Molecular Dynamics Simulation Data Research Articles

Semirational Protein Engineering of a Decarboxylative Aldolase for the Regiodivergent and Stereodivergent Synthesis of Cyclic Imino Acids

AbstractAldolases are powerful C−C bond‐forming enzymes for asymmetric organic synthesis because of their supreme stereoselectivity, compatibility with diverse electrophiles and nucleophiles, and promising scalability. Stereodivergent engineering of aldolases to tune the selectivity for the synthesis of stereoisomers of chiral molecules is highly desirable but has rarely been reported. Herein we report the semirational engineering of the decarboxylative aldolase UstD with a focused rational iterative site‐specific mutagenesis (FRISM) strategy to perform a C−C bond‐forming reaction with dione electrophiles. The variant obtained from a small mutant library showed divergent regioselectivity and diastereoselectivity compared to the wild‐type enzyme, resulting in the production of 30 cyclic imino acids with stereocenters at the α and γ positions. Molecular dynamics simulation and kinetic data revealed the basis of selectivity.

In silico Analysis of Natural Iridoids as Primary Amoebic Meningoencephalitis Inhibitors: Molecular Docking, MD Simulation, MMPBSA, and DFT Analyses

Iridoids have demonstrated various activities, including anti-inflammatory, anticancer, cardioprotective, antiviral, hepatoprotective, antihyperglycemic, and antiparasitic effects. The brain-eating amoeba Naegleria fowleri is responsible for primary amoebic meningoencephalitis, a brain inflammation. In this study, 52 iridoids were selected through an extensive literature survey, and 22 of these iridoids passed the drug-likeness filter. The selected iridoids were molecularly docked against the N. fowleri CYP51 receptor, using voriconazole as a standard for comparison. The docking score for voriconazole was -7.6 kcal/mol, while the scores for 10-isovaleroyl-dihydropenstemide and Patrinalloside A were -8.9 and -8.6 kcal/mol, respectively. According to molecular dynamics (MD) simulation data, the interacting amino acid residues exhibited fluctuations within a specific range, with the Root Mean Square Deviation (RMSD) values stabilizing throughout the experiment. When interacting with the receptor linked to amoebic meningoencephalitis, 10-isovaleroyl-dihydropenstemide and Patrinalloside A showed free binding energies of -71.922 kJ/mol and -61.243 kJ/mol, respectively, based on Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) calculations. Furthermore, Fragment Molecular Orbital (FMO) and Molecular Electrostatic Potential (MEP) analyses of 10-isovaleroyl-dihydropenstemide and Patrinalloside A revealed potential nucleophilic-electrophilic attack zones, indicating they are chemically reactive. The analysis of both compounds' ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) indicated non-toxic behaviour. These findings suggest that natural iridoids have significant potential in combating primary amoebic meningoencephalitis.

Semirational Protein Engineering of a Decarboxylative Aldolase for Regiodivergent and Stereodivergent Synthesis of Cyclic Imino Acids.

Aldolases are powerful C-C bond-forming enzymes for asymmetric organic synthesis because of their supreme stereoselectivity, diverse electrophiles and nucleophiles, and promising scalability. Stereodivergent engineering of aldolases to tune the selectivity for the synthesis of stereoisomers of chiral molecules is highly desirable but has rarely been reported. This study documented the semirational engineering of the decarboxylative aldolase UstD with the focused rational iterative site-specific mutagenesis (FRISM) strategy to perform a C-C bond-forming reaction with dione electrophiles. The variant obtained from a small mutant library showed divergent regioselectivity and diastereoselectivity to the wild-type enzyme, which resulted in the production of thirty cyclic imino acids with stereocenters at the α and γ positions. Molecular dynamics simulation and kinetic data revealed the basis of selectivity.

Nucleation and growth dynamics of nanobubbles on smooth and rough surfaces

<sec>The interfacial nanobubbles (INBs) have been confirmed to exist, and have significant potential for applications in fields such as mineral flotation, aquaculture, and wastewater treatment. However, the microscopic nucleation process of INBs is still poorly understood. This study investigates the nucleation process and growth dynamics of INBs on smooth and rough surfaces under different levels of gas supersaturation. Molecular dynamics (MD) simulations using GROMACS software package are conducted to observe the microscopic nucleation process and the temporal evolution of the geometric characteristics of the INBs. Additionally, a growth dynamics model for INBs is derived based on the Epstein-Plesset gas diffusion theory, and the predictions from the model are compared with the MD simulation data.</sec><sec>The results indicate that on smooth homogeneous surfaces, the curvature radius and width of INBs increase progressively with time after nucleation. This growth process is well captured by the theoretical model, indicating that the gas diffusion theory provides an accurate description of INB growth dynamics. In addition, the contact angle (measured on the gas side) during INB growth is not constant but increases initially before stabilizing. This phenomenon is caused by reducing solid-gas interfacial tension due to higher Laplace pressure, thus leading the contact angle to increase as the INB radius grows. Furthermore, on smooth homogeneous surfaces, INBs are observed to nucleate at 81 ns, 17 ns, 6 ns, and 1.3 ns under gas supersaturation levels of 100, 120, 150, and 200, respectively. This demonstrates that higher gas supersaturation significantly shortens the nucleation time. Additionally, as gas supersaturation increases, the growth rate of INBs after nucleation will also accelerate. However, at a gas supersaturation level of 50, no nucleation occurrs during the simulation period of 200 ns. Theoretical analysis reveals that the INBs can only nucleate and grow when the radius of gas aggregates exceeds the critical nucleation radius (<inline-formula><tex-math id="M1">\begin{document}$ {R}_{{\mathrm{critical}}} = \dfrac{\sigma }{\zeta {P}_{0}} $\end{document}</tex-math></inline-formula>, where <inline-formula><tex-math id="M2">\begin{document}$ \sigma $\end{document}</tex-math></inline-formula> is the liquid-gas interfacial tension, <inline-formula><tex-math id="M3">\begin{document}$ \zeta $\end{document}</tex-math></inline-formula> is the gas supersaturation level, and <inline-formula><tex-math id="M4">\begin{document}$ {P}_{0} $\end{document}</tex-math></inline-formula> is the ambient pressure). As gas supersaturation decreases, <inline-formula><tex-math id="M5">\begin{document}$ {R}_{{\mathrm{c}}{\mathrm{r}}{\mathrm{i}}{\mathrm{t}}{\mathrm{i}}{\mathrm{c}}{\mathrm{a}}{\mathrm{l}}} $\end{document}</tex-math></inline-formula> increases, thus significantly increasing the difficulty of nucleation.</sec><sec>On rough surfaces, pits with widths of 1 nm, 2 nm, 4 nm, and 10 nm are introduced. At a gas supersaturation of 50,where no INB nucleation occurrs on the smooth surfaces, gas nuclei rapidly form within the pits. However, only gas nuclei in pits with widths larger than 2 nm can grow into INBs. This is because in the growth process the pinning effect at the pit edges causes the curvature radius of the gas nucleus to initially decrease and then increase. Only when the minimum curvature radius exceeds the critical nucleation radius, can gas nuclei develop into INBs.</sec><sec>The findings of this study provide more in-depth insights into the nucleation mechanism of INBs, and practical guidance for controlling their generation, and they also deliver theoretical support for relevant applications such as mineral flotation and other industrial processes.</sec>

Theoretical and computational study on structure, dynamics, and configurational entropy correlation in gold-silicon liquid

The structure–property relationship of partially ordered systems poses a different type of open problem for both theoretical and experimental condensed matter researchers. Configurational entropy is an important thermodynamic property that characterizes the glass transition ability of binary liquid alloys. Recently, various experimental and computational approaches have been reported to investigate the configurational entropy in liquids; however, a well-established theoretical definition is still lacking. In this study, the configurational entropy of binary melts has been computed using their pair correlation functions. We determine three partial structure factors that govern the total structure factor S(k) in liquid AuySix alloys at different compositions and temperatures. Fourier inversion of partial and total structure factors gives partial pair correlation functions and radial distribution functions g(r) of AuySix melts, respectively. The computed values of S(k) and g(r) are in excellent agreement with available experimental results. The present model calculation of S(k) for eutectic AuySix melts (x = 19 at. % Si) shows better agreement with the experimental values than the molecular dynamics simulation data. Furthermore, we determine the friction coefficients experienced by constituent particles in the attractive and repulsive regions of the square-well (SW) potential function and employed in Einstein's equation to determine the self- and mutual diffusion coefficients as a function of composition and temperature. The diffusivity of Au and the mutual diffusion coefficient of the alloy are also in good agreement with experimental values compared to molecular dynamics data at its eutectic composition, which confirms the applicability of the SW model for such alloys.

Modeling the structure and relaxation in glycerol-silica nanocomposites.

The relationship between the dynamics and structure of amorphous thin films and nanocomposites near their glass transition is an important problem in soft-matter physics. Here, we develop a simple theoretical approach to describe the density profile and the α-relaxation time of a glycerol-silica nanocomposite (S. Cheng et al., J. Chem. Phys., 2015, 143, 194704). We begin by applying the Derjaguin approximation, where we replace the curved surface of the particle with the planar one; thus, modeling the nanocomposite is reduced to that of a confined thin film. Subsequently, by employing the molecular dynamics (MD) simulation data of Cheng et al., we approximate the density profile of a supported liquid thin film as a stationary solution of a fourth-order partial differential equation (PDE). We then construct an appropriate density functional, from which the density profile emerges through the minimization of free energy. Our final assumption is that of a consistent, temperature-independent scaled density profile, ensuring that the free volume throughout the entire nanocomposite increases with temperature in a smooth, monotonic fashion. Considering the established relationship between glycerol relaxation time and temperature, we can employ Doolittle-type analysis ("naïve" free-volume model), to calculate the relaxation time based on temperature and film thickness. We then convert the film thickness into the interparticle distance and subsequently the filler volume fraction for the nanocomposites and compare our model predictions with experimental data, resulting in a good agreement. The proposed approach can be easily extended to other nanocomposite and film systems.

Molecular dynamics simulations to decipher the hotspots at the allosteric site of human 5-lipoxygenase.

Human 5-lipoxygenase (LOX) is a non-heme, Fe-containing LOX which catalyses the conversion of arachidonic acid (AA) to leukotriene A4 (LTA4). LTA4 is subsequently converted to cysteinyl-LTs and LTB4 that cause bronchoconstriction and act as chemotactic and chemokinetic agent on human leukocytes, respectively. Leukotrienes play significant roles in inflammation in asthma, cardiovascular diseases, allergic rhinitis, atopic dermatitis, inflammatory bowel disease, rheumatoid arthritis, psoriasis and many more. Thus, in order to suppress LT formation for the management of such diseases, the intrinsic details of the structure of 5-LOX are crucial for the design/development of 5-LOX inhibitors. Here, we deciphered the role of various amino acids at the allosteric site of 5-LOX through molecular dynamics simulations. 3-O-Acetyl-11-keto-beta-boswellic acid (AKBA), a well-recognized allosteric inhibitor of 5-LOX, was used as reference compound. The consequences of amino acid mutations (R101, E108, H130, E134) on AKBA binding have been studied in silico. The changes were characterized at the interaction level. Our observations provide structural insights into crucial residues which are important for stabilizing the ligand at the allosteric site. Principal component analysis (PCA) was applied to the molecular dynamics simulation data to identify the structural fluctuations in the 5-LOX structure. The derived mechanistic details of allosteric 5-LOX inhibition may facilitate the development of novel therapeutics targeting 5-LOX.

Domain Mobility in the ORF2p Complex Revealed by Molecular Dynamics Simulations and Big Data Analysis

ORF2p (open reading frame 2 protein) is a multifunctional multidomain enzyme that demonstrates both reverse transcriptase and endonuclease activities and is associated with the pathophysiology of cancer. The 3D structure of the entire seven-domain ORF2p complex was revealed with the recent achievements in structural studies. The different arrangements of the CTD (carboxy-terminal domain) and tower domains were identified as the “closed-ring” and “open-ring” conformations, which differed by the hairpin position of the tower domain, but the structural diversity of these complexes has the potential to be more extensive. To study this, we performed sub-microsecond all-atom molecular dynamics simulations of the entire ORF2p complex with different starting configurations. The obtained molecular dynamic trajectories frames were assigned to several clusters following the dimension reduction to three principal components of the 1275 distances feature matrix. Five and six clusters were obtained for the “open” and “closed” ring models, respectively. While the fingers–palm–thumb core retains its rigid configuration during the MD (molecular dynamics) simulations, all other domains display the complicated dynamic behavior not observed in the experimental structures. The EN (endonuclease) and CTD domains display significant translations and rotations while their internal structures stay rigid. The CTD domain can either form strong contacts with the tower or be far apart from it for both formal “open” and “closed” ring states because the tower hairpin position is not the only determining factor of the protein complex configuration. While only the “thumb up” conformation is observed in all the trajectories, the active site can be obstructed by the movement of the CTD domain. Thus, molecular modeling and machine learning techniques provide valuable insights into the dynamical behavior of the ORF2p complex, which is hard to uncover with experimental methods, given the complexity and size of the object.

Modeling the Influence of Deposition Parameters on the Crystalline Degree in the Simulation of Polycrystalline Silicon

Polycrystalline silicon (poly‐Si) has been and still is a pivotal material, particularly in the electronics and solar energy industries. Controlling crystallization is one of the challenges, e.g., in producing poly‐Si films for radio frequency applications. Since film growth by deposition is a random process, producing a specific grain size distribution for poly‐Si is challenging. By combining molecular dynamics simulation data with surface diffusion physics, novel transparent models are constructed that shed light on the physics behind the deposition of poly‐Si thin films and assist the selection of simulation parameters. Both probabilistic and geometric approaches are used to find relevant simulation parameters and their bounds to describe the complex grain–grain boundary interactions in the growth of poly‐Si thin films. Poly‐Si growth simulations provide valuable information to better understand the features of optimal growth conditions. The constructed parameterized deposition model is fitted to the simulation data. In addition to further refining the simulation of customized poly‐Si films, the presented modeling concept can also be used more generally in the analysis of physical vapor deposition.

Molecular insights into the elevator-type mechanism of the cyanobacterial bicarbonate transporter BicA.

Cyanobacteria are responsible for up to 80% of aquatic carbon dioxide fixation and have evolved a specialized carbon concentrating mechanism to increase photosynthetic yield. As such, cyanobacteria are attractive targets for synthetic biology and engineering approaches to address the demands of global energy security, food production, and climate change for an increasing world's population. The bicarbonate transporter BicA is a sodium-dependent, low-affinity, high-flux bicarbonate symporter expressed in the plasma membrane of cyanobacteria. Despite extensive biochemical characterization of BicA, including the resolution of the BicA crystal structure, the dynamic understanding of the bicarbonate transport mechanism remains elusive. To this end, we have collected over 1ms of all-atom molecular dynamics simulation data of the BicA dimer to elucidate the structural rearrangements involved in the substrate transport process. We further characterized the energetics of the transition of BicA protomers and investigated potential mutations that are shown to decrease the free energy barrier of conformational transitions. In all, our study illuminates a detailed mechanistic understanding of the conformational dynamics of bicarbonate transporters and provides atomistic insights to engineering these transporters for enhanced photosynthetic production.

Interaction between the Polyelectrolytes Unfractionated Heparin and Universal Heparin Reversal Agents.

The interaction of unfractionated heparin (UFH) with universal heparin reversal agent 7 (UHRA-7) is investigated. UHRA-7 is composed of a hyperbranched polyglycerol core onto which an array of methylated tris(2-aminoethylamine) (Me-TREN) charged groups is grafted, which in turn are shielded with a layer of small chain poly(ethylene glycol) methyl ether (mPEG) chains. This system has previously been shown to be biocompatible and to be effective at neutralizing heparin. The binding constant Kb was determined from isothermal titration calorimetry experiments, at temperatures ranging from 278 to 323 K and salt concentrations ranging from 0.06 to 0.20 M NaCl. The data were analyzed in terms of a number of different theoretical models to determine the contribution of counterion release and water release to driving the interaction between UFH and UHRA-7. With the support of NMR and molecular dynamics simulation data, a model of the interaction between UFH and UHRA-7 is proposed. The binding of heparin and universal heparin reversal agent 7 is mainly due to charge-charge interactions between the negatively charged units on UFH with positively charged Me-TREN and mPEG chains.

Natural Flavonoids as Primary Amoebic Meningoencephalitis Inhibitor: Virtual Screening, Molecular Docking, MD Simulation, MMPBSA, Density Functional Theory, Principal Component, and Gibbs Free Energy Landscape Analyses

ABSTRACTFlavonoids have been showing diversified bioactivities. Primary amoebic meningoencephalitis is a brain inflammation caused by Naegleria fowleri brain eating amoeba. In this manuscript, we selected 93 flavonoids by extensive literature survey and 83 flavonoids passed drug likeness parameter. Selected flavonoids were molecular docked against primary amoebic meningoencephalitis N. fowleri CYP51 receptor considering voriconazole as standard. Beta naphthoflavone, abyssinone I, and abyssinone III showed maximum docking scores of −10.9 kcal/mol, −10.7 kcal/mol, and −10.6 kcal/mol, respectively, whereas voriconazole showed docking scores of −7.6 kcal/mol. Molecular dynamic simulation data showed that RMSD values attained almost a static value during the simulation, and all nearest interacting amino acid residues were fluctuated within limit. Molecular Mechanics Poisson‐Boltzmann Surface Area (MMPBSA) data of beta naphthoflavone abyssinone I, abyssinone III, and voriconazole showed free binding energies of −82.755 kJ/mol, −1924.193 kJ/mol, −1890.335 kJ/mol, and −540.141 kJ/mol, respectively. Frontier molecular orbital (FMO) analysis showed that abyssinone III was the chemically reactive molecule and beta naphthoflavone showed maximum electrophilicity. Molecular electrostatic potential (MEP) analysis portrayed possible nucleophilic‐electrophilic attack areas of the structures. PCA and free energy landscape (FEL) analysis data confirmed the stable conformations between flavonoids and receptor. Abyssinone I and III showed nontoxic behavior. These data confirmed that if we repurpose these flavonoids against primary amoebic meningoencephalitis, it will be beneficial for mankind.

Existence of a maximum flow rate in electro-osmotic systems

In this work, we investigate the effect of the hydrodynamic wall–fluid friction in electro-osmotic flows. First, we present the solution to the electro-hydrodynamic equation for the electro-osmotic velocity profile, which is derived for an ionic system composed of cations immersed in uncharged solvent particles. The system (solution and walls) is kept electrically neutral using negatively charged walls and will here be referred to as a “counterion-only” system. The theory predicts the existence of a counterion concentration that results in maximum electro-osmotic flow rate, but only if the wall–fluid friction, or equivalently the slip length, is correlated with the system electrostatic screening length. Through equilibrium molecular dynamics simulations, we precisely determine the hydrodynamic slip from the wall–fluid friction, and then, this is used as input to the theoretical predictions. Comparison between the theory and independent non-equilibrium molecular dynamics simulation data confirms the existence of the maximum. In addition, we find that standard hydrodynamic theory quantitatively agrees with the simulation results for charged nanoscale systems for sufficiently small charge densities and ion charges, if the correct slip boundaries are applied.

Efficient screening and discovery of umami peptides in Douchi enhanced by molecular dynamics simulations

In this study, a partial least squares discriminant analysis (PLS-DA) discriminant model for umami peptides was constructed based on molecular dynamics simulation data, achieving a R2 value of 0.949 and a Q2 value of 0.558. Using this novel model and bioinformatics screening methods, five new umami peptides (EALEATAQ, SPPTEE, SEEG, KEE, and FEE, with umami taste thresholds of 0.139, 0.085, 0.096, 0.060, and 0.079 mg/mL, respectively) were identified in Douchi. Molecular docking revealed that the residues ASN150 of T1R1, as well as SER170, GLU301 and GLN389 of T1R3, might be key amino acid residues for the binding of umami peptides to T1R1/T1R3. Molecular dynamics simulations revealed significant differences in the root-mean-square fluctuation (RMSF) values between the two complex systems of umami peptides-T1R1/T1R3 and non-umami peptides-T1R1/T1R3. The newly constructed umami peptide discriminant model can improve the accuracy of umami peptide screening and enhance the efficiency of discovering new umami peptides.

HexagonRingCalculator: A Handy Code for Hexagonal Ring Characterization in Atomistic Simulations.

Hexagonal rings are critical to the properties of many nanomaterials by determining their mechanical strength, thermal stability, and electrical conductivity, therefore this kind of structure has been intensively concerned in computational studies. However, existing molecular dynamics (MD) simulation tools lack specialized functions for identifying and characterizing them. To address this gap, we developed HexagonRingCalculator, a tool for identifying hexagonal rings and calculating their geometric properties, including bond lengths, ring area, and circularity, directly from MD simulation data. The code facilitates the analysis of ring deformation under varying conditions, such as temperature changes. We demonstrate its functionality and accuracy through classic and ab initio MD simulations of graphene and cellulose, highlighting its potential to advance computational studies in nanomaterials.

Investigation of Improving Stability in Desulfurized-Rubber-Modified Asphalt Using Cerium-Stearate Incorporation

To enhance the compatibility of high-content desulfurized-rubber-modified asphalt (DRMA), the innovative selection of cerium hard acid is employed in this study to investigate its impact on the compatibility of DRMA. The results indicate that when the optimal content of cerium stearate is 1%, the compatibility of the modified asphalt is improved. On the microscopic level, it is observed that the total heat absorption of the modified asphalt decreases and thermal storage stability is enhanced as measured by differential scanning calorimetry. On the macroscopic level, it gives the smallest difference in softening point, optimal storage stability, and best compatibility of the modified asphalt. Additionally, dissolution tests and adhesion tests demonstrate that the inclusion of cerium stearate increases the solubility of desulfurized rubber in asphalt and reduces the stripping rate of desulfurized-rubber particles on the asphalt surface, thereby decreasing phase separation and promoting the compatibility of DRMA. Furthermore, rheological tests indicate that cerium stearate improves both high-temperature and low-temperature performance of the modified asphalt. The addition of cerium stearate increases the dynamic shear modulus of the modified asphalt, maintaining good stability and elasticity under shear loading, with minimal change in low-temperature rheological properties and lower temperature sensitivity, indicating the best compatibility at this point. Finally, molecular-dynamics simulation data indicate that the addition of cerium stearate decreases the parameter difference in the dissolution of modified asphalt and enhances the binding energy of the modified asphalt, demonstrating the feasibility of cerium stearate in promoting the compatibility of modified asphalt.

Assessment of ethanolic extract of Dittrichia viscosa from Kardoussa Douar region of Taza in Morocco as antioxidant and green inhibitor for carbon steel corrosion in acidic medium

This study targeted evaluating the anticorrosive and antioxidative characteristics of Dittrichia viscosa (ZS-OH) extract. ZS-OH was first extracted by deploying a soxhlet and characterized by chromatographic analysis (GC/MS). In addition, a quantitative assessment of the total phenolic (TPC) and flavonoids (FC) content of the ZS-OH extract, as well as phytochemical analyses, were carried out. Antioxidant testing was conducted using the bioassay: 2,2-diphenyl-1-picrylhydrazyl (DPPH). The ability of ZS-OH extract to stymie the corrosion of carbon steel in 1.0 M HCl was considered through potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). ZS-OH extract yield was 4.73 %, and GC-MS revealed 32 distinct chemicals. Neryl isovalerate (29.8 %), 1,10-di-epi-Cubenol (25.4 %), and 2,5-dimethoxy-p-cymene (11.6 %) made up the majority of the ZS-OH extract. The electrochemical results reveal that the ZS-OH extract acts as a mixed-type with an inhibition efficiency of up to 96.8 % at 500 ppm under 303 K. Surface analyses using SEM/EDS confirmed the formation of the protective layer of ZS-OH extract molecules on the C-S surface. The three major components are fully optimized in the DFT through the B3LYP functional and 6–311++G(d,p) basis sets. Molecular dynamics simulation data show the molecules of ZS-OH extract oriented beneficially on metal surfaces, providing a high surface coverage, and thus, a high inhibition performance.

Synthesis and Molecular Modeling Studies and In silico Anthelmintic Activity of N-(benzo[d]thiazol-2-yl)-3- Chloro-6-Nitrobenzo[b]thiophene- 2-Carboxamide Derivatives

Helminthiasis is a noteworthy health problem with increased morbidity. In this manuscript, we developed a series of N-(benzo[d]thiazol-2-yl)-3-chloro-6-nitrobenzo[b]thiophene-2-carboxamide derivatives (3a-f) and evaluated against Pheretima posthuma and Perionyx excavates helminths. The compounds 3a-f were synthesized by reaction of 3-chloro-6-nitrobenzo[b]thiophene-2-carbonyl chloride (1) and appropriate benzo[d]thiazol-2-amines (2a-f) presence of pyridine. A compound 1 was synthesized by reaction of 4-nitro-cinnamic acid reacts with thionyl chloride in the presence of pyridine and chlorobenzene. Results showed that molecule 3c observed with maximum anthelmintic against P. excavates and P. posthuma with mean paralyzing time of 13.15 min and 17.39 min and mean death time of 16.17 min and 20.14 min, respectively. Molecular docking against 3VRA receptor showed that molecule 3c showed maximum dock score of -7.3 kcal/mol and reference standard albendazole with dock score of -5.5 kcal/mol. Molecular dynamic simulation data reflected the stable ligand-receptor interaction. As per Molecular Mechanics Poisson-Boltzmann Surface Area analysis, maximum free binding energy of -31.224 kJ/mol showed by 3c and ARG 76 was the most contributed residue. Density functional theory calculation data confirmed that most of the molecules were soft molecules with electrophilic nature. Molecular electrostatic potential data of 3c showed that terminal nitro group, ketone group, -COO group of ester were responsible for electrophilic attack and benzo[b]thiophne and -NH groups were responsible for nucleophilic attack. The activity profile of the synthesized molecules against helminthes was 3c >3e >3d >3f >3b >3a.. KEYWORDS :Molecular docking, Molecular dynamic simulation, Molecular mechanics poisson-boltzmann surface area, Density functional theory, Anthelmintic activity.

Predicting protein conformational motions using energetic frustration analysis and AlphaFold2

Proteins perform their biological functions through motion. Although high throughput prediction of the three-dimensional static structures of proteins has proved feasible using deep-learning-based methods, predicting the conformational motions remains a challenge. Purely data-driven machine learning methods encounter difficulty for addressing such motions because available laboratory data on conformational motions are still limited. In this work, we develop a method for generating protein allosteric motions by integrating physical energy landscape information into deep-learning-based methods. We show that local energetic frustration, which represents a quantification of the local features of the energy landscape governing protein allosteric dynamics, can be utilized to empower AlphaFold2 (AF2) to predict protein conformational motions. Starting from ground state static structures, this integrative method generates alternative structures as well as pathways of protein conformational motions, using a progressive enhancement of the energetic frustration features in the input multiple sequence alignment sequences. For a model protein adenylate kinase, we show that the generated conformational motions are consistent with available experimental and molecular dynamics simulation data. Applying the method to another two proteins KaiB and ribose-binding protein, which involve large-amplitude conformational changes, can also successfully generate the alternative conformations. We also show how to extract overall features of the AF2 energy landscape topography, which has been considered by many to be black box. Incorporating physical knowledge into deep-learning-based structure prediction algorithms provides a useful strategy to address the challenges of dynamic structure prediction of allosteric proteins.

A new framework for predicting tensile stress of natural rubber based on data augmentation and molecular dynamics simulation data

A new framework for predicting tensile stress of natural rubber based on data augmentation and molecular dynamics simulation data