Biology subjects

Mora, A. N.

Publications and source records attributed to Mora, A. N..

3 recordsLinked to original sources

bioRxiv2026

Designing enzymes for new-to-nature chemistry and non-natural substrates with AlphaProtein Novo

Creating highly active enzymes for arbitrary reactions is a transformative goal for the molecular sciences (1). Traditional protein engineering (2,3) is constrained by a reliance on existing natural starting points, which are often challenging to discover. De novo design offers the potential to overcome this by creating enzymes from first principles (4), but has yet to achieve practically relevant catalytic properties. Here we present AlphaProtein Novo (AP Novo), a machine-learning pipeline that demonstrates, for the first time, that de novo enzyme design can outperform natural sequence mining in addressing challenging chemistry. We used AP Novo to design new-to-nature nitrene transferases to synthesise the pharmacophore piperidine with unprecedented product selectivity, and to create enzymes that degrade the environmental toxin DEHP under conditions that denature natural enzymes. We also obtained state-of-the-art catalytic efficiencies on two well-studied model reactions, and through iterative design and analysis found that key enablers of success were mechanism-inspired metrics based on AlphaFold 3 predictions and sequence-ensemble-based scoring of designed backbones. Our results show that de novo design has become a powerful complement to natural enzyme diversity for discovering catalysts for a range of applications.

synthetic biology↗

bioRxiv2022

SiRCle (Signature Regulatory Clustering) model integration reveals mechanisms of phenotype regulation in renal cancer

Clear cell renal cell carcinoma (ccRCC) tumours develop and progress via complex remodelling of the kidney epigenome, transcriptome, proteome, and metabolome. Given the subsequent tumour and inter-patient heterogeneity, drug-based treatments report limited success, calling for multi-omics studies to extract regulatory relationships, and ultimately, to develop targeted therapies. However, current methods are unable to extract nonlinear multi-omics perturbations. Here, we present SiRCle (Signature Regulatory Clustering), a novel method to integrate DNA methylation, RNA-seq and proteomics data. Applying SiRCle to a case study of ccRCC, we disentangle the layer (DNA methylation, transcription and/or translation) where dys-regulation first occurs and find the primary biological processes altered. Next, we detect regulatory differences between patient subsets by using a variational autoencoder to integrate omics data followed by statistical comparisons on the integrated space. In ccRCC patients, SiRCle allows to identify metabolic enzymes and cell-type-specific markers associated with survival along with the likely molecular driver behind the genes perturbations.

cancer biology↗

bioRxiv2022

HIRA loss transforms FH-deficient cells

Fumarate Hydratase (FH) is a mitochondrial enzyme that catalyses the reversible hydration of fumarate to malate in the TCA cycle. Germline mutations of FH lead to HLRCC, a cancer syndrome characterised by a highly aggressive form of renal cancer(1). Although HLRCC tumours metastasise rapidly, FH-deficient mice develop premalignant cysts in the kidneys, rather than carcinomas (2). How Fh1-deficient cells overcome these tumour suppressive events during transformation is unknown. Here, we perform a genome-wide CRISPR/Cas9 screen to identify genes that, when ablated, enhance the proliferation of Fh1-deficient cells. We found that the depletion of HIRA enhances proliferation and invasion of Fh1-deficient cells in vitro and in vivo. Mechanistically, Hira loss enables the activation of MYC and its target genes, increasing nucleotide metabolism specifically in Fh1-deficient cells, independent of its histone chaperone activity. These results are instrumental for understanding mechanisms of tumorigenesis in HLRCC and the development of targeted treatments for patients.

cancer biology↗