Predicting and Interpreting Protein Developability Via Transfer of Convolutional Sequence Representation.

Engineered proteins have emerged as novel diagnostics, therapeutics, and catalysts. Often, poor protein developability─quantified by expression, solubility, and stability─hinders utility. The ability to predict protein developability from amino acid sequence would reduce the experimental burden when selecting candidates.

A Platform for Deep Sequence-Activity Mapping and Engineering Antimicrobial Peptides.

Developing potent antimicrobials, and platforms for their study and engineering, is critical as antibiotic resistance grows. A high-throughput method to quantify antimicrobial peptide and protein (AMP) activity across a broad continuum would be powerful to elucidate sequence-activity landscapes and identify potent mutants. Yet the complexity of antimicrobial activity has largely constrained the scope and mechanistic bandwidth of AMP variant analysis.

High-throughput developability assays enable library-scale identification of producible protein scaffold variants.

Proteins require high developability-quantified by expression, solubility, and stability-for robust utility as therapeutics, diagnostics, and in other biotechnological applications. Measuring traditional developability metrics is low throughput in nature, often slowing the developmental pipeline. We evaluated the ability of 10 variations of three high-throughput developability assays to predict the bacterial recombinant expression of paratope variants of the protein scaffold Gp2.

Biophysical Characterization Platform Informs Protein Scaffold Evolvability.

Evolving specific molecular recognition function of proteins requires strategic navigation of a complex mutational landscape. Protein scaffolds aid evolution via a conserved platform on which a modular paratope can be evolved to alter binding specificity. Although numerous protein scaffolds have been discovered, the underlying properties that permit binding evolution remain unknown.

Presence of Rigid Red Blood Cells in Blood Flow Interferes with the Vascular Wall Adhesion of Leukocytes.

The symptoms of many blood diseases can often be attributed to irregularities in cellular dynamics produced by abnormalities in blood cells, particularly red blood cells (RBCs). Contingent on the disease and its severity, RBCs can be afflicted with increased membrane rigidity as seen in malaria and sickle cell disease. Despite this understanding, little experimental work has been conducted toward understanding the effect of RBC rigidity on cellular dynamics in physiologic blood flow.

Exploring deformable particles in vascular-targeted drug delivery: Softer is only sometimes better.

The ability of vascular-targeted drug carriers (VTCs) to localize and bind to a targeted, diseased endothelium determines their overall clinical utility. Here, we investigate how particle modulus and size determine adhesion of VTCs to the vascular wall under physiological blood flow conditions. In general, deformable microparticles (MPs) outperformed nanoparticles (NPs) in all experimental conditions tested.

In vivo evaluation of vascular-targeted spheroidal microparticles for imaging and drug delivery application in atherosclerosis.

Objective: Vascular-targeting remains a promising strategy for improving the diagnosis and treatment of coronary artery disease (CAD) by providing localized delivery of imaging and therapeutic agents to atherosclerotic lesions. In this work we evaluate how size and shape affects the capacity for a vascular-targeted carrier system to bind inflamed endothelial cells over plaque using ApoE -/- mice with developed atherosclerosis.

Method: We investigated the adhesion levels along mouse aortae of ellipsoidal and spherical particles targeted to the inflammatory molecules E-selectin and VCAM-1, as well as the biodistribution of targeted and untargeted particles in major organs following injection via tail-vein and a 30-min circulation time.