2P267 Re-docking scheme for prediction of protein-protein interactions using interaction fingerprints(22A. Bioinformatics: Structural genomics,Poster)
2P267 相互作用プロファイルを用いたRe-docking法によるタンパク質間相互作用予測(22A.生命情報科学:構造ゲノミクス,ポスター,日本生物物理学会年会第51回(2013年度))

Nobuyuki Uchikoga, Yuri Matsuzaki, Masahito Ohue, Takatsugu Hirokawa, Yutaka Akiyama
2013 Seibutsu Butsuri  
Recent progress in molecular biology and genome science leads to finding many functional RNAs which control gene expression and replication. These functions are achieved through the protein-RNA and RNA-RNA interactions. Deriving the tertiary structures of these complex is very helpful to clarify the mechanism of those functions in detail. We developed the new method based on fragment assembly algorithm to predict RNA-RNA complex structures from nucleotide sequence and secondary structure
more » ... tion. We applied our method to predict several kinds of RNA-RNA complex structures which include kissing-loops, hammerhead ribozymes and other difficult targets, and derived successful results especially in the prediction of kissing-loop targets. 2P267 相互作用プロファイルを用いた Re-docking 法によるタンパ ク質間相互作用予測 We approach to problems of protein-protein Interaction network using rigid-body docking algorithm, generating many decoys including false positives. Although this docking method is popular and useful, there are some serious cases with no near-native decoys. Then, we developed iterated method for generating more near-native decoys using Interaction FingerPrints (IFPs). We applied this method to obtaining region including native interacting residue pairs for re-docking process. We examined re-docking process using IFPs after an initial-docking process after investigating docking surfaces of proteins. As results, we could obtain a set of decoys with higher similarities than that of decoys generated in the initial docking process. 2P268 Protein binding pocket and ligand shape comparison The aim of the study is to understand molecular recognition for drug discovery and design. We analyzed binding pocket and corresponding ligand with respect to their shapes using selected data from DUD (directory of useful decoys). The respective ligand and pocket shape overlap was calculated. In addition, we addressed the effect of protein molecular dynamics on shape similarity between a protein pocket and its ligand. MD simulations were used to explore the structural change of a target protein, especially of its active site. We also assessed if a comparison of shape and size of protein pockets and ligands could be helpful in virtual screening context. It is discussed if the comparison method can filter out compounds prior to other docking methods. 2P269 膜タンパク質の顕微鏡画像と立体構造データとの照合用デー タベースの構築 Construction of database for comparing structural data with microscopic image of transmembrane protein Go Inoue, Masami Ikeda, Makiko Suwa (Grad. Sch. Sci and Eng. AGU) It is important to visualize the interaction between the transmembrane proteins (TMPs) which are difficult to determine structure by X-ray crystallography and NMR, when we understand these functions. Recent methodology "visual proteomics" is expected to annotate comprehensively the name of whole proteins in the cell by comparing 3D volume with cryoelectron tomography images. We have been studying to identify localization of TMPs, projected on membrane surface by comparing their electron microscopic images with tomographic images of 3D structure of TMPs. We have constructed a database including 734 entries of TMPs (2,021 chains), with their calculated features such as the tomographic image, the perimeter, the image area, and the circularity for each structure. 2P270 β2 アドレナリン受容体 -Gαs 間の結合要素の解析 Structural analysis of coupling element between β2 adrenergic receptor and G-protein Hidenori Sakaki, Masami Ikeda, Makiko Suwa (Grad. Sch. Sci and Eng. AGU) G protein-coupled receptors (GPCRs) transduce signals from extracellular ligands to intracellular G-proteins. The study of the GPCR-G protein interface is important to understand the functional mechanism of GPCRs. Based on the 3D structure of β2 adrenergic receptor ( βAR) with Gs type G-protein complex, we made several mutated structures ( βAR with non-Gs proteins), by comparative modeling, and optimized the side chain structures of native / mutated complex, by using AMBER99 force field. Comparing interactions energy between these modeled structures, it was suggested that the native βAR structure, binding with Gs, is most stable with interaction energy several tens or more kcal/mol less than that of other mutants.
doi:10.2142/biophys.53.s203_2 fatcat:ibrrl5k57betbpafu4hdnxcxdu