Using Gaussian accelerated molecular dynamics combined with Markov state models to explore the mechanism of action of new oral inhibitors on Complex I.

In this study, our focus was on investigating H-1,2,3-triazole derivative HP661 as a novel and highly efficient oral OXPHOS inhibitor, with its molecular-level inhibitory mechanism not yet fully understood. We selected the ND1, NDUFS2, and NDUFS7 subunits of Mitochondrial Complex I as the receptor proteins and established three systems for comparative analysis: protein-IACS-010759, protein-lead compound 10, and protein-HP661. Through extensive analysis involving 500 ns Gaussian molecular dynamics simulations, we gained insights into these systems. Additionally, we constructed a Markov State Models to examine changes in secondary structures during the motion processes. The research findings suggest that the inhibitor HP661 enhances the extensibility and hydrophilicity of the receptor protein. Furthermore, HP661 induces the unwinding of the α-helical structure in the region of residues 726-730. Notably, key roles were identified for Met37, Phe53, and Pro212 in the binding of various inhibitors. In conclusion, we delved into the potential molecular mechanisms of triazole derivative HP661 in inhibiting Complex I. These research outcomes provide crucial information for a deeper understanding of the mechanisms underlying OXPHOS inhibition, offering valuable theoretical support for drug development and disease treatment design.

Elucidating the structural basis of vitamin B12 derivatives as novel potent inhibitors of PTP1B: Insights from inhibitory mechanisms using Gaussian accelerated molecular dynamics (GaMD) and in vitro study.

Vitamin B12 is a group of biologically active cobalamin compounds. In this study, we investigated the inhibitory effects of methylcobalamin (MeCbl) and hydroxocobalamin acetate (OHCbl Acetate) on protein tyrosine phosphatase 1B (PTP1B). MeCbl and OHCbl Acetate exhibited an IC50 of approximately 58.390 ± 2.811 µM and 8.998 ± 0.587 µM, respectively. The Ki values of MeCbl and OHCbl Acetate were 25.01 µM and 4.04 µM respectively. To elucidate the inhibition mechanism, we conducted a 500 ns Gaussian accelerated molecular dynamics (GaMD) simulation. Utilizing PCA and tICA, we constructed Markov state models (MSM) to examine secondary structure changes during motion. Our findings revealed that the α-helix at residues 37-42 remained the most stable in the PTP1B-OHCbl Acetate system. Furthermore, upon binding of OHCbl Acetate or MeCbl, the WPD loop of PTP1B moved inward to the active pocket, forming a closed conformation and potentially obstructs substrate entry. Protein-ligand interaction analysis and MM-PBSA showed that OHCbl Acetate exhibited lower binding free energy and engaged in more residue interactions with PTP1B. In summary, our study confirmed the substantial inhibitory activity of OHCbl Acetate against PTP1B, with its inhibitory potency notably surpassing that of MeCbl. We demonstrated potential molecular mechanisms of OHCbl Acetate inhibiting PTP1B.

Mulberry Leaf Compounds and Gut Microbiota in Alzheimer's Disease and Diabetes: A Study Using Network Pharmacology, Molecular Dynamics Simulation, and Cellular Assays.

Recently, studies have reported a correlation that individuals with diabetes show an increased risk of developing Alzheimer's disease (AD). Mulberry leaves, serving as both a traditional medicinal herb and a food source, exhibit significant hypoglycemic and antioxidative properties. The flavonoid compounds in mulberry leaf offer therapeutic effects for relieving diabetic symptoms and providing neuroprotection. However, the mechanisms of this effect have not been fully elucidated. This investigation aimed to investigate the combined effects of specific mulberry leaf flavonoids (kaempferol, quercetin, rhamnocitrin, tetramethoxyluteolin, and norartocarpetin) on both type 2 diabetes mellitus (T2DM) and AD. Additionally, the role of the gut microbiota in these two diseases' treatment was studied. Using network pharmacology, we investigated the potential mechanisms of flavonoids in mulberry leaves, combined with gut microbiota, in combating AD and T2DM. In addition, we identified protein tyrosine phosphatase 1B (PTP1B) as a key target for kaempferol in these two diseases. Molecular docking and molecular dynamics simulations showed that kaempferol has the potential to inhibit PTP1B for indirect treatment of AD, which was proven by measuring the IC50 of kaempferol (279.23 µM). The cell experiment also confirmed the dose-dependent effect of kaempferol on the phosphorylation of total cellular protein in HepG2 cells. This research supports the concept of food-medicine homology and broadens the range of medical treatments for diabetes and AD, highlighting the prospect of integrating traditional herbal remedies with modern medical research.

Unveiling Anti-Diabetic Potential of Baicalin and Baicalein from Baikal Skullcap: LC-MS, In Silico, and In Vitro Studies.

Type 2 diabetes mellitus (T2DM) is marked by persistent hyperglycemia, insulin resistance, and pancreatic ß-cell dysfunction, imposing substantial health burdens and elevating the risk of systemic complications and cardiovascular diseases. While the pathogenesis of diabetes remains elusive, a cyclical relationship between insulin resistance and inflammation is acknowledged, wherein inflammation exacerbates insulin resistance, perpetuating a deleterious cycle. Consequently, anti-inflammatory interventions offer a therapeutic avenue for T2DM management. In this study, a herb called Baikal skullcap, renowned for its repertoire of bioactive compounds with anti-inflammatory potential, is posited as a promising source for novel T2DM therapeutic strategies. Our study probed the anti-diabetic properties of compounds from Baikal skullcap via network pharmacology, molecular docking, and cellular assays, concentrating on their dual modulatory effects on diabetes through Protein Tyrosine Phosphatase 1B (PTP1B) enzyme inhibition and anti-inflammatory actions. We identified the major compounds in Baikal skullcap using liquid chromatography-mass spectrometry (LC-MS), highlighting six flavonoids, including the well-studied baicalein, as potent inhibitors of PTP1B. Furthermore, cellular experiments revealed that baicalin and baicalein exhibited enhanced anti-inflammatory responses compared to the active constituents of licorice, a known anti-inflammatory agent in TCM. Our findings confirmed that baicalin and baicalein mitigate diabetes via two distinct pathways: PTP1B inhibition and anti-inflammatory effects. Additionally, we have identified six flavonoid molecules with substantial potential for drug development, thereby augmenting the T2DM pharmacotherapeutic arsenal and promoting the integration of herb-derived treatments into modern pharmacology.

Mlp4green: A Binary Classification Approach Specifically for Green Odor.

Fresh green leaves give off a smell known as "green odor." It has antibacterial qualities and can be used to attract or repel insects. However, a common method for evaluating green odor molecules has never existed. Machine learning techniques are widely used in research to forecast molecular attributes for binary classification. In this work, the green odor molecules were first trained and learned using machine learning methods, and then clustering analysis and molecular docking were performed to further explore their molecular characteristics and mechanisms of action. For comparison, four algorithmic models were employed, MLP performed the best in all metrics, including Accuracy, Precision, Average Precision, Matthews coefficient, and Area under curve. We determined by difference analysis that, in comparison to non-green odor molecules, green odor molecules have a lower molecular mass and fewer electrons. Based on the MLP algorithm, we constructed a binary classification prediction website for green odors. The first application of deep learning techniques to the study of green odor molecules can be seen as a signal of a new era in which green odor research has advanced into intelligence and standardization.

Exploring the anti-gout potential of sunflower receptacles alkaloids: A computational and pharmacological analysis.

Gout, a painful condition marked by elevated uric acid levels often linked to the diet's high purine and alcohol content, finds a potential treatment target in xanthine oxidase (XO), a crucial enzyme for uric acid production. This study explores the therapeutic properties of alkaloids extracted from sunflower (Helianthus annuus L.) receptacles against gout. By leveraging computational chemistry and introducing a novel R-based clustering algorithm, "TriDimensional Hierarchical Fingerprint Clustering with Tanimoto Representative Selection (3DHFC-TRS)," we assessed 231 alkaloid molecules from sunflower receptacles. Our clustering analysis pinpointed six alkaloids with significant gout-targeting potential, particularly emphasizing the fifth cluster's XO inhibition capabilities. Through molecular docking and the BatchDTA prediction model, we identified three top compounds-2-naphthylalanine, medroxalol, and fenspiride-with the highest XO affinity. Further molecular dynamics simulations assessed their enzyme active site interactions and binding free energies, employing MM-PBSA calculations. This investigation not only highlights the discovery of promising compounds within sunflower receptacle alkaloids via LC-MS but also introduces medroxalol as a novel gout treatment candidate, showcasing the synergy of computational techniques and LC-MS in drug discovery.

Using deep learning and molecular dynamics simulations to unravel the regulation mechanism of peptides as noncompetitive inhibitor of xanthine oxidase.

Xanthine oxidase (XO) is a crucial enzyme in the development of hyperuricemia and gout. This study focuses on LWM and ALPM, two food-derived inhibitors of XO. We used molecular docking to obtain three systems and then conducted 200 ns molecular dynamics simulations for the Apo, LWM, and ALPM systems. The results reveal a stronger binding affinity of the LWM peptide to XO, potentially due to increased hydrogen bond formation. Notable changes were observed in the XO tunnel upon inhibitor binding, particularly with LWM, which showed a thinner, longer, and more twisted configuration compared to ALPM. The study highlights the importance of residue F914 in the allosteric pathway. Methodologically, we utilized the perturbed response scan (PRS) based on Python, enhancing tools for MD analysis. These findings deepen our understanding of food-derived anti-XO inhibitors and could inform the development of food-based therapeutics for reducing uric acid levels with minimal side effects.

Study on the Mechanism of Interaction between Dipeptidyl Peptidase 4 and Inhibitory Peptides Based on Gaussian Accelerated Molecular Dynamic Simulation.

Dipeptidyl peptidase 4 (DPP4) inhibitors can effectively inhibit the activity of DPP4, increasing the concentrations of glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), which allows for them to effectively contribute to the reduction of blood sugar levels. Leu-Pro-Ala-Val-Thr-Ile-Arg (LPAVTIR) and Leu-Pro-Pro-Glu-His-Asp-Trp-Arg (LPPEHDWR) were the two peptides with the strongest inhibitory activity against DPP4 selected from silkworm pupa proteins. In this study, four systems were established: Apo (ligand-free DPP4), IPI (IPI-bound DPP4), LPAVTIR (LPAVTIR-bound DPP4), LPPEHDWR (LPPEHDWR-bound DPP4), and Gaussian accelerated molecular dynamic (GaMD) simulation was conducted to investigate the mechanism of action of two inhibitory peptides binding to DPP4. Our study revealed that the LPAVTIR peptide possessed a more stable structure and exhibited a tighter binding to the Ser630 active site in DPP4, thus exhibiting a favorable competitive inhibition effect. In contrast, the LPPEHDWR peptide caused the horizontal α-helix (residues 201-215) composed of Glu205 and Glu206 residues in DPP4 to disappear. The spatial arrangement of active sites Ser630 relative to Glu205 and Glu206 was disrupted, resulting in enzyme inactivation. Moreover, the size of the substrate channel and cavity volume was significantly reduced after the binding of the inhibitory peptide to the protein, which was an important factor in the inhibition of the enzyme activity. A similar effect was also found from IPI (our positive control). By stabilizing the active site of DPP4, the IPI peptide induced the disappearance of the horizontal α-helix and a notable reduction in the active cavity volume. In conclusion, our study provided a solid theoretical foundation for the inhibitory mechanisms of IPI, LPAVTIR, and LPPEHDWR on DPP4, offering valuable insights for advancing the development of drug targets for type 2 diabetes.

Deciphering single-cell protein secretion and gene expressions by constructing cell-antibody conjugates.

Secreted proteins play critical roles in regulating immune responses, exerting cytotoxic effects on tumor cells, promoting inflammatory processes, and influencing cellular metabolism. Deciphering the intricate relationship between the heterogeneity of secreted proteins and their transcriptional states is pivotal in the study of cellular heterogeneity. Here we proposed a cell-antibody conjugate-based sequencing methodology (Cellab-seq) for joint characterization of secreted proteins and transcriptome. Cellab-seq utilizes a chemoenzymatic strategy to construct cell-antibody conjugates, which enables the capture of secreted proteins and their signal transduction with the incorporation of barcode detection antibodies. We applied Cellab-seq to investigate how gene expression influences the activity of secreted proteins in NK cells. Altogether, this strategy facilitates a nuanced understanding of cellular dynamics under diverse physiological conditions, ultimately contributing to the prevention, diagnosis and treatment of diseases.

Network Pharmacology Combined with Machine Learning to Reveal the Action Mechanism of Licochalcone Intervention in Liver Cancer.

There are reports indicating that licochalcones can inhibit the proliferation, migration, and invasion of cancer cells by promoting the expression of autophagy-related proteins, inhibiting the expression of cell cycle proteins and angiogenic factors, and regulating autophagy and apoptosis. This study aims to reveal the potential mechanisms of licochalcone A (LCA), licochalcone B (LCB), licochalcone C (LCC), licochalcone D (LCD), licochalcone E (LCE), licochalcone F (LCF), and licochalcone G (LCG) inhibition in liver cancer through computer-aided screening strategies. By using machine learning clustering analysis to search for other structurally similar components in licorice, quantitative calculations were conducted to collect the structural commonalities of these components related to liver cancer and to identify key residues involved in the interactions between small molecules and key target proteins. Our research results show that the seven licochalcones molecules interfere with the cancer signaling pathway via the NF-κB signaling pathway, PDL1 expression and PD1 checkpoint pathway in cancer, and others. Glypallichalcone, Echinatin, and 3,4,3',4'-Tetrahydroxy-2-methoxychalcone in licorice also have similar structures to the seven licochalcones, which may indicate their similar effects. We also identified the key residues (including ASN364, GLY365, TRP366, and TYR485) involved in the interactions between ten flavonoids and the key target protein (nitric oxide synthase 2). In summary, we provide valuable insights into the molecular mechanisms of the anticancer effects of licorice flavonoids, providing new ideas for the design of small molecules for liver cancer drugs.

Probing the mechanisms of hydrazide-based HDAC inhibitors binding to HDAC3 using Gaussian accelerated molecular dynamics (GaMD) simulations.

Histone deacetylases (HDACs) have emerged as promising targets for anticancer drug development. They regulate gene expression by removing acetyl groups from lysine residues on histone tails, leading to chromatin condensation. A hydrazide-based HDAC inhibitor, N-(4-(2-Propylhydrazine-1-carbonyl)benzyl)-1H-indole-2-carboxamide (11h), has been reported to exhibit significant in vivo antitumor activity. In comparison to the lead compound N-(4-(2-Propylhydrazine-1-carbonyl)benzyl)cinnamamide (17), compound 11h demonstrates 2- to 5-fold higher HDAC inhibition and cell-based antitumor activity. However, the inhibitory mechanism of 11h remains insufficiently explored. In this study, we conducted 500 ns Gaussian Accelerated Molecular Dynamics (GaMD) simulations on Histone deacetylase 3 (HDAC3) and two complex systems (HDAC3-17 and HDAC3-11h). Our findings revealed that upon inhibitor binding, the active pocket volume of HDAC3 undergone alterations, and the movement of the L6-loop toward the active site impeded substrate entry. Moreover, we observed a destabilization of the α-helix in the aa75-89 region of HDAC3 compared to the two complex systems, indicating partial unwinding. Notably, 11h exhibited a closer proximity of its carbonyl oxygen to the active pocket's Zn2+ metal compared to 17, increasing the likelihood of coordination with the Zn2+ metal. The analysis of protein-ligand interactions highlighted a greater number of hydrogen bonds and other interactions between 11h and the receptor protein when compared to 17, underscoring the stronger binding of 11h to HDAC3. In conclusion, our study provided theoretical insights into the inhibitory mechanism of hydrazide-based HDAC inhibitors on HDAC3, thereby contributing to the development of improved drug targets for cancer therapy.Communicated by Ramaswamy H. Sarma.

Functionalized Fullerene Potentially Inhibits SARS-CoV-2 Infection by Modulating Spike Protein Conformational Changes.

The disease of SARS-CoV-2 has caused considerable morbidity and mortality globally. Spike proteins on the surface of SARS-CoV-2 allow it to bind with human cells, leading to infection. Fullerenes and their derivatives are promising SARS-CoV-2 inhibitors and drug-delivery vehicles. In this study, Gaussian accelerated molecular dynamics simulations and the Markov state model were employed to delve into the inhibitory mechanism of Fullerene-linear-polyglycerol-b-amine sulfate (F-LGPS) on spike proteins. During the study, it was discovered that fullerene derivatives can operate at the interface of the receptor-binding domain (RBD) and the N-terminal domain (NTD), keeping structural domains in a downward conformation. It was also observed that F-LGPS demonstrated superior inhibitory effects on the XBB variant in comparison to the wild-type variant. This study yielded invaluable insights for the potential development of efficient therapeutics targeting the spike protein of SARS-CoV-2.

Investigating the Vital Role of the Identified Abietic Acid from Helianthus annuus L. Calathide Extract against Hyperuricemia via Human Embryonic Kidney 293T Cell Model.

To explore the anti-hyperuricemia components in sunflower (Helianthus annuus L.) calathide extract (SCE), we identified abietic acid (AA) via liquid chromatography-mass spectrometry and found an excellent inhibitor of xanthine oxidase (IC50 = 10.60 µM, Ki = 193.65 nM) without cytotoxicity. Based on the transcriptomics analysis of the human embryonic kidney 293T cell model established using 1 mM uric acid, we evaluated that AA showed opposite modulation of purine metabolism to the UA group and markedly suppressed the intensity of purine nucleoside phosphorylase, ribose phosphate pyrophosphokinase 2, and ribose 5-phosphate isomerase A. Molecular docking also reveals the inhibition of purine nucleoside phosphorylase and ribose phosphate pyrophosphokinase 1. The SCE exhibits similar regulation of these genes, so we conclude that AA was a promising component in SCE against hyperuricemia. This present study provided a novel cell model for screening anti-hyperuricemia natural drugs in vitro and illustrated that AA, a natural diterpenoid, is a potential inhibitor of purine biosynthesis or metabolism.

Ru(bpy)3 2+ -Enabled Cell-Surface Photocatalytic Proximity Labeling toward More Efficient Capture of Physically Interacting Cells.

Intercellular proximity labeling has emerged as a promising approach to enable the study of cell-cell interactions (CCIs), but the efficiency of current platforms is limited. Here, we use Ru(bpy)3 2+ to construct an efficient photocatalytic proximity labeling (PPL) system on the cell surface that allows the highly discriminative CCI detection with spatiotemporal resolution. Through the mechanism study and quantitative characterization on living cells, we demonstrate that the singlet-oxygen (1 O2 ) mechanism is more efficient and specific than the single electron transfer (SET) mechanism in Ru-mediated PPL. Ru(bpy)3 2+ catalysts with different cell-anchoring moieties are prepared to facilitate the catalyst loading on primary cells. Finally, based on this system, we develop a "live" T cell receptor (TCR) multimer with TCR-T cells that could sensitively identify and discriminate cells presenting antigens of different affinity, providing a powerful tool to better understand the heterogeneity of antigen presenting cells.

Use of intercellular proximity labeling to quantify and decipher cell-cell interactions directed by diversified molecular pairs.

FucoID is an intercellular proximity labeling technique for studying cell-cell interactions (CCIs) via fucosyltransferase (FT)-meditated fucosyl-biotinylation, which has been applied to probe antigen-specific dendritic cell (DC)-T cell interactions. In this system, bait cells of interest with cell surface-anchored FT are used to capture the interacting prey cells by transferring a biotin-modified substrate to prey cells. Here, we leveraged FucoID to study CCIs directed by different molecular pairs, e.g., programmed cell death protein-1(PD-1)/programmed cell death protein-ligand-1 (PD-L1), and identify unknown or little studied CCIs, e.g., the interaction of DCs and B cells. To expand the application of FucoID to complex systems, we also synthesized site-specific antibody-based FT conjugate, which substantially improves the ability of FucoID to probe molecular signatures of specific CCI when cells of interest (bait cells) cannot be purified, e.g., in clinical samples. Collectively, these studies demonstrate the general applicability of FucoID to study unknown CCIs in complex systems at a molecular resolution.

In Silico Discovery of Anticancer Peptides from Sanghuang.

Anticancer peptide (ACP) is a short peptide with less than 50 amino acids that has been discovered in a variety of foods. It has been demonstrated that traditional Chinese medicine or food can help treat cancer in some cases, which suggests that ACP may be one of the therapeutic ingredients. Studies on the anti-cancer properties of Sanghuangporus sanghuang have concentrated on polysaccharides, flavonoids, triterpenoids, etc. The function of peptides has not received much attention. The purpose of this study is to use computer mining techniques to search for potential anticancer peptides from 62 proteins of Sanghuang. We used mACPpred to perform sequence scans after theoretical trypsin hydrolysis and discovered nine fragments with an anticancer probability of over 0.60. The study used AlphaFold 2 to perform structural modeling of the first three ACPs discovered, which had blast results from the Cancer PPD database. Using reverse docking technology, we found the target proteins and interacting residues of two ACPs with an unknown mechanism. Reverse docking results predicted the binding modes of the ACPs and their target protein. In addition, we determined the active part of ACPs by quantum chemical calculation. Our study provides a framework for the future discovery of functional peptides from foods. The ACPs discovered have the potential to be used as drugs in oncology clinical treatment after further research.

In silico study to predict potential precursors of human dipeptidyl peptidase-IV inhibitors from hazelnut.

Chinese hazelnut was chosen to become a probable precursor of biological active peptides via computer simulations in this article. There were a large number of bioactive peptides in Chinese hazelnut sequences according to analytical results from the BIOPEP database. The most prominent of these was the inhibitory peptide for dipeptidyl peptidase-IV (DPP-IV; EC 3.4.14.5), which can be used to treat type 2 diabetes, so the theoretical method to obtain DPP-IV inhibitory peptides by hydrolysis with a single or combination of enzymes was studied. Cytotoxicity analysis performed by ToxinPred showed that all of the DPP-IV inhibitory peptides generated from protein hydrolysis were not cytotoxic. Structural interaction fingerprint analysis revealed that Asp663 and Phe357 may be important residues for ligand binding. In order to further understand the inhibitory mechanism of peptide, VR with lowest half maximum inhibitory concentration (IC50) and IPI (inhibitors have been reported) were selected as ligand of DPP-IV to perform steered molecular dynamics simulations and PMF calculations. The results showed that P1 is the preferred (un)binding tunnel for the inhibitors obtained. Our findings help in the development of new DPP-IV inhibitors which were derived from common food.Communicated by Ramaswamy H. Sarma.

Chemical Compounds, Antioxidant Activities, and Inhibitory Activities Against Xanthine Oxidase of the Essential Oils From the Three Varieties of Sunflower (Helianthus annuus L.) Receptacles.

Background/Aim: Essential oils of sunflower receptacles (SEOs) have antibacterial and antioxidant potential. However, the differences of biological activities from the different varieties of sunflowers have not been studied till now. The purpose of this study was to compare the differences of chemical compounds, antioxidant activities, and inhibitory activities against xanthine oxidase (XO) of SEOs from the three varieties of sunflowers including LD5009, SH363, and S606. Methods: SEOs were extracted by using the optimal extraction conditions selected by response surface methodology (RSM). Chemical compounds of SEOs were identified from the three varieties of sunflowers by gas chromatography-mass spectrometry (GC-MS). Antioxidant activities of SEOs were detected by 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), 2,2-diphenyl-1-picrylhydrazyl (DPPH), and iron ion reduction ability. Inhibitory activities of SEOs against XO were measured by using UV spectrophotometer. XO inhibitors were selected from the main chemical compounds of SEOs by the high-throughput selections and molecular simulation docking. Results: The extraction yields of SEOs from LD5009, SH363, and S606 were 0.176, 0.319, and 0.580%, respectively. A total of 101 chemical compounds of SEOs were identified from the three varieties of sunflowers. In addition, the results of inhibitory activities against XO showed that SEOs can reduce uric acid significantly. Eupatoriochromene may be the most important chemical compounds of SEOs for reducing uric acid. The results of antioxidant activities and inhibitory activities against XO showed that SEOs of LD5009 had the strongest antioxidant and XO inhibitory activities. The Pearson correlation coefficient (r > 0.95) showed that γ-terpinene, (E)-citral, and L-Bornyl acetate were highly correlated with the antioxidant activities and XO inhibitory ability. Conclusion: SEOs had antioxidant activities and XO inhibitory ability. It would provide more scientific information for utilization and selection of varieties of sunflowers, which would increase the food quality of sunflowers and incomes of farmers.

Molecular Dynamics Simulations Study of the Interactions between Human Dipeptidyl-Peptidase III and Two Substrates.

Human dipeptidyl-peptidase III (hDPP III) is capable of specifically cleaving dipeptides from the N-terminal of small peptides with biological activity such as angiotensin II (Ang II, DRVYIHPF), and participates in blood pressure regulation, pain modulation, and the development of cancers in human biological activities. In this study, 500 ns molecular dynamics simulations were performed on free-hDPP III (PDB code: 5E33), hDPP III-Ang II (PDB code: 5E2Q), and hDPP III-IVYPW (PDB code: 5E3C) to explore how these two peptides affect the catalytic efficiency of enzymes in terms of the binding mode and the conformational changes. Our results indicate that in the case of the hDPP III-Ang II complex, subsite S1 became small and hydrophobic, which might be propitious for the nucleophile to attack the substrate. The structures of the most stable conformations of the three systems revealed that Arg421-Lys423 could form an α-helix with the presence of Ang II, but only part of the α-helix was produced in hDPP III-IVYPW. As the hinge structure in hDPP III, the conformational changes that took place in the Arg421-Lys423 residue could lead to the changes in the shape and space of the catalytic subsites, which might allow water to function as a nucleophile to attack the substrate. Our results may provide new clues to enable the design of new inhibitors for hDPP III in the future.

Targeting N-Terminal Human Maltase-Glucoamylase to Unravel Possible Inhibitors Using Molecular Docking, Molecular Dynamics Simulations, and Adaptive Steered Molecular Dynamics Simulations.

There are multiple drugs for the treatment of type 2 diabetes, including traditional sulfonylureas biguanides, glinides, thiazolidinediones, α-glucosidase inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, dipeptidyl peptidase IV (DPP-4) inhibitors, and sodium-glucose cotransporter 2 (SGLT2) inhibitors. α-Glucosidase inhibitors have been used to control postprandial glucose levels caused by type 2 diabetes since 1990. α-Glucosidases are rather crucial in the human metabolic system and are principally found in families 13 and 31. Maltase-glucoamylase (MGAM) belongs to glycoside hydrolase family 31. The main function of MGAM is to digest terminal starch products left after the enzymatic action of α-amylase; hence, MGAM becomes an efficient drug target for insulin resistance. In order to explore the conformational changes in the active pocket and unbinding pathway for NtMGAM, molecular dynamics (MD) simulations and adaptive steered molecular dynamics (ASMD) simulations were performed for two NtMGAM-inhibitor [de-O-sulfonated kotalanol (DSK) and acarbose] complexes. MD simulations indicated that DSK bound to NtMGAM may influence two domains (inserted loop 1 and inserted loop 2) by interfering with the spiralization of residue 497-499. The flexibility of inserted loop 1 and inserted loop 2 can influence the volume of the active pocket of NtMGAM, which can affect the binding progress for DSK to NtMGAM. ASMD simulations showed that compared to acarbose, DSK escaped from NtMGAM easily with lower energy. Asp542 is an important residue on the bottleneck of the active pocket of NtMGAM and could generate hydrogen bonds with DSK continuously. Our theoretical results may provide some useful clues for designing new α-glucosidase inhibitors to treat type 2 diabetes.