Biology subjects

Ekimoto, T.

Publications and source records attributed to Ekimoto, 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↗

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↗

bioRxiv2022

Binding and unbinding pathways of peptide substrate on SARS-CoV-2 3CL protease

Based on many crystal structures of ligand complexes, much study has been devoted to understanding the molecular recognition of SARS-CoV-2 3C-like protease (3CLpro), a potent drug target for COVID-19. In this research, to extend this present static view, we examined the kinetic process of binding/unbinding of an eight-residue substrate peptide to/from 3CLpro by evaluating the path ensemble with the weighted ensemble simulation. The path ensemble showed the mechanism of how a highly flexible peptide folded into the bound form. At the early stage, the dominant motion was the diffusion on the protein surface showing a broad distribution, whose center was led into the cleft of the Chymotrypsin fold. We observed a definite sequential formation of the hydrogen bonds at the later stage occurring in the cleft, initiated between Glu166 (3CLpro) and P3_Val (peptide), followed by binding to the oxyanion hole and completed by the sequencespecific recognition at P1_Gln.

biophysics↗

bioRxiv2021

Allosteric regulation of 3CL protease of SARS-CoV-2 and SARS-CoV observed in the crystal structure ensemble

The 3C-like protease (3CLpro) of SARS-CoV-2 is a potential therapeutic target for COVID-19. Importantly, it has an abundance of structural information solved as a complex with various drug candidate compounds. Collecting these crystal structures (83 Protein Data Bank (PDB) entries) together with those of the highly homologous 3CLpro of SARS-CoV (101 PDB entries), we constructed the crystal structure ensemble of 3CLpro to analyze the dynamic regulation of its catalytic function. The structural dynamics of the 3CLpro dimer observed in the ensemble were characterized by the motions of four separate loops (the C-loop, E-loop, H-loop, and Linker) and the C-terminal domain III on the rigid core of the chymotrypsin fold. Among the four moving loops, the C-loop (also known as the oxyanion binding loop) causes the order (active)-disorder (collapsed) transition, which is regulated cooperatively by five hydrogen bonds made with the surrounding residues. The C-loop, E-loop, and Linker constitute the major ligand binding sites, which consist of a limited variety of binding residues including the substrate binding subsites. Ligand binding causes a ligand size dependent conformational change to the E-loop and Linker, which further stabilize the C-loop via the hydrogen bond between the C-loop and E-loop. The T285A mutation from SARS-CoV 3CLpro to SARS-CoV-2 3CLpro significantly closes the interface of the domain III dimer and allosterically stabilizes the active conformation of the C-loop via hydrogen bonds with Ser1 and Gly2; thus, SARS-CoV-2 3CLpro seems to have increased activity relative to that of SARS-CoV 3CLpro.

biophysics↗

bioRxiv2020

Moving toward generalizable NZ-1 labeling for 3D structure determination with optimized epitope tag insertion

Antibody labeling has been extensively conducted for structure determination in both x-ray crystallography and EM analysis. However, establishing target-specific antibodies is a prerequisite for applying antibody-assisted structural analysis. To expand the applicability of this strategy, we have developed an alternative method to prepare an antibody-complex by inserting an exogenous epitope into the target. We have already demonstrated that the Fab of monoclonal antibody NZ-1 could form a stable complex with the target containing a PA12 tag as an inserted epitope. Nevertheless, we also found that the complex formation through the inserted PA12 tag inevitably caused structural change around the insertion site of the target. Hence, we here attempted to improve the insertion method and consequently discovered that utilization of a PA14 tag significantly reduced the structural change in the target. By adopting a closed ring-like conformation inside the antigen-binding pocket, the inserted PA14 tag had less impact on the folding of the target. Due to this structural property, the PA14 tag could also be inserted into the sterically hindered loop for labeling. Molecular dynamics simulations also indicated that the folding of the target was rigid regardless of the PA14 insertion and the complex formation with the NZ-1 Fab. Using the improved labeling technique, we performed negative-stain EM on a bacterial site-2 protease, which enabled us to approximate the domain arrangement based on the docking mode of the NZ-1 Fab.

biophysics↗