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Lowegard, A. U.

Publications and source records attributed to Lowegard, A. U..

3 recordsLinked to original sources

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

The K* algorithm provably approximates partition functions for a set of states (e.g., protein, ligand, and protein-ligand complex) to a user-specified accuracy{varepsilon} . Often, reaching an{varepsilon} -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: O_SCPLOWFRIESC_SCPLOW, 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). O_SCPLOWFRIESC_SCPLOW/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 O_SCPLOWFRIESC_SCPLOW/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 O_SCPLOWOSPREYC_SCPLOW) to create a new variant of c-Raf-RBD, c-Raf-RBD(RKY). O_SCPLOWFRIESC_SCPLOW/EWAK* in O_SCPLOWOSPREYC_SCPLOW 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 O_SCPLOWFRIESC_SCPLOW/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.\n\nAuthor 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, O_SCPLOWFRIESC_SCPLOW 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 O_SCPLOWFRIESC_SCPLOW and EWAK* within the O_SCPLOWOSPREYC_SCPLOW 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.

biochemistry↗

Computational Analysis of Energy Landscapes Reveals Dynamic Features that Contribute to Binding of Inhibitors to CFTR-Associated Ligand

PDZ domains are small protein-binding domains that interact with short, mostly C-terminal peptides and play important roles in cellular signaling and the trafficking and localization of ion channels. The CFTR-associated ligand PDZ domain (CALP) binds to the cystic fibro-sis transmembrane conductance regulator (CFTR) and mediates degradation of mature CFTR through lysosomal pathways. Inhibition of the CALP:CFTR interaction has been explored as a potential therapeutic avenue for cystic fibrosis (CF).1 Previously, we reported2 the ensemble-based computational design of a novel 6-residue peptide inhibitor of CALP, which resulted in the most binding-efficient inhibitor of CALP to date. This inhibitor, kCAL01, was designed using OSPREY3 and displayed significant biological activity in in vitro cell-based assays. Here, we report a crystal structure of kCAL01 bound to CALP (PDB ID: 6OV7). To elucidate the structural basis for the enhanced binding efficiency of kCAL01, we compare this structure to that of a previously developed inhibitor of CALP, iCAL36 (PDB ID: 4E34). In addition to per-forming traditional structural analysis, we compute the side-chain energy landscapes for each structure using the recently developed MARK* partition function approximation algorithm.4 Analysis of these energy landscapes not only enables approximation of binding thermodynamics for these structural models of CALP:inhibitor binding, but also foregrounds important structural features and reveals dynamic features, both of which contribute to the comparatively efficient binding of kCAL01. The investigation of energy landscapes complements traditional analysis of the few low-energy conformations found in crystal structures, and provides information about the entire conformational ensemble that is accessible to a protein structure model. Finally, we compare the previously reported NMR-based design model ensemble for kCAL01 vs. the new crystal structure and show that, despite the notable differences between the CALP NMR model and crystal structure, many significant features are successfully captured in the design ensemble. This suggests not only that ensemble-based design captured thermodynamically significant features observed in vitro, but also that a design algorithm eschewing ensembles would likely miss the kCAL01 sequence entirely.\n\nGraphical TOC Entry\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC=\"FIGDIR/small/720342v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@2a1036org.highwire.dtl.DTLVardef@18e5fe0org.highwire.dtl.DTLVardef@38ab86org.highwire.dtl.DTLVardef@84f1b5_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

OSPREY 3.0: Open-Source Protein Redesign for You, with Powerful New Features

We present O_SCPCAPOSPREYC_SCPCAP 3.0, a new and greatly improved release of the O_SCPLOWOSPREYC_SCPLOW protein design software. O_SCPLOWOSPREYC_SCPLOW 3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions of O_SCPLOWOSPREYC_SCPLOW when running the same algorithms on the same hardware. Moreover, O_SCPLOWOSPREYC_SCPLOW 3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions of O_SCPLOWOSPREYC_SCPLOWO_SCPCAP, C_SCPCAPO_SCPLOWOSPREYC_SCPLOW 3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically that O_SCPLOWOSPREYC_SCPLOW 3.0 accurately predicts the effect of mutations on protein-protein binding. O_SCPLOWOSPREYC_SCPLOW 3.0 is available at http://www.cs.duke.edu/donaldlab/osprey.php as free and open-source software.\n\nO_TEXTBOX\n\nWe present the third major release of the OSPREY protein design software, along with comparisons to experimental data that confirm its ability to optimize protein mutants for desired functions. osprey 3.0 has significant efficiency, ease-of-use, and algorithmic improvements over previous versions, including GPU acceleration and a new Python interface.\n\nC_TEXTBOX\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=162 SRC=\"FIGDIR/small/306324v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (54K):\norg.highwire.dtl.DTLVardef@f08b0dorg.highwire.dtl.DTLVardef@393b61org.highwire.dtl.DTLVardef@16997ddorg.highwire.dtl.DTLVardef@1713405_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗