Scalable molecular dynamics with NAMD

Rational design, synthesis, and molecular modelling insights of dual DNA binders/DHFR inhibitors bearing arylidene-hydrazinyl-1,3-thiazole scaffold with apoptotic and anti-migratory potential in breast MCF-7 cancer cells

In light of searching for new breast cancer therapies, DNA-targeted small molecules were rationally designed to simultaneously bind DNA and inhibit human dihydrofolate reductase (hDHFR). Fourteen new arylidene-hydrazinyl-1,3-thiazoles (5-18) were synthesised and their dual DNA groove binding potential and in vitro hDHFR inhibition were performed. Two compounds, 5 and 11, proved their dual efficacy. Molecular docking and molecular dynamics simulations were performed for those active derivatives to explore their mode of binding and stability of interactions inside DHFR active site. Anti-breast cancer activity was assessed for 5 and 11 on MCF-7 cells using MTX as reference. IC50 measurements revealed that both compounds were more potent and selective than MTX. Cytotoxicity was examined against normal skin fibroblasts to examine safety and selectivity Moreover, mechanistic studies including apoptosis induction and wound healing were performed. Further in silico ADMET assessment was conducted to determine their eligibility as drug leads suitable for future optimisation and development.

Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep learning

Highly concentrated antibody solutions are necessary for developing subcutaneous injections but often exhibit high viscosities, posing challenges in antibody-drug development, manufacturing, and administration. Previous computational models were only limited to a few dozen data points for training, a bottleneck for generalizability. In this study, we measured the viscosity of a panel of 229 monoclonal antibodies (mAbs) to develop predictive models for high concentration mAb screening. We developed DeepViscosity, consisting of 102 ensemble artificial neural network models to classify low-viscosity (≤20 cP) and high-viscosity (>20 cP) mAbs at 150 mg/mL, using 30 features from a sequence-based DeepSP model. Two independent test sets, comprising 16 and 38 mAbs with known experimental viscosity, were used to assess DeepViscosity's generalizability. The model exhibited an accuracy of 87.5% and 89.5% on both test sets, respectively, surpassing other predictive methods. DeepViscosity will facilitate early-stage antibody development to select low-viscosity antibodies for improved manufacturability and formulation properties, critical for subcutaneous drug delivery. The webserver-based application can be freely accessed via https://devpred.onrender.com/DeepViscosity.

Elucidating OASL-RNA Interactions: Structural and energetic insights into vault RNAs binding

Oligoadenylate synthetase-like (OASL) proteins play an essential role in the innate immune response by detecting RNA molecules and modulating antiviral signalling pathways. This study investigated the structural and functional dynamics of OASL in its interaction with endogenous vault RNAs (vtRNAs) through computational analyses, including molecular docking and molecular dynamics simulations. Predicted 3D structures of vtRNAs revealed key interactions within the positively charged RNA-binding groove of OASL, involving residues such as Arg45, Lys63, and Arg196. Among the vtRNAs analysed, vtRNA 1-1 exhibited the highest binding affinity and stability, inducing conformational changes in OASL consistent with canonical activation mechanisms. In contrast, vtRNA 1-2 and 1-3 demonstrated moderate interactions, while vtRNA 2-1 had minimal impact on OASL conformation. Our results underscore the critical role of guanine- and cytosine-enriched regions in mediating binding stability and specificity, as corroborated by MM/GBSA calculations. The study highlights the molecular determinants of OASL-vtRNA interactions, offering structural insights into the mechanisms of nucleic acid recognition.

InSty: A ProDy Module for Evaluating Protein Interactions and Stability

ProDy is a widely used application programming interface for analyzing the collective dynamics of proteins and their complexes, offering enhanced capabilities to address the growing needs of the computational biology community to bridge structure and function. Here, we introduce InSty, a new module integrated into ProDy to identify and quantify intra- and intermolecular interactions critical to protein stability and structural dynamics. InSty analyzes the non-covalent interactions using conformational ensemble data from both experiments and computational predictions, assesses their time evolution and persistence during molecular dynamics simulations as well as their conservation across homologs. It provides insights into the significance of these interactions in achieving function and/or supporting stability. InSty outputs lend themselves to statistical evaluation, visualization, and automated ensemble analysis for interpreting the significance of the interactions in the context of protein dynamics, sequence evolution, and allostery. Consolidation of InSty with various ProDy modules enables its efficient usage as a versatile tool that supports mutagenesis studies and identifies critical spots for functional interactions. The InSty module is available as part of the ProDy package at https://github.com/prody/ProDy.

Particulate methane monooxygenase and cytochrome P450-induced reactive oxygen species facilitate 17β-estradiol biodegradation in a methane-fed biofilm

Methane-fed biosystems have shown great potential for degrading various organic micropollutants, yet underlying molecular degradation mechanisms remain largely unexplored. In this study, we uncover the critical role of biogenic reactive oxygen species (ROS) in driving the degradation of 17β-estradiol (E2) within a methane-fed biofilm reactor. Metagenomic analyses confirm that aerobic methanotrophs, specifically Methylococcus and Methylomonas, are responsible for the efficient degradation of E2, achieving a degradation rate of 367.7 ± 8.3 μg/L/d. ROS scavenging in conjunction with enzyme inhibition experiments indicate that particulate methane monooxygenase (pMMO) and cytochrome P450 monooxygenase (CYP450) could generate hydroxyl radicals (•OH), which are the primary ROS involved in E2 degradation. Molecular dynamics simulations suggest that E2 can enter the active catalytic site of pMMO through electrostatic attraction. Four amino acid residues are found to form stable hydrogen bonds with E2, with a high binding free energy, indicating a high affinity for the substrate. Additionally, density functional theory calculations combined with transformation product analysis reveal that •OH targets carbon atoms on the benzene ring and the hydroxyl group attaches to the cyclopentane ring, primarily through hydrogen abstraction and hydroxylation reactions. This work provides critical insights into the mechanisms of E2 biodegradation in methane-fed systems and highlights the potential for optimizing microbial pathways to enhance the degradation of organic micropollutants from contaminated water.

Murine norovirus allosteric escape mutants mimic gut activation

Murine norovirus (MNV) undergoes large conformational changes in response to the environment. The T=3 icosahedral capsid is composed of 180 copies of ~58 kDa VP1 that has N-terminal (N), shell (S), and C-terminal protruding (P) domains. In phosphate-buffered saline, the P domains are loosely tethered to the shell and float ~15 Å above the surface. At conditions found in the gut (i.e., low pH with high metal ion and bile salt concentrations), the P domain rotates and drops onto the shell with intra P domain changes that enhance receptor interactions while blocking antibody binding. Two of our monoclonal antibodies (2D3 and 4F9) have broad strain recognition, and the only escape mutants, V339I and D348E, are located on the C'D' loop and ~20 Å from the epitope. Here, we determined the cryo-EM structures of V339I and D348E at neutral pH +/-metal ions and bile salts. These allosteric escape mutants have the activated conformation in the absence of gut triggers. Since this conformation is not recognized by antibodies, it explains how these mutants evade antibody recognition. Dynamic simulations of the P domain further suggest that movement of the C'D' loop may be the rate-limiting step in the conformational change and that V339I increases the motion of the A'B'/E'F' loops compared to the wild-type (WT), facilitating the transition to the activated state. These findings have important implications for norovirus vaccine design since they uncover a form of the viral capsid that should lend superior immune protection against subsequent challenge by wild-type virus.IMPORTANCEImmune protection from norovirus infection is notoriously transient in both humans and mice. Our results strongly suggest that this is likely because the "activated" form of the virus found in gut conditions is not recognized by antibodies created in the circulation. By reversibly presenting one structure in the gut and a completely different antigenic structure in circulation, the gut tissue can be infected in subsequent challenges, while extraintestinal organs are protected. We find here that allosteric escape mutants to the most broadly neutralizing antibodies thwart recognition by transitioning to the activated state without the need for gut triggers (i.e., bile, low pH, or metal ions). These findings are significant because it is now feasible to present the activated form of the virus to the immune system (for example, as a vaccine) to better protect the gut tissue for longer periods of time.

High-Precision Multistage Molecular Dynamics Simulations and Quantum Mechanics Investigation of Adsorption Mechanisms of Cerium-Based H3BTC MOF (Ce-H3BTC-MOF) on Pristine and Functionalized Carbon Nanotubes

Metal-organic frameworks (MOFs) and carbon nanotubes (CNTs) exhibit exceptional physicochemical properties, making them promising candidates for nanotherapeutics, catalysis, and drug delivery. However, CNTs face inherent limitations in solubility and functionalization, which hinder their practical applications. This study systematically investigates the adsorption mechanisms of cerium-based benzene-1,3,5-tricarboxylate MOFs (Ce-H3BTC-MOF) on pristine (PCNT), mildly functionalized (MFCNT), and densely functionalized (DFCNT) CNTs using multistage molecular dynamics simulations and quantum mechanics calculations. Functionalization was achieved by grafting 5 (-COOH) groups on the MFCNT and 20 (-COOH) groups on the DFCNT, enhancing interfacial interactions. Loading configurations of 1-5 Ce-H3BTC MOF molecules were analyzed to understand binding stability and molecular dispersion. Simulation results demonstrated enhanced adsorption on functionalized CNTs due to π-π stacking and electrostatic interactions, with 5CeBTC-1DFCNT exhibiting the highest cohesive energy (311.01 kcal/mol) and optimized solubility (1.13 MPa1/2). Density functional theory calculations revealed a HOMO-LUMO energy gap of 0.21029 eV for BTC and 0.23089 eV for CeO2, indicating electronic stability. Root mean square deviation (rmsd) and radius of gyration (Rg) analyses confirmed structural stability, with 1CeBTC-1MFCNT maintaining the lowest rmsd (∼2.47 Å) and 5CeBTC-1DFCNT exhibiting significant fluctuations (∼6.87 Å) due to steric hindrance. This study advances the understanding of CNT-MOF hybrid systems by elucidating their interfacial dynamics, providing a foundation for future applications in nanomedicine and catalysis.

The influence of downstream structured elements within mRNA on the dynamics of intersubunit rotation in ribosomes

Proper codon/anticodon pairing within the ribosome necessitates linearity of the transcript. Any structures formed within a messenger RNA (mRNA) must be unwound before the respective codon is interpreted. Linearity, however, is not always the norm; some intricate structures within mRNA are able to exert unique ribosome/mRNA interactions to regulate translation. Intrinsic kinetic and thermal stability in many of these structures are efficient in slowing translation causing pausing of the ribosome. Altered translation kinetics arising from atypical interactions have been shown to affect intersubunit rotation. Here, we employ single-molecule Förster resonance energy transfer (smFRET) to observe changes in intersubunit rotation of the ribosome as it approaches downstream structured nucleic acid. The emergence of the hyperrotated state is critically dependent on the distance between downstream structure and the ribosome, suggesting interactions with the helicase center are allosterically coupled to intersubunit rotation. Further, molecular dynamics (MD) simulations were performed to determine ribosomal protein/mRNA interactions that may play a pivotal role in helicase activity and ultimately unwinding of downstream structure.

A molecular conveyor belt-associated protein controls the rotational direction of the bacterial type 9 secretion system

Many bacteria utilize the type 9 secretion system (T9SS) for gliding motility, surface colonization, and pathogenesis. This dual-function motor supports both gliding motility and protein secretion, where rotation of the T9SS plays a central role. Fueled by the energy of the stored proton motive force and transmitted through the torque of membrane-anchored stator units, the rotary T9SS propels an adhesin-coated conveyor belt along the bacterial outer membrane like a molecular snowmobile, thereby enabling gliding motion. However, the mechanisms controlling the rotational direction and gliding motility of T9SS remain elusive. Shedding light on this mechanism, we find that in the gliding bacterium Flavobacterium johnsoniae, deletion of the C-terminus of the conveyor belt-associated protein GldJ controls and, in fact, reverses the rotational direction of T9SS from counterclockwise (CCW) to clockwise (CW). This suggests that the interface between the conveyor belt-associated protein GldJ and the T9SS ring protein GldK plays an important role in controlling the directionality of T9SS, potentially by modulating its interaction with the stator complex GldLM, which drives motor rotation. Combined with MD simulation of the T9SS stator units GldLM, we suggest a "tri-component gearset" model where GldJ controls the rotational direction of its driver, the T9SS, thus providing adaptive sensory feedback to influence the motility of the gliding bacterium.

IMPORTANCE

The type 9 secretion system (T9SS) is fundamental to bacterial gliding motility, pathogenesis, and surface colonization. Our findings reveal that the C-terminal region of the conveyor belt-associated protein GldJ functions as a molecular switch which is capable of reversing the rotational direction of T9SS. Through the coordinated actions of the T9SS stator units (akin to a driving motor), the GldK ring (the gear that converts rotational energy into linear movement), and GldJ, this machinery forms a smart conveyor belt system reminiscent of flexible or cognitive mechanical conveyors. Such advanced conveyors can alter their direction to adapt to shifting demands. Here, we show that the bacterial T9SS similarly adjusts its rotational bias based on feedback from the conveyor belt-associated protein GldJ. This dual-role feedback mechanism underscores an evolved, controllable biological snowmobile, offering new avenues for studying how bacteria fine-tune motility in dynamic environments.

Mechanisms of CO2 Absorption in Amino Acid-Based Deep Eutectic Solvents: Insights from Molecular Dynamics and DFT Calculations

This study explores the mechanisms of CO2 absorption in two amino acid-containing deep eutectic solvents (DESs) through molecular dynamics (MD) simulations and density functional theory (DFT) calculations. The MD simulations, which focus mainly on physical absorption, reveal that alanine-based DES (Ala DES) exhibits higher CO2 solubility than l-arginine-based DES (l-arg DES), attributed to stronger physical absorption. Furthermore, the hydrogen bond donor paired with the amino acids is identified as a critical factor for enhancing physical absorption efficiency. DFT calculations, which account for chemical absorption, investigate two reaction pathways: single-molecule reactions involving intramolecular proton transfer and two-molecule reactions involving intermolecular proton exchange. While Ala DES does not exhibit spontaneous chemical absorption, l-arg DES demonstrates such reactions, leading to the formation of carbamic acid or carbamate (ΔG < 0), indicative of CO2 capture through chemical interactions. Consequently, Ala DES primarily relies on physical absorption, whereas l-arg DES utilizes multiple reactive sites for chemical absorption. These results are consistent with experimental findings, which show that l-arg DES achieves higher CO2 solubility under atmospheric conditions. Overall, our study highlights the interplay between DES components and reactivity in enhancing CO2 capture efficiency.

Synthetic Retinoids for the Modulation of Genomic and Nongenomic Processes in Neurodegenerative Diseases

Retinoids, such as all-trans retinoic acid (ATRA), are the active metabolite forms of endogenous Vitamin A and function as key signaling molecules involved in the regulation of a variety of cellular processes. Due to their highly diverse biological roles, retinoids have been implicated in a wide range of diseases such as neurological disorders and some cancers. However, their therapeutic potential is limited due to their chemical and metabolic instability and adverse side effects. Synthetic retinoid analogues with increased stability and specificity have therefore attracted significant attention. In this study, we developed a scalable synthetic platform to generate a library of novel synthetic retinoids. Twenty-three new compounds were synthesized, and their receptor binding was assessed by an in vitro fluorescence competition binding assay, complemented by molecular docking and molecular dynamics (MD) simulations. We show that while computational studies are extremely useful for predicting binding modes and hence can guide synthetic efforts, the binding assays demonstrated that these novel retinoids exhibit strong binding albeit with limited selectivity for the different retinoic acid receptors (RARs). Therefore, their biological activity was measured by assessing their genomic and nongenomic activities in neuroblastoma cells with the goal of correlating binding properties and pathway activation to neuro-regenerative potential measured by neurite outgrowth. Importantly, four of the novel retinoids are shown to bind tightly to RARs and exhibit dual action in the relevant cellular models, with an ability to induce both genomic and nongenomic responses as well as significant neurite outgrowth. The compound with the highest biological activity possesses significant potential to be used as therapeutics for treating a wide range of neurological disorders like Alzheimer's disease and motor neuron disease.

Recent advances in medicinal chemistry strategies for the development of METTL3 inhibitors

N6-methyladenosine (m6A), the most abundant RNA modification in eukaryotic cells, exerts a critical influence on RNA function and gene expression. It has attracted considerable attention within the rapidly evolving field of epitranscriptomics. METTL3 is a key enzyme for m6A modification and is essential for maintaining normal m6A levels. High expression of METTL3 is closely associated with various cancers, including gastric cancer, liver cancer, and leukemia. Inhibiting METTL3 has shown potential in slowing cancer progression, thereby driving the development of METTL3 inhibitors. In this work, we summarize recent advancements in the development of METTL3 inhibitor, with a focus on medicinal chemistry strategies employed during discovery and optimization phases. We explore the application of structure-activity relationship (SAR) studies and protein-targeted degradation techniques, while addressing key challenges associated with their characterization and clinical translation. This review underscores the therapeutic potential of METTL3 inhibitors in modulating epitranscriptomic pathways and aims to offer perspectives for future research in this rapidly evolving field.

Magnetosensitivity of Model Flavin-Tryptophan Radical Pairs in a Dynamic Protein Environment

Light-induced radical pairs in cryptochrome proteins located in the retina are thought to be the receptors at the heart of the magnetic compass sense of migratory songbirds. Reliable simulations of the performance of such sensors face several fundamental challenges. The quantum spin dynamics of large spin systems must be modeled for periods in excess of a microsecond including realistic local magnetic interactions that fluctuate on a picosecond to microsecond time scale as a result of thermal motion. Here we employ newly developed computational methods that combine explicitly time-dependent internal magnetic interactions, obtained from molecular dynamics simulations and electronic structure calculations, with efficiently and accurately modeled spin dynamics of multinuclear electron-nuclear spin systems. We identify the range of frequencies of molecular motions that are expected to have the greatest effects on the sensitivity of the proposed compass to the direction of an Earth-strength magnetic field and obtain new insights into the potential enhancements in detection sensitivity afforded by thermal modulations of electron-nuclear hyperfine interactions.

The presence of substrate warrants oxygen access tunnels toward the catalytic site of lipoxygenases

Ferroptosis is a regulated form of cell death driven by lipid peroxidation, with 15-lipoxygenase (15LOX) enzyme playing a critical role in catalyzing the oxygenation of polyunsaturated fatty acid-containing phospholipids, such as 1-stearoyl-2-arachidonoyl-sn-glycero-3-phosphoethanolamine (SAPE), to initiate this process. The molecular oxygen required for this catalytic reaction is subject to continuous competition among various oxygen-consuming enzymes, which influences the efficiency of lipid peroxidation. In this study, we utilized structure-based modeling and all-atom molecular dynamics simulations to explore the oxygen diffusion pathways in 15LOX-1 under varying oxygen concentrations and in the presence of key components, including a substrate, binding partner PE-binding protein 1 (PEBP1), and the membrane environment. Extensive computational experiments were performed on various system configurations, examining the role of substrate binding, membrane presence, and PEBP1 association in oxygen acquisition. Our computational results indicate that the substrate binding induces a conformational change in 15LOX-1, facilitating the simultaneous recruitment of one or two O2 molecules, which drive peroxidation, leading predominantly to monohydroperoxide products and, less frequently, to dihydroperoxide products. A similar trend was observed in our redox lipidomics analysis. Moreover, we noticed that the presence of the membrane significantly reduces irrelevant oxygen binding spots, directing oxygen molecules toward a primary tunnel essential for the catalytic activity. We identified two primary oxygen tunnels with sequentially and structurally conserved regions across the lipoxygenase family. These findings provide novel insights into the regulation of oxygen acquisition mechanism for LOX members, shedding light on the molecular basis of ferroptosis signaling.

(-)-Epicatechin metabolites as a GPER ligands: a theoretical perspective

Diet habits and nutrition quality significantly impact health and disease. Here is delve into the intricate relationship between diet habits, nutrition quality, and their direct impact on health and homeostasis. Focusing on (-)-Epicatechin, a natural flavanol found in various foods like green tea and cocoa, known for its positive effects on cardiovascular health and diabetes prevention. The investigation encompasses the absorption, metabolism, and distribution of (-)-Epicatechin in the human body, revealing a diverse array of metabolites in the circulatory system. Notably, (-)-Epicatechin demonstrates an ability to activate nitric oxide synthase (eNOS) through the G protein-coupled estrogen receptor (GPER). While the precise role of GPER and its interaction with classical estrogen receptors (ERs) remains under scrutiny, the study employs computational methods, including density functional theory, molecular docking, and molecular dynamics simulations, to assess the physicochemical properties and binding affinities of key (-)-Epicatechin metabolites with GPER. DFT analysis revealed distinct physicochemical properties among metabolites, influencing their reactivity and stability. Rigid and flexible molecular docking demonstrated varying binding affinities, with some metabolites surpassing (-)-Epicatechin. Molecular dynamics simulations highlighted potential binding pose variations, while MMGBSA analysis provided insights into the energetics of GPER-metabolite interactions. The outcomes elucidate distinct interactions, providing insights into potential molecular mechanisms underlying the effects of (-)-Epicatechin across varied biological contexts.

SEC-SAXS/MC Ensemble Structural Studies of the Microtubule Binding Protein Cdt1 Show Monomeric, Folded-Over Conformations

Cdt1 is a mixed folded protein critical for DNA replication licensing and it also has a "moonlighting" role at the kinetochore via direct binding to microtubules and the Ndc80 complex. However, it is unknown how the structure and conformations of Cdt1 could allow it to participate in these multiple, unique sets of protein complexes. While robust methods exist to study entirely folded or unfolded proteins, structure-function studies of combined, mixed folded/disordered proteins remain challenging. In this work, we employ orthogonal biophysical and computational techniques to provide structural characterization of mitosis-competent human Cdt1. Thermal stability analyses shows that both folded winged helix domains1 are unstable. CD and NMR show that the N-terminal and linker regions are intrinsically disordered. DLS shows that Cdt1 is monomeric and polydisperse, while SEC-MALS confirms that it is monomeric at high concentrations, but without any apparent inter-molecular self-association. SEC-SAXS enabled computational modeling of the protein structures. Using the program SASSIE, we performed rigid body Monte Carlo simulations to generate a conformational ensemble of structures. We observe that neither fully extended nor extremely compact Cdt1 conformations are consistent with SAXS. The best-fit models have the N-terminal and linker disordered regions extended into the solution and the two folded domains close to each other in apparent "folded over" conformations. We hypothesize the best-fit Cdt1 conformations could be consistent with a function as a scaffold protein that may be sterically blocked without binding partners. Our study also provides a template for combining experimental and computational techniques to study mixed-folded proteins.

Biocontrol potential of Vibrio maritimus chitinase: Heterologous expression and insecticidal activity against Acanthoscelides obtectus

In this study, the chitinase gene from the marine bacterium Vibrio maritimus was heterologously expressed in Escherichia coli, purified via affinity chromatography and tested for its insecticidal activity against the storage pest Acanthoscelides obtectus. The recombinant VmChiA protein exhibited a molecular mass of ∼60 kDa, with optimum activity observed at pH 6.0 and 40 °C. Enzyme kinetic analysis revealed a Km value of 0.042 mM, Vmax of 17.48 μmol min-1, kcat of 1.75 min-1 and catalytic efficiency of 41.61 mM-1 min-1, respectively. Furthermore, a dose of 40 U mL-1 of recombinant VmChiA showed similar efficacy to malathion insecticide against A. obtectus, with 100 % mortality in both treatments. LC50 and LC90 values of VmChiA were 13.95 U mL-1 and 27.66 U mL-1, respectively. Furthermore, the three-dimensional structure of the catalytic site of VmChiA was modeled. Molecular dynamics simulation technique was used to explore and analyze the dynamics and interactions. A salt bridge (GLU274-ARG296) in the α + β domain was observed as a critical feature facilitating substrate (GlcNAc)2 binding and enzymatic activity. These findings demonstrate that recombinant VmChiA possesses potent insecticidal properties, highlighting its potential as a bio-based, eco-friendly alternative for managing significant agricultural pests.

Substituted aryl piperazine ligands as new dual 5-hLOX/COX-2 inhibitors. Synthesis, biological and computational studies

Two series of cyano (1a-l) and amino (2a-l) aryl piperazines were synthesized and evaluated for their inhibitory activity against 5-lipoxygenase (5-hLOX) and cyclooxygenase-2 (COX-2). The newly designed derivatives feature diphenyl methyl (a-d), phenyl (e-h), or methoxyphenyl (i-l) groups, respectively, and demonstrated significant inhibition of 5-hLOX. Noteworthy were compounds 1b, 1 g, 1 k, 2f, and 2 g, exhibiting IC50 values ranging from 2.2 to 3.3 μM. The most potent inhibitors (1b, 1 g, 1 k, 2c, and 2f) were characterized by a competitive inhibition mechanism, with Ki values ranging between 1.77 μM and 9.50 μM. Additionally, compounds 2a, 2b, 2 g, and 2 h displayed promising dual inhibition of 5-hLOX and COX-2, with IC50 values below 15 μM. Cytotoxicity assessments against HEK293 cells revealed that the cyano derivatives (1a-l) were non-cytotoxic (CC50 > 200 μM), whereas the amino derivatives (2a-l) exhibited moderate cytotoxicity (CC50 < 50 μM). Notably, the most active derivatives against both targets were non-cytotoxic at their respective inhibitory concentrations. Computational studies, including docking and molecular dynamics simulations, indicated that compound 1 g demonstrated greater stability within the catalytic site of 5-hLOX compared to compound 2f, correlating with the higher affinity observed in kinetic assays. Furthermore, quantitative structure-activity relationship (QSAR) analyses revealed strong correlations between theoretical and experimental IC50 values (97 % for 1a-l and 93 % for 2a-l). These findings, combined with absorption, distribution, metabolism, and excretion (ADME) predictions, suggest that these derivatives are promising candidates as dual inhibitors of 5-hLOX and COX-2.

Screening single nucleotide changes to tropomyosin to identify novel cardiomyopathy mutants

Inherited cardiomyopathy is a broad class of heart disease that includes pathological cardiac remodeling such as hypertrophic and dilated cardiomyopathy, affecting 1/250-1/500 people worldwide. In many cases, mutations in proteins that make up the sarcomere, the basic subcellular unit of contraction, alter thin filament regulation and are the root cause of hypertrophic and dilated cardiomyopathy. Initially, compensations can maintain cardiac function, so patients may remain asymptomatic for years before a major cardiac episode. Early therapeutic intervention could rescue the deleterious effects of mutations thereby avoiding pathological remodeling, so prediction of potential outcomes and severity of as yet uncharacterized and known mutants of uncertain significance is critical. To accomplish this goal, we begin with the structure of the thin filament containing actin, tropomyosin, and troponin in its regulatory B- and C-states, incorporate all potential single nucleotide mutations to the tropomyosin sequence (over 1700 unique mutations), and then measure the interaction energy between tropomyosin and actin after energy minimization. Analysis of the database thus generated shows the tropomyosin residues resulting in large changes in tropomyosin-actin interaction, and therefore most likely to be deleterious to function. Some of these mutants have been observed in human patients, whereas others are novel. Global analysis further refines hotspots of mutation-sensitive, coiled-coil tropomyosin residues affecting actin interactions. Altogether, the database will allow research to focus in great depth on key candidates for functional analysis, for instance, by assaying in vitro motility and engineered heart tissue mechanics and assessing outcomes in animal models.

Drosera rotundifolia L. as E. coli biofilm inhibitor: Insights into the mechanism of action using proteomics/metabolomics and toxicity studies

The successful sustainable cultivation of the well-known medicinal plant sundew on rewetted peatlands not only leads to the preservation of natural populations, but also provides a basis for the sustainable pharmaceutical use of the plant. The bioactive compounds of sundew, flavonoids and naphthoquinones, show biofilm-inhibiting properties against multidrug-resistant, ESBL-producing E. coli strains and open up new therapeutic possibilities. This study investigates the molecular mechanisms of these compounds in biofilm inhibition through proteomic analyses. Specific fractions of flavonoids and naphthoquinones, as well as individual substances like 7-methyljuglone and 2″-O-galloylhyperoside, are analyzed. Results show that naphthoquinones appear to act via central regulatory proteins such as OmpR and alter the stress response while flavonoids likely affect biofilm formation by creating an iron-poor environment through iron complexation and additionally influence polyamine balance, reducing intracellular spermidine levels. Further investigations including assays for iron complexation and analysis of polyamines confirmed the proteomic data. Safety evaluations through cytotoxicity tests in 3D cell cultures and the Galleria mellonella in vivo model confirm the safety of the extracts used. These findings highlight sundew as a promising candidate for new phytopharmaceuticals.

Parallelization of Particle-Based Reaction-Diffusion Simulations Using MPI

Particle-based reaction-diffusion offers a high-resolution alternative to the continuum reaction-diffusion approach, capturing the volume-excluding nature of molecules undergoing stochastic dynamics. This is essential for simulating self-assembly into higher-order structures like filaments, lattices, or macromolecular complexes. Applications of self-assembly are ubiquitous in chemistry, biology, and materials science, but these higher-resolution methods increase computational cost. Here, we present a parallel implementation of the particle-based NERDSS software using the message passing interface (MPI), achieving close to linear scaling for up to 96 processors. By using a spatial decomposition of the system across processors, our approach extends to very large simulation volumes. The scalability of parallel NERDSS is evaluated for reversible reactions and several examples of higher-order self-assembly in 3D and 2D, with all test cases producing accurate solutions. Parallel efficiency depends on the system size, timescales, and reaction network, showing optimal scaling for smaller assemblies with slower timescales. We provide parallel NERDSS code open-source, supporting development and extension to other particle-based reaction-diffusion software.

2Danalysis: A toolbox for analysis of lipid membranes and biopolymers in two-dimensional space

Molecular simulations expand our ability to learn about the interplay of biomolecules. Biological membranes, composed of diverse lipids with varying physicochemical properties, are highly dynamic environments involved in cellular functions. Proteins, nucleic acids, glycans, and biocompatible polymers are the machinery of cellular processes both in the cytosol and at the lipid membrane interface. Lipid species directly modulate membrane properties, and affect the interaction and function of other biomolecules. Natural molecular diffusion results in changes of local lipid distribution, affecting the membrane properties. Projecting biophysical, structural membrane and biopolymer properties to a two-dimensional plane can be beneficial to quantify molecular signatures in a reduced dimensional space to identify relevant interactions at the interface of interest, i.e., the membrane surface or biopolymer-surface interface. Here, we present a toolbox designed to project membrane and biopolymer properties to a two-dimensional plane to characterize patterns of interaction and spatial correlations between lipid-lipid and lipid-biopolymer interfaces. The toolbox contains two hubs implemented using MDAKits architecture, one for membranes and one for biopolymers, that can be used independently or together. Three case studies demonstrate the versatility of the toolbox with detailed tutorials in GitHub. The toolbox and tutorials will be periodically updated with other functionalities and resolutions to expand our understanding of the structure-function relationship of biomolecules in two dimensions. VIDEO ABSTRACT.

Identification of a rare variant in TNNT3 responsible for familial dilated cardiomyopathy through whole-exome sequencing and in silico analysis

BACKGROUND

Dilated cardiomyopathy (DCM) is a prevalent etiology of heart failure, distinguished by the gradual and frequently irreversible myocardial muscle impairment. Roughly 50% of DCM occurrences stem from hereditary rare variants. In this study, our aim was to identify the genetic cause of DCM in a pedigree with several affected individuals across four generations.

METHODS

Whole exome sequencing was performed on the proband, with variants filtered and analyzed using in silico tools. Co-segregation analysis was conducted using Sanger sequencing. Protein structure modeling and protein-protein interaction evaluations were performed using AlphaFold3 and HADDOCK2.4, respectively.

RESULTS

We identified a missense rare variant in the TNNT3 gene, leading to the p.Glu125Gly alteration in the Troponin T3 (TNNT3). This rare variant is strongly implicated as the causative factor for DCM in the pedigree. Several key factors underscore its significance: the rare variant co-segregates with the disease in the pedigree, is absent in 850 control samples, alters a conserved amino acid, is predicted to detrimentally affect protein function, and results in structural changes.

CONCLUSIONS

Our findings suggest that TNNT3 rare variants can induce DCM by weakening the binding energy between TNNT3 and Tropomyosin (TPM), leading to functional deficiencies in muscle contraction, as demonstrated by our structural modeling and docking studies. Troponin T is essential for the proper contraction of striated muscles and is related to cardiac development. Bioinformatics investigations have elucidated the involvement of TNNT3-related pathways, notably the Striated Muscle Contraction pathway and Cardiac Conduction. TNNT3 resides within loci previously implicated in cardiomyopathy. Given its crucial role in muscle contractile function, rare variants in TNNT3 hold the potential to be a significant contributing factor in the pathogenesis of DCM. A wealth of literature substantiates the correlation between troponin T and cardiac disorders. Our findings further corroborate this association.

Correlating molecular structures and self-assembly mechanisms via temporal analysis of multidimensional chemical interaction space: application to assemblies of isomeric peptides

Computational modelling of self-assembly mechanisms is a promising way to establish chemically meaningful relationships between molecular structures of the building blocks and the final outcomes of the spontaneous assemblies. However, such connections are not immediately apparent, due to the presence of complex interplay involving a multitude of intermolecular interactions with complicated temporal variations. In this paper, we propose a method called temporal analysis of multidimensional chemical interaction space (TAMCIS), which looks at important combinations of interactions, rather than analysing them one at a time. Each molecule was assigned a vector order parameter, with components representing appropriately chosen chemical interactions. The aggregate data were processed using density-based clustering, resulting in "interaction clusters". Time dependent partitioning of the molecules among these clusters revealed the mechanism in terms of interactions, thereby making a direct connection to the molecular structures of the building blocks. We applied the method to a comparative study of assembly mechanisms of two isomeric hydrophobic tri-peptides in water, namely tri-L-leucine (LLL) and tri-L-isoleucine(III). Initially, both systems started to aggregate via non-bonded interactions through sidechains. But at later stages, they diverged in the interaction space when hydrogen bonding and electrostatic contacts became important. Overall, a stark difference was observed. LLL assembly grew by a combination of interactions. In contrast, the III system primarily utilized one type of hydrogen bonding, leading to β-sheet-like arrangements found in proteins. The TAMCIS provided a clear path for deciphering the origins of emergent complexities in spontaneous self-assemblies from dynamical simulation data.

Influence of mutations at different distances from the active center on the activity and stability of laccase 13B22

Laccases with high catalytic efficiency and high thermostability can drive a broader application scope. However, the structural distribution of key amino acids capable of significantly influencing the performance of laccases has not been explored in depth. Thirty laccase 13B22 mutants with changes in amino acids at distances of 5 Å (first shell), 5-8 Å (second shell), and 8-12 Å (third shell) from the active center were validated experimentally with 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) as substrate. Twelve of these mutants (first shell, 1; second shell, 4; third shell, 7) showed higher catalytic efficiency than the wild-type enzyme. Mutants D511E and I88L-D511E showed 5.36- and 10.58-fold increases in kcat/Km, respectively, with increases in optimal temperature of 15 °C and optimal pH from 7.0 to 8.0. Furthermore, both mutants exhibited greater thermostability compared to the wild-type, with increases of 3.33 °C and 5.06 °C in Tm and decreases of 0.39 J and 0.59 J in total structure energy, respectively. The D511E mutation resides in the third shell, while I88L is in the second shell, and their performance enhancements were attributed to alterations in the rigidity or flexibility of specific protein structural domains. Both mutants showed enhanced degradation efficiency for benzo[a]pyrene and zearalenone. These findings highlight the importance of the residues located far from the active center in the function of laccase (second shell and third shell), suggesting broader implications for enzyme optimization and biotechnological applications.

Moltiverse: Molecular Conformer Generation Using Enhanced Sampling Methods

Accurately predicting the diverse bound-state conformations of small molecules is crucial for successful drug discovery and design, particularly when detailed protein-ligand interactions are unknown. Established tools exist, but efficiently exploring the vast conformational space remains challenging. This work introduces Moltiverse, a novel protocol using enhanced sampling molecular dynamics (MD) simulations for conformer generation. The extended adaptive biasing force (eABF) algorithm combined with metadynamics, guided by a single collective variable (radius of gyration, RDGYR), efficiently samples the conformational landscape of a small molecule. Moltiverse demonstrates comparable accuracy and, in some cases, superior quality when benchmarked against established software like RDKit, CONFORGE, Balloon, iCon, and Conformator in the Platinum Diverse Data set for drug-like small molecules and the Prime data set for macrocycles. We present multiple quantitative metrics and statistical analysis for robust conformer generation algorithm comparisons and provide recommendations for their improvement based on our findings. Our extensive evaluation shows that Moltiverse is particularly effective for challenging systems with high conformational flexibility, such as macrocycles, where it achieves the highest accuracy among the tested algorithms. The physics-based approach employed by Moltiverse effectively handles a wide range of molecular complexities, positioning it as a valuable tool for computational drug discovery workflows requiring accurate representation of molecular flexibility.

Novel benzimidazole hybrids: design, synthesis, mechanistic studies, antifungal potential and molecular dynamics

In this study, two series of benzimidazole hybrids were developed and designed using different strategies. The target compounds were designed through straight chemistry pathways and were screened as possible antimicrobial agents. Twenty new compounds were synthesized, among which compounds 11 and 12 displayed excellent activity against Candida albicans and Cryptococcus neoformans with growth inhibition percentage ranging from 86.42% to 100%. For gaining better insights into the mechanistic ability of the active candidates 11 and 12, their inhibitory activity against lanosterol 14α-demethylase was studied. Results showed IC50 values of 5.6 and 7.1 μM for 11 and 12, respectively, which were comparable to the reference value of fluconazole (2.3 μM), indicating low drug interaction possibilities. Notably, compound 11 displayed excellent inhibition of biofilm metabolic activity. In addition, their synergistic activity against C. neoformans displayed a 2-fold increase compared with fluconazole. Furthermore, it exhibited sustained antifungal activity with time clearance of over 24 h, which was better than the time clearance of fluconazole (6 h). Moreover, compounds 11 and 12 displayed considerable safety profiles, with no cytotoxicity reported against human embryonic kidney cells or hemolysis of red blood cells. Molecular dynamics simulation (MDS) experiments over 100 ns of compound 11 showed its ability to interact with the HEM binding site as the co-crystallized ligand (fluconazole). Finally, in silico ADMET studies predicted its significant oral bioavailability as antifungal candidates.

Dual-Site Targeting by Peptide Inhibitors of the N-Terminal Domain of Hsp90: Mechanism and Design

Heat shock protein 90 (Hsp90) is a pivotal molecular chaperone crucial in the maturation of client proteins, positioning it as a significant target for cancer therapy. However, the design of effective Hsp90 inhibitors presents substantial challenges due to the complex interaction network and the requisite specificity of the inhibitors. This study tackles the task of designing peptide inhibitors capable of concurrently binding to both the ATP-binding pocket and the Cdc37-binding site within the N-terminal domain of Hsp90. In response to these challenges, we developed an advanced peptide screening protocol that merges machine learning with various molecular simulation techniques to boost the identification and optimization of potent inhibitors. Our integrated approach employs a convolutional neural network-based framework to predict peptide binding propensities. This predictive model is augmented by comprehensive molecular docking and dynamic simulations to assess the stability and interaction dynamics of Hsp90/peptide complexes. We successfully identified three heptapeptides that demonstrate the ability to interact with both binding sites, effectively obstructing the entrance to the ATP-binding pocket. This study elucidates the inhibitory mechanisms of these peptides, paves the way for the development of more efficacious therapeutic agents targeting Hsp90, and underscores the value of integrating machine learning techniques with molecular modeling in the peptide design process.

Substrate Activation Efficiency in Active Sites of Hydrolases Determined by QM/MM Molecular Dynamics and Neural Networks

The active sites of enzymes are able to activate substrates and perform chemical reactions that cannot occur in solutions. We focus on the hydrolysis reactions catalyzed by enzymes and initiated by the nucleophilic attack of the substrate's carbonyl carbon atom. From an electronic structure standpoint, substrate activation can be characterized in terms of the Laplacian of the electron density. This is a simple and easily visible imaging technique that allows one to "visualize" the electrophilic site on the carbonyl carbon atom, which occurs only in the activated species. The efficiency of substrate activation by the enzymes can be quantified from the ratio of reactive and nonreactive states derived from the molecular dynamics trajectories executed with quantum mechanics/molecular mechanics potentials. We propose a neural network that assigns the species to reactive and nonreactive ones using the Laplacian of electron density maps. The neural network is trained on the cysteine protease enzyme-substrate complexes, and successfully validated on the zinc-containing hydrolase, thus showing a wide range of applications using the proposed approach.

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores. This method makes it easier to interpret the movement of the protein complex from heterogeneity analysis and to compare the structural dynamics observed from CryoEM data with results from other experimental and simulation techniques.

Design, synthesis, biological evaluation and in silico studies of 2-anilino- 4-(benzimidazol- 1-yl)pyrimidine scaffold as antitumor agents

In an attempt to rationalize the search for new potential Chemotherapeutic agents, a new series of 2-anilinobenzimidazol derivatives with CDK activity have been synthesized. The newly synthesized compounds have been assessed for their cytotoxic effects and CDK activity. These presented compounds showed strong inhibition of cell proliferation in various solid cancer cell lines, suggesting a promising approach for treating malignant tumors. Compounds 4 g, 4j, 4 m, and 4q displayed remarkably strong anticancer potencies against HepG2 cells, with IC50 of 7.59, 8.54, 3.56 and 5.88 µM, respectively, compared to the positive control, DOX (IC50 = 4.50 µM). while compound 4 m, and 4q had the highest anticancer activity against HeLa cells, with an IC50 of 6.39 and 9.71 µM, respectively, compared to the positive control DOX (IC50 = 5.57 µM). On the other hand, comparison of IC50 values against MCF-7 cells revealed that compounds 4 g, 4 m, and 4q showed significant anticancer potency with IC50 of 5.08, 2.18 and 8.19 µM, respectively compared to that of the positive control DOX (IC50 = 4.17 µM). Moreover, compound 4 m and 4q were the most potent CDK9 and CDK12 inhibitors. Furthermore, a molecular docking simulation were performed to explore the ability of compounds 4 m to adopt the common binding pattern of CDK9 and CDK12/T1 inhibitors. In silico ADMET results showed that all compounds have favourable drug-like properties since they met Lipinski's rule of five criteria. Overall, the synthesized anilinopyrimidine derivatives exhibit significant potential as chemotherapeutic agents.

Tailoring the Regioselectivity of Lentinula edodes O-Methyltransferases for Precise O-Methylation of Flavonoids

A novel O-methyltransferase, LeOMT4, from Lentinula edodes was identified, expressed, and characterized. Although its catalytic activity was lower than that of the previously reported LeOMT2, LeOMT4 displayed strong regioselectivity for the meta-hydroxy group across different catecholic compounds, producing e.g., ferulic acid with an almost exclusive regioisomeric ratio of 98:2 and homoeriodictyol with a ratio of 82:18 (3'-product:4'-product). Leveraging the high sequence and predicted structural similarity between LeOMT2 and LeOMT4, key sites for the tailoring of LeOMT2 were identified through site-directed mutagenesis. This approach aimed for robust mutants retaining the high specific activity of LeOMT2, while enhancing regioselectivity. A single amino acid substitution, F182Y, enabled a regioisomeric ratio of 91:9 for the production of homoeriodictyol. Notably, another single amino acid substitution, I53M reversed the regioselectivity to 2:98 in favor of hesperetin. This strategy enables the selective production of sought-after pharmacologically active flavonoids (butein) and flavor-active flavonoids (homoeriodictyol, hesperetin, hesperetin dihydrochalcone).

Synergistic in silico exploration of some pyrazole-based potential anticancer agents: a DFT, molecular docking, and molecular dynamics study

CONTEXT

Understanding the interaction between therapeutic molecules with in vivo receptors is very essential in developing potential anticancer agents. In recent years, pyrazole derivatives have been evolving as a significant bioactive candidate due to their remarkable pharmacological properties in novel drug design and discovery. Herein, we present a comprehensive computational and theoretical analysis of some selected pyrazole derivatives with potential anticancer properties, employing quantum chemical calculations, molecular docking, and molecular dynamics simulation.

METHOD

In this study, quantum chemical calculations were employed using density functional theory (DFT) with B3LYP functional and 6-31G(d,p) basis set in Gaussian16 to investigate the electronic properties and intermolecular interactions of pyrazole derivatives. Natural bond orbital (NBO) analysis was performed to explore charge distribution and donor-acceptor interactions. Similarly, advanced topological analyses, viz., reduced density gradient (RDG), quantum theory of atoms in molecules (QTAIM), electron localisation function (ELF), localised orbital indicator (LOL), and electrostatic potential (ESP), to characterise intermolecular interactions and electron density features. Molecular docking studies were conducted to assess the binding affinity of the pyrazole derivatives with DNA (PDB ID: 2m2c), specifically focussing on interactions with base pairs. Molecular dynamics simulations were employed to examine the stability and characteristics of interactions over a prolonged timescale. This comprehensive approach integrates quantum chemical tools, molecular docking, and molecular dynamics simulations to elucidate the interaction mechanisms between pyrazole derivatives and DNA nucleobases, enhancing their potential novelty as anticancer agents.

Insights into the solution structure of the actin-binding tail domain of metavinculin by small angle X-ray scattering and molecular dynamics simulations

Vinculin is a ubiquitously expressed focal adhesion protein that plays an important role in cell-matrix and cell-to-cell junctions. Metavinculin, a muscle-specific splice variant of vinculin, contains a 68-amino acid disordered insert region in its actin binding tail domain (MVt). Mutations in this insert are linked to cardiomyopathies. This study investigates the solution structures and structural ensembles of wild-type (WT) and two mutant MVts, ΔLeu954 and R975W, which have been associated with cardiomyopathies, using small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations. SAXS analyses revealed subtle differences in the estimated maximum dimensions and corroborated the elongated shape of the MVts. Quantitative comparisons of SAXS profiles indicated similarity between the WT and ΔLeu954, whereas R975W exhibited differences in the small-angle region. MD simulations demonstrated reduced conformational flexibility and greater packing of the insert in WT compared to mutants. Notably, a salt-bridge observed between R975 and D928 in a WT simulation provides a structural basis for the destabilization caused by the R975W mutation. These findings provide insights into the structure and dynamics of WT and mutant MVt, reflecting the promise of SAXS combined with MD simulations to elucidate the structural properties of proteins with structural disorder.

Molecular insights into human phosphatidylserine synthase 2 and its regulation of SREBP pathways

Homologous proteins share similar sequences, enabling them to work together in cells to support normal physiological functions. Phosphatidylserine synthases 1 and 2 (PSS1 and PSS2) are homologous enzymes that catalyze the synthesis of phosphatidylserine (PS) from different substrates. PSS2 shows a preference for phosphatidylethanolamine (PE) as its substrate, whereas PSS1 can utilize either PE or phosphatidylcholine. Previous studies showed that inhibiting PSS1 promotes SREBP-2 cleavage. Interestingly, despite their homology, our findings reveal that PSS2 exerts an opposing effect on the cleavage of both SREBP-1 and SREBP-2. We resolved the cryo-electron microscopy (cryo-EM) structure of human PSS2 at 3.3 Å resolution. Structural comparison of the catalytic cavities between PSS1 and PSS2 along with molecular dynamics simulations uncovers the molecular details behind the substrate preference of PSS2 for PE. The lipidomic analysis showed that PSS2 deficiency leads to PE accumulation in the endoplasmic reticulum, which has been shown to inhibit the cleavage of sterol regulatory element-binding proteins (SREBPs) in mice. Thus, our findings reveal the intricate network of intracellular phospholipid metabolism and underscore the distinct regulatory roles of homologous proteins in cellular activities.

Quantitative Nanometrology of Binary Particle Systems Using Fluorescence Recovery after Photobleaching: Application to Colloidal Silica

We present an application of fluorescence recovery after photobleaching (FRAP) to measure the size of the individual nanoparticles in binary systems. The presence of nanoparticles with varying sizes was successfully demonstrated using a straightforward biexponential model and their sizes were accurately determined. Furthermore, we have demonstrated the benefits of preprocessing the data using a simple machine learning algorithm based on the gradient boosting machine and fitting the resulting curves to a triexponential model. This approach allows the accurate recovery of the sizes of each of the three components in a binary particle system, namely, the 6 nm LUDOX HS40, 11 nm LUDOX AS40, and the free R6G labeling dye. Lastly, it has been demonstrated using molecular dynamics simulations that R6G adsorption to silica nanoparticles (SNPs) is indeed size-dependent, with larger constructs as the preferred target because of their higher charge and smaller curvature. The theoretical and experimental results were therefore consistent with one another.

Atomistic Mechanism Underlying the Regulation of the GPA1 G Protein Signaling Pathway Mediated by the Gibberellin A1 Phytohormone Binding to the GCR1 Plant G-Protein-Coupled Receptor

We propose an atomistic mechanism suggesting that fundamental plant processes, including seed germination, root elongation, and flower and fruit production, may be regulated by phytohormones such as Gibberellin A1 (GA1) binding to the GCR1 plant G-protein-coupled receptor. This parallels the central roles of GPCRs in animals for vision, taste, smell, pain, depression, and nerve signaling, among others. Validating GCR1 as a genuine GPCR in plants, particularly its interaction with GPA1, G-protein, would mark a groundbreaking advancement in understanding plant processes, both biologically and agronomically. However, experimental confirmation of this interaction and evidence supporting the idea that binding of GA1 to GCR1 would regulate GPA1 activation are lacking. Indeed, the design of experiments to explore these hypotheses is impeded by the absence of structural information relating to interactions of GPA1 with the GA1-GCR1 complex. To address this gap, we employ molecular dynamics and metadynamics simulations to demonstrate that binding GPA1 to the GA1-GCR1 complex induces conformational changes that open up the Ras and Helical domains of GPA1 to release GDP for exchange with GTP, thereby enabling signaling. Our results suggest numerous mutations involving GA1 binding at the GCR1 site and the coupling of GCR1 to the GPA1 G-protein that could be used to validate (or not validate) our predicted mechanism. Such validation would serve as a foundation for devising strategies to design novel agonists and inverse agonists to provide precise control of crucial plant processes.

Current advancements and future perspectives of 1,2,3-triazoles to target lanosterol 14α-demethylase (CYP51), a cytochrome P450 enzyme: A computational approach

Antifungal resistance has become a significant challenge, necessitating the development of novel antifungal agents. Resistance often arises from prolonged and widespread use of existing treatments, leading to mutations in fungal enzymes that reduce drug efficacy. Amongst various scaffolds, 1,2,3-triazoles have emerged as antifungal agents due to their ability to bind effectively to fungal enzymes. This review examines the binding interactions of 1,2,3-triazoles with lanosterol 14α-demethylase (CYP51), an enzyme in Candida albicans (PDB IDs:5TZ1and5V5Z), highlighting their potential in fighting resistance. The CYP51 family is a captivating topic to investigate the structural and functional roles of P450 and makes for a key medical focus. It is one of crucial step in biosynthesis of sterol in eukaryotes. Antifungals mostly work on CYP51 and could also be used to treat protozoan diseases in the future. 1,2,3-Triazoles exert their antifungal effects by inhibiting the CYP51 enzyme, which is crucial for ergosterol synthesis in fungal cell membranes thereby leading to disruption of membrane integrity and ultimately leads to death of fungal cell. In silico studies like molecular docking and molecular dynamics (MD) simulations, reveal that these compounds establish strong interactions (e.g., π-π, π-alkyl, CH, hydrogen bonding, and Van der Waals interactions) with active site residues, stabilizing the ligand-enzyme complex. This review of virtual screening assays shows the adaptability of the 1,2,3-triazole scaffold and its widespread use in core antifungal compounds, making it a key pharmacophore for new lead development against resistant fungal species.

A CoQ10 analog ameliorates cognitive impairment and early brain injury after subarachnoid hemorrhage by regulating ferroptosis and neuroinflammation

Subarachnoid hemorrhage (SAH) represents a stroke subtype that can lead to prolonged cognitive deficits as well as death or disability. Prior investigation has suggested that CoQ10 analogs can mitigate oxidative stress and inflammation and promote mitochondrial biogenesis in the context of brain injury and neurodegenerative disorders. However, the precise mechanisms underlying early brain injury (EBI) following SAH remain incompletely understood, and the detailed molecular processes have yet to be completely clarified. This investigation examined the neuroprotective properties of a CoQ10 analog concerning EBI post-SAH and identified potential mechanistic pathways. Our findings indicate that SAH led to alterations in innate and learned behaviors in aged C57BL/6J mice while also triggering ferroptosis and neuroinflammation within hippocampal neurons. Additionally, SAH was associated with reduced ferroptosis-related proteins, exacerbation of iron accumulation, elevation of lipid ROS, and decreased FSP1, HO-1, and NQO1 levels. The CoQ10 analog idebenone (IDB) demonstrated a capacity to alleviate EBI, as evidenced by improvements in both innate and learned behaviors, alongside a reduction in ferroptosis-related gene/protein expression. Silencing of FSP1 exacerbated EBI, ferroptosis, and neuroinflammation, and partially counteracted the neuroprotective effects of the CoQ10 analog. These results suggest that IDB may enhance the recovery from SAH-induced EBI in aged mice by modulating FSP1 protein stability via NMT-mediated N-myristoylation, thereby inhibiting both ferroptosis and neuroinflammation. The potential therapeutic application of IDB as a clinical intervention for EBI following SAH is also highlighted.

GPU Accelerated Hybrid Particle-Field Molecular Dynamics: Multi-Node/Multi-GPU Implementation and Large-Scale Benchmarks of the OCCAM Code

A parallelization strategy for hybrid particle-field molecular dynamics (hPF-MD) simulations on multi-node multi-GPU architectures is proposed. Two design principles have been followed to achieve a massively parallel version of the OCCAM code for distributed GPU computing: performing all the computations only on GPUs, minimizing data exchange between CPU and GPUs, and among GPUs. The hPF-MD scheme is particularly suitable to develop a GPU-resident and low data exchange code. Comparison of performances obtained using the previous multi-CPU code with the proposed multi-node multi-GPU version are reported. Several non-trivial issues to enable applications for systems of considerable sizes, including large input files handling and memory occupation, have been addressed. Large-scale benchmarks of hPF-MD simulations for system sizes up to 10 billion particles are presented. Performances obtained using a moderate quantity of computational resources highlight the feasibility of hPF-MD simulations in systematic studies of large-scale multibillion particle systems. This opens the possibility to perform systematic/routine studies and to reveal new molecular insights for problems on scales previously inaccessible to molecular simulations.

The molecular mechanisms of visual chromophore release from cellular retinaldehyde-binding protein

Cellular retinaldehyde-binding protein (CRALBP) is an 11-cis-retinoid binding protein operating within the visual cycle. CRALBP serves as the terminal acceptor of 11-cis-retinaldehyde (11cRAL) produced within the retinal pigment epithelium (RPE) and mediates 11cRAL transport to the RPE apical microvilli. Crystallographic structures of CRALBP revealed that the 11cRAL-binding pocket is sealed off from bulk solvent, indicating a necessity for conformational changes to allow ligand egress. Here, we performed long timescale all-atom molecular dynamics simulations of CRALBP to elucidate the mechanisms of ligand release. CRALBP exhibits slower diffusive behavior in the presence of membranes containing negatively charged phospholipids, which bind to an exposed cationic pocket in CRALBP. Umbrella sampling calculations revealed thermodynamically likely pathways for 11cRAL egress. Our data suggest that the CRALBP-acidic phospholipid interaction facilitates 11cRAL release through allosteric, conformational changes that perturb the binding site, lowering ligand affinity. These findings offer insights into the molecular pathology of CRALBP-associated retinopathy.

Quantifying Ionic Liquid Affinity and Its Effect on Phospholipid Membrane Structure and Dynamics

Understanding the interactions between ionic liquids (ILs) and biomembranes is pivotal for uncovering the origins of IL-induced biological activities and their potential applications in pharmaceuticals. In this study, we investigate the influence of imidazolium-based ILs on the viscoelasticity, dynamics, and phase behavior of two model membrane systems: (i) lipid monolayers and (ii) unilamellar vesicles, both composed of dipalmitoylphosphatidylcholine (DPPC). Two different ILs with varying alkyl chain lengths, namely, 1-decyl-3-methylimidazolium bromide (DMIM[Br]) and 1-hexyl-3-methylimidazolium bromide (HMIM[Br]) are used to investigate the role of alkyl chain lengths. Our findings demonstrate that both ILs induce significant disorder in lipid membranes by altering the area per lipid molecule, thereby modulating their viscoelastic properties. ILs with a longer alkyl chain show stronger interactions with membranes, causing a more pronounced disorder. Fourier transform infrared spectroscopy indicates that IL incorporation shifts the membrane's main phase transition to lower temperatures and introduces gauche defects, signifying increased structural disorder. This effect is amplified by longer alkyl chains and higher IL concentrations. Quasielastic neutron scattering studies highlight that ILs markedly enhance the lateral diffusion of lipids within the membrane leaflet, with the extent of enhancement determined by the membrane's physical state, IL concentration, and alkyl chain length. The most pronounced acceleration in lateral diffusion occurs in the ordered membrane phase with higher concentrations of the longer-chain IL. Molecular dynamics simulations corroborate these experimental findings, showing that longer-chain ILs extensively disrupt lipid organization, introduce more gauche defects, increase the area per lipid, and consequently enhance lateral diffusion. This increase in the lipid fluidity and permeability provides a mechanistic basis for the observed higher toxicity associated with longer-chain ILs. These results offer critical insights into the molecular-level interactions of ILs with lipid membranes, advancing our understanding of their toxicological and pharmaceutical implications.

Loss of lipid asymmetry facilitates plasma membrane blebbing by decreasing membrane lipid packing

Membrane blebs have important roles in cell migration, apoptosis, and intercellular communication through extracellular vesicles (EVs). While plasma membranes (PM) typically maintain phosphatidylserine (PS) on their cytoplasmic leaflet, most blebs have PS exposed on their outer leaflet, revealing that loss of steady-state lipid asymmetry often accompanies PM blebbing. How these changes in PM lipid organization regulate membrane properties and affect bleb formation remains unknown. We confirmed that lipid scrambling through the scramblase TMEM16F is essential for chemically induced membrane blebbing across cell types, with the kinetics of PS exposure being tightly coupled to the kinetics of bleb formation. Measurement of lipid packing with environment-sensitive probes revealed that lipid scrambling changes the physical properties of the PM, reducing lipid packing and facilitating the bilayer bending required for bleb formation. Accordingly, reducing lipid packing of the PM through cholesterol extraction, elevated temperature, or treatment with biological amphiphiles promoted blebbing in the absence of TMEM16F. Consistent with these cellular observations, blebbing in Caenorhabditis elegans embryos measured via EV production was significantly reduced by depleting the TMEM16-homolog ANOH-2. Our findings suggest that changing membrane biophysical properties by lipid scrambling is an important contributor to the formation of blebs and EVs and potentially other cellular processes involving PM deformation.

A Thermodynamic Cycle to Predict the Competitive Inhibition Outcomes of an Evolving Enzyme

Understanding competitive inhibition at the molecular level is essential for unraveling the dynamics of enzyme-inhibitor interactions and predicting the evolutionary outcomes of resistance mutations. In this study, we present a framework linking competitive inhibition to alchemical free energy perturbation (FEP) calculations, focusing on Escherichia coli dihydrofolate reductase (DHFR) and its inhibition by trimethoprim (TMP). Using thermodynamic cycles, we relate experimentally measured binding constants (Ki and Km) to free energy differences associated with wild-type and mutant forms of DHFR with a mean error of 0.9 kcal/mol, providing insight into the molecular underpinnings of TMP resistance. Our findings highlight the importance of local conformational dynamics in competitive inhibition. Mutations in DHFR affect substrate and inhibitor binding affinities differently, influencing the fitness landscape under selective pressure from TMP. Our FEP simulations reveal that resistance mutations stabilize inhibitor-bound or substrate-bound states through specific structural and/or dynamical effects. The interplay of these effects showcases significant molecular-level epistasis in certain cases. The ability to separately assess substrate and inhibitor binding provides valuable insights, allowing for a more precise interpretation of mutation effects and epistatic interactions. Furthermore, we identify key challenges in FEP simulations, including convergence issues arising from charge-changing mutations and long-range allosteric effects. By integrating computational and experimental data, we provide an effective approach for predicting the functional impact of resistance mutations and their contributions to evolutionary fitness landscapes. These insights pave the way for constructing robust mutational scanning protocols and designing more effective therapeutic strategies against resistant bacterial strains.

Impact of Native Environment in Multiheme-Cytochrome Chains of the MtrCAB Complex

MtrCAB protein complex plays a crucial role in exporting electrons through the outer membrane (OM) to external acceptors. This complex consists of three proteins and contains 20 hemes. Optimal protein-protein interactions and, consequently, heme-heme interactions facilitate efficient electron transfer through the conduit of hemes. The cytochrome MtrA remains mostly inside porin MtrB, and the MtrB barrel contains two calcium ions on its surface. In this study, we investigate the effect of porin-bound calcium ions on the heme-heme distances in the twenty-heme network. We performed all-atom molecular dynamics simulations of the OM-protein complex, MtrCAB, in the presence and absence of the MtrB-bound calcium ions. We observe that the calcium ions bound to MtrB affect the interfacial heme-heme distance when all of the hemes are oxidized and impact one of the heme-heme distances in MtrC when all of the hemes are reduced. In both cases, the absence of calcium ions increases the heme-heme distance, highlighting the crucial role of calcium ions in maintaining the heme network, which is essential for long-range charge transport.

Application of in-silico approaches in subunit vaccines: Overcoming the challenges of antigen and adjuvant development

Subunit vaccines are crucial in preventing modern diseases due to their safety, stability, and ability to elicit targeted immune responses. However, challenges in antigen and adjuvant design hinder their development. Recent advancements in in-silico approaches, including reverse vaccinology, structural vaccinology, and machine learning, have revolutionized vaccine development from empirical practices to rational design approaches. This review summarizes the transformative impact of in-silico approaches on subunit vaccine development. We address the challenges of antigen identification and designation, highlighting how advanced computational techniques are employed to accelerate antigen acquisition. We also examine the challenges in adjuvant discovery and illustrate how machine learning helps overcome these barriers. Finally, we explore potential future directions for subunit vaccines, highlighting the importance of combining computational methods with other technologies to tackle the challenges associated with subunit vaccine development.

Collective Vibration Decoupling of Confined Water in Membrane Channels

We previously reported that the asymmetric IR absorption of monolayer water confined within two-dimensional nanochannels is capable of nonthermally inducing a unidirectional flow [Zhang, Q. L. Phys. Rev. Lett. 2024, 132, 184003], while the reason for the difference in the collective vibration IR spectrum between the confined water (CW) and bulk water is still not fully understood. Here, using molecular dynamics simulations, we systematically demonstrated that the CW in narrow graphene membrane channels will appear as a predominant fingerprint-peak and a subpeak in the collective vibration spectrum band. A comparison with the calculated IR spectrum for the CW in the channels with different interlayer spacings revealed that the double-peaked pattern originates from the decoupling of the CW's collective vibration. The highlight spectral intensity of the fingerprint-peak is attributed to the low-cost out-of-plane vibration (wag mode) of the CW molecules. These findings help us understand the physical origins of the unique IR spectra of CW in nanochannels, thereby providing a robust theoretical support for the regulation of the CW's structure and dynamics properties by a remote terahertz stimulation.

Lipid-GPCR interactions in an asymmetric plasma membrane model

We report simulations and analysis of the A2A adenosine receptor in its fully active state, in two different membrane environments. The first is a model in which the lipids are distributed asymmetrically according to recent lipidomics, simulations, and biophysical measurements, which together establish the distribution of lipids and cholesterol between the two leaflets. The second is the symmetrized version, which captures the membrane state following loss of lipid asymmetry. By comparing lipid-protein interactions between these two cases we show that solvation by phosphatidyl serine (PS) is insensitive to the loss of asymmetry-an abundance of positively charged sidechains around the cytoplasmic side of the receptor enriches solvation by PS in both membrane states. Cholesterol interactions are sensitive to the loss of asymmetry, with the abundance of cholesterol in the exoplasmic leaflet driving long-lived cholesterol interactions in the asymmetric state. However, one cholesterol interaction site on helix 6 is observed in both cases, and was also observed in earlier work with different membrane models, supporting its identification as a bona fide cholesterol binding site.

RIBOsensor for FRET-based, real-time ribose measurements in live cells

d-Ribose is a building block of many essential biomolecules, including all nucleic acids, and its supplementation can enhance energy production, particularly under stress conditions such as ischemia and heart failure. The distribution, biosynthesis, and regulation of ribose in mammalian systems remain poorly understood. To explore intracellular ribose dynamics, we developed a genetically encoded fluorescence resonance energy transfer (FRET) sensor using ribose binding protein (RBP) and enhanced cyan and yellow fluorescent proteins (FPs). The RIBOsensor, which positions one FP near the active site of RBP, achieves the necessary sensitivity for cellular imaging by increasing the FRET signal upon ribose binding, compared to traditional N- and C-terminal FP orientations. This sensor rapidly, reversibly, and selectively detects labile ribose in live cells-enabling longitudinal studies-and can be employed for intracellular ribose quantitation, which provides a valuable tool for investigating ribose transport and metabolism in normal and disease states.

Strong protection by bazedoxifene against chemically-induced ferroptotic neuronal death in vitro and in vivo

Ferroptosis, a form of regulated cell death associated with glutathione depletion and excess lipid peroxidation, can be induced in cultured cells by chemicals (e.g., erastin and RSL3). It has been shown that protein disulfide isomerase (PDI) is a mediator of chemically-induced ferroptosis and also a crucial target for ferroptosis protection. The present study reports that bazedoxifene (BAZ), a selective estrogen receptor modulator, is an inhibitor of PDI and can strongly rescue neuronal cells from chemically-induced oxidative ferroptosis. We find that BAZ can directly bind to PDI and inhibit its catalytic activity. Computational modeling analysis reveals that BAZ forms a hydrogen bond with PDI's His256 residue. Inhibition of PDI by BAZ markedly reduces iNOS and nNOS dimerization (i.e., catalytic activation) and NO accumulation, and these effects of BAZ are associated with reductions in cellular ROS and lipid-ROS and protection against chemically-induced ferroptosis. In addition, the direct antioxidant activity of BAZ may also partially contribute to its protection against chemically-induced ferroptosis. In vivo animal experiments show that mice treated with BAZ are strongly protected against kainic acid-induced oxidative hippocampal neuronal injury and memory deficits. Together, these results reveal that BAZ is a potent inhibitor of PDI and can strongly protect against chemically-induced ferroptosis in hippocampal neurons both in vitro and in vivo. This work provides evidence for an estrogen receptor-independent, PDI-mediated novel mechanism of neuroprotection by BAZ.