17,072 results on '"Baker, David A."'
Search Results
2. Obliquities of Exoplanet Host Stars: 19 New and Updated Measurements, and Trends in the Sample of 205 Measurements
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Knudstrup, Emil, Albrecht, Simon H., Winn, Joshua N., Gandolfi, Davide, Zanazzi, John J., Persson, Carina M., Fridlund, Malcolm, Marcussen, Marcus L., Chontos, Ashley, Keniger, Marcelo A. F., Eisner, Nora L., Bieryla, Allyson, Isaacson, Howard, Howard, Andrew W., Hirsch, Lea A., Murgas, Felipe, Narita, Norio, Palle, Enric, Kawai, Yugo, and Baker, David
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Astrophysics - Earth and Planetary Astrophysics - Abstract
Measurements of the obliquities in exoplanet systems have revealed some remarkable architectures, some of which are very different from the Solar System. Nearly 200 obliquity measurements have been obtained through observations of the Rossiter-McLaughlin (RM) effect. Here we report on observations of 19 planetary systems that led to 17 clear detections of the RM effect and 2 less secure detections. After adding the new measurements to the tally, we use the entire collection of RM measurements to investigate four issues that have arisen in the literature. i) Does the obliquity distribution show a peak at approximately 90$^\circ$? We find tentative evidence that such a peak does exist when restricting attention to the sample of sub-Saturn planets and hot Jupiters orbiting F stars. ii) Are high obliquities associated with high eccentricities? We find the association to be weaker than previously reported, and that a stronger association exists between obliquity and orbital separation, possibly due to tidal obliquity damping at small separations. iii) How low are the lowest known obliquities? Among hot Jupiters around cool stars, we find the dispersion to be $1.4\pm0.7^\circ$, smaller than the 6$^\circ$ obliquity of the Sun, which serves as additional evidence for tidal damping. iv) What are the obliquities of stars with compact and flat systems of multiple planets? We find that they generally have obliquities lower than $10^\circ$, with several remarkable exceptions possibly caused by wide-orbiting stellar or planetary companions., Comment: 47 pages, 43 figures. Accepted for publication in A&A
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- 2024
3. De novo design of proteins housing excitonically coupled chlorophyll special pairs
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Ennist, Nathan M, Wang, Shunzhi, Kennedy, Madison A, Curti, Mariano, Sutherland, George A, Vasilev, Cvetelin, Redler, Rachel L, Maffeis, Valentin, Shareef, Saeed, Sica, Anthony V, Hua, Ash Sueh, Deshmukh, Arundhati P, Moyer, Adam P, Hicks, Derrick R, Swartz, Avi Z, Cacho, Ralph A, Novy, Nathan, Bera, Asim K, Kang, Alex, Sankaran, Banumathi, Johnson, Matthew P, Phadkule, Amala, Reppert, Mike, Ekiert, Damian, Bhabha, Gira, Stewart, Lance, Caram, Justin R, Stoddard, Barry L, Romero, Elisabet, Hunter, C Neil, and Baker, David
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Biological Sciences ,Chemical Sciences ,Physical Chemistry ,Biotechnology ,Affordable and Clean Energy ,Chlorophyll ,Crystallography ,X-Ray ,Models ,Molecular ,Photosynthesis ,Energy Transfer ,Cryoelectron Microscopy ,Protein Conformation ,Light-Harvesting Protein Complexes ,Medicinal and Biomolecular Chemistry ,Biochemistry and Cell Biology ,Biochemistry & Molecular Biology ,Biochemistry and cell biology ,Medicinal and biomolecular chemistry - Abstract
Natural photosystems couple light harvesting to charge separation using a 'special pair' of chlorophyll molecules that accepts excitation energy from the antenna and initiates an electron-transfer cascade. To investigate the photophysics of special pairs independently of the complexities of native photosynthetic proteins, and as a first step toward creating synthetic photosystems for new energy conversion technologies, we designed C2-symmetric proteins that hold two chlorophyll molecules in closely juxtaposed arrangements. X-ray crystallography confirmed that one designed protein binds two chlorophylls in the same orientation as native special pairs, whereas a second designed protein positions them in a previously unseen geometry. Spectroscopy revealed that the chlorophylls are excitonically coupled, and fluorescence lifetime imaging demonstrated energy transfer. The cryo-electron microscopy structure of a designed 24-chlorophyll octahedral nanocage with a special pair on each edge closely matched the design model. The results suggest that the de novo design of artificial photosynthetic systems is within reach of current computational methods.
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- 2024
4. Wide Binary Orbits are Preferentially Aligned with the Orbits of Small Planets, but Probably Not Hot Jupiters
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Christian, Sam, Vanderburg, Andrew, Becker, Juliette, Kraus, Adam L., Pearce, Logan, Collins, Karen A., Rice, Malena, Jensen, Eric L. N., Baker, David, Benni, Paul, Bieryla, Allyson, Binnenfeld, Abraham, Collins, Kevin I., Conti, Dennis M., Evans, Phil, Girardin, Eric, Gregorio, Joao, Mazeh, Tsevi, Murgas, Felipe, Panahi, Aviad, Pozuelos, Francisco J., Relles, Howard M., Frustaglia, Fabian Rodriguez, Schwarz, Richard P., Srdoc, Gregor, Stockdale, Chris, Tan, Thiam-Guan, Waalkes, William C., Wang, Gavin, Wittrock, Justin, and Zucker, Shay
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Astrophysics - Earth and Planetary Astrophysics ,Astrophysics - Solar and Stellar Astrophysics - Abstract
Studying the relative orientations of the orbits of exoplanets and wide-orbiting binary companions (semimajor axis greater than 100 AU) can shed light on how planets form and evolve in binary systems. Previous observations by multiple groups discovered a possible alignment between the orbits of visual binaries and the exoplanets that reside in them. In this study, using data from \textit{Gaia} DR3 and TESS, we confirm the existence of an alignment between the orbits of small planets $(R<6 R_\oplus)$ and binary systems with semimajor axes below 700 AU ($p=10^{-6}$). However, we find no statistical evidence for alignment between planet and binary orbits for binary semimajor axes greater than 700 AU, and no evidence for alignment of large, closely-orbiting planets (mostly hot Jupiters) and binaries at any separation. The lack of orbital alignment between our large planet sample and their binary companions appears significantly different from our small planet sample, even taking into account selection effects. Therefore, we conclude that any alignment between wide-binaries and our sample of large planets (predominantly hot Jupiters) is probably not as strong as what we observe for small planets in binaries with semimajor axes less than 700 AU. The difference in the alignment distribution of hot Jupiters and smaller planets may be attributed to the unique evolutionary mechanisms occuring in systems that form hot Jupiters, including potentially destabilizing secular resonances that onset as the protoplanetary disk dissipates and high-eccentricity migration occurring after the disk is gone., Comment: 16 pages, 10 figures, submitted to AJ. Email corresponding author for data files
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- 2024
5. De novo design of allosterically switchable protein assemblies
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Pillai, Arvind, Idris, Abbas, Philomin, Annika, Weidle, Connor, Skotheim, Rebecca, Leung, Philip J. Y., Broerman, Adam, Demakis, Cullen, Borst, Andrew J., Praetorius, Florian, and Baker, David
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- 2024
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6. Design of amyloidogenic peptide traps
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Sahtoe, Danny D., Andrzejewska, Ewa A., Han, Hannah L., Rennella, Enrico, Schneider, Matthias M., Meisl, Georg, Ahlrichs, Maggie, Decarreau, Justin, Nguyen, Hannah, Kang, Alex, Levine, Paul, Lamb, Mila, Li, Xinting, Bera, Asim K., Kay, Lewis E., Knowles, Tuomas P. J., and Baker, David
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- 2024
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7. De novo design of buttressed loops for sculpting protein functions
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Jiang, Hanlun, Jude, Kevin M., Wu, Kejia, Fallas, Jorge, Ueda, George, Brunette, T. J., Hicks, Derrick R., Pyles, Harley, Yang, Aerin, Carter, Lauren, Lamb, Mila, Li, Xinting, Levine, Paul M., Stewart, Lance, Garcia, K. Christopher, and Baker, David
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- 2024
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8. A Prototype Software Framework for Transferable Computational Health Economic Models and Its Early Application in Youth Mental Health
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Hamilton, Matthew P., Gao, Caroline, Wiesner, Glen, Filia, Kate M., Menssink, Jana M., Plencnerova, Petra, Baker, David G., McGorry, Patrick D., Parker, Alexandra, Karnon, Jonathan, Cotton, Sue M., and Mihalopoulos, Cathrine
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- 2024
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9. Condom Failure Among HIV-Negative Men in Serodiscordant Relationships in Australia, Brazil, and Thailand
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Gray, James, Prestage, Garrett, Jin, Fengyi, Phanuphak, Nittaya, Friedman, Ruth K., Fairley, Christopher K., Templeton, David J., Zablotska-Manos, Iryna, Hoy, Jennifer, Bloch, Mark, Baker, David, Brown, Graham, Grulich, Andrew, and Bavinton, Benjamin
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- 2024
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10. Computational design of soluble and functional membrane protein analogues
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Goverde, Casper A., Pacesa, Martin, Goldbach, Nicolas, Dornfeld, Lars J., Balbi, Petra E. M., Georgeon, Sandrine, Rosset, Stéphane, Kapoor, Srajan, Choudhury, Jagrity, Dauparas, Justas, Schellhaas, Christian, Kozlov, Simon, Baker, David, Ovchinnikov, Sergey, Vecchio, Alex J., and Correia, Bruno E.
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- 2024
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11. De novo design of pH-responsive self-assembling helical protein filaments
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Shen, Hao, Lynch, Eric M., Akkineni, Susrut, Watson, Joseph L., Decarreau, Justin, Bethel, Neville P., Benna, Issa, Sheffler, William, Farrell, Daniel, DiMaio, Frank, Derivery, Emmanuel, De Yoreo, James J., Kollman, Justin, and Baker, David
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- 2024
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12. Blueprinting extendable nanomaterials with standardized protein blocks
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Huddy, Timothy F, Hsia, Yang, Kibler, Ryan D, Xu, Jinwei, Bethel, Neville, Nagarajan, Deepesh, Redler, Rachel, Leung, Philip JY, Weidle, Connor, Courbet, Alexis, Yang, Erin C, Bera, Asim K, Coudray, Nicolas, Calise, S John, Davila-Hernandez, Fatima A, Han, Hannah L, Carr, Kenneth D, Li, Zhe, McHugh, Ryan, Reggiano, Gabriella, Kang, Alex, Sankaran, Banumathi, Dickinson, Miles S, Coventry, Brian, Brunette, TJ, Liu, Yulai, Dauparas, Justas, Borst, Andrew J, Ekiert, Damian, Kollman, Justin M, Bhabha, Gira, and Baker, David
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Biochemistry and Cell Biology ,Engineering ,Biological Sciences ,Generic health relevance ,Crystallography ,X-Ray ,Nanostructures ,Proteins ,Microscopy ,Electron ,Reproducibility of Results ,General Science & Technology - Abstract
A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures1. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight 'train track' assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence-structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to 'back of an envelope' architectural blueprints.
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- 2024
13. Rapid and automated design of two-component protein nanomaterials using ProteinMPNN
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de Haas, Robbert J, Brunette, Natalie, Goodson, Alex, Dauparas, Justas, Yi, Sue Y, Yang, Erin C, Dowling, Quinton, Nguyen, Hannah, Kang, Alex, Bera, Asim K, Sankaran, Banumathi, de Vries, Renko, Baker, David, and King, Neil P
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Biochemistry and Cell Biology ,Biological Sciences ,Bioengineering ,Biotechnology ,Generic health relevance ,Models ,Molecular ,Proteins ,Amino Acid Sequence ,Nanostructures ,Protein Conformation ,ProteinMPNN ,nanomaterials ,protein design - Abstract
The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.
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- 2024
14. De novo design of high-affinity binders of bioactive helical peptides.
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Vázquez Torres, Susana, Leung, Philip, Venkatesh, Preetham, Lutz, Isaac, Hink, Fabian, Huynh, Huu-Hien, Becker, Jessica, Yeh, Andy, Juergens, David, Bennett, Nathaniel, Hoofnagle, Andrew, Huang, Eric, MacCoss, Michael, Expòsit, Marc, Lee, Gyu, Bera, Asim, Kang, Alex, De La Cruz, Joshmyn, Levine, Paul, Li, Xinting, Lamb, Mila, Gerben, Stacey, Murray, Analisa, Heine, Piper, Korkmaz, Elif, Nivala, Jeff, Stewart, Lance, Watson, Joseph, Rogers, Joseph, and Baker, David
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Biosensing Techniques ,Computer-Aided Design ,Deep Learning ,Diffusion ,Glucagon ,Luminescent Measurements ,Mass Spectrometry ,Parathyroid Hormone ,Peptides ,Protein Structure ,Secondary ,Proteins ,Substrate Specificity ,Models ,Molecular - Abstract
Many peptide hormones form an α-helix on binding their receptors1-4, and sensitive methods for their detection could contribute to better clinical management of disease5. De novo protein design can now generate binders with high affinity and specificity to structured proteins6,7. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion8 to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.
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- 2024
15. Improving Protein Expression, Stability, and Function with ProteinMPNN
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Sumida, Kiera H, Núñez-Franco, Reyes, Kalvet, Indrek, Pellock, Samuel J, Wicky, Basile IM, Milles, Lukas F, Dauparas, Justas, Wang, Jue, Kipnis, Yakov, Jameson, Noel, Kang, Alex, De La Cruz, Joshmyn, Sankaran, Banumathi, Bera, Asim K, Jiménez-Osés, Gonzalo, and Baker, David
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Engineering ,Chemical Sciences ,Temperature ,Endopeptidases ,Recombinant Fusion Proteins ,General Chemistry ,Chemical sciences - Abstract
Natural proteins are highly optimized for function but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here, we show that the deep neural network ProteinMPNN, together with evolutionary and structural information, provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins.
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- 2024
16. A prototype software framework for transferable computational health economic models and its early application in youth mental health
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Hamilton, Matthew P, Gao, Caroline X, Wiesner, Glen, Filia, Kate M, Menssink, Jana M, Plencnerova, Petra, Baker, David G, McGorry, Patrick D, Parker, Alexandra, Karnon, Jonathan, Cotton, Sue M, and Mihalopoulos, Cathrine
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Economics - General Economics ,J.4 - Abstract
We are developing an economic model to explore multiple topics in Australian youth mental health policy. We want that model to be readily transferable to other jurisdictions. We developed a software framework for authoring transparent, reusable and updatable Computational Health Economic Models (CHEMs) (the software files that implement health economic models). We specified framework user requirements of a template CHEM module that facilitates modular model implementations, a simple programming syntax and tools for authoring new CHEM modules, supplying CHEMs with data, reporting reproducible CHEM analyses, searching for CHEM modules and maintaining a CHEM project website. We implemented the framework as six development version code libraries in the programming language R that integrate with online services for software development and research data archiving. We used the framework to author five development version R libraries of CHEM modules focused on utility mapping in youth mental health. These modules provide tools for variable validation, dataset description, multi-attribute instrument scoring, construction of mapping models, reporting of mapping studies and making out of sample predictions. We assessed these CHEM module libraries as mostly meeting transparency, reusability and updatability criteria that we have previously developed, but requiring more detailed documentation and unit testing of individual modules. Our software framework has potential value as a prototype for future tools to support the development of transferable CHEMs., Comment: 16 pages, 3 tables, 1 figure
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- 2023
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17. Effective strategies for correcting spatial sampling bias in species distribution models without independent test data
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Baker, David J., Maclean, Ilya M. D., and Gaston, Kevin J.
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- 2024
18. Cardiac point-of-care ultrasound: Practical integration in the pediatric and neonatal intensive care settings
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Conlon, Thomas W., Baker, David, and Bhombal, Shazia
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- 2024
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19. Identification of the Top TESS Objects of Interest for Atmospheric Characterization of Transiting Exoplanets with JWST
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Hord, Benjamin J., Kempton, Eliza M. -R., Mikal-Evans, Thomas, Latham, David W., Ciardi, David R., Dragomir, Diana, Colón, Knicole D., Ross, Gabrielle, Vanderburg, Andrew, de Beurs, Zoe L., Collins, Karen A., Watkins, Cristilyn N., Bean, Jacob, Cowan, Nicolas B., Daylan, Tansu, Morley, Caroline V., Ih, Jegug, Baker, David, Barkaoui, Khalid, Batalha, Natalie M., Behmard, Aida, Belinski, Alexander, Benkhaldoun, Zouhair, Benni, Paul, Bernacki, Krzysztof, Bieryla, Allyson, Binnenfeld, Avraham, Bosch-Cabot, Pau, Bouchy, François, Bozza, Valerio, Brahm, Rafael, Buchhave, Lars A., Calkins, Michael, Chontos, Ashley, Clark, Catherine A., Cloutier, Ryan, Cointepas, Marion, Collins, Kevin I., Conti, Dennis M., Crossfield, Ian J. M., Dai, Fei, de Leon, Jerome P., Dransfield, Georgina, Dressing, Courtney, Dustor, Adam, Esquerdo, Gilbert, Evans, Phil, Fajardo-Acosta, Sergio B., Fiołka, Jerzy, Forés-Toribio, Raquel, Frasca, Antonio, Fukui, Akihiko, Fulton, Benjamin, Furlan, Elise, Gan, Tianjun, Gandolfi, Davide, Ghachoui, Mourad, Giacalone, Steven, Gilbert, Emily A., Gillon, Michaël, Girardin, Eric, Gonzales, Erica, Horta, Ferran Grau, Gregorio, Joao, Greklek-McKeon, Michael, Guerra, Pere, Hartman, J. D., Hellier, Coel, Hełminiak, Krzysztof G., Henning, Thomas, Hill, Michelle L., Horne, Keith, Howard, Andrew W., Howell, Steve B., Huber, Daniel, Isaacson, Howard, Isopi, Giovanni, Jehin, Emmanuel, Jenkins, Jon M., Jensen, Eric L. N., Johnson, Marshall C., Jordán, Andrés, Kane, Stephen R., Kielkopf, John F., Krushinsky, Vadim, Lasota, Sławomir, Lee, Elena, Lewin, Pablo, Livingston, John H., Lubin, Jack, Lund, Michael B., Mallia, Franco, Mann, Christopher R., Marino, Giuseppe, Maslennikova, Nataliia, Massey, Bob, Matson, Rachel, Matthews, Elisabeth, Mayo, Andrew W., Mazeh, Tsevi, McLeod, Kim K., Michaels, Edward J., Močnik, Teo, Mori, Mayuko, Mraz, Georgia, Muñoz, Jose A., Narita, Norio, Nielsen, Louise Dyregaard, Osborn, Hugh, Palle, Enric, Panahi, Aviad, Papini, Riccardo, Polanski, Alex S., Popowicz, Adam, Pozuelos, Francisco J., Quinn, Samuel N., Radford, Don J., Reed, Phillip A., Relles, Howard M., Rice, Malena, Robertson, Paul, Rodriguez, Joseph E., Rosenthal, Lee J., Rubenzahl, Ryan A., Schanche, Nicole, Schlieder, Joshua, Schwarz, Richard P., Sefako, Ramotholo, Shporer, Avi, Sozzetti, Alessandro, Srdoc, Gregor, Stockdale, Chris, Tarasenkov, Alexander, Tan, Thiam-Guan, Timmermans, Mathilde, Ting, Eric B., Van Zandt, Judah, Vignes, JP, Waite, Ian, Watanabe, Noriharu, Weiss, Lauren M., Wittrock, Justin, Zhou, George, Ziegler, Carl, and Zucker, Shay
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Astrophysics - Earth and Planetary Astrophysics - Abstract
JWST has ushered in an era of unprecedented ability to characterize exoplanetary atmospheres. While there are over 5,000 confirmed planets, more than 4,000 TESS planet candidates are still unconfirmed and many of the best planets for atmospheric characterization may remain to be identified. We present a sample of TESS planets and planet candidates that we identify as "best-in-class" for transmission and emission spectroscopy with JWST. These targets are sorted into bins across equilibrium temperature $T_{\mathrm{eq}}$ and planetary radius $R{_\mathrm{p}}$ and are ranked by transmission and emission spectroscopy metric (TSM and ESM, respectively) within each bin. In forming our target sample, we perform cuts for expected signal size and stellar brightness, to remove sub-optimal targets for JWST. Of the 194 targets in the resulting sample, 103 are unconfirmed TESS planet candidates, also known as TESS Objects of Interest (TOIs). We perform vetting and statistical validation analyses on these 103 targets to determine which are likely planets and which are likely false positives, incorporating ground-based follow-up from the TESS Follow-up Observation Program (TFOP) to aid the vetting and validation process. We statistically validate 23 TOIs, marginally validate 33 TOIs to varying levels of confidence, deem 29 TOIs likely false positives, and leave the dispositions for 4 TOIs as inconclusive. 14 of the 103 TOIs were confirmed independently over the course of our analysis. We provide our final best-in-class sample as a community resource for future JWST proposals and observations. We intend for this work to motivate formal confirmation and mass measurements of each validated planet and encourage more detailed analysis of individual targets by the community., Comment: Submitted to AJ. Machine-readable versions of Tables 2 and 3 are included. 40 pages, 7 figures, 3 tables
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- 2023
20. Precisely patterned nanofibres made from extendable protein multiplexes
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Bethel, Neville P, Borst, Andrew J, Parmeggiani, Fabio, Bick, Matthew J, Brunette, TJ, Nguyen, Hannah, Kang, Alex, Bera, Asim K, Carter, Lauren, Miranda, Marcos C, Kibler, Ryan D, Lamb, Mila, Li, Xinting, Sankaran, Banumathi, and Baker, David
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Chemical Sciences ,Nanofibers ,Models ,Molecular ,Protein Conformation ,alpha-Helical ,Protein Subunits ,Organic Chemistry ,Chemical sciences - Abstract
Molecular systems with coincident cyclic and superhelical symmetry axes have considerable advantages for materials design as they can be readily lengthened or shortened by changing the length of the constituent monomers. Among proteins, alpha-helical coiled coils have such symmetric, extendable architectures, but are limited by the relatively fixed geometry and flexibility of the helical protomers. Here we describe a systematic approach to generating modular and rigid repeat protein oligomers with coincident C2 to C8 and superhelical symmetry axes that can be readily extended by repeat propagation. From these building blocks, we demonstrate that a wide range of unbounded fibres can be systematically designed by introducing hydrophilic surface patches that force staggering of the monomers; the geometry of such fibres can be precisely tuned by varying the number of repeat units in the monomer and the placement of the hydrophilic patches.
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- 2023
21. De novo design of monomeric helical bundles for pH‐controlled membrane lysis
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Goldbach, Nicolas, Benna, Issa, Wicky, Basile IM, Croft, Jacob T, Carter, Lauren, Bera, Asim K, Nguyen, Hannah, Kang, Alex, Sankaran, Banumathi, Yang, Erin C, Lee, Kelly K, and Baker, David
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Biochemistry and Cell Biology ,Biological Sciences ,Bioengineering ,Generic health relevance ,Histidine ,Liposomes ,Protein Structure ,Secondary ,Hydrogen-Ion Concentration ,coiled-coil ,endosomal escape ,membrane disruption ,pH responsive ,protein design ,Computation Theory and Mathematics ,Other Information and Computing Sciences ,Biophysics ,Biochemistry and cell biology ,Medicinal and biomolecular chemistry - Abstract
Targeted intracellular delivery via receptor-mediated endocytosis requires the delivered cargo to escape the endosome to prevent lysosomal degradation. This can in principle be achieved by membrane lysis tightly restricted to endosomal membranes upon internalization to avoid general membrane insertion and lysis. Here, we describe the design of small monomeric proteins with buried histidine containing pH-responsive hydrogen bond networks and membrane permeating amphipathic helices. Of the 30 designs that were experimentally tested, all expressed in Escherichia coli, 13 were monomeric with the expected secondary structure, and 4 designs disrupted artificial liposomes in a pH-dependent manner. Mutational analysis showed that the buried histidine hydrogen bond networks mediate pH-responsiveness and control lysis of model membranes within a very narrow range of pH (6.0-5.5) with almost no lysis occurring at neutral pH. These tightly controlled lytic monomers could help mediate endosomal escape in designed targeted delivery platforms.
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- 2023
22. Unraveling the functional dark matter through global metagenomics.
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Baltoumas, Fotis, Liu, Sirui, Selvitopi, Oguz, Camargo, Antonio, Nayfach, Stephen, Azad, Ariful, Roux, Simon, Call, Lee, Chen, I, Paez-Espino, David, Karatzas, Evangelos, Iliopoulos, Ioannis, Konstantinidis, Konstantinos, Tiedje, James, Pett-Ridge, Jennifer, Baker, David, Ouzounis, Christos, Ovchinnikov, Sergey, Buluç, Aydin, Ivanova, Natalia, Kyrpides, Nikos, Visel, Axel, and Pavlopoulos, Georgios
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Cluster Analysis ,Metagenome ,Metagenomics ,Proteins ,Databases ,Protein ,Protein Conformation ,Microbiology - Abstract
Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities1,2. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyse 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database3. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical and gene neighbourhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter.
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- 2023
23. 8 Lunar Impact Features and Processes
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Osinski, Gordon R., primary, Melosh, H. Jay, additional, Andrews-Hanna, Jeff, additional, Baker, David, additional, Denevi, Brett, additional, Dhingra, Deepak, additional, Ghent, Rebecca, additional, Hayne, Paul O., additional, Hill, Patrick, additional, James, Peter B., additional, Jaret, Steven, additional, Johnson, Brandon, additional, Kenkmann, Thomas, additional, Kring, David, additional, Mahanti, Prasun, additional, Minton, David, additional, Neish, Catherine D., additional, Neumann, Greg, additional, Plescia, Jeff, additional, Potter, Ross W. K., additional, Richardson, Jim, additional, Silber, Elizabeth A., additional, Soderblom, Jason M., additional, Zanetti, Michael, additional, and Zellner, Nicolle, additional
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- 2024
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24. Design of cell-type-specific hyperstable IL-4 mimetics via modular de novo scaffolds.
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Yang, Huilin, Ulge, Umut, Quijano-Rubio, Alfredo, Bernstein, Zachary, Maestas, David, Chun, Jung-Ho, Wang, Wentao, Lin, Jian-Xin, Jude, Kevin, Singh, Srujan, Orcutt-Jahns, Brian, Li, Peng, Mou, Jody, Chung, Liam, Kuo, Yun-Huai, Ali, Yasmin, Meyer, Aaron, Grayson, Warren, Heller, Nicola, Garcia, K, Leonard, Warren, Silva, Daniel-Adriano, Elisseeff, Jennifer, Baker, David, and Spangler, Jamie
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Animals ,Interleukin-4 ,Cytokines ,Signal Transduction - Abstract
The interleukin-4 (IL-4) cytokine plays a critical role in modulating immune homeostasis. Although there is great interest in harnessing this cytokine as a therapeutic in natural or engineered formats, the clinical potential of native IL-4 is limited by its instability and pleiotropic actions. Here, we design IL-4 cytokine mimetics (denoted Neo-4) based on a de novo engineered IL-2 mimetic scaffold and demonstrate that these cytokines can recapitulate physiological functions of IL-4 in cellular and animal models. In contrast with natural IL-4, Neo-4 is hyperstable and signals exclusively through the type I IL-4 receptor complex, providing previously inaccessible insights into differential IL-4 signaling through type I versus type II receptors. Because of their hyperstability, our computationally designed mimetics can directly incorporate into sophisticated biomaterials that require heat processing, such as three-dimensional-printed scaffolds. Neo-4 should be broadly useful for interrogating IL-4 biology, and the design workflow will inform targeted cytokine therapeutic development.
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- 2023
25. ModelCIF: An Extension of PDBx/mmCIF Data Representation for Computed Structure Models
- Author
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Vallat, Brinda, Tauriello, Gerardo, Bienert, Stefan, Haas, Juergen, Webb, Benjamin M, Žídek, Augustin, Zheng, Wei, Peisach, Ezra, Piehl, Dennis W, Anischanka, Ivan, Sillitoe, Ian, Tolchard, James, Varadi, Mihaly, Baker, David, Orengo, Christine, Zhang, Yang, Hoch, Jeffrey C, Kurisu, Genji, Patwardhan, Ardan, Velankar, Sameer, Burley, Stephen K, Sali, Andrej, Schwede, Torsten, Berman, Helen M, and Westbrook, John D
- Subjects
Biological Sciences ,Bioinformatics and Computational Biology ,Networking and Information Technology R&D (NITRD) ,Bioengineering ,Underpinning research ,1.4 Methodologies and measurements ,Generic health relevance ,Databases ,Protein ,Macromolecular Substances ,Protein Conformation ,Software ,ModelCIF ,PDBx/mmCIF ,Data Standard ,Computed Structure Models ,Protein Structure Prediction ,Medicinal and Biomolecular Chemistry ,Biochemistry and Cell Biology ,Microbiology ,Biochemistry & Molecular Biology ,Biochemistry and cell biology - Abstract
ModelCIF (github.com/ihmwg/ModelCIF) is a data information framework developed for and by computational structural biologists to enable delivery of Findable, Accessible, Interoperable, and Reusable (FAIR) data to users worldwide. ModelCIF describes the specific set of attributes and metadata associated with macromolecular structures modeled by solely computational methods and provides an extensible data representation for deposition, archiving, and public dissemination of predicted three-dimensional (3D) models of macromolecules. It is an extension of the Protein Data Bank Exchange / macromolecular Crystallographic Information Framework (PDBx/mmCIF), which is the global data standard for representing experimentally-determined 3D structures of macromolecules and associated metadata. The PDBx/mmCIF framework and its extensions (e.g., ModelCIF) are managed by the Worldwide Protein Data Bank partnership (wwPDB, wwpdb.org) in collaboration with relevant community stakeholders such as the wwPDB ModelCIF Working Group (wwpdb.org/task/modelcif). This semantically rich and extensible data framework for representing computed structure models (CSMs) accelerates the pace of scientific discovery. Herein, we describe the architecture, contents, and governance of ModelCIF, and tools and processes for maintaining and extending the data standard. Community tools and software libraries that support ModelCIF are also described.
- Published
- 2023
26. Theoretische Zugänge zur Bildungsrevolution in der post-industriellen Gesellschaft: Mythen, Fakten und die Akademisierung der Berufsrollen
- Author
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Baker, David P., Zentrum für Schul- und Bildungsforschung (ZSB) der Martin-Luther-Universität Halle-Wittenberg, Mitterle, Alexander, editor, Matthies, Annemarie, editor, Maiwald, Annett, editor, and Schubert, Christoph, editor
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- 2024
- Full Text
- View/download PDF
27. De novo design of miniprotein antagonists of cytokine storm inducers
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Huang, Buwei, Coventry, Brian, Borowska, Marta T., Arhontoulis, Dimitrios C., Exposit, Marc, Abedi, Mohamad, Jude, Kevin M., Halabiya, Samer F., Allen, Aza, Cordray, Cami, Goreshnik, Inna, Ahlrichs, Maggie, Chan, Sidney, Tunggal, Hillary, DeWitt, Michelle, Hyams, Nathaniel, Carter, Lauren, Stewart, Lance, Fuller, Deborah H., Mei, Ying, Garcia, K. Christopher, and Baker, David
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- 2024
- Full Text
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28. Enhancing extracellular vesicle cargo loading and functional delivery by engineering protein-lipid interactions
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Peruzzi, Justin A., Gunnels, Taylor F., Edelstein, Hailey I., Lu, Peilong, Baker, David, Leonard, Joshua N., and Kamat, Neha P.
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- 2024
- Full Text
- View/download PDF
29. Engaging a community to focus on upper limb function in people with multiple sclerosis: the ThinkHand campaign case study
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Thomson, Alison, Horne, Rachel, Chapman, Christine, Bharadia, Trishna, Burke, Patrick, Colwell, Elizabeth, Harrington, Mark, Boskovic, Bonnie, Stennett, Andrea, Baker, David, Giovannoni, Gavin, and Schmierer, Klaus
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- 2024
- Full Text
- View/download PDF
30. Hydrophobic mismatch drives self-organization of designer proteins into synthetic membranes
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Peruzzi, Justin A., Steinkühler, Jan, Vu, Timothy Q., Gunnels, Taylor F., Hu, Vivian T., Lu, Peilong, Baker, David, and Kamat, Neha P.
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- 2024
- Full Text
- View/download PDF
31. Machine learning-guided engineering of genetically encoded fluorescent calcium indicators
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Wait, Sarah J., Expòsit, Marc, Lin, Sophia, Rappleye, Michael, Lee, Justin Daho, Colby, Samuel A., Torp, Lily, Asencio, Anthony, Smith, Annette, Regnier, Michael, Moussavi-Harami, Farid, Baker, David, Kim, Christina K., and Berndt, Andre
- Published
- 2024
- Full Text
- View/download PDF
32. Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA
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Baek, Minkyung, McHugh, Ryan, Anishchenko, Ivan, Jiang, Hanlun, Baker, David, and DiMaio, Frank
- Published
- 2024
- Full Text
- View/download PDF
33. A family of process-based models to simulate landscape use by multiple taxa
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Gardner, Emma, Robinson, Robert A., Julian, Angela, Boughey, Katherine, Langham, Steve, Tse-Leon, Jenny, Petrovskii, Sergei, Baker, David J., Bellamy, Chloe, Buxton, Andrew, Franks, Samantha, Monk, Chris, Morris, Nicola, Park, Kirsty J., Petrovan, Silviu, Pitt, Katie, Taylor, Rachel, Turner, Rebecca K., Allain, Steven J. R., Bradley, Val, Broughton, Richard K., Cartwright, Mandy, Clarke, Kevin, Cranfield, Jon, Fuentes-Montemayor, Elisa, Gandola, Robert, Gent, Tony, Hinsley, Shelley A., Madsen, Thomas, Reading, Chris, Redhead, John W., Reveley, Sonia, Wilkinson, John, Williams, Carol, Woodward, Ian, Baker, John, Briggs, Philip, Dyason, Sheila, Langton, Steve, Mawby, Ashlea, Pywell, Richard F., and Bullock, James M.
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- 2024
- Full Text
- View/download PDF
34. The Future of Libraries, Librarianship, and Information Services
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Baker, David, primary
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- 2024
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35. Music Libraries
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Baker, David, primary
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- 2024
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36. Types of Libraries
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Baker, David, primary
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- 2024
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37. Hybrid Libraries
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Baker, David, primary
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- 2024
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38. Education: The Great Equalizer, Social Reproducer, or Legitimator of New Forms of Social Stratification?
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Baker, David P., primary, Schaub, Maryellen, additional, Choi, Junghee, additional, and Ford, Karly, additional
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- 2024
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39. New York Public Library
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Baker, David, primary
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- 2024
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40. Consultancy and Information Businesses
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Baker, David, primary
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- 2024
- Full Text
- View/download PDF
41. Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains
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Wang, Jing Yang, Khmelinskaia, Alena, Sheffler, William, Miranda, Marcos C, Antanasijevic, Aleksandar, Borst, Andrew J, Torres, Susana V, Shu, Chelsea, Hsia, Yang, Nattermann, Una, Ellis, Daniel, Walkey, Carl, Ahlrichs, Maggie, Chan, Sidney, Kang, Alex, Nguyen, Hannah, Sydeman, Claire, Sankaran, Banumathi, Wu, Mengyu, Bera, Asim K, Carter, Lauren, Fiala, Brooke, Murphy, Michael, Baker, David, Ward, Andrew B, and King, Neil P
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Medical Biotechnology ,Biological Sciences ,Biomedical and Clinical Sciences ,Bioengineering ,Vaccine Related ,Biotechnology ,Nanotechnology ,Generic health relevance ,Proteins ,Nanoparticles ,Vaccines ,biochemistry ,protein design ,nanoparticles - Abstract
Computationally designed protein nanoparticles have recently emerged as a promising platform for the development of new vaccines and biologics. For many applications, secretion of designed nanoparticles from eukaryotic cells would be advantageous, but in practice, they often secrete poorly. Here we show that designed hydrophobic interfaces that drive nanoparticle assembly are often predicted to form cryptic transmembrane domains, suggesting that interaction with the membrane insertion machinery could limit efficient secretion. We develop a general computational protocol, the Degreaser, to design away cryptic transmembrane domains without sacrificing protein stability. The retroactive application of the Degreaser to previously designed nanoparticle components and nanoparticles considerably improves secretion, and modular integration of the Degreaser into design pipelines results in new nanoparticles that secrete as robustly as naturally occurring protein assemblies. Both the Degreaser protocol and the nanoparticles we describe may be broadly useful in biotechnological applications.
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- 2023
42. The ϕPA3 phage nucleus is enclosed by a self-assembling 2D crystalline lattice.
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Nieweglowska, Eliza S, Brilot, Axel F, Méndez-Moran, Melissa, Kokontis, Claire, Baek, Minkyung, Li, Junrui, Cheng, Yifan, Baker, David, Bondy-Denomy, Joseph, and Agard, David A
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Bacteriophages ,Viral Proteins ,CRISPR-Cas Systems ,1.1 Normal biological development and functioning ,Underpinning research - Abstract
To protect themselves from host attack, numerous jumbo bacteriophages establish a phage nucleus-a micron-scale, proteinaceous structure encompassing the replicating phage DNA. Bacteriophage and host proteins associated with replication and transcription are concentrated inside the phage nucleus while other phage and host proteins are excluded, including CRISPR-Cas and restriction endonuclease host defense systems. Here, we show that nucleus fragments isolated from ϕPA3 infected Pseudomonas aeruginosa form a 2-dimensional lattice, having p2 or p4 symmetry. We further demonstrate that recombinantly purified primary Phage Nuclear Enclosure (PhuN) protein spontaneously assembles into similar 2D sheets with p2 and p4 symmetry. We resolve the dominant p2 symmetric state to 3.9 Å by cryo-EM. Our structure reveals a two-domain core, organized into quasi-symmetric tetramers. Flexible loops and termini mediate adaptable inter-tetramer contacts that drive subunit assembly into a lattice and enable the adoption of different symmetric states. While the interfaces between subunits are mostly well packed, two are open, forming channels that likely have functional implications for the transport of proteins, mRNA, and small molecules.
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- 2023
43. De novo design of luciferases using deep learning.
- Author
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Yeh, Andy Hsien-Wei, Norn, Christoffer, Kipnis, Yakov, Tischer, Doug, Pellock, Samuel J, Evans, Declan, Ma, Pengchen, Lee, Gyu Rie, Zhang, Jason Z, Anishchenko, Ivan, Coventry, Brian, Cao, Longxing, Dauparas, Justas, Halabiya, Samer, DeWitt, Michelle, Carter, Lauren, Houk, KN, and Baker, David
- Subjects
Luciferases ,Enzyme Stability ,Catalytic Domain ,Substrate Specificity ,Oxidation-Reduction ,Luminescence ,Hot Temperature ,Biocatalysis ,Deep Learning ,Luciferins ,Biotechnology ,Generic health relevance ,General Science & Technology - Abstract
De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds1,2, but has been limited by a lack of suitable protein structures and the complexity of native protein sequence-structure relationships. Here we describe a deep-learning-based 'family-wide hallucination' approach that generates large numbers of idealized protein structures containing diverse pocket shapes and designed sequences that encode them. We use these scaffolds to design artificial luciferases that selectively catalyse the oxidative chemiluminescence of the synthetic luciferin substrates diphenylterazine3 and 2-deoxycoelenterazine. The designed active sites position an arginine guanidinium group adjacent to an anion that develops during the reaction in a binding pocket with high shape complementarity. For both luciferin substrates, we obtain designed luciferases with high selectivity; the most active of these is a small (13.9 kDa) and thermostable (with a melting temperature higher than 95 °C) enzyme that has a catalytic efficiency on diphenylterazine (kcat/Km = 106 M-1 s-1) comparable to that of native luciferases, but a much higher substrate specificity. The creation of highly active and specific biocatalysts from scratch with broad applications in biomedicine is a key milestone for computational enzyme design, and our approach should enable generation of a wide range of luciferases and other enzymes.
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- 2023
44. Accurate computational design of three-dimensional protein crystals
- Author
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Li, Zhe, Wang, Shunzhi, Nattermann, Una, Bera, Asim K., Borst, Andrew J., Yaman, Muammer Y., Bick, Matthew J., Yang, Erin C., Sheffler, William, Lee, Byeongdu, Seifert, Soenke, Hura, Greg L., Nguyen, Hannah, Kang, Alex, Dalal, Radhika, Lubner, Joshua M., Hsia, Yang, Haddox, Hugh, Courbet, Alexis, Dowling, Quinton, Miranda, Marcos, Favor, Andrew, Etemadi, Ali, Edman, Natasha I., Yang, Wei, Weidle, Connor, Sankaran, Banumathi, Negahdari, Babak, Ross, Michael B., Ginger, David S., and Baker, David
- Published
- 2023
- Full Text
- View/download PDF
45. Hallucination of closed repeat proteins containing central pockets
- Author
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An, Linna, Hicks, Derrick R., Zorine, Dmitri, Dauparas, Justas, Wicky, Basile I. M., Milles, Lukas F., Courbet, Alexis, Bera, Asim K., Nguyen, Hannah, Kang, Alex, Carter, Lauren, and Baker, David
- Published
- 2023
- Full Text
- View/download PDF
46. Unraveling the functional dark matter through global metagenomics
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Pavlopoulos, Georgios A., Baltoumas, Fotis A., Liu, Sirui, Selvitopi, Oguz, Camargo, Antonio Pedro, Nayfach, Stephen, Azad, Ariful, Roux, Simon, Call, Lee, Ivanova, Natalia N., Chen, I. Min, Paez-Espino, David, Karatzas, Evangelos, Iliopoulos, Ioannis, Konstantinidis, Konstantinos, Tiedje, James M., Pett-Ridge, Jennifer, Baker, David, Visel, Axel, Ouzounis, Christos A., Ovchinnikov, Sergey, Buluç, Aydin, and Kyrpides, Nikos C.
- Published
- 2023
- Full Text
- View/download PDF
47. Faculty Perceptions of Teaching Online during the COVID-19 University Transition of Courses to an Online Format
- Author
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Sims, Shantia Kerr and Baker, David M.
- Abstract
As a result of the 2019 coronavirus disease pandemic, many universities were required to make quick decisions to accommodate social-distancing guidelines. Cherished university events such as commencement and spring convocations were postponed or canceled. Such decisions were made in an effort to curb the number of people infected with the virus. Institutions were also forced to consider how to continue educating students in the midst of a pandemic. In many instances, faculty were required to transition their face-to-face courses to an online format. Some instructors were familiar with the instructional strategies and technological tools needed for effective online teaching, whereas other, novice faculty were hesitant or even resistant to the idea of online teaching and learning. This case study at a Midwestern master's level university examines the perceptions of faculty (N = 183) regarding the quick transition of their courses to an online medium during the spring 2020 semester. We administered a web-based survey instrument consisting of two sections. Section I had 20 demographic questions and Section II had 28 statements rated on a 7-point Likert-type scale ranging from 1 ("strongly disagree") to 7 ("strongly agree"). Section II assessed perceptions and attitudes about the quick transition to online, perceptions of students' engagement in the courses before and after the transition, and professors' level of satisfaction with the transition. The data were analyzed using frequency, mean, and analysis of covariance. Findings reveal that generally faculty felt that course quality remained the same, that students' engagement and performance declined during the pandemic, and that satisfaction levels with the transition were low.
- Published
- 2021
48. An Examination of the Factors Leading to Students' Preference and Satisfaction with Online Courses
- Author
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Baker, David Mc. A., Unni, Ramaprasad, Kerr-Sims, Shantia, and Marquis, Gerald
- Abstract
This paper presents the results of a one-year study of undergraduate business students' preference and level of satisfaction with online instruction at one university. A questionnaire was voluntarily completed by 305 undergraduate business students during the 2019-2020 academic year. Multiple regression analysis revealed that prior experience with online courses, ease of communication, personal benefits--convenience of taking online courses and expectation of improving GPA were positively associated with satisfaction in online courses relative to face-to-face courses. Learning benefits from online courses such as availability of course materials did not have a significant relationship. Satisfaction was positively related to preference for online courses. Demographic factors such as age and gender had no significant effect on satisfaction with online courses.
- Published
- 2021
49. Twilight Sleep
- Author
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Baker, David
- Published
- 2023
- Full Text
- View/download PDF
50. Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem
- Author
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Trippe, Brian L., Yim, Jason, Tischer, Doug, Baker, David, Broderick, Tamara, Barzilay, Regina, and Jaakkola, Tommi
- Subjects
Quantitative Biology - Biomolecules ,Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
Construction of a scaffold structure that supports a desired motif, conferring protein function, shows promise for the design of vaccines and enzymes. But a general solution to this motif-scaffolding problem remains open. Current machine-learning techniques for scaffold design are either limited to unrealistically small scaffolds (up to length 20) or struggle to produce multiple diverse scaffolds. We propose to learn a distribution over diverse and longer protein backbone structures via an E(3)-equivariant graph neural network. We develop SMCDiff to efficiently sample scaffolds from this distribution conditioned on a given motif; our algorithm is the first to theoretically guarantee conditional samples from a diffusion model in the large-compute limit. We evaluate our designed backbones by how well they align with AlphaFold2-predicted structures. We show that our method can (1) sample scaffolds up to 80 residues and (2) achieve structurally diverse scaffolds for a fixed motif., Comment: Appearing in ICLR 2023. Code available: github.com/blt2114/ProtDiff_SMCDiff
- Published
- 2022
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