scholarly journals Novel, provable algorithms for efficient ensemble-based computational protein design and their application to the redesign of the c-Raf-RBD:KRas protein-protein interface

2020 ◽  
Vol 16 (6) ◽  
pp. e1007447 ◽  
Author(s):  
Anna U. Lowegard ◽  
Marcel S. Frenkel ◽  
Graham T. Holt ◽  
Jonathan D. Jou ◽  
Adegoke A. Ojewole ◽  
...  
Keyword(s):  
Protein Design ◽  
Computational Protein Design ◽  
Protein Interface ◽  
Provable Algorithms

scholarly journals Novel, provable algorithms for efficient ensemble-based computational protein design and their application to the redesign of the c-Raf-RBD:KRas protein-protein interface

2019 ◽  
Author(s):  
Anna U. Lowegard ◽  
Marcel S. Frenkel ◽  
Jonathan D. Jou ◽  
Adegoke A. Ojewole ◽  
Graham T. Holt ◽  
...  
Keyword(s):  
Protein Design ◽  
Input Sequence ◽  
Binding Domain ◽  
Computational Protein Design ◽  
Partition Functions ◽  
Protein Interface ◽  
Computational Structure ◽  
New Variant ◽  
Provable Algorithms ◽  
New Algorithms

AbstractThe K* algorithm provably approximates partition functions for a set of states (e.g., protein, ligand, and protein-ligand complex) to a user-specified accuracy ε. Often, reaching an ε-approximation for a particular set of partition functions takes a prohibitive amount of time and space. To alleviate some of this cost, we introduce two algorithms into the osprey suite for protein design: fries, a Fast Removal of Inadequately Energied Sequences, and EWAK*, an Energy Window Approximation to K*. In combination, these algorithms provably retain calculational accuracy while limiting the input sequence space and the conformations included in each partition function calculation to only the most energetically favorable. This combined approach leads to significant speed-ups compared to the previous state-of-the-art multi-sequence algorithm, BBK*. As a proof of concept, we used these new algorithms to redesign the protein-protein interface (PPI) of the c-Raf-RBD:KRas complex. The Ras-binding domain of the protein kinase c-Raf (c-Raf-RBD) is the tightest known binder of KRas, a historically “undruggable” protein implicated in difficult-to-treat cancers including pancreatic ductal adenocarcinoma (PDAC). fries/EWAK* accurately retrospectively predicted the effect of 38 out of 41 different sets of mutations in the PPI of the c-Raf-RBD:KRas complex. Notably, these mutations include mutations whose effect had previously been incorrectly predicted using other computational methods. Next, we used fries/EWAK* for prospective design and discovered a novel point mutation that improves binding of c-Raf-RBD to KRas in its active, GTP-bound state (KRasGTP). We combined this new mutation with two previously reported mutations (which were also highly-ranked by osprey) to create a new variant of c-Raf-RBD, c-Raf-RBD(RKY). fries/EWAK* in osprey computationally predicted that this new variant would bind even more tightly than the previous best-binding variant, c-Raf-RBD(RK). We measured the binding affinity of c-Raf-RBD(RKY) using a bio-layer interferometry (BLI) assay and found that this new variant exhibits single-digit nanomolar affinity for KRasGTP, confirming the computational predictions made with fries/EWAK*. This study steps through the advancement and development of computational protein design by presenting theory, new algorithms, accurate retrospective designs, new prospective designs, and biochemical validation.Author summaryComputational structure-based protein design is an innovative tool for redesigning proteins to introduce a particular or novel function. One such possible function is improving the binding of one protein to another, which can increase our understanding of biomedically important protein systems toward the improvement or development of novel therapeutics. Herein we introduce two novel, provable algorithms, fries and EWAK*, for more efficient computational structure-based protein design as well as their application to the redesign of the c-Raf-RBD:KRas protein-protein interface. These new algorithms speed up computational structure-based protein design while maintaining accurate calculations, allowing for larger, previously infeasible protein designs. Using fries and EWAK* within the osprey suite, we designed the tightest known binder of KRas, an “undruggable” cancer target. This new variant of a KRas-binding domain, c-Raf-RBD, should serve as an important tool to probe the protein-protein interface between KRas and its effectors as work continues toward an effective therapeutic targeting KRas.

scholarly journals cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design

2016 ◽  
Vol 23 (9) ◽  
pp. 737-749 ◽  
Author(s):  
Yuchao Pan ◽  
Yuxi Dong ◽  
Jingtian Zhou ◽  
Mark Hallen ◽  
Bruce R. Donald ◽  
...  
Keyword(s):  
Protein Design ◽  
Distributed Algorithm ◽  
Large Scale ◽  
Computational Protein Design

scholarly journals Discovery of Substrates for a SET Domain Lysine Methyltransferase Predicted by Multistate Computational Protein Design

Structure ◽  
2015 ◽  
Vol 23 (1) ◽  
pp. 206-215 ◽  
Author(s):  
Sylvain Lanouette ◽  
James A. Davey ◽  
Fred Elisma ◽  
Zhibin Ning ◽  
Daniel Figeys ◽  
...  
Keyword(s):  
Protein Design ◽  
Computational Protein Design ◽  
Set Domain ◽  
Lysine Methyltransferase

Electrostatics in computational protein design

2005 ◽  
Vol 9 (6) ◽  
pp. 622-626 ◽  
Author(s):  
Christina L Vizcarra ◽  
Stephen L Mayo
Keyword(s):  
Protein Design ◽  
Computational Protein Design

scholarly journals Pushing the limits of automatic computational protein design: design, expression, and characterization of a large synthetic protein based on a fungal laccase scaffold

2011 ◽  
Vol 5 (1-2) ◽  
pp. 45-58 ◽  
Author(s):  
Doris J. Glykys ◽  
Géza R. Szilvay ◽  
Pablo Tortosa ◽  
María Suárez Diez ◽  
Alfonso Jaramillo ◽  
...  
Keyword(s):  
Protein Design ◽  
Computational Protein Design ◽  
Fungal Laccase ◽  
Synthetic Protein

Current methods and applications in computational protein design for food industry

2019 ◽  
Vol 60 (19) ◽  
pp. 3259-3270 ◽  
Author(s):  
Qiuming Chen ◽  
Yaqin Xiao ◽  
Wenli Zhang ◽  
Wanmeng Mu
Keyword(s):  
Protein Design ◽  
Food Industry ◽  
Computational Protein Design
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