Article
Multidisciplinary Sciences
Andy Hsien-Wei Yeh, Christoffer Norn, Yakov Kipnis, Doug Tischer, Samuel J. Pellock, Declan Evans, Pengchen Ma, Gyu Rie Lee, Jason Z. Zhang, Ivan Anishchenko, Brian Coventry, Longxing Cao, Justas Dauparas, Samer Halabiya, Michelle DeWitt, Lauren Carter, K. N. Houk, David Baker
Summary: We have successfully designed an artificial luciferase with high selectivity and catalytic efficiency using a deep-learning-based approach. This achievement is a major milestone in computational enzyme design and has broad applications in biomedical research.
Article
Multidisciplinary Sciences
Alfredo Quijano-Rubio, Hsien-Wei Yeh, Jooyoung Park, Hansol Lee, Robert A. Langan, Scott E. Boyken, Marc J. Lajoie, Longxing Cao, Cameron M. Chow, Marcos C. Miranda, Jimin Wi, Hyo Jeong Hong, Lance Stewart, Byung-Ha Oh, David Baker
Summary: Protein switches have been repurposed for biosensor development by inverting the flow of information, creating modular molecular devices with a closed dark state and an open luminescent state. These sensors, based on thermodynamic coupling, require only one target binding domain for direct readout in solution, allowing for the detection of various molecules clinically, including the SARS-CoV-2 spike protein with high sensitivity and a 50-fold higher luminescence signal than background level. The modularity and sensitivity of this platform enable rapid sensor construction for a wide range of analytes, demonstrating the power of de novo protein design in creating multi-state protein systems with new functions.
Article
Multidisciplinary Sciences
Tamuka M. Chidyausiku, Soraia R. Mendes, Jason C. Klima, Marta Nadal, Ulrich Eckhard, Jorge Roel-Touris, Scott Houliston, Tibisay Guevara, Hugh K. Haddox, Adam Moyer, Cheryl H. Arrowsmith, F. Xavier Gomis-Ruth, David Baker, Enrique Marcos
Summary: The researchers develop design rules for tailoring immunoglobulin domains and demonstrate their ability to accurately design these domains de novo with high stability and the ability to scaffold functional loops.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Anastassia A. Vorobieva, Paul White, Binyong Liang, Jim E. Horne, Asim K. Bera, Cameron M. Chow, Stacey Gerben, Sinduja Marx, Alex Kang, Alyssa Q. Stiving, Sophie R. Harvey, Dagan C. Marx, G. Nasir Khan, Karen G. Fleming, Vicki H. Wysocki, David J. Brockwell, Lukas K. Tamm, Sheena E. Radford, David Baker
Summary: Through computational design, researchers successfully developed novel TMBs with no homology to known TMBs, which can reversibly insert and fold into synthetic lipid membranes, and exhibit experimental structures highly similar to computational models. This advancement is expected to facilitate the custom design of pores for various applications.
Review
Chemistry, Multidisciplinary
Dan Qiao, Yuang Chen, Haojing Tan, Ruhong Zhou, Jiandong Feng
Summary: This review discusses the crucial relationship between design and structure of transmembrane nanopores, compares different building blocks of bottom-up built nanopores in terms of construction methods, structures and applications, and describes important advances in de novo designed proteins from the perspective of theoretical simulations. An outlook for artificial intelligence-assisted nanopore design is also provided.
SCIENCE CHINA-CHEMISTRY
(2022)
Article
Multidisciplinary Sciences
Zander Harteveld, Jaume Bonet, Stephene Rosset, Che Yang, Fabian Sesterhenn, Bruno E. Correia
Summary: De novo protein design is a powerful tool to explore new sequences and structures not found in nature. By using the TopoBuilder method, we were able to design sequences that adopt predicted folds and demonstrated their stability through experimental characterization.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Multidisciplinary Sciences
Derrick R. Hicks, Madison A. Kennedy, Kirsten A. Thompson, Michelle DeWitt, Brian Coventry, Alex Kang, Asim K. Bera, T. J. Brunette, Banumathi Sankaran, Barry Stoddard, David Baker
Summary: Researchers have successfully designed hyperstable C2 symmetric proteins with pockets of diverse size and shape. By docking repeat proteins into C2 symmetric homodimers, they generated a wide range of C2 symmetric cavities. Experimental characterization showed that some of these designs matched computational models, providing starting points for binding various C2 symmetric compounds.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Chemistry, Medicinal
Sowmya Ramaswamy Krishnan, Navneet Bung, Sarveswara Rao Vangala, Rajgopal Srinivasan, Gopalakrishnan Bulusu, Arijit Roy
Summary: This study proposes a deep learning-based method for de novo drug design using the knowledge of the active site structure of the target protein. The method utilizes a graph attention model to learn the features of amino acids in the active site and employs a pretrained generative model to generate new molecules. The conditional generative model is further optimized using a bioactivity prediction model in a reinforcement learning framework.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Review
Pharmacology & Pharmacy
Joshua Meyers, Benedek Fabian, Nathan Brown
Summary: This review discusses the application of computational methods in drug discovery, focusing on molecular design strategies and de novo approaches. The methods of molecular design are categorized based on the coarseness of molecular representation, such as atom-based, fragment-based, or reaction-based paradigms. The importance of strong benchmarks, challenges in practical application, and potential opportunities for exploration and growth in the field are highlighted.
DRUG DISCOVERY TODAY
(2021)
Review
Chemistry, Multidisciplinary
Matthew J. Chalkley, Samuel I. Mann, William F. DeGrado
Summary: De novo protein design aims to define an amino acid sequence that encodes a specific structure and function of metalloproteins. By exploring ligand geometries, redox potentials, and catalytic reactions, significant progress has been made in designing diverse functional metalloproteins. The use of xenobiological metals and principles from inorganic chemistry also contributes to deriving new-to-nature functions in proteins.
NATURE REVIEWS CHEMISTRY
(2022)
Article
Materials Science, Multidisciplinary
Dong Zhang, Yijing Tang, Jintao Yang, Yijing Gao, Chunxin Ma, Lingbin Che, Jianguo Wang, Jiang Wu, Jie Zheng
Summary: Zwitterionic materials and allochroic materials offer distinct properties and functions for different applications. The development of zwitterionic, allochroic materials remains challenging. In this study, water-soluble and allochroic polymers of pVPES were designed and synthesized, which can self-polymerize into different architectures or co-polymerize with other functional polymers to become different smart devices. The pVPES-based hydrogel patches not only accelerated wound healing but also distinguished different types of wounds through color changes.
Article
Multidisciplinary Sciences
Tae-Eun Kim, Kotaro Tsuboyama, Scott Houliston, Cydney M. Martell, Claire M. Phoumyvong, Alexander Lemak, Hugh K. Haddox, Cheryl H. Arrowsmith, Gabriel J. Rocklin
Summary: Designing new protein structures remains challenging, and our study successfully designed stable aPPa proteins through large-scale design and test cycles, shedding light on the biophysical determinants of folding.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Biochemical Research Methods
Tim Kucera, Matteo Togninalli, Laetitia Meng-Papaxanthos
Summary: Motivation: Protein design is crucial for medical and biotechnological applications. However, creating novel proteins is laborious and time-consuming due to the complex mechanisms involved. Machine learning has shown promise in solving complex problems, particularly in generative modeling. In this study, the authors address the problem of general protein design by developing a conditional generative adversarial network called ProteoGAN. They evaluate the model using biologically and statistically inspired metrics and demonstrate its superiority over other deep-learning baselines.
Article
Biochemical Research Methods
Jianmin Wang, Yanyi Chu, Jiashun Mao, Hyeon-Nae Jeon, Haiyan Jin, Amir Zeb, Yuil Jang, Kwang-Hwi Cho, Tao Song, Kyoung Tai No
Summary: This study constructs a dataset for protein-protein interaction (PPI) targeted drug-likeness and proposes a deep molecular generative framework to generate novel drug-like molecules based on the features of seed compounds. The results show that the generated molecules have better PPI-targeted drug-likeness and drug-likeness, and the model performs comparably to other state-of-the-art molecule generation models.
BRIEFINGS IN BIOINFORMATICS
(2022)
Review
Biochemistry & Molecular Biology
Derek N. Woolfson
Summary: Protein design has evolved from rational design to computational design, leading to more complex and sophisticated designs. The ability to generate and manipulate synthetic proteins has advanced, offering realistic alternatives to natural protein functions. Challenges and opportunities lie ahead for the burgeoning field of de novo protein design.
JOURNAL OF MOLECULAR BIOLOGY
(2021)
Article
Biotechnology & Applied Microbiology
Ruwan Gunaratne, Shekhar Kumar, James W. Frederiksen, Steven Stayrook, Jens L. Lohrmann, Kay Perry, Kristin M. Bompiani, Charlene V. Chabata, Nabil K. Thalji, Michelle D. Ho, Gowthami Arepally, Rodney M. Camire, Sriram Krishnaswamy, Bruce A. Sullenger
NATURE BIOTECHNOLOGY
(2018)
Article
Biochemistry & Molecular Biology
Bruce R. Lichtenstein, Tammer A. Farid, Goutham Kodali, Lee A. Solomon, J. L. Ross Anderson, Molly M. Sheehan, Nathan M. Ennist, Bryan A. Fry, Sarah E. Chobot, Chris Bialas, Joshua A. Mancini, Craig T. Armstrong, Zhenyu Zhao, Tatiana V. Esipova, David Snell, Sergei A. Vinogradov, Bohdana M. Discher, Christopher C. Moser, P. Leslie Dutton
BIOCHEMICAL SOCIETY TRANSACTIONS
(2012)
Article
Biochemistry & Molecular Biology
Brenda Watt, Guillaume van Niel, Douglas M. Fowler, Ilse Hurbain, Kelvin C. Luk, Steven E. Stayrook, Mark A. Lemmon, Graca Raposo, James Shorter, Jeffery W. Kelly, Michael S. Marks
JOURNAL OF BIOLOGICAL CHEMISTRY
(2009)
Article
Multidisciplinary Sciences
Steven Stayrook, Peera Jaru-Ampornpan, Jenny Ni, Ann Hochschild, Mitchell Lewis
Article
Multidisciplinary Sciences
Daryl E. Klein, Steven E. Stayrook, Fumin Shi, Kartik Narayan, Mark A. Lemmon
Article
Multidisciplinary Sciences
Amanda L. Stouffer, Rudresh Acharya, David Salom, Anna S. Levine, Luigi Di Costanzo, Cinque S. Soto, Valentina Tereshko, Vikas Nanda, Steven Stayrook, William F. DeGrado
Article
Biochemistry & Molecular Biology
Tammer A. Farid, Goutham Kodali, Lee A. Solomon, Bruce R. Lichtenstein, Molly M. Sheehan, Bryan A. Fry, Chris Bialas, Nathan M. Ennist, Jessica A. Siedlecki, Zhenyu Zhao, Matthew A. Stetz, Kathleen G. Valentine, J. L. Ross Anderson, A. Joshua Wand, Bohdana M. Discher, Christopher C. Moser, P. Leslie Dutton
NATURE CHEMICAL BIOLOGY
(2013)
Article
Biochemistry & Molecular Biology
Joshua B. Sheetz, Sebastian Mathea, Hanna Karvonen, Ketan Malhotra, Deep Chatterjee, Wilhelmiina Niininen, Robert Perttila, Franziska Preuss, Krishna Suresh, Steven E. Stayrook, Yuko Tsutsui, Ravi Radhakrishnan, Daniela Ungureanu, Stefan Knapp, Mark A. Lemmon
Article
Multidisciplinary Sciences
Chun Hu, Carlos A. Leche, Anatoly Kiyatkin, Zhaolong Yu, Steven E. Stayrook, Kathryn M. Ferguson, Mark A. Lemmon
Summary: The epidermal growth factor receptor (EGFR) frequently mutates in human cancer, and is an important therapeutic target. However, EGFR inhibitors have limited effectiveness in glioblastoma multiforme (GBM) due to exclusive mutations in the extracellular region. This study reveals that GBM mutations impair EGFR's ability to distinguish between activating ligands, which may have implications for therapeutic targeting.
Article
Multidisciplinary Sciences
Tongqing Li, Steven E. Stayrook, Yuko Tsutsui, Jianan Zhang, Yueyue Wang, Hengyi Li, Andrew Proffitt, Stefan G. Krimmer, Mansoor Ahmed, Olivia Belliveau, Ian X. Walker, Krishna C. Mudumbi, Yoshihisa Suzuki, Irit Lax, Diego Alvarado, Mark A. Lemmon, Joseph Schlessinger, Daryl E. Klein
Summary: The proto-oncogene ALK encodes anaplastic lymphoma kinase, which is primarily expressed in the developing nervous system. Its activity is associated with learning and memory, energy expenditure, and obesity prevention. Aberrant ALK signaling causes various cancers, including being a driver in pediatric neuroblastoma. The study reveals the crystal structures of ALK's extracellular glycine-rich domain (GRD) and how it regulates receptor activity, providing insights into potential therapeutics for ALK-expressing cancers.
Article
Biochemistry & Molecular Biology
Nathan M. M. Ennist, Steven E. E. Stayrook, P. Leslie Dutton, Christopher C. C. Moser
Summary: New technologies that efficiently convert solar energy into fuel can help shift the world from fossil fuels to renewable energy. By designing new reaction centers, researchers are gaining a deeper understanding of photosynthetic charge separation, which may eventually lead to the production of biofuels with higher efficiency than natural photosystems. A recent study described the successful multi-step electron-transfer activity of a designed reaction center protein, demonstrating the potential for rational protein design in enhancing energy conversion. Crystal structures and spectroscopic assays confirmed the effectiveness of the design and suggested a path towards even higher thermodynamic efficiency.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Multidisciplinary Sciences
Iris K. van Alderwerelt van Rosenburgh, David M. Lu, Michael J. Grant, Steven E. Stayrook, Manali Phadke, Zenta Walther, Sarah B. Goldberg, Katerina Politi, Mark A. Lemmon, Kumar D. Ashtekar, Yuko Tsutsui
Summary: This study investigates the molecular basis for the varying response of non-small cell lung cancers driven by EGFR mutations to tyrosine kinase inhibitors. The researchers identify structural features that contribute to inhibitor sensitivity and propose a classification system for predicting clinical outcomes.
NATURE COMMUNICATIONS
(2022)
Article
Chemistry, Multidisciplinary
Indrek Kalvet, Mary Ortmayer, Jingming Zhao, Rebecca Crawshaw, Nathan M. Ennist, Colin Levy, Anindya Roy, Anthony P. Green, David Baker
Summary: In this study, a high-affinity heme-binding protein, dnHEM1, was designed with an axial histidine ligand, a vacant coordination site, and a tunable distal pocket. This protein was converted into a proficient peroxidase and enantiocomplementary carbene transferases by reconfiguring the distal pocket. This approach allows for the custom design of enzymes with a variety of shapes and functionalities.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
