bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.64898/2026.08.03.742579

Humanized Anti-PD-1 Antibodies Generated Using The Conditional Kernel-Elastic Autoencoder

Shi, Y.·Li, H.·Liu, P.·Bunick, C. G.·Tang, S.·Wang, J.·Batista, V. S.
View original source ↗Export metadata ↓

Abstract

The human immune system excels at generating highly effective antibodies through natural selection and somatic hypermutation, but adapting these antibodies for therapeutic use, referred to as "antibody medicine-likeness", requires careful consideration of biochemical and physiological properties. Traditional redesign methods are often slow and limited in scope. In this study, we introduce a machine learning-based approach to evolve new anti-PD-1 antibodies within a chemically informed latent space using a conditional kernel-elastic autoencoder (CKEA) between nivolumab and pembrolizumab, both of which bind the FG-loop "hotspot" of PD-1 in the most distantly related orientations, differing by 174{degrees}. This generative framework is designed to preserve favorable therapeutic features while exploring variants with different potency, ultimately for improved potency. To evaluate structural and functional viability, we performed molecular dynamics (MD) simulations of the generated antibody - PD-1 complexes and described their MD properties. These simulations reveal detailed free-energy landscapes and identify stable binding conformations, providing a strong basis for experimental validation. To validate our designs, we expressed and experimentally tested the antibodies for binding affinity to PD-1. Upon expression and purification, three out of six designed antibodies exhibited some binding to PD-1, whose properties could likely be improved using other computational saturation mutagenesis or laboratory evolution. Our results demonstrate the potential of artificial intelligence (AI)-guided interpolation methods to generate novel, high-affinity antibodies with therapeutic promise, offering a powerful strategy for next-generation antibody development. SYNOPSIS TOCCombination of MD simulations with machine learning algorithms could revolutionize the antibody-breeding sciences to lead to new antibody discovery that is compatible with or better than naturally occurring antibodies. Topics of Content (TOC)Fingerprints of R86 finger of PD-1 are recognized by our designed P2N_2 anti-PD-1 antibody according to our MD simulations O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=173 SRC="FIGDIR/small/742579v1_ufig1.gif" ALT="Figure 1000"> View larger version (49K): org.highwire.dtl.DTLVardef@130fd5aorg.highwire.dtl.DTLVardef@1495cd8org.highwire.dtl.DTLVardef@16e822forg.highwire.dtl.DTLVardef@25004c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Explore related subjects

biochemistryPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Shi, Y., Li, H., Liu, P., Bunick, C. G., Tang, S., Wang, J., Batista, V. S.. 2026-08-04. Humanized Anti-PD-1 Antibodies Generated Using The Conditional Kernel-Elastic Autoencoder. https://doi.org/10.64898/2026.08.03.742579

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Aging Remodels the Female Skeletal Muscle Proteome Toward Matrix, Chromatin and Lysosomal Programs that Track Loss of Physical Function

Loss of skeletal muscle strength and mobility is among the most consequential features of human aging, yet the molecular programs that accompany this decline in women remain poorly understood. Here, we performed deep comprehensive data-independent acquisition (DIA) proteomic profiling of vastus lateralis biopsies from 10 younger (24-30 years) and 10 older (70-84 years) healthy women enrolled through the NIH Common Fund Cellular Senescence Network (SenNet), with matched measurements of grip strength and gait speed. Of 2,391 quantified protein groups, 163 were significantly altered with age, and partial least squares-discriminant analysis completely separated the age groups (cross-validated AUC = 1.00). Older muscle showed increased extracellular matrix and vascular remodeling proteins (TIMP3, COL8A1, ELN, FBN1), nuclear, chromatin and RNA-binding proteins (HMGB1, HMGB2, histone H1.0, MATR3, NCL), and lysosomal and senescence-associated secretory phenotype (SASP)-associated proteins (CTSZ, CTSD, PSAP), together with reduced glycolytic and energetic proteins (GAPDH, ENO3, PHKA1, CYCS). Age effects were robust to adjust for body mass index (BMI). Integrating differential abundance, multivariate importance and participant-level consistency, we defined a 24-protein skeletal muscle aging signature whose score separated all younger from all elderly women. Combining grip strength and gait speed into a combined function score, we found that 23 of the 24 signature proteins correlated with physical function (FDR < 0.05), and the signature score correlated strongly with function (r = -0.79). The senescence-associated alarmins HMGB1 and HMGB2 emerged as lead proteins: HMGB1 showed the strongest association with function (r = -0.86), and both remained associated after adjustment for age group. Together, these data define a senotype proteomic program in aging female skeletal muscle and a molecular signature of muscle function that, after validation, may serve as a readout for interventions that aim to preserve physical performance in elderly women.

biochemistry↗
bioRxiv2026

SUMOylation Regulates IRF2BP2 Nuclear Localization and Stability

Interferon Regulatory Factor-2 Binding Protein 2 (IRF2BP2) is a transcriptional cofactor implicated in diverse biological processes. Although it functions primarily as a repressor, it can also activate gene expression. However, the mechanisms governing IRF2BP2 regulation remain poorly understood. Here, we demonstrate that IRF2BP2 interacts with UBE2I, the SUMO E2 ligase, and undergoes multi-SUMOylation, which enhances its nuclear localization. We further show that IRF2BP2 nuclear import is importin-{beta}-dependent and requires the functional nuclear localization signal (NLS). IRF2BP2 preferentially accumulates in transcriptionally active euchromatin in both resting and S-phase cells, consistent with its role in transcriptional control. We further reveal that SUMOylation contributes to IRF2BP2 stability. Moreover, IRF2BP2 is also ubiquitinated, predominantly through K6-linked ubiquitin chains, a non-proteolytic modification that aligns with our observation that IRF2BP2 is not degraded by the proteasome. Together, these findings identify SUMOylation and non-proteolytic ubiquitination as key mechanisms regulating IRF2BP2, highlighting a novel SUMO1-NLS-importin-{beta}-dependent pathway that governs its localization.

biochemistry↗
bioRxiv2026

S-adenosylmethionine supply controls DNA methylation turnover in synovial sarcoma

Background: Methionine is the nutrient source of the metabolite S-adenosylmethionine (SAM) used to methylate chromatin for regulation of gene expression. Disruptions to this metabolic supply, including nutritional deficiency of certain B vitamins, alter chromatin methylation and have been implicated in tumor growth. Objective: To define how cellular SAM supply controls DNA methylation dynamics and the disruption of oncogenic gene expression in synovial sarcoma. Methods: Cell line models of synovial sarcoma were treated with the DNA methyltransferase inhibitor azacitidine or the small-molecule MAT2A inhibitor AG-270, which blocks SAM synthesis from methionine. Intracellular SAM concentrations were quantified by liquid chromatography-mass spectrometry. Global DNA methylation rates were measured by stable isotope tracing with [2H3-methyl]-methionine. Genomic sites of altered DNA methylation were identified by EM-seq and the associated transcriptional changes measured by RNA-seq. Results: Inhibition of SAM synthesis reduced intracellular SAM concentration from 94 uM to 5.6 uM (p value < 0.0001) at 24 hours. This was associated with a 19% decrease (p value < 0.0001) in the global 5-methyldeoxycytosine turnover rate, while total DNA methylation levels were maintained. In contrast to the global DNA hypomethylation induced by azacitidine, SAM depletion resulted in a redistribution of DNA methylation with loss at 252 and gain at 206 genomic sites, and the transcriptional response to SAM depletion was not associated with changes in promoter methylation at the altered genes. Both azacitidine and SAM depletion activated mesenchymal genes, while suppressing cell cycle progression. Conclusions: Metabolic supply of SAM is a major regulator of DNA methylation turnover providing a mechanism by which nutritional or genetic disruptions to SAM metabolism can alter chromatin methylation and gene expression.

biochemistry↗