Mark J. S. Kelly

A Hybrid Physics-Deep Learning Framework for Combinatorial De Novo Design of Small-Molecule Binding Proteins

This paper introduces a hybrid physics-deep learning framework for designing small-molecule binding proteins, achieving experimental success in binding affinity and structural accuracy.

AcrIF11 is a potent CRISPR-specific ADP-ribosyltransferase encoded by phage and plasmid

This study characterizes AcrIF11, an ADP-ribosyltransferase that inhibits CRISPR-Cas systems with high potency and specificity, and shows its reversibility through macrodomain enzymes.

Deep learning guided design of dynamic proteins

This paper designs dynamic proteins with switch-like behavior using deep learning, validated by structure solving and simulations showing controllable conformational changes.

De novo design of proteins that bind naphthalenediimides, powerful photooxidants with tunable photophysical properties

This paper designs a protein to bind naphthalenediimides and evaluates its ability to generate reactive species for proximity labeling.

Requirements for efficient endosomal escape by designed mini-proteins

This paper identifies the requirements for efficient endosomal escape by ZF5.3, a mini-protein, showing pH-induced unfolding and lipid-BMP interaction are critical for its function.

Biophysical basis of cellular multi-specificity encoded in a model molecular switch

The paper investigates how the GTPase Ran/Gsp1 achieves functional multi-specificity through biophysical and genetic perturbations, revealing that its effects are linked to kinetic parameters of the switch cycle rather than direct interaction sites.