CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields

Isomer-sourced structure iteration methods for in silico development of inhibitors: Inducing GTP-bound NRAS-Q61 oncogenic mutations to an "off-like" state

The NRAS-mutant subset of melanoma represent some of the most aggressive and deadliest types associated with poor overall survival. Unfortunately, for more than 40 years, no therapeutic agent directly targeting NRAS mutations has been clinically approved. In this work, based on microsecond scale molecular dynamics simulations, the effect of Q61 mutations on NRAS conformational characteristics is revealed at the atomic level. The GTP-bound NRAS-Q61R and Q61K mutations show a specific targetable pocket between Switch-II and α-helix 3 whereas the NRAS-Q61L non-polar mutation category shows a different targetable pocket. Moreover, a new isomer-sourced structure iteration method has been developed for the in silico design of potential inhibitor prototypes for oncogenes. We show the possibility of a designed prototype HM-387 to target activated NRAS-Q61R and that it can gradually induce the transition from the activated NRAS-Q61R to an "off-like" state.

Combined role of stearic acid and maleic anhydride in the development of thermoplastic starch-based materials with ultrahigh ductility and durability

The diverse properties reported for starch-based materials indicate their potential for use in the preparation of biodegradable flexible actuators. However, their natural brittleness and lack of durability after modification limit their practical application. Therefore, we propose a strategy for preparing flexible starch-based composites. The results of macro/micro property characterizations and molecular dynamics simulations indicated that using starch, maleic anhydride, and stearic acid (SA), the mobility of the starch chains was enhanced and retrogradation was inhibited through the synergistic effects induced by chain breaking, complex formation with SA, and esterification of the starch molecules. In addition, the elongation at break of the modified starch (MS) reached 2070 %, and considerable ductility (>1000 %) as well as well-complexed structure were maintained after six months. Furthermore, the MS was able to undergo self-healing after fracture or a temperature-controlled stiffness transition. Moreover, it underwent complete degradation in soil within 30 d. Finally, an actuator was prepared by doping the MS with nano-Fe3O4 particles to realize a dual magnetic and optical response. Dynamic monitoring was also achieved based on the electrical signal, thereby demonstrating the broad application scope of this material in the development of biodegradable flexible actuators.

Comprehensive analysis of resorcinyl-imidazole Hsp90 inhibitor design

Human Hsp90 chaperones are implicated in various aspects of cancer. Due to this, Hsp90 has been explored as potential target in cancer treatment. Initial attempts to use Hsp90 inhibitors in drug trials failed due to toxicity and inefficacy. The next generation of drugs were less toxic but still insufficiently effective in a clinical setting. Recently, a lot of effort is being put into understanding the consequences of Hsp90 isoform selective inhibition, expecting that this might hold the key in targeting Hsp90 for disease treatment. Here we investigate a series of compounds containing the aryl-resorcinol scaffold with a 5-membered ring as a promising class of new human Hsp90 inhibitors, reaching nanomolar affinity. We compare how the replacement of 5-membered ring, from thiadiazole to imidazole, as well as a variety of their substituents, influences the potency of these inhibitors for Hsp90 alpha and beta isoforms. To further elucidate the dissimilarity in ligand selectivity between the isoforms, a mutant protein was constructed and tested against the ligand library. In addition, we performed a series of molecular dynamics (MD) and docking simulations to further explain our experimental findings as well as evaluated key compounds in cell assays. Our results deepen the understanding of Hsp90 isoform ligand selectivity and serve as an informative base for further Hsp90 inhibitor optimization.

Unraveling the impact of the p.R107L mutation on the structure and function of human αB-Crystallin: Implications for cataract formation

To date, several pathogenic mutations have been identified in the primary structure of human α-Crystallin, frequently involving the substitution of arginine with a different amino acid. These mutations can lead to the incidence of cataracts and myopathy. Recently, an important cataract-associated mutation has been reported in the functional α-Crystallin domain (ACD) of human αB-Crystallin protein, where arginine 107 (R107) is replaced by a leucine. In this study, we investigated the structure, chaperone function, stability, oligomerization, and amyloidogenic properties of the p.R107L human αB-Crystallin using a number of different techniques. Our results suggest that the p.R107L mutation can cause significant changes in the secondary, tertiary, and quaternary structures of αB-Crystallin. This cataractogenic mutation led to the formation of protein oligomers with larger sizes than the wild-type protein and reduced the chemical and thermal stability of the mutant chaperone. Both fluorescence and microscopic assessments indicated that this mutation significantly altered the amyloidogenic properties of human αB-Crystallin. Furthermore, the mutant protein indicated an attenuated in vitro chaperone activity. The molecular dynamics (MD) simulation confirmed the experimental results and indicated that p.R107L mutation could alter the proper conformation of human αB-Crystallin dimers. In summary, our results indicated that the p.R107L mutation could promote the formation of larger oligomers, diminish the stability and chaperone activity of human αB-Crystallin, and these changes, in turn, can play a crucial role in the development of cataract disorder.

Virtual high throughput screening of natural peptides against ErbB1 and ErbB2 to identify potential inhibitors for cancer chemotherapy

Human epidermal growth factor receptors (EGFR), namely ErbB1/HER1, ErbB2/HER2/neu, ErbB3/HER3, and ErbB4/HER4, the trans-membrane family of tyrosine kinase receptors, are overexpressed in many types of cancers. These receptors play an important role in cell proliferation, differentiation, invasion, metastasis and angiogenesis including unregulated activation of cancer cells. Overexpression of ErbB1 and ErbB2 that occurs in several types of cancers is associated with poor prognosis leading to resistance to ErbB1-directed therapies. In this connection, promising strategy to overcome the disadvantages of the existing chemotherapeutic drugs is the use of short peptides as anticancer agents. In the present study, we have performed virtual high throughput screening of natural peptides against ErbB1 and ErbB2 to identify potential dual inhibitors and identified five inhibitors based on their binding affinities, ADMET analysis, MD simulation studies and calculation of free energy of binding. These natural peptides could be further exploited for developing drugs for treating cancer.Communicated by Ramaswamy H. Sarma.

Dynamics of eugenol included in β-cyclodextrin by nuclear magnetic resonance and molecular simulations

Eugenol-β-cyclodextrin complex has been widely used because of the enhanced stability and conservation of the properties of eugenol. Applications in food and health sciences have been shown previously, which makes this complex an excellent model to understand and develop methodologies for the analysis and prediction of physical properties. In this work, the dynamics of eugenol incorporated into β-cyclodextrin are presented, using NMR relaxation rates, and the predictive capabilities of molecular dynamics simulations are discussed. Results show a hindered rotation of eugenol around the principal inertial axes when located inside β-cyclodextrin. Moreover, a translational movement of the whole complex is demonstrated.

Repurposing phytochemicals of Citrullus colocynthis against maltase-glucoamylase using molecular docking, MMGBSA, MD simulation and linear regression to identify potential anti-diabetic compounds

Diabetes is a common lifestyle disorder found in populations of different age groups. Maltase-glucoamylase catalyses the release of the glucose molecule in the final enzymatic reaction of starch digestion; therefore, inhibition of maltase-glucoamylase is one of the approaches in the development of therapeutics for diabetes. Citrullus colocynthis is commonly recommended in Ayurveda for the treatment of diabetes. The current study applied a structure-based drug design approach to repurpose the phytochemicals of Citrullus colocynthis to identify potential inhibitors for maltase-glucoamylase. 70 phytochemicals of Citrullus colocynthis were screened against maltase-glucoamylase and top 5 molecules 8-p-hydroxybenzylisovitexin, isoorientin, cucurbitacin B, cucurbitacin E, and cucurbitacin I with significant binding energy of -10 kcal/mol, -9.9 kcal/mol, -9.6 kcal/mol, -9.2 kcal/mol, and -7.7 kcal/mol were identified. Furthermore, MMGBSA, pharmacokinetics properties and toxicity prediction were performed on the five identified molecules and top 3 molecules were selected for molecular dynamics (MD) simulation. It was observed from the structural flexibility and dynamic behaviour of the systems that conformational changes were noticed in the complexes as compared to its native state, which suggests that the 3 molecules, namely 8-p-hydroxybenzylisovitexin, isoorientin, and cucurbitacin I of Citrullus colocynthis may act as inhibitors for maltase-glucoamylase.Communicated by Ramaswamy H. Sarma.

Discovery of Novel Small Molecule Dual Inhibitor Targeting Toll-Like Receptors 7 and 9

The aberrant secretion of proinflammatory cytokines by immune cells is the principal cause of inflammatory diseases, such as systemic lupus erythematosus and rheumatoid arthritis. Toll-like receptor 7 (TLR7) and TLR9, sequestered to the endosomal compartment of dendritic cells and macrophages, are closely associated with the initiation and progression of these diseases. Therefore, the development of drugs targeting dysregulated endosomal TLRs is imperative to mitigate systemic inflammation. Here, we applied the principles of computer-aided drug discovery to identify a novel low-molecular-weight compound, TLR inhibitory compound 10 (TIC10), and its potent derivative (TIC10g), which demonstrated dual inhibition of TLR7 and TLR9 signaling pathways. Compared to TIC10, TIC10g exhibited a more pronounced inhibition of the TLR7- and TLR9-mediated secretion of the proinflammatory cytokine tumor necrosis factor-α in a mouse macrophage cell line and mouse bone marrow dendritic cells in a concentration-dependent manner. While TIC10g slightly prevented TLR3 and TLR8 activation, it had no impact on cell surface TLRs (TLR1/2, TLR2/6, TLR4, or TLR5), indicating its selectivity for TLR7 and TLR9. Additionally, mechanistic studies suggested that TIC10g interfered with TLR9 activation by CpG DNA and suppressed downstream pathways by directly binding to TLR9. Western blot analysis revealed that TIC10g downregulated the phosphorylation of the p65 subunit of nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) and mitogen-activated protein kinases (MAPKs), including extracellular-signal-regulated kinase, p38-MAPK, and c-Jun N-terminal kinase. These findings indicate that the novel ligand, TIC10g, is a specific dual inhibitor of endosomal TLRs (TLR7 and TLR9), disrupting MAPK- and NF-κB-mediated proinflammatory gene expression.

Conformational flexibility driving charge-selective substrate translocation across a bacterial transporter

Bacterial membrane porins facilitate the translocation of small molecules while restricting large molecules, and this mechanism remains elusive at the molecular level. Here, we investigate the selective uptake of large cyclic sugars across an unusual passive membrane transporter, CymA, comprising a charged zone and a constricting N terminus segment. Using a combination of electrical recordings, protein mutagenesis and molecular dynamics simulations, we establish substrate translocation across CymA governed by the electrostatic pore properties and conformational dynamics of the constriction segment. Notably, we show that the variation in pH of the environment resulted in reversible modulation of the substrate binding site in the pore, thereby regulating charge-selective transport of cationic, anionic and neutral cyclic sugars. The quantitative kinetics of cyclic sugar translocation across CymA obtained in electrical recordings at different pHs are comparable with molecular dynamics simulations that revealed the transport pathway, energetics and favorable affinity sites in the pore for substrate binding. We further define the molecular basis of cyclic sugar translocation and establish that the constriction segment is flexible and can reside inside or outside the pore, regulating substrate translocation distinct from the ligand-gated transport mechanism. Our study provides novel insights into energy-independent large molecular membrane transport for targeted drug design strategies.

Current State of Open Source Force Fields in Protein-Ligand Binding Affinity Predictions

In drug discovery, the in silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy (RBFE) calculations based on molecular dynamics (MD) simulations are nowadays a popular approach for the accurate affinity ranking of compounds. MD simulations rely on empirical force field parameters, which strongly influence the accuracy of the predicted affinities. Here, we evaluate the ability of six different small-molecule force fields to predict experimental protein-ligand binding affinities in RBFE calculations on a set of 598 ligands and 22 protein targets. The public force fields OpenFF Parsley and Sage, GAFF, and CGenFF show comparable accuracy, while OPLS3e is significantly more accurate. However, a consensus approach using Sage, GAFF, and CGenFF leads to accuracy comparable to OPLS3e. While Parsley and Sage are performing comparably based on aggregated statistics across the whole dataset, there are differences in terms of outliers. Analysis of the force field reveals that improved parameters lead to significant improvement in the accuracy of affinity predictions on subsets of the dataset involving those parameters. Lower accuracy can not only be attributed to the force field parameters but is also dependent on input preparation and sampling convergence of the calculations. Especially large perturbations and nonconverged simulations lead to less accurate predictions. The input structures, Gromacs force field files, as well as the analysis Python notebooks are available on GitHub.

HessFit: A Toolkit to Derive Automated Force Fields from Quantum Mechanical Information

In this study, we introduce a novel approach to enhance the accuracy of molecular dynamics simulations by refining the force fields (FFs) through a combination of transferable parameters and molecule-specific characteristics derived from quantum mechanical (QM) calculations. Traditional FFs often prioritize generality over precision, leading to limitations in the accuracy of accurately capturing intra- and intermolecular interactions. To address this, we present an open-source toolkit, called HessFit, designed to integrate QM-derived bonded parameters and atomic charges into existing FFs. In combination with bond, angle, torsional, and nonbonded parameters derivation, HessFit can easily extract multiple barrier terms of dihedrals from QM Hessian and gradient or return all terms through a fitting procedure scheme of QM potential energy surface. We showcase the effectiveness of HessFit through comprehensive evaluations of vibrational properties across a diverse set of small molecules and demonstrate that experimental results support its ability in predicting thermodynamic properties of organic molecules compared to previous state-of-the-art approaches. We further explore its application to Zn2+ metalloprotein models, which are hard systems to treat with automatic approaches. Our results demonstrate that HessFit parameters compete with GAFF2 and OPLS parameters to describing small organic molecules, and its feasibility is also comparable to current FFs used to modeling nonstandard residues in Zn proteins for molecular dynamics simulations. The effectiveness of the HessFit protocol makes it a valuable tool for deriving or extending force field parameters for novel compounds in several molecular modeling applications.

Surfactant-Polymer Complexation and Competition on Drug Nanocrystal Surfaces Control Crystallinity

Nanosizing drug crystals has emerged as a successful approach to enabling oral bioavailability, as increasing drug crystal surface area improves dissolution kinetics and effective solubility. Recently, bottom-up methods have been developed to directly assemble nanosized crystals by leveraging polymer and surfactant excipients during crystallization to control crystal size, morphology, and structure. However, while significant research has investigated how polymers and other single additives inhibit or promote crystallization in pharmaceutical systems, there is little work studying the mechanistic interactions of multiple excipients on drug crystal structure and the extent of crystallinity, which can influence formulation performance. This study explores how the structure and crystallinity of a model hydrophobic drug crystal, fenofibrate, change as a result of competitive interfacial chemisorption between common nonionic surfactants (polysorbate 80 and sorbitan monooleate) and a surface-active polymer excipient (methylcellulose). Classical molecular dynamics simulations highlight how key intermolecular interactions, including surfactant-polymer complexation and surfactant screening of the crystal surface, modify the resulting crystal structure. In parallel, experiments generating drug nanocrystals in hydrogel thin films validate that drug crystallinity increases with an increasing weight fraction of surfactant. Simulation results reveal a connection between accelerated dynamics in the bulk crystal and the experimentally measured extent of crystallinity. To our knowledge, these are the first simulations that directly characterize structural changes in a drug crystal as a result of excipient surface composition and relate the experimental extent of crystallinity to structural changes in the molecular crystal. Our approach provides a mechanistic understanding of crystallinity in nanocrystallization, which can expand the range of orally deliverable small molecule therapies.

Simulations predict preferred Mg2+ coordination in a nonenzymatic primer-extension reaction center

The mechanism by which genetic information was copied prior to the evolution of ribozymes is of great interest because of its importance to the origin of life. The most effective known process for the nonenzymatic copying of an RNA template is primer extension by a two-step pathway in which 2-aminoimidazole-activated nucleotides first react with each other to form an imidazolium-bridged intermediate that subsequently reacts with the primer. Reaction kinetics, structure-activity relationships, and X-ray crystallography have provided insight into the overall reaction mechanism, but many puzzles remain. In particular, high concentrations of Mg2+ are required for efficient primer extension, but the mechanism by which Mg2+ accelerates primer extension remains unknown. By analogy with the mechanism of DNA and RNA polymerases, a role for Mg2+ in facilitating the deprotonation of the primer 3'-hydroxyl is often assumed, but no catalytic metal ion is seen in crystal structures of the primer-extension complex. To explore the potential effects of Mg2+ binding in the reaction center, we performed atomistic molecular dynamics simulations of a series of modeled complexes in which a Mg2+ ion was placed in the reaction center with inner-sphere coordination with different sets of functional groups. Our simulations suggest that coordination of a Mg2+ ion with both O3' of the terminal primer nucleotide and the pro-Sp nonbridging oxygen of the reactive phosphate of an imidazolium-bridged dinucleotide would help to pre-organize the structure of the primer/template substrate complex to favor the primer-extension reaction. Our results suggest that the catalytic metal ion may play an important role in overcoming electrostatic repulsion between a deprotonated O3' and the reactive phosphate of the bridged dinucleotide and lead to testable predictions of the mode of Mg2+ binding that is most relevant to catalysis of primer extension.

Unravelling the interactions between small molecules and liposomal bilayers via molecular dynamics and thermodynamic modelling

Lipid-based drug delivery systems hold immense promise in addressing critical medical needs, from cancer and neurodegenerative diseases to infectious diseases. By encapsulating active pharmaceutical ingredients - ranging from small molecule drugs to proteins and nucleic acids - these nanocarriers enhance treatment efficacy and safety. However, their commercial success faces hurdles, such as the lack of a systematic design approach and the issues related to scalability and reproducibility. This work aims to provide insights into the drug-phospholipid interaction by combining molecular dynamic simulations and thermodynamic modelling techniques. In particular, we have made a connection between the structural properties of the drug-phospholipid system and the physicochemical performance of the drug-loaded liposomal nanoformulations. We have considered two prototypical drugs, felodipine (FEL) and naproxen (NPX), and one model hydrogenated soy phosphatidylcholine (HSPC) bilayer membrane. Molecular dynamic simulations revealed which regions within the phospholipid bilayers are most and least favoured by the drug molecules. NPX tends to reside at the water-phospholipid interface and is characterized by a lower free energy barrier for bilayer membrane permeation. Meanwhile, FEL prefers to sit within the hydrophobic tails of the phospholipids and is characterized by a higher free energy barrier for membrane permeation. Flory-Huggins thermodynamic modelling, small angle X-ray scattering, dynamic light scattering, TEM, and drug release studies of these liposomal nanoformulations confirmed this drug-phospholipid structural difference. The naproxen-phospholipid system has a lower free energy barrier for permeation, higher drug miscibility with the bilayer, larger liposomal nanoparticle size, and faster drug release in the aqueous medium than felodipine. We suggest that this combination of molecular dynamics and thermodynamics approach may offer a new tool for designing and developing lipid-based nanocarriers for unmet medical applications.

Highly accurate carbohydrate-binding site prediction with DeepGlycanSite

As the most abundant organic substances in nature, carbohydrates are essential for life. Understanding how carbohydrates regulate proteins in the physiological and pathological processes presents opportunities to address crucial biological problems and develop new therapeutics. However, the diversity and complexity of carbohydrates pose a challenge in experimentally identifying the sites where carbohydrates bind to and act on proteins. Here, we introduce a deep learning model, DeepGlycanSite, capable of accurately predicting carbohydrate-binding sites on a given protein structure. Incorporating geometric and evolutionary features of proteins into a deep equivariant graph neural network with the transformer architecture, DeepGlycanSite remarkably outperforms previous state-of-the-art methods and effectively predicts binding sites for diverse carbohydrates. Integrating with a mutagenesis study, DeepGlycanSite reveals the guanosine-5'-diphosphate-sugar-recognition site of an important G-protein coupled receptor. These findings demonstrate DeepGlycanSite is invaluable for carbohydrate-binding site prediction and could provide insights into molecular mechanisms underlying carbohydrate-regulation of therapeutically important proteins.

Stable and Fast Ion Transport Electrolyte Interfaces Modified with Novel Fluorine- and Nitrogen-Containing Solvents for Ni-Rich Cathode Materials

Ternary nickel-rich layered oxide LiNi0.8Co0.1Mn0.1O2 (NCM811) is recognized as a cathode material with a promising future, attributed to its high energy density. However, the pulverization of cathode particles, structural collapse, and electrolyte decomposition are closely associated with the fragile cathode-electrolyte interphases (CEI), which seriously affect the electrochemical performances of ternary high-nickel materials. In this paper, fluorine- and nitrogen-containing methyl-2-nitro-4-(trifluoromethyl)benzoate (MNTB) was selected, which was synergistically regulated with fluoroethylene carbonate (FEC) to generate a robust CEI film. The preferential decomposition of MNTB/FEC results in the formation of an inorganic-rich (Li3N, LiF, and Li2O) CEI film with uniformly dense and stable characteristics, which is conducive to the migration of Li+ and the stability of the NCM811 structure and enhances the cycling stability of the battery system. Simultaneously, MNTB effectively suppresses the adverse reaction associated with increased polarization caused by higher interface impedance due to conventional single FEC additives, further improving the rate capability of the battery. Moreover, MNTB/FEC can effectively eliminate HF, preventing its corrosion on the NCM811 cathode. Under the synergistic effect of MNTB/FEC, after 300 discharge cycles at a high cutoff voltage of 4.3 V and a current density of 1 C (2 mA cm-2), the discharge capacity of the NCM811||Li battery was 150.12 mA h g-1 with a capacity retention of 81.10%, while it was only 32.8% for the standard electrolyte (STD). The discharged capacity of the MNTB/FEC-containing battery was about 115.43 mA h g-1 at the high rate of 7 C, which was considerably higher than that of the STD (93.34 mA h g-1). In this study, the designed MNTB as a novel solvent synergistically regulated with FEC will contribute to the enhanced stability of NCM811 materials at high cutoff voltages and at the same time provide an effective modified strategy to enhance the stability of commercial electrodes.

Exploration and optimisation of structure-activity relationships of new triazole-based C-terminal Hsp90 inhibitors towards in vivo anticancer potency

The development of new anticancer agents is one of the most urgent topics in drug discovery. Inhibition of molecular chaperone Hsp90 stands out as an approach that affects various oncogenic proteins in different types of cancer. These proteins rely on Hsp90 to obtain their functional structure, and thus Hsp90 is indirectly involved in the pathophysiology of cancer. However, the most studied ATP-competitive inhibition of Hsp90 at the N-terminal domain has proven to be largely unsuccessful clinically. Therefore, research has shifted towards Hsp90 C-terminal domain (CTD) inhibitors, which are also the focus of this study. Our recent discovery of compound C has provided us with a starting point for exploring the structure-activity relationship and optimising this new class of triazole-based Hsp90 inhibitors. This investigation has ultimately led to a library of 33 analogues of C that have suitable physicochemical properties and several inhibit the growth of different cancer types in the low micromolar range. Inhibition of Hsp90 was confirmed by biophysical and cellular assays and the binding epitopes of selected inhibitors were studied by STD NMR. Furthermore, the most promising Hsp90 CTD inhibitor 5x was shown to induce apoptosis in breast cancer (MCF-7) and Ewing sarcoma (SK-N-MC) cells while inducing cause cell cycle arrest in MCF-7 cells. In MCF-7 cells, it caused a decrease in the levels of ERα and IGF1R, known Hsp90 client proteins. Finally, 5x was tested in zebrafish larvae xenografted with SK-N-MC tumour cells, where it limited tumour growth with no obvious adverse effects on normal zebrafish development.

Discovery of azaleatin as a potential allosteric inhibitor for dengue NS2B-NS3 protease using in vitro and in silico studies

The rise in dengue cases in tropical and sub-tropical areas has become a significant health concern. At present, there is no definitive cure for dengue fever, which underscores the importance of identifying potent inhibitors. Dengue NS2B-NS3 protease is the prime drug target due to its vital function for replication. Quercetin, a flavone, has anti-dengue virus properties but is limited by low bioavailability. Previous studies have shown that methoxy substitution in flavones improves bioavailability and metabolic stability. Azaleatin is a derivative of quercetin with a methoxy substitution at the C5 position, however its ability to inhibit dengue is unknown. In this study, azaleatin was investigated for its inhibition against dengue NS2B-NS3 protease using in vitro and in silico techniques. The fluorescence assay was used to determine the IC50 value and inhibition kinetics. The molecular interaction between azaleatin and NS2B-NS3 was studied using CB-Dock2 and AutoDock Vina. The complex's stability was then analysed using GROMACS. Besides, the ADMETlab 2.0 was utilized to predict pharmacokinetic of the azaleatin. Results showed that azaleatin inhibits dengue NS2B-NS3 protease non-competitively with a Ki of 26.82 µg/ml and an IC50 of 38 µg/ml. Molecular docking indicated binding of the azaleatin to the allosteric pocket of NS2B-NS3 with a docking score of -8.2 kcal/mol. Azaleatin was found stable in the pocket along 100 ns, supporting its inhibitory mode. The compound has favourable pharmacokinetic profiles and conformed to Lipinski's Rule of Five. Taken together, azaleatin inhibits NS2B-NS3 protease in a non-competitive mode, suggesting its potential as safer anti-dengue compound.Communicated by Ramaswamy H. Sarma.

Synthesis, molecular docking and molecular dynamics simulations, drug-likeness studies, ADMET prediction and biological evaluation of novel pyrazole-carboxamides bearing sulfonamide moiety as potent carbonic anhydrase inhibitors

Pyrazoles are unique bioactive molecules with a versatile biological profile and they have gained an important place on pharmaceutical chemistry. Pyrazole compounds containing sulfonamide nuclei also attract attention as carbonic anhydrase (CA) inhibitors. In this study, a library of pyrazole-carboxamides were synthesized and the structures of the synthesized molecules were characterized using FT-IR, 1H-NMR, 13C-NMR and HRMS. Then the inhibition effects of newly synthesized molecules on human erythrocyte hCA I and hCA II isoenzymes were investigated. Ki values of the compounds were in the range of 0.063-3.368 µM for hCA I and 0.007-4.235 µM for hCA II. Molecular docking studies were performed between the most active compounds 6a, 6b and the reference inhibitor, acetazolamide (AAZ) and the hCA I and hCA II receptors to investigate the binding mechanisms between the compounds and the receptors. These compounds showed better interactions than the AAZ. ADMET analyzes were performed for the compounds and it was seen that the compounds did not show AMES toxicity. The stability of the molecular docking results over time was analysed by 50 ns molecular dynamics simulations. Molecular dynamics simulations revealed that 6a and 6b exhibited good stability after docking to the binding sites of hCA I and hCA II receptors, with minor conformational changes and fluctuations.

Photocontrolled Reversible Amyloid Fibril Formation of Parathyroid Hormone-Derived Peptides

Peptide fibrillization is crucial in biological processes such as amyloid-related diseases and hormone storage, involving complex transitions between folded, unfolded, and aggregated states. We here employ light to induce reversible transitions between aggregated and nonaggregated states of a peptide, linked to the parathyroid hormone (PTH). The artificial light-switch 3-{[(4-aminomethyl)phenyl]diazenyl}benzoic acid (AMPB) is embedded into a segment of PTH, the peptide PTH25-37, to control aggregation, revealing position-dependent effects. Through in silico design, synthesis, and experimental validation of 11 novel PTH25-37-derived peptides, we predict and confirm the amyloid-forming capabilities of the AMPB-containing peptides. Quantum-chemical studies shed light on the photoswitching mechanism. Solid-state NMR studies suggest that β-strands are aligned parallel in fibrils of PTH25-37, while in one of the AMPB-containing peptides, β-strands are antiparallel. Simulations further highlight the significance of π-π interactions in the latter. This multifaceted approach enabled the identification of a peptide that can undergo repeated phototriggered transitions between fibrillated and defibrillated states, as demonstrated by different spectroscopic techniques. With this strategy, we unlock the potential to manipulate PTH to reversibly switch between active and inactive aggregated states, representing the first observation of a photostimulus-responsive hormone.

Gaseous inhibition of the transsulfuration pathway by cystathionine β-synthase

The transsulfuration pathway plays a key role in mammals for maintaining the balance between cysteine and homocysteine, whose concentrations are critical in several biochemical processes. Human cystathionine β-synthase is a heme-containing, pyridoxal 5'-phosphate (PLP)-dependent enzyme found in this pathway. The heme group does not participate directly in catalysis, but has a regulatory function, whereby CO or NO binding inhibits the PLP-dependent reactions. In this study, we explore the detailed structural changes responsible for inhibition using quantum chemical calculations to validate the experimentally observed bonding patterns associated with heme CO and NO binding and molecular dynamics simulations to explore the medium-range structural changes triggered by gas binding and propagating to the PLP active site, which is more than 20 Å distant from the heme group. Our results support a previously proposed mechanical signaling model, whereby the cysteine decoordination associated with gas ligand binding leads to breaking of a hydrogen bond with an arginine residue on a neighbouring helix. In turn, this leads to a shift in position of the helix, and hence also of the PLP cofactor, ultimately disrupting a key hydrogen bond that stabilizes the PLP in its catalytically active form.

Mechanistic insights into G-protein coupling with an agonist-bound G-protein-coupled receptor

G-protein-coupled receptors (GPCRs) activate heterotrimeric G proteins by promoting guanine nucleotide exchange. Here, we investigate the coupling of G proteins with GPCRs and describe the events that ultimately lead to the ejection of GDP from its binding pocket in the Gα subunit, the rate-limiting step during G-protein activation. Using molecular dynamics simulations, we investigate the temporal progression of structural rearrangements of GDP-bound Gs protein (Gs·GDP; hereafter GsGDP) upon coupling to the β2-adrenergic receptor (β2AR) in atomic detail. The binding of GsGDP to the β2AR is followed by long-range allosteric effects that significantly reduce the energy needed for GDP release: the opening of α1-αF helices, the displacement of the αG helix and the opening of the α-helical domain. Signal propagation to the Gs occurs through an extended receptor interface, including a lysine-rich motif at the intracellular end of a kinked transmembrane helix 6, which was confirmed by site-directed mutagenesis and functional assays. From this β2AR-GsGDP intermediate, Gs undergoes an in-plane rotation along the receptor axis to approach the β2AR-Gsempty state. The simulations shed light on how the structural elements at the receptor-G-protein interface may interact to transmit the signal over 30 Å to the nucleotide-binding site. Our analysis extends the current limited view of nucleotide-free snapshots to include additional states and structural features responsible for signaling and G-protein coupling specificity.

Thermodynamic Driving Forces for the Self-Assembly of Diblock Polypeptoids

Peptoid polymers with sequence-defined side chains are observed to self-assemble into a variety of structures spanning nanometer and micron scales. We explored a diblock copolypeptoid, poly(N-decylglycine)10-block-poly(N-2-(2-(2-methoxyethoxy)ethoxy)-ethylglycine)10 (abbreviated as Ndc10-Nte10), which forms crystalline nanofibers and nanosheets as evidenced by recent cryo-transmission electron microscopy, atomic force microscopy, X-ray diffraction, and calorimetry. Using all-atom molecular dynamics simulations, we examined the thermodynamic forces driving such self-assembly and how nanoscale morphology is tailored through modification of the N-terminus or via the addition of small molecules (urea). We have found that the hydrophobic Ndc domain alignment is key to the formation of molecular stacks whose growth is limited by electrostatic repulsion between protonated N-termini. These stacks are the building blocks that assemble via cooperative van der Waals attraction between the tips of extended decyl side chains to form nanofibers or nanosheets with a well-converged intermolecular interaction energy. Assemblies are significantly more stable in urea solution due to its strong attraction to the peptoid-solvent interface. Isolated peptoids exhibit curved all-cis backbones, which straighten within molecular stacks to maximize contact and registry between neighboring molecules. We hypothesize that competition between this attractive interaction and a strain cost for straightening the backbone is what leads to finite stack widths that define crystalline nanofibers of protonated Ndc10-Nte10. Growth is proposed to proceed through backbone unfurling via trans defects, which is more prevalent in aqueous solution than in THF, indicating a possible pathway to self-assembly under experimentally defined synthesis conditions (viz., THF evaporation).

All-atom molecular dynamics simulations of polymer and polyelectrolyte brushes

Densely grafted polymer and polyelectrolyte (PE) brushes, owing to their significant abilities to functionalize surfaces for a plethora of applications in sensing, diagnostics, current rectification, surface wettability modification, drug delivery, and oil recovery, have attracted significant attention over the past several decades. Unfortunately, most of the attention has primarily focused on understanding the properties of the grafted polymer and the PE chains with little attention devoted to studying the behavior of the brush-supported ions (counterions needed to screen the PE chains) and water molecules. Over the past few years, our group has been at the forefront of addressing this gap: we have employed all-atom molecular dynamics (MD) simulations for studying a wide variety of polymer and PE brush systems with specific attention to unraveling the properties and behavior of the brush-supported water molecules and ions. Our findings have revealed some of the most fascinating properties of such brush-supported ions and water molecules, including the most remarkable control of nanofluidic transport afforded by the specific ion and water responses induced by the PE brushes grafted on the inner walls of the nanochannel. This feature article aims to summarize some of our key contributions associated with such atomistic simulations of polymer and PE brushes and brush-supported water molecules and counterions.

Pharmacophore Virtual Screening Identifies Riboflavin as an Inhibitor of the Schistosome Cathepsin B1 Protease with Antiparasitic Activity

Schistosomiasis is a neglected disease of poverty that affects over 200 million people worldwide and relies on a single drug for therapy. The cathepsin B1 cysteine protease (SmCB1) of Schistosoma mansoni has been investigated as a potential target. Here, a structure-based pharmacophore virtual screening (VS) approach was used on a data set of approved drugs to identify potential antischistosomal agents targeting SmCB1. Pharmacophore (PHP) models underwent validation through receiver operating characteristics curves achieving values >0.8. The data highlighted riboflavin (RBF) as a compound of particular interest. A 1 μs molecular dynamics simulation demonstrated that RBF altered the conformation of SmCB1, causing the protease's binding site to close around RBF while maintaining the protease's overall integrity. RBF inhibited the activity of SmCB1 at low micromolar values and killed the parasite in vitro. Finally, in a murine model of S. mansoni infection, oral administration of 100 mg/kg RBF for 7 days significantly decreased worm burdens by ∼20% and had a major impact on intestinal and fecal egg burdens, which were decreased by ∼80%.

Lambda-ABF: Simplified, Portable, Accurate, and Cost-Effective Alchemical Free-Energy Computation

We introduce the lambda-Adaptive Biasing Force (lambda-ABF) method for the computation of alchemical free-energy differences. We propose a software implementation and showcase it on biomolecular systems. The method arises from coupling multiple-walker adaptive biasing force with λ-dynamics. The sampling of the alchemical variable is continuous and converges toward a uniform distribution, making manual optimization of the λ schedule unnecessary. Contrary to most other approaches, alchemical free-energy estimates are obtained immediately without any postprocessing. Free diffusion of λ improves orthogonal relaxation compared to fixed-λ thermodynamic integration or free-energy perturbation. Furthermore, multiple walkers provide generic orthogonal space coverage with minimal user input and negligible computational overhead. We show that our high-performance implementations coupling the Colvars library with NAMD and Tinker-HP can address real-world cases including ligand-receptor binding with both fixed-charge and polarizable models, with a demonstrably richer sampling than fixed-λ methods. The implementation is fully open-source, publicly available, and readily usable by practitioners of current alchemical methods. Thanks to the portable Colvars library, lambda-ABF presents a unified user interface regardless of the back-end (NAMD, Tinker-HP, or any software to be interfaced in the future), sparing users the effort of learning multiple interfaces. Finally, the Colvars Dashboard extension of the visual molecular dynamics (VMD) software provides an interactive monitoring and diagnostic tool for lambda-ABF simulations.

CHARMM-GUI QM/MM Interfacer for a Quantum Mechanical and Molecular Mechanical (QM/MM) Simulation Setup: 1. Semiempirical Methods

Quantum mechanical (QM) treatments, when combined with molecular mechanical (MM) force fields, can effectively handle enzyme-catalyzed reactions without significantly increasing the computational cost. In this context, we present CHARMM-GUI QM/MM Interfacer, a web-based cyberinfrastructure designed to streamline the preparation of various QM/MM simulation inputs with ligand modification. The development of QM/MM Interfacer has been achieved through integration with existing CHARMM-GUI modules, such as PDB Reader and Manipulator, Solution Builder, and Membrane Builder. In addition, new functionalities have been developed to facilitate the one-stop preparation of QM/MM systems and enable interactive and intuitive ligand modifications and QM atom selections. QM/MM Interfacer offers support for a range of semiempirical QM methods, including AM1(+/d), PM3(+/PDDG), MNDO(+/d, +/PDDG), PM6, RM1, and SCC-DFTB, tailored for both AMBER and CHARMM. A nontrivial setup related to ligand modification, link-atom insertion, and charge distribution is automatized through intuitive user interfaces. To illustrate the robustness of QM/MM Interfacer, we conducted QM/MM simulations of three enzyme-substrate systems: dihydrofolate reductase, insulin receptor kinase, and oligosaccharyltransferase. In addition, we have created three tutorial videos about building these systems, which can be found at https://www.charmm-gui.org/demo/qmi. QM/MM Interfacer is expected to be a valuable and accessible web-based tool that simplifies and accelerates the setup process for hybrid QM/MM simulations.

Analyzing energetics and dynamics of hepatitis C virus polymerase interactions with marine bacterial compounds: a computational study

Hepatitis C Virus (HCV) is a significant health concern affecting a large portion of the global population and is a major cause of acute liver diseases, including cirrhosis. The variability in the HCV genome mainly results from the rapid replication facilitated by the NS5B polymerase, making it a prime target for anti-HCV drug development. This study explores potential compounds from marine bacteria that could inhibit the HCV NS5B polymerase by virtual screening, analyzing the energetics, and dynamic behavior of target-compound complexes. Virtual screening with the Lipinski filter was employed to select compounds from the marine bacteria database that demonstrated strong binding affinity to NS5B. The top four (CMNPD27216, CMNPD21066, CMNPD21065, and CMNPD27283) compounds, ranked by their re-docking scores, underwent additional evaluation. Molecular dynamics simulations for 200 ns were conducted to assess the dynamic stability of these complexes in a solvent environment. Furthermore, methods such as MM-GBSA, PCA, and free energy landscape analysis were used to analyze the system's energetics and identify stable conformations by locating transition states. The findings suggest that these compounds exhibit promising binding capabilities to HCV polymerase and could be considered for future experimental validation.

Learning QM/MM potential using equivariant multiscale model

The machine learning (ML) method emerges as an efficient and precise surrogate model for high-level electronic structure theory. Its application has been limited to closed chemical systems without considering external potentials from the surrounding environment. To address this limitation and incorporate the influence of external potentials, polarization effects, and long-range interactions between a chemical system and its environment, the first two terms of the Taylor expansion of an electrostatic operator have been used as extra input to the existing ML model to represent the electrostatic environments. However, high-order electrostatic interaction is often essential to account for external potentials from the environment. The existing models based only on invariant features cannot capture significant distribution patterns of the external potentials. Here, we propose a novel ML model that includes high-order terms of the Taylor expansion of an electrostatic operator and uses an equivariant model, which can generate a high-order tensor covariant with rotations as a base model. Therefore, we can use the multipole-expansion equation to derive a useful representation by accounting for polarization and intermolecular interaction. Moreover, to deal with long-range interactions, we follow the same strategy adopted to derive long-range interactions between a target system and its environment media. Our model achieves higher prediction accuracy and transferability among various environment media with these modifications.

Varying the position of phospholipid acyl chain unsaturation modulates hopanoid and sterol ordering

The cell membrane must balance mechanical stability with fluidity to function as both a barrier and an organizational platform. Key to this balance is the ordering of hydrocarbon chains and the packing of lipids. Many eukaryotes synthesize sterols, which are uniquely capable of modulating the lipid order to decouple membrane stability from fluidity. Ancient sterol analogs known as hopanoids are found in many bacteria and proposed as ancestral ordering lipids. The juxtaposition of sterols and hopanoids in extant organisms prompts us to ask why both pathways persist, especially in light of their convergent ability to order lipids. In this work, simulations, monolayer experiments, and cellular assays show that hopanoids and sterols order unsaturated phospholipids differently based on the position of double bonds in the phospholipid acyl chain. We find that cholesterol and diplopterol's methyl group distributions lead to distinct effects on unsaturated lipids. In Mesoplasma florum, diplopterol's constrained ordering capacity reduces membrane resistance to osmotic stress, unlike cholesterol. These findings suggest that cholesterol's broader lipid-ordering ability may have facilitated the exploration of a more diverse lipidomic landscape in eukaryotic membranes.

Triplet-Triplet Annihilation Upconverting Liposomes: Mechanistic Insights into the Role of Membranes in Two-Dimensional TTA-UC

Triplet-triplet annihilation upconversion (TTA-UC) implemented in nanoparticle assemblies is of emerging interest in biomedical applications, including in drug delivery and imaging. As it is a bimolecular process, ensuring sufficient mobility of the sensitizer and annihilator to facilitate effective collision in the nanoparticle is key. Liposomes can provide the benefits of two-dimensional confinement and condensed concentration of the sensitizer and annihilator along with superior fluidity compared to other nanoparticle assemblies. They are also biocompatible and widely applied across drug delivery modalities. However, there are relatively few liposomal TTA-UC systems reported to date, so systematic studies of the influence of the liposomal environment on TTA-UC are currently lacking. Here, we report the first example of a BODIPY-based sensitizer TTA-UC system within liposomes and use this system to study TTA-UC generation and compare the relative intensity of the anti-Stokes signal for this system as a function of liposome composition and membrane fluidity. We report for the first time on time-resolved spectroscopic studies of TTA-UC in membranes. Nanosecond transient absorption data reveal the BODIPY-perylene dyad sensitizer has a long triplet lifetime in liposome with contributions from three triplet excited states, whose lifetimes are reduced upon coinclusion of the annihilator due to triplet-triplet energy transfer, to a greater extent than in solution. This indicates triplet energy transfer between the sensitizer and the annihilator is enhanced in the membrane system. Molecular dynamics simulations of the sensitizer and annihilator TTA collision complex are modeled in the membrane and confirm the co-orientation of the pair within the membrane structure and that the persistence time of the bound complex exceeds the TTA kinetics. Modeling also reliably predicted the diffusion coefficient for the sensitizer which matches closely with the experimental values from fluorescence correlation spectroscopy. The relative intensity of the TTA-UC output across nine liposomal systems of different lipid compositions was explored to examine the influence of membrane viscosity on upconversion (UC). UC showed the highest relative intensity for the most fluidic membranes and the weakest intensity for highly viscous membrane compositions, including a phase separation membrane. Overall, our study reveals that the co-orientation of the UC pair within the membrane is crucial for effective TTA-UC within a biomembrane and that the intensity of the TTA-UC output can be tuned in liposomal nanoparticles by modifying the phase and fluidity of the liposome. These new insights will aid in the design of liposomal TTA-UC systems for biomedical applications.

AI-based prediction of protein-ligand binding affinity and discovery of potential natural product inhibitors against ERK2

Determination of protein-ligand binding affinity (PLA) is a key technological tool in hit discovery and lead optimization, which is critical to the drug development process. PLA can be determined directly by experimental methods, but it is time-consuming and costly. In recent years, deep learning has been widely applied to PLA prediction, the key of which lies in the comprehensive and accurate representation of proteins and ligands. In this study, we proposed a multi-modal deep learning model based on the early fusion strategy, called DeepLIP, to improve PLA prediction by integrating multi-level information, and further used it for virtual screening of extracellular signal-regulated protein kinase 2 (ERK2), an ideal target for cancer treatment. Experimental results from model evaluation showed that DeepLIP achieved superior performance compared to state-of-the-art methods on the widely used benchmark dataset. In addition, by combining previously developed machine learning models and molecular dynamics simulation, we screened three novel hits from a drug-like natural product library. These compounds not only had favorable physicochemical properties, but also bound stably to the target protein. We believe they have the potential to serve as starting molecules for the development of ERK2 inhibitors.

Native ESI-MS and Collision-Induced Unfolding (CIU) of the Complex between Bacterial Elongation Factor-Tu and the Antibiotic Enacyloxin IIa

Collision-induced unfolding (CIU) of protein ions, monitored by ion mobility-mass spectrometry, can be used to assess the stability of their compact gas-phase fold and hence provide structural information. The bacterial elongation factor EF-Tu, a key protein for mRNA translation in prokaryotes and hence a promising antibiotic target, has been studied by CIU. The major [M + 12H]12+ ion of EF-Tu unfolded in collision with Ar atoms between 40 and 50 V, corresponding to an Elab energy of 480-500 eV. Binding of the cofactor analogue GDPNP and the antibiotic enacyloxin IIa stabilized the compact fold of EF-Tu, although dissociation of the latter from the complex diminished its stabilizing effect at higher collision energies. Molecular dynamics simulations of the [M + 12H]12+ EF-Tu ion showed similar qualitative behavior to the experimental results.

Exploring ligands that target von Willebrand factor selectively under oxidizing conditions through docking and molecular dynamics simulations

The blood protein von Willebrand factor (VWF) is a large multimeric protein that, when activated, binds to blood platelets, tethering them to the site of vascular injury and initiating blood coagulation. This process is critical for the normal hemostatic response, but especially under inflammatory conditions, it is thought to be a major player in pathological thrombus formation. For this reason, VWF has been the target for the development of anti-thrombotic therapeutics. However, it is challenging to prevent pathological thrombus formation while still allowing normal physiological blood coagulation, as currently available anti-thrombotic therapeutics are known to cause unwanted bleeding, in particular intracranial hemorrhage. This work explores the possibility of inhibiting VWF selectively under the inflammatory conditions present during pathological thrombus formation. In particular, the A2 domain of VWF is known to inhibit the neighboring A1 domain from binding to the platelet surface receptor GpIbα, and this auto-inhibitory mechanism has been shown to be removed by oxidizing agents released during inflammation. Hence, finding drug molecules that bind at the interface between A1 and A2 only under oxidizing conditions could restore such an auto-inhibitory mechanism. Here, by using a combination of computational docking, molecular dynamics simulations, and free energy perturbation calculations, a ligand from the ZINC15 database was identified that binds at the A1A2 interface, with the interaction being stronger under oxidizing conditions. The results provide a framework for the discovery of drug molecules that bind to a protein selectively in the presence of inflammatory conditions.

Unleashing the power of generative AI in drug discovery

Artificial intelligence (AI) is revolutionizing drug discovery by enhancing precision, reducing timelines and costs, and enabling AI-driven computer-aided drug design. This review focuses on recent advancements in deep generative models (DGMs) for de novo drug design, exploring diverse algorithms and their profound impact. It critically analyses the challenges that are intricately interwoven into these technologies, proposing strategies to unlock their full potential. It features case studies of both successes and failures in advancing drugs to clinical trials with AI assistance. Last, it outlines a forward-looking plan for optimizing DGMs in de novo drug design, thereby fostering faster and more cost-effective drug development.

CHARMM GUI Membrane Builder for oxidized phospholipid membrane modeling and simulation

Oxidative stress leads to the production of oxidized phospholipids (oxPLs) that modulate the biophysical properties of phospholipid monolayers and bilayers. As many immune cells are responsible for surveilling cells and tissues for the presence of oxPLs, oxPL-dependent mechanisms have been suggested as targets for treating chronic kidney disease, atherosclerosis, diabetes, and cancer metastasis. This review details recent experimental and computational studies that characterize oxPLs' behaviors in various monolayers and bilayers. These studies investigate how the tail length and polar functional groups of OxPLs impact membrane properties, how oxidized membranes can be stabilized, and how membrane integrity is generally affected by oxidized lipids. In addition, for oxPL-containing membrane modeling and simulation, CHARMM-GUI Membrane Builder has been extended to support a variety of oxPLs, accelerating the simulation system building process for these biologically relevant lipid bilayers.

Insights into short chain polyethylene penetration of phospholipid bilayers via atomistic molecular dynamics simulations

The escalation of global plastic production, reaching an annual output of 400 million tons, has significantly intensified concerns regarding plastic waste management. This has been exacerbated by improper recycling and disposal practices, contributing to the impending crisis of plastic pollution. Predictions indicate that by 2025, the environment will bear the burden of over ten billion metric tons of accumulated plastic waste. This situation has led to the concerning release of microplastics and nanoplastics (NPs) into the environment as plastic materials degrade, thereby posing risks to both ecosystems and human health. Nanoparticle interactions with living organisms have garnered significant attention due to their potential to disrupt vital biological processes. Of particular interest are lipid membranes, acting as crucial gatekeepers, underscoring the importance of comprehending the intricate process of NP penetration. Molecular dynamics (MD) simulations serve as a robust tool, offering molecular-level insights into these intricate interactions. In this study, we leverage all-atom MD simulations to delve into the interactions between lipid bilayers and polyethylene (PETH) chains of varying lengths. The investigation spans diverse lipid bilayer compositions-ranging from pure POPC to POPC:DPPC mixtures-revealing how PETH accommodates itself, adopts extended conformations, and influences membrane structure and ordering. Significantly, while longer PETH chains demonstrate limited passive diffusion, their potential to penetrate bilayers over extended timescales emerges as a significant revelation. Overall, this research significantly advances our comprehension of NP-membrane interactions, shedding light on the potential environmental and health implications that lie ahead.

Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions

Due to its emerging resistance to first-line anti-TB medications, tuberculosis (TB) is one of the most contagious illness in the world. According to reports, the effectiveness of treating TB is severely impacted by drug resistance, notably resistance caused by mutations in the pncA gene-encoded pyrazinamidase (PZase) to the front-line drug pyrazinamide (PZA). The present study focused on investigating the resistance mechanism caused by the mutations D12N, T47A, and H137R to better understand the structural and molecular events responsible for the resistance acquired by the pncA gene of Mycobacterium tuberculosis (MTB) at the structural level. Bioinformatics analysis predicted that all three mutations were deleterious and located near the active centre of the pncA, affecting its functional activity. Furthermore, molecular dynamics simulation (MDS) results established that mutations significantly reduced the structural stability and caused the rearrangement of FE2+ in the active centre of pncA. Moreover, essential dynamics analysis, including principal component analysis (PCA) and free energy landscape (FEL), concluded variations in the protein motion and decreased conformational space in the mutants. Additionally, the mutations potentially impacted the network topologies and altered the residual communications in the network. The complex simulation study results established the significant movement of the flap region from the active centre of mutant complexes, further supporting the flap region's significance in developing resistance to the PZA drug. This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).

Computational identification of new TKI as potential noncovalent reversible EGFRL858R/T790M inhibitors: VHTS, molecular docking, DFT study and molecular dynamic simulation

The mutations concerned with non-small cell lung cancer involving epidermal growth factor receptor of tyrosine kinase family have primarily targeted. In this study, we employed a scalable high-throughput virtual screening (HTVS) framework and a targeted compound library of over 50.000 Erlotinib-derived compounds as noncovalent reversible EGFRL858R/T790M inhibitors. Our HTVS work flow leverages include HTVS, SP (Standard Precision) and XP (Extra Precision) docking protocol along with its relative binding free energy calculation, cluster analysis study and ADMET properties. Then we used multiple ns-time scale molecular dynamics (MD) simulations and density functional theory (DFT) precise calculation techniques to elucidate how the bound ligand interact with the complexes conformational states involving motions both proximal and distal to the binding site. Based on glide score and protein-ligand interactions, the highest scoring molecule was selected for molecular dynamic simulation providing a complete insight into the conformational stability. A hyperfine analysis of DFT based refinement strategy highly supported their stability by strong intermolecular interactions. Together, our results demonstrate that the virtually screened top retained molecules present the best moieties introduced to Erlotinib. They exhibit interesting pharmacokinetic properties that can act as potent antitumor drug candidates than the lead compound drug and in some extent tackling the drug resistance problem which offer a springboard for further therapeutic experiments and applications.Communicated by Ramaswamy H. Sarma.

Discovery of New Dual-Target Agents Against PPAR-γ and α-Glucosidase Enzymes with Molecular Modeling Methods: Molecular Docking, Molecular Dynamic Simulations, and MM/PBSA Analysis

Type 2 diabetes mellitus (T2DM) has become a serious public health problem both in our country and worldwide, being the most prevalent type of diabetes. The combined use of drugs in the treatment of T2DM leads to serious side effects, including gastrointestinal problems, liver toxicity, hypoglycemia, and treatment costs. Hence, there has been a growing emphasis on drugs that demonstrate dual interactions. Several studies have suggested that dual-target agents for peroxisome proliferator-activated receptor-γ (PPAR-γ) and alpha-glucosidase (α-glucosidase) could be a potent approach for treating patients with diabetes. We aim to develop new antidiabetic agents that target PPAR-γ and α-glucosidase enzymes using molecular modeling techniques. These compounds show dual interactions, are more effective, and have fewer side effects. The molecular docking method was employed to investigate the enzyme-ligand interaction mechanisms of 159 newly designed compounds with target enzymes. Additionally, we evaluated the ADME properties and pharmacokinetic suitability of these compounds based on Lipinski and Veber's rules. Compound 70, which exhibited favorable ADME properties, demonstrated more effective binding energy with both PPAR-γ and α-glucosidase enzymes (-12,16 kcal/mol, -10.07 kcal/mol) compared to the reference compounds of Acetohexamide (-9.31 kcal/mol, -7.48 kcal/mol) and Glibenclamide (-11.12 kcal/mol, -8.66 kcal/mol). Further, analyses of MM/PBSA binding free energy and molecular dynamics (MD) simulations were conducted for target enzymes with compound 70, which exhibited the most favorable binding affinities with both enzymes. Based on this information, our study aims to contribute to the development of new dual-target antidiabetic agents with improved efficacy, reduced side effects, and enhanced reliability for diabetes treatment.

In silico designing of novel epitope-based peptide vaccines against HIV-1

The HIV-1 virus has been regarded as a catastrophe for human well-being. The global incidence of HIV-1-infected individuals is increasing. Hence, development of effective immunostimulatory molecules has recently attracted an increasing attention in the field of vaccine design against HIV-1 infection. In this study, we explored the impacts of CD40L and IFN-γ as immunostimulatory adjuvants for our candidate HIV-1 Nef vaccine in human and mouse using immunoinformatics analyses. Overall, 18 IFN-γ-based vaccine constructs (9 constructs in human and 9 constructs in mouse), and 18 CD40L-based vaccine constructs (9 constructs in human and 9 constructs in mouse) were designed. To find immunogenic epitopes, important characteristics of each component (e.g., MHC-I and MHC-II binding, and peptide-MHC-I/MHC-II molecular docking) were determined. Then, the selected epitopes were applied to create multiepitope constructs. Finally, the physicochemical properties, linear and discontinuous B cell epitopes, and molecular interaction between the 3D structure of each construct and CD40, IFN-γ receptor or toll-like receptors (TLRs) were predicted. Our data showed that the full-length CD40L and IFN-γ linked to the N-terminal region of Nef were capable of inducing more effective immune response than multiepitope vaccine constructs. Moreover, molecular docking of the non-allergenic full-length- and epitope-based CD40L and IFN-γ constructs to their cognate receptors, CD40 and IFN-γ receptors, and TLRs 4 and 5 in mouse were more potent than in human. Generally, these findings suggest that the full forms of these adjuvants could be more efficient for improvement of HIV-1 Nef vaccine candidate compared to the designed multiepitope-based constructs.

Therapeutic peptides for coronary artery diseases: in silico methods and current perspectives

Many drug formulations containing small active molecules are used for the treatment of coronary artery disease, which affects a significant part of the world's population. However, the inadequate profile of these molecules in terms of therapeutic efficacy has led to the therapeutic use of protein and peptide-based biomolecules with superior properties, such as target-specific affinity and low immunogenicity, in critical diseases. Protein‒protein interactions, as a consequence of advances in molecular techniques with strategies involving the combined use of in silico methods, have enabled the design of therapeutic peptides to reach an advanced dimension. In particular, with the advantages provided by protein/peptide structural modeling, molecular docking for the study of their interactions, molecular dynamics simulations for their interactions under physiological conditions and machine learning techniques that can work in combination with all these, significant progress has been made in approaches to developing therapeutic peptides that can modulate the development and progression of coronary artery diseases. In this scope, this review discusses in silico methods for the development of peptide therapeutics for the treatment of coronary artery disease and strategies for identifying the molecular mechanisms that can be modulated by these designs and provides a comprehensive perspective for future studies.

Effect of leaflet asymmetry on the stretching elasticity of lipid bilayers with phosphatidic acid

The asymmetry of membranes has a significant impact on their biophysical characteristics and behavior. This study investigates the composition and mechanical properties of symmetric and asymmetric membranes in giant unilamellar vesicles (GUVs) made of palmitoyloleoyl phosphatidylcholine (POPC) and palmitoyloleoyl phosphatidic acid (POPA). A combination of fluorescence quantification, zeta potential measurements, micropipette aspiration, and bilayer molecular dynamics simulations are used to characterize these membranes. The outer leaflet composition in vesicles is found consistent across the two preparation methods we employed, namely electroformation and inverted emulsion transfer. However, characterizing the inner leaflet poses challenges. Micropipette aspiration of GUVs show that oil residues do not substantially alter membrane elasticity, but simulations reveal increased membrane thickness and decreased interleaflet coupling in the presence of oil. Asymmetric membranes with a POPC:POPA mixture in the outer leaflet and POPC in the inner leaflet display similar stretching elasticity values to symmetric POPC:POPA membranes, suggesting potential POPA insertion into the inner leaflet during vesicle formation and suppressed asymmetry. The inverse compositional asymmetry, with POPC in the outer leaflet and POPC:POPA in the inner one yield less stretchable membranes with higher compressibility modulus compared with their symmetric counterparts. Challenges in achieving and predicting compositional correspondence highlight the limitations of phase-transfer-based methods. In addition, caution is advised when using fluorescently labeled lipids (even at low fractions of 0.5 mol %), as unexpected gel-like domains in symmetric POPC:POPA membranes were observed only with a specific type of labeled DOPE (dioleoylphosphatidylethanolamine) and the same fraction of unlabeled DOPE. The latter suggest that such domain formation may result from interactions between lipids and membrane fluorescent probes. Overall, this study underscores the complexity of factors influencing GUV membrane asymmetry, emphasizing the need for further research and improvement of characterization techniques.

Pulsed electric field induces exocytosis and overexpression of MAGE antigens in melanoma

Nanosecond pulsed electric field (nsPEF) has emerged as a promising approach for inducing cell death in melanoma, either as a standalone treatment or in combination with chemotherapeutics. However, to date, there has been a shortage of studies exploring the impact of nsPEF on the expression of cancer-specific molecules. In this investigation, we sought to assess the effects of nsPEF on melanoma-specific MAGE (Melanoma Antigen Gene Protein Family) expression. To achieve this, melanoma cells were exposed to nsPEF with parameters set at 8 kV/cm, 200 ns duration, 100 pulses, and a frequency of 10 kHz. We also aimed to comprehensively describe the consequences of this electric field on melanoma cells' invasion and proliferation potential. Our findings reveal that following exposure to nsPEF, melanoma cells release microvesicles containing MAGE antigens, leading to a simultaneous increase in the expression and mRNA content of membrane-associated antigens such as MAGE-A1. Notably, we observed an unexpected increase in the expression of PD-1 as well. While we did not observe significant differences in the cells' proliferation or invasion potential, a remarkable alteration in the cells' metabolomic and lipidomic profiles towards a less aggressive phenotype was evident. Furthermore, we validated these results using ex vivo tissue cultures and 3D melanoma culture models. Our study demonstrates that nsPEF can elevate the expression of membrane-associated proteins, including melanoma-specific antigens. The mechanism underlying the overexpression of MAGE antigens involves the initial release of microvesicles containing MAGE antigens, followed by a gradual increase in mRNA levels, ultimately resulting in elevated expression of MAGE antigens post-experiment. These findings shed light on a novel method for modulating cancer cells to overexpress cancer-specific molecules, thereby potentially enhancing their sensitivity to targeted anticancer therapy.

Actuation mechanism of a nanoscale drilling rig based on nested carbon nanotubes

With the increasing emphasis on health and the continuous improvement of medical standards, more and more micro/nano devices are being used in the medical field. However, the existing micro/nano devices cannot effectively solve various problems encountered in medical processes and achieve specific therapeutic effects. Based on this, this article designs a new type of nanoscale drilling rig. The nanoscale drilling rig is composed of double-layer nested carbon nanotubes with multiple electrodes, and is powered by an external power source, making it easy to perform long-term surgery in the human body. Through coding strategies, we can adjust the surface charge density and distribution of the nanoscale drilling rig, thereby controlling its periodical rotation and achieving precise medical treatment. In addition, in order to control the length of the nanoscale drill bit, meet the treatment needs of different parts of the human body, and reduce damage to the human body, we have designed a structure of ion electric double layers so that the drill bit can be fixed in different positions, reducing the risk of treatment to a certain extent. This drilling rig enriches the functions of micro/nano devices, which is beneficial for the development of the medical industry.

Identifying and Assessing Putative Allosteric Sites and Modulators for CXCR4 Predicted through Network Modeling and Site Identification by Ligand Competitive Saturation

The chemokine receptor CXCR4 is a critical target for the treatment of several cancer types and HIV-1 infections. While orthosteric and allosteric modulators have been developed targeting its extracellular or transmembrane regions, the intramembrane region of CXCR4 may also include allosteric binding sites suitable for the development of allosteric drugs. To investigate this, we apply the Gaussian Network Model (GNM) to the monomeric and dimeric forms of CXCR4 to identify residues essential for its local and global motions located in the hinge regions of the protein. Residue interaction network (RIN) analysis suggests hub residues that participate in allosteric communication throughout the receptor. Mutual residues from the network models reside in regions with a high capacity to alter receptor dynamics upon ligand binding. We then investigate the druggability of these potential allosteric regions using the site identification by ligand competitive saturation (SILCS) approach, revealing two putative allosteric sites on the monomer and three on the homodimer. Two screening campaigns with Glide and SILCS-Monte Carlo docking using FDA-approved drugs suggest 20 putative hit compounds including antifungal drugs, anticancer agents, HIV protease inhibitors, and antimalarial drugs. In vitro assays considering mAB 12G5 and CXCL12 demonstrate both positive and negative allosteric activities of these compounds, supporting our computational approach. However, in vivo functional assays based on the recruitment of β-arrestin to CXCR4 do not show significant agonism and antagonism at a single compound concentration. The present computational pipeline brings a new perspective to computer-aided drug design by combining conformational dynamics based on network analysis and cosolvent analysis based on the SILCS technology to identify putative allosteric binding sites using CXCR4 as a showcase.

Insights into Transfer of Supramolecular Doxorubicin/Congo Red Aggregates through Phospholipid Membranes

Doxorubicin (DOX) is a commonly used chemotherapeutic drug, from the anthracycline class, which is genotoxic to neoplastic cells via a DNA intercalation mechanism. It is effective and universal; however, it also causes numerous side effects. The most serious of them are cardiotoxicity and a decrease in the number of myeloid cells. For this reason, targeted DOX delivery systems are desirable, since they would allow lowering the drug dose and therefore limiting systemic side effects. Recently, synthetic dyes, in particular Congo red (CR), have been proposed as possible DOX carriers. CR is a planar molecule, built of a central biphenyl moiety and two substituted naphthalene rings, connected with diazo bonds. In water, it forms elongated ribbon-shaped supramolecular structures, which are able to selectively interact with immune complexes. In our previous studies, we have shown that CR aggregates can intercalate DOX molecules. In this way, they preclude DOX precipitation in water solutions and increase its uptake by MCF7 breast cancer cells. In the present work, we further explore the interactions between DOX, CR, and their aggregates (CR/DOX) with phospholipid membranes. In addition to neutral molecules, the protonated doxorubicin form, DXP, is also studied. Molecular dynamics simulations are employed to study the transfer of CR, DOX, DXP, and their aggregates through POPC bilayers. Interactions of CR, DOX, and CR/DOX with model monolayers are studied with Langmuir trough measurements. This study shows that CR may support the transfer of doxorubicin molecules into the bilayer. Both electrostatic and van der Waals interactions with lipids are important in this respect. The former promote the initial stages of the insertion process, the latter keep guest molecules inside the bilayer.

Comparative Retention Analysis of Intercalated Cations Inside the Interlayer Gallery of Lamellar and Nonlamellar Graphene Oxide Membranes in Reverse Osmosis Process: A Molecular Dynamics Study

Over the past decade, multilayered graphene oxide (GO) membranes have emerged as promising candidates for desalination applications. Despite their potential, a comprehensive understanding of separation mechanisms remains elusive due to the intricate morphology and structural arrangement of interlayer galleries. Moreover, a critical concern of multilayered GO membranes is their susceptibility to swelling within aqueous environments, which hinders their practical implementation. Therefore, this study introduces cation intercalation within GO laminates to elucidate the underlying factors governing swelling behavior and subsequently mitigate it. Moreover, this study performed nonequilibrium molecular dynamics simulations on the cation (Mg2+ or K+)-intercalated lamellar and nonlamellar GO membranes to understand the effect of the arrangement of GO sheets on the retention time of intercalated cations within GO layers, water permeance, and salt rejection mechanism in the reverse osmosis process using cation-intercalated GO membranes. Our results highlight that lamellar GO membranes exhibit higher water permeance, attributed to their well-defined interlayer gallery structure. On the other hand, nonlamellar GO membranes display superior salt rejection due to their complex interlayer gallery structure that impedes salt permeation. Moreover, the structural complexity of nonlamellar GO membranes contributes to greater stability by retention of the more intercalated cations for a longer time within the layers. Furthermore, it is observed that a higher percentage of Mg2+ cations remained inside the GO laminates as compared to K+ cations, hence resulting in the greater stability of the Mg2+-intercalated GO membrane in the aqueous environment.

Efficient Refinement of Complex Structures of Flexible Histone Peptides Using Post-Docking Molecular Dynamics Protocols

Histones are keys to many epigenetic events and their complexes have therapeutic and diagnostic importance. The determination of the structures of histone complexes is fundamental in the design of new drugs. Computational molecular docking is widely used for the prediction of target-ligand complexes. Large, linear peptides like the tail regions of histones are challenging ligands for docking due to their large conformational flexibility, extensive hydration, and weak interactions with the shallow binding pockets of their reader proteins. Thus, fast docking methods often fail to produce complex structures of such peptide ligands at a level appropriate for drug design. To address this challenge, and improve the structural quality of the docked complexes, post-docking refinement has been applied using various molecular dynamics (MD) approaches. However, a final consensus has not been reached on the desired MD refinement protocol. In this present study, MD refinement strategies were systematically explored on a set of problematic complexes of histone peptide ligands with relatively large errors in their docked geometries. Six protocols were compared that differ in their MD simulation parameters. In all cases, pre-MD hydration of the complex interface regions was applied to avoid the unwanted presence of empty cavities. The best-performing protocol achieved a median of 32% improvement over the docked structures in terms of the change in root mean squared deviations from the experimental references. The influence of structural factors and explicit hydration on the performance of post-docking MD refinements are also discussed to help with their implementation in future methods and applications.

Binding of Carbon Monoxide to Hemoglobin in an Oxygen Environment: Force Field Development for Molecular Dynamics

Carbon monoxide (CO) is a byproduct of the incomplete combustion of carbon-based fuels, such as wood, coal, gasoline, or natural gas. As incomplete combustion in a fire accident or in an engine, massively produced CO leads to a serious life threat because CO competes with oxygen (O2) binding to hemoglobin and makes people suffer from hypoxia. Although there is hyperbaric O2 therapy for patients with CO poisoning, the nanoscale mechanism of CO dissociation in the O2-rich environment is not completely understood. In this study, we construct the classical force field parameters compatible with the CHARMM for simulating the coordination interactions between hemoglobin, CO, and O2, and use the force field to reveal the impact of O2 on the binding strength between hemoglobin and CO. Density functional theory and Car-Parrinello molecular dynamics simulations are used to obtain the bond energy and equilibrium geometry, and we used machine learning enabled via a feedforward neural network model to obtain the classical force field parameters. We used steered molecular dynamics simulations with a force field to characterize the mechanical strength of the hemoglobin-CO bond before rupture under different simulated O2-rich environments. The results show that as O2 approaches the Fe2+ of heme at a distance smaller than ∼2.8 Å, the coordination bond between CO and Fe2+ is reduced to 50% bond strength in terms of the peak force observed in the rupture process. This weakening effect is also shown by the free energy landscape measured by our metadynamics simulation. Our work suggests that the O2-rich environment around the hemoglobin-CO bond effectively weakens the bonding, so that designing of O2 delivery vector to the site is helpful for alleviating CO binding, which may shed light on de novo drug design for CO poisoning.