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Viral fusion proteins undergo dramatic conformational transitions during membrane fusion. For viruses that enter through the endosome, these conformational rearrangements are typically pH sensitive. Here we provide a comprehensive review of the molecular interactions that govern pH-dependent rearrangements and introduce a novel paradigm for electrostatic residue pairings that regulate progress through the viral fusion coordinate. Analysis of structural data demonstrates a significant role for side chain protonation in triggering conformational change. To characterize this behavior we identify two distinct residue pairings, which we define as Histidine-Cation (HisCat) and Anion-Anion (AniAni) interactions. These side chain pairings destabilize a particular conformation via electrostatic repulsion through side chain protonation. Furthermore, two energetic control mechanisms, thermodynamic and kinetic, regulate these structural transitions. This review expands on the current literature by identification of these residue clusters, discussion of data demonstrating their function, and speculation of how these residue pairings contribute to the energetic controls.

The de novo design of globular beta sheet proteins remains largely an unsolved problem. It is unclear whether most designs are failing because the designed sequences do not have favorable energies in the target conformations or whether more emphasis should be placed on negative design, that is, explicitly identifying sequences that have poor energies when adopting undesired conformations. We tested whether we could redesign the sequence of a naturally occurring beta sheet protein, tenascin, with a design algorithm that does not include explicit negative design. Denaturation experiments indicate that the designs are significantly more stable than the wild-type protein and the crystal structure of one design closely matches the design model. These results suggest that extensive negative design is not required to create well-folded beta sandwich proteins. However, it is important to note that negative design elements may be encoded in the conformation of the protein backbone which was preserved from the wild-type protein.

Larger rotamer libraries, which provide a fine grained discretization of side chain conformation space by sampling near the canonical rotamers, allow protein designers to find better conformations, but slow down the algorithms that search for them. We present a dynamic programming solution to the side chain placement problem which treats rotamers at high or low resolution only as necessary. Dynamic programming is an exact technique; we turn it into an approximation, but can still analyze the error that can be introduced. We have used our algorithm to redesign the surface residues of ubiquitin's beta sheet.

Structure-based design efforts on antibodies are frequently hamstrung by the general difficulty of crystallizing antibody molecules. Computational approaches are getting more success and playing a very important role in protein structure prediction and design. A combined platform with both computational predication and experimental verification would have a transformative research capability on antibody engineering. We have been developing and integrating RosettaAntibody (homology modeling and H3 loop modeling), RosettaDock (SnugDock and EnsembleDock) and RosettaDesign (non-canonical amino acids design) into a systematic computational pipeline. Using the targets of M18/Anthrax complex, which has solved crystal structure, and anti-MS2/MS2 complex, whose antibody structure is not available, the new pipeline is capable of building homology models for antibody from its sequence, and predicting the docked antibody-antigen structures. The correct antigen epitope can be identified by iteratively refining the predicted candidates with experimental verifications such as interface alanine scanning. This is followed by computational CDR designs utilizing non-canonical amino acids, which can form covalent bonds with epitope residues. Along with experimental confirmations, the incorporation of the systematical computational method was proved to significantly facilitate the epitope identification and non-canonical amino acid designs. These efforts eventually substantially increased the antibody-antigen binding affinity of the two targets.