Elucidating structural variability in p53 conformers using combinatorial refinement strategies and molecular dynamics

Low molecular weight proteins and protein assemblies can now be investigated using cryo-electron microscopy (EM) as a complement to traditional structural biology techniques. It is important, however, to not lose sight of the dynamic information inherent in macromolecules that give rise to their exquisite functionality. As computational methods continue to advance the field of biomedical imaging, so must strategies to resolve the minute details of disease-related entities. Here, we employed combinatorial modeling approaches to assess flexible properties among low molecular weight proteins (~100 kDa or less). Through a blend of rigid body refinement and simulated annealing, we determined new hidden conformations for wild type p53 monomer and dimer forms. Structures for both states converged to yield new conformers, each revealing good stereochemistry and dynamic information about the protein. Based on these insights, we identified fluid parts of p53 that complement the stable central core of the protein responsible for engaging DNA. Molecular dynamics simulations corroborated the modeling results and helped pinpoint the more flexible residues in wild type p53. Overall, the new computational methods may be used to shed light on other small protein features in a vast ensemble of structural data that cannot be easily delineated by other algorithms.

Discovery of novel and potent dual-targeting AXL/HDAC2 inhibitors for colorectal cancer treatment via structure-based pharmacophore modelling, virtual screening, and molecular docking, molecular dynamics simulation studies, and biological evaluation

Colorectal cancer (CRC) is one of the most common cancers worldwide. Nowadays, owing to the complex mechanism of tumorigenesis, simultaneous inhibition of multiple targets is an important anticancer strategy. Recent studies have demonstrated receptor tyrosine kinase AXL (AXL) and histone deacetylase 2 (HDAC2) are closely associated with colorectal cancer. Herein, we identified five hit compounds concurrently targeting AXL and HDAC2 using virtual screening. Inhibitory experiments revealed these hit compounds potently inhibited AXL and HDAC2 in the nanomolar range. Among them, Hit-3 showed the strongest inhibitory effects which were better than that of the positive control groups. Additionally, MD assays showed that Hit-3 could bind stably to the AXL and HDAC2 active pockets. Further MTT assays demonstrated that Hit-3 showed potent anti-proliferative activity. Most importantly, Hit-3 exhibited significant in vivo antitumor efficacy in xenograft models. Collectively, this study is the first discovery of dual-targeting AXL/HDAC2 inhibitors for colorectal cancer treatment.

Development of novel ALOX15 inhibitors combining dual machine learning filtering and fragment substitution optimisation approaches, molecular docking and dynamic simulation methods

The oxidation of unsaturated lipids, facilitated by the enzyme Arachidonic acid 15-lipoxygenase (ALOX15), is an essential element in the development of ferroptosis. This study combined a dual-score exclusion strategy with high-throughput virtual screening, naive Bayesian and recursive partitioning machine learning models, the already established ALOX15 inhibitor i472, and a docking-based fragment substitution optimisation approach to identify potential ALOX15 inhibitors, ultimately leading to the discovery of three FDA-approved drugs that demonstrate optimal inhibitory potential against ALOX15. Through fragment substitution-based optimisation, seven new inhibitor structures have been developed. To evaluate their practicality, ADMET predictions and molecular dynamics simulations were performed. In conclusion, the compounds found in this study provide a novel approach to combat conditions related to ferroptosis-related injury by inhibiting ALOX15.

Unraveling the binding mechanisms of transglutaminase and substrate subjected to microwaves: Molecular docking and molecular dynamic simulations

Previous studies showed that transglutaminase (TGase) and microwaves acted synergistically to improve the functional properties of proteins. The mechanism behind this has yet to be elucidated. In this study, the phenomenon of microwaves enhancing TGase activity was experimentally validated. Molecular docking and molecular dynamics simulations revealed that moderate microwaves (105 and 108 V/m) increased the structural flexibility of TGase and promoted the orientation of the side chain carboxylate anion group on Asp255, driving the reaction forward. Also, TGase underwent partial transformation from α-helix to turns or coils at 105 and 108 V/m, exposing more residues in the active site and facilitating the binding of the substrate (CBZ-Gln-Gly) to TGase. However, 109 V/m microwaves completely destroyed the TGase structure, inactivating the enzyme. This study provides insights into the molecular mechanisms underlying the interactions between TGase and substrate subjected to microwaves, promoting the future applications of TGase and microwaves in food processing.

Taste properties and mechanism of umami peptides from fermented goose bones based on molecular docking and molecular dynamics simulation using umami receptor T1R1/T1R3

Umami peptides are valuable taste substances due to their exceptional taste and beneficial properties. In this study, purification of fermented goose bone broth was performed using continuous chromatography and sensory analysis, and after identification through nano-LC-MS/MS, four umami peptides were screened out by umami activity prediction and molecular docking, which are VGYDAE, GATGRDGAR, GETGEAGER, and GETGEAGERG derived from collagen. Sensory analysis indicated that they were also umami-enhancing, with thresholds ranging from 0.41 to 1.15 mmol/L, among which GER9 was the best. Combining the results of docking and molecular dynamics simulation, it was known that hydrogen bond and electrostatic interactions were vital in driving the umami formation. Moreover, Glu, Ser, and Asp of umami receptor T1R1/T1R3 were the key residues for the binding between four umami peptides and T1R1/T1R3. These findings provide novel insights into the high-value utilization of goose bones and offer profound theoretical guidance for understanding the umami mechanism.

Unraveling the molecular dynamics of sugammadex-rocuronium complexation: A blueprint for cyclodextrin drug design

Sugammadex, marketed as Bridion™, is an approved cyclodextrin (CD) based drug for the reversal of neuromuscular blockade in adults undergoing surgery. Sugammadex forms an inclusion complex with the neuromuscular blocking agent (NMBA) rocuronium, allowing rapid reversal of muscle paralysis. In silico methods have been developed for studying CD inclusion complexes, aimed at accurately predicting their structural, energetic, dynamic, and kinetic properties, as well as binding constants. Here, a computational study aimed at characterizing the sugammadex-rocuronium system from the perspective of docking calculations, free molecular dynamics (MD) simulations, and biased metadynamics simulations with potential of mean force (PMF) calculations is presented. The aim is to provide detailed information about this system, as well as to use it as a model system for validation of the methods. This method predicts results in line with experimental evidence for both the optimal structure and the quantitative value for the binding constant. Interestingly, there is a less profound preference for the orientation than might be assumed based on electrostatic interactions, suggesting that both orientations may exist in solution. These results show that this technology can efficiently analyze CD inclusion complexes and could be used to facilitate the development and optimization of novel applications for CDs.

Molecular dynamics simulations and experimental investigation of viscosity of CuO-oil nanolubricant at different temperatures and volume fractions of nanoparticles

Nanolubricant viscosity plays a crucial role in various industries due to its impact on pressure drop, pumping power, and heat transfer. The purpose of this research is to measure the viscosity of a (base oil) C30H62-CuO nano-lubricant experimentally using a viscometer and determine its viscosity using the equilibrium molecular dynamics (MD) simulation. In addition, the impacts of nano CuO particle volume fraction and temperature on the viscosity were investigated within different concentrations of nano CuO particles (0%, 0.25%, 0.5%, and 0.75%) and variable temperatures (300 K, 313 K, 323 K, and 373 K). The simulation results agreed with experimental results and depicted that the viscosity of base oil and nano lubricant of CuO-base oil decreased with increasing temperature. Additionally, increasing the concentration of nanoparticles increased the viscosity of the nano lubricant, but the effect of increasing the concentration of nanoparticles at high temperatures was not significant. For instance, the viscosity of the base oil increased by 1.2% and 1.5% after adding 0.5% and 0.75% copper oxide nanoparticles at 373 K. Based on our research; no study has been done to calculate the viscosity of nanolubricant (C30H62 (base oil) - CuO) and its influencing factors by molecular dynamics simulation and compare its results with experimental methods. The research findings have practical implications for using nano lubricants in various industries, such as the internal combustion engine industry or other industries that use lubricants, and it is a critical parameter in heat transfer.

Molecular dynamics simulations shows real-time lid opening in Hsp70 chaperone

The stress-inducible mammalian heat shock protein Hsp70 and its bacterial orthologue DnaK are highly conserved molecular chaperones and a crucial part of the machinery responsible for protein folding and homeostasis. Hsp70 is a three-domain, 70 kDa protein that cycles between an ATP-bound state in which all three domains are securely coupled into one unit and an ADP-bound state in which they are loosely attached via a flexible interdomain linker. The Hsp70 presents an alluring novel therapeutic target since it is crucial for maintaining cellular proteostasis and is particularly crucial to cancer cells. We have performed molecular dynamics simulations of the SBD (substrate binding domain) along with the Lid domain in response to experimental efforts to identify small molecule inhibitors that impair the functioning of Hsp70. Our intent has been to characterize the motion of the SBD/Lid allosteric machinery and in, addition, to identify the effect of the PET16 molecule on this motion. Interestingly, we noticed the opening of the entire Lid domain in the apo-form of the dimer. The configuration of the open structure was very different from previously published structures (PDB 4JN4) of the open and docked conformation of the ATP bound form. MD simulations revealed the Lid to be capable of far greater dynamical excursions than has been anticipated by experimental structural biology. This is of value in future drug discovery efforts targeted to modulating Hsp70 activity. The PET16 molecule appears to be weakly bound and its effect on the dynamics of the complex is yet to be elucidated.

Multiscale modeling of unfolding and bond dissociation of rubredoxin metalloprotein

Mechanical properties of proteins that have a crucial effect on their operation. This study used a molecular dynamics simulation package to investigate rubredoxin unfolding on the atomic scale. Different simulation techniques were applied, and due to the dissociation of covalent/hydrogen bonds, this protein demonstrates several intermediate states in force-extension behavior. A conceptual model based on the cohesive finite element method was developed to consider the intermediate damages that occur during unfolding. This model is based on force-displacement curves derived from molecular dynamics results. The proposed conceptual model is designed to accurately identify bond rupture points and determine the associated forces. This is achieved by conducting a thorough comparison between molecular dynamics and cohesive finite element results. The utilization of a viscoelastic cohesive zone model allows for the consideration of loading rate effects. This rate-dependent model can be further developed and integrated into the multiscale modeling of large assemblies of metalloproteins, providing a comprehensive understanding of mechanical behavior while maintaining a reduced computational cost.

Experimental and computational investigation of the effect of Hsc70 structural variants on inhibiting amylin aggregation

The misfolding and aggregation of human islet amyloid polypeptide (hIAPP), also known as amylin, have been implicated in the pathogenesis of type 2 diabetes (T2D). Heat shock proteins, specifically, heat shock cognate 70 (Hsc70), are molecular chaperones that protect against hIAPP misfolding and inhibits its aggregation. Nevertheless, there is an incomplete understanding of the mechanistic interactions between Hsc70 domains and hIAPP, thus limiting their potential therapeutic role in diabetes. This study investigates the inhibitory capacities of different Hsc70 variants, aiming to identify the structural determinants that strike a balance between efficacy and cytotoxicity. Our experimental findings demonstrate that the ATPase activity of Hsc70 is not a pivotal factor for inhibiting hIAPP misfolding. We underscore the significance of the C-terminal substrate-binding domain of Hsc70 in inhibiting hIAPP aggregation, emphasizing that the removal of the lid subdomain diminishes the inhibitory effect of Hsc70. Additionally, we employed atomistic discrete molecular dynamics simulations to gain deeper insights into the interaction between Hsc70 variants and hIAPP. Integrating both experimental and computational findings, we propose a mechanism by which Hsc70's interaction with hIAPP monomers disrupts protein-protein connections, primarily by shielding the β-sheet edges of the Hsc70-β-sandwich. The distinctive conformational dynamics of the alpha helices of Hsc70 potentially enhance hIAPP binding by obstructing the exposed edges of the β-sandwich, particularly at the β5-β8 region along the alpha helix interface. This, in turn, inhibits fibril growth, and similar results were observed following hIAPP dimerization. Overall, this study elucidates the structural intricacies of Hsc70 crucial for impeding hIAPP aggregation, improving our understanding of the potential anti-aggregative properties of molecular chaperones in diabetes treatment.

Effects of anthocyanidins on the conformational transition of Aβ(1-42) peptide: Insights from molecular docking and molecular dynamics simulations

Recent evidence from in vitro and in vivo studies has shown that anthocyanins and anthocyanidins can reduce and inhibit the amyloid beta (Aβ) species, one of the hallmarks of Alzheimer's disease (AD). However, their inhibition mechanisms on Aβ species at molecular details remain elusive. Therefore, in the present study, molecular modelling methods were employed to investigate their inhibitory mechanisms on Aβ(1-42) peptide. The results highlighted that anthocyanidins effectively inhibited the conformational transitions of helices into beta-sheet (β-sheet) conformation within Aβ(1-42) peptide by two different mechanisms: 1) the obstruction of two terminals from coming into contact due to the binding of anthocyanidins with residues of N- and second hydrophobic core (SHC)-C-terminals, and 2) the prevention of the folding process due to the binding of anthocyanidin with the central polar (Asp23 and Lys28) and native helix (Asp23, Lys28, and Leu34) residues. These new findings on the inhibition of β-sheet formation by targeting both N- and SHC-C-terminals, and the long-established target, D23-K28 salt bridge residues, not with the conventional central hydrophobic core (CHC) as reported in the literature, might aid in designing more potent inhibitors for AD treatment.

Molecular dynamics investigation of DNA fragments bound to the anti-HIV protein SAMHD1 reveals alterations in allosteric communications

The sterile alpha motif and histidine-aspartate domain-containing protein 1 (or SAMHD1), a human dNTP-triphosphohydrolase, contributes to HIV-1 restriction in select terminally differentiated cells of the immune system. While the prevailing hypothesis is that the catalytically active form of the protein is an allosterically triggered tetramer, whose HIV-1 restriction properties are attributed to its dNTP - triphosphohydrolase activity, it is also known to bind to ssRNA and ssDNA oligomers. A complete picture of the structure-function relationship of the enzyme is still elusive and the function corresponding to its nucleic acid binding ability is debated. In this in silico study, we investigate the stability, preference and allosteric effects of DNA oligomers bound to SAMHD1. In particular, we compare the binding of DNA and RNA oligomers of the same sequence and also consider the binding of DNA fragments with phosphorothioate bonds in the backbone. The results are compared with the canonical form with the monomers connected by GTP/dATP crossbridges. The simulations indicate that SAMHD1 dimers preferably bind to DNA and RNA oligomers compared to GTP/dATP. However, allosteric communication channels are altered in the nucleic acid acid bound complexes compared to the canonical form. All results are consistent with the hypothesis that the DNA bound form of the protein correspond to an unproductive off-pathway state where the protein is sequestered and not available for dNTP hydrolysis.

Thermal rectification in novel two-dimensional hybrid graphene/BCN sheets: A molecular dynamics simulation

The graphene-like monolayer of carbon, boron and nitrogen that maintains the native hexagonal atomic lattice (BCN), is a novel semiconductor with special thermal properties. Herein, with the aid of a non-equilibrium molecular dynamics approach (NEMD), we study phonon thermal rectification in a hybrid system of pure graphene and BCN (G-BCN) in various configurations under a series of positive and negative temperature gradients. We begin by investigating the relation of thermal rectification to sample's mean temperature, T, and the imposed temperature difference, ΔT, between the two heat baths at its ends. We then move to explore the effect of varying strain levels of our sample on thermal rectification, followed by Kapitza resistance calculations at the G-BCN interface, which shed light on the interface effects on thermal rectification. Our simulation results reveal a BCN-configuration-dependent behavior of thermal rectification. Finally, the underlying mechanism leading to a preferred direction for phonons is studied using phonon density of states (DOS) on both sides of the G-BCN interface.

Binding interactions and in silico ADME prediction of isoconessimine derivatives as potent acetylcholinesterase inhibitors

In pursuit of new acetylcholinesterase (AChE) inhibitors for treating Alzheimer's disease (AD), a series of ten previously synthesized isoconessimine compounds (7a-7j) was in silico investigated for their binding interactions with AChE and pharmacokinetics based on absorption, distribution, metabolism, and excretion (ADME) properties using molecular docking, ONIOM (Our own N-layered Integrated molecular Orbital and molecular Mechanics) method and SwissADME tools. Docking experiments showed that all compounds bind within the active site gorge of AChE (PDB entry 1C2B), posing its aryloxy-substitutional ethyl group to catalytic site and conessine skeleton to peripheral anionic site. ONIOM interaction energy was used as an ONIOM score to improve docking score, and it ranked 7b as the most potent AChE inhibitor, in agreement with previous experiment. Residues, ASP74, TRP86, GLY122, GLU202, TRP286, GLU292, SER293, ILE294, TYR337, TYR341, and HIS447 were identified as important for the binding of the AChE-isoconessimine complex. The SwissADME investigation suggested that four compounds (7a, 7c, 7d and 7f) agree with the rules of drug-likeness. The steric and electronic effects on the aryloxy-substitutional ethyl group as important factors in the AChE inhibition were also discussed, which brings a better understanding of Alzheimer's disease drug development.

Mechanical behaviors of CL-20 under an impact loading: A molecular dynamics study

Study on the dynamic process of CL-20 crystal under impact is critical for the safe utilization of energetic materials under extreme conditions. Herein, the mechanical and structural evolution of CL-20 under the impact of a diamond ball is investigated by using molecular dynamics simulation. The considerations are given to the effect of different impact velocity, impact direction and impact angle. It is found that a high impact velocity results in a large indentation depth and force, as well as more significant energy transition and the formation of a large number of molecular fragments. Moreover, CL-20 exhibits weak anisotropy along different impact directions due to the crystalline distribution anisotropy. Furthermore, the mechanical response of CL-20 is angle-dependent, which is caused by the discrepancy in local molecular re-arrangement. These results may enhance the understanding of the mechanical behavior of CL-20 and promote its wide applications.

Elucidating the interaction mechanism of rice glutelin and soybean 11S globulin using multi-spectroscopy and molecular dynamics simulation methods

Rice gluten, as the hydrophobic protein, exhibits restricted application value in hydrophilic food, which may be enhanced through interaction with soybean 11S globulin, characterized by favorable functional properties. This study aims at revealing their interaction mechanism via multi-spectroscopy and molecular dynamics simulation. The formation and structural change of rice glutelin-soybean 11S globulin complexes were detected using fluorescence, ultra-violet and circular dichroism spectra. The addition of 11S globulin increased the contents of α-helix, β-turn and random coil, but decreased β-sheet content, and the change in secondary structure was correlated with particle size. Moreover, exposure of hydrophobic groups and formation of disulfide bonds occurred in the complexes. Molecular dynamics simulation verified these experimental results through analyses of root mean square deviation and fluctuation, hydrogen bond, secondary structure, and binding free energy analysis. This study contributes to expounding the interaction mechanism of protein and protein from the molecular level.

MD simulation to comprehend polygalacturonase inactivation mechanism during thermal and non-thermal effects of infrared processing

Food quality is greatly impacted by traditional heat methods for polygalacturonase (PG) inactivation; therefore, it's imperative to develop a novel infrared (IR) inactivation approach and identify its mechanism. Utilizing molecular dynamics (MD) simulation, this study verified the PG's activity, structure, active sites, and substrate channel under the single thermal and non-thermal effects of IR. PG activity was significantly reduced by IR, and structure was unfolded by increasing random coils (65.62 %) and decreasing β-sheets (29.11 %). MD data indicated that the relative locations of PG's active sites were altered by both IR effects, and the enzyme-substrate channel was shortened (10.53 % at 18 μm and 15.79 % at 80 °C). The thermal effect of IR on the inactivation of PG was significantly more pronounced than its non-thermal effect. This study unveiled the mechanism by which the infrared disrupted PG's activity, active sites, and substrate channels; thus, it expanded the infrared technique's efficacy in enzyme control.

Targeting ATP-binding site of WRN Helicase: Identification of novel inhibitors through pocket analysis and Molecular Dynamics-Enhanced virtual screening

WRN helicase is a critical protein involved in maintaining genomic stability, utilizing ATP hydrolysis to dissolve DNA secondary structures. It has been identified as a promising synthetic lethal target for microsatellite instable (MSI) cancers. However, few WRN helicase inhibitors have been discovered, and their potential binding sites remain unexplored. In this study, we analyzed potential binding sites for WRN inhibitors and focused on the ATP-binding site for screening new inhibitors. Through molecular dynamics-enhanced virtual screening, we identified two compounds, h6 and h15, which effectively inhibited WRN's helicase and ATPase activity in vitro. Importantly, these compounds selectively targeted WRN's ATPase activity, setting them apart from other non-homologous proteins with ATPase activity. In comparison to the homologous protein BLM, h6 exhibits some degree of selectivity towards WRN. We also investigated the binding mode of these compounds to WRN's ATP-binding sites. These findings offer a promising strategy for discovering new WRN inhibitors and present two novel scaffolds, which might be potential for the development of MSI cancer treatment.

Probing solution conformations of l-DOPA: Integration of experiment and simulation via vibrational optical activity

l-DOPA plays a critical role as a precursor to dopamine and is a standard treatment for Parkinson's disease. Recent research has highlighted the potential therapeutic advantages of deuterated l-DOPA analogs having a longer biological half-life. For their spectroscopic characterization, the in-detail characterization of l-DOPA itself is necessary. This article presents a thorough examination of the vibrational spectra of l-DOPA, with a particular emphasis on chirally sensitive VOA techniques. We successfully obtained high-quality Raman and ROA spectra of l-DOPA in its cationic form, under low pH conditions, and at a high concentration of 100 mg/ml. These spectra cover a broad spectral range, allowing for precise comparisons with theoretical simulations. We also obtained IR and VCD spectra, but they faced limitations due to the narrow accessible spectral region. Exploration of l-DOPA's conformational landscape revealed its intrinsic flexibility, with multiple coexisting conformations. To characterize these conformations, we employed two methods: one involved potential energy surface scans with implicit solvation, and the other utilized molecular dynamics simulations with explicit solvation. Comparing ROA spectra from different conformer groups and applying spectral decomposition proved crucial in determining the correct conformer ratios. The use of explicit solvation significantly improved the quality of the final simulated spectral profiles. The accurate determination of conformer ratios, rather than solely relying on the number of averaged spectra, played a crucial role in simulation accuracy. In conclusion, our study offers valuable insights into the structure and conformational behavior of l-DOPA and represents a valuable resource for subsequent spectroscopic studies of its deuterated analogs.

Modulation of protein-ligand interactions in the presence of ZIF-8: Spectroscopy and molecular dynamics simulation

In this paper, we investigated the protein-ligand interactions in the presence of ZIF-8 using multi-spectroscopic approaches and molecular dynamics simulation. Fluorescence experiments and molecular docking results showed that ZIF-8 did not change the type of quenching and interaction force between ciprofloxacin (CIP) and human serum albumin (HSA), but made the binding constant of HSA-CIP to be smaller, suggesting that ZIF-8 maybe accelerate the dissociation of CIP from HSA-CIP complex. Moreover, the effect of ZIF-8 on the physiological function of HSA was explored. Multi-spectroscopic methods revealed that ZIF-8 did not significantly alter the microenvironment of amino acid groups, but cause a slight decrease in the content of α-helical conformation, and a sparse and flexible structure of the protein backbone. These peculiarities might lead to the diminution of HSA's ability to control drugs. In short, ZIF-8 might enhance drug effect due to affecting the binding of drugs to proteins. However, the present study is only a preliminary investigation of the suitability of ZIF-8 as a drug carrier in vitro, and subsequent in vivo experimental studies will be required to further confirm the idea.

Raman spectroscopy study of 7,8-dihydrofolate inhibition on the Wuhan strain SARS-CoV-2 binding to human ACE2 receptor

Emerging evidence suggests that elevated levels of folic acid in the bloodstream may confer protection against Wuhan-SARS-CoV-2 infection and mitigate its associated symptoms. Notably, two comprehensive studies of COVID-19 patients in Israel and UK uncovered a remarkable trend, wherein individuals with heightened folic acid levels exhibited only mild symptoms and necessitated no ventilatory support. In parallel, research has underscored the potential connection between decreased folic acid levels and the severity of Covid-19 among hospitalized patients. Yet, the underlying mechanisms governing this intriguing inhibition remain elusive. In a quest to elucidate these mechanisms, we conducted a molecular dynamics simulation approach followed by a Raman spectroscopy study to delve into the intricate interplay between the folic acid metabolite, 7,8-dihydrofolate (DHF), and the angiotensin-converting enzyme ACE2 receptor, coupled with its interaction with the receptor-binding domain (RBD) of the Wuhan strain of SARS-CoV-2. Through a meticulous exploration, we scrutinized the transformation of the ACE2 + RBD complex, allowing these reactants to form bonds. This was juxtaposed with a similar investigation where ACE2 was initially permitted to react with DHF, followed by the exposure of the ACE2 + DHF complex to RBD. We find that DHF, when bonded to ACE2, functions as a physical barrier, effectively inhibiting the binding of the Wuhan strain RBD. This physicochemical process offers a cogent explanation for the observed inhibition of host cell infection in subjects receiving supplementary folic acid doses, as epidemiologically substantiated in multiple studies. This study not only sheds light on a potential avenue for mitigating SARS-CoV-2 infection but also underscores the crucial role of folic acid metabolites in host-virus interactions. This research paves the way for novel therapeutic strategies in the battle against COVID-19 and reinforces the significance of investigating the molecular mechanisms underlying the protective effects of folic acid in the context of viral infections.

GPER binding site detection and description: A flavonoid-based docking and molecular dynamics simulations study

Flavonoids, a phenolic compounds class widely distributed in the plant kingdom, have attracted much interest for their implications on several health and disease processes. Usually, the consumption of this type of compounds is approximately 1 g/d, primarily obtained from cereals, chocolate, and dry legumes ensuring its beneficial role in maintaining the homeostasis of the human body. In this context, in cancer disease prominent data points to the role of flavonoids as adjuvant treatment aimed at the regression of the disease. GPER, an estrogen receptor on the cell surface, has been postulated as a probable orchestrator of the beneficial effects of several flavonoids through modulation/inhibition of various mechanisms that lead to cancer progression. Therefore, applying pocket and cavity protein detection and docking and molecular dynamics simulations (MD), we generate, from a cluster composed of 39 flavonoids, crucial insights into the potential role as GPER ligands, of Puerarin, Isoquercetin, Kaempferol 3-O-glucoside and Petunidin 3-O-glucoside, aglycones whose sugar moiety delimits a new described sugar-acceptor sub-cavity into the cavity binding site on the receptor, as well as of the probable activation mechanism of the receptor and the pivotal residues involved in it. Altogether, our results shed light on the potential use of the aforementioned flavonoids as GPER ligands and for further evaluations in in vitro and in vivo assays to elucidate their probable anti-cancer activity.

Computational insight into the effect of alkyl chain length in tetraalkylammonium-based deep eutectic solvents

The effect of the increase in the alkyl chain length of cation on the properties of deep eutectic solvents based on ethylene glycol has been investigated employing classical molecular dynamics simulations. The change in the structural and dynamic properties in both the bulk and liquid-vapor interface is explored through various analyses. The interaction between the anion and the ethylene glycol increases with an increase in the alkyl chain length of the cation, as observed in the increase of the lifetime of the hydrogen bond formed between the two. The terminal carbon atoms are found to be closer to each other when the cation changes from tetraethylammonium to tetrabutylammonium. The cations are located closer to the interface, and the association of the alkyl chains becomes more significant with increased alkyl chain length, decreasing the surface tension values.

Computational and experimental identification of keystone interactions in Ebola virus matrix protein VP40 dimer formation

The Ebola virus (EBOV) is a lipid-enveloped virus with a negative sense RNA genome that can cause severe and often fatal viral hemorrhagic fever. The assembly and budding of EBOV is regulated by the matrix protein, VP40, which is a peripheral protein that associates with anionic lipids at the inner leaflet of the plasma membrane. VP40 is sufficient to form virus-like particles (VLPs) from cells, which are nearly indistinguishable from authentic virions. Due to the restrictions of studying EBOV in BSL-4 facilities, VP40 has served as a surrogate in cellular studies to examine the EBOV assembly and budding process from the host cell plasma membrane. VP40 is a dimer where inhibition of dimer formation halts budding and formation of new VLPs as well as VP40 localization to the plasma membrane inner leaflet. To better understand VP40 dimer stability and critical amino acids to VP40 dimer formation, we integrated computational approaches with experimental validation. Site saturation/alanine scanning calculation, combined with molecular mechanics-based generalized Born with Poisson-Boltzmann surface area (MM-GB/PBSA) method and molecular dynamics simulations were used to predict the energetic contribution of amino acids to VP40 dimer stability and the hydrogen bonding network across the dimer interface. These studies revealed several previously unknown interactions and critical residues predicted to impact VP40 dimer formation. In vitro and cellular studies were then pursued for a subset of VP40 mutations demonstrating reduction in dimer formation (in vitro) or plasma membrane localization (in cells). Together, the computational and experimental approaches revealed critical residues for VP40 dimer stability in an alpha-helical interface (between residues 106-117) as well as in a loop region (between residues 52-61) below this alpha-helical region. This study sheds light on the structural origins of VP40 dimer formation and may inform the design of a small molecule that can disrupt VP40 dimer stability.

Computational modelling and optimization studies of electropentamer for molecular imprinting of DJ-1

Parkinson's disease (PD) is the most prevalent type of incurable movement disorder. Recent research findings propose that the familial PD-associated molecule DJ-1 exists in cerebrospinal fluid (CSF) and that its levels may be altered as Parkinson's disease advances. By using a molecularly imprinted polymer (MIP) as an artificial receptor, it becomes possible to create a functional MIP with predetermined selectivity for various templates, particularly for the DJ-1 biomarker associated with Parkinson's disease. It mostly depends on molecular recognition via interactions between functional monomers and template molecules. So, the computational methods for the appropriate choice of functional monomers for creating molecular imprinting electropolymers (MIEPs) with particular recognition for the detection of DJ-1, a pivotal biomarker involved in PD, are undertaken in this study. Here, molecular docking, molecular dynamics simulations (MD), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods, and quantum mechanical calculation have been applied to investigate the intermolecular interaction between DJ-1 and several functional electropentamers, viz., polypyrrole (PPy), poly(3,4-ethylenedioxythiophene) (PEDOT), poly(o-aminophenol) (POAP), and polythiophene (PTS). In this context, the electropentamers were selected to mimic the imprinted electropolymer system. We analyzed the most stable configurations of the formed complexes involving DJ-1 and electropentamers as a model system for MIEPs. Among these, PEDOT exhibited a more uniform arrangement around DJ-1, engaging in numerous van der Waals, H-bond, electrostatic, and hydrophobic interactions. Hence, it can be regarded as a preferable choice for synthesizing a MIP for DJ-1 recognition. Thus, it will aid in selecting a suitable functional monomer, which is of greater significance in the design and development of selective DJ-1/MIP sensors.

Enumeration of olive derived lignan, pinoresinol for activity against recent Omicron variant spike protein for structure-based drug design, DFT, molecular dynamics simulations, and MMGBSA studies

The coronavirus disease 2019 (COVID-19) was first found in Wuhan, China, in December 2019. Because the virus spreads quickly, it quickly became a global worry. Coronaviridae is the family that contains both SARS-CoV-2 and the viruses that came before (i.e., MERS-CoV and SARS-CoV). Recent sources portray that the COVID-19 virus has affected 344,710,576 people worldwide and killed about 5,598,511 people in the last 2 years. The B.1.1.529 strain, later called "Omicron," was named a Variant of Concern on November 24, 2021. The SARS-CoV-2 virus has gone through a never-ending chain of changes that have never happened before. As a result, it has many different traits. Most of these changes have occurred in the spike protein, where antibodies bind. Because of these changes, the Omicron type is very contagious and easy to pass on. There have been a lot of studies done to try to figure out this new challenge in the COVID-19 strains race, but there is still a lot that needs to be explained. This study focuses on virtual screening, docking, and molecular dynamic analysis; we aimed to identify therapeutic candidates for the SARS-CoV-2 variant Omicron based on their ability to inhibit non-structural proteins. We investigate the prediction of the properties of a substantial database of drug molecules obtained from the OliveNet™ database. Compounds that did not exhibit adequate gastrointestinal absorption and failed the Lipinski test are not considered for further research. The filtered compounds were coupled with our primary target, SARS-CoV-2 Omicron spike protein. We focused on SARS-CoV-2 Omicron spike protein and filtering potent olive compounds. Pinoresinol, the most likely candidate, is bound best (- 8.5 kcal/mol). Pinoresinol's strong interaction with the active site made the complex's dynamic structure more resilient. MD simulations explain the protein-ligand complex's stability and function. Pinoresinol may be a promising SARS-CoV-2 Omicron spike protein receptor lead drug, and additional research may assist the scientific community.

Synergy and anti-cooperativity in allostery: Molecular dynamics study of WT and oncogenic KRAS-RGL1

This study focuses on investigating the effects of an oncogenic mutation (G12V) on the stability and interactions within the KRAS-RGL1 protein complex. The KRAS-RGL1 complex is of particular interest due to its relevance to KRAS-associated cancers and the potential for developing targeted drugs against the KRAS system. The stability of the complex and the allosteric effects of specific residues are examined to understand their roles as modulators of complex stability and function. Using molecular dynamics simulations, we calculate the mutual information, MI, between two neighboring residues at the interface of the KRAS-RGL1 complex, and employ the concept of interaction information, II, to measure the contribution of a third residue to the interaction between interface residue pairs. Negative II indicates synergy, where the presence of the third residue strengthens the interaction, while positive II suggests anti-cooperativity. Our findings reveal that MI serves as a dominant factor in determining the results, with the G12V mutation increasing the MI between interface residues, indicating enhanced correlations due to the formation of a more compact structure in the complex. Interestingly, although II plays a role in understanding three-body interactions and the impact of distant residues, it is not significant enough to outweigh the influence of MI in determining the overall stability of the complex. Nevertheless, II may nonetheless be a relevant factor to consider in future drug design efforts. This study provides valuable insights into the mechanisms of complex stability and function, highlighting the significance of three-body interactions and the impact of distant residues on the binding stability of the complex. Additionally, our findings demonstrate that constraining the fluctuations of a third residue consistently increases the stability of the G12V variant, making it challenging to weaken complex formation of the mutated species through allosteric manipulation. The novel perspective offered by this approach on protein dynamics, function, and allostery has potential implications for understanding and targeting other protein complexes involved in vital cellular processes. The results contribute to our understanding of the effects of oncogenic mutations on protein-protein interactions and provide a foundation for future therapeutic interventions in the context of KRAS-associated cancers and beyond.

Deciphering ACE2-RBD binding affinity through peptide scanning: A molecular dynamics simulation approach

Rapid discovery of target information for protein-protein interactions (PPIs) is significant in drug design, diagnostics, vaccine development, antibody therapy, etc. Peptide microarray is an ideal tool for revealing epitope information of PPIs. In this work, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spike receptor-binding domain (RBD) and the host cell receptor angiotensin-converting enzyme 2 (ACE2) were introduced as a model to study the epitope information of RBD-specific binding to ACE2 via a combination of theoretical calculations and experimental validation. Through dock and molecular dynamics simulations, it was found that among the 22 peptide fragments that consist of RBD, #14 (YNYLYRLFRKSNLKP) has the highest binding strength. Subsequently, the experiments of peptide microarray constructed based on plasmonic materials chip also confirmed the theoretical calculation data. Compared to other methods, such as phage display technology and surface plasmon resonance (SPR), this method is rapid and cost-effective, providing insights into the investigation of pathogen invasion processes and the timely development of peptide drugs and other fields.

Alleviates Acute Pancreatitis by Regulating Th17 Cell Differentiation: An Integrated Network Pharmacology Analysis, Molecular Dynamics Simulation and Experimental Validation

OBJECTIVE

To identify the core targets of Rheum palmatum L. and Salvia miltiorrhiza Bge., (Dahuang-Danshen, DH-DS) and the mechanism underlying its therapeutic efficacy in acute pancreatitis (AP) using a network pharmacology approach and validate the findings in animal experiments.

METHODS

Network pharmacology analysis was used to elucidate the mechanisms underlying the therapeutic effects of DH-DS in AP. The reliability of the results was verified by molecular docking simulation and molecular dynamics simulation. Finally, the results of network pharmacology enrichment analysis were verified by immunohistochemistry, Western blot analysis and real-time quantitative PCR, respectively.

RESULTS

Sixty-seven common targets of DH-DS in AP were identified and mitogen-activated protein kinase 3 (MAPK3), Janus kinase 2 (JAK2), signal transducer and activator of transcription 3 (STAT3), protein c-Fos (FOS) were identified as core targets in the protein interaction (PPI) network analysis. Gene ontology analysis showed that cellular response to organic substance was the main functions of DH-DS in AP, and Kyoto Encyclopedia of Genes and Genomes analysis showed that the main pathway included Th17 cell differentiation. Molecular docking simulation confirmed that DH-DS binds with strong affinity to MAPK3, STAT3 and FOS. Molecular dynamics simulation revealed that FOS-isotanshinone II and STAT3-dan-shexinkum d had good binding capacity. Animal experiments indicated that compared with the AP model group, DH-DS treatment effectively alleviated AP by inhibiting the expression of interleukin-1β, interleukin-6 and tumor necrosis factor-α, and blocking the activation of Th17 cell differentiation (P<0.01).

CONCLUSION

DH-DS could inhibit the expression of inflammatory factors and protect pancreatic tissues, which would be functioned by regulating Th17 cell differentiation-related mRNA and protein expressions.

Aggregation of graphene oxide upon the stripping of oxidized debris: An experimental and molecular dynamics simulation study

The most recent structural study of graphene oxide (GO) indicates that the oxidized debris (ODs) adhered to as-prepared GO will strip in certain aquatic settings. The impact of ODs stripping on the characteristics of GO has been widely reported, but its effects on GO aggregation have received less attention. Here, the influence of OD stripping on the GO aggregation property was identified, and the aggregation of as-prepared GO and GO upon OD stripping was compared. Upon ODs stripping, the pKa values of GO shifted from 3.91, 6.25, and 9.84 to 4.54, 6.65, and 10.21, respectively. Further analysis indicated the removal of ODs reduced the net negative charge and improved the hydrophobicity of GO, hence promoting the aggregation of GO. The acceleration of GO-Ca2+-OD aggregate formation was facilitated by the collective effects of ODs stripping, functional group deprotonation, double layer compression, OD bridging, and charge neutralization. The metal ions and stripped ODs attach to GO edges and link GO, which perform like bridges and contribute to further aggregation. In general, the existence of ODs adds complexity to the constructions and characteristics of GO, and it is important to take this into account while evaluating the aggregation characteristic of GO-based materials.

Interaction analysis of SARS-CoV-2 omicron BA1 and BA2 of RBD with fifty monoclonal antibodies: Molecular dynamics approach

This report provides detailed insights into the interaction of fifty monoclonal antibodies with two recent Omicron variants, BA1 and BA2. It has been observed that numerous mutations in the receptor binding domain (RBD) result in significant structural changes in Omicron, enhancing its ability to mediate viral infections compared to other variants of concern. The following antibodies, namely JX3S304, 7KMG, 7CH4, 7BELCOVOX45, 7CDJ, 7C01, 7JX3S2H14, 6XCA, 7CDI, 7JMO, 7B3O, 6ZER, 6XC7CR3022, JX3S309, 6XC7CC123, 7CM4, 7KMI, 7L7EAZD8895, exhibit a superior binding affinity towards the Spike when compared to the reference CR3022. Four best-docked systems were subjected to further testing through molecular dynamics (MD) simulations. The MM/GBSA free energy for the top-scored complexes of BA1 variant are BA1_JX3S3O4, BA1_7KMI, BA1_7CH4, and BA1_7KMG, with respective values of -56.120 kcal/mol, -41.30 kcal/mol, -17.546 kcal/mol, and -8.527 kcal/mol; and of BA2 variant are BA2_JX3S3O4, BA2_7CM4, BA2_KMG, and BA2_7CH4, with respective values of -40.903 kcal/mol, -23.416 kcal/mol, -17.350 kcal/mol, and -5.460 kcal/mol. Detailed structural/energetic parameters, principal component analysis, and free energy landscape (FEL) studies reveal a significant decrease in antibody resistance due to the disappearance of numerous hydrogen bond interactions and various metastable states. We believe that these crucial mechanistic insights will contribute to breakthroughs in SARS-CoV-2 research.

Understanding cellulose pyrolysis via ab initio deep learning potential field

Comprehensive and dynamic studies of cellulose pyrolysis reaction mechanisms are crucial in designing experiments and processes with enhanced safety, efficiency, and sustainability. The details of the pyrolysis mechanism are not readily available from experiments but can be better described via molecular dynamics (MD) simulations. However, the large size of cellulose molecules challenges accurate ab initio MD simulations, while existing reactive force field parameters lack precision. In this work, precise ab initio deep learning potentials field (DPLF) are developed and applied in MD simulations to facilitate the study of cellulose pyrolysis mechanisms. The formation mechanism and production rate of both valuable and greenhouse products from cellulose at temperatures larger than 1073 K are comprehensively described. This study underscores the critical role of advanced simulation techniques, particularly DLPF, in achieving efficient and accurate understanding of cellulose pyrolysis mechanisms, thus promoting wider industrial applications.

Four-dimensional imaging for cryo-electron microscopy experiments using molecular simulations and manifold learning

Elucidating protein conformational changes is essential because conformational changes are closely related to the functions of proteins. Cryo-electron microscopy (cryo-EM) experiment can be used to reconstruct protein conformational changes via a method that involves using the experimental data (two-dimensional protein images). In this study, a reconstruction method, referred to as the "four-dimensional imaging," was proposed. In our four-dimensional imaging technique, the protein conformational change was obtained using the two-dimensional protein images (the three-dimensional electron density maps used in previously proposed techniques were not used). The protein conformation for each two-dimensional protein image was obtained using our original protocol with molecular dynamics simulations. Using a manifold-learning technique and two-dimensional protein images, the protein conformations were arranged according to the conformational change of the protein. By arranging the protein conformations according to the arrangement of the protein images, four-dimensional imaging is constructed. A simulation for a cryo-EM experiment demonstrated the validity of our four-dimensional imaging technique.

Studying the ssDNA loaded adeno-associated virus aggregation using coarse-grained molecular dynamics simulations

The aggregation of adeno-associated viral (AAV) capsids in an aqueous environment was investigated via coarse-grained molecular dynamics (CG-MD) simulations. The primary driving force and mechanism of the aggregation were investigated with or without single-strand DNA (ssDNA) loaded at various process temperatures. Capsid aggregation appeared to involve multiple residue interactions (i.e., hydrophobic, polar and charged residues) leading to complex protein aggregation. In addition, two aggregation mechanisms (i.e., the fivefold face-to-face contact and the edge-to-edge contact) were identified from this study. The ssDNA with its asymmetric structure could be the reason for destabilizing protein subunits and enhancing the interaction between the charged residues, and further result in the non-reversible face-to-face contact. At higher temperature, the capsid structure was found to be unstable with the significant size expansion of the loaded ssDNA which could be attributed to reduced number of intramolecular hydrogen bonds, the increased conformational deviations of protein subunits and the higher residue fluctuations. The CG-MD model was further validated with previous experimental and simulation data, including the full capsid size measurement and the capsid internal pressure. Thus, a good understanding of AAV capsid aggregation, instability and the role of ssDNA were revealed by applying the developed computational model.

The search for novel proline analogs for viscosity reduction and stabilization of highly concentrated monoclonal antibody solutions

Administration of monoclonal antibodies (mAbs) is currently focused on subcutaneous injection associated with increased patient adherence and reduced treatment cost, leading to sustainable healthcare. The main bottleneck is low volume that can be injected, requiring highly concentrated mAb solutions. The latter results in increased solution viscosity with pronounced mAb aggregation propensity because of intensive protein-protein interactions. Small molecule excipients have been proposed to restrict the protein-protein interactions, contributing to reduced viscosity. The aim of the study was to discover novel compounds that reduce the viscosity of highly concentrated mAb solution. First, the chemical space of proline analogs was explored and 35 compounds were determined. Viscosity measurements revealed that 18 proline analogs reduced the mAb solution viscosity similar to or more than proline. The compounds forming both electrostatic and hydrophobic interactions with mAb reduced the viscosity of the formulation more efficiently without detrimentally effecting mAb physical stability. A correlation between the level of interaction and viscosity-reducing effect was confirmed with molecular dynamic simulations. Structure rigidity of the compounds and aromaticity contributed to their viscosity-reducing effect, dependent on molecule size. The study results highlight the novel proline analogs as an effective approach in viscosity reduction in development of biopharmaceuticals for subcutaneous administration.

Effect of GM1 concentration change on plasma membrane: molecular dynamics simulation and analysis

Ganglioside GM1 is a class of glycolipids predominantly located in the nervous system. Comprising a ceramide anchor and an oligosaccharide chain containing sialic acid, GM1 plays a pivotal role in various cellular processes, including signal transduction, cell adhesion, and membrane organization. Moreover, GM1 has been implicated in the pathogenesis of several neurological disorders, such as Parkinson's disease, Alzheimer's disease, and stroke. In this study, by creating a neural cell model membrane simulation system and employing rigorous molecular models, we utilize a coarse-grained molecular dynamics approach to explore the structural and dynamic characteristics of multi-component neuronal plasma membranes at varying GM1 ganglioside concentrations. The simulation results reveal that as GM1 concentration increases, a greater number of hydrogen bonds form between GM1 molecules, resulting in the formation of larger clusters, which leads to reduced membrane fluidity, increased lipid ordering, decreased membrane thickness and surface area and higher levels of GM1 dissociation. Through a meticulous analysis, while considering GM1's structural attributes, we offer valuable insights into the structural and dynamic traits of the cell membrane. This study provides a robust methodology for exploring membrane characteristics and enhances our comprehension of GM1 molecules, serving as a resource for both experimental and computational researchers in this field.

C-type inactivation and proton modulation mechanisms of the TASK3 channel

The TWIK-related acid-sensitive K+ channel 3 (TASK3) belongs to the two-pore domain (K2P) potassium channel family, which regulates cell excitability by mediating a constitutive "leak" potassium efflux in the nervous system. Extracellular acidification inhibits TASK3 channel, but the molecular mechanism by which channel inactivation is coupled to pH decrease remains unclear. Here, we report the cryo-electron microscopy structures of human TASK3 at neutral and acidic pH. Structural comparison revealed selectivity filter (SF) rearrangements upon acidification, characteristic of C-type inactivation, but with a unique structural basis. The extracellular mouth of the SF was prominently dilated and simultaneously blocked by a hydrophobic gate. His98 protonation shifted the conformational equilibrium between the conductive and C-type inactivated SF toward the latter by engaging a cation-π interaction with Trp78, consistent with molecular dynamics simulations and electrophysiological experiments. Our work illustrated how TASK3 is gated in response to extracellular pH change and implies how physiological stimuli might directly modulate the C-type gating of K2P channels.

Unraveling the Ligand-Binding Sites of CYP3A4 by Molecular Dynamics Simulations with Solvent Probes

Cytochrome P450 3A4 (CYP3A4) is one of the most important drug-metabolizing enzymes in the human body and is well known for its complicated, atypical kinetic characteristics. The existence of multiple ligand-binding sites in CYP3A4 has been widely recognized as being capable of interfering with the active pocket through allosteric effects. The identification of ligand-binding sites other than the canonical active site above the heme is especially important for understanding the atypical kinetic characteristics of CYP3A4 and the intriguing association between the ligand and the receptor. In this study, we first employed mixed-solvent molecular dynamics (MixMD) simulations coupled with the online computational predictive tools to explore potential ligand-binding sites in CYP3A4. The MixMD approach demonstrates better performance in dealing with the receptor flexibility compared with other computational tools. From the sites identified by MixMD, we then picked out multiple sites for further exploration using ensemble docking and conventional molecular dynamics (cMD) simulations. Our results indicate that three extra sites are suitable for ligand binding in CYP3A4, including one experimentally confirmed site and two novel sites.

Computational Investigation of the Covalent Inhibition Mechanism of Bruton's Tyrosine Kinase by Ibrutinib

Covalent inhibitors represent a promising class of therapeutic compounds. Nonetheless, rationally designing covalent inhibitors to achieve a right balance between selectivity and reactivity remains extremely challenging. To better understand the covalent binding mechanism, a computational study is carried out using the irreversible covalent inhibitor of Bruton tyrosine kinase (BTK) ibrutinib as an example. A multi-μs classical molecular dynamics trajectory of the unlinked inhibitor is generated to explore the fluctuations of the compound associated with the kinase binding pocket. Then, the reaction pathway leading to the formation of the covalent bond with the cysteine residue at position 481 via a Michael addition is determined using the string method in collective variables on the basis of hybrid quantum mechanical-molecular mechanical (QM/MM) simulations. The reaction pathway shows a strong correlation between the covalent bond formation and the protonation/deprotonation events taking place sequentially in the covalent inhibition reaction, consistent with a 3-step reaction with transient thiolate and enolates intermediate states. Two possible atomistic mechanisms affecting deprotonation/protonation events from the thiolate to the enolate intermediate were observed: a highly correlated direct pathway involving proton transfer to the Cα of the acrylamide warhead from the cysteine involving one or a few water molecules and a more indirect pathway involving a long-lived enolate intermediate state following the escape of the proton to the bulk solution. The results are compared with experiments by simulating the long-time kinetics of the reaction using kinetic modeling.

Modeling Zinc Complexes Using Neural Networks

Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build potential energy surfaces and explore chemical space. However, most of this work has focused on organic molecules due to the simplicity of their electronic structures as well as the availability of data sets. In this work, we build a deep learning architecture to model the energetics of zinc organometallic complexes. To achieve this, we have compiled a configurationally and conformationally diverse data set of zinc complexes using metadynamics to overcome the limitations of traditional sampling methods. In terms of the neural network potentials, our results indicate that for zinc complexes, partial charges play an important role in modeling the long-range interactions with a neural network. Our developed model outperforms semiempirical methods in predicting the relative energy of zinc conformers, yielding a mean absolute error (MAE) of 1.32 kcal/mol with reference to the double-hybrid PWPB95 method.

Why Does the E1219V Mutation Expand T-Rich PAM Recognition in Cas9 from Streptococcus pyogenes?

Popular RNA-guided DNA endonuclease Cas9 from Streptococcus pyogenes (SpCas9) recognizes the canonical 5'-NGG-3' protospacer adjacent motif (PAM) and triggers double-stranded DNA cleavage activity. Mutations in SpCas9 were demonstrated to expand the PAM readability and hold promise for therapeutic and genome editing applications. However, the energetics of the PAM recognition and its relation to the atomic structure remain unknown. Using the X-ray structure (precatalytic SpCas9:sgRNA:dsDNA) as a template, we calculated the change in the PAM binding affinity in response to SpCas9 mutations using computer simulations. The E1219V mutation in SpCas9 fine-tunes the water accessibility in the PAM binding pocket and promotes new interactions in the SpCas9:noncanonical T-rich PAM, thus weakening the PAM stringency. The nucleotide-specific interaction of two arginine residues (i.e., R1333 and R1335 of SpCas9) ensured stringent 5'-NGG-3' PAM recognition. R1335A substitution (SpCas9R1335A) completely disrupts the direct interaction between SpCas9 and PAM sequences (canonical or noncanonical), accounting for the loss of editing activity. Interestingly, the double mutant (SpCas9R1335A,E1219V) boosts DNA binding affinity by favoring protein:PAM electrostatic contact in a desolvated pocket. The underlying thermodynamics explain the varied DNA cleavage activity of SpCas9 variants. A direct link between the energetics, structures, and activity is highlighted, which can aid in the rational design of improved SpCas9-based genome editing tools.

Nonbonded Force Field Parameters from MBIS Partitioning of the Molecular Electron Density Improve Binding Affinity Predictions of the T4-Lysozyme Double Mutant

The use of computer simulation for binding affinity prediction is growing in drug discovery. However, its wider use is constrained by the accuracy of the free energy calculations. The key sources of error are the force fields used to depict molecular interactions and insufficient sampling of the configurational space. To improve the quality of the force field, we developed a Python-based computational workflow. The workflow described here uses the minimal basis iterative stockholder (MBIS) method to determine atomic charges and Lennard-Jones parameters from the polarized molecular density. This is done by performing electronic structure calculations on various configurations of the ligand when it is both bound and unbound. In addition, we validated a simulation procedure that accounts for the protein and ligand degrees of freedom to precisely calculate binding free energies. This was achieved by comparing the self-adjusted mixture sampling and nonequilibrium thermodynamic integration methods using various protein and ligand conformations. The accuracy of predicting binding affinity is improved by using MBIS-derived force field parameters and a validated simulation procedure. This improvement surpasses the chemical precision for the eight aromatic ligands, reaching a root-mean-square error of 0.7 kcal/mol.

Computational Insights into the Conformational Dynamics of HIV-1 Vpr in a Lipid Bilayer for Ion Channel Modeling

HIV-1 Vpr is a multifunctional accessory protein consisting of 96 amino acids that play a critical role in viral pathogenesis. Among its diverse range of activities, Vpr can create a cation-selective ion channel within the plasma membrane. However, the oligomeric state of this channel has not yet been elucidated. In this study, we investigated the conformational dynamics of Vpr helices to model the ion channel topology. First, we employed a series of multiscale simulations to investigate the specific structure of monomeric Vpr in a membrane model. During the lipid bilayer self-assembly coarse grain simulation, the C-terminal helix (residues 56-77) effectively formed the transmembrane region, while the N-terminal helix exhibited an amphipathic nature by associating horizontally with a single leaflet. All-atom molecular dynamics (MD) simulations of full-length Vpr inside a phospholipid bilayer show that the C-terminal helix remains very stable inside the bilayer core in a vertical orientation. Subsequently, using the predicted C-terminal helix orientation and conformation, various oligomeric states (ranging from tetramer to heptamer) possibly forming the Vpr ion channel were built and further evaluated. Among these models, the pentameric form exhibited consistent stability in MD simulations and displayed a compatible conformation for a water-assisted ion transport mechanism. This study provides structural insights into the ion channel activity of the Vpr protein and the foundation for developing therapeutics against HIV-1 Vpr-related conditions.

Binding Sites of Bicarbonate in Phosphoenolpyruvate Carboxylase

Phosphoenolpyruvate carboxylase (PEPC) is used in plant metabolism for fruit maturation or seed development as well as in the C4 and crassulacean acid metabolism (CAM) mechanisms in photosynthesis, where it is used for the capture of hydrated CO2 (bicarbonate). To find the yet unknown binding site of bicarbonate in this enzyme, we have first identified putative binding sites with nonequilibrium molecular dynamics simulations and then ranked these sites with alchemical free energy calculations with corrections of computational artifacts. Fourteen pockets where bicarbonate could bind were identified, with three having realistic binding free energies with differences with the experimental value below 1 kcal/mol. One of these pockets is found far from the active site at 14 Å and predicted to be an allosteric binding site. In the two other binding sites, bicarbonate is in direct interaction with the magnesium ion; neither sequence alignment nor the study of mutant K606N allowed to discriminate between these two pockets, and both are good candidates as the binding site of bicarbonate in phosphoenolpyruvate carboxylase.

Deciphering S100B Allosteric Signaling: The Role of a Peptide Target, TRTK-12, as an Ensemble Modulator

Allostery is an essential biological phenomenon in which perturbation at one site in a biomolecule elicits a functional response at a distal location(s). It is integral to biological processes, such as cellular signaling, metabolism, and transcription regulation. Understanding allostery is also crucial for rational drug discovery. In this work, we focus on an allosteric S100B protein that belongs to the S100 class of EF-hand Ca2+-binding proteins. The Ca2+-binding affinity of S100B is modulated allosterically by TRTK-12 peptide binding 25 Å away from the Ca2+-binding site. We investigated S100B allostery by carrying out nuclear magnetic resonance (NMR) measurements along with microsecond-long molecular dynamics (MD) simulations on S100B/Ca2+ with/without TRTK-12 at different NaCl salt concentrations. NMR HSQC results show that TRTK-12 reorganizes how S100B/Ca2+ responds to different salt concentrations at both orthosteric and allosteric sites. The MD data suggest that TRTK-12 breaks the dynamic aromatic and hydrogen-bond interactions (not observed in X-ray crystallographic structures) between the hinge/helix and Ca2+-binding EF-hand loop of the two subunits in the homodimeric protein. This triggers rearrangement in the protein network architectures and leads to allosteric communication. Finally, computational studies of S100B at distinct ionic strengths suggest that ligand-bound species are more robust to the changing environment relative to the S100B/Ca2+ complex.

An Unsupervised Machine Learning Approach for the Automatic Construction of Local Chemical Descriptors

Condensing the many physical variables defining a chemical system into a fixed-size array poses a significant challenge in the development of chemical Machine Learning (ML). Atom Centered Symmetry Functions (ACSFs) offer an intuitive featurization approach by means of a tedious and labor-intensive selection of tunable parameters. In this work, we implement an unsupervised ML strategy relying on a Gaussian Mixture Model (GMM) to automatically optimize the ACSF parameters. GMMs effortlessly decompose the vastness of the chemical and conformational spaces into well-defined radial and angular clusters, which are then used to build tailor-made ACSFs. The unsupervised exploration of the space has demonstrated general applicability across a diverse range of systems, spanning from various unimolecular landscapes to heterogeneous databases. The impact of the sampling technique and temperature on space exploration is also addressed, highlighting the particularly advantageous role of high-temperature Molecular Dynamics (MD) simulations. The reliability of the resulting features is assessed through the estimation of the atomic charges of a prototypical capped amino acid and a heterogeneous collection of CHON molecules. The automatically constructed ACSFs serve as high-quality descriptors, consistently yielding typical prediction errors below 0.010 electrons bound for the reported atomic charges. Altering the spatial distribution of the functions with respect to the cluster highlights the critical role of symmetry rupture in achieving significantly improved features. More specifically, using two separate functions to describe the lower and upper tails of the cluster results in the best performing models with errors as low as 0.006 electrons. Finally, the effectiveness of finely tuned features was checked across different architectures, unveiling the superior performance of Gaussian Process (GP) models over Feed Forward Neural Networks (FFNNs), particularly in low-data regimes, with nearly a 2-fold increase in prediction quality. Altogether, this approach paves the way toward an easier construction of local chemical descriptors, while providing valuable insights into how radial and angular spaces should be mapped. Finally, this work opens the possibility of encoding many-body information beyond angular terms into upcoming ML features.

Calcium-Driven In Silico Inactivation of a Human Olfactory Receptor

Conformational changes as well as molecular determinants related to the activation and inactivation of olfactory receptors are still poorly understood due to the intrinsic difficulties in the structural determination of this GPCR family. Here, we perform, for the first time, the in silico inactivation of human olfactory receptor OR51E2, highlighting the possible role of calcium in this receptor state transition. Using molecular dynamics simulations, we show that a divalent ion in the ion binding site, coordinated by two acidic residues at positions 2.50 and 3.39 conserved across most ORs, stabilizes the receptor in its inactive state. In contrast, protonation of the same two acidic residues is not sufficient to drive inactivation within the microsecond timescale of our simulations. Our findings suggest a novel molecular mechanism for OR inactivation, potentially guiding experimental validation and offering insights into the possible broader role of divalent ions in GPCR signaling.

Helical Content Correlations and Hydration Structures of the Folding Ensemble of the B Domain of Protein A

The B domain of protein A (BdpA), a small three-helix bundle, folds on a time scale of a few microseconds with heterogeneous native and unfolded states. It is widely used as a model for understanding protein folding mechanisms. In this work, we use structure-based models (SBMs) and atomistic simulations to comprehensively investigate how BdpA folding is associated with the formation of its secondary structure. The energy landscape visualization method (ELViM) was used to characterize the pathways that connect the folded and unfolded states of BdpA as well as the sets of structures displaying specific ellipticity patterns. We show that the native state conformational diversity is due mainly to the conformational variability of helix I. Helices I, II, and III occur in a weakly correlated manner, with Spearman's rank correlation coefficients of 0.1539 (I and II), 0.1259 (I and III), and 0.2561 (II and III). These results, therefore, suggest the highest cooperativity between helices II and III. Our results allow the clustering of partially folded structures of folding of the B domain of protein A on the basis of its secondary structure, paving the way to an understanding of environmental factors in the relative stability of the basins of the folding ensemble, which are illustrated by the structural dependency of the protein hydration structures, as computed with minimum-distance distribution functions.

Molecular Insights into the Variability in Infection and Immune Evasion Capabilities of SARS-CoV-2 Variants: A Sequence and Structural Investigation of the RBD Domain

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continuously emerge, an increasing number of mutations are accumulating in the Spike protein receptor-binding domain (RBD) region. Through sequence analysis of various Variants of Concern (VOC), we identified that they predominantly fall within the ο lineage although recent variants introduce any novel mutations in the RBD. Molecular dynamics simulations were employed to compute the binding free energy of these variants with human Angiotensin-converting enzyme 2 (ACE2). Structurally, the binding interface of the ο RBD displays a strong positive charge, complementing the negatively charged binding interface of ACE2, resulting in a significant enhancement in the electrostatic potential energy for the ο variants. Although the increased potential energy is partially offset by the rise in polar solvation free energy, enhanced electrostatic potential contributes to the long-range recognition between the ο variant's RBD and ACE2. We also conducted simulations of glycosylated ACE2-RBD proteins. The newly emerged ο (JN.1) variant has added a glycosylation site at N-354@RBD, which significantly weakened its binding affinity with ACE2. Further, our interaction studies with three monoclonal antibodies across multiple SARS-CoV-2 strains revealed a diminished neutralization efficacy against the ο variants, primarily attributed to the electrostatic repulsion between the antibodies and RBD interface. Considering the characteristics of the ο variant and the trajectory of emerging strains, we propose that newly developed antibodies against SARS-CoV-2 RBD should have surfaces rich in negative potential and, postbinding, exhibit strong van der Waals interactions. These findings provide invaluable guidance for the formulation of future therapeutic strategies.

Molecular Insights into the Differential Effects of Acetylation on the Aggregation of Tau Microtubule-Binding Repeats

Aggregation of tau protein into intracellular fibrillary inclusions is characterized as the hallmark of tauopathies, including Alzheimer's disease and chronic traumatic encephalopathy. The microtubule-binding (MTB) domain of tau, containing either three or four repeats with sequence similarities, plays an important role in determining tau's aggregation. Previous studies have reported that abnormal acetylation of lysine residues displays a distinct effect on the formation of pathological tau aggregates. However, the underlying molecular mechanism remains mostly elusive. In this study, we performed extensive replica exchange molecular dynamics (REMD) simulations of 144 μs in total to systematically investigate the dimerization of four tau MTB repeats and explore the impacts of Lys280 (K280) or Lys321 (K321) acetylation on the conformational ensembles of the R2 or R3 dimer. Our results show that R3 is the most prone to aggregation among the four repeats, followed by R2 and R4, while R1 displays the weakest aggregation propensity with a disordered structure. Acetylation of K280 could promote the aggregation of R2 peptides by increasing the formation of β-sheet structures and strengthening the interchain interaction. However, K321 acetylation decreases the β-sheet content of the R3 dimer, reduces the ability of R3 peptides to form long β-strands, and promotes the stable helix structure formation. The salt bridge and Y310-Y310 π-π stacking interactions of the R3 dimer are greatly weakened by K321 acetylation, resulting in the inhibition of dimerization. This study uncovers the structural ensembles of tau MTB repeats and provides mechanistic insights into the influences of acetylation on tau aggregation, which may deepen the understanding of the pathogenesis of tauopathies.