The dynamics of a biological system occurs at multiple time and length scales and are interconnected: from the jiggling of atoms (pico-seconds), the domain movements (micro- to milli-seconds), protein folding and diffusion (milli-second to seconds), binding, assembly, and translocation (seconds to minutes). Experimental knowledge of the motions occurring at these different time scales is mostly deduced by inference from static structures derived from kinetically stable states or from stand-alone kinematic and non-dynamical computational models. There is a critical gap in dynamic data from the inability of current methods to “see” the structure, especially at the nanometer and msec-sec scales.
The MoE Tier 3 programme: An integrated framework to study the dynamics of biological structures is designed to fill this gap, first by developing new experimental methods and computational approaches that can generate knowledge on the missing dynamical steps of fundamentally critical biological systems. Equally important is the second step, to develop a platform that allows for the integration of multi-scale dynamical data generated by modelers and experimentalists. Such a platform is essential for assimilating these disparate data into a conceptual framework. The framework is applied to a model biological system, the problem of infection by the Dengue virus (DENV). DENV infects approximately 100 million people worldwide annually and frequent outbreaks of dengue disease have been detected in Singapore.
An integrated framework to study the dynamics of biological structures
The major achievements reported here highlight successes over the first two years and a half of funding for the programme. The common thread uniting them is the consistent developments of new methods, both experimental and computational, to study the dynamics of DENV over a range of scales that was not previously accessible. The report features the core services that have been set up, the methodological advancements that have been made, as well as the new insights that are provided on the DENV infection cycle.
- DENV production
- SAXS/WAXS platform
- Imaging platform
- HDXMS platform
- Better liquid cells for imaging proteins in room temperature liquid water
- Better probes for electron microscopy
- Better signal processing techniques for TEM
- Better techniques for characterizing the ensemble of conformations available to a multiple domain protein
- Improved techniques for the determination of kinetic parameters of minor states of proteins by NMR
- Better coarse-grained models to study the dynamics of proteins
- Improved fitting of small-angle and wide-angle X-ray scattering data to protein structures by explicit water modeling
- Generation of a reliable, near-atomistic model of the DENV envelope for Molecular Dynamics studies
- Better methods to study transition paths
Many experimental groups in the world are working on the different serotypes of the Dengue virus, studying their structures using high-resolution techniques such as X-ray crystallography, NMR, or cryo-EM, their infection mechanisms, as well as their interactions with antibodies as a means to develop vaccine candidates. Some of the most advanced laboratories in those fields are already directly affiliated to this programme or act as collaborators. What is unique however in the setting of this programme is a comprehensive integration of these two approaches (experimental and computational), both for methodology developments and for applications.
A possible short title for the programme is “From basic research to bedside”. Namely, the intended impact of the proposal is to improve the wellbeing of patients affected with Dengue Virus related diseases. It is expected however that efforts put in reaching this goal will have broader impacts.
The programme has brought together a diverse interdisciplinary team of researchers from mathematics, core disciplines in imaging sciences, and virology. This concentration of diverse talents and expertise provides a unique opportunity to train a new generation of graduate students and postdoctoral fellows. The team is taking the necessary steps to engage students involved in experimental research to understand the processes by which their data are translated into knowledge and understanding.
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