Computational Approaches to Discover Novel Natural Compounds for SARS-CoV-2 Therapeutics

Scientists all over the world are facing a challenging task of finding effective therapeutics for the coronavirus disease (COVID-19). One of the fastest ways of finding putative drug candidates is the use of computational drug discovery approaches. The purpose of the current study is to retrieve natural compounds that have obeyed to drug-like properties as potential inhibitors. Computational molecular modelling techniques were employed to discover compounds with potential SARS-CoV-2 inhibition properties. Accordingly, the InterBioScreen (IBS) database was obtained and was prepared by minimizing the compounds. To the resultant compounds, the absorption, distribution, metabolism, excretion and toxicity (ADMET) and Lipinski's Rule of Five was applied to yield drug-like compounds. The obtained compounds were subjected to molecular dynamics simulation studies to evaluate their stabilities. In the current article, we have employed the docking based virtual screening method using InterBioScreen (IBS) natural compound database yielding two compounds has potential hits. These compounds have demonstrated higher binding affinity scores than the reference compound together with good pharmacokinetic properties. Additionally, the identified hits have displayed stable interaction results inferred by molecular dynamics simulation results. Taken together, we advocate the use of two natural compounds, STOCK1N-71493 and STOCK1N-45683 as SARS-CoV-2 treatment regime.     

4-苯基-1,3-硒唑衍生物的合成及其对蛋白酪氨酸磷酸酯酶-1B抑制活性

蛋白酪氨酸磷酸酯酶-1B(PTP1B)是抗糖尿病治疗的重要靶点,因此创制活性优良的PTP1B抑制剂具有重要意义。 本文设计并合成了11个含1,3-硒唑和1,2,4-三唑活性组块新型结构目标分子(ZLXZ1-ZLXZ11),并利用傅里叶变换红外光谱仪(FTIR)、核磁共振波谱仪(NMR)和高分辨质谱(HRMS)等对其进行了结构表征。 首先选择ZLXZ1和ZLXZ11在MOE 2015.10程序上,与PTP1B进行分子对接模拟,结果表明,在ZLXZ1分子中硒唑环上的硒原子与PTP1B中副催化位点Tyr46、Ala217、Lys120和Asp 48分别形成了π-H作用和氢键作用。 在ZLXZ11分子中硒唑上的硒原子与PTP1B中Asp181、Arg221和Asp48形成了氢键作用。 在分子对接模拟的基础上,测试了11个目标分子的抑制活性,结果表明,所有目标分子的抑制率均在87.02%以上,其中3个目标分子PTP1B抑制活性高于阳性参照物齐墩果酸,抑制活性优良,有望成为潜在的PTP1B抑制剂。     

Analysis of dissolution profiles of iron,zinc, and manganese from complex dietary supplements by ion chromatography and chemometrics

Four commercially available formulations containing iron, zinc, and manganese were subjected to dissolution profile testing during 60 min and the dissolution was analyzed by ion chromatography. The obtained curves were analyzed directly by principal component analysis (PCA). The main trend (87.1% of variance) was connected with average dissolution percentage over the investigated time. The second component (11.2% of variance) is connected with shape of dissolution profile. All metals behave in the similar way and the differences were connected with excipients. An additional fit was completed on 12 kinetic models: first order kinetics (4 variants), Higuchi (2 variants), Hixson-Crowell (2 variants), Korsemeyer-Peppas, Logistic (2 variants), Peppas-Sahlin, Quadratic (2 variants), Weibull (3 variants), and Zero order kinetics (2 variants). The ranking of the fitting was performed by Akaike information criteria (AIC) values with additional PCA analysis on them, an approach presented in literature for the first time. The main trend (67.4% of variance) was connected with average fit. The second (14.8% of variance) is connected with differences of fitting ability to investigated dissolution curves. This methodology brought an overall look to trends and variances inside obtained data, both the profile shape and fitting ability to particular models.     

Schrödinger药物虚拟筛选流程模块在大学生物和化学信息学教学中的应用

介绍了Schr?dinger药物虚拟筛选的基本原理和流程,结合大学生物和化学信息学课程的相关教学内容,分别描述了蛋白受体的预处理、类药性五原则、毒药物动力学(ADME)、泛筛选干扰化合物(PAINS)、高通量虚拟筛选、标准精度筛选、高精度筛选和MM/GBSA的打分排序原理和使用方法。该软件可以在大学生物和化学信息学的教学中演示,有助于提高学生对蛋白结构、分子构象、药物虚拟筛选和计算机辅助分子设计的理解,该软件有很好的图形界面,可以给学生直观的体验,大大丰富了大学课堂的教学内容。此外,该软件在药物设计领域里面也有很好的应用价值,大大节约了药物筛选的成本,提高了药物发现的效率。     

嘧啶衍生物与人血清白蛋白的相互作用

在模拟生理条件下,运用荧光光谱、激光闪光光解(LFP)和分子对接等技术研究了8种具有抗肿瘤活性的嘧啶衍生物(PDs,其中PDs A 5-FU为成药,PDs B-H为实验室自制)与人血清白蛋白(HSA)的相互作用.利用Stern-Volmer方程和激光闪光光解技术分析了PDs对HSA的荧光猝灭机制,PDs A和B为静态猝灭,PDs G和H为动态猝灭.用双倒数曲线法得出5种PDs与HSA的结合常数Ka和结合位点数n,在测定条件下5种PDs与载体结合位点数均为1,且均以弱结合力结合,通过热力学参数ΔH,ΔS和ΔG推测出PDs B,C和E与HSA之间的作用力为静电作用力和疏水作用力,PDs A和D与HSA之间的作用力是氢键和范德华力,分子对接结果与其一致.根据F9rster非辐射能量转移理论(FRET)分析了HSA和PDs之间的结合距离(r),其结果均小于4 nm,符合能量转移理论.进一步利用同步荧光、三维荧光和圆二色光谱考察了PDs与HSA结合过程中HSA空间构象的变化,结果显示,仅PDs A和C对HSA的芳香族氨基酸周围的疏水性略有增强作用.体外实验结果表明,HSA可以作为优良的载体来运输和储存PDs A~E,这为嘧啶衍生物的后续研究提供了可参考的实验数据.     

二氢嘧啶并[4,5-d]嘧啶类衍生物作为集落刺激因子-1受体激酶抑制剂的分子对接和定量构效关系研究

集落刺激因子-1受体激酶（CSF-1R）属于Ⅲ型受体酪氨酸激酶家族成员,其在调控单核巨噬细胞系中发挥重要作用。CSF-1R及其配体异常表达与肿瘤发展过程密切相关。因此,CSF-1R信号传导可成为抗肿瘤治疗的有吸引力的靶标。本文用比较分子场分析法（CoMFA）和比较分子相似性指数分析法（CoMSIA）研究了54个二氢嘧啶并[4,5-d]嘧啶类CSF-1R激酶抑制剂的三维定量构效关系（3D-QSAR）。基于配体叠合,CoMFA和CoMSIA模型的交叉验证系数（q2）分别为0.725和0.636,拟合验证系数（r2）分别为0.960和0.958,结果表明这两种模型均具有较好的预测能力。所建模型的等势图能直观反映分子不同取代基对活性的影响,其中立体场和疏水场对活性的贡献较大。通过分子对接研究显示,氨基酸残基Cys666、Asp796在配体和受体结合过程中产生作用,分子对接的结合模式与3D-QSAR得到的结果一致。这些信息为进一步优化CSF-1R激酶抑制剂提供了理论基础。     

基于对偶四元数的卫星信息一致性控制

为了解决航天器控制信息一致性问题,提出了利用对偶四元数来描述对象的位置及姿态信息,实现位置与姿态的统一表述。同时利用信息一致性理论,通过设计航天器间的信息传递模型来解决分布式航天器间的状态同步问题。采用对偶四元数及信息一致性理论为工具,分别给出了位姿同步及跟踪两种控制方法并针对两种信息拓扑模型,以空间交会对接问题进行仿真实验,实验结果表明,在500s以内,卫星的位置及姿态实现了同步及跟踪控制。     

New Blood Coagulation Factor XIIa Inhibitors: Molecular Modeling,Synthesis, and Experimental Confirmation

In the modern world, complications caused by disorders in the blood coagulation system are found in almost all areas of medicine. Thus, the development of new, more advanced drugs that can prevent pathological conditions without disrupting normal hemostasis is an urgent task. The blood coagulation factor XIIa is one of the most promising therapeutic targets for the development of anticoagulants based on its inhibitors. The initial stage of drug development is directly related to computational methods of searching for a lead compound. In this study, docking followed by quantum chemical calculations was used to search for noncovalent low-molecular-weight factor XIIa inhibitors in a focused library of druglike compounds. As a result of the study, four low-molecular-weight compounds were experimentally confirmed as factor XIIa inhibitors. Selectivity testing revealed that two of the identified factor XIIa inhibitors were selective over the coagulation factors Xa and XIa.     

Interactions between Human Serum Albumin and Sulfadimethoxine Determined Using Spectroscopy and Molecular Docking

Sulfonamides are widely used antibiotics in agricultural production. However, the potential threat of these drugs to human health has increased global concern. Human serum albumin (HSA) is the main reservoir and transporter of exogenous small molecules in humans. In this study, the interaction between sulfadimethoxine (SMT) and human serum albumin (HSA) was studied using spectroscopy and computer simulation. Our results showed that the hydrogen bonding and van der Waals forces drove SMT to enter the binding site I of HSA spontaneously and resulted in the fluorescence quenching of HSA. The stability of the HSA–SMT complex decreased with an increase in temperature. The binding of SMT to HSA induced alterations in the secondary structure of HSA, where the content of α-helix decreased from 61.0% of the free state to 59.0% of the compound state. The π–π, π–σ, and π–alkyl interactions between HSA and SMT were found to play important roles in maintaining the stability of the complex.     

Drug Design—Past,Present, Future

Drug design is a complex pharmaceutical science with a long history. Many achievements have been made in the field of drug design since the end of 19th century, when Emil Fisher suggested that the drug–receptor interaction resembles the key and lock interplay. Gradually, drug design has been transformed into a coherent and well-organized science with a solid theoretical background and practical applications. Now, drug design is the most advanced approach for drug discovery. It utilizes the innovations in science and technology and includes them in its wide-ranging arsenal of methods and tools in order to achieve the main goal: discovery of effective, specific, non-toxic, safe and well-tolerated drugs. Drug design is one of the most intensively developing modern sciences and its progress is accelerated by the implication of artificial intelligence. The present review aims to capture some of the most important milestones in the development of drug design, to outline some of the most used current methods and to sketch the future perspective according to the author’s point of view. Without pretending to cover fully the wide range of drug design topics, the review introduces the reader to the content of Molecules’ Special Issue “Drug Design—Science and Practice”.