Electrostatic Similarity Determination Using Multiresolution Analysis

Engineering pre-SUMO4 as efficient substrate of SENP2

SUMOylation, one of the most important protein post-translational modifications, plays critical roles in a variety of physiological and pathological processes. SENP (Sentrin/SUMO-specific protease), a family of SUMO-specific proteases, is responsible for the processing of pre-SUMO and removal of SUMO from conjugated substrates. SUMO4, the latest discovered member in the SUMO family, has been found as a type 1 diabetes susceptibility gene and its maturation is not understood so far. Despite the 14 amino acid differences between pre-SUMO4 and SUMO2, pre-SUMO4 is not processed by SENP2 but pre-SUMO2 does. A novel interdisciplinary approach involving computational modeling and a FRET-based protease assay was taken to engineer pre-SUMO4 as a substrate of SENP2. Given the difference in net charge between pre-SUMO4 and pre-SUMO2, the computational framework analysis of electrostatic similarities of proteins was applied to determine the contribution of each ionizable amino acid in a model of SENP2-(pre-SUMO4) binding, and to propose pre-SUMO4 mutations. The specificities of the SENP2 toward different pre-SUMO4 mutants were determined using a quantitative FRET assay by characterizing the catalytic efficiencies (kcat/KM). A single amino acid mutation made pre-SUMO4 amenable to SENP2 processing and a combination of two amino acid mutations made it highly accessible as SENP2 substrate. The combination of the two approaches provides a powerful protein engineering tool for future SUMOylation studies.

Insights into the structure, correlated motions, and electrostatic properties of two HIV-1 gp120 V3 loops

The V3 loop of the glycoprotein 120 (gp120) is a contact point for cell entry of HIV-1 leading to infection. Despite sequence variability and lack of specific structure, the highly flexible V3 loop possesses a well-defined role in recognizing and selecting cell-bound coreceptors CCR5 and CXCR4 through a mechanism of charge complementarity. We have performed two independent molecular dynamics (MD) simulations to gain insights into the dynamic character of two V3 loops with slightly different sequences, but significantly different starting crystallographic structures. We have identified highly populated trajectory-specific salt bridges between oppositely charged stem residues Arg9 and Glu25 or Asp29. The two trajectories share nearly identical correlated motions within the simulations, despite their different overall structures. High occupancy salt bridges play a key role in the major cross-correlated motions in both trajectories, and may be responsible for transient structural stability in preparation for coreceptor binding. In addition, the two V3 loops visit conformations with similarities in spatial distributions of electrostatic potentials, despite their inherent flexibility, which may play a role in coreceptor recognition. It is plausible that cooperativity between overall electrostatic potential, charged residue interactions, and correlated motions could be associated with a coreceptor selection and binding.

Clustering of HIV-1 Subtypes Based on gp120 V3 Loop electrostatic properties

BACKGROUND

The V3 loop of the glycoprotein gp120 of HIV-1 plays an important role in viral entry into cells by utilizing as coreceptor CCR5 or CXCR4, and is implicated in the phenotypic tropisms of HIV viruses. It has been hypothesized that the interaction between the V3 loop and CCR5 or CXCR4 is mediated by electrostatics. We have performed hierarchical clustering analysis of the spatial distributions of electrostatic potentials and charges of V3 loop structures containing consensus sequences of HIV-1 subtypes.

RESULTS

Although the majority of consensus sequences have a net charge of +3, the spatial distribution of their electrostatic potentials and charges may be a discriminating factor for binding and infectivity. This is demonstrated by the formation of several small subclusters, within major clusters, which indicates common origin but distinct spatial details of electrostatic properties. Some of this information may be present, in a coarse manner, in clustering of sequences, but the spatial details are largely lost. We show the effect of ionic strength on clustering of electrostatic potentials, information that is not present in clustering of charges or sequences. We also make correlations between clustering of electrostatic potentials and net charge, coreceptor selectivity, global prevalence, and geographic distribution. Finally, we interpret coreceptor selectivity based on the N6X7T8|S8X9 sequence glycosylation motif, the specific positive charge location according to the 11/24/25 rule, and the overall charge and electrostatic potential distribution.

CONCLUSIONS

We propose that in addition to the sequence and the net charge of the V3 loop of each subtype, the spatial distributions of electrostatic potentials and charges may also be important factors for receptor recognition and binding and subsequent viral entry into cells. This implies that the overall electrostatic potential is responsible for long-range recognition of the V3 loop with coreceptors CCR5/CXCR4, whereas the charge distribution contributes to the specific short-range interactions responsible for the formation of the bound complex. We also propose a scheme for coreceptor selectivity based on the sequence glycosylation motif, the 11/24/25 rule, and net charge.