MHCEpitopeEnergy, a Flexible Rosetta-Based Biotherapeutic Deimmunization Platform

Yachnin, Brahm J.; Mulligan, Vikram Khipple; Khare, Sagar D.; Bailey‐Kellogg, Chris

doi:10.1021/acs.jcim.1c00056

Cited by 15 publications

(21 citation statements)

References 68 publications

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“…In this study, we noted that Roxadustat + oral iron was associated with fewer adverse reactions, indicating that Roxadustat + oral iron may have a good safety profile. e possible explanation is that HIF-PHI can effectively promote the production of endogenous EPO in patients, thereby accelerating the production of red blood cells in patients, and mitigating the symptoms of anemia in patients [21][22][23]. In traditional Chinese medicine, the etiology and pathogenesis of renal anemia in CKD is mainly "kidney deficiency with damp-heat and blood stasis," and the lesions are mainly located in the spleen, kidney and liver.…”

Section: Discussionmentioning

confidence: 99%

Efficacy and Mechanism of Roxadustat plus Oral Iron in the Treatment of Elderly Chronic Kidney Disease with Anemia

Liu

Shi

Tian

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Objective. For investigating the efficacy and mechanism of Roxadustat + oral iron in the treatment of elderly chronic kidney disease (CKD) complicated with anemia. Methods. A total of 100 elderly patients with CKD and anemia admitted to our hospital between April 2020 and December 2021 were enrolled as research subjects, and the patients were assigned to control group (Con group, n = 50) or experimental group (Exp group, n = 50). The patients in the Con group were given oral iron, and those in the Exp group were given Roxadustat capsule based on the Con group. Both groups were given subcutaneous injection of recombinant human erythropoietin. The clinical efficacy, anemia indexes, iron metabolism indexes, inflammatory indexes, and adverse reactions were compared between the two groups. Results. The Exp group showed a notably higher treatment effective rate than the Con group ( P < 0.05 ). After treatment, the anemia indexes, iron metabolism indexes, and inflammatory indexes in the Exp group were notably better than those in the Con group ( P < 0.05 ). The Exp group showed a notably lower incidence of adverse reactions during treatment than the Con group ( P < 0.05 ). Conclusion. Roxadustat plus oral iron yields a pronounced clinical efficacy in the therapy of elderly patients with CKD and anemia.

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Section: Discussionmentioning

confidence: 99%

Efficacy and Mechanism of Roxadustat plus Oral Iron in the Treatment of Elderly Chronic Kidney Disease with Anemia

Liu

Shi

Tian

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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“…recently developed a Rosetta-based platform to deimmunize therapeutic proteins. 108 They incorporated a new score term utilizing predicted or experimentally identified T-cell epitope information into the scoring function so that computational protein design calculations can be guided based on the epitope information as well as the energetic stability.…”

Section: Computational Developability Assessment Using Biopharmaceutical Informaticsmentioning

confidence: 99%

Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics

Khetan

Curtis

Deane

et al. 2022

mAbs

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Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the “developability assessment” of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability guidelines based on in silico metrics that can be used for the assessment of antibody stability and manufacturability.

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“…(1) We develop CAPE-XVAE, a novel machine learning (ML)-based approach combining the abilities of Variational Autoencoders (VAEs) and language models (LMs) with reinforcement learning (RL), to generate MHC-I immune-visibility modified protein sequences. (2) We modify the existing physics-based approach from Yachnin et al [6] that uses the Rosetta Packer [9,10] in a novel fashion to enable it to reduce or increase MHC-I immune-visibility. We call this CAPE-Packer.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Bootwala et al [5] demonstrated substantial reduction in binding to murine, rabbit, and human polyclonal antibodies. Another strategy for minimizing antibody visibility is employed by Yachnin et al [6], wherein they aim to decrease the presentation of MHC Class II (MHC-II) epitopes that are crucial for B-cell activation.…”

Section: Introductionmentioning

confidence: 99%

Guiding a language-model based protein design method towards MHC Class-I immune-visibility profiles for vaccines and therapeutics

Gasser

Oyarzún

Rajan

et al. 2023

Preprint

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Protein therapeutics promise to revolutionize medicine, with an arsenal of applications that include disrupting viral replication, acting as potent vaccines, and replacing genetically deficient proteins. Therapeutics must avoid triggering unwanted immune responses towards the therapeutic protein or viral vector proteins. In contrast, vaccines require a robust immune reaction targeting a broad range of pathogen variants. Therefore, computational methods modifying proteins' immune visibility, while maintaining functionality, are needed. This paper focuses on visibility to cytotoxic T-lymphocytes, which use the MHC Class I pathway to detect destruction targets. To explore the limits of modifying MHC-I immune visibility within the distribution of naturally occurring sequences, we developed a novel machine learning technique, CAPE-XVAE, that combines a language model with reinforcement learning to modify a protein's immune visibility. Our results show that CAPE-XVAE effectively modifies the MHC-I immune visibility of the HIV Nef protein. We contrast CAPE-XVAE to CAPE-Packer, a physics-based method we also developed, and observe that while the machine learning approach generates more natural appearing sequences, the physics-based approach achieves a greater reduction in immune visibility. Compared to CAPE-Packer, CAPE-XVAE has a propensity to suggest sequences that draw upon local sequence similarities in the training set. This is particularly important for vaccine development, to be representative of the real viral population and the approach holds promise for preserving both known and unknown functional constraints, which are essential for deimmunization of therapeutic proteins. CAPE-Packer, solely focuses on preserving the protein's fold, falling short of capturing this complexity.

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MHCEpitopeEnergy, a Flexible Rosetta-Based Biotherapeutic Deimmunization Platform

Cited by 15 publications

References 68 publications

Efficacy and Mechanism of Roxadustat plus Oral Iron in the Treatment of Elderly Chronic Kidney Disease with Anemia

Efficacy and Mechanism of Roxadustat plus Oral Iron in the Treatment of Elderly Chronic Kidney Disease with Anemia

Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics

Guiding a language-model based protein design method towards MHC Class-I immune-visibility profiles for vaccines and therapeutics

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