Multi-constraint computational design suggests that native sequences of germline antibody H3 loops are nearly optimal for conformational flexibility

Defining and Studying B Cell Receptor and TCR Interactions

BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.

Conformational plasticity of the HIV-1 gp41 immunodominant region is recognized by multiple non-neutralizing antibodies

The early humoral immune response to acute HIV-1 infection is largely non-neutralizing. The principal target of these antibodies is the primary immunodominant region (PID) on the gp41 fusion protein. The PID is a highly conserved 15-residue region displayed on the surface of HIV-1 virions. In this study, we analyzed the humoral determinants of HIV-1 gp41 PID binding using biophysical, structural, and computational methods. In complex with a patient-derived near-germline antibody fragment, the PID motif adopts an elongated random coil, whereas the PID bound to affinity-matured Fab adopts a strand-turn-helix conformation. Molecular dynamics simulations showed that the PID is structurally plastic suggesting that the PID can form an ensemble of structural states recognized by various non-neutralizing antibodies, facilitating HIV-1 immunodominance observed in acute and chronic HIV-1 infections. An improved understanding of how the HIV-1 gp41 PID misdirects the early humoral response should guide the development of an effective HIV-1 vaccine.

The 15-amino-acid primary immunodominant (PID) region on HIV-1 gp41 adopts an ensemble of conformational states. This conformational plasticity is suggested to misdirect the early humoral immune response.

Selective Recognition of Carbohydrate Antigens by Germline Antibodies Isolated from AID Knockout Mice

Germline antibodies, the initial set of antibodies produced by the immune system, are critical for host defense, and information about their binding properties can be useful for designing vaccines, understanding the origins of autoantibodies, and developing monoclonal antibodies. Numerous studies have found that germline antibodies are polyreactive with malleable, flexible binding pockets. While insightful, it remains unclear how broadly this model applies, as there are many families of antibodies that have not yet been studied. In addition, the methods used to obtain germline antibodies typically rely on assumptions and do not work well for many antibodies. Herein, we present a distinct approach for isolating germline antibodies that involves immunizing activation-induced cytidine deaminase (AID) knockout mice. This strategy amplifies antigen-specific B cells, but somatic hypermutation does not occur because AID is absent. Using synthetic haptens, glycoproteins, and whole cells, we obtained germline antibodies to an assortment of clinically important tumor-associated carbohydrate antigens, including Lewis Y, the Tn antigen, sialyl Lewis C, and Lewis X (CD15/SSEA-1). Through glycan microarray profiling and cell binding, we demonstrate that all but one of these germline antibodies had high selectivity for their glycan targets. Using molecular dynamics simulations, we provide insights into the structural basis of glycan recognition. The results have important implications for designing carbohydrate-based vaccines, developing anti-glycan monoclonal antibodies, and understanding antibody evolution within the immune system.

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs) are tremendous, the design and discovery of new candidates remain a time and cost-intensive endeavor. In this regard, progress in the generation of data describing antigen binding and developability, computational methodology, and artificial intelligence may pave the way for a new era of in silico on-demand immunotherapeutics design and discovery. Here, we argue that the main necessary machine learning (ML) components for an in silico mAb sequence generator are: understanding of the rules of mAb-antigen binding, capacity to modularly combine mAb design parameters, and algorithms for unconstrained parameter-driven in silico mAb sequence synthesis. We review the current progress toward the realization of these necessary components and discuss the challenges that must be overcome to allow the on-demand ML-based discovery and design of fit-for-purpose mAb therapeutic candidates.

Protein Engineering: Advances in Phage Display for Basic Science and Medical Research

Functional Protein Engineering became the hallmark in biomolecule manipulation in the new millennium, building on and surpassing the underlying structural DNA manipulation and recombination techniques developed and employed in the last decades of 20th century. Because of their prominence in almost all biological processes, proteins represent extremely important targets for engineering enhanced or altered properties that can lead to improvements exploitable in healthcare, medicine, research, biotechnology, and industry. Synthetic protein structures and functions can now be designed on a computer and/or evolved using molecular display or directed evolution methods in the laboratory. This review will focus on the recent trends in protein engineering and the impact of this technology on recent progress in science, cancer- and immunotherapies, with the emphasis on the current achievements in basic protein research using synthetic antibody (sABs) produced by phage display pipeline in the Kossiakoff laboratory at the University of Chicago (KossLab). Finally, engineering of the highly specific binding modules, such as variants of Streptococcal protein G with ultra-high orthogonal affinity for natural and engineered antibody scaffolds, and their possible applications as a plug-and-play platform for research and immunotherapy will be described.

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.

Local and Global Rigidification Upon Antibody Affinity Maturation

During the affinity maturation process the immune system produces antibodies with higher specificity and activity through various rounds of somatic hypermutations in response to an antigen. Elucidating the affinity maturation process is fundamental in understanding immunity and in the development of biotherapeutics. Therefore, we analyzed 10 pairs of antibody fragments differing in their specificity and in distinct stages of affinity maturation using metadynamics in combination with molecular dynamics (MD) simulations. We investigated differences in flexibility of the CDR-H3 loop and global changes in plasticity upon affinity maturation. Among all antibody pairs we observed a substantial rigidification in flexibility and plasticity reflected in a substantial decrease of conformational diversity. To visualize and characterize these findings we used Markov-states models to reconstruct the kinetics of CDR-H3 loop dynamics and for the first time provide a method to define and localize surface plasticity upon affinity maturation.

[Semi-rational Design of Target-binding Small Proteins for Cancer Treatment]

Small proteins that have a high affinity for cancer cell surface markers can be promising cheap alternatives to antibodies (antibody mimetics). Various types of antibody mimetics have thus been extensively developed. We recently found that a target-binding peptide binds to its target molecule more strongly when it is structurally constrained. To apply this finding to the development of chemically synthesizable small antibody mimetics, we have established an efficient method of creating such proteins, named fluctuation-regulated affinity proteins (FLAPs). To identify desirable scaffolds, first, 13 human proteins (46-104 aa) were selected from the Protein Data Bank. Then, thirteen graft acceptor (GA) sites that efficiently immobilize the grafted peptide structure were identified from six small protein scaffolds using molecular dynamics simulation. To assess the designed antibody mimetics in vitro, human epidermal growth factor receptor 2 (HER2)-binding peptides were selected from the anti-HER2 antibody drugs trastuzumab and pertuzumab by calculating the binding energy, and these were then grafted into the GA sites of scaffolds to create 65 FLAP candidates. The FLAP candidates were expressed in bacteria as fusion proteins with Renilla luciferase (Rluc), and their relative binding affinity to HER2 was easily determined by measuring the Rluc bioluminescence intensity without protein purification. Finally, four out of the 65 showed specific binding to HER2 with a dissociation constant (K_D) of 24-65 nM, and these were used for the detection of HER2-expressing cancer cells. Our design strategy will promote the development of antibody mimetics for the effective treatment of cancers and other diseases.

Design Strategy to Create Antibody Mimetics Harbouring Immobilised Complementarity Determining Region Peptides for Practical Use

Monoclonal antibodies (mAbs) are attractive therapeutics for treating a wide range of human disorders, and bind to the antigen through their complementarity-determining regions (CDRs). Small stable proteins containing structurally retained CDRs are promising alternatives to mAbs. In this report, we present a method to create such proteins, named fluctuation-regulated affinity proteins (FLAPs). Thirteen graft acceptor (GA) sites that efficiently immobilise the grafted peptide structure were initially selected from six small protein scaffolds by computational identification. Five CDR peptides extracted by binding energy calculations from mAbs against breast cancer marker human epithelial growth factor receptor type 2 (HER2) were then grafted to the selected scaffolds. The combination of five CDR peptides and 13 GA sites in six scaffolds revealed that three of the 65 combinations showed specific binding to HER2 with dissociation constants (K_D) of 270–350 nM in biolayer interferometry and 24–65 nM in ELISA. The FLAPs specifically detected HER2-overexpressing cancer cells. Thus, the present strategy is a promising and practical method for developing small antibody mimetics.

Structure and Dynamics of Stacking Interactions in an Antibody Binding Site

For years, antibodies (Abs) have been used as a paradigm for understanding how protein structure contributes to molecular recognition. However, with the ability to evolve Abs that recognize specific chromophores, they also have great potential as models for how protein dynamics contribute to molecular recognition. We previously raised murine Abs to different chromophores and, with the use of three-pulse photon echo peak shift spectroscopy, demonstrated that the immune system is capable of producing Abs with widely varying flexibility. We now report the characterization of the complexes formed between two Abs, 5D11 and 10A6, and the chromophoric ligand that they were evolved to recognize, 8-methoxypyrene-1,3,6-trisulfonic acid (MPTS). The sequences of the Ab genes indicate that they evolved from a common precursor. We also used a variety of spectroscopic methods to probe the photophysics and dynamics of the Ab-MPTS complexes and found that they are similar to each other but distinct from previously characterized anti-MPTS Abs. Structural studies revealed that this difference likely results from a unique mode of binding in which MPTS is sandwiched between the side chain of Phe^H98, which interacts with the chromophore via T-stacking, and the side chain of Trp^L91, which interacts with the chromophore via parallel stacking. The T-stacking interaction appears to mediate relaxation on the picosecond time scale, while the parallel stacking appears to mediate relaxation on an ultrafast, femtosecond time scale, which dominates the response. The anti-MPTS Abs thus not only demonstrate the simultaneous use of the two limiting modes of stacking for molecular recognition, but also provide a unique opportunity to characterize how dynamics might contribute to molecular recognition. Both types of stacking are common in proteins and protein complexes where they may similarly contribute to dynamics and molecular recognition.

Human adaptive immune receptor repertoire analysis-Past, present, and future

The genes encoding adaptive immune antigen receptors, namely the immunoglobulins expressed in membrane-bound or secreted forms by B cells, and the cell surface T cell receptors, are unique in human biology because they are generated by combinatorial rearrangement of the genomic DNA. The diversity of receptors so generated in populations of lymphocytes enables the human immune system to recognize antigens expressed by pathogens, but also underlies the pathological specificity of autoimmune diseases and the mistargeted immunity in allergies. Several recent technological developments, foremost among them the invention of high-throughput DNA sequencing instruments, have enabled much deeper and thorough evaluation of clones of human B cells and T cells and the antigen receptors they express during physiological and pathogenic immune responses. The evolutionary struggles between host adaptive immune responses and populations of pathogens are now open to greater scrutiny, elucidation of the underlying reasons for successful or failed immunity, and potential predictive modeling, than ever before. Here we give an overview of the foundations, recent progress, and future prospects in this dynamic area of research.

Multistate design of influenza antibodies improves affinity and breadth against seasonal viruses

Influenza is an annual threat to global public health, in part because of constant antigenic drift that facilitates evasion of the antibody response. Rapid changes in the influenza HA protein make it difficult for an antibody to achieve broad activity against different virus subtypes. We developed a computational method that can optimize an antibody sequence to be robust against seasonal variation. As a proof of concept, we tested this method by redesigning a known antibody against a set of diverse HA antigens and showed that the variant redesigned antibodies have improved activity against the virus panel, as predicted. This work shows that computational design can improve naturally occurring antibodies for recognition of different virus strains.

Influenza is a yearly threat to global public health. Rapid changes in influenza surface proteins resulting from antigenic drift and shift events make it difficult to readily identify antibodies with broadly neutralizing activity against different influenza subtypes with high frequency, specifically antibodies targeting the receptor binding domain (RBD) on influenza HA protein. We developed an optimized computational design method that is able to optimize an antibody for recognition of large panels of antigens. To demonstrate the utility of this multistate design method, we used it to redesign an antiinfluenza antibody against a large panel of more than 500 seasonal HA antigens of the H1 subtype. As a proof of concept, we tested this method on a variety of known antiinfluenza antibodies and identified those that could be improved computationally. We generated redesigned variants of antibody C05 to the HA RBD and experimentally characterized variants that exhibited improved breadth and affinity against our panel. C05 mutants exhibited improved affinity for three of the subtypes used in design by stabilizing the CDRH3 loop and creating favorable electrostatic interactions with the antigen. These mutants possess increased breadth and affinity of binding while maintaining high-affinity binding to existing targets, surpassing a major limitation up to this point.

Characterizing the Diversity of the CDR-H3 Loop Conformational Ensembles in Relationship to Antibody Binding Properties

We present an approach to assess antibody CDR-H3 loops according to their dynamic properties using molecular dynamics simulations. We selected six antibodies in three pairs differing substantially in their individual promiscuity respectively specificity. For two pairs of antibodies crystal structures are available in different states of maturation and used as starting structures for the analyses. For a third pair we chose two antibody CDR sequences obtained from a synthetic library and predicted the respective structures. For all three pairs of antibodies we performed metadynamics simulations to overcome the limitations in conformational sampling imposed by high energy barriers. Additionally, we used classic molecular dynamics simulations to describe nano- to microsecond flexibility and to estimate up to millisecond kinetics of captured conformational transitions. The methodology represents the antibodies as conformational ensembles and allows comprehensive analysis of structural diversity, thermodynamics of conformations and kinetics of structural transitions. Referring to the concept of conformational selection we investigated the link between promiscuity and flexibility of the antibodies' binding interfaces. The obtained detailed characterization of the binding interface clearly indicates a link between structural flexibility and binding promiscuity for this set of antibodies.

Conformational changes in antibody Fab fragments upon binding and their consequences on the performance of docking algorithms

BACKGROUND

The existence of conformational changes in antibodies upon binding has been previously established. However, existing analyses focus on individual cases and no quantitative study provides a more global view of potential moves and repacking, especially on recent data. The present study focuses on analyzing the conformational changes in various antibodies upon binding, providing quantitative observations to be exploited for antibody-related modeling.

METHODS

Cartesian and dihedral Root-Mean-Squared Deviations were calculated for different subparts of 27 different antibodies, for which X-ray structures in the bound and unbound states are available. Elbow angle variations were also calculated. Previously reported results of four docking algorithms were condensed into one score giving overall docking success for each of 16 antibody-antigen cases.

RESULTS

Very diverse movements are observed upon binding. While many loops stay very rigid, several others display side-chain repacking or backbone rearrangements, or both, at many different levels. Large conformational changes restricted to one or more antibody hypervariable loops were found to be a better indicator of docking difficulty than overall conformational variation at the antibody-antigen interface. However, the failure of docking algorithms on some almost-rigid cases shows that scoring is still a major bottleneck in docking pose prediction.

CONCLUSIONS

This study is aimed to help scientists working on antibody analysis and design by giving insights into the nature and the extent of conformational changes at different levels upon antigen binding.

Repertoire Analysis of Antibody CDR-H3 Loops Suggests Affinity Maturation Does Not Typically Result in Rigidification

Antibodies can rapidly evolve in specific response to antigens. Affinity maturation drives this evolution through cycles of mutation and selection leading to enhanced antibody specificity and affinity. Elucidating the biophysical mechanisms that underlie affinity maturation is fundamental to understanding B-cell immunity. An emergent hypothesis is that affinity maturation reduces the conformational flexibility of the antibody's antigen-binding paratope to minimize entropic losses incurred upon binding. In recent years, computational and experimental approaches have tested this hypothesis on a small number of antibodies, often observing a decrease in the flexibility of the complementarity determining region (CDR) loops that typically comprise the paratope and in particular the CDR-H3 loop, which contributes a plurality of antigen contacts. However, there were a few exceptions and previous studies were limited to a small handful of cases. Here, we determined the structural flexibility of the CDR-H3 loop for thousands of recent homology models of the human peripheral blood cell antibody repertoire using rigidity theory. We found no clear delineation in the flexibility of naïve and antigen-experienced antibodies. To account for possible sources of error, we additionally analyzed hundreds of human and mouse antibodies in the Protein Data Bank through both rigidity theory and B-factor analysis. By both metrics, we observed only a slight decrease in the CDR-H3 loop flexibility when comparing affinity matured antibodies to naïve antibodies, and the decrease was not as drastic as previously reported. Further analysis, incorporating molecular dynamics simulations, revealed a spectrum of changes in flexibility. Our results suggest that rigidification may be just one of many biophysical mechanisms for increasing affinity.

The Unusual Genetics and Biochemistry of Bovine Immunoglobulins

Antibodies are the key circulating molecules that have evolved to fight infection by the adaptive immune system of vertebrates. Typical antibodies of most species contain six complementarity-determining regions (CDRs), where the third CDR of the heavy chain (CDR H3) has the greatest diversity and often makes the most significant contact with antigen. Generally, the process of V(D)J recombination produces a vast repertoire of antibodies; multiple V, D, and J gene segments recombine with additional junctional diversity at the V-D and D-J joints, and additional combinatorial possibilities occur through heavy- and light-chain pairing. Despite these processes, the overall structure of the resulting antibody is largely conserved, and binding to antigen occurs predominantly through the CDR loops of the immunoglobulin V domains. Bovines have deviated from this general paradigm by having few VH regions and thus little germline combinatorial diversity, but their antibodies contain long CDR H3 regions, with substantial diversity generated through somatic hypermutation. A subset of the repertoire comprises antibodies with ultralong CDR H3s, which can reach over 70 amino acids in length. Structurally, these unusual antibodies form a β-ribbon "stalk" and disulfide-bonded "knob" that protrude far from the antibody surface. These long CDR H3s allow cows to mount a particularly robust immune response when immunized with viral antigens, particularly to broadly neutralizing epitopes on a stabilized HIV gp140 trimer, which has been a challenge for other species. The unusual genetics and structural biology of cows provide for a unique paradigm for creation of immune diversity and could enable generation of antibodies against especially challenging targets and epitopes.

Antibody-Based Protective Immunity against Helminth Infections: Antibody Phage Display Derived Antibodies against BmR1 Antigen

Helminth parasite infections are significantly impacting global health, with more than two billion infections worldwide with a high morbidity rate. The complex life cycle of the nematodes has made host immune response studies against these parasites extremely difficult. In this study, we utilized two phage antibody libraries; the immune and naïve library were used to identify single chain fragment variable (scFv) clones against a specific filarial antigen (BmR1). The V-gene analysis of isolated scFv clones will help shed light on preferential VDJ gene segment usage against the filarial BmR1 antigen in healthy and infected states. The immune library showed the usage of both lambda and kappa light chains. However, the naïve library showed preferential use of the lambda family with different amino acid distributions. The binding characteristics of the scFv clones identified from this work were analyzed by immunoassay and immunoaffinity pull down of BmR1. The work highlights the antibody gene usage pattern of a naïve and immune antibody library against the same antigen as well as the robust nature of the enriched antibodies for downstream applications.

The H3 loop of antibodies shows unique structural characteristics

The H3 loop in the Complementarity Determining Region of antibodies plays a key role in their ability to bind the diverse space of potential antigens. It is also exceptionally difficult to model computationally causing a significant hurdle for in silico development of antibody biotherapeutics. In this article, we show that most H3s have unique structural characteristics which may explain why they are so challenging to model. We found that over 75% of H3 loops do not have a sub‐Angstrom structural neighbor in the non‐antibody world. Also, in a comparison with a nonredundant set of all protein fragments over 30% of H3 loops have a unique structure, with the average for all of other loops being less than 3%. We further observed that this structural difference can be seen at the level of four residue fragments where H3 loops present numerous novel conformations, and also at the level of individual residues with Tyrosine and Glycine often found in energetically unfavorable conformations. Proteins 2017; 85:1311–1318. © 2017 Wiley Periodicals, Inc.

A generalized quantitative antibody homeostasis model: regulation of B-cell development by BCR saturation and novel insights into bone marrow function

In a pair of articles, we present a generalized quantitative model for the homeostatic function of clonal humoral immune system. In this first paper, we describe the cycles of B-cell expansion and differentiation driven by B-cell receptor engagement. The fate of a B cell is determined by the signals it receives via its antigen receptor at any point of its lifetime. We express BCR engagement as a function of apparent affinity and free antigen concentration, using the range of 10⁻¹⁴–10⁻³ M for both factors. We assume that for keeping their BCR responsive, B cells must maintain partial BCR saturation, which is a narrow region defined by [Ag]≈K_D. To remain in this region, B cells respond to changes in [Ag] by proliferation or apoptosis and modulate K_D by changing BCR structure. We apply this framework to various niches of B-cell development such as the bone marrow, blood, lymphoid follicles and germinal centers. We propose that clustered B cells in the bone marrow and in follicles present antigen to surrounding B cells by exposing antigen captured on complement and Fc receptors. The model suggests that antigen-dependent selection in the bone marrow results in (1) effector BI cells, which develop in blood as a consequence of the inexhaustible nature of soluble antigens, (2) memory cells that survive in antigen rich niches, identified as marginal zone B cells. Finally, the model implies that memory B cells could derive survival signals from abundant non-cognate antigens.

Accurate Structure Prediction of CDR H3 Loops Enabled by a Novel Structure-Based C-Terminal Constraint

Ab structure prediction has made great strides, but accurately modeling CDR H3 loops remains elusive. Unlike the other five CDR loops, CDR H3 does not adopt canonical conformations and must be modeled de novo. During Antibody Modeling Assessment II, we found that biasing simulations toward kinked conformations enables generating low-root mean square deviation models (Weitzner et al. 2014. Proteins 82: 1611-1623), and since then, we have presented new geometric parameters defining the kink conformation (Weitzner et al. 2015. Structure 23: 302-311). In this study, we use these parameters to develop a new biasing constraint. When applied to a benchmark set of high-quality CDR H3 loops, the average minimum root mean square deviation sampled is 0.93 Å, compared with 1.34 Å without the constraint. We then test the performance of the constrained de novo method for homology modeling and rigid-body docking and present the results for 1) the Antibody Modeling Assessment II targets, 2) the 2009 RosettaAntibody benchmark set, and 3) the high-quality set.

Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences

Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a 'single state' design (SSD) paradigm. Multi-specificity design (MSD), on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON). The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain) an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design "promiscuous", polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes.

Rigidity Emerges during Antibody Evolution in Three Distinct Antibody Systems: Evidence from QSFR Analysis of Fab Fragments

The effects of somatic mutations that transform polyspecific germline (GL) antibodies to affinity mature (AM) antibodies with monospecificity are compared among three GL-AM Fab pairs. In particular, changes in conformational flexibility are assessed using a Distance Constraint Model (DCM). We have previously established that the DCM can be robustly applied across a series of antibody fragments (VL to Fab), and subsequently, the DCM was combined with molecular dynamics (MD) simulations to similarly characterize five thermostabilizing scFv mutants. The DCM is an ensemble based statistical mechanical approach that accounts for enthalpy/entropy compensation due to network rigidity, which has been quite successful in elucidating conformational flexibility and Quantitative Stability/Flexibility Relationships (QSFR) in proteins. Applied to three disparate antibody systems changes in QSFR quantities indicate that the VH domain is typically rigidified, whereas the VL domain and CDR L2 loop become more flexible during affinity maturation. The increase in CDR H3 loop rigidity is consistent with other studies in the literature. The redistribution of conformational flexibility is largely controlled by nonspecific changes in the H-bond network, although certain Arg to Asp salt bridges create highly localized rigidity increases. Taken together, these results reveal an intricate flexibility/rigidity response that accompanies affinity maturation.

Antibodies are protective proteins used by the immune system to recognize and neutralize foreign objects through interactions with a specific part of the target, called an antigen. Antibody structures are Y-shaped, contain multiple protein chains, and include two antigen-binding sites. The binding sites are located at the end of the Fab fragments, which are the upward facing arms of the Y-structure. The Fab fragments maintain binding affinity by themselves, and are thus often used as surrogates to student antibody-antigen interactions. High affinity antibodies are produced during the course of an immune response by successive mutations to germline gene-encoded antibodies. Germline antibodies are more likely to be polyspecific, whereas the affinity maturation process yields monoclonal antibodies that bind specifically to the target antigen. In this work, we use a computational Distance Constraint Model to characterize how mechanical properties change as three disparate germline antibodies are converted to affinity mature. Our results reveal a rich set of mechanical responses throughout the Fab structure. Nevertheless, increased rigidity in the VH domain is consistently observed, which is consistent with the transition from polyspecificity to monospecificity. That is, flexible antibody structures are able to recognize multiple antigens, while increased affinity and specificity is achieved—in part—by structural rigidification.

Structural analysis of the unmutated ancestor of the HIV-1 envelope V2 region antibody CH58 isolated from an RV144 vaccine efficacy trial vaccinee

Human monoclonal antibody CH58 isolated from an RV144 vaccinee binds at Lys169 of the HIV-1 Env gp120 V2 region, a site of vaccine-induced immune pressure. CH58 neutralizes HIV-1 CRF_01 AE strain 92TH023 and mediates ADCC against CD4 + T cell targets infected with CRF_01 AE tier 2 virus. CH58 and other antibodies that bind to a gp120 V2 epitope have a second light chain complementarity determining region (LCDR2) bearing a glutamic acid, aspartic acid (ED) motif involved in forming salt bridges with polar, basic side amino acid side chains in V2. In an effort to learn how V2 responses develop, we determined the crystal structures of the CH58-UA antibody unliganded and bound to V2 peptide. The structures showed an LCDR2 structurally pre-conformed from germline to interact with V2 residue Lys169. LCDR3 was subject to conformational selection through the affinity maturation process. Kinetic analyses demonstrate that only a few contacts were responsible for a 2000-fold increase in K_D through maturation, and this effect was predominantly due to an improvement in off-rate. This study shows that preconformation and preconfiguration can work in concert to produce antibodies with desired immunogenic properties.

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With only 2-3% mutation from germline, the HIV-1 antibody CH58 developed neutralizing and ADCC capabilities.

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The LCDR2 Glu–Asp motif of the RV144 antibody CH58 is pre-conformed from germline to interact with the gp120 V2 loop.

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Affinity and neutralization gains resulted from tuning local interactions rather than gross sequence or structure changes.

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Structural analyses show the second light chain complementarity determining region Glu–Asp motif of the CH58 antibody isolated from an RV144 vaccinee is optimally pre-conformed from germline to interact with the gp120 V2 loop. The increased binding affinity and neutralization capacity of the mature antibody compared to its germline precursor were achieved with only 2–3% mutation from germline, and the fact that these gains appeared to be a result of the tuning of local interactions rather than gross sequential or conformational changes provides hope that a rational immunogen design for HIV-1 treatment may become a reality.

Structure of the apo anti-influenza CH65 Fab

Influenza viruses remain a persistent challenge to human health owing to their inherent ability to evade the immune response by antigenic drift. However, the discovery of broadly neutralizing antibodies (bnAbs) against divergent viruses has sparked renewed interest in a universal influenza vaccine and novel therapeutic opportunities. Here, a crystal structure at 1.70 Å resolution is presented of the Fab of the human antibody CH65, which has broad neutralizing activity against a range of seasonal H1 isolates. Previous studies proposed that affinity maturation of this antibody lineage pre-organizes the complementarity-determining region (CDR) loops into an energetically favorable HA-bound conformation. Indeed, from the structural comparisons of free and HA-bound CH65 presented here, the CDR loops, and in particular the heavy-chain CDR3, adopt the same conformations in the free and bound forms. Thus, these findings support the notion that affinity maturation of the CH65 lineage favorably preconfigures the CDR loops for high-affinity binding to influenza hemagglutinin.

Affinity enhancement of antibodies: how low-affinity antibodies produced early in immune responses are followed by high-affinity antibodies later and in memory B-cell responses

The antibodies produced initially in response to most antigens are high molecular weight (MW) immunoglobulins (IgM) with low affinity for the antigen, while the antibodies produced later are lower MW classes (e.g., IgG and IgA) with, on average, orders of magnitude higher affinity for that antigen. These changes, often termed affinity maturation, take place largely in small B-cell clusters (germinal center; GC) in lymphoid tissues in which proliferating antigen-stimulated B cells express the highly mutagenic cytidine deaminase that mediates immunoglobulin class-switching and sequence diversification of the immunoglobulin variable domains of antigen-binding receptors on B cells (BCR). Of the large library of BCR-mutated B cells thus rapidly generated, a small minority with affinity-enhancing mutations are selected to survive and differentiate into long-lived antibody-secreting plasma cells and memory B cells. BCRs are also endocytic receptors; they internalize and cleave BCR-bound antigen, yielding peptide-MHC complexes that are recognized by follicular helper T cells. Imperfect correlation between BCR affinity for antigen and cognate T-cell engagement may account for the increasing affinity heterogeneity that accompanies the increasing average affinity of antibodies. Conservation of mechanisms underlying mutation and selection of high-affinity antibodies over the ≈200 million years of evolution separating bird and mammal lineages points to the crucial role of antibody affinity enhancement in adaptive immunity.

Antibodies: Computer-Aided Prediction of Structure and Design of Function

With the advent of high-throughput sequencing, and the increased availability of experimental structures of antibodies and antibody-antigen complexes, comes the improvement of computational approaches to predict the structure and design the function of antibodies and antibody-antigen complexes. While antibodies pose formidable challenges for protein structure prediction and design due to their large size and highly flexible loops in the complementarity-determining regions, they also offer exciting opportunities: the central importance of antibodies for human health results in a wealth of structural and sequence information that—as a knowledge base—can drive the modeling algorithms by limiting the conformational and sequence search space to likely regions of success. Further, efficient experimental platforms exist to test predicted antibody structure or designed antibody function, thereby leading to an iterative feedback loop between computation and experiment. We briefly review the history of computer-aided prediction of structure and design of function in the antibody field before we focus on recent methodological developments and the most exciting application examples.

Antibody modeling using the prediction of immunoglobulin structure (PIGS) web server [corrected]

Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

Ontogeny of recognition specificity and functionality for the broadly neutralizing anti-HIV antibody 4E10

The process of antibody ontogeny typically improves affinity, on-rate, and thermostability, narrows polyspecificity, and rigidifies the combining site to the conformer optimal for binding from the broader ensemble accessible to the precursor. However, many broadly-neutralizing anti-HIV antibodies incorporate unusual structural elements and recognition specificities or properties that often lead to autoreactivity. The ontogeny of 4E10, an autoreactive antibody with unexpected combining site flexibility, was delineated through structural and biophysical comparisons of the mature antibody with multiple potential precursors. 4E10 gained affinity primarily by off-rate enhancement through a small number of mutations to a highly conserved recognition surface. Controverting the conventional paradigm, the combining site gained flexibility and autoreactivity during ontogeny, while losing thermostability, though polyspecificity was unaffected. Details of the recognition mechanism, including inferred global effects due to 4E10 binding, suggest that neutralization by 4E10 may involve mechanisms beyond simply binding, also requiring the ability of the antibody to induce conformational changes distant from its binding site. 4E10 is, therefore, unlikely to be re-elicited by conventional vaccination strategies.

Antigen exposure leads to rigidification of germline antibody combining site

Immune complexes involving diverse antigens and corresponding antibodies were analyzed for mapping conformational transitions of an antibody before antigen binding, upon antigen binding and after antigen release. Molecular dynamics simulations of the two comprehensive datasets consisting of the antigen-free and antigen-bound structures of the germline antibodies 36-65 and BBE6.12H3 provided mechanistic model of antigen encounter by primary antibodies. While native germline antibodies exhibit substantial mobility in the antigen-combining sites, their antigen-bound states exhibit relatively rigid conformations, even in the absence of the antigen suggesting preservation of the structural state after antigen release. It is proposed that acquired rigidity by a germline antibody upon antigen binding may be the first step in affinity maturation in favor of that antigen.

Backbone flexibility of CDR3 and immune recognition of antigens

Conformational entropy is an important component of protein-protein interactions; however, there is no reliable method for computing this parameter. We have developed a statistical measure of residual backbone entropy in folded proteins by using the ϕ-ψ distributions of the 20 amino acids in common secondary structures. The backbone entropy patterns of amino acids within helix, sheet or coil form clusters that recapitulate the branching and hydrogen bonding properties of the side chains in the secondary structure type. The same types of residues in coil and sheet have identical backbone entropies, while helix residues have much smaller conformational entropies. We estimated the backbone entropy change for immunoglobulin complementarity-determining regions (CDRs) from the crystal structures of 34 low-affinity T-cell receptors and 40 high-affinity Fabs as a result of the formation of protein complexes. Surprisingly, we discovered that the computed backbone entropy loss of only the CDR3, but not all CDRs, correlated significantly with the kinetic and affinity constants of the 74 selected complexes. Consequently, we propose a simple algorithm to introduce proline mutations that restrict the conformational flexibility of CDRs and enhance the kinetics and affinity of immunoglobulin interactions. Combining the proline mutations with rationally designed mutants from a previous study led to 2400-fold increase in the affinity of the A6 T-cell receptor for Tax-HLAA2. However, this mutational scheme failed to induce significant binding changes in the already-high-affinity C225-Fab/huEGFR interface. Our results will serve as a roadmap to formulate more effective target functions to design immune complexes with improved biological functions.

Human germline antibody gene segments encode polyspecific antibodies

Structural flexibility in germline gene-encoded antibodies allows promiscuous binding to diverse antigens. The binding affinity and specificity for a particular epitope typically increase as antibody genes acquire somatic mutations in antigen-stimulated B cells. In this work, we investigated whether germline gene-encoded antibodies are optimal for polyspecificity by determining the basis for recognition of diverse antigens by antibodies encoded by three VH gene segments. Panels of somatically mutated antibodies encoded by a common VH gene, but each binding to a different antigen, were computationally redesigned to predict antibodies that could engage multiple antigens at once. The Rosetta multi-state design process predicted antibody sequences for the entire heavy chain variable region, including framework, CDR1, and CDR2 mutations. The predicted sequences matched the germline gene sequences to a remarkable degree, revealing by computational design the residues that are predicted to enable polyspecificity, i.e., binding of many unrelated antigens with a common sequence. The process thereby reverses antibody maturation in silico. In contrast, when designing antibodies to bind a single antigen, a sequence similar to that of the mature antibody sequence was returned, mimicking natural antibody maturation in silico. We demonstrated that the Rosetta computational design algorithm captures important aspects of antibody/antigen recognition. While the hypervariable region CDR3 often mediates much of the specificity of mature antibodies, we identified key positions in the VH gene encoding CDR1, CDR2, and the immunoglobulin framework that are critical contributors for polyspecificity in germline antibodies. Computational design of antibodies capable of binding multiple antigens may allow the rational design of antibodies that retain polyspecificity for diverse epitope binding.

Flexible backbone sampling methods to model and design protein alternative conformations

Sampling alternative conformations is key to understanding how proteins work and engineering them for new functions. However, accurately characterizing and modeling protein conformational ensembles remain experimentally and computationally challenging. These challenges must be met before protein conformational heterogeneity can be exploited in protein engineering and design. Here, as a stepping stone, we describe methods to detect alternative conformations in proteins and strategies to model these near-native conformational changes based on backrub-type Monte Carlo moves in Rosetta. We illustrate how Rosetta simulations that apply backrub moves improve modeling of point mutant side-chain conformations, native side-chain conformational heterogeneity, functional conformational changes, tolerated sequence space, protein interaction specificity, and amino acid covariation across protein-protein interfaces. We include relevant Rosetta command lines and RosettaScripts to encourage the application of these types of simulations to other systems. Our work highlights that critical scoring and sampling improvements will be necessary to approximate conformational landscapes. Challenges for the future development of these methods include modeling conformational changes that propagate away from designed mutation sites and modulating backbone flexibility to predictively design functionally important conformational heterogeneity.

Tilting the balance between canonical and noncanonical conformations for the H1 hypervariable loop of a llama VHH through point mutations

Nanobodies are single-domain antibodies found in camelids. These are the smallest naturally occurring binding domains and derive functionality via three hypervariable loops (H1-H3) that form the binding surface. They are excellent candidates for antibody engineering because of their favorable characteristics like small size, high solubility, and stability. To rationally engineer antibodies with affinity for a specific target, the hypervariable loops can be tailored to obtain the desired binding surface. As a first step toward such a goal, we consider the design of loops with a desired conformation. In this study, we focus on the H1 loop of the anti-hCG llama nanobody that exhibits a noncanonical conformation. We aim to "tilt" the stability of the H1 loop structure from a noncanonical conformation to a (humanized) type 1 canonical conformation by studying the effect of selected mutations to the amino acid sequence of the H1, H2, and proximal residues. We use all-atomistic, explicit-solvent, biased molecular dynamic simulations to simulate the wild-type and mutant loops in a prefolded framework. We thus find mutants with increasing propensity to form a stable type 1 canonical conformation of the H1 loop. Free energy landscapes reveal the existence of conformational isomers of the canonical conformation that may play a role in binding different antigenic surfaces. We also elucidate the approximate mechanism and kinetics of transitions between such conformational isomers by using a Markovian model. We find that a particular three-point mutant has the strongest thermodynamic propensity to form the H1 type 1 canonical structure but also to exhibit transitions between conformational isomers, while a different, more rigid three-point mutant has the strongest propensity to be kinetically trapped in such a canonical structure.

Preconfiguration of the antigen-binding site during affinity maturation of a broadly neutralizing influenza virus antibody

Affinity maturation refines a naive B-cell response by selecting mutations in antibody variable domains that enhance antigen binding. We describe a B-cell lineage expressing broadly neutralizing influenza virus antibodies derived from a subject immunized with the 2007 trivalent vaccine. The lineage comprises three mature antibodies, the unmutated common ancestor, and a common intermediate. Their heavy-chain complementarity determining region inserts into the conserved receptor-binding pocket of influenza HA. We show by analysis of structures, binding kinetics and long time-scale molecular dynamics simulations that antibody evolution in this lineage has rigidified the initially flexible heavy-chain complementarity determining region by two nearly independent pathways and that this preconfiguration accounts for most of the affinity gain. The results advance our understanding of strategies for developing more broadly effective influenza vaccines.

A systematic comparison of free and bound antibodies reveals binding-related conformational changes

To study structural changes that occur in Abs upon Ag binding, we systematically compared free and bound structures of all 141 crystal structures of the 49 Abs that were solved in these two forms. We found that many structural changes occur far from the Ag binding site. Some of them may constitute a mechanism for the recently suggested allosteric effects in Abs. Within the binding site itself, CDR-H3 is the only element that shows significant binding-related conformational changes; however, this occurs in only one third of the Abs. Beyond the binding site, Ag binding is associated with changes in the relative orientation of the H and L chains in both the variable and constant domains. An even larger change occurs in the elbow angle between the variable and the constant domains, and it is significantly larger for binding of big Ags than for binding of small ones. The most consistent and substantial conformational changes occur in a loop in the H chain constant domain. This loop is implicated in the interaction between the H and L chains, is often intrinsically disordered, and is involved in complement binding. Hence, we suggest that it may have a role in Ab function. These findings provide structural insight into the recently proposed allosteric effects in Abs.

Computer-aided antibody design

Recent clinical trials using antibodies with low toxicity and high efficiency have raised expectations for the development of next-generation protein therapeutics. However, the process of obtaining therapeutic antibodies remains time consuming and empirical. This review summarizes recent progresses in the field of computer-aided antibody development mainly focusing on antibody modeling, which is divided essentially into two parts: (i) modeling the antigen-binding site, also called the complementarity determining regions (CDRs), and (ii) predicting the relative orientations of the variable heavy (V(H)) and light (V(L)) chains. Among the six CDR loops, the greatest challenge is predicting the conformation of CDR-H3, which is the most important in antigen recognition. Further computational methods could be used in drug development based on crystal structures or homology models, including antibody-antigen dockings and energy calculations with approximate potential functions. These methods should guide experimental studies to improve the affinities and physicochemical properties of antibodies. Finally, several successful examples of in silico structure-based antibody designs are reviewed. We also briefly review structure-based antigen or immunogen design, with application to rational vaccine development.

Predicting antibody complementarity determining region structures without classification

Antibodies are used extensively in medical and biological research. Their complementarity determining regions (CDRs) define the majority of their antigen binding functionality. CDR structures have been intensively studied and classified (canonical structures). Here we show that CDR structure prediction is no different from the standard loop structure prediction problem and predict them without classification. FREAD, a successful database loop prediction technique, is able to produce accurate predictions for all CDR loops (0.81, 0.42, 0.96, 0.98, 0.88 and 2.25 Å RMSD for CDR-L1 to CDR-H3). In order to overcome the relatively poor predictions of CDR-H3, we developed two variants of FREAD, one focused on sequence similarity (FREAD-S) and another which includes contact information (ConFREAD). Both of the methods improve accuracy for CDR-H3 to 1.34 Å and 1.23 Å respectively. The FREAD variants are also tested on homology models and compared to RosettaAntibody (CDR-H3 prediction on models: 1.98 and 2.62 Å for ConFREAD and RosettaAntibody respectively). CDRs are known to change their structural conformations upon binding the antigen. Traditional CDR classifications are based on sequence similarity and do not account for such environment changes. Using a set of antigen-free and antigen-bound structures, we compared our FREAD variants. ConFREAD which includes contact information successfully discriminates the bound and unbound CDR structures and achieves an accuracy of 1.35 Å for bound structures of CDR-H3.

The antibody response to an HLA mismatch: a model for nonself-self discrimination in relation to HLA epitope immunogenicity

Antibodies to HLA mismatches are specific for epitopes rather than antigens. HLAMatchmaker considers each HLA antigen as a string of eplets that represent key elements of epitopes. Certain antibodies are specific for single eplets, but recent studies have demonstrated that epitopes defined by eplet pairs always involve one nonself-eplet and a self-eplet shared between the immunizing antigen and the antibody producer. This suggests an autoreactive component of the alloantibody response to an HLA mismatch and this report expands this concept. During B-cell development, V(H) and V(L) gene rearrangements produce a diversity of Ig receptors that can recognize epitopes on autologous proteins. It is hypothesized that B cells carry low-affinity receptors for self-HLA antigens. Their interactions with self-HLA proteins will not lead to B-cell activation or antibody production. In contrast, exposure to HLA mismatches induces often strong alloantibody responses. The activation of self-HLA-specific B cell by a nonself-eplet may require that the remainder of the structural epitope of the immunizing antigen has considerable structural similarity with one of the antibody producer's alleles. This hypothesis has been tested in molecular modelling studies with six epitopes defined by human monoclonal antibodies. In each case, one allele of the antibody producer had no or few differences with the immunizing allele in antibody-accessible positions defined by a 15 Ångstrom radius of the mismatched eplet. The other alleles of the antibody producer showed significantly greater numbers of residue differences with the immunizer (5.8 ± 2.0 versus 1.0 ± 0.6, P < 0.0001). These data support the concept that HLA antibodies originate from B cells with self-HLA immunoglobulin receptors that recognize mismatched eplets as nonself entities on immunizing antigens. The nonself-self paradigm provides a new insight of HLA epitope immunogenicity and may explain why sensitized patients have antibodies to a restricted number of mismatched epitopes.

Effects of somatic mutations on CDR loop flexibility during affinity maturation

Prior studies suggest that antibody affinity maturation is achieved, in part, via prearranging the CDRs for binding. The implication is that the entropy cost of binding is reduced and that this rigidification occurs as a consequence of somatic mutations during maturation. However, how these mutations modulate CDR flexibility is unclear. Here, molecular dynamics simulations captured CDR flexibility differences between four mature antibodies (7G12, AZ28, 28B4, and 48G7) and their germline predecessors. Analysis of their trajectories: (1) rationalized how mutations during affinity maturation restrict CDR motility, (2) captured the equilibrium between bound and unbound conformations for the H3 loop of unliganded 7G12, and (3) predicted a set of new mutations that, according to our simulations, should diminish binding by increasing flexibility.

Protein binding specificity versus promiscuity

Interactions between macromolecules in general, and between proteins in particular, are essential for any life process. Examples include transfer of information, inhibition or activation of function, molecular recognition as in the immune system, assembly of macromolecular structures and molecular machines, and more. Proteins interact with affinities ranging from millimolar to femtomolar and, because affinity determines the concentration required to obtain 50% binding, the amount of different complexes formed is very much related to local concentrations. Although the concentration of a specific binding partner is usually quite low in the cell (nanomolar to micromolar), the total concentration of other macromolecules is very high, allowing weak and non-specific interactions to play important roles. In this review we address the question of binding specificity, that is, how do some proteins maintain monogamous relations while others are clearly polygamous. We examine recent work that addresses the molecular and structural basis for specificity versus promiscuity. We show through examples how multiple solutions exist to achieve binding via similar interfaces and how protein specificity can be tuned using both positive and negative selection (specificity by demand). Binding of a protein to numerous partners can be promoted through variation in which residues are used for binding, conformational plasticity and/or post-translational modification. Natively unstructured regions represent the extreme case in which structure is obtained only upon binding. Many natively unstructured proteins serve as hubs in protein-protein interaction networks and such promiscuity can be of functional importance in biology.

Spatially addressed combinatorial protein libraries for recombinant antibody discovery and optimization

Antibody discovery typically uses hybridoma- or display-based selection approaches, which lack the advantages of directly screening spatially addressed compound libraries as in small-molecule discovery. Here we apply the latter strategy to antibody discovery, using a library of ∼10,000 human germline antibody Fabs created by de novo DNA synthesis and automated protein expression and purification. In multiplexed screening assays, we obtained specific hits against seven of nine antigens. Using sequence-activity relationships and iterative mutagenesis, we optimized the binding affinities of two hits to the low nanomolar range. The matured Fabs showed full and partial antagonism activities in cell-based assays. Thus, protein drug leads can be discovered using surprisingly small libraries of proteins with known sequences, questioning the requirement for billions of members in an antibody discovery library. This methodology also provides sequence, expression and specificity information at the first step of the discovery process, and could enable novel antibody discovery in functional screens.

Practically useful: what the Rosetta protein modeling suite can do for you

The objective of this review is to enable researchers to use the software package Rosetta for biochemical and biomedicinal studies. We provide a brief review of the six most frequent research problems tackled with Rosetta. For each of these six tasks, we provide a tutorial that illustrates a basic Rosetta protocol. The Rosetta method was originally developed for de novo protein structure prediction and is regularly one of the best performers in the community-wide biennial Critical Assessment of Structure Prediction. Predictions for protein domains with fewer than 125 amino acids regularly have a backbone root-mean-square deviation of better than 5.0 Å. More impressively, there are several cases in which Rosetta has been used to predict structures with atomic level accuracy better than 2.5 Å. In addition to de novo structure prediction, Rosetta also has methods for molecular docking, homology modeling, determining protein structures from sparse experimental NMR or EPR data, and protein design. Rosetta has been used to accurately design a novel protein structure, predict the structure of protein−protein complexes, design altered specificity protein−protein and protein−DNA interactions, and stabilize proteins and protein complexes. Most recently, Rosetta has been used to solve the X-ray crystallographic phase problem.