Max-Planck-Institute for Biophysical Chemistry, Göttingen (Germany)
Local Project ID:
HPC Platform used:
SuperMUC of LRZ
HIV is one of the most significant global public health threats. The virus evolves rapidly, and multi-drug resistant strains have already emerged. The drugs approved to date target only four HIV proteins. While two novel drug targets, Rev and the capsid protein (CA), have been identified, so far none have reached clinical trials. Scientists leverage the computing power of HPC system SuperMUC to simulate detailed and accurate models of the protein-protein interactions of these targets with the aim to facilitate the design of more effective drugs.
How does HIV (human immunodeficiency virus) pass its genetic material into and out of the cell nucleus without being detected by the human host cell? Two HIV proteins (Rev and capsid/CA) are responsible, but the molecular mechanisms they use to disguise the ribonucleic acid of HIV and proteins from the human nuclear pore complex are not understood. A study, conducted by scientists of the Max-Planck-Institute for Biophysical Chemistry in Göttingen, aims to provide structural information on the relevant protein-protein interactions, which is a necessary step in the rational design of drugs targeting Rev and CA.
HIV evolves rapidly, and multi-drug resistant strains have already emerged. However, only 31 drugs have been approved, which target only four HIV proteins. Two novel drug targets were the focus of this research: Rev and the capsid (CA) protein. Rev is essential to replication of the virus, while the HIV core particle is enclosed by many copies of CA. Drugs targeting Rev and CA have been identified, but so far none have reached clinical trials. The Göttingen based scientists leveraged the computing power of HPC system SuperMUC to simulate detailed and accurate models of the protein-protein interactions involved with the aim to facilitate the design of more effective drugs.
The scientists carried out a rigorous evaluation of the accuracy of de novo intrinsically disordered protein (IDP) ensembles. IDPs fulfil many essential biological roles from cell signalling to maintaining the selective barrier of the nuclear pore complex. Their disordered nature has been shown in many cases to be crucial to their function.
While molecular simulations are increasingly being used to obtain conformational ensembles of IDPs, there is currently no consensus on the accuracy of these ensembles, or the suitability of modern empirical force fields for this purpose. In their study, the scientists assessed the accuracy of IDP ensembles obtained using state-of-the-art force fields (Rauscher 2015). Carrying out such a comparative study presented a huge computational challenge, which was only possible with the large compute time allocation on HPC system SuperMUC.
The conducted comparison of force fields led to several unexpected results. First, the extent of the difference between ensembles is unexpectedly large, spanning the complete range from globule-like to highly expanded. The key finding of the researchers' joint experimental-computational study is that one single force field, CHARMM 22*, stands out in that it is consistent with small angle x-ray scattering and NMR data within experimental error. Thus, having obtained an accurate IDP ensemble, the potential long-term impact of this work extends far beyond an assessment of force field accuracy.
Following up on this work, in a joint study together with the groups of Alex MacKerell (Univ. of Maryland) and Michael Feig (Michigan State), the researchers developed and carried out tests of a new version of the CHARMM protein force field (CHARMM 36m) (Huang 2017). Extensive tests of the new force field for both folded and disordered proteins were carried out on SuperMUC. In all test cases, CHARMM 36m outperformed its predecessor, CHARMM 36. The potential impact of this work is significant because now there is a force field suitable for simulations of both folded and disordered proteins, which forms the basis for the study of the HIV proteins.
Huang, J., Rauscher, S., Nawrocki, G., Ran,T., Feig, M., de Groot, B. L., Grubmüller, H., and MacKerell Jr., A. D. (2017) CHARMM36m: An Improved Force Field for Folded and Intrinsically Disordered Proteins. Nature Methods 14, 71-73 ?
Kutzner, C., Apostolov, R., Hess, B., Grubmüller, H. Scaling of the GROMACS 4.6 molecular dynamics code on SuperMUC. Parallel Computing: Accelerating Computational Science and Engineering (CSE) 722-730, IOS Press, NL (2014).
Rauscher, S., Gapsys, V., Gajda, M. J., Zweckstetter, M., de Groot, B. L., and Grubmüller, H. (2015) Structural Ensembles of Intrinsically Disordered Proteins Depend Strongly on Force Field: A Comparison to Experiment. Journal of Chemical Theory and Computation 11, 5513?5524.
Prof. Dr. Helmut Grubmüller
Theoretical and Computational Biophysics Dept.
Max-Planck-Institute for Biophysical Chemistry
Am Fassberg 11, D-37077 Göttingen (Germany)