Key residues controlling binding of diverse ligands to human cytochrome P450 2A enzymes.

Although the human lung cytochrome P450 2A13 (CYP2A13) and its liver counterpart cytochrome P450 2A6 (CYP2A6) are 94% identical in amino acid sequence, they metabolize a number of substrates with substantially different efficiencies. To determine differences in binding for a diverse set of cytochrome P450 2A ligands, we have measured the spectral binding affinities (K(D)) for nicotine, phenethyl isothiocyanate (PEITC), coumarin, 2'-methoxyacetophenone (MAP), and 8-methoxypsoralen. The differences in the K(D) values for CYP2A6 versus CYP2A13 ranged from 74-fold for 2'-methoxyacetophenone to 1.1-fold for coumarin, with CYP2A13 demonstrating the higher affinity. To identify active site amino acids responsible for the differences in binding of MAP, PEITC, and coumarin, 10 CYP2A13 mutant proteins were generated in which individual amino acids from the CYP2A6 active site were substituted into CYP2A13 at the corresponding position. Titrations revealed that substitutions at positions 208, 300, and 301 individually had the largest effects on ligand binding. The collective relevance of these amino acids to differential ligand selectivity was verified by evaluating binding to CYP2A6 mutant enzymes that incorporate several of the CYP2A13 amino acids at these positions. Inclusion of four CYP2A13 amino acids resulted in a CYP2A6 mutant protein (I208S/I300F/G301A/S369G) with binding affinities for MAP and PEITC much more similar to those observed for CYP2A13 than to those for CYP2A6 without altering coumarin binding. The structure-based quantitative structure-activity relationship analysis using COMBINE successfully modeled the observed mutant-ligand trends and emphasized steric roles for active site residues including four substituted amino acids and an adjacent conserved Leu(370).

CHEMICAL COMPOUND CLASSIFICATION WITH AUTOMATICALLY MINED STRUCTURE PATTERNS.

In this paper we propose new methods of chemical structure classification based on the integration of graph database mining from data mining and graph kernel functions from machine learning. In our method, we first identify a set of general graph patterns in chemical structure data. These patterns are then used to augment a graph kernel function that calculates the pairwise similarity between molecules. The obtained similarity matrix is used as input to classify chemical compounds via a kernel machines such as the support vector machine (SVM). Our results indicate that the use of a pattern-based approach to graph similarity yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art approaches. In addition, the identification of highly discriminative patterns for activity classification provides evidence that our methods can make generalizations about a compound's function given its chemical structure. While we evaluated our methods on molecular structures, these methods are designed to operate on general graph data and hence could easily be applied to other domains in bioinformatics.

Novel splice isoforms for NLGN3 and NLGN4 with possible implications in autism.

OBJECTIVE: To screen cDNA for NLGN3 and NLGN4 from lymphoblastoid cells from autistic subjects. METHODS AND RESULTS: 10 young autistic females and 30 non-autistic subjects were studied for alterations in two X linked genes, NLGN3 and NLGN4. A novel NLGN4 isoform lacking exon 4, which occurred de novo on the paternal allele, was identified in one of the autistic females. Monoallelic expression of NLGN4 was seen in this subject and in 11 of 14 informative autistic and non-autistic females using a single nucleotide polymorphism found at 3' UTR. Additionally, the NLGN3 transcript was present in two isoforms (with and without exon 7) in nine of 10 autistic females and in 30 non-autistic subjects, including parents of the autistic female having only the complete transcript with exon 7, and from the whole brain of a control. The novel truncated NLGN3 product may have a regulatory role, as reported in other proteins (for example, vasopressin receptor) by attenuating the function of the full length isoform, resulting in a reduction of the mature protein. Three dimensional protein structures were characterised using comparative modelling, and significant changes were suggested in the protein cores for these two neuroligin isoforms. CONCLUSIONS: Splice variants may lead to potentially abnormal neuroligins in the causation of autism spectrum disorders.

Orientational dynamics and dye-DNA interactions in a dye-labeled DNA aptamer.

We report the picosecond and nanosecond timescale rotational dynamics of a dye-labeled DNA oligonucleotide or "aptamer" designed to bind specifically to immunoglobulin E. Rotational dynamics in combination with fluorescence lifetime measurements provide information about dye-DNA interactions. Comparison of Texas Red (TR), fluorescein, and tetramethylrhodamine (TAMRA)-labeled aptamers reveals surprising differences with significant implications for biophysical studies employing such conjugates. Time-resolved anisotropy studies demonstrate that the TR- and TAMRA-aptamer anisotropy decays are dominated by the overall rotation of the aptamer, whereas the fluorescein-aptamer anisotropy decay displays a subnanosecond rotational correlation time much shorter than that expected for the overall rotation of the aptamer. Docking and molecular dynamics simulations suggest that the low mobility of TR is a result of binding in the groove of the DNA helix. Additionally, associated anisotropy analysis of the TAMRA-aptamer reveals both quenched and unquenched states that experience significant coupling to the DNA motion. Therefore, quenching of TAMRA by guanosine must depend on the configuration of the dye bound to the DNA. The strong coupling of TR to the rotational dynamics of the DNA aptamer, together with the absence of quenching of its fluorescence by DNA, makes it a good probe of DNA orientational dynamics. The understanding of the nature of dye-DNA interactions provides the basis for the development of bioconjugates optimized for specific biophysical measurements and is important for the sensitivity of anisotropy-based DNA-protein interaction studies employing such conjugates.