树状大分子研究在超分子化学领域中的拓展

简要介绍近年来树状大分子研究在超分子化学领域中的拓展概况,总结当前在该研究领域中已经取得的一些令人激动的研究成果,从中了解树状大分子在新型超分子体系的构筑方面所具有的优势,探讨树状大分子未来在该领域中的研究和应用前景     

分子印迹技术在生物大分子分离识别中的应用

分子印迹技术是近些年发展起来的模拟抗体-抗原相互作用原理的新技术。该文介绍了分子印迹技术的产生和发展,重点介绍了生物大分子印迹聚合物的制备条件、聚合方法及其识别机理,并对该技术的应用前景及目前存在的问题进行了探讨。     

基于生物刺激源的响应性聚合物及其可控自组装

基于生物刺激源的响应性大分子自组装体系对智能聚合物领域的发展具有重要的意义。本文回顾并综述了近年来在该领域内针对生物大分子及各种小分子作为刺激源的大分子自组装体系及其研究现状。依据不同类型的刺激源进行分类,论述了近年来的研究进展,并合理展望了该领域未来的发展前景。     

生物分子的单分子检测研究

本文评述了生物单分子检测的方法及其在生物大分子结构与功能之间的关系、酶的活性、反应动力学、分子构象、DNA和RNA的转录、蛋白质折叠等生物学重要问题研究上的应用。对生物单分子检测技术这一研究领域的发展趋势作了展望。     

金属离子印迹技术研究进展

作为分子印迹技术的一个重要发展方向,金属离子印迹技术的发展对于环境、生命和材料科学等领域具有重要的学术和应用价值。与金属离子有关的印迹技术属于分子印迹技术中的前沿内容,其中有两方面尤其值得关注,一是以金属离子作为模板的离子印迹技术,另一是利用金属离子与生物分子的配位作用促进和实现生物大分子的分子印迹技术。本文对近年来国内外有关金属离子的分子印迹技术进展作了介绍和综述,并对该领域目前存在的问题进行了分析和展望。     

金属配位树状大分子的研究进展*

本文介绍了一类含有金属的高度支化的树状大分子,总结了在该领域中已取得的一些重要的成果,对树状大分子的制备、性质和应用做了扼要的介绍,探讨了此类大分子在该领域中的研究和应用前景。     

新型生物医用材料: 肽类树枝状大分子及其生物医学应用

肽类树枝状大分子是近年来发展起来的一类新型生物医用高分子材料, 它在具有普通树枝状大分子的特征如规整性、高度支化、表面呈现高密度功能团、尺度为纳米级、通过可控制备可得到单一分子量等之外, 同时还具有类似蛋白一样的球状结构、好的生物相容性、水溶性、耐蛋白酶水解、生物降解等独特的性能. 肽类树枝状大分子的上述特点, 使其在生物医学应用中显示出诱人的前景. 本综述从肽类树枝状大分子的制备出发、详尽介绍了肽类树枝状大分子的功能化及其在疾病诊断和治疗中的应用等方面的研究进展, 籍此推动肽类树枝状大分子在生物医学领域的研究与开发.     

生物大分子液-液相分离研究方法

生物大分子液-液相分离是一种普遍存在的生物物理现象,是近年来生命科学领域的新兴研究热点。生物大分子通过多价相互作用不断富集,当分子浓度达到溶液中的溶解阈值,就会以液-液相分离的形式从溶液中析出。这一现象与细胞内许多重要的生物学过程(如无膜细胞器的形成等)息息相关。随着相分离相关研究的不断深入,其研究方法也在不断发展与完善。本文从相分离的原理与特点出发,对目前常用的一些相分离研究方法进行了介绍,为后续相分离研究提供方法依据,促进相分离技术和方法的进一步发展。     

分子印迹聚合物研究:从小分子到生物大分子

分子印迹技术是一项制备功能聚合物材料的方法,其对印迹分子的专一性选择识别能力引起了人们的广泛关注。随着方法的基本确立和技术的逐渐成熟,其应用领域和范围不断扩大。本文在总结以往研究结果的基础上,对迄今为止进展相对缓慢的生物大分子印迹研究予以了特别关注,对相关的水环境下的分子识别问题进行了仔细的讨论,认真的分析了生物大分子印迹研究工作的难点和不利因素,对分子印迹技术的未来发展和应用前景进行了展望。     

原子间相互作用对无序大分子结构和动力学影响的中子散射研究

不同单体在原子尺度的相互作用使得不同大分子体系在微观、介观的多尺度复杂结构及动力学行为有明显差异,从而进一步影响了体系的宏观性质.联用中子散射和计算机模拟,利用相同分子量和分子量分布的氘代大分子与氢化大分子具有相同分子结构、不同中子衬度,以及中子散射和计算机模拟宽广的时间、空间观察尺度,我们可以得到无序大分子体系最可几全原子结构,进而分析其从原子到纳米的多尺度空间结构,与从皮秒到微秒的多模式动力学行为的成因.近年来,我们使用该方法,从小分子到大分子的稀溶液、溶胀体系,从大分子熔体到玻璃态,成功分析了原子间相互作用对不同空间尺度结构和跨时间运动模式动力学行为的影响.本文介绍了这些典型的例子,希望将该方法推广到更广阔的研究领域,把大分子原子结构的多样性与多尺度的复杂结构和动力学有机地联系起来.     

分子力场进展

分子力学（简称ＭＭ）是近年来化学家常用的一种计算方法。与量子力学从头计算和半经验方法相比，用分子力学处理大分子可以大大节省计算时间，而且，在大多数情况下，用分子力学方法计算得到的分子几何构型参数与实验值之间的差值可在实验误差范围之内。所以，分子力学是研究生物化学体系的有效和可行的手段。分子力学的核心是分子力场。本文介绍了分子力场的量子力学背景、分子力场和光谱力场之间的关系。分子力场的一般形式、分力     

Assessment and acceleration of binding energy calculations for protein–ligand complexes by the fragment molecular orbital method

In the field of drug discovery, it is important to accurately predict the binding affinities between target proteins and drug applicant molecules. Many of the computational methods available for evaluating binding affinities have adopted molecular mechanics‐based force fields, although they cannot fully describe protein–ligand interactions. A noteworthy computational method in development involves large‐scale electronic structure calculations. Fragment molecular orbital (FMO) method, which is one of such large‐scale calculation techniques, is applied in this study for calculating the binding energies between proteins and ligands. By testing the effects of specific FMO calculation conditions (including fragmentation size, basis sets, electron correlation, exchange‐correlation functionals, and solvation effects) on the binding energies of the FK506‐binding protein and 10 ligand complex molecule, we have found that the standard FMO calculation condition, FMO2‐MP2/6‐31G(d), is suitable for evaluating the protein–ligand interactions. The correlation coefficient between the binding energies calculated with this FMO calculation condition and experimental values is determined to be R = 0.77. Based on these results, we also propose a practical scheme for predicting binding affinities by combining the FMO method with the quantitative structure–activity relationship (QSAR) model. The results of this combined method can be directly compared with experimental binding affinities. The FMO and QSAR combined scheme shows a higher correlation with experimental data (R = 0.91). Furthermore, we propose an acceleration scheme for the binding energy calculations using a multilayer FMO method focusing on the protein–ligand interaction distance. Our acceleration scheme, which uses FMO2‐HF/STO‐3G:MP2/6‐31G(d) at R_int = 7.0 Å, reduces computational costs, while maintaining accuracy in the evaluation of binding energy. © 2015 Wiley Periodicals, Inc.     

Periodicity and map for discovery of new ionic liquids

1 Introduction In undertaking the researches on ionic liquids, we wished to establish periodicity and draw a “map” of ionic liquids for providing definite guidance to dis-cover, design, and choose the proper ionic liquids to meet the specific applicatio…     

A new hierarchical parallelization scheme: generalized distributed data interface (GDDI), and an application to the fragment molecular orbital method (FMO)

A two-level hierarchical scheme, generalized distributed data interface (GDDI), implemented into GAMESS is presented. Parallelization is accomplished first at the upper level by assigning computational tasks to groups. Then each group does parallelization at the lower level, by dividing its task into smaller work loads. The types of computations that can be used with this scheme are limited to those for which nearly independent tasks and subtasks can be assigned. Typical examples implemented, tested, and analyzed in this work are numeric derivatives and the fragment molecular orbital method (FMO) that is used to compute large molecules quantum mechanically by dividing them into fragments. Numeric derivatives can be used for algorithms based on them, such as geometry optimizations, saddle-point searches, frequency analyses, etc. This new hierarchical scheme is found to be a flexible tool easily utilizing network topology and delivering excellent performance even on slow networks. In one of the typical tests, on 16 nodes the scalability of GDDI is 1.7 times better than that of the standard parallelization scheme DDI and on 128 nodes GDDI is 93 times faster than DDI (on a multihub Fast Ethernet network). FMO delivered scalability of 80-90% on 128 nodes, depending on the molecular system (water clusters and a protein). A numerical gradient calculation for a water cluster achieved a scalability of 70% on 128 nodes. It is expected that GDDI will become a preferred tool on massively parallel computers for appropriate computational tasks.     

A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations

Molecular mechanics models have been applied extensively to study the dynamics of proteins and nucleic acids. Here we report the development of a third-generation point-charge all-atom force field for proteins. Following the earlier approach of Cornell et al., the charge set was obtained by fitting to the electrostatic potentials of dipeptides calculated using B3LYP/cc-pVTZ//HF/6-31G** quantum mechanical methods. The main-chain torsion parameters were obtained by fitting to the energy profiles of Ace-Ala-Nme and Ace-Gly-Nme di-peptides calculated using MP2/cc-pVTZ//HF/6-31G** quantum mechanical methods. All other parameters were taken from the existing AMBER data base. The major departure from previous force fields is that all quantum mechanical calculations were done in the condensed phase with continuum solvent models and an effective dielectric constant of epsilon = 4. We anticipate that this force field parameter set will address certain critical short comings of previous force fields in condensed-phase simulations of proteins. Initial tests on peptides demonstrated a high-degree of similarity between the calculated and the statistically measured Ramanchandran maps for both Ace-Gly-Nme and Ace-Ala-Nme di-peptides. Some highlights of our results include (1) well-preserved balance between the extended and helical region distributions, and (2) favorable type-II poly-proline helical region in agreement with recent experiments. Backward compatibility between the new and Cornell et al. charge sets, as judged by overall agreement between dipole moments, allows a smooth transition to the new force field in the area of ligand-binding calculations. Test simulations on a large set of proteins are also discussed.     

Downfalls of Chemical Probes Acting at the Kinase ATP-Site: CK2 as a Case Study

Protein kinases are a large class of enzymes with numerous biological roles and many have been implicated in a vast array of diseases, including cancer and the novel coronavirus infection COVID-19. Thus, the development of chemical probes to selectively target each kinase is of great interest. Inhibition of protein kinases with ATP-competitive inhibitors has historically been the most widely used method. However, due to the highly conserved structures of ATP-sites, the identification of truly selective chemical probes is challenging. In this review, we use the Ser/Thr kinase CK2 as an example to highlight the historical challenges in effective and selective chemical probe development, alongside recent advances in the field and alternative strategies aiming to overcome these problems. The methods utilised for CK2 can be applied to an array of protein kinases to aid in the discovery of chemical probes to further understand each kinase’s biology, with wide-reaching implications for drug development.     

Protein‐specific force field derived from the fragment molecular orbital method can improve protein–ligand binding interactions

Accurate computational estimate of the protein–ligand binding affinity is of central importance in rational drug design. To improve accuracy of the molecular mechanics (MM) force field (FF) for protein–ligand simulations, we use a protein‐specific FF derived by the fragment molecular orbital (FMO) method and by the restrained electrostatic potential (RESP) method. Applying this FMO‐RESP method to two proteins, dodecin, and lysozyme, we found that protein‐specific partial charges tend to differ more significantly from the standard AMBER charges for isolated charged atoms. We did not see the dependence of partial charges on the secondary structure. Computing the binding affinities of dodecin with five ligands by MM PBSA protocol with the FMO‐RESP charge set as well as with the standard AMBER charges, we found that the former gives better correlation with experimental affinities than the latter. While, for lysozyme with five ligands, both charge sets gave similar and relatively accurate estimates of binding affinities. © 2013 Wiley Periodicals, Inc.     

Generalized hybrid orbital for the treatment of boundary atoms in combined quantum mechanical and molecular mechanical calculations using the semiempirical parameterized model 3 method

The application of combined quantum mechanical (QM) and molecular mechanical methods to large molecular systems requires an adequate treatment of the boundary between the two approaches. In this article, we extend the generalized hybrid orbital (GHO) method to the semiempirical parameterized model 3 (PM3) Hamiltonian combined with the CHARMM force field. The GHO method makes use of four hybrid orbitals, one of which is included in the QM region in self-consistent field optimization and three are treated as auxiliary orbitals that do not participate in the QM optimization, but they provide an effective electric field for interactions. An important feature of the GHO method is that the semiempirical parameters for the boundary atom are transferable, and these parameters have been developed for a carbon boundary atom consistent with the PM3 model. The combined GHO-PM3/CHARMM model has been tested on molecular geometry and proton affinity for a series of organic compounds.Acknowledgement We thank the National Institutes of Health for support of this research.Contribution to the Jacopo Tomasi Honorary Issue     

分子筛限域金属纳米粒子及其氧化还原反应应用的研究进展

沸石分子筛是一类孔隙均匀、结晶度高、结构多样、比表面积大的材料,在催化、分离、吸附等方面得到了广泛的应用。沸石分子筛已被证明是金属纳米粒子(MNPs)的理想载体。金属纳米粒子@沸石分子筛催化剂不仅表现出优异的催化活性,而且具有较高的稳定性和择形催化性。此外,限域的金属纳米粒子与具有活性位点的纳米孔骨架的协同作用可以进一步提高复合催化剂的催化活性。金属纳米粒子@沸石分子筛催化剂由于具有较高的活性、择形性和热稳定性等优点,在工业相关应用中引起了人们的极大关注。本文综述了金属纳米粒子@沸石分子筛催化剂的研究进展,重点介绍了多种合成方法以及其在氢化和氧化反应中的应用进展。指出了金属纳米粒子@沸石分子筛催化剂领域存在的问题和挑战并对其未来发展进行展望。     

Robust Atomistic Modeling of Materials,Organometallic, and Biochemical Systems

Modern chemistry seems to be unlimited in molecular size and elemental composition. Metal-organic frameworks or biological macromolecules involve complex architectures and a large variety of elements. Yet, a general and broadly applicable theoretical method to describe the structures and interactions of molecules beyond the 1000-atom size regime semi-quantitatively is not self-evident. For this purpose, a generic force field named GFN-FF is presented, which is completely newly developed to enable fast structure optimizations and molecular-dynamics simulations for basically any chemical structure consisting of elements up to radon. The freely available computer program requires only starting coordinates and elemental composition as input from which, fully automatically, all potential-energy terms are constructed. GFN-FF outperforms other force fields in terms of generality and accuracy, approaching the performance of much more elaborate quantum-mechanical methods in many cases.