Minimization-Aware Recursive $$K^{*}$$ K ∗ ( $${ MARK}^{*}$$ MARK ∗ ): A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape

Jou, Jonathan; Holt, Graham T.; Lowegard, Anna U.; Donald, Bruce Randall

doi:10.1007/978-3-030-17083-7_7

Cited by 4 publications

(19 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nine residues for CALP and the six most C-terminal residues for kCAL01 or iCAL36 (for a total of 15 residues in in each bound complex, see Table S2) were modeled as continuously flexible using continuous rotamers 68,69 in OSPREY. As in Refs., 4,44,68,70 rotamers from the Penultimate Rotamer Library 48 were allowed to adopt any side-chain conformation such that all χ-angles are within ±9 • of their modal χ-angles.…”

Section: Methodsmentioning

confidence: 99%

“…Aggregate values for the ensembles in each state were computed by bounding the energy for each conformation in the ensemble, and combining these energy bounds. For each bound and unbound state, we first computed bounds on the the energy of each conformation in the conformational ensemble defined by that state, as was done in Ref., [2][3][4]42,71,72 Although the K * score exhibits good Spearman's rank correlation with experimental K a values, 3,71 the correlation between K * scores and K a is not yet quantitative. First, most physics-based 9 energy functions are based on small-molecule energetics, which can overestimate van der Waals terms and thereby overestimate internal energy.…”

Section: Entropy Internal Energy and Helmholtz Free Energy Calculationmentioning

confidence: 99%

“…Therefore, we scaled our thermodynamic values, decreasing internal energy U by a factor of 4, similar to the method described in Ref. 4…”

Section: Entropy Internal Energy and Helmholtz Free Energy Calculationmentioning

confidence: 99%

“…For a full description of ring diagram visualizations, see Ref. 4 Briefly, each concentric ring represents a design amino acid residue, with each ring arc representing a single rotamer assignment to that residue given the residue assignments of the inner arcs, or "partial conformation." Therefore, any arc in the outermost ring represents a "full conformation", where all amino acid positions are each assigned a single rotamer.…”

Section: Interpretation Of Energy Landscape Diagramsmentioning

confidence: 99%

“…bound complex, unbound protein and ligand), allows visualization of the entire energy landscape accessible to a protein input model. 4 MARK * provably bounds the energy and statistical weight of every conformation in the input model conformation space, allowing designers to compute and visualize changes in conformation distribution, instead of merely analyzing changes to a small set of low-energy conformations, or to ensemble averaged values like free energy or K a . By computing both a conformation distribution and provably approximating energies for every conformation, MARK * enables visualization of the energy landscape.…”

mentioning

confidence: 99%

See 4 more Smart Citations

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

Holt

Jou²,

Gill

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

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 fibrosis 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 reported 2 the ensemblebased 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 OSPREY 3 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 performing traditional structural analysis, we compute the side-chain energy landscapes for each structure using the recently developed MARK * partition function approximation algorithm. 4Analysis 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. 2Interactions between proteins and short linear motif peptides are important in many cellular contexts. 5 One such class of peptide-binding proteins is the PDZ (PSD-95, discs large, ZO-1) domain family, characterized by an 80-90 residue motif 6 that adopts a conserved fold comprised of 2-3 α-helices and 5-6 β-strands and binds C-terminal peptides through β-sheet interactions. 7 These domains commonly modulate protein localization and complex assembly 8-10 and regulate cell signalling, 11,12 thereby playing critical roles in auditory and visual systems; 13,14 epilepsy, pain, and addiction; 10,15 synapse formation; 9 cancer; 11,12,16,17 and cystic fibrosis. [18][19][20][21] Protein-peptide interactions have been imp...

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Entropy Internal Energy and Helmholtz Free Energy Calculationmentioning

confidence: 99%

“…Therefore, we scaled our thermodynamic values, decreasing internal energy U by a factor of 4, similar to the method described in Ref. 4…”

Section: Entropy Internal Energy and Helmholtz Free Energy Calculationmentioning

confidence: 99%

Section: Interpretation Of Energy Landscape Diagramsmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

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

Holt

Jou²,

Gill

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

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

et al. 2019

Self Cite

View full text Add to dashboard Cite

The CFTR-associated ligand PDZ domain (CALP) binds to the cystic fibrosis transmembrane conductance regulator (CFTR) and mediates lysosomal degradation of mature CFTR. Inhibition of this interaction has been explored as a therapeutic avenue for cystic fibrosis. Previously, we reported the ensemble-based computational design of a novel peptide inhibitor of CALP, which resulted in the most binding-efficient inhibitor to date. This inhibitor, kCAL01, was designed using OSPREY and evinced significant biological activity in in vitro cell-based assays. Here, we report a crystal structure of kCAL01 bound to CALP and compare structural features against iCAL36, a previously developed inhibitor of CALP. We compute side-chain energy landscapes for each structure to not only enable approximation of binding thermodynamics but also reveal ensemble features that contribute to the comparatively efficient binding of kCAL01. Finally, we compare the previously reported design ensemble for kCAL01 vs the new crystal structure and show that, despite small differences between the design model and crystal structure, significant biophysical features that enhance inhibitor binding are captured in the design ensemble. This suggests not only that ensemble-based design captured thermodynamically significant features *

show abstract

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

Lowegard

Frenkel²,

Jou³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

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 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 September 25, 2019 1/34 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 (KRas GTP ).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 KRas GTP , 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 int...

show abstract

Minimization-Aware Recursive $$K^{}$$ K ∗ ( $${ MARK}^{}$$ MARK ∗ ): A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape

Cited by 4 publications

References 48 publications

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

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

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

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

Contact Info

Product

Resources

About