Beyond Modeling: All-Atom Olfactory Receptor Model Simulations

Olfactory receptors (ORs) are a type of GTP-binding protein-coupled receptor (GPCR). These receptors are responsible for mediating the sense of smell through their interaction with odor ligands. OR-odorant interactions marks the first step in the process that leads to olfaction. Computational studies on model OR structures can generate focused and novel hypotheses for further bench investigation by providing a view of these interactions at the molecular level beyond inferences that are drawn merely from static docking. Here we have shown the specific advantages of simulating the dynamic environment associated with OR-odorant interactions. We present a rigorous protocol which ranges from the creation of a computationally derived model of an olfactory receptor to simulating the interactions between an OR and an odorant molecule. Given the ubiquitous occurrence of GPCRs in the membranes of cells, we anticipate that our OR-developed methodology will serve as a model for the computational structural biology of all GPCRs

An Olfactory Receptor Pseudogene whose Function emerged in Humans

Human olfactory receptor, hOR17-210, is identified as a pseudogene in the human genome. Experimental data has shown however, that the gene product of cloned hOR17-210 cDNA was able to bind an odorant-binding protein and is narrowly tuned for excitation by cyclic ketones. Supported by experimental results, we used the bioinformatics methods of sequence analysis, computational protein modeling and docking, to show that functionality in this receptor is retained due to sequence-structure features not previously observed in mammalian ORs. This receptor does not possess the first two transmembrane helical domains (of seven typically seen in GPCRs). It however, possesses an additional TM that has not been observed in other human olfactory receptors. By incorporating these novel structural features, we created two putative models for this receptor. We also docked odor ligands that were experimentally shown to bind hOR17-210 model. We show how and why structural modifications of OR17-210 do not hinder this receptor's functionality. Our studies reveal that novel gene rearrangement that result in sequence and structural diversity in has a bearing on OR and GPCR function and evolution

A Framework for Exploring Functional Variability in Olfactory Receptor Genes

Background: Olfactory receptors (ORs) are the largest gene family in mammalian genomes. Since nearly all OR genes are orphan receptors, inference of functional similarity or differences between odorant receptors typically relies on sequence comparisons. Based on the alignment of entire coding region sequence, OR genes are classified into families and subfamilies, a classification that is believed to be a proxy for OR gene functional variability. However, the assumption that overall protein sequence diversity is a good proxy for functional properties is untested.Methodology: Here, we propose an alternative sequence-based approach to infer the similarities and differences in OR binding capacity. Our approach is based on similarities and differences in the predicted binding pockets of OR genes, rather than on the entire OR coding region.Conclusions: Interestingly, our approach yields markedly different results compared to the analysis based on the entire OR coding-regions. While neither approach can be tested at this time, the discrepancy between the two calls into question the assumption that the current classification reliably reflects OR gene functional variability.</p

Integrated olfactory receptor and microarray gene expression databases

<p>Abstract</p> <p>Background</p> <p>Gene expression patterns of olfactory receptors (ORs) are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD) to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB), which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction.</p> <p>Description</p> <p>ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data.</p> <p>Conclusion</p> <p>ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.</p

A Framework for Exploring Functional Variability in Olfactory Receptor Genes

BACKGROUND: Olfactory receptors (ORs) are the largest gene family in mammalian genomes. Since nearly all OR genes are orphan receptors, inference of functional similarity or differences between odorant receptors typically relies on sequence comparisons. Based on the alignment of entire coding region sequence, OR genes are classified into families and subfamilies, a classification that is believed to be a proxy for OR gene functional variability. However, the assumption that overall protein sequence diversity is a good proxy for functional properties is untested. METHODOLOGY: Here, we propose an alternative sequence-based approach to infer the similarities and differences in OR binding capacity. Our approach is based on similarities and differences in the predicted binding pockets of OR genes, rather than on the entire OR coding region. CONCLUSIONS: Interestingly, our approach yields markedly different results compared to the analysis based on the entire OR coding-regions. While neither approach can be tested at this time, the discrepancy between the two calls into question the assumption that the current classification reliably reflects OR gene functional variability

Substituted 2‑(Dimethylamino)biphenyl-2′-carboxaldehydes as Substrates for Studying n→π* Interactions and as a Promising Framework for Tracing the Bürgi–Dunitz Trajectory

The Bürgi–Dunitz trajectory traces points along the pathway of bond formation between a nucleophile and electrophile. Previous X-ray crystallographic studies of some molecules containing a nucleophilic nitrogen atom and electrophilic carbonyl group provided some initial evidence for various degrees of bond formation via initial n→π* interactions. Observation of a complete set of points along the trajectory, however, has not yet been attained. In this paper, we present a DFT computational study investigating substituted 2-(dimethylamino)­biphenyl-2′-carboxaldehydes as substrates for further examination of n→π* interactions and as a potential framework for more complete tracing of the Bürgi–Dunitz trajectory. These compounds are particulary suitable for study because of the rotational freedom granted by the C–C bond connecting the two aromatic rings allowing the molecule to choose the degree of interaction between the two complementary groups. The extent of interaction is measured by interatomic distance, NBO second-order perturbative analysis energies, volume of transferred electron density as provided by ETS-NOCV analysis, and differences in energies between models that allow for n→π* interactions and those that do not. A series of substituted biphenyls are ultimately identified as future synthetic targets that have maximum potential for providing improved tracing of the Bürgi–Dunitz trajectory