Seminar by Prof. Giorgio Colombo

University of Pavia (Italy)

Combining computational and bioorganic chemistry for the design of new chemical tools

In this seminar, I will present recent our results on the development of computational strategies for the discovery of new modulators of protein-protein interactions with drug-like properties and for the design of epitopes starting from the structures of protein antigens.

In the first part, we will present novel methods of computational analysis of signal propagation mechanisms and communication pathways in proteins. The analysis is carried out using molecular dynamics (MD) simulations, combined with a signal propagation model. We elucidate the mechanisms of signal propagation and determine hot spot residues involved in the regulation of the functionally oriented aspects of protein conformational dynamics. Interestingly, we find that different communication mechanisms are triggered by different ligands. This information is then used to design and synthesize new allosteric modulators of the internal dynamics as well as the interactions properties of the targeted proteins. The activities of the modulators are tested in various models in vitro and in vivo.

In the second part, we discuss new methods to investigate the role of sequence and structures in determining the interaction properties of proteins and domains. In particular, we focus on the prediction of antibody-binding sites: Epitope prediction has in fact proven challenging. The antibody binding properties of an antigen depend on its structure and related dynamics. To this end, we have developed an integrated analysis of the dynamical and energetic properties of antigens, to identify non-optimized, low-intensity energetic interaction-networks in the protein structure isolated in solution. The method is based on the idea that recognition sites may correspond to localized regions with low-intensity energetic couplings with the rest of the protein allowing them to undergo conformational changes, to be recognized by a binding partner and to tolerate mutations with minimal energetic expense. Analyzing the results on isolated proteins and benchmarking against antibody-complexes, the method successfully identifies binding sites located on the protein surface and accessible by putative binding partners. The combination of dynamics and energetics can thus discriminate between epitopes and other substructures based only on physical properties.

Next, we test our predictions on a series of antigens from B.pseudomallei, a Gram-negative bacterium responsible for melioidosis, a serious and often fatal infectious disease that is poorly controlled by existing treatments. Predicted epitopes are engineered as synthetic peptides and shown to be selectively immunorecognized to the same extent as recombinant proteins in sera from melioidosis-affected subjects. Moreover, antibodies raised against designed sequences prove to be bactericidal.

Finally we will discuss the implication of these methods in drug and vaccine discovery.