新型非拟肽磺胺类HIV蛋白酶抑制剂Darunavir的研究进展

综述新型非拟肽磺胺类人类免疫缺陷病毒(HIV)蛋白酶抑制剂Darunavir (TMC-114)的发现, 抗病毒的活性, 分子模拟以及结构优化的研究进展. Darunavir不但对野生型的HIV蛋白酶有很好的抑制活性, 而且对多种抗性突变的HIV蛋白酶也有良好的活性, 是针对耐药性HIV所开发的新药.     

HIV-1逆转录酶抑制剂的3D-QSAR研究及分子设计

采用Topomer Co MFA方法对24个二芳基苯胺衍生物进行三维定量构效关系研究,建立了3DQSAR模型,所得优化模型的非交叉相关系数、交互验证系数以及外部验证的复相关系数分别为0.928,0.654和0.940,结果表明该模型具有良好的稳定性和预测能力。采用分子对接技术对药物与受体的作用机制进行了研究,结果显示,药物与HIV-1逆转录酶的LYS172,GLU138,LYS101等位点作用明显。运用这些信息进行分子设计,在理论上获得了一些具有较高活性的新的二芳基苯胺类抗艾滋病药物,该QSAR的研究结果可为新药合成提供理论参考。     

Enhancing protein backbone binding--a fruitful concept for combating drug-resistant HIV

The evolution of drug resistance is one of the most fundamental problems in medicine. In HIV/AIDS, the rapid emergence of drug-resistant HIV-1 variants is a major obstacle to current treatments. HIV-1 protease inhibitors are essential components of present antiretroviral therapies. However, with these protease inhibitors, resistance occurs through viral mutations that alter inhibitor binding, resulting in a loss of efficacy. This loss of potency has raised serious questions with regard to effective long-term antiretroviral therapy for HIV/AIDS. In this context, our research has focused on designing inhibitors that form extensive hydrogen-bonding interactions with the enzyme's backbone in the active site. In doing so, we limit the protease's ability to acquire drug resistance as the geometry of the catalytic site must be conserved to maintain functionality. In this Review, we examine the underlying principles of enzyme structure that support our backbone-binding concept as an effective means to combat drug resistance and highlight their application in our recent work on antiviral HIV-1 protease inhibitors.     

Understanding the basis of I50V‐induced affinity decrease in HIV‐1 protease via molecular dynamics simulations using polarized force field

Human immunodeficiency virus (HIV)‐1 protease is one of the most promising drug target commonly utilized to combat Acquired Immune Deficiency Syndrome (AIDS). However, with the emergence of drug resistance arising from mutations, the efficiency of protease inhibitors (PIs) as a viable treatment for AIDS has been greatly reduced. I50V mutation as one of the most significant mutations occurring in HIV‐1 protease will be investigated in this study. Molecular dynamics (MD) simulation was utilized to examine the effect of I50V mutation on the binding of two PIs namely indinavir and amprenavir to HIV‐1 protease. Prior to the simulations conducted, the electron density distributions of the PI and each residue in HIV‐1 protease are derived by combining quantum fragmentation approach molecular fractionation with conjugate caps and Poisson–Boltzmann solvation model based on polarized protein‐specific charge scheme. The atomic charges of the binding complex are subsequently fitted using delta restrained electrostatic potential (delta‐RESP) method to overcome the poor charge determination of buried atom. This way, both intraprotease polarization and the polarization between protease and the PI are incorporated into partial atomic charges. Through this study, the mutation‐induced affinity variations were calculated and significant agreement between experiments and MD simulations conducted was observed for both HIV‐1 protease‐drug complexes. In addition, the mechanism governing the decrease in the binding affinity of PI in the presence of I50V mutation was also explored to provide insights pertaining to the design of the next generation of anti‐HIV drugs. © 2015 Wiley Periodicals, Inc.     

HIV-1 protease cleavage site prediction based on amino acid property

Knowledge of the polyprotein cleavage sites by HIV protease will refine our understanding of its specificity, and the information thus acquired is useful for designing specific and efficient HIV protease inhibitors. Recently, several works have approached the HIV-1 protease specificity problem by applying a number of classifier creation and combination methods. The pace in searching for the proper inhibitors of HIV protease will be greatly expedited if one can find an accurate, robust, and rapid method for predicting the cleavage sites in proteins by HIV protease. In this article, we selected HIV-1 protease as the subject of the study. 299 oligopeptides were chosen for the training set, while the other 63 oligopeptides were taken as a test set. The peptides are represented by features constructed by AAIndex (Kawashima et al., Nucleic Acids Res 1999, 27, 368; Kawashima and Kanehisa, Nucleic Acids Res 2000, 28, 374). The mRMR method (Maximum Relevance, Minimum Redundancy; Ding and Peng, Proc Second IEEE Comput Syst Bioinformatics Conf 2003, 523; Peng et al., IEEE Trans Pattern Anal Mach Intell 2005, 27, 1226) combining with incremental feature selection (IFS) and feature forward search (FFS) are applied to find the two important cleavage sites and to select 364 important biochemistry features by jackknife test. Using KNN (K-nearest neighbors) to combine the selected features, the prediction model obtains high accuracy rate of 91.3% for Jackknife cross-validation test and 87.3% for independent-set test. It is expected that our feature selection scheme can be referred to as a useful assistant technique for finding effective inhibitors of HIV protease, especially for the scientists in this field.     

Molecular modeling studies of human immunodeficiency virus type 1 protease inhibitors using three‐dimensional quantitative structure‐activity relationship,virtual screening,and docking simulations

In this paper, two 3‐dimensional quantitative structure‐activity relationship models for 60 human immunodeficiency virus (HIV)‐1 protease inhibitors were established using random sampling analysis on molecular surface and translocation comparative molecular field vector analysis (Topomer CoMFA). The non–cross‐validation (r²), cross‐validation (q²), correlation coefficient of external validation (Q²_ext), and F of 2 models were 0.94, 0.80, 0.79, and 198.84 and 0.94, 0.72, 0.75, and 208.53, respectively. The results indicated that 2 models were reasonable and had good prediction ability. Topomer Search was used to search R groups in the ZINC database, 20 new compounds were designed, and the Topomer CoMFA model was used to predicate the biological activity. The results showed that 18 new compounds were more active than the template molecule. So the Topomer Search is effective in screening and can guide the design of new HIV/AIDS drugs. The mechanism of action was studied by molecular docking, and it showed that the protease inhibitors and Ile50, Asp25, and Arg8 sites of HIV‐1 protease have interactions. These results have provided an insight for the design of new potent inhibitors of HIV‐1 protease.