Discrimination between Olfactory Receptor Agonists and Non‐agonists

A joint approach combining free‐energy calculations and calcium‐imaging assays on the broadly tuned human 1G1 olfactory receptor is reported. The free energy of binding of ten odorants was computed by means of molecular‐dynamics simulations. This state function allows separating the experimentally determined eight agonists from the two non‐agonists. This study constitutes a proof‐of‐principle for the computational deorphanization of olfactory receptors.     

Fast and high precision algorithms for optimization in large-scale genomic problems

There are several very difficult problems related to genetic or genomic analysis that belong to the field of discrete optimization in a set of all possible orders. With n elements (points, markers, clones, sequences, etc.), the number of all possible orders is n!/2 and only one of these is considered to be the true order. A classical formulation of a similar mathematical problem is the well-known traveling salesperson problem model (TSP). Genetic analogues of this problem include: ordering in multilocus genetic mapping, evolutionary tree reconstruction, building physical maps (contig assembling for overlapping clones and radiation hybrid mapping), and others. A novel, fast and reliable hybrid algorithm based on evolution strategy and guided local search discrete optimization was developed for TSP formulation of the multilocus mapping problems. High performance and high precision of the employed algorithm named guided evolution strategy (GES) allows verification of the obtained multilocus orders based on different computing-intensive approaches (e.g., bootstrap or jackknife) for detection and removing unreliable marker loci, hence, stabilizing the resulting paths. The efficiency of the proposed algorithm is demonstrated on standard TSP problems and on simulated data of multilocus genetic maps up to 1000 points per linkage group.     

A group of independent stochastic automata as a search optimization system

Results are presented of mathematical experiments having as their purpose the further clarification of search and optimization possibilities of a group of independent automata.Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 15, No. 3, pp. 365–375, March, 1972.     

Multilocus consensus genetic maps (MCGM): formulation, algorithms, and results

In process of creating genetic maps different labs/research groups obtain overlapping parts of the map. Merging these parts into one integrative map is based on looking for maximum shared marker orders among the maps. Really, not all shared markers of such maps have consensus order that obstructs building of the integrative maps. In this paper we propose a new approach to build verified multilocus consensus genetic maps in which shared markers always are integrated in stable consensus order. The approach is based on combined analysis of initial mapping data rather than manipulating with previously constructed maps. We show that more effective and reliable solutions may be obtained based on "synchronized ordering" facilitated by cycles of "re-sampling-->ordering-->removing unstable markers". The proposed formulation of consensus genetic mapping can be considered as a version of traveling salesperson problem (TSP) that we refer to as synchronized-TSP. From the viewpoint of optimization, synchronized-TSP belongs to discrete constrained optimization problems. Earlier we developed new powerful and fast guided evolution strategy algorithms for some types of discrete constrained optimization. These algorithms were used here as a basis for solving more challenging problems of consensual marker ordering.     

Characterization of N-glycans of recombinant human thyrotropin using mass spectrometry

Thyroid-stimulating hormone is a vital component of the regulatory mechanism that maintains the structure and function of the thyroid gland and governs thyroid hormone release. In this paper we report the first detailed structural characterization of the N-linked oligosaccharides of recombinant human thyroid-stimulating hormone (rhTSH). Using a strategy combining mass spectrometric analysis and sequential exoglycosidase digestion, we have defined the structures of the N-glycans released from recombinant human thyrotropin by peptide N-glycosidase F. All glycans are complex-type glycans and are mainly of the bi- and triantennary type with variable degrees of fucosylation and sialylation. The major non-reducing epitope in the complex-type glycans is: NeuAcalpha2-3Galbeta1-4GlcNAc (sialylated LacNAc). The carbohydrate microheterogeneity at the three glycosylation sites was studied using reversed-phase high-performance liquid chromatography (RP-HPLC), concanavalin A affinity chromatography and mass spectrometric techniques, including both matrix-assisted laser desorption/ionization (MALDI) and electrospray. rhTSH was reduced, carboxymethylated and then digested with trypsin. The mixture of peptides and glycopeptides was subjected to RP-HPLC and the structures of the glycopeptides were determined by MALDI in conjunction with on-target exoglycosidase digestions. After PNGase F digestion, the peptide moiety of the glycopeptide was determined by the presence of the b- and y-series ions derived from its amino acid sequence in the quadrupole time-of-flight tandem mass (QTOF-MS/MS) spectrum. Glycosylation sites Asn-alpha52 and Asn-alpha78 contain mainly bi- and triantennary complex-type glycans. Only glycosylation site Asn-alpha52 bears fucosylated N-glycans. Minor tetraantennary complex structures were also observed on both glycosylation sites. Profiling of the carbohydrate moieties of Asn-beta23 indicates a large heterogeneity. Bi-, tri-, and tetraantennary N-glycans were present at this site. These data demonstrate site-specificity of glycosylation in the alpha subunit but not in the beta subunit of rhTSH with Asn-alpha52 bearing essentially di- and triantennary glycans with or without core fucosylation and bi- and triantennary glycans with no core fucosylation being attached to Asn-alpha78.