Restrained electrostatic potential atomic partial charges for condensed-phase simulations of carbohydrates

Structure-Activity Relationship of Synthetic Linear KTS-Peptides Containing Meta-Aminobenzoic Acid as Antagonists of α1β1 Integrin with Anti-Angiogenic and Melanoma Anti-Tumor Activities

To develop peptide drugs targeting integrin receptors, synthetic peptide ligands endowed with well-defined selective binding motifs are necessary. The snake venom KTS-containing disintegrins, which selectively block collagen α1β1 integrin, were used as lead compounds for the synthesis and structure-activity relationship of a series of linear peptides containing the KTS-pharmacophore and alternating natural amino acids and 3-aminobenzoic acid (MABA). To ensure a better stiffness and metabolic stability, one, two and three MABA residues, were introduced around the KTS pharmacophore motif. Molecular dynamics simulations determined that the solution conformation of MABA peptide 4 is more compact, underwent larger conformational changes until convergence, and spent most of the time in a single cluster. The peptides' binding affinity has been characterized by an enzyme linked immunosorbent assay in which the most potent peptide 4 inhibited with IC50 of 324 ± 8 µM and 550 ± 45 µM the binding of GST-α1-A domain to collagen IV fragment CB3, and the cell adhesion to collagen IV using α1-overexpressor cells, respectively. Docking studies and MM-GBSA calculations confirmed that peptide 4 binds a smaller region of the integrin near the collagen-binding site and penetrated deeper into the binding site near Trp1. Peptide 4 inhibited tube formation by endothelial cell migration in the Matrigel angiogenesis in vitro assay. Peptide 4 was acutely tolerated by mice, showed stability in human serum, decreased tumor volume and angiogenesis, and significantly increased the survival of mice injected with B16 melanoma cells. These findings propose that MABA-peptide 4 can further serve as an α1β1-integrin antagonist lead compound for further drug optimization in angiogenesis and cancer therapy.

Elucidating the binding mechanisms of GABA and Muscimol as an avenue to discover novel GABA-mimetic small molecules

Gamma-aminobutyric acid (GABA) signaling is the principal inhibitory pathway in the central nervous system. It is critical in neuronal cell proliferation and fate determination. Any aberration in GABA inhibition results in psychiatric and neurological diseases. Thus, modulating GABAergic neurotransmission has become the basis of drug therapy for psychiatric and several neurological diseases. Though GABA and muscimol are classical inhibitors of GABA receptors, the search for novel inhibitors continues unabated. In this study, the binding mechanism of GABA and muscimol was elucidated and applied in the search for small molecule GABAergic inhibitors using comprehensive computational techniques. It was revealed that a high-affinity binding of GABA and muscimol was mediated by a water molecule involving α1Thr129 and then stabilized by strong interactions including salt bridges with β2Glu155 and α1Arg66 amidst hydrogen bonds, π-π stacking, and π -cation interactions with other residues. The binding of GABA and muscimol was also characterized by stability and deeper penetration into the hydrophobic core of the protein which resulted in conformational changes of the binding pocket and domain, by inducing correlated motions of the residues. Thermodynamics analysis showed GABA and muscimol exhibited total binding free energies of -19.85 ± 8.83 Kcal/mol and -26.55 ± 3.42 Kcal/mol, respectively. A pharmacophore model search, based on the energy contributions of implicating binding residues, resulted in the identification of ZINC68604167, ZINC19735138, ZINC04202466, ZINC00901626, and ZINC01532854 as potential GABA-mimetic compounds from metabolites and natural products libraries. This study has elucidated the binding mechanisms of GABA and muscimol and successfully applied in the identification of GABA-mimetic compounds.Communicated by Ramaswamy H. Sarma.

Oligo-PROTAC strategy for cell-selective and targeted degradation of activated STAT3

Decoy oligodeoxynucleotides (ODNs) allow targeting undruggable transcription factors, such as STAT3, but their limited potency and lack of delivery methods hampered translation. To overcome these challenges, we conjugated a STAT3-specific decoy to thalidomide, a ligand to cereblon in E3 ubiquitin ligase complex, to generate a proteolysis-targeting chimera (STAT3DPROTAC). STAT3DPROTAC downregulated STAT3 in target cells, but not STAT1 or STAT5. Computational modeling of the STAT3DPROTAC ternary complex predicted two surface lysines, K601 and K626, in STAT3 as potential ubiquitination sites. Accordingly, K601/K626 point mutations in STAT3, as well as proteasome inhibition or cereblon deletion, alleviated STAT3DPROTAC effect. Next, we conjugated STAT3DPROTAC to a CpG oligonucleotide targeting Toll-like receptor 9 (TLR9) to generate myeloid/B cell-selective C-STAT3DPROTAC. Naked C-STAT3DPROTAC was spontaneously internalized by TLR9+ myeloid cells, B cells, and human and mouse lymphoma cells but not by T cells. C-STAT3DPROTAC effectively decreased STAT3 protein levels and also STAT3-regulated target genes critical for lymphoma cell proliferation and/or survival (BCL2L1, CCND2, and MYC). Finally, local C-STAT3DPROTAC administration to human Ly3 lymphoma-bearing mice triggered tumor regression, while control C-STAT3D and C-SCR treatments had limited effects. Our results underscore the feasibility of using a PROTAC strategy for cell-selective, decoy oligonucleotide-based STAT3 targeting of and potentially other tumorigenic transcription factors for cancer therapy.

Unusual catalytic strategy by non-heme Fe(ii)/2-oxoglutarate-dependent aspartyl hydroxylase AspH

Biocatalytic C-H oxidation reactions are of important synthetic utility, provide a sustainable route for selective synthesis of important organic molecules, and are an integral part of fundamental cell processes. The multidomain non-heme Fe(ii)/2-oxoglutarate (2OG) dependent oxygenase AspH catalyzes stereoselective (3R)-hydroxylation of aspartyl- and asparaginyl-residues. Unusually, compared to other 2OG hydroxylases, crystallography has shown that AspH lacks the carboxylate residue of the characteristic two-His-one-Asp/Glu Fe-binding triad. Instead, AspH has a water molecule that coordinates Fe(ii) in the coordination position usually occupied by the Asp/Glu carboxylate. Molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) studies reveal that the iron coordinating water is stabilized by hydrogen bonding with a second coordination sphere (SCS) carboxylate residue Asp721, an arrangement that helps maintain the six coordinated Fe(ii) distorted octahedral coordination geometry and enable catalysis. AspH catalysis follows a dioxygen activation-hydrogen atom transfer (HAT)-rebound hydroxylation mechanism, unusually exhibiting higher activation energy for rebound hydroxylation than for HAT, indicating that the rebound step may be rate-limiting. The HAT step, along with substrate positioning modulated by the non-covalent interactions with SCS residues (Arg688, Arg686, Lys666, Asp721, and Gln664), are essential in determining stereoselectivity, which likely proceeds with retention of configuration. The tetratricopeptide repeat (TPR) domain of AspH influences substrate binding and manifests dynamic motions during catalysis, an observation of interest with respect to other 2OG oxygenases with TPR domains. The results provide unique insights into how non-heme Fe(ii) oxygenases can effectively catalyze stereoselective hydroxylation using only two enzyme-derived Fe-ligating residues, potentially guiding enzyme engineering for stereoselective biocatalysis, thus advancing the development of non-heme Fe(ii) based biomimetic C-H oxidation catalysts, and supporting the proposal that the 2OG oxygenase superfamily may be larger than once perceived.

Cyclic peptides discriminate BCL-2 and its clinical mutants from BCL-XL by engaging a single-residue discrepancy

Overexpressed pro-survival B-cell lymphoma-2 (BCL-2) family proteins BCL-2 and BCL-XL can render tumor cells malignant. Leukemia drug venetoclax is currently the only approved selective BCL-2 inhibitor. However, its application has led to an emergence of resistant mutations, calling for drugs with an innovative mechanism of action. Herein we present cyclic peptides (CPs) with nanomolar-level binding affinities to BCL-2 or BCL-XL, and further reveal the structural and functional mechanisms of how these CPs target two proteins in a fashion that is remarkably different from traditional small-molecule inhibitors. In addition, these CPs can bind to the venetoclax-resistant clinical BCL-2 mutants with similar affinities as to the wild-type protein. Furthermore, we identify a single-residue discrepancy between BCL-2 D111 and BCL-XL A104 as a molecular "switch" that can differently engage CPs. Our study suggests that CPs may inhibit BCL-2 or BCL-XL by delicately modulating protein-protein interactions, potentially benefiting the development of next-generation therapeutics.

Insight into the Molecular Mechanism of Surface Interactions of Phosphatidylcholines─Langmuir Monolayer Study Complemented with Molecular Dynamics Simulations

Mutual interactions between components of biological membranes are pivotal for maintaining their proper biophysical properties, such as stability, fluidity, or permeability. The main building blocks of biomembranes are lipids, among which the most important are phospholipids (mainly phosphatidylcholines (PCs)) and sterols (mainly cholesterol). Although there is a plethora of reports on interactions between PCs, as well as between PCs and cholesterol, their molecular mechanism has not yet been fully explained. Therefore, to resolve this issue, we carried out systematic investigations based on the classical Langmuir monolayer technique complemented with molecular dynamics simulations. The studies involved systems containing 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) analogues possessing in the structure one or two polar functional groups similar to those of DPPC. The interactions and rheological properties of binary mixtures of DPPC analogues with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and cholesterol were compared with reference systems (DPPC/POPC and DPPC/cholesterol). This pointed to the importance of the ternary amine group in PC/cholesterol interactions, while in PC mixtures, the phosphate group played a key role. In both cases, the esterified glycerol group had an effect on the magnitude of interactions. The obtained results are crucial for establishing structure-property relationships as well as for designing substitutes for natural lipids.

Prediction of toluene/water partition coefficients of SAMPL9 compounds: comparison of the molecular dynamics force fields GAFF/RESP and GAFF/IPolQ-Mod + LJ-fit

The SAMPL9 blind challenge aims to predict the toluene/water partition coefficient of 16 active pharmaceutical ingredients. In this work, the transfer free energy between the solvation in water and toluene is predicted by molecular dynamics simulations using the MBAR method [M. R. Shirts and J. D. Chodera, J. Chem. Phys., 2008, 129, 123105] with replica exchange molecular dynamics [Y. Sugita, A. Kitao and Y. Okamoto, J. Chem. Phys., 2000, 113, 6042-6051]. Thereby, simulation results using the force field GAFF/IPolQ-Mod + LJ-fit [A. Mecklenfeld and G. Raabe, ADMET and DMPK, 2020, 8, 274-296] are compared to simulations with the standard GAFF/RESP model [J. Wang, R. M. Wolf, J. W. Caldwell, P. A. Kollman and D. A. Case, J. Comput. Chem., 2004, 25, 1157-1174]. By statistical evaluation of RMSD and R2, we compare the results with other participants of the blind challenge. Furthermore, we provide a detailed analysis of solvation structures using the combined distribution function for simulations in water and the plane projection analysis for simulations in toluene, and we work out differences and similarities of the two force fields. These studies allow to gain important insights to increase the understanding of the mechanism of interactions between the drugs and the solvent.

Insights from in silico exploration of major curcumin analogs targeting human dipeptidyl peptidase IV

The goal of this work is to use a variety of in-silico techniques to identify anti-diabetic agents against DPP-IV enzyme from five main curcumin analogues. To produce the successful molecules, five main curcumin analogues were docked into the active site of DPP-IV enzyme. In comparison to the control molecule (Saxagliptin, -6.9 kcal/mol), all the compounds have the highest binding affinity (-7.6 to -7.7 kcal/mol) for the DPP-IV enzyme. These compounds underwent further testing for studies on drug-likeness, pharmacokinetics, and acute toxicity to see the efficacy and safety of compounds. To assess the stability of the docking complex and the binding posture identified during the docking experiment, our study got THC as the lead compound, which was then exposed to 200 ns of molecular dynamic simulation and PCA analysis. Additionally, DFT calculations were conducted to determine the thermodynamic, molecular orbital, and electrostatic potential characteristics of lead compound. Overall, the lead chemical has shown strong drug-like properties, is non-toxic, and has a sizable affinity for the DPP-IV enzyme.Communicated by Ramaswamy H. Sarma.

Molecular Dynamics Simulations for Rationalizing Polymer Bioconjugation Strategies: Challenges, Recent Developments, and Future Opportunities

The covalent modification of proteins with polymers is a well-established method for improving the pharmacokinetic properties of therapeutically valuable biologics. The conjugated polymer chains of the resulting hybrid represent highly flexible macromolecular structures. As the dynamics of such systems remain rather elusive for established experimental techniques from the field of protein structure elucidation, molecular dynamics simulations have proven as a valuable tool for studying such conjugates at an atomistic level, thereby complementing experimental studies. With a focus on new developments, this review aims to provide researchers from the polymer bioconjugation field with a concise and up to date overview of such approaches. After introducing basic principles of molecular dynamics simulations, as well as methods for and potential pitfalls in modeling bioconjugates, the review illustrates how these computational techniques have contributed to the understanding of bioconjugates and bioconjugation strategies in the recent past and how they may lead to a more rational design of novel bioconjugates in the future.

Performance of point charge embedding schemes for excited states in molecular organic crystals

Modeling excited state processes in molecular crystals is relevant for several applications. A popular approach for studying excited state molecular crystals is to use cluster models embedded in point charges. In this paper, we compare the performance of several embedding models in predicting excited states and S1-S0 optical gaps for a set of crystals from the X23 molecular crystal database. The performance of atomic charges based on ground or excited states was examined for cluster models, Ewald embedding, and self-consistent approaches. We investigated the impact of various factors, such as the level of theory, basis sets, embedding models, and the level of localization of the excitation. We consider different levels of theory, including time-dependent density functional theory and Tamm-Dancoff approximation (TDA) (DFT functionals: ωB97X-D and PBE0), CC2, complete active space self-consistent field, and CASPT2. We also explore the impact of selection of the QM region, charge leakage, and level of theory for the description of different kinds of excited states. We implemented three schemes based on distance thresholds to overcome overpolarization and charge leakage in molecular crystals. Our findings are compared against experimental data, G0W0-BSE, periodic TDA, and optimally tuned screened range-separated functionals.

Self-assembly morphology transition mechanism of similar amphiphilic molecules

Molecular self-assembly is a powerful synthesis method for nanomaterials. Promoting the development of self-assembly is not only conducive to the efficient preparation of nanomaterials but also promotes progress in other research fields. Therefore, it is necessary to enhance the advancement of molecular self-assembly, and the key is to deepen the understanding of the correlation between molecular characteristics and self-assembly morphologies. However, some similar amphipihlic molecules self-assemble into assemblies with significant morphology difference, which is challenging to clear the mechanism for experimenters. In this work, we explore the microscopic mechanism of six similar molecules by MD simulations, and the influences of molecular conformation, atomic groups, and polycyclic aromatic hydrocarbons on morphologies are discussed in detail. Our findings enrich the design principles of amphiphilic molecules for self-assembly, which promotes the modular design of molecular self-assembly.

Speeding-up Hybrid Functional-Based Ab Initio Molecular Dynamics Using Multiple Time-stepping and Resonance-Free Thermostat

Ab initio molecular dynamics (AIMD) based on density functional theory (DFT) has become a workhorse for studying the structure, dynamics, and reactions in condensed matter systems. Currently, AIMD simulations are primarily carried out at the level of generalized gradient approximation (GGA), which is at the second rung of DFT functionals in terms of accuracy. Hybrid DFT functionals, which form the fourth rung in the accuracy ladder, are not commonly used in AIMD simulations as the computational cost involved is 100 times or higher. To facilitate AIMD simulations with hybrid functionals, we propose here an approach using multiple time stepping with adaptively compressed exchange operator and resonance-free thermostat, that could speed up the calculations by ∼30 times or more for systems with a few hundred of atoms. We demonstrate that by achieving this significant speed up and making the compute time of hybrid functional-based AIMD simulations at par with that of GGA functionals, we are able to study several complex condensed matter systems and model chemical reactions in solution with hybrid functionals that were earlier unthinkable to be performed.

Insights into the structure and Ion transport of pectin-[BMIM][PF6] electrolytes

We investigate the effect of pectin on the structure and ion transport properties of the room-temperature ionic liquid electrolyte 1-n-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF6]) using molecular dynamics simulations. We find that pectin induces intriguing structural changes in the electrolyte that disrupt large ionic aggregates and promote the formation of smaller ionic clusters, which is a promising finding for ionic conductivity. Due to pectin in [BMIM][PF6] electrolytes, the diffusion coefficient of cations and anions is observed to decrease by a factor of four for a loading of 25 wt. % of pectin in [BMIM][PF6] electrolyte. A strong correlation between the ionic diffusivities (D) and ion-pair relaxation timescales (τc) is observed such that D ∼ τc-0.75 for cations and D ∼ τc-0.82 for anions. The relaxation timescale exponents indicate that the ion transport mechanisms in pectin-[BMIM][PF6] electrolytes are slightly distinct from those found in neat [BMIM][PF6] electrolytes (D∼τc-1). Since pectin marginally affects ionic diffusivities at the gain of smaller ionic aggregates and viscosity, our results suggest that pectin-ionic liquid electrolytes offer improved properties for battery applications, including ionic conductivity, mechanical stability, and biodegradability.

Selective Adsorption of Organic Micro-Pollutants by Smectite Clays Revealed from Atomistic Simulations

In this study, atomistic simulations were carried out to study the difference in the adsorption process between two similar molecules, diazepam and oxazepam, on Na+-montmorillonite. Kinetic and XRD measurements showed a contrasting adsorption mechanism of these two molecules, differing only by the presence/absence of methyl and hydroxyl groups, with a larger adsorption amount and intercalation for the oxazepam. The structural characterization of these molecules was investigated through DFT calculations and showed the vicinity of hydroxyl and carbonyl groups for only the chair conformation of oxazepam compared to the boat conformation. Classical molecular dynamics simulations of diazepam and the two forms of oxazepam on the external surface of Na+-montmorillonite highlighted the better coordination of the oxazepam-chair conformation, compared to its boat counterpart and diazepam. This has been confirmed through DFT calculations, from which a coordination energy that is greater by 10 kcal·mol-1 is observed. This strongly suggests that the experimentally observed intercalation of oxazepam occurs only in the chair form because of the strong coordination with the Na+ cation present in the Na-Mt interlayer. Classical MD simulations of the intercalated oxazepam chair molecule in the Na-Mt interlayer allowed the evaluation of the interlayer spacing d001, which was in very good agreement with the experimental XRD measurement.

Catalysis by KDM6 Histone Demethylases - A Synergy between the Non-Heme Iron(II) Center, Second Coordination Sphere, and Long-Range Interactions

KDM6A (UTX) and KDM6B (JMJD3) are human non-heme Fe(II) and 2-oxoglutarate (2OG) dependent JmjC oxygenases that catalyze the demethylation of trimethylated lysine 27 in the N-terminal tail of histone H3, a post-translational modification that regulates transcription. A Combined Quantum Mechanics/ Molecular Mechanics (QM/MM) and Molecular Dynamics (MD) study on the catalytic mechanism of KDM6A/B reveals that the transition state for the rate-limiting hydrogen atom transfer (HAT) reaction in KDM6A catalysis is stabilized by polar (Asn217) and aromatic (Trp369)/non-polar (Pro274) residues in contrast to KDM4, KDM6B and KDM7 demethylases where charged residues (Glu, Arg, Asp) are involved. KDM6A employs both σ- and π-electron transfer pathways for HAT, whereas KDM6B employs the σ-electron pathway. Differences in hydrogen bonding of the Fe-chelating Glu252(KDM6B) contribute to the lower energy barriers in KDM6B vs. KDM6A. The study reveals a dependence of the activation barrier of the rebound hydroxylation on the Fe-O-C angle in the transition state of KDM6A. Anti-correlation of the Zn-binding domain with the active site residues is a key factor distinguishing KDM6A/B from KDM7/4s. The results reveal the importance of communication between the Fe center, second coordination sphere, and long-range interactions in catalysis by KDMs and, by implication, other 2OG oxygenases.

Pathway for Water Transport through Breathable Nanocomposite Membranes of PEBAX with Ionic Liquid [C12C1im]Cl

Water transport through membranes is an attractive topic among the research dedicated to dehydration processes, microenvironment regulation, or more simply, recovery of freshwater. Herein, an atomistic computer simulation is proposed to provide new insights about a water vapor transport mechanism through PEBAX membranes filled with ionic liquid (IL) [C12C1im]Cl. Starting from experimental evidence that indicates an effective increase in water permeation as the IL is added to the polymer matrix (e.g., up to 85·10-3 (g·m)/(m2·day) at 318.15 K for PEBAX@2533 membranes loaded with 70% of IL), molecular dynamics simulations are proposed to explore the key role of IL in water transport inside membranes. The polar region composed of anions and cationic head groups of the IL is demonstrated to serve as the pathway for water transport through the membrane. Water molecules always stay near the pathway, which becomes wider and thus has a larger water-accessible area with increasing IL concentration. Hence, the diffusion coefficients of water molecules and ions increase as the IL concentration increases. The simulation provides useful indications about a microscopic mechanism that regulates the transport of water vapor through a kind of PEBAX/IL membrane, resulting in full agreement with the experimental evidence.

C≡N Stretching Frequency as a Convenient Reporter of Charge Separation in Molecular Systems

Previously, several studies have shown that, for a set of structurally related nitrile compounds, there could be a linear relationship between the total charge on the nitrile group (qCN) and its stretching frequency (νCN). However, it is unclear whether the corresponding frequency and charge properties of structurally different nitrile compounds can be described by a single linear νCN-qCN relationship. Herein, we compute the qCN magnitudes of a large number of nitrile-containing molecules whose νCN values cover a spectral range of ca. 200 cm-1 and are measured under different experimental conditions. Our results reveal that νCN indeed exhibits a linear dependence on qCN, with a slope of 637 ± 30 cm-1/charge. Because the nitrile moiety is a commonly used building block in electronic donor-acceptor (D-A) molecular systems, we believe that this linear relationship will find utility in a wide range of applications where such D-A constructs are used, such as in organic photovoltaic assemblies. In addition, we apply this linear relationship to characterize the degree of charge transfer upon photoexcitation of two indole derivatives, 5-cyanoindole and 6-cyanoindole, and are able to show that in both cases, the fluorescence emission arises from a charge-transfer or La state.

Oligo-PROTAC strategy for cell-selective and targeted degradation of activated STAT3

Decoy-oligodeoxynucleotides (D-ODNs) can target undruggable transcription factors, such as STAT3. However, challenges in D-ODN delivery and potency hampered their translation. To overcome these limitations, we conjugated STAT3-specific D-ODN to thalidomide (Tha), a known ligand to cereblon (CRBN, a component of E3 ubiquitin ligase) to generate a proteolysis-targeting chimera (STAT3D PROTAC ). STAT3D PROTAC downregulated STAT3, but not STAT1 or STAT5, in target cells. Computational modeling of the STAT3D PROTAC ternary complex predicted two surface lysines on STAT3, K601 and K626 as potential ubiquitination sites for the PROTAC bound E3 ligase. Accordingly, K601/K626 point mutations in STAT3, as well as proteasome inhibitors, and CRBN deletion alleviated STAT3D PROTAC effect. Next, we conjugated STAT3D PROTAC to a CpG ligand targeting Toll-like receptor 9 (TLR9) to generate myeloid/B-cell-selective C-STAT3D PROTAC conjugate. Naked C-STAT3D PROTAC was spontaneously internalized by TLR9 + myeloid cells, B cells as well as human Ly18 and mouse A20 lymphoma cells, but not by T cells. C-STAT3D PROTAC decreased STAT3 levels to 50% at 250 nM and over 85% at 2 µM dosing in myeloid cells. We also observed significantly improved downregulation of STAT3 target genes involved in lymphoma cell proliferation and/or survival ( BCL2L1, CCND2, MYC ). Finally, we assessed the antitumor efficacy of C-STAT3D PROTAC compared to C-STAT3D or scrambled control (C-SCR) against human lymphoma xenotransplants. Local C-STAT3D PROTAC administration triggered lymphoma regression while control treatments had limited effects. Our results underscore feasibility of using PROTAC strategy for cell-selective, decoy oligonucleotide-based targeting of STAT3 and potentially other tumorigenic transcription factors for cancer therapy.

Application of molecular dynamics simulation in the field of food enzymes: improving the thermal-stability and catalytic ability

Enzymes can produce high-quality food with low pollution, high function, high acceptability, and medical aid. However, most enzymes, in their native form, do not meet the industrial requirements. Sequence-based and structure-based methods are the two main strategies used for enzyme modification. Molecular Dynamics (MD) simulation is a sufficiently comprehensive technology, from a molecular perspective, which has been widely used for structure information analysis and enzyme modification. In this review, we summarize the progress and development of MD simulation, particularly for software, force fields, and a standard procedure. Subsequently, we review the application of MD simulation in various food enzymes for thermostability and catalytic improvement was reviewed in depth. Finally, the limitations and prospects of MD simulation in food enzyme modification research are discussed. This review highlights the significance of MD simulation and its prospects in food enzyme modification.

The opening dynamics of the lateral gate regulates the activity of rhomboid proteases

Rhomboid proteases hydrolyze substrate helices within the lipid bilayer to release soluble domains from the membrane. Here, we investigate the mechanism of activity regulation for this unique but wide-spread protein family. In the model rhomboid GlpG, a lateral gate formed by transmembrane helices TM2 and TM5 was previously proposed to allow access of the hydrophobic substrate to the shielded hydrophilic active site. In our study, we modified the gate region and either immobilized the gate by introducing a maleimide-maleimide (M2M) crosslink or weakened the TM2/TM5 interaction network through mutations. We used solid-state nuclear magnetic resonance (NMR), molecular dynamics (MD) simulations, and molecular docking to investigate the resulting effects on structure and dynamics on the atomic level. We find that variants with increased dynamics at TM5 also exhibit enhanced activity, whereas introduction of a crosslink close to the active site strongly reduces activity. Our study therefore establishes a strong link between the opening dynamics of the lateral gate in rhomboid proteases and their enzymatic activity.

Lysine vitcylation is a novel vitamin C-derived protein modification that enhances STAT1-mediated immune response

Vitamin C (vitC) is a vital nutrient for health and also used as a therapeutic agent in diseases such as cancer. However, the mechanisms underlying vitC's effects remain elusive. Here we report that vitC directly modifies lysine without enzymes to form vitcyl-lysine, termed "vitcylation", in a dose-, pH-, and sequence-dependent manner across diverse proteins in cells. We further discover that vitC vitcylates K298 site of STAT1, which impairs its interaction with the phosphatase PTPN2, preventing STAT1 Y701 dephosphorylation and leading to increased STAT1-mediated IFN pathway activation in tumor cells. As a result, these cells have increased MHC/HLA class-I expression and activate immune cells in co-cultures. Tumors collected from vitC-treated tumor-bearing mice have enhanced vitcylation, STAT1 phosphorylation and antigen presentation. The identification of vitcylation as a novel PTM and the characterization of its effect in tumor cells opens a new avenue for understanding vitC in cellular processes, disease mechanisms, and therapeutics.

Trans-palmitoleic acid, a dairy fat biomarker, stimulates insulin secretion and activates G protein-coupled receptors with a different mechanism from the cis isomer

Dietary trans-palmitoleic acid (trans 16:1n-7, tPOA), a biomarker for high-fat dairy product intake, has been associated with a lower risk of type 2 diabetes mellitus (T2DM) in some cross-sectional and prospective epidemiological studies. Here, we investigated the insulin secretion-promoting activity of tPOA and compared them with the effects evoked by the cis-POA isomer (cPOA), an endogenous lipokine biosynthesized in the liver and adipose tissue, and found in some natural food sources. The debate about the positive and negative relationships of those two POA isomers with metabolic risk factors and the underlying mechanisms is still going on. Therefore, we examined the potency of both POA isomers to potentiate insulin secretion in murine and human pancreatic β cell lines. We also investigated whether POA isomers activate G protein-coupled receptors proposed as potential targets for T2DM treatment. We show that tPOA and cPOA augment glucose-stimulated insulin secretion (GSIS) to a similar extent; however, their insulin secretagogue activity is associated with different signaling pathways. We also performed ligand docking and molecular dynamics simulations to predict the preferred orientation of POA isomers and the strength of association between those two fatty acids and GPR40, GPR55, GPR119, and GPR120 receptors. Overall, this study provides insight into the bioactivity of tPOA and cPOA toward selected GPCR functions, indicating them as targets responsible for the insulin secretagogue action of POA isomers. It reveals that both tPOA and cPOA may promote insulin secretion and subsequently regulate glucose homeostasis.

Water Influence on the Physico-Chemical Properties and 3D Printability of Choline Acrylate-Bacterial Cellulose Inks

The aim of this work was to study the influence of water as a co-solvent on the interaction between a polymerizable ionic liquid-choline acrylate (ChA)-and bacterial cellulose. Bacterial cellulose dispersed in ChA is a new type of UV-curable biopolymer-based ink that is a prospective material for the 3D printing of green composite ion-gels. Higher cellulose content in inks is beneficial for the ecological and mechanical properties of materials, and leads to increased viscosity and the yield stress of such systems and hampers printability. It was found that the addition of water results in (1) a decrease in the solvent viscosity and yield stress; and (2) a decrease in the stability of dispersion toward phase separation under stress. In this work, an optimal composition in the range of 30-40 wt% water content demonstrating 97-160 Pa of yield stress was found that ensures the printability and stability of inks. The rheological properties of inks and mechanical characteristics (0.7-0.8 MPa strength and 1.1-1.2 MPa Young's modulus) were obtained. The mechanism of influence of the ratio ChA/water on the properties of ink was revealed with atomic force microscopy, wide-angle X-ray diffraction studies of bacterial cellulose after regeneration from solvent, and computer simulation of ChA/water mixtures and their interaction with the cellulose surface.

Does a Machine-Learned Potential Perform Better Than an Optimally Tuned Traditional Force Field? A Case Study on Fluorohydrins

We present a comparative study that evaluates the performance of a machine learning potential (ANI-2x), a conventional force field (GAFF), and an optimally tuned GAFF-like force field in the modeling of a set of 10 γ-fluorohydrins that exhibit a complex interplay between intra- and intermolecular interactions in determining conformer stability. To benchmark the performance of each molecular model, we evaluated their energetic, geometric, and sampling accuracies relative to quantum-mechanical data. This benchmark involved conformational analysis both in the gas phase and chloroform solution. We also assessed the performance of the aforementioned molecular models in estimating nuclear spin-spin coupling constants by comparing their predictions to experimental data available in chloroform. The results and discussion presented in this study demonstrate that ANI-2x tends to predict stronger-than-expected hydrogen bonding and overstabilize global minima and shows problems related to inadequate description of dispersion interactions. Furthermore, while ANI-2x is a viable model for modeling in the gas phase, conventional force fields still play an important role, especially for condensed-phase simulations. Overall, this study highlights the strengths and weaknesses of each model, providing guidelines for the use and future development of force fields and machine learning potentials.

Unraveling an Alternative Mechanism in Polymer Self-Assemblies: An Order-Order Transition with Unusual Molecular Interactions between Hydrophilic and Hydrophobic Polymer Blocks

Polymer self-assembly leading to cooling-induced hydrogel formation is relatively rare for synthetic polymers and typically relies on H-bonding between repeat units. Here, we describe a non-H-bonding mechanism for a cooling-induced reversible order-order (sphere-to-worm) transition and related thermogelation of solutions of polymer self-assemblies. A multitude of complementary analytical tools allowed us to reveal that a significant fraction of the hydrophobic and hydrophilic repeat units of the underlying block copolymer is in close proximity in the gel state. This unusual interaction between hydrophilic and hydrophobic blocks reduces the mobility of the hydrophilic block significantly by condensing the hydrophilic block onto the hydrophobic micelle core, thereby affecting the micelle packing parameter. This triggers the order-order transition from well-defined spherical micelles to long worm-like micelles, which ultimately results in the inverse thermogelation. Molecular dynamics modeling indicates that this unexpected condensation of the hydrophilic corona onto the hydrophobic core is due to particular interactions between amide groups in the hydrophilic repeat units and phenyl rings in the hydrophobic ones. Consequently, changes in the structure of the hydrophilic blocks affecting the strength of the interaction could be used to control macromolecular self-assembly, thus allowing for the tuning of gel characteristics such as strength, persistence, and gelation kinetics. We believe that this mechanism might be a relevant interaction pattern for other polymeric materials as well as their interaction in and with biological environments. For example, controlling the gel characteristics could be considered important for applications in drug delivery or biofabrication.

Ligand-Triggered Self-Assembly of Flexible Carbon Dot Nanoribbons for Optoelectronic Memristor Devices and Neuromorphic Computing

Carbon dots (CDs) are widely utilized in sensing, energy storage, and catalysis due to their excellent optical, electrical and semiconducting properties. However, attempts to optimize their optoelectronic performance through high-order manipulation have met with little success to date. In this study, through efficient packing of individual CDs in two-dimensions, the synthesis of flexible CDs ribbons is demonstrated technically. Electron microscopies and molecular dynamics simulations, show the assembly of CDs into ribbons results from the tripartite balance of π-π attractions, hydrogen bonding, and halogen bonding forces provided by the superficial ligands. The obtained ribbons are flexible and show excellent stability against UV irradiation and heating. CDs ribbons offer outstanding performance as active layer material in transparent flexible memristors, with the developed devices providing excellent data storage, retention capabilities, and fast optoelectronic responses. A memristor device with a thickness of 8 µm shows good data retention capability even after 10⁴ cycles of bending. Furthermore, the device functions effectively as a neuromorphic computing system with integrated storage and computation capabilities, with the response speed of the device being less than 5.5 ns. These properties create an optoelectronic memristor with rapid Chinese character learning capability. This work lays the foundation for wearable artificial intelligence.

Computational Study of the Inhibition of RgpB Gingipain, a Promising Target for the Treatment of Alzheimer's Disease

Alzheimer's disease represents one of the most ambitious challenges for biomedical sciences due to the growing number of cases worldwide in the elderly population and the lack of efficient treatments. One of the recent attempts to develop a treatment points to the cysteine protease RgpB as a promising drug target. In this attempt, several small-molecule covalent inhibitors of this enzyme have been proposed. Here, we report a computational study at the atomic level of the inhibition mechanism of the most promising reported compounds. Molecular dynamics simulations were performed on six of them, and their binding energies in the active site of the protein were computed. Contact maps and interaction energies were decomposed by residues to disclose those key interactions with the enzyme. Finally, quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations were performed to evaluate the reaction mechanism by which these drug candidates lead to covalently bound complexes, inhibiting the RgpB protease. The results provide a guide for future re-design of prospective and efficient inhibitors for the treatment of Alzheimer's disease.

Discovery of allosteric SHP2 inhibitors through ensemble-based consensus molecular docking, endpoint and absolute binding free energy calculations

SHP2 (Src homology-2 domain-containing protein tyrosine phosphatase-2) is a cytoplasmic protein -tyrosine phosphatase encoded by the gene PTPN11. It plays a crucial role in regulating cell growth and differentiation. Specifically, SHP2 is an oncoprotein associated with developmental pathologies and several different cancer types, including gastric, leukemia and breast cancer and is of great therapeutic interest. Given these roles, current research efforts have focused on developing SHP2 inhibitors. Allosteric SHP2 inhibitors have been shown to be more selective and pharmacologically appealing compared to competitive catalytic inhibitors targeting SHP2. Nevertheless, there remains a need for novel allosteric inhibitor scaffolds targeting SHP2 to develop compounds with improved selectivity, cell permeability, and bioavailability. Towards this goal, this study applied various computational tools to screen over 6 million compounds against the allosteric site within SHP2. The top-ranked hits from our in-silico screening were validated using protein thermal shift and biolayer interferometry assays, revealing three potent compounds. Kinetic binding assays were employed to measure the binding affinities of the top-ranked compounds and demonstrated that they all bind to SHP2 with a nanomolar affinity. Hence the compounds and the computational workflow described herein provide an effective approach for identifying and designing a generation of improved allosteric inhibitors of SHP2.

Finding a prospective dual-target drug for the treatment of coronavirus disease by theoretical study

Spike protein of coronavirus is a key protein in binding and entrance of virus to the human cell via binding to the receptor-binding domain (RBD) domain of S1 subunit to peptidase domain region of ACE2 receptor. In this study, the possible effect of 24 antiviral drugs on the RBD domain of spike protein was investigated via docking and molecular dynamics simulation for finding a dual-target drug. At first, all drugs were docked to the RBD domain of spike protein, and then all complexes and free RBD domains were separately used for molecular dynamics simulation for 50 ns via amber18 software. The simulation results showed that 10 ligands from 28 ligands were separated from the RBD domain, and among 18 remained ligands, baloxavir marboxil, and danoprevir drugs, besides endonuclease activity and protease inhibitory, can bind to key residues of the RBD domain. Then these drugs have a dual target and should be more effective than current drugs, and experimental studies should be done on baloxavir marboxil and danoprevir as more potential drugs for coronavirus disease Communicated by Ramaswamy H. Sarma.

Mechanism of Action of Flavin-Dependent Halogenases

To rationally engineer the substrate scope and selectivity of flavin-dependent halogenases (FDHs), it is essential to first understand the reaction mechanism and substrate interactions in the active site. FDHs have long been known to achieve regioselectivity through an electrophilic aromatic substitution at C7 of the natural substrate Trp, but the precise role of a key active-site Lys residue remains ambiguous. Formation of hypochlorous acid (HOCl) at the cofactor-binding site is achieved by the direct reaction of molecular oxygen and a single chloride ion with reduced FAD and flavin hydroxide, respectively. HOCl is then guided 10 Å into the halogenation active site. Lys79, located in this site, has been proposed to direct HOCl toward Trp C7 through hydrogen bonding or a direct reaction with HOCl to form an -NH₂Cl⁺ intermediate. Here, we present the most likely mechanism for halogenation based on molecular dynamics (MD) simulations and active-site density functional theory "cluster" models of FDH PrnA in complex with its native substrate l-tryptophan, hypochlorous acid, and the FAD cofactor. MD simulations with different protonation states for key active-site residues suggest that Lys79 directs HOCl through hydrogen bonding, which is confirmed by calculations of the reaction profiles for both proposed mechanisms.

A data-driven and topological mapping approach for the a priori prediction of stable molecular crystalline hydrates

Predictions of the structures of stoichiometric, fractional, or nonstoichiometric hydrates of organic molecular crystals are immensely challenging due to the extensive search space of different water contents, host molecular placements throughout the crystal, and internal molecular conformations. However, the dry frameworks of these hydrates, especially for nonstoichiometric or isostructural dehydrates, can often be predicted from a standard anhydrous crystal structure prediction (CSP) protocol. Inspired by developments in the field of drug binding, we introduce an efficient data-driven and topologically aware approach for predicting organic molecular crystal hydrate structures through a mapping of water positions within the crystal structure. The method does not require a priori specification of water content and can, therefore, predict stoichiometric, fractional, and nonstoichiometric hydrate structures. This approach, which we term a mapping approach for crystal hydrates (MACH), establishes a set of rules for systematic determination of favorable positions for water insertion within predicted or experimental crystal structures based on considerations of the chemical features of local environments and void regions. The proposed approach is tested on hydrates of three pharmaceutically relevant compounds that exhibit diverse crystal packing motifs and void environments characteristic of hydrate structures. Overall, we show that our mapping approach introduces an advance in the efficient performance of hydrate CSP through generation of stable hydrate stoichiometries at low cost and should be considered an integral component for CSP workflows.

Modulation of Membrane Microviscosity by Protein-Mediated Carotenoid Delivery as Revealed by Time-Resolved Fluorescence Anisotropy

Carotenoids are potent antioxidants with a wide range of biomedical applications. However, their delivery into human cells is challenging and relatively inefficient. While the use of natural water-soluble carotenoproteins capable to reversibly bind carotenoids and transfer them into membranes is promising, the quantitative estimation of the delivery remains unclear. In the present work, we studied echinenone (ECN) delivery by cyanobacterial carotenoprotein AnaCTDH (C-terminal domain homolog of the Orange Carotenoid Protein from Anabaena), into liposome membranes labelled with BODIPY fluorescent probe. We observed that addition of AnaCTDH-ECN to liposomes led to the significant changes in the fast-kinetic component of the fluorescence decay curve, pointing on the dipole-dipole interactions between the probe and ECN within the membrane. It may serve as an indirect evidence of ECN delivery into membrane. To study the delivery in detail, we carried out molecular dynamics modeling of the localization of ECN within the lipid bilayer and calculate its orientation factor. Next, we exploited FRET to assess concentration of ECN delivered by AnaCTDH. Finally, we used time-resolved fluorescence anisotropy to assess changes in microviscosity of liposomal membranes. Incorporation of liposomes with β-carotene increased membrane microviscosity while the effect of astaxanthin and its mono- and diester forms was less pronounced. At temperatures below 30 °C addition of AnaCTDH-ECN increased membrane microviscosity in a concentration-dependent manner, supporting the protein-mediated carotenoid delivery mechanism. Combining all data, we propose FRET-based analysis and assessment of membrane microviscosity as potent approaches to characterize the efficiency of carotenoids delivery into membranes.

Structural basis for product specificities of MLL family methyltransferases

Human mixed-lineage leukemia (MLL) family methyltransferases methylate histone H3 lysine 4 to different methylation states (me1/me2/me3) with distinct functional outputs, but the mechanism underlying the different product specificities of MLL proteins remains unclear. Here, we develop methodologies to quantitatively measure the methylation rate difference between mono-, di-, and tri-methylation steps and demonstrate that MLL proteins possess distinct product specificities in the context of the minimum MLL-RBBP5-ASH2L complex. Comparative structural analyses of MLL complexes by X-ray crystal structures, fluorine-19 nuclear magnetic resonance, and molecular dynamics simulations reveal that the dynamics of two conserved tyrosine residues at the "F/Y (phenylalanine/tyrosine) switch" positions fine-tune the product specificity. The variation in the intramolecular interaction between SET-N and SET-C affects the F/Y switch dynamics, thus determining the product specificities of MLL proteins. These results indicate a modified F/Y switch rule applicable for most SET domain methyltransferases and implicate the functional divergence of MLL proteins.

Structural view on the role of the TRD loop in regulating DNMT3A activity: a molecular dynamics study

DNA methyltransferase 3A (DNMT3A) has been regarded as a potential epigenetic target for the development of cancer therapeutics. A number of DNMT3A inhibitors have been reported, but most of them do not have good potency, high selectivity and/or low cytotoxicity. It has been suggested that a non-conserved region around the target recognition domain (TRD) loop is implicated in the DNMT3A activity under the allosteric regulation of the ATRX-DNMT3-DNMT3L (ADD) domain, but the molecular mechanism of the regulation of the TRD loop on the DNMT3A activity needs to be elucidated. In this study, based on the reported crystal structures, the dynamics of the TRD loop in different multimerization with/without the bound guest molecule, namely the ADD domain or the DNA molecule, was investigated using conventional molecular dynamics (MD) and umbrella sampling simulations. The simulation results illustrate that the TRD loop exhibits relatively higher flexibility than the other components in the whole catalytic domain (CD), which could be well stabilized into different local minima through the binding with either the ADD domain or the DNA molecule by forming tight hydrogen-bond and salt-bridge networks involving distinct residues. Moreover, the movement of the TRD loop away from the catalytic loop upon activation could be triggered simply by the detachment of the ADD domain, but not necessarily induced by the ADD domain relocation on the CD. All these dynamic structural details could be a supplement to the previously reported crystal structure, which underlines the importance of the structural flexibility for the critical residues in the TRD loop, arousing more interest in the rational design of novel DNMT3A inhibitors targeting this region.

Integrated Approach to Interaction Studies of Pyrene Derivatives with Bovine Serum Albumin: Insights from Theory and Experiment

This work aimed to investigate the interaction of bovine serum albumin with newly synthesized potent new pyrene derivatives (PS1 and PS2), which might prove useful to have a better antibacterial character as found for similar compounds in the previous report [Low et al. Bioconjugate Chemistry2014, 12, 2269−2284]. However, to date, binding studies with plasma protein are still unknown. Steady-state fluorescence spectroscopy and lifetime fluorescence studies show that the static interaction binding mode and binding constants of PS1 and PS2 are 7.39 and 7.81 [K_b × 10⁵ (M^–1)], respectively. The experimental results suggest that hydrophobic forces play a crucial role in interacting pyrene derivatives with BSA protein. To verify this, molecular docking and molecular dynamics simulations were performed to predict the nature of the interaction and the dynamic behavior of the two compounds in the BSA complex, PS1 and PS2, under physiological conditions of pH = 7.1. In addition, the free energies of binding for the BSA-PS1 and BSA-PS2 complexes were estimated at 300 K based on the molecular mechanics of the Poisson–Boltzmann surface (MMPBSA) with the Gromacs package. PS2 was found to have a higher binding affinity than PS1. To determine the behavior of the orbital transitions in the ground state geometry, we found that both compounds have similar orbital transitions from HOMO–LUMO via π → π* and HOMO–1–LUMO+1 via n → π*, which was included in the FMO analysis. A cytotoxicity study was performed to determine the toxicity of the compounds. Based on the MD study, the stability of the compounds with BSA and the dynamic binding modes were further revealed, as well as the nature of the binding force components involved and the important residues involved in the binding process. From the binding energy analysis, it can be assumed that PS2 may be more active than PS1.

Self-Consistent Parameterization of DNA Residues for the Non-Polarizable AMBER Force Fields

Fixed-charge (non-polarizable) forcefields are accurate and computationally efficient tools for modeling the molecular dynamics of nucleic acid polymers, particularly DNA, well into the µs timescale. The continued utility of these forcefields depends in part on expanding the residue set in step with advancing nucleic acid chemistry and biology. A key step in parameterizing new residues is charge derivation which is self-consistent with the existing residues. As atomic charges are derived by fitting against molecular electrostatic potentials, appropriate structural models are critical. Benchmarking against the existing charge set used in current AMBER nucleic acid forcefields, we report that quantum mechanical models of deoxynucleosides, even at a high level of theory, are not optimal structures for charge derivation. Instead, structures from molecular mechanics minimization yield charges with up to 6-fold lower RMS deviation from the published values, due to the choice of such an approach in the derivation of the original charge set. We present a contemporary protocol for rendering self-consistent charges as well as optimized charges for a panel of nine non-canonical residues that will permit comparison with literature as well as studying the dynamics of novel DNA polymers.

Alchemical Design of Pharmacological Chaperones with Higher Affinity for Phenylalanine Hydroxylase

Phenylketonuria (PKU) is a rare metabolic disease caused by variations in a human gene, PAH, encoding phenylalanine hydroxylase (PAH), and the enzyme converting the essential amino acid phenylalanine into tyrosine. Many PKU-causing variations compromise the conformational stability of the encoded enzyme, decreasing or abolishing its catalytic activity, and leading to an elevated concentration of phenylalanine in the blood, which is neurotoxic. Several therapeutic approaches have been developed to treat the more severe manifestations of the disorder, but they are either not entirely effective or difficult to adhere to throughout life. In a search for novel pharmacological chaperones to treat PKU, a lead compound was discovered (compound IV) that exhibited promising in vitro and in vivo chaperoning activity on PAH. The structure of the PAH-IV complex has been reported. Here, using alchemical free energy calculations (AFEC) on the structure of the PAH-IV complex, we design a new generation of compound IV-analogues with a higher affinity for the enzyme. Seventeen novel analogues were synthesized, and thermal shift and isothermal titration calorimetry (ITC) assays were performed to experimentally evaluate their stabilizing effect and their affinity for the enzyme. Most of the new derivatives bind to PAH tighter than lead compound IV and induce a greater thermostabilization of the enzyme upon binding. Importantly, the correspondence between the calculated alchemical binding free energies and the experimentally determined ΔΔG_b values is excellent, which supports the use of AFEC to design pharmacological chaperones to treat PKU using the X-ray structure of their complexes with the target PAH enzyme.

Multidimensional redox potential/pKa coupling in multicopper oxidases from molecular dynamics: implications for the proton transfer mechanism

Bilirubin oxidases (BOD) are metalloenzymes that catalyze the conversion of O₂ and bilirubin to biliverdin and water in the metabolism of chlorophyll and porphyrin. In this work we have used the CpHMD method to analyze the effects of the different oxidation states on the BOD trinuclear cluster (TNC). Our results demonstrate that there is a link between the different oxidation states of copper ions and the protonation capacity of nearby titratable residues. Each configuration affects pK_a differently, creating proton gradients within the enzyme that act in an extremely orderly manner. This order is closely linked to the catalytic mechanism and leads us to the conclusion of the entry of the O₂ molecule and its reduction in water molecules is associated with the probability of the release of protons from nearby acid groups. With this information, we deduce that under the initial reaction conditions the acidic side chains of nearby residues can be protonated; this allows the enzyme to reduce the activation energy of the reaction by coupling the proton transfer to oxidation state changes in the metallic center.

Searching and designing potential inhibitors for SARS-CoV-2 Mpro from natural sources using atomistic and deep-learning calculations

The spread of severe acute respiratory syndrome coronavirus 2 novel coronavirus (SARS-CoV-2) worldwide has caused the coronavirus disease 2019 (COVID-19) pandemic. A hundred million people were infected, resulting in several millions of death worldwide. In order to prevent viral replication, scientists have been aiming to prevent the biological activity of the SARS-CoV-2 main protease (3CL pro or Mpro). In this work, we demonstrate that using a reasonable combination of deep-learning calculations and atomistic simulations could lead to a new approach for developing SARS-CoV-2 main protease (Mpro) inhibitors. Initially, the binding affinities of the natural compounds to SARS-CoV-2 Mpro were estimated via atomistic simulations. The compound tomatine, thevetine, and tribuloside could bind to SARS-CoV-2 Mpro with nanomolar/high-nanomolar affinities. Secondly, the deep-learning (DL) calculations were performed to chemically alter the top-lead natural compounds to improve ligand-binding affinity. The obtained results were then validated by free energy calculations using atomistic simulations. The outcome of the research will probably boost COVID-19 therapy.

The hybrid DeepFrag/atomistic simulation approach could lead to a new scheme for developing SARS-CoV-2 3CLpro/Mpro inhibitors.

A combination of solid-state NMR and MD simulations reveals the binding mode of a rhomboid protease inhibitor

Intramembrane proteolysis plays a fundamental role in many biological and pathological processes. Intramembrane proteases thus represent promising pharmacological targets, but few selective inhibitors have been identified. This is in contrast to their soluble counterparts, which are inhibited by many common drugs, and is in part explained by the inherent difficulty to characterize the binding of drug-like molecules to membrane proteins at atomic resolution. Here, we investigated the binding of two different inhibitors to the bacterial rhomboid protease GlpG, an intramembrane protease characterized by a Ser–His catalytic dyad, using solid-state NMR spectroscopy. H/D exchange of deuterated GlpG can reveal the binding position while chemical shift perturbations additionally indicate the allosteric effects of ligand binding. Finally, we determined the exact binding mode of a rhomboid protease-inhibitor using a combination of solid-state NMR and molecular dynamics simulations. We believe this approach can be widely adopted to study the structure and binding of other poorly characterized membrane protein–ligand complexes in a native-like environment and under physiological conditions.

Proton-detected solid-state NMR in combination with molecular docking and molecular dynamics (MD) simulations allow the study of rhomboid protease inhibition under native-like conditions.

Protein C-GeM: A Coarse-Grained Electron Model for Fast and Accurate Protein Electrostatics Prediction

The electrostatic potential (ESP) is a powerful property for understanding and predicting electrostatic charge distributions that drive interactions between molecules. In this study, we compare various charge partitioning schemes including fitted charges, density-based quantum mechanical (QM) partitioning schemes, charge equilibration methods, and our recently introduced coarse-grained electron model, C-GeM, to describe the ESP for protein systems. When benchmarked against high quality density functional theory calculations of the ESP for tripeptides and the crambin protein, we find that the C-GeM model is of comparable accuracy to ab initio charge partitioning methods, but with orders of magnitude improvement in computational efficiency since it does not require either the electron density or the electrostatic potential as input.

Application of Molecular Dynamics Simulations in the Analysis of Cyclodextrin Complexes

Cyclodextrins (CDs) are highly respected for their ability to form inclusion complexes via host-guest noncovalent interactions and, thus, ensofance other molecular properties. Various molecular modeling methods have found their applications in the analysis of those complexes. However, as showed in this review, molecular dynamics (MD) simulations could provide the information unobtainable by any other means. It is therefore not surprising that published works on MD simulations used in this field have rapidly increased since the early 2010s. This review provides an overview of the successful applications of MD simulations in the studies on CD complexes. Information that is crucial for MD simulations, such as application of force fields, the length of the simulation, or solvent treatment method, are thoroughly discussed. Therefore, this work can serve as a guide to properly set up such calculations and analyze their results.

Molecular dynamics simulation for mechanism revelation of the safety and nutrition of lipids and derivatives in food: State of the art

Molecular dynamics (MD) simulation has proved to be a powerful tool in the study of proteins, nucleic acids, lipids, and carbohydrates et al. in fields of health, nutrition, and food science. In particular, MD simulation has been employed in the investigation of various lipid systems such as triglycerides, phospholipid membranes, etc. Due to the continuous updating of computing resources and the development of new MD simulation methods and force field parameters, the simulation's time and size scale of lipids system has increased by several orders of magnitude. However, MD simulation cannot be used for systems invovle chemical reactions. These greatly limit its further application in the field of lipid research. This paper reviews the progress and development of MD simulation, especially for the application of MD simulation in different lipid systems. In this paper, MD simulation and its general workflow was briefly introduced firstly. Subsequently, the application of MD simulation in various lipid systems was reviewed in-depth. Finally, the limitation and future prospects of MD simulation in lipid research were also discussed. This review provided new insights into the investigation of MD simulation, and a novel thought for lipid study. We believe that MD simulation will exhibit more and more great advantages in the investigation of lipids in the future due to the development of novlel methods.

1'-Ribose cyano substitution allows Remdesivir to effectively inhibit nucleotide addition and proofreading during SARS-CoV-2 viral RNA replication

COVID-19 has recently caused a global health crisis and an effective interventional therapy is urgently needed. Remdesivir is one effective inhibitor for SARS-CoV-2 viral RNA replication. It supersedes other NTP analogues because it not only terminates the polymerization activity of RNA-dependent RNA polymerase (RdRp), but also inhibits the proofreading activity of intrinsic exoribonuclease (ExoN). Even though the static structure of Remdesivir binding to RdRp has been solved and biochemical experiments have suggested it to be a "delayed chain terminator", the underlying molecular mechanisms is not fully understood. Here, we performed all-atom molecular dynamics (MD) simulations with an accumulated simulation time of 24 microseconds to elucidate the inhibitory mechanism of Remdesivir on nucleotide addition and proofreading. We found that when Remdesivir locates at an upstream site in RdRp, the 1'-cyano group experiences electrostatic interactions with a salt bridge (Asp865-Lys593), which subsequently halts translocation. Our findings can supplement the current understanding of the delayed chain termination exerted by Remdesivir and provide an alternative molecular explanation about Remdesivir's inhibitory mechanism. Such inhibition also reduces the likelihood of Remdesivir to be cleaved by ExoN acting on 3'-terminal nucleotides. Furthermore, our study also suggests that Remdesivir's 1'-cyano group can disrupt the cleavage site of ExoN via steric interactions, leading to a further reduction in the cleavage efficiency. Our work provides plausible and novel mechanisms at the molecular level of how Remdesivir inhibits viral RNA replication, and our findings may guide rational design for new treatments of COVID-19 targeting viral replication.

Redirecting substrate regioselectivity using engineered ΔN123-GBD-CD2 branching sucrases for the production of pentasaccharide repeating units of S. flexneri 3a, 4a and 4b haptens

The (chemo-)enzymatic synthesis of oligosaccharides has been hampered by the lack of appropriate enzymatic tools with requisite regio- and stereo-specificities. Engineering of carbohydrate-active enzymes, in particular targeting the enzyme active site, has notably led to catalysts with altered regioselectivity of the glycosylation reaction thereby enabling to extend the repertoire of enzymes for carbohydrate synthesis. Using a collection of 22 mutants of ΔN₁₂₃-GBD-CD2 branching sucrase, an enzyme from the Glycoside Hydrolase family 70, containing between one and three mutations in the active site, and a lightly protected chemically synthesized tetrasaccharide as an acceptor substrate, we showed that altered glycosylation product specificities could be achieved compared to the parental enzyme. Six mutants were selected for further characterization as they produce higher amounts of two favored pentasaccharides compared to the parental enzyme and/or new products. The produced pentasaccharides were shown to be of high interest as they are precursors of representative haptens of Shigella flexneri serotypes 3a, 4a and 4b. Furthermore, their synthesis was shown to be controlled by the mutations introduced in the active site, driving the glucosylation toward one extremity or the other of the tetrasaccharide acceptor. To identify the molecular determinants involved in the change of ΔN₁₂₃-GBD-CD2 regioselectivity, extensive molecular dynamics simulations were carried out in combination with in-depth analyses of amino acid residue networks. Our findings help to understand the inter-relationships between the enzyme structure, conformational flexibility and activity. They also provide new insight to further engineer this class of enzymes for the synthesis of carbohydrate components of bacterial haptens.

Adsorption of Pharmaceuticals onto Smectite Clay Minerals: A Combined Experimental and Theoretical Study

The adsorption of two pharmaceuticals, carbamazepine and paracetamol, onto the expandable clay mineral saponite has been studied through the combination of kinetic experiments, X-ray diffraction, and theoretical modeling. Kinetic experiments indicate low adsorption for carbamazepine and paracetamol on expandable smectite clay. Accordingly, X-ray diffraction experiments show that neither compound enters smectite interlayer space. Molecular dynamics simulations were carried out to understand the interactions between the two pharmaceuticals and the saponite basal surface in the presence of Na+ cations. Calculations reveal that paracetamol almost does not coordinate solution cations, whereas a rather low coordination to cation is observed for carbamazepine. As a result, the adsorption onto the clay surface results mainly from van der Waals interactions for both pharmaceuticals. Carbamazepine does adsorb the surface via two configurations, one involving cation coordination, which corresponds to a rather stable adsorption compared to paracetamol. This is confirmed by structural analyses completed with desorption free energy profile.

BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules

A broad collection of technologies, including e.g. drug metabolism, biofuel combustion, photochemical decontamination of water, and interfacial passivation in energy production/storage systems rely on chemical processes that involve bond-breaking molecular reactions. In this context, a fundamental thermodynamic property of interest is the bond dissociation energy (BDE) which measures the strength of a chemical bond. Fast and accurate prediction of BDEs for arbitrary molecules would lay the groundwork for data-driven projections of complex reaction cascades and hence a deeper understanding of these critical chemical processes and, ultimately, how to reverse design them. In this paper, we propose a chemically inspired graph neural network machine learning model, BonDNet, for the rapid and accurate prediction of BDEs. BonDNet maps the difference between the molecular representations of the reactants and products to the reaction BDE. Because of the use of this difference representation and the introduction of global features, including molecular charge, it is the first machine learning model capable of predicting both homolytic and heterolytic BDEs for molecules of any charge. To test the model, we have constructed a dataset of both homolytic and heterolytic BDEs for neutral and charged (−1 and +1) molecules. BonDNet achieves a mean absolute error (MAE) of 0.022 eV for unseen test data, significantly below chemical accuracy (0.043 eV). Besides the ability to handle complex bond dissociation reactions that no previous model could consider, BonDNet distinguishes itself even in only predicting homolytic BDEs for neutral molecules; it achieves an MAE of 0.020 eV on the PubChem BDE dataset, a 20% improvement over the previous best performing model. We gain additional insight into the model's predictions by analyzing the patterns in the features representing the molecules and the bond dissociation reactions, which are qualitatively consistent with chemical rules and intuition. BonDNet is just one application of our general approach to representing and learning chemical reactivity, and it could be easily extended to the prediction of other reaction properties in the future.

Prediction of bond dissociation energies for charged molecules with a graph neural network enabled by global molecular features and reaction difference features between products and reactants.