An all-atom molecular dynamics study of the anti-interferon signaling of Ebola virus: interaction mechanisms of EBOV VP24 binding to Karyopherin alpha5

Ebola virus (EBOV) is highly lethal due to virally encoded immune antagonists, and the combination of EBOV VP24 with karyopherin alpha (KPNA) will trigger anti-interferon (IFN) signaling. The crystal structure of VP24-KPNA5 has been proposed in recent studies, but the precise binding mechanisms are still unclear. In order to explore the VP24-KPNA5 protein binding micro-mechanisms, Molecular Dynamic (MD) simulations and Molecular Mechanics Generalized Born Surface Area (MM-GB/SA) energy calculation are performed. The obtained results show that EBOV VP24 binding to KPNA5 will rigidify their binding-face, and both proteins will be compacted during binding. According to the analyses of binding free energies of WT and the eight mutant systems, MUT3 makes the most effective contributions to the interaction; additionally MUT4, R398A and the double mutant have the second most effective influence. Hydrogen bond analysis demonstrates that inhibitors which can interfere with the formation of hydrogen bonds D480-T138, E483-R137 and D205-R396 will prevent the anti-IFN effect. Meanwhile, by combining the decomposition of binding free energies (DC) with computational alanine scanning (CAS) results, it is shown that VP24 residues R137 and T138 will be potential targets for EBOV VP24 inhibitors, and KPNA5 residues R396, R398, R480, Y477 and F484 will be potential targets to prevent KPNA5 binding to VP24, which will ultimately block anti-IFN signaling. Our investigations provide theoretical data to understand the binding modes of VP24-KPNA5. The precise binding mechanisms of the complex may shed light on the development of potential novel inhibitors against EBOV infection.

Microsecond molecular dynamics simulations provide insight into the ATP-competitive inhibitor-induced allosteric protection of Akt kinase phosphorylation

Akt is a serine/threonine protein kinase, a critical mediator of growth factor-induced survival in key cellular pathways. Allosteric signaling between protein intramolecular domains requires long-range communication mediated by hotspot residues, often triggered by ligand binding. Here, based on extensive 3 μs explicit solvent molecular dynamics (MD) simulations of Akt1 kinase domain in the unbound (apo) and ATP-competitive inhibitor, GDC-0068-bound states, we propose a molecular mechanism for allosteric regulation of Akt1 kinase phosphorylation by GDC-0068 binding to the ATP-binding site. MD simulations revealed that the apo Akt1 is flexible with two disengaged N- and C-lobes, equilibrated between the open and closed conformations. GDC-0068 occupancy of the ATP-binding site shifts the conformational equilibrium of Akt1 from the open conformation toward the closed conformation and stabilizes the closed state. This effect enables allosteric signal propagation from the GDC-0068 to the phosphorylated T308 (pT308) in the activation loop and restrains phosphatase access to pT308, thereby protecting the pT308 in the GDC-0068-bound Akt1. Importantly, functional hotspots involved in the allosteric communication from the GDC-0068 to the pT308 are identified. Our analysis of GDC-0068-induced allosteric protection of Akt kinase phosphorylation yields important new insights into the molecular mechanism of allosteric regulation of Akt kinase activity.

Exploring the mechanism how Marburg virus VP35 recognizes and binds dsRNA by molecular dynamics simulations and free energy calculations

Filoviruses often cause terrible infectious disease which has not been successfully dealt with pharmacologically. All filoviruses encode a unique protein termed VP35 which can mask doubled-stranded RNA to deactivate interferon. The interface of VP35-dsRNA would be a feasible target for structure-based antiviral agent design. To explore the essence of VP35-dsRNA interaction, molecular dynamics simulation combined with MM-GBSA calculations were performed on Marburg virus VP35-dsRNA complex and several mutational complexes. The energetic analysis indicates that nonpolar interactions provide the main driving force for the binding process. Although the intermolecular electrostatic interactions play important roles in VP35-dsRNA interaction, the whole polar interactions are unfavorable for binding which result in a low binding affinity. Compared with wild type VP35, the studied mutants F228A, R271A, and K298A have obviously reduced binding free energies with dsRNA reflecting in the reduction of polar or nonpolar interactions. The results also indicate that the loss of binding affinity for one dsRNA strand would abolish the total binding affinity. Three important residues Arg271, Arg294, and Lys298 which makes the largest contribution for binding in VP35 lose their binding affinity significantly in mutants. The uncovering of VP35-dsRNA recognition mechanism will provide some insights for development of antiviral drug.

Synergistic Modification Induced Specific Recognition between Histone and TRIM24 via Fluctuation Correlation Network Analysis

Histone modification plays a key role in gene regulation and gene expression. TRIM24 as a histone reader can recognize histone modification. However the specific recognition mechanism between TRIM24 and histone modification is unsolved. Here, systems biology method of dynamics correlation network based on molecular dynamics simulation was used to answer the question. Our network analysis shows that the dynamics correlation network of H3K23ac is distinctly different from that of wild type and other modifications. A hypothesis of “synergistic modification induced recognition” is then proposed to link histone modification and TRIM24 binding. These observations were further confirmed from community analysis of networks with mutation and network perturbation. Finally, a possible recognition pathway is also identified based on the shortest path search for H3K23ac. Significant difference of recognition pathway was found among different systems due to methylation and acetylation modifications. The analysis presented here and other studies show that the dynamic network-based analysis might be a useful general strategy to study the biology of protein post-translational modification and associated recognition.

Conformational selection and induced fit for RNA polymerase and RNA/DNA hybrid backtracked recognition

RNA polymerase catalyzes transcription with a high fidelity. If DNA/RNA mismatch or DNA damage occurs downstream, a backtracked RNA polymerase can proofread this situation. However, the backtracked mechanism is still poorly understood. Here we have performed multiple explicit-solvent molecular dynamics (MD) simulations on bound and apo DNA/RNA hybrid to study backtracked recognition. MD simulations at room temperature suggest that specific electrostatic interactions play key roles in the backtracked recognition between the polymerase and DNA/RNA hybrid. Kinetics analysis at high temperature shows that bound and apo DNA/RNA hybrid unfold via a two-state process. Both kinetics and free energy landscape analyses indicate that bound DNA/RNA hybrid folds in the order of DNA/RNA contracting, the tertiary folding and polymerase binding. The predicted Φ-values suggest that C7, G9, dC12, dC15, and dT16 are key bases for the backtracked recognition of DNA/RNA hybrid. The average RMSD values between the bound structures and the corresponding apo ones and Kolmogorov-Smirnov (KS) P-test analyses indicate that the recognition between DNA/RNA hybrid and polymerase might follow an induced fit mechanism for DNA/RNA hybrid and conformation selection for polymerase. Furthermore, this method could be used to relative studies of specific recognition between nucleic acid and protein.

Theoretical perspectives on nonnative interactions and intrinsic disorder in protein folding and binding

The diverse biological functions of intrinsically disordered proteins (IDPs) have markedly raised our appreciation of protein conformational versatility, whereas the existence of energetically favorable yet functional detrimental nonnative interactions underscores the physical limitations of evolutionary optimization. Here we survey recent advances in using biophysical modeling to gain insight into experimentally observed nonnative behaviors and IDP properties. Simulations of IDP interactions to date focus mostly on coupled folding-binding, which follows essentially the same organizing principle as the local-nonlocal coupling mechanism in cooperative folding of monomeric globular proteins. By contrast, more innovative theories of electrostatic and aromatic interactions are needed for the conceptually novel but less-explored 'fuzzy' complexes in which the functionally bound IDPs remain largely disordered.

Kink turn sRNA folding upon L7Ae binding using molecular dynamics simulations

The kink-turn sRNA motif in archaea, whose combination with protein L7Ae initializes the assembly of small ribonucleoprotein particles (sRNPs), plays a key role in ribosome maturation and the translation process. Although many studies have been reported on this motif, the mechanism of sRNA folding coupled with protein binding is still poorly understood. Here, room and high temperature molecular dynamics (MD) simulations were performed on the complex of 25-nt kink-turn sRNA and L7Ae. The average RMSD values between the bound and corresponding apo structures and Kolmogorov-Smirnov P test analysis indicate that sRNA may follow an induced fit mechanism upon binding with L7Ae, both locally and globally. These conclusions are further supported by high-temperature unfolding kinetic analysis. Principal component analysis (PCA) found both closing and opening motions of the kink-turn sRNA. This might play a key role in the sRNP assembly and methylation catalysis. These combined computational methods can be used to study the specific recognition of other sRNAs and proteins.

Evolutionarily conserved and conformationally constrained short peptides might serve as DNA recognition elements in intrinsically disordered regions

Despite recent advances, it is yet not clear how intrinsically disordered regions in proteins recognize their targets without any defined structures. Short linear motifs had been proposed to mediate molecular recognition by disordered regions; however, the underlying structural prerequisite remains elusive. Moreover, the role of short linear motifs in DNA recognition has not been studied. We report a repertoire of short evolutionarily Conserved Recognition Elements (CoREs) in long intrinsically disordered regions, which have very distinct amino-acid propensities from those of known motifs, and exhibit a strong tendency to retain their three-dimensional conformations compared to adjacent regions. The majority of CoREs directly interact with the DNA in the available 3D structures, which is further supported by literature evidence, analyses of ΔΔG values of DNA-binding energies and threading-based prediction of DNA binding potential. CoREs were enriched in cancer-associated missense mutations, further strengthening their functional nature. Significant enrichment of glycines in CoREs and the preference of glycyl ϕ-Ψ values within the left-handed bridge range in the l-disallowed region of the Ramachandran plot suggest that Gly-to-nonGly mutations within CoREs might alter the backbone conformation and consequently the function, a hypothesis that we reconciled using available mutation data. We conclude that CoREs might serve as bait for DNA recognition by long disordered regions and that certain mutations in these peptides can disrupt their DNA binding potential and consequently the protein function. We further hypothesize that the preferred conformations of CoREs and of glycyl residues therein might play an important role in DNA binding. The highly ordered nature of CoREs hints at a therapeutic strategy to inhibit malicious molecular interactions using small molecules mimicking CoRE conformations.

Exploring the molecular basis of dsRNA recognition by Mss116p using molecular dynamics simulations and free-energy calculations

DEAD-box proteins are the largest family of helicase that are important in nearly all aspects of RNA metabolism. However, it is unclear how these proteins recognize and bind RNA. Here, we present a detailed analysis of the related DEAD-box protein Mss116p-RNA interaction, using molecular dynamics simulations with MM-GBSA calculations. The energetic analysis indicates that the two strands of double strands RNA (dsRNA) are recognized asymmetrically by Mss116p. The strand 1 of dsRNA provides the main binding affinity. Meanwhile, the nonpolar interaction provides the main driving force for the binding process. Although the contribution of polar interaction is small, it is vital in stabilizing the protein-RNA interaction. Compared with the wild type Mss116p, two studied mutants Q412A and D441A have obviously reduced binding free energies with dsRNA because of the decreasing of polar interaction. Three important residues Lys409, Arg415 and Arg438 lose their binding affinity significantly in mutants. In conclusion, these results complement previous experiments to advance comprehensive understanding of Mss116p-dsRNA interaction. The results also would provide support for the application of similar approaches to the understanding of other DEAD-box protein-RNA complexes.

Insights into the Binding of Intrinsically Disordered Proteins from Molecular Dynamics Simulation

Intrinsically disordered proteins (IDPs) are a class of protein that, in the native state, possess no well-defined secondary or tertiary structure, existing instead as dynamic ensembles of conformations. They are biologically important, with approximately 20% of all eukaryotic proteins disordered, and found at the heart of many biochemical networks. To fulfil their biological roles, many IDPs need to bind to proteins and/or nucleic acids. And while unstructured in solution, IDPs typically fold into a well-defined three-dimensional structure upon interaction with a binding partner. The flexibility and structural diversity inherent to IDPs makes this coupled folding and binding difficult to study at atomic resolution by experiment alone, and computer simulation currently offers perhaps the best opportunity to understand this process. But simulation of coupled folding and binding is itself extremely challenging; these molecules are large and highly flexible, and their binding partners, such as DNA or cyclins, are also often large. Therefore, their study requires either or both simplified representations and advanced enhanced sampling schemes. It is not always clear that existing simulation techniques, optimized for studying folded proteins, are well-suited to IDPs. In this article, we examine the progress that has been made in the study of coupled folding and binding using molecular dynamics simulation. We summarise what has been learnt, and examine the state of the art in terms of both methodologies and models. We also consider the lessons to be learnt from advances in other areas of simulation and highlight the issues that remain of be addressed.

Atomistic mechanism of microRNA translation upregulation via molecular dynamics simulations

MicroRNAs are endogenous 23–25 nt RNAs that play important gene-regulatory roles in animals and plants. Recently, miR369-3 was found to upregulate translation of TNFα mRNA in quiescent (G0) mammalian cell lines. Knock down and immunofluorescence experiments suggest that microRNA-protein complexes (with FXR1 and AGO2) are necessary for the translation upregulation. However the molecular mechanism of microRNA translation activation is poorly understood. In this study we constructed the microRNA-mRNA-AGO2-FXR1 quadruple complex by bioinformatics and molecular modeling, followed with all atom molecular dynamics simulations in explicit solvent to investigate the interaction mechanisms for the complex. A combined analysis of experimental and computational data suggests that AGO2-FXR1 complex relocalize microRNA:mRNA duplex to polysomes in G0. The two strands of dsRNA are then separated upon binding of AGO2 and FXR1. Finally, polysomes may improve the translation efficiency of mRNA. The mutation research confirms the stability of microRNA-mRNA-FXR1 and illustrates importance of key residue of Ile304. This possible mechanism can shed more light on the microRNA-dependent upregulation of translation.

Insight into the stability of cross-β amyloid fibril from VEALYL short peptide with molecular dynamics simulation

Amyloid fibrils are found in many fatal neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, type II diabetes, and prion disease. The VEALYL short peptide from insulin has been confirmed to aggregate amyloid-like fibrils. However, the aggregation mechanism of amyloid fibril is poorly understood. Here, we utilized molecular dynamics simulation to analyse the stability of VEALYL hexamer. The statistical results indicate that hydrophobic residues play key roles in stabilizing VEALYL hexamer. Single point and two linkage mutants confirmed that Val1, Leu4, and Tyr5 of VEALYL are key residues. The consistency of the results for the VEALYL oligomer suggests that the intermediate states might be trimer (3-0) and pentamer(3-2). These results can help us to obtain an insight into the aggregation mechanism of amyloid fibril. These methods can be used to study the stability of amyloid fibril from other short peptides.

Revealing interaction mode between HIV-1 protease and mannitol analog inhibitor

HIV protease is a key enzyme to play a key role in the HIV-1 replication cycle and control the maturation from HIV viruses to an infectious virion. HIV-1 protease has become an important target for anti-HIV-1 drug development. Here, we used molecular dynamics simulation to study the binding mode between mannitol derivatives and HIV-1 protease. The results suggest that the most active compound (M35) has more stable hydrogen bonds and stable native contacts than the less active one (M17). These mannitol derivatives might have similar interaction mode with HIV-1 protease. Then, 3D-QSAR was used to construct quantitative structure-activity models. The cross-validated q(2) values are found as 0.728 and 0.611 for CoMFA and CoMSIA, respectively. And the non-cross-validated r(2) values are 0.973 and 0.950. Nine test set compounds validate the model. The results show that this model possesses better prediction ability than the previous work. This model can be used to design new chemical entities and make quantitative prediction of the bioactivities for HIV-1 protease inhibitors before resorting to in vitro and in vivo experiment.