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Biology subjects

Anslyn, E. V.

Publications and source records attributed to Anslyn, E. V..

4 recordsLinked to original sources

Learning from human and chemical languages to predict biological function

Understanding how molecular structure encodes biological function remains a grand challenge in drug discovery. Here, we present PubCheF-1, a deep learning model that predicts literature-derived biological function directly from chemical structure. PubCheF-1 was trained on a dataset linking molecules to labels derived from the scientific articles in which they appear, a strategy that connects disparate compounds through the language used to describe their functionalities. When tasked with identifying inhibitors of {beta}-lactamases, including enzymes considered largely refractory to inhibition, PubCheF-1 predicted structurally distinct compounds that collectively have activity against all {beta}-lactamase classes. Furthermore, hit compounds directly bind the enzyme active site, restore antibiotic efficacy in multidrug-resistant high-priority pathogens, and demonstrate potent activity in animal infection models. Together, these findings establish that machine learning-based prediction of biological function derived from the language of scientific literature allows the identification of bioactive molecules at high hit rates, thereby accelerating therapeutic discovery.

bioinformatics↗

Robust and scalable single-molecule protein sequencing with fluorosequencing

The need to accurately survey proteins and their modifications with ever higher sensitivities, particularly in clinical settings with limited samples, is spurring development of new single molecule proteomics technologies. Fluorosequencing is one such highly parallelized single molecule peptide sequencing platform, based on determining the sequence positions of select amino acid types within peptides to enable their identification and quantification from a reference database. Here, we describe substantial improvements to fluorosequencing, including identifying fluorophores compatible with the sequencing chemistry, mitigating dye-dye interactions through the use of extended polyproline linkers, and developing an end-to-end workflow for sample preparation and sequencing. We demonstrate by fluorosequencing peptides in mixtures and identifying a target neoantigen from a database of decoy MHC peptides, highlighting the potential of the technology for high sensitivity clinical applications.

molecular biology↗

Photoredox-catalyzed decarboxylative C-terminal differentiation for bulk and single molecule proteomics

Methods for the selective labeling of biogenic functional groups on peptides are being developed and used in the workflow of both current and emerging proteomics technologies, such as single-molecule fluorosequencing. To achieve successful labeling with any one method requires that the peptide fragments contain the functional group for which the labeling chemistry is designed. In practice, only two functional groups are present on every peptide fragment regardless of the protein cleavage site, namely, an N-terminal amine and a C-terminal carboxylic acid. Developing a global-labeling technology, therefore, requires one to specifically target the N- and/or C-terminus of peptides. In this work, we showcase the first successful application of photocatalyzed C-terminal decarboxylative-alkylation for peptide mass-spectrometry and single molecule protein sequencing, that can be broadly applied to any proteome. We demonstrate that peptides in complex mixtures generated from enzymatic digests from bovine serum albumin, as well as protein mixtures from yeast and human cell extracts, can be site-specifically labeled at their C-terminal residue with a Michael acceptor. Using two distinct analytical approaches, we characterize C-terminal labeling efficiencies of greater than 50% across complete proteomes and document the proclivity of various C-terminal amino acid residues for decarboxylative-labeling, showing histidine and tryptophan to be the most disfavored. Finally, we combine C-terminal decarboxylative labeling with an orthogonal carboxylic acid labeling technology in tandem, to establish a new platform for fluorosequencing.

biochemistry↗

Solid-Phase Peptide Capture and Release for Bulk and Single-Molecule Proteomics

The field of proteomics has expanded recently with more sensitive techniques for the bulk measurement of peptides as well as single-molecule techniques. One limiting factor for some of these methods is the need for multiple chemical derivatizations and highly pure proteins free of contaminants. We demonstrate a solid-phase capture strategy suitable for the proteolysis, purification, and subsequent chemical modification of peptides. We use this resin on an HEK293T cell lysate and perform one-pot proteolysis, capture, and derivatization to generate a cellular proteome that identified over 40,000 bead-bound peptides. We also show that this capture can be reversed in a traceless manner, such that it is amenable for single-molecule proteomics techniques. With this technique, we perform a fluorescent labeling and C-terminal derivatization on a peptide and subject it to fluorosequencing, demonstrating that washing the resin is sufficient to remove excess dyes and other reagents prior to single-molecule protein sequencing.

biochemistry↗