Computational design of intermolecular stability and specificity in protein self-assembly

How electrostatic networks modulate specificity and stability of collagen

One-quarter of the 28 types of natural collagen exist as heterotrimers. The oligomerization state of collagen affects the structure and mechanics of the extracellular matrix, providing essential cues to modulate biological and pathological processes. A lack of high-resolution structural information limits our mechanistic understanding of collagen heterospecific self-assembly. Here, the 1.77-Å resolution structure of a synthetic heterotrimer demonstrates the balance of intermolecular electrostatics and hydrogen bonding that affects collagen stability and heterospecificity of assembly. Atomistic simulations and mutagenesis based on the solved structure are used to explore the contributions of specific interactions to energetics. A predictive model of collagen stability and specificity is developed for engineering novel collagen structures.

The Framework of Computational Protein Design

Computational protein design (CPD) has established itself as a leading field in basic and applied science with a strong coupling between the two. Proteins are computationally designed from the level of amino acids to the level of a functional protein complex. Design targets range from increased thermo- (or other) stability to specific requested reactions such as protein-protein binding, enzymatic reactions, or nanotechnology applications. The design scheme may encompass small regions of the proteins or the entire protein. In either case, the design may aim at the side-chains or at the full backbone conformation. Herein, the main framework for the process is outlined highlighting key elements in the CPD iterative cycle. These include the very definition of CPD, the diverse goals of CPD, components of the CPD protocol, methods for searching sequence and structure space, scoring functions, and augmenting the CPD with other optimization tools. Taken together, this chapter aims to introduce the framework of CPD.

Enzyme informatics

Over the last 50 years, sequencing, structural biology and bioinformatics have completely revolutionised biomolecular science, with millions of sequences and tens of thousands of three dimensional structures becoming available. The bioinformatics of enzymes is well served by, mostly free, online databases. BRENDA describes the chemistry, substrate specificity, kinetics, preparation and biological sources of enzymes, while KEGG is valuable for understanding enzymes and metabolic pathways. EzCatDB, SFLD and MACiE are key repositories for data on the chemical mechanisms by which enzymes operate. At the current rate of genome sequencing and manual annotation, human curation will never finish the functional annotation of the ever-expanding list of known enzymes. Hence there is an increasing need for automated annotation, though it is not yet widespread for enzyme data. In contrast, functional ontologies such as the Gene Ontology already profit from automation. Despite our growing understanding of enzyme structure and dynamics, we are only beginning to be able to design novel enzymes. One can now begin to trace the functional evolution of enzymes using phylogenetics. The ability of enzymes to perform secondary functions, albeit relatively inefficiently, gives clues as to how enzyme function evolves. Substrate promiscuity in enzymes is one example of imperfect specificity in protein-ligand interactions. Similarly, most drugs bind to more than one protein target. This may sometimes result in helpful polypharmacology as a drug modulates plural targets, but also often leads to adverse side-effects. Many chemoinformatics approaches can be used to model the interactions between druglike molecules and proteins in silico. We can even use quantum chemical techniques like DFT and QM/MM to compute the structural and energetic course of enzyme catalysed chemical reaction mechanisms, including a full description of bond making and breaking.

Design of net-charged abc-type collagen heterotrimers

Net-negatively-charged heterospecific A:B:C collagen peptide heterotrimers were designed using an automated computational approach. The design algorithm considers both target stability and the energy gap between the target states and misfolded competing states. Structural characterization indicates the net-negative charge balance on the new designs enhances the specificity of the target state at the expense of its stability.

Dynamic factors affecting gaseous ligand binding in an artificial oxygen transport protein

We report the functional analysis of an artificial hexacoordinate oxygen transport protein, HP7, which operates via a mechanism similar to that of human neuroglobin and cytoglobin: the destabilization of one of two heme-ligating histidine residues. In the case of HP7, this is the result of the coupling of histidine side chain ligation with the burial of three charged glutamate residues on the same helix. Here we compare gaseous ligand binding, including rates, affinities, and oxyferrous state lifetimes, of both heme binding sites in HP7. We find that despite the identical sequence of helices in both binding sites, there are differences in oxygen affinity and oxyferrous state lifetime that may be the result of differences in the freedom of motion imposed by the candelabra fold on the two sites of the protein. We further examine the effect of mutational removal of the buried glutamates on function. Heme iron in the ferrous state of this mutant is rapidly oxidized when exposed to oxygen. Compared to that of HP7, the distal histidine affinity is increased by a 22-fold decrease in the histidine ligand off rate. Electron paramagnetic resonance comparison of these ferric hemoproteins demonstrates that the mutation increases the level of disorder at the heme binding site. Nuclear magnetic resonance-detected deuterium exchange demonstrates that the mutation greatly increases the degree of penetration of water into the protein core. The inability of the mutant protein to bind oxygen may be due to an increased level of water penetration, the large decrease in binding rate caused by the increase in distal histidine affinity, or a combination of the two factors. Together, these data underline the importance of the control of protein dynamics in the design of functional artificial proteins.

Computational design of a collagen A:B:C-type heterotrimer

We have successfully designed an A:B:C collagen peptide heterotrimer using an automated computational approach. The algorithm maximizes the energy gap between the target and competing misfolded states while enforcing a minimum target stability. Circular dichroism (CD) measurements confirm that all three peptides are required to form a stable, structured triple helix. This study highlights the power of automated computational design, providing model systems to probe the biophysics of collagen assembly and developing general methods for the design of fibrous proteins.