Structure and function prediction of human homologue hABH5 of _E. coli_ ALKB5 using in silico approach

Newly discovered human homologues of ALKB protein have shown the activity of DNA damaging drugs, used for cancer therapy. Little is known about the structure and function of hABH5, one of the members of this superfamily. Therefore, in the present study we intend to predict its structure and function using various bioinformatics tools. Modeling was done with modeler 9v7 to predict the 3D structure of the hABH5 protein. 3-D model of hABH5, ALKBH5.B99990005.pdb was predicted and evaluated. Validation results showed 96.8% residues in favor and an additional allowed region of the Ramachandran plot. Ligand binding residues prediction showed four ligand clusters, having 25 ligands in cluster 1. Importantly, conserved pattern of Pro158-X-Asp160-Xn-His266 in the functional domain was detected. DNA and RNA binding sites were also predicted in the model. The predicted and validated model of human homologue hABH5 resulting from this study may unveil the mechanism of DNA damage repair in humans and accelerate research on designing appropriate inhibitors, aiding in chemotherapy and cancer related diseases

Structure and function prediction of human homologue hABH5 of _E. coli_ ALKB5 using in silico approach

Newly discovered human homologues of ALKB protein have shown the activity of DNA damaging drugs, used for cancer therapy. Little is known about the structure and function of hABH5, one of the members of this superfamily. Therefore, in the present study we intend to predict its structure and function using various bioinformatics tools. Modeling was done with modeler 9v7 to predict the 3D structure of the hABH5 protein. 3-D model of hABH5, ALKBH5.B99990005.pdb was predicted and evaluated. Validation results showed 96.8% residues in favor and an additional allowed region of the Ramachandran plot. Ligand binding residues prediction showed four ligand clusters, having 25 ligands in cluster 1. Importantly, conserved pattern of Pro158-X-Asp160-Xn-His266 in the functional domain was detected. DNA and RNA binding sites were also predicted in the model. The predicted and validated model of human homologue hABH5 resulting from this study may unveil the mechanism of DNA damage repair in humans and accelerate research on designing appropriate inhibitors, aiding in chemotherapy and cancer related diseases

Molecular modelling and Function Prediction of hABH7, human homologue of _E. coli_ ALKB7

Human homologues of ALKB protein have shown the prime role in DNA damaging drugs, used for cancer therapy. Little is known about structure and function of hABH7, one of the members of this superfamily. Therefore, in the present study we intend to predict its structure and function using various bioinformatics tools. Modeling was done with modeller 9v7 to predict the 3D structure of the hABH7 protein. The tertiary structure model of hABH7, ALKBH7.B99990002.pdb was predicted and evaluated. Validation results showed 97.8% residues in favored and additional allowed regions of Ramachandran plots. Ligand binding residues prediction showed four ligand clusters, having 25 ligands in cluster 1. Importantly, presence of a Phe120-Gly121-Gly122 conserved pattern in the functional domain was detected. In the predicted structural model of hABH7, amino acid residues, Arginine at 57, 58, 59 and 60 along with tyrosine at 61 were predicted in RNA binding sites of the model. The predicted and validated model of human homologue hABH7 resulting from this study may unveil the mechanism of DNA damage repair in humans and accelerate the research on designing appropriate inhibitors aiding in chemotherapy and cancer related diseases

The Phyre2 web portal for protein modeling, prediction and analysis

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission

ConSole: using modularity of contact maps to locate solenoid domains in protein structures.

BackgroundPeriodic proteins, characterized by the presence of multiple repeats of short motifs, form an interesting and seldom-studied group. Due to often extreme divergence in sequence, detection and analysis of such motifs is performed more reliably on the structural level. Yet, few algorithms have been developed for the detection and analysis of structures of periodic proteins.ResultsConSole recognizes modularity in protein contact maps, allowing for precise identification of repeats in solenoid protein structures, an important subgroup of periodic proteins. Tests on benchmarks show that ConSole has higher recognition accuracy as compared to Raphael, the only other publicly available solenoid structure detection tool. As a next step of ConSole analysis, we show how detection of solenoid repeats in structures can be used to improve sequence recognition of these motifs and to detect subtle irregularities of repeat lengths in three solenoid protein families.ConclusionsThe ConSole algorithm provides a fast and accurate tool to recognize solenoid protein structures as a whole and to identify individual solenoid repeat units from a structure. ConSole is available as a web-based, interactive server and is available for download at http://console.sanfordburnham.org

Initiator tRNA genes template the 3\u27 CCA end at high frequencies in bacteria.

BACKGROUND: While the CCA sequence at the mature 3\u27 end of tRNAs is conserved and critical for translational function, a genetic template for this sequence is not always contained in tRNA genes. In eukaryotes and Archaea, the CCA ends of tRNAs are synthesized post-transcriptionally by CCA-adding enzymes. In Bacteria, tRNA genes template CCA sporadically. RESULTS: In order to understand the variation in how prokaryotic tRNA genes template CCA, we re-annotated tRNA genes in tRNAdb-CE database version 0.8. Among 132,129 prokaryotic tRNA genes, initiator tRNA genes template CCA at the highest average frequency (74.1%) over all functional classes except selenocysteine and pyrrolysine tRNA genes (88.1% and 100% respectively). Across bacterial phyla and a wide range of genome sizes, many lineages exist in which predominantly initiator tRNA genes template CCA. Convergent and parallel retention of CCA templating in initiator tRNA genes evolved in independent histories of reductive genome evolution in Bacteria. Also, in a majority of cyanobacterial and actinobacterial genera, predominantly initiator tRNA genes template CCA. We also found that a surprising fraction of archaeal tRNA genes template CCA. CONCLUSIONS: We suggest that cotranscriptional synthesis of initiator tRNA CCA 3\u27 ends can complement inefficient processing of initiator tRNA precursors, bootstrap rapid initiation of protein synthesis from a non-growing state, or contribute to an increase in cellular growth rates by reducing overheads of mass and energy to maintain nonfunctional tRNA precursor pools. More generally, CCA templating in structurally non-conforming tRNA genes can afford cells robustness and greater plasticity to respond rapidly to environmental changes and stimuli

Alignment of helical membrane protein sequences using AlignMe

Few sequence alignment methods have been designed specifically for integral membrane proteins, even though these important proteins have distinct evolutionary and structural properties that might affect their alignments. Existing approaches typically consider membrane-related information either by using membrane-specific substitution matrices or by assigning distinct penalties for gap creation in transmembrane and non-transmembrane regions. Here, we ask whether favoring matching of predicted transmembrane segments within a standard dynamic programming algorithm can improve the accuracy of pairwise membrane protein sequence alignments. We tested various strategies using a specifically designed program called AlignMe. An updated set of homologous membrane protein structures, called HOMEP2, was used as a reference for optimizing the gap penalties. The best of the membrane-protein optimized approaches were then tested on an independent reference set of membrane protein sequence alignments from the BAliBASE collection. When secondary structure (S) matching was combined with evolutionary information (using a position-specific substitution matrix (P)), in an approach we called AlignMePS, the resultant pairwise alignments were typically among the most accurate over a broad range of sequence similarities when compared to available methods. Matching transmembrane predictions (T), in addition to evolutionary information, and secondary-structure predictions, in an approach called AlignMePST, generally reduces the accuracy of the alignments of closely-related proteins in the BAliBASE set relative to AlignMePS, but may be useful in cases of extremely distantly related proteins for which sequence information is less informative. The open source AlignMe code is available at https://sourceforge.net/projects/alignme​/, and at http://www.forrestlab.org, along with an online server and the HOMEP2 data set

MODBASE, a database of annotated comparative protein structure models and associated resources.

MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by MODPIPE, an automated modeling pipeline that relies primarily on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE currently contains 5,152,695 reliable models for domains in 1,593,209 unique protein sequences; only models based on statistically significant alignments and/or models assessed to have the correct fold are included. MODBASE also allows users to calculate comparative models on demand, through an interface to the MODWEB modeling server (http://salilab.org/modweb). Other resources integrated with MODBASE include databases of multiple protein structure alignments (DBAli), structurally defined ligand binding sites (LIGBASE), predicted ligand binding sites (AnnoLyze), structurally defined binary domain interfaces (PIBASE) and annotated single nucleotide polymorphisms and somatic mutations found in human proteins (LS-SNP, LS-Mut). MODBASE models are also available through the Protein Model Portal (http://www.proteinmodelportal.org/)