Biology subjects

Kowalski, D.

Publications and source records attributed to Kowalski, D..

3 recordsLinked to original sources

bioRxiv2025

An Ehrlich-inspired retrobiosynthesis of pharmaceutical scaffolds

Brewers yeast (Saccharomyces cerevisiae) acquires nitrogen from branched-chain and aromatic amino acids via the Ehrlich pathway, generating flavor (fusel) byproducts. Recently, diverting 4-hydroxyphenylacetaldehyde from Ehrlich catabolism of -tyrosine has enabled microbial production of opioids and other plant benzylisoquinolines. Yet, fusel metabolism is versatile in substrate scope, offering an untapped entry point for synthesizing structurally diverse aldehydes. Here, we repurpose the yeast Ehrlich pathway into a modular biocatalytic conduit for manufacturing privileged pharmaceutical alkaloids. We utilize retrobiosynthetic analysis and enzyme screening to derive scaffolds representative of solifenacin, colchicine, and ephedrine pharmaceuticals from simple amino acids. We survey wild yeasts for catabolism of -phenylglycine and demonstrate Ehrlich conversion to benzyl alcohol or (R)-phenylacetylcarbinol by 29 strains across nine genera. Implementing an {omega}-transaminase enables production of norephedrine from a simple amino acid input. This work unveils a generalizable biocatalytic route to clinically important alkaloids by exploiting metabolic logic from a yeast flavor pathway.

synthetic biology↗

bioRxiv2024

ARTEM: a method for RNA tertiary motif identification with backbone permutations, and its example application to kink-turn-like motifs

The functions of non-coding RNAs are largely defined by their three-dimensional structures. RNA 3D structure is organized hierarchically and consists of recurrent building blocks called tertiary motifs. The computational problem of RNA tertiary motif search remains largely unsolved, as standard approaches are restrained by sequence, interaction network, or backbone topology. We developed the ARTEM superposition algorithm, which is free from these limitations. Here, we present a version of ARTEM that allows automated searches of RNA and DNA structure databases to identify 3D structure motifs. We exemplify it by a search of motifs isosteric to the kink-turn motif. This widespread motif plays a role in many aspects of RNA function, and its mutations are known to cause several human syndromes. With ARTEM, we discovered two new kink-turn topologies, multiple no-kink variants of the motif, and showed that a ribosomal junction in bacteria forms either a kink or a no-kink variant depending on the species. Additionally, we identified kink-turns in the catalytic core of group II introns, whose structures have not previously been characterized as containing kink-turns. ARTEM opens a fundamentally new way to study RNA and DNA 3D folds and motifs and analyze their correlations and variations.

bioinformatics↗

bioRxiv2018

The structure of the genetic code as an optimal graph clustering problem

The standard genetic code (SGC) is the set of rules by which genetic information is translated into proteins, from codons, i.e. triplets of nucleotides, to amino acids. The questions about the origin and the main factor responsible for the present structure of the code are still under a hot debate. Various methodologies have been used to study the features of the code and assess the level of its potential optimality. Here, we introduced a new general approach to evaluate the quality of the genetic code structure. This methodology comes from graph theory and allows us to describe new properties of the genetic code in terms of conductance. This parameter measures the robustness of codon groups against the potential changes in translation of the protein-coding sequences generated by single nucleotide substitutions. We described the genetic code as a partition of an undirected and unweighted graph, which makes the model general and universal. Using this approach, we showed that the structure of the genetic code is a solution to the graph clustering problem. We presented and discussed the structure of the codes that are optimal according to the conductance. Despite the fact that the standard genetic code is far from being optimal according to the conductance, its structure is characterised by many codon groups reaching the minimum conductance for their size. The SGC represents most likely a local minimum in terms of errors occurring in protein-coding sequences and their translation.

systems biology↗