Journal of Biomolecular Structure & Dynamics最新文献

Molecular dynamics (MD) simulations provide valuable insights into biomolecular interactions by analyzing atomic-level motion. However, conventional analysis primarily relies on positional metrics, which often fail to capture the relative direction of molecules or potentially degrade the actual molecular motion due to RMSD-based preprocessing. In this study, we introduce a Rigid Body Transformation (RBT)-based approach to assess molecular movements quantitatively. To validate our method, we applied controlled transformations, including translation, rotation, and noise addition, to artificially generated motion data. The RBT-based alignment successfully restored the original configurations with near-zero reconstruction errors, demonstrating its robustness in preserving motion similarity even under noisy conditions. Furthermore, our approach effectively characterized the dynamics of a designed complex, distinguishing positional and orientational linear relationships in motion patterns. Additionally, we applied our method to MD data of the Q108R CRBP(I)-atREA complex. While conventional salt-bridge analysis suggested persistent interactions between Lys-40 and Arg-108, our center of mass (COM) and dipole moment analysis revealed distinct dynamic behaviors, aligning with experimental findings. These results highlight the importance of incorporating both positional and orientational consistency in MD data analysis, offering new insights into biomolecular motion.

The SPINK2 protein, encoded by the SPINK2 gene, plays an essential role in the normal development of spermatozoa, and its deficiency is associated with spermatogenesis disorders ranging from aspermia to azoospermia. This study aimed to identify the most deleterious variants of the SPINK2 gene and to evaluate their effects on protein structure and function through an in silico approach. A total of 8,028 variants were identified, including 72 missense variants. Using 11 bioinformatics tools, six variants (P50L, T58I, C66Y, E62A, P42S, and P45L) were predicted to have deleterious effects. Protein-protein interaction analysis using the STRING database revealed strong functional associations between SPINK2, SPINK1, and ACR, and medium-confidence associations with SPINK4, SPINK13, PMPCA, KLK4, SPINK9, SPINK6, SPACA1, and NUDT8. Local structural analysis showed that variants such as T58I and C66Y gained additional hydrophobic interactions, whereas P50L and P42S lost key interactions, potentially impairing protein stability and function. Molecular dynamics simulations using GROMACS revealed that P50L enhances protein stability, reduces amino acid flexibility, and increases the overall dimensions of the protein. T58I had a mild effect on stability, whereas E62A and C66Y decreased stability and flexibility while increasing protein size. P42S and P45L induced slight stability alterations, reduced flexibility, and enlarged the protein. Overall, these structural and dynamic changes suggest functional impairment of SPINK2. To our knowledge, this is the first study to identify six deleterious SPINK2 variants with potential roles in the disruption of spermatogenesis, providing a foundation for future functional and clinical investigations.

This study aimed to induce fibril formation in human insulin under physiological conditions and to investigate the inhibitory potential of caffeic acid (CA) on these fibrils in-vitro. Various techniques including circular dichroism (CD) spectroscopy, Thioflavin T, ANS fluorescence, Rayleigh light scattering (RLS), and turbidity analysis were conducted to elucidate fibril formation and CA inhibition potential. Fibril formation in insulin was induced by heating (37 °C) and agitation (600 rpm) significantly increased (27.01-fold) the ThT binding after 120 h of incubation. Aggregation also increased turbidity and enhanced RLS fluorescence at 350 nm. Secondary structure analysis revealed at loss of α-helical content and a concomitant increase in β-sheet content in human insulin following aggregation. The presence of varying concentrations of CA resulted in fewer perturbations in the secondary structure of insulin compared with the aggregated insulin sample. Fibril formation was also reduced (80%) in the presence of CA (500 µM). To gain insight, the biophysical interactions between CA and insulin were studied. CA showed moderate affinity (5.54 × 10³ M^-1) towards insulin in static quenching mode. The positive ΔH and ΔS values obtained indicate that the reaction was driven by hydrophobic interactions and the negative value of ΔG indicates a spontaneous reaction between the complexes. Docking analysis showed the interaction of CA with various amino acids of insulin via H-bonds, van der Waals forces, and hydrophobic interactions. Molecular simulations of RMSD, RMSF, and R_g showed that CA formed a stable complex with insulin.

A novel PET hydrolase-like enzyme identified from metagenomic databases using HMMR search was computationally fused with five different carbohydrate-binding modules (CBMs). AlphaFold3 predicted the 3D structures of the fused enzyme-CBM, which were validated using ERRAT, Verify3D, and PROCHECK. Molecular docking was performed with polycaprolactone triol using AutoDock Vina, followed by 100 ns molecular dynamics (MD) simulations using AMBER. Trajectory analyses and binding free energy calculations (QM/MM-GBSA) were conducted. The putative PET hydrolase-like enzyme shared 49.62% similarity with Ideonella sakaiensis PETase (5XJH). The fused models exhibited the best stability, with an instability index of <40 and a thermostability aliphatic index between 58.83 and 68.27. Structure validation confirmed high-quality 3D models, with >90% of the residues in the allowed Ramachandran regions. All the fused models showed favourable binding to PCL-triol, exhibiting strong interactions. In MD simulations, BlCBM5 and TrCBM complexes displayed a minimal fluctuation: all-atom RMSD ∼0.35 and ∼0.45 nm, backbone RMSD ∼0.48, ∼0.41 nm, atom contacts ∼4.2-5, ∼2-6, and H-bonds ∼2-5, ∼1-2, respectively. The BlCBM5 and TrCBM complexes showed the lowest binding energies, with MM-GBSA values of -36.66 ± 0.12 and -21.48 ± 0.11 kcal/mol, and QM/MM-GBSA values of -37.36 ± 0.13 and -21.70 ± 0.11 kcal/mol, respectively. Residue-level analysis identified key contributors (M133, W157, and F62) in both models. BlCBM5 and TrCBM complexes were the top candidates for enhancing PCL plastic degradation. The findings of this study were based on predictive insights, and experimental validation is required in the future.

Microtubule affinity-regulating kinase 4 (MARK4) is a viable therapeutic target for neurodegenerative disorders and various solid cancers. To identify small molecule inhibitors targeting MARK4, a virtual high-throughput screening of a kinase-specific library and an in-house library was performed using Schrödinger Maestro suite. The study identified JMI-1094 (Docking score -8.486 kcal/mol) as a promising compound among top ten hits with high binding affinities for MARK4, exhibiting strong interactions with active site residues Lys85, Glu133, and Ala135. The binding potential is also supported by Prime/MM-GBSA binding free energy calculations. The stability of MARK4-JMI-1094 complex was also accessed through MD simulation studies of 100 ns. The analysis of MD trajectories in terms of root mean square deviation (RMSD) and root mean square fluctuation (RMSF) revealed that MARK4-JMI-1094 complex displayed lower RMSD values than the apoprotein, signifying a strong and stable binding of JMI-1094 with MARK4. Hydrogen bond interactions with Glu133 and Ala135 persisted for 99% of the simulation time. The cell-based tau-phosphorylation assay suggests that it substantially inhibits the activity of MARK4. Moreover, the efficacy of JMI-1094 was evaluated high MARK4 expressing cell lines from breast (MCF-7) and non-small cell lung cancer (A549) and it decreased the viability of these cell lines with an IC₅₀ value of 4.14 µM and 6.22 µM, respectively. The treatment with JMI-1094 significantly decreased the colonization and cell migration potential of MCF-7 and A549 cell lines, and induced apoptosis. These findings suggest JMI-1094 as a promising MARK4 inhibitor with potential future therapeutic implications in MARK4-mediated cancer(s).

The structural and functional consequences of mutations located throughout the S1 and S2 subunit domains of spike protein among omicron and D614G-mutant originating forms of the SARS-CoV-2 virus are examined. These structural mutations were identified by a mass-based phylogenetics approach. The T95I mutation, located in the S1 N-terminal domain, and the T547K mutation of the receptor-binding domain both help to stabilise the spike protein structure and contribute to viral fitness in omicron variants. The D796Y within the N-terminal portion of the S2 subunit, also stabilises the protein, while the effects of Q954H and N969K combine to reduce infectivity through displacement of the backbone of the heptad repeat 2 (HR2) region. The N856K mutation, within the fusion peptide region, introduces a stabilising H-bond at residue T572 that both alters the S1/S2 interaction and hampers conformational change resulting in a mixed stabilisation effect.

Structure-based drug design involves utilizing the three-dimensional structure of a biological target to guide the design and development of new therapeutic compounds. Traditionally, a huge number of structure-based drug discovery methods have been adopted, but their time-consuming, erroneous molecule formation, and highly complex characteristics prevent their extensive application in drug discovery. Therefore, to mitigate such intricacies, an effective Hybrid Hierarchical Scaled attention-enabled Variational Autoencoder-based Latent Generative Adversarial Network (HVLGAN) is proposed. The inclusion of the Graph-based pocket encoding (GPE) aided in the effective generation of the Simplified Molecular Input Line Entry System (SMILES) strings to stipulate the drug discovery process with reduced computational complexity. Further, the Hybrid Hierarchical Scaled (H2S) attention strategy generates additional significant details for the effective generation of new drug molecules. In addition, the incorporation of the latent encoder and decoder enhanced the drug discovery performance by effectively processing the high-dimensional features. Nevertheless, the Variational Autoencoder (VAE) alleviated the long-term dependency problems, thereby resulting in a faster drug discovery process. Moreover, the performance validation performed in terms of performance metrics showed efficacy by attaining 0.96 validity, 0.96 novelty, and 0.96 unique scores for 90 training percentages using the MOSES package.

The solute carrier family 6 (SLC6) transporters are essential for regulating neurotransmitter homeostasis through the reuptake of amino acids and monoamines. Among them, the glycine transporter type 1 (GlyT1, SLC6A9) plays a central role in modulating NMDA receptor function and glutamatergic signaling. Despite their therapeutic relevance, the selectivity profiles of GlyT1 inhibitors remain poorly defined, raising concerns about off-target effects. In this study, we employed an integrative in silico approach combining homology modeling, molecular docking, consensus scoring, and molecular dynamics simulations to characterize the multitarget potential of GlyT1 inhibitors toward related SLC6 transporters-GlyT2, PROT, SERT, NET, and DAT. High-quality three-dimensional models were generated and validated through structural refinement and quality metrics. Consensus docking with DockThor, GOLD, and AutoDock Vina followed by Exponential Consensus Ranking (ECR) identified NFPS_2 as the most potent GlyT1 ligand (ECR = 1.896), forming π-π interactions with TYR99 and TRP279, while Org 24598_2 preferentially bound GlyT2, and Bitopertin showed high affinity for DAT. Molecular dynamics simulations (300 ns) confirmed the structural stability of all complexes (RMSD < 0.25 nm), with low residue fluctuations within the binding pockets and stable solvent exposure profiles. MMPBSA energy analyses revealed favorable binding free energies for GlyT1, NET, and DAT (ΔG ≈ -25 to -30 kcal/mol). These results demonstrate the intrinsic multitarget behavior of GlyT1 inhibitors, highlighting conserved interaction motifs within the SLC6 family. Collectively, our findings emphasize the importance of structure-guided optimization to improve selectivity and reduce potential off-target effects while maintaining therapeutic efficacy.

The polycyclic aromatic hydrocarbons (PAH) degraded by bacterial laccase with the aid of 2, 2'-Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) as mediator has been experimentally discovered by researchers, but its binding detail helping to deeply understand the enzymatic degradation process is still unclear. Here, the binding of low rank coal PAH, such as naphthalene (NAP), phenanthrene (PHE), anthracene (ANT) and pyrene (PYR), with ABTS mediated laccase were investigated with docking and molecular dynamics (MD). The results indicate that the number of hydrophobic interactions and key residues involved in laccase-PYR were the largest, and hydrophobic interaction were important to maintain their binding. The laccase was the most stable when it bound to PYR, and the water number in binding pocket maintained the minimal, which was difficult to form the hydration shell. The binding of PYR resulted in the quick folding of enzyme, and the water number in cavity increased to the largest to improve its solvent environment.

This study evaluated the impact of the rs1695 (Ile105Val) substitution on GSTP1 structural stability, phosphorylation accessibility, and interaction with ethacrynic acid (EA), as a substrate. Molecular dynamics (MD) simulations were conducted for wild-type (WT) and Val105 mutant GSTP1 variants using the CHARMM36m force field in GROMACS. EA was docked to phosphorylated models, followed by 100 ns MD simulations comprising minimization, equilibration, and production phases. Structural and functional effects were analyzed through RMSD, RMSF, radius of gyration (Rg), solvent-accessible surface area (SASA), and MM-PBSA binding energy calculations, with PyMOL, VMD, and BIOVIA employed for visualization. Both WT and mutant GSTP1 maintained stable RMSD profiles over 100 ns. The Val105 variant displayed reduced fluctuations (RMSF) and sustained compactness (Rg:1.68-1.75 nm) with stable solvent exposure (SASA ≈105 nm²). EA binding further stabilized the mutant, although MM-PBSA analysis indicated slightly lower affinity compared to WT. Nonetheless, interaction energies remained sufficient to preserve ligand binding. Overall, the Ile105Val substitution in GSTP1 induces subtle conformational rearrangements that decrease flexibility and modestly reduce EA binding affinity while maintaining overall structural integrity. These findings provide a mechanistic basis for reduced detoxification efficiency and altered phosphorylation regulation, potentially contributing to disease susceptibility.