Day 4

Plenary Session 6: Crystalline Sponge Method: X-Ray Structure Analysis Without Crystallization

Makoto Fujita from the University of Tokyo presented his work involving a new protocol for X-ray single crystal diffraction (SCD) analysis that does not require crystallization of the sample. Instead, the crystalline sponge method is used to prepare the sample. Pretty impressive stuff although admittedly, this presentation fell in the “too technical” basket once again.


Plenary Session 7: Designing Organic Materials Using High-Throughput Quantum Chemistry and Machine Learning


Alan Aspuru-Guzik from Harvard University was full of energy the moment he stepped on to the stage. His Mexican accent was heavy but not hard to understand. Not sure if it was the area of research he was presenting or his overall enthusiasm as a presenter that made me like this guy, but I liked him a lot. So much so that he warrants three images in total.



Essentially, he uses computational methods to minimise chemical space in search of useful molecular “libraries”. He also promoted the Harvard Clean Energy Project, an initiative that allows people to donate idle computer time on their PCs for the discovery and design of new materials. Its database analyses 2.3 million candidate compounds for organic photovoltaics. It is an open resource designed to give researchers in the field of organic electronics access to promising leads for new material developments.


Theory II: New Methods for Chemical Quantum Dynamics

Terry Frankcombe from the Australian National University presented a new theoretical method called the Basis Expansion Leap Multi-Configurational Guassian (BEL-MCG). This research was a bit too mathematical (alas, even for me!) but interesting nonetheless. Not really sure what it was all about, except that the Schrödinger equation was being solved at one stage during the presentation.


Theory III: Efficient Alternatives for the Quantum-Chemical Treatment of Peptides and Proteins

Lars Goerigk from the University of Melbourne presented work that was more up my alley, despite the quantum mechanics side of his research (my work is in the molecular mechanics realm). But as the old adage goes, two sides to a coin. He discussed the standard approaches in the field of computational biomolecular quantum chemistry, including the Møller–Plesset perturbation theory and BP86 density functions. However, he noted the deficiencies of these approaches, namely the basis-set-superposition error (BSSE) and the inadequate treatment of London-dispersion effects. As a consequence, alternatives include the linear-scaling optimization of proteins which draw from Hartree-Fock theory rather than density functional theory. Although I studied CHEM210 Quantum and Thermochemical Structure this year, I probably need to complete PHYS301 Microscopic to Macroscopic Physics and Chemistry before attempting to grasp any of Lars’ research. Admittedly, I did get a thrill when he showed an RMSD graph (root-mean-square deviation) on one of his slides.


Theory III: Molecular Docking: Extended Conformational Sampling of Peptides and Carbohydrates

Although I didn’t actually attend this presentation by Tamir Dingjan from Monash University (for I was feeling unwell towards the end of the afternoon), I had a brief chat with him the next day, realising that we both attended the Molecular Dynamics Fundamentals workshop at La Trobe Institute of Molecular Science (LIMS) two months ago. His work focuses on predicting structures of protein-ligand complexes and estimating ligand affinities with an approach called molecular docking. According to his abstract, “extended sampling is of greatest benefit to peptide ligands longer than six residues, but is of limited benefit to carbohydrate ligands.” I plan to email him to enquire further about his work.

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