Human immunodeficiency virus type 1 (HIV-1) neutralizing antibodies are thought be distinguished from nonneutralizing antibodies by their ability to recognize functional gp120/gp41 envelope glycoprotein (Env) trimers. The antibody responses induced by natural HIV-1 infection or by vaccine candidates tested to date consist largely of nonneutralizing antibodies. One might have expected a more vigorous neutralizing response, particularly against virus particles that bear functional trimers. The recent surprising observation that nonneutralizing antibodies can specifically capture HIV-1 may provide a clue relating to this paradox. Specifically, it was suggested that forms of Env, to which nonneutralizing antibodies can bind, exist on virus surfaces. Here, we present evidence that HIV-1 particles bear nonfunctional gp120/gp41 monomers and gp120-depleted gp41 stumps. Using a native electrophoresis band shift assay, we show that antibody-trimer binding predicts neutralization and that the nonfunctional forms of Env may account for virus capture by nonneutralizing antibodies. We hypothesize that these nonfunctional forms of Env on particle surfaces serve to divert the antibody response, helping the virus to evade neutralization.

SignificanceIt is commonly thought that each globular protein has a single 3D structure, or fold, that fosters its function. In contrast, recent studies have identified several fold-switching proteins whose secondary structures can be remodeled in response to cellular stimuli. Although thought to be rare, we found 96 literature-validated fold-switching proteins by exhaustively searching the database of protein structures [Protein Data Bank (PDB)]. Characterizing these proteins led us to hypothesize that their abundance may be underrepresented in the PDB. Thus, we developed a computational method that identifies fold-switching proteins and used it to estimate that 0.5–4% of PDB proteins switch folds. These results suggest that proteins switch folds with significant frequency, which has implications for cell biology, genomics, and human health.

AlphaFold2 has revolutionized protein structure prediction by leveraging sequence information to rapidly model protein folds with atomic-level accuracy. Nevertheless, previous work has shown that these predictions tend to be inaccurate for structurally heterogeneous proteins. To systematically assess factors that contribute to this inaccuracy, we tested AlphaFold2's performance on 98-fold-switching proteins, which assume at least two distinct-yet-stable secondary and tertiary structures. Topological similarities were quantified between five predicted and two experimentally determined structures of each fold-switching protein. Overall, 94% of AlphaFold2 predictions captured one experimentally determined conformation but not the other. Despite these biased results, AlphaFold2's estimated confidences were moderate-to-high for 74% of fold-switching residues, a result that contrasts with overall low confidences for intrinsically disordered proteins, which are also structurally heterogeneous. To investigate factors contributing to this disparity, we quantified sequence variation within the multiple sequence alignments used to generate AlphaFold2's predictions of fold-switching and intrinsically disordered proteins. Unlike intrinsically disordered regions, whose sequence alignments show low conservation, fold-switching regions had conservation rates statistically similar to canonical single-fold proteins. Furthermore, intrinsically disordered regions had systematically lower prediction confidences than either foldswitching or single-fold proteins, regardless of sequence conservation. AlphaFold2's high prediction confidences for fold switchers indicate that it uses sophisticated pattern recognition to search for one most probable conformer rather than protein biophysics to model a protein's structural ensemble. Thus, it is not surprising that its predictions often fail for proteins whose properties are not fully apparent from solved protein structures. Our results emphasize the need to look at protein structure as an ensemble and suggest that systematic examination of fold-switching sequences may reveal propensities for multiple stable secondary and tertiary structures.

A protein backbone has two degrees of conformational freedom per residue, described by its φ,ψ-angles. Accordingly, the energy landscape of a blocked peptide unit can be mapped in two dimensions, as shown by Ramachandran, Sasisekharan, and Ramakrishnan almost half a century ago. With atoms approximated as hard spheres, the eponymous Ramachandran plot demonstrated that steric clashes alone eliminate ¾ of φ,ψ-space, a result that has guided all subsequent work. Here, we show that adding hydrogen-bonding constraints to these steric criteria eliminates another substantial region of φ,ψ-space for a blocked peptide; for conformers within this region, an amide hydrogen is solvent-inaccessible, depriving it of a hydrogen-bonding partner. Yet, this "forbidden" region is well populated in folded proteins, which can provide longer-range intramolecular hydrogen-bond partners for these otherwise unsatisfied polar groups. Consequently, conformational space expands under folding conditions, a paradigm-shifting realization that prompts an experimentally verifiable conjecture about likely folding pathways.protein folding | hydrogen bonding | β-turns | helix nucleation

Folded proteins are assumed to be built upon fixed scaffolds of secondary structure, α-helices and β-sheets. Experimentally determined structures of >58,000 non-redundant proteins support this assumption, though it has recently been challenged by ~100 fold-switching proteins. Though ostensibly rare, these proteins raise the question of how many uncharacterized proteins have shapeshifting–rather than fixed–secondary structures. Here, we use a comparative sequence-based approach to predict fold switching in the universally conserved NusG transcription factor family, one member of which has a 50-residue regulatory subunit experimentally shown to switch between α-helical and β-sheet folds. Our approach predicts that 24% of sequences in this family undergo similar α-helix ⇌ β-sheet transitions. While these predictions cannot be reproduced by other state-of-the-art computational methods, they are confirmed by circular dichroism and nuclear magnetic resonance spectroscopy for 10 out of 10 sequence-diverse variants. This work suggests that fold switching may be a pervasive mechanism of transcriptional regulation in all kingdoms of life.

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Although most proteins conform to the classical one‐structure/one‐function paradigm, an increasing number of proteins with dual structures and functions have been discovered. In response to cellular stimuli, such proteins undergo structural changes sufficiently dramatic to remodel even their secondary structures and domain organization. This “fold‐switching” capability fosters protein multi‐functionality, enabling cells to establish tight control over various biochemical processes. Accurate predictions of fold‐switching proteins could both suggest underlying mechanisms for uncharacterized biological processes and reveal potential drug targets. Recently, we developed a prediction method for fold‐switching proteins using structure‐based thermodynamic calculations and discrepancies between predicted and experimentally determined protein secondary structure (Porter and Looger, Proc Natl Acad Sci U S A 2018; 115:5968–5973). Here we seek to leverage the negative information found in these secondary structure prediction discrepancies. To do this, we quantified secondary structure prediction accuracies of 192 known fold‐switching regions (FSRs) within solved protein structures found in the Protein Data Bank (PDB). We find that the secondary structure prediction accuracies for these FSRs vary widely. Inaccurate secondary structure predictions are strongly associated with fold‐switching proteins compared to equally long segments of non‐fold‐switching proteins selected at random. These inaccurate predictions are enriched in helix‐to‐strand and strand‐to‐coil discrepancies. Finally, we find that most proteins with inaccurate secondary structure predictions are underrepresented in the PDB compared with their alternatively folded cognates, suggesting that unequal representation of fold‐switching conformers within the PDB could be an important cause of inaccurate secondary structure predictions. These results demonstrate that inconsistent secondary structure predictions can serve as a useful preliminary marker of fold switching.

Protein domains are conspicuous structural units in globular proteins, and their identification has been a topic of intense biochemical interest dating back to the earliest crystal structures. Numerous disparate domain identification algorithms have been proposed, all involving some combination of visual intuition and/or structurebased decomposition. Instead, we present a rigorous, thermodynamically-based approach that redefines domains as cooperative chain segments. In greater detail, most small proteins fold with high cooperativity, meaning that the equilibrium population is dominated by completely folded and completely unfolded molecules, with a negligible subpopulation of partially folded intermediates. Here, we redefine structural domains in thermodynamic terms as cooperative folding units, based on m-values, which measure the cooperativity of a protein or its substructures. In our analysis, a domain is equated to a contiguous segment of the folded protein whose mvalue is largely unaffected when that segment is excised from its parent structure. Defined in this way, a domain is a self-contained cooperative unit; i.e., its cooperativity depends primarily upon intrasegment interactions, not intersegment interactions. Implementing this concept computationally, the domains in a large representative set of proteins were identified; all exhibit consistency with experimental findings. Specifically, our domain divisions correspond to the experimentally determined equilibrium folding intermediates in a set of nine proteins. The approach was also proofed against a representative set of 71 additional proteins, again with confirmatory results. Our reframed interpretation of a protein domain transforms an indeterminate structural phenomenon into a quantifiable molecular property grounded in solution thermodynamics.protein folding | protein structure | protein architecture | protein parsing D omains are visually arresting protein substructures with an influential history in protein biochemistry (1). These familiar, self-contained structural units were first noticed in some of the earliest solved protein structures (2, 3) and soon came to be recognized as common features of protein architecture (4).Dissecting proteins into their constituent domains provides a simple, intuitive approach to classifying protein structure, a molecular application of the time-honored principle of "carving nature at its joints" (5). Many structure-based computer algorithms have been devised to parse the ever-increasing number of solved proteins into discrete units; a highly abbreviated sample includes (6-13). Today, CATH (14) and SCOP (15) are the two most widely used domain classifications. Both are based on computational algorithms but rely ultimately on the human eye as the final arbiter of domain boundaries.However, seeing can be deceiving. The dependence on visual intuition introduces an unavoidable element of ambiguity into procedures for domain recognition. The most enduring domain definition, "potentially independent, stable folding uni...