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Maksymenko K, Maurer A, Aghaallaei N, Barry C, Borbarán-Bravo N, Ullrich T, Dijkstra TM, Hernandez Alvarez B, Müller P, Lupas AN, Skokowa J, ElGamacy M. The design of functional proteins using tensorized energy calculations. CELL REPORTS METHODS 2023; 3:100560. [PMID: 37671023 PMCID: PMC10475850 DOI: 10.1016/j.crmeth.2023.100560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 05/25/2023] [Accepted: 07/21/2023] [Indexed: 09/07/2023]
Abstract
In protein design, the energy associated with a huge number of sequence-conformer perturbations has to be routinely estimated. Hence, enhancing the throughput and accuracy of these energy calculations can profoundly improve design success rates and enable tackling more complex design problems. In this work, we explore the possibility of tensorizing the energy calculations and apply them in a protein design framework. We use this framework to design enhanced proteins with anti-cancer and radio-tracing functions. Particularly, we designed multispecific binders against ligands of the epidermal growth factor receptor (EGFR), where the tested design could inhibit EGFR activity in vitro and in vivo. We also used this method to design high-affinity Cu2+ binders that were stable in serum and could be readily loaded with copper-64 radionuclide. The resulting molecules show superior functional properties for their respective applications and demonstrate the generalizable potential of the described protein design approach.
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Affiliation(s)
- Kateryna Maksymenko
- Department of Protein Evolution, Max Planck Institute for Biology, 72076 Tübingen, Germany
- Friedrich Miescher Laboratory of the Max Planck Society, 72076 Tübingen, Germany
| | - Andreas Maurer
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University, 72076 Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180) “Image Guided and Functionally Instructed Tumor Therapies,” Eberhard Karls University, 72076 Tübingen, Germany
| | - Narges Aghaallaei
- Division of Translational Oncology, University Hospital Tübingen, 72076 Tübingen, Germany
| | - Caroline Barry
- Department of Protein Evolution, Max Planck Institute for Biology, 72076 Tübingen, Germany
- Krieger School of Arts and Sciences, Johns Hopkins University, Washington, DC 20036, USA
| | - Natalia Borbarán-Bravo
- Division of Translational Oncology, University Hospital Tübingen, 72076 Tübingen, Germany
| | - Timo Ullrich
- Department of Protein Evolution, Max Planck Institute for Biology, 72076 Tübingen, Germany
- Friedrich Miescher Laboratory of the Max Planck Society, 72076 Tübingen, Germany
| | - Tjeerd M.H. Dijkstra
- Department of Protein Evolution, Max Planck Institute for Biology, 72076 Tübingen, Germany
- Department for Women’s Health, University Hospital Tübingen, 72076 Tübingen, Germany
- Translational Bioinformatics, University Hospital Tübingen, 72072 Tübingen, Germany
| | | | - Patrick Müller
- Friedrich Miescher Laboratory of the Max Planck Society, 72076 Tübingen, Germany
| | - Andrei N. Lupas
- Department of Protein Evolution, Max Planck Institute for Biology, 72076 Tübingen, Germany
| | - Julia Skokowa
- Division of Translational Oncology, University Hospital Tübingen, 72076 Tübingen, Germany
| | - Mohammad ElGamacy
- Department of Protein Evolution, Max Planck Institute for Biology, 72076 Tübingen, Germany
- Friedrich Miescher Laboratory of the Max Planck Society, 72076 Tübingen, Germany
- Division of Translational Oncology, University Hospital Tübingen, 72076 Tübingen, Germany
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Grybauskas A, Gražulis S. Building protein structure-specific rotamer libraries. Bioinformatics 2023; 39:btad429. [PMID: 37439702 PMCID: PMC10359632 DOI: 10.1093/bioinformatics/btad429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 06/19/2023] [Indexed: 07/14/2023] Open
Abstract
MOTIVATION Identifying the probable positions of the protein side-chains is one of the protein modelling steps that can improve the prediction of protein-ligand and protein-protein interactions. Most of the strategies predicting the side-chain conformations use predetermined dihedral angle lists, also called rotamer libraries, that are usually generated from a subset of high-quality protein structures. Although these methods are fast to apply, they tend to average out geometries instead of taking into account the surrounding atoms and molecules and ignore structures not included in the selected subset. Such simplifications can result in inaccuracies when predicting possible side-chain atom positions. RESULTS We propose an approach that takes into account both of these circumstances by scanning through sterically accessible side-chain conformations and generating dihedral angle libraries specific to the target proteins. The method avoids the drawbacks of lacking conformations due to unusual or rare protein structures and successfully suggests potential rotamers with average RMSD closer to the experimentally determined side-chain atom positions than other widely used rotamer libraries. AVAILABILITY AND IMPLEMENTATION The technique is implemented in open-source software package rotag and available at GitHub: https://www.github.com/agrybauskas/rotag, under GNU Lesser General Public License.
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Affiliation(s)
- Algirdas Grybauskas
- Sector of Crystallography and Cheminformatics, Institute of Biotechnology, Life Sciences Center, Vilnius University, 7 Saulėtekio Ave, Vilnius, LT- 10257, Lithuania
| | - Saulius Gražulis
- Sector of Crystallography and Cheminformatics, Institute of Biotechnology, Life Sciences Center, Vilnius University, 7 Saulėtekio Ave, Vilnius, LT- 10257, Lithuania
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Childers MC, Daggett V. Molecular Dynamics Methods for Antibody Design. Methods Mol Biol 2023; 2552:109-124. [PMID: 36346588 DOI: 10.1007/978-1-0716-2609-2_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Complex and coordinated dynamics are closely connected with protein functions, including the binding of antibodies to antigens. Knowledge of such dynamics could improve the design of antibodies. Molecular dynamics (MD) simulations provide a "computational microscope" that can resolve atomic motions and inform antibody design efforts.
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Affiliation(s)
| | - Valerie Daggett
- Department of Bioengineering, University of Washington, Seattle, WA, USA.
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Prosswimmer T, Daggett V. The role of α-sheet structure in amyloidogenesis: characterization and implications. Open Biol 2022; 12:220261. [PMID: 36416010 PMCID: PMC9682440 DOI: 10.1098/rsob.220261] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 11/01/2022] [Indexed: 11/25/2022] Open
Abstract
Amyloid diseases are linked to protein misfolding whereby the amyloidogenic protein undergoes a conformational change, aggregates and eventually forms amyloid fibrils. While the amyloid fibrils and plaques are hallmarks of these diseases, they typically form late in the disease process and do not correlate with disease. Instead, there is growing evidence that smaller, soluble toxic oligomers form prior and appear to be early triggers of the molecular pathology underlying these diseases. Nearly 20 years ago, we proposed the α-sheet hypothesis after discovering that the early conformational changes observed during atomistic molecular dynamics simulations involve the formation of a non-standard protein structure, α-sheet. Furthermore, we proposed that toxic oligomers contain α-sheet structure and that preferentially targeting this structure could neutralize the toxicity, prevent further aggregation and serve as the basis for early detection of disease. Here, we present the origin of the α-sheet hypothesis and describe α-sheet structure and the corresponding mechanisms of conversion. We discuss experimental studies demonstrating that both mammalian and bacterial amyloid systems form α-sheet oligomers before converting to conventional β-sheet fibrils. Furthermore, we show that the process can be inhibited with de novo designed α-sheet peptides complementary to the structure in the toxic oligomers.
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Affiliation(s)
- Tatum Prosswimmer
- Molecular Engineering Program, University of Washington, Seattle, WA 98195-5013, USA
| | - Valerie Daggett
- Molecular Engineering Program, University of Washington, Seattle, WA 98195-5013, USA
- Department of Bioengineering, University of Washington, Seattle, WA 98195-5013, USA
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Childers MC, Daggett V. Insights from molecular dynamics simulations for computational protein design. MOLECULAR SYSTEMS DESIGN & ENGINEERING 2017; 2:9-33. [PMID: 28239489 PMCID: PMC5321087 DOI: 10.1039/c6me00083e] [Citation(s) in RCA: 133] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures.
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Affiliation(s)
| | - Valerie Daggett
- Corresponding author: , Phone: 1.206.685.7420, Fax: 1.206.685.3300
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