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Hypoxia inducible factors (HIFs) are transcription factors belonging to the basic helix−loop−helix PER-ARNT-SIM (bHLH-PAS) protein family with a role in sensing oxygen levels in the cell. Under hypoxia, the HIF-α degradation pathway is blocked and dimerization with the aryl hydrocarbon receptor nuclear translocator (ARNT) makes HIF-α transcriptionally active. Due to the common hypoxic environment of tumors, inhibition of this mechanism by destabilization of HIF-α:ARNT dimerization has been proposed as a promising therapeutic strategy. Following the discovery of a druggable cavity within the PAS-B domain of HIF-2α, research efforts have been directed to identify artificial ligands that can impair heterodimerization. Although the crystallographic structures of the HIF-2α:ARNT complex have elucidated the dimer architecture and the 0X3-inhibitor placement within the HIF-2α PAS-B, unveiling the inhibition mechanism requires investigation of how ligand-induced perturbations could dynamically propagate through the structure and affect dimerization. To this end, we compared evolutionary features, intrinsic dynamics and energetic properties of the dimerization interfaces of HIF-2α:ARNT in both the apo and holo forms. Residue conservation analysis highlighted inter-domain connecting elements that have a role in dimerization. Analysis of domain contributions to the dimerization energy demonstrated the importance of bHLH and PAS-A of both partners and of HIF-2α PAS-B domain in dimer stabilization. Among quaternary structure oscillations revealed by Molecular Dynamics simulations, the hinge-bending motion of the ARNT PAS-B domain around the flexible PAS-A/PAS-B linker supports a general model for ARNT dimerization in different heterodimers. Comparison of the HIF-2α:ARNT dynamics in the apo and 0X3-bound forms indicated a model of inhibition where the HIF-2α-PAS-B interfaces are destabilised as a result of water-bridged ligand-protein interactions and these local effects allosterically propagate to perturb the correlated motions of the domains and inter-domain communication. These findings will guide the design of improved inhibitors to contrast cell survival in tumor masses., Author summary A low oxygen condition, called hypoxia, often occurs in tumor masses and generally correlates with worse prognosis. Cells in a tumor react to low oxygen levels with a metabolism modification induced by the activation of hypoxia inducible factors (HIFs) through dimerization with a partner protein and binding to a DNA target. Disrupting this protein-protein interaction could be a potential therapeutic strategy, but directly interfering with dimer formation can be troublesome because of the difficulty to design drugs that bind to protein interfaces. However, ligands that bind internal protein cavities can indirectly perturb the interfaces reducing dimers stability. Albeit protein crystallography had offered a detailed static picture of a HIF dimer bound to candidate inhibitors, it is not able to describe either the perturbation caused by binding or the molecular mechanism of dimer destabilization. Here we exploit molecular dynamics to identify the crucial interfaces in the HIF dimer stabilization and, by comparing the results obtained in the bound and unbound forms, we reveal the mechanism of ligand inhibition at atomic detail. All these findings will guide toward the design of improved dimerization inhibitors, to contrast cell survival in tumor masses.

Molecular modeling has given important contributions to elucidation of the main stages in the AhR signal transduction pathway. Despite the lack of experimentally determined structures of the AhR functional domains, information derived from homologous systems has been exploited for modeling their structure and interactions. Homology models of the AhR PASB domain have provided information on the binding cavity and contributed to elucidate species-specific differences in ligand binding. Molecular Docking simulations of the ligand binding process have given insights into differences in binding of diverse agonists, antagonists, and selective AhR modulators, and their application to virtual screening of large databases of compounds have allowed identification of novel AhR ligands. Recently available structural information on protein–protein and protein-DNA complexes of other bHLH-PAS systems has opened the way for modeling the AhR:ARNT dimer structure and investigating the mechanisms of AhR transformation and DNA binding. Future research directions should include simulation of the protein dynamics to obtain a more reliable description of intermolecular interactions involved in signal transmission.

Antibody affinity maturation is one of the fundamental processes of immune defense against invading pathogens. From the biological point of view, the clonal selection hypothesis represents the most accepted mechanism to explain how mutations increasing the affinity for target antigens are introduced and selected in antibody molecules. However, understanding at the molecular level how protein modifications, such as point mutation, can modify and modulate the affinity of an antibody for its antigen is still a major open issue in molecular biology. In this paper, we address various aspects of this problem by analyzing and comparing atomistic simulations of 17 variants of the bevacizumab antibody, all directed against the common target protein VEGF-A. In particular, we examine MD-based descriptors of the internal energetics and dynamics of mutated antibodies and their possible correlations with experimentally determined affinities for the antigens. Our results show that affinity improvement is correlated with a variation of the internal stabilization energy of the antibody molecule when bound to the antigen, compensated by the variation in the interaction energy between the antigen and the antibody, paralleled by an overall modulation of internal coordination within the antibody molecular structure. A possible model of the mechanism of rigidification and of the main residues involved is proposed. Overall, our results can help in understanding the molecular determinants of antigen recognition and have implications in the rational design of new antibodies with optimized affinities.

The Aryl hydrocarbon Receptor (AhR) is a transcription factor that mediates the biochemical response to xenobiotics and the toxic effects of a number of environmental contaminants, including dioxins. Recently, endogenous regulatory roles for the AhR in normal physiology and development have also been reported, thus extending the interest in understanding its molecular mechanisms of activation. Since dimerization with the AhR Nuclear Translocator (ARNT) protein, occurring through the Helix-Loop-Helix (HLH) and PER-ARNT-SIM (PAS) domains, is needed to convert the AhR into its transcriptionally active form, deciphering the AhR:ARNT dimerization mode would provide insights into the mechanisms of AhR transformation. Here we present homology models of the murine AhR:ARNT PAS domain dimer developed using recently available X-ray structures of other bHLH-PAS protein dimers. Due to the different reciprocal orientation and interaction surfaces in the different template dimers, two alternative models were developed for both the PAS-A and PAS-B dimers and they were characterized by combining a number of computational evaluations. Both well-established hot spot prediction methods and new approaches to analyze individual residue and residue-pairwise contributions to the MM-GBSA binding free energies were adopted to predict residues critical for dimer stabilization. On this basis, a mutagenesis strategy for both the murine AhR and ARNT proteins was designed and ligand-dependent DNA binding ability of the AhR:ARNT heterodimer mutants was evaluated. While functional analysis disfavored the HIF2α:ARNT heterodimer-based PAS-B model, most mutants derived from the CLOCK:BMAL1-based AhR:ARNT dimer models of both the PAS-A and the PAS-B dramatically decreased the levels of DNA binding, suggesting this latter model as the most suitable for describing AhR:ARNT dimerization. These novel results open new research directions focused at elucidating basic molecular mechanisms underlying the functional activity of the AhR., Author Summary Computational modeling combined with experimental validation may give insight into structural and functional properties of protein systems. The basic Helix-Loop-Helix PER-ARNT-SIM (bHLH-PAS) proteins show conserved functional domains despite the broad range of functions exerted by the different systems. Within this protein family, the Aryl hydrocarbon Receptor (AhR) is known to mediate the toxic effects of a number of environmental contaminants, including dioxins and dioxin-like chemicals, and it also exerts other biochemical and physiological effects. Despite the absence of experimentally determined structures, theoretical models of the AhR PAS domains developed on the basis of homologous systems have allowed understanding of some aspects of the molecular mechanisms underlying its function. In this work we present alternative structural models of the transcriptionally active complex of AhR with the AhR Nuclear Translocator (ARNT) protein. Computational characterization of the modeled protein-protein interaction interfaces guided the design of mutagenesis experiments, and evaluation of the DNA binding ability of the resulting AhR:ARNT dimer mutants allowed validation of the models and selection of the most reliable one. These findings open new research directions for understanding the molecular mechanisms underlying the functional activity of the AhR.

Unraveling the molecular basis of immune recognition still represents a challenging task for current biological sciences, both in terms of theoretical knowledge and practical implications. Here, we describe the physical-chemistry methods and computational protocols for the prediction of antibody-binding epitopes and MHC-II loaded epitopes, starting from the atomic coordinates of antigenic proteins (PDB file). These concepts are the base of the Web tool BEPPE (Binding Epitope Prediction from Protein Energetics), a free service that returns a list of putative epitope sequences and related blast searches against the Uniprot human complete proteome. BEPPE can be employed for the study of the biophysical processes at the basis of the immune recognition, as well as for immunological purposes such as the rational design of biomarkers and targets for diagnostics, therapeutics, and vaccine discovery.

Unraveling the molecular basis of immune recognition still represents a challenging task for current biological sciences, both in terms of theoretical knowledge and practical implications. Here, we describe the physical-chemistry methods and computational protocols for the prediction of antibody-binding epitopes and MHC-II loaded epitopes, starting from the atomic coordinates of antigenic proteins (PDB file). These concepts are the base of the Web tool BEPPE (Binding Epitope Prediction from Protein Energetics), a free service that returns a list of putative epitope sequences and related blast searches against the Uniprot human complete proteome. BEPPE can be employed for the study of the biophysical processes at the basis of the immune recognition, as well as for immunological purposes such as the rational design of biomarkers and targets for diagnostics, therapeutics, and vaccine discovery.

MicroRNAs (miRNAs) are potent modulators of protein expression that play key roles in brain pathways regulating neurogenesis and synaptic plasticity. These small RNAs may be critical for the pathophysiology of mental disorders and may influence the effectiveness of psychotropic drugs. To investigate the possible involvement of miRNAs in the mechanism of action of antidepressants (AD), we conducted a whole-miRNome quantitative analysis with qRT-PCR of the changes in the blood of 10 depressed subjects after 12 weeks of treatment with escitalopram. Thirty miRNAs were differentially expressed after the AD treatment: 28 miRNAs were up-regulated, and 2 miRNAs were strongly down-regulated. miRNA target gene prediction and functional annotation analysis showed that there was a significant enrichment in several pathways associated with neuronal brain function (such as neuroactive ligand-receptor interaction, axon guidance, long-term potentiation and depression), supporting the hypothesis that the differentially regulated miRNAs may be involved in the AD mechanism. (C) 2012 Elsevier B.V. and ECNP. All rights reserved.

Motivations. Protein-protein interactions are deeply involved in the antibody::antigen recognition process. Crystallographic data offer evidence of conformational changes between apo and holo forms of antibodies complexed with antigens. Nevertheless, the dynamical aspects of intermolecular relationships still remain a challenging issue. Extensive molecular dynamics (MD) simulations offer the suitable tool for generating statistical ensembles of conformations from which various energetic, structural and dynamic properties can be collected. The interaction energy correlations between all residue pairs can be investigated in order to find relevant regions involved in the fold stability; furthermore, a global overview of these sites can highlight preferential signaling pathways along the protein structures. In the present work, we will describe those conformational change events which derive from the formation of antibody::antigen complex. In particular, we will define those pathways that start from the paratope region and propagate through the immunoglobulin domains. Methods. We have taken into account a dataset of 24 Fab::antigen complexes, whose structures have been deposited at the Protein Data Bank. For most of them, 50ns unrestrained MD simulations were computed, with a 2fs time-step. Three structures targeting the same epitope and sharing similar paratopes were submitted to 200ns MD simulations. Each case of the dataset was duplicated, considering two systems: the isolated Fab structure (apo form) and the complex (holo form). An amount of 3,300ns of MD simulations was performed. The time-curves of RMSD on backbone atoms were used to monitor system equilibration. For every simulation the first 10ns were discarded for the further analyses. The structures sampled from the trajectories were clustered with the purpose of defining the conformational space explored. From the most representative structures (medoids) of the most populated clusters energy interaction matrices were calculated, considering all the non-bonded interactions between each residue pairs. Principal component analyses were performed over such matrices (Energy Decomposition Analysis), and only the relevant eigenvectors were considered. Since every component renders the relative contribution of each residue to the overall stabilization energy, we selected those components whose values are higher than a threshold value which depends on the number of the residues in the protein. All the residues were mapped to a common reference, obtained from joining the Chothia numbering schema with structural multiple alignment based schema, for variable and constant domains respectively. Finally, we mapped the energetic relevant residues of each case to the numbering schema depicted above, in order to summarize a common residue pattern referred to a generic Fab structure. We then collected the occurrencies for each position, and we termed them as Interaction Energy Recurrent Positions (IERPs). Results. The results obtained herein are intended at identifying those interactions that define the formation of antibody::antigen complexes. The correlated motions are also investigated, reducing the complex protein dynamics to its essential degrees of freedom. The analyses of global distance fluctuation matrices show that the motions of residues belonging to the same domain appear more correlated with each other. The constant domains of the heavy chain (CH) show a higher mobility, with respect to the remaining protein. The CH domains are close to the boundary between Fab and Fc fragments; hence, CH domains may benefit from a greater degree of unrestrained motion. From the interaction energy analyses, we collected three subset of IERPs: the first ones are extracted only from apo forms simulations, the second ones are typical of holo forms, the third ones appear as relevant in both forms. The distribution of these subsets along the polypeptide chains of the Fab structures indicates that heavy chains contain most of the shared IERPs; in contrast, it seem that apo and holo forms show differerential IERPs profiles along the sequence of light chains. Then, we compared the distribution of IERPs, typical of apo and holo forms, along the four Ig domains VH, VL, CH and CL. In holo forms CL domains show lesser amount of IERPs, while CH domains appear enriched; variable domains (VH and VL) do not show significant differences between apo and holo. In holo form, CL domains still mantain few sparse IERPs that could be considered as local stabilizing hotspots. The visual inspection of the structures of the dataset illuminates the spatial distribution of IERPs. In the antigen bound Fabs (holo forms) the selected residues starts from the framework regions of variable domains and propagate downstream, preferentially along the CH domain. Finally, the signal arrive at the base of costant domains, focusing around the C-terminal regions. On the opposite side unbound Fabs (apo forms) do not show a preferential pattern.

miRNA target genes prediction represents a crucial step in miRNAs functional characterization. In this context, the challenging issue remains predictions accuracy and recognition of false positive results. In this article myMIR, a web based system for increasing reliability of miRNAs predicted targets lists, is presented. myMIR implements an integrated pipeline for computing ranked miRNA::target lists and provides annotations for narrowing them down. The system relies on knowledge base data, suitably integrated in order to extend the functional characterization of targeted genes to miRNAs, by highlighting the search on over-represented annotation terms. Validation results show a dramatic reduction in the quantity of predictions and an increase in the sensitivity, when compared to other methods. This improves the predictions accuracy and allows the formulation of novel hypotheses on miRNAs functional involvement.

Chicken liver bile acid binding protein (cL-BABP) crystallizes with water molecules in its binding site. To obtain insights on the role of internal water, we performed two 100 ns molecular dynamics (MD) simulations in explicit solvent for cL-BABP, as apo form and as a complex with two molecules of cholic acid, and analyzed in detail the dynamics properties of all water molecules. The diffusion coefficients of the more persistent internal water molecules are significantly different from the bulk, but similar between the two protein forms. A different number of molecules and a different organization are observed for apo- and holo-cL-BABP. Most water molecules identified in the binding site of the apo-crystal diffuse to the bulk during the simulation. In contrast, almost all the internal waters of the holo-crystal maintain the same interactions with internal sidechains and ligands, which suggests they have a relevant role in protein-ligand molecular recognition. Only in the presence of these water molecules we were able to reproduce, by a classical molecular docking approach, the structure of the complex cL-BABP::cholic acid with a low ligand root mean square deviation (RMSD) with respect to its reference positioning. Literature data reported a conserved pattern of hydrogen bonds between a single water molecule and three amino acid residues of the binding site in a series of crystallized FABP. In cL-BABP, the interactions between this conserved water molecule and the three residues are present in the crystal of both apo- and holo-cL-BABP but are lost immediately after the start of molecular dynamics. Copyright © 2008 John Wiley & Sons, Ltd.

Antibody-antigen recognition plays a key role in the immune response against pathogens. Here, we have investigated various aspects of this problem by analyzing a large and diverse set of antibodies and their respective complexes with protein antigens through atomistic simulations. Common features of antibody response to the presence of antigens are elucidated by the analysis of the proteins' internal dynamics and coordination in different ligand states, combined with the analysis of the interaction networks implicated in the stabilization of functional structures. The use of a common structural reference reveals preferential changes in the dynamic coordination and intramolecular interaction networks induced by antigen binding and shared by all antibodies. Such changes propagate from the binding region through the whole immunoglobulin domains. Overall, complexed antibodies show more diffuse networks of nonbonded interactions and a general higher internal dynamic coordination, which preferentially involve the immunoglobulin (Ig) domains of the heavy chain. The combined results provide atomistic insights into the correlations between the modulation of conformational dynamics, structural stability, and allosteric signal transduction. In particular, the results suggest that specific networks of residues, shared among all the analyzed proteins, define the molecular pathways by which antibody structures respond to antigen binding. Our studies may have implications in practical use, such as the rational design of antibodies with specifically modulated antigen-binding affinities.