Bond Occupancy Research Articles

Computational and experimental investigation on functional monomer selection for a novel molecularly imprinting polymer of remdesivir

Molecularly-imprinted polymers (MIPs) are a sample preparation technique with a functional cavity that can rebind the same or similar analyte to the template. It also can increase the selectivity of the analytical method. Computational approaches are capable of making predictions about the most optimal synthesis conditions, including the most appropriate monomers and solvents. This study used the DFT method, GFN2-xTB, and molecular dynamics simulation to predict MIP synthesis’s best functional monomer, solvent, and stoichiometric ratio. Remdesivir (RMD), used as a template, has also never been developed to be made as MIP. The monomers were acrylic acid (AA), 2-hydroxyethyl methacrylate (HEMA), and acrylamide (AM). Laboratory testing, association constant, and Job plot analysis are carried out to confirm the results of computational tests. The polymer was synthesized using precipitation and characterized using SEM, FTIR, and TGA. The adsorption capacity was evaluated in two different solvents, i.e. acetonitrile (ACN) and water: ACN=9: 1 (v/v). Computational study results identified acrylamide as the most interactive ligand with RMD as a template. The results of molecular dynamics simulations identify that the RMD: AM=1: 1 complex is the most stable in terms of the radial distribution function, hydrogen bond occupancy, and Gibbs bond free energy. The adsorption ability test results show that MIP 1 and MIP 2 have imprinting factor values of 1.36 and 1.15, respectively.

Computational and Experimental Comparison of Molecularly Imprinted Polymers Prepared by Different Functional Monomers-Quantitative Parameters Defined Based on Molecular Dynamics Simulation.

In recent years, the advancement of computational chemistry has offered new insights into the rational design of molecularly imprinted polymers (MIPs). From this aspect, our study tried to give quantitative parameters for evaluating imprinting efficiency and exploring the formation mechanism of MIPs by combining simulation and experiments. The pre-polymerization system of sulfadimethoxine (SDM) was investigated using a combination of quantum chemical (QC) calculations and molecular dynamics (MD) simulations. MIPs were prepared on the surface of silica gel by a surface-initiated supplemental activator and reducing agent atom transfer radical polymerization (SI-SARA ATRP). The results of the QC calculations showed that carboxylic monomers exhibited higher bonding energies with template molecules than carboxylic ester monomers. MD simulations confirmed the hydrogen bonding sites predicted by QC calculations. Furthermore, it was observed that only two molecules of monomers could bind up to one molecule of SDM, even when the functional monomer ratio was up to 10. Two quantitative parameters, namely, the effective binding number (EBN) and the maximum hydrogen bond number (HBNMax), were defined. Higher values of EBN and HBNMax indicated a higher effective binding efficiency. Hydrogen bond occupancies and RDF analysis were performed to analyze the hydrogen bond formation between the template and the monomer from different perspectives. Furthermore, under the influence of the EBN and collision probability of the template and the monomers, the experimental results show that the optimal molar ratio of template to monomer is 1:3. The method of monomer screening presented in this study can be extended to future investigations of pre-polymerization systems involving different templates and monomers.

Determination of Hydrogen Bonds in GROMACS: A New Implementation to Overcome Memory Limitation.

This work introduces a new faster implementation of the hydrogen bond network (complex arrangement of hydrogen bonds between or within molecules) search algorithm in biomacromolecules and their environment. Existing implementation of such an algorithm in GROMACS [Abraham et al. GROMACS 2024.2 Manual. 2024.] has limitations in the analysis of large structures and trajectories. The new implementation, in the form of a native GROMACS trajectory analysis module, allows for quick analysis of molecular dynamics trajectories without restrictions, thus overcoming the limitations of the original algorithm. The application of the developed method enabled the acquisition and analysis of hydrogen bond networks in the studied defensin-like protein Pentadiplandra brazzeana, as well as the study of hydrogen bond occupancies between the protein's residues and water molecules. The data obtained using the new implementation coincided with the experimental data.

Identification of Helicobacter pylori-carcinogenic TNF-alpha-inducing protein inhibitors via daidzein derivatives through computational approaches.

Gastric cancer is considered a class 1 carcinogen that is closely linked to infection with Helicobacter pylori (H. pylori), which affects over 1 million people each year. However, the major challenge to fight against H. pylori and its associated gastric cancer due to drug resistance. This research gap had led our research team to investigate a potential drug candidate targeting the Helicobacter pylori-carcinogenic TNF-alpha-inducing protein. In this study, a total of 45 daidzein derivatives were investigated and the best 10 molecules were comprehensively investigated using in silico approaches for drug development, namely pass prediction, quantum calculations, molecular docking, molecular dynamics simulations, Lipinski rule evaluation, and prediction of pharmacokinetics. The molecular docking study was performed to evaluate the binding affinity between the target protein and the ligands. In addition, the stability of ligand-protein complexes was investigated by molecular dynamics simulations. Various parameters were analysed, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA) and dynamic cross-correlation matrix (DCCM). The results has confirmed that the ligand-protein complex CID: 129661094 (07) and 129664277 (08) formed stable interactions with the target protein. It was also found that CID: 129661094 (07) has greater hydrogen bond occupancy and stability, while the ligand-protein complex CID 129664277 (08) has greater conformational flexibility. Principal component analysis revealed that the ligand-protein complex CID: 129661094 (07) is more compact and stable. Hydrogen bond analysis revealed favourable interactions with the reported amino acid residues. Overall, this study suggests that daidzein derivatives in particular show promise as potential inhibitors of H. pylori.

Allosteric modulation of fluorescence revealed by hydrogen bond dynamics in a genetically encoded maltose biosensor.

Genetically encoded fluorescent biosensors (GEFBs) proved to be reliable tracers for many metabolites and cellular processes. In the simplest case, a fluorescent protein (FP) is genetically fused to a sensing protein which undergoes a conformational change upon ligand binding. This drives a rearrangement in the chromophore environment and changes the spectral properties of the FP. Structural determinants of successful biosensors are revealed only in hindsight when the crystal structures of both ligand-bound and ligand-free forms are available. This makes the development of new biosensors for desired analytes a long trial-and-error process. In the current study, we conducted μs-long all atom molecular dynamics (MD) simulations of a maltose biosensor in both the apo (dark) and holo (bright) forms. We performed detailed hydrogen bond occupancy analyses to shed light on the mechanism of ligand induced conformational change in the sensor protein and its allosteric effect on the chromophore environment. We find that two strong indicators for distinguishing bright and dark states of biosensors are due to substantial changes in hydrogen bond dynamics in the system and solvent accessibility of the chromophore.

Discovery of natural agents against Staphylococcus aureus based on EIIC by protein modeling, virtual screening and molecular dynamics

In this study, a reasonable 3D structure of enzyme IIC (EIIC) was established using ab initio methods. Curcumin, baicalein and phloretin were screened out from 127,695 natural products based on EIIC protein in Staphylococcus aureus (S. aureus) by using the virtual screening technology. The antibacterial assays results confirmed that these three compounds could inhibit S. aureus cell growth. The results of molecular docking, molecular dynamics and molecular mechanics/generalized born surface area calculation indicated that curcumin, baicalein and phloretin mainly bound to Glu275, His231, and Phe359 of EIIC through hydrogen bonds and van der Waals forces to obstruct the transport of glucose-based carbohydrates, and thereby inhibited the carbohydrate metabolism of S. aureus. The steered molecular dynamics analysis revealed the existence of transfer channel in EIIC and illustrated that curcumin, baicalein and phloretin could dissociate from EIIC when pulling force on them. Furthermore, alanine scanning and hydrogen bond occupancy analyses found that Glu275 played an important role in stabilizing EIIC-baicalein/curcumin/phloretin complexes, and 275Glu@OE1 was a stable hydrogen bond acceptor. Therefore, Glu275 may be a hot spot residue that can maintain the stable binding of agents to EIIC, which may be a direction for the development of new drugs against S. aureus.

A comparative study of deep eutectic solvents based on fatty acids and the effect of water on their intermolecular interactions

In this work, intermolecular interactions among the species of fatty acids-based DESs with different hydrogen bond acceptors (HBA) in the adjacent water have been investigated using molecular dynamics (MD) simulation. The results of this work provide deep insights into understanding the water stability of the DESs based on thymol and the eutectic mixtures of choline chloride and fatty acids at a temperature of 353.15 K and atmospheric pressure. Stability, hydrogen bond occupancy analysis, and the distribution of the HBA and HBD around each other were attributed to the alkyl chain length of FAs and the type of HBA. Assessed structural properties include the combined distribution functions (CDFs), the radial distribution functions (RDFs), the angular distribution functions (ADFs), and the Hydrogen bonding network between species and Spatial distribution functions (SDF). The reported results show the remarkable role of the strength of the hydrogen bond between THY molecules and fatty acids on the stability of DES in water. The transport properties of molecules in water–eutectic mixtures were analyzed by using the mean square displacement (MSD) of the centers of mass of the species, self-diffusion coefficients, vector reorientation dynamics (VRD) of bonds and the velocity autocorrelation function (VACF) for the center of the mass of species.

Molecular mechanism of regulation of RhoA GTPase by phosphorylation of RhoGDI

Rho-specific guanine nucleotide dissociation inhibitors (RhoGDIs) play a crucial role in the regulation of Rho family GTPases. They act as negative regulators that prevent the activation of Rho GTPases by forming complexes with the inactive GDP-bound state of GTPase. Release of Rho GTPase from the RhoGDI-bound complex is necessary for Rho GTPase activation. Biochemical studies provide evidence of a "phosphorylation code," where phosphorylation of some specific residues of RhoGDI selectively releases its GTPase partner (RhoA, Rac1, Cdc42, etc.). This work attempts to understand the molecular mechanism behind this specific phosphorylation-induced reduction in binding affinity. Using several microseconds long atomistic molecular dynamics simulations of the wild-type and phosphorylated states of the RhoA-RhoGDI complex, we propose a molecular-interaction-based mechanistic model for the dissociation of the complex. Phosphorylation induces major structural changes, particularly in the positively charged polybasic region (PBR) of RhoA and the negatively charged N-terminal region of RhoGDI that contribute most to the binding affinity. Molecular mechanics Poisson-Boltzmann surface area binding energy calculations show a significant weakening of interaction on phosphorylation at the RhoA-specific site of RhoGDI. In contrast, phosphorylation at a Rac1-specific site does not affect the overall binding affinity significantly, which confirms the presence of a phosphorylation code. RhoA-specific phosphorylation leads to a reduction in the number of contacts between the PBR of RhoA and the N-terminal region of RhoGDI, which manifests a reduction of the binding affinity. Using hydrogen bond occupancy analysis and energetic perturbation network, we propose a mechanistic model for the allosteric response, i.e., long-range signal propagation from the site of phosphorylation to the PBR and buried geranylgeranyl group in the form of rearrangement and rewiring of hydrogen bonds and salt bridges. Our results highlight the crucial role of specific electrostatic interactions in manifestation of the phosphorylation code.

A Computational Study into the Mechanism of B−B Bond Cleavage in a Magnesium(II) Diboranate Complex

AbstractThe breaking of the asymmetric B−B bond within a MgII diboranate complex, [Mg](pinBB(nBu)pin) when [(MeBDIDipp)Mg]≡[Mg], in the presence of DMAP (4‐dimethylaminopyridine), is analyzed with DFT (Density Functional Theory) and NBO (Natural Bond Orbital) methods. The formation of a magnesium‐boryl species, [Mg](Bpin)(DMAP)], which exhibits boron “umpolung” nucleophilic behaviour, is explored through “inner” and “outer” sphere mechanisms, alongside a spontaneous base capture pathway. Charges, bond occupancies, Frontier Orbitals and a steric parameter are used to rationalise the mechanistic features of the system, as well as various reactivity observations. Functional testing results and attempts to model unusual 11B NMR data are also reported.

Molecularly imprinted polymer-based sensors for identification volatile compounds in pharmaceutical products: in silico rational design

The present study aimed to strategically design a Molecularly Imprinted Polymer (MIP) with selective extraction capabilities for volatile compounds found in pork. These specific volatile compounds, such as 3-methyl-1-butanol, 1-nonanal, octanal, hexanal, 2-pentyl-furan, 1-penten-3-one, N-morpholinomethyl-isopropyl-sulfide, methyl butyrate, and (E,E)-2,4-decadienal, are primarily responsible for the distinctive aroma and flavor characteristics associated with pork. Molecular dynamics simulations were employed to investigate the stability of the pre-polymerization system, simulating the interactions between the volatile compounds as templates, 4-hydroxyethyl methacrylate (HEMA) as monomers, and ethylene glycol dimethacrylate (EGDMA) as crosslinkers. Computational simulations revealed that the optimal mole ratio of 1:4:20 for templates, monomers, and crosslinkers resulted in the most favorable functional radial distribution and exhibited the strongest interactions. To validate the computational findings, additional analyses were performed utilizing Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA), radial distribution function (RDF), and hydrogen bond (HBond) occupancy. The calculated binding free energy demonstrated that all template molecules were capable to bind with both the monomers and crosslinkers, including 1-penten-3-one and N-morpholinomethyl-isopropyl-sulfide displaying the strongest interactions, with values of −12,674 kJ/mol and −11,646 kJ/mol, respectively. The congruence between the results obtained from the molecular simulation analyses highlights the crucial role of molecular dynamics simulations in the study and development of MIP for the analysis of marker compounds present in pork. Communicated by Ramaswamy H. Sarma

Classical Molecular Dynamics Simulation of Glyonic Liquids: Structural Insights and Relation to Conductive Properties.

Rhamnolipids are biosurfactants that have obtained wide industrial and environmental interests with their biodegradability and great surface activity. Besides their important roles as surfactants, they are found to function as a new type of glycolipid-based protic ionic liquids (ILs)─glyonic liquids (GLs). GLs are reported to have impressive physicochemical properties, especially superionic conductivity, and it was reported in experiments that specific ion selections and the fraction of water content have a strong effect on the conductivity. Also, the shape of the conductivity curve as a function of water fraction in GLs is interesting with a sharp increase first and a long plateau. We related the conductivities to the three-dimensional (3D) networks composed of -OH inside the GLs utilizing classical molecular dynamics (MD) simulations. The amount and size of these networks vary with both ion species and water fractions. Before reaching the first hydration layer, the -OH networks with higher projection/box length ratios indicate better conductivity; after reaching the first hydration layer and forming continuous structures, the conductivity retains with more water molecules participating in the continuous networks. Therefore, networks are found to be a qualitative predictor of actual conductivity. This is explained by the analysis of the atomic structures, including radial distribution function, fraction free volume, anion conformations, and hydrogen bond occupancies, of GLs and their water mixtures under different chemical conditions.

A study of ab initio folding of chignolins using replica-exchange molecular dynamics simulations.

More and more studies have confirmed the importance of polarization effects in hydrogen bonding interactions in protein folding simulations. In this paper, a recently developed charge update scheme termed polarized structure-specific backbone charge (PSBC) model was applied to the folding of 10-residue chignolin. A comparison between simulations performed using PSBC and a nonpolarizable (AMBER99SB) force field demonstrably showed the importance of the electrostatic polarization effect in the folding of the short β-hairpin peptide by a series of analyses such as DSSP, free-energy landscape, hydrogen bond occupancy, and melting curve. The PSBC model was further validated by folding two other chignolin variants.

De novo design of dual-target JAK2, SMO inhibitors based on deep reinforcement learning, molecular docking and molecular dynamics simulations

Triple-negative breast cancer (TNBC) and HER2-positive breast cancer are particularly aggressive and the effectiveness of current therapies for them is limited. TNBC lacks effective therapies and HER2-positive cancer is often resistant to HER2-targeted drugs after an initial response. The recent studies have demonstrated that the combination of JAK2 inhibitors and SMO inhibitors can effectively inhibit the growth and metastasis of TNBC and HER2-positive drug resistant breast cancer cells. In this study, deep reinforcement learning was used to learn the characteristics of existing small molecule inhibitors of JAK2 and SMO, and to generate a novel library of small molecule compounds that may be able to inhibit both JAK2 and SMO. Subsequently, the molecule library was screened by molecular docking and a total of 7 compounds were selected out as dual inhibitors of JAK2 and SMO. Molecular dynamics simulations and binding free energies showed that the top three compounds stably bound to both JAK2 and SMO proteins. The binding free energies and hydrogen bond occupancy of key amino acids indicate that A8976 and A10625 has good properties and could be a potential dual-target inhibitor of JAK2 and SMO.

Species Differences in Response to Binding Interactions of Bisphenol A and its Analogs with the Modeled Estrogen Receptor 1 and In Vitro Reporter Gene Assay in Human and Zebrafish.

Adverse impacts associated with the interactions of numerous endocrine-disruptor chemicals (EDCs) with estrogen receptor 1 play a pivotal role in reproductive dysfunction. The predictive studies on these interactions thus are crucial in the risk assessment of EDCs but rely heavily on the accuracy of specific protein structure in three dimensions. As the three-dimensional (3D) structure of zebrafish estrogen receptor 1 (zEsr1) is not available, the 3D structure of zEsr1 ligand-binding domain (zEsr1-LBD) was generated using MODELLER and its quality was assessed by the PROCHECK, ERRAT, ProSA, and Verify-3D tools. After the generated model was verified as reliable, bisphenol A and its analogs were docked on the zEsr1-LBD and human estrogen receptor 1 ligand-binding domain (hESR1-LBD) using the Discovery Studio and Autodock Vina programs. The molecular dynamics followed by molecular docking were simulated using the Nanoscale Molecular Dynamics program and compared to those of the in vitro reporter gene assays. Some chemicals were bound with an orientation similar to that of 17β-estradiol in both models and in silico binding energies showed moderate or high correlations with in vitro results (0.33 ≤ r2 ≤ 0.71). Notably, hydrogen bond occupancy during molecular dynamics simulations exhibited a high correlation with in vitro results (r2 ≥ 0.81) in both complexes. These results show that the combined in silico and in vitro approaches is a valuable tool for identifying EDCs in different species, facilitating the assessment of EDC-induced reproductive toxicity. Environ Toxicol Chem 2022;41:2431-2443. © 2022 SETAC.

DHFR Mutants Modulate Their Synchronized Dynamics with the Substrate by Shifting Hydrogen Bond Occupancies.

Antibiotic resistance is a global health problem in which mutations occurring in functional proteins render drugs ineffective. The working mechanisms of the arising mutants are seldom apparent; a methodology to decipher these mechanisms systematically would render devising therapies to control the arising mutational pathways possible. Here we utilize Cα-Cβ bond vector relaxations obtained from moderate length MD trajectories to determine conduits for functionality of the resistance conferring mutants of Escherichia coli dihydrofolate reductase. We find that the whole enzyme is synchronized to the motions of the substrate, irrespective of the mutation introducing gain-of-function or loss-of function. The total coordination of the motions suggests changes in the hydrogen bond dynamics with respect to the wild type as a possible route to determine and classify the mode-of-action of individual mutants. As a result, nine trimethoprim-resistant point mutations arising frequently in evolution experiments are categorized. One group of mutants that display the largest occurrence (L28R, W30G) work directly by modifying the dihydrofolate binding region. Conversely, W30R works indirectly by the formation of the E139-R30 salt bridge which releases energy resulting from tight binding by distorting the binding cavity. A third group (D27E, F153S, I94L) arising as single, resistance invoking mutants in evolution experiment trajectories allosterically and dynamically affects a hydrogen bonding motif formed at residues 59-69-71 which in turn modifies the binding site dynamics. The final group (I5F, A26T, R98P) consists of those mutants that have properties most similar to the wild type; these only appear after one of the other mutants is fixed on the protein structure and therefore display clear epistasis. Thus, we show that the binding event is governed by the entire enzyme dynamics while the binding site residues play gating roles. The adjustments made in the total enzyme in response to point mutations are what make quantifying and pinpointing their effect a hard problem. Here, we show that hydrogen bond dynamics recorded on sub-μs time scales provide the necessary fingerprints to decipher the various mechanisms at play.

A thermodynamic investigation of amyloid precursor protein processing by human γ-secretase

Human γ-secretase cleaves the transmembrane domains (TMDs) of amyloid precursor protein (APP) into pathologically relevant amyloid-β peptides (Aβs). The detailed mechanisms of the unique endoproteolytic cleavage by the presenilin 1 domain (PS1) of γ-secretase are still poorly understood. Herein, we provide thermodynamic insights into how the α-helical APP TMD is processed by γ-secretase and elucidate the specificity of Aβ48/Aβ49 cleavage using unbiased molecular dynamics and bias-exchange metadynamics simulations. The thermodynamic data show that the unwinding of APP TMD is driven by water hydration in the intracellular pocket of PS1, and the scissile bond T32-L33 or L33-V34 of the APP TMD can slide down and up to interact with D257/D385 to achieve endoproteolysis. In the wild-type system, the L33-V34 scissile bond is more easily hijacked by D257/D385 than T32-L33, resulting in higher Aβ49 cleavage, while the T32N mutation on the APP TMD decreases the energy barrier of the sliding of the scissile bonds and increases the hydrogen bond occupancy for Aβ48 cleavage. In summary, the thermodynamic analysis elucidates possible mechanisms of APP TMD processing by PS1, which might facilitate rational drug design targeting γ-secretase.

Insights on the cellulose pretreatment at room temperature by choline-chloride-based deep eutectic solvents: an atomistic study

The pretreatment or disruption of a cellulose I \(\beta \) crystallite by four deep eutectic solvents (DES): choline-chloride ethylene glycol, choline-chloride oxalic acid, choline-chloride urea, and choline-chloride levulinic acid, was described from the atomistic interactions observed in molecular dynamics and ab-initio (NCI-AIM) studies. The cellulose I \(\beta \) disruption was studied considering plausible correlations between the Kamlet-Taft (α and β) solvent parameters, and a series of thermodynamic, structural, and energetic properties. It was found that the Kamlet-Taft parameters correlated with the thermodynamic properties of the DES, as well as their variations after the addition of the cellulose crystallite. Structural analysis revealed that the weaker the interactions within the molecules of the solvent, the stronger the interactions between the hydroxyl group from cellulose with the chloride anion and with the hydrogen bond donor. Further analysis indicated that the \(R-CO-R\) moieties in the hydrogen bond donor within the solvent, displayed best interplaying with the cellulose. The hydrogen bond occupancies within the cellulose crystallite, evidenced that the main \(O6-H6\cdots O2/O3\) and \(O2-H2\cdots O6\) interchain hydrogen bonds in the glucan located at the edge of the solute, were replaced by weak \(O6-H6\cdots O4\) hydrogen bonds in all solvents. This effect was related to the \({O/Cl}_{DES}\cdots H-donor\) and \({O}_{DES}-{H}_{DES}\cdots acceptor\) HBs between cellulose and DES molecules, and it was confirmed by the non-covalent interactions obtained through DFT calculations. The energetic interactions and the atomistic degree of disruption of the cellulose crystallite, were not completely described by the Kamlet-Taft β or α parameters when considered separately. Surprisingly, by using the net basicity (\(\beta -\alpha \)) definition such correlations were improved, suggesting that both parameters must be considered together to develop new, green, and sustainable solvents for cellulose pretreatment process.Graphic abstract

Structural Dynamics and Susceptibility of Anti-Alzheimer’s Drugs Donepezil and Galantamine against Human Acetylcholinesterase

Alzheimer’s disease (AD) is a major public health problem worldwide due to an increase in the elderly population. The current pharmacotherapy for the early stages of AD is mainly dependent on cholinesterase inhibitors. Two of the most commonly used anti-AD drugs, donepezil (DPZ) and galantamine (GLM), are selective inhibitors for human acetylcholinesterase (hAChE). However, the inhibitory activity of DPZ on hAChE was more potent than GLM by ~85 times. To better understand the molecular basis for differences in mode of inhibition of hAChE by both drugs, molecular dynamics (MD) simulation was performed. The results showed that the active site residues of hAChE/DPZ had the higher hydrogen bond occupancies as compared to hAChE/GLM. Nevertheless, the 2 drugs directly formed hydrogen bonds with the catalytic residue H447 of hAChE. The per-residue free energy decomposition suggested that DPZ interacted with the residues in peripheral anionic site of hAChE, resulting in the greater binding affinity of DPZ than that of GLM toward hAChE. The binding free energy calculation based on MM-PBSA and MM-GBSA methods indicated that van der Waal interactions played a predominant role as the driving force for binding process of DPZ and GLM to hAChE. Moreover, the predicted total binding free energy of hAChE/DPZ was stronger than hAChE/GLM, which was consistent well with the experimental data. We hope that our findings provide useful information for further design of novel hAChE inhibitors.
 HIGHLIGHTS
 
 Anti-Alzheimer’s drugs donepezil and galantamine in complex with human acetylcholinesterase were explored by MD simulations and binding free energy calculations
 The MM-PB(GB)SA-based binding free energy indicated that donepezil exhibited a more favorable binding affinity to human acetylcholinesterase than galantamine
 The molecular rotation of galantamine during MD simulation resulted in the reduction of hydrogen bond occupancies with D74 and S203
 The van der Waals interactions were considered as the major contributor to the binding of both drugs
 
 GRAPHICAL ABSTRACT

Computational studies evidenced the potential of steroidal lactone to disrupt surface interaction of SARS-CoV-2 spike protein and hACE2

The critical event in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogenesis is recognition of host cells by the virus, which is facilitated by protein-protein interaction (PPI) of viral Spike-Receptor Binding Domain (S-RBD) and Human Angiotensin Converting Enzyme 2-Receptor (hACE2-R). Thus, disrupting the interaction between S-RBD and hACE2-R is widely accepted as a primary strategy for managing COVID-19. The purpose of this study is to assess the ability of three steroidal lactones (SL) (4-Dehydrowithaferin A, Withaferin A, and Withalongolide A) derived from plants to disrupt the PPI of S-RBD and hACE2-R under two conditions (CON–I and CON-II) using in-silico methods. Under CON–I, 4-Dehydrowithaferin A destabilizing the interactions between S-RBD and hACE2-R, as indicated by an increase in binding energy (BE) from −1028.5 kJ/mol (control) to −896.12 kJ/mol 4-Dehydrowithaferin A exhibited a strong interaction with S-RBD GLY496 with a hydrogen bond occupancy (HBO) of 37.33%. Under CON-II, Withalongolide A was capable of disrupting all types of PPI, as evidenced by an increased BE from −913 kJ/mol (control) to −133.69 kJ/mol and an increased distance (>3.55 nm) between selected AAR combinations of S-RBD and hACE2-R. Withalongolide A formed a hydrogen bond with TYR453 (97%, HBO) of S-RBD, which is required for interaction with hACE2-R's HIS34. Our studies demonstrated that SL molecules have the potential to disrupt the S-RBD and hACE2-R interaction, thereby preventing SARS-CoV-2 from recognizing host cells. The SL molecules can be considered for additional in-vitro and in-vivo studies with this research evidence.

Dynamical shifts in hydrogen bond occupancies identify mechanisms responsible for resistance conferring mutations

We pose hydrogen bond (HB) occupancy shifts as a reliable method to distinguish dynamical changes onset in a protein by point mutations. As a target problem, we select antibiotic resistance in which mutations occurring in functional proteins render the drugs ineffective. Here, the working mechanisms of nine mutations appearing in trimethoprim (TMP) resistant dihydrofolate reductase (DHFR)[1]. MD trajectories on the order of hundreds of nanoseconds each are carried out for wild type (WT) and nine mutants.