CHARMM: the biomolecular simulation program

Structural Insights Into the Impact of the Glycine-Rich Loop Mutation in Noonan Syndrome on the ATP Binding Pocket of CRAF Kinase

The pathogenic G361A variant of CRAF, associated with increased intrinsic kinase activity in Noonan syndrome (NS), remains poorly understood in terms of its molecular and structural impact on kinase activity. To elucidate the mechanistic implications of the glycine to alanine substitution at residue 361 in CRAF, we employed molecular dynamics simulations. Our findings reveal that this mutation predominantly affects the ATP binding pocket and critical intermolecular interactions within the active cleft that favors the phosphate transfer reaction. Notably, our data highlight significant alterations in key interactions involving Lys470/Asp486 and ATP.Mg2+ in CRAFG361A that are absent in wild-type CRAF. Additionally, we identified a novel interaction mode between Lys431 and γ-phosphate in wild-type CRAF, a residue evolutionarily conserved in CRAFs but not in related kinases such as BRAF, ARAF, and KSR1/2. Furthermore, observed shifts in the αC-helix and G-loop relative to the wild-type correlate with an enlarged ATP-binding cavity in the mutant, reflecting structural adaptations due to these mutations. Overall, these structural insights underscore the elevated intrinsic kinase activity of the CRAFG361A variant and provide crucial mechanistic details that could inform the development of specific inhibitors targeting this variant.

Design, synthesis, molecular modeling, and biological evaluations of novel chalcone based 4-Nitroacetophenone derivatives as potent anticancer agents targeting EGFR-TKD

A series of chalcone-based 4-Nitroacetophenone derivatives were designed and synthesized by the single-step condensation method. These compounds were identified by 1H NMR,13C NMR, MS, and FTIR analysis. Further, the derivatives were evaluated against four cancer cell lines H1299, MCF-7, HepG2, and K526. The IC50 value of potent compounds NCH-2, NCH-4, NCH-5, NCH-6, NCH-8, and NCH-10 was 4.5-11.4 μM in H1299, 4.3-15.7 μM in MCF-7, 2.7-4.1 μM in HepG2 and 4.9-19.7 μM in K562. To assess the toxicity against healthy cells all potent molecules were evaluated against the HEK-293T cell line, and IC50 values exhibited by NCH-2, and NCH-3 were 77.8, 74.3, and other molecules showed IC50 values > 100 μM. The EGFR expression was determined by using rabbit anti-EGFR monoclonal antibody and significant EGFR expression was knocked down observed in H1299 treated with NCH-10 as well as erlotinib. The underlying mechanism behind cell death was investigated through bioinformatics. First, the molecules were optimized and docked to the binding site of the EGFR kinase domain. The best complexes were simulated for 100-ns and compounds NCH-2, NCH-4, and NCH-10 achieved stability similar to the erlotinib bound kinase domain. The free energy binding (ΔGbind) of NCH-10 was found to be more negative -226.616 ± 2.148 kJ/mol calculated by Molecular Mechanics Poisson Boltzmann's Surface Area (MM-PBSA) method. Both in vitro and in silico results conclude that the present class of chalcone-based 4-Nitroacetophenone derivatives are potent anti-cancer agents targeting EGFR-TKD and are 39 folds more effective against H1299, MCF-7, HepG2, and K562 carcinoma cell lines than healthy HEK-293T cell lines.

Discovery of new dual butyrylcholinesterase (BuChE) inhibitors and 5-HT7 receptor antagonists as compounds used to treat Alzheimer's disease symptoms

Alzheimer's disease is a neurodegenerative condition with no effective cure, and current therapies, like donepezil, only alleviate symptoms. Research has explored cholinesterase inhibitors and strategies targeting tau protein, often combining inhibitors with 5-HT receptor antagonists, particularly 5-HT6. However, dual-action BuChE inhibitors and 5-HT7 antagonists have not been studied until now. This study evaluated such compounds in an animal model, focusing on two candidates: compound 18 (BuChE IC50 = 4.75 μM; 5-HT7Ki = 7 nM) and compound 50 (BuChE IC50 = 2.53 μM; 5-HT7Ki = 1 nM). Compound 50 showed robust cognitive improvements, enhancing memory consolidation and acquisition, particularly in reversing scopolamine-induced deficits. In contrast, compound 18 exhibited limited or dose-dependent efficacy, potentially limiting its applicability. These findings highlight the strong potential of compound 50 for cognitive enhancement therapies and suggest it warrants further investigation.

Development of new anticancer thiadiazole-sulfonamides as dual EGFR/carbonic anhydrase inhibitors

BACKGROUND

Thiadiazole-sulfonamide derivatives were synthesized as dual inhibitors of epidermal growth factor receptor (EGFR) and carbonic anhydrase IX (CA-IX) to develop selective anticancer agents.

METHODS

Cytotoxicity was evaluated against MDA-MB-231 and MCF-7 breast cancer cells, with selectivity tested on Vero cells. Enzymatic inhibition studies were conducted against EGFR and CA-IX, using erlotinib and acetazolamide as reference drugs. Apoptosis was assessed through gene expression analysis of BAX/Bcl-2, caspase-8, and caspase-9, alongside flow cytometry for apoptosis and cell cycle analysis. Molecular docking and 200 ns molecular dynamics (MD) simulations evaluated binding interactions. Density Functional Theory (DFT) calculations and in silico ADMET predictions assessed stability, electronic properties, and safety.

RESULTS

Compound 14 exhibited potent cytotoxicity (IC₅₀ = 5.78 μM, MDA-MB-231; 8.05 μM, MCF-7) and high selectivity (IC₅₀ = 313.08 μM, Vero). It inhibited EGFR (IC₅₀ = 5.92 nM) and CA-IX (IC₅₀ = 63 nM), surpassing reference drugs. Apoptosis induction was confirmed by a 13.97-fold increase in BAX/Bcl-2, caspase upregulation, and G1-phase arrest. Computational analyses confirmed stable binding and favorable safety.

CONCLUSIONS

Compound 14 represents a promising dual EGFR/CA-IX inhibitor with selective anticancer activity. Further in vivo studies are warranted.

Highly tail-asymmetric lipids interdigitate and cause bidirectional ordering

Phospholipids form structurally and compositionally diverse membranes. A less studied type of compositional diversity involves phospholipid tail variety. Some phospholipids contain two acyl tails which differ in length. These tail-asymmetric lipids are shown to contribute to temperature sensitivity, oxygen adaptability, and membrane fluidity. Membranes of a highly virulent intracellular bacterium, Francisella tularensis, contain highly tail-asymmetric 1-lignoceroyl-2-decanoyl-sn-glycero-3-phosphatidylethanolamine (XJPE) lipids which were previously shown to inhibit inflammatory responses in host cells. XJPE tails have unusually high asymmetry, and how they contribute to membrane properties on a molecular level is unknown. Here, we use small angle X-ray scattering and molecular dynamics simulations to investigate how varying XJPE ratios alters properties of simple membranes. Our results demonstrate that at high concentration they promote liquid-to-gel transition in otherwise liquid membranes, while at low concentration they are tolerated well, minimally altering membrane properties. In liquid membranes, XJPE lipids dynamically adopt two main conformations; with the long tail extended into the opposing leaflet or bent-back residing in its own leaflet. When added to both leaflets XJPE primarily adopts an extended confirmation, while asymmetric addition results in more bent-back orientations. The former increases tail ordering and the latter decreases it. XJPE tails adopt different conformations that induce composition- and leaflet-dependent bidirectional effect on membrane fluidity and this suggests that Francisella tularensis could use tail asymmetry to facilitate vesicle fusion and destabilize host cells. The effect of tail-asymmetric lipids on complex membranes should be further investigated to reveal the regulatory roles of high tail asymmetry.

Transport of phenoxyacetic acid herbicides by PIN-FORMED auxin transporters

Auxins are a group of phytohormones that control plant growth and development. Their crucial role in plant physiology has inspired development of potent synthetic auxins that can be used as herbicides. Phenoxyacetic acid derivatives are a widely used group of auxin herbicides in agriculture and research. Despite their prevalence, the identity of the transporters required for distribution of these herbicides in plants is both poorly understood and the subject of controversial debate. Here we show that PIN-FORMED auxin transporters transport a range of phenoxyacetic acid herbicides across the membrane. We go on to characterize the molecular determinants of substrate specificity using a variety of different substrates as well as protein mutagenesis to probe the binding site. Finally, we present cryogenic electron microscopy structures of Arabidopsis thaliana PIN8 bound to either 2,4-dichlorophenoxyacetic acid or 4-chlorophenoxyacetic acid. These structures represent five key states from the transport cycle, allowing us to describe conformational changes associated with the transport cycle. Overall, our results reveal that phenoxyacetic acid herbicides use the same export machinery as endogenous auxins and exemplify how transporter binding sites undergo transformations that dictate substrate specificity. These results provide a foundation for future development of novel synthetic auxins and for precision breeding of herbicide-resistant crop plants.

Discovery of therapeutic promising natural products to target Kv1.3 channel, a transmembrane protein regulating immune disorders, through multidimensional virtual screening, molecular dynamics simulations and biological validation

Kv1.3 voltage-gated potassium channel, is a transmembrane protein that facilitates K+ movement through cell membranes via its intrinsic pores, regulating the cell signaling cascades, especially in immune disorders. In this paper, we employed multidimensional virtual screening to identify 24 potential Kv1.3 inhibitors from a library of 27,637 compounds, with electrophysiological assays confirming 8 active inhibitors (33.33 % hit rate). Structure-activity relationship (SAR) analysis demonstrated that 4-methylpentyl group in side chain and furan ring in Furanocoumarins skeleton are crucial to the bioactivity of target compounds. Orthogonal projection to latent structures model reveals that increasing the QPlogPo/w of the compound can increase activity. Molecular dynamics simulations revealed key roles of residues (VAL469 and ILE472) as active binding sites of Kv1.3 for binding of specific compound. Notopterol (Z4), the most potent Kv1.3 inhibitor (IC50 = 311.90 ± 1.24 nM), significantly suppressed IFN-γ release from CD4+ T cells, whereas, Kv1.3 inactive compound Z20 at 5 μM showed no significant difference in IFN-γ release from CD4+ T cells. In atopic dermatitis rat model, Notopterol reduced epidermal thickening, IgE, Kv1.3, IL-1β production, and infiltration of CD4+ T cells and mast cells. These findings establish Notopterol as a promising Kv1.3 inhibitor for therapeutic applications in immune disorders.

Organic-solvent mediated self-assembly of protoporphyrin IX with human serum albumin

This study investigates the non-native interactions between the photosensitizer protoporphyrin IX (PPIX) and human serum albumin (HSA). Non-covalent binding between small molecules and proteins, is crucial for various applications in biomedicine, food processing, energy conversion, and sensing. The research focuses on the role of a series of organic solvents in facilitating the binding of water-insoluble PPIX to the protein. By using dialysis and centrifugation for sample preparation and combining experimental and computational methods for characterization, the study found that non-protic solvents such as THF and DMSO are more effective in forming the PPIX:HSA complex compared to protic solvents. Additionally, the temporary presence of these organic solvents during incubation does not cause significant and irreversible changes in the protein structure. Instead, THF and DMSO temporarily loosen the protein, increasing the distance between two tyrosine residues (Y138 and Y161) that are believed to coordinate the porphyrin at its binding site. This finding underscores the importance of selecting appropriate solvents to enhance the binding efficiency of small ligands to proteins.

Strategic lead compound design and development utilizing computer-aided drug discovery (CADD) to address herbicide-resistant Phalaris minor in wheat fields

Wheat (Triticum aestivum) is a vital cereal crop and a staple food source worldwide. However, wheat grain productivity has significantly declined as a consequence of infestations by Phalaris minor. Traditional weed control methods have proven inadequate owing to the physiological similarities between P. minor and wheat during early growth stages. Consequently, farmers have turned to herbicides, targeting acetyl-CoA carboxylase (ACCase), acetolactate synthase (ALS) and photosystem II (PSII). Isoproturon targeting PSII was introduced in mid-1970s, to manage P. minor infestations. Despite their effectiveness, the repetitive use of these herbicides has led to the development of herbicide-resistant P. minor biotypes, posing a significant challenge to wheat productivity. To address this issue, there is a pressing need for innovative weed management strategies and the discovery of novel herbicide molecules. The integration of computer-aided drug discovery (CADD) techniques has emerged as a promising approach in herbicide research, that facilitates the identification of herbicide targets and enables the screening of large chemical libraries for potential herbicide-like molecules. By employing techniques such as homology modelling, molecular docking, molecular dynamics simulation and pharmacophore modelling, CADD has become a rapid and cost-effective medium to accelerate the herbicide discovery process significantly. This approach not only reduces the dependency on traditional experimental methods, but also enhances the precision and efficacy of herbicide development. This article underscores the critical role of bioinformatics and CADD in developing next-generation herbicides, offering new hope for sustainable weed management and improved wheat cultivation practices. © 2024 Society of Chemical Industry.

Computational modeling of the anti-inflammatory complexes of IL37

Interleukin (IL) 37 is an anti-inflammatory cytokine belonging to the IL1 protein family. Owing to its pivotal role in modulating immune responses, elucidating the IL37 complex structures holds substantial therapeutic promise for various autoimmune disorders and cancers. However, none of the structures of IL37 complexes have been experimentally characterized. This computational study aims to address this gap through molecular modeling and classical molecular dynamics simulations. We modeled all protein-protein complexes of IL37 using a range of methods from homology modeling to AlphaFold2 multimer predictions. Models that successfully recapitulated experimental features underwent further analysis through molecular dynamics simulations. As positive controls, binary and ternary complexes of IL18 from PDB were included for comparison. Several key findings emerged from the comparative analysis of IL37 and IL18 complexes. IL37 complexes exhibited higher mobility than the IL18 complexes. Simulations of the IL37-IL18Rα complex revealed altered receptor conformations capable of accommodating a dimeric IL37, with the N-terminal loop of IL37 contributing significantly to complex mobility. Additionally, the glycosyl chain on N297 of IL18Rα, which contours one edge of the cytokine binding surface, acted as a steric block against the N-terminal loop of IL37. Further, investigations into interactions between IL37 and IL18BP suggested that a binding mode homologous to IL18 was unstable for IL37, indicating an alternative binding mechanism. Altogether, this study accesses to the structure and dynamics of IL37 complexes, revealing the structural underpinnings of the IL37's modulatory effect on the IL18 signaling pathway.

Quantum Mechanics/Molecular Mechanics Studies on the Excited-State Relaxation Mechanisms of Cytidine Analogues: 2'-Deoxy-5-Methylcytidine and 2'-Deoxy-5-Hydroxymethylcytidine in Aqueous Solution

We have used the high-level QM(CASPT2//CASSCF)/MM method to investigate the excited-state properties and decay pathways of two important cytidine analogues, i.e., 2'-deoxy-5-methylcytidine (5mdCyd) and 2'-deoxy-5-hydroxymethylcytidine (5hmdCyd), in aqueous solution. In view of the computed minimum-energy structures, conical intersections, and crossing points, and the relevant excited-state decay paths including the different internal conversion (IC) and intersystem crossing (ISC) routes in and between the S1, T1, T2, and S0 states, we finally provided the feasible excited-state relaxation mechanisms of these two important epigenetic DNA nucleosides. Upon 285 nm photoexcitation, the lowest spectroscopically bright S1(ππ*) state is initially populated in the Franck-Condon (FC) region in both solvated systems and then mainly occurs direct IC to the ground state through the nearby accessible S1/S0 conical intersection, with the QM(CASPT2)/MM computed energy barriers of 9.5 and 1.6 kcal/mol for 5mdCyd and 5hmdCyd, respectively. In addition, the S1(ππ*) state can partially hop to the T1(ππ*) state directly or is mediated by the T2(ππ*) state. In comparison to the favorable singlet-mediated IC channel, the minor S1→T1 and S1→T2→T1 ISCs would take place slowly. Subsequently, the T1 state will further approach the nearby T1/S0 crossing point to slowly deactivate to the S0 state. Due to the T1/S0 crossing point above the T1-MIN as well with the small T1/S0 SOC, i.e., 9.8 kcal/mol and 0.3 cm-1 in 5mdCyd and 8.7 kcal/mol and 1.9 cm-1 in 5hmdCyd, the slow ISC would trap the system in the T1 state for a long time. The present work rationalizes the excited-state dynamics of 5mdCyd and 5hmdCyd in aqueous solution and could provide mechanistic insights into understanding the photophysics and photochemistry of similar epigenetic DNA nucleosides and their derivatives.

Computational study of interaction of calixarene with ebola virus structural proteins and its potential therapeutic implications

Ebola virus (EBOV) is a negative-strand RNA virus that causes hemorrhagic fever and fatal illness in humans. According to WHO, the Ebola virus caused 28,646 fatal cases and 11,323 deaths in West Africa due to hemorrhagic fever and deadly disease in humans between 2013 and 2016. Between 1976 and 2022, approximately 15,409 fatalities caused by EBOV took place worldwide. Unfortunately, no effective vaccine or drugs are available to prevent this deadly disease. In the present study, State-of-the-art tools based on in-silico methods were used to elucidate the interaction pattern of calixarene (CAL) with seven EBOV structural proteins, i.e., GP1,2, nucleoprotein (NP), polymerase cofactor (VP35), (VP40), transcription activator (VP30), VP24, and RNA-dependent RNA polymerase (L). CAL is a cage-like compound with supramolecular features. The molecular docking lead analysis using AutoDock tool has been performed to find out the binding pattern of CAL with EBOV proteins. Obtained results revealed efficient inhibitory properties of calixarene (CAL) against seven Ebola virus structural proteins i.e., GP1,2, nucleoprotein (NP), polymerase cofactor (VP35), (VP40), transcription activator (VP30), VP24, and RNA-dependent RNA polymerase (L). Molecular docking analysis shows that the interaction of CAL with VP24 was highest with the total binding energy -12.47 kcal/mol and 26.90 nM inhibitions constant. Molecular Dynamics study has also quantified the efficiency of CAL against VP24. In conclusion, the present study suggests that CAL and its derivatives could be used as inhibitors to counter EBOV infection. Furthermore, in vitro and in vivo laboratory experimentation is required to establish CAL and its derivatives as a potential inhibitor against EBOV.

Structural and functional analysis of engineered antibodies for cancer immunotherapy: insights into protein compactness and solvent accessibility

Antibodies are crucial tools in various biomedical applications, including immunotherapy. In this study, we focused on designing and engineering antibodies to enhance their structural dynamics and functional properties. By employing advanced computational techniques and experimental validation, we gained crucial insights into the impact of specific mutations on the engineered antibodies. This study investigates the design and engineering of antibodies to improve their structural dynamics and functional properties. Structural attributes, such as protein compactness and solvent accessibility, were assessed, revealing interesting trends in anti-CD3 and anti-HER2 antibodies. Mutations in CD3 antibodies resulted in a more stable conformation, while mutant HER2 antibodies exhibited altered interaction with the target. Analysis of secondary structure assignments demonstrated significant changes in the folding and stability of the mutant antibodies compared to the wild-type counterparts. The conformational landscape of the engineered antibodies was explored, providing insights into folding pathways and binding mechanisms. Overall, the current study highlights the significance of antibody design and engineering in modulating structural dynamics and functional properties. The findings contribute to developing improved immunotherapeutic strategies by optimising antibody-based therapeutics for targeted diseases with enhanced efficacy and precision.

Oxidation of retromer complex controls mitochondrial translation

Reactive oxygen species (ROS) underlie human pathologies including cancer and neurodegeneration1,2. However, the proteins that sense ROS levels and regulate their production through their cysteine residues remain ill defined. Here, using systematic base-editing and computational screens, we identify cysteines in VPS35, a member of the retromer trafficking complex3, that phenocopy inhibition of mitochondrial translation when mutated. We find that VPS35 underlies a reactive metabolite-sensing pathway that lowers mitochondrial translation to decrease ROS levels. Intracellular hydrogen peroxide oxidizes cysteine residues in VPS35, resulting in retromer dissociation from endosomal membranes and subsequent plasma membrane remodelling. We demonstrate that plasma membrane localization of the retromer substrate SLC7A1 is required to sustain mitochondrial translation. Furthermore, decreasing VPS35 levels or oxidation of its ROS-sensing cysteines confers resistance to ROS-generating chemotherapies, including cisplatin, in ovarian cancer models. Thus, we identify that intracellular ROS levels are communicated to the plasma membrane through VPS35 to regulate mitochondrial translation, connecting cytosolic ROS sensing to mitochondrial ROS production.

On the Use of PDB X-Ray Crystal Structures as Force Field Target and Validation Data for Pyranose Ring Puckering

The carbon and oxygen atoms of tetrahydropyran form the common substructure of pyranose monosaccharides in vertebrate glycans. This substructure can assume various ring puckering chair and skew-boat conformations, and can thereby impact glycan conformations relevant for biomolecular structure and signaling. The Protein Data Bank (PDB) provides a wealth of experimental glycan structural biology data that can be useful in the development and validation of molecular mechanics force fields for these molecules. However, these experimental data are typically from solvent-depleted crystalline environments at very low temperatures, in contrast to biological conditions that are aqueous and near ambient temperature, which is the regime targeted by biomolecular force fields. To determine if these PDB X-ray crystal data can be of utility as references for carbohydrate force fields, we compared ring puckering conformations from these experimental data to both vacuum and explicit aqueous solvent puckering free energy data from extended-system adaptive biasing force (eABF) molecular dynamics simulations using the previously validated CHARMM36 force field. We found that, for monosaccharides that are not charged (glucose, N-acetylglucosamine, galactose, N-acetylgalactosamine, mannose, xylose, and fucose), both the vacuum and aqueous simulation puckering preferences strongly correlate with PDB data, and therefore with each other. In contrast, all charged monosaccharides that were considered (the conjugate bases of N-acetylneuraminic acid, glucuronic acid, and iduronic acid) had puckering preferences correlating with PDB data only in aqueous simulations and not in vacuum simulations. These results suggest that comparing puckering preferences from aqueous simulations to PDB X-ray crystal puckering conformation data can be a valid and useful component of carbohydrate force field development and validation.

Substrates (Acyl-CoA and Diacylglycerol) Entry and Products (CoA and Triacylglycerol) Egress Pathways in DGAT1

Diacylglycerol O-acyltransferase 1 (DGAT1) is an integral membrane protein that uses acyl-coenzyme A (acyl-CoA) and diacylglycerol (DAG) to catalyze the formation of triacylglycerides (TAGs). The acyl transfer reaction occurs between the activated carboxylate group of the fatty acid and the free hydroxyl group on the glycerol backbone of DAG. However, how the two substrates enter DGAT1's catalytic reaction chamber and interact with DGAT1 remains elusive. This study aims to explore the structural basis of DGAT1's substrate recognition by investigating each substrate's pathway to the reaction chamber. Using a human DGAT1 cryo-EM structure in complex with an oleoyl-CoA substrate, we designed two different all-atom molecular dynamics (MD) simulation systems: DGAT1away (both acyl-CoA and DAG away from the reaction chamber) and DGAT1bound (acyl-CoA bound in and DAG away from the reaction chamber). Our DGAT1away simulations reveal that acyl-CoA approaches the reaction chamber via interactions with positively charged residues in transmembrane helix 7. DGAT1bound simulations show DAGs entering into the reaction chamber from the cytosol leaflet. The bound acyl-CoA's fatty acid lines up with the headgroup of DAG, which appears to be competent to TAG formation. We then converted them into TAG and coenzyme (CoA) and used adaptive biasing force (ABF) simulations to explore the egress pathways of the products. We identify their escape routes, which are aligned with their respective entry pathways. Visualization of the substrate and product pathways and their interactions with DGAT1 is expected to guide future experimental design to better understand DGAT1 structure and function.

Antibacterial activity of tamoxifen derivatives against methicillin-resistant Staphylococcus aureus

The development of new antimicrobial therapeutic strategies requires urgent attention to prevent the tens of millions of deaths predicted to occur by 2050 as a result of multidrug-resistant (MDR) bacterial infections. This study aimed to discover new tamoxifen derivatives with antimicrobial potential, particularly targeting methicillin-resistant Staphylococcus aureus (MRSA). The minimum inhibitory concentration (MIC) of 22 tamoxifen derivatives was determined against S. aureus reference and MRSA strains using microdilution assays. The antibacterial effects of selected tamoxifen derivatives against MRSA (USA7 strain) were assessed through bacterial growth assays. Additionally, bacterial membrane permeability and molecular dynamics (MD) simulation assays were performed. The MIC of the tamoxifen derivatives against reference S. aureus and MRSA strains ranged from to 16 to >64 μg/mL. Bacterial growth assays demonstrated that tamoxifen derivatives 2, 5, and 6, the only compounds bearing the electron-donating hydroxyl group in the para position on both phenyl rings of the tamoxifen skeleton, dose-dependently reduced the growth of the USA7 strain. Moreover, treatment of MRSA with derivatives 2 and 5 resulted in a slight increase of membrane permeabilization. Extensive MD simulations on the interaction between 5 and 6 and the S. aureus membrane model suggest that the compounds do not act by destabilizing the membrane integrity. These findings suggest that tamoxifen derivatives exhibit antibacterial activity against MRSA, potentially broadening the spectrum of available drug treatments for combating antimicrobial-resistant S. aureus.

Studying the Protein Thermostabilities and Folding Rates by the Interaction Energy Network in Solvent

Residue interaction networks determine various characteristics of proteins, such as the folding rate, thermostability, and allosteric process. The interactions between residues can be described by distances or energies. The former is simple but less rigorous. The latter is complicated but more precise, especially when considering the solvent effect. In this work, we apply an existing energy decomposition method based on the Poisson-Boltzmann equation solver. The calculation is especially accelerated on GPU for higher performance. In four formal applications, the constructed interaction energy (IE) network shows good results. First, it is found that the protein folding rate has a stronger correlation with the energy-based contact order than the distance-based contact order. The Pearson correlation coefficient (PCC) is 0.839 versus 0.784 on a dataset of non-two-state proteins. Second, we find that most thermophilic proteins have lower IEs than mesophilic proteins. The IE in solvent acts as an indicator to evaluate the thermostabilities of proteins. Third, we use the IE network to predict the key residues in the formation of the insulin dimer. Most key residues are in agreement with the findings in previous alanine-scanning experiments. Lastly, we propose a novel method (called APFN) to predict the allosteric pathway based on the IE network. The method gives the same allosteric pathway for CheY protein as in previous nuclear magnetic resonance spectroscopy experiments. On the whole, the IE network in the solvent has been demonstrated to be reliable in describing the characteristics embedded in protein structures.

New nicotinamide-thiadiazol hybrids as VEGFR-2 inhibitors for breast cancer therapy: design, synthesis and in silico and in vitro evaluation

Vascular endothelial growth factor receptor-2 (VEGFR-2) is a key regulator of tumor angiogenesis and has become an important target in anticancer drug development. In this study, novel nicotinamide-thiadiazol hybrids were synthesized and evaluated for their anti-breast cancer potential through VEGFR-2 inhibition. The compounds were assessed in vitro for their cytotoxicity against MDA-MB-231 and MCF-7 cell lines. Among the nicotinamide-thiadiazol hybrids, 7a exhibited the most potent anticancer activity, with IC50 values of 4.64 ± 0.3 μM in MDA-MB-231 and 7.09 ± 0.5 μM in MCF-7, showing comparable efficacy to sorafenib. VEGFR-2 inhibition assays confirmed strong inhibitory potential with an IC50 of 0.095 ± 0.05 μM. In vitro cell cycle analysis indicated that 7a induced S-phase arrest, while apoptosis assays demonstrated a substantial increase in late apoptotic cells (44.01%). Other in vitro mechanistic studies further confirmed the activation of the intrinsic apoptotic pathway, as evidenced by caspase-3 activation (8.2-fold), Bax upregulation (6.9-fold), and Bcl-2 downregulation (3.68-fold). Computational studies, including molecular docking and 200 ns molecular dynamics (MD) simulations, confirmed the stable interaction of 7a with VEGFR-2, showing binding affinities comparable to sorafenib. Further validation through MM-GBSA, ProLIF, PCAT, and FEL analyses reinforced its strong binding capability. Additionally, ADMET predictions suggested favorable pharmacokinetic properties, including good absorption, high plasma protein binding, and non-CYP2D6 inhibition. Moreover, toxicity analysis classified 7a as non-mutagenic and non-carcinogenic, with a lower predicted toxicity than sorafenib. Finally, density functional theory (DFT) calculations highlighted the structural stability and reactivity of 7a, further supporting its potential as a VEGFR-2 inhibitor. These findings suggest that 7a is a promising VEGFR-2 inhibitor with significant anticancer potential, favorable pharmacokinetics, and an improved safety profile. Further preclinical studies and structural modifications are warranted to optimize its therapeutic potential.

Quantifying Acyl Chain Interdigitation in Simulated Bilayers via Direct Transbilayer Interactions

In a lipid bilayer, the interactions between the lipid hydrocarbon chains from opposing leaflets can influence membrane properties. These interactions include the phenomenon of interdigitation, in which an acyl chain of one leaflet extends past the bilayer midplane and into the opposing leaflet. While static interdigitation is well understood in gel-phase bilayers from X-ray diffraction measurements, much less is known about dynamic interdigitation in fluid phases. In this regard, atomistic molecular dynamics simulations can provide mechanistic information on interleaflet interactions that can be used to generate experimentally testable hypotheses. To address limitations of existing computational methodologies that provide results that are either indirect or averaged over time and space, here we introduce three novel ways of quantifying the extent of chain interdigitation. Our protocols include the analysis of instantaneous interactions at the level of individual carbon atoms, thus providing temporal and spatial resolution for a more nuanced picture of dynamic interdigitation. We compare the methods on bilayers composed of lipids with an equal total number of carbon atoms, but different mismatches between the sn-1 and sn-2 chain lengths. We find that these metrics, which are based on freely available software packages and are easy to implement, provide complementary details that help characterize various features of lipid-lipid contacts at the bilayer midplane. The new frameworks thus allow for a deeper look at fundamental molecular mechanisms underlying bilayer structure and dynamics and present a valuable expansion of the membrane biophysics toolkit.

The Amsterdam Modeling Suite

In this paper, we present the Amsterdam Modeling Suite (AMS), a comprehensive software platform designed to support advanced molecular and materials simulations across a wide range of chemical and physical systems. AMS integrates cutting-edge quantum chemical methods, including Density Functional Theory (DFT) and time-dependent DFT, with molecular mechanics, fluid thermodynamics, machine learning techniques, and more, to enable multi-scale modeling of complex chemical systems. Its design philosophy allows for seamless coupling between components, facilitating simulations that range from small molecules to complex biomolecular and solid-state systems, making it a versatile tool for tackling interdisciplinary challenges, both in industry and in academia. The suite also emphasizes user accessibility, with an intuitive graphical interface, extensive scripting capabilities, and compatibility with high-performance computing environments.

Self-Assembled Multilayered Concentric Supraparticle Architecture

Supraparticles (SPs) with unique properties are emerging as versatile platforms for applications in catalysis, photonics, and medicine. However, the synthesis of novel SPs with complex internal structures remains a challenge. Self-Assembled Multilayered Supraparticles (SAMS) presented here are composed of concentric lamellar spherical structures made from metallic nanoparticles, formed from a synergistic three-way interaction phenomenon between gold nanoparticles, lipidoid, and gelatin, exhibiting interlayer spacing of 3.5  ± 0.2 nm within a self-limited 156.8  ± 56.6 nm diameter. The formation is critically influenced by both physical (including nanoparticle size, lipidoid chain length) and chemical factors (including elemental composition, nanoparticle cap, and organic material), which collectively modulate the surface chemistry and hydrophobicity, affecting interparticle interactions. SAMS can efficiently deliver labile payloads such as siRNA, achieving dose-dependent silencing in vivo, while also showing potential for complex payloads such as mRNA. This work not only advances the field of SP design by introducing a new structure and interaction phenomenon but also demonstrates its potential in nanomedicine.

Understanding the Mechanism of Bent DNA Amplifying Sensors Using All-Atom Molecular Dynamics Simulations

Bent DNA amplifying sensors were recently developed to amplify and quantify the interactions of DNA with various salts and molecules. However, a thorough quantitative understanding of their mechanism is missing. Here, using all-atom molecular dynamics (MD) simulations, we investigate the behavior and dynamics of sharply bent DNA molecules in the absence and presence of Mg2+ ions at different concentrations. The simulations show that Mg2+ ions reduce the fluctuations of DNA strands, enhance base-pairing, and stabilize bent DNA molecules. The computational results are further verified by both melting curve experiments and ensemble FRET measurements, highlighting the mechanical instability and sensitivity of bent DNA molecules.

Design of a stapled peptide that binds to the Ebola virus matrix protein dimer interface

The Ebola virus (EBOV) is a filamentous lipid-enveloped RNA virus that can cause viral hemmorhagic fever and has a high fatility rate. EBOV encodes seven genes including the lipid-binding matrix protein, VP40, which lies beneath the lipid-envelope. VP40 is a 326 amino acid protein with a N-terminal domain (NTD) harboring a high affinity dimer interface and a C-terminal domain (CTD) critical to plasma membrane lipid interactions. Disruption of VP40 dimer formation via mutagenesis inhibits assembly and budding of VP40. A series of conformationally constrained mimics of the VP40 α2 helix were designed based on the crystal structures of the VP40 dimer. A thermal shift assay was used to screen constrained and native peptides for significant alterations in VP40 stability. The most meritorious peptides were then confirmed to directly bind VP40 using microscale thermophoresis and isothermal titration calorimetry. A constrained VP40 peptide mimetic with a di-cysteine staple emerged with micromolar affinity for the VP40 dimer. This peptide was able to shift the VP40 dimer-monomer equilibrium as evidenced by size exclusion chromatography and bound near the NTD α-helix dimer interface. This study provides the first evidence of a designed small molecule induced disruption of VP40 dimer-monomer equilibrium.

Cationic antimicrobial peptides: potential templates for anticancer agents

Cancer is a major global health concern and one of the leading causes of death worldwide. According to the World Health Organization (WHO), there is an urgent need for novel therapeutic agents to treat this disease. Some antimicrobial peptides (AMPs) have demonstrated activity against both microbial pathogens and cancer cells. Among these, cationic AMPs (CAMPs) have garnered significant attention because of their ability to selectively interact with the negatively charged surfaces of cancer cell membranes. CAMPs present several advantages such as high specificity for targeting cancer cells, minimal toxicity to normal cells, reduced probability of inducing resistance, stability under physiological conditions, ease of chemical modification, and low production costs. This review focuses on CAMPs with anticancer properties such as KLA, bovine lactoferricin derivatives, and LTX-315, and briefly explores common bioinformatics tools for Anticancer Peptides (ACPs) selection pipeline from AMPs.

Nitration at tyrosine 61 residue of Macrophomina phaseolina secretory glucanase brings a conformational change through a lock-unlock mechanism

Nitration of Tyrosine residue, is a footprint of its preceding nitrosative stress conditions that make nitric oxide-derived oxidants abundant. Such a post-translational chemical modification, as byproduct of a stressed condition, could be an onset of a functional pathway. Macrophomina phaseolina, which is a global devastating necrotrophic fungal pathogen, is hereby reported to have at least nine tyrosine nitrated proteins in its secretome; among them Glucanase is an important virulence secretory protein that gets nitrated at Y61. The immediate impact on the Glucanase is likely to be a perturbation on the protein itself, which would prepare the protein to function, i.e. structurally ready to recognize binding partners which could not get recognized otherwise. Y61 nitration stabilizes the enzyme's structure, particularly, its central channel within the enzyme's core. Its mechanical consequences operate at both local and global scales. The key driving factor is a positional switch of Y61 which is triggered by charge-charge repulsion between D63 and Y61 upon nitration. This switching is responsible for a critical 'lock-unlock' mechanism at the upper junction of the channel that regulates solvent exposure, underscoring Y61's pivotal role as a gating residue for the channel. While it's 'gating-in' at the junction unlocks and distorts the channel shape, its 'gating-out' locks the channel into a well-guarded conformation systematically regulating its overall exposure that can potentiate precise substrate routing towards the active site. The findings suggest that Y61 nitration-induced conformational changes have the potential to drive enzyme activation, representing a novel insight into the behavior of M. phaseolina glucanase.

Systems Biology-Driven Discovery of Host-Targeted Therapeutics for Oropouche Virus: Integrating Network Pharmacology, Molecular Docking, and Drug Repurposing

Background: Oropouche virus (OROV), part of the Peribunyaviridae family, is an emerging pathogen causing Oropouche fever, a febrile illness endemic in South and Central America. Transmitted primarily through midge bites (Culicoides paraensis), OROV has no specific antiviral treatment or vaccine. This study aims to identify host-targeted therapeutics against OROV using computational approaches, offering a potential strategy for sustainable antiviral drug discovery. Methods: Virus-associated host targets were identified using the OMIM and GeneCards databases. The Enrichr and DSigDB platforms were used for drug prediction, filtering compounds based on Lipinski's rule for drug likeness. A protein-protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape 3.10.3 software. Four key host targets-IL10, FASLG, PTPRC, and FCGR3A-were prioritized based on their roles in immune modulation and OROV pathogenesis. Molecular docking simulations were performed using the PyRx software to evaluate the binding affinities of selected small-molecule inhibitors-Acetohexamide, Deptropine, Methotrexate, Retinoic Acid, and 3-Azido-3-deoxythymidine-against the identified targets. Results: The PPI network analysis highlighted immune-mediated pathways such as Fc-gamma receptor signaling, cytokine control, and T-cell receptor signaling as critical intervention points. Molecular docking revealed strong binding affinities between the selected compounds and the prioritized targets, suggesting their potential efficacy as host-targeting antiviral candidates. Acetohexamide and Deptropine showed strong binding to multiple targets, indicating broad-spectrum antiviral potential. Further in vitro and in vivo validations are needed to confirm these findings and translate them into clinically relevant treatments. Conclusions: This study highlights the potential of using computational approaches to identify host-targeted therapeutics for Oropouche virus (OROV). By targeting key host proteins involved in immune modulation-IL10, FASLG, PTPRC, and FCGR3A-the selected compounds, Acetohexamide and Deptropine, demonstrate strong binding affinities, suggesting their potential as broad-spectrum antiviral candidates. Further experimental validation is needed to confirm their efficacy and potential for clinical application, offering a promising strategy for sustainable antiviral drug discovery.

Targeting VEGFR-2 in breast cancer: synthesis and in silico and in vitro characterization of quinoxaline-based inhibitors

A novel series of quinoxaline derivatives was designed and synthesized to target VEGFR-2, a receptor critical in cancer progression, with a focus on favorable pharmacophoric features. Among these derivatives, compound 11d emerged as a promising candidate, exhibiting potent cytotoxicity against MDA-MB-231 and MCF-7 cancer cell lines, with IC50 values of 21.68 μM and 35.81 μM, respectively, while displaying significantly reduced toxicity in normal cell lines WI-38 and WISH (IC50 values of 82.46 μM and 75.27 μM). Compared to standard treatments doxorubicin and sorafenib, compound 11d demonstrated a favorable therapeutic window. Inhibition assays showed that 11d inhibits VEGFR-2 with an IC50 of 62.26 nM ± 2.77, comparable to sorafenib. Mechanistically, treatment with 11d upregulated pro-apoptotic markers BAX, caspase-8, and caspase-9, while downregulating the anti-apoptotic marker Bcl-2, resulting in a significant BAX/Bcl-2 ratio increase (16.11). A wound healing assay confirmed 11d's anti-migratory effects, limiting wound closure in MDA-MB-231 cells to 27.51% compared to untreated cells. Additionally, flow cytometry revealed that 11d induced both early (46.43%) and late apoptosis (31.49%) in MDA-MB-231 cells, alongside G1 phase cell cycle arrest, reducing S and G2/M phase progression. Molecular docking and dynamics simulations over 200 ns demonstrated stable binding of compound 11d to VEGFR-2, with docking scores superior and comparable to sorafenib. Density Functional Theory (DFT) calculations underscored 11d's stability and reactivity, while in silico ADMET analysis predicted a favorable safety profile over sorafenib, particularly with respect to carcinogenic and chronic toxicity risks. These findings indicate that quinoxaline derivative 11d holds potential as a selective and effective VEGFR-2 inhibitor with promising antitumor and anti-metastatic properties, warranting further investigation.

Can We Ever Develop an Ideal RNA Force Field? Lessons Learned from Simulations of the UUCG RNA Tetraloop and Other Systems

Molecular dynamics (MD) simulations are an important and well-established tool for investigating RNA structural dynamics, but their accuracy relies heavily on the quality of the employed force field (ff). In this work, we present a comprehensive evaluation of widely used pair-additive and polarizable RNA ffs using the challenging UUCG tetraloop (TL) benchmark system. Extensive standard MD simulations, initiated from the NMR structure of the 14-mer UUCG TL, revealed that most ffs did not maintain the native state, instead favoring alternative loop conformations. Notably, three very recent variants of pair-additive ffs, OL3CP-gHBfix21, DES-Amber, and OL3R2.7, successfully preserved the native structure over a 10 × 20 μs time scale. To further assess these ffs, we performed enhanced sampling folding simulations of the shorter 8-mer UUCG TL, starting from the single-stranded conformation. Estimated folding free energies (ΔG°fold) varied significantly among these three ffs, with values of 0.0 ± 0.6, 2.4 ± 0.8, and 7.4 ± 0.2 kcal/mol for OL3CP-gHBfix21, DES-Amber, and OL3R2.7, respectively. The ΔG°fold value predicted by the OL3CP-gHBfix21 ff was closest to experimental estimates, ranging from -1.6 to -0.7 kcal/mol. In contrast, the higher ΔG°fold values obtained using DES-Amber and OL3R2.7 were unexpected, suggesting that key interactions are inaccurately described in the folded, unfolded, or misfolded ensembles. These discrepancies led us to further test DES-Amber and OL3R2.7 ffs on additional RNA and DNA systems, where further performance issues were observed. Our results emphasize the complexity of accurately modeling RNA dynamics and suggest that creating an RNA ff capable of reliably performing across a wide range of RNA systems remains extremely challenging. In conclusion, our study provides valuable insights into the capabilities of current RNA ffs and highlights key areas for future ff development.

Transfer of the Slip Plane in Lipid Bilayer Lubrication

Lipid bilayers are commonly found in articular cartilage and cell membranes, playing a key role in biological lubrication, which is attributed to the hydration lubrication mechanism of the headgroups. In physiological environments, lipid bilayers inevitably interact with ions, but their exact effect on lubrication is currently unclear. Here, through molecular dynamics simulations, we discover an ion-induced slip plane transfer behavior. Ions weaken the hydration lubrication effect at the headgroup-headgroup interface between bilayers, forcing the slip plane to partially shift to the acyl tail-tail interface within the bilayer and increasing friction. However, the above behavior is not observed under high hydration levels. Extensive comparison and analysis show that the transfer of the slip plane is determined by the lubrication state of two types of interfaces, with sliding always occurring at the interface with a lower dissipation at the current moment. This maximizes lubrication efficiency while providing lubrication assurance, even under high load, low hydration, and ion influence, maintaining a good lubrication performance. Our results provide valuable insights into the efficient and robust lubrication of lipid bilayers.

Small-Molecule FICD Inhibitors Suppress Endogenous and Pathologic FICD-Mediated Protein AMPylation

The AMP transferase, FICD, is an emerging drug target fine-tuning stress signaling in the endoplasmic reticulum (ER). FICD is a bifunctional enzyme, catalyzing both AMP addition (AMPylation) and removal (deAMPylation) from the ER-resident chaperone BiP/GRP78. Despite increasing evidence linking excessive BiP/GRP78 AMPylation to human diseases, small molecules that inhibit pathogenic FICD variants are lacking. Using an in vitro high-throughput screen, we identify two small-molecule FICD inhibitors, C22 and C73. Both molecules significantly inhibit FICD-mediated BiP/GRP78 AMPylation in intact cells while only weakly inhibiting BiP/GRP78 deAMPylation. C22 and C73 also inhibit pathogenic FICD variants and improve proinsulin processing in β cells. Our study identifies and validates FICD inhibitors, highlighting a novel therapeutic avenue against pathologic protein AMPylation.

In Silico and in vitro evaluation of the anticancer effect of a 1,5-Benzodiazepin-2-One derivative (3b) revealing potent dual inhibition of HER2 and HDAC1

Benzodiazepines are widely recognized for their therapeutic benefits in the treatment of anxiety and insomnia. However, in the pursuit of innovative anticancer agents, they have gained attention as a possible pharmacophore. One of those promising anticancer benzodiazepines is 3b which was demonstrated to exert good antiproliferative effects. To investigate the anticancer effect of 3b, in silico prediction of the possible targets were performed. Then, the predicted targets were investigated through in vitro study. Furthermore, 3b was evaluated for its effects on cell cycle suppression and induction of apoptosis. Molecular docking was used to study the possible types of interactions while molecular dynamics simulations were conducted to estimate the protein-ligand complex's stability and dynamic behavior. Results demonstrated that 3b is a potent dual inhibitor of HER2 and HDAC1 with IC50 values of 0.023 and 0.041 nM, respectively. Moreover, 3b was found to suppress cell cycle progression in G2/M phase and induce early and late apoptosis in HepG2 cancer cells. Further analysis of apoptotic markers revealed an induction of Caspase 3 and BAX proapoptotic proteins along with a suppression of the antiapoptotic protein (Bcl-2). Molecular docking of 3b into the active site of HER2 and HDAC1 displayed significant types of interactions with active sites of these target proteins while molecular dynamics simulations demonstrated the overall structural stability of HER2 and HDAC1 is maintained or even enhanced upon ligand binding. In conclusion, 3b is a powerful anticancer agent that exerts its effects by inhibiting HDAC1 and HER2, resulting in cell cycle arrest and cancer cell death through apoptosis. Nonetheless, additional investigations are needed to explore its mechanisms and therapeutic efficacy in more detail.

Neural Network-Based Molecular Dynamics Simulation of Water Assisted by Active Learning

In our study, we combined classical molecular dynamics (MD) simulations with the simulated annealing (SA) method to explore the conformational landscape of water molecules. By using the K-means clustering method, we processed the MD simulation data to extract representative samples of water molecular structures used to train a deep potential (DP) model. Our DeePMD method showed accuracy in predicting water structural properties compared to DFT-MD results. Meanwhile, this approach achieves a balanced prediction of water density and self-diffusion coefficients compared with earlier DeePMD simulations. These results highlight the essential role of representative sampling techniques in training the DP model. Furthermore, we demonstrated the effectiveness of combining the DeePMD simulation with the centroid molecular dynamics (CMD) approach, which incorporates nuclear quantum effects (NQEs). This approach successfully reproduced the shoulder feature at 3250 cm-1 in the Raman spectra for the O-H stretch. Incorporating the path integral method into the DeePMD simulations underscores the importance of considering NQEs in understanding water molecules' structural and dynamic behaviors.

Identification of Novel Compounds That Bind to the HGF β-Chain In Silico, Verification by Molecular Mechanics and Quantum Mechanics, and Validation of Their HGF Inhibitory Activity In Vitro

The development of small-molecule drugs targeting growth factors for cancer therapy remains a significant challenge, with only limited successful cases. We attempted to identify hepatocyte growth factor (HGF) inhibitors as novel anti-cancer small-molecule drugs. To identify compounds that bind to the β-chain of HGF and inhibit signaling through HGF and its receptor Met interaction, we performed a hierarchical in silico drug screen using a three-dimensional compound structure library (Chembridge, 154,118 compounds). We experimentally tested whether 10 compounds selected as candidates for novel anticancer agents exhibit inhibition of HGF activity. Compounds 6 and 7 potently inhibited Met phosphorylation in the human EHEMES-1 cell line, with IC50 values of 20.4 and 11.9 μM, respectively. Molecular dynamics simulations of the Compound 6/7-HGF β-chain complex structures suggest that Compounds 6 and 7 stably bind to the interface pocket of the HGF β-chain. MM-PBSA, MM-GBSA, and FMO analyses identified crucial amino acid residues for inhibition against the HGF β-chain. By interfering with the HGF/Met interaction, these compounds may attenuate downstream signaling pathways involved in cancer cell proliferation and metastasis. Further optimization and comprehensive evaluations are necessary to advance these compounds toward clinical application in cancer therapy.

Dissecting Large-Scale Structural Transitions in Membrane Transporters Using Advanced Simulation Technologies

Membrane transporters are integral membrane proteins that act as gatekeepers of the cell, controlling fundamental processes such as recruitment of nutrients and expulsion of waste material. At a basic level, transporters operate using the "alternating access model," in which transported substances are accessible from only one side of the membrane at a time. This model usually involves large-scale structural changes in the transporter, which often cannot be captured using unbiased, conventional molecular simulation techniques. In this article, we provide an overview of some of the major simulation techniques that have been applied to characterize the structural dynamics and energetics involved in the transition of membrane transporters between their functional states. After briefly introducing each technique, we discuss some of their advantages and limitations and provide some recent examples of their application to membrane transporters.

Discovery of novel HBV core protein inhibitors by high throughput virtual screening

Hepatitis B Virus (HBV) constitutes a chronic viral infection with limited therapeutic options and a significant global health challenge. The virus lifecycle intricacy significantly relies on the core protein crucial for virus structure stability and interaction with host cells thus contributing to the infection's persistence and severity. This study employs advanced techniques for the identification of novel core protein inhibitors through the screening of two chemical databases ZINC and BIMP utilizing computational methods such as structure-based virtual screening, drug-likeness, ADME, toxicity, consensus molecular docking, density functional theory, and 100 ns molecular dynamics simulation. The compound ZINC00674395 possesses high affinity and specificity towards core protein demonstrating drug-like properties, favorable ADME profiles, non-toxicity, and favorable electronic configuration with high stability at the core protein active site thus highlighting its potential as a therapeutic agent. These findings offer new insights into core protein interaction and pave the way for developing effective HBV therapeutics.

Flipping out: role of arginine in hydrophobic interactions and biological formulation design

Arginine has been a mainstay in biological formulation development for decades. To date, the way arginine modulates protein stability has been widely studied and debated. Here, we employed a hydrophobic polymer to decouple hydrophobic effects from other interactions relevant to protein folding. While existing hypotheses for the effects of arginine can generally be categorized as either direct or indirect, our results indicate that direct and indirect mechanisms of arginine co-exist and oppose each other. At low concentrations, arginine was observed to stabilize hydrophobic polymer folding via a sidechain-dominated direct mechanism, while at high concentrations, arginine stabilized polymer folding via a backbone-dominated indirect mechanism. Upon introducing partially charged polymer sites, arginine destabilized polymer folding. Further, we found arginine-induced destabilization of a model virus similar to direct-mechanism destabilization of the charged polymer and concentration-dependent stabilization of a model protein similar to the indirect mechanism of hydrophobic polymer stabilization. These findings highlight the modular nature of the widely used additive arginine, with relevance in the information-driven design of stable biological formulations.

Uncovering Amyloid-β Interactions: Gray versus White Matter

Alzheimer's disease is characterized by the accumulation of amyloid plaques in the brain. Recent studies suggest that amyloid-β (Aβ) peptides interact with cell membranes, potentially catalyzing plaque formation. However, the effect of varying cell membrane compositions on this catalytic process requires further investigation. Using molecular dynamics simulations, we demonstrate that a model gray matter membrane significantly influences the secondary structure of β-amyloid peptides. Notably, residues Asp1 and Glu22 play crucial roles in the membrane interaction. Glutamic acid at position 22, located in the middle of the peptide chain, appears to promote the formation of β-hairpin conformations, which are critical for aggregation. Additionally, our simulations reveal that the model white matter membrane allows a spontaneous insertion of segments of the peptide into the membrane, suggesting that membrane interaction not only alters the peptide structure but may also compromise membrane integrity. Our results show that the different membrane compositions in the brain may play different roles when interacting with β-amyloid peptides.

In Silico Design and Characterization of a Multiepitope Vaccine Candidate Against Brucella canis Using a Reverse Vaccinology Approach

Brucella canis is a Gram-negative bacterium that causes canine brucellosis, a zoonotic disease with serious implications for public health and the global economy. Currently, there is no effective preventive vaccine for B. canis. Control measures include diagnostic testing, isolation, and euthanasia of infected animals. However, these measures face significant limitations, such as diagnostic challenges, ethical concerns, and limited success in preventing transmission. Epidemiologically, canine brucellosis exhibits seroprevalence rates ranging from less than 1% to over 15%, with higher rates reported in stray dogs and regions of low socioeconomic development. This study employed a reverse vaccinology approach to design and characterize a multiepitope vaccine candidate against B. canis, aiming to prevent infection caused by this pathogen. A comprehensive in silico analysis of the complete B. canis proteome was conducted to identify proteins with potential as vaccine targets. Predicted epitopes for B and T cells were analyzed, and those with the highest capacity to elicit a robust immune response were selected. These proteins were classified as plasma membrane proteins, outer membrane proteins (OMPs), or proteins with similarity to virulence factors. Selection criteria emphasized their essential roles in bacterial function, lack of homology with proteins from dogs or mice, and presence of fewer than two transmembrane domains. From this process, four candidate proteins were identified. Epitopes for B and T cells within these proteins were predicted and analyzed, selecting the most immunogenic sequences. The overlap between B- and T-cell epitopes narrowed the selection to six final epitopes. These selected epitopes were then assembled into a multiepitope vaccine construct using flexible linkers to ensure structural integrity and molecular adjuvants to enhance immunogenicity. The physicochemical properties, antigenicity, and toxicity of the designed vaccine were evaluated. Additionally, the secondary and tertiary structure of the vaccine was predicted and refined, followed by a molecular interaction analysis with the Toll-like receptor 4 (TLR4) receptor. The designed vaccine proved to be highly antigenic, nonallergenic, and nontoxic. Validation of its secondary and tertiary structures, along with molecular docking analysis, revealed a high binding affinity to the TLR4 receptor. Molecular dynamics simulations and normal mode analysis further confirmed the vaccine's structural stability and binding capacity. A multiepitope vaccine candidate against B. canis was successfully designed and characterized using a reverse vaccinology approach. This vaccine construct is expected to induce robust humoral and cellular immune responses, potentially conferring protective immunity against B. canis. The results of this study are promising; however, in vitro and in vivo tests are necessary to validate the vaccine's protective efficacy. Furthermore, the described method could serve as a framework for developing vaccines against other pathogens.

Charge distribution and helicity tune the binding of septin's amphipathic helix domain to membranes

Amphipathic helices (AHs) are secondary structures that can facilitate binding of proteins to the membrane by folding into a helix with hydrophobic and hydrophilic faces that interact with the same surfaces in the lipid membrane. Septins are cytoskeletal proteins that preferentially bind to domains of micron-scale curvature on the cell membrane. Studies have shown that AH domains in septin are essential for curvature sensing. We present the first computational study of septin AH interactions with lipid bilayers. Using all-atom simulations and metadynamics-enhanced sampling, we study the effect of charge distribution at the flanking ends of septin AH on the energy for helical folding and its consequences on the binding configuration and affinity to the membrane. This is relevant to septins, since the net positive charge on the flanking C-terminal amino acids is a conserved property across several organisms. Simulations revealed that the energy barrier for folding in the neutral-capped AH is much larger than the charge-capped AH, leading to a small fraction of AH folding and integration to the membrane compared to a significantly folded configuration in the bound charge-capped AH. These observations are consistent with the binding measurements of synthetic AH constructs with variable helicity to lipid vesicles. Additionally, we examined an extended AH sequence including eight amino acids upstream and downstream of the AH to mimic the native protein. Again, simulations and experiments show that the extended peptide, with a net positive charge at C-terminus, adopts a strong helical configuration in solution, giving rise to a higher membrane affinity. Altogether, these results identify the energy cost for folding of AHs as a regulator of AH binding configuration and affinity and provide a basic template for parameterizing AH-membrane interactions as a starting point for the future multiscale simulations for septin-membrane interactions.

Role of Cre Dynamics in Autoinhibition and Priming

Cre recombinase, a powerful tool for genome engineering, associates into an intasome, a tetrameric complex of alternate active and inactive monomers that bring together two loxP sequences, stabilized by key protein-protein and protein-DNA interactions. High-resolution structural information for free Cre is still missing, in contrast to the many structures found for Cre-DNA complexes in the Protein Data Bank, hindering understanding of the initial steps in intasome formation. To approach Cre structure and dynamics, we carried out 100 μs of molecular dynamics simulations of free Cre, starting from five Cre structures from different stages of intasome assembly. In the generated ensemble, the linker connecting the CBD and CAT domains is an intrinsically disordered region (IDR) that promotes different orientations of the two domains. The domains remain folded and interact with each other through short-lived interactions, retaining ∼70% of their surface available for interaction with loxP. The C-terminal Helix N in the CAT domain is also an IDR that interacts with the entire protein, including the active site, transiently forming an autoinhibited complex. The active site can be assembled in the absence of DNA, albeit inefficiently. The CAT domain has a clam-like motion, opening and closing the cavity where helix N docks, establishing protein-protein interactions in the intasome. Helix A in the CBD domain slides over the domain like a windshield wiper, sampling intasome-like conformations, among others. The wide range of intramolecular motion sampled by free Cre suggests that it uses conformational selection, using primed DNA-binding surfaces in both domains while assembling into the intasome.

Computational Design and Evaluation of Peptides to Target SARS-CoV-2 Spike-ACE2 Interaction

The receptor-binding domain (RBD) of SARS-CoV-2 spike protein is responsible for the recognition of the Angiotensin-Converting Enzyme 2 (ACE2) receptor in human cells and, thus, plays a critical role in viral infection. The therapeutic value of targeting this interaction has been proven by a sizable body of research investigating antibodies, small proteins, aptamers, and peptides. This study presents a novel peptide that impinges the interaction between RBD and ACE2. Starting from a very large pool of structurally designed peptides extracted from our database, PepI-Covid19, a diverse set of peptides were studied using molecular dynamics simulations. Ten of the most promising were chemically synthesized and validated both in vitro and in a cell-based assay. Our results indicate that one of the peptides (PEP10) exhibited the highest disruption of the RBD/ACE2 complex, effectively blocking the binding of two molecules and consequently inhibiting the SARS-CoV-2 spike-mediated cell entry of viruses pseudotyped with the spike of the D614G, Delta, and Omicron variants. PEP10 can potentially serve as a scaffold that can be further optimized for improved affinity and efficacy.

Structure-based profiling of putative therapeutics against monkeypox virus VP39 using pharmacophore modelling and molecular dynamics simulation studies

The growing global health threat of the monkeypox virus (MPXV) underscores the critical need for effective antiviral agents, since there are currently no therapeutics. The MPXV VP39, a methyltransferase, is essential for viral replication, hence a potential target for anti-MPXV drug candidates. Herein, a structure-based pharmacophore modelling and molecular docking approach was employed to screen natural compounds (NCs: 581,426) from the COCONUT database for potential inhibitors of MPXV VP39. After ranking of the docking scores, an ensemble-based docking of the top-ranked 20 NCs against multiple conformations obtained from ttcluster analysis of the molecular dynamics simulation trajectory of unbound MPXV VP39 further identified five leads with favourable interaction profiles, drug-likeness, ADMET properties, and synthetic features when compared to the reference standard (sinefungin). Further analysis of the thermodynamic stability of the resulting complexes of the leads over a 100-ns MD simulation period revealed varying degrees of thermodynamic stability while maintaining the structural integrity of MPXV VP39. Furthermore, the thermodynamic binding free energy calculation, while corroborating the docking analysis, identified CNP0297833 (-39.07 kcal/mol), CNP0371756 (-25.76 kcal/mol), and CNP0402319 (-19.26 kcal/mol) as the most promising candidates, with better modulatory effect against MPXV VP39 relative to sinefungin (-3.68 kcal/mol). These leads were stabilised with hydrophobic (Phe115, Val139, and Val116) and electrostatic (Glu46 and Asp138) interactions in different conformational clusters. In addition to the observed consistent interaction patterns, favourable binding energies, pharmacokinetics, ADMET, thermodynamic stability, and molecular orbital energies of these leads, the potential for optimisation for enhanced binding features for the active site of MPXV VP39 was elucidated. Further in vitro investigation to validate these findings is suggested to establish the putative leads as therapeutics targeting the replication phase of MPXV.

Allosteric modulation by the fatty acid site in the glycosylated SARS-CoV-2 spike

The spike protein is essential to the SARS-CoV-2 virus life cycle, facilitating virus entry and mediating viral-host membrane fusion. The spike contains a fatty acid (FA) binding site between every two neighbouring receptor-binding domains. This site is coupled to key regions in the protein, but the impact of glycans on these allosteric effects has not been investigated. Using dynamical nonequilibrium molecular dynamics (D-NEMD) simulations, we explore the allosteric effects of the FA site in the fully glycosylated spike of the SARS-CoV-2 ancestral variant. Our results identify the allosteric networks connecting the FA site to functionally important regions in the protein, including the receptor-binding motif, an antigenic supersite in the N-terminal domain, the fusion peptide region, and another allosteric site known to bind heme and biliverdin. The networks identified here highlight the complexity of the allosteric modulation in this protein and reveal a striking and unexpected link between different allosteric sites. Comparison of the FA site connections from D-NEMD in the glycosylated and non-glycosylated spike revealed that glycans do not qualitatively change the internal allosteric pathways but can facilitate the transmission of the structural changes within and between subunits.

Peptide-Based Regulation of TNF-α-Mediated Cytotoxicity

Tumor necrosis factor alpha (TNF-α) is a pro-inflammatory cytokine associated with TNF receptor 1 (TNFR1) and TNF receptor 2 (TNFR2), which play important roles in several inflammatory diseases. There is a growing interest in developing alternative molecules that can be used as TNF blockers. In this study, we focused on TNF-α-, TNFR1-, and TNFR2-mimicking peptides to inhibit TNF-α receptor binding in various ways. Six peptides (OB1, OB2, OB5, OB6, OB7, and OB8) were developed to bind TNFR1, TNFR2, and TNF-α. OB1 and OB2 bound to TNF-α with lower Kd values of 300 and 46.7 nM, respectively, compared to previously published sequences. These synthetic peptides directly and indirectly inhibited TNF-α in vitro without cytotoxicity to L929 cells, and OB1 significantly inhibited apoptosis in the presence of hTNF-α. Peptides developed in this study may prove to be useful for therapeutic inhibition of TNF-α.

Methods for Theoretical Treatment of Local Fields in Proteins and Enzymes

Electric fields generated by protein scaffolds are crucial in enzymatic catalysis. This review surveys theoretical approaches for detecting, analyzing, and comparing electric fields, electrostatic potentials, and their effects on the charge density within enzyme active sites. Pioneering methods like the empirical valence bond approach rely on evaluating ionic and covalent resonance forms influenced by the field. Strategies employing polarizable force fields also facilitate field detection. The vibrational Stark effect connects computational simulations to experimental Stark spectroscopy, enabling direct comparisons. We highlight how protein dynamics induce fluctuations in local fields, influencing enzyme activity. Recent techniques assess electric fields throughout the active site volume rather than only at specific bonds, and machine learning helps relate these global fields to reactivity. Quantum theory of atoms in molecules captures the entire electron density landscape, providing a chemically intuitive perspective on field-driven catalysis. Overall, these methodologies show protein-generated fields are highly dynamic and heterogeneous, and understanding both aspects is critical for elucidating enzyme mechanisms. This holistic view empowers rational enzyme engineering by tuning electric fields, promising new avenues in drug design, biocatalysis, and industrial applications. Future directions include incorporating electric fields as explicit design targets to enhance catalytic performance and biochemical functionalities.

Swinging lever mechanism of myosin directly shown by time-resolved cryo-EM

Myosins produce force and movement in cells through interactions with F-actin1. Generation of movement is thought to arise through actin-catalysed conversion of myosin from an ATP-generated primed (pre-powerstroke) state to a post-powerstroke state, accompanied by myosin lever swing2,3. However, the initial, primed actomyosin state has never been observed, and the mechanism by which actin catalyses myosin ATPase activity is unclear. Here, to address these issues, we performed time-resolved cryogenic electron microscopy (cryo-EM)4 of a myosin-5 mutant having slow hydrolysis product release5,6. Primed actomyosin was predominantly captured 10 ms after mixing primed myosin with F-actin, whereas post-powerstroke actomyosin predominated at 120 ms, with no abundant intermediate states detected. For detailed interpretation, cryo-EM maps were fitted with pseudo-atomic models. Small but critical changes accompany the primed motor binding to actin through its lower 50-kDa subdomain, with the actin-binding cleft open and phosphate release prohibited. Amino-terminal actin interactions with myosin promote rotation of the upper 50-kDa subdomain, closing the actin-binding cleft, and enabling phosphate release. The formation of interactions between the upper 50-kDa subdomain and actin creates the strong-binding interface needed for effective force production. The myosin-5 lever swings through 93°, predominantly along the actin axis, with little twisting. The magnitude of lever swing matches the typical step length of myosin-5 along actin7. These time-resolved structures demonstrate the swinging lever mechanism, elucidate structural transitions of the power stroke, and resolve decades of conjecture on how myosins generate movement.

ERK Allosteric Activation: The Importance of Two Ordered Phosphorylation Events

ERK, a coveted proliferation drug target, is a pivotal kinase in the Ras/ERK signaling cascade. Despite this, crucial questions about its activation have not been fully explored on the foundational, conformational level. Such questions include (i) Why ERK's activation demands dual phosphorylation; (ii) What is the role of each phosphorylation site in the activation loop; and (iii) Exactly how the (ordered) phosphorylation steps affect the conformational ensembles of the activation loop, their propensities and restriction to a narrower range favoring ERK's catalytic action. Here we used explicit molecular dynamics simulations to study ERK's stability and the conformational changes in different stages along the activation process. The initial monophosphorylation event elongates the activation loop to enable successive phosphorylations, which reintroduce stability/compactness through newly formed salt bridges. The interactions formed by monophosphorylation are site-dependent, with threonine's phosphorylation presenting stronger electrostatic interactions compared to tyrosine's. Dual phosphorylated ERKs revealed a compact kinase structure which allows the HRD catalytic motif to stabilize the ATP. We further observe that the hinge and the homodimerization binding site responded to a tri-state signaling code based solely on the phosphorylation degree (unphosphorylated, monophosphorylated, dual phosphorylated) of the activation loop, confirming that the activation loop can allosterically influence distant regions. Last, our findings indicate that threonine phosphorylation as the second step is necessary for ERK to become effectively activated and that activation depends on the phosphorylation order. Collectively, we offer ERK's dual allosteric phosphorylation code in activation and explain why the phosphorylation site order is crucial.

Targeted TPS Shooting Using Computer Vision to Generate Ensemble of Trajectories

This study presents a transition path sampling (TPS) procedure to create an ensemble of trajectories describing a chemical transformation from a reactant to a product state, augmented with a computer vision technique. A 3D convolutional neural network (CNN) sorts the slices of the TPS trajectories into reactant or product state categories, which aids in automatically accepting or rejecting a newly generated trajectory. Furthermore, information about the geometrical configuration of each slice enables one to calculate the percentage of reactant and product states within a specific shooting range. These statistics are used to determine the most appropriate shooting range and, if needed, to improve a shooting acceptance rate. To test the automated 3D CNN TPS technique, we applied it to collect an ensemble of the transition paths for the rate-limiting step of the Morita-Bayliss-Hillman (MBH) reaction.

Targeted Transferable Machine-Learned Potential for Linear Alkanes Trained on C14H30 and Tested for C4H10 to C30H62

Given the great importance of linear alkanes in fundamental and applied research, an accurate machine-learned potential (MLP) would be a major advance in computational modeling of these hydrocarbons. Recently, we reported a novel, many-body permutationally invariant model that was trained specifically for the 44-atom hydrocarbon C14H30 on roughly 250,000 B3LYP energies (Qu, C.; Houston, P. L.; Allison, T.; Schneider, B. I.; Bowman, J. M. J. Chem. Theory Comput. 2024, 20, 9339-9353). Here, we demonstrate the accuracy of the transferability of this potential for linear alkanes ranging from butane C4H10 up to C30H62. Unlike other approaches for transferability that aim for universal applicability, the present approach is targeted for linear alkanes. The mean absolute error (MAE) for energy ranges from 0.26 kcal/mol for butane and rises to 0.73 kcal/mol for C30H62 over the energy range up to 80 kcal/mol for butane and 600 kcal/mol for C30H62. These values are unprecedented for transferable potentials and indicate the high performance of a targeted transferable potential. The conformational barriers are shown to be in excellent agreement with high-level ab initio calculations for pentane, the largest alkane for which such calculations have been reported. Vibrational power spectra of C30H62 from molecular dynamics calculations are presented and briefly discussed. Finally, the evaluation time for the potential is shown to vary linearly with the number of atoms.