Conservation and specialization in PAS domain dynamics

The PAS (Per-ARNT-Sim) superfamily is presented as a well-suited study case to demonstrate how comparison of functional motions among distant homologous proteins with conserved fold characteristics may give insight into their functional specialization. Based on the importance of structural flexibility of the receptive structures in anticipating the signal-induced conformational changes of these sensory systems, the dynamics of these structures were analysed. Molecular dynamics was proved to be an effective method to obtain a reliable picture of the dynamics of the crystal structures of HERG, phy3, PYP and FixL, provided that an extensive conformational space sampling is performed. Other reliable sources of dynamic information were the ensembles of NMR structures of hPASK, HIF-2α and PYP. Essential dynamics analysis was successfully employed to extract the relevant information from the sampled conformational spaces. Comparison of motion patterns in the essential subspaces, based on the structural alignment, allowed identification of the specialized region in each domain. This appears to be evolved in the superfamily by following a specific trend, that also suggests the presence of a limited number of general solutions adopted by the PAS domains to sense external signals. These findings may give insight into unknown mechanisms of PAS domains and guide further experimental studies. © The Author 2005. Published by Oxford University Press. All rights reserved

Predicting the accuracy of protein-ligand docking on homology models

Ligand-protein docking is increasingly used in Drug Discovery. The initial limitations imposed by a reduced availability of target protein structures have been overcome by the use of theoretical models, especially those derived by homology modeling techniques. While this greatly extended the use of docking simulations, it also introduced the need for general and robust criteria to estimate the reliability of docking results given the model quality. To this end, a large-scale experiment was performed on a diverse set including experimental structures and homology models for a group of representative ligand-protein complexes. A wide spectrum of model quality was sampled using templates at different evolutionary distances and different strategies for target-template alignment and modeling. The obtained models were scored by a selection of the most used model quality indices. The binding geometries were generated using AutoDock, one of the most common docking programs. An important result of this study is that indeed quantitative and robust correlations exist between the accuracy of docking results and the model quality, especially in the binding site. Moreover, state-of-the-art indices for model quality assessment are already an effective tool for an a priori prediction of the accuracy of docking experiments in the context of groups of proteins with conserved structural characteristics.Contract/grant sponsor: National Institutes of Health; contract/grant numbers: ES00768

Structural alphabets derived from attractors in conformational space

Background: The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis.Results: A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness.Conclusions: The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics. © 2010 Pandini et al; licensee BioMed Central Ltd

GSATools: Analysis of allosteric communication and functional local motions using a structural alphabet

Motivation: GSATools is a free software package to analyze conformational ensembles and to detect functional motions in proteins by means of a structural alphabet. The software integrates with the widely used GROMACS simulation package and can generate a range of graphical outputs. Three applications can be supported: (i) investigation of the conformational variability of local structures; (ii) detection of allosteric communication; and (iii) identification of local regions that are critical for global functional motions. These analyses provide insights into the dynamics of proteins and allow for targeted design of functional mutants in theoretical and experimental studies. Availability: The C source code of the GSATools, along with a set of pre-compiled binaries, is freely available under GNU General Public License from http://mathbio.nimr.mrc.ac.uk/wiki/GSATools. Contact: alessandro.pandini@kcl. ac.uk or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. © 2013 The Author 2013. Published by Oxford University Press

Exploiting the WH/ZH symmetry in the search for New Physics

We suggest to isolate the loop-induced gluon-initiated component ($gg\to ZH$) for associated $ZH$ production by using the similarity of the Drell-Yan-like component for $ZH$ production to the $WH$ process. We argue that the cross-section ratio of the latter two processes can be predicted with high theoretical accuracy. Comparing it to the experimental $ZH/WH$ cross-section ratio should allow to probe for New Physics in the $gg\to ZH$ component at the HL-LHC. We consider typical BSM scenarios in order to exemplify the effect they would have on the proposed observable.Comment: 22 pages, 10 figures. v2: Minor changes; matches published versio

Structural and functional characterization of the aryl hydrocarbon receptor ligand binding domain by homology modeling and mutational analysis

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that is activated by a structurally diverse array of synthetic and natural chemicals, including toxic halogenated aromatic hydrocarbons such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Analysis of the occurring in the AhR ligand binding and activation processes requires structural information on the AhR Per-Arnt-Sim (PAS) B-containing ligand binding domain, for which no experimentally determined structure has been reported. With the availability of extensive structural information on homologous PAS-containing proteins, a reliable model of the mouse AhR PAS B domain was developed by comparative modeling techniques. The PAS domain structures of the functionally related hypoxia-inducible factor 2α (HIF-2α) and AhR nuclear translocator (ARNT) proteins, which exhibit the highest degree of sequence identity and similarity with AhR, were chosen to develop a two-template model. To confirm the features of the modeled domain, the effects of point mutations in selected residue positions on both TCDD binding to the AhR and TCDD-dependent transformation and DNA binding were analyzed. Mutagenesis and functional analysis results are consistent with the proposed model and confirm that the cavity modeled in the interior of the domain is indeed involved in ligand binding. Moreover, the physicochemical characteristics of some residues and of their mutants, along with the effects of mutagenesis on TCDD and DNA binding, also suggest some key features that are required for ligand binding and activation of mAhR at a molecular level, thus providing a framework for further studies. © 2007 American Chemical Society

Using local states to drive the sampling of global conformations in proteins

Conformational changes associated with protein function often occur beyond the time scale currently accessible to unbiased molecular dynamics (MD) simulations, so that different approaches have been developed to accelerate their sampling. Here we investigate how the knowledge of backbone conformations preferentially adopted by protein fragments, as contained in precalculated libraries known as structural alphabets (SA), can be used to explore the landscape of protein conformations in MD simulations. We find that (a) enhancing the sampling of native local states in both metadynamics and steered MD simulations allows the recovery of global folded states in small proteins; (b) folded states can still be recovered when the amount of information on the native local states is reduced by using a low-resolution version of the SA, where states are clustered into macrostates; and (c) sequences of SA states derived from collections of structural motifs can be used to sample alternative conformations of preselected protein regions. The present findings have potential impact on several applications, ranging from protein model refinement to protein folding and design.The computer resources, technical expertise, Red Española de Supercomputación, Cristian Micheletti, Michael Sadowski and Katarzyna Maksimia

Detection of the TCDD binding-fingerprint within the Ah receptor ligand binding domain by structurally driven mutagenesis and functional analysis

The aryl hydrocarbon receptor (AhR) is a ligand-dependent, basic helix-loop-helix Per-Arnt-Sim (PAS)-containing transcription factor that can bind and be activated by structurally diverse chemicals, including the toxic environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Our previous three-dimensional homology model of the mouse AhR (mAhR) PAS B ligand binding domain allowed identification of the binding site and its experimental validation. We have extended this analysis by conducting comparative structural modeling studies of the ligand binding domains of six additional highaffinity mammalian AhRs. These results, coupled with site-directed mutagenesis and AhR functional analysis, have allowed detection of the "TCDD binding-fingerprint" of conserved residues within the ligand binding cavity necessary for high-affinity TCDD binding and TCDD-dependent AhR transformation DNA binding. The essential role of selected residues was further evaluated using molecular docking simulations of TCDD with both wild-type and mutant mAhRs. Taken together, our results dramatically improve our understanding of the molecular determinants of TCDD binding and provide a basis for future studies directed toward rationalizing the observed species differences in AhR sensitivity to TCDD and understanding the mechanistic basis for the dramatic diversity in AhR ligand structure. © 2009 American Chemical Society

Structural and functional diversity of ferredoxin-NADP+ reductases

Although all ferredoxin-NADP+ reductases (FNRs) catalyze the same reaction, i.e. the transfer of reducing equivalents between NADP(H) and ferredoxin, they belong to two unrelated families of proteins: the plant-type and the glutathione reductase-type of FNRs. Aim of this review is to provide a general classification scheme for these enzymes, to be used as a framework for the comparison of their properties. Furthermore, we report on some recent findings, which significantly increased the understanding of the structure–function relationships of FNRs, i.e. the ability of adrenodoxin reductase and its homologs to catalyze the oxidation of NADP+ to its 4-oxo derivative, and the properties of plant-type FNRs from non-photosynthetic organisms. Plant-type FNRs from bacteria and Apicomplexan parasites provide examples of novel ways of FAD- and NADP(H)-binding. The recent characterization of an FNR from Plasmodium falciparum brings these enzymes into the field of drug design