Conformations of a highly expressed Z19 α-zein studied with AlphaFold2 and MD simulations.

α-zeins are amphiphilic maize seed storage proteins with material properties suitable for a multitude of applications e.g., in renewable plastics, foods, therapeutics and additive manufacturing (3D-printing). To exploit their full potential, molecular-level insights are essential. The difficulties in experimental atomic-resolution characterization of α-zeins have resulted in a diversity of published molecular models. However, deep-learning α-zein models are largely unexplored. Therefore, this work studies an AlphaFold2 (AF2) model of a highly expressed α-zein using molecular dynamics (MD) simulations. The sequence of the α-zein cZ19C2 gave a loosely packed AF2 model with 7 α-helical segments connected by turns/loops. Compact tertiary structure was limited to a C-terminal bundle of three α-helices, each showing notable agreement with a published consensus sequence. Aiming to chart possible α-zein conformations in practically relevant solvents, rather than the native solid-state, the AF2 model was subjected to MD simulations in water/ethanol mixtures with varying ethanol concentrations. Despite giving structurally diverse endpoints, the simulations showed several patterns: In water and low ethanol concentrations, the model rapidly formed compact globular structures, largely preserving the C-terminal bundle. At ≥ 50 mol% ethanol, extended conformations prevailed, consistent with previous SAXS studies. Tertiary structure was partially stabilized in water and low ethanol concentrations, but was disrupted in ≥ 50 mol% ethanol. Aggregated results indicated minor increases in helicity with ethanol concentration. ß-sheet content was consistently low (∼1%) across all conditions. Beyond structural dynamics, the rapid formation of branched α-zein aggregates in aqueous environments was highlighted. Furthermore, aqueous simulations revealed favorable interactions between the protein and the crosslinking agent glycidyl methacrylate (GMA). The proximity of GMA epoxide carbons and side chain hydroxyl oxygens simultaneously suggested accessible reactive sites in compact α-zein conformations and pre-reaction geometries for methacrylation. The findings may assist in expanding the applications of these technologically significant proteins, e.g., by guiding chemical modifications.

Fast collective motions of backbone in transmembrane α helices are critical to water transfer of aquaporin.

Fast collective motions are widely present in biomolecules, but their functional relevance remains unclear. Herein, we reveal that fast collective motions of backbone are critical to the water transfer of aquaporin Z (AqpZ) by using solid-state nuclear magnetic resonance (ssNMR) spectroscopy and molecular dynamics (MD) simulations. A total of 212 residue site-specific dipolar order parameters and 158 15N spin relaxation rates of the backbone are measured by combining the 13C- and 1H-detected multidimensional ssNMR spectra. Analysis of these experimental data by theoretic models suggests that the small-amplitude (~10°) collective motions of the transmembrane α helices on the nanosecond-to-microsecond timescales are dominant for the dynamics of AqpZ. The MD simulations demonstrate that these collective motions are critical to the water transfer efficiency of AqpZ by facilitating the opening of the channel and accelerating the water-residue hydrogen bonds renewing in the selectivity filter region.

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.

In Silico Comparison of Bioactive Compounds Characterized from Azadirachta indica with an FDA-Approved Drug against Schistosomal Agents: New Insight into Schistosomiasis Treatment.

The burden of human schistosomiasis, a known but neglected tropical disease in Sub-Saharan Africa, has been worrisome in recent years. It is becoming increasingly difficult to tackle schistosomiasis with praziquantel, a drug known to be effective against all Schistosoma species, due to reports of reduced efficacy and resistance. Therefore, this study seeks to investigate the antischistosomal potential of phytochemicals from Azadirachta indica against proteins that have been implicated as druggable targets for the treatment of schistosomiasis using computational techniques. In this study, sixty-three (63) previously isolated and characterized phytochemicals from A. indica were identified from the literature and retrieved from the PubChem database. In silico screening was conducted to assess the inhibitory potential of these phytochemicals against three receptors (Schistosoma mansoni Thioredoxin glutathione reductase, dihydroorotate dehydrogenase, and Arginase) that may serve as therapeutic targets for schistosomiasis treatment. Molecular docking, ADMET prediction, ligand interaction, MMGBSA, and molecular dynamics simulation of the hit compounds were conducted using the Schrodinger molecular drug discovery suite. The results show that Andrographolide possesses a satisfactory pharmacokinetic profile, does not violate the Lipinski rule of five, binds with favourable affinity with the receptors, and interacts with key amino acids at the active site. Importantly, its interaction with dihydroorotate dehydrogenase, an enzyme responsible for the catalysis of the de novo pyrimidine nucleotide biosynthetic pathway rate-limiting step, shows a glide score and MMGBSA of -10.19 and -45.75 Kcal/mol, respectively. In addition, the MD simulation shows its stability at the active site of the receptor. Overall, this study revealed that Andrographolide from Azadirachta indica could serve as a potential lead compound for the development of an anti-schistosomal drug.

Identifying the Multitarget Pharmacological Mechanism of Action of Genistein on Lung Cancer by Integrating Network Pharmacology and Molecular Dynamic Simulation.

Food supplements have become beneficial as adjuvant therapies for many chronic disorders, including cancer. Genistein, a natural isoflavone enriched in soybeans, has gained potential interest as an anticancer agent for various cancers, primarily by modulating apoptosis, the cell cycle, and angiogenesis and inhibiting metastasis. However, in lung cancer, the exact impact and mechanism of action of genistein still require clarification. To provide more insight into the mechanism of action of genistein, network pharmacology was employed to identify the key targets and their roles in lung cancer pathogenesis. Based on the degree score, the hub genes AKT1, CASP3, EGFR, STAT3, ESR1, SRC, PTGS2, MMP9, PRAG, and AR were significantly correlated with genistein treatment. AKT1, EGFR, and STAT3 were enriched in the non-small cell lung cancer (NSCLC) pathway according to Kyoto Encyclopedia of Genes and Genomes analysis, indicating a significant connection to lung cancer development. Moreover, the binding affinity of genistein to NSCLC target proteins was further verified by molecular docking and molecular dynamics simulations. Genistein exhibited potential binding to AKT1, which is involved in apoptosis, cell migration, and metastasis, thus holding promise for modulating AKT1 function. Therefore, this study aimed to investigate the mechanism of action of genistein and its therapeutic potential for the treatment of NSCLC.

Integrating Explicit and Implicit Fullerene Models into UNRES Force Field for Protein Interaction Studies.

Fullerenes, particularly C60, exhibit unique properties that make them promising candidates for various applications, including drug delivery and nanomedicine. However, their interactions with biomolecules, especially proteins, remain not fully understood. This study implements both explicit and implicit C60 models into the UNRES coarse-grained force field, enabling the investigation of fullerene-protein interactions without the need for restraints to stabilize protein structures. The UNRES force field offers computational efficiency, allowing for longer timescale simulations while maintaining accuracy. Five model proteins were studied: FK506 binding protein, HIV-1 protease, intestinal fatty acid binding protein, PCB-binding protein, and hen egg-white lysozyme. Molecular dynamics simulations were performed with and without C60 to assess protein stability and investigate the impact of fullerene interactions. Analysis of contact probabilities reveals distinct interaction patterns for each protein. FK506 binding protein (1FKF) shows specific binding sites, while intestinal fatty acid binding protein (1ICN) and uteroglobin (1UTR) exhibit more generalized interactions. The explicit C60 model shows good agreement with all-atom simulations in predicting protein flexibility, the position of C60 in the binding pocket, and the estimation of effective binding energies. The integration of explicit and implicit C60 models into the UNRES force field, coupled with recent advances in coarse-grained modeling and multiscale approaches, provides a powerful framework for investigating protein-nanoparticle interactions at biologically relevant scales without the need to use restraints stabilizing the protein, thus allowing for large conformational changes to occur. These computational tools, in synergy with experimental techniques, can aid in understanding the mechanisms and consequences of nanoparticle-biomolecule interactions, guiding the design of nanomaterials for biomedical applications.

Synthesis, In Vivo Anticonvulsant Activity Evaluation and In Silico Studies of Some Quinazolin-4(3H)-One Derivatives.

Two series, "a" and "b", each consisting of nine chemical compounds, with 2,3-disubstituted quinazolin-4(3H)-one scaffold, were synthesized and evaluated for their anticonvulsant activity. They were investigated as dual potential positive allosteric modulators of the GABAA receptor at the benzodiazepine binding site and inhibitors of carbonic anhydrase II. Quinazolin-4(3H)-one derivatives were evaluated in vivo (D1-3 = 50, 100, 150 mg/kg, administered intraperitoneally) using the pentylenetetrazole (PTZ)-induced seizure model in mice, with phenobarbital and diazepam, as reference anticonvulsant agents. The in silico studies suggested the compounds act as anticonvulsants by binding on the allosteric site of GABAA receptor and not by inhibiting the carbonic anhydrase II, because the ligands-carbonic anhydrase II predicted complexes were unstable in the molecular dynamics simulations. The mechanism targeting GABAA receptor was confirmed through the in vivo flumazenil antagonism assay. The pentylenetetrazole experimental anticonvulsant model indicated that the tested compounds, 1a-9a and 1b-9b, present a potential anticonvulsant activity. The evaluation, considering the percentage of protection against PTZ, latency until the onset of the first seizure, and reduction in the number of seizures, revealed more favorable results for the "b" series, particularly for compound 8b.

Ensemble-Based Virtual Screening Led to the Discovery of Novel Lead Molecules as Potential NMBAs.

Neuromuscular blocking agents (NMBAs) are routinely used during anesthesia to relax skeletal muscle. Nicotinic acetylcholine receptors (nAChRs) are ligand-gated ion channels; NMBAs can induce muscle paralysis by preventing the neurotransmitter acetylcholine (ACh) from binding to nAChRs situated on the postsynaptic membranes. Despite widespread efforts, it is still a great challenge to find new NMBAs since the introduction of cisatracurium in 1995. In this work, an effective ensemble-based virtual screening method, including molecular property filters, 3D pharmacophore model, and molecular docking, was applied to discover potential NMBAs from the ZINC15 database. The results showed that screened hit compounds had better docking scores than the reference compound d-tubocurarine. In order to further investigate the binding modes between the hit compounds and nAChRs at simulated physiological conditions, the molecular dynamics simulation was performed. Deep analysis of the simulation results revealed that ZINC257459695 can stably bind to nAChRs' active sites and interact with the key residue Asp165. The binding free energies were also calculated for the obtained hits using the MM/GBSA method. In silico ADMET calculations were performed to assess the pharmacokinetic properties of hit compounds in the human body. Overall, the identified ZINC257459695 may be a promising lead compound for developing new NMBAs as an adjunct to general anesthesia, necessitating further investigations.

Reactive Force Field Molecular Dynamics Investigation of NH3 Generation Mechanism during Protein Pyrolysis Process.

The mechanism of ammonia formation during the pyrolysis of proteins in biomass is currently unclear. To further investigate this issue, this study employed the AMS 2023.104 software to select proteins (actual proteins) as the model compounds and the amino acids contained within them (assembled amino acids) as the comparative models. ReaxFF molecular dynamics simulations were conducted to explore the nitrogen transformation and NH3 generation mechanisms in three-phase products (char, tar, and gas) during protein pyrolysis. The research results revealed several key findings. Regardless of whether the model compounds are actual proteins or assembled amino acids, NH3 is the primary nitrogen-containing product during pyrolysis. However, as the temperature rises to higher levels, such as 2000 K and 2500 K, the amount of NH3 decreases significantly in the later stages of pyrolysis, indicating that it is being converted into other nitrogen-bearing species, such as HCN and N2. Simultaneously, we also observed significant differences between the pyrolysis processes of actual proteins and assembled amino acids. Notably, at 2000 K, the amount of NH3 generated from the pyrolysis of assembled amino acids was twice that of actual proteins. This discrepancy mainly stems from the inherent structural differences between proteins and amino acids. In proteins, nitrogen is predominantly present in a network-like structure (NH-N), which shields it from direct external exposure, thus requiring more energy for nitrogen to participate in pyrolysis reactions, making it more difficult for NH3 to form. Conversely, assembled amino acids can release NH3 through a simpler deamination process, leading to a significant increase in NH3 production during their pyrolysis.

Exploring the Key Amino Acid Residues Surrounding the Active Center of Lactate Dehydrogenase A for the Development of Ideal Inhibitors.

Lactate dehydrogenase A (LDHA) primarily catalyzes the conversion between lactic acid and pyruvate, serving as a key enzyme in the aerobic glycolysis pathway of sugar in tumor cells. LDHA plays a crucial role in the occurrence, development, progression, invasion, metastasis, angiogenesis, and immune escape of tumors. Consequently, LDHA not only serves as a biomarker for tumor diagnosis and prognosis but also represents an ideal target for tumor therapy. Although LDHA inhibitors show great therapeutic potential, their development has proven to be challenging. In the development of LDHA inhibitors, the key active sites of LDHA are emphasized. Nevertheless, there is a relative lack of research on the amino acid residues around the active center of LDHA. Therefore, in this study, we investigated the amino acid residues around the active center of LDHA. Through structure comparison analysis, five key amino acid residues (Ala30, Met41, Lys131, Gln233, and Ala259) were identified. Subsequently, the effects of these five residues on the enzymatic properties of LDHA were investigated using site-directed mutagenesis. The results revealed that the catalytic activities of the five mutants varied to different degrees in both the reaction from lactic acid to pyruvate and pyruvate to lactic acid. Notably, the catalytic activities of LDHAM41G and LDHAK131I were improved, particularly in the case of LDHAK131I. The results of the molecular dynamics analysis of LDHAK131I explained the reasons for this phenomenon. Additionally, the optimum temperature of LDHAM41G and LDHAQ233M increased from 35 °C to 40 °C, whereas in the reverse reaction, the optimum temperature of LDHAM41G and LDHAK131I decreased from 70 °C to 60 °C. These findings indicate that Ala30, Met41, Lys131, Gln233, and Ala259 exert diverse effects on the catalytic activity and optimum temperature of LHDA. Therefore, these amino acid residues, in addition to the key catalytic site of the active center, play a crucial role. Considering these residues in the design and screening of LDHA inhibitors may lead to the development of more effective inhibitors.

Green and Efficient Extraction of Phenolic Components from Plants with Supramolecular Solvents: Experimental and Theoretical Studies.

The supramolecular solvent (SUPRAS) has garnered significant attention as an innovative, efficient, and environmentally friendly solvent for the effective extraction and separation of bioactive compounds from natural resources. However, research on the use of a SUPRAS for the extraction of phenolic compounds from plants, which are highly valued in food products due to their exceptional antioxidant properties, remains scarce. The present study developed a green, ultra-sound-assisted SUPRAS method for the simultaneous determination of three phenolic acids in Prunella vulgaris using high-performance liquid chromatography (HPLC). The experimental parameters were meticulously optimized. The efficiency and antioxidant properties of the phenolic compounds obtained using different extraction methods were also compared. Under optimal conditions, the extraction efficiency of the SUPRAS, prepared with octanoic acid reverse micelles dispersed in ethanol-water, significantly exceeded that of conventional organic solvents. Moreover, the SUPRAS method demonstrated greater antioxidant capacity. Confocal laser scanning microscopy (CLSM) images revealed the spherical droplet structure of the SUPRAS, characterized by a well-defined circular fluorescence position, which coincided with the position of the phenolic acids. The phenolic acids were encapsulated within the SUPRAS droplets, indicating their efficient extraction capacity. Furthermore, molecular dynamics simulations combined with CLSM supported the proposed method's mechanism and theoretically demonstrated the superior extraction performance of the SUPRAS. In contrast to conventional methods, the higher extraction efficiency of the SUPRAS can be attributed to the larger solvent contact surface area, the formation of more types of hydrogen bonds between the extractants and the supramolecular solvents, and stronger, more stable interaction forces. The results of the theoretical studies corroborate the experimental outcomes.

Structure-Based Design of Novel Thiazolone[3,2-a]pyrimidine Derivatives as Potent RNase H Inhibitors for HIV Therapy.

Ribonuclease H (RNase H) was identified as an important target for HIV therapy. Currently, no RNase H inhibitors have reached clinical status. Herein, a series of novel thiazolone[3,2-a]pyrimidine-containing RNase H inhibitors were developed, based on the hit compound 10i, identified from screening our in-house compound library. Some of these derivatives exhibited low micromolar inhibitory activity. Among them, compound 12b was identified as the most potent inhibitor of RNase H (IC50 = 2.98 µM). The experiment of magnesium ion coordination was performed to verify that this ligand could coordinate with magnesium ions, indicating its binding ability to the catalytic site of RNase H. Docking studies revealed the main interactions of this ligand with RNase H. A quantitative structure activity relationship (QSAR) was also conducted to disclose several predictive mathematic models. A molecular dynamics simulation was also conducted to determine the stability of the complex. Taken together, thiazolone[3,2-a]pyrimidine can be regarded as a potential scaffold for the further development of RNase H inhibitors.

Structural insights into drug transport by an aquaglyceroporin.

Pentamidine and melarsoprol are primary drugs used to treat the lethal human sleeping sickness caused by the parasite Trypanosoma brucei. Cross-resistance to these two drugs has recently been linked to aquaglyceroporin 2 of the trypanosome (TbAQP2). TbAQP2 is the first member of the aquaporin family described as capable of drug transport; however, the underlying mechanism remains unclear. Here, we present cryo-electron microscopy structures of TbAQP2 bound to pentamidine or melarsoprol. Our structural studies, together with the molecular dynamic simulations, reveal the mechanisms shaping substrate specificity and drug permeation. Multiple amino acids in TbAQP2, near the extracellular entrance and inside the pore, create an expanded conducting tunnel, sterically and energetically allowing the permeation of pentamidine and melarsoprol. Our study elucidates the mechanism of drug transport by TbAQP2, providing valuable insights to inform the design of drugs against trypanosomiasis.

Structural basis of human NOX5 activation.

NADPH oxidase 5 (NOX5) catalyzes the production of superoxide free radicals and regulates physiological processes from sperm motility to cardiac rhythm. Overexpression of NOX5 leads to cancers, diabetes, and cardiovascular diseases. NOX5 is activated by intracellular calcium signaling, but the underlying molecular mechanism of which - in particular, how calcium triggers electron transfer from NADPH to FAD - is still unclear. Here we capture motions of full-length human NOX5 upon calcium binding using single-particle cryogenic electron microscopy (cryo-EM). By combining biochemistry, mutagenesis analyses, and molecular dynamics (MD) simulations, we decode the molecular basis of NOX5 activation and electron transfer. We find that calcium binding to the EF-hand domain increases NADPH dynamics, permitting electron transfer between NADPH and FAD and superoxide production. Our structural findings also uncover a zinc-binding motif that is important for NOX5 stability and enzymatic activity, revealing modulation mechanisms of reactive oxygen species (ROS) production.

Novel anthraquinone amide derivatives as potential glyoxalase-I inhibitors.

This study aimed to identify novel Glyoxalase-I (Glo-I) inhibitors with potential anticancer properties, focusing on anthraquinone amide-based derivatives. We synthesized a series of these derivatives and conducted in silico docking studies to predict their binding interactions with Glo-I. In vitro assessments were performed to evaluate the anti-Glo-I activity of the synthesized compounds. A comprehensive structure-activity relationship (SAR) analysis identified key features responsible for specific binding affinities of anthraquinone amide-based derivatives to Glo-I. Additionally, a 100 ns molecular dynamics simulation assessed the stability of the most potent compound compared to a co-crystallized ligand. Compound MQ3 demonstrated a remarkable inhibitory effect against Glo-I, with an IC50 concentration of 1.45 µM. The inhibitory potency of MQ3 may be attributed to the catechol ring, amide functional group, and anthraquinone moiety, collectively contributing to a strong binding affinity with Glo-I. Anthraquinone amide-based derivatives exhibit substantial potential as Glo-I inhibitors with prospective anticancer activity. The exceptional inhibitory efficacy of compound MQ3 indicates its potential as an effective anticancer agent. These findings underscore the significance of anthraquinone amide-based derivatives as a novel class of compounds for cancer therapy, supporting further research and advancements in targeting the Glo-I enzyme to combat cancer.

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%.

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.

Ionic Liquid Gating Induces Anomalous Permeation through Membrane Channel Proteins.

Membrane channel proteins (MCPs) play key roles in matter transport through cell membranes and act as major targets for vaccines and drugs. For emerging ionic liquid (IL) drugs, a rational understanding of how ILs affect the structure and transport function of MCP is crucial to their design. In this work, GPU-accelerated microsecond-long molecular dynamics simulations were employed to investigate the modulating mechanism of ILs on MCP. Interestingly, ILs prefer to insert into the lipid bilayer and channel of aquaporin-2 (AQP2) but adsorb on the entrance of voltage-gated sodium channels (Nav). Molecular trajectory and free energy analysis reflect that ILs have a minimal impact on the structure of MCPs but significantly influence MCP functions. It demonstrates that ILs can decrease the overall energy barrier for water through AQP2 by 1.88 kcal/mol, whereas that for Na+ through Nav is increased by 1.70 kcal/mol. Consequently, the permeation rates of water and Na+ can be enhanced and reduced by at least 1 order of magnitude, respectively. Furthermore, an abnormal IL gating mechanism was proposed by combining the hydrophobic nature of MCP and confined water/ion coordination effects. More importantly, we performed experiments to confirm the influence of ILs on AQP2 in human cells and found that treatment with ILs significantly accelerated the changes in cell volume in response to altered external osmotic pressure. Overall, these quantitative results will not only deepen the understanding of IL-cell interactions but may also shed light on the rational design of drugs and disease diagnosis.

Click Chemistry-Based Force Spectroscopy Revealed Enhanced Binding Dynamics of Phosphorylated HMGB1 to Cisplatin-DNA.

Cisplatin, a cornerstone in cancer chemotherapy, is known for its DNA-binding capacity and forms lesions that lead to cancer cell death. However, the repair of these lesions compromises cisplatin's effectiveness. This study investigates how phosphorylation of HMGB1, a nuclear protein, modifies its binding to cisplatin-modified DNA (CP-DNA) and thus protects it from repair. Despite numerous methods for detecting protein-DNA interactions, quantitative approaches for understanding their molecular mechanism remain limited. Here, we applied click chemistry-based single-molecule force spectroscopy, achieving high-precision quantification of the interaction between phosphorylated HMGB1 and CP-DNA. This method utilizes a synergy of click chemistry and enzymatic ligation for precise DNA-protein immobilization and interaction in the system. Our results revealed that HMGB1 binds to CP-DNA with a significantly high rupture force of ∼130 pN, stronger than most natural DNA-protein interactions and varying across different DNA sequences. Moreover, Ser14 is identified as the key phosphorylation site, enhancing the interaction's kinetic stability by 35-fold. This increase in stability is attributed to additional hydrogen bonding suggested by molecular dynamics (MD) simulations. Our findings not only reveal the important role of phosphorylated HMGB1 in potentially improving cisplatin's therapeutic efficacy but also provide a precise method for quantifying protein-DNA interactions.