Natural evolution must explore a vast landscape of possible sequences for desirable yet rare mutations, suggesting that learning from natural evolutionary strategies could guide artificial evolution. Here we report that general protein language models can efficiently evolve human antibodies by suggesting mutations that are evolutionarily plausible, despite providing the model with no information about the target antigen, binding specificity or protein structure. We performed language-model-guided affinity maturation of seven antibodies, screening 20 or fewer variants of each antibody across only two rounds of laboratory evolution, and improved the binding affinities of four clinically relevant, highly mature antibodies up to sevenfold and three unmatured antibodies up to 160-fold, with many designs also demonstrating favorable thermostability and viral neutralization activity against Ebola and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pseudoviruses. The same models that improve antibody binding also guide efficient evolution across diverse protein families and selection pressures, including antibiotic resistance and enzyme activity, suggesting that these results generalize to many settings.

Natural evolution must explore a vast landscape of possible sequences for desirable yet rare mutations, suggesting that learning from natural evolutionary strategies could accelerate artificial evolution. Here, we report that deep learning algorithms known as protein language models can evolve human antibodies with high efficiency, despite providing the models with no information about the target antigen, binding specificity, or protein structure, and also requiring no additional task-specific finetuning or supervision. We performed language-model-guided affinity maturation of seven diverse antibodies, screening 20 or fewer variants of each antibody across only two rounds of evolution. Our evolutionary campaigns improved the binding affinities of four clinically relevant antibodies up to 7-fold and three unmatured antibodies up to 160-fold across diverse viral antigens, with many designs also demonstrating improved thermostability and viral neutralization activity. Notably, our algorithm requires only a single wildtype sequence and computes recommended amino acid changes in less than a second. Moreover, the same models that improve antibody binding also guide efficient evolution across diverse protein families and selection pressures, indicating that these results generalize to many natural settings. Contrary to prevailing notions of evolution as difficult and resource-intensive, our results suggest that when constrained to a narrow manifold of evolutionary plausibility, evolution can become much easier, which we refer to as the “efficient manifold hypothesis.”

Despite its essential role in antigen presentation, enhancing proteasomal processing is an unexploited strategy for improving vaccines. pepVIII, an anticancer vaccine targeting EGFRvIII, has been tested in several trials for glioblastoma. We examined 20 peptides in silico and experimentally, which showed that a tyrosine substitution (Y6-pepVIII) maximizes proteasome cleavage and survival in a subcutaneous tumor model in mice. In an intracranial glioma model, Y6-pepVIII showed a 62 and 31% improvement in median survival compared to control animals and pepVIII-vaccinated mice. Y6-pepVIII vaccination altered tumor-infiltrating lymphocyte subsets and expression of PD-1 on intratumoral T cells. Combination with anti–PD-1 therapy cured 45% of the Y6-pepVIII–vaccinated mice but was ineffective for pepVIII-treated mice. Liquid chromatography–tandem mass spectrometry analysis of proteasome-digested pepVIII and Y6-pepVIII revealed that most fragments were similar but more abundant in Y6-pepVIII digests and 77% resulted from proteasome-catalyzed peptide splicing (PCPS). We identified 10 peptides that bound human and murine MHC class I. Nine were PCPS products and only one peptide was colinear with EGFRvIII, indicating that PCPS fragments may be a component of MHC class I recognition. Despite not being colinear with EGFRvIII, two of three PCPS products tested were capable of increasing survival when administered independently as vaccines. We hypothesize that the immune response to a vaccine represents the collective contribution from multiple PCPS and linear products. Our work suggests a strategy to increase proteasomal processing of a vaccine that results in an augmented immune response and enhanced survival in mice.

pepVIII, an anticancer vaccine targeting EGFRvIII, has been tested in several trials for glioblastoma including ACT IV. a randomized Phase III trial for newly diagnosed patients. While results from ACT IV were equivocal, available data suggests the elimination of EGFRvIII was not robust. Despite its essential role in antigen presentation, enhancing proteasomal processing is an unexploited strategy for improving vaccines. We examined 20 peptides in silico and experimentally, which showed that a tyrosine substitution (Y6-pepVIII) maximizes proteasome cleavage and survival in a subcutaneous tumor model. In an intracranial glioma model, Y6-pepVIII showed a 62 and 31% improvement in median survival compared to control animals and pepVIII-vaccinated mice. Y6-pepVIII vaccination altered tumor-infiltrating lymphocyte subsets and expression of PD-1 on intratumoral T cells. Combination with anti–PD-1 therapy cured 45% of the Y6-pepVIII–vaccinated mice but was ineffective for pepVIII-treated mice. LC-MS/MS analysis of proteasome-digested pepVIII and Y6-pepVIII revealed that most fragments were similar but more abundant inY6-pepVIII digests and 77% resulted from proteasome-catalyzed peptide splicing (PCPS). We identified 10 peptides that bound human and murine MHC class I. Nine were PCPS products and only one peptide was colinear with EGFRvIII, indicating that PCPS fragments may be a component of MHC class I recognition. Despite not being colinear with EGFRvIII, two of three PCPS products tested were capable of increasing survival when administered independently as vaccines. We hypothesize that the immune response to a vaccine represents the collective contribution from multiple PCPS and linear products. Our work suggests a strategy to increase proteasomal processing of a vaccine that results in an augmented immune response and enhanced survival in mice.