Biology subjects

Sanchez-Ruiz, J.

Publications and source records attributed to Sanchez-Ruiz, J..

3 recordsLinked to original sources

bioRxiv2025

Efficient searches in protein sequence space through AI-driven iterative learning

Protein sequence space is vast. This fact, together with the prevalence of epistasis, hampers the engineering of novel enzymes through library screening and is a major obstacle to any attempt to predict natural protein evolution. Recently, specialized methodologies have been used to determine fitness data on [~]260000 sequences for the gene of the enzyme dihydrofolate reductase and antibody affinity data for all combinations of the mutations present in the receptor binding domain (RBD) of the Omicron strain of SARS-CoV-2 ([~]30000 variants). We show that, upon iterative training on a total of just a few hundred variants, various state-of-the-art AI tools (multi-layer perceptron, random forest and XGBoost algorithms) find very high fitness variants of the enzyme and predict the antibody-evasion patterns of the RBD. This work provides a basis for efficient, widely applicable, low-throughput experimental approaches to assess viral protein evolution and to engineer enzymes for biotechnological applications.

bioinformatics↗

bioRxiv2022

Cell survival enabled by leakage of a labile metabolic intermediate

Many metabolic pathways are of ancient origin and have evolved over long periods of time (Noda-Garcia et al., 2018). Yet, new pathways can also emerge in short time scales in response, for instance, to the presence of anthropogenic chemicals in the environment (Copley, 2009). Models of metabolic pathway emergence and evolution often emphasize the acquisition of new reactions through horizontal gene transfer and promiscuous enzyme functionalities (Pal et al., 2005; Schulenburg & Miller, 2014; Copley, 2015; Noda-Garcia et al., 2018; Peracchi, 2018). A fundamentally different mechanism of metabolic innovation is revealed by the evolutionary repair experiments reported here. A block in the proline biosynthetic pathway that compromises cell survival is efficiently rescued by many single mutations (12 at least) in the gene of glutamine synthetase. The mutations cause the leakage to the intracellular milieu of a sequestered phosphorylated intermediate common to the biosynthetic pathways of proline and glutamine, thus generating a new route to proline. Metabolic intermediates may undergo a variety of chemical and enzymatic transformations, but are typically protected as shielded reaction intermediates or through channeling in multi-enzyme complexes and metabolons (Srere, 1987; Huang et al., 2001; Grunwald, 2018; Pareek et al., 2021). Our results show that intermediate leakage can readily occur and contribute to organismal adaptation. Enhanced availability of reactive molecules may enable the generation of new biochemical pathways. We therefore anticipate applications of mutation-induced leakage in metabolic engineering.

molecular biology↗

bioRxiv2020

Novel heme-binding enables allosteric modulation in an ancient TIM-barrel glycosidase

Glycosidases are phylogenetically widely distributed enzymes that are crucial for the cleavage of glycosidic bonds. Here, we present the exceptional properties of a putative ancestor of bacterial and eukaryotic family-1 glycosidases. The ancestral protein shares the TIM-barrel fold with its modern descendants but displays large regions with greatly enhanced conformational flexibility. Yet, the barrel core remains comparatively rigid and the ancestral glycosidase activity is stable, with an optimum temperature within the experimental range for thermophilic family-1 glycosidases. None of the ~5500 reported crystallographic structures of ~1400 modern glycosidases show a bound porphyrin. Remarkably, the ancestral glycosidase binds heme tightly and stoichiometrically at a well-defined buried site. Heme binding rigidifies this TIM-barrel and allosterically enhances catalysis. Our work demonstrates the capability of ancestral protein reconstructions to reveal valuable but unexpected biomolecular features when sampling distant sequence space. The potential of the ancestral glycosidase as a scaffold for custom catalysis and biosensor engineering is discussed.

biophysics↗