Zheng Lab - Research

We Move to UTSA and 2 Ph.D Positions and 1 Postdoc are Available Immediately, Details in "Position" Page

Research Overview

Our research is highly interdisciplinary, focusing on the design and fundamental understanding of bio-functional materials, disease-related proteins, and environmentally benign/energy-sustainable polymers. By integrating data-driven modeling, molecular simulations, and biophysical experiments, we elucidate the sequence/composition–structure–function relationships of these systems across multiple length and time scales—from the molecular to the macroscopic. This knowledge drives the development of next-generation biomedical devices, therapeutic materials, and sustainable polymer platforms.

Currently, our research projects are centered around the following areas of interest:

Amyloid Peptides Associated with Neurodegenerative Diseases

Amyloid peptides, such as Aβ associated with Alzheimer's disease, hIAPP with type II diabetes, α-synuclein with Parkinson's disease, and over 20 other peptides, exhibit an intrinsic propensity to form β-sheet-rich aggregates of varying molecular sizes, which are highly cytotoxic to cells. However, the mechanisms underlying the formation of these amyloid aggregates and their induction of cytotoxicity in neuronal cells remain largely elusive. The lack of atomic-level details regarding amyloid oligomeric structures and their interactions with cell membranes presents a significant challenge in comprehending the biological roles of amyloid oligomers in aggregation and toxicity mechanisms. Additionally, this hinders the rational design of structural-based inhibitors and probes against amyloid diseases.

We combine a variety of biophysical techniques and computational approaches to achieve several key objectives in our research. Firstly, we aim to determine atomic-resolution structures of amyloid oligomers with different sequences. Additionally, we investigate the complete adsorption and aggregation process of amyloid peptides, along with their membrane disruption mechanisms in the presence of cell membranes. Furthermore, our research involves designing small organic molecules, nanoparticles, and peptides as inhibitors to prevent amyloid aggregation and mitigate toxicity. We also explore the repurposing of existing drugs currently used for cardiovascular disease and high blood pressure as potential amyloid inhibitors. Moreover, our investigations extend to examining cross-seeding interactions between amyloid proteins and other disease-related proteins, such as antimicrobial peptides and cancer proteins. By uncovering molecular links and spreading mechanisms across different diseases, we aim to gain insights into the broader implications of amyloid aggregation. Additionally, we develop aggregation-induced emission (AIE) and fluorescent molecules as probes for the early detection of amyloid proteins. Overall, our primary objective is to provide a comprehensive and fundamental understanding of the molecular mechanisms governing amyloid structure, toxicity, inhibition, and detection across different pathological pathways.

Repurposing of intestinal defensins as multi-target, dual function amyloid inhibitors via cross-seeding, Chemical Science (2022)
Design and engineering of amyloid aggregation-prone fragments and their antimicrobial conjugates with multi-target functionality, Advanced Functional Materials (2021)
Antimicrobial alpha-defensins as multi-target inhibitors against amyloid formation and microbial infection, Chemical Science (2021)
Dual amyloid cross-seeding reveals steric zipper-facilitated fibrillization and pathological links between protein misfolding diseases, J. Materials Chemistry B (2021)
Conformational-specific self-assembled peptides as dual-mode, multi-target inhibitors and detectors for different amyloid proteins, J. Materials Chemistry B (2022)
Fundamentals and exploration of aggregation-induced emission molecules for amyloid protein aggregation, J. Materials Chemistry B (2022)
Molecular understanding of a potential functional link between antimicrobial and amyloid peptides, Soft Matter (2014)

Smart and Tough Hydrogels

Many hydrogels suffer from mechanical brittleness and weakness, which limits their broad applicability. In our work, we leverage molecular simulations and experimental techniques to develop a series of physically-linked double-network hydrogels using innovative design strategies and synthesis methods. Our goal is to create hydrogels that fulfill several key requirements:

Attain high mechanical properties and exceptional fatigue resistance.
Demonstrate rapid self-recovery and self-healing capabilities.
Offer diverse functionalities, such as biocompatibility, mechanoresponse, freezing tolerance, conductivity, and interfacial adhesion, to cater to various applications.
Investigate new toughening mechanisms inherent in physically-linked gels, complementing those found in chemically-linked counterparts.

By addressing these objectives, we aim to overcome the limitations of conventional hydrogels and pave the way for their widespread use in diverse fields.

A general protein unfolding-chemical coupling strategy for pure protein hydrogels with mechanically strong and multifunctional properties, Advanced Science (2022)
A general crosslinker strategy to realize intrinsic frozen-resistance of hydrogels, Advanced Materials (2021)
A universal coating strategy for controllable functionalized polymer surfaces, Advanced Functional Materials (2020)
A novel design of multi-mechanoresponsive and mechanically strong hydrogels, Advanced Materials (2017)
Super bulk and interfacial toughness of physically-crosslinked double-network hydrogels, Advanced Functional Materials (2017)
A novel design strategy for fully physically-linked double network hydrogels with tough, fatigue resistant, and self-healing properties, Advanced Functional Materials (2015)
A robust, one-pot synthesis of highly mechanical and recoverable double-network hydrogels using thermo-reversible sol-gel polysaccharide, Advanced Materials (2013)

Multifunctional Biomaterials

The design and synthesis of highly bioinert and biocompatible antifouling materials are critical for numerous fundamental and practical applications. To address this need, we have developed a computational-data-driven platform that enables us to test design principles and rationally engineer new antifouling materials. Leveraging computational design, we have synthesized and evaluated a diverse range of biomaterials, including polyacrylamide/acrylate-, polyethylene glycol (PEG)-, and zwitterionic-based polymers. These materials have been utilized for various applications, such as antifouling surfaces and coatings, antifouling wound dressings, antifouling nanogels, and antifouling and antimicrobial hydrogels. Additionally, our research encompasses the investigation of antifouling biomimetic nanochannels, polymer-protein interactions, the fundamental mechanisms underlying antifouling properties, and the development of tough and self-healing hydrogels. Through these efforts, we aim to advance the field of antifouling materials and contribute to the development of innovative solutions for biomedical and industrial challenges.

Formulating zwitterionic, responsive polymers for designing smart soils, Small (2022)
Molecular understanding and structural-based design of polyacrylamides and polyacrylates as antifouling materials, Langmuir (2016)
Probing structure-antifouling activity relationships of polyacrylamides and polyacrylates, Biomaterials (2013)
Surface hydration: principles and applications toward lowfouling/nonfouling biomaterials, Polymer (2010)

Engineering Biomaterials for Biomedical Applications

In order to address a wide range of biomedical requirements, spanning from laboratory research to clinical application, we have engineered smart zwitterionic polymers. These polymers are tailored with various stimuli-responsive groups and are formulated into different formats, including nanogels, hydrogels, brushes, and fibers. Our aim is to deploy these innovative materials for applications such as wound dressing, substitutes for contact lenses, and drug/gene delivery systems. By offering versatile and adaptable solutions, we strive to enhance healthcare outcomes and improve patient well-being.

Salt-responsive bilayer hydrogels with pseudo double network structure actuated by polyelectrolyte and anti-polyelectrolyte effects, ACS Applied Materials & Interfaces (2017)
Importance of zwitterionic incorporation into polymethacrylate-based hydrogels for simultaneously improving optical transparency, oxygen permeability, and antifouling property, J. Materials Chemistry B (2017)
Comparative study of heparin-poloxamer hydrogel modified bFGF and aFGF for in vivo wound healing efficiency, ACS Applied Materials & Interfaces (2016)

Development of Advanced Computational Algorithms and Models

we are the forefront of the development of highly efficient and precise computational techniques, particularly tailored for intricate biomolecular systems. These cutting-edge methodologies and models serve as a crucial bridge between nano- or microscopic simulations and macroscopic observables. Our computational toolkit encompasses a diverse array of techniques, including:

Quantitative Structure-Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) methodologies
Data mining and machine learning algorithms for accelerating the design of novel materials, peptides, and drugs
Peptide-packing programs facilitating the self-assembly of nanostructures
Hybrid Monte Carlo and molecular dynamics (MCMD) simulations
Coarse-grained force fields and models optimized for biomolecular systems
Bio-interface programs designed to elucidate interactions at biological interfaces. Through the development and application of these advanced computational techniques, we aim to unravel complex biological phenomena and accelerate the discovery of innovative solutions in biomedical research.

DFBP: a comprehensive database of food-derived bioactive peptides for peptidomics research, Bioinformatics (2022)
Machine learning-enabled repurposing and design of antifouling polymer brushes, Chemical Engineering J. (2021)
Machine learning-enabled design and prediction of protein resistance on self-assembled monolayers and beyond, ACS Applied Materials & Interfaces (2021)
A multiscale polymerization framework towards network structure and fracture of double-network hydrogels, npj Computational Materials (2021)
Polymorphic associations and structures of the cross-seeding of Aβ1-42 and hIAPP1-37 polypeptides, J. Chemical Information and Modeling (2015)

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