Biology subjects

Yamane, T.

Publications and source records attributed to Yamane, T..

6 recordsLinked to original sources

bioRxiv2026

Development of force-field corrections for the RNA A-bulge motif

Many functional RNA motifs adopt structures that deviate from the canonical A-form helix and are emerging targets for RNA-directed therapeutics. The microtubule-associated protein tau (MAPT) A-bulge motif (5'-GCAGU/5'-ACGU) is one such motif. Because its structure is stabilized by a delicate balance of local interactions, its accurate modeling remains a major challenge for molecular dynamics (MD) simulations. The experimentally determined nuclear magnetic resonance (NMR) structure of the MAPT A-bulge motif provides a stringent test of whether RNA force fields can accurately reproduce the experimentally observed conformation. Most current AMBER-family RNA force-field models have incorrectly favored a non-native base-triple state of the MAPT A-bulge motif over the experimentally observed stacked state. Structural comparison of the stacked and base-triple conformations revealed that overly favorable NH-N hydrogen bonds between the bulged adenosine and an adjacent Watson-Crick base pair were the primary source of this imbalance. We developed gHBfix-18Ab, an 18-component hydrogen-bond correction that distinguishes NH and NH2; donors. gHBfix-18Ab was combined with the previously developed OL3CP and NBfix0BPh corrections to generate the composite model gHBfix-18Ab*. This model restored the experimentally observed stacked state as the global minimum in the calculated free-energy profile and improved agreement with NMR-derived distance data for the A-bulge region. Importantly, gHBfix-18Ab* did not produce marked structural destabilization of the cUUCGg tetraloop, a widely used benchmark for RNA force-field validation, suggesting that the refinement preserves the stability of the unrelated RNA motif. These results demonstrate that targeted refinement of hydrogen-bond interactions provides a practical strategy for systematic improvement of RNA force fields toward more accurate modeling of noncanonical RNA motifs.

biophysics↗

bioRxiv2026

Co-folding of Membrane Proteins and Lipid Molecules Improves Membrane-Protein Structure Prediction Accuracy

Recent advances in deep-learning-based structure prediction have greatly improved the accuracy of protein structure modeling and enabled prediction of biomolecular complexes. However, the surrounding molecular environments are typically not represented explicitly, and their effects are therefore captured only implicitly. This limitation is particularly relevant for membrane proteins, whose structures and interactions are strongly influenced by the membrane environment. Here we introduce co-folding of membrane proteins and lipid molecules (CoMPLip), a method that imposes an explicit membrane context by co-folding proteins with lipid molecules during AlphaFold 3 (AF3) predictions. In CoMPLip, lipid molecules arrange into bilayer-like configurations around transmembrane regions, providing a membrane-like environment during structure prediction. Across benchmark datasets of ligand-bound membrane proteins, full-length single-pass membrane proteins, and dynamic transporters, CoMPLip improves ligand-pose prediction, promotes correct extracellular-intracellular domain separation, and enables sampling of multiple conformational states. CoMPLip is training-free and is compatible with the existing AF3 workflows.

bioinformatics↗

bioRxiv2025

intDesc-AbMut: Describing and understanding how antibody mutations impact their environmental interactions

Previously, we proposed a double-point mutation (DPM) strategy involving the simultaneous substitution of two amino acids to optimize antibodies. By selecting mutants based on the criterion that favorable interactions between mutated residues and their local environments are preserved or enhanced, improvements in antibody affinity were achieved. Nonetheless, manual extraction of these interactions proved to be time-consuming and labor-intensive. Thus, to streamline this process, we developed intDesc-AbMut, an automated software tool designed to extract interactions between designated mutant residues and their surroundings from three-dimensional antigen-antibody complex structures. intDesc-AbMut identifies and classifies 36 distinct types of interactions, enabling visualization of changes before and after mutation. Additionally, the effects of mutations can be represented by interaction descriptors generated from the extracted interactions. As a practical application, we constructed a machine learning model using these descriptors combined with side-chain rotamer frequencies to determine whether the environment around mutated residues in antigen-antibody complexes is crystal-like, achieving a Matthews correlation coefficient of 0.505 and an accuracy of 0.855. The intDesc-AbMut software is available at: https://github.com/riken-yokohama-AI-drug/intDesc/tree/intDesc-AbMut.

bioengineering↗

bioRxiv2025

Novel humanized anti-Nav1.7 antibodies with long-lasting, side-effect-free analgesic effects

Neuropathic pain remains difficult to treat effectively because of the limitations of current pain medications. The Nav1.7 sodium channel plays a crucial role in pain sensation. The development of selective inhibitors has been challenging because of the high similarity among Nav channel subtypes. To address this issue, we developed monoclonal antibodies that selectively target Nav1.7 and humanized them for clinical use for the first time. When administered systemically to neuropathic pain model rats, a potent analgesic effect was observed that lasted for at least 96 hours. Electrophysiological studies revealed that the antibody reduced mechanically-evoked and spontaneous neuronal activity in the model. Importantly, the antibodies did not impact physiological pain or motor function. Collectively, our findings suggest that these novel Nav1.7-targeting antibodies are potentially effective analgesic drugs for chronic pain, including neuropathic pain. Our novel humanized anti-Nav1.7 antibodies have the potential to be used for the development of new analgesic, and one such antibody, S-151128 is currently in clinical trial.

pharmacology and toxicology↗

bioRxiv2024

Molecular dynamics unveils multiple-site binding of inhibitors with reduced activity on the surface of dihydrofolate reductase

The sensitivity to protein inhibitors is altered by modifications or protein mutations, as represented by drug resistance. The mode of stable drug binding to the protein pocket has been experimentally clarified. However, the nature of the binding of inhibitors with reduced sensitivity remains unclear at the atomic level. In this study, we analyzed the thermodynamics and kinetics of inhibitor binding to the surface of wild-type and mutant dihydrofolate reductase (DHFR) using molecular dynamics simulations combined with Markov state modeling. A strong inhibitor of methotrexate (MTX) showed a preference for the active site of wild-type DHFR with minimal binding to unrelated (secondary) sites. Deletion of a side-chain fragment in MTX largely destabilized the active site-bound state, with clear evidence of binding to secondary sites. Similarly, the F31V mutation in DHFR diminished the specificity of MTX binding to the active site. These results reveal the presence of multiple-bound states whose stabilities are comparable to or higher than those of the unbound state, suggesting that a reduction in the binding affinity for the active site significantly elevates the fractions of these states. This study sheds light on the specific drug recognition by proteins and the selectivity of drug binding sites on protein surfaces. (199 words)

biophysics↗

bioRxiv2017

Energetics and Conformational Pathways of Functional Rotation in the Multidrug Transporter AcrB

The multidrug transporter AcrB transports a broad range of drugs out of the cell by means of the proton-motive force. The asymmetric crystal structure of trimeric AcrB suggests a functionally rotating mechanism for drug transport. Despite various supportive evidences from biochemical and simulation studies for this mechanism, the link between the functional rotation and proton translocation across the membrane remains elusive. Here, calculating the minimum free energy pathway of the functional rotation for the complete AcrB trimer, we describe the structural and energetic basis behind the coupling between the functional rotation and the proton translocation at atomic-level. Free energy calculations show that protonation of Asp408 in the transmembrane portion of the drug-bound protomer drives the functional rotation. The conformational pathway identifies vertical shear motions among several transmembrane helices, which regulates alternate access of water in the transmembrane as well as peristaltic motions pumping drugs in the periplasm.

biophysics↗