HIV‐1 protease function and structure studies with the simplicial neighborhood analysis of protein packing method

Abstract

The Simplicial Neighborhood Analysis of Protein Packing (SNAPP) method was used to predict the effect of mutagenesis on the enzymatic activity of the HIV-1 protease (HIVP). SNAPP relies on a four-body statistical scoring function derived from the analysis of spatially nearest neighbor residue compositional preferences in a diverse and representative subset of protein structures from the Protein Data Bank. The method was applied to the analysis of HIVP mutants with residue substitutions in the hydrophobic core as well as at the interface between the two protease monomers. Both wild type and tethered structures were employed in the calculations. We obtained a strong correlation, with R2 as high as 0.96, between ΔSNAPP score (i.e., the difference in SNAPP scores between wild type and mutant proteins) and the protease catalytic activity for tethered structures. A weaker but significant correlation was also obtained for non-tethered structures as well. Our analysis identified residues both in the hydrophobic core and at the dimeric interface (DI) that are very important for the protease function. This study demonstrates a potential utility of the SNAPP method for rational design of mutagenesis studies and protein engineering.

Modeling Cell Proliferation Activity of Human Interleukin-3 Upon Single Residue Replacements

“…Although amino acids positions in the neighborhood are all structurally near their shared residue in 3D Euclidean space, they are often distant from the shared residue in primary sequence. For an amino acid at primary sequence position i in the protein, the residue environment score q i is defined as the sum of scores of all tetrahedral simplices that share its Cα vertex (Carter et al, 2001, Zhang et al, 2008.…”

“…However, the only environment scores that are actually altered occur at the mutated position j and at those that form its neighborhood in the tessellation. The difference R mut = Q mut -Q wt = < EC 1 , EC 2 , EC 3 , …, EC N > is a sparse mutant vector that quantifies relative environmental changes or perturbations EC i = q i,mut -q i,wt at every residue position i in the protein due to the mutation (Carter et al, 2001, Zhang et al, 2008. Since the only nonzero EC components of R mut occur at mutated position j and at positions in its neighborhood, important local effects of a mutation are effectively modelled; however, long-range consequences at structurally distant protein positions are excluded ( Figure 2C).…”

An automated workflow by using KNIME Analytical Platform: a case study for modelling and predicting HIV-1 protease inhibitors

“…Studies have shown that the life cycle of the HIV-1 is truly depends on the key enzyme, HIV-1 protease (HIVP) [5,6] .…”

Another look at the conditions for the extraction of protein knowledge‐based potentials

“…Since then, a wide variety of KBPs have been introduced using different levels of geometry resolution, different terms contributing to the potential energy, different procedures to relate the energies to the observed frequencies, different levels of applicability (from all proteins in general to only a specific protein family), and for different purposes ranging from native fold recognition to protein stability and dynamic simulations 8–54. In particular, many variations of Sippl's atomic‐level potential have been obtained 1, 22, 23, 32, 37, 45–47.…”

“…In particular, many variations of Sippl's atomic‐level potential have been obtained 1, 22, 23, 32, 37, 45–47. Multibody potentials introduced by Gan et al ., in the form of four‐body residue interactions, are still actively under development 34, 35, 51–53, 55. Orientation dependent KBPs for Hydrogen bonds have been obtained by Kortemme et al .,39 and more general residue pairwise interactions with orientation dependencies have been derived by Buchete, et al 42.…”