Biology subjects

Zorine, D.

Publications and source records attributed to Zorine, D..

4 recordsLinked to original sources

bioRxiv2024

Design of Repeat Alpha-Beta Proteins with Capping Helices

Proteins composed of a single structural unit tandemly repeated multiple times carry out a wide range of functions in biology. There has hence been considerable interest in designing such repeat proteins; previous approaches have employed strict constraints on secondary structure types and relative geometries, and most characterized designs either mimic a known natural topology, adhere closely to a parametric helical bundle architecture, or exploit very short repetitive sequences. Here, we describe Rosetta-based and deep learning hallucination methods for generating novel repeat protein architectures featuring mixed alpha-helix and beta-strand topologies, and 25 new highly stable alpha-beta proteins designed using these methods. We find that incorporation of terminal caps which prevent beta strand mediated intermolecular interactions increases the solubility and monomericity of individual designs as well as overall design success rate.

bioengineering↗

bioRxiv2023

De novo design of diverse small molecule binders and sensors using Shape Complementary Pseudocycles

A general method for designing proteins to bind and sense any small molecule of interest would be widely useful. Due to the small number of atoms to interact with, binding to small molecules with high affinity requires highly shape complementary pockets, and transducing binding events into signals is challenging. Here we describe an integrated deep learning and energy based approach for designing high shape complementarity binders to small molecules that are poised for downstream sensing applications. We employ deep learning generated psuedocycles with repeating structural units surrounding central pockets; depending on the geometry of the structural unit and repeat number, these pockets span wide ranges of sizes and shapes. For a small molecule target of interest, we extensively sample high shape complementarity pseudocycles to generate large numbers of customized potential binding pockets; the ligand binding poses and the interacting interfaces are then optimized for high affinity binding. We computationally design binders to four diverse molecules, including for the first time polar flexible molecules such as methotrexate and thyroxine, which are expressed at high levels and have nanomolar affinities straight out of the computer. Co-crystal structures are nearly identical to the design models. Taking advantage of the modular repeating structure of pseudocycles and central location of the binding pockets, we constructed low noise nanopore sensors and chemically induced dimerization systems by splitting the binders into domains which assemble into the original pseudocycle pocket upon target molecule addition. One Sentence SummaryWe use a pseuodocycle-based shape complementarity optimizing approach to design nanomolar binders to diverse ligands, including the flexible and polar methotrexate and thyroxine, that can be directly converted into ligand-gated nanopores and chemically induced dimerization systems.

biochemistry↗

bioRxiv2022

Hallucination of closed repeat proteins containing central pockets

In pseudocyclic proteins such as TIM barrels, {beta} barrels, and some helical transmembrane channels, a single subunit is repeated in a cyclic pattern, giving rise to a central cavity which can serve as a pocket for ligand binding or enzymatic activity. Inspired by these proteins, we devised a deep learning-based approach to broadly exploring the space of closed repeat proteins starting from only a specification of the repeat number and length. Biophysical data for 38 structurally diverse pseudocyclic designs produced in E. coli are consistent with the design models, and two crystal structures we were able to obtain are very close to the designed structures. Docking studies suggest the diversity of folds and central pockets provide effective starting points for designing small molecule binders or enzymes.

molecular biology↗

bioRxiv2017

Biophysical determinants of mutational robustness in a viral molecular fitness landscape

Biophysical interactions between proteins and peptides are key determinants of genotype-fitness landscapes, but an understanding of how molecular structure and residue-level energetics at protein-peptide interfaces shape functional landscapes remains elusive. Combining information from yeast-based library screening, next-generation sequencing and structure-based modeling, we report comprehensive sequence-energetics-function mapping of the specificity landscape of the Hepatitis C Virus (HCV) NS3/4A protease, whose function -- site-specific cleavages of the viral polyprotein -- is a key determinant of viral fitness. We elucidate the cleavability of 3.2 million substrate variants by the HCV protease and find extensive clustering of cleavable and uncleavable motifs in sequence space indicating mutational robustness, and thereby providing a plausible molecular mechanism to buffer the effects of low replicative fidelity of this RNA virus. Specificity landscapes of known drug-resistant variants are similarly clustered. Our results highlight the key and constraining role of molecular-level energetics in shaping plateau-like fitness landscapes from quasispecies theory.

biophysics↗