新型冠状病毒相关靶点小分子抑制剂虚拟筛选

为确定治疗新型冠状病毒(SARS-CoV-2)感染的候选药物,开展了针对SARS-CoV-2的药物虚拟筛选研究。以SARS-CoV-2的刺突蛋白(S蛋白)和3CL蛋白酶(主蛋白酶)作为药物靶点,以美国食品药品监督管理局(FDA)批准上市的2 726个小分子药物作为候选,通过分子对接方法,筛选出了3种(阿巴瑞克(Abarelix)、西曲瑞克(Cetrorelix)、鞣酸(Tannic acid))与S蛋白具有较强结合能力的小分子药物,1种(戈舍瑞林(Goserelin))与3CL蛋白酶具有较好结合能力的小分子药物,它们理论上都具有抑制新型冠状病毒复制的效果。将靶向3CL蛋白酶的候选药物与辉瑞公司开发的药物Paxlovid进行比较,发现其作用位点均集中于3CL蛋白酶的第130-200位的残基周围,具有相似的结合位点与相互作用。此外也对候选药物的物理与化学性质及与基因相互作用进行了分析。本研究可为开发新型冠状病毒感染的治疗药物提供参考。     

虚拟筛选与新药发现

虚拟筛选是创新药物研究的新方法和新技术,近年来引起了研究机构和制药公司的高度重视,并且已经成为一种与高通量筛选互补的实用化工具,加入到了创新药物研究的工作流程(pipeline)中。本文介绍国际上虚拟筛选及其在创新药物发现中应用的研究进展,特别介绍了我国这方面研究的状况。     

反向虚拟筛选平台及应用

靶标确证是老药新用、药物毒副作用研究的关键。基于分子对接方法 Auto Dock Vina和内部构建的疾病靶标数据库,采用分布式架构,构建了反向虚拟筛选平台。应用该平台对药物吡斯的明进行靶标确证,最终成功找到其靶标乙酰胆碱酯酶,验证了平台的实用性和准确性。     

基于虚拟筛选技术对氟康唑细胞毒性的机制评价

目的 探讨氟康唑对细胞是否具有毒性,能否用于防治细胞污染。方法 虚拟筛选与分子对接技术筛选潜在的毒性靶点。使用人肝癌SMMC-7721细胞、人胚肝HHL-5细胞与人胚肾HEK-293细胞进行体外实验。CCK8实验验证氟康唑对细胞活性的影响。Hoechst 33342/PI双染实验进行形态学观察。qRT-PCR实验进一步验证氟康唑对虚拟筛选所获的靶点是否有影响,明确对细胞影响的机制。结果 虚拟筛选前6个核心毒性靶点是IL-6、TP53、TNF、IL-1β、VEGFA以及EGFR。CCK8实验与Hoechst 33342/PI双染实验显示氟康唑对SMMC-7721细胞和HHL-5细胞具有抑制作用,对HEK-293细胞具有促增殖作用。qRT-PCR实验表明氟康唑导致细胞毒性的核心靶点是IL-6、IL-1β和EGFR。结论 氟康唑不适合广泛应用于预防细胞污染。     

面向虚拟筛选的GPU加速的分子对接方法

虚拟筛选是在计算机上对化合物分子进行模拟预筛选,找出容易和药物靶标结合的小分子(配体),从而降低实际实验测试次数,提高药物先导化合物的发现效率。常用的分子对接软件可以用于基于结构的虚拟筛选,寻找配体与靶标的最佳的作用模式和结合构象,并通过打分函数来筛选出潜在的配体。现有的对接软件如AutoDock Vina等在分子对接过程中需要耗费大量时间和计算资源,特别是面对大规模分子对接时,过长的筛选时间不能满足应用需求,因此,本文在最高效的QVina2对接软件基础上,提出一种基于GPU的QVina 2并行化方法QVina2-GPU,利用GPU硬件高度并行体系加速分子对接。具体包括增加初始化分子构象数量,以扩展蒙特卡罗的迭代局部搜索中线程的并行规模,增加蒙特卡罗的迭代搜索的广度以减少每次蒙特卡罗迭代搜索深度,并利用Wolfe-Powell准则改进局部搜索算法,提高了对接精度,进一步减少蒙特卡罗迭代搜索深度,最后,在NVIDIA Geforce RTX 3090平台上在公开的配体数据库上验证了QVina2-GPU的性能,实验表明在保证分子对接精度的基础上,我们提出的QVina2-GPU对Qvina2的平均加速比达到5.18倍,最大加速比达到12.28倍。     

计算机虚拟筛选技术在害虫行为调节剂研究中的应用

害虫行为调节剂是一种以嗅觉系统为靶标的绿色农药,在害虫的田间管理中发挥着重要的作用。然而,其先导化合物的发现通常依赖一系列生物测定的方法,不仅费时费力,且发现效率低。近年来,随着昆虫嗅觉功能数据的积累和结构生物学的飞速发展,以机器学习技术和分子对接为代表的2种基于计算机的药物虚拟筛选方法在害虫行为调节剂的先导化合物研究中发挥着重要的作用,极大地促进了先导化合物的发现效率,减少了筛选的盲目性。本文系统综述了2种虚拟筛选方法及其在害虫行为调节剂先导化合物研究中的应用,并对2种筛选策略在实际应用中存在的问题及应用前景进行了讨论。     

基于TCMSP数据库的分子对接虚拟筛选JAK3特异性抑制剂CSCD

以LeDock分子对接软件对TCMSP数据库中的13445种中草药成分小分子与JAK3激酶进行分子模拟对接研究,分析对接结合自由能与配体效率,筛选出18种小分子,再根据受体与配体的相互作用进一步分析,得到7种与JAK3激酶有较好结合作用的小分子,并且发现JAK3激酶分子中氨基酸残基Arg953、Asp967、Lys830、Ala966和Asn954是小分子与酶形成氢键作用的重要位点,为JAK3抑制剂的开发设计提供有力依据。以其他JAK家族成员为靶蛋白,进行反向筛选,发现断马钱子苷(scologanin)对JAK3激酶表现出强结合力与高选择性。本研究意在寻找可以作为JAK3激酶高选择性抑制剂的中草药药效小分子,结果发现断马钱子苷具备相应的潜力,值得进一步深入研究。     

红藤化学成分中端粒酶TERT基因激动剂的虚拟筛选

目的:为了发现红藤中能够激活端粒酶逆转录酶(TERT)的化学成分.方法:检索文献和数据库,确定红藤中的小分子化合物(配体);使用AutodockVina软件与受体TERT(PDB ID:5CQG)进行分子对接,根据结合能(打分值)确定潜在的激活TERT的化合物.结果:红藤中126种化合物与5CQG的结合能与化合物的结构...     

流感病毒神经氨酸酶抑制剂的筛选

以神经氨酸酶为药物靶点筛选神经氨酸酶抑制剂, 是研究和开发抗流感病毒药物的重要途径. 应用虚拟药物筛选方法, 从化合物数据库中选出部分待测化合物, 然后应用已建立的 神经氨酸酶抑制剂的高通量筛选模型, 检测了这些化合物的抑制活性, 从中发现了3个活性较高、结构新颖的化合物, 其IC50在0.1~3 μmol/L之间, 这些活性化合物的结构特点, 对于新型神经氨酸酶抑制剂的设计与开发, 将提供重要的信息指导. 流感病毒神经氨酸酶抑制剂的筛选结果表明, 虚拟筛选技术与高通量筛选技术的合理结合, 将有利于促进药物筛选与药物发现.     

基于天然产物的蛋白酪氨酸磷酸酶1B 抑制剂的虚拟筛选

蛋白酪氨酸磷酸酶1B(protein tyrosine phosphatase 1B,PTP1B)是治疗Ⅱ型糖尿病的靶点之一,筛选PTP1B抑制剂具有十分重要的意义.本文采用分子对接虚拟筛选方法,构建共含有42 296个小分子的天然产物库,分别与PTP1B靶点蛋白进行分子对接,以原配体的结合能量为阈值,经过三轮筛选选取打分值高于阈值的小分子进行药代动力学参数和毒性参数预测,最终筛选出3个PTP1B抑制剂,对苯醌类化合物7、异香豆素类衍生物10和Clavepictine类似物11.结合方式研究表明,3个候选抑制剂类药性良好,均具有较好的PTP1B抑制活性,其中化合物10和11的PTP1B抑制活性未见报道.对化合物10进行体外抑制活性检测,其IC50为(74.58±1.23)μmol/L,可作为潜在Ⅱ型糖尿病治疗药物.     

Discovery of new potent inhibitors for carbonic anhydrase IX by structure-based virtual screening

Through structure-based virtual screening, some dozen of benzene sulfonamides with novel scaffolds are identified as potent inhibitors against carbonic anhydrase (CA) IX with IC₅₀ values ranging from 2.86 to 588.34 nM. Among them, compounds 1 and 9 show high selectivity against tumor-target CA IX over CA II (the selectivity ratios are 21.3 and 136.6, respectively). The possible binding poses of hit compounds are also explored and the selectivity is elucidated by molecular docking simulations. The hit compounds discovered in this work would provide novel scaffolds for further hit-to-lead optimization.     

Discovery of novel DNA methyltransferase 3A inhibitors via structure-based virtual screening and biological assays

DNA methyltransferases are involved in diverse biological processes and abnormal methylation patterns play essential roles in cancer initiation and progression. DNA methyltransferase 3A (DNMT3A) acting as a de novo DNA methyltransferase, has gained widespread attention especially in haematological diseases. To date, large numbers of DNMTs inhibitors have been discovered, however, the small molecular inhibitors targeting DNMT3A are still in its infancy. In this study, structure-based virtual screening in combination with biological assays was performed to discovery potent novel DNMT3A inhibitors. Compound 40 and 40_3 displayed comparable in vitro inhibitory activity against DNMT3A with IC₅₀ values of 46.5 μM and 41 μM, respectively. Further binding mode analysis suggested these molecules inhibit DNMT3A activity through binding the S-adenosyl-l-methionine (SAM) pocket. Overall, 40 and 40_3 may serve as novel scaffolds for further optimization and small molecular probes for investigating DNMT3A function.     

Discovery of the first SecA inhibitors using structure-based virtual screening

Bacterial protein secretion is a critical and complex process. The Sec machinery provides a major pathway for protein translocation across and integration into the cellular membrane in bacteria. Small molecule probes that perturb the functions of individual member proteins within the Sec machinery will be very important research tools as well as leads for future antimicrobial agent development. Herein we describe the discovery of inhibitors, through virtual screening, that specifically act on SecA ATPase, which is a critical member of the Sec system. These are the very first inhibitors reported for intrinsic SecA ATPase.     

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM,pharmacophore and docking model

Abstract

Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLIF) pharmacophore and docking was utilised for screening the CDK2 inhibitors. The evaluation of the validation set indicated that this method can be used to screen large chemical databases because it has a high hit-rate and enrichment factor (80.1% and 332.83 respectively). Six compounds were screened out from NCI, Enamine and Pubchem database. After molecular dynamics and binding free energy calculation, two compounds had great potential as novel CDK2 inhibitors and they also showed selective inhibition against CDK2 in the kinase activity assay.     

New potential inhibitors of mTOR: a computational investigation integrating molecular docking,virtual screening and molecular dynamics simulation

The mTOR (mammalian or mechanistic Target Of Rapamycin), a complex metabolic pathway that involves multiple steps and regulators, is a major human metabolic pathway responsible for cell growth control in response to multiple factors and that is dysregulated in various types of cancer. The classical inhibition of the mTOR pathway is performed by rapamycin and its analogs (rapalogs). Considering that rapamycin binds to an allosteric site and performs a crucial role in the inhibition of the mTOR complex without causing the deleterious side effects common to ATP-competitive inhibitors, we employ ligand-based drug design strategies, such as virtual screening methodology, computational determination of ADME/Tox properties of selected molecules, and molecular dynamics in order to select molecules with the potential to become non-ATP-competitive inhibitors of the mTOR enzymatic complex. Our findings suggest five novel potential mTOR inhibitors, with similar or better properties than the classic inhibitor complex, rapamycin.     

Identification of influenza PA-Nter endonuclease inhibitors using pharmacophore- and docking-based virtual screening

Searching for new antiviral agents, we focused our interest on the influenza PA-Nter endonuclease. Therefore, we developed a three-dimensional pharmacophore model which contains the binding features addressed to the metal-chelating active site. The obtained hypothesis has been fruitfully employed to select three “hit compounds” through an in silico screening campaign on our in-house database of small molecules. We studied the binding poses of these hit compounds using molecular docking, and subjected them to an enzymatic assay with recombinant PA-Nter endonuclease. Compound 20 proved the most active inhibitor of the endonucleolytic cleavage reaction, with an IC₅₀ value of 12?μM.     

Structure-based virtual screening and biological evaluation of novel small-molecule BTK inhibitors

Bruton tyrosine kinase (BTK) is linked to multiple signalling pathways that regulate cellular survival, activation, and proliferation. A covalent BTK inhibitor has shown favourable outcomes for treating B cell malignant leukaemia. However, covalent inhibitors require a high reactive warhead that may contribute to unexpected toxicity, poor selectivity, or reduced effectiveness in solid tumours. Herein, we report the identification of a novel noncovalent BTK inhibitor. The binding interactions (i.e. interactions from known BTK inhibitors) for the BTK binding site were identified and incorporated into a structure-based virtual screening (SBVS). Top-rank compounds were selected and testing revealed a BTK inhibitor with >50% inhibition at 10 µM concentration. Examining analogues revealed further BTK inhibitors. When tested across solid tumour cell lines, one inhibitor showed favourable inhibitory activity, suggesting its potential for targeting BTK malignant tumours. This inhibitor could serve as a basis for developing an effective BTK inhibitor targeting solid cancers.     

The discovery of novel and selective fatty acid binding protein 4 inhibitors by virtual screening and biological evaluation

Adipocyte fatty acid binding protein (AFABP, FABP4) has been proven to be a potential therapeutic target for diabetes, atherosclerosis and inflammation-related diseases. In this study, a series of new scaffolds of small molecule inhibitors of FABP4 were identified by virtual screening and were validated by a bioassay. Fifty selected compounds were tested, which led to the discovery of seven hits. Structural similarity-based searches were then performed based on the hits and led to the identification of one high affinity compound 33b (K_i = 0.29 ± 0.07 μM, ΔT_m = 8.5 °C). This compound’s effective blockade of inflammatory response was further validated by its ability to suppress pro-inflammatory cytokines induced by lipopolysaccharide (LPS) stimulation. Molecular dynamics simulation (MD) and mutagenesis studies validated key residues for its inhibitory potency and thus provide an important clue for the further development of drugs.     

Discovery of novel HCV polymerase inhibitors using pharmacophore-based virtual screening

We report the use of pharmacophore-based virtual screening as an efficient tool for the discovery of novel HCV polymerase inhibitors. A three-dimensional pharmacophore model for the HCV-796 binding site, NNI site IV inhibitor, to the enzyme was built by means of the structure-based focusing module in Cerius2 program. Using these models as a query for virtual screening, we produced a successful example of using pharmacophore-based virtual screening to identify novel compounds with HCV replicon assay through inhibition of HCV polymerization. Among the hit compounds, compounds 1 and 2 showed 56% and 48% inhibition of NS5B polymerization activity at 20 μM, respectively. In addition, compound 1 also exhibited replicon activity with EC₅₀ value of 2.16 μM. Following up the initial hit, we obtained derivatives of compound 1 and evaluated polymerization inhibition activity and HCV replicon assay. These results provide information necessary for the development of more potent NS5B inhibitors.     

Discovering novel carbonic anhydrase type IX (CA IX) inhibitors from seven million compounds using virtual screening and in vitro analysis

Carbonic anhydrase type IX (CA IX) enzyme is mostly over expressed in different cancer cell lines and tumor tissues. Potent CA IX inhibitors can be effective for adjusting the pH imbalance in tumor cells. In the present work, we represented the successful application of high throughput virtual screening (HTVS) of large dataset from ZINC database included of ～7 million compounds to discover novel inhibitors of CA IX. HTVS and molecular docking were performed using consequence Glide/standard precision (SP), extra precision (XP) and induced fit docking (IFD) molecular docking protocols. For each compound, docking code calculates a set of low-energy poses and then exhaustively scans the binding pocket of the target with small compounds. Novel CA IX inhibitor candidates were suggested based on molecular modeling studies and a few of them were tested using in vitro analysis. These compounds were determined as good inhibitors against human CA IX target with K_i in the range of 0.85–1.58?μM. In order to predict the pharmaceutical properties of the selected compounds, ADME (absorption, distribution, metabolism and excretion) analysis was also carried out.