Manipulation of photosynthetic energy transfer by vibrational strong coupling.

Uncovering the mystery of efficient and directional energy transfer in photosynthetic organisms remains a critical challenge in quantum biology. Recent experimental evidence and quantum theory developments indicate the significance of quantum features of molecular vibrations in assisting photosynthetic energy transfer, which provides the possibility of manipulating the process by controlling molecular vibrations. Here, we propose and theoretically demonstrate efficient manipulation of photosynthetic energy transfer by using vibrational strong coupling between the vibrational state of a Fenna-Matthews-Olson (FMO) complex and the vacuum state of an optical cavity. Specifically, based on a full-quantum analytical model to describe the strong coupling effect between the optical cavity and molecular vibration, we realize efficient manipulation of energy transfer efficiency (from 58% to 92%) and energy transfer time (from 20 to 500 ps) in one branch of FMO complex by actively controlling the coupling strength and the quality factor of the optical cavity under both near-resonant and off-resonant conditions, respectively. Our work provides a practical scenario to manipulate photosynthetic energy transfer by externally interfering molecular vibrations via an optical cavity and a comprehensible conceptual framework for researching other similar systems.

In Silico Search for Drug Candidates Targeting the PAX8-PPARγ Fusion Protein in Thyroid Cancer.

The PAX8/PPARγ rearrangement, producing the PAX8-PPARγ fusion protein (PPFP), is thought to play an essential role in the oncogenesis of thyroid follicular tumors. To identify PPFP-targeted drug candidates and establish an early standard of care for thyroid tumors, we performed ensemble-docking-based compound screening. Specifically, we investigated the pocket structure that should be adopted to search for a promising ligand compound for the PPFP; the position of the ligand-binding pocket on the PPARγ side of the PPFP is similar to that of PPARγ; however, the shape is slightly different between them due to environmental factors. We developed a method for selecting a PPFP structure with a relevant pocket and high prediction accuracy for ligand binding. This method was validated using PPARγ, whose structure and activity values are known for many compounds. Then, we performed docking calculations to the PPFP for 97 drug or drug-like compounds registered in the DrugBank database with a thiazolidine backbone, which is one of the characteristics of ligands that bind well to PPARγ. Furthermore, the binding affinities of promising ligand candidates were estimated more reliably using the molecular mechanics Poisson-Boltzmann surface area method. Thus, we propose promising drug candidates for the PPFP with a thiazolidine backbone.

Holographic Brain Theory: Super-Radiance, Memory Capacity and Control Theory.

We investigate Quantum Electrodynamics corresponding to the holographic brain theory introduced by Pribram to describe memory in the human brain. First, we derive a super-radiance solution in Quantum Electrodynamics with non-relativistic charged bosons (a model of molecular conformational states of water) for coherent light sources of holograms. Next, we estimate memory capacity of a brain neocortex, and adopt binary holograms to manipulate optical information. Finally, we introduce a control theory to manipulate holograms involving biological water's molecular conformational states. We show how a desired waveform in holography is achieved in a hierarchical model using numerical simulations.

End-to-end protein-ligand complex structure generation with diffusion-based generative models.

BACKGROUND: Three-dimensional structures of protein-ligand complexes provide valuable insights into their interactions and are crucial for molecular biological studies and drug design. However, their high-dimensional and multimodal nature hinders end-to-end modeling, and earlier approaches depend inherently on existing protein structures. To overcome these limitations and expand the range of complexes that can be accurately modeled, it is necessary to develop efficient end-to-end methods. RESULTS: We introduce an equivariant diffusion-based generative model that learns the joint distribution of ligand and protein conformations conditioned on the molecular graph of a ligand and the sequence representation of a protein extracted from a pre-trained protein language model. Benchmark results show that this protein structure-free model is capable of generating diverse structures of protein-ligand complexes, including those with correct binding poses. Further analyses indicate that the proposed end-to-end approach is particularly effective when the ligand-bound protein structure is not available. CONCLUSION: The present results demonstrate the effectiveness and generative capability of our end-to-end complex structure modeling framework with diffusion-based generative models. We suppose that this framework will lead to better modeling of protein-ligand complexes, and we expect further improvements and wide applications.

Thermal conductivity and conductance of protein in aqueous solution: Effects of geometrical shape.

Considering the importance of elucidating the heat transfer in living cells, we evaluated the thermal conductivity κ and conductance G of hydrated protein through all-atom non-equilibrium molecular dynamics simulation. Extending the computational scheme developed in earlier studies for spherical protein to cylindrical one under the periodic boundary condition, we enabled the theoretical analysis of anisotropic thermal conduction and also discussed the effects of protein size correction on the calculated results. While the present results for myoglobin and green fluorescent protein (GFP) by the spherical model were in fair agreement with previous computational and experimental results, we found that the evaluations for κ and G by the cylindrical model, in particular, those for the longitudinal direction of GFP, were enhanced substantially, but still keeping a consistency with experimental data. We also studied the influence by salt addition of physiological concentration, finding insignificant alteration of thermal conduction of protein in the present case.

Remarked suppression of Aß42 protomer-protomer dissociation reaction elucidated by molecular dynamics simulation.

Multimeric protein complexes are molecular apparatuses to regulate biological systems and often determine their fate. Among proteins forming such molecular assemblies, amyloid proteins have drawn attention over a half-century since amyloid fibril formation of these proteins is supposed to be a common pathogenic cause for neurodegenerative diseases. This process is triggered by the accumulation of fibril-like aggregates, while the microscopic mechanisms are mostly elusive due to technical limitation of experimental methodologies in individually observing each of diverse aggregate species in the aqueous solution. We then addressed this problem by employing atomistic molecular dynamics simulations for the paradigmatic amyloid protein, amyloid-ß (Aß42 ). Seven different dimeric forms of oligomeric Aß42 fibril-like aggregate in aqueous solution, ranging from tetramer to decamer, were considered. We found additive effects of the size of these fibril-like aggregates on their thermodynamic stability and have clarified kinetic suppression of protomer-protomer dissociation reactions at and beyond the point of pentamer dimer formation. This observation was obtained from the specific combination of the Aß42 protomer structure and the physicochemical condition that we here examined, while it is worthwhile to recall that several amyloid fibrils take dimeric forms of their protomers. We could thus conclude that the stable formation of fibril-like protomer dimer should be involved in a turning point where rapid growth of amyloid fibrils is triggered.

Protein-ligand binding affinity prediction of cyclin-dependent kinase-2 inhibitors by dynamically averaged fragment molecular orbital-based interaction energy.

Fragment molecular orbital (FMO) method is a powerful computational tool for structure-based drug design, in which protein-ligand interactions can be described by the inter-fragment interaction energy (IFIE) and its pair interaction energy decomposition analysis (PIEDA). Here, we introduced a dynamically averaged (DA) FMO-based approach in which molecular dynamics simulations were used to generate multiple protein-ligand complex structures for FMO calculations. To assess this approach, we examined the correlation between the experimental binding free energies and DA-IFIEs of six CDK2 inhibitors whose net charges are zero. The correlation between the experimental binding free energies and snapshot IFIEs for X-ray crystal structures was R2  = 0.75. Using the DA-IFIEs, the correlation significantly improved to 0.99. When an additional CDK2 inhibitor with net charge of -1 was added, the DA FMO-based scheme with the dispersion energies still achieved R2  = 0.99, whereas R2 decreased to 0.32 employing all the energy terms of PIEDA.

Computational prediction of heteromeric protein complex disassembly order using hybrid Monte Carlo/molecular dynamics simulation.

The physicochemical entities comprising the biological phenomena in the cell form a network of biochemical reactions and the activity of such a network is regulated by multimeric protein complexes. Mass spectroscopy (MS) experiments and multimeric protein docking simulations based on structural bioinformatics techniques have revealed the molecular-level stoichiometry and static configuration of subcomplexes in their bound forms, thus revealing the subcomplex population and formation orders. Meanwhile, these methodologies are not designed to straightforwardly examine the temporal dynamics of multimeric protein assembly and disassembly, essential physicochemical properties to understand the functional expression mechanisms of proteins in the biological environment. To address this problem, we have developed an atomistic simulation in the framework of the hybrid Monte Carlo/molecular dynamics (hMC/MD) method and succeeded in observing the disassembly of a homomeric pentamer of the serum amyloid P component protein in an experimentally consistent order. In this study, we improved the hMC/MD method to examine the disassembly processes of the tryptophan synthase tetramer, a paradigmatic heteromeric protein complex in MS studies. We employed the likelihood-based selection scheme to determine a dissociation-prone subunit pair at every hMC/MD simulation cycle and achieved highly reliable predictions of the disassembly orders without a priori knowledge of the MS experiments and structural bioinformatics simulations. The success rate for the experimentally-observed disassembly order is over 0.9. We similarly succeeded in reliable predictions for three other tetrameric protein complexes. These achievements indicate the potential applicability of our hMC/MD approach as a general-purpose methodology to obtain microscopic and physicochemical insights into multimeric protein complex formation.

Interspecies Comparison of Interaction Energies between Photosynthetic Protein RuBisCO and 2CABP Ligand.

Ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) functions as the initial enzyme in the dark reactions of photosynthesis, catalyzing reactions that extract CO2 from the atmosphere and fix CO2 into organic compounds. RuBisCO is classified into four types (isoforms I-IV) according to sequence-based phylogenetic trees. Given its size, the computational cost of accurate quantum-chemical calculations for functional analysis of RuBisCO is high; however, recent advances in hardware performance and the use of the fragment molecular orbital (FMO) method have enabled the ab initio analyses of RuBisCO. Here, we performed FMO calculations on multiple structural datasets for various complexes with the 2'-carboxylarabinitol 1,5-bisphosphate (2CABP) ligand as a substrate analog and investigated whether phylogenetic relationships based on sequence information are physicochemically relevant as well as whether novel information unobtainable from sequence information can be revealed. We extracted features similar to the phylogenetic relationships found in sequence analysis, and in terms of singular value decomposition, we identified residues that strongly interacted with the ligand and the characteristics of the isoforms for each principal component. These results identified a strong correlation between phylogenetic relationships obtained by sequence analysis and residue interaction energies with the ligand. Notably, some important residues were located far from the ligand, making comparisons among species using only residues proximal to the ligand insufficient.

FMODB: The World's First Database of Quantum Mechanical Calculations for Biomacromolecules Based on the Fragment Molecular Orbital Method.

We developed the world's first web-based public database for the storage, management, and sharing of fragment molecular orbital (FMO) calculation data sets describing the complex interactions between biomacromolecules, named FMO Database (https://drugdesign.riken.jp/FMODB/). Each entry in the database contains relevant background information on how the data was compiled as well as the total energy of each molecular system and interfragment interaction energy (IFIE) and pair interaction energy decomposition analysis (PIEDA) values. Currently, the database contains more than 13 600 FMO calculation data sets, and a comprehensive search function implemented at the front-end. The procedure for selecting target proteins, preprocessing the experimental structures, construction of the database, and details of the database front-end were described. Then, we demonstrated a use of the FMODB by comparing IFIE value distributions of hydrogen bond, ion-pair, and XH/π interactions obtained by FMO method to those by molecular mechanics approach. From the comparison, the statistical analysis of the data provided standard reference values for the three types of interactions that will be useful for determining whether each interaction in a given system is relatively strong or weak compared to the interactions contained within the data in the FMODB. In the final part, we demonstrate the use of the database to examine the contribution of halogen atoms to the binding affinity between human cathepsin L and its inhibitors. We found that the electrostatic term derived by PIEDA greatly correlated with the binding affinities of the halogen containing cathepsin L inhibitors, indicating the importance of QM calculation for quantitative analysis of halogen interactions. Thus, the FMO calculation data in FMODB will be useful for conducting statistical analyses to drug discovery, for conducting molecular recognition studies in structural biology, and for other studies involving quantum mechanics-based interactions.

In silico modeling of PAX8-PPARγ fusion protein in thyroid carcinoma: influence of structural perturbation by fusion on ligand-binding affinity.

Paired box 8 (PAX8)-peroxisome proliferator-activated receptor γ (PPARγ) rearrangement is believed to play an important role in tumorigenesis of PAX8-PPARγ fusion protein (PPFP) thyroid carcinomas, while without establishing any standard treatment, including drugs. Although PPFP is a potential promising target for therapeutic agents, the three-dimensional (3D) structure and functions have not yet been experimentally elucidated. In this study, we aimed to construct the 3D structure of PPFP and to aid in the development of therapies that can target PPFP for thyroid carcinomas. The 3D structure of PPFP was constructed by homology modeling based on crystallographic structure data. To validate the modeled structure, we analyzed the thermal fluctuations by molecular dynamics simulations and predicted the physical properties using bioinformatic analyses. We found that the modeled structure was stable under hydrated conditions and had features indicating the actual existence of the structure. Furthermore, the binding free energies of the ligand rosiglitazone with PPARγ and PPFP were evaluated by the molecular mechanics-Poisson-Boltzmann surface area method. We found that rosiglitazone has different binding affinities for the same binding pockets of PPARγ and PPFP, and the optimal compound for PPFP can differ from that of PPARγ. This suggests the need for the development of drugs targeting PPFP that allow for the fusion, rather than focusing on the PPARγ side of PPFP and searching for the best compounds for that pocket. Our findings are expected to lead to the development of new therapies for thyroid tumors.

Elucidating microscopic events driven by GTP hydrolysis reaction in the Ras-GAP system with semi-reactive molecular dynamics simulations: the alternative role of a phosphate binding loop for mechanical energy storage.

ATPase and GTPase have been widely found as chemical energy-mechanical work transducers, whereas the physicochemical mechanisms are not satisfactorily understood. We addressed the problem by examining John Ross' conjecture that repulsive Coulomb interaction between ADP/GDP and inorganic phosphate (Pi) does the mechanical work upon the system. We effectively simulated the consequence of a GTP hydrolysis reaction in a complex system of Rat sarcoma (Ras) and GTPase activation protein (GAP) in the framework of classical molecular dynamics by switching force field parameters between the reactant and product systems. We then observed a ca. 5 kcal mol-1 increase of potential energy about the phosphate-binding loop (P-loop) in the Ras protein, indicating that the mechanical work generated via the GTP hydrolysis is converted into the local interaction energy and stored in the P-loop. Interestingly, this local energy storage in the P-loop depends on neither impulsive nor consecutive collisions of GDP and Pi with the P-loop. Instead, GTP-GDP conversion itself does work on the Ras system, elevating the potential energy. These observations encourage us to challenge a conjecture previously given by Ross. We assert that triphosphate nucleotide hydrolyses do mechanical work by producing emergent steric interaction accompanied by relaxation, namely, a shift of the biomolecular system to the non-equilibrium state on the reshaped potential energy landscape. Recalling the universality of the P-loop motif among GTPases and ATPases, the observations that we obtained through this study would progress the physicochemical understanding of the operating principles of GTP/ATP hydrolysis-driven biological nano-machines.

Improvement of the Force Field for ß-d-Glucose with Machine Learning.

While the construction of a dependable force field for performing classical molecular dynamics (MD) simulation is crucial for elucidating the structure and function of biomolecular systems, the attempts to do this for glycans are relatively sparse compared to those for proteins and nucleic acids. Currently, the use of GLYCAM06 force field is the most popular, but there have been a number of concerns about its accuracy in the systematic description of structural changes. In the present work, we focus on the improvement of the GLYCAM06 force field for ß-d-glucose, a simple and the most abundant monosaccharide molecule, with the aid of machine learning techniques implemented with the TensorFlow library. Following the pre-sampling over a wide range of configuration space generated by MD simulation, the atomic charge and dihedral angle parameters in the GLYCAM06 force field were re-optimized to accurately reproduce the relative energies of ß-d-glucose obtained by the density functional theory (DFT) calculations according to the structural changes. The validation for the newly proposed force-field parameters was then carried out by verifying that the relative energy errors compared to the DFT value were significantly reduced and that some inconsistencies with experimental (e.g., NMR) results observed in the GLYCAM06 force field were resolved relevantly.

Effective Static Approximation: A Fast and Reliable Tool for Warm-Dense Matter Theory.

We present an effective static approximation (ESA) to the local field correction (LFC) of the electron gas that enables highly accurate calculations of electronic properties like the dynamic structure factor S(q,ω), the static structure factor S(q), and the interaction energy v. The ESA combines the recent neural-net representation by T. Dornheim et al., [J. Chem. Phys. 151, 194104 (2019)JCPSA60021-960610.1063/1.5123013] of the temperature-dependent LFC in the exact static limit with a consistent large wave-number limit obtained from quantum Monte Carlo data of the on-top pair distribution function g(0). It is suited for a straightforward integration into existing codes. We demonstrate the importance of the LFC for practical applications by reevaluating the results of the recent x-ray Thomson scattering experiment on aluminum by Sperling et al. [Phys. Rev. Lett. 115, 115001 (2015)PRLTAO0031-900710.1103/PhysRevLett.115.115001]. We find that an accurate incorporation of electronic correlations in terms of the ESA leads to a different prediction of the inelastic scattering spectrum than obtained from state-of-the-art models like the Mermin approach or linear-response time-dependent density functional theory. Furthermore, the ESA scheme is particularly relevant for the development of advanced exchange-correlation functionals in density functional theory.

Fragment Molecular Orbital Based Interaction Analyses on COVID-19 Main Protease - Inhibitor N3 Complex (PDB ID: 6LU7).

The worldwide spread of COVID-19 (new coronavirus found in 2019) is an emergent issue to be tackled. In fact, a great amount of works in various fields have been made in a rather short period. Here, we report a fragment molecular orbital (FMO) based interaction analysis on a complex between the SARS-CoV-2 main protease (Mpro) and its peptide-like inhibitor N3 (PDB ID: 6LU7). The target inhibitor molecule was segmented into five fragments in order to capture site specific interactions with amino acid residues of the protease. The interaction energies were decomposed into several contributions, and then the characteristics of hydrogen bonding and dispersion stabilization were made clear. Furthermore, the hydration effect was incorporated by the Poisson-Boltzmann (PB) scheme. From the present FMO study, His41, His163, His164, and Glu166 were found to be the most important amino acid residues of Mpro in interacting with the inhibitor, mainly due to hydrogen bonding. A guideline for optimizations of the inhibitor molecule was suggested as well based on the FMO analysis.

Temperature relaxation in binary hard-sphere mixture system: Molecular dynamics and kinetic theory study.

Computational schemes to describe the temperature relaxation in the binary hard-sphere mixture system are given on the basis of molecular dynamics (MD) simulation and renormalized kinetic theory. Event-driven MD simulations are carried out for three model systems in which the initial temperatures and the ratios of diameter and mass of two components are different to study the temporal evolution of each component temperature in nanoscale molecular conditions mimicking those in living cells. On the other hand, the temperature changes of the two components are also described in terms of a mean-field kinetic theory with the correlation functions calculated in the Percus-Yevick approximation. The calculated results by both the computational approaches have shown fair agreement with each other, whereas slight deviations have been found in the temporal range of femto- to picoseconds when the initial temperatures of the two components are significantly different, such as 300 K vs 1000 K. This discrepancy can be ascribed to the fast intra-component temperature relaxation assumed in the kinetic theory, and its violation in the MD simulations can be evaluated in terms of the Kullback-Leibler divergence between the equilibrated Maxwell-Boltzmann distribution at each temperature and the actual non-equilibrium velocity distribution realized in the MD. Thus, the present analysis provides a quantitative basis for addressing the temperature inhomogeneities experimentally observed in nanoscale crowding conditions.

Pursuing origins of (poly)ethylene glycol-induced G-quadruplex structural modulations.

Molecular crowding conditions provided by high concentration of cosolutes are utilized for characterization of biomolecules in cell-mimicking environment and development of drug-delivery systems. In this context, (poly)ethylene glycols are often used for studying non-canonical DNA structures termed G-quadruplexes, which came into focus by emerging structural biology findings and new therapeutic drug design approaches. Recently, several reports were made arguing against using (poly)ethylene glycols in role of molecular crowding agents due to their direct impact on DNA G-quadruplex stability and topology. However, the available data on structural details underlying DNA interaction is very scarce and thus limits in-depth comprehension. Herein, structural and thermodynamic analyses were strategically combined to assess G-quadruplex-cosolute interactions and address previously reported variances regarding the driving forces of G-rich DNA structural transformations under molecular crowding conditions. With the use of complementary (CD, NMR and UV) spectroscopic methods and model approach we characterized DNA G-quadruplex in the presence of the smallest and one of the largest typically used (poly)ethylene glycols. Dehydration effect is the key contributor to ethylene-glycol-induced increased stability of the G-quadruplex, which is in the case of the large cosolute mainly guided by the subtle direct interactions between PEG 8000 and the outer G-quartet regions.

Nanoscale Quantum Thermal Conductance at Water Interface: Green's Function Approach Based on One-Dimensional Phonon Model.

We have derived the fundamental formula of phonon transport in water for the evaluation of quantum thermal conductance by using a one-dimensional phonon model based on the nonequilibrium Green's function method. In our model, phonons are excited as quantum waves from the left or right reservoir and propagate from left to right of H 2 O layer or vice versa. We have assumed these reservoirs as being of periodic structures, whereas we can also model the H 2 O sandwiched between these reservoirs as having aperiodic structures of liquid containing N water molecules. We have extracted the dispersion curves from the experimental absorption spectra of the OH stretching and intermolecular modes of water molecules, and calculated phonon transmission function and quantum thermal conductance. In addition, we have simplified the formulation of the transmission function by employing a case of one water molecule (N=1). From this calculation, we have obtained the characteristic that the transmission probability is almost unity at the frequency bands of acoustic and optical modes, and the transmission probability vanishes by the phonon attenuation reflecting the quantum tunnel effect outside the bands of these two modes. The classical limit of the thermal conductance calculated by our formula agreed with the literature value (order of 10 - 10 W/K) in high temperature regime (>300 K). The present approach is powerful enough to be applicable to molecular systems containing proteins as well, and to evaluate their thermal conductive characteristics.

New Modified Deoxythymine with Dibranched Tetraethylene Glycol Stabilizes G-Quadruplex Structures.

Methods for stabilizing G-quadruplex formation is a promising therapeutic approach for cancer treatment and other biomedical applications because stable G-quadruplexes efficiently inhibit biological reactions. Oligo and polyethylene glycols are promising biocompatible compounds, and we have shown that linear oligoethylene glycols can stabilize G-quadruplexes. Here, we developed a new modified deoxythymine with dibranched or tribranched tetraethylene glycol (TEG) and incorporated these TEG-modified deoxythymines into a loop region that forms an antiparallel G-quadruplex. We analyzed the stability of the modified G-quadruplexes, and the results showed that the tribranched TEG destabilized G-quadruplexes through entropic contributions, likely through steric hindrance. Interestingly, the dibranched TEG modification increased G-quadruplex stability relative to the unmodified DNA structures due to favorable enthalpic contributions. Molecular dynamics calculations suggested that dibranched TEG interacts with the G-quadruplex through hydrogen bonding and CH-π interactions. Moreover, these branched TEG-modified deoxythymine protected the DNA oligonucleotides from degradation by various nucleases in human serum. By taking advantage of the unique interactions between DNA and branched TEG, advanced DNA materials can be developed that affect the regulation of DNA structure.

Ab initio molecular dynamics study of prebiotic production processes of organic compounds at meteorite impacts on ocean.

Recent experiments concerning prebiotic materials syntheses suggest that the iron-bearing meteorite impacts on ocean during Late Heavy Bombardment provided abundant organic compounds associated with biomolecules such as amino acids and nucleobases. However, the molecular mechanism of a series of chemical reactions to produce such compounds is not well understood. In this study, we simulate the shock compression state of a meteorite impact for a model system composed of CO2 , H2 O, and metallic iron slab by ab initio molecular dynamics combined with multiscale shock technique, and clarify possible elementary reaction processes up to production of organic compounds. The reactions included not only pathways similar to the Fischer-Tropsch process known as an important hydrocarbon synthesis in many planetary processes but also those resulting in production of a carboxylic acid. It is also found that bicarbonate ions formed from CO2 and H2 O participated in some forms in most of these observed elementary reaction processes. These findings would deepen the understanding of the full range of chemical reactions that could occur in the meteorite impact events. © 2018 Wiley Periodicals, Inc.