Noncovalent keystone interactions controlling biomembrane structure

There is a biomedical need to develop molecular recognition systems that selectively target the interfaces of protein and lipid aggregates in biomembranes. This is an extremely challenging problem in supramolecular chemistry because the biological membrane is a complex dynamic assembly of multifarious molecular components with local inhomogeneity. Two simplifying concepts are presented as a framework for basing molecular design strategies. The first generalization is that association of two binding partners in a biomembrane will be dominated by one type of non-covalent interaction which is referred to as the keystone interaction. Structural mutations in membrane proteins that alter the strength of this keystone interaction will likely have a major effect on biological activity and often will be associated with disease. The second generalization is to view the structure of a cell membrane as three spatial regions, that is, the polar membrane surface, the midpolar interfacial region and the non-polar membrane interior. Each region has a distinct dielectric, and the dominating keystone interaction between binding partners will be different. At the highly polar membrane surface, the keystone interactions between charged binding partners are ion-ion and ion-dipole interactions; whereas, ion-dipole and ionic hydrogen bonding are very influential at the mid-polar interfacial region. In the non-polar membrane interior, van der Waals forces and neutral hydrogen bonding are the keystone interactions that often drive molecular association. Selected examples of lipid and transmembrane protein association systems are described to illustrate how the association thermodynamics and kinetics are dominated by these keystone noncovalent interactions.     

Hit-to-Lead Short Peptides against Dengue Type 2 Envelope Protein: Computational and Experimental Investigations

Data from the World Health Organisation show that the global incidence of dengue infection has risen drastically, with an estimated 400 million cases of dengue infection occurring annually. Despite this worrying trend, there is still no therapeutic treatment available. Herein, we investigated short peptide fragments with a varying total number of amino acid residues (peptide fragments) from previously reported dengue virus type 2 (DENV2) peptide-based inhibitors, DN58wt (GDSYIIIGVEPGQLKENWFKKGSSIGQMF), DN58opt (TWWCFYFCRRHHPFWFFYRHN), DS36wt (LITVNPIVTEKDSPVNIEAE), and DS36opt (RHWEQFYFRRRERKFWLFFW), aided by in silico approaches: peptide–protein molecular docking and 100 ns of molecular dynamics (MD) simulation via molecular mechanics using Poisson–Boltzmann surface area (MMPBSA) and molecular mechanics generalised Born surface area (MMGBSA) methods. A library of 11,699 peptide fragments was generated, subjected to in silico calculation, and the candidates with the excellent binding affinity and shown to be stable in the DI-DIII binding pocket of DENV2 envelope (E) protein were determined. Selected peptides were synthesised using conventional Fmoc solid-phase peptide chemistry, purified by RP-HPLC, and characterised using LCMS. In vitro studies followed, to test for the peptides’ toxicity and efficacy in inhibiting the DENV2 growth cycle. Our studies identified the electrostatic interaction (from free energy calculation) to be the driving stabilising force for the E protein–peptide interactions. Five key E protein residues were also identified that had the most interactions with the peptides: (polar) LYS36, ASN37, and ARG350, and (nonpolar) LEU351 and VAL354; these residues might play crucial roles in the effective binding interactions. One of the peptide fragments, DN58opt_8-13 (PFWFFYRH), showed the best inhibitory activity, at about 63% DENV2 plague reduction, compared with no treatment. This correlates well with the in silico studies in which the peptide possessed the lowest binding energy (−9.0 kcal/mol) and was maintained steadily within the binding pocket of DENV2 E protein during the MD simulations. This study demonstrates the use of computational studies to expand research on lead optimisation of antiviral peptides, thus explaining the inhibitory potential of the designed peptides.     

IL-18与IL-18R分子对接计算发展模拟蛋白质互作研究方法

研究蛋白质互作的化学生物学方法主要有荧光共振能量转移(Fluorescence resonance energy transfer, FRET)、酵母双杂交(Yeast two-hybrid technology, YTH)、免疫共沉淀(Co-immunoprecipitation, Co-IP)等。在此基础上,为了发展一种新的研究生物大分子互作,特别是膜蛋白相互作用的定量计算方法,依据前期研究发现,应用ELISA方法与QAH-NEU-1定量芯片技术检测NLRP2:ShRNAs慢病毒(Lentivirus)感染人脑微血管内皮细胞(Human brain microvascular endothelial cells, HBMEC), 敲除(Knocking down)NLRP2基因后的IL-18的分泌量与对照组比较, 显著提高(IL-18: 998 pg/mL),表明它在炎症免疫中起关键调控作用。本文采用高性能的Discovery Studio 2021(DS2018R2)大分子计算模拟软件,在RCSB PDB数据库中调用蛋白质文件建立其立体结构,应用ZDOCK程序算法探究IL-18亚基(AB亚基或B亚基)与IL-18R互作的空间结构与构象变化,计算找到了相互作用界面的氨基酸的一级序列与二级结构,以及它们之间的相互作用力,并用拉氏图评估对接构象,研究发现B亚基在IL-18与IL-18R的结合中起主要作用。该计算方法与实验方法比较,可快速找到蛋白-蛋白相互作用的构象空间,优化膜蛋白互作的精度;能从原子与量子水平探究细胞因子与膜蛋白受体的互作;更深入解析分子机理,数据精确定量。研究结果表明本文应用ZDOCK算法建立了通过计算模拟膜蛋白生物大分子互作的新领域,为细胞因子与化学因子的多肽类药物开发提供新的思路; 为细菌病毒感染/肿瘤疾病的防治提供科学理论依据; 在分子识别,神经元网络深度学习,生物信息处理领域具有广泛的应用。     

Energy transfer dynamics and kinetics of elementary processes (promoted) by gas‐phase CO2‐N2 collisions: Selectivity control by the anisotropy of the interaction

In this work, we exploit a new formulation of the potential energy and of the related computational procedures, which embodies the coupling between the intra and intermolecular components, to characterize possible propensities of the collision dynamics in energy transfer processes of interest for simulation and control of phenomena occurring in a variety of equilibrium and nonequilibrium environments. The investigation reported in the paper focuses on the prototype CO₂–N₂ system, whose intramolecular component of the interaction is modeled in terms of a many body expansion while the intermolecular component is modeled in terms of a recently developed bonds‐as‐interacting‐molecular‐centers' approach. The main advantage of this formulation of the potential energy surface is that of being (a) truly full dimensional (i.e., all the variations of the coordinates associated with the molecular vibrations and rotations on the geometrical and electronic structure of the monomers, are explicitly taken into account without freezing any bonds or angles), (b) more flexible than other usual formulations of the interaction and (c) well suited for fitting procedures better adhering to accurate ab initio data and sensitive to experimental arrangement dependent information. Specific attention has been given to the fact that a variation of vibrational and rotational energy has a higher (both qualitative and quantitative) impact on the energy transfer when a more accurate formulation of the intermolecular interaction (with respect to that obtained when using rigid monomers) is adopted. This makes the potential energy surface better suited for the kinetic modeling of gaseous mixtures in plasma, combustion and atmospheric chemistry computational applications. © 2016 Wiley Periodicals, Inc.     

Modeling electrochemical interfaces from ab initio molecular dynamics: water adsorption on metal surfaces at potential of zero charge

The origin of the potential difference between the potential of zero charge of a metal/water interface and the work function of the metal is a recurring issue because it is related to how water interacts with metal surface in the absence of surface charge. Recently ab initio molecular dynamics method has been used to model electrochemical interfaces to study interfacial potential and the structure of interface water. Here, we will first introduce the computational standard hydrogen electrode method, which allows for ab initio determination of electrode potentials that can be directly compared with experiment. Then, we will review the recent progress from ab initio molecular dynamics simulation in understanding the interaction between water and metal and its impact on interfacial potential. Finally, we will give our perspective for future development of ab initio computational electrochemistry.     

量子力学和分子力学组合方法及其应用

QM/MM组合方法在研究凝聚态中的化学反应及生物大分子的结构和活性之间的关系等方面已取得重要进展。这一方法的要点在于将大体系配分成几部分,根据需要对不同部分进行不同级别的处理,因此既利用了量子力学的精确性,又利用了分子力学的高效性。对QM/MM组合理论及其一些最新进展作一简单介绍,并以最近进行了几个工作为例说明QM、MM组合方法的应用。     

Mechanism of chemical reactions in the active site of aspartate N-acetyltransferase NAT8L revealed by molecular modeling

The results of a computational study of the synthesis of a key brain metabolite, N-acetyl-l-aspartate, catalyzed by aspartate N-acetyltransferase, encoded by the NAT8L gene, are reported. The reaction Gibbs energy profiles were computed using molecular dynamics simulations with interaction potentials estimated on-the-fly by the quantum mechanics/molecular mechanics QM(PBE0/6-31G**)/MM(CHARMM) approach. The revealed reaction mechanism includes four elementary steps with corresponding activation energies not exceeding 14 kcal mol^?1     

In Silico Design and Selection of New Tetrahydroisoquinoline-Based CD44 Antagonist Candidates

CD44 promotes metastasis, chemoresistance, and stemness in different types of cancer and is a target for the development of new anti-cancer therapies. All CD44 isoforms share a common N-terminal domain that binds to hyaluronic acid (HA). Herein, we used a computational approach to design new potential CD44 antagonists and evaluate their target-binding ability. By analyzing 30 crystal structures of the HA-binding domain (CD44HAbd), we characterized a subdomain that binds to 1,2,3,4-tetrahydroisoquinoline (THQ)-containing compounds and is adjacent to residues essential for HA interaction. By computational combinatorial chemistry (CCC), we designed 168,190 molecules and compared their conformers to a pharmacophore containing the key features of the crystallographic THQ binding mode. Approximately 0.01% of the compounds matched the pharmacophore and were analyzed by computational docking and molecular dynamics (MD). We identified two compounds, Can125 and Can159, that bound to human CD44HAbd (hCD44HAbd) in explicit-solvent MD simulations and therefore may elicit CD44 blockage. These compounds can be easily synthesized by multicomponent reactions for activity testing and their binding mode, reported here, could be helpful in the design of more potent CD44 antagonists.     

Hydrogen bond lifetime for water in classic and quantum molecular dynamics

The lifetime of hydrogen bonds in water at T = 298 K and p = 0.1 MPa is computed by means of classic molecular dynamics with eight different potentials of pair lifetime interaction and Car-Parinello molecular dynamics. The results obtained using various computational techniques for hydrogen bond life-times are compared. It is shown that they can differ from one another by several times. The dependence for the hydrogen bond lifetime computed in our numerical experiment upon the method of its determination is found.     

Substituent Effect Parameters: Extending the Applications to Organometallic Chemistry

Typically, metal complexes are constituted of an acceptor metal ion and one or more Iigands containing the donor atoms. Accordingly, the properties of a metal complex are equally dependent on the nature of the metal ion and the ligands. Minute structural variations in the ligand will may result in linear changes in the respective energetic parameters and such linear relationships have paramount importance in organometallic chemistry. The variation in ligands is virtually limitless and substantial because of the extent of organic chemistry available for the modelling of desirable ligands, apart from the variation in metal ions. Anyhow, there is still a need for new parameters for the design and quantification of new ligands which in turn leads to the synthesis of metal complexes with possibly predictable chemical properties. Previous studies have demonstrated that quantum chemically derived molecular electrostatic potential (MESP) parameters can be listed as one of the superior quantifiers in this regard, which can act as an effective ligand electronic parameter. The interaction between the ligand part and metal-containing part will be crucial in assessing the reactivity of organometallic complexes. Here we are applying MESP based substituent constants derived from substituted benzenes to forecast the interaction energies in (pyr^*)W(CO)₅, (NHC^*)Mo(CO)₅ and (η⁶-arene^*)Cr(CO)₃ complexes. Ligands and metal ions are varied in each case for better understanding and transparency.     

Computational algorithmic and molecular dynamics study of functional and structural impacts of non-synonymous single nucleotide polymorphisms in human DHFR gene

Human dihydrofolate reductase (DHFR) is a conserved enzyme that is central to folate metabolism and is widely targeted in pathogenic diseases as well as cancers. Although studies have reported the fact that genetic mutations in DHFR leads to a rare autosomal recessive inborn error of folate metabolism and drug resistance, there is a lack of an extensive study on how the deleterious non-synonymous SNPs (nsSNPs) disrupt its phenotypic effects. In this study, we aim at discovering the structural and functional consequences of nsSNPs in DHFR by employing a combined computational approach consisting of ten recently developed in silico tools for identification of damaging nsSNPs and molecular dynamics (MD) simulation for getting deeper insights into the magnitudes of damaging effects. Our study revealed the presence of 12 most deleterious nsSNPs affecting the native phenotypic effects, with three (R71T, G118D, Y122D) identified in the co-factor and ligand binding active sites. MD simulations also suggested that these three SNPs particularly Y122D, alter the overall structural flexibility and dynamics of the native DHFR protein which can provide more understandings into the crucial roles of these mutants in influencing the loss of DHFR function.     

A computationally inexpensive modification of the point dipole electrostatic polarization model for molecular simulations

We present an approximation, which allows reduction of computational resources needed to explicitly incorporate electrostatic polarization into molecular simulations utilizing empirical force fields. The proposed method is employed to compute three-body energies of molecular complexes with dipolar electrostatic probes, gas-phase dimerization energies, and pure liquid properties for five systems that are important in biophysical and organic simulations-water, methanol, methylamine, methanethiol, and acetamide. In all the cases, the three-body energies agreed with high level ab initio data within 0.07 kcal/mol, dimerization energies-within 0.43 kcal/mol (except for the special case of the CH(3)SH), and computed heats of vaporization and densities differed from the experimental results by less than 2%. Moreover, because the presented method allows a significant reduction in computational cost, we were able to carry out the liquid-state calculations with Monte Carlo technique. Comparison with the full-scale point dipole method showed that the computational time was reduced by 3.5 to more than 20 times, depending on the system in hand and on the desired level of the full-scale model accuracy, while the difference in energetic results between the full-scale and the presented approximate model was not great in the most cases. Comparison with the nonpolarizable OPLS-AA force field for all the substances involved and with the polarizable POL3 and q90 models for water and methanol, respectively, demonstrates that the presented technique allows reduction of computational cost with no sacrifice of accuracy. We hope that the proposed method will be of benefit to research employing molecular modeling technique in the biophysical and physical organic chemistry areas.     

Combinatorial chemistry approach to chiral catalyst engineering and screening: rational design and serendipity

An efficient asymmetric catalyst relies on the successful combination of a large number of interrelated variables, including rational design, intuition, persistence, and good fortune-not all of which are necessarily well-understood; this renders such practice largely empirical. As a result, the possibility of using combinatorial chemistry methods in asymmetric catalysis research has been widely recognized to be highly desirable. In this account, we attempt to show the principle and application of combinatorial approach in the discovery of chiral catalysts for enantioselective reactions. The concept focuses on the strategy for the creation of a modular chiral catalyst library by two-component ligand modification of metal ions on the basis of molecular recognition and assembly. The self-assembled chiral catalyst with two different ligands indeed exhibited synergistic effects in terms of both enantioselectivity and activity in comparison with its corresponding homocombinations in many reactions. The examples described in this paper demonstrated the powerfulness of combinatorial approach for the discovery of novel chiral catalyst systems, particularly for the development of highly efficient, enantioselective, and practical catalysts for enantioselective reactions. We hope this concept will stimulate further work on the discovery of more highly efficient and enantioselective catalysts, as well as unexpected classes of catalysts or catalytic enantioselective reactions in the future with the help of a combinatorial chemistry approach.     

An integrated computational tool for the study of the optical properties of nanoscale devices: application to solar cells and molecular wires

We present a combined computational strategy for the study of the optical properties of nanoscale systems, using a combination of codes and techniques based on Density Functional Theory (DFT) and its Time Dependent extension (TDDFT). In particular, we describe the use of Car–Parrinello molecular dynamics simulations for the study of nanoscale devices and show the integration of the obtained results with available quantum chemistry codes for the calculation of TDDFT excitation energies, including solvation effects by continuum solvation models. We review some prototypical applications of this integrated computational strategy, ranging from the interaction of dye sensitizers with TiO₂ nanoparticles, of interest in the field of dye-sensitized solar cells, to transition metal molecular wires exceeding 3 nm length.     

In silico modeling and structural analysis of asparaginyl endopeptidase of schistosoma mansoni (Sm32): Immunological and drug target implications

Asparaginyl endopeptidase (AE) of Schistosoma mansoni (Sm32), also known as legumain, is a cysteine protease indirectly involved in the digestion of hemoglobin of Schistosoma sp. in the gastrodermis, being a vaccine candidate against this trematode and a potential drug target. This study presents a model for the three-dimensional structure of Sm32 determined by means of homology modeling and a molecular dynamics simulation with explicit solvent refinement. The structure proved to be consistent with other AEs of known crystal structures described in their proenzyme form, revealing a catalytic domain that has a caspase-like overall structure and a C-terminal prodomain that adopts a death-domain-like architecture. We identified amino acid mutations in the βIV strand, differences in the active site and in the surface electrostatic potentials between Sm32 and its homologous proteins of mouse and human. Additionally, amino acid changes in the activation peptide (AP) of the S. mansoni protein were determined. Our results strongly suggest that Sm32 can be exploited as a potential target for drug design and for the development of biomarkers used in diagnosis and in novel vaccines for the control of parasitic infection, opening the perspective of medicinal chemistry developments.     

Investigation of binding features: Effects on the interaction between CYP2A6 and inhibitors

A computational investigation has been carried out on CYP2A6 and its naphthalene inhibitors to explore the crucial molecular features contributing to binding specificity. The molecular bioactive orientations were obtained by docking (FlexX) these compounds into the active site of the enzyme. And the density functional theory method was further used to optimize the molecular structures with the subsequent analysis of molecular lipophilic potential (MLP) and molecular electrostatic potential (MEP). The minimal MLPs, minimal MEPs, and the band gap energies (the energy difference between the highest occupied molecular orbital and lowest unoccupied molecular orbital) showed high correlations with the inhibition activities (pIC₅₀s), illustrating their significant roles in driving the inhibitor to adopt an appropriate bioactive conformation oriented in the active site of CYP2A6 enzyme. The differences in MLPs, MEPs, and the orbital energies have been identified as key features in determining the binding specificity of this series of compounds to CYP2A6 and the consequent inhibitory effects. In addition, the combinational use of the docking, MLP and MEP analysis is also demonstrated as a good attempt to gain an insight into the interaction between CYP2A6 and its inhibitors. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010