High-resolution Structural and Thermodynamic Analysis of Extreme Stabilization of Human Procarboxypeptidase by Computational Protein Design

By G. Dantas, Colin Corrent, S. Reichow, James J. Havranek, Ziad M. Eletr, N. Isern, Brian Kuhlman, Gabriele Varani, E. Merritt, David Baker. 2007

90 citations recorded by the source corpus.

Recent efforts to design de novo or redesign the sequence and structure of proteins using computational techniques have met with significant success. Most, if not all, of these computational methodologies attempt to model atomic-level interactions, and hence high-resolution structural characterization of the designed proteins is critical for evaluating the atomic-level accuracy of the underlying design force-fields. We previously used our computational protein design protocol RosettaDesign to completely redesign the sequence of the activation domain of human procarboxypeptidase A2. With 68% of the wild-type sequence changed, the designed protein, AYEdesign, is over 10 kcal/mol more stable than the wild-type protein. Here, we describe the high-resolution crystal structure and solution NMR structure of AYEdesign, which show that the experimentally determined backbone and side-chains conformations are effectively superimposable with the computational model at atomic resolution. To isolate the origins of the remarkable stabilization, we have designed and characterized a new series of procarboxypeptidase mutants that gain significant thermodynamic stability with a minimal number of mutations; one mutant gains more than 5 kcal/mol of stability over the wild-type protein with only four amino acid changes. We explore the relationship between force-field smoothing and conformational sampling by comparing the experimentally determined free energies of the overall design and these focused subsets of mutations to those predicted using modified force-fields, and both fixed and flexible backbone sampling protocols.

Subfields: Materials Chemistry, Molecular Biology, Oncology

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Citations in the corpus

Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement (2013, background): “…energy functions (Liang & Grishin, 2002; Petrella, Lazaridis, & Karplus, 1998), including extensive use to evaluate the Rosetta energy function (Dantas et al., 2007; Dobson, Dantas, Baker, & Varani, 2006; Jacak et al., 2012; Kortemme et al., 2003), the ORBIT energy function (Sharabi, Yanover,…”
Practically Useful: What the Rosetta Protein Modeling Suite Can Do for You (2010, unknown): “2kcal/mol( 75 ).”
A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function (2012, methodology): “Computational methods generally rely on physicochemical models to estimate the thermodynamic impact of mutations (28, 29).”
A de novo protein binding pair by computational design and directed evolution (2011, result): “In contrast to standard RosettaDesign, which has proven useful in designing hydrophobic cores for monomeric proteins (Dantas et al., 2007; Dantas et al., 2003; Kuhlman et al., 2003), our method focuses on the unique requirements and characteristics of a dissociable protein-protein interface.”
Achievements and Challenges in Computational Protein Design. (2017, background): “One of these designs, human procarboxypeptidase A2, was structurally resolved in 2007 enabling to discretely analyze residues contributing to different types of hydrophobic packing: interhelical, inter-strand, and helix-strand packing [46].”
Computational Protein Design with Explicit Consideration of Surface Hydrophobic Patches (2011, methodology): “Subsequent NMR analysis indicated that at concentrations >100 µM the redesigned protein self-associates and buries the hydrophobic residues on the surface of the β -sheet 4 .”
Direct prediction of profiles of sequences compatible with a protein structure by neural networks with fragment‐based local and energy‐based nonlocal profiles (2014, background): “Significant progress in protein design has been made in recent years with a number of designed sequences successfully validated experimentally in terms of their structures and their functions 1–11 .”
Energy functions in de novo protein design: current challenges and future prospects. (2013, background): “Currently, on the other hand, specific structures of de novo designed proteins are routinely validated by NMR or X-ray structure determination (5, 9, 17, 21, 27, 41, 56, 60, 82, 104, 115).”