An ant colony optimization approach to flexible protein–ligand docking

The prediction of the complex structure of a small ligand with a protein, the so-called protein–ligand docking problem, is a central part of the rational drug design process. For this purpose, we introduce the docking algorithm PLANTS (Protein–Ligand ANT System), which is based on ant colony optimization, one of the most successful swarm intelligence techniques. We study the effectiveness of PLANTS for several parameter settings and present a direct comparison of PLANTS’s performance to a state-of-the-art program called GOLD, which is based on a genetic algorithm and frequently used in the pharmaceutical industry for this task. Last but not least, we also show that PLANTS can make effective use of protein flexibility giving example results on cross-docking and virtual screening experiments for protein kinase A. This article is based on a paper that won the best paper award at ANTS 2006, the 5th International Workshop on Ant Colony Optimization and Swarm Intelligence held in Brussels, Belgium, 2006. This article includes new types of experiments and also the possibility of considering flexibility of protein side-chains.     

Identification and Biochemical Studies on Novel Non-Nucleoside Inhibitors of the Enzyme Adenosine Kinase

The enzyme adenosine kinase (AK) plays a key role in the regulation of intracellular and extracellular concentration of adenosine (Ado), which exhibits potent hormonal activity in cardiovascular, nervous and immune systems. In view of the pharmacological effects of Ado, there is much interest in identifying inhibitors of AK, which can augment its tissue-protective effects. In this study, we have screened 1040 compounds from a chemical library of putative kinase inhibitors for their effect on purified human recombinant AK. These studies have identified 8 novel, non-nucleoside AK inhibitors. Four of these compounds (viz. 2-tert-butyl-4H-benzo[1,2,4]thiadiazine-3-thione (2759–0749); N-(5,6-diphenyl-furo[2,3-d]pyrimidin-4-yl)-propionamide (3998–0118); 3-[5,6-Bis-(4-methoxy-phenyl)-furo[2,3-d]pyrimidin-4-ylamino]-propan-1-ol (4072–2732); and 2-[2-(3,4-dihydroxy-phenyl)-5-phenyl-1H-imidazol-4-yl]-fluoren-9-one (8008–6198)), which inhibited human AK in a concentration-dependent manner in a low micromolar range (IC₅₀ = 0.38 ∼ 1.98 μM) were further studied. Kinetic and structural studies on these compounds provide evidence that inhibition of AK by these compounds was competitive with respect to Ado and non-competitive for ATP. All of these compounds also inhibited uptake of Ado and its metabolism in cultured mammalian cells at comparable concentrations indicating their efficient cellular penetrability. These AK inhibitors, whose chemical structures differ significantly from all previously known inhibitors, provide useful lead compounds for identification of more potent but less toxic AK inhibitors that may prove useful for therapeutic purposes.     

三角梅苞叶色彩参数和色素含量分析及蓝色转基因受体的筛选北大核心CSCD

三角梅作为重要的观赏植物颜色繁多,但缺乏稀有的蓝色。为筛选适合的蓝色转基因受体,明确不同品种三角梅苞片吸收利用DHM(二氢杨梅素)合成甜菜色素途径竞争产物(类黄酮色素)的潜在能力,该研究对红色、白色、黄色和紫色4大花色6个品种的三角梅苞片进行离体诱导培养,测定诱导培养后苞片色彩参数及色素含量变化,并进行相关性分析。结果显示:(1)三角梅苞片红绿色相值(a*)是决定苞片呈色的主要色彩参数,其色彩主要由甜菜色素和黄酮类色素决定,并以甜菜红素的影响最大。(2)除白色品种三角梅苞片中黄酮类色素含量大于甜菜色素含量外,其余品种苞片发育中甜菜色素含量均呈上升趋势,黄酮类色素呈下降趋势。(3)甜菜色苷含量与苞片a*值呈显著正相关关系,同时与苞片黄蓝色相值(b*)呈显著负相关关系;总黄酮含量与苞片b*值呈显著正相关关系,与苞片a*值呈极显著负相关关系。(4)经DHM体外诱导培养后,苞片总黄酮含量及占比在4个品种三角梅(‘新加坡大白’、‘宝老橙’、‘中国丽人’、‘黄蝶’)中明显升高,但各品种苞片总甜菜色素含量及占比均下降,并以‘新加坡大白’苞片中总黄酮含量上升幅度最大(65.77%),含量占比变化(增加26.91%)也为6个品种中最大。(5)灰色关联度综合分析显示,白色品种‘新加坡大白’与灰色关联度分析拟定的参考品种关联度最高(0.7444),表明三角梅品种中‘新加坡大白’可考虑作为蓝色转基因三角梅的受体品种。     

皮肤类器官的构建、功能及其应用研究进展

皮肤类器官作为一种新型的类器官模型,不仅能高度模拟皮肤组织的生理结构和功能,更好地在不同体外环境下还原较真实的皮肤生态,还可以应用于皮肤发育研究、皮肤疾病病理研究及药物筛选等领域。在干细胞研究中,皮肤类器官模型可以在特殊的生境下对具有特定功能的皮肤细胞及其附属物进行重建和改造,以弥补现有体外皮肤模型在结构、功能等方面的不足。基于此,皮肤类器官将会在皮肤再生、组织修复、药物筛选及医学美容等方面扮演越来越重要的角色。本文详述了皮肤类器官构建中所参与的细胞来源及近年来的应用,并对未来皮肤类器官的发展与优化做出了展望。     

油葵苗期抗旱相关性状的QTL定位及候选基因筛选

干旱是限制向日葵生长发育的重要因素之一。为探究向日葵苗期抗旱性分子机制,该研究以向日葵K55与K58杂交构建的150个F₇重组自交系群体为材料,对其在正常浇水和干旱胁迫两种水分处理条件下的叶片相对电导率、叶绿素含量、叶面积、叶片相对含水量、根长进行表型测定,利用前期建立的SNP、SSR分子标记遗传连锁图谱,通过复合区间作图法对5个抗旱相关的性状进行QTL定位。结果表明：(1)共定位到向日葵QTL位点11个,其中正常浇水条件下5个,干旱胁迫条件下6个,表型贡献率为0.768%~7.547%,且5号连锁群上定位到的QTL位点最多(3个)。(2)QTL置信区间内共筛选到62个与干旱相关的候选基因,包括位于qLA 8 1上的rna23019、rna23004、rna22661、rna22193、rna23294、rna22783和位于qCC 13 1上的rna40140,这些基因可作为后续基因克隆及功能研究的重点候选基因。该研究结果为向日葵抗旱性研究及其遗传改良奠定了基础。     

病毒功能性受体的筛选新策略及其应用

病毒通过与靶细胞表面的特异性受体结合,进而吸附、入侵靶细胞,劫持细胞的复制机器完成自身的复制周期。细胞受体作为病毒入侵宿主的门户,细胞受体的结构与功能及其介导病毒入侵的机制一直是病毒学研究的热点之一。对细胞受体的研究有助于了解病毒的致病机制并为病毒性疾病的防控提供科学依据。近年来,利用功能缺失性基因组学筛选病毒功能性受体的进展极大地拓展了人类对病毒入侵机制的认识和理解。目前,应用较为广泛的病毒功能性受体筛选策略包括RNA干扰技术、利用单倍体细胞系随机插入逆转录病毒致突变技术以及基于CRISPR/Cas9系统的新型编辑技术。本文系统介绍并比较了这三种病毒功能性受体筛选新策略,同时对其应用及优缺点进行了归纳总结,可为相关研究者提供一定的参考。     

Cover Image,Volume 116, Number 2, February 2019

A key point of protein stability engineering is to identify specific target residues whose mutations can stabilize the protein structure without negatively affecting the function or activity of the protein. Here, we propose a method called RiSLnet (Rapid i dentification of Smart mutant Library using residue network) to identify such residues by combining network analysis for protein residue interactions, identification of conserved residues, and evaluation of relative solvent accessibility. To validate its performance, the method was applied to four proteins, that is, T4 lysozyme, ribonuclease H, barnase, and cold shock protein B. Our method predicted beneficial mutations in thermal stability with ~62% average accuracy when the thermal stability of the mutants was compared with the ones in the Protherm database. It was further applied to lysine decarboxylase (CadA) to experimentally confirm its accuracy and effectiveness. RiSLnet identified mutations increasing the thermal stability of CadA with the accuracy of ~60% and significantly reduced the number of candidate residues (~99%) for mutation. Finally, combinatorial mutations designed by RiSLnet and in silico saturation mutagenesis yielded a thermally stable triple mutant with the half-life (T _1/2) of 114.9 min at 58°C, which is approximately twofold higher than that of the wild-type.     

Expansion of the scaffold diversity for the development of highly selective butyrylcholinesterase (BChE) inhibitors: Discovery of new hits through the pharmacophore model generation,virtual screening and molecular dynamics simulation

Butyrylcholinesterase (BChE) is recently considered as a new target for the treatment of Alzheimer’s disease (AD). There is an increasing interest in the development of BChE inhibitors. In the present study, a set of pharmacophore models for BChE was developed and validated. Based on the models, virtual screening was performed on five compound collections, from which seventeen potential hits were retained for biological investigation. In total, eight of these seventeen potential hits showed selective BChE inhibitory activity. Moreover, four compounds displayed IC₅₀ values in sub-micromolar range on eqBChE and three displayed IC₅₀ values < 2 μM on huBChE. The diverse scaffolds of the active compounds provided good starting point further development of selective BChE inhibitors. As far as we concerned, here we disclose the first selective pharmacophore model targeting BChE. The high rate of the model in the identification of active hits indicates it is a valuable tool for the development of selective BChE inhibitors, which may benefit the treatment of AD.     

Combinatorial peptide library screening for discovery of diverse α-glucosidase inhibitors using molecular dynamics simulations and binary QSAR models

Human α-glucosidase is an enzyme involved in the catalytic cleavage of the glucoside bond and involved in numerous functionalities of the organism, as well as in the insurgence of diabetes mellitus 2 and obesity. Thus, developing chemicals that inhibit this enzyme is a promising approach for the treatment of several pathologies. Small peptides such as di- and tri-peptides may be in natural organism as well as in the GI tract in high concentration, coming from the digestive process of meat, wheat and milk proteins. In this work, we reported the first tentative hierarchical structure-based virtual screening of peptides for human α-glucosidase. The goal of this work is to discover novel and diverse lead compounds that my act as inhibitors of α-glucosidase such as small peptides by performing a computer aided virtual screening and to find novel scaffolds for further development. Thus, in order to select novel candidates with original structure we performed molecular dynamics (MD) simulations among the 12 top-ranked peptides taking as comparison the MD simulations performed on crystallographic inhibitor acarbose. The compounds with the lower RMSD variability during the MD, were reserved for in vitro biological assay. The selected 4 promising structures were prepared on solid phase peptide synthesis and used for the inhibitory assay, among them compound 2 showed good inhibitory activity, which validated our method as an original strategy to discover novel peptide inhibitors. Moreover, pharmacokinetic profile predictions of these 4 peptides were also carried out with binary QSAR models using MetaCore/MetaDrug applications.