Engineering gain-of-function mutants of a WW domain by dynamics and structural analysis.

Proteins gain optimal fitness such as foldability and function through evolutionary selection. However, classical studies have found that evolutionarily designed protein sequences alone cannot guarantee foldability, or at least not without considering local contacts associated with the initial folding steps. We previously showed that foldability and function can be restored by removing frustration in the folding energy landscape of a model WW domain protein, CC16, which was designed based on Statistical Coupling Analysis (SCA). Substitutions ensuring the formation of five local contacts identified as "on-path" were selected using the closest homolog native folded sequence, N21. Surprisingly, the resulting sequence, CC16-N21, bound to Group I peptides, while N21 did not. Here, we identified single-point mutations that enable N21 to bind a Group I peptide ligand through structure and dynamic-based computational design. Comparison of the docked position of the CC16-N21/ligand complex with the N21 structure showed that residues at positions 9 and 19 are important for peptide binding, whereas the dynamic profiles identified position 10 as allosterically coupled to the binding site and exhibiting different dynamics between N21 and CC16-N21. We found that swapping these positions in N21 with matched residues from CC16-N21 recovers nature-like binding affinity to N21. This study validates the use of dynamic profiles as guiding principles for affecting the binding affinity of small proteins.

Adenine nucleotide translocase is acetylated in vivo in human muscle: Modeling predicts a decreased ADP affinity and altered control of oxidative phosphorylation.

Proteomics techniques have revealed that lysine acetylation is abundant in mitochondrial proteins. This study was undertaken (1) to determine the relationship between mitochondrial protein acetylation and insulin sensitivity in human skeletal muscle, identifying key acetylated proteins, and (2) to use molecular modeling techniques to understand the functional consequences of acetylation of adenine nucleotide translocase 1 (ANT1), which we found to be abundantly acetylated. Eight lean and eight obese nondiabetic subjects had euglycemic clamps and muscle biopsies for isolation of mitochondrial proteins and proteomics analysis. A number of acetylated mitochondrial proteins were identified in muscle biopsies. Overall, acetylation of mitochondrial proteins was correlated with insulin action (r = 0.60; P < 0.05). Of the acetylated proteins, ANT1, which catalyzes ADP-ATP exchange across the inner mitochondrial membrane, was acetylated at lysines 10, 23, and 92. The extent of acetylation of lysine 23 decreased following exercise, depending on insulin sensitivity. Molecular dynamics modeling and ensemble docking simulations predicted the ADP binding site of ANT1 to be a pocket of positively charged residues, including lysine 23. Calculated ADP-ANT1 binding affinities were physiologically relevant and predicted substantial reductions in affinity upon acetylation of lysine 23. Insertion of these derived binding affinities as parameters into a complete mathematical description of ANT1 kinetics predicted marked reductions in adenine nucleotide flux resulting from acetylation of lysine 23. Therefore, acetylation of ANT1 could have dramatic physiological effects on ADP-ATP exchange. Dysregulation of acetylation of mitochondrial proteins such as ANT1 therefore could be related to changes in mitochondrial function that are associated with insulin resistance.

BP-Dock: a flexible docking scheme for exploring protein-ligand interactions based on unbound structures.

Molecular docking serves as an important tool in modeling protein-ligand interactions. However, it is still challenging to incorporate overall receptor flexibility, especially backbone flexibility, in docking due to the large conformational space that needs to be sampled. To overcome this problem, we developed a novel flexible docking approach, BP-Dock (Backbone Perturbation-Dock) that can integrate both backbone and side chain conformational changes induced by ligand binding through a multi-scale approach. In the BP-Dock method, we mimic the nature of binding-induced events as a first-order approximation by perturbing the residues along the protein chain with a small Brownian kick one at a time. The response fluctuation profile of the chain upon these perturbations is computed using the perturbation response scanning method. These response fluctuation profiles are then used to generate binding-induced multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, we applied our approach on a large and diverse data set using unbound structures as receptors. We also compared the BP-Dock results with bound and unbound docking, where overall receptor flexibility was not taken into account. Our results highlight the importance of modeling backbone flexibility in docking for recapitulating the experimental binding affinities, especially when an unbound structure is used. With BP-Dock, we can generate a wide range of binding site conformations realized in nature even in the absence of a ligand that can help us to improve the accuracy of unbound docking. We expect that our fast and efficient flexible docking approach may further aid in our understanding of protein-ligand interactions as well as virtual screening of novel targets for rational drug design.

The antiviral lectin cyanovirin-N: probing multivalency and glycan recognition through experimental and computational approaches.

CVN (cyanovirin-N), a small lectin isolated from cyanobacteria, exemplifies a novel class of anti-HIV agents that act by binding to the highly glycosylated envelope protein gp120 (glycoprotein 120), resulting in inhibition of the crucial viral entry step. In the present review, we summarize recent work in our laboratory and others towards determining the crucial role of multivalency in the antiviral activity, and we discuss features that contribute to the high specificity and affinity for the glycan ligand observed in CVN. An integrated approach that encompasses structural determination, mutagenesis analysis and computational work holds particular promise to clarify aspects of the interactions between CVN and glycans.

Electrostatic effect of the ribosomal surface on nascent polypeptide dynamics.

The crucial molecular events accompanying protein folding in the cell are still largely unexplored. As nascent polypeptides emerge from the ribosomal exit tunnel, they come in close proximity with the highly negatively charged ribosomal surface. How is the nascent polypeptide influenced by the ribosomal surface? We address this question via the intrinsically disordered protein PIR and a number of its variably charged mutants. Two different populations are identified: one is highly spatially biased, and the other is highly dynamic. The more negatively charged nascent polypeptides emerging from the ribosome are richer in the extremely dynamic population. Hence, nascent proteins with a net negative charge are less likely to interact with the ribosome. Surprisingly, the amplitude of the local motions of the highly dynamic population is much wider than that of disordered polypeptides under physiological conditions, implying that proximity to the ribosomal surface enhances the molecular flexibility of a subpopulation of the nascent protein, much like a denaturing agent would. This effect could be important for a proper structural channeling of the nascent protein and the prevention of cotranslational kinetic trapping. Interestingly, a significant population of the highly spatially biased nascent chain, probably interacting extensively with the ribosome, is present even for very negatively charged nascent proteins. This "sticking" effect likely serves to protect nascent proteins (e.g., from cotranslational aggregation). In all, our results highlight the influence of the ribosome in nascent protein dynamics and show that the ribosome's function in protein biogenesis extends well beyond catalysis of peptide bond formation.

Conformational search of peptides and proteins: Monte Carlo minimization with an adaptive bias method applied to the heptapeptide deltorphin.

The energy function of a protein consists of a tremendous number of minima. Locating the global energy minimum (GEM) structure, which corresponds approximately to the native structure, is a severe problem in global optimization. Recently we have proposed a conformational search technique based on the Monte Carlo minimization (MCM) method of Li and Scheraga, where trial dihedral angles are not selected at random within the range [-180 degrees,180 degrees ] (as with MCM) but with biased probabilities depending on the increased structure-energy correlations as the GEM is approached during the search. This method, called the Monte Carlo minimization with an adaptive bias (MCMAB), was applied initially to the pentapeptide Leu-enkephalin. Here we study its properties further by applying it to the larger peptide with bulky side chains, deltorphin (H-Tyr-D-Met-Phe-His-Leu-Met-Asp-NH(2)). We find that on average the number of energy minimizations required by MCMAB to locate the GEM for the first time is smaller by a factor of approximately three than the number required by MCM-in accord with results obtained for Leu-enkephalin.