Sachithanandham Jaiprasath, Konda Reddy Karnati, Solomon King, David Shoba, Kumar Singh Sanjeev, Vadhini Ramalingam Veena, Alexander Pulimood Susanne, Cherian Abraham Ooriyapadickal, Rupali Pricilla, Sridharan Gopalan, Kannangai Rajesh
Departments of Clinical Virology Alagappa University, Karaikudi, Tamil Nadu, India.
SNHRC Vellore and Computer-Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics Alagappa University, Karaikudi, Tamil Nadu, India.
Bioinformation. 2016 Jun 15;12(3):221-230. doi: 10.6026/97320630012221. eCollection 2016.
The degree of sequence variation in HIV-1 integrase genes among infected patients and their impact on clinical response to Anti retroviral therapy (ART) is of interest. Therefore, we collected plasma samples from 161 HIV-1 infected individuals for subsequent integrase gene amplification (1087 bp). Thus, 102 complete integrase gene sequences identified as HIV-1 subtype-C was assembled. This sequence data was further used for sequence analysis and multiple sequence alignment (MSA) to assess position specific frequency of mutations within pol gene among infected individuals. We also used biophysical geometric optimization technique based molecular modeling and docking (Schrodinger suite) methods to infer differential function caused by position specific sequence mutations towards improved inhibitor selection. We thus identified accessory mutations (usually reduce susceptibility) leading to the resistance of some known integrase inhibitors in 14% of sequences in this data set. The Stanford HIV-1 drug resistance database provided complementary information on integrase resistance mutations to deduce molecular basis for such observation. Modeling and docking analysis show reduced binding by mutants for known compounds. The predicted binding values further reduced for models with combination of mutations among subtype C clinical strains. Thus, the molecular basis implied for the consequence of mutations in different variants of integrase genes of HIV-1 subtype C clinical strains from South India is reported. This data finds utility in the design, modification and development of a representative yet an improved inhibitor for HIV-1 integrase.
HIV-1感染者中整合酶基因的序列变异程度及其对抗逆转录病毒疗法（ART）临床反应的影响备受关注。因此，我们收集了161名HIV-1感染者的血浆样本，用于后续整合酶基因扩增（1087 bp）。由此，组装出102个鉴定为HIV-1 C亚型的完整整合酶基因序列。这些序列数据进一步用于序列分析和多序列比对（MSA），以评估感染者中pol基因内突变的位置特异性频率。我们还使用基于生物物理几何优化技术的分子建模和对接（薛定谔套件）方法，推断位置特异性序列突变导致的功能差异，以改进抑制剂的选择。我们在该数据集中14%的序列中鉴定出导致对某些已知整合酶抑制剂耐药的辅助突变（通常会降低敏感性）。斯坦福HIV-1耐药数据库提供了整合酶耐药突变的补充信息，以推断此类观察结果的分子基础。建模和对接分析表明，突变体对已知化合物的结合减少。对于C亚型临床菌株中具有突变组合的模型，预测的结合值进一步降低。因此，报道了印度南部HIV-1 C亚型临床菌株整合酶基因不同变体中突变后果的分子基础。这些数据在设计、修饰和开发具有代表性且改进的HIV-1整合酶抑制剂方面具有实用价值。
