Search Results (84)

Background/Objectives: Ginsenosides, one of the most pharmaceutically valuable chemical compounds in Panax ginseng, are synthesized with several enzymes, including UGTs. UGTs determine absorbability and physiological function upon consumption. Thus, understanding the functional residues of ginsenoside biosynthesis-associated UGTs is crucial for enhancing the production of valuable ginsenoside varieties. Methods: We collected the UGT homologs of high sequence similarity from two rate-limiting steps of the biosynthetic pathway. The 3D structures of these proteins were predicted using the AlphaFold3 model. The ligand-binding interactions of these UGTs were examined using SwissDock and CB-Dock2. Enzyme kinetics were analyzed with MPEK. Using these tools, we performed in silico mutagenic analyses to identify the functional residues of UGTs in detail. Results: We elucidated the molecular mechanisms of experimentally verified functional residues in UGTs, many of which were associated with optimal ligand interaction angles that expose target carbons. We also identified putatively important amino acid residues that mediate ligand interactions and modulate reaction kinetics by more than 25%. In this study, residues at positions 62, 224, 397, and 398 were shown to significantly influence enzyme kinetics. Conclusions: Our study provides the first structural analysis of the functional residues of ginsenoside biosynthetic UGTs based on their 3D structures. We identified several key amino acid residues essential for proper ginsenoside biosynthesis: (1) residues determining ligand interactions, (2) residues modulating ligand binding angles, and (3) residues affecting reaction kinetics. Our findings demonstrate an effective approach to identifying functional residues in plant enzymes and present valuable UGT candidates for future experimental validation. Full article

Background: Cytochrome P450 (CYP450) enzymes play a central role in the metabolism of xenobiotics, including plant-derived compounds such as terpenoids. Objectives: This study aimed to predict the molecular interactions of linalool (LIN) and linalyl acetate (LINAct), major constituents of lavender essential oil, with the canine CYP2B11, CYP2C21, and CYP2D15 isoforms, using in silico approaches. Methods: Three-dimensional (3D) models of the target enzymes were generated through homology modeling using SWISS-MODEL and validated based on global model quality estimate (GMQE) and QMEAN Z-score metrics. Ligand structures were optimized in the Molecular Operating Environment (MOE), and pharmacophoric features were analyzed. Molecular docking simulations were performed using AutoDock Vina, followed by visualization of interactions in MOE. Results: LIN and LINAct exhibit favorable binding affinities with all three isoforms, suggesting their potential as substrates or modulators. Hydrogen bonding and hydrophobic interactions were the predominant forces stabilizing the ligand–enzyme complexes. Conclusions: These findings provide a computational basis for understanding the hepatic metabolism of LIN and LINAct in dogs, offering preliminary insights into the role of specific CYP isoforms in their biotransformation. Full article

Background: Hydroxycarboxylic acid receptor 3 (HCAR3) is a receptor that is mainly expressed in human adipose tissue. It can inhibit lipolysis through the inhibition of adenylyl cyclase; thus, it is closely related to the regulation of lipids in the human body. This makes HCAR3 a compelling target for developing drugs against dyslipidemia. Notably, the reported active compounds for HCAR3 are all carboxylic acids. This observation is in line with the fact that ARG111 has been reported as the key residue to anchor the active compound in a closely related homologous protein—HCAR2. Methods: In this study, we aim to discover new chemicals, through virtual screening, that may bind with HCAR3. As there are several choices for the receptor conformation, cross-docking was conducted and the root-mean-square deviation of the docking pose from the conformation of the crystal ligand was employed to determine the best receptor conformation for screening. Ligands from the ZINC20 database were screened through molecular docking, and 30 candidates were subjected to 100 ns MD simulations. Six stable complexes were further assessed by umbrella sampling to estimate binding affinity. Results: The homology model (HCAR3_homology) was selected as the receptor. Following the protocol determined by the retrospective docking process, prospective docking was conducted to screen the ligands from the ZINC20 database. Subsequently, the top 30 compounds with a good docking score and a good interaction with ARG111 were subjected to 100 ns molecular dynamics (MD) simulations, and their binding stability was analyzed based on the resulting trajectories. Finally, six compounds were chosen for binding free energy calculation using umbrella sampling; all showed negative binding affinities. Conclusions: All six compounds selected for umbrella sampling showed negative binding affinities, suggesting their potential as novel HCAR3 ligands for the development of drugs against dyslipidemia. Full article

Umami is a fundamental taste sensation, often described as a delicious and pleasant flavor perception. To enhance or complement the original flavor and meet the tastes of diverse regions, umami dipeptides have been extensively utilized in global food manufacturing. Currently, the application and purification techniques of dipeptides are relatively mature, while their umami mechanisms and molecular modification are both scarce. In this work, the 3D structure of the umami dipeptide target T1R1/T1R3 was first obtained through sequence alignment and homology modeling, then followed by the successful construction of a database containing 400 samples of dipeptides. Subsequently, the complex models of T1R1/T1R3, respectively, with DG (Asp-Gly) and EK (Glu-Lys) (i.e., T1R1_DG/T1R3, T1R1/T1R3_DG, T1R1_EK/T1R3, and T1R1/T1R3_EK) were obtained via molecular docking and virtual screening. Finally, based on comparative molecular dynamics (MD) simulation trajectories, the binding free energy was calculated to investigate receptor–ligand recognition and conformational changes, providing some implications for potential modifications of umami dipeptides. T1R1 tends to bind relatively small umami dipeptides, whereas T1R3 does the opposite, both of which favor the recognition of acidic and hydrophilic dipeptides. By comparing strategies such as hydroxyl introduction and chain length alteration, electrostatic effects may be more important than non-polar effects in molecular design. This work not only explores the recognition mechanism of umami dipeptides with the receptor T1R1/T1R3 showing certain theoretical significance, but also provides feasible suggestions for dipeptide screening and modification having certain application value. Full article

3CL protease (3CL^pro), a key enzyme of SARS-CoV-2 replication, is one of the most selective targets of antivirals, as no homologous protease has been recognized in the human body. As proteolysis-targeting chimeras (PROTACs) are superior to traditional inhibitors, based on the reported cereblon (CRBN) ligands thalidomide and lenalidomide, 3CL^pro ligands of peptidomimetic inhibitors, and suitable linkers, we aimed to develop novel PROTACs that may trigger efficient intracellular 3CL^pro degradation through a balance of hydrophilicity and lipophilicity. In brief, we designed and synthesized 5 PROTAC molecules. The 3CL^pro degradation efficiency of the PROTACs was assayed in stable SARS-CoV-2 3CL^pro expression HEK293 cell models and evaluated by Western blot. All compounds showed prominent 3CL^pro degradation activity with tolerable HEK293 cytotoxicity. The most prominent PROTAC compounds, 15 and 16, have DC₅₀ values of approximately 1 µM, and D_max of 89.3% and 75% respectively, indicating good potential for further application. Full article

Despite its ecological and economic importance, many aspects of Varroa destructor’s biology remain poorly understood, particularly its defense mechanisms against pathogens. The limited knowledge of Varroa’s immunity has hindered the development of RNA interference (RNAi)-based strategies targeting immune-related genes. In this study, we investigated the immune gene repertoire of V. destructor by querying its NCBI nr protein database and comparing it to model species of ticks (Ixodes scapularis) and mites (Galendromus occidentalis and Tetranychus urticae). Transcription of candidate immune genes was confirmed by analyzing a de novo assembled transcriptome of V. destructor. Our findings reveal that V. destructor shares key immunological traits with ticks, including lysozymes, chitinases, and thioester-containing proteins (TEPs), but also shares the absence of transmembrane peptidoglycan recognition proteins (PGRPs), Gram-negative binding proteins, and several lectin families involved in pathogen recognition. Additionally, Varroa mites, like ticks, lack homologs of crucial immune signaling components, such as the unpaired ligand (JAK/STAT), Eiger (JNK), and multiple elements of the IMD pathway. They also do not encode canonical antimicrobial peptides (AMPs) like defensins but possess putative homologs of ctenidins, AMPs previously identified in spiders and ticks, which may be adopted as a novel genetic readout for immune response in mites. Our findings lay the groundwork for future functional studies on mite immunity and open new avenues for RNAi-based biocontrol strategies targeting immune pathways to enhance Varroa management. Full article

The increasing challenge of marine biofouling, mainly due to barnacle settlement, necessitates the development of effective antifoulants with minimal environmental toxicity. In this study, fifteen derivatives of brusatol were synthesized and characterized using ¹³C-NMR, ¹H-NMR, and mass spectrometry. All the semi-synthesized compounds obtained using the Multi-Target-Directed Ligand (MTDL) strategy, when evaluated as anti-settlement agents against barnacles, showed promising activity. Compound 3 exhibited the highest anti-settlement capacity, with an EC₅₀ value of 0.1475 μg/mL, an LC₅₀/EC₅₀ ratio of 42.2922 (>15 indicating low toxicity), and a resuscitation rate of 71.11%, while it showed no significant phenotypic differences in the zebrafish embryos after treatment for 48 h. The toxicity screening of zebrafish also demonstrated the low ecotoxicity of the selected compounds. Furthermore, homology modeling of the HSP90 structure was performed based on related protein sequences in barnacles. Subsequently, molecular docking studies were conducted on HSP90 using these newly synthesized derivatives. Molecular docking analyses showed that most activated derivatives displayed low binding energies with HSP90, aligning well with the biological results. They were found to interact with key residues in the binding site, specifically ARG243, TYR101, and LEU73. These computational findings are anticipated to aid in predicting the enzyme targets of the tested inhibitors and their potential interactions, thus facilitating the design of novel antifoulants in future research endeavors. Full article

Primary aldosteronism is characterised by the excessive production of aldosterone, which is a key regulator of salt metabolism, and is the most common cause of secondary hypertension. Studies have investigated the association between primary aldosteronism and genetic alterations, with pathogenic mutations being identified. This includes a glycine-to-arginine substitution at position 151 (G151R) of the G protein-activated inward rectifier potassium (K⁺) channel 4 (GIRK4), which is encoded by the KCNJ5 gene. Mutations in GIRK4 have been found to reduce the selectivity for K⁺ ions, resulting in membrane depolarisation, the activation of voltage-gated Ca²⁺ channels, and an increase in aldosterone secretion. As a result, there is an interest in identifying and exploring the mechanisms of action of small molecule modulators of wildtype (WT) and mutant channels. In order to investigate the potential modulation of homotetrameric GIRK4^WT and GIRK4^G151R channels, homology models were generated. Molecular dynamics (MD) simulations were performed, followed by a cluster analysis to extract starting structures for molecular docking. The central cavity has been previously identified as a binding site for small molecules, including natural compounds. The OliveNet^TM database, which consists of over 600 compounds from Olea europaea, was subsequently screened against the central cavity. The binding affinities and interactions of the docked ligands against the GIRK4^WT and GIRK4^G151R channels were then examined. Based on the results, luteolin-7-O-rutinoside, pheophorbide a, and corosolic acid were identified as potential lead compounds. The modulatory activity of olive-derived compounds against the WT and mutated forms of the GIRK4 channel can be evaluated further in vitro. Full article

Statistical analyses of homologous protein sequences can identify amino acid residue positions that co-evolve to generate family members with different properties. Based on the hypothesis that the coevolution of residue positions is necessary for maintaining protein structure, coevolutionary traits revealed by statistical models provide insight into residue–residue interactions that are important for understanding protein mechanisms at the molecular level. With the rapid expansion of genome sequencing databases that facilitate statistical analyses, this sequence-based approach has been used to study a broad range of protein families. An emerging application of this approach is to design hybrid transcriptional regulators as modular genetic sensors for novel wiring between input signals and genetic elements to control outputs. Among many allosterically regulated regulator families, the members contain structurally conserved and functionally independent protein domains, including a DNA-binding module (DBM) for interacting with a specific genetic element and a ligand-binding module (LBM) for sensing an input signal. By hybridizing a DBM and an LBM from two different family members, a hybrid regulator can be created with a new combination of signal-detection and DNA-recognition properties not present in natural systems. In this review, we present recent advances in the development of hybrid regulators and their applications in cellular engineering, especially focusing on the use of statistical analyses for characterizing DBM–LBM interactions and hybrid regulator design. Based on these studies, we then discuss the current limitations and potential directions for enhancing the impact of this sequence-based design approach. Full article

G-protein-coupled receptors (GPCRs) represent a family of druggable targets when treating several diseases and continue to be a leading part of the drug discovery process. Trace amine-associated receptors (TAARs) are GPCRs involved in many physiological functions with TAAR1 having important roles within the central nervous system (CNS). By using homology modeling methods, the responsiveness of TAAR1 to endogenous and synthetic ligands has been explored. In addition, the discovery of different chemo-types as selective murine and/or human TAAR1 ligands has helped in the understanding of the species-specificity preferences. The availability of TAAR1–ligand complexes sheds light on how different ligands bind TAAR1. TAAR5 is considered an olfactory receptor but has specific involvement in some brain functions. In this case, the drug discovery effort has been limited. Here, we review the successful computational efforts developed in the search for novel TAAR1 and TAAR5 ligands. A specific focus on applying structure-based and/or ligand-based methods has been done. We also give a perspective of the experimental data available to guide the future drug design of new ligands, probing species-specificity preferences towards more selective ligands. Hints for applying repositioning approaches are also discussed. Full article

Bacterial infections are the second-leading cause of death, globally. The prevalence of antibacterial resistance has kept the demand strong for the development of new and potent drug candidates. It has been demonstrated that Src protein tyrosine kinases (TKs) play an important role in the regulation of inflammatory responses to tissue injury, which can trigger the onset of several severe diseases. We carried out a search for novel Src protein TK inhibitors, commencing from reported highly potent anti-bacterial compounds obtained using the Mannich reaction, using a combination of e-pharmacophore modeling, virtual screening, ensemble docking, and core hopping. The top-scoring compounds from ligand-based virtual screening were modified using protein structure-based design approaches, and their binding to the Src homology-2 domain of p56^lck TK was predicted using ensemble molecular docking. We have prepared a database of 202 small molecules and have identified six novel top hits that can be subjected to further investigation. We have also performed in silico ADMET property prediction for the hit compounds. This combined computer-aided drug design approach can serve as a starting point for identifying novel TK inhibitors that could be further subjected to in vitro studies and validation of antimicrobial activity. Full article

Coenzyme Q (CoQ) is a lipidic compound that is widely distributed in nature, with crucial functions in metabolism, protection against oxidative damage and ferroptosis and other processes. CoQ biosynthesis is a conserved and complex pathway involving several proteins. COQ2 is a member of the UbiA family of transmembrane prenyltransferases that catalyzes the condensation of the head and tail precursors of CoQ, which is a key step in the process, because its product is the first intermediate that will be modified in the head by the next components of the synthesis process. Mutations in this protein have been linked to primary CoQ deficiency in humans, a rare disease predominantly affecting organs with a high energy demand. The reaction catalyzed by COQ2 and its mechanism are still unknown. Here, we aimed at clarifying the COQ2 reaction by exploring possible substrate binding sites using a strategy based on homology, comprising the identification of available ligand-bound homologs with solved structures in the Protein Data Bank (PDB) and their subsequent structural superposition in the AlphaFold predicted model for COQ2. The results highlight some residues located on the central cavity or the matrix loops that may be involved in substrate interaction, some of which are mutated in primary CoQ deficiency patients. Furthermore, we analyze the structural modifications introduced by the pathogenic mutations found in humans. These findings shed new light on the understanding of COQ2’s function and, thus, CoQ’s biosynthesis and the pathogenicity of primary CoQ deficiency. Full article

The advent of deep learning algorithms for protein folding opened a new era in the ability of predicting and optimizing the function of proteins once the sequence is known. The task is more intricate when cofactors like metal ions or small ligands are essential to functioning. In this case, the combined use of traditional simulation methods based on interatomic force fields and deep learning predictions is mandatory. We use the example of [FeFe] hydrogenases, enzymes of unicellular algae promising for biotechnology applications to illustrate this situation. [FeFe] hydrogenase is an iron–sulfur protein that catalyzes the chemical reduction of protons dissolved in liquid water into molecular hydrogen as a gas. Hydrogen production efficiency and cell sensitivity to dioxygen are important parameters to optimize the industrial applications of biological hydrogen production. Both parameters are related to the organization of iron–sulfur clusters within protein domains. In this work, we propose possible three-dimensional structures of Chlorella vulgaris 211/11P [FeFe] hydrogenase, the sequence of which was extracted from the recently published genome of the given strain. Initial structural models are built using: (i) the deep learning algorithm AlphaFold; (ii) the homology modeling server SwissModel; (iii) a manual construction based on the best known bacterial crystal structure. Missing iron–sulfur clusters are included and microsecond-long molecular dynamics of initial structures embedded into the water solution environment were performed. Multiple-walkers metadynamics was also used to enhance the sampling of structures encompassing both functional and non-functional organizations of iron–sulfur clusters. The resulting structural model provided by deep learning is consistent with functional [FeFe] hydrogenase characterized by peculiar interactions between cofactors and the protein matrix. Full article

Tyrosinase serves as the key enzyme in melanin biosynthesis, catalyzing the initial steps of the pathway, the hydroxylation of the amino acid L-tyrosine into L-3,4-dihydroxyphenylalanine (L-DOPA), followed by the subsequent oxidation of L-DOPA into dopaquinone (DQ), and it facilitates the conversion of 5,6-dihydroxyindole-2-carboxylic acid (DHICA) into 5,6-indolequinone-2-carboxylic acid (IQCA) and 5,6-dihydroxy indole (DHI) into indolequinone (IQ). Despite its versatile substrate capabilities, the precise mechanism underlying tyrosinase’s multi-substrate activity remains unclear. Previously, we expressed, purified, and characterized the recombinant intra-melanosomal domain of human tyrosinase (rTyr). Here, we demonstrate that rTyr mimics native human tyrosinase’s catalytic activities in vitro and in silico. Molecular docking and molecular dynamics (MD) simulations, based on rTyr’s homology model, reveal variable durability and binding preferences among tyrosinase substrates and products. Analysis of root mean square deviation (RMSD) highlights the significance of conserved residues (E203, K334, F347, and V377), which exhibit flexibility during the ligands’ binding. Additionally, in silico analysis demonstrated that the OCA1B-related P406L mutation in tyrosinase substantially influences substrate binding, as evidenced by the decreased number of stable ligand conformations. This correlation underscores the mutation’s impact on substrate docking, which aligns with the observed reduction in rTyr activity. Our study highlights how rTyr dynamically adjusts its structure to accommodate diverse substrates and suggests a way to modulate rTyr ligand plasticity. Full article

Recent research has uncovered a promising approach to addressing the growing global health concern of obesity and related disorders. The inhibition of inositol hexakisphosphate kinase 1 (IP6K1) has emerged as a potential therapeutic strategy. This study employs multiple ligand-based in silico modeling techniques to investigate the structural requirements for benzisoxazole derivatives as IP6K1 inhibitors. Firstly, we developed linear 2D Quantitative Structure–Activity Relationship (2D-QSAR) models to ensure both their mechanistic interpretability and predictive accuracy. Then, ligand-based pharmacophore modeling was performed to identify the essential features responsible for the compounds’ high activity. To gain insights into the 3D requirements for enhanced potency against the IP6K1 enzyme, we employed multiple alignment techniques to set up 3D-QSAR models. Given the absence of an available X-ray crystal structure for IP6K1, a reliable homology model for the enzyme was developed and structurally validated in order to perform structure-based analyses on the selected dataset compounds. Finally, molecular dynamic simulations, using the docked poses of these compounds, provided further insights. Our findings consistently supported the mechanistic interpretations derived from both ligand-based and structure-based analyses. This study offers valuable guidance on the design of novel IP6K1 inhibitors. Importantly, our work exclusively relies on non-commercial software packages, ensuring accessibility for reproducing the reported models. Full article