Effect of internal cleavage site mutations in human immunodeficiency virus type 1 capsid protein on its structure and function

Different Mutation Tolerance of Lentiviral (HIV-1) and Deltaretroviral (BLV and HTLV) Protease Precursors

The bovine leukemia virus (BLV) and the human T-lymphothropic viruses (HTLVs) are members of the deltaretrovirus genus of Retroviridae family. An essential event of the retroviral life cycle is the processing of the polyproteins by the viral protease (PR); consequently, these enzymes became important therapeutic targets of the anti-retroviral drugs. As compared to human immunodeficiency viruses (HIVs), the deltaretroviruses have a different replication strategy, as they replicate predominantly in the DNA form, by forcing the infected cell to divide, unlike HIV-1, which replicates mainly by producing a vast number of progeny virions and by reinfection. Due to bypassing the error-prone reverse transcription step of replication, the PRs of deltaretroviruses did not undergo such extensive evolution as HIV PRs and remained more highly conserved. In this work, we studied the abilities of wild-type and modified BLV, HTLV (type 1, 2 and 3), and HIV-1 PRs (fused to an N-terminal MBP tag) for self-processing. We designed a cleavage site mutant MBP-fused BLV PR precursor as well, this recombinant enzyme was unable for self-proteolysis, the MBP fusion tag decreased its catalytic efficiency but showed an unusually low K_i for the IB-268 protease inhibitor. Our results show that the HTLV and BLV deltaretrovirus PRs exhibit lower mutation tolerance as compared to HIV-1 PR, and are less likely to retain their activity upon point mutations at various positions, indicating a higher flexibility of HIV-1 PR in tolerating mutations under selective pressure.

Exploring Energy Profiles of Protein-Protein Interactions (PPIs) Using DFT Method

Background:

Large-scale energy landscape characterization of protein-protein interactions (PPIs) is important to understand the interaction mechanism and protein-protein docking methods. The experimental methods for detecting energy landscapes are tedious and the existing computational methods require longer simulation time.

Objective:

The objective of the present work is to ascertain the energy profiles at the interface regions in a rapid manner to analyze the energy landscape of protein-protein interactions.

Methods:

The atomic coordinates obtained from the X-ray and NMR spectroscopy data are considered as inputs to compute cumulative energy profiles for experimentally validated protein-protein complexes. The energies computed by the program were comparable to the standard molecular dynamics simulations.

Results:

The PPI Profiler not only enables rapid generation of energy profiles but also facilitates the detection of hot spot residue atoms involved therein.

Conclusion:

The hotspot residues and their computed energies matched with the experimentally determined hot spot residues and their energies which correlated well by employing the MM/GBSA method. The proposed method can be employed to scan entire proteomes across species at an atomic level to study the key PPI interactions.