Polymers of intrinsic microporosity for gas permeation: a molecular simulation study

We report a molecular simulation study for gas permeation in two membranes constructed from polymers of intrinsic microporosity (PIM-1 and PIM-7). With rigid ladder polymer chains, the membranes posses approximately 47.7 and 46.6% fractional free volumes (FFVs) in PIM-1 and PIM-7, respectively. The voids in the membranes have a diameter up to 9 Å and are largely interconnected. The sorption and diffusion of four gases (H₂, O₂, CH₄ and CO₂) were calculated by Monte Carlo and molecular dynamics simulations. The solubility coefficients increase in the order of H₂ < O₂ < CH₄ < CO₂, while the diffusion coefficients increase in the following order: CH₄ < CO₂ < O₂ < H₂. The simulation results agree well with experimental data, particularly for the solubility coefficients. The solubility and diffusion coefficients correlate well separately with the critical temperatures and effective diameters of gases. These molecular-based correlations can be used in the prediction for other gases. As attributed to the microporous structure, PIM-1 and PIM-7 outperform most glassy polymeric membranes in sorption and diffusion. PIM-1 has larger solubility and diffusion coefficients than PIM-7 because the cyano groups in PIM-1 lead to a stronger affinity and a larger FFV. The simulated solubility, diffusivity and permeation selectivities of CO₂/H₂, CO₂/O₂ and CO₂/CH₄ are consistent with experimental data. The quantitative microscopic understanding of gas permeation in the PIM membranes is useful for the new development of high-performance membranes.     

Molecular design of Stat3‐derived peptide selectivity between BET proteins Brd2 and Brd4 in ovarian cancer

Stat3 signaling has been recognized as a potential therapeutic target of human ovarian cancer. The signaling is transducted through the peptide‐medicated interaction of Stat3 with BET family members Brd2 and Brd4 –– 2 highly homologous proteins involved in differential downstream pathways. Here, we reported a successful design of peptide selectivity between the Brd2 and Brd4. The design resulted in 3 linear peptides SMSLQCX YLGVA, QSKVLTX SYWGA, and RQCNLGX LYMNY with high or moderate selectivity for Brd2 over Brd4 (S = 3.3‐fold, 6.8‐fold, and 4.2‐fold, respectively) as compared with the native Stat3 peptide ²⁸¹HNLLRIX QFLQS²⁹² (S = 2.5‐fold). Structural analysis revealed that peptide N‐terminus and hydrogen bonds play important roles in the peptide interaction stability and specificity with Brd2 and Brd4. This study would help to establish an integrated in silico‐in vitro method for rational molecular design of peptide ligand selectivity between homologous protein receptors.     

Domain-selective targeting of BET proteins in cancer and immunological diseases

Cancer and inflammation are strongly interconnected processes. Chronic inflammatory pathologies can be at the heart of tumor development; similarly, tumor-elicited inflammation is a consequence of many cancers. The mechanistic interdependence between cancer and inflammatory pathologies points toward common protein effectors which represent potential shared targets for pharmacological intervention. Epigenetic mechanisms often drive resistance to cancer therapy and immunomodulatory strategies. The bromodomain and extraterminal domain (BET) proteins are epigenetic adapters which play a major role in controlling cell proliferation and the production of inflammatory mediators. A plethora of small molecules aimed at inhibiting BET protein function to treat cancer and inflammatory diseases have populated academic and industry efforts in the last 10 years. In this review, we will discuss recent pharmacological approaches aimed at targeting a single or a subset of the eight bromodomains within the BET family which have the potential to tease apart clinical efficacy and safety signals of BET inhibitors.     

Computational structure characterisation tools in application to ordered and disordered porous materials

In this article, we present a set of computational tools for systematic characterisation of ordered and disordered porous materials. These tools include calculation of the accessible surface area and geometric pore size distribution, analysis of the structure connectivity and percolation analysis of the porous space. We briefly discuss the algorithms behind these calculations. To demonstrate the capabilities of the tools and the type of insights that can be gained from their application, we consider a series of case studies. These case studies include small molecular fragments, several crystalline metal-organic materials, and variants of these materials with induced defects and disorder in their structure. The simulation package is available upon request.     

Comparison of force fields for Alzheimer's A : A case study for intrinsically disordered proteins

Intrinsically disordered proteins are essential for biological processes such as cell signalling, but are also associated to devastating diseases including Alzheimer's disease, Parkinson's disease or type II diabetes. Because of their lack of a stable three‐dimensional structure, molecular dynamics simulations are often used to obtain atomistic details that cannot be observed experimentally. The applicability of molecular dynamics simulations depends on the accuracy of the force field chosen to represent the underlying free energy surface of the system. Here, we use replica exchange molecular dynamics simulations to test five modern force fields, OPLS, AMBER99SB, AMBER99SB*ILDN, AMBER99SBILDN‐NMR and CHARMM22*, in their ability to model Aβ₄₂, an intrinsically disordered peptide associated with Alzheimer's disease, and compare our results to nuclear magnetic resonance (NMR) experimental data. We observe that all force fields except AMBER99SBILDN‐NMR successfully reproduce local NMR observables, with CHARMM22* being slightly better than the other force fields.     

Comparison of multiple Amber force fields and development of improved protein backbone parameters

The ff94 force field that is commonly associated with the Amber simulation package is one of the most widely used parameter sets for biomolecular simulation. After a decade of extensive use and testing, limitations in this force field, such as over-stabilization of alpha-helices, were reported by us and other researchers. This led to a number of attempts to improve these parameters, resulting in a variety of "Amber" force fields and significant difficulty in determining which should be used for a particular application. We show that several of these continue to suffer from inadequate balance between different secondary structure elements. In addition, the approach used in most of these studies neglected to account for the existence in Amber of two sets of backbone phi/psi dihedral terms. This led to parameter sets that provide unreasonable conformational preferences for glycine. We report here an effort to improve the phi/psi dihedral terms in the ff99 energy function. Dihedral term parameters are based on fitting the energies of multiple conformations of glycine and alanine tetrapeptides from high level ab initio quantum mechanical calculations. The new parameters for backbone dihedrals replace those in the existing ff99 force field. This parameter set, which we denote ff99SB, achieves a better balance of secondary structure elements as judged by improved distribution of backbone dihedrals for glycine and alanine with respect to PDB survey data. It also accomplishes improved agreement with published experimental data for conformational preferences of short alanine peptides and better accord with experimental NMR relaxation data of test protein systems.     

Physical scoring function based on AMBER force field and Poisson-Boltzmann implicit solvent for protein structure prediction

A well-behaved physics-based all-atom scoring function for protein structure prediction is analyzed with several widely used all-atom decoy sets. The scoring function, termed AMBER/Poisson-Boltzmann (PB), is based on a refined AMBER force field for intramolecular interactions and an efficient PB model for solvation interactions. Testing on the chosen decoy sets shows that the scoring function, which is designed to consider detailed chemical environments, is able to consistently discriminate all 62 native crystal structures after considering the heteroatom groups, disulfide bonds, and crystal packing effects that are not included in the decoy structures. When NMR structures are considered in the testing, the scoring function is able to discriminate 8 out of 10 targets. In the more challenging test of selecting near-native structures, the scoring function also performs very well: for the majority of the targets studied, the scoring function is able to select decoys that are close to the corresponding native structures as evaluated by ranking numbers and backbone Calpha root mean square deviations. Various important components of the scoring function are also studied to understand their discriminative contributions toward the rankings of native and near-native structures. It is found that neither the nonpolar solvation energy as modeled by the surface area model nor a higher protein dielectric constant improves its discriminative power. The terms remaining to be improved are related to 1-4 interactions. The most troublesome term is found to be the large and highly fluctuating 1-4 electrostatics term, not the dihedral-angle term. These data support ongoing efforts in the community to develop protein structure prediction methods with physics-based potentials that are competitive with knowledge-based potentials.     

Lead optimization and efficacy evaluation of quinazoline-based BET family inhibitors for potential treatment of cancer and inflammatory diseases

Extensive optimization of quinazoline-based lead 8 is described. The structure-activity relationship studies indicate the S-configuration is preferred for the phenylmorpholine substitution. Together with incorporation of a (2-hydroxyl-2-methylpropyl)pyrazole moiety at the 2-position leads to analogs with comparable potency and marked improvement in the pharmacokinetic profile over our previously reported lead compounds. Further in vivo efficacy studies in Kasumi-1 xenograft mouse model demonstrates that the selected inhibitors are well tolerated and highly efficacious in the inhibition of tumor growth. Additionally, the representative analog 19 also demonstrated significant improvement of arthritis severity in a collagen-induced arthritis (CIA) mouse model. These results indicate potential use of these quinazoline-based BET inhibitors for treatment of cancer and inflammatory diseases. A brief discussion of the co-crystallized structure of 19 with BRD4 (BD1) is also highlighted.     

Structure of palmitoylated BET3: insights into TRAPP complex assembly and membrane localization

BET3 is a component of TRAPP, a complex involved in the tethering of transport vesicles to the cis-Golgi membrane. The crystal structure of human BET3 has been determined to 1.55-A resolution. BET3 adopts an alpha/beta-plait fold and forms dimers in the crystal and in solution, which predetermines the architecture of TRAPP where subunits are present in equimolar stoichiometry. A hydrophobic pocket within BET3 buries a palmitate bound through a thioester linkage to cysteine 68. BET3 and yeast Bet3p are palmitoylated in recombinant yeast cells, the mutant proteins BET3 C68S and Bet3p C80S remain unmodified. Both BET3 and BET3 C68S are found in membrane and cytosolic fractions of these cells; in membrane extractions, they behave like tightly membrane-associated proteins. In a deletion strain, both Bet3p and Bet3p C80S rescue cell viability. Thus, palmitoylation is neither required for viability nor sufficient for membrane association of BET3, which may depend on protein-protein contacts within TRAPP or additional, yet unidentified modifications of BET3. A conformational change may facilitate palmitoyl extrusion from BET3 and allow the fatty acid chain to engage in intermolecular hydrophobic interactions.     

Adsorption behaviors of hydrogen sulphide on Au(110) nanoslit array surfaces using molecular dynamics simulations

The adsorption behaviour of gas molecules on detector surfaces has a profound influence on the sensitivity of the detector. For this reason, this study used molecular dynamics simulation to explore the dynamic adsorption behaviour of hydrogen sulphide (H₂S) molecules on various types of Au surfaces, including a planar Au(1?1?0) structure and three types of slit array structures. The influence of system temperature, adsorbate concentration and the slit width of nanoarrays on diffusivity, average adsorption energy and static adsorption amount were systematically examined. Simulation results indicate that the self-diffusivity of the adsorbate molecules increases with temperature but decreases with adsorbate concentration. At low concentrations (~3 mol/L), each type of Au(1?1?0) surface structure shows good capacity to adsorb all H₂S molecules. With increasing concentration at 6.5 mol/L, the high concentration leads to adsorption saturation and many free H₂S molecules in the planar Au(1?1?0) structure. Moreover, desorption also begins to appear on the planar structures at a temperature of 300 K (at 6.5 mol/L). The simulation results indicate that the columnar array structures with a slit width ≥5.76 Å allow molecules to swiftly spread into the slits and provide more stable adsorption sites (i.e. with a higher adsorption energy), which can effectively address the issues of high-temperature desorption and adsorption saturation. Particularly at low temperatures (≤100 K), slit structures presented a level of static adsorption of H₂S that was 30% to 35 higher than that of planar structures.     

BET抑制剂JQ1通过调控GSK3对结肠癌细胞HCT116增殖及凋亡的影响

摘要 目的：探讨BET抑制剂JQ1通过调控GSK3对结肠癌细胞HCT116增殖及凋亡的影响。方法：将HCT116细胞进行培养,按处理方式的不同分为对照组（NC组）、给药组（JQ1组）、给药+沉默组（JQ1+siRNA-GSK3组）与给药+过表达组（JQ1+OE-GSK3组）。分别通过细胞增殖-毒性检测（CCK-8）实验检测细胞增殖情况;原位末端标记（TUNEL）染色观察细胞凋亡水平;流式细胞术检测细胞凋亡数量;逆转录-聚合酶链反应（RT-PCR）检测相关mRNA含量水平表达变化;蛋白质印迹法（Western Blot）检测增殖与凋亡相关蛋白表达情况。结果：与NC组表现出的高增殖活性相比,给予JQ1后能够明显抑制HCT116细胞的增殖活性（P<0.05）;与JQ1组相比,沉默GSK3后其增殖活性则进一步下降,过表达GSK3后其增殖活性明显上升（P<0.05）。TUNEL染色结果显示,对NC组相比,JQ1组及JQ1+siRNA-GSK3组细胞凋亡水平显著上升;与JQ1组相比,过表达GSK3后其凋亡水平明显降低（P<0.05）。流式细胞术结果显示,NC组细胞凋亡数量最少,而给予JQ1后凋亡细胞数量显著增加,同时沉默GSK3后其细胞凋亡数量进一步上升,过表达GSK3后细胞凋亡数量明显下降（P<0.05）。Western Blot与RT-PCR显示;与NC组相比,给予JQ1及siRNA-GSK3处理后Caspase-3及BAX表达显著增加,GSK3与PCNA表达显著降低（P<0.05）;与JQ1组相比,过表达GSK3后Caspase-3及BAX表达明显降低,GSK3与PCNA表达明显上调（P<0.05）。结论：JQ1能够抑制HCT116细胞的增殖水平并促进其凋亡,从而发挥抗肿瘤作用,这一过程可能与JQ1能够抑制GSK3的表达有关。     

Modeling the interaction between anti-cancer drug penicillamine and pristine and functionalized carbon nanotubes for medical applications: density functional theory investigation and a molecular dynamics simulation

Abstract

The present study focuses on the prediction and investigation of binding properties of penicillamine with pure (5,5) single-walled carbon nanotube (SWCNT) and functionalized SWCNT (f-SWCNT) through the B3LYP and M06-2X functionals using the 6-31G** basis set. The electronic and structural properties, adsorption energy and frontier molecular orbitals of various configurations are examined. Our theoretical results indicated that the interaction of the nanotubes with penicillamine molecule is weak so that the drug adsorption process is typically physisorption. Also, results of theoretical calculations show that the adsorption of the drug molecule on f-SWCNT is stronger with shorter intermolecular distances in comparison to pure SWCNT. The natural bond orbital (NBO) analysis of studied systems demonstrates that the charge is transferred from penicillamine molecule to the nanotubes. Furthermore, molecular dynamics (MD) simulation is employed to evaluate the dynamic and diffusion behavior of drug molecule on SWCNT and f-SWCNT. Energy results show that drug molecule spontaneously moves toward the carriers, and the van der Waals energy contributions in drug adsorption are more than electrostatic interaction. The obtained results from MD simulation confirm that the functionalization of SWCNT leads to increase in the solubility of the carrier in aqueous solution.

Communicated by Ramaswamy H. Sarma     

分子生物学与进化的新理论

论述了由于分子生物学取得的成就,而形成的生物进化的新理论,并阐述了若干新理论指导生产实践取得的巨大应用成果。     

Surface imprinting polymers for the recognition of nucleotides

A highly selective polymer has been prepared for the selective separation of nucleotides by the surface imprinting polymerization. A dialkyl quaternary ammonium chloride was effective as the functional molecule for recognizing the difference in the structure of nucleotides. Adsorptive behavior of the ionic species of the structural analogues, inosine-5'-monophosphoric acid (IMP) and guanosine-5'-monophosphoric acid (GMP), could be controlled by changing the pH condition. Surface imprinting polymers were prepared under different pH conditions; pH 9.0 and pH 8.5. The IMP-imprinted polymers exhibited higher template effect for IMP than for a structural analogue, GMP. A reference polymer prepared without the imprint molecule neither exhibit any selectivity to IMP nor to GMP. The adsorption behavior was quantitatively evaluated by the binding constants for the IMP-imprinted polymer. The imprinting polymer was found to recognize a small structural difference in nucleotides.     

Molecular simulation for separation of ethylene and ethane by functionalised graphene membrane

ABSTRACT

Graphene is an excellent adsorbent and a membrane material for separation which has attracted wide attention in recent years. Moreover, compared with typical polymer materials, porous graphene has exhibited superior performance. In this paper, molecular dynamics and quantum mechanics were used to explore the appropriate pore size and separation mechanism of graphene. The 2N-Pore-13 (modified by N and H atom) membrane can prevent the penetration of ethane while maintaining high ethylene flux. The permeation rate of ethylene reached 3.7×10⁶ GPU in 5N-Pore-13 membrane, while the one of ethane was only 227 GPU. The mechanism is based on the fact that molecular structure of ethylene is two-dimensional, so that ethylene can get closer to membrane surface when it is adsorbed. When passing through the pores, ethylene has lower enthalpy and entropy barrier.     

A brief review of coarse-grained and other computational studies of molecularly imprinted polymers

Molecular imprinting is an established method for the creation of artificial recognition sites in synthetic materials through polymerization and cross-linking in the presence of template molecules. Removal of the templates leaves cavities that are complementary to the template molecules in size, shape, and functionality. In recent years, various theoretical and computational models have been developed as tools to aid in the design of molecularly imprinted polymers (MIPs) or to provide insight into the features that determine MIP performance. These studies can be grouped into two general approaches-screening for possible functional monomers for particular templates and macromolecular models focusing on the structural characterization of the imprinted material. In this review, we pay special attention to coarse-grained models that characterize the functional heterogeneity in imprinted pores, but also cover recent advances in atomistic and first principle studies. We offer a critical assessment of the potential impact of the various models towards improving the state-of-the-art of molecular imprinting.     

Co-targeting BET bromodomain BRD4 and RAC1 suppresses growth,stemness and tumorigenesis by disrupting the c-MYC-G9a-FTH1axis and downregulating HDAC1 in molecular subtypes of breast cancer

BET bromodomain BRD4 and RAC1 oncogenes are considered important therapeutic targets for cancer and play key roles in tumorigenesis, survival and metastasis. However, combined inhibition of BRD4-RAC1 signaling pathways in different molecular subtypes of breast cancer including luminal-A, HER-2 positive and triple-negative breast (TNBC) largely remains unknown. Here, we demonstrated a new co-targeting strategy by combined inhibition of BRD4-RAC1 oncogenic signaling in different molecular subtypes of breast cancer in a context-dependent manner. We show that combined treatment of JQ1 (inhibitor of BRD4) and NSC23766 (inhibitor of RAC1) suppresses cell growth, clonogenic potential, cell migration and mammary stem cells expansion and induces autophagy and cellular senescence in molecular subtypes of breast cancer cells. Mechanistically, JQ1/NSC23766 combined treatment disrupts MYC/G9a axis and subsequently enhances FTH1 to exert antitumor effects. Furthermore, combined treatment targets HDAC1/Ac-H3K9 axis, thus suggesting a role of this combination in histone modification and chromatin modeling. C-MYC depletion and co-treatment with vitamin-C sensitizes different molecular subtypes of breast cancer cells to JQ1/NSC23766 combination and further reduces cell growth, cell migration and mammosphere formation. Importantly, co-targeting RAC1-BRD4 suppresses breast tumor growth in vivo using xenograft mouse model. Clinically, RAC1 and BRD4 expression positively correlates in breast cancer patient''s samples and show high expression patterns across different molecular subtypes of breast cancer. Both RAC1 and BRD4 proteins predict poor survival in breast cancer patients. Taken together, our results suggest that combined inhibition of BRD4-RAC1 pathways represents a novel and potential therapeutic approach in different molecular subtypes of breast cancer and highlights the importance of co-targeting RAC1-BRD4 signaling in breast tumorigenesis via disruption of C-MYC/G9a/FTH1 axis and down regulation of HDAC1.