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Experimental protein energy maps in the (φ, ψ) space for the dipeptides of 20 naturally occurring amino acids using the current collections of high-resolution entries in the protein data bank (PDB) are presented here. Data sets were generated for hydrogen bond distance cut-off values of 2.7 Å and 3.1 Å. Neighborhood effects of proline residues on the (φ, ψ) maps have been examined. The impact of disulphide bridges on these maps has been critically examined. The comparisons of experimental maps with those obtained using various molecular mechanics and molecular dynamics methods were published earlier. The comparison metrics are: (i) locations of global and secondary minima, (ii) percentage areas enclosed by isoenergy contours, (iii) energybased RMSD and (iv) barriers to conformational transitions. The experimental maps for individual amino acid dipeptide motifs show a higher degree of qualitative consistency with theoretical maps derived using molecular mechanics when compared to those from molecular dynamics methods. We also demonstrate that a majority of backbone conformations observed in the structures of small peptides in the Cambridge Crystallographic Database are within the allowed regions of the experimental Ramachandran maps. A few protein models obtained from NMR spectroscopy were evaluated in terms of the amino acid outlier energies using the experimental maps. [ABSTRACT FROM AUTHOR]

The cysteine and alkanethiol adsorption on Au(111) surfaces is investigated using density functional theory (DFT) and classic molecular dynamics (MD). Understanding the S–Au interaction across different scales poses major challenges. DFT provides atomic‐level precision but it hardly provides insight on nanosecond scale dynamics of this interface. Alternatively, MD, although it enables modeling larger systems for longer periods, its accuracy heavily relies on the parameterization of the force fields (FF). To address this, an MD potential is fitted using DFT calculations, bridging the gap in accuracy and efficiency. At the DFT level, it is found that PBE with DFT‐D3 reproduces complex approaches at a fraction of the computational cost. Separating PBE and DFT‐D3 contributions reveals consistent PBE energy across molecules (chemisorption), while dispersion varies (physisorption). Thus, the interaction energy of cysteine and two short‐chain alkanethiols is calculated to parameterize both Morse and Lennard–Jones (LJ) potentials. The parameterization improves the potential energy in the preferred adsorption sites: the threefold hcp and fcc with respect to the previous proposals in the literature. Furthermore, the transferability is here demonstrated. At last, these results show that LJ potentials outperform more complex Morse potentials. The procedure is general, and the codes and supporting inputs are publicly available, allowing swift generation of potential energy surfaces (PES) at the DFT level, and fitted LJ or Morse potentials to any molecular interface. [ABSTRACT FROM AUTHOR]

• The modified energy method evaluated the elastic properties of SWBNNT, and the inversion energy term was considered. • Temperature's impact on BNNT's elastic properties was explored by incorporating it as an independent variable. • MSM and continuum mechanics models are used to evaluate the changes in different bonds, bond angles, and reaction angles. The elastic properties of boron nitride nanotubes (BNNTs) were investigated utilizing an enhanced energy method. By considering small deformations and applying the principle of minimum potential energy, the variations in atomic bonds and bond angles within the nanotube structure were determined. The modified model incorporated the contribution of inversion energy to the overall potential energy of the system, leading to the derivation of analytical expressions for the Young's modulus, shear modulus, and strain energy of both armchair and zigzag BNNTs under varying temperatures. The results indicate that compared to zigzag BNNTs, the impact of inversion energy on the elastic constants of armchair BNNTs is more significant, especially at small diameters (<1 nm). In thermal environment, this study demonstrates that the change in Young's modulus of BNNTs is lower than that of carbon nanotubes (CNTs), confirming the superior thermal stability of BNNTs over CNTs. Furthermore, molecular structure mechanics (MSM) and continuum mechanics models were employed to analyze the strain energy of BNNTs. The effects of different bonds, bond angles, and inversion angles on strain energy were analyzed in a thermal environment, revealing distinct differences between the two types of BNNTs. These findings provide more accurate theoretical guidance for thermal applications based on the stretching of BNNTs. [ABSTRACT FROM AUTHOR]

In the current study, we have investigated the secondary metabolites present in ethnomedical plants used for medicinal purposes—Astilbe chinensis (EK1), Scutellaria barbata D. Don (EK2), Uncaria rhynchophylla (EK3), Fallugia paradoxa (EK4), and Curcuma zedoaria (Christm.) Thread (EK5)—and we have compared them with five compounds of synthetic origin for the inhibition of PARP-1, which is linked to abnormal DNA replication, generating carcinogenic cells. We have studied these interactions through molecular dynamics simulations of each interacting system under physiological conditions (pH, temperature, and pressure) and determined that the compounds of natural origin have a capacity to inhibit PARP-1 (Poly(ADP-ribose) Polymerase 1) in all the cases inspected in this investigation. However, it is essential to mention that their interaction energy is relatively lower compared to that of compounds of synthetic origin. Given that binding energy is mandatory for the generation of a scale or classification of which is the best interacting agent, we can say that we assume that compounds of natural origin, having a complexation affinity with PARP-1, induce cell apoptosis, a potential route for the prevention of the proliferation of carcinogenic cells.

Simple Summary: Despite considerable progress in cancer research and treatment, cancer continues to be a major health challenge, often requiring invasive treatments with substantial side effects. Immuno-therapy, which targets the immune system's PD-1/PD-L1 pathway, represents a promising alternative. This critical pathway allows cancer cells to avoid immune destruction by inhibiting T-cells. Our study employs computational techniques to develop inhibitors that block the PD-L1 pathway, specifically in the acidic environment of tumors. By analyzing around 10,000 natural compounds, we identified a potential pH-selective inhibitor that shows greater effectiveness in the acidic conditions typical of cancerous tissues. This research suggests a novel approach for experimental groups to explore, focusing on developing targeted, pH-dependent inhibitors that could mark a significant step in enhancing the precision and effectiveness of immunotherapy treatments, potentially revolutionizing cancer therapy. Immunotherapy, particularly targeting the PD-1/PD-L1 pathway, holds promise in cancer treatment by regulating the immune response and preventing cancer cells from evading immune destruction. Nonetheless, this approach poses a risk of unwanted immune system activation against healthy cells. To minimize this risk, our study proposes a strategy based on selective targeting of the PD-L1 pathway within the acidic microenvironment of tumors. We employed in silico methods, such as virtual screening, molecular mechanics, and molecular dynamics simulations, analyzing approximately 10,000 natural compounds from the MolPort database to find potential hits with the desired properties. The simulations were conducted under two pH conditions (pH = 7.4 and 5.5) to mimic the environments of healthy and cancerous cells. The compound MolPort-001-742-690 emerged as a promising pH-selective inhibitor, showing a significant affinity for PD-L1 in acidic conditions and lower toxicity compared to known inhibitors like BMS-202 and LP23. A detailed 1000 ns molecular dynamics simulation confirmed the stability of the inhibitor-PD-L1 complex under acidic conditions. This research highlights the potential of using in silico techniques to discover novel pH-selective inhibitors, which, after experimental validation, may enhance the precision and reduce the toxicity of immunotherapies, offering a transformative approach to cancer treatment. [ABSTRACT FROM AUTHOR]

A simplified molecular-dynamics-based electronic circular dichroism (ECD) approach was tested on three condensed derivatives with limited conformational flexibility and an isochroman-2H-chromene hybrid, the ECD spectra of which could not be precisely reproduced by the conventional ECD calculation protocol. Application of explicit solvent molecules at the molecular mechanics (MD) level in the dynamics simulations and subsequent TDDFT-ECD calculation for the unoptimized MD structures was able to improve the agreements between experimental and computed spectra. Since enhancements were achieved even for molecules with limited conformational flexibility, deformations caused by the solvent molecules and multitudes of conformers produced with unoptimized geometries seem to be key factors for better agreement. The MD approach could confirm that aggregation of the phenanthrene natural product luzulin A had a significant contribution to a specific wavelength range of the experimental ECD. The MD approach has proved that dimer formation occurred in solution and this was responsible for the anomalous ECD spectrum. The scope and limitations of the method have also been discussed. [ABSTRACT FROM AUTHOR]

Abstract The cysteine and alkanethiol adsorption on Au(111) surfaces is investigated using density functional theory (DFT) and classic molecular dynamics (MD). Understanding the S–Au interaction across different scales poses major challenges. DFT provides atomic‐level precision but it hardly provides insight on nanosecond scale dynamics of this interface. Alternatively, MD, although it enables modeling larger systems for longer periods, its accuracy heavily relies on the parameterization of the force fields (FF). To address this, an MD potential is fitted using DFT calculations, bridging the gap in accuracy and efficiency. At the DFT level, it is found that PBE with DFT‐D3 reproduces complex approaches at a fraction of the computational cost. Separating PBE and DFT‐D3 contributions reveals consistent PBE energy across molecules (chemisorption), while dispersion varies (physisorption). Thus, the interaction energy of cysteine and two short‐chain alkanethiols is calculated to parameterize both Morse and Lennard–Jones (LJ) potentials. The parameterization improves the potential energy in the preferred adsorption sites: the threefold hcp and fcc with respect to the previous proposals in the literature. Furthermore, the transferability is here demonstrated. At last, these results show that LJ potentials outperform more complex Morse potentials. The procedure is general, and the codes and supporting inputs are publicly available, allowing swift generation of potential energy surfaces (PES) at the DFT level, and fitted LJ or Morse potentials to any molecular interface.

Abstract In this paper, the quantum effects of fine scaling on the buckling behavior of carbon nanotubes (CNTs) under axial loading are investigated. Molecular mechanics and quantum mechanics are respectively utilized to study the buckling behavior and to obtain the molecular mechanics coefficients of fine-scale nanotubes. The results of buckling behavior of CNTs with different chiralities with finite and infinite dimensions are given, and a comparison study is presented on them. The differences between finite and infinite nanotubes reflect the quantum effects of fine scaling on the buckling behavior. In addition, the results show that the dimensional changes highly affect the mechanical properties and the buckling behavior of CNTs to certain dimensions. Moreover, dimensional changes have a significant effect on the critical buckling strain. Beside, in addition to the structure dimensions, the arrangement of structural and boundary atoms have a major influence on the buckling behavior.

Context: Hydroxypropyl-β-cyclodextrin (HPβCD) is one of the derivatized cyclodextrins most widely used as an excipient in the pharmaceutical industry, for its capacity to improve certain drugs properties. Different configurations of HPβCD are possible depending on the number and location of the 2-hydroxypropyl groups substituted on the glucose rings. Rifampicin has become the most commonly clinically used antibiotic against tuberculosis in recent years, despite its low solubility and variable bioavailability. Different techniques and materials have been proposed to enhance the properties of rifampicin: cyclodextrin complexation is one of them. The van der Waals term was the main contribution to the interaction energy, which then decisively conditioned the complex configurations. The size of rifampicin did not allow the whole molecule to fit into the host. Moreover, interaction energy was much greater when the guest was located near each rim of HPβCD, where rifampicin was partially included in the cavity and formed inclusion complexes. The piperazine tail of rifampicin was included inside the host in minimum energy structures and the guest was situated near the primary rim of HPβCD in most cases, although the complex configurations depended on the degree of substitution. Methods: A molecular mechanics simulation based on the GROMOS 53A6 force field was applied in this work to study the inclusion complexes formed by twelve configurations of HPβCD, with different degrees of substitution and rifampicin in water solution. We determined the penetration potential, the complex structures with minimum energies, the possibility of forming inclusion complexes other than those of minimum energies and potential energy surfaces. [ABSTRACT FROM AUTHOR]

In this paper, the quantum effects of fine scaling on the buckling behavior of carbon nanotubes (CNTs) under axial loading are investigated. Molecular mechanics and quantum mechanics are respectively utilized to study the buckling behavior and to obtain the molecular mechanics coefficients of fine-scale nanotubes. The results of buckling behavior of CNTs with different chiralities with finite and infinite dimensions are given, and a comparison study is presented on them. The differences between finite and infinite nanotubes reflect the quantum effects of fine scaling on the buckling behavior. In addition, the results show that the dimensional changes highly affect the mechanical properties and the buckling behavior of CNTs to certain dimensions. Moreover, dimensional changes have a significant effect on the critical buckling strain. Beside, in addition to the structure dimensions, the arrangement of structural and boundary atoms have a major influence on the buckling behavior. [ABSTRACT FROM AUTHOR]

Prismanes have been attracting interest for nearly 50 years because of their geometric symmetry, highly strained structures, and unique applications due to their high carbon densities and bulky structures. Although [3]-, [4]-, and [5]-prismanes have been synthesised, [6]-prismanes and their derivatives remain elusive. Herein, fluorine chemistry, molecular mechanics, molecular orbital package, and density functional theory calculations were used to design and implement the photoisomerisation of octafluoro[2.2]paracyclophane (selected based on the good overlap of its lowest unoccupied molecular orbitals and short distance between the benzene rings) into octafluoro-[6]-prismane. Specifically, a dilute solution of the above precursor in CH3CN/H2O/dimethyl sulfoxide (DMSO) (2:1:8, v/v/v) solution was irradiated with ultraviolet light, with the formation of the desired product confirmed through the use of nuclear magnetic resonance spectroscopy and gas chromatography–mass spectrometry. The product was thermally stable in solution but not under work-up conditions, which complicated the further analysis and single-crystal preparation. The key criteria for successful photoisomerisation were the presence of fluorine substituents in the cyclophane structure and DMSO in the solvent system. A more stable derivative design requires the isolation of prismane products. The proposed fluorination-based synthetic strategy is applicable to developing novel high-strain molecules/materials with three-dimensional skeletons. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a neurological disease, and its signs and symptoms appear slowly over time. Although current Alzheimer's disease treatments can alleviate symptoms, they cannot prevent the disease from progressing. To accurately diagnose and treat Alzheimer's disease, it is therefore necessary to establish effective methods for diagnosis. Apolipoprotein E4 (ApoE4), the most frequent genetic risk factor for AD, is expressed in more than half of patients with AD, making it an attractive target for AD therapy. We used molecular docking simulations, classical molecular mechanics optimizations, and ab initio fragment molecular orbital (FMO) calculations to investigate the specific interactions between ApoE4 and the naturally occurring compounds found in the plant Moringa Oleifera. According to the FMO calculations, quercetin had the highest binding affinity to ApoE4 among the sixteen compounds because its hydroxyl groups generated strong hydrogen bonds with the ApoE4 residues Trp11, Asp12, Arg15, and Asp130. As a result, we proposed various quercetin derivatives by introducing a hydroxyl group into quercetin and studied their ApoE4 binding properties. The FMO data clearly showed that adding a hydroxyl group to quercetin improved its binding capacity to ApoE4. Furthermore, ApoE4 Trp11, Asp12, Arg15, and Asp130 residues were discovered to be required for significant interactions between ApoE4 and quercetin derivatives. They had a higher ApoE4 binding affinity than our previously proposed epicatechin derivatives. Accordingly, the current results evaluated using the ab initio FMO method will be useful for designing potent ApoE4 inhibitors that can be used as a candidate agent for AD treatment. [ABSTRACT FROM AUTHOR]

In response to hydrostatic pressure, the cation channel transient receptor potential vanilloid 1 (TRPV1) is essential in signaling pathways linked to glaucoma. When activated, TRPV1 undergoes a gating transition from a closed to an open state that allows the influx of Ca2+ ions. However, the gating mechanism of TRPV1 in response to hydrostatic pressure at the molecular level is still lacking. To understand the effect of hydrostatic pressure on the activation of TRPV1, we conducted molecular-dynamics (MD) simulations on TRPV1 under different hydrostatic pressure configurations, with and without a cell membrane. The TRPV1 membrane-embedded model is more stable than the TPRV1-only model, indicating the importance of including the cell membrane in MD simulation. Under elevated pressure at 27.6 mmHg, we observed a more dynamic and outward motion of the TRPV1 domains in the lower-gate area than in the simulation under normal pressure at 12.6 mmHg. While a complete closed-to-open-gate transition was not evident in the limited course of our MD simulations, an increase in the channel radius at the lower gate was observed at 27.6 mmHg versus that at 12.6 mmHg. These findings provide novel information regarding the effect of hydrostatic pressure on TRPV1 channels.

Computational chemistry lets us model intermolecular interactions in ways assays cannot. My project focuses on the multi-kinase interactions of the cancer drug, imatinib. Most cancer drugs target one kinase, but some affect multiple kinases. Imatinib treats chronic myeloid leukemia by targeting ABL kinase. Proteomics data reveals it can interact with other kinases, such as KIT to treat gastrointestinal stromal tumors, but the mechanisms are unknown. Imatinib has different affinities for similar kinases, such as a 3000x difference between ABL and SRC, despite sharing 50% structural homology. Here, I investigate the conformational differences between free and imatinib-bound ABL, KIT, and SRC using Molecular Dynamics simulations to understand the key imatinib-kinase interactions. The alignment analysis shows the docked conformations are similar to co-crystal structures in the Protein Data Bank. Root-mean-square-deviation and fluctuation (RMSD and RMSF) analysis show that all simulations converge at 45 ns, with some regions exhibiting differential flexibility. Hydrogen bond analysis across 100 ns simulations show that ABL has one main H-bond, KIT has three main H-bonds, and SRC has no main H-bonds. All the drug-kinase complexes feature at least 15 key salt bridge interactions relevant for structural stability. The dihedral distributions reveal that most residues adopt a single conformation, but some can adopt multiple, increasing the protein flexibility. The entropy results quantify the protein disorder, revealing KIT and SRC favors the apoprotein while ABL favors the complex. This signifies that broad protein similarity does not govern imatinib binding, instead, it is explained by smaller structural details.

A simplified molecular-dynamics-based electronic circular dichroism (ECD) approach was tested on three condensed derivatives with limited conformational flexibility and an isochroman-2H-chromene hybrid, the ECD spectra of which could not be precisely reproduced by the conventional ECD calculation protocol. Application of explicit solvent molecules at the molecular mechanics (MD) level in the dynamics simulations and subsequent TDDFT-ECD calculation for the unoptimized MD structures was able to improve the agreements between experimental and computed spectra. Since enhancements were achieved even for molecules with limited conformational flexibility, deformations caused by the solvent molecules and multitudes of conformers produced with unoptimized geometries seem to be key factors for better agreement. The MD approach could confirm that aggregation of the phenanthrene natural product luzulin A had a significant contribution to a specific wavelength range of the experimental ECD. The MD approach has proved that dimer formation occurred in solution and this was responsible for the anomalous ECD spectrum. The scope and limitations of the method have also been discussed.

The popularity of the Python programming language in chemistry is growing every year. Python provides versatility, simplicity, and a rich ecosystem of libraries, making it the preferred choice for solving chemical problems. It is widely used for kinetic and thermodynamic calculations, as well as in quantum chemistry and molecular mechanics. Python is used extensively for laboratory automation and software development. Data analysis and visualization in chemistry have also become easier with the libraries available in Python. The evolution of theoretical and computational chemistry is expected in the future, especially at intersections with other fields such as machine learning. This review presents tools developed for applications in kinetic, thermodynamic, and quantum chemistry, instruments for molecular mechanics, and laboratory equipment. Online courses that help scientists without programming experience adapt Python to their chemical problems are also listed. [ABSTRACT FROM AUTHOR]

The present study of biologically active Val-Trp dipeptide has been performed using computer modeling methods. To search the stable structures the different theoretically possible conformations of this molecule were calculated within molecular mechanics framework. The results showed that two types of conformations, folded and extended, are realized for this compound. Afterwards, the most stable conformations of the Val-Trp dipeptide were optimized using DFT/B3LYP level of theory with 6-31+G(d,p) basis set. The geometry, energy parameters, electronic properties, molecular electrostatic potential (MEP) map, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies, chemical reactivity descriptors, nonlinear optical properties such as the electric dipole moment and polarizability were computed and compared for the optimized extended and folded structures of this molecule. The differences in the electronic structure between two characteristic conformations of title dipeptide were revealed. It was found the redistribution of charges as a result of folding of the peptide chain leads to a decrease in the dipole moment of this molecule. The effects of intramolecular hydrogen bonding on geometry of Val-Trp dipeptide were observed. [ABSTRACT FROM AUTHOR]

Background: Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. Methods: Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. Results: We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94S and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Conclusions: This study provides an extensive test of the performance of different molecular mechanics force fields on a diverse molecule set, and highlights two (OPLS3e and OpenFF 1.2) that perform better than the others tested on the present comparison. Our molecule set and results are available for other researchers to use in testing.

Functionalized nanotubes (NTs), nanosheets, nanorods, and porous organometallic scaffolds are potential in vivo carriers for cancer therapeutics. Precise delivery through these agents depends on factors like hydrophobicity, payload capacity, bulk/surface adsorption, orientation of molecules inside the host matrix, bonding, and nonbonding interactions. Herein, we summarize advances in simulation techniques, which are extremely valuable in initial geometry optimization and evaluation of the loading and unloading behavior of encapsulated drug molecules. Computational methods broadly involve the use of quantum and classical mechanics for studying the behavior of molecular properties. Combining theoretical processes with experimental techniques, such as X-ray crystallography, NMR spectroscopy, and bioassays, can provide a more comprehensive understanding of the structure and function of biological molecules. This integrated approach has led to numerous breakthroughs in drug discovery, enzyme design, and the study of complex biological processes. This short review provides an overview of results and challenges described from erstwhile investigations on the molecular interaction of anticancer drugs with nanocarriers of different aspect ratios.

Polyethylene terephthalate (PET) is the largest produced polyester globally, and less than 30% of all the PET produced globally (∼6 billion pounds annually) is currently recycled into lower-quality products. The major drawbacks in current recycling methods (mechanical and chemical), have inspired the exploration of potentially efficient and sustainable PET depolymerization using biological approaches. Researchers have discovered efficient PET hydrolyzing enzymes in the plastisphere and have demonstrated the selective degradation of PET to original monomers thus enabling biological recycling or upcycling. However, several significant hurdles such as the less efficiency of the hydrolytic reaction, low thermostability of the enzymes, and the inability of the enzyme to depolymerize crystalline PET must be addressed in order to establish techno-economically feasible commercial-scale biological PET recycling or upcycling processes. Researchers leverage a synthetic biology-based design; build, test, and learn (DBTL) methodology to develop commercially applicable efficient PET hydrolyzing enzymes through 1) high-throughput metagenomic and proteomic approaches to discover new PET hydrolyzing enzymes with superior properties: and, 2) enzyme engineering approaches to modify and optimize PET hydrolyzing properties. Recently, in-silico platforms including molecular mechanics and machine learning concepts are emerging as innovative tools for the development of more efficient and effective PET recycling through the exploration of novel mutations in PET hydrolyzing enzymes. In-silico-guided PET hydrolyzing enzyme engineering with DBTL cycles enables the rapid development of efficient variants of enzymes over tedious conventional enzyme engineering methods such as random or directed evolution. This review highlights the potential of in-silico-guided PET degrading enzyme engineering to create more efficient variants, including Ideonella sakaiensis PETase (IsPETase) and leaf-branch compost cutinases (LCC). Furthermore, future research prospects are discussed to enable a sustainable circular economy through the bioconversion of PET to original or high-value platform chemicals.

Prismanes have been attracting interest for nearly 50 years because of their geometric symmetry, highly strained structures, and unique applications due to their high carbon densities and bulky structures. Although [3]-, [4]-, and [5]-prismanes have been synthesised, [6]-prismanes and their derivatives remain elusive. Herein, fluorine chemistry, molecular mechanics, molecular orbital package, and density functional theory calculations were used to design and implement the photoisomerisation of octafluoro[2.2]paracyclophane (selected based on the good overlap of its lowest unoccupied molecular orbitals and short distance between the benzene rings) into octafluoro-[6]-prismane. Specifically, a dilute solution of the above precursor in CH3CN/H2O/dimethyl sulfoxide (DMSO) (2:1:8, v/v/v) solution was irradiated with ultraviolet light, with the formation of the desired product confirmed through the use of nuclear magnetic resonance spectroscopy and gas chromatography–mass spectrometry. The product was thermally stable in solution but not under work-up conditions, which complicated the further analysis and single-crystal preparation. The key criteria for successful photoisomerisation were the presence of fluorine substituents in the cyclophane structure and DMSO in the solvent system. A more stable derivative design requires the isolation of prismane products. The proposed fluorination-based synthetic strategy is applicable to developing novel high-strain molecules/materials with three-dimensional skeletons.

(-)-Menthol has been widely used in clinical medicine, flavor, and fragrance. However, high volatility, short retention time, low solubility in water, and whisker growth of menthol are crucial problems for its application. In this paper, (-)-menthol-β-cyclodextrin inclusion complex was fabricated to solve these problems. The product was characterized by X-ray diffraction, Fourier transform infrared spectroscopy and thermogravimetric analysis. The results showed that menthol was successfully encapsulated in the cavity of β-cyclodextrin. Menthol itself vaporized almost completely at around 120 oC, while the maximum menthol release rate occurred at 267.5 oC after the formation of the inclusion complex. The stability and retention time were improved. The menthol release reaction order, apparent activation energy and the pre-exponential factor were obtained and their values were 0, 142.9 kJ/mol and 1.6 × 1013 respectively. The structure of menthol-β-cyclodextrin inclusion complex was investigated by molecular simulation and the minimum energy, –116.7 kJ/mol, was obtained at –0.8 × 10–10 m.

Computer-aided drug design is a powerful and promising tool for drug design and development, with a reduced cost and time. In the current study, we rationally selected a library of 34 fused imidazo[1,2-a]quinoxaline derivatives and performed virtual screening, molecular docking, and molecular mechanics for a lead identification against tubulin as an anticancer molecule. The computational analysis and pharmacophoric features were represented as 1A2; this was a potential lead against tubulin, with a maximized affinity and binding score at the colchicine-binding site of tubulin. The efficiency of this lead molecule was further identified using an in vitro assay on a tubulin enzyme and the anticancer potential was established using an MTT assay. Compound 1A2 (IC50 = 4.33–6.11 µM against MCF-7, MDA-MB-231, HCT-116, and A549 cell lines) displayed encouraging results similar to the standard drug colchicine in these in vitro studies, which further confirmed the effectiveness of CADD in new drug developments. Thus, we successfully applied the utility of in silico techniques to identify the best plausible leads from the fused azaheterocycles. [ABSTRACT FROM AUTHOR]

Enzyme design is an important application of computational protein design (CPD). It can benefit enormously from the additional chemistries provided by noncanonical amino acids (ncAAs). These can be incorporated into an 'expanded' genetic code, and introduced in vivo into target proteins. The key step for genetic code expansion is to engineer an aminoacyl-transfer RNA (tRNA) synthetase (aaRS) and an associated tRNA that handles the ncAA. Experimental directed evolution has been successfully used to engineer aaRSs and incorporate over 200 ncAAs into expanded codes. But directed evolution has severe limits, and is not yet applicable to noncanonical AA backbones. CPD can help address several of its limitations, and has begun to be applied to this problem. We review efforts to redesign aaRSs, studies that designed new proteins and functionalities with the help of ncAAs, and some of the method developments that have been used, such as adaptive landscape flattening Monte Carlo, which allows an enzyme to be redesigned with substrate or transition state binding as the design target. [ABSTRACT FROM AUTHOR]

Carbon nanotubes (CNTs) are widely used as reinforcements in cement-based composites. The improvement in the mechanical properties of the resulting materials depends on the characteristics of the interface formed between CNTs and the cement matrix. The experimental characterization of the interfacial properties of these composites is still limited and hard to achieve with currently available technologies. In this work, molecular dynamics and molecular mechanics pull-out simulations of pristine and functionalized CNTs, taken from a tobermorite crystal, were carried out to study interfacial shear strength (ISS) from an atomic perspective. ISS was calculated from the potential energy of the systems. The effects of the CNT diameter and the degree of functionalization on the pull-out process were analyzed according to the ISS and non-bonded energy results. The influence of H-bonding and electrostatic interactions between the CNT and the matrix were also studied. The results show that ISS decreases with increasing CNT radius for pristine CNTs and depends upon the number of H-bonds for functionalized CNTs. ISS values are positively correlated to Enon-bonded energy, which is related to the number of carboxyl groups on the CNT surface. A high degree of functionalization increases both the number of H-bonds and the number of Ca2+-O interactions between the CNT and the tobermorite surface. This results in a stronger interfacial interaction and, therefore, an elevated ISS value. [ABSTRACT FROM AUTHOR]

[Display omitted] • Optimized GbD encapsulation via MD simulations, enhancing bioavailability with γ-CD derivatives. • Octakis(6-O-sulfo)-γ-CD/GbD shows superior stability, driven by favorable Gibbs free energy. • IGMH analysis reveals maximal non-covalent interactions in the Octakis-γ-CD/GbD complex. • Temperature stability study confirms robust GbD inclusion in Octakis(6-O-sulfo)-γ-CD. Glabridin (GbD), a plant-derived bioactive molecule, exhibits diverse biological activities as documented in the literature. However, its low aqueous solubility limits its clinical utility and bioavailability. This study extensively screened β-cyclodextrin (β-CD), γ-CD, and their derivatives to identify the optimal CD for GbD encapsulation to enhance its bioavailability. Molecular dynamics simulations were performed on all docked inclusion complexes (ICs), with selection based on binding energy scores derived via the MM/PBSA method. The selected complexes, γ-CD/GbD and Octakis(6-O-sulfo)-γ-CD/GbD-1, underwent robust umbrella sampling simulations and quantum mechanics calculations using the DFT method (wB97X-D/6-311 + G(d,p)) to determine their thermodynamics. Additionally, MD simulations of the most stable ICs were conducted over a temperature range of 35 °C to 75 °C to assess temperature-dependent structural stability. The analysis revealed higher stability for the Octakis(6-O-sulfo)-γ-CD/GbD-1 complex, attributed to its more favorable Gibbs free energy (−349.92 kJ/mol) compared to γ-CD/GbD (−141.18 kJ/mol). The primary focus of the research was to maximize non-covalent interactions by selecting the appropriate CD form, with Octakis(6-O-sulfo)-γ-CD exhibiting the highest number of non-covalent interactions as elucidated by the IGMH method. Consequently, the Octakis(6-O-sulfo)-γ-CD/GbD-1 IC in 1:1 stoichiometry presents a promising strategy for the future clinical application of GbD. [ABSTRACT FROM AUTHOR]

The mortalities and morbidities of leishmaniasis are high and the disease is under reported globally. The absence of vaccines coupled with chemotherapeutic challenges including chemoresistance, scarcity and toxicity have made the fight against leishmaniasis an arduous one. Furthermore, the treatment options currently available for leishmaniasis are long and sometimes require hospitalization. There is therefore the need to explore novel pathways to identify new compounds with alternative mechanisms of action. A pharmacophore-based screening was employed in identifying new potential inhibitors with unique scaffolds targeting Leishmania donovani sterol methyltransferase (LdSMT), a key enzyme for ergosterol biosynthesis. To accomplish this, 22,26-azasterol, a known inhibitor of this target and five other derivatives with IC50 less than 10 μM were used to generate a robust 3D pharmacophore model via LigandScout with a score of 0.9144. The validated model was used as a query to screen a library of 69034 natural products obtained from the InterBioScreen Limited. Compounds with pharmacophore fit scores above 50 were docked against the modelled structure of LdSMT. Altogether, ten molecules with binding energies between −7 and −11 kcal/mol were identified as potential bioactive molecules. The molecular dynamics simulation and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) calculations reinforced the results from the docking studies suggesting the selected hits bind effectively at the active sites of the target protein. The compounds were observed to bind in the S-adenosine-L-homocysteine binding pocket of the modelled LdSMT with Trp208 and Val330 predicted as key residues critical for ligand binding. Prediction of biological activity with probability of activity (Pa) greater than probability of inactivity (Pi) revealed that seven compounds (STOCKIN-54848, STOCKIN-89115, STOCKIN-68720, STOCKIN-44724, STOCKIN-76694, STOCKIN-47277 and STOCKIN-95708) possessed antileishmanial properties. STOCKIN-89115, STOCKIN-68720, STOCKIN-44724, and STOCKIN-47277 were predicted to be membrane permeability inhibitors, while all ten hit compounds possessed antineoplastic activity. The compounds have the propensity of disrupting ergosterol biosynthesis leading to the suppression of growth in Leishmania donovani. The compounds were predicted to have good absorption, distribution, metabolism, excretion and toxicity profiles, hence their potential antileishmanial activity can be exploited upon experimental corroboration.

In response to antibiotics that inhibit a bacterial enzyme, resistance mutations inevitably arise. Predicting them ahead of time would aid target selection and drug design. The simplest resistance mechanism would be to reduce antibiotic binding without sacrificing too much substrate binding. The property that reflects this is the enzyme “vitality”, defined here as the difference between the inhibitor and substrate binding free energies. To predict such mutations, we borrow methodology from computational protein design. We use a Monte Carlo exploration of mutation space and vitality changes, allowing us to rank thousands of mutations and identify ones that might provide resistance through the simple mechanism considered. As an illustration, we chose dihydrofolate reductase, an essential enzyme targeted by several antibiotics. We simulated its complexes with the inhibitor trimethoprim and the substrate dihydrofolate. 20 active site positions were mutated, or “redesigned” individually, then in pairs or quartets. We computed the resulting binding free energy and vitality changes. Out of seven known resistance mutations involving active site positions, five were correctly recovered. Ten positions exhibited mutations with significant predicted vitality gains. Direct couplings between designed positions were predicted to be small, which reduces the combinatorial complexity of the mutation space to be explored. It also suggests that over the course of evolution, resistance mutations involving several positions do not need the underlying point mutations to arise all at once: they can appear and become fixed one after the other.

Furfuryl mercaptan has the aroma characteristics of coffee. However, it is unstable during storage of coffee brew and roasted coffee. In order to enhance the stability of furfuryl mercaptan, furfuryl mercaptan-β-cyclodextrin inclusion complex was synthesized using the precipitation method in this work. Fourier transform infrared spectroscopy, x-ray diffraction, and thermogravimetric analysis (TG) were used to characterize the resulting products. The interaction of furfuryl mercaptan with β-cyclodextrin was investigated by the molecular mechanics (MM) method. These changes in FTIR and XRD gave supporting evidence for the successful formation of furfuryl mercaptan-β-cyclodextrin inclusion complex. The TG results showed that the formation of furfuryl mercaptan-β-cyclodextrin inclusion complex could improve the thermal stability of furfuryl mercaptan and provide a long-lasting effect. The structure of furfuryl mercaptan-β-cyclodextrin inclusion complex with the minimum energy was obtained by MM2 calculation, and the minimum binding energy was –77.0 kJ mol−1 at –1.96 × 10–10 m.

The rapid spread of SARS-CoV-2 required immediate actions to control the transmission of the virus and minimize its impact on humanity. An extensive mutation rate of this viral genome contributes to the virus' ability to quickly adapt to environmental changes, impacts transmissibility and antigenicity, and may facilitate immune escape. Therefore, it is of great interest for researchers working in vaccine development and drug design to consider the impact of mutations on virus-drug interactions. Here, we propose a multitarget drug discovery pipeline for identifying potential drug candidates which can efficiently inhibit the Receptor Binding Domain (RBD) of spike glycoproteins from different variants of SARS-CoV-2. Eight homology models of RBDs for selected variants were created and validated using reference crystal structures. We then investigated interactions between host receptor ACE2 and RBDs from nine variants of SARS-CoV-2. It led us to conclude that efficient multi-variant targeting drugs should be capable of blocking residues Q(R)493 and N487 in RBDs. Using methods of molecular docking, molecular mechanics, and molecular dynamics, we identified three lead compounds (hesperidin, narirutin, and neohesperidin) suitable for multitarget SARS-CoV-2 inhibition. These compounds are flavanone glycosides found in citrus fruits – an active ingredient of Traditional Chinese Medicines. The developed pipeline can be further used to (1) model mutants for which crystal structures are not yet available and (2) scan a more extensive library of compounds against other mutated viral proteins. [ABSTRACT FROM AUTHOR]

Quantum mechanical (QM) calculations at the level of density-functional tight-binding are applied to a protein–DNA complex (PDB: 2o8b) consisting of 3763 atoms, averaging 100 snapshots from molecular dynamics simulations. A detailed comparison of QM and force field (Amber) results is presented. It is shown that, when solvent screening is taken into account, the contributions of the backbones are small, and the binding of nucleotides in the double helix is governed by the base–base interactions. On the other hand, the backbones can make a substantial contribution to the binding of amino acid residues to nucleotides and other residues. The effect of charge transfer on the interactions is also analyzed, revealing that the actual charge of nucleotides and amino acid residues can differ by as much as 6 and 8% from the formal integer charge, respectively. The effect of interactions on topological models (protein -residue networks) is elucidated. [ABSTRACT FROM AUTHOR]

The partitioning of the molecular mechanics (MM) energy in calculations involving biomolecular systems is important to identify the source of major stabilizing interactions, e.g., in ligand–protein interactions, or to identify residues with considerable contributions in hybrid multiscale calculations, i.e., quantum mechanics/molecular mechanics (QM/MM). Here, we describe Energy Split, a software program to calculate MM energy partitioning considering the AMBER Hamiltonian and parameters. Energy Split includes a graphical interface plugin for VMD to facilitate the selection of atoms and molecules belonging to each part of the system. Energy Split is freely available at or can be easily installed through the VMD Store. [ABSTRACT FROM AUTHOR]

Claudins are cell-cell adhesion proteins within tight junctions that connect epithelial cells together. Claudins polymerize into a network of strand-like structures within the membrane of adjoining cells and create ion channels that control paracellular permeability to water and small molecules. Tight junction morphology and barrier function is tissue specific and regulated by claudin subtypes. Here, we present a molecular dynamics study of claudin-15 strands within lipid membranes and the role of a single-point mutation (A134P) on the third transmembrane helix (TM3) of claudin-15 in determining the morphology of the strand. Our results indicate that the A134P mutation significantly affects the lateral flexibility of the strands, increasing the persistence length of claudin-15 strands by a factor of three. Analyses of claudin-claudin contact in our μsecond-long trajectories show that the mutation does not alter the intermolecular contacts (interfaces) between claudins. However, the dynamics and frequency of interfacial contacts are significantly affected. The A134P mutation introduces a kink in TM3 of claudin-15 similar to the one observed in claudin-3 crystal structure. The kink on TM3 skews the rotational flexibility of the claudins in the strands and limits their fluctuation in one direction. This asymmetric movement in the context of the double rows reduces the lateral flexibility of the strand and leads to higher persistence lengths of the mutant.

In response to hydrostatic pressure, the cation channel transient receptor potential vanilloid 1 (TRPV1) is essential in signaling pathways linked to glaucoma. When activated, TRPV1 undergoes a gating transition from a closed to an open state that allows the influx of Ca2+ ions. However, the gating mechanism of TRPV1 in response to hydrostatic pressure at the molecular level is still lacking. To understand the effect of hydrostatic pressure on the activation of TRPV1, we conducted molecular-dynamics (MD) simulations on TRPV1 under different hydrostatic pressure configurations, with and without a cell membrane. The TRPV1 membrane-embedded model is more stable than the TPRV1-only model, indicating the importance of including the cell membrane in MD simulation. Under elevated pressure at 27.6 mmHg, we observed a more dynamic and outward motion of the TRPV1 domains in the lower-gate area than in the simulation under normal pressure at 12.6 mmHg. While a complete closed-to-open-gate transition was not evident in the limited course of our MD simulations, an increase in the channel radius at the lower gate was observed at 27.6 mmHg versus that at 12.6 mmHg. These findings provide novel information regarding the effect of hydrostatic pressure on TRPV1 channels. [ABSTRACT FROM AUTHOR]

Possessing exceptional properties, graphene has garnered immense interest in the research community for a wide array of potential applications. The mechanical properties play an important role in the success of the potential applications and thus a thorough understanding is cardinal. Computational modeling and simulation is an important tool in the design process due to the low costs compared to the experimental means. This review aims to consolidate the findings of works of computational modeling and simulation of graphene, with focus on models at the continuum and molecular levels. The review shows intrinsic differences in focus of the applications and types of graphene investigated by the different scale models, thus highlighting the advantages and shortcomings of each type of modeling approach. [ABSTRACT FROM AUTHOR]

Cytochrome P450 (CYP) enzymes play essential roles in the synthesis and metabolic activation of physiologically active substances. CYP has a prosthetic heme (iron protoporphyrin IX) in its active center, where Fe ion (heme-Fe) is deeply involved in enzymatic reactions of CYP. To precisely describe the structure and electronic states around heme-Fe, we modified the force fields (FFs) around heme-Fe in molecular mechanics (MM) simulations and conducted ab initio fragment molecular orbital (FMO) calculations for the CYP–ligand complex. To describe the coordination bond between heme-Fe and its coordinated ligand (ketoconazole), we added FF between heme-Fe and the N atom of ketoconazole, and then the structure of the complex was optimized using the modified FF. Its adequacy was confirmed by comparing the MM-optimized structure with the X-ray crystal one of the CYP–ketoconazole complex. We also performed 100 ns molecular dynamics simulations and revealed that the coordination bonds around heme-Fe were maintained even at 310 K and that the CYP–ketoconazole structure was kept similar to the X-ray structure. Furthermore, we investigated the electronic states of the complex using the ab initio FMO method to identify the CYP residues and parts of ketoconazole that contribute to strong binding between CYP and ketoconazole. The present procedure of constructing FF between heme-Fe and ketoconazole can be applicable to other CYP–ligand complexes, and the modified FF can provide their accurate structures useful for predicting the specific interactions between CYP and its ligands. Optimized conformation of ketoconazole coordinated to heme-Fe using MM method with bonded FF. The distance between heme-Fe and the N atom of ketoconazole is indicated. [Display omitted] • We studied structure and electronic states of cytochrome P450 (CYP) and ketoconazole complex. • Force fields around heme-Fe of CYP were modified to describe precisely coordination bonds around Fe. • MM optimized structure of CYP−ketoconazole complex was comparable to the X-ray structure. • Stability of the MM optimized structure was confirmed by MD simulations. • Specific interactions between ketoconazole and CYP residues and heme were investigated using ab initio fragment MO method. [ABSTRACT FROM AUTHOR]

The multiscaling quantum mechanics/molecular mechanics (QM/MM) approach was introduced in 1976, while the extensive acceptance of this methodology started in the 1990s. The combination of QM/MM approach with molecular dynamics (MD) simulation, otherwise known as the QM/MM/MD approach, is a powerful and promising tool for the investigation of chemical reactions' mechanism of complex molecular systems, drug delivery, properties of molecular devices, organic electronics, etc. In the present review, the main methodologies in the multiscaling approaches, i.e., density functional theory (DFT), semiempirical methodologies (SE), MD simulations, MM, and their new advances are discussed in short. Then, a review on calculations and reactions on metalloproteins is presented, where particular attention is given to nitrogenase that catalyzes the conversion of atmospheric nitrogen molecules N₂ into NH₃ through the process known as nitrogen fixation and the FeMo-cofactor. [ABSTRACT FROM AUTHOR]

Molecular mechanics force field calculations have historically shown significant limitations in modeling the energetic and conformational interconversions of highly substituted furanose rings. This is primarily due to the gauche effect that is not easily captured using pairwise energy potentials. In this study, we present a refinement to the set of torsional parameters in the General Amber Force Field (gaff) used to calculate the potential energy of mono, di-, and gem-fluorinated nucleosides. The parameters were optimized to reproduce the pseudorotation phase angle and relative energies of a diverse set of mono- and difluoro substituted furanose ring systems using quantum mechanics umbrella sampling techniques available in the IpolQ engine in the Amber suite of programs. The parameters were developed to be internally consistent with the gaff force field and the TIP3P water model. The new set of angle and dihedral parameters and partial charges were validated by comparing the calculated phase angle probability to those obtained from experimental nuclear magnetic resonance experiments. [ABSTRACT FROM AUTHOR]

When engineering a protein for its biological function, many physicochemical properties are also optimized throughout the engineering process, and the protein's solubility is among the most important properties to consider. Here, we report two novel computational methods to calculate the pH‐dependent protein solubility, and to rank the solubility of mutants. The first is an empirical method developed for fast ranking of the solubility of a large number of mutants of a protein. It takes into account electrostatic solvation energy term calculated using Generalized Born approximation, hydrophobic patches, protein charge, and charge asymmetry, as well as the changes of protein stability upon mutation. This method has been tested on over 100 mutations for 17 globular proteins, as well as on 44 variants of five different antibodies. The prediction rate is over 80%. The antibody tests showed a Pearson correlation coefficient, R, with experimental data from.83 to.91. The second method is based on a novel, completely force‐field‐based approach using CHARMm program modules to calculate the binding energy of the protein to a part of the crystal lattice, generated from X‐ray structure. The method predicted with very high accuracy the solubility of Ribonuclease SA and its 3K and 5K mutants as a function of pH without any parameter adjustments of the existing BIOVIA Discovery Studio binding affinity model. Our methods can be used for rapid screening of large numbers of design candidates based on solubility, and to guide the design of solution conditions for antibody formulation. [ABSTRACT FROM AUTHOR]

The intrinsic inductive properties of atoms or functional groups depend on the chemical properties of either electron-withdrawing groups (EWGs) or electron-donating groups (EDGs). This study aimed to evaluate in silico methods to determine whether changes in chemical properties of the compound by single atomic substitution affect the biological activity of target proteins and whether the results depend on the properties of the functional groups. We found an imidazo[4,5-b]pyridine-based PAK4 inhibitor, compound 1, as an initial hit compound with the well-defined binding mode for PAK4. In this study, we used both experimental and in silico methods to investigate the effect of atomic substitution on biological activity to optimize the initial hit compound. In biological assays, in the case of EWG, as the size of the halogen atom became smaller and the electronegativity increased, the biological activity IC50 value ranged from 5150 nM to inactive; in the case of EDG, biological activity was inactive. Furthermore, we analyzed the interactions of PAK4 with compounds, focusing on the hinge region residues, L398 and E399, and gatekeeper residues, M395 and K350, of the PAK4 protein using molecular docking studies and fragment molecular orbital (FMO) methods to determine the differences between the effect of EWG and EDG on the activity of target proteins. These results of the docking score and binding energy did not explain the differences in biological activity. However, the pair-interaction energy obtained from the results of the FMO method indicated that there was a difference in the interaction energy between the EWG and EDG in the hinge region residues, L398 and E399, as well as in M395 and K350. The two groups with different properties exhibited opposite electrostatic energy and charge transfer energy between L398 and E399. Additionally, we investigated the electron distribution of the parts interacting with the hinge region by visualizing the molecular electrostatic potential (MEP) surface of the compounds. In conclusion, we described the properties of functional groups that affect biological activity using an in silico method, FMO. [ABSTRACT FROM AUTHOR]

Pyridoxal-5′-phosphate (PLP) is a cofactor in the reactions of over 160 enzymes, several of which are implicated in diseases. Methionine γ-lyase (MGL) is of interest as a therapeutic protein for cancer treatment. It binds PLP covalently through a Schiff base linkage and digests methionine, whose depletion is damaging for cancer cells but not normal cells. To improve MGL activity, it is important to understand and engineer its PLP binding. We develop a simulation model for MGL, starting with force field parameters for PLP in four main states: two phosphate protonation states and two tautomeric states, keto or enol for the Schiff base moiety. We used the force field to simulate MGL complexes with each form, and showed that those with a fully-deprotonated PLP phosphate, especially keto, led to the best agreement with MGL structures in the PDB. We then confirmed this result through alchemical free energy simulations that compared the keto and enol forms, confirming a moderate keto preference, and the fully-deprotonated and singly-protonated phosphate forms. Extensive simulations were needed to adequately sample conformational space, and care was needed to extrapolate the protonation free energy to the thermodynamic limit of a macroscopic, dilute protein solution. The computed phosphate pKa was 5.7, confirming that the deprotonated, −2 form is predominant. The PLP force field and the simulation methods can be applied to all PLP enzymes and used, as here, to reveal fine details of structure and dynamics in the active site.

Abstract Three shape‐persistent [4+4] imine cages with truncated tetrahedral geometry with different window sizes were studied as hosts for the encapsulation of tetra‐n‐alkylammonium salts of various bulkiness. In various solvents the cages behave differently. For instance, in dichloromethane the cage with smallest window size takes up NEt4+ but not NMe4+, which is in contrast to the two cages with larger windows hosting both ions. To find out the reason for this, kinetic experiments were carried out to determine the velocity of uptake but also to deduce the activation barriers for these processes. To support the experimental results, calculations for the guest uptakes have been performed by molecular mechanics’ simulations. Finally, the complexation of pharmaceutical interested compounds, such as acetylcholine, muscarine or denatonium have been determined by NMR experiments.

Computer-aided drug design is a powerful and promising tool for drug design and development, with a reduced cost and time. In the current study, we rationally selected a library of 34 fused imidazo[1,2-a]quinoxaline derivatives and performed virtual screening, molecular docking, and molecular mechanics for a lead identification against tubulin as an anticancer molecule. The computational analysis and pharmacophoric features were represented as 1A2; this was a potential lead against tubulin, with a maximized affinity and binding score at the colchicine-binding site of tubulin. The efficiency of this lead molecule was further identified using an in vitro assay on a tubulin enzyme and the anticancer potential was established using an MTT assay. Compound 1A2 (IC50 = 4.33–6.11 µM against MCF-7, MDA-MB-231, HCT-116, and A549 cell lines) displayed encouraging results similar to the standard drug colchicine in these in vitro studies, which further confirmed the effectiveness of CADD in new drug developments. Thus, we successfully applied the utility of in silico techniques to identify the best plausible leads from the fused azaheterocycles.

In the current study, we have investigated the secondary metabolites present in ethnomedical plants used for medicinal purposes-Astilbe chinensis (EK1), Scutellaria barbata D. Don (EK2), Uncaria rhynchophylla (EK3), Fallugia paradoxa (EK4), and Curcuma zedoaria (Christm.) Thread (EK5)-and we have compared them with five compounds of synthetic origin for the inhibition of PARP-1, which is linked to abnormal DNA replication, generating carcinogenic cells. We have studied these interactions through molecular dynamics simulations of each interacting system under physiological conditions (pH, temperature, and pressure) and determined that the compounds of natural origin have a capacity to inhibit PARP-1 (Poly(ADP-ribose) Polymerase 1) in all the cases inspected in this investigation. However, it is essential to mention that their interaction energy is relatively lower compared to that of compounds of synthetic origin. Given that binding energy is mandatory for the generation of a scale or classification of which is the best interacting agent, we can say that we assume that compounds of natural origin, having a complexation affinity with PARP-1, induce cell apoptosis, a potential route for the prevention of the proliferation of carcinogenic cells.

Carbon nanotubes (CNTs) are widely used as reinforcements in cement-based composites. The improvement in the mechanical properties of the resulting materials depends on the characteristics of the interface formed between CNTs and the cement matrix. The experimental characterization of the interfacial properties of these composites is still limited and hard to achieve with currently available technologies. In this work, molecular dynamics and molecular mechanics pull-out simulations of pristine and functionalized CNTs, taken from a tobermorite crystal, were carried out to study interfacial shear strength (ISS) from an atomic perspective. ISS was calculated from the potential energy of the systems. The effects of the CNT diameter and the degree of functionalization on the pull-out process were analyzed according to the ISS and non-bonded energy results. The influence of H-bonding and electrostatic interactions between the CNT and the matrix were also studied. The results show that ISS decreases with increasing CNT radius for pristine CNTs and depends upon the number of H-bonds for functionalized CNTs. ISS values are positively correlated to Enon-bonded energy, which is related to the number of carboxyl groups on the CNT surface. A high degree of functionalization increases both the number of H-bonds and the number of Ca2+-O interactions between the CNT and the tobermorite surface. This results in a stronger interfacial interaction and, therefore, an elevated ISS value.

Theoretical methods, such as molecular mechanics and molecular dynamics, are very useful in understanding differences in interactions at the single molecule level. In the life sciences, small conformational changes, including substituent modifications, often have a significant impact on function in vivo. Changes in binding interactions between nucleic acid molecules and binding proteins are a prime example. In this study, we propose a strategy to predict the complex structure of DNA-binding proteins with arbitrary DNA and analyze the differences in their interactions. We tested the utility of our strategy using the anticancer drug trifluoro-thymidine (FTD), which exerts its pharmacological effect by incorporation into DNA, and confirmed that the binding affinity of the BCL-2-associated X sequence to the p53 tetramer is increased by FTD incorporation. On the contrary, in p53-binding sequences extracted from FTD-resistant cells, the binding affinity of DNA containing FTD was found to be greatly reduced compared to normal DNA. This suggests that thymidine randomly substituted for FTD in resistant cells may acquire resistance by entering a position that inhibits binding to DNA-binding proteins. We believe that this is a versatile procedure that can also take energetics into account and will increase the importance of computational science in the life sciences.

Quantum mechanical (QM) calculations at the level of density-functional tight-binding are applied to a protein–DNA complex (PDB: 2o8b) consisting of 3763 atoms, averaging 100 snapshots from molecular dynamics simulations. A detailed comparison of QM and force field (Amber) results is presented. It is shown that, when solvent screening is taken into account, the contributions of the backbones are small, and the binding of nucleotides in the double helix is governed by the base–base interactions. On the other hand, the backbones can make a substantial contribution to the binding of amino acid residues to nucleotides and other residues. The effect of charge transfer on the interactions is also analyzed, revealing that the actual charge of nucleotides and amino acid residues can differ by as much as 6 and 8% from the formal integer charge, respectively. The effect of interactions on topological models (protein -residue networks) is elucidated.

The rapid spread of SARS-CoV-2 required immediate actions to control the transmission of the virus and minimize its impact on humanity. An extensive mutation rate of this viral genome contributes to the virus’ ability to quickly adapt to environmental changes, impacts transmissibility and antigenicity, and may facilitate immune escape. Therefore, it is of great interest for researchers working in vaccine development and drug design to consider the impact of mutations on virus-drug interactions. Here, we propose a multitarget drug discovery pipeline for identifying potential drug candidates which can efficiently inhibit the Receptor Binding Domain (RBD) of spike glycoproteins from different variants of SARS-CoV-2. Eight homology models of RBDs for selected variants were created and validated using reference crystal structures. We then investigated interactions between host receptor ACE2 and RBDs from nine variants of SARS-CoV-2. It led us to conclude that efficient multi-variant targeting drugs should be capable of blocking residues Q(R)493 and N487 in RBDs. Using methods of molecular docking, molecular mechanics, and molecular dynamics, we identified three lead compounds (hesperidin, narirutin, and neohesperidin) suitable for multitarget SARS-CoV-2 inhibition. These compounds are flavanone glycosides found in citrus fruits – an active ingredient of Traditional Chinese Medicines. The developed pipeline can be further used to (1) model mutants for which crystal structures are not yet available and (2) scan a more extensive library of compounds against other mutated viral proteins.

A series of stiff stilbene macrocycles have been studied to investigate the possible impact of the macrocycle ring size on their photodynamic properties. The results show that reducing the ring size counteracts the photoisomerization ability of the macrocycles. However, even the smallest macrocycle studied (stiff stilbene subunits linked by a six carbon chain) showed some degree of isomerization when irradiated. DFT calculations of the energy differences between the E- and Z-isomers show the same trend as the experimental results. Interestingly the DFT study highlights that the energy difference between the E- and Z-isomers of even the largest macrocycle (linked by a twelve carbon chain) is significantly higher than that of the stiff stilbene unit itself. In general, it is indicated that addition of even a flexible chain to the stiff stilbene unit may significantly affect its photochemical properties and increase the photostability of the resulting macrocycle.