Artificial Intelligence (AI) assisted novel design and molecular dynamics simulation of anti-thrombotic peptides and experimental validation by nanomedicine delivery

Summary

Research Area:

Molecular dynamics simulation, AlphaFold, Molecular docking, Computational biology, Peptide, nanoparticle

Supervisor

Dr Lining (Arnold) Ju.

Research location

Biomedical Engineering

Synopsis

Project Description:

Heart and vascular diseases remain a significant concern in modern medicine, with a shocking 5.6% of Australian adults over 18 facing these challenges in 2017-18. While the interplay of shear in blood flow and its effect on proteins like von Willebrand factor (VWF) and FVIII is evident, a comprehensive understanding of their structures remains elusive.

Enter the revolutionary AlphaFold, a DeepMind-developed AI software, which demonstrated unparalleled accuracy in predicting protein structures, particularly with its AlphaFold 2 version. This project aims to harness the profound capabilities of AlphaFold to dive deep into the intricate mechanisms of these proteins.

Once we decode and design our anti-thrombotic peptides, the journey doesn't stop. We will step into the exhilarating world of nanotechnology. Using cutting-edge techniques, we plan to design nanocarriers tailored for optimal drug delivery, ensuring that our drugs not only impede thrombosis but are also delivered efficiently to their intended targets without interfering with hemostasis. This integration of computational design with experimental nanotechnology offers students a chance to be at the forefront of interdisciplinary research.

Further information:

We are looking for candidates with the following skills and experience:

• Academic knowledge in the discipline of biophysics, biomechanics, electrophysiology, cell biology and biochemistry.
• Experience of Linux/Unix commanding line (Unix shell).
• Capability of using two or more of GROMACS, Hex, LabVIEW, Python, AutoCAD, MATLAB and other software.

Preferred experience includes:

• Solid basic knowledge of biology and hands-on experience in PC2 biological laboratory, using flow cytometer, ELISA, Western blots, protein-protein interaction assays, protein/antibody purification and functional characterizations.
• Experience in theoretical simulation using and MATLAB or COMSOL, or LabVIEW programming to control equipment and devices. 
• Capability of independently output processing models and drawings, be capable of CNC programming, use other conventional processing platform equipment to manufacture mechanical parts, and use 3D printers for part manufacturing.
• Pre-doctoral track records with publications, conference papers, reports, professional or technical contributions with evidence of independent research ability.
• Excellent oral and written communication skills.

To learn more about the Snow-Ju Lab: Mechanobiology and Biomechanics Laboratory (MBL) and our research, please visit our official website (https://snowmedical.org.au/fellow/lining-arnold-ju/). For more information on A/Prof Ju's Snow Fellowship and groundbreaking research, check out these public release news articles:

A father had a heart attack at 54. His son’s technology could have predicted it (https://www.smh.com.au/national/nsw/a-father-had-a-heart-attack-at-56-his-son-s-technology-could-ve-predicted-it-20230327-p5cvkj.html)

Additional information

How to Apply:

To apply, please email arnold.ju@sydney.edu.au with the subject line “PhD Application”, the project title in the body of the email, and attach the following:

• CV
• Transcripts

And complete an Expression of Interest Form via https://sydney.au1.qualtrics.com/jfe/form/SV_5vSA2po0sooUt0i

Want to find out more?

Opportunity ID

The opportunity ID for this research opportunity is 3500

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