MDcons: Intermolecular contact maps as a tool to analyze the interface of protein complexes from molecular dynamics trajectories

T cell epitope based vaccine design while targeting outer capsid proteins of rotavirus strains infecting neonates: an immunoinformatics approach

Gastrointestinal diarrhea is majorly caused by the rotavirus (RV) in the children who generally are under the age group of 5 years. WHO estimates that ∼95% of the children contract RV infection, by this age. The disease is highly contagious; notably in many cases, it is proven fatal with high mortality rates especially in the developing countries. In India alone, an estimated 145,000 yearly deaths occurs due to RV related gastrointestinal diarrhea. WHO pre-qualified vaccines that are available for RV are all live attenuated vaccines with modest efficacy range between 40 and 60%. Further, the risk of intussusceptions has been reported in some children on RV vaccination. Thus, in a quest to develop alternative candidate to overcome challenges associated with these oral vaccines, we chose immunoinformatics approach to design a multi-epitope vaccine (MEV) while targeting the outer capsid viral proteinsVP4 and VP7 of the neonatal strains of rotavirus. Interestingly, ten epitopes, that is, six CD8+T-cells and four CD4+T-cell epitopes were identified which were predicted to be antigenic, non-allergic, non-toxic and stable. These epitopes were then linked to adjuvants, linkers, and PADRE sequences to create a multi-epitope vaccine for RV. The in silico designed RV-MEV and human TLR5 complex displayed stable interactions during molecular dynamics simulations. Further, the immune simulation studies of RV-MEV corroborated that the vaccine candidate emerges as a promising immunogen. Future investigations while performing in vitro and in vivo analyses with designed RV-MEV construct are highly desirable to warrant the potential of this vaccine candidate in protective immunity against different strains of RVs infecting neonates.Communicated by Ramaswamy H. Sarma.

Application of Funnel Metadynamics to the Platelet Integrin αIIbβ3 in Complex with an RGD Peptide

Integrin αIIbβ3 mediates platelet aggregation by binding the Arginyl-Glycyl-Aspartic acid (RGD) sequence of fibrinogen. RGD binding occurs at a site topographically proximal to the αIIb and β3 subunits, promoting the conformational activation of the receptor from bent to extended states. While several experimental approaches have characterized RGD binding to αIIbβ3 integrin, applying computational methods has been significantly more challenging due to limited sampling and the need for a priori information regarding the interactions between the RGD peptide and integrin. In this study, we employed all-atom simulations using funnel metadynamics (FM) to evaluate the interactions of an RGD peptide with the αIIb and β3 subunits of integrin. FM incorporates an external history-dependent potential on selected degrees of freedom while applying a funnel-shaped restraint potential to limit RGD exploration of the unbound state. Furthermore, it does not require a priori information about the interactions, enhancing the sampling at a low computational cost. Our FM simulations reveal significant molecular changes in the β3 subunit of integrin upon RGD binding and provide a free-energy landscape with a low-energy binding mode surrounded by higher-energy prebinding states. The strong agreement between previous experimental and computational data and our results highlights the reliability of FM as a method for studying dynamic interactions of complex systems such as integrin.

Charge Engineering of the Nucleic Acid Binding Cleft of a Thermostable HIV-1 Reverse Transcriptase Reveals Key Interactions and a Novel Mechanism of RNase H Inactivation

Coupled with PCR, reverse transcriptases (RTs) have been widely used for RNA detection and gene expression analysis. Increased thermostability and nucleic acid binding affinity are desirable RT properties to improve yields and sensitivity of these applications. The effects of amino acid substitutions in the RT RNase H domain were tested in an engineered HIV-1 group O RT, containing mutations K358R/A359G/S360A and devoid of RNase H activity due to the presence of E478Q (O3MQ RT). Twenty mutant RTs with Lys or Arg at positions interacting with the template-primer (i.e., at positions 473-477, 499-502 and 505) were obtained and characterized. Most of them produced significant amounts of cDNA at 37, 50 and 65 °C, as determined in RT-PCR reactions. However, a big loss of activity was observed with mutants A477K/R, S499K/R, V502K/R and Y505K/R, particularly at 65 °C. Binding affinity experiments confirmed that residues 477, 502 and 505 were less tolerant to mutations. Amino acid substitutions Q500K and Q500R produced a slight increase of cDNA synthesis efficiency at 50 and 65 °C, without altering the KD for model DNA/DNA and RNA/DNA heteroduplexes. Interestingly, molecular dynamics simulations predicted that those mutations inactivate the RNase H activity by altering the geometry of the catalytic site. Proof of this unexpected effect was obtained after introducing Q500K or Q500R in the wild-type HIV-1BH10 RT and mutant K358R/A359G/S360A RT. Our results reveal a novel mechanism of RNase H inactivation that preserves RT DNA binding and polymerization efficiency without substituting RNase H active site residues.

Unveiling CD59-Antibody Interactions to Design Paratope-Mimicking Peptides for Complement Modulation

CD59 is an abundant immuno-regulatory human protein that protects cells from damage by inhibiting the complement system. CD59 inhibits the assembly of the Membrane Attack Complex (MAC), the bactericidal pore-forming toxin of the innate immune system. In addition, several pathogenic viruses, including HIV-1, escape complement-mediated virolysis by incorporating this complement inhibitor in their own viral envelope. This makes human pathogenic viruses, such as HIV-1, not neutralised by the complement in human fluids. CD59 is also overexpressed in several cancer cells to resist the complement attack. Consistent with its importance as a therapeutical target, CD59-targeting antibodies have been proven to be successful in hindering HIV-1 growth and counteracting the effect of complement inhibition by specific cancer cells. In this work, we make use of bioinformatics and computational tools to identify CD59 interactions with blocking antibodies and to describe molecular details of the paratope-epitope interface. Based on this information, we design and produce paratope-mimicking bicyclic peptides able to target CD59. Our results set the basis for the development of antibody-mimicking small molecules targeting CD59 with potential therapeutic interest as complement activators.

Unveiling New Druggable Pockets in Influenza Non-Structural Protein 1: NS1-Host Interactions as Antiviral Targets for Flu

Influenza viruses are responsible for significant morbidity and mortality worldwide in winter seasonal outbreaks and in flu pandemics. Influenza viruses have a high rate of evolution, requiring annual vaccine updates and severely diminishing the effectiveness of the available antivirals. Identifying novel viral targets and developing new effective antivirals is an urgent need. One of the most promising new targets for influenza antiviral therapy is non-structural protein 1 (NS1), a highly conserved protein exclusively expressed in virus-infected cells that mediates essential functions in virus replication and pathogenesis. Interaction of NS1 with the host proteins PI3K and TRIM25 is paramount for NS1's role in infection and pathogenesis by promoting viral replication through the inhibition of apoptosis and suppressing interferon production, respectively. We, therefore, conducted an analysis of the druggability of this viral protein by performing molecular dynamics simulations on full-length NS1 coupled with ligand pocket detection. We identified several druggable pockets that are partially conserved throughout most of the simulation time. Moreover, we found out that some of these druggable pockets co-localize with the most stable binding regions of the protein-protein interaction (PPI) sites of NS1 with PI3K and TRIM25, which suggests that these NS1 druggable pockets are promising new targets for antiviral development.

Immunoinformatics-Aided Design of a Peptide Based Multiepitope Vaccine Targeting Glycoproteins and Membrane Proteins against Monkeypox Virus

Monkeypox is a self-limiting zoonotic viral disease and causes smallpox-like symptoms. The disease has a case fatality ratio of 3-6% and, recently, a multi-country outbreak of the disease has occurred. The currently available vaccines that have provided immunization against monkeypox are classified as live attenuated vaccinia virus-based vaccines, which pose challenges of safety and efficacy in chronic infections. In this study, we have used an immunoinformatics-aided design of a multi-epitope vaccine (MEV) candidate by targeting monkeypox virus (MPXV) glycoproteins and membrane proteins. From these proteins, seven epitopes (two T-helper cell epitopes, four T-cytotoxic cell epitopes and one linear B cell epitopes) were finally selected and predicted as antigenic, non-allergic, interferon-γ activating and non-toxic. These epitopes were linked to adjuvants to design a non-allergic and antigenic candidate MPXV-MEV. Further, molecular docking and molecular dynamics simulations predicted stable interactions between predicted MEV and human receptor TLR5. Finally, the immune-simulation analysis showed that the candidate MPXV-MEV could elicit a human immune response. The results obtained from these in silico experiments are promising but require further validation through additional in vivo experiments.

SINAPs: A Software Tool for Analysis and Visualization of Interaction Networks of Molecular Dynamics Simulations

As long as the structural study of molecular mechanisms requires multiple molecular dynamics reflecting contrasted bioactive states, the subsequent analysis of molecular interaction networks remains a bottleneck to be fairly treated and requires a user-friendly 3D view of key interactions. Structural Interaction Network Analysis Protocols (SINAPs) is a proprietary python tool developed to (i) quickly solve key interactions able to distinguish two protein states, either from two sets of molecular dynamics simulations or from two crystallographic structures, and (ii) render a user-friendly 3D view of these key interactions through a plugin of UCSF Chimera, one of the most popular open-source viewing software for biomolecular systems. Through two case studies, glucose transporter-1 (GLUT-1) and A2A adenosine receptor (A2AR), SINAPs easily pinpointed key interactions observed experimentally and relevant for their bioactivities. This very effective tool was thus applied to identify the amino acids involved in the molecular enzymatic mechanisms ruling the activation of an immunomodulator drug candidate, P28 glutathione-S-transferase (P28GST). SINAPs is freely available at https://github.com/ParImmune/SINAPs.

D936Y and Other Mutations in the Fusion Core of the SARS-CoV-2 Spike Protein Heptad Repeat 1: Frequency, Geographical Distribution, and Structural Effect

The crown of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is constituted by its spike (S) glycoprotein. S protein mediates the SARS-CoV-2 entry into the host cells. The “fusion core” of the heptad repeat 1 (HR1) on S plays a crucial role in the virus infectivity, as it is part of a key membrane fusion architecture. While SARS-CoV-2 was becoming a global threat, scientists have been accumulating data on the virus at an impressive pace, both in terms of genomic sequences and of three-dimensional structures. On 15 February 2021, from the SARS-CoV-2 genomic sequences in the GISAID resource, we collected 415,673 complete S protein sequences and identified all the mutations occurring in the HR1 fusion core. This is a 21-residue segment, which, in the post-fusion conformation of the protein, gives many strong interactions with the heptad repeat 2, bringing viral and cellular membranes in proximity for fusion. We investigated the frequency and structural effect of novel mutations accumulated over time in such a crucial region for the virus infectivity. Three mutations were quite frequent, occurring in over 0.1% of the total sequences. These were S929T, D936Y, and S949F, all in the N-terminal half of the HR1 fusion core segment and particularly spread in Europe and USA. The most frequent of them, D936Y, was present in 17% of sequences from Finland and 12% of sequences from Sweden. In the post-fusion conformation of the unmutated S protein, D936 is involved in an inter-monomer salt bridge with R1185. We investigated the effect of the D936Y mutation on the pre-fusion and post-fusion state of the protein by using molecular dynamics, showing how it especially affects the latter one.

Exploring interfacial dynamics in homodimeric S-ribosylhomocysteine lyase (LuxS) from Vibrio cholerae through molecular dynamics simulations

To the best of our knowledge, this is the first molecular dynamics simulation study on the dimeric form of the LuxS enzyme from Vibrio cholerae to evaluate its structural and dynamical properties including the dynamics of the interface formed by the two monomeric chains of the enzyme. The dynamics of the interfacial region were investigated in terms of inter-residual contacts and the associated interface area of the enzyme in its ligand-free and ligand–bound states which produced characteristics contrast in the interfacial dynamics. Moreover, the binding patterns of the two inhibitors (RHC and KRI) to the enzyme forming two different enzyme–ligand complexes were analyzed which pointed towards a varying inhibition potential of the inhibitors as also revealed by the free energies of ligand binding. It is shown that KRI is a more potent inhibitor than RHC – a substrate analogue, showing correlation with experimental data. Moreover, the role of a loop in chain B of the enzyme was found to facilitate the binding of RHC similar to that of the substrate, while KRI demonstrates a differing binding pattern. The computation of the free energy of binding for the two ligands was also carried out via thermodynamic integration which ultimately served to correlate the dynamical properties with the inhibition potential of two different ligands against the enzyme. Furthermore, this successful study provides a rational to suggest novel LuxS inhibitors which could become promising candidates to treat the diseases caused by a broad variety of bacterial species.

To the best of our knowledge, this is the first molecular dynamics simulation study on the dimeric form of the LuxS enzyme from Vibrio cholerae to evaluate its structural and dynamical properties including the dynamics of the interface formed by the two monomeric chains of the enzyme.

The CASP13-CAPRI targets as case studies to illustrate a novel scoring pipeline integrating CONSRANK with clustering and interface analyses

Background

Properly scoring protein-protein docking models to single out the correct ones is an open challenge, also object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), a community-wide blind docking experiment. We introduced in the field CONSRANK (CONSensus RANKing), the first pure consensus method. Also available as a web server, CONSRANK ranks docking models in an ensemble based on their ability to match the most frequent inter-residue contacts in it. We have been blindly testing CONSRANK in all the latest CAPRI rounds, where we showed it to perform competitively with the state-of-the-art energy and knowledge-based scoring functions. More recently, we developed Clust-CONSRANK, an algorithm introducing a contact-based clustering of the models as a preliminary step of the CONSRANK scoring process.

In the latest CASP13-CAPRI joint experiment, we participated as scorers with a novel pipeline, combining both our scoring tools, CONSRANK and Clust-CONSRANK, with our interface analysis tool COCOMAPS. Selection of the 10 models for submission was guided by the strength of the emerging consensus, and their final ranking was assisted by results of the interface analysis.

Results

As a result of the above approach, we were by far the first scorer in the CASP13-CAPRI top-1 ranking, having high/medium quality models ranked at the top-1 position for the majority of targets (11 out of the total 19). We were also the first scorer in the top-10 ranking, on a par with another group, and the second scorer in the top-5 ranking. Further, we topped the ranking relative to the prediction of binding interfaces, among all the scorers and predictors. Using the CASP13-CAPRI targets as case studies, we illustrate here in detail the approach we adopted.

Conclusions

Introducing some flexibility in the final model selection and ranking, as well as differentiating the adopted scoring approach depending on the targets were the key assets for our highly successful performance, as compared to previous CAPRI rounds. The approach we propose is entirely based on methods made available to the community and could thus be reproduced by any user.

Barrier-to-autointegration factor 1 (Banf1) regulates poly [ADP-ribose] polymerase 1 (PARP1) activity following oxidative DNA damage

The DNA repair capacity of human cells declines with age, in a process that is not clearly understood. Mutation of the nuclear envelope protein barrier-to-autointegration factor 1 (Banf1) has previously been shown to cause a human progeroid disorder, Néstor–Guillermo progeria syndrome (NGPS). The underlying links between Banf1, DNA repair and the ageing process are unknown. Here, we report that Banf1 controls the DNA damage response to oxidative stress via regulation of poly [ADP-ribose] polymerase 1 (PARP1). Specifically, oxidative lesions promote direct binding of Banf1 to PARP1, a critical NAD⁺-dependent DNA repair protein, leading to inhibition of PARP1 auto-ADP-ribosylation and defective repair of oxidative lesions, in cells with increased Banf1. Consistent with this, cells from patients with NGPS have defective PARP1 activity and impaired repair of oxidative lesions. These data support a model whereby Banf1 is crucial to reset oxidative-stress-induced PARP1 activity. Together, these data offer insight into Banf1-regulated, PARP1-directed repair of oxidative lesions.

Mutation of the nuclear envelope protein, barrier-to-autointegration factor 1 (Banf1), has previously been associated with the development of ageing associated diseases in a human progeria syndrome. Here, the authors reveal the functional link between Banf1-regulated, PARP1-directed repair of oxidative lesions.

Evolutionary couplings detect side-chain interactions

Patterns of amino acid covariation in large protein sequence alignments can inform the prediction of de novo protein structures, binding interfaces, and mutational effects. While algorithms that detect these so-called evolutionary couplings between residues have proven useful for practical applications, less is known about how and why these methods perform so well, and what insights into biological processes can be gained from their application. Evolutionary coupling algorithms are commonly benchmarked by comparison to true structural contacts derived from solved protein structures. However, the methods used to determine true structural contacts are not standardized and different definitions of structural contacts may have important consequences for interpreting the results from evolutionary coupling analyses and understanding their overall utility. Here, we show that evolutionary coupling analyses are significantly more likely to identify structural contacts between side-chain atoms than between backbone atoms. We use both simulations and empirical analyses to highlight that purely backbone-based definitions of true residue–residue contacts (i.e., based on the distance between Cα atoms) may underestimate the accuracy of evolutionary coupling algorithms by as much as 40% and that a commonly used reference point (Cβ atoms) underestimates the accuracy by 10–15%. These findings show that co-evolutionary outcomes differ according to which atoms participate in residue–residue interactions and suggest that accounting for different interaction types may lead to further improvements to contact-prediction methods.

Human LC3 and GABARAP subfamily members achieve functional specificity via specific structural modulations

Autophagy is a conserved adaptive cellular pathway essential to maintain a variety of physiological functions. Core components of this machinery are the six human Atg8 orthologs that initiate formation of appropriate protein complexes. While these proteins are routinely used as indicators of autophagic flux, it is presently not possible to discern their individual biological functions due to our inability to predict specific binding partners. In our attempts towards determining downstream effector functions, we developed a computational pipeline to define structural determinants of human Atg8 family members that dictate functional diversity. We found a clear evolutionary separation between human LC3 and GABARAP subfamilies and also defined a novel sequence motif responsible for their specificity. By analyzing known protein structures, we observed that functional modules or microclusters reveal a pattern of intramolecular network, including distinct hydrogen bonding of key residues (F52/Y49; a subset of HP2) that may directly modulate their interaction preferences. Multiple molecular dynamics simulations were performed to characterize how these proteins interact with a common protein binding partner, PLEKHM1. Our analysis showed remarkable differences in binding modes via intrinsic protein dynamics, with PLEKHM1-bound GABARAP complexes showing less fluctuations and higher number of contacts. We further mapped 373 genomic variations and demonstrated that distinct cancer-related mutations are likely to lead to significant structural changes. Our findings present a quantitative framework to establish factors underlying exquisite specificity of human Atg8 proteins, and thus facilitate the design of precise modulators.Abbreviations: Atg: autophagy-related; ECs: evolutionary constraints; GABARAP: GABA type A receptor-associated protein; HsAtg8: human Atg8; HP: hydrophobic pocket; KBTBD6: kelch repeat and BTB domain containing 6; LIR: LC3-interacting region; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MD: molecular dynamics; HIV-1 Nef: human immunodeficiency virus type 1 negative regulatory factor; PLEKHM1: pleckstrin homology and RUN domain containing M1; RMSD: root mean square deviation; SQSTM1/p62: sequestosome 1; WDFY3/ALFY: WD repeat and FYVE domain containing 3.

Hydrodynamic and Electrophoretic Properties of Trastuzumab/HER2 Extracellular Domain Complexes as Revealed by Experimental Techniques and Computational Simulations

The combination of hydrodynamic and electrophoretic experiments and computer simulations is a powerful approach to study the interaction between proteins. In this work, we present hydrodynamic and electrophoretic experiments in an aqueous solution along with molecular dynamics and hydrodynamic modeling to monitor and compute biophysical properties of the interactions between the extracellular domain of the HER2 protein (eHER2) and the monoclonal antibody trastuzumab (TZM). The importance of this system relies on the fact that the overexpression of HER2 protein is related with the poor prognosis breast cancers (HER2++ positives), while the TZM is a monoclonal antibody for the treatment of this cancer. We have found and characterized two different complexes between the TZM and eHER2 proteins (1:1 and 1:2 TZM:eHER2 complexes). The conformational features of these complexes regulate their hydrodynamic and electrostatic properties. Thus, the results indicate a high degree of molecular flexibility in the systems that ultimately leads to higher values of the intrinsic viscosity, as well as lower values of diffusion coefficient than those expected for simple globular proteins. A highly asymmetric charge distribution is detected for the monovalent complex (1:1 complex), which has strong implications in correlations between the experimental electrophoretic mobility and the modeled net charge. In order to understand the dynamics of these systems and the role of the specific domains involved, it is essential to find biophysical correlations between dynamics, macroscopic transport and electrostatic properties. The results should be of general interest for researchers working in this area.

Distinguishing crystallographic from biological interfaces in protein complexes: role of intermolecular contacts and energetics for classification

BACKGROUND

Study of macromolecular assemblies is fundamental to understand functions in cells. X-ray crystallography is the most common technique to solve their 3D structure at atomic resolution. In a crystal, however, both biologically-relevant interfaces and non-specific interfaces resulting from crystallographic packing are observed. Due to the complexity of the biological assemblies currently tackled, classifying those interfaces, i.e. distinguishing biological from crystal lattice interfaces, is not trivial and often prone to errors. In this context, analyzing the physico-chemical characteristics of biological/crystal interfaces can help researchers identify possible features that distinguish them and gain a better understanding of the systems.

RESULTS

In this work, we are providing new insights into the differences between biological and crystallographic complexes by focusing on "pair-properties" of interfaces that have not yet been fully investigated. We investigated properties such intermolecular residue-residue contacts (already successfully applied to the prediction of binding affinities) and interaction energies (electrostatic, Van der Waals and desolvation). By using the XtalMany and BioMany interface datasets, we show that interfacial residue contacts, classified as a function of their physico-chemical properties, can distinguish between biological and crystallographic interfaces. The energetic terms show, on average, higher values for crystal interfaces, reflecting a less stable interface due to crystal packing compared to biological interfaces. By using a variety of machine learning approaches, we trained a new interface classification predictor based on contacts and interaction energetic features. Our predictor reaches an accuracy in classifying biological vs crystal interfaces of 0.92, compared to 0.88 for EPPIC (one of the main state-of-the-art classifiers reporting same performance as PISA).

CONCLUSION

In this work we have gained insights into the nature of intermolecular contacts and energetics terms distinguishing biological from crystallographic interfaces. Our findings might have a broader applicability in structural biology, for example for the identification of near native poses in docking. We implemented our classification approach into an easy-to-use and fast software, freely available to the scientific community from http://github.com/haddocking/interface-classifier .

Investigating cyclic peptides inhibiting CD2-CD58 interactions through molecular dynamics and molecular docking methods

The CD2-CD58 protein-protein interaction is known to favor the recognition of antigen presenting cells by T cells. The structural, energetics, and dynamical properties of three known cyclic CD58 ligands, named P6, P7, and RTD-c, are studied through molecular dynamics (MD) simulations and molecular docking calculations. The ligands are built so as to mimic the C and F β-strands of protein CD2, connected via turn inducers. The MD analyses focus on the location of the ligands with respect to the experimental binding site and on the direct and water-mediated hydrogen bonds (H bonds) they form with CD58. Ligand P6, with a sequence close to the experimental β-strands of CD2, presents characteristics that explain its higher experimental affinity, e.g., the lower mobility and flexibility at the CD58 surface, and the larger number and occurrence frequency of ligand-CD58 H bonds. For the two other ligands, the structural modifications lead to changes in the binding pattern with CD58 and its dynamics. In parallel, a large set of molecular docking calculations, carried out with various search spaces and docking algorithms, are compared to provide a consensus view of the preferred ligand binding modes. The analysis of the ligand side chain locations yields results that are consistent with the CD2-CD58 crystal structure and suggests various binding modes of the experimentally identified hot spot of the ligands, i.e., Tyr86. P6 is shown to form a number of contacts that are also present in the experimental CD2-CD58 structure.

Further Insight into the Interactions of the Cytotoxic Macrolides Laulimalide and Peloruside A with Their Common Binding Site

The binding site of the macrolides laulimalide and peloruside A, which is different from that of the clinically useful drugs paclitaxel/taxol and ixabepilone (tax site), is known to be between two adjacent β-tubulin units (ext site). Here, we report our study of the binding of these molecules to an α1β1/α2β2-tubulin "tetramer" model. AutoDock 4.2.6//AutoDock Vina dockings predicted that the affinities of laulimalide and peloruside A for the tax site are quite similar to those for the ext site. However, molecular dynamics (MD) simulations indicated that only when these two ligands are located at the ext site, there are contacts that help stabilize the system, favoring the β1/β2 interactions. The binding affinity of laulimalide for this site is stronger than that of peloruside A, but this is compensated for by additional β1/β2 contacts that are induced by peloruside A. MD studies also suggested that epothilones at the tax site and either laulimalide or peloruside A at the ext site cause similar stabilizing effects (mainly linking the M-loop of β1 and loop H1-B2 of β2). In a "hexamer" model (3 units of αβ-tubulin), the effects are confirmed. Metadynamics simulations of laulimalide and peloruside A, which are reported for the first time, suggest that peloruside A produces a stronger change in the M-loop, which explains the stabilization of the β1/β2 interaction.

Molecular and hydrodynamic properties of human epidermal growth factor receptor HER2 extracellular domain and its homodimer: Experiments and multi-scale simulations

BACKGROUND

In a broad range of human carcinomas gene amplification leads to HER2 overexpression, which has been proposed to cause spontaneous dimerization and activation in the absence of ligand. This makes HER2 attractive as a therapeutic target. However, the HER2 homodimerization mechanism remains unexplored. It has been suggested that the "back-to-back" homodimer does not form in solution. Notwithstanding, very recently the crystal structure of the HER2 extracellular domain homodimer formed with a "back-to-head" interaction has been resolved. We intend to explore the existence of such interactions.

METHODS

A combination of experiments, molecular dynamics and hydrodynamic modeling were used to monitor the transport properties of HER2 in solution.

RESULTS & CONCLUSIONS

We have detected the HER2 extracellular domain homodimer in solution. The results show a high degree of molecular flexibility, which ultimately leads to quite higher values of the intrinsic viscosity and lower values of diffusion coefficient than those corresponding to globular proteins. This flexibility obeys to the open conformation of the receptor and to the large fluctuations of the different domains. We also report that for obtaining the correct hydrodynamic constants from the modeling one must consider the glycosylation of the systems.

GENERAL SIGNIFICANCE

Conformational features of epidermal growth factor receptors regulate their hydrodynamic properties and control their activity. It is essential to understand the dynamics of these systems and the role of the specific domains involved. To find biophysical correlations between dynamics and macroscopic transport properties is of general interest for researches working in this area. This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue.

Analyzing the role of CagV, a VirB8 homolog of the type IV secretion system of Helicobacter pylori

The type IV secretion system of Helicobacter pylori (Cag‐T4SS) is composed of ~ 27 components including a VirB8 homolog, CagV. We have characterized CagV and reported that it is an inner membrane protein and, like VirB8, forms a homodimer. Its stability is not dependent on the other Cag components and the absence of cagV affects the stability of only CagI, a protein involved in pilus formation. CagV is not required for the stability and localization of outer membrane subcomplex proteins, but interacts with them through CagX. It also interacts with the inner membrane‐associated components, CagF and CagZ, and is required for the surface localization of CagA. The results of this study might help in deciphering the mechanistic contributions of CagV in the Cag‐T4SS biogenesis and function.

Introducing a Clustering Step in a Consensus Approach for the Scoring of Protein-Protein Docking Models

Correctly scoring protein-protein docking models to single out native-like ones is an open challenge. It is also an object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), the community-wide blind docking experiment. We introduced in the field the first pure consensus method, CONSRANK, which ranks models based on their ability to match the most conserved contacts in the ensemble they belong to. In CAPRI, scorers are asked to evaluate a set of available models and select the top ten ones, based on their own scoring approach. Scorers’ performance is ranked based on the number of targets/interfaces for which they could provide at least one correct solution. In such terms, blind testing in CAPRI Round 30 (a joint prediction round with CASP11) has shown that critical cases for CONSRANK are represented by targets showing multiple interfaces or for which only a very small number of correct solutions are available. To address these challenging cases, CONSRANK has now been modified to include a contact-based clustering of the models as a preliminary step of the scoring process. We used an agglomerative hierarchical clustering based on the number of common inter-residue contacts within the models. Two criteria, with different thresholds, were explored in the cluster generation, setting either the number of common contacts or of total clusters. For each clustering approach, after selecting the top (most populated) ten clusters, CONSRANK was run on these clusters and the top-ranked model for each cluster was selected, in the limit of 10 models per target. We have applied our modified scoring approach, Clust-CONSRANK, to SCORE_SET, a set of CAPRI scoring models made recently available by CAPRI assessors, and to the subset of homodimeric targets in CAPRI Round 30 for which CONSRANK failed to include a correct solution within the ten selected models. Results show that, for the challenging cases, the clustering step typically enriches the ten top ranked models in native-like solutions. The best performing clustering approaches we tested indeed lead to more than double the number of cases for which at least one correct solution can be included within the top ten ranked models.

Analysis of the interface variability in NMR structure ensembles of protein-protein complexes

NMR structures consist in ensembles of conformers, all satisfying the experimental restraints, which exhibit a certain degree of structural variability. We analyzed here the interface in NMR ensembles of protein-protein heterodimeric complexes and found it to span a wide range of different conservations. The different exhibited conservations do not simply correlate with the size of the systems/interfaces, and are most probably the result of an interplay between different factors, including the quality of experimental data and the intrinsic complex flexibility. In any case, this information is not to be missed when NMR structures of protein-protein complexes are analyzed; especially considering that, as we also show here, the first NMR conformer is usually not the one which best reflects the overall interface. To quantify the interface conservation and to analyze it, we used an approach originally conceived for the analysis and ranking of ensembles of docking models, which has now been extended to directly deal with NMR ensembles. We propose this approach, based on the conservation of the inter-residue contacts at the interface, both for the analysis of the interface in whole ensembles of NMR complexes and for the possible selection of a single conformer as the best representative of the overall interface. In order to make the analyses automatic and fast, we made the protocol available as a web tool at: https://www.molnac.unisa.it/BioTools/consrank/consrank-nmr.html.

The D173G mutation in ADAMTS-13 causes a severe form of congenital thrombotic thrombocytopenic purpura. A clinical, biochemical and in silico study

Congenital thrombotic thrombocytopenic purpura (TTP) is a rare form of thrombotic microangiopathy, inherited with autosomal recessive mode as a dysfunction or severe deficiency of ADAMTS-13 (A Disintegrin And Metalloprotease with ThromboSpondin 1 repeats Nr. 13), caused by mutations in the ADAMTS-13 gene. About 100 mutations of the ADAMTS-13 gene were identified so far, although only a few characterised by in vitro expression studies. A new Asp to Gly homozygous mutation at position 173 of ADAMTS-13 sequence was identified in a family of Romanian origin, with some members affected by clinical signs of TTP. In two male sons, this mutation caused a severe (< 3%) deficiency of ADAMTS-13 activity and antigen level, associated with periodic thrombocytopenia, haemolytic anaemia and mild mental confusion. Both parents, who are cousins, showed the same mutation in heterozygous form. Expression studies of the mutant ADAMTS-13, performed in HEK293 cells, showed a severe decrease of the enzyme's activity and secretion, although the protease was detected inside the cells. Molecular dynamics found that in the D173G mutant the interface area between the metalloprotease domain and the disintegrin-like domain significantly decreases during the simulations, while the proline-rich 20 residues linker region (LR, 285-304) between them undergoes extensive conformational changes. Inter-domain contacts are also significantly less conserved in the mutant compared to the wild-type. Both a decrease of the inter-domain contacts along with a substantial conformational rearrangement of LR interfere with the proper maturation and folding of the mutant ADAMTS-13, thus impairing its secretion.

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

Structural insights into tumor-specific chaperoning activity of gamma synuclein in protecting estrogen receptor alpha 36 and its role in tamoxifen resistance in breast cancer

This study investigates structural aspects underlying the chaperoning activity of an intrinsically disordered protein, gamma synuclein, in promoting estrogen mediated breast cancer.

Structural basis for the recognition in an idiotype-anti-idiotype antibody complex related to celiac disease

Anti-idiotype antibodies have potential therapeutic applications in many fields, including autoimmune diseases. Herein we report the isolation and characterization of AIM2, an anti-idiotype antibody elicited in a mouse model upon expression of the celiac disease-specific autoantibody MB2.8 (directed against the main disease autoantigen type 2 transglutaminase, TG2). To characterize the interaction between the two antibodies, a 3D model of the MB2.8-AIM2 complex has been obtained by molecular docking. Analysis and selection of the different obtained docking solutions was based on the conservation within them of the inter-residue contacts. The selected model is very well representative of the different solutions found and its stability is confirmed by molecular dynamics simulations. Furthermore, the binding mode it adopts is very similar to that observed in most of the experimental structures available for idiotype-anti-idiotype antibody complexes. In the obtained model, AIM2 is directed against the MB2.8 CDR region, especially on its variable light chain. This makes the concurrent formation of the MB2.8-AIM2 complex and of the MB2.8-TG2 complex incompatible, thus explaining the experimentally observed inhibitory effect on the MB2.8 binding to TG2.