Lamzin Group
Development of an integrative modelling platform for structural biology
Evolution of macromolecular patterns in an electron density map during X-ray crystal structure determination.
We are fascinated by complex computational methods in information processing that can address data interpretation problems as we encounter them in structural biology. Recognising patterns in experimental data that describe macromolecules is an application of artificial intelligence (see figure). Structure determination provides essential data for integrative modelling of the basis of life: DNA, RNA, proteins, macromolecular complexes and assemblies. Current approaches, predominantly based on macromolecular X-ray crystallography, are static in nature and concentrate on a reductionist view of a single structure from a single method or experiment. Future applications (e.g. a quantitative description of the living cell) will necessitate novel approaches where a wider context of information, originating from complementary tools, is implemented in order to arrive at an integrated platform for a model of life.
Previous and current research
Pattern-recognition based methods are the foundation of one of the group’s main foci, the ARP/wARP soft ware project (Langer et al., 2008) for protein/DNA/ligand crystal structure determination. The already comprehensive range of implemented methodologies and algorithms, complemented by an intuitive graphical user interface, is being continually improved and augmented with new procedures for dealing with more challenging problems of structural biology (Hattne & Lamzin, 2011). We can now recognise structural motifs in lower resolution maps (Heuser et al., 2009), which should permit the combination of X-ray crystallographic data with that derived from electron microscopy. In a similar vein, sophisticated algorithms are being developed for the modelling of bound ligands and identification of novel binding sites.
The design of artificial intelligence to find the best way through the maze of structure determination protocols available is implemented in the group’s AutoRickshaw soft ware for validation of synchrotron beamline experiments and the building of macromolecular models. The group continues to enhance the range of state-of-the-art computational facilities that enable hundreds of researchers worldwide to perform remote structure determination.
The group uses its expertise to develop methods that aid the analysis of crystal growth. We have developed novel soft ware XREC/FREC for the detection of crystals in situ and aim at downstream applications in the automation of experimental sample handling (Watts et al., 2010). We also apply our techniques to the structural biologydriven characterisation of proteins from humans and their pathogens. Current targets include macromolecules from the malarial oxidative phosphorylation pathway, enzymes involved in drug and vitamin syntheses, and those related to the amyloidal fibril formation process (Wrenger et al., 2011; Lapkouski et al., 2009).
Future projects and goals
Our activities will continue to focus on arising trends in the field, aiming to push currently perceived boundaries and helping to shape future structural biology research. Coherent free-electron laser sources in Stanford and at DESY already allow experiments with biological samples that were previously unimaginable. Additionally, the state-of-the-art PETRA III synchrotron beamlines will soon be available. The field will play an increasing role in investigations of biological interactions, and we will remain at the forefront of developments.