Colin M. Edge

In this study, we report the optimization of screening hit 1 to the selective brain-penetrant LRRK2 inhibitor 39.

Analysis of the molecular and structural features of the GSK crystal structure database and Cambridge Structural Database leads to improved reliability in hydrogen bond propensity models for pharmaceutical polymorphs.

Simulation and data analysis have evolved into powerful methods for discovering and understanding molecular modes of action and designing new compounds to exploit these modes. The combination provides a strong impetus to create and exploit new tools and techniques at the interfaces between physics, biology, and data science as a pathway to new scientific insight and accelerated discovery. In this context, we explore the rational design of novel antimicrobial peptides (short protein sequences exhibiting broad activity against multiple species of bacteria). We show how datasets can be harvested to reveal features which inform new design concepts. We introduce new analysis and visualization tools: a graphical representation of the k-mer spectrum as a fundamental property encoded in antimicrobial peptide databases and a data-driven representation to illustrate membrane binding and permeation of helical peptides.

Aldose reductase is the first enzyme of the polyol pathway in which glucose is converted to fructose via sorbitol. The understanding of this key enzyme is important as it has been linked to some diabetes mellitus complications. The mechanism of the enzyme was investigated using a hybrid quantum mechanics/molecular mechanics (QM/MM) method. It was found that depending on the protonation state of His110 the mechanism can be concerted or stepwise and the proton donor can be either Tyr48 or His110. These findings are different from the previous theoretical studies based on QM/MM calculations using either AM1 or HF/4-31G, in which the reduction is, respectively, a stepwise or one-step process. The QM/MM energy barriers for the reduction of d-glyceraldehyde were evaluated at a B3LYP/6-31G* level for both HIP and HIE protonation states of His110. These were, respectively, 6.5 ± 2.2 and 16.7 ± 1.0 kcal/mol, which makes only the HIE protonation state consistent with the experimental value of 14.8 kcal/mol derived from kinetics experiments and makes Tyr48 the most probable proton donor.

An ability to organize and encapsulate multiple active proteins into defined objects and spaces at the nanoscale has potential applications in biotechnology, nanotechnology, and synthetic biology. Previously, we have described the design, assembly, and characterization of peptide-based self-assembled cages (SAGEs). These ≈100 nm particles comprise thousands of copies of de novo designed peptide-based hubs that array into a hexagonal network and close to give caged structures. Here, we show that, when fused to the designed peptides, various natural proteins can be co-assembled into SAGE particles. We call these constructs pSAGE for protein-SAGE. These particles tolerate the incorporation of multiple copies of folded proteins fused to either the N or the C termini of the hubs, which modeling indicates form the external and internal surfaces of the particles, respectively. Up to 15% of the hubs can be functionalized without compromising the integrity of the pSAGEs. This corresponds to hundreds of copies giving mM local concentrations of protein in the particles. Moreover, and illustrating the modularity of the SAGE system, we show that multiple different proteins can be assembled simultaneously into the same particle. As the peptide–protein fusions are made via recombinant expression of synthetic genes, we envisage that pSAGE systems could be developed modularly to actively encapsulate or to present a wide variety of functional proteins, allowing them to be developed as nanoreactors through the immobilization of enzyme cascades or as vehicles for presenting whole antigenic proteins as synthetic vaccine platforms.