The luciferase-based in vivo protein-protein interaction assay revealed that CHK1 promotes PP2A and PME-1 interaction.

Protein phosphatase 2A (PP2A) is an essential serine/threonine protein phosphatase, and its dysfunction is involved in the onset of cancer and neurodegenerative disorders. PP2A functions as a trimeric holoenzyme whose composition is regulated by the methyl-esterification (methylation) of the PP2A catalytic subunit (PP2Ac). Protein phosphatase methylesterase-1 (PME-1) is the sole PP2Ac methylesterase, and the higher PME-1 expression is observed in various cancer and neurodegenerative diseases. Apart from serving as a methylesterase, PME-1 acts as a PP2A inhibitory protein, binding directly to PP2Ac and suppressing its activity. The intricate function of PME-1 hinders drug development by targeting the PME-1/PP2Ac axis. This study applied the NanoBiT system, a bioluminescence-based protein interaction assay, to elucidate the molecular mechanism that modulates unknown PME-1/PP2Ac protein-protein interaction (PPI). Compound screening identified that the CHK1 inhibitors inhibited PME-1/PP2Ac association without affecting PP2Ac methylation levels. CHK1 directly phosphorylates PP2Ac to promote PME-1 association. Phospho-mass spectrometry identified multiple phospho-sites on PP2Ac, including the Thr219, that affect PME-1 interaction. An anti-phospho-Thr219 PP2Ac antibody was generated and showed that CHK1 regulates the phosphorylation levels of this site in cells. On the contrary, in vitro phosphatase assay showed that CHK1 is the substrate of PP2A, and PME-1 hindered PP2A-mediated dephosphorylation of CHK1. Our data provides novel insights into the molecular mechanisms governing the PME-1/PP2Ac PPI and the triad relationship between PP2A, PME-1, and CHK1.

Interfacial Layer Breaker: A Violation of Stokes' Law in High-Speed Atomic Force Microscope Flows.

Structured water near surfaces is important in nonclassical crystallization, biomineralization, and restructuring of cellular membranes. In addition to equilibrium structures, studied by atomic force microscopy (AFM), high-speed AFM (H-S AFM) can now detect piconewton forces in microseconds. With increasing speeds and decreasing tip diameters, there is a danger that continuum water models will not hold, and molecular dynamic (MD) simulations would be needed for accurate predictions. MD simulations, however, can only evolve over tens of nanoseconds due to memory and computational efficiency/speed limitations, so new methods are needed to bridge the gap. Here, we report a hybrid, multiscale simulation method, which can bridge the size and time scale gaps to existing experiments. Structured water is studied between a moving silica AFM colloidal tip and a cleaved mica surface. The computational domain includes 1,472,766 atoms. To mimic the effect of long-range hydrodynamic forces occurring in water, when moving the AFM tip at speeds from 5 × 10-7 to 30 m/s, a hybrid multiscale method with local atomistic resolution is used, which serves as an effective open-domain boundary condition. The multiscale simulation is thus equivalent to using a macroscopically large computational domain with equilibrium boundary conditions. Quantification of the drag force shows the breaking of continuum behavior. Nonmonotonic dependence on both the tip speed and distance from the surface implies breaking of the hydration layer around the moving tip at time scales smaller than water cluster formation and strong water compressibility effects at the highest speeds.

Constant pH molecular dynamics of porcine circovirus 2 capsid protein reveals a mechanism for capsid assembly.

Spatiotemporal regulation of viral capsid assembly ensures the selection of the viral genome for encapsidation. The porcine circovirus 2 is the smallest autonomously replicating pathogenic virus, yet how PCV2 capsid assembly is regulated to occur within the nucleus remains unknown. We report that pure PCV2 capsid proteins, in the absence of nucleic acids, require acidic conditions to assemble into empty capsids in vitro. By employing constant pH replica exchange molecular dynamics, we unveil the atomistic mechanism of pH-dependency for capsid assembly. The results show that an appropriate protonation configuration for a cluster of acidic amino acids is necessary to appropriately position the GH-loop for driving the capsid assembly. We demonstrate that assembly is prohibited at neutral pH because deprotonation of these residues results in their electrostatic repulsion, shifting the GH-loop to a position incompatible with capsid assembly. We propose that encapsulation of nucleic acids overcomes this repulsion to suitably position the GH-loop. Our findings provide the first atomic resolution mechanism of capsid assembly regulation. These findings are useful for the development of therapeutics that inhibit PCV2 self-assembly.

Molecular Dynamics Study of Conformational Changes of Tankyrase 2 Binding Subsites upon Ligand Binding.

The interactions between proteins and ligands are involved in various biological functions. While experimental structures provide key static structural information of ligand-unbound and ligand-bound proteins, dynamic information is often insufficient for understanding the detailed mechanism of protein-ligand binding. Here, we studied the conformational changes of the tankyrase 2 binding pocket upon ligand binding using molecular dynamics simulations of the ligand-unbound and ligand-bound proteins. The ligand-binding pocket has two subsites: the nicotinamide and adenosine subsite. Comparative analysis of these molecular dynamics trajectories revealed that the conformational change of the ligand-binding pocket was characterized by four distinct conformations of the ligand-binding pocket. Two of the four conformations were observed only in molecular dynamics simulations. We found that the pocket conformational change on ligand binding was based on the connection between the nicotinamide and adenosine subsites that are located adjacently in the pocket. From the analysis, we proposed the protein-ligand binding mechanism of tankyrase 2. Finally, we discussed the computational prediction of the ligand binding pose using the tankyrase 2 structures obtained from the molecular dynamics simulations.

Theoretical insights into the DNA repair function of Arabidopsis thaliana cryptochrome-DASH.

Following the discovery of cryptochrome-DASH (CRYD) as a new type of blue-light receptor cryptochrome, theoretical and experimental findings on CRYD have been reported. Early studies identified CRYD as highly homologous to the DNA repair enzyme photolyases (PLs), suggesting the involvement of CRYD in DNA repair. However, an experimental study reported that CRYD does not exhibit DNA repair activity in vivo. Successful PL-mediated DNA repair requires: (i) the recognition of UV-induced DNA lesions and (ii) an electron transfer reaction. If either of them is inefficient, the DNA repair activity will be low. To elucidate the functional differences between CRYD and PL, we theoretically investigated the electron transfer reactivity and DNA binding affinity of CRYD and also performed supplementary experiments. The average electronic coupling matrix elements value for Arabidopsis thaliana CRYD (AtCRYD) was estimated to be 5.3 meV, comparable to that of Anacystis nidulans cyclobutane pyrimidine dimer PLs (AnPL) at 4.5 meV, indicating similar electron transfer reactivities. We also confirmed the DNA repair activity of AtCRYD for UV-damaged single-stranded DNA by the experimental analysis. In addition, we investigated the dynamic behavior of AtCRYD and AnPL in complex with double-stranded DNA using molecular dynamics simulations and observed the formation of a transient salt bridge between protein and DNA in AtCRYD, in contrast to AnPL in which it was formed stably. We suggested that the instability of the salt bridge between protein and DNA will lead to reduced DNA binding affinity for AtCRYD.

Drug binding dynamics of the dimeric SARS-CoV-2 main protease, determined by molecular dynamics simulation.

We performed molecular dynamics simulation of the dimeric SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) main protease (Mpro) to examine the binding dynamics of small molecular ligands. Seven HIV inhibitors, darunavir, indinavir, lopinavir, nelfinavir, ritonavir, saquinavir, and tipranavir, were used as the potential lead drugs to investigate access to the drug binding sites in Mpro. The frequently accessed sites on Mpro were classified based on contacts between the ligands and the protein, and the differences in site distributions of the encounter complex were observed among the ligands. All seven ligands showed binding to the active site at least twice in 28 simulations of 200 ns each. We further investigated the variations in the complex structure of the active site with the ligands, using microsecond order simulations. Results revealed a wide variation in the shapes of the binding sites and binding poses of the ligands. Additionally, the C-terminal region of the other chain often interacted with the ligands and the active site. Collectively, these findings indicate the importance of dynamic sampling of protein-ligand complexes and suggest the possibilities of further drug optimisations.

Large-scale all-atom molecular dynamics alanine-scanning of IAPP octapeptides provides insights into the molecular determinants of amyloidogenicity.

In order to investigate the early phase of the amyloid formation by the short amyloidogenic octapeptide sequence ('NFGAILSS') derived from IAPP, we carried out a 100ns all-atom molecular dynamics (MD) simulations of systems that contain 27 peptides and over 30,000 water molecules. The large-scale calculations were performed for the wild type sequence and seven alanine-scanned sequences using AMBER 8.0 on RIKEN's special purpose MD-GRAPE3 supercomputer, using the all-atom point charge force field ff99, which do not favor ß-structures. Large peptide clusters (size 18-26 mers) were observed for all simulations, and our calculations indicated that isoleucine at position 5 played important role in the formation of ß-rich clusters. In the oligomeric state, the wild type and the S7A sequences had the highest ß-structure content (~14%), as calculated by DSSP, in line with experimental observations, whereas I5A and G3A had the highest helical content (~20%). Importantly, the ß-structure preferences of wild type IAPP originate from its association into clusters and are not intrinsic to its sequence. Altogether, the results of this first large-scale, multi-peptide all-atom molecular dynamics simulation appear to provide insights into the mechanism of amyloidogenic and non-amyloidogenic oligomers that mainly corroborate previous experimental observations.

Use of the Multilayer Fragment Molecular Orbital Method to Predict the Rank Order of Protein-Ligand Binding Affinities: A Case Study Using Tankyrase 2 Inhibitors.

In computational drug discovery, ranking a series of compound analogues in the order that is consistent with the experimental binding affinities remains a challenge. Many of the computational methods available for evaluating binding affinities have adopted molecular mechanics (MM)-based force fields, although they cannot completely describe protein-ligand interactions. By contrast, quantum mechanics (QM) calculations play an important role in understanding the protein-ligand interactions; however, their huge computational costs hinder their application in drug discovery. In this study, we have evaluated the ability to rank the binding affinities of tankyrase 2 ligands by combining both MM and QM calculations. Our computational approach uses the protein-ligand binding energies obtained from a cost-effective multilayer fragment molecular orbital (MFMO) method combined with the solvation energy obtained from the MM-Poisson-Boltzmann/surface area (MM-PB/SA) method to predict the binding affinity. This approach enabled us to rank tankyrase 2 inhibitor analogues, outperforming several MM-based methods, including rescoring by molecular docking and the MM-PB/SA method alone. Our results show that this computational approach using the MFMO method is a promising tool for predicting the rank order of the binding affinities of inhibitor analogues.

All-Atom Molecular Dynamics Simulations of Entire Virus Capsid Reveal the Role of Ion Distribution in Capsid's Stability.

Present experimental methods do not have sufficient resolution to investigate all processes in virus particles at atomistic details. We report the results of molecular dynamics simulations and analyze the connection between the number of ions inside an empty capsid of PCV2 virus and its stability. We compare the crystallographic structures of the capsids with unresolved N-termini and without them in realistic conditions (room temperature and aqueous solution) and show that the structure is preserved. We find that the chloride ions play a key role in the stability of the capsid. A low number of chloride ions results in loss of the native icosahedral symmetry, while an optimal number of chloride ions create a neutralizing layer next to the positively charged inner surface of the capsid. Understanding the dependence of the capsid stability on the distribution of the ions will help clarify the details of the viral life cycle that is ultimately connected to the role of packaged viral genome inside the capsid.

Evaluation of protein-ligand affinity prediction using steered molecular dynamics simulations.

In computational drug design, ranking a series of compound analogs in a manner that is consistent with experimental affinities remains a challenge. In this study, we evaluated the prediction of protein-ligand binding affinities using steered molecular dynamics simulations. First, we investigated the appropriate conditions for accurate predictions in these simulations. A conic harmonic restraint was applied to the system for efficient sampling of work values on the ligand unbinding pathway. We found that pulling velocity significantly influenced affinity predictions, but that the number of collectable trajectories was less influential. We identified the appropriate pulling velocity and collectable trajectories for binding affinity predictions as 1.25 Å/ns and 100, respectively, and these parameters were used to evaluate three target proteins (FK506 binding protein, trypsin, and cyclin-dependent kinase 2). For these proteins using our parameters, the accuracy of affinity prediction was higher and more stable when Jarzynski's equality was employed compared with the second-order cumulant expansion equation of Jarzynski's equality. Our results showed that steered molecular dynamics simulations are effective for predicting the rank order of ligands; thus, they are a potential tool for compound selection in hit-to-lead and lead optimization processes.

A pre-metazoan origin of the CRK gene family and co-opted signaling network.

CRK and CRKL adapter proteins play essential roles in development and cancer through their SRC homology 2 and 3 (SH2 and SH3) domains. To gain insight into the origin of their shared functions, we have investigated their evolutionary history. We propose a term, crk/crkl ancestral (crka), for orthologs in invertebrates before the divergence of CRK and CRKL in the vertebrate ancestor. We have isolated two orthologs expressed in the choanoflagellate Monosiga brevicollis, a unicellular relative to the metazoans. Consistent with its highly-conserved three-dimensional structure, the SH2 domain of M. brevicollis crka1 can bind to the mammalian CRK/CRKL SH2 binding consensus phospho-YxxP, and to the SRC substrate/focal adhesion protein BCAR1 (p130CAS) in the presence of activated SRC. These results demonstrate an ancient origin of the CRK/CRKL SH2-target recognition specificity. Although BCAR1 orthologs exist only in metazoans as identified by an N-terminal SH3 domain, YxxP motifs, and a C-terminal FAT-like domain, some pre-metazoan transmembrane proteins include several YxxP repeats in their cytosolic region, suggesting that they are remotely related to the BCAR1 substrate domain. Since the tyrosine kinase SRC also has a pre-metazoan origin, co-option of BCAR1-related sequences may have rewired the crka-dependent network to mediate adhesion signals in the metazoan ancestor.

Fluorogenic Enhancement of an in Vitro-Selected Peptide Ligand by Replacement of a Fluorescent Group.

To prepare a fluorogenic peptide ligand which binds to an arbitrary target, we previously succeeded in seeking a fluorogenic ligand to calmodulin using in vitro selection. In this study the environment-sensitive fluorescent group in the selected peptide ligand was replaced with other fluorescent groups to find the possibility to increase the fluorogenic activity. Surface plasmon resonance measurement exhibited that the binding affinity was held even after the replacement. However, the replacement significantly affected the fluorogenic activity. It depended on the kind of incorporated fluorophors and linker length. As a result, the incorporation of 4-N,N-dimethylamino-1,8-naphthalimide enhanced the fluorescence intensity over 100-fold in the presence of target calcium-bound calmodulin. This study demonstrated that the functionality of in vitro selected peptide can be tuned with keeping the binding affinity.

All-atom molecular dynamics analysis of multi-peptide systems reproduces peptide solubility in line with experimental observations.

In order to investigate the contribution of individual amino acids to protein and peptide solubility, we carried out 100 ns molecular dynamics (MD) simulations of 10(6) Å(3) cubic boxes containing ~3 × 10(4) water molecules and 27 tetra-peptides regularly positioned at 23 Å from each other and composed of a single amino acid type for all natural amino acids but cysteine and glycine. The calculations were performed using Amber with a standard force field on a special purpose MDGRAPE-3 computer, without introducing any "artificial" hydrophobic interactions. Tetra-peptides composed of I, V, L, M, N, Q, F, W, Y, and H formed large amorphous clusters, and those containing A, P, S, and T formed smaller ones. Tetra-peptides made of D, E, K, and R did not cluster at all. These observations correlated well with experimental solubility tendencies as well as hydrophobicity scales with correlation coefficients of 0.5 to > 0.9. Repulsive Coulomb interactions were dominant in ensuring high solubility, whereas both Coulomb and van der Waals (vdW) energies contributed to the aggregations of low solubility amino acids. Overall, this very first all-atom molecular dynamics simulation of a multi-peptide system appears to reproduce the basic properties of peptide solubility, essentially in line with experimental observations.

Assessment and acceleration of binding energy calculations for protein-ligand complexes by the fragment molecular orbital method.

In the field of drug discovery, it is important to accurately predict the binding affinities between target proteins and drug applicant molecules. Many of the computational methods available for evaluating binding affinities have adopted molecular mechanics-based force fields, although they cannot fully describe protein-ligand interactions. A noteworthy computational method in development involves large-scale electronic structure calculations. Fragment molecular orbital (FMO) method, which is one of such large-scale calculation techniques, is applied in this study for calculating the binding energies between proteins and ligands. By testing the effects of specific FMO calculation conditions (including fragmentation size, basis sets, electron correlation, exchange-correlation functionals, and solvation effects) on the binding energies of the FK506-binding protein and 10 ligand complex molecule, we have found that the standard FMO calculation condition, FMO2-MP2/6-31G(d), is suitable for evaluating the protein-ligand interactions. The correlation coefficient between the binding energies calculated with this FMO calculation condition and experimental values is determined to be R = 0.77. Based on these results, we also propose a practical scheme for predicting binding affinities by combining the FMO method with the quantitative structure-activity relationship (QSAR) model. The results of this combined method can be directly compared with experimental binding affinities. The FMO and QSAR combined scheme shows a higher correlation with experimental data (R = 0.91). Furthermore, we propose an acceleration scheme for the binding energy calculations using a multilayer FMO method focusing on the protein-ligand interaction distance. Our acceleration scheme, which uses FMO2-HF/STO-3G:MP2/6-31G(d) at R(int) = 7.0 Å, reduces computational costs, while maintaining accuracy in the evaluation of binding energy.

Single-molecule motions of MHC class II rely on bound peptides.

The major histocompatibility complex (MHC) class II protein can bind peptides of different lengths in the region outside the peptide-binding groove. Peptide-flanking residues (PFRs) contribute to the binding affinity of the peptide for MHC and change the immunogenicity of the peptide/MHC complex with regard to T cell receptor (TCR). The mechanisms underlying these phenomena are currently unknown. The molecular flexibility of the peptide/MHC complex may be an important determinant of the structures recognized by certain T cells. We used single-molecule x-ray analysis (diffracted x-ray tracking (DXT)) and fluorescence anisotropy to investigate these mechanisms. DXT enabled us to monitor the real-time Brownian motion of the peptide/MHC complex and revealed that peptides without PFRs undergo larger rotational motions than peptides with PFRs. Fluorescence anisotropy further revealed that peptides without PFRs exhibit slightly larger motions on the nanosecond timescale. These results demonstrate that peptides without PFRs undergo dynamic motions in the groove of MHC and consequently are able to assume diverse structures that can be recognized by T cells.

Visualising and controlling the flow in biomolecular systems at and between multiple scales: from atoms to hydrodynamics at different locations in time and space.

A novel framework for modelling biomolecular systems at multiple scales in space and time simultaneously is described. The atomistic molecular dynamics representation is smoothly connected with a statistical continuum hydrodynamics description. The system behaves correctly at the limits of pure molecular dynamics (hydrodynamics) and at the intermediate regimes when the atoms move partly as atomistic particles, and at the same time follow the hydrodynamic flows. The corresponding contributions are controlled by a parameter, which is defined as an arbitrary function of space and time, thus, allowing an effective separation of the atomistic 'core' and continuum 'environment'. To fill the scale gap between the atomistic and the continuum representations our special purpose computer for molecular dynamics, MDGRAPE-4, as well as GPU-based computing were used for developing the framework. These hardware developments also include interactive molecular dynamics simulations that allow intervention of the modelling through force-feedback devices.

A new set of atomic radii for accurate estimation of solvation free energy by Poisson-Boltzmann solvent model.

The Poisson-Boltzmann implicit solvent (PB) is widely used to estimate the solvation free energies of biomolecules in molecular simulations. An optimized set of atomic radii (PB radii) is an important parameter for PB calculations, which determines the distribution of dielectric constants around the solute. We here present new PB radii for the AMBER protein force field to accurately reproduce the solvation free energies obtained from explicit solvent simulations. The presented PB radii were optimized using results from explicit solvent simulations of the large systems. In addition, we discriminated PB radii for N- and C-terminal residues from those for nonterminal residues. The performances using our PB radii showed high accuracy for the estimation of solvation free energies at the level of the molecular fragment. The obtained PB radii are effective for the detailed analysis of the solvation effects of biomolecules.

Two novel ALK mutations mediate acquired resistance to the next-generation ALK inhibitor alectinib.

PURPOSE: The first-generation ALK tyrosine kinase inhibitor (TKI) crizotinib is a standard therapy for patients with ALK-rearranged non-small cell lung cancer (NSCLC). Several next-generation ALK-TKIs have entered the clinic and have shown promising activity in crizotinib-resistant patients. As patients still relapse even on these next-generation ALK-TKIs, we examined mechanisms of resistance to the next-generation ALK-TKI alectinib and potential strategies to overcome this resistance. EXPERIMENTAL DESIGN: We established a cell line model of alectinib resistance, and analyzed a resistant tumor specimen from a patient who had relapsed on alectinib. We developed Ba/F3 models harboring alectinib-resistant ALK mutations and evaluated the potency of other next-generation ALK-TKIs in these models. We tested the antitumor activity of the next-generation ALK-TKI ceritinib in the patient with acquired resistance to alectinib. To elucidate structure-activity relationships of ALK mutations, we performed computational thermodynamic simulation with MP-CAFEE. RESULTS: We identified a novel V1180L gatekeeper mutation from the cell line model and a second novel I1171T mutation from the patient who developed resistance to alectinib. Both ALK mutations conferred resistance to alectinib as well as to crizotinib, but were sensitive to ceritinib and other next-generation ALK-TKIs. Treatment of the patient with ceritinib led to a marked response. Thermodynamics simulation suggests that both mutations lead to distinct structural alterations that decrease the binding affinity with alectinib. CONCLUSIONS: We have identified two novel ALK mutations arising after alectinib exposure that are sensitive to other next-generation ALK-TKIs. The ability of ceritinib to overcome alectinib-resistance mutations suggests a potential role for sequential therapy with multiple next-generation ALK-TKIs.

MDGRAPE-4: a special-purpose computer system for molecular dynamics simulations.

We are developing the MDGRAPE-4, a special-purpose computer system for molecular dynamics (MD) simulations. MDGRAPE-4 is designed to achieve strong scalability for protein MD simulations through the integration of general-purpose cores, dedicated pipelines, memory banks and network interfaces (NIFs) to create a system on chip (SoC). Each SoC has 64 dedicated pipelines that are used for non-bonded force calculations and run at 0.8 GHz. Additionally, it has 65 Tensilica Xtensa LX cores with single-precision floating-point units that are used for other calculations and run at 0.6 GHz. At peak performance levels, each SoC can evaluate 51.2 G interactions per second. It also has 1.8 MB of embedded shared memory banks and six network units with a peak bandwidth of 7.2 GB s(-1) for the three-dimensional torus network. The system consists of 512 (8×8×8) SoCs in total, which are mounted on 64 node modules with eight SoCs. The optical transmitters/receivers are used for internode communication. The expected maximum power consumption is 50 kW. While MDGRAPE-4 software has still been improved, we plan to run MD simulations on MDGRAPE-4 in 2014. The MDGRAPE-4 system will enable long-time molecular dynamics simulations of small systems. It is also useful for multiscale molecular simulations where the particle simulation parts often become bottlenecks.

A fluorogenic peptide probe developed by in vitro selection using tRNA carrying a fluorogenic amino acid.

A peptide that binds and emits fluorescence in response to conformational change in a target protein was developed by in vitro selection using tRNA carrying a fluorogenic amino acid. This technology could prove to be useful for the development of separation-free immunoassays and bio-imaging analyses.