Skip to main navigationSkip to main content
The University of Southampton

Computational Enzymology: Virtually Climbing Hills and Breaking Through Barriers to Reveal Reaction Mechanisms Seminar

20 March 2018
Building 27, Lecture Room 2003, Chemistry, University of Southampton

For more information regarding this seminar, please email Prof Jon Essex at .

Event details

Seminar with Prof Kevin J. Naidoo

I will present the generalized adaptive reaction coordinate force biasing method developed in our laboratory and show its ability to produce multidimensional reaction volumes. I’ve termed this the Free Energies from Adaptive Reaction Coordinate Forces (FEARCF) method.1-2 To illustrate FEARCF’s effective searching and sampling effiency I will discuss how enzyme catalysed reaction spaces and molecular conformations that are key to the progress of a reaction are modelled. This will be done by describing how multidmensional FEARCF reaction simulations are used to decipher the inner workings of enzyme catalysis. As a demonstration the competition between substitution and elimination pathways in the Trypanosoma cruzi trans-sialidase(TcTS) catalysed reaction3 and TcTS’ suppression of its side reactions to yield a single product will be discussed.

Another FEARCF enabled discovery is the mechanism by which carbohydrate processing enzymes induce puckering of glucopyranose rings. This is described in the context of cellobiohydrolase I (CBHI) catalysis of the hydrolysis of cellulose glycosidic bonds.4

Reaction surfaces have been computed using semiempirical levels of theory however, I will show that the use of higher levels of theory combined with extensive sampling of configurational, conformational and reaction space is now possible.

To this end I will describe the Quantum Supercharger Library (QSL) developed by my group. QSL5-6 can be “plugged into” legacy codes such as GAMESS-UK, GAMESS-US, NWChem, etc and accelerate DFT/MM reaction dynamics. These initiatives introduce an era where highly accurate dynamic simulations of complex molecular systems are possible.7



1. Strümpfer, J.; Naidoo, K. J., Computing free energy hypersurfaces for anisotropic intermolecular associations. J.Comp. Chem. 2010, 31 (2), 308-316.

2. Naidoo, K. J., Multidimensional free energy volumes offer unique insights into reaction mechanisms, molecular conformation and association. Phys. Chem. Chem. Phys. 2012, 14 (25), 9026-9036.

3. Rogers, I. L.; Naidoo, K. J., Multidimensional Reaction Dynamics Reveal How the Enzyme TcTS Suppresses Competing Side Reactions and Their Side Products. ACS Catalysis 2016, 6384-6392.

4. Barnett, C. B.; Wilkinson, K. A.; Naidoo, K. J., Pyranose Ring Transition State Is Derived from Cellobiohydrolase I Induced Conformational Stability and Glycosidic Bond Polarization. J. Am. Chem. Soc. 2010, 132 (37), 12800-12803.

5. Fernandes, K. D.; Renison, C. A.; Naidoo, K. J., Quantum supercharger library: Hyper-parallelism of the Hartree–Fock method. J. Comp. Chem. 2015, 36 (18), 1399-1409.

6. Renison, C. A.; Fernandes, K. D.; Naidoo, K. J., Quantum supercharger library: Hyper-parallel integral derivatives algorithms for ab initioQM/MM dynamics. J. Comp. Chem. 2015, 36 (18), 1410-1419.

7. Rogers, I. L.; Naidoo, K. J., Producing DFT/MM enzyme reaction trajectories from SCC-DFTB/MM driving forces to probe the underlying electronics of a glycosyltransferase reaction. J. Comput. Chem., 10.1002/jcc.24820.

Computational Enzymology
Computational Enzymology

Speaker information

Prof Kevin J.Naidoo, University of Cape Town, South Africa. I am a computational scientist with an expertise in the development of Parallel and Hybrid model computer code for application to chemical, life and biomedical sciences. I have been awarded a multiyear (2007-2011) South African Research Chair (SARChI) in Scientific Computing which was renewed twice (2012-2016) and (2017-2021). My research is balanced between development of life science software and its application to biomedical projects where more recently the biomedical application has been cancer. An example of my scientific compute expertise is my research group’s participation in an alpha and then beta international testing consortium to assist Portland Group International (PGI, Oregon USA) in their development of the Accelerate compiler. In another illustration of my expertise in scientific code development I am a member of Nvidia’s life science development team (Nvidia, California USA). My scientific interests are focused on the roles that carbohydrates play in biological processes. A demonstration of the application of computational expertise is my use of molecular modeling simulations to develop therapeutics for cancer as well as my use of data analytics and informatics methods to develop diagnostics and prognostics for cancer. Using my laboratories’ competitive advantage of development, modelling and analytics, we have developed functional libraries and modules that can be linked into the legacy codes as well as build an open source informatics platform (Glycome Analytics Platform, GAP). My expertise in developing algorithms for life and biomedical science for implementation on next generation hardware accelerators such as GPU and FPGA is widespread. However, all my code development is motivated by a search for an understanding the critical mechanistic role that glycans play in biology. A recent illustration of this is my linking glycobioinformatics and genomics data analytics to build computational tools and use them to understand glycoenzymatic action in cancer biological pathways. I have raised funding to draw computing and laboratory based research together. As an illustration of this I am the PI on a Medical Research Council (MRC) Grant to develop immunotherapeutic glycoenzyme inhibitors for breast cancer therapy and I am the PI on a Technology Innovation Agency (TIA) grant to undertake a “proof of concept” study of an Early Diagnostic using my invention of a GlycoEnzyme Gene Classification of Cancer Types and Subtypes.

Privacy Settings