One-shot design elevates functional expression levels of a voltage-gated potassium channel.

Membrane proteins play critical physiological roles as receptors, channels, pumps, and transporters. Despite their importance, however, low expression levels often hamper the experimental characterization of membrane proteins. We present an automated and web-accessible design algorithm called mPROSS (https://mPROSS.weizmann.ac.il), which uses phylogenetic analysis and an atomistic potential, including an empirical lipophilicity scale, to improve native-state energy. As a stringent test, we apply mPROSS to the Kv1.2-Kv2.1 paddle chimera voltage-gated potassium channel. Four designs, encoding 9-26 mutations relative to the parental channel, were functional and maintained potassium-selective permeation and voltage dependence in Xenopus oocytes with up to 14-fold increase in whole-cell current densities. Additionally, single-channel recordings reveal no significant change in the channel-opening probability nor in unitary conductance, indicating that functional expression levels increase without impacting the activity profile of individual channels. Our results suggest that the expression levels of other dynamic channels and receptors may be enhanced through one-shot design calculations.

Opportunities and challenges in design and optimization of protein function.

The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calculations, as well as machine learning tools, have dramatically improved protein engineering and design. In this Review, we discuss how these methods have enabled the design of increasingly complex structures and therapeutically relevant activities. Additionally, protein optimization methods have improved the stability and activity of complex eukaryotic proteins. Thanks to their increased reliability, computational design methods have been applied to improve therapeutics and enzymes for green chemistry and have generated vaccine antigens, antivirals and drug-delivery nano-vehicles. Moreover, the high success of design methods reflects an increased understanding of basic rules that govern the relationships among protein sequence, structure and function. However, de novo design is still limited mostly to α-helix bundles, restricting its potential to generate sophisticated enzymes and diverse protein and small-molecule binders. Designing complex protein structures is a challenging but necessary next step if we are to realize our objective of generating new-to-nature activities.

Anti-SARS-CoV-2 immunoadhesin remains effective against Omicron and other emerging variants of concern.

Blocking the interaction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with its angiotensin-converting enzyme 2 (ACE2) receptor was proved to be an effective therapeutic option. Various protein binders as well as monoclonal antibodies that effectively target the receptor-binding domain (RBD) of SARS-CoV-2 to prevent interaction with ACE2 were developed. The emergence of SARS-CoV-2 variants that accumulate alterations in the RBD can severely affect the efficacy of such immunotherapeutic agents, as is indeed the case with Omicron that resists many of the previously isolated monoclonal antibodies. Here, we evaluate an ACE2-based immunoadhesin that we have developed early in the pandemic against some of the recent variants of concern (VoCs), including the Delta and the Omicron variants. We show that our ACE2-immunoadhesin remains effective in neutralizing these variants, suggesting that immunoadhesin-based immunotherapy is less prone to escape by the virus and has a potential to remain effective against future VoCs.

Assessing and enhancing foldability in designed proteins.

Recent advances in protein-design methodology have led to a dramatic increase in reliability and scale. With these advances, dozens and even thousands of designed proteins are automatically generated and screened. Nevertheless, the success rate, particularly in design of functional proteins, is low and fundamental goals such as reliable de novo design of efficient enzymes remain beyond reach. Experimental analyses have consistently indicated that a major reason for design failure is inaccuracy and misfolding relative to the design conception. To address this challenge, we describe complementary methods to diagnose and ameliorate suboptimal regions in designed proteins: first, we develop a Rosetta atomistic computational mutation scanning approach to detect energetically suboptimal positions in designs (available on a web server https://pSUFER.weizmann.ac.il); second, we demonstrate that AlphaFold2 ab initio structure prediction flags regions that may misfold in designed enzymes and binders; and third, we focus FuncLib design calculations on suboptimal positions in a previously designed low-efficiency enzyme, improving its catalytic efficiency by 330-fold. Furthermore, applied to a de novo designed protein that exhibited limited stability, the same approach markedly improved stability and expressibility. Thus, foldability analysis and enhancement may dramatically increase the success rate in design of functional proteins.

Biomolecular Recognition of the Glycan Neoantigen CA19-9 by Distinct Antibodies.

Glycans decorate the cell surface, secreted glycoproteins and glycolipids, and altered glycans are often found in cancers. Despite their high diagnostic and therapeutic potential, however, glycans are polar and flexible molecules that are quite challenging for the development and design of high-affinity binding antibodies. To understand the mechanisms by which glycan neoantigens are specifically recognized by antibodies, we analyze the biomolecular recognition of the tumor-associated carbohydrate antigen CA19-9 by two distinct antibodies using X-ray crystallography. Despite the potential plasticity of glycans and the very different antigen-binding surfaces presented by the antibodies, both structures reveal an essentially identical extended CA19-9 conformer, suggesting that this conformer's stability selects the antibodies. Starting from the bound structure of one of the antibodies, we use the AbLIFT computational algorithm to design a variant with seven core mutations in the variable domain's light-heavy chain interface that exhibits tenfold improved affinity for CA19-9. The results reveal strategies used by antibodies to specifically recognize glycan antigens and show how automated antibody-optimization methods may be used to enhance the clinical potential of existing antibodies.

PROSS 2: a new server for the design of stable and highly expressed protein variants.

SUMMARY: Many natural and designed proteins are only marginally stable limiting their usefulness in research and applications. Recently, we described an automated structure and sequence-based design method, called PROSS, for optimizing protein stability and heterologous expression levels that has since been validated on dozens of proteins. Here, we introduce improvements to the method, workflow and presentation, including more accurate sequence analysis, error handling and automated analysis of the quality of the sequence alignment that is used in design calculations. AVAILABILITY AND IMPLEMENTATION: PROSS2 is freely available for academic use at https://pross.weizmann.ac.il.

One-step sequence and structure-guided optimization of HIV-1 envelope gp140.

Stabilization of the metastable envelope glycoprotein (Env) of HIV-1 is hypothesized to improve induction of broadly neutralizing antibodies. We improved the expression yield and stability of the HIV-1 envelope glycoprotein BG505SOSIP.664 gp140 by means of a previously described automated sequence and structure-guided computational thermostabilization approach, PROSS. This combines sequence conservation information with computational assessment of mutant stabilization, thus taking advantage of the extensive natural sequence variation present in HIV-1 Env. PROSS is used to design three gp140 variants with 17-45 mutations relative to the parental construct. One of the designs is experimentally observed to have a fourfold improvement in yield and a 4 °C increment in thermostability. In addition, the designed immunogens have similar antigenicity profiles to the native flexible linker version of wild type, BG505SOSIP.664 gp140 (NFL Wt) to major epitopes targeted by broadly neutralizing antibodies. PROSS eliminates the laborious process of screening many variants for stability and functionality, providing a proof of principle of the method for stabilization and improvement of yield without compromising antigenicity for next generation complex, highly glycosylated vaccine candidates.

A lipophilicity-based energy function for membrane-protein modelling and design.

Membrane-protein design is an exciting and increasingly successful research area which has led to landmarks including the design of stable and accurate membrane-integral proteins based on coiled-coil motifs. Design of topologically more complex proteins, such as most receptors, channels, and transporters, however, demands an energy function that balances contributions from intra-protein contacts and protein-membrane interactions. Recent advances in water-soluble all-atom energy functions have increased the accuracy in structure-prediction benchmarks. The plasma membrane, however, imposes different physical constraints on protein solvation. To understand these constraints, we recently developed a high-throughput experimental screen, called dsTßL, and inferred apparent insertion energies for each amino acid at dozens of positions across the bacterial plasma membrane. Here, we express these profiles as lipophilicity energy terms in Rosetta and demonstrate that the new energy function outperforms previous ones in modelling and design benchmarks. Rosetta ab initio simulations starting from an extended chain recapitulate two-thirds of the experimentally determined structures of membrane-spanning homo-oligomers with <2.5Å root-mean-square deviation within the top-predicted five models (available online: http://tmhop.weizmann.ac.il). Furthermore, in two sequence-design benchmarks, the energy function improves discrimination of stabilizing point mutations and recapitulates natural membrane-protein sequences of known structure, thereby recommending this new energy function for membrane-protein modelling and design.

Interplay between hydrophobicity and the positive-inside rule in determining membrane-protein topology.

The energetics of membrane-protein interactions determine protein topology and structure: hydrophobicity drives the insertion of helical segments into the membrane, and positive charges orient the protein with respect to the membrane plane according to the positive-inside rule. Until recently, however, quantifying these contributions met with difficulty, precluding systematic analysis of the energetic basis for membrane-protein topology. We recently developed the dsTßL method, which uses deep sequencing and in vitro selection of segments inserted into the bacterial plasma membrane to infer insertion-energy profiles for each amino acid residue across the membrane, and quantified the insertion contribution from hydrophobicity and the positive-inside rule. Here, we present a topology-prediction algorithm called TopGraph, which is based on a sequence search for minimum dsTßL insertion energy. Whereas the average insertion energy assigned by previous experimental scales was positive (unfavorable), the average assigned by TopGraph in a nonredundant set is -6.9 kcal/mol. By quantifying contributions from both hydrophobicity and the positive-inside rule we further find that in about half of large membrane proteins polar segments are inserted into the membrane to position more positive charges in the cytoplasm, suggesting an interplay between these two energy contributions. Because membrane-embedded polar residues are crucial for substrate binding and conformational change, the results implicate the positive-inside rule in determining the architectures of membrane-protein functional sites. This insight may aid structure prediction, engineering, and design of membrane proteins. TopGraph is available online (topgraph.weizmann.ac.il).

Mutational scanning reveals the determinants of protein insertion and association energetics in the plasma membrane.

Insertion of helix-forming segments into the membrane and their association determines the structure, function, and expression levels of all plasma membrane proteins. However, systematic and reliable quantification of membrane-protein energetics has been challenging. We developed a deep mutational scanning method to monitor the effects of hundreds of point mutations on helix insertion and self-association within the bacterial inner membrane. The assay quantifies insertion energetics for all natural amino acids at 27 positions across the membrane, revealing that the hydrophobicity of biological membranes is significantly higher than appreciated. We further quantitate the contributions to membrane-protein insertion from positively charged residues at the cytoplasm-membrane interface and reveal large and unanticipated differences among these residues. Finally, we derive comprehensive mutational landscapes in the membrane domains of Glycophorin A and the ErbB2 oncogene, and find that insertion and self-association are strongly coupled in receptor homodimers.

Overcoming a species-specificity barrier in development of an inhibitory antibody targeting a modulator of tumor stroma.

The secreted disulfide catalyst Quiescin sulfhydryl oxidase-1 (QSOX1) affects extracellular matrix organization and is overexpressed in various adenocarcinomas and associated stroma. Inhibition of extracellular human QSOX1 by a monoclonal antibody decreased tumor cell migration in a cell co-culture model and hence may have therapeutic potential. However, the species specificity of the QSOX1 monoclonal antibody has been a setback in assessing its utility as an anti-metastatic agent in vivo, a common problem in the antibody therapy industry. We therefore used structurally guided engineering to expand the antibody species specificity, improving its affinity toward mouse QSOX1 by at least four orders of magnitude. A crystal structure of the re-engineered variant, complexed with its mouse antigen, revealed that the antibody accomplishes dual-species targeting through altered contacts between its heavy and light chains, plus replacement of bulky aromatics by flexible side chains and versatile water-bridged polar interactions. In parallel, we produced a surrogate antibody targeting mouse QSOX1 that exhibits a new QSOX1 inhibition mode. This set of three QSOX1 inhibitory antibodies is compatible with various mouse models for pre-clinical trials and biotechnological applications. In this study we provide insights into structural blocks to cross-reactivity and set up guideposts for successful antibody design and re-engineering.