Broadly Neutralizing Antibody PGT121 Allosterically Modulates CD4 Binding via Recognition of the HIV-1 gp120 V3 Base and Multiple Surrounding Glycans

Abstract

New broad and potent neutralizing HIV-1 antibodies have recently been described that are largely dependent on the gp120 N332 glycan for Env recognition. Members of the PGT121 family of antibodies, isolated from an African donor, neutralize ∼70% of circulating isolates with a median IC50 less than 0.05 µg ml−1. Here, we show that three family members, PGT121, PGT122 and PGT123, have very similar crystal structures. A long 24-residue HCDR3 divides the antibody binding site into two functional surfaces, consisting of an open face, formed by the heavy chain CDRs, and an elongated face, formed by LCDR1, LCDR3 and the tip of the HCDR3. Alanine scanning mutagenesis of the antibody paratope reveals a crucial role in neutralization for residues on the elongated face, whereas the open face, which accommodates a complex biantennary glycan in the PGT121 structure, appears to play a more secondary role. Negative-stain EM reconstructions of an engineered recombinant Env gp140 trimer (SOSIP.664) reveal that PGT122 interacts with the gp120 outer domain at a more vertical angle with respect to the top surface of the spike than the previously characterized antibody PGT128, which is also dependent on the N332 glycan. We then used ITC and FACS to demonstrate that the PGT121 antibodies inhibit CD4 binding to gp120 despite the epitope being distal from the CD4 binding site. Together, these structural, functional and biophysical results suggest that the PGT121 antibodies may interfere with Env receptor engagement by an allosteric mechanism in which key structural elements, such as the V3 base, the N332 oligomannose glycan and surrounding glycans, including a putative V1/V2 complex biantennary glycan, are conformationally constrained.

Cleavage strongly influences whether soluble HIV-1 envelope glycoprotein trimers adopt a native-like conformation

“…The cleaved SOSIP.R6 trimers were regular and homogeneous ( Fig. 4 A and B), consistent with earlier reports of the same construct (there designated BG505 SOSIP.664 gp140) (17)(18)(19). A semiquantitative analysis of the class averages showed that ∼100% of the SOSIP.R6 trimer images resembled virion-associated, native trimers from HIV-1 BaL (EMDB-5019) (Fig.…”

“…Thus, cleaved, SOSIP-stabilized BG505 gp140 trimers [SOSIP.R6; referred to elsewhere as "SOSIP.664" (17-19)] are highly homogeneous and their configurations resemble native Env spikes, as judged by negative-stain EM (17)(18)(19) (Fig. 4 A and B).…”

“…Cleavage is not, however, sufficient for a cleaved, soluble trimer to be usefully stable, as these entities rapidly disintegrate unless they also include the stabilizing SOS and I559P changes. The resulting soluble, cleaved, SOSIP-stabilized trimers are highly homogeneous, resemble native Env spikes, and are useful for structural (17)(18)(19) and immunogenicity studies. The cryo-EM and X-ray diffraction structures of the BG505 SOSIP.664 gp140 trimers at ∼5 Å resolution show they adopt the prefusion form of Env (35,36).…”

“…Additional modifications have improved their stability, homogeneity, and antigenicity (15)(16)(17). Our current design, based on the BG505 subtype A env gene, yields SOSIP.664 trimers that mimic native, virion-associated Env spikes antigenically and when viewed by negative-stain electron microscopy (EM) (17)(18)(19).…”

Antigenicity-defined conformations of an extremely neutralization-resistant HIV-1 envelope spike

“…Based on an analysis of 50 bnAbs, we first defined mutational patterns that are statistically associated with resistance and sensitivity, using phylogenetically corrected methods (17), for four classes of bnAbs: the CD4 binding site; a trimer-specific, glycan-dependent V1V2 region; an N332-glycan-dependent V3 region; and the membrane proximal external region (MPER). The CH120.6 sequence retained key epitope-defining patterns of specific amino acid residues and N-linked glycosylation sites in these bnAb epitopes (18)(19)(20). We then used these signature patterns to predict the relative sensitivity of CH120.6 to the different antibodies shown in Table S2 using the machine-learning strategy Random Forests (21) implemented in the Python package scikitlearn (22).…”