Biology subjects

Lubner, J. M.

Publications and source records attributed to Lubner, J. M..

5 recordsLinked to original sources

bioRxiv2025

Massively parallel assessment of designed protein solution properties using mass spectrometry and peptide barcoding

Library screening and selection methods can determine the binding activities of individual members of large protein libraries given a physical link between protein and nucleotide sequence, which enables identification of functional molecules by DNA sequencing. However, the solution properties of individual protein molecules cannot be probed using such approaches because they are completely altered by DNA attachment. Mass spectrometry enables parallel evaluation of protein properties amenable to physical fractionation such as solubility and oligomeric state, but current approaches are limited to libraries of 1,000 or fewer proteins. Here, we improved mass spectrometry barcoding by co-synthesizing proteins with barcodes optimized to be highly multiplexable and minimally perturbative, scaling to libraries of >5,000 proteins. We use these barcodes together with mass spectrometry to assay the solution behavior of libraries of de novo-designed monomeric scaffolds, oligomers, binding proteins and nanocages, rapidly identifying design failure modes and successes.

biochemistry↗

bioRxiv2024

Bond-centric modular design of protein assemblies

We describe a modular bond-centric approach to protein nanomaterial design inspired by the rich diversity of chemical structures that can be generated from the small number of atomic valencies and bonding interactions. We design protein building blocks with regular coordination geometries and bonding interactions that enable the assembly of a wide variety of closed and opened nanomaterials using simple geometrical principles. Experimental characterization confirms successful formation of more than twenty multi-component polyhedral protein cages, 2D arrays, and 3D protein lattices, with a high (10-50 %) success rate and electron microscopy data closely matching the corresponding design models. Because of the modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable systems.

biochemistry↗

bioRxiv2022

Accurate Computational Design of 3D Protein Crystals

Protein crystallization plays a central role in structural biology1, with broad impact2 in pharmaceutical formulation3, drug delivery4, biosensing5, and biocatalysis6,7. Despite this importance, the process of protein crystallization remains poorly understood and highly empirical8-10, with largely unpredictable crystal contacts, lattice packing arrangements, and space group preferences, and the programming of protein crystallization through precisely engineered sidechain-sidechain interactions across multiple protein-protein interfaces is an outstanding challenge. Here we develop a general computational approach to designing three-dimensional (3D) protein crystals with pre-specified lattice architectures at atomic accuracy that hierarchically constrains the overall degree of freedoms (DOFs) of the system. We use the approach to design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into large 3D crystals (>100 m). Small-angle X-ray scattering and X-ray crystallography show these crystals are nearly identical to the computational design models, with the design target F4132 and I432 space groups and closely corresponding overall architectures and protein-protein interfaces. The crystal unit cell dimensions can be systematically redesigned while retaining space group symmetry and overall architecture, and the crystals are both extremely porous and highly stable, enabling the robust scaffolding of inorganic nanoparticle arrays. Our approach thus enables the computational design of protein crystals with high accuracy, and since both structure and assembly are encoded in the primary sequence, provides a powerful new platform for biological material engineering.

synthetic biology↗

bioRxiv2016

Cushing’s Syndrome mutant PKAL205R exhibits altered substrate specificity

The PKAL205R hotspot mutation has been implicated in Cushings Syndrome through hyperactive gain-of-function PKA signaling, however its influence on substrate specificity has not been investigated. Here, we employ the Proteomic Peptide Library (ProPeL) approach to create high-resolution models for PKAWT and PKAL205R substrate specificity. We reveal that the L205R mutation reduces canonical hydrophobic preference at the substrate P+1 position, and increases acidic preference in downstream positions. Using these models, we designed peptide substrates that exhibit altered selectivity for specific PKA variants, and demonstrate the feasibility of selective PKAL205R loss-of-function signaling. Through these results, we suggest that substrate rewiring may contribute to Cushings Syndrome disease etiology, and introduce a powerful new paradigm for investigating mutation-induced kinase substrate rewiring in human disease.

biochemistry↗

bioRxiv2016

Reprogramming protein kinase substrate specificity through synthetic mutations

Protein kinase specificity is largely imparted through substrate binding pocket motifs. Missense mutations in these regions are frequently associated with human disease, and in some cases can alter substrate specificity. However, current efforts at decoding the influence of mutations on substrate specificity have been focused on disease-associated mutations. Here, we adapted the Proteomic Peptide Library (ProPeL) approach for determining kinase specificity to the task of exploring structure-function relationships in kinase specificity by interrogating the effects of synthetic mutation. We established a specificity model for the wild-type DYRK1A kinase with unprecedented resolution. Using existing crystallographic and sequence homology data, we rationally designed mutations that precisely reprogrammed the DYRK1A kinase at the P+1 position to mimic the substrate preferences of a related kinase, CK II. This study illustrates a new synthetic biological approach to reprogram kinase specificity by design, and a powerful new paradigm to investigate structure-function relationships underpinning kinase substrate specificity.

biochemistry↗