Biology subjects

Kurisaki, I.

Publications and source records attributed to Kurisaki, I..

8 recordsLinked to original sources

bioRxiv2026

Atomistic simulation study reveals transduction of mechanical work generated by ATP hydrolysis onto myosin II functional loops

Myosin II is a paradigm of biological molecular energy transducers that convert the chemical energy of ATP, via hydrolysis, into mechanical work with high efficiency in living cells. The physicochemical mechanisms underlying energy conversion by myosin II have been extensively investigated. However, a remaining challenge concerns the initial stage of the ATP hydrolysis cycle, specifically the conversion of ATP-to-ADP:Pi, because of technical difficulties in directly and seamlessly observing atomic trajectories during this early step and the subsequent processes. Here, we simulate the consequences of the chemical reaction by switching force field parameters between reactant and product systems within classical molecular dynamics simulations. We consider two possible ATP hydrolysis mechanisms in which either singly protonated (Pi{superscript 2}-) or doubly protonated (Pi-) inorganic phosphate is produced. Our results indicate that, in both Pi-generating processes, the kinetic energy supplied by conversion of ATP-to-ADP:Pi increases only transiently, whereas myosin functional loops store several kcal/mol of potential energy. Meanwhile, the amount of potential energy stored in the Pi{superscript 2}--producing reaction is approximately five-fold larger than that in the Pi--producing reaction. Our analysis indicates that this difference emerges when ATP-derived mechanical work is transmitted into the functional loops via rearrangement of intermolecular hydrogen bonds with the hydrolysis products. Notably, these steric interactions remain stably established even when the kinetic energy input associated with ATP-to-ADP:Pi conversion is actively quenched. We therefore propose that transient storage of ATP-derived mechanical work as atomic-scale conformational strain within myosin molecules constitutes a critical step for efficient conversion of ATP chemical energy into mechanical work under conditions of intracellular thermal noise. SignificanceMyosin II converts chemical energy released by ATP hydrolysis into mechanical work with exceptionally high efficiency, even in the presence of substantial thermal fluctuations in living systems. It has long been proposed that release of inorganic phosphate (Pi) from myosin II is a critical step for efficient energy transfer. However, this prevailing view has been challenged by recent state-of-the-art experimental observations, necessitating a reexamination of the chemical steps responsible for ATP-derived energy storage. Here, we employ atomistic molecular dynamics simulations specifically designed to capture key aspects of ATP hydrolysis. We demonstrate that ATP hydrolysis increases the potential energy of myosin II functional loops while Pi remains bound, and that this increase occurs independently of heat release associated with the reaction. Together, these findings identify an alternative mechanism for energy retention and emphasize the intrinsic robustness of myosin II as a highly efficient molecular motor.

biophysics↗

bioRxiv2025

Blind Prediction of Complex Water and Ion Ensembles Around RNA in CASP16

Biomolecules rely on water and ions for stable folding, but these interactions are often transient, dynamic, or disordered and thus hidden from experiments and evaluation challenges that represent biomolecules as single, ordered structures. Here, we compare blindly predicted ensembles of water and ion structure to the cryo-EM densities observed around the Tetrahymena ribozyme at 2.2-2.3 [A] resolution, collected through target R1260 in the CASP16 competition. 26 groups participated in this solvation cryo-ensemble prediction challenge, submitting over 350 million atoms in total, offering the first opportunity to compare blind predictions of dynamic solvent shell ensembles to cryo-EM density. Predicted atomic ensembles were converted to density through local alignment and these densities were compared to the cryo-EM densities using Pearson correlation, Spearman correlation, mutual information, and precision-recall curves. These predictions show that an ensemble representation is able to capture information of transient or dynamic water and ions better than traditional atomic models, but there remains a large accuracy gap to the performance ceiling set by experimental uncertainty. Overall, molecular dynamics approaches best matched the cryo-EM density, with blind predictions from bussilab_plain_md, SoutheRNA, bussilab_replex, coogs2, and coogs3 outperforming the baseline molecular dynamics prediction. This study indicates that simulations of water and ions can be quantitatively evaluated with cryo-EM maps. We propose that further community-wide blind challenges can drive and evaluate progress in modeling water, ions and other previously hidden components of biomolecular systems.

biophysics↗

bioRxiv2025

Deep learning generates apo RNA conformations with cryptic ligand binding site

RNA plays vital roles in diverse biological processes and represents an attractive class of therapeutic targets. In particular, cryptic ligand-binding sites--absent in apo structures but formed upon conformational rearrangement--offer high specificity for RNA-ligand recognition, yet remain rare among experimentally-resolved RNA-ligand complex structures and difficult to predict in silico. RNA-targeted structure-based drug design (SBDD) is therefore limited by challenges in sampling cryptic states. Here, we apply Molearn, a hybrid molecular dynamics-deep generative framework, to expand apo RNA conformational ensembles toward cryptic states. Focusing on the paradigmatic HIV-1 TAR-MV2003 system, Molearn was trained exclusively on apo TAR conformations and used to generate a diverse ensemble of TAR structures. Candidate cryptic MV2003-binding conformations were subsequently identified using post-generation geometric analyses. Docking simulations of these conformations with MV2003 yielded binding poses with RNA-ligand interaction scores comparable to those of NMR-derived complexes. Notably, this work provides the first demonstration that a generative model can access cryptic RNA conformations that are ligand-binding competent and have not been recovered in prior molecular dynamics and deep generative modeling studies. Finally, we discuss current limitations in scalability and systematic detection, including application to the Internal Ribosome Entry Site, and outline future directions toward RNA-targeted SBDD.

bioinformatics↗

bioRxiv2022

Non-micelle-like Amyloid Aggregate Stabilizes Amyloid β (1-42) Growth Nuclei Formation

Protein aggregate formations are essential processes to regulate biochemical networks in the cell, while anomalously formed aggregates such as amyloid fibrils cause serious neuronal diseases. It has been discussed for a quarter century that protein crowding milieus, such as micelle-like aggregates, promote the formation of growth nuclei, fibril-growth competent aggregates which trigger rapid growth of pathogenic amyloid fibrils, but the mechanisms are still elusive, in particular at microscopic level. In this study, we examined the long-standing problem by employing atomistic molecular dynamics simulations for amyloid {beta}(1-42) (A{beta}42), the paradigmatic amyloid-forming peptide. First, we constructed an atomistic model of A{beta}42 growth nuclei in A{beta}42 aggregate milieu, the pentameric A{beta}42 protomer dimer surrounded by 40 A{beta}42 monomers. Next, we simulated A{beta}42 monomer dissociation from the A{beta}42 growth nuclei and examined the effect of A{beta}42 aggregate milieu on the process. A{beta}42 aggregates spatially restrict A{beta}42 monomer dissociation pathways, while such spatial restriction itself does not significantly suppress A{beta}42 monomer dissociation from the growth nuclei. Rather, A{beta}42 aggregate milieus thermodynamically stabilize an A{beta}42 monomer binding to the growth edge by making atomic contacts with the monomer and contributes to stable formation of growth nuclei. A part of the aggregate milieu anchors dissociating monomer to the remaining part of growth nuclei, suggesting cooperative suppression of A{beta}42 monomer dissociation from A{beta}42 growth nuclei. Since the A{beta}42 aggregate milieu does not take a micelle-like configuration, we here discuss a new mechanism for stable formation of A{beta}42 growth nuclei in the presence of aggregate milieu.

biophysics↗

bioRxiv2022

Computational Prediction of Heteromeric Protein Complex Disassembly Order with Hybrid Monte Carlo/Molecular Dynamics Simulation

The physicochemical entity of biological phenomenon in the cell is 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, then revealing the subcomplex populations and formation orders. Meanwhile, these methodologies are not designed to straightforwardly examine temporal dynamics of multimeric protein assembly and disassembly, essential physicochemical properties to understand functional expression mechanisms of proteins in the biological environment. To address the problem, we had developed an atomistic simulation in the framework of the hybrid Monte Carlo/Molecular Dynamics (hMC/MD) method and succeeded in observing disassembly of homomeric pentamer of the serum amyloid P component protein in experimentally consistent order. In this study, we improved the hMC/MD method to examine 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 each hMC/MD simulation cycle and achieved highly reliable predictions of the disassembly orders with the success rate over 0.9 without a priori knowledge of the MS experiments and structural bioinformatics simulations. We similarly succeeded in reliable predictions for the other three tetrameric protein complexes. These achievements indicate the potential availability of our hMC/MD approach as the general purpose methodology to obtain microscopic and physicochemical insights into multimeric protein complex formation.

biophysics↗

bioRxiv2021

Physicochemical Insights into Microscopic Events Driven by GTP Hydrolysis Reaction in Ras-GAP system

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 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 ca. 5 kcal/mol raise of potential energy about the phosphate-binding loop (P-loop) in 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 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 with relaxation, namely, a shift of biomolecular system to 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 physicochemical understanding for the operating principles of GTP/ATP hydrolysis-driven biological nano-machines.

biophysics↗

bioRxiv2021

Inactivation of Aβ42 Protomer-dimer Dissociation Reaction via Increasing Protomer Size

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-{beta} (1-42) (A{beta}42). Seven different dimeric forms of oligomeric A{beta}42 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 A{beta}42 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.

biophysics↗

bioRxiv2020

Reaction Pathway Sampling and Free Energy Analyses for Multimeric Protein Complex Disassembly with Employing Hybrid Configuration Bias Monte Carlo/Molecular Dynamics Simulation

Physicochemical characterization of multimeric biomacromolecule assembly and disassembly processes is a milestone to understand the mechanisms for biological phenomena at molecular level. Mass spectroscopy (MS) and structural bioinformatics (SB) approaches have become feasible to identify subcomplexes involved in assembly and disassembly, while they cannot provide atomic information sufficient for free energy calculation to characterize transition mechanism between two different sets of subcomplexes. To combine observations derived from MS and SB approaches with conventional free energy calculation protocols, we here designed a new reaction pathway sampling method with employing hybrid configuration bias Monte Carlo/Molecular Dynamics (hcbMC/MD) scheme and applied it to simulate disassembly process of serum amyloid P component (SAP) pentamer. The results we obtained are consistent with those of the earlier MS and SB studies with respect to SAP subcomplex species and the initial stage of SAP disassembly processes. Furthermore, we observed a novel dissociation event, ring-opening reaction of SAP pentamer. Employing free energy calculation combined with the hcbMC/MD reaction pathway trajectories, we moreover obtained experimentally testable observations on (1) reaction time of the ring-opening reaction and (2) importance of Asp42 and Lys117 for stable formation of SAP oligomer.

biophysics↗