Molecular features related to HIV integrase inhibition obtained from structure- and ligand-based approaches

Structural effects of HIV-1 subtype C integrase mutations on the activity of integrase strand transfer inhibitors in South African patients

HIV-1 integrase enzyme is responsible for the integration of viral DNA into the host genomic DNA. Integrase strand transfer inhibitors (INSTIs) are highly potent antiretroviral agents that inhibit this process, and are internationally approved for the treatment of both naïve and treated HIV-1 patients. However, their long-term efficacy is threatened by development of drug resistance strains resulting in resistance mutations. This work aimed to examine the effect of INSTI resistance-associated mutations (RAMs) and polymorphisms on the structure of HIV-1 subtype C (HIV-1C) integrase. Genetic analysis was performed on seven HIV-1C infected individuals with virologic failure after at least 6 months of INSTI-based antiretroviral therapy, presenting at the King Edward VIII hospital in Durban, South Africa. These were compared with sequences from 41 INSTI-naïve isolates. Integrase structures of selected isolates were modeled on the SWISS model online server. Molecular docking and dynamics simulations were also conducted using AutoDock-Vina and AMBER 18 force fields, respectively. Only one INSTI-treated isolate (14.28%) harboured major mutations (G140A + Q148R) as well as the E157Q minor mutation. Interestingly, S119T and V151I were only found in patients failing raltegravir (an INSTI drug). Molecular modeling and docking showed that RAMs and polymorphisms associated with INSTI-based therapy affect protein stability and this is supported by their weakened hydrogen-bond interactions compared to the wild-type. To the best of our knowledge, this is the first study to identify a double mutant in the 140's loop region from South African HIV-1C isolates and study its effects on Raltegravir, Elvitegravir, and Dolutegravir binding.Communicated by Ramaswamy H. Sarma.

Development of HIV-1 integrase inhibitors: recent molecular modeling perspectives

Of the three viral enzymes essential to HIV replication, HIV-1 integrase (IN) is gaining popularity as a target for the antiviral therapy of AIDS. Substantial work focusing on IN has been done over the past three decades, which has facilitated and led to the approval of three drugs. Here, we discuss in detail the development of IN inhibitors between January 2012 and May 2014, with a particular focus on molecular simulation. We highlight controversial aspects of computational drug design and refer to alternative practices where appropriate. The analysis of these computational approaches provides some useful clues to the possible future discovery of novel IN inhibitors.

Understanding electrostatic and steric requirements related to hypertensive action of AT(1) antagonists using molecular modeling techniques

AT1 receptor is an interesting biological target involved in several important diseases, such as blood hypertension and cardiovascular pathologies. In this study we investigated the main electrostatic and steric features of a series of AT1 antagonists related to hypertensive activity using structure and ligand-based strategies (docking and CoMFA). The generated 3D model had good internal and external consistency and was used to predict the potency of an external test set. The predicted values of pIC50 are in good agreement with the experimental results of biological activity, indicating that the 3D model can be used to predict the biological property of untested compounds. The electrostatic and steric CoMFA maps showed molecular recognition patterns, which were analyzed with structure-based molecular modeling studies (docking). The most and the least potent compounds docked into the AT1 binding site were subjected to molecular dynamics simulations with the aim to verify the stability and the flexibility of the ligand-receptor interactions. These results provided valuable insights on the electronic/structural requirements to design novel AT1 antagonists.