Biology subjects

Agrawal, H.

Publications and source records attributed to Agrawal, H..

3 recordsLinked to original sources

bioRxiv2026

An Energy Landscape Approach to Miniaturizing Enzymes using Protein Language Model Embeddings

AO_SCPLOWBSTRACTC_SCPLOWWe present a general approach to find amino acid sequences corresponding to the most compact enzyme likely to retain the structure of a given catalytic site. Our approach is based on using Monte Carlo (MC) simulations to sample an energy landscape where minima correspond, by construction, to sequences with the aforementioned properties. Building on previous work (Wu et al., 2025) and with the BAGEL package (Lala et al., 2025), we implement a route to achieve this goal using only the information extracted from a protein language model (PLM), without structural information. After generating a set of candidate sequences with this PLM-guided BAGEL optimization, we further filter potential candidates for downstream experimental validation using a two-stage protocol. First, deep-learning-based structure prediction models (ESMFold, Chai-1, Boltz-2) are used to identify a structural consensus among designs with highly conserved active-site geometries, yielding many candidates with active-site RMSD below a few angstroms relative to the wild-type and pLDDT scores above 80. Second, molecular dynamics simulations are performed on a filtered subset of sequences (based on active-site RMSD and SolubleMPNN log-likelihoods) to evaluate active-site stability when including thermal fluctuations. For the most promising enzymes, these yield RMSF values in the active site below 1.0 [A] and an active-site RMSD drift between 0.5 and 1.5 [A], making these mini-variants comparable to the wild type, though outcomes vary across enzymes. Given the protocols generality, we believe these results represent a step forward in AI-guided enzyme design. To facilitate rapid experimental validation by the broader community, we open-source all sequences generated by our computational pipeline. These include designs for four representative enzymes of this study: PETase, subtilisin Carlsberg (serine protease), Taq DNA polymerase, and VioA.

bioinformatics↗

bioRxiv2025

EIF3H Regulates ERK-Driven Oncogenic Signaling in Breast Cancer Metastasis

Breast cancer remains a leading cause of cancer-related mortality among women, with metastasis being the primary driver of poor prognosis. The ubiquitin-proteasome system (UPS) is a central regulator of protein homeostasis, and its dysregulation is associated with multiple cancers. Within this system, deubiquitinating enzymes (DUBs), which remove ubiquitin moieties from target proteins and thereby modulate their stability and function, have emerged as attractive therapeutic targets. Eukaryotic initiation factor 3 subunit H (EIF3H), a JAMM family DUB, is overexpressed in multiple cancers and implicated in stabilizing oncogenic proteins. Using clinical transcriptomic datasets, we identified EIF3H as significantly upregulated in breast invasive carcinoma, with high expression correlating with poor patient outcomes. Functional assays demonstrated that EIF3H overexpression enhances proliferation, migration, and invasion of breast cancer cells, whereas its knockdown suppresses these traits. Mechanistically, EIF3H physically interacts with and deubiquitinates phosphorylated ERK (pERK), preventing its degradation and sustaining MAPK pathway activation. This represents the first report of pERK as a direct EIF3H substrate, revealing a novel mechanism linking EIF3H to metastatic progression. Moreover, EIF3H-deficient cells display increased sensitivity to chemotherapeutic drugs, suggesting that pharmacological inhibition of EIF3H may simultaneously impair metastasis and improve therapeutic efficacy. Collectively, our findings identify EIF3H as a potential therapeutic target for combating metastatic breast cancer.

cancer biology↗

bioRxiv2024

Proliferative events ameliorate DNA damage accumulation without affecting function in hematopoietic stem cells

Upon aging, HSCs show functional decline with increased proliferation, myeloid skewing, and poor engraftment efficiency. Accumulation of DNA damage has been causally linked with this phenomenon, with the debatable role of proliferative events. In this study, we sought to enquire the effect of increased hematopoietic stem cell (HSC) proliferation during the lifetime on the hematopoietic aging in mice. Multiple rounds of blood withdrawals were performed between two to twelve months of adult life to maintain higher proliferation rate in HSC population. Our experiments showed little effect of increased proliferation rate on age-associated functional decline in hematopoietic system. However, we noted a decrease in the double strand breaks (DSBs) accumulated with age in mice that underwent serial bleeding regimen. Analysis of single-cell sequencing data from mouse and human HSPCs showed enrichment of DNA damage response pathways confirmed by increased expression of the genes involved. Importantly, we demonstrate that the induction of HSC proliferation in aged mice is sufficient to decrease the load of DSBs. Hence, our results show that proliferative events during lifetime might aid in clearing age-associated DSBs. While these DNA damages might not be directly linked with the functional decline, proliferation induced clearance can have clinical implications.

cell biology↗