新型光系统II抑制剂的设计、合成和生物活性测定

根据药效团模型，合理设计并合成了新型光系统II(PSII)抑制剂化合物，进行 了元素分析和红外、紫外及核磁数据表征。希尔反应测试表明，亿合成的化合物均 具有抑制光系统II电子传递功能的生物活性，有的化合物活性较高，为新型PSII除 草剂的开发显示了广阔的应用前景。     

新型光系统II抑制剂的设计、合成和生物活性测定

根据药效团模型,合理设计并合成了新型光系统II(PSII)抑制剂化合物,进行 了元素分析和红外、紫外及核磁数据表征。希尔反应测试表明,亿合成的化合物均 具有抑制光系统II电子传递功能的生物活性,有的化合物活性较高,为新型PSII除 草剂的开发显示了广阔的应用前景。     

ALS抑制剂合理分子设计的研究进展

以乙酰乳酸合成酶为靶标合理设计开发新型超高效除草剂是当前除草剂化学研究中的重要领域。结合本课题组的研究工作,从ALS抑制剂的结构特征、分子力学与量子化学研究、定量构效关系(QSAR)与三维定量构效关系(3D-QSAR)研究、非线性QSAR研究以及新型除草剂的分子设计等几个方面对该领域的研究现状进行了总结报道,并对该领域的发展前景及存在的问题进行了展望。     

药效团检索设计新的HIV-1蛋白酶抑制剂

通过对自建的未开发化合物三维结构库进行药效团检索,得到了4个对HIV-1蛋白酶抑制活化的化合物,通过构象分析发现包含药效团的构象处于优势构象,而且4个结构都含有带两个邻位羟基的苯环和一个间位羰基的药效团以及公共子结构。通过计算发现它们的疏水参数都很小。在考虑满足包含药效团的结构特征和有适中的疏水参数两个因素的前提下,设计出了新的具有潜在抑制HIV-1蛋白酶活性的化合物。它们的结构都比检索得到的四个化合物更为简单,因此易于合成。     

基于药效团模型设计合成新型ALS抑制剂

以ALS抑制剂药效团模型为基础建立了提问结构,将药效团模型中的生物结构信息输入到多种小分子三维结构数据库(NCI-3D和ACD-3D数据库)中,分别搜寻出100多个符合特征结构信息的全新结构候选化合物.以这些命中结构的分子特征信息为基础设计合成了一系列新型的ALS抑制剂,初步生物活性测试结果表明,预期有生物活性的化合物显示出一定的ALS酶抑制剂活性.     

拟除虫菊酯筛选及分子设计

综述了拟除虫菊酯的进展及新拟除虫菊酯的筛选和分子设计的方法等。参考文献５８篇。     

一些生物活性分子的合成进展

对一些生物活性分子的合成研究进展，如NADH（nicotinamide adenine dinucleotide hydrogen)模型、类胡萝卡素相关分子、卟啉衍生物的合成研究作 了简要的概述。     

机器学习设计新型有机分子研究进展

新型有机分子一直是有机化学领域的研究重点,其在开发高性能材料方面具有重要意义.传统的有机分子发现是一个类似于炒菜的试错过程,它耗时耗能且效率相对低下.常见的量子化学方法试图根据期望属性值筛选出合理的分子结构,以更好地指导实验,然而,由于计算资源相对于算法复杂度严重不足,精确给出实验指导在大多数情况下难以实现.近年来...     

虚拟活性化合物的自动生成

虚拟活性化合物的自动生成是从药效团和预先设定的结构碎片出发,通过碎片选择、碎片组装和柔性构象搜索来获得虚拟活性结构。经过对HIV-1蛋白酶抑制剂药效团进行虚拟活性化合物生成,得到了16个虚拟活性化合物,通过构象分析发现生成的化合物满足药效团的限制条件。说明这一方法能够有效的生成虚拟活性结构,与药效团检索结果对比发现生成的虚拟活性结构新颖易于合成。     

A fast method for large‐scale De Novo peptide and miniprotein structure prediction

Although peptides have many biological and biomedical implications, an accurate method predicting their equilibrium structural ensembles from amino acid sequences and suitable for large‐scale experiments is still missing. We introduce a new approach—PEP‐FOLD—to the de novo prediction of peptides and miniproteins. It first predicts, in the terms of a Hidden Markov Model‐derived structural alphabet, a limited number of local conformations at each position of the structure. It then performs their assembly using a greedy procedure driven by a coarse‐grained energy score. On a benchmark of 52 peptides with 9–23 amino acids, PEP‐FOLD generates lowest‐energy conformations within 2.8 and 2.3 Å Cα root‐mean‐square deviation from the full nuclear magnetic resonance structures (NMR) and the NMR rigid cores, respectively, outperforming previous approaches. For 13 miniproteins with 27–49 amino acids, PEP‐FOLD reaches an accuracy of 3.6 and 4.6 Å Cα root‐mean‐square deviation for the most‐native and lowest‐energy conformations, using the nonflexible regions identified by NMR. PEP‐FOLD simulations are fast—a few minutes only—opening therefore, the door to in silico large‐scale rational design of new bioactive peptides and miniproteins. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.     

Computational approaches to shed light on molecular mechanisms in biological processes

Computational approaches based on Molecular Dynamics simulations, Quantum Mechanical methods and 3D Quantitative Structure-Activity Relationships were employed by computational chemistry groups at the University of Milano-Bicocca to study biological processes at the molecular level. The paper reports the methodologies adopted and the results obtained on Aryl hydrocarbon Receptor and homologous PAS proteins mechanisms, the properties of prion protein peptides, the reaction pathway of hydrogenase and peroxidase enzymes and the defibrillogenic activity of tetracyclines.     

A novel method for enzyme design

Rational design of enzymes is a stringent test of our understanding of protein structure and function relationship, which also has numerous potential applications. We present a novel method for enzyme design that can find good candidate protein scaffolds in a protein-ligand database based on vector matching of key residues. Residues in the vicinity of the active site were also compared according to a similarity score between the scaffold protein and the target enzyme. Suitable scaffold proteins were selected, and the side chains of residues around the active sites were rebuilt using a previously developed side-chain packing program. Triose phosphate isomerase (TIM) was used as a validation test for enzyme design. Selected scaffold proteins were found to accommodate the enzyme active sites and successfully form a good transition state complex. This method overcomes the limitations of the current enzyme design methods that use limited number of protein scaffold and based on the position of ligands. As there are a large number of protein scaffolds available in the Protein Data Band, this method should be widely applicable for various types of enzyme design.     

In silico design novel (5-imidazol-2-yl-4-phenylpyrimidin-2-yl)[2-(2-pyridylamino)ethyl]amine derivatives as inhibitors for glycogen synthase kinase 3 based on 3D-QSAR,molecular docking and molecular dynamics simulation

Glycogen Synthase Kinase 3 (GSK-3) is a member of cellular kinase with various functions, such as glucose regulation, cellular differentiation, neuronal function and cell apoptosis. It has been proved as an important therapeutic target in type 2 diabetes mellitus and Alzheimer's disease. To better understand their structure–activity relationships and mechanism of action, an integrated computational study, including three dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, and molecular dynamics (MD), was performed on 79 (5-Imidazol-2-yl-4-phenylpyrimidin-2-yl)[2-(2-pyridylamino)ethyl]amine GSK-3 inhibitors. In this paper, we constructed 3D-QSAR using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) method. The results showed that the CoMFA model (q ² = 0.743, r² = 0.980) and the CoMSIA model (q² = 0.813, r² = 0.976) had stable and reliable predictive ability. The electrostatic and H-bond donor fields play important roles in the models. The contour maps of the model visually showed the relationship between the activity of compounds and their three-dimensional structure. Molecular docking was used to identify the key amino acid residues at the active site of GSK-3 and explore its binding mode with ligands. Based on 3D-QSAR models, contour maps and the binding feature between GSK-3 and inhibitor, we designed 10 novel compounds with good potential activity and ADME/T profile. Molecular dynamics simulation results validated that Ile62, Val70 and Lys85 located in the active site play a key role for GSK-3 complexed with inhibitors. These results might provide important information for designing GSK-3 inhibitors with high activity.     

A new system,tutors, for computer-aided molecular design

Computer-aided molecular design by TUTORS (TUTORial System) which is under development, is described. The system is based on two types of process, information reduction and information integration. TUTORS consists of two major subsystems, TUTORS-DB and TUTORS-SG, corresponding to these functions. TUTORS-DB involves management of chemical compound data, molecular modeling and data analysis for structure/activity problems. TUTORS-SG involves generation of candidate structures with the required activity by using the knowledge obtained from TUTORS-DB. The major functions of each subsystem and the approach for practical structure design are discussed.     

预测烷烃密度的新方法: 基团键贡献法

根据分子结构的特点,通过用染色矩阵和邻接矩阵对分子结构进行矩阵化表征,发展了一种根据分子结构信息烷烃密度的新方法---基团键贡献法。该方法有机地将基团贡献法和化学键贡献法结合在一起,既考虑了分子中基团的特性,又考虑了基团之间的连接性(化学键),具有基团贡献法和化学键贡献法的特点。对658种烷烃的计算结果表明,密度预测值十分接近实验值,平均误差0.245%,进一步外推对聚乙烯、聚丙烯和聚1-丁烯等聚合物的密度进行预测,也取得了令人满意的结果。     

A new method for determining molecular masses of polyheteroarylenes

It is shown that the nondestructive ablation of polyheteroarylenes induced by submillimeter radiation of a free electron laser may be used to determine the molecular masses of polymers. The experimental procedure is described, and its results are compared with GPC data.