Molecular Interaction Energy Research Articles

Prediction of luciferase inhibitors by the high-performance MIEC-GBDT approach based on interaction energetic patterns.

High-throughput screening (HTS) is widely applied in many fields ranging from drug discovery to clinical diagnostics and toxicity assessment. Firefly luciferase is commonly used as a reporter to monitor the effect of chemical compounds on the activity of a specific target or pathway in HTS. However, the false positive rate of luciferase-based HTS is relatively high because many artifacts or promiscuous compounds that have direct interaction with the luciferase reporter enzyme are usually identified as active compounds (hits). Therefore, it is necessary to develop a rapid screening method to identify these compounds that can inhibit the luciferase activity directly. In this study, a virtual screening (VS) classification model called MIEC-GBDT (MIEC: Molecular Interaction Energy Components; GBDT: Gradient Boosting Decision Tree) was developed to distinguish luciferase inhibitors from non-inhibitors. The MIECs calculated by Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy decomposition were used to energetically characterize the binding pattern of each small molecule at the active site of luciferase, and then the GBDT algorithm was employed to construct the classifiers based on MIECs. The predictions to the test set show that the optimized MIEC-GBDT model outperformed molecular docking and MM/GBSA rescoring. The best MIEC-GBDT model based on the MIECs with the energy terms of ΔGele, ΔGvdW, ΔGGB, and ΔGSA achieves the prediction accuracies of 87.2% and 90.3% for the inhibitors and non-inhibitors in the test sets, respectively. Moreover, the energetic analysis of the vital residues suggests that the energetic contributions of the vital residues to the binding of inhibitors are quite different from those to the binding of non-inhibitors. These results suggest that the MIEC-GBDT model is reliable and can be used as a powerful tool to identify potential interference compounds in luciferase-based HTS experiments.

Putative model for heat shock protein 70 complexation with receptor of advanced glycation end products through fluorescence proximity assays and normal mode analyses.

Extracellular heat shock protein 70 (HSP70) is recognized by receptors on the plasma membrane, such as Toll-like receptor 4 (TLR4), TLR2, CD14, and CD40. This leads to activation of nuclear factor-kappa B (NF-κB), release of pro-inflammatory cytokines, enhancement of the phagocytic activity of innate immune cells, and stimulation of antigen-specific responses. However, the specific characteristics of HSP70 binding are still unknown, and all HSP70 receptors have not yet been described. Putative models for HSP70 complexation to the receptor for advanced glycation endproducts (RAGEs), considering both ADP- and ATP-bound states of HSP70, were obtained through molecular docking and interaction energy calculations. This interaction was detected and visualized by a proximity fluorescence-based assay in A549 cells and further analyzed by normal mode analyses of the docking complexes. The interacting energy of the complexes showed that the most favored docking situation occurs between HSP70 ATP-bound and RAGE in its monomeric state. The fluorescence proximity assay presented a higher number of detected spots in the HSP70 ATP treatment, corroborating with the computational result. Normal-mode analyses showed no conformational deformability in the interacting interface of the complexes. Results were compared with previous findings in which oxidized HSP70 was shown to be responsible for the differential modulation of macrophage activation, which could result from a signaling pathway triggered by RAGE binding. Our data provide important insights into the characteristics of HSP70 binding and receptor interactions, as well as putative models with conserved residues on the interface area, which could be useful for future site-directed mutagenesis studies.

Theoretical study of the interaction energy of benzodifuranone dye molecule rings

The aim of this paper was to reveal the relationship between the interaction energy of benzodifuranone dyes and dyeing performance indices such as dyeing temperature and colour fastness. Dimer models of benzene–benzene, benzodifuranone–benzene, and benzodifuranone–benzodifuranone configuration were set up, and geometry optimisation and interaction energy were calculated using a density functional theory ωB97XD, 6‐311G++ (d, p) basis set. The calculation results showed that the benzodifuranone molecule had better coplanarity. The molecular interaction energy of benzene–benzene, benzodifuranone–benzene, and benzodifuranone–benzodifuranone rings decreased at first, and then increased with growth in the distance between the rings, the lowest energy occurring at a distance of about 3.25–3.75 Å. The dispersion force affected the interaction energy of benzodifuranone–benzene rings most, while both dispersion force and electrostatic force influenced the interaction energy of benzodifuranone–benzodifuranone rings. These calculation and experimental results revealed that a greater energy was needed to destroy the dye–fibre and dye–dye interaction energy of benzodifuranone‐based disperse dyes.

Mathematical modeling of interaction energies between nanoscale objects: A review of nanotechnology applications

In many nanotechnology areas, there is often a lack of well-formed conceptual ideas and sophisticated mathematical modeling in the analysis of fundamental issues involved in atomic and molecular interactions of nanostructures. Mathematical modeling can generate important insights into complex processes and reveal optimal parameters or situations that might be difficult or even impossible to discern through either extensive computation or experimentation. We review the use of applied mathematical modeling in order to determine the atomic and molecular interaction energies between nanoscale objects. In particular, we examine the use of the 6-12 Lennard-Jones potential and the continuous approximation, which assumes that discrete atomic interactions can be replaced by average surface or volume atomic densities distributed on or throughout a volume. The considerable benefit of using the Lennard-Jones potential and the continuous approximation is that the interaction energies can often be evaluated analytically, which means that extensive numerical landscapes can be determined virtually instantaneously. Formulae are presented for idealized molecular building blocks, and then, various applications of the formulae are considered, including gigahertz oscillators, hydrogen storage in metal-organic frameworks, water purification, and targeted drug delivery. The modeling approach reviewed here can be applied to a variety of interacting atomic structures and leads to analytical formulae suitable for numerical evaluation.

Quantitative In Silico Analysis of Retention of Nitrobenzofurazan-Amino Acids in Reversed-Phase Ion-Pair Liquid Chromatography.

The retention mechanisms of nitrobenzofurazan (NBD)-amino acids in reversed-phase ion-pair liquid chromatography were quantitatively analyzed in silico The most contributed interaction for the retention is the Lewis acid-base interaction between an aromatic ring of NBD-amino acids and hydroxyl-group hydrogen of tetra-butyl-ammonium hydroxide coated on the hydrophobic phase. Solvent effects significantly improved the relation between the calculated molecular interaction (MI) energy values using a molecular mechanics program and log k values measured in chromatography. The correlation coefficient between the calculated MI energy values and the log k values was>0.95.

Kirkwood-Buff Integrals for Aqueous Urea Solutions Based upon the Quantum Chemical Electrostatic Potential and Interaction Energies.

Cosolvents, such as urea, affect protein folding and binding, and the solubility of solutes. The modeling of cosolvents has been facilitated significantly by the rigorous Kirkwood-Buff (KB) theory of solutions, which can describe structural thermodynamics over the entire composition range of aqueous cosolvent mixtures based only on the solution density and the KB integrals (KBIs), i.e., the net excess radial distribution functions from the bulk. Using KBIs to describe solution thermodynamics has given rise to a clear guideline that an accurate prediction of KBIs is equivalent to accurate modeling of cosolvents. Taking urea as an example, here we demonstrate that an improvement in the prediction of KBIs comes from an improved reproduction of high-level quantum chemical (QC) electrostatic potential and molecular pairwise interaction energies. This rational approach to the improvement of the KBI prediction stems from a comparison of existing force fields, AMOEBA, and the generalized AMBER force field, as well as the further optimization of the former to enable better agreement with QC interaction energies. Such improvements would pave the way toward a rational and systematic determination of the transferable force field parameters for a number of important small molecule cosolvents.

Methane adsorption on the graphene sheets, activated carbon and carbon black

Behavior of methane adsorption on typical carbon based materials was comparatively studied for development of storage medium for adsorbed natural gas (ANG). Three kinds of carbon materials, graphene sheets (GS), activated carbon and carbon black, which respectively has a specific surface area about 300m2/g, 1118m2/g and 76m2/g, were selected for adsorption equilibrium testes within temperature-pressure range from 253.15K to 293.15K and 0 to 8MPa. Langmuir-Freundlich (L-F) equation and a lattice theory based adsorption model were employed to determine the isosteric heat of adsorption and the molecular interaction energy between adsorbates. It is found that mean relative deviations between the experimental results and those predicted by L-F equation are less than 1%, and an adsorbent having a larger specific surface area has a higher adsorption amount and a bigger isosteric heat of adsorption. It is also noted that molecular energy among methane molecules within the adsorption layer on the carbon black is the largest in comparing with those on the GS and the activated carbon. Results also reveal that interaction mechanism between methane and the activated carbon is similar to that between methane and the GS. It suggests that the GS-related storage medium for ANG should have a higher specific surface area.

Multipolar Electrostatic Energy Prediction for all 20 Natural Amino Acids Using Kriging Machine Learning.

A machine learning method called kriging is applied to the set of all 20 naturally occurring amino acids. Kriging models are built that predict electrostatic multipole moments for all topological atoms in any amino acid based on molecular geometry only. These models then predict molecular electrostatic interaction energies. On the basis of 200 unseen test geometries for each amino acid, no amino acid shows a mean prediction error above 5.3 kJ mol(-1), while the lowest error observed is 2.8 kJ mol(-1). The mean error across the entire set is only 4.2 kJ mol(-1) (or 1 kcal mol(-1)). Charged systems are created by protonating or deprotonating selected amino acids, and these show no significant deviation in prediction error over their neutral counterparts. Similarly, the proposed methodology can also handle amino acids with aromatic side chains, without the need for modification. Thus, we present a generic method capable of accurately capturing multipolar polarizable electrostatics in amino acids.

Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery.

The MIEC-SVM approach, which combines molecular interaction energy components (MIEC) derived from free energy decomposition and support vector machine (SVM), has been found effective in capturing the energetic patterns of protein-peptide recognition. However, the performance of this approach in identifying small molecule inhibitors of drug targets has not been well assessed and validated by experiments. Thereafter, by combining different model construction protocols, the issues related to developing best MIEC-SVM models were firstly discussed upon three kinase targets (ABL, ALK, and BRAF). As for the investigated targets, the optimized MIEC-SVM models performed much better than the models based on the default SVM parameters and Autodock for the tested datasets. Then, the proposed strategy was utilized to screen the Specs database for discovering potential inhibitors of the ALK kinase. The experimental results showed that the optimized MIEC-SVM model, which identified 7 actives with IC50 < 10 μM from 50 purchased compounds (namely hit rate of 14%, and 4 in nM level) and performed much better than Autodock (3 actives with IC50 < 10 μM from 50 purchased compounds, namely hit rate of 6%, and 2 in nM level), suggesting that the proposed strategy is a powerful tool in structure-based virtual screening.

Next-Generation Force Fields from Symmetry-Adapted Perturbation Theory.

Symmetry-adapted perturbation theory (SAPT) provides a unique set of advantages for parameterizing next-generation force fields from first principles. SAPT provides a direct, basis-set superposition error free estimate of molecular interaction energies, a physically intuitive energy decomposition, and a seamless transition to an asymptotic picture of intermolecular interactions. These properties have been exploited throughout the literature to develop next-generation force fields for a variety of applications, including classical molecular dynamics simulations, crystal structure prediction, and quantum dynamics/spectroscopy. This review provides a brief overview of the formalism and theory of SAPT, along with a practical discussion of the various methodologies utilized to parameterize force fields from SAPT calculations. It also highlights a number of applications of SAPT-based force fields for chemical systems of particular interest. Finally, the review ends with a brief outlook on the future opportunities and challenges that remain for next-generation force fields based on SAPT.

Copper hydroxide nanostructure-modified carbon ionic liquid electrode as an efficient voltammetric sensor for detection of metformin: a theoretical and experimental study

The electrocatalytic oxidation of metformin (MET) was investigated at Cu(OH)2 nanoparticle-modified carbon ionic liquid electrode (Cu(OH)2/CILE). This electrode exhibited excellent characteristic for the electrocatalytic oxidation of metformin at the potential of +0.6 V with good sensitivity and selectivity. The presence of Cu(OH)2 nanostructures in the composite electrode leads to the appearance of oxidation peak of MET. Under optimal experimental conditions, the peak current response increased linearly with metformin concentration over the range of 1 µM–4 mM. The detection limit of the method is 0.5 µM. Moreover, the closer look was taken at the electronic properties of MET and its Cu (II) complexes such as frontier molecular orbital (HOMO and LUMO) and binding interaction energies using density functional theory. Effect of pH was also investigated at B3LYP/6-311++g** level. Theoretical results confirmed the experimental evidences of Cu (II) complexation. Therefore, Ease of preparation, wide linear range, low overpotential, high sensitivity and selectivity provide the possibility of applying this method for the detection of MET in biological samples.

Investigation of Surface and Solubility Properties of N-Vinylimidazolium Tetrahalogenidoferrate(III) Magnetic Ionic Liquids Using Density Functional Theory

N-Vinyl-3-alkylimidazolium tetrahalogenidoferrate(III) ([VRIM][FeX4], X4 = Cl3Br, Cl4) and N-vinyl-3-esterimidazolium tetrachloroferrate(III)([VEIM][FeCl4]) magnetic ionic liquids were synthesized. They were characterized by 1H NMR, Raman, electrospray ionization mass spectrometry, differential scanning calorimetry and thermogravimetric analysis. Through Gaussian09/B3LYP/LANL2DZ density functional theory, the interaction energies of ion pairs and dipole moment of [VRIM][FeX4] and [VEIM][FeCl4] were obtained. The relationships between the surface tensions and temperature, molecular structure, and interaction energies of ion pairs along with the relationships between the solubility and molecular structure, common solvents, and interaction energies of ion pairs were discussed systematically. The relationship between the surface tensions and solubility parameter for [VRIM][FeX4] was expressed by using a Hildebrand–Scoff equation. And the hydrophilic–lipophilic balance (HLB) values of [VRIM][FeX4] were obtaine...

Quantitative In Silico Analysis of Retention of Phenylthiohydantoin-Amino Acids in Reversed-Phase Ion-Pair Liquid Chromatography.

The retention mechanisms of phenylthiohydantoin (PTH)-amino acids in reversed-phase ion-pair liquid chromatography were quantitatively analyzed in silico. The most significant interaction for the retention was the Lewis acid-base interaction between an aromatic ring of a PTH-amino acid and a hydroxyl-group hydrogen of tetra-alkyl ammonium hydroxide. Solvent effects, addition of molecular interaction (MI) energy values between an analyte and solvent molecules, significantly improved the relationship between the MI energy values, calculated using a molecular mechanics program, and logk values, measured via chromatography. The correlation coefficient between the calculated MI energy values and the logk values was 0.98 (n = 19).

Binary adsorption isotherms of two ionic liquids and ibuprofen on an activated carbon cloth: simulation and interpretations using statistical and COSMO-RS models

Chemical structures of IL1, IL2 and IBP.

Interaction of osmium(ii) redox probes with DNA: insights from theory.

In the course of developing ultrasensitive and quantitative electrochemical point-of-care analytical tools for genetic detection of infectious diseases, osmium(ii) metallointercalators were revealed to be suitable and efficient redox probes to monitor the in vitro DNA amplification [Defever etal, Anal. Chem., 2011, 83, 1815-1821]. In this work, we thus propose a complete computational protocol in order to evaluate the affinity between Os(ii) complexes with double-stranded DNA. This protocol is based on molecular dynamics, with the parametrization of the GAFF force field for the Os(ii) complexes presenting an octahedral environment with polypyridine ligands, and QM/QM' calculations to evaluate the binding energy. For three Os(ii) probes and different binding sites, molecular dynamics simulations and interaction energies calculated at the QM/QM' level are successively discussed and compared to experimental data in order to identify the most stable binding sites. The computational protocol we propose should then be used to design more efficient Os(ii) metallointercalators.

Hydrogen-Bonded Complexes of Phenylacetylene-Acetylene: Who is the Proton Donor?

Hydrogen-bonded complexes of C2H2 and phenylacetylene (PhAc) were studied using matrix isolation infrared spectroscopy and quantum chemical computations. Both C2H2 and PhAc, being potential proton donors, the question arises as to which of the two species would be the proton donor in the PhAc-C2H2 complex; a question that this work primarily addresses. The molecular structures, vibrational frequencies, and interaction energies of the PhAc-C2H2 complexes were calculated at the M06-2X and MP2 levels of theory, employing both 6-311++G(d,p) and aug-cc-pVDZ basis sets. At the M06-2X/aug-cc-pVDZ level, two nearly isoenergetic complexes (BSSE corrected) were indicated to be the global minima; one a C-H···π complex, where C2H2 served as a proton donor to the phenyl π-system in PhAc, and the other a C-H···π complex, where C2H2 served as a proton donor to the acetylene π-system in PhAc. Of the two, only the second complex was identified in the matrix, evidenced by a characteristic large shift in the ≡C-H stretch of C2H2. Experiments were also performed using PhAc deuterated at the acetylene hydrogen (PhAcD) to study the isotopic effects on the vibrational spectra of complexes. The isotopic studies further confirmed the structure of the complex trapped in the matrix, thereby presenting unambiguous evidence that C2H2 served as the proton donor to the acetylene π-system of PhAc. The theory of atoms-in-molecules (AIM), energy decomposition (EDA), and natural bond orbital (NBO) analysis were performed to understand the nature of the interactions involved in the complexes.

Biological Applications of Isothermal Titration Calorimetry

Most of the biological phenomena are influenced by intermolecular recognition and interaction. Thus, understanding the thermodynamics of biomacromolecule ligand interaction is a very interesting area in biochemistry and biotechnology. One of the most powerful techniques to obtain precise information about the energetics of (bio) molecules binding to other biological macromolecules is isothermal titration calorimetry (ITC). In a typical ITC experiment, a macromolecule solution is titrated by a solution containing a reactant at a constant temperature, and exchanged heat of the reaction is measured, allowing determination of thermodynamic parameters (enthalpy change, entropy change, change in Gibbs free energy, binding affinity and stoichiometry) of molecular interactions. In this review article, we describe the ITC approach briefly and review some applications of ITC for studying protein-ligand interactions, protein-protein interactions, self-association, and drug design processes. Furthermore, the application of ITC for determination of kinetic parameters of enzyme catalyzed reactions as well as thermodynamic parameters will be discussed.

Interplay between hydrogen bond and single-electron tetrel bond: H3C⋯COX2⋯HY and H3C⋯CSX2⋯HY (X = F, Cl; Y = CN, NC) complexes as a working model

UMP2 calculations with aug-cc-pVTZ basis set were performed to analyze intermolecular interactions in a series of ring-shaped molecular complexes formed by CH3, CO(S)X2 (X=F, Cl) and HCN(NC) which are connected via two hydrogen bonds and a single-electron tetrel bond interactions. Molecular geometries and interaction energies of triads are investigated at the UMP2/aug-cc-pVTZ computational level. Particular attention is paid to many-body interaction energies. The impacts of the hydrogen bonds on the single-electron tetrel bond in each complex are systematically investigated. The electronic properties of the complexes are analyzed using parameters derived from the atoms in molecules (AIM) methodology.

Penetration of spherical gold nanoparticle through lipid bilayer

Safety issues for the use of products containing nanoparticles need to be considered, since these nanoparticles may break through human skin to damage cells. In this paper, applied mathematical techniques are used to model the penetration of a spherical gold nanoparticle into an assumed circular hole in a lipid bilayer. The 6–12 Lennard-Jones potential is employed, and the total molecular interaction energy is obtained using the continuous approximation. Nanoparticles of three different radii, namely, 10, 15 and 20 Å, are studied, which are initiated at rest, confined to the axis of the hole. A similar behaviour for these three cases is observed. The critical hole radii at which these nanoparticles enter the bilayer are 12.65, 17.62 and 22.60 Å, respectively. Further, once the hole radii become larger than 20.79, 23.14 and 27.02 Å, respectively, the gold nanoparticles tend to remain at the mid-plane of the bilayer, and do not pass through the bilayer. doi:10.1017/S1446181115000103

Energy behaviour for DNA translocation through graphene nanopores

Nanoparticles have considerable promise for many applications in electronics, energy storage, bioscience and biotechnologies. Here we use applied mathematical modelling to exploit the basic principles of mechanics and the 6–12 Lennard-Jones potential function together with the continuum approach, which assumes that a discrete atomic structure can be replaced by an average constant atomic surface density of atoms that is assumed to be smeared over each molecule. We identify a circular hole in a graphene sheet as a nanopore and we consider the molecular interaction energy for both single-strand and double-strand DNA molecules assumed to move through the circular hole in a graphene sheet to determine the radius b of the hole that gives the minimum energy. By minimizing the interaction energy, we observe that the single-strand DNA and double-strand DNA molecules penetrate through a graphene nanopore when the pore radii b> 7.8Å and b> 12.7Å, respectively. Our results can be adopted to offer new applications in the atomic surface processes and electronic sensing.