Investigation of morphology and structure of drug-loaded PLA-b-PEO-b-PLA polymeric micelle: A dissipative particle dynamics simulations study.

The dissipative particle dynamics (DPD) simulation was used to study the morphologies and structures of the paclitaxel-loaded PLA-b-PEO-b-PLA polymeric micelle. We focused on the influences of PLA block length, PLA-b-PEO-b-PLA copolymer concentration, paclitaxel drug content on morphologies and structures of the micelle. Our simulations show that: (i) with the PLA block length increase, the self-assemble structure of PLA-b-PEO-b-PLA copolymers with paclitaxel vary between onion-like structure (core-middle layer-shell) to spherical core-shell structure. The PEO shell thins and the size of the PLA core increases. The onionlike structures are comprised of the PEO hydrophilic core, the PLA hydrophobic middle layer, and the PEO hydrophilic shell, the distribution of the paclitaxel drug predominantly occurs within the hydrophobic intermediate layer; (ii) The system forms a spherical core-shell structure when a small amount of the drug is added, and within a certain range, the size of the spherical structure increases as the drug amount increases. When the drug contents (volume fraction) cdrug = 10%, it can be observed that the PLA4-b-PEO19-b-PLA4 spherical structures connect to form rod-shaped structures. With the length of PLA block NPLA = 8, as the paclitaxel drug concentrations cdrug = 4%, PEO has been insufficient to completely encapsulate the PLA and paclitaxel drug beads. To enhance drug loading capacity while maintaining stability of the system in aqueous solution, the optimal composition for loading paclitaxel is PLA4-b-PEO19-b-PLA4; the drug content is not higher than 4%; (iii) The paclitaxel-loaded PLA4-b-PEO19-b-PLA4 micelle undergo the transition from onionlike (core-middle layer-shell) to spherical (core-shell) to rod-shaped and lamellar structure as the PLA4-b-PEO19-b-PLA4 copolymer concentration increases from ccp = 10% to 40%.

Globospiramine from Voacanga globosa Exerts Robust Cytotoxic and Antiproliferative Activities on Cancer Cells by Inducing Caspase-Dependent Apoptosis in A549 Cells and Inhibiting MAPK14 (p38α): In Vitro and Computational Investigations.

Bisindole alkaloids are a source of inspiration for the design and discovery of new-generation anticancer agents. In this study, we investigated the cytotoxic and antiproliferative activities of three spirobisindole alkaloids from the traditional anticancer Philippine medicinal plant Voacanga globosa, along with their mechanisms of action. Thus, the alkaloids globospiramine (1), deoxyvobtusine (2), and vobtusine lactone (3) showed in vitro cytotoxicity and antiproliferative activities against the tested cell lines (L929, KB3.1, A431, MCF-7, A549, PC-3, and SKOV-3) using MTT and CellTiter-Blue assays. Globospiramine (1) was also screened against a panel of breast cancer cell lines using the sulforhodamine B (SRB) assay and showed moderate cytotoxicity. It also promoted the activation of apoptotic effector caspases 3 and 7 using Caspase-Glo 3/7 and CellEvent-3/7 apoptosis assays. Increased expressions of cleaved caspase 3 and PARP in A549 cells treated with 1 were also observed. Apoptotic activity was also confirmed when globospiramine (1) failed to promote the rapid loss of membrane integrity according to the HeLa cell membrane permeability assay. Network pharmacology analysis, molecular docking, and molecular dynamics simulations identified MAPK14 (p38α), a pharmacological target leading to cancer cell apoptosis, as a putative target. Low toxicity risks and favorable drug-likeness were also predicted for 1. Overall, our study demonstrated the anticancer potentials and apoptotic mechanisms of globospiramine (1), validating the traditional medicinal use of Voacanga globosa.

Multi-epitope vaccine design using in silico analysis of glycoprotein and nucleocapsid of NIPAH virus.

According to the 2018 WHO R&D Blueprint, Nipah virus (NiV) is a priority disease, and the development of a vaccine against NiV is strongly encouraged. According to criteria used to categorize zoonotic diseases, NiV is a stage III disease that can spread to people and cause unpredictable outbreaks. Since 2001, the NiV virus has caused annual outbreaks in Bangladesh, while in India it has caused occasional outbreaks. According to estimates, the mortality rate for infected individuals ranges from 70 to 91%. Using immunoinformatic approaches to anticipate the epitopes of the MHC-I, MHC-II, and B-cells, they were predicted using the NiV glycoprotein and nucleocapsid protein. The selected epitopes were used to develop a multi-epitope vaccine construct connected with linkers and adjuvants in order to improve immune responses to the vaccine construct. The 3D structure of the engineered vaccine was anticipated, optimized, and confirmed using a variety of computer simulation techniques so that its stability could be assessed. According to the immunological simulation tests, it was found that the vaccination elicits a targeted immune response against the NiV. Docking with TLR-3, 7, and 8 revealed that vaccine candidates had high binding affinities and low binding energies. Finally, molecular dynamic analysis confirms the stability of the new vaccine. Codon optimization and in silico cloning showed that the proposed vaccine was expressed to a high degree in Escherichia coli. The study will help in identifying a potential epitope for a vaccine candidate against NiV. The developed multi-epitope vaccine construct has a lot of potential, but they still need to be verified by in vitro & in vivo studies.

An Overview of SARS-CoV-2 Potential Targets, Inhibitors, and Computational Insights to Enrich the Promising Treatment Strategies.

The rapid spread of the SARS-CoV-2 virus has emphasized the urgent need for effective therapies to combat COVID-19. Investigating the potential targets, inhibitors, and in silico approaches pertinent to COVID-19 are of utmost need to develop novel therapeutic agents and reprofiling of existing FDA-approved drugs. This article reviews the viral enzymes and their counter receptors involved in the entry of SARS-CoV-2 into host cells, replication of genomic RNA, and controlling the host cell physiology. In addition, the study provides an overview of the computational techniques such as docking simulations, molecular dynamics, QSAR modeling, and homology modeling that have been used to find the FDA-approved drugs and other inhibitors against SARS-CoV-2. Furthermore, a comprehensive overview of virus-based and host-based druggable targets from a structural point of view, together with the reported therapeutic compounds against SARS-CoV-2 have also been presented. The current study offers future perspectives for research in the field of network pharmacology investigating the large unexplored molecular libraries. Overall, the present in-depth review aims to expedite the process of identifying and repurposing drugs for researchers involved in the field of COVID-19 drug discovery.

Multimodal binding and inhibition of bacterial ribosomes by the antimicrobial peptides Api137 and Api88.

Proline-rich antimicrobial peptides (PrAMPs) inhibit bacterial protein biosynthesis by binding to the polypeptide exit tunnel (PET) near the peptidyl transferase center. Api137, an optimized derivative of honeybee PrAMP apidaecin, inhibits protein expression by trapping release factors (RFs), which interact with stop codons on ribosomes to terminate translation. This study uses cryo-EM, functional assays and molecular dynamic (MD) simulations to show that Api137 additionally occupies a second binding site near the exit of the PET and can repress translation independently of RF-trapping. Api88, a C-terminally amidated (-CONH2) analog of Api137 (-COOH), binds to the same sites, occupies a third binding pocket and interferes with the translation process presumably without RF-trapping. In conclusion, apidaecin-derived PrAMPs inhibit bacterial ribosomes by multimodal mechanisms caused by minor structural changes and thus represent a promising pool for drug development efforts.

Isolation, Characterization, Genome Annotation, and Evaluation of Hyaluronidase Inhibitory Activity in Secondary Metabolites of Brevibacillus sp. JNUCC 41: A Comprehensive Analysis through Molecular Docking and Molecular Dynamics Simulation.

Brevibacillus sp. JNUCC 41, characterized as a plant-growth-promoting rhizobacterium (PGPR), actively participates in lipid metabolism and biocontrol based on gene analysis. This study aimed to investigate the crucial secondary metabolites in biological metabolism; fermentation, extraction, and isolation were performed, revealing that methyl indole-3-acetate showed the best hyaluronidase (HAase) inhibitory activity (IC50: 343.9 µM). Molecular docking results further revealed that the compound forms hydrogen bonds with the residues Tyr-75 and Tyr-247 of HAase (binding energy: -6.4 kcal/mol). Molecular dynamics (MD) simulations demonstrated that the compound predominantly binds to HAase via hydrogen bonding (MM-PBSA binding energy: -24.9 kcal/mol) and exhibits good stability. The residues Tyr-247 and Tyr-202, pivotal for binding in docking, were also confirmed via MD simulations. This study suggests that methyl indole-3-acetate holds potential applications in anti-inflammatory and anti-aging treatments.

Molecular Dynamics Insights into the Aggregation Behavior of N-Terminal ß-Lactoglobulin Peptides.

ß-lactoglobulin (BLG) forms amyloid-like aggregates at high temperatures, low pH, and low ionic strengths. At a pH below 2, BLG undergoes hydrolysis into peptides, with N-terminal peptides 1-33 and 1-52 being prone to fibrillization, forming amyloid-like fibrils. Due to their good mechanical properties, BLG amyloids demonstrate great potential for diverse applications, including biosensors, nanocomposites, and catalysts. Consequently, further studies are essential to comprehensively understand the factors governing the formation of BLG amyloid-like morphologies. In this study, all-atom molecular dynamics simulations were employed to explore the aggregation of N-terminal 1-33 and 1-52 BLG peptides under conditions of pH 2 and at 10 mM NaCl concentration. The simulations revealed that the peptides spontaneously assembled into aggregates of varying sizes. The aggregation process was enabled by the low charge of peptides and the presence of hydrophobic residues within them. As the peptides associated into aggregates, there was a concurrent increase in ß-sheet structures and the establishment of hydrogen bonds, enhancing the stability of the aggregates. Notably, on average, 1-33 peptides formed larger aggregates compared to their 1-52 counterparts, while the latter exhibited a slightly higher content of ß-sheets and higher cluster orderliness. The applied approach facilitated insights into the early stages of amyloid-like aggregation and molecular-level insight into the formation of ß-sheets, which serve as nucleation points for further fibril growth.

Differential Solvent DEEP-STD NMR and MD Simulations Enable the Determinants of the Molecular Recognition of Heparin Oligosaccharides by Antithrombin to Be Disentangled.

The interaction of heparin with antithrombin (AT) involves a specific sequence corresponding to the pentasaccharide GlcNAc/NS6S-GlcA-GlcNS3S6S-IdoA2S-GlcNS6S (AGA*IA). Recent studies have revealed that two AGA*IA-containing hexasaccharides, which differ in the sulfation degree of the iduronic acid unit, exhibit similar binding to AT, albeit with different affinities. However, the lack of experimental data concerning the molecular contacts between these ligands and the amino acids within the protein-binding site prevents a detailed description of the complexes. Differential epitope mapping (DEEP)-STD NMR, in combination with MD simulations, enables the experimental observation and comparison of two heparin pentasaccharides interacting with AT, revealing slightly different bound orientations and distinct affinities of both glycans for AT. We demonstrate the effectiveness of the differential solvent DEEP-STD NMR approach in determining the presence of polar residues in the recognition sites of glycosaminoglycan-binding proteins.

How to Personalize General Anesthesia-A Prospective Theoretical Approach to Conformational Changes of Halogenated Anesthetics in Fire Smoke Poisoning.

Smoke intoxication is a central event in mass burn incidents, and toxic smoke acts at different levels of the body, blocking breathing and oxygenation. The majority of these patients require early induction of anesthesia to preserve vital functions. We studied the influence of hemoglobin (HMG) and myoglobin (MGB) blockade by hydrochloric acid (HCl) in an interaction model with gaseous anesthetics using molecular docking techniques. In the next part of the study, molecular dynamics (MD) simulations were performed on the top-scoring ligand-receptor complexes to investigate the stability of the ligand-receptor complexes and the interactions between ligands and receptors in more detail. Through docking analysis, we observed that hemoglobin creates more stable complexes with anesthetic gases than myoglobin. Intoxication with gaseous hydrochloric acid produces conformational and binding energy changes of anesthetic gases to the substrate (both the pathway and the binding site), the most significant being recorded in the case of desflurane and sevoflurane, while for halothane and isoflurane, they remain unchanged. According to our theoretical model, the selection of anesthetic agents for patients affected by fire smoke containing hydrochloric acid is critical to ensure optimal anesthetic effects. In this regard, our model suggests that halothane and isoflurane are the most suitable choices for predicting the anesthetic effects in such patients when compared to sevoflurane and desflurane.

Competitive Inhibition of Okanin against Plasmodium falciparum Tyrosyl-tRNA Synthetase.

Malaria is a severe disease that presents a significant threat to human health. As resistance to current drugs continues to increase, there is an urgent need for new antimalarial medications. Aminoacyl-tRNA synthetases (aaRSs) represent promising targets for drug development. In this study, we identified Plasmodium falciparum tyrosyl-tRNA synthetase (PfTyrRS) as a potential target for antimalarial drug development through a comparative analysis of the amino acid sequences and three-dimensional structures of human and plasmodium TyrRS, with particular emphasis on differences in key amino acids at the aminoacylation site. A total of 2141 bioactive compounds were screened using a high-throughput thermal shift assay (TSA). Okanin, known as an inhibitor of LPS-induced TLR4 expression, exhibited potent inhibitory activity against PfTyrRS, while showing limited inhibition of human TyrRS. Furthermore, bio-layer interferometry (BLI) confirmed the high affinity of okanin for PfTyrRS. Molecular dynamics (MD) simulations highlighted the stable conformation of okanin within PfTyrRS and its sustained binding to the enzyme. A molecular docking analysis revealed that okanin binds to both the tyrosine and partial ATP binding sites of the enzyme, preventing substrate binding. In addition, the compound inhibited the production of Plasmodium falciparum in the blood stage and had little cytotoxicity. Thus, okanin is a promising lead compound for the treatment of malaria caused by P. falciparum.

Investigation of collagen reconstruction mechanism in skin wound through dual-beam laser welding: Insights from multi-spectroscopy, molecular dynamics simulation, and finite element multiphysics simulation.

Since the mechanism underlying real-time acquisition of mechanical strength during laser-induced skin wound fusion remains unclear, and collagen is the primary constituent of skin tissue, this study investigates the structural and mechanical alterations in collagen at temperatures ranging from 40 °C to 60 °C using various spectroscopic techniques and molecular dynamics calculations. The COMSOL Multiphysics coupling is employed to simulate the three-dimensional temperature field, stress-strain relationship, and light intensity distribution in the laser thermal affected zone of skin wounds during dual-beam laser welding process. Raman spectroscopy, synchronous fluorescence spectroscopy and circular dichroism measurement results confirm that laser energy activates biological activity in residues, leading to a transformation in the originally fractured structure of collagen protein for enhanced mechanical strength. Molecular dynamics simulations reveal that stable hydrogen bonds form at amino acid residues within the central region of collagen protein when the overall temperature peak around the wound reaches 60 °C, thereby providing stability to previously fractured skin incisions and imparting instantaneous strength. However, under a 55 °C system, Type I collagen ensures macrostructural stability while activating biological properties at amino acid bases to promote wound healing function; this finding aligns with experimental analysis results. The COMSOL simulation outcomes also correspond well with macroscopic morphology after laser welding samples, confirming that by maintaining temperatures between 55 °C-60 °C during laser welding of skin incisions not only can certain instantaneous mechanical strength be achieved but irreversible thermal damage can also be effectively controlled. It is anticipated that these findings will provide valuable insights into understanding the healing mechanism for laser-welded skin wounds.

Unveiling molecular insights: in silico exploration of TLR4 antagonist for management of dry eye syndrome.

BACKGROUND: Dry eye disease is the most commonplace multifractional ocular complication, which has already affected millions of people in the world. It is identified by the excessive buildup of reactive oxygen species, leading to substantial corneal epithelial cell demise and ocular surface inflammation attributed to TLR4. In this study, we aimed to identify potential compounds to treat of dry eye syndrome by exploring in silico methods. METHODS: In this research, molecular docking and dynamics simulation tests were used to examine the effects of selected compounds on TLR4 receptor. Compounds were extracted from different databases and were prepared and docked against TLR4 receptor via Autodock Vina. Celastrol, lumacaftor and nilotinib were selected for further molecular dynamics studies for a deeper understanding of molecular systems consisting of protein and ligands by using the Desmond module of the Schrodinger Suite. RESULTS: The docking results revealed that the compounds are having binding affinity in the range of -5.1 to -8.78 based on the binding affinity and three-dimensional interactions celastrol, lumacaftor and nilotinib were further studied for their activity by molecular dynamics. Among the three compounds, celastrol was the most stable based on molecular dynamics trajectory analysis from 100 ns in the catalytic pockets of 2Z63.pdb.pdb. Root mean square deviation of celastrol/2Z63 was in the range of 1.8-4.8 Å. CONCLUSION: In particular, Glu376 of TLR4 receptor is crucial for the identification and binding of lipopolysaccharides (LPS), which are part of Gram-negative bacteria's outer membrane. In our investigation, celastrol binds to Glu376, suggesting that celastrol may prevent the dry eye syndrome by inhibiting LPS's binding to TLR4.

Treatment of flexibility of protein backbone in simulations of protein-ligand interactions using steered molecular dynamics.

To ensure that an external force can break the interaction between a protein and a ligand, the steered molecular dynamics simulation requires a harmonic restrained potential applied to the protein backbone. A usual practice is that all or a certain number of protein's heavy atoms or Cα atoms are fixed, being restrained by a small force. This present study reveals that while fixing both either all heavy atoms and or all Cα atoms is not a good approach, while fixing a too small number of few atoms sometimes cannot prevent the protein from rotating under the influence of the bulk water layer, and the pulled molecule may smack into the wall of the active site. We found that restraining the Cα atoms under certain conditions is more relevant. Thus, we would propose an alternative solution in which only the Cα atoms of the protein at a distance larger than 1.2 nm from the ligand are restrained. A more flexible, but not too flexible, protein will be expected to lead to a more natural release of the ligand.

Dishevelled2 activates WGEF via its interaction with a unique internal peptide motif of the GEF.

The Wnt-planar cell polarity (Wnt-PCP) pathway is crucial in establishing cell polarity during development and tissue homoeostasis. This pathway is found to be dysregulated in many pathological conditions, including cancer and autoimmune disorders. The central event in Wnt-PCP pathway is the activation of Weak-similarity guanine nucleotide exchange factor (WGEF) by the adapter protein Dishevelled (Dvl). The PDZ domain of Dishevelled2 (Dvl2PDZ) binds and activates WGEF by releasing it from its autoinhibitory state. However, the actual Dvl2PDZ binding site of WGEF and the consequent activation mechanism of the GEF have remained elusive. Using biochemical and molecular dynamics studies, we show that a unique "internal-PDZ binding motif" (IPM) of WGEF mediates the WGEF-Dvl2PDZ interaction to activate the GEF. The residues at P2, P0, P-2 and P-3 positions of IPM play an important role in stabilizing the WGEFpep-Dvl2PDZ interaction. Furthermore, MD simulations of modelled Dvl2PDZ-WGEFIPM peptide complexes suggest that WGEF-Dvl2PDZ interaction may differ from the reported Dvl2PDZ-IPM interactions. Additionally, the apo structure of human Dvl2PDZ shows conformational dynamics different from its IPM peptide bound state, suggesting an induced fit mechanism for the Dvl2PDZ-peptide interaction. The current study provides a model for Dvl2 induced activation of WGEF.

Identification of Helicobacter pylori-carcinogenic TNF-alpha-inducing protein inhibitors via daidzein derivatives through computational approaches.

Gastric cancer is considered a class 1 carcinogen that is closely linked to infection with Helicobacter pylori (H. pylori), which affects over 1 million people each year. However, the major challenge to fight against H. pylori and its associated gastric cancer due to drug resistance. This research gap had led our research team to investigate a potential drug candidate targeting the Helicobacter pylori-carcinogenic TNF-alpha-inducing protein. In this study, a total of 45 daidzein derivatives were investigated and the best 10 molecules were comprehensively investigated using in silico approaches for drug development, namely pass prediction, quantum calculations, molecular docking, molecular dynamics simulations, Lipinski rule evaluation, and prediction of pharmacokinetics. The molecular docking study was performed to evaluate the binding affinity between the target protein and the ligands. In addition, the stability of ligand-protein complexes was investigated by molecular dynamics simulations. Various parameters were analysed, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA) and dynamic cross-correlation matrix (DCCM). The results has confirmed that the ligand-protein complex CID: 129661094 (07) and 129664277 (08) formed stable interactions with the target protein. It was also found that CID: 129661094 (07) has greater hydrogen bond occupancy and stability, while the ligand-protein complex CID 129664277 (08) has greater conformational flexibility. Principal component analysis revealed that the ligand-protein complex CID: 129661094 (07) is more compact and stable. Hydrogen bond analysis revealed favourable interactions with the reported amino acid residues. Overall, this study suggests that daidzein derivatives in particular show promise as potential inhibitors of H. pylori.

RmsdXNA: RMSD prediction of nucleic acid-ligand docking poses using machine-learning method.

Small molecule drugs can be used to target nucleic acids (NA) to regulate biological processes. Computational modeling methods, such as molecular docking or scoring functions, are commonly employed to facilitate drug design. However, the accuracy of the scoring function in predicting the closest-to-native docking pose is often suboptimal. To overcome this problem, a machine learning model, RmsdXNA, was developed to predict the root-mean-square-deviation (RMSD) of ligand docking poses in NA complexes. The versatility of RmsdXNA has been demonstrated by its successful application to various complexes involving different types of NA receptors and ligands, including metal complexes and short peptides. The predicted RMSD by RmsdXNA was strongly correlated with the actual RMSD of the docked poses. RmsdXNA also outperformed the rDock scoring function in ranking and identifying closest-to-native docking poses across different structural groups and on the testing dataset. Using experimental validated results conducted on polyadenylated nuclear element for nuclear expression triplex, RmsdXNA demonstrated better screening power for the RNA-small molecule complex compared to rDock. Molecular dynamics simulations were subsequently employed to validate the binding of top-scoring ligand candidates selected by RmsdXNA and rDock on MALAT1. The results showed that RmsdXNA has a higher success rate in identifying promising ligands that can bind well to the receptor. The development of an accurate docking score for a NA-ligand complex can aid in drug discovery and development advancements. The code to use RmsdXNA is available at the GitHub repository https://github.com/laiheng001/RmsdXNA.

A salt bridge of the C-terminal carboxyl group regulates PHPT1 substrate affinity and catalytic activity.

PHPT1 is a histidine phosphatase that modulates signaling in eukaryotes through its catalytic activity. Here, we present an analysis of the structure and dynamics of PHPT1 through a combination of solution NMR, molecular dynamics, and biochemical experiments. We identify a salt bridge formed between the R78 guanidinium moiety and the C-terminal carboxyl group on Y125 that is critical for ligand binding. Disruption of the salt bridge by appending a glycine residue at the C-terminus (G126) leads to a decrease in catalytic activity and binding affinity for the pseudo substrate, para-nitrophenylphosphate (pNPP), as well as the active site inhibitor, phenylphosphonic acid (PPA). We show through NMR chemical shift, 15N relaxation measurements, and analysis of molecular dynamics trajectories, that removal of this salt bridge results in an active site that is altered both structurally and dynamically thereby significantly impacting enzymatic function and confirming the importance of this electrostatic interaction.

Decoding the mechanism governing the structural stability of wheat germ agglutinin and its isolated domains: A combined calorimetric, NMR, and MD simulation study.

Wheat germ agglutinin (WGA) demonstrates potential as an oral delivery agent owing to its selective binding to carbohydrates and its capacity to traverse biological membranes. In this study, we employed differential scanning calorimetry and molecular dynamics simulations to comprehensively characterize the thermal unfolding process of both the complete lectin and its four isolated domains. Furthermore, we present the nuclear magnetic resonance structures of three domains that were previously lacking experimental structures in their isolated forms. Our results provide a collective understanding of the energetic and structural factors governing the intricate unfolding mechanism of the complete agglutinin, shedding light on the specific role played by each domain in this process. The analysis revealed negligible interdomain cooperativity, highlighting instead significant coupling between dimer dissociation and the unfolding of the more labile domains. By comparing the dominant interactions, we rationalized the stability differences among the domains. Understanding the structural stability of WGA opens avenues for enhanced drug delivery strategies, underscoring its potential as a promising carrier throughout the gastrointestinal environment.

Deep learning path-like collective variable for enhanced sampling molecular dynamics.

Several enhanced sampling techniques rely on the definition of collective variables to effectively explore free energy landscapes. The existing variables that describe the progression along a reactive pathway offer an elegant solution but face a number of limitations. In this paper, we address these challenges by introducing a new path-like collective variable called the "deep-locally non-linear-embedding," which is inspired by principles of the locally linear embedding technique and is trained on a reactive trajectory. The variable mimics the ideal reaction coordinate by automatically generating a non-linear combination of features through a differentiable generalized autoencoder that combines a neural network with a continuous k-nearest neighbor selection. Among the key advantages of this method is its capability to automatically choose the metric for searching neighbors and to learn the path from state A to state B without the need to handpick landmarks a priori. We demonstrate the effectiveness of DeepLNE by showing that the progression along the path variable closely approximates the ideal reaction coordinate in toy models, such as the Müller-Brown potential and alanine dipeptide. Then, we use it in the molecular dynamics simulations of an RNA tetraloop, where we highlight its capability to accelerate transitions and estimate the free energy of folding.

Utilizing a structure-based virtual screening approach to discover potential LSD1 inhibitors.

BACKGROUND: Lysine-specific demethylase 1 (LSD1) is highly expressed in a variety of malignant tumors, rendering it a crucial epigenetic target for anti-tumor therapy. Therefore, the inhibition of LSD1 activity has emerged as a promising innovative therapeutic approach for targeted cancer treatment. METHODS: In our study, we employed innovative structure-based drug design methods to meticulously select compounds from the ZINC15 database. Utilizing virtual docking, we evaluated docking scores and binding modes to identify potential inhibitors. To further validate our findings, we harnessed molecular dynamic simulations and conducted meticulous biochemical experiments to deeply analyze the binding interactions between the protein and compounds. RESULTS: Our results showcased that ZINC10039815 exhibits an exquisite binding mode with LSD1, fitting perfectly into the active pocket and forming robust interactions with multiple critical residues of the protein. CONCLUSIONS: With its significant inhibitory effect on LSD1 activity, ZINC10039815 emerges as a highly promising candidate for the development of novel LSD1 inhibitors.