Biology subjects

Kaufman, S.

Publications and source records attributed to Kaufman, S..

4 recordsLinked to original sources

bioRxiv2026

Benchmarking AlphaFold and related deep learning approaches for modeling antibody and TCR antigen recognition

Determining the structural basis of antigen recognition by antibodies and T cell receptors (TCRs) provides critical insights into effective immune targeting and can inform design of biotherapeutics and vaccines. Accurate computational modeling of antibodies and TCRs in complex with their targets poses a major challenge for predictive methods, including AlphaFold, which is generally accurate for modeling protein complexes but has shown limited success for immune recognition. In this study we assessed the performance of AlphaFold2, AlphaFold3, increased sampling protocols, and related deep learning methods for modeling antibody-protein, antibody-peptide, and TCR-peptide-major histocompatibility complex (pMHC) recognition. We show that increased sampling and AlphaFold3 generally improve performance relative to default sampling and AlphaFold2, however predictive accuracy and improvement levels varied considerably among interface classes, with antibody-peptide complexes representing a challenge despite their small antigen size. Comparing per-case success across methods showed some complementarity, indicating opportunities for increased success through model pooling approaches, for instance increasing antibody-peptide near-native success from 41% to 59%. Analysis of AlphaFold confidence scores and modeling of a noncanonical complex provided further insights into predictive performance. These results highlight considerations for predictive antibody and TCR complex modeling efforts, while revealing key distinctions among protocols, scoring, and immune complex classes.

bioinformatics↗

bioRxiv2021

Impaired T-cell and antibody immunity after COVID-19 infection in chronically immunosuppressed transplant recipients

Assessment of T-cell immunity to the COVID-19 coronavirus requires reliable assays and is of great interest, given the uncertain longevity of the antibody response. Some recent reports have used immunodominant spike (S) antigenic peptides and anti-CD28 co-stimulation in varying combinations to assess T-cell immunity to SARS-CoV-2. These assays may cause T-cell hyperstimulation and could overestimate antiviral immunity in chronically immunosuppressed transplant recipients, who are predisposed to infections and vaccination failures. Here, we evaluate CD154-expressing T-cells induced by unselected S antigenic peptides in 204 subjects-103 COVID-19 patients and 101 healthy unexposed subjects. Subjects included 72 transplanted and 130 non-transplanted subjects. S-reactive CD154+T-cells co-express and can thus substitute for IFN{gamma} (n=3). Assay reproducibility in a variety of conditions was acceptable with coefficient of variation of 2-10.6%. S-reactive CD154+T-cell frequencies were a) higher in 42 healthy unexposed transplant recipients who were sampled pre-pandemic, compared with 59 healthy non-transplanted subjects (p=0.02), b) lower in Tr COVID-19 patients compared with healthy transplant patients (p<0.0001), c) lower in Tr patients with severe COVID-19 (p<0.0001), or COVID-19 requiring hospitalization (p<0.05), compared with healthy Tr recipients. S-reactive T-cells were not significantly different between the various COVID-19 disease categories in NT recipients. Among transplant recipients with COVID-19, cytomegalovirus co-infection occurred in 34%; further, CMV-specific T-cells (p<0.001) and incidence of anti-receptor-binding-domain IgG (p=0.011) were lower compared with non-transplanted COVID-19 patients. Healthy unexposed transplant recipients exhibit pre-existing T-cell immunity to SARS-CoV-2. COVID-19 infection leads to impaired T-cell and antibody responses to SARS-CoV-2 and increased risk of CMV co-infection in transplant recipients.

immunology↗

bioRxiv2021

Molecular strategies for antibody binding and escape of SARS-CoV-2 and its mutations

The COVID19 pandemic, caused by SARS-CoV-2, has infected more than 100 million people worldwide. Due to the rapid spreading of SARS-CoV-2 and its impact, it is paramount to find effective treatments against it. Human neutralizing antibodies are an effective method to fight viral infection. However, the recent discovery of new strains that substantially change the S-protein sequence has raised concern about vaccines and antibodies effectiveness. Here, we investigated the binding mechanisms between the S-protein and several antibodies. Multiple mutations were included to understand the strategies for antibody escape in new variants. We found that the combination of mutations K417N and E484K produced higher binding energy to ACE2 than the wild type, suggesting higher efficiency to enter host cells. The mutations effect depends on the antibody class. While Class I enhances the binding avidity in the presence of N501Y mutation, class II antibodies showed a sharp decline in the binding affinity. Our simulations suggest that Class I antibodies will remain effective against the new strains. In contrast, Class II antibodies will have less affinity to the S-protein, potentially affecting these antibodies efficiency.

biophysics↗

bioRxiv2018

Disruption of IRE1α through its Kinase Domain Attenuates Multiple Myeloma

Multiple myeloma (MM) arises from malignant immunoglobulin-secreting plasma cells and remains an incurable, often lethal disease despite recent therapeutic advances. The unfolded-protein response sensor IRE1 supports protein secretion by deploying a kinase-endoribonuclease module to activate the transcription factor XBP1s. MM cells may coopt the IRE1-XBP1s pathway; however, the validity of IRE1 as a potential MM therapeutic target is controversial. Here we show that genetic disruption of IRE1 or XBP1s, or pharmacologic IRE1 kinase inhibition, attenuated subcutaneous or orthometastatic growth of MM tumors in mice, and augmented efficacy of two well-established frontline antimyeloma agents, bortezomib or lenalidomide. Mechanistically, IRE1 perturbation inhibited expression of key components of the ER-associated degradation machinery, as well as cytokines and chemokines known to promote MM growth. Selective IRE1 kinase inhibition reduced viability of CD138+ plasma cells while sparing CD138- cells from bone marrow of newly diagnosed MM patients or patients whose disease relapsed after 1 - 4 lines of treatment in both US- and EU-based cohorts. IRE1 inhibition preserved survival and glucose-induced insulin secretion by pancreatic microislets. Together, these results establish a strong therapeutic rationale for targeting IRE1 with kinase-based small-molecule inhibitors in MM.\n\nSignificance statementMultiple myeloma (MM) is a lethal malignancy of plasma cells. MM cells have an expanded endoplasmic reticulum (ER) that is constantly under stress due to immunoglobulin hyperproduction. The ER-resident sensor IRE1 mitigates ER stress by expanding the ERs protein-folding capacity while supporting proteasomal degradation of misfolded ER proteins. IRE1 elaborates these functions by deploying its cytoplasmic kinase-RNase module to activate the transcription factor XBP1s. The validity of IRE1 as a potential therapeutic target in MM has been questioned. Using genetic and pharmacologic disruption in vitro and in vivo, we demonstrate that the IRE1-XBP1s pathway plays a critical role in MM growth. We further show that IRE1s kinase domain is an effective and safe potential small-molecule target for MM therapy.

cancer biology↗