An enumerative algorithm for de novo design of proteins with diverse pocket structures

Basanta, Benjamin; Bick, Matthew J.; Bera, Asim K.; Norn, Christoffer; Chow, Cameron M.; Carter, Lauren; Goreshnik, Inna; DiMaio, Frank; Baker, David

doi:10.1073/pnas.2005412117

Cited by 71 publications

(71 citation statements)

References 43 publications

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“…The name of the modifier in Rosetta is ‘BluePrintBDR’, and it is usually referred to as the ‘blueprint builder’. The protein folds (i.e., the arrangement of a suite of secondary structure elements, SSEs; Schaeffer & Daggett, 2011) that have been generated include ferredoxin‐like folds (Koga et al., 2012), Rossmann 2 × 2 folds (Lin et al., 2015), TIM barrel folds (Huang et al., 2016), nuclear transport factor 2−like protein folds (NTF2‐like; Basanta et al., 2020; Marcos et al., 2018), β‐barrel folds (Dou et al., 2018), and multiple miniprotein folds (Chevalier et al., 2017). The β‐barrel is a family of barrel‐like protein structures that are composed of a suite of β‐sheets, among which the first strand and the last strand of the β‐sheet are connected via backbone hydrogen bonds to form a closed barrel shape.…”

Section: Introductionmentioning

confidence: 99%

De Novo Protein Design Using the Blueprint Builder in Rosetta

Lee

2020

CP Protein Science

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While native proteins cover diverse structural spaces and achieve various biological events, not many of them can directly serve human needs. One reason is that the native proteins usually contain idiosyncrasies evolved for their native functions but disfavoring engineering requirements. To overcome this issue, one strategy is to create de novo proteins which are designed to possess improved stability, high environmental tolerance, and enhanced engineering potential. Compared to other protein engineering strategies, in silico design of de novo proteins has significantly expanded the protein structural and sequence spaces, reduced wet lab workload, and incorporated engineered features in a guided and efficient manner. In the Baker laboratory we have been applying a design pipeline that uses the blueprint builder to design different folds of de novo proteins, and have successfully obtained libraries of de novo proteins with improved stability and engineering potential. In this article, we will use the design of de novo β‐barrel proteins as an example to describe the principles and basic procedures of the blueprint builder−based design pipeline. © 2020 Wiley Periodicals LLC. Basic Protocol 1: The construction of blueprints Alternate Protocol: Build blueprints based on existing protein .pdb files Basic Protocol 2: De novo protein design pipeline using the blueprint builder

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Section: Introductionmentioning

confidence: 99%

De Novo Protein Design Using the Blueprint Builder in Rosetta

Lee

2020

CP Protein Science

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“…Advances in computational protein structure sampling methods (20) have expanded the accessible structure space of de novo designed proteins. In particular, two recently developed computational methods (15,16) are capable of engineering de novo protein families that contain defined variations in geometry of proteins that share the same overall fold topology. We probed the functional implications of de novo protein fold families generated by the LUCS method (15) by matching known ligand binding sites to both native and de novo fold families.…”

Section: Discussionmentioning

confidence: 99%

“…This strategy has recently been mimicked by advances in computational protein design methods. These methods have generated de novo designed protein fold families with large numbers of diverse geometries (15,16), which have significantly expanded the accessible designable protein structure space. The resulting de novo proteins might be able to support binding sites that cannot be built onto naturally occurring proteins in the PDB, but the extent to which de novo fold families could improve binding site design has not been explored.…”

Section: Introductionmentioning

confidence: 99%

De novoprotein fold families expand the designable ligand binding site space

Pan

Kortemme

2021

Preprint

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A major challenge in designing proteins de novo to bind user-defined ligands with high specificity and affinity is finding backbones structures that can accommodate a desired binding site geometry with high precision. Recent advances in methods to generate protein fold families de novo have expanded the space of accessible protein structures, but it is not clear to what extend de novo proteins with diverse geometries also expand the space of designable ligand binding functions. We constructed a library of 25,806 high-quality ligand binding sites and developed a fast protocol to place (“match”) these binding sites into both naturally occurring and de novo protein families with two fold topologies: Rossman and NTF2. 5,896 and 7,475 binding sites could be matched to the Rossmann and NTF2 fold families, respectively. De novo designed Rossman and NTF2 protein families can support 1,791 and 678 binding sites that cannot be matched to naturally existing structures with the same topologies, respectively. While the number of protein residues in ligand binding sites is the major determinant of matching success, ligand size and primary sequence separation of binding site residues also play important roles. The number of matched binding sites are power law functions of the number of members in a fold family. Our results suggest that de novo sampling of geometric variations on diverse fold topologies can significantly expand the space of designable ligand binding sites for a wealth of possible new protein functions.Author summaryDe novo design of proteins that can bind to novel and highly diverse user-defined small molecule ligands could have broad biomedical and synthetic biology applications. Because ligand binding site geometries need to be accommodated by protein backbone scaffolds at high accuracy, the diversity of scaffolds is a major limitation for designing new ligand binding functions. Advances in computational protein structure design methods have significantly increased the number of accessible stable scaffold structures. Understanding how many new ligand binding sites can be accommodated by the de novo scaffolds is important for designing novel ligand binding proteins. To answer this question, we constructed a large library of ligand binding sites from the Protein Data Bank (PDB). We tested the number of ligand binding sites that can be accommodated by de novo scaffolds and naturally existing scaffolds with same fold topologies. The results showed that de novo scaffolds significantly expanded the ligand binding space of their respective fold topologies. We also identified factors that affect difficulties of binding site accommodation, as well as the relationship between the number of scaffolds and the accessible ligand binding site space. We believe our findings will benefit future method development and applications of ligand binding protein design.

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“…The Baker lab has taken a general approach to small molecule binding, creating an algorithm that takes advantage of the structural stability, and diversity, of a naturally occurring protein family, NTF-2. Basanta and coauthors developed an enumerative algorithm that first docks a ligand into a protein cavity, then systematically samples a variety of different amino acid combinations in that cavity to find the most ideal binding partner [ 100 ]. Overall they were able to sample over 1600 different protein variations, able to bind different ligands.…”

Section: New Algorithms For Protein Designmentioning

confidence: 99%

Recent Progress Using De Novo Design to Study Protein Structure, Design and Binding Interactions

Ferrando

Solomon

2021

Life

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De novo protein design is a powerful methodology used to study natural functions in an artificial-protein context. Since its inception, it has been used to reproduce a plethora of reactions and uncover biophysical principles that are often difficult to extract from direct studies of natural proteins. Natural proteins are capable of assuming a variety of different structures and subsequently binding ligands at impressively high levels of both specificity and affinity. Here, we will review recent examples of de novo design studies on binding reactions for small molecules, nucleic acids, and the formation of protein-protein interactions. We will then discuss some new structural advances in the field. Finally, we will discuss some advancements in computational modeling and design approaches and provide an overview of some modern algorithmic tools being used to design these proteins.

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An enumerative algorithm for de novo design of proteins with diverse pocket structures

Cited by 71 publications

References 43 publications

De Novo Protein Design Using the Blueprint Builder in Rosetta

De Novo Protein Design Using the Blueprint Builder in Rosetta

De novoprotein fold families expand the designable ligand binding site space

Recent Progress Using De Novo Design to Study Protein Structure, Design and Binding Interactions

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