Journal of Biomolecular Structure & Dynamics最新文献

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.

Drug repurposing for cancer treatment is a valuable strategy to identify existing drugs with known safety profiles that could combat the neoplasm, by reducing costs. Oral squamous cell carcinoma, an ulcer-proliferative lesion on the mucosal epithelium, is the most common oral malignancy. About 10% of cancer patients within the Indian subcontinent suffer from OSCC, primarily due to chewing of betel plant derivatives. Concomitant administration of the chemotherapeutic agent (Cisplatin/Paclitaxel) is the treatment of choice. Analysis of the oral mycobiome of OSCC patients has projected the role of Candida albicans in potentiating OSCC. Hence, repurposing antifungal drugs emerges as a promising approach, as these drugs could target both the cancer cells and the infection. Cancer cells often have heightened energy requirements, and targeting mitochondrial proteins to disrupt mitochondrial division and induce dysfunction contributing to cell death, offers a method for treating OSCC. We identified 18 mitochondrial targets playing a crucial role in the maintenance of mitochondrial homeostasis. They were docked against 125 antifungal ligand molecules sourced from PUBCHEM. Ligand profiling was performed using Lipinski's rule of 5, SwissADME and ProTox. Also, molecular dynamics and MM-PBSA were performed to validate our results. Among all protein ligand interactions, we observed that targeting DRP1 with itraconazole yielded superior binding and stability. Overall, lower toxicity and thumping ADME properties solidified the choice of ligand. We hope this experimental approach will enable us to provide a basis for selecting a lead molecule for a possible novel nano-formulation and validate our finding through in-vitro cell line-based testing.

Superoxide dismutase 1 (SOD1) is a vital enzyme responsible for attenuating oxidative stress through its ability to facilitate the dismutation of the superoxide radical into oxygen and hydrogen peroxide. The progressive loss of motor neurons characterize amyotrophic lateral sclerosis (ALS), a crippling neurodegenerative disease that is caused by mutations in the SOD1 gene. In this study, in silico mutational analysis was performed to study the various mutations, the pathogenicity and stability ΔΔG (binding free energy) of the variant of SOD1. x in the protein variant analysis showed a considerable destabilizing effect with a ΔΔG value of -4.2 kcal/mol, signifying a notable impact on protein stability. Molecular dynamics simulations were conducted on both wild-type and C146R mutant SOD1. RMSD profiles indicated that both maintained consistent structural conformation over time. Additionally, virtual screening of 3067 FDA-approved drugs against the mutant SOD1 identified two potential binders, Tucatinib (51039094) and Regorafenib (11167602), which interacted with Leu106, similar to the control drug, Ebselen. Further simulations assessed the dynamic properties of SOD1 in monomeric and dimeric forms while bound to these compounds. 11167602 maintained stable interaction with the monomeric SOD1 mutant, whereas 51039094 and Ebselen dissociated from the monomeric protein's binding site. However, all three compounds were stably bound to the dimeric SOD1. MM/GBSA analysis revealed similar negative binding free energies for 11167602 and 51039094, identifying them as strong binders due to their interaction with Cys111. Experimental validation, including in vitro, cell-based, and in vivo assays are essential to confirm these candidates before advancing to clinical trials.

The main aim of this study is to address the global health crisis posed by tuberculosis (TB) through the exploration of novel therapeutic strategies targeting Mycobacterial phosphoribosyl pyrophosphate synthetase (MtPrsA), an untried enzyme involved in essential metabolic pathways of Mycobacterium tuberculosis. This enzyme plays a crucial role in cell wall synthesis, nucleotide biosynthesis and amino acid synthesis in M tb. Any hindrance to these may affect the growth and survival of the organism. Phytochemicals were systematically screened for potential inhibitors to MtPrsA. Subsequently, based on molecular docking studies, three compounds, namely, hesperidin, rebaudiosideA and rutin were selected. The binding stabilities of these compounds were analyzed using molecular dynamics simulation. Based on the RMSD score obtained, the binding stability of the compounds was confirmed. To validate the findings, an enzyme inhibition assay was done using recombinant MtPrsA. Ligation Independent Cloning (LIC cloning) method was used to produce recombinant His-tagged MtPrsA, followed by purification using Histrap columns. Enzyme kinetic studies unveiled the distinct modes of inhibition exhibited by each compound towards MtPrsA. RebaudiosideA and rutin emerged as competitive inhibitors, while hesperidin showcased a mixed inhibition profile. In conclusion, the study contributes valuable insights into potential therapeutic strategies for TB, through the exploration of alternative enzyme targets and the identification of phytochemical inhibitors. Notably, todate, no effective plant compounds have been reported as inhibitors to MtPrsA.

Adansonia digitata extracts are well known for their wide range of nutritional and medicinal benefits, including anti-diabetic, anti-inflammatory, antioxidant, and anti-cancerous properties. Yet, its efficacy against breast cancer has not been well-studied so far. Hence this study aims to investigate the anti-cancer properties of phytochemicals from the bark extract of the Adansonia digitata tree against BBOX1, a protein that stimulates the growth of Triple Negative Breast Cancer (TNBC) cells. TNBC is a highly aggressive and fatal form of cancer with limited therapeutic options available. By incorporating computational bioinformatics including Molecular docking, MMGBSA/PBSA, Molecular dynamics, and PCA/FEL analysis, the phytocompounds were scrutinized against BBOX1. Among 274 Phytocompounds only 37 compounds with good pharmacokinetic profiles based on ADME analysis were selected and docked with BBOX1. Of these compounds, the top 6 phytocompounds (CID_22217550, CID_559476, CID_6423866, CID_595387, CID_550931, and CID_559495) demonstrated good binding affinity, with better docking scores ranging from -8.599 to -7.207 kcal/mol respectively. Furthermore, based on MM/GBSA, Interaction profiling, and DFT analysis, only three phytocompounds namely CID_22217550, CID_559476, and CID_550931 were found to interact with the key residues such as Tyr_177, Trp_181, Asp_191, and Tyr_366 with better binding efficacy. In addition, these compounds were also observed to have the least RMS deviations with stable H-bond interactions maintained throughout the MD production run. Henceforth, the overall analysis infers that the phytocompounds CID_22217550, CID_559476, and CID_550931 shall act as potent inhibitors of BBOX1. However, their inhibitory efficacy has be to analyzed with further in vitro and in vivo analysis.

Ten novel 1,2,3,4-tetrahydroquinolone-triazole compounds (denoted as 6a-6j) were synthesized using click chemistry. These compounds were thoroughly characterized using various analytical techniques, such as FT-IR, mass spectrometry,¹H NMR, and ¹³C NMR. To gather a deeper understanding regarding structural properties of the synthesized compounds, we conducted Density Functional Theory (DFT) studies employing the B3LYP/6-311G (d,p) methodology. These calculations allowed us to evaluate important properties such as the HOMO-LUMO energy gap, chemical potential (µ), electrophilicity (ω), chemical hardness (η), dipole moment (Debye), and total energy (a.u.) for the synthesized hybrids. Moving on to the practical application of these hybrids, we evaluated in vitro antimicrobial inhibitory potential against two gram-positive and two gram-negative strains, and three fungal strains. Obtained outcomes revealed a range of antibacterial activity, with some compounds exhibiting excellent to moderate efficacy. Compounds 6b and 6i showed a very good result with a MIC of 12.5 μg/mL compared to standard Ciprofloxacin (MIC 25 μg/mL), demonstrating strong antibacterial activity against E. coli among the 6a-6j compounds. Furthermore, in silico docking validated our compounds' interaction with E. coli DNA gyrase B. Further, a 200 ns simulation revealed that the promising compounds maintained stability within the binding cavity, with RMSD values below 3 Å, and exhibited reduced structural fluctuations compared to the Apo protein, as evidenced by lower average RMSF values in the ligand-protein complexes. Additionally, an in silico ADME study assessed the drug-likeness of the hybrids, offering insights for future drug development.