure features of proteins that share a common biochemical function. The method does not depend on overall similarity of structures and sequences of compared proteins or on previous knowledge about functionally relevant residues. The compared protein structures are condensed to a graph representation, with atoms as nodes and distances as edge labels. Protein graphs are then compared to extract all possible Common Structural Cliques. These cliques are merged to create Structural Templates: graphs that describe structural analogies between compared proteins. Structures of serine endopeptidases were compared in pairs using the presented algorithm with different geometrical parameters. Additionally, a Structural Template was extracted from the structures of aminotransferases, two different proteins that catalyze the same type of chemical reaction. The results presented show that the method works efficiently even in the case of large protein systems and allows for extraction of common structural features from proteins catalyzing a particular chemical reaction, but that evolved from different ancestors by convergent evolution.

Algorithms↗

PubMed2002

Functional annotation of proteomic sequences based on consensus of sequence and structural analysis.

To maximise the assignment of function of the proteins encoded by a genome and to aid the search for novel drug targets, there is an emerging need for sensitive methods of predicting protein function on a genome-wide basis. GeneAtlas is an automated, high-throughput pipeline for the prediction of protein structure and function using sequence similarity detection, homology modelling and fold recognition methods. GeneAtlas is described in detail here. To test GeneAtlas, a 'virtual' genome was used, a subset of PDB structures from the SCOP database, in which the functional relationships are known. GeneAtlas detects additional relationships by building 3D models in comparison with the sequence searching method PSI-BLAST. Functionally related proteins with sequence identity below the twilight zone can be recognised correctly.

Consensus Sequence↗