Prion protein region 23–32 interacts with tubulin and inhibits microtubule assembly

In previous studies we have demonstrated that prion protein (PrP) binds directly to tubulin and this interaction leads to the inhibition of microtubule formation by inducement of tubulin oligomerization. This report is aimed at mapping the regions of PrP and tubulin involved in the interaction and identification of PrP domains responsible for tubulin oligomerization. Preliminary studies focused our attention to the N‐terminal flexible part of PrP encompassing residues 23–110. Using a panel of deletion mutants of PrP, we identified two microtubule‐binding motifs at both ends of this part of the molecule. We found that residues 23–32 constitute a major site of interaction, whereas residues 101–110 represent a weak binding site. The crucial role of the 23–32 sequence in the interaction with tubulin was confirmed employing chymotryptic fragments of PrP. Surprisingly, the octarepeat region linking the above motifs plays only a supporting role in the interaction. The binding of Cu²⁺ to PrP did not affect the interaction. We also demonstrate that PrP deletion mutants lacking residues 23–32 exhibit very low efficiency in the inducement of tubulin oligomerization. Moreover, a synthetic peptide corresponding to this sequence, but not that identical with fragment 101–110, mimics the effects of the full‐length protein on tubulin oligomerization and microtubule assembly. At the cellular level, peptide composed of the PrP motive 23–30 and signal sequence (1–22) disrupted the microtubular cytoskeleton. Using tryptic and chymotryptic fragments of α‐ and β‐tubulin, we mapped the docking sites for PrP within the C‐terminal domains constituting the outer surface of microtubule. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

The flexible C‐terminal arm of the Lassa arenavirus Z‐protein mediates interactions with multiple binding partners

The arenavirus genome encodes for a Z‐protein, which contains a RING domain that coordinates two zinc ions, and has been identified as having several functional roles at various stages of the virus life cycle. Z‐protein binds to multiple host proteins and has been directly implicated in the promotion of viral budding, repression of mRNA translation, and apoptosis of infected cells. Using homology models of the Z‐protein from Lassa strain arenavirus, replica exchange molecular dynamics (MD) was used to refine the structures, which were then subsequently clustered. Population‐weighted ensembles of low‐energy cluster representatives were predicted based upon optimal agreement of the chemical shifts computed with the SPARTA program with the experimental NMR chemical shifts. A member of the refined ensemble was indentified to be a potential binder of budding factor Tsg101 based on its correspondence to the structure of the HIV‐1 Gag late domain when bound to Tsg101. Members of these ensembles were docked against the crystal structure of human eIF4E translation initiation factor. Two plausible binding modes emerged based upon their agreement with experimental observation, favorable interaction energies and stability during MD trajectories. Mutations to Z are proposed that would either inhibit both binding mechanisms or selectively inhibit only one mode. The C‐terminal domain conformation of the most populated member of the representative ensemble shielded protein‐binding recognition motifs for Tsg101 and eIF4E and represents the most populated state free in solution. We propose that C‐terminal flexibility is key for mediating the different functional states of the Z‐protein. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Molecular dynamics simulation study on the interaction of collagen‐like peptides with gelatinase‐A (MMP‐2)

Although several models have been proposed for the interaction of collagen with gelatinase‐A (matrix metalloproteinases‐2 (MMP‐2)), the extensive role of each domain of gelatinase A in hydrolyzing the collagens with and without interruptions is still elusive. Molecular docking, molecular dynamics (MD) simulation, normal mode analysis (NMA) and framework rigidity optimized dynamics algorithm (FRODAN) based analysis were carried out to understand the function of various domains of MMP‐2 upon interaction with collagen like peptides. The results reveal that the collagen binding domain (CBD) binds to the C‐terminal of collagen like peptide with interruption. CBD helps in unwinding the loosely packed interrupted region of triple helical structure to a greater extent. It can be possible to speculate that the role of hemopexin (HPX) domain is to prevent further unwinding of collagen like peptide by binding to the other end of the collagen like peptide. The catalytic (CAT) domain then reorients itself to interact with the part of the unwound region of collagen like peptide for further hydrolysis. In conclusion the CBD of MMP‐2 recognizes the collagen and aids in unwinding the collagen like peptide with interruptions, and the HPX domain of MMP‐2 binds to the other end of the collagen allowing CAT domain to access the cleavage site. This study provides a comprehensive understanding of the structural basis of collagenolysis by MMP‐2. © 2013 Wiley Periodicals, Inc. Biopolymers 101: 779–794, 2014.     

Complexes of HIV‐1 integrase with HAT proteins: Multiscale models,dynamics, and hypotheses on allosteric sites of inhibition

A new and very promising strategy for HIV drug discovery consists in blocking the multiple functional interactions between HIV‐1 integrase (IN) and its cellular cofactors. At present, this line of action is hindered by the absence of three‐dimensional structures of IN in complex with any of them. In this article, we developed a full‐length three‐dimensional structure of IN, including the highly flexible terminal residues 270–288, which are not experimentally solved. Additionally, we built models of IN complexed to the human acetyltransferases GCN5 and p300 based on available structural and mutagenesis data. Then, we studied the dynamical behavior of these models by means of the Coarse‐Grained Molecular Dynamics (CGMD) and Essential Dynamics (ED) to locate and characterize the nature of the largest collective motions. We found correlated motions involving distant regions of IN. Moreover, we found that these are influenced by the binding with the acetyltransferases (HATs). Taken together these findings suggest a way to affect the acetyltransferase binding by an allosteric type of inhibition and provide an important new approach for the drug design against HIV disease. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

NMR reveals structural rearrangements associated to substrate insertion in nucleotide‐adding enzymes

The protein NP_344798.1 from Streptococcus pneumoniae TIGR4 exhibits a head and base‐interacting neck domain architecture, as observed in class II nucleotide‐adding enzymes. Although it has less than 20% overall sequence identity with any member of this enzyme family, the residues involved in substrate‐recognition and catalysis are highly conserved in NP_344798.1. NMR studies showed binding affinity of NP_344798.1 for nucleotides and revealed μs to ms time scale rate processes involving residues constituting the active site. The results thus obtained indicate that large‐amplitude rearrangements of regular secondary structures facilitate the penetration of the substrate into the occluded nucleotide‐binding site of NP_344798.1 and, by inference based on sequence and structural homology, probably a wide range of other nucleotide‐adding enzymes.     

Holo‐BtuF stabilizes the open conformation of the vitamin B12 ABC transporter BtuCD

While there is evidence that other ABC transporters can tell between empty and loaded substrate binding protein, reconstitution experiments suggest otherwise for the Escherichia coli vitamin B12 importer BtuCD‐F. Here, we address the question of BtuCD‐F substrate sensitivity in a combined protein–protein docking and molecular dynamics simulation approach. Starting from the BtuCD and holo‐BtuF crystal structures, we model two holo‐BtuCD‐F docking complexes differing by a 180° orientation of BtuF. One of these is similar to the apo‐BtuCD‐F crystal structure. Both docking complexes were embedded in a lipid/water environment to investigate their dynamics and BtuCD's conformational response to the presence and absence of BtuF, vitamin B12, and Mg‐ATP in a series of 28 independent MD simulations. We find holo‐BtuF stabilizing the open conformation of BtuCD, whereas the transporter begins to close again when BtuF or vitamin B12 is removed—suggesting BtuCD‐F is capable of substrate sensitivity. We identified BtuC transmembrane helices 3 and 5, the L‐loops and the adjacent helices comprised of BtuC residues 170–180 as hotspots of conformational change. We propose the latter to act as substrate sensors. BtuF‐Trp44 appears to act as a lid on the vitamin B12 binding cleft in BtuF X‐ray structures and protrudes into the BtuCD transport channel in one of our simulations, which might represent an initial step in vitamin B12 uptake. On an average, we observe subunit motions where the nucleotide binding domains approach each other while the transmembrane domains display an opening trend toward the periplasm. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

DockRank: Ranking docked conformations using partner‐specific sequence homology‐based protein interface prediction

Selecting near‐native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner‐specific sequence homology‐based protein–protein interface predictor (PS‐HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state‐of‐the‐art docking scoring functions using Success Rate (the percentage of cases that have at least one near‐native conformation among the top m conformations) and Hit Rate (the percentage of near‐native conformations that are included among the top m conformations). In cases where it is possible to obtain partner‐specific (PS) interface predictions from PS‐HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state‐of‐the‐art energy‐based scoring functions (improving Success Rate by up to 4‐fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39‐fold). The latter result underscores the importance of using partner‐specific interface residues in scoring docked conformations. We show that DockRank, when used to re‐rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/ . Proteins 2014; 82:250–267. © 2013 Wiley Periodicals, Inc.     

Mitotic spindle association of TACC3 requires Aurora‐A‐dependent stabilization of a cryptic α‐helix

Aurora‐A regulates the recruitment of TACC3 to the mitotic spindle through a phospho‐dependent interaction with clathrin heavy chain (CHC). Here, we describe the structural basis of these interactions, mediated by three motifs in a disordered region of TACC3. A hydrophobic docking motif binds to a previously uncharacterized pocket on Aurora‐A that is blocked in most kinases. Abrogation of the docking motif causes a delay in late mitosis, consistent with the cellular distribution of Aurora‐A complexes. Phosphorylation of Ser558 engages a conformational switch in a second motif from a disordered state, needed to bind the kinase active site, into a helical conformation. The helix extends into a third, adjacent motif that is recognized by a helical‐repeat region of CHC, not a recognized phospho‐reader domain. This potentially widespread mechanism of phospho‐recognition provides greater flexibility to tune the molecular details of the interaction than canonical recognition motifs that are dominated by phosphate binding.     

Key mutations stabilize antigen‐binding conformation during affinity maturation of a broadly neutralizing influenza antibody lineage

Affinity maturation, the process in which somatic hypermutation and positive selection generate antibodies with increasing affinity for an antigen, is pivotal in acquired humoral immunity. We have studied the mechanism of affinity gain in a human B‐cell lineage in which two main maturation pathways, diverging from a common ancestor, lead to three mature antibodies that neutralize a broad range of H1 influenza viruses. Previous work showed that increased affinity in the mature antibodies derives primarily from stabilization of the CDR H3 loop in the antigen‐binding conformation. We have now used molecular dynamics simulations and existing crystal structures to identify potentially key maturation mutations, and we have characterized their effects on the CDR H3 loop and on antigen binding using further simulations and experimental affinity measurements, respectively. In the two maturation pathways, different contacts between light and heavy chains stabilize the CDR H3 loop. As few as two single‐site mutations in each pathway can confer substantial loop stability, but none of them confers experimentally detectable stability on its own. Our results support models of the germinal center reaction in which two or more mutations can occur without concomitant selection and show how divergent pathways have yielded functionally equivalent antibodies. Proteins 2014; 83:771–780. © 2014 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.     

Complex formation dynamics of native and mutated pyrin's B30.2 domain with caspase‐1

Pyrin protein is the product of the MEFV gene, mutations in which cause manifestation of familial Mediterranean fever (FMF). Functions of pyrin are not completely clear. The secondary structure of the pyrin is represented with four domains and two motifs. Mutations p.M680I, p.M694V, p.M694I, p.K695R, p.V726A, and p.A744S, which are located in the B30.2 domain of pyrin protein, are responsible for manifestation of the most common and severe forms of FMF. All the domains and the motifs of pyrin, are directly or indirectly, involved in the protein–protein interaction with proteins of apoptosis and regulate the cascade of inflammatory reactions, which is impaired due to pyrin mutations. It is well known, that malfunction of the pyrin‐caspase‐1 complex is the main reason of inflammation during FMF. Complete tertiary structure of pyrin and the effects of mutations in it are experimentally not studied yet. The aim of this study was to identify possible effects of the abovementioned mutations in the B30.2 domain tertiary structure and to determine their potential consequences in formation of the B30.2‐caspase‐1 complex. Using in silico methods, it was found, that these mutations led to structural rearrangements in B30.2 domain tertiary structure, causing shifts of binding sites and altering the interaction energy between B30.2 and caspase‐1.     

Microtubules dual chemo and thermo‐responsive depolymerization

The effects of chemotherapeutic agent vinblastine versus low temperature of 277 K were investigated on the structure of αβ‐tubulin heterodimer by means of molecular dynamics simulations. Individual experiments have shown that the vinblastine‐bound heterodimer, and its apo structure under low temperature of 277 K, both undergo conformational changes toward destabilization of the dimer as compared to the apo tubulin at 300 K. Both factors exhibited weakening of the longitudinal interactions of tubulin heterodimer through displacing dimer interfacial segments, resulting in dominant electrostatic repulsion at the interface of the subunits. The two independent factors of temperature and anti‐mitotic agent facilitate alteration of secondary structure in functional segments such as H1‐S2 loop, H3, H10 helices, and T7 loop, which are known to be important in either longitudinal or lateral contacts among αβ‐heterodimers in MTs protofilaments and their depolymerization mechanism. Proteins 2015; 83:970–981. © 2015 Wiley Periodicals, Inc.     

Discovery of binding proteins for a protein target using protein–protein docking‐based virtual screening

Target structure‐based virtual screening, which employs protein‐small molecule docking to identify potential ligands, has been widely used in small‐molecule drug discovery. In the present study, we used a protein–protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all‐to‐all protein–protein docking run on a large dataset was performed. The three‐dimensional rigid docking program SDOCK was used to examine protein–protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z‐score, and convergency of the low‐score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all‐to‐all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor‐α (TNFα), which is a well‐known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top‐ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein–protein docking for the discovery of novel binding proteins for specific protein targets. Proteins 2014; 82:2472–2482. © 2014 Wiley Periodicals, Inc.     

Using collections of structural models to predict changes of binding affinity caused by mutations in protein–protein interactions

Protein–protein interactions (PPIs) in all the molecular aspects that take place both inside and outside cells. However, determining experimentally the structure and affinity of PPIs is expensive and time consuming. Therefore, the development of computational tools, as a complement to experimental methods, is fundamental. Here, we present a computational suite: MODPIN, to model and predict the changes of binding affinity of PPIs. In this approach we use homology modeling to derive the structures of PPIs and score them using state‐of‐the‐art scoring functions. We explore the conformational space of PPIs by generating not a single structural model but a collection of structural models with different conformations based on several templates. We apply the approach to predict the changes in free energy upon mutations and splicing variants of large datasets of PPIs to statistically quantify the quality and accuracy of the predictions. As an example, we use MODPIN to study the effect of mutations in the interaction between colicin endonuclease 9 and colicin endonuclease 2 immune protein from Escherichia coli. Finally, we have compared our results with other state‐of‐art methods.     

Molecular modeling study for conformational changes of Sirtuin 2 due to substrate and inhibitor binding

Sirtuin is a member of NAD⁺-dependent deacetylase family. The structural details of Sirtuin 2 (SIRT2) complex will be very useful to discover the drug which might have beneficial effects on various diseases like cancer, diabetes, etc. Unfortunately, SIRT2 complex structure is not available yet, hence molecular docking was carried out to dock the substrate (NAD⁺ and acetylated lysine) and inhibitor (sirtinol) in the NAD⁺ binding site. The suitable binding orientation of substrate and inhibitor in the SIRT2 active site was selected and subjected to 5?ns molecular dynamics simulations to adjust the binding orientation of inhibitor and substrate as well as to identify the conformational changes in the active site. The result provides an insight about 3D SIRT2 structural details as well as the importance of F96 in deacetylation function. In addition, our simulations revealed the displacement of F96 upon substrate and inhibitor binding, inducing an extended conformation of loop3 and changing its interactions with the rest of SIRT2. We believe that our study could be helpful to gain a structural insight of SIRT2 and to design the receptor-based inhibitors.     

Interolog interfaces in protein–protein docking

Proteins are essential elements of biological systems, and their function typically relies on their ability to successfully bind to specific partners. Recently, an emphasis of study into protein interactions has been on hot spots, or residues in the binding interface that make a significant contribution to the binding energetics. In this study, we investigate how conservation of hot spots can be used to guide docking prediction. We show that the use of evolutionary data combined with hot spot prediction highlights near‐native structures across a range of benchmark examples. Our approach explores various strategies for using hot spots and evolutionary data to score protein complexes, using both absolute and chemical definitions of conservation along with refinements to these strategies that look at windowed conservation and filtering to ensure a minimum number of hot spots in each binding partner. Finally, structure‐based models of orthologs were generated for comparison with sequence‐based scoring. Using two data sets of 22 and 85 examples, a high rate of top 10 and top 1 predictions are observed, with up to 82% of examples returning a top 10 hit and 35% returning top 1 hit depending on the data set and strategy applied; upon inclusion of the native structure among the decoys, up to 55% of examples yielded a top 1 hit. The 20 common examples between data sets show that more carefully curated interolog data yields better predictions, particularly in achieving top 1 hits. Proteins 2015; 83:1940–1946. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.