Journal of Biomolecular Structure & Dynamics最新文献

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.

Antithrombotic drugs are associated with drawbacks however they continue to be used globally for thrombus control. A majority of these anticoagulants activate antithrombin for enhanced inhibition of coagulation proteases like thrombin and factor Xa. Protein C Inhibitor (PCI) is able to inhibit both thrombin and activated protein C to regulate procoagulant and anticoagulant pathways. It is a potential drug lead in treating septic shock due to its strong anticoagulant and anti-inflammatory properties. A comprehensive screening of natural compounds that can bind PCI show a high affinity for naringin (-9.4 kcal/mol). Naringin is a flavonoid that is commonly found in the citrus fruit and has been shown to impart protection against cardiovascular diseases. Interestingly, naringin binds to the shutter region of the PCI away from the heparin binding site. A molecular dynamic simulation of PCI conformation showed exposure of the reactive center loop on binding naringin, a region that binds and catalyses the inhibition of the target proteases. Consequently, addition of naringin (50 µM) resulted in a significant decrease in the coagulation rates in the extrinsic and common pathways, however an increased rate was observed in the intrinsic pathway. A UV-Vis spectroscopic, fluorometric and circular dichroism based structural assessment showed PCI-naringin binding stoichiometry to be 1.0, with ground state-static binding and largely conserved secondary structure. Interestingly, the study reveals that naringin imparts its affect on PCI through enhancing the rate of inhibition of thrombin and activated protein C by 22-fold and 21-fold respectively, which might indicate an alternate basis of cardiovascular protection.

PTP1B is a potent target for the treatment of various diseases, such as cancer, diabetes, and autoimmune deficiency diseases. However, most PTP1B inhibitors show biological activity on its high homologous tumor target SHP2 resulting the potential toxic side effects. Therefore, it is urgent to elucidate the action mechanisms at molecular level, and further design novel PTP1B inhibitors with high specificity and activity. Based on our results from molecular dynamics simulations, the closure degree of WPD loop was identified as the key influence factor on PTP1B/SHP2 activity in this study. What's more, the closure degree of WPD loop on PTP1B was mainly came from the conventional hydrogen bond and π-Alkyl interactions between R47 and inhibitor 14. Subsequently, a PTP1B inhibitor Q1 was designed to enhance the π-Alkyl interaction between inhibitor and PTP1B and increase the closure degree of WPD loop. The experimental results showed that Q1 with an IC₅₀ of 2.45 μM against PTP1B exhibited more than 20-fold greater selectivity for PTP1B than for SHP2. Therefore, our efforts provided a new way to predict the selectivity and activity of small molecules for PTP1B and SHP2.

Gwt1, an essential acyltransferase in the glycosylphosphatidylinositol (GPI) biosynthesis pathway, is a promising target for the development of high-selectivity antifungal agents. In this study, we combined molecular dynamics (MD) simulations and free energy calculations to characterize the binding mechanism of Gwt1 with its native substrate, palmitoyl-CoA. Our simulations identified key hydrogen-bonding and ionic interactions critical for substrate recognition, particularly involving residues Lys123, Arg181, and Asn432. Potential of mean force (PMF) calculations revealed multiple conformational states of palmitoyl-CoA, including an I-shaped conformation that sterically occludes the GlcN-PI binding site, thereby hindering the acyl transfer step. Leveraging these structural insights, we performed virtual screening targeting the hydrophobic pocket formed by Tyr129, Tyr400, Phe404, and Tyr408, which identified two approved drugs, tivozanib and rosiglitazone, as potential Gwt1 inhibitors. Experimental validation confirmed their antifungal activities against pathogenic fungi, including Cryptococcus neoformans, Candida albicans, and Aspergillus fumigatus. This work provides dynamic mechanistic insights into Gwt1 function and offers a rational strategy for repurposing existing drugs as antifungals targeting the GPI pathway.

The rise of drug-resistant Mycobacterium tuberculosis (Mtb) strains has driven the search for novel therapeutic targets beyond conventional anti-tubercular agents. One such promising target is the ClpP protease complex, composed of ClpP1 and ClpP2 subunits, which is essential for proteostasis and bacterial survival under stress. This study explores the molecular dynamics (MD) and activation mechanism of Mtb ClpP subunits by N-[(benzyloxy)carbonyl]-L-isoleucyl-L-leucine (ZIL), an N-blocked dipeptide activator. MD simulations (200-1000 ns) were used to analyze structural stability, ligand interactions, and domain dynamics of both subunits in active and inactive states. ZIL-bound simulations showed that ClpP1 and ClpP2 maintained structural integrity, with conserved ligand-proximal residues forming stable interactions, although ClpP2 exhibited more variable polar contacts. In contrast, ligand-free simulations (500 ns) revealed significant instability, particularly in the handle domain and S1 binding pocket, underscoring the stabilizing role of ZIL. A 1000 ns simulation, with ZIL placed away from its known binding site on inactive ClpP1, showed that the ligand approached its target site and triggered a conformational shift in the handle domain, an early allosteric response, even though it did not fully dock as observed in the crystal structure. Notably, the residues in proximity to ZIL were associated with the observed structural changes in the simulations. The resulting MD trajectories provide a continuous, atomic-level view of ligand-induced dynamics and early activation events. Conducted without prior mechanistic assumptions, this unbiased simulation highlights the potential of targeting allosteric activation mechanisms and offers valuable insight into the rational design of ClpP-based therapeutics against drug-resistant Mtb.

Subcellular localization of mRNA plays a crucial regulatory role in eukaryotic cells, directly affecting protein synthesis, functional localization and cellular activities. Its abnormal regulation is closely associated with various pathological conditions. Therefore, accurate elucidation of the mechanisms underlying mRNA subcellular localization is of great significance for biomedical research. However, existing multi-label prediction methods mainly rely on traditional feature encoding techniques and still face considerable limitations. To address these challenges, this study proposes a novel resampling technique that combines Manhattan Mean-Direction Oversampling with Manhattan Density-Preserved Undersampling. Moreover, in light of the advantages of large language models, this study explores the use of several popular models to extract key information from sequences. Based on the experimental results, ESM2 was ultimately selected for feature extraction. Building upon these methods, we developed a novel prediction tool named EMMPREDMLsub. Results demonstrate that EMMPREDMLsub outperforms current state-of-the-art models in multi-label prediction tasks. Furthermore, SHAP-based interpretability analysis reveals that traditional models tend to focus on single key features, while deep learning models rely on synergistic interactions among multiple features. Notably, the A and T nucleotides at the 5' end and the C and G nucleotides at the 3' end of mRNA sequences contribute significantly to the predictions, suggesting that nucleotide composition and feature combinations in different regions play critical biological roles in subcellular localization. To facilitate broader use, we have developed a free and open-access online tool: http://www.emmpredmlsub.com.

The conformational dynamics of the switch domain 1 (SWI) of KRAS plays an important role in binding of KRAS to effectors. Clarifying molecular mechanism of the effect of mutations in SWI on conformational dynamics of KRAS is of significance for understanding the function of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations were performed on GDP/GTP-wild type (WT) and mutated KRAS to investigate the influences of two mutations P34R and T35S in SWI on conformational dynamics of KRAS. The analyses of free energy landscapes (FELs) reveal that P34R and T35S induce looser switch regions than WT KRAS, moreover the switch regions in GTP-P34R and T35S KRAS are wider than those in GDP-P34R and T35S one. Meanwhile, P34R and T35S highly affect structural flexibility of SWI and the loop L3, which disturbs binding of KRAS to effectors or regulators and the allosteric regulation of KRAS activity. In addition, the analyses of interaction networks suggest that P34R and T35S weaken hydrogen bonding interactions (HBIs) of SWI with GDP/GTP and influence electrostatic interactions (EIs) of SWI with magnesium ion (Mg²⁺), which also implies the effects of P34R and T35S on binding of KRAS to effectors or regulators and KRAS activity. This work is expected to contribute theoretical help and dynamics information for further understanding the function of KRAS and drug design toward the RAS proteins.

Neurons in the brain communicate through interactions between neurotransmitters and their receptors. Structure-based rational design of opioid drugs remains a major challenge, largely due to a lack of mechanistic insight into opioid-receptor selectivity and receptor activation. To address this gap, we present an enhanced Triangular Spatial Relationship (TSR)-based method to define and quantitatively characterize ligand-induced conformational changes in both receptors and ligands. To accurately model the geometries of neurotransmitters and opioids, we developed a novel algorithm for extracting their three-dimensional structural features. The key contributions of this work are summarized as follows: (i) Synergistic improvements in elucidating structure-function relationships were achieved by simultaneously applying two feature-engineering strategies. (ii) The influence of local receptor environments on the structural variations of glutamate and aspartate was quantitatively analyzed to elucidate conformational changes. (iii) Complementary structural features between fentanyl and its biosensor were identified, providing insights into binding specificity. (iv) Tyrosine residues within neurotransmitter binding sites were shown to be structurally distinct from those located outside these sites. (v) For the first time, the TSR-based method was integrated with Density Functional Theory and Quantum Mechanics/Molecular Mechanics optimization, revealing a clear relationship between structure and energy. (vi) The TSR-based method demonstrated superior performance compared with RMSD, USR, ROSHAMBO, and Phase approaches. In conclusion, this study establishes an advanced computational framework for representing and quantifying neurotransmitter structures. The TSR-based approach provides a powerful tool for dissecting structural specificity in ligand-receptor interactions and lays a solid foundation for deeper mechanistic insight and more effective rational drug design.