NDM-1型金属-β-内酰胺酶及其抑制剂研究进展

金属β-内酰胺酶(MBLs)尤其是NDM-1型金属酶介导的细菌耐药性在全球范围内不断扩散,给人类健康带来日益严重的威胁。虽然使用抑制剂阻止酶的水解作用是临床上应对产β-内酰胺酶耐药菌的重要手段,并已成功上市了奥格门汀等药物,但临床所用抑制剂仅对丝氨酸β-内酰胺酶有效,对MBLs尤其是NDM-1没有效果。本综述概述了近年来NDM-1抑制剂的研究进展,介绍了MBLs抑制剂筛选新方法,以期为研究者们提供新的思路,更有效地设计或筛选出活性较好的MBLs抑制剂。     

超级细菌NDM-1及其抑制剂的研究进展

细菌中抗生素耐药性的迅速发展威胁着将人类带回到"后抗生素时代"。新德里金属β-内酰胺酶(NDM-1)几乎可以水解所有的β-内酰胺抗生素,包括碳青霉烯。携带blaNDM-1基因的细菌被称为超级细菌,至今临床上仍缺乏针对NDM-1的抑制剂。新型NDM-1抑制剂的研发是一个具有挑战性但值得深入研究的领域。本文对NDM-1及其抑制剂研究进展进行阐述,为后续研发提供借鉴。     

基于虚拟筛选和分子动力学模拟的PD-1/PD-L1小分子抑制剂的发现

目的 发现具有新型结构的PD-1/PD-L1小分子抑制剂，并测试其对PD-1/PD-L1蛋白的阻断活性，为后续相关研究提供参考。方法 利用AutoDock Vina对TCM和TargetMol两种天然产物分子库进行虚拟筛选，获得打分较高的分子，采用HTRF方法测试所得化合物的体外抑制活性，并通过分子动力学模拟对其稳定性和结合模式进行分析。结果与结论最终确定了一种能够与PD-L1相互作用的新型化合物754792,并证明其可以有效阻断PD-1/PD-L1与配体的结合。该研究为开发免疫检查点抑制剂提供了重要的理论依据，为进一步开发高效的PD-1/PD-L1小分子抑制剂奠定了基础。     

基于中草药数据库的法尼酯受体抑制剂的计算机虚拟筛选

目的:用现代化学信息学手段和中草药化学数据库寻找中草药中法尼酯受体(FXR)的抑制剂。方法:采用Accelrys公司Cerius2分子模拟软件包(版本4.10)对蛋白质晶体结构数据库PDB中FXR-fexaramine复合物(PDB代码:1OSH)三维结构活性部位进行分析,通过配体对接模块进行分子对接。结果:以原配体fexaramine的打分函数为阈值,筛选出中草药化学数据库中10个与FXR结合较好的的化学成分。结论:本研究结果可促进新型降脂药物的研制,并有助于揭示药物分子与FXR的作用机制。     

Survivin小分子抑制剂的计算机虚拟筛选及初步活性研究

目的通过计算机虚拟筛选,寻找生存素(survivin)的小分子抑制剂,并对其活性进行初步研究。方法基于sur-vivin与其抑制性配体Smac/Diablo复合物的三维结构,用分子对接的方法对含有149,214个小分子的三维结构数据库进行筛选。通过初步活性测定确定活性较高的化合物,进一步研究其对凋亡,细胞周期及活性氧产生的影响。利用分子图像学方法分析化合物与survivin之间的作用模式。结果通过能量打分并根据结构多样性和类药性原则,最终选择了35个化合物进行初步活性测定,其中有9个化合物显示出明显的抑制活性,3个化合物的半数抑制浓度在30μmol.L-1以下。选择其中活性最高的化合物1-19进行进一步研究,结果显示小剂量的1-19能够促进细胞的早期凋亡,诱导细胞内活性氧产生,导致细胞发生S和G2/M期阻滞。分子图像学分析显示活性最高的1-19能够与survivin配体结合区的71位天门冬氨酸形成两个稳定的氢键。结论通过计算机辅助药物设计、药理活性测试以及分子图像学分析,初步确定了一个针对survivin的全新的先导化合物,为今后survivin小分子抑制剂的研究奠定了基础。     

天然产物中细菌群体感应抑制剂虚拟筛选研究进展

群体感应现象是近年来微生物学领域研究的热点。随着对群体感应研究的不断深入,各种群体感应抑制剂相继涌现。虚拟筛选是基于小分子数据库开展的活性化合物筛选手段,是寻找先导化合物、发现药物构效关系、优化药物设计、发现药物作用靶标的有效方法。虚拟筛选具有成本低、效率高的优点,将该技术应用于筛选群体感应抑制剂研究具有良好的应用前景。本文主要依据细菌群体感应信号分子的种类,综述目前应用虚拟筛选技术筛查天然产物来源群体感应抑制剂的研究现状。     

聚腺苷二磷酸核糖聚合酶-1抑制剂高通量筛选模型

目的建立体外聚腺苷二磷酸核糖聚合酶-1[Poly(ADP-ribose)polymerase-1,PARP-1]抑制剂的高通量筛选模型,筛选潜在的PARP-1抑制剂。方法将PARP-1、裸DNA与底物NAD+反应,再将剩余底物NAD+转化为荧光物质,通过测定其荧光强度来决定PARP-1的活性,并以此筛选PARP-1的抑制剂。建立384孔板的高通量筛选模型,对9280个化合物(包括合成化合物、天然产物、微生物发酵提取物)组成的随机库进行体外筛选。结果筛选出148个活性化合物对PARP-1的抑制作用大于70%,最终确定3个化合物具有较高的抑制活性。结论建立的PARP-1抑制剂高通量筛选模型具有灵敏度高、快速、微量、准确的特点。     

基于结构设计的三肽分子对NDM-1的抑制活性研究

产生β-内酰胺酶是致病菌对抗生素耐药性的最主要原因。虽然丝氨酸β-内酰胺酶抑制剂已经广泛用于临床,但是针对金属β-内酰胺酶目前尚无有效药物通过临床试验。因此新型MBLs抑制剂的研发成为了热点。鉴于抗菌肽在自然界发挥的快速有效的抗菌活性及其不易导致耐药性的特点,结合不断被报道的卡托普利与青霉素的结构特征,本研究设计了一系列含有半胱氨酸的小分子肽,并测定了其对NDM-1的抑制活性,发现FCf对NDM-1的抑制活性最好,IC₅₀为26.59μmol/L,能够使头孢呋辛对NDM-1重组菌的MIC降低4倍。Cys和N端Phe构型的改变都会使三肽分子的活性降低,C端引入Pro也会导致活性下降。本研究可为合理设计新型MBLs抑制剂提供借鉴。     

应用虚拟筛选方法寻找链阳霉素A乙酰转移酶抑制剂

维吉尼亚霉素乙酰转移酶D(VatD)通过灭活链阳霉素A而在链阳霉素耐药性的产生中起重要作用。本研究采用虚拟筛选技术寻找VatD的抑制剂,此VatD抑制剂可以和链阳霉素联合使用,从而提供新的治疗耐药菌感染的方法。作者首次应用基于结构的虚拟筛选方法(分子对接)从含300 000化合物的商业化数据库中筛选对抗VatD底物结合位点的化合物,从200个评分最高的化合物中选取26个测定对VatD酶活性的抑制作用。将构建的质粒pRSET B/vatD转染宿主细胞E.coli(TrxB)用于过表达,纯化的VatD对维吉尼亚霉素M1表现乙酰转移酶活性。26个化合物中有3个对VatD表现抑制作用,IC₅₀分别为168.6,91.0和55.2 μmol·L^-1。其他化合物在反应体系中不溶解和/或对酶活性的抑制作用很小(IC₅₀>200 μmol·L^-1)。本文首次设计VatD的小分子化合物抑制剂,发现了3个有活性的化合物,希望其可作为先导化合物进一步发展为新的对抗链阳霉素耐药性的药物。     

BACE1抑制剂分子水平高通量筛选体系的建立

目的建立体外分子水平β-分泌酶（BACE1）抑制剂高通量筛选体系。方法采用均相时间分辨荧光法（HTRF）,通过优化反应时间、酶浓度、检测仪器等实验条件,建立BACE1抑制剂高通量筛选体系,根据待测样品对BACE1活性抑制程度筛选其抑制剂。结果采用HTRF法建立了BACE1抑制剂高通量筛选体系,其中反应时间确定为6h、BACE1浓度为670U/L,采用VICTOR3酶标仪测得信噪比为649.6,信背比为44.6,Z′因子为0.91,变异系数小于10%,并筛选到一系列IC50小于10-6mol/L的化合物。结论采用HTRF法建立的BACE1抑制剂筛选体系灵敏度高、特异性和稳定性好,可用于BACE1抑制剂的高通量筛选。     

Identification of Novel Selective Lysine‐Specific Demethylase 1 (LSD1) Inhibitors Using a Pharmacophore‐Based Virtual Screening Combined with Docking

Lysine‐specific demethylase 1 (LSD1) plays an important role in regulating the lysine methylation at residues K4 and K9 on histone H3. High levels of LSD1 expression have been observed in several malignant tumors. In this study, we presented a pharmacophore‐based virtual screening of a moderate database of 171 143 small molecules. A pharmacophore of LSD1 inhibitors was constructed for the first time and then used to screen the compound library combined with validated molecular docking tools followed by biochemical assays, led to the identification of 9 novel LSD1 inhibitors, showing their IC₅₀ values in a range of 2.41–101 μm . Furthermore, compound XZ 09 exhibited less inhibition against the homologous monoamine oxidase A (MAO‐A) and B (MAO‐B) displaying its moderate selectivity. Our study provides an effective virtual screening method to identify new LSD1 inhibitors and XZ09 represents a potent and selective lead compound to deserve further optimization for the treatment of LSD1 overexpressing cancers.     

Identification of Novel Gyrase B Inhibitors as Potential Anti‐TB drugs: Homology Modelling,Hybrid Virtual Screening and Molecular Dynamics Simulations

Using an integrated computational approach involving homology modelling, pharmacophore/structure‐based virtual screening, molecular dynamics simulations and per‐residue energy contribution, 10 compounds were proposed as potential TB inhibitors. Via validated docking calculations, binding free energy calculations showed that the proposed compounds presented better binding affinity with DNA gyrase B when compared to novobiocin. The compiled in silico approach employed in this study may serve as a useful tool in the process of the design and development of drugs, not only against TB, but also for a wide range of biological systems.     

Discovery of Novel Vascular Endothelial Growth Factor Receptor 2 Inhibitors: A Virtual Screening Approach

A virtual screening approach was performed to develop novel and potent vascular endothelial growth factor receptor 2 inhibitors. The Specs database was filtered by ‘rule of five’, a pharmacophore model, and docking filter. Sixteen molecules were selected for tube formation assay, a naphthalenol group containing molecule, 12 , showed good performance in the study. In the following aortic ring assay and 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay, 12 was discovered to efficiently inhibit angiogenesis and tumor cell growth. It is the first time to discover naphthalenol scaffold as potent vascular endothelial growth factor receptor 2 inhibitors. Thus, a molecular dynamic simulation process was applied to discover key features of 12 in binding to vascular endothelial growth factor receptor 2. Hydrophobic interactions were discovered to play significant role in the ligand–receptor binding.     

Virtual Screening Approach to Identifying a Novel and Tractable Series of Pseudomonas aeruginosa Elastase Inhibitors

Novel therapies are required to treat chronic bacterial infections in cystic fibrosis (CF) sufferers. The most common pathogen responsible for these infections is Pseudomonas aeruginosa, which persists within the lungs of CF sufferers despite intensive antibiotic treatment. P. aeruginosa elastase (also known as LasB or pseudolysin) is a key virulence determinant that contributes to the pathogenesis and persistence of P. aeruginosa infections in CF patients. The crucial role of LasB in pseudomonal virulence makes it a good target for the development of an adjuvant drug for CF treatment. Herein we discuss the discovery of a new series of LasB inhibitors by virtual screening and computer assisted drug design (CADD) and their optimization leading to compounds 29 and 39 (K_i = 0.16 μM and 0.12 μM, respectively).     

Evaluating the Predictivity of Virtual Screening for Abl Kinase Inhibitors to Hinder Drug Resistance

Virtual screening methods are now widely used in early stages of drug discovery, aiming to rank potential inhibitors. However, any practical ligand set (of active or inactive compounds) chosen for deriving new virtual screening approaches cannot fully represent all relevant chemical space for potential new compounds. In this study, we have taken a retrospective approach to evaluate virtual screening methods for the leukemia target kinase ABL1 and its drug‐resistant mutant ABL1‐T315I. ‘Dual active’ inhibitors against both targets were grouped together with inactive ligands chosen from different decoy sets and tested with virtual screening approaches with and without explicit use of target structures (docking). We show how various scoring functions and choice of inactive ligand sets influence overall and early enrichment of the libraries. Although ligand‐based methods, for example principal component analyses of chemical properties, can distinguish some decoy sets from active compounds, the addition of target structural information via docking improves enrichment, and explicit consideration of multiple target conformations (i.e. types I and II) achieves best enrichment of active versus inactive ligands, even without assuming knowledge of the binding mode. We believe that this study can be extended to other therapeutically important kinases in prospective virtual screening studies.     

Discovery of Novel Allosteric Eg5 Inhibitors Through Structure‐Based Virtual Screening

Mitotic kinesin Eg5 is an attractive anticancer drug target. Discovery of Eg5 inhibitors has been focused on targeting the ‘monastrol‐binding site’. However, acquired drug resistance has been reported for such inhibitors. Therefore, identifying new Eg5 inhibitors which function through a different mechanism(s) could complement current drug candidates and improve drug efficacy. In this study, we explored a novel allosteric site of Eg5 and identified new Eg5 inhibitors through structure‐based virtual screening. Experiments with the saturation‐transfer difference NMR demonstrated that the identified Eg5 inhibitor SRI35566 binds directly to Eg5 without involving microtubules. Moreover, SRI35566 and its two analogs significantly induced monopolar spindle formation in colorectal cancer HCT116 cells and suppressed cancer cell viability and colony formation. Together, our findings reveal a new allosteric regulation mechanism of Eg5 and a novel drug targeting site for cancer therapy.     

A Specific Pharmacophore Model of Aurora B Kinase Inhibitors and Virtual Screening Studies Based on it

In this study, 3D‐pharmacophore models of Aurora B kinase inhibitors have been developed by using HipHop and HypoGen modules in Catalyst software package. The best pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9911), consists of one hydrogen‐bond acceptor, one hydrogen‐bond donor, one hydrophobic aliphatic moiety and one ring aromatic feature. Hypo1 was validated by test set and cross‐validation methods. And the specificity of Hypo1 to Aurora B inhibitors was examined with the use of selective inhibitors against Aurora B and its paralogue Aurora A. The results clearly indicate that Hypo1 can differentiate selective inhibitors of Aurora B from those of Aurora A, and the ring aromatic feature likely plays some important roles for the specificity of Hypo1. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge and Chinese Nature Product Database (CNPD) for identifying new inhibitors of Aurora B. The hit compounds were subsequently subjected to filtering by Lipinski’s rule of five and docking studies to refine the retrieved hits, and some compounds selected from the top ranked hits have been suggested for further experimental assay studies.