In Silico Identification and Molecular Validation of Putative Antimicrobial Peptides for HIV Therapy

Abstract

Objective: Despite the effort to reduce the rate of HIV infection, AIDS still remains the major cause of death around the world, predominantly in Sub-Sahara Africa. Neither a cure, nor an HIV vaccine has been found to date and the disease can only be managed by using High Active Antiretroviral Therapy (HAART). The need for non-toxic regiments has brought about the necessity for additional HIV treatment to lower mortality rates. Antimicrobial Peptides (AMPs) had proven to be a promising therapeutic agent against HIV. The aim of this research was to identify AMPs, which binds gp120 at the area where gp120 interacts with CD4+, to prevent HIV invasion and HIV replication. Method: Putative AMPs were identified using an In Silico mathematical algorithm, Profile Hidden Markov Models (HMMER). The AMPS 3-D structures was carried out using I-TASSER and the modelled AMPs were docked against the HIV protein gp120 using PATCHDOCK. Subsequently, molecular method was used to show the anti-HIV ability of these putative to validate by inhibiting HIV-1 replication. Results: The In Silico results showed that 30 putative anti-HIV AMPs were identified. Furthermore, out of the 10 best ranked putative AMPs, based on their E-value, selected for In Silico docking, two AMPs proved to inhibit HIV-1 NL4- 3 with maximal effective concentration (EC50) values of 37.5 μg/ml and 93.75 μg/ml respectively. This result looks promising since 150 μg/ml AMPs could not achieved 80% toxicity of the human T cells, thus high Therapeutics Index (TI) might be obtained if 50% cytotoxic concentration (CC50) is established. Conclusion: The ability of these AMPs to inhibit HIV replication justifies the usage of HMMER in design and discovery. Additionally, these AMPs pave the way for the design of anti-HIV peptide-based drugs.