A smooth particle mesh Ewald method

Comparison of two peroxidases with high potential for biotechnology applications - HRP vs. APEX2

Peroxidases are essential elements in many biotechnological applications. An especially interesting concept involves split enzymes, where the enzyme is separated into two smaller and inactive proteins that can dimerize into a fully active enzyme. Such split forms were developed for the horseradish peroxidase (HRP) and ascorbate peroxidase (APX) already. Both peroxidases have a high potential for biotechnology applications. In the present study, we performed biophysical comparisons of these two peroxidases and their split analogues. The active site availability is similar for all four structures. The split enzymes are comparable in stability with their native analogues, meaning that they can be used for further biotechnology applications. Also, the tertiary structures of the two peroxidases are similar. However, differences that might help in choosing one system over another for biotechnology applications were noticed. The main difference between the two systems is glycosylation which is not present in the case of APX/sAPEX2, while it has a high impact on the HRP/sHRP stability. Further differences are calcium ions and cysteine bridges that are present only in the case of HRP/sHRP. Finally, computational results identified sAPEX2 as the systems with the smallest structural variations during molecular dynamics simulations showing its dominant stability comparing to other simulated proteins. Taken all together, the sAPEX2 system has a high potential for biotechnological applications due to the lack of glycans and cysteines, as well as due to high stability.

Cyclodextrins: Establishing building blocks for AI-driven drug design by determining affinity constants in silico

Cyclodextrins (CDs) are cyclic carbohydrate polymers that hold significant promise for drug delivery and industrial applications. Their effectiveness depends on their ability to encapsulate target molecules with strong affinity and specificity, but quantifying affinities in these systems accurately is challenging for a variety of reasons. Computational methods represent an exceptional complement to in vitro assays because they can be employed for existing and hypothetical molecules, providing high resolution structures in addition to a mechanistic, dynamic, kinetic, and thermodynamic characterization. Here, we employ potential of mean force (PMF) calculations obtained from guided metadynamics simulations to characterize the 1:1 inclusion complexes between four different modified βCDs, with different type, number, and location of substitutions, and two sterol molecules (cholesterol and 7-ketocholesterol). Our methods, validated for reproducibility through four independent repeated simulations per system and different post processing techniques, offer new insights into the formation and stability of CD-sterol inclusion complexes. A systematic distinct orientation preference where the sterol tail projects from the CD's larger face and significant impacts of CD substitutions on binding are observed. Notably, sampling only the CD cavity's wide face during simulations yielded comparable binding energies to full-cavity sampling, but in less time and with reduced statistical uncertainty, suggesting a more efficient approach. Bridging computational methods with complex molecular interactions, our research enables predictive CD designs for diverse applications. Moreover, the high reproducibility, sensitivity, and cost-effectiveness of the studied methods pave the way for extensive studies of massive CD-ligand combinations, enabling AI algorithm training and automated molecular design.

DeepSP: Deep learning-based spatial properties to predict monoclonal antibody stability

Therapeutic antibody development faces challenges due to high viscosities and aggregation tendencies. The spatial charge map (SCM) and spatial aggregation propensity (SAP) are computational techniques that aid in predicting viscosity and aggregation, respectively. These methods rely on structural data derived from molecular dynamics (MD) simulations, which are computationally demanding. DeepSCM, a deep learning surrogate model based on sequence information to predict SCM, was recently developed to screen high-concentration antibody viscosity. This study further utilized a dataset of 20,530 antibody sequences to train a convolutional neural network deep learning surrogate model called Deep Spatial Properties (DeepSP). DeepSP directly predicts SAP and SCM scores in different domains of antibody variable regions based solely on their sequences without performing MD simulations. The linear correlation coefficient between DeepSP scores and MD-derived scores for 30 properties achieved values between 0.76 and 0.96 with an average of 0.87. DeepSP descriptors were employed as features to build machine learning models to predict the aggregation rate of 21 antibodies, and the performance is similar to the results obtained from the previous study using MD simulations. This result demonstrates that the DeepSP approach significantly reduces the computational time required compared to MD simulations. The DeepSP model enables the rapid generation of 30 structural properties that can also be used as features in other research to train machine learning models for predicting various antibody stability using sequences only. DeepSP is freely available as an online tool via https://deepspwebapp.onrender.com and the codes and parameters are freely available at https://github.com/Lailabcode/DeepSP.

In silico and in vivo analysis reveal impact of c-Myc tag in FMC63 scFv-CD19 protein interface and CAR-T cell efficacy

Anti-CD19 CAR-T cell therapy represents a breakthrough in the treatment of B-cell malignancies, and it is expected that this therapy modality will soon cover a range of solid tumors as well. Therefore, a universal cheap and sensitive method to detect CAR expression is of foremost importance. One possibility is the use of epitope tags such as c-Myc, HA or FLAG tags attached to the CAR extracellular domain, however, it is important to determine whether these tags can influence binding of the CAR with its target molecule. Here, we conducted in-silico structural modelling of an FMC63-based anti-CD19 single-chain variable fragment (scFv) with and without a c-Myc peptide tag added to the N-terminus portion and performed molecular dynamics simulation of the scFv with the CD19 target. We show that the c-Myc tag presence in the N-terminus portion does not affect the scFv's structural equilibrium and grants more stability to the scFv. However, intermolecular interaction potential (IIP) analysis reveals that the tag can approximate the complementarity-determining regions (CDRs) present in the scFv and cause steric impediment, potentially disturbing interaction with the CD19 protein. We then tested this possibility with CAR-T cells generated from human donors in a Nalm-6 leukemia model, showing that CAR-T cells with the c-Myc tag have overall worse antitumor activity, which was also observed when the tag was added to the C-terminus position. Ultimately, our results suggest that tag addition is an important aspect of CAR design and can influence CAR-T cell function, therefore its use should be carefully considered.

Avian cryptochrome 4 binds superoxide

Flavin-binding cryptochromes are blue-light sensitive photoreceptors that have been implicated with magnetoreception in some species. The photocycle involves an intra-protein photo-reduction of the flavin cofactor, generating a magnetosensitive radical pair, and its subsequent re-oxidation. Superoxide (O2 • - ) is generated in the re-oxidation with molecular oxygen. The resulting O2 • - -containing radical pairs have also been hypothesised to underpin various magnetosensitive traits, but due to fast spin relaxation when tumbling in solution would require immobilisation. We here describe our insights in the binding of superoxide to cryptochrome 4 from C. livia based on extensive all-atom molecular dynamics studies and density-functional theory calculations. The positively charged "crypt" region that leads to the flavin binding pocket transiently binds O2 • - at 5 flexible binding sites centred on arginine residues. Typical binding times amounted to tens of nanoseconds, but exceptional binding events extended to several hundreds of nanoseconds and slowed the rotational diffusion, thereby realising rotational correlation times as large as 1 ns. The binding sites are particularly efficient in scavenging superoxide escaping from a putative generation site close to the flavin-cofactor, possibly implying a functional relevance. We discuss our findings in view of a potential magnetosensitivity of biological flavin semiquinone/superoxide radical pairs.

Deciphering inhibitory activity of marine algae Ecklonia cava phlorotannins against SARS CoV-2 main protease: A coupled in-silico docking and molecular dynamics simulation study

The onset of COVID-19 due to the SARS CoV-2 virus has spurred an urgent need for potent therapeutics and vaccines to combat this global pandemic. The main protease (Mpro) of the virus, crucial in its replication, has become a focal point in developing anti-COVID-19 drugs. The cysteine protease Mpro in SARS CoV-2 bears a significant resemblance to the same protease found in SARS CoV-1. Previous research highlighted phlorotannins derived from Ecklonia cava, an edible marine algae, as inhibitors of SARS CoV-1 Mpro activity. However, it remains unclear whether these marine-derived phlorotannins also exert a similar inhibitory effect on SARS CoV-2 Mpro. To unravel this, our study utilized diverse in-silico methodologies. We explored the pharmacological potential of various phlorotannins (phloroglucinol, triphloretol-A, eckol, 2-phloroeckol, 7-phloroeckol, fucodiphloroethol G, dieckol, and phlorofucofuroeckol-A) and assessed their binding efficacies alongside established Mpro inhibitors (N3 and lopinavir) through molecular docking studies. Among these compounds, five phlorotannins (eckol, 2-phloroeckol, 7-phloroeckol, dieckol, and phlorofucofuroeckol-A) exhibited potent binding affinities comparable to or surpassing N3 and lopinavir, interacting especially with the catalytic residues His41 and Cys145 of Mpro. Moreover, molecular dynamics simulations revealed that these five Mpro-phlorotannin complexes displayed enhanced stability and maintained comparable or slightly reduced compactness. They exhibited reduced conformational changes and increased expansion relative to the Mpro-N3 and/or Mpro-lopinavir complex. Our MM-GBSA analysis further supported these findings. Overall, our investigation highlights the potential of these five phlorotannins in inhibiting the proteolytic function of SARS CoV-2 Mpro, offering promise for anti-COVID-19 drug development.

Glycosaminoglycans exhibit distinct interactions and signaling with BMP2 according to their nature and localization

The role of glycosaminoglycans (GAGs) in modulating bone morphogenetic protein (BMP) signaling represents a recent and underexplored area. Conflicting reports suggest a dual effect: some indicate a positive influence, while others demonstrate a negative impact. This duality suggests that the localization of GAGs (either at the cell surface or within the extracellular matrix) or the specific type of GAG may dictate their signaling role. The precise sulfation patterns of heparan sulfate (HS) responsible for BMP2 binding remain elusive. BMP2 exhibits a preference for binding to HS over other GAGs. Using well-characterized biomaterials mimicking the extracellular matrix, our research reveals that HS promotes BMP2 signaling in the extracellular space, contrary to chondroitin sulfate (CS), which enhances BMP2 bioactivity at the cell surface. Further observations indicate that a central IdoA (2S)-GlcNS (6S) tri-sulfated motif within HS hexasaccharides enhances binding. Nevertheless, BMP2 exhibits a degree of adaptability to various HS sulfation types and sequences. Molecular dynamic simulations attribute this adaptability to the BMP2 N-terminal end flexibility. Our findings illustrate the complex interplay between GAGs and BMP signaling, highlighting the importance of localization and specific sulfation patterns. This understanding has implications for the development of biomaterials with tailored properties for therapeutic applications targeting BMP signaling pathways.

Repurposing of antimycobacterium drugs for COVID-19 treatment by targeting SARS CoV-2 main protease: An in-silico perspective

The global mortality rate has been significantly impacted by the COVID-19 pandemic, caused by the SARS CoV-2 virus. Although the pursuit for a potent antiviral is still in progress, experimental therapies based on repurposing of existing drugs is being attempted. One important therapeutic target for COVID-19 is the main protease (Mpro) that cleaves the viral polyprotein in its replication process. Recently minocycline, an antimycobacterium drug, has been successfully implemented for the treatment of COVID-19 patients. But it's mode of action is still far from clear. Furthermore, it remains unresolved whether alternative antimycobacterium drugs can effectively regulate SARS CoV-2 by inhibiting the enzymatic activity of Mpro. To comprehend these facets, eight well-established antimycobacterium drugs were put through molecular docking experiments. Four of the antimycobacterium drugs (minocycline, rifampicin, clofazimine and ofloxacin) were selected by comparing their binding affinities towards Mpro. All of the four drugs interacted with both the catalytic residues of Mpro (His41 and Cys145). Additionally, molecular dynamics experiments demonstrated that the Mpro-minocyline complex has enhanced stability, experiences reduced conformational fluctuations and greater compactness than other three Mpro-antimycobacterium and Mpro-N3/lopinavir complexes. This research furnishes evidences for implementation of minocycline against SARS CoV-2. In addition, our findings also indicate other three antimycobacterium/antituberculosis drugs (rifampicin, clofazimine and ofloxacin) could potentially be evaluated for COVID-19 therapy.

Supramolecular citrate poly allylamine hydrochloride nanoparticles for citrate delivery and calcium oxalate nanocrystal dissolution

HYPOTHESIS

Renal calculi (kidney stones) are mainly made by calcium oxalate and can cause different complications including malfunction of the kidney. The most important urinary stone inhibitors are citrate molecules. Unfortunately, the amount of citrate reaching the kidney after oral ingestion is low. We hypothesized that nanoparticles of polyallylamine hydrochloride (CIT-PAH) carrying citrate ions could simultaneously deliver citrates while PAH would complex oxalate triggering dissolution and removal of CaOx nanocrystals.

EXPERIMENTS

We successfully prepared nanoparticles of citrate ions with polyallylamine hydrochloride (CIT-PAH), PAH with oxalate (OX-PAH) and characterize them by Small Angle X ray Scattering (SAXS), Transmission Electron Microscopy (TEM), Dynamic Light Scattering (DLS) and NMR. Dissolution of CaOx nanocrystals in presence of CIT-PAH have been followed with Wide Angle Xray Scattering (WAXS), DLS and Confocal Raman Microscopy. Raman spectroscopy was used to study the dissolution of crystals in synthetic urine samples. The release of citrate from CIT-PAH was followed by diffusion NMR. Molecular dynamics (MD) simulations were carried out to study the interaction of CIT and OX ions with PAH.

FINDINGS

CIT-PAH nanoparticles dissolves CaOx nanocrystals as shown by NMR, DLS, TEM and WAXS in water and by Raman spectroscopy in artificial human urine. WAXS and Raman show that the crystal structure of CaOx disappears in the presence of CIT-PAH. DLS shows that the time required for CaOX dissolution will depend on the concentration of CIT-PAH NPs. NMR proves that citrate ions are released from the CIT PAH NPs during CaOX dissolution, MD simulations showed that oxalates exhibit a stronger interaction for PAH than citrate, explaining the removal of oxalate ions and replacement of the citrate in the polymer nanoparticles.

Molecular dynamics simulations of the interfacial behaviors and photo-oxidation of phytosterol under different emulsion oil content

Phytosterol, recognized for its health benefits, is predominantly extracted from plants and exhibits significantly reduced stability under varying light conditions. Their photooxidation is significantly influenced by emulsion interfaces. This study examined the mechanism of interface structure on phytosterol photooxidation with unparalleled molecular precision, utilizing molecular dynamics simulations and experimental procedures. Hydrogen bonding between the hydroxyl group at the C3 position of phytosterols and water molecules, coupled with van der Waals forces between the hydrophobic regions and the oil phase, induced phytosterol molecules to disperse toward the interface. The elevated polarity of the oil phase, specifically in tributyrin, facilitated the permeation of water molecules into the oil phase. This was achieved by diminishing the emulsion's interfacial tension, thereby fostering the development of more interface or micelles, and accelerating the photooxidation process of phytosterols. These simulations unraveled that the preponderance of phytosterol distribution is localized and oxidized at the oil-water interface.

In silico study on graphene quantum dots modified with various functional groups inhibiting α‑synuclein dimerization

HYPOTHESIS

Graphene quantum dots (GQDs) with various functional groups are hypothesized to inhibit the α-synuclein (αS) dimerization, a crucial step in Parkinson's disease pathogenesis. The potential of differently functionalized GQDs is systematically explored.

EXPERIMENTS

All-atom replica-exchange molecular dynamics simulations (accumulating to 75.6 μs) in explicit water were performed to study the dimerization of the αS non-amyloid component region and the influence of GQDs modified with various functional groups. Conformation ensemble, binding behavior, and free energy analysis were conducted.

FINDINGS

All studied GQDs inhibit β-sheet and backbone hydrogen bond formation in αS dimers, leading to looser oligomeric conformations. Charged GQDs severely impede the growth of extended β-sheets by providing extra contact surface. GQD binding primarily disrupts αS inter-peptide interactions through π-π stacking, CH-π interactions, and for charged GQDs, additionally through salt-bridge and hydrogen bonding interactions. GQD-COO- showed the most optimal inhibitory effect, binding mode, and intensity, which holds promise for the development of nanomedicines targeting amyloid aggregation in neurodegenerative diseases.

PURA and GLUT1: Sweet partners for brain health

PURA, also known as Pur-alpha, is an evolutionarily conserved DNA/RNA-binding protein crucial for various cellular processes, including DNA replication, transcriptional regulation, and translational control. Comprising three PUR domains, it engages with nucleic acids and has a role in protein-protein interactions. The manifestation of PURA syndrome, arising from mutations in the PURA gene, presents neurologically with developmental delay, hypotonia, and seizures. In our prior work from 2018, we highlighted the unique case of a PURA patient displaying hypoglycorrhachia, suggesting a potential association with GLUT1 dysfunction in this syndrome. In this current study, we expand the patient cohort with PURA mutations exhibiting hypoglycorrhachia and aim to unravel the molecular basis of this phenomenon. We established an in vitro model in HeLa cells to modulate PURA expression and investigated GLUT1 function and expression. Our findings indicate that PURA levels directly impact glucose uptake through the functioning of GLUT1, without influencing significantly GLUT1 expression. Moreover, our study reveals evidence for a possible physical interaction between PURA and GLUT1, demonstrated by colocalization and co-immunoprecipitation of both proteins. Computational analyses, employing molecular dynamics, further corroborates these findings, demonstrating that PURA:GLUT1 interactions are plausible, and that the stability of the complex is altered when PURA is truncated and/or mutated. In conclusion, our results suggest that PURA plays a pivotal role in driving the function of GLUT1 for glucose uptake, potentially forming a regulatory complex. Additional investigations are warranted to elucidate the precise mechanisms governing this complex and its significance in ensuring proper GLUT1 function.

Identifying potential Alzheimer's disease therapeutics through GSK-3β inhibition: A molecular docking and dynamics approach

Emerging as a promising drug target for Alzheimer's disease (AD) therapy, glycogen synthase kinase 3β (GSK-3β) has garnered attention. This study sought to rigorously scrutinize a compendium of natural compounds retrieved from the ZINC database through pharmacodynamic experiments, employing a 1 H-indazole-3-carboxamide (INDZ) scaffold, to identify compounds capable of inhibiting the GSK-3β protein. Utilizing a multi-step approach, the study involved pharmacophore analysis, followed by molecular docking to select five promising ligands for further investigation. Subsequently, ESMACS simulations were employed to assess the stability of the ligand-protein interactions. Evaluation of the binding modes and free energy of the ligands revealed that five compounds (2a-6a) exhibited crucial interactions with the active site residues. Furthermore, various methodologies, including hydrogen bond and clustering analyses, were utilized to ascertain their inhibitory potential and elucidate the factors contributing to ligand binding in the protein's active site. The findings from MMPBSA/GBSA analysis indicated that these five selected small molecules closely approached the IC50 value of the reference ligand (OH8), yielding energy values of -34.85, -32.58, -31.71, and -30.39 kcal/mol, respectively. Additionally, an assessment of the interactions using hydrogen bond and dynamic analyses delineated the effective binding of the ligands with the binding pockets in the protein. Through computational analysis, we obtained valuable insights into the molecular mechanisms of GSK-3β, aiding in the development of more potent inhibitors.

Molecular simulations guide immobilization of lipase on nest-like ZIFs with regulatable hydrophilic/hydrophobic surface

The catalytic performance of immobilized lipase is greatly influenced by functional support, which attracts growing interest for designing supports to achieve their promotive catalytic activity. Many lipases bind strongly to hydrophobic surfaces where they undergo interfacial activation. Herein, the behavioral differences of lipases with distinct lid structures on interfaces of varying hydrophobicity levels were firstly investigated by molecular simulations. It was found that a reasonable hydrophilic/hydrophobic surface could facilitate the lipase to undergo interfacial activation. Building on these findings, a novel "nest"-like superhydrophobic ZIFs (ZIFN) composed of hydrophobic ligands was prepared for the first time and used to immobilize lipase from Aspergillus oryzae (AOL@ZIFN). The AOL@ZIFN exhibited 2.0-folds higher activity than free lipase in the hydrolysis of p-Nitrophenyl palmitate (p-NPP). Especially, the modification of superhydrophobic ZIFN with an appropriate amount of hydrophilic tannic acid can significantly improve the activity of the immobilized lipase (AOL@ZIFN-TA). The AOL@ZIFN-TA exhibited 30-folds higher activity than free lipase, and still maintained 82% of its initial activity after 5 consecutive cycles, indicating good reusability. These results demonstrated that nanomaterials with rational arrangement of the hydrophilic/hydrophobic surface could facilitate the lipase to undergo interfacial activation and improve its activity, displaying the potential of the extensive application.

Accurate prediction of dynamic protein-ligand binding using P-score ranking

Protein-ligand binding prediction typically relies on docking methodologies and associated scoring functions to propose the binding mode of a ligand in a biological target. Significant challenges are associated with this approach, including the flexibility of the protein-ligand system, solvent-mediated interactions, and associated entropy changes. In addition, scoring functions are only weakly accurate due to the short time required for calculating enthalpic and entropic binding interactions. The workflow described here attempts to address these limitations by combining supervised molecular dynamics with dynamical averaging quantum mechanics fragment molecular orbital. This combination significantly increased the ability to predict the experimental binding structure of protein-ligand complexes independent from the starting position of the ligands or the binding site conformation. We found that the predictive power could be enhanced by combining the residence time and interaction energies as descriptors in a novel scoring function named the P-score. This is illustrated using six different protein-ligand targets as case studies.

Modeling solvent effects and convergence of 31P-NMR shielding calculations with COBRAMM

Solvent effects on 31P-NMR parameters for triphenylphosphine oxide and triphenylphosphine in chloroform have been extensively investigated by testing different solvation models. The solvent is described implicitly, mixed implicitly/explicitly, and using full explicit models. Polarizable continuum model (PCM), molecular dynamic (MD) simulations, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations are used to disclose the effects of solute/solvent interactions and, more generally, the role of the embedding in NMR simulations. The results show the beneficial effect of carrying out QM/MM optimizations on top of geometries directly extracted from classical MD simulations, used to ensure representative conformational sampling. The nuclear shielding convergence has been tested against a different number of snapshots and with the inclusion of solvent shells into the QM region. An automated MD//QM/MM//GIAO protocol, implemented in the COBRAMM package, is here proposed and tested on trimethyl phosphite showing that our approach boosts the convergence of nuclear shielding satisfactorily. The present work aims to be a stepping-stone to assess proper QM/MM computational strategies in simulating chemical shifts in non-homogeneous systems like supramolecular and biological systems.

Computational and experimental examinations of new antitumor palladium(II) complex: CT-DNA-/BSA-binding, in-silico prediction, DFT perspective, docking, molecular dynamics simulation and ONIOM

Since the design of metal complexes with better biological activities is important, herein a new palladium(II) complex bearing en and acac (en and acac stand for ethylenediamine and acetylacetonato, respectively) as its ligands, [Pd(en)(acac)]NO3 complex, was synthesized and fully characterized. Quantum chemical computations of the palladium(II) complex were done via DFT/B3LYP method. Cytotoxicity activity of the new compound on leukemia cell line (K562) was assessed via MTT method. The findings indicated that the metal complex has remarkable cytotoxic effect than cisplatin. OSIRIS DataWarrior software was employed to calculate in-silico physicochemical and toxicity parameters of the synthesized complex which rendered significant results. To comprehend the interaction type of new metal compound with macromolecules, the in depth investigation of interaction of mentioned complex with CT-DNA and BSA was accomplished by fluorescence, UV-Visible absorption spectroscopy, viscosity measurement, gel electrophoresis, FRET analysis and circular dichroism (CD) spectroscopy. On the other hand, computational molecular docking was carried out and the obtained data demonstrated that H-bond and van der Waals forces are the dominant forces for the binding of the compound to the mentioned biomolecules. Molecular dynamics simulation was also done and confirmed the stability of best docked pose of palladium(II) complex inside DNA or BSA over the time and in presence of water solvent. Also, Our own N-layered Integrated molecular Orbital and molecular Mechanics (ONIOM) methodology based on the hybridization of quantum mechanics and molecular mechanics (QM/MM) methodology was accomplished to inquire about binding of Pd(II) complex with DNA or BSA.HIGHLIGHTSNew biologically active Pd(II) complex was synthesized and characterized.The in silico studies of the designed complex and its ligands were accomplished by OSIRIS DataWarrior softwareInteraction with CT-DNA and BSA was assessed by various spectroscopic methods.Molecular docking simulation supported the interaction with both macromolecules.Based on ONIOM analysis, the structures of the complex and biomolecules are altered after binding. Communicated by Ramaswamy H. Sarma.

Exploring the interaction of a potent anti-cancer drug Selumetinib with bovine serum albumin: Spectral and computational attributes

The binding of drugs to plasma proteins determines its fate within the physiological system, hence profound understanding of its interaction within the bloodstream is important to understand its pharmacodynamics and pharmacokinetics and thereby its therapeutic potential. In this regard, our work delineates the mechanism of interaction of Selumetinib (SEL), a potent anti-cancer drug showing excellent effect against multiple solid tumors, with plasma protein bovine serum albumin (BSA), using methods such as absorption, steady-state fluorescence, time-resolved, fluorescence resonance energy transfer, Fourier transform infrared spectra (FTIR), circular dichroism (CD), synchronous and 3D-fluorescence, salt fluorescence, molecular docking and molecular dynamic simulations. The BSA fluorescence intensity was quenched with increasing concentration of SEL which indicates interactions of SEL with BSA. Stern-Volmer quenching analysis and lifetime studies indicate the involvement of dynamic quenching. However, some contributions from the static quenching mechanism could not be ruled out unambiguously. The association constant was found to be 5.34 × 105 M-1 and it has a single binding site. The Förster distance (r) indicated probable energy transmission between the BSA and SEL. The positive entropy changes and enthalpy change indicate that the main interacting forces are hydrophobic forces, also evidenced by the results of molecular modeling studies. Conformation change in protein framework was revealed from FTIR, synchronous and 3D fluorescence and CD studies. Competitive binding experiments as well as docking studies suggest that SEL attaches itself to site I (subdomain IIA) of BSA where warfarin binds. Molecular dynamic simulations indicate the stability of the SEL-BSA complex. The association energy between BSA and SEL is affected in the presence of different metals differently.

A study of hydrophobic domain formation of polymeric drug precipitation inhibitors in aqueous solution

Despite the widespread use of polymers as precipitation inhibitors in supersaturating drug formulations, the current understanding of their mechanisms of action is still incomplete. Specifically, the role of hydrophobic drug interactions with polymers by considering possible supramolecular conformations in aqueous dispersion is an interesting topic. Accordingly, this study investigated the tendency of polymers to create hydrophobic domains, where lipophilic compounds may nest to support drug solubilisation and supersaturation. Fluorescence spectroscopy with the environment-sensitive probe pyrene was compared with atomistic molecular dynamics simulations of the model drug fenofibrate (FENO). Subsequently, kinetic drug supersaturation and thermodynamic solubility experiments were conducted. As a result, the different polymers showed hydrophobic domain formation to a varying degree and the molecular simulations supported interpretation of fluorescence spectroscopy data. Molecular insights were gained into the conformational structure of how the polymers interacted with FENO in solution phase, which apart from nucleation and crystal growth effects, determined drug concentrations in solution. Notable was that even at the lowest polymer concentration of 0.01 %, w/v, there were polymer-specific solubilisation effects of FENO observed and the resulting reduction in apparent drug supersaturation provided relevant knowledge both from a mechanistic and practical perspective.

Structure-based virtual screening, molecular docking, and molecular dynamics simulation approaches for identification of new potential inhibitors of class a β-lactamase enzymes

Bacteria are smart organisms that create drug resistance by decreasing the effect of antibiotics in different ways, such as secretion of the β-lactamase enzymes. Finding the compounds that can act as the inhibitors of these enzymes is a great help in reducing drug resistance and treat all types of infections. In this study, using molecular docking and molecular dynamics simulation techniques, we introduced two Relebactam substructures as new inhibitors of class A β-lactamase enzymes. Results of molecular docking show that the conformation of these two compounds in the active site of class A β-lactamase enzymes has a good match with Relebactam and their binding affinity to enzymes is equal to or better than Relebactam. Results showed a good tendency for binding and the formation of van der Waals and hydrogen interactions between the desired compounds and the β-lactamase enzymes. The results of the analysis of the molecular dynamics simulation trajectories showed that in the presence of the desired compounds, the second structures of the enzymes did not undergo many changes and in none of the systems, the binding of the compounds to the enzyme did not cause much instability, and in most cases made the structure stable. The hydrogen bonds were stable during the simulation time and in most cases, the new compounds formed more hydrogen bonds and had better binding affinity than Relebactam confirms the docking results. The results of this study can be helpful in designing new beta-lactamase inhibitors and new treatment methods to deal with drug resistance.Communicated by Ramaswamy H. Sarma.

Molecular dynamics simulations of choline chloride and ascorbic acid deep eutectic solvents: Investigation of structural and dynamics properties

Deep eutectic solvents (DESs) composed of choline chloride (ChCl) and ascorbic acid (AA) were investigated using the molecular dynamics (MD) simulations. The analyses of the configuration, radial distribution function (RDFs), coordination number, spatial distribution function (SDFs), interaction energies, hydrogen bond number, and self-diffusion coefficient of the ChCl/AA binary systems of different concentrations showed that the stability of the hydrogen bond network and the mutual attraction between systems were the strongest at the experimental eutectic concentration (molar ratio of 2:1). In our simulated temperature range from 303.15 to 353.15 K, the hydrogen bonding network of ChCl/AA DES does not undergo considerable alterations, indicating that its stability was insensitive to temperature. In addition, the influence of the water content on the ChCl/AA DES system was further investigated. The simulated results revealed that the water molecules could disrupt the formation of the hydrogen bonding network by occupyin positions that are essential for the formation of hydrogen bonds within the DES system.

Structural bases for stoichiometry-selective calcium potentiation of a neuronal nicotinic receptor

BACKGROUND AND PURPOSE

α4β2 nicotinic acetylcholine (nACh) receptors assemble in two stoichiometric forms, one of which is potentiated by calcium. The sites of calcium binding that underpin potentiation are not known.

EXPERIMENTAL APPROACH

To identify calcium binding sites, we applied cryo-electron microscopy (cryo-EM) and molecular dynamics (MD) simulations to each stoichiometric form of the α4β2 nACh receptor in the presence of calcium ions. To test whether the identified calcium sites are linked to potentiation, we generated mutants of anionic residues at the sites, expressed wild type and mutant receptors in clonal mammalian fibroblasts, and recorded ACh-elicited single-channel currents with or without calcium.

KEY RESULTS

Both cryo-EM and MD simulations show calcium bound to a site between the extracellular and transmembrane domains of each α4 subunit (ECD-TMD site). Substituting alanine for anionic residues at the ECD-TMD site abolishes stoichiometry-selective calcium potentiation, as monitored by single-channel patch clamp electrophysiology. Additionally, MD simulation reveals calcium association at subunit interfaces within the extracellular domain. Substituting alanine for anionic residues at the ECD sites reduces or abolishes stoichiometry-selective calcium potentiation.

CONCLUSIONS AND IMPLICATIONS

Stoichiometry-selective calcium potentiation of the α4β2 nACh receptor is achieved by calcium association with topographically distinct sites framed by anionic residues within the α4 subunit and between the α4 and β2 subunits. Stoichiometry-selective calcium potentiation could result from the greater number of calcium sites in the stoichiometric form with three rather than two α4 subunits. The results are relevant to modulation of signalling via α4β2 nACh receptors in physiological and pathophysiological conditions.

Pyroglutamylation modulates electronic properties and the conformational ensemble of the amyloid β-peptide

Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by the formation of extracellular amyloid-β (Aβ) plaques. The underlying cause of AD is unknown, however, post-translational modifications (PTMs) of Aβ have been found in AD patients and are thought to play a role in protein aggregation. One such PTM is pyroglutamylation, which can occur at two sites in Aβ, Glu3 and Glu11. This modification of Aβ involves the truncation and charge-neutralization of N-terminal glutamate, causing Aβ to become more hydrophobic and prone to aggregation. The molecular mechanism by which the introduction of pyroglutamate (pE) promotes aggregation has not been determined. To gain a greater understanding of the role that charge neutralization and truncation of the N-terminus plays on Aβ conformational sampling, we used the Drude polarizable force field (FF) to perform molecular dynamics simulations on AβpE3-42 and AβpE11-42 and comparing their properties to previous simulations of Aβ1-42. The Drude polarizable FF allows for a more accurate representation of electrostatic interactions, therefore providing novel insights into the role that charge plays in protein dynamics. Here, we report the parametrization of pE in the Drude polarizable FF and the effect of pyroglutamylation on Aβ. We found that AβpE3-42 and AβpE11-42 alter the permanent and induced dipoles of the peptide. Specifically, we found that AβpE3-42 and AβpE11-42 have modification-specific backbone and sidechain polarization response and perturbed solvation properties that shift the Aβ conformational ensemble.

Structural packing of the non-amyloid component core domain in α-synuclein plays a role in the stability of the fibrils

Parkinson's disease (PD) is one of many neurodegenerative diseases. The protein associated with PD is α-synuclein (AS). Aggregation of AS protein into oligomers, protofilaments, and finally to fibrils yields to the development of PD. The aggregation process of AS leads to the formation of polymorphic AS fibrils. Herein, we compared four polymorphic full-length AS1-140 fibrils, using extensive computational tools. The main conclusion of this study emphasizes the role of the structurally packed non-amyloid component (NAC) core domain in AS fibrils. Polymorphic AS fibrils that presented a packed NAC core domain, exhibited more β-sheets and fewer fluctuations in the NAC domain. Hence, these AS fibrils are more stable and populated than the AS fibrils, by which the NAC domains are more exposed, more fluctuate and less packed in the fibrillary structure. Therefore, this study emphasizes the importance of the NAC domain packing in the morphology of AS fibrils. The results obtained in this study will initiate future studies to develop compounds to prevent and inhibit AS aggregation.

Effect of quercetin on the protein-substrate interactions in SIRT6: Insight from MD simulations

SIRT6 is of interest for its promising effect in the treatment of aging-related diseases. Studies have shown quercetin (QUE) and its derivatives have varying degrees of effect on the catalytic effect of SIRT6. In the research, the effect of QUE on the protein-substrate interaction in the SIRT6-mediated mono-ADP ribosylation system was investigated by conventional molecular dynamics (MD) simulations combined with MM/PBSA binding free energy calculations. The results show that QUE can bind stably to SIRT6 with the binding energy of -22.8 kcal/mol and further affect the atomic interaction between SIRT6 and NAD+ (or H3K9), resulting in an increased affinity between SIRT6-NAD+ and decreased SIRT6-H3K9 binding capacity. At the same time, the binding of QUE can also alter some structural characteristics of the protein, with large shifts occurring in the residue regions involving the N-terminal (residues 1-27), Rossmann fold regions (residues 55-92), and ZBD (residues 164-179). Thus, QUE shows great potential as a scaffold for the design of novel potent SIRT6 modulators.

Insights into the mechanism of peptide fibril growth on gold surface

Understanding the formation of β-fibrils over the gold surface is of paramount interest in nano-bio-medicinal Chemistry. The intricate mechanism of self-assembly of neurofibrillogenic peptides and their growth over the gold surface remains elusive, as experiments are limited in unveiling the microscopic dynamic details, in particular, at the early stage of the peptide aggregation. In this work, we carried out equilibrium molecular dynamics and enhanced sampling simulations to elucidate the underlying mechanism of the growth of an amyloid-forming sequence of tau fragments over the gold surface. Our results disclose that the collective intermolecular interactions between the peptide chains and peptides with the gold surface facilitate the peptide adsorption, followed by integration, finally leading to the fibril formation.

Identification of pseudobaptigenin as a novel polyphenol-based multi-target antagonist of different hormone receptors for breast cancer therapeutics

Breast cancer (BC) is one of the most prevalent cancers in the world and is one of the major reasons for the death of women worldwide. BC is majorly categorized based on the presence or absence of three cell receptors ER, PR and HER2. The latest treatment for BC involves interfering with the production and action of hormones such as estrogen and progesterone. These hormones bind with receptors such as ER and PR and enhance the growth and proliferation of the BC cells. Although the available are effective, the increasing resistance and side effects related to hormonal imbalance are significant and hence there is a need for designing. On the other hand, plant-derivative products have gained a lot of popularity for their promising anti-cancerous activities. Polyphenols are one such group of plant derivatives that have proven to be useful against cancer. In the present study, an in-silico approach was used to search for a polyphenol that can inhibit ER. In this work, a total of 750 polyphenols were taken into consideration. This number was narrowed down to 55, based on their ADMET properties. These 55 polyphenols were then docked to the receptors, ER, PR and HER2. The molecular docking was followed by Molecular Dynamics (MD) simulations. Based on molecular docking and MD simulation results it was concluded that Pseudobaptigenin has the potential to be an inhibitor of ER, PR and HER2.Communicated by Ramaswamy H. Sarma.

In silico modelling of ciprofloxacin specific aptamer for the development of high-performance biosensor

Ciprofloxacin (CFX), a widely used fluoroquinolone antibiotic, is critical in healthcare settings for treating patients. However, improper treatment of wastewater from these facilities can lead to environmental contamination with CFX. This underscores the need for an efficient, straightforward method for early detection. In this study, a DNA aptamer was selected through a hierarchical docking workflow, and the stability and interactions were assessed by Molecular Dynamics (MD) simulation. The aptamer-CFX complex that showed the most promise had a docking score of -8.596 kcal/mol and was further analyzed using MD simulation and MM/PBSA. Based on the overall results, the identified ssDNA sequence length of 60 nt (CAGCGCTAGGGCTTTTAGCGTAATGGGTAGGGTGGTGCGGTGCAGATATCGGAATTGGTG) was immobilized over a gold transducer surface through the self-assembled monolayer (SAM; Au-S-ssDNA) method. The ssDNA-modified surface has demonstrated a high affinity towards CFX, which is confirmed by cyclic voltammogram (CV) and electrochemical impedance spectroscopy measurements (EIS). The DNA-aptamer modified electrode demonstrated a good linear range (10 × 10-9 - 200 × 10-9 M), detection limit (1.0 × 10-9 M), selectivity, reproducibility, and stability. The optimized DNA-aptamer-based CFX sensor was further utilized for the accurate determination of CFX with good recoveries in real samples.

Nanostructured lipopeptide-based membranomimetics for stabilizing bacteriorhodopsin

Nanostructured 7-9-residue cyclic and unstructured lipopeptide-based facial detergents have been engineered to stabilize the model integral membrane protein, bacteriorhodopsin. Formation of a cylindrical-type micelle assembly induced by facial amphipathic lipopeptides resembles a biological membrane more effectively than conventional micelles. The hydrophobic face of this cylindrical-type micelle provides extended stability to the membrane protein and the hydrophilic surface interacts with an aqueous environment. In our present study, we have demonstrated experimentally and computationally that lipopeptide-based facial detergents having an unstructured or β-turn conformation can stabilize membrane proteins. However, constrained peptide detergents can provide enhanced stability to bacteriorhodopsin. In this study, we have computationally examined the structural stability of bacteriorhodopsin in the presence of helical, beta-strand, and cyclic unstructured peptide detergents, and conventional detergent-like peptides. Our study demonstrates that optimal membranomimetics (detergents) for stabilizing a specific membrane protein can be screened based on the following criteria: (i) hydrodynamic radii of the self-assembled peptide detergents, (ii) stability assay of detergent-encased membrane proteins, (iii) percentage covered area of detergent-encased membrane proteins obtained computationally and (iv) protein-detergent interaction energy.

A Membrane-Assisted Mechanism for the Release of Ceramide from the CERT START Domain

Ceramide transfer protein CERT is the mediator of nonvesicular transfer of ceramide from the ER to Golgi. In CERT, START is the domain responsible for the binding and transport of ceramide. A wealth of structural data has revealed a helix-grip fold surrounding a large hydrophobic cavity holding the ceramide. Yet, little is known about the mechanisms by which START releases the ceramide through the polar region and into the packed environment of cellular membranes. As such events do not lend themselves easily to experimental investigations, we used multiple unbiased microsecond-long molecular simulations. We propose a membrane-assisted mechanism in which the membrane acts as an allosteric effector initiating the release of ceramide and where the passage of the ceramide acyl chains is facilitated by the intercalation of a single phosphatidylcholine lipid in the cavity, practically greasing the ceramide way out. We verify using free energy calculation and experimental lipidomics data that CERT forms stable complexes with phosphatidylcholine lipids, in addition to ceramide, thus providing validation for the proposed mechanism.

In vitro antimicrobial, antibiofilm photodynamic activity, and molecular dynamic simulations of tetra-cationic porphyrinmembrane interactions against foodborne microorganisms

This manuscript presents a new report on the in vitro antimicrobial photo-inactivation of foodborne microorganisms (Salmonella spp. and Listeria monocytogenes) using tetra-cationic porphyrins. Isomeric tetra-cationic porphyrins (3MeTPyP, 4MeTPyP, 3PtTPyP, and 4PtTPyP) were tested, and antimicrobial activity assays were performed at specific photosensitizer concentrations under dark and white-light LED irradiation conditions. Among the tested bacterial strains, 4MeTPyP exhibited the highest efficiency, inhibiting bacterial growth within just 60 min at low concentrations (17.5 μM). The minimal inhibitory concentration of 4MeTPyP increased when reactive oxygen species scavengers were present, indicating the significant involvement of singlet oxygen species in the photooxidation mechanism. Furthermore, the checkerboard assay testing the association of 4MeTPyP showed an indifferent effect. Atomic force microscopy analyses and dynamic simulations were conducted to enhance our understanding of the interaction between this porphyrin and the strain's membrane.

Orientational dynamics of the water layer adjacent to Au surface accelerated by polarization effect

The orientation and rearrangement of water on a gold electrode significantly influences its physicochemical heterogeneous performance. Despite numerous experimental and theoretical studies aimed at uncovering the structural characteristics of interfacial water, the orientational behavior resulting from electrode-induced rearrangements remains a subject of ongoing debate. Here, we employed molecular dynamics simulations to investigate the adaptive structure and dynamics properties of interfacial water on Au(111) and Au(100) surfaces by considering a polarizable model for Au atoms in comparison with the non-polarizable model. Compared to the nonpolarizable systems, the polarization effect can enhance the interaction between water molecules and the gold surface. Unexpectedly, the rotational dynamics directly associated with the orientational behavior of water adjacent to the gold surface is accelerated, thereby reducing the hydrogen bond lifetime. The underlying mechanism for this anomalous phenomenon originates from the polarization effect, which induces the attraction of the positive hydrogen atoms to the surface by the negative image charge. This leads to a change in orientation that disrupts the hydrogen bonds in the first water layer and subsequently accelerates reorientation dynamics of water molecules adjacent to the gold surface. These results shed light on the intricate interplay between polarization effects and water molecule dynamics on metal surfaces, establishing the foundation for the rational regulation of the orientation of interfacial water.

Structural basis of tolvaptan binding to the vasopressin V2 receptor

The vasopressin V2 receptor (V2R) is a validated therapeutic target for autosomal dominant polycystic kidney disease (ADPKD), with tolvaptan being the first FDA-approved antagonist. Herein, we used Gaussian accelerated molecular dynamics simulations to investigate the spontaneous binding of tolvaptan to both active and inactive V2R conformations at the atomic-level. Overall, the binding process consists of two stages. Tolvaptan binds initially to extracellular loops 2 and 3 (ECL2/3) before overcoming an energy barrier to enter the pocket. Our simulations result highlighted key residues (e.g., R181, Y205, F287, F178) involved in this process, which were experimentally confirmed by site-directed mutagenesis. This work provides structural insights into tolvaptan-V2R interactions, potentially aiding the design of novel antagonists for V2R and other G protein-coupled receptors.

Repurposing of therapeutic antibodies against dengue virus envelope protein receptor binding domain

Dengue virus (DENV) is the leading cause of numerous deaths every year due to its high infectivity. In this study we have tried to target the DENV envelope protein receptor binding domain, the region crucial for binding to host receptors which leads to membrane fusion and entry of the viral genome into the human host cell. We have taken 13 known FDA approved antiviral therapeutic antibodies from therapeutic antibody database and tried to repurpose them against the DENV envelope protein. Based on the humanness analysis, 10 antibodies were selected against the DENV envelope protein. Computational affinity maturation of the 10 selected antibodies was performed to increase their binding affinity and specificity against the DENV envelope protein which ultimately led to 8 mutant antibodies having better binding affinity than the native ones. Molecular Dynamics (MD) simulation shows that, the stability of the complexes involving both the native and mutant antibodies were found to be the same although the binding energy between the protein and the respective antibodies was seen to improve upon computational affinity maturation. Contact analyses show similar robustness of the interaction for both the mutant and native antibodies during complex formation with the DENV envelope protein. This has led to the selection of total 18 antibodies including 10 natural and 8 affinity matured mutants which have a high probability of interacting with the DENV envelope protein. Finally, based on all these analyses along with heated MD simulation, Bamlanivimab, Etesivimab and Tixagevimab with a mutation of residue 100 of the heavy chain from serine to tyrosine were selected as prospective therapeutic antibodies to combat DENV infection. This study may open a new avenue in designing therapeutics to combat Dengue viral infection.

Human cytomegalovirus deploys molecular mimicry to recruit VPS4A to sites of virus assembly

The AAA-type ATPase VPS4 is recruited by proteins of the endosomal sorting complex required for transport III (ESCRT-III) to catalyse membrane constriction and membrane fission. VPS4A accumulates at the cytoplasmic viral assembly complex (cVAC) of cells infected with human cytomegalovirus (HCMV), the site where nascent virus particles obtain their membrane envelope. Here we show that VPS4A is recruited to the cVAC via interaction with pUL71. Sequence analysis, deep-learning structure prediction, molecular dynamics and mutagenic analysis identify a short peptide motif in the C-terminal region of pUL71 that is necessary and sufficient for the interaction with VPS4A. This motif is predicted to bind the same groove of the N-terminal VPS4A Microtubule-Interacting and Trafficking (MIT) domain as the Type 2 MIT-Interacting Motif (MIM2) of cellular ESCRT-III components, and this viral MIM2-like motif (vMIM2) is conserved across β-herpesvirus pUL71 homologues. However, recruitment of VPS4A by pUL71 is dispensable for HCMV morphogenesis or replication and the function of the conserved vMIM2 during infection remains enigmatic. VPS4-recruitment via a vMIM2 represents a previously unknown mechanism of molecular mimicry in viruses, extending previous observations that herpesviruses encode proteins with structural and functional homology to cellular ESCRT-III components.

Complexation Mechanisms of Aqueous Amylose: Molecular Dynamics Study Using 3-Pentadecylphenol

Molecular dynamics (MD) simulations of linear amylose fragments containing 10 to 40 glucose units were used to study the complexation of the prototypical compound, 3-pentadecylphenol (PDP)─a natural product with surfactant-like properties─in aqueous solution. The amylose-PDP binding leverages mainly hydrophobic interactions together with excluded volume effects. It was found that while the most stable complexes contained PDP inside the helical structure of the amylose in the expected guest-host (inclusion) complexation manner, at higher temperatures, the commonly observed PDP-amylose complexes often involved more nonspecific interactions than inclusion complexation. In the case where a stoichiometric excess of PDP was added to the simulation box, self-aggregation of the small molecule precluded its ability to enter the internal helical part of the oligosaccharide, and as a result, inclusion complexation became ineffective. MD simulation trajectories were analyzed preliminarily using cluster analysis (CA), followed by more rigorous solvent accessible surface area (SASA) determination over the temperature range spanning from 277 to 433 K. It was found that using the SASA of PDP corrected for its intrinsic conformational changes, together with a generic hidden Markov model (HMM), an adequate quantification of the different types of PDP-amylose aggregates was obtained to allow further analysis. The enthalpy change associated with the guest-host binding equilibrium constant (Kgh) in aqueous solution was estimated to be -75 kJ/mol, which is about twice as high as one might expect based on experimentally measured values of similar complexes in the solid state where the (unsolvated) helical structure of amylose remains rigid. On the other hand, the nonspecific binding (Kns) enthalpy change associated with PDP-amylose interactions in the same solution environment was found to be about half of the inclusion complexation value.

Markov State Models Reveal How Folding Kinetics Influence Absorption Spectra of Foldamers

Self-assembly of platinum(II) complex foldamers is an essential approach to fabricate advanced luminescent materials. However, a comprehensive understanding of folding kinetics and their absorption spectra remains elusive. By constructing Markov state models (MSMs) from large-scale molecular dynamics simulations, we reveal that two largely similar dinuclear alknylplatinum(II) terpyridine foldamers, Pt-PEG and Pt-PE with slightly different bridges, exhibit distinctive folding kinetics. Particularly, Pt-PEG bears bridge-dominant, plane-dominant, and cooperative pathways, while Pt-PE only prefers the plane-dominant pathway. Such preference originates from their difference in intrabridge electrostatic interactions, leading to contrastive distributions of metastable states. We also found that the bridge-dominant pathway for Pt-PEG becomes more favorable when lowering the temperature. Interestingly, based on the comprehensive conformation ensembles from our MSMs, we reveal the conformation-dependent absorption spectra of Pt-PEG and Pt-PE. Our theoretical spectra not only align with experimental results but also reveal the contributions of diverse conformations to the overall absorption bands explicitly, facilitating the rational design of stimuli-responsive smart luminescent molecules.

Exploring transmembrane allostery in the MexB: DB08385 variant as a promising inhibitor-like candidate against Pseudomonas aeruginosa antibiotic resistance: a computational study

Pseudomonas aeruginosa, a formidable pathogen renowned for its antimicrobial resistance, poses a significant threat to immunocompromised individuals. In this regard, the MexAB-OprM efflux pump acts as a pivotal line of defense by extruding antimicrobials from bacterial cells. The inner membrane homotrimeric protein MexB captures antibiotics and translocates them into the outer membrane OprM channel protein connected through the MexA adaptor protein. Despite extensive efforts, competitive inhibitors targeting the tight (T) protomer of the MexB protein have not received FDA approval for medical use. Over the past few years, allosteric inhibitors have become popular as alternatives to the classical competitive inhibitor-based approach because of their higher specificity, lower dosage, and reduced toxicological effects. Hence, in this study, we unveiled the existence of a transmembrane allosteric binding pocket of MexB inspired by the recent discovery of an important allosteric inhibitor, BDM88855, for the homolog AcrB protein. While repurposing BDM88855 proved ineffective in controlling the MexB loose (L) protomer, our investigation identified a promising alternative: a chlorine-containing variant of DB08385 (2-Cl DB08385 or Variant 1). Molecular dynamics simulations, including binding free energy estimation coupled with heterogeneous dielectric implicit membrane model (implicit-membrane MM/PBSA), interaction entropy (IE) analysis and potential of mean force (PMF) calculation, demonstrated Variant 1's superior binding affinity to the transmembrane pocket, displaying the highest energy barrier in the ligand unbinding process. To elucidate the allosteric crosstalk between the transmembrane and porter domain of MexB, we employed the 'eigenvector centrality' measure in the linear mutual information obtained from the protein correlation network. Notably, this study confirmed the presence of an allosteric transmembrane site in the MexB L protomer. In addition to this, Variant 1 emerged as a potent regulator of allosteric crosstalk, inducing an 'O-L intermediate state' in the MexB L protomer. This induced state might hold the potential to diminish substrate intake into the access pocket, leading to the ineffective efflux of antibiotics.

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

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

Rational Design of Dual-Functionalized Gd@C82 Nanoparticles to Relieve Neuronal Cytotoxicity in Alzheimer's Disease via Inhibition of Aβ Aggregation

The accumulation of amyloid-β (Aβ) peptides is a major hallmark of Alzheimer's disease (AD) and plays a crucial role in its pathogenesis. Particularly, the structured oligomeric species rich in β-sheet formations were implicated in neuronal organelle damage. Addressing this formidable challenge requires identifying candidates capable of inhibiting peptide aggregation or disaggregating preformed oligomers for effective antiaggregation-based AD therapy. Here, we present a dual-functional nanoinhibitor meticulously designed to target the aggregation driving force and amyloid fibril spatial structure. Leveraging the exceptional structural stability and facile tailoring capability of endohedral metallofullerene Gd@C82, we introduce desired hydrogen-binding sites and charged groups, which are abundant on its surface for specific designs. Impressively, these designs endow the resultant functionalized-Gd@C82 nanoparticles (f-Gd@C82 NPs) with high capability of redirecting peptide self-assembly toward disordered, off-pathway species, obstructing the early growth of protofibrils, and disaggregating the preformed well-ordered protofibrils or even mature Aβ fibrils. This results in considerable alleviation of Aβ peptide-induced neuronal cytotoxicity, rescuing neuronal death and synaptic loss in primary neuron models. Notably, these modifications significantly improved the dispersibility of f-Gd@C82 NPs, thus substantially enhancing its bioavailability. Moreover, f-Gd@C82 NPs demonstrate excellent cytocompatibility with various cell lines and possess the ability to penetrate the blood-brain barrier in mice. Large-scale molecular dynamics simulations illuminate the inhibition and disaggregation mechanisms. Our design successfully overcomes the limitations of other nanocandidates, which often overly rely on hydrophobic interactions or photothermal conversion properties, and offers a viable direction for developing anti-AD agents through the inhibition and even reversal of Aβ aggregation.

Softening in Two-Component Lipid Mixtures by Spontaneous Curvature Variance

The bending modulus of a lipid bilayer quantifies its mechanical resistance to curvature. It is typically understood in terms of thickness; e.g., thicker bilayers are usually stiffer. Here, we describe an additional and powerful molecular determinant of stiffness─the variance in the distribution of curvature sensitivity of lipids and lipid conformations. Zwitterionic choline and ethanolamine headgroups of glycerophospholipids dynamically explore inter- and intraspecies interactions, leading to transient clustering. We demonstrate that these clusters couple strongly to negative curvature, exciting undulatory membrane modes and reducing the apparent bending modulus. Three force fields (Martini 2, Martini 3, and all-atom CHARMM C36) each show the effect to a different extent, with the coarse-grained Martini models showing the most clustering and thus the most softening. The theory is a guide to understanding the stiffness of biological membranes with their complex composition, as well as how choices of force field parameterization are translated into mechanical stiffness.

Structural Determinants of Peptide Nanopore Formation

We have evolved the nanopore-forming macrolittin peptides from the bee venom peptide melittin using successive generations of synthetic molecular evolution. Despite their sequence similarity to the broadly membrane permeabilizing cytolytic melittin, the macrolittins have potent membrane selectivity. They form nanopores in synthetic bilayers made from 1-palmitoyl, 2-oleoyl-phosphatidylcholine (POPC) at extremely low peptide concentrations and yet have essentially no cytolytic activity against any cell membrane, even at high concentration. Here, we explore the structural determinants of macrolittin nanopore stability in POPC bilayers using atomistic molecular dynamics simulations and experiments on macrolittins and single-site variants. Simulations of macrolittin nanopores in POPC bilayers show that they are stabilized by an extensive, cooperative hydrogen bond network comprised of the many charged and polar side chains interacting with each other via bridges of water molecules and lipid headgroups. Lipid molecules with unusual conformations participate in the H-bond network and are an integral part of the nanopore structure. To explore the role of this H-bond network on membrane selectivity, we swapped three critical polar residues with the nonpolar residues found in melittin. All variants have potency, membrane selectivity, and cytotoxicity that were intermediate between a cytotoxic melittin variant called MelP5 and the macrolittins. Simulations showed that the variants had less organized H-bond networks of waters and lipids with unusual structures. The membrane-spanning, cooperative H-bond network is a critical determinant of macrolittin nanopore stability and membrane selectivity. The results described here will help guide the future design and optimization of peptide nanopore-based applications.

Semi-rational design of nitroarene dioxygenase for catalytic ability toward 2,4-dichloronitrobenzene

Rieske non-heme dioxygenase family enzymes play an important role in the aerobic biodegradation of nitroaromatic pollutants, but no active dioxygenases are available in nature for initial reactions in the degradation of many refractory pollutants like 2,4-dichloronitrobenzene (24DCNB). Here, we report the engineering of hotspots in 2,3-dichloronitrobenzene dioxygenase from Diaphorobacter sp. strain JS3051, achieved through molecular dynamic simulation analysis and site-directed mutagenesis, with the aim of enhancing its catalytic activity toward 24DCNB. The computationally predicted activity scores were largely consistent with the detected activities in wet experiments. Among them, the two most beneficial mutations (E204M and M248I) were obtained, and the combined mutant reached up to a 62-fold increase in activity toward 24DCNB, generating a single product, 3,5-dichlorocatechol, which is a naturally occurring compound. In silico analysis confirmed that residue 204 affected the substrate preference for meta-substituted nitroarenes, while residue 248 may influence substrate preference by interaction with residue 295. Overall, this study provides a framework for manipulating nitroarene dioxygenases using computational methods to address various nitroarene contamination problems.IMPORTANCEAs a result of human activities, various nitroaromatic pollutants continue to enter the biosphere with poor degradability, and dioxygenation is an important kickoff step to remove toxic nitro-groups and convert them into degradable products. The biodegradation of many nitroarenes has been reported over the decades; however, many others still lack corresponding enzymes to initiate their degradation. Although rieske non-heme dioxygenase family enzymes play extraordinarily important roles in the aerobic biodegradation of various nitroaromatic pollutants, prediction of their substrate specificity is difficult. This work greatly improved the catalytic activity of dioxygenase against 2,4-dichloronitrobenzene by computer-aided semi-rational design, paving a new way for the evolution strategy of nitroarene dioxygenase. This study highlights the potential for using enzyme structure-function information with computational pre-screening methods to rapidly tailor the catalytic functions of enzymes toward poorly biodegradable contaminants.

Kinetic Network in Milestoning: Clustering, Reduction, and Transition Path Analysis

We present a reduction of the Milestoning (ReM) algorithm to analyze the high-dimensional Milestoning kinetic network. The algorithm reduces the Milestoning network to low dimensions but preserves essential kinetic information, such as local residence time, exit time, and mean first passage time between any two states. This is achieved in three steps. First, nodes (milestones) in the high-dimensional Milestoning network are grouped into clusters based on the metastability identified by an auxiliary continuous-time Markov chain. Our clustering method is applicable not only to time-reversible networks but also to nonreversible networks generated from practical simulations with statistical fluctuations. Second, a reduced network is established via network transformation, containing only the core sets of clusters as nodes. Finally, transition pathways are analyzed in the reduced network based on the transition path theory. The algorithm is illustrated using a toy model and a solvated alanine dipeptide in two and four dihedral angles.

Interaction of MRI Contrast Agent [Gd(DOTA)]- with Lipid Membranes: A Molecular Dynamics Study

Contrast agents are important imaging probes in clinical MRI, allowing the identification of anatomic changes that otherwise would not be possible. Intensive research on the development of new contrast agents is being made to image specific pathological markers or sense local biochemical changes. The most widely used MRI contrast agents are based on gadolinium(III) complexes. Due to their very high charge density, they have low permeability through tight biological barriers such as the blood-brain barrier, hampering their application in the diagnosis of neurological disorders. In this study, we explore the interaction between the widely used contrast agent [Gd(DOTA)]- (Dotarem) and POPC lipid bilayers by means of molecular dynamics simulations. This metal complex is a standard reference where several chemical modifications have been introduced to improve key properties such as bioavailability and targeting. The simulations unveil detailed insights into the agent's interaction with the lipid bilayer, offering perspectives beyond experimental methods. Various properties, including the impact on global and local bilayer properties, were analyzed. As expected, the results indicate a low partition coefficient (KP) and high permeation barrier for this reference compound. Nevertheless, favorable interactions are established with the membrane leading to moderately long residence times. While coordination of one inner-sphere water molecule is maintained for the membrane-associated chelate, the physical-chemical attributes of [Gd(DOTA)]- as a MRI contrast agent are affected. Namely, increases in the rotational correlation times and in the residence time of the inner-sphere water are observed, with the former expected to significantly increase the water proton relaxivity. This work establishes a reference framework for the use of simulations to guide the rational design of new contrast agents with improved relaxivity and bioavailability and for the development of liposome-based formulations for use as imaging probes or theranostic agents.

Totally Caged Type I Pro-Photosensitizer for Oxygen-Independent Synergistic Phototherapy of Hypoxic Tumors

Activatable type I photosensitizers are an effective way to overcome the insufficiency and imprecision of photodynamic therapy in the treatment of hypoxic tumors, however, the incompletely inhibited photoactivity of pro-photosensitizer and the limited oxidative phototoxicity of post-photosensitizer are major limitations. It is still a great challenge to address these issues using a single and facile design. Herein, a series of totally caged type I pro-photosensitizers (Pro-I-PSs) are rationally developed that are only activated in tumor hypoxic environment and combine two oxygen-independent therapeutic mechanisms under single-pulse laser irradiation to enhance the phototherapeutic efficacy. Specifically, five benzophenothiazine-based dyes modified with different nitroaromatic groups, BPN 1-5, are designed and explored as latent hypoxia-activatable Pro-I-PSs. By comparing their optical responses to nitroreductase (NTR), it is identified that the 2-methoxy-4-nitrophenyl decorated dye (BPN 2) is the optimal Pro-I-PSs, which can achieve NTR-activated background-free fluorescence/photoacoustic dual-modality tumor imaging. Furthermore, upon activation, BPN 2 can simultaneously produce an oxygen-independent photoacoustic cavitation effect and a photodynamic type I process at single-pulse laser irradiation. Detailed studies in vitro and in vivo indicated that BPN 2 can effectively induce cancer cell apoptosis through synergistic effects. This study provides promising potential for overcoming the pitfalls of hypoxic-tumor photodynamic therapy.

Unveiling the Cleavage Mechanism of an RNA Model Compound on the whole pH Scale: Computations Meet Experiments in the Determination of Reaction Rates

The knowledge of the mechanism of reactions occurring in solution is a primary research line both in the context of theoretical-computational chemistry and in the field of organic and bio-organic chemistry. Given the importance of the hydrolysis of nucleic acids in life-related phenomena, here we present a combined experimental and computational study on the cleavage of an RNA model compound. This phosphodiester features a cleavage rate strictly dependent on the pH with three different dependence domains. Such experimental evidence, highlighted by an in-depth kinetic investigation, unequivocally suggests a change in the reaction mechanism along the pH scale. In order to interpret the data and to explain the experimental behavior, we have applied a theoretical-computational procedure, involving a hybrid quantum/classical approach, able to model chemical reactions in complex environments, i. e. in solution. This study turns out to quantitatively reproduce the experimental data with accuracy and, in addition, provides useful mechanistic insight into the transesterification process of the investigated compound. The study indicates that the cleavage can occur through anA N D N ${A_N D_N }$ , anA N + D N ${A_N + D_N }$ , and aD N A N ${D_N A_N }$ mechanism depending on the pH values.

Developing Dynamic Structure-Based Pharmacophore and ML-Trained QSAR Models for the Discovery of Novel Resistance-Free RET Tyrosine Kinase Inhibitors Through Extensive MD Trajectories and NRI Analysis

Activation of RET tyrosine kinase plays a critical role in the pathogenesis of various cancers, including non-small cell lung cancer, papillary thyroid cancers, multiple endocrine neoplasia type 2A and 2B (MEN2A, MEN2B), and familial medullary thyroid cancer. Gene fusions and point mutations in the RET proto-oncogene result in constitutive activation of RET signaling pathways. Consequently, developing effective inhibitors to target RET is of utmost importance. Small molecules have shown promise as inhibitors by binding to the kinase domain of RET and blocking its enzymatic activity. However, the emergence of resistance due to single amino acid changes poses a significant challenge. In this study, a structure-based dynamic pharmacophore-driven approach using E-pharmacophore modeling from molecular dynamics trajectories is proposed to select low-energy favorable hypotheses, and ML-trained QSAR models to predict pIC50 values of compounds. For this aim, extensive small molecule libraries were screened using developed ligand-based models, and potent compounds that are capable of inhibiting RET activation were proposed.

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

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

Evaluation of the efficacy of marine natural products against PARP-1/2 proteins in high-grade serous ovarian cancer: insights into MD and SMD simulations

High-grade serous ovarian cancer (HGSOC) is the most malignant and ubiquitous phenotype of epithelial ovarian cancer. Originating in the fallopian tubes and rapidly spreading to the ovaries, this highly heterogeneous disease is a result of serous tubal intraepithelial carcinoma. The proteins known as poly(ADP-ribose) polymerase (PARP) aid in the development of HGSOC by repairing the cancer cells that proliferate and spread metastatically. By using molecular docking to screen 1100 marine natural products (MNPs) from different marine environments against PARP-1/2 proteins, prominent PARP inhibitors (PARPi) were identified. Four compounds, alisiaquinone A, alisiaquinone C, ascomindone D and (+)-zampanolide referred to as MNP-1, MNP-2, MNP-3 and MNP-4, respectively, were chosen based on their binding affinity towards PARP-1/2 proteins, and their bioavailability and drug-like qualities were accessed using ADMET analysis. To investigate the structural stability and dynamics of these complexes, molecular dynamics simulations were performed for 200 ns. These results were compared with the complexes of olaparib (OLA), a PARPi that has been approved by the FDA for the treatment of advanced ovarian cancer. We determined that MNP-4 exhibited stronger binding energies with PARP-1/2 proteins than OLA by using MM/PBSA calculations. Hotspot residues from PARP-1 (E883, M890, Y896, D899 and Y907) and PARP-2 (Y449, F450, A451, S457 and Y460) showed strong interactions with the compounds. To comprehend the unbinding mechanism of MNP-4 complexed with PARP-1/2, steered molecular dynamics (SMD) simulations were performed. We concluded from the free energy landscape (FEL) map that PARP-1/2 are well-stabilised when the compound MNP-4 is bound rather than being pulled away from its binding pockets. This finding provides significant evidence regarding PARPi, which could potentially be employed in the therapeutic treatment of HGSOC.Communicated by Ramaswamy H. Sarma.