{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T04:18:53Z","timestamp":1784175533840,"version":"3.55.0"},"reference-count":78,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T00:00:00Z","timestamp":1767916800000},"content-version":"vor","delay-in-days":8,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>We propose a simple and practical machine learning-based desktop solution for analyzing biologically relevant protein motions. We termed our technology reinforced molecular dynamics (rMD) combining MD trajectory data and free-energy (FE) map data to train a dual loss function autoencoder network that can explore conformational space retroactively with no need for additional simulations. The key insight of rMD is that it replaces the latent space with an FE map for structure prediction, thus infusing the autoencoder network with physical context. The FE map is computed from a biased MD simulation over a low-dimensional collective variable (CV) space that captures some biological function. In the proposed rMD framework, the FE map can then be used directly to generate more protein structures in poorly sampled regions or to follow alternative paths in CV space to explore multiple conformational transitions. The rMD technology is entirely self-contained, does not rely on any pretrained model, and can be run on a GPU desktop computer. We present our rMD computations in a key area of molecular-glue degraders aimed at a deeper understanding of the structural transition from open to closed conformations of CRBN.<\/jats:p>","DOI":"10.1093\/pnasnexus\/pgaf408","type":"journal-article","created":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T16:33:51Z","timestamp":1767976431000},"source":"Crossref","is-referenced-by-count":3,"title":["Reinforced molecular dynamics: Physics-infused generative machine learning model simulates protein motion"],"prefix":"10.1093","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0424-4577","authenticated-orcid":false,"given":"Istv\u00e1n","family":"Kolossv\u00e1ry","sequence":"first","affiliation":[{"name":"Flagship Pioneering , Pioneering Intelligence, 55 Cambridge Pkwy, Cambridge, MA 02142 ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,1,9]]},"reference":[{"issue":"7873","key":"2026011303365280500_pgaf408-B1","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1038\/s41586-021-03819-2","article-title":"Highly accurate protein structure prediction with AlphaFold","volume":"596","author":"Jumper","year":"2021","journal-title":"Nature"},{"issue":"8016","key":"2026011303365280500_pgaf408-B2","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1038\/s41586-024-07487-w","article-title":"Accurate structure prediction of biomolecular interactions with AlphaFold 3","volume":"630","author":"Abramson","year":"2024","journal-title":"Nature"},{"issue":"6557","key":"2026011303365280500_pgaf408-B3","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1126\/science.abj8754","article-title":"Accurate prediction of protein structures and interactions using a three-track neural network","volume":"373","author":"Baek","year":"2021","journal-title":"Science"},{"issue":"8","key":"2026011303365280500_pgaf408-B4","doi-asserted-by":"crossref","first-page":"1514","DOI":"10.1038\/s41592-024-02272-z","article-title":"Openfold: retraining alphafold2 yields new insights into its learning mechanisms and capacity for generalization","volume":"21","author":"Ahdritz","year":"2024","journal-title":"Nat Methods"},{"key":"2026011303365280500_pgaf408-B5","doi-asserted-by":"publisher","author":"Wohlwend","year":"2024","DOI":"10.1101\/2024.11.19.624167"},{"issue":"6637","key":"2026011303365280500_pgaf408-B6","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1126\/science.ade2574","article-title":"Evolutionary-scale prediction of atomic-level protein structure with a language model","volume":"379","author":"Lin","year":"2023","journal-title":"Science"},{"issue":"1","key":"2026011303365280500_pgaf408-B7","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1038\/s41467-024-45051-2","article-title":"Protein structure generation via folding diffusion","volume":"15","author":"Wu","year":"2024","journal-title":"Nat Commun"},{"key":"2026011303365280500_pgaf408-B8","doi-asserted-by":"publisher","author":"Liu","year":"2024","DOI":"10.48550\/arXiv.2410.19110"},{"key":"2026011303365280500_pgaf408-B9","doi-asserted-by":"publisher","author":"Lewis","year":"2024","DOI":"10.1101\/2024.12.05.626885"},{"issue":"6","key":"2026011303365280500_pgaf408-B10","doi-asserted-by":"crossref","first-page":"1034","DOI":"10.1016\/j.str.2019.03.018","article-title":"Coupling molecular dynamics and deep learning to mine protein conformational space","volume":"27","author":"Degiacomi","year":"2019","journal-title":"Structure"},{"issue":"8","key":"2026011303365280500_pgaf408-B11","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1002\/prot.26068","article-title":"Predicting new protein conformations from molecular dynamics simulation conformational landscapes and machine learning","volume":"89","author":"Jin","year":"2021","journal-title":"Proteins"},{"issue":"19","key":"2026011303365280500_pgaf408-B12","doi-asserted-by":"crossref","first-page":"194108","DOI":"10.1063\/5.0069708","article-title":"Variational embedding of protein folding simulations using Gaussian mixture variational autoencoders","volume":"155","author":"Ghorbani","year":"2021","journal-title":"J Chem Phys"},{"key":"2026011303365280500_pgaf408-B13","doi-asserted-by":"crossref","first-page":"781635","DOI":"10.3389\/fmolb.2021.781635","article-title":"Explore protein conformational space with variational autoencoder","volume":"8","author":"Tian","year":"2021","journal-title":"Front Mol Biosci"},{"issue":"04","key":"2026011303365280500_pgaf408-B14","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1142\/S2737416523500217","article-title":"Assessments of variational autoencoder in protein conformation exploration","volume":"22","author":"Xiao","year":"2023","journal-title":"J Comput Biophys Chem"},{"issue":"7","key":"2026011303365280500_pgaf408-B15","doi-asserted-by":"crossref","first-page":"2689","DOI":"10.1021\/acs.jctc.3c01057","article-title":"Protein ensemble generation through variational autoencoder latent space sampling","volume":"20","author":"Mansoor","year":"2024","journal-title":"J Chem Theory Comput"},{"issue":"14","key":"2026011303365280500_pgaf408-B16","doi-asserted-by":"crossref","first-page":"4351","DOI":"10.1021\/acs.jctc.3c00290","article-title":"Alphafold2-rave: from sequence to Boltzmann ranking","volume":"19","author":"Vani","year":"2023","journal-title":"J Chem Theory Comput"},{"key":"2026011303365280500_pgaf408-B17","doi-asserted-by":"publisher","author":"Teng","year":"2025","DOI":"10.26434\/chemrxiv-2025-q3mwr"},{"issue":"1","key":"2026011303365280500_pgaf408-B18","first-page":"011052","article-title":"Deep learning protein conformational space with convolutions and latent interpolations","volume":"11","author":"Ramaswamy","year":"2021","journal-title":"Phys Rev X"},{"issue":"1","key":"2026011303365280500_pgaf408-B19","doi-asserted-by":"crossref","first-page":"3023","DOI":"10.1038\/s41467-021-23246-1","article-title":"Deep learning the structural determinants of protein biochemical properties by comparing structural ensembles with diffnets","volume":"12","author":"Ward","year":"2021","journal-title":"Nat Commun"},{"key":"2026011303365280500_pgaf408-B20","first-page":"2006080","article-title":"Machine learning in the analysis of biomolecular simulations","volume":"7","author":"Kaptan","year":"2022","journal-title":"Adv Phys X"},{"issue":"10","key":"2026011303365280500_pgaf408-B21","doi-asserted-by":"crossref","first-page":"4047","DOI":"10.3390\/molecules28104047","article-title":"Machine learning generation of dynamic protein conformational ensembles","volume":"28","author":"Zheng","year":"2023","journal-title":"Molecules"},{"key":"2026011303365280500_pgaf408-B22","doi-asserted-by":"publisher","author":"Murtada","year":"2024","DOI":"10.1101\/2024.11.25.625337"},{"issue":"5","key":"2026011303365280500_pgaf408-B23","doi-asserted-by":"crossref","first-page":"2487","DOI":"10.1021\/acs.jcim.4c01838","article-title":"Sampling conformational ensembles of highly dynamic proteins via generative deep learning","volume":"65","author":"Ruzmetov","year":"2024","journal-title":"J Chem Inf Model"},{"issue":"1","key":"2026011303365280500_pgaf408-B24","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1038\/s43586-025-00383-1","article-title":"Computational protein design","volume":"5","author":"Albanese","year":"2025","journal-title":"Nat Rev Methods Primers"},{"key":"2026011303365280500_pgaf408-B25","doi-asserted-by":"publisher","author":"Izaguirre","year":"2025","DOI":"10.1101\/2025.01.13.632817"},{"issue":"4","key":"2026011303365280500_pgaf408-B26","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1038\/nrc1323","article-title":"The evolution of thalidomide and its IMiD derivatives as anticancer agents","volume":"4","author":"Bartlett","year":"2004","journal-title":"Nat Rev Cancer"},{"issue":"5971","key":"2026011303365280500_pgaf408-B27","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1126\/science.1177319","article-title":"Identification of a primary target of thalidomide teratogenicity","volume":"327","author":"Ito","year":"2010","journal-title":"Science"},{"issue":"6168","key":"2026011303365280500_pgaf408-B28","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1126\/science.1244851","article-title":"Lenalidomide causes selective degradation of IKZF1 and IKZF3 in multiple myeloma cells","volume":"343","author":"Kr\u00f6nke","year":"2014","journal-title":"Science"},{"issue":"3","key":"2026011303365280500_pgaf408-B29","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1021\/acs.biochem.2c00245","article-title":"Molecular glues: the adhesive connecting targeted protein degradation to the clinic","volume":"62","author":"Sasso","year":"2022","journal-title":"Biochemistry"},{"issue":"8","key":"2026011303365280500_pgaf408-B30","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1016\/j.it.2024.06.004","article-title":"Vav1 as a putative therapeutic target in autoimmune and chronic inflammatory diseases","volume":"45","author":"Neurath","year":"2024","journal-title":"Trends Immunol"},{"key":"2026011303365280500_pgaf408-B31","doi-asserted-by":"publisher","author":"Sylvain","year":"2024","DOI":"10.1101\/2024.11.06.622079"},{"issue":"1","key":"2026011303365280500_pgaf408-B32","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-024-44698-1","article-title":"Selective CK1\u03b1 degraders exert antiproliferative activity against a broad range of human cancer cell lines","volume":"15","author":"Nishiguchi","year":"2024","journal-title":"Nat Commun"},{"issue":"7597","key":"2026011303365280500_pgaf408-B33","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1038\/nature16979","article-title":"Structural basis of lenalidomide-induced CK1\u03b1 degradation by the crl4crbn ubiquitin ligase","volume":"532","author":"Petzold","year":"2016","journal-title":"Nature"},{"issue":"6414","key":"2026011303365280500_pgaf408-B34","doi-asserted-by":"crossref","DOI":"10.1126\/science.aat0572","article-title":"Defining the human C2H2 zinc finger degrome targeted by thalidomide analogs through CRBN","volume":"362","author":"Sievers","year":"2018","journal-title":"Science"},{"issue":"6619","key":"2026011303365280500_pgaf408-B35","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1126\/science.add7574","article-title":"Molecular glue CELMoD compounds are regulators of cereblon conformation","volume":"378","author":"Watson","year":"2022","journal-title":"Science"},{"issue":"20","key":"2026011303365280500_pgaf408-B36","doi-asserted-by":"crossref","first-page":"12562","DOI":"10.1073\/pnas.202427399","article-title":"Escaping free-energy minima","volume":"99","author":"Laio","year":"2002","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"41","key":"2026011303365280500_pgaf408-B37","doi-asserted-by":"crossref","first-page":"13435","DOI":"10.1021\/ja062463w","article-title":"Free-energy landscape for \u03b2 hairpin folding from combined parallel tempering and metadynamics","volume":"128","author":"Bussi","year":"2006","journal-title":"J Am Chem Soc"},{"issue":"17","key":"2026011303365280500_pgaf408-B38","doi-asserted-by":"crossref","first-page":"4553","DOI":"10.1021\/jp067873l","article-title":"A bias-exchange approach to protein folding","volume":"111","author":"Piana","year":"2007","journal-title":"J Phys Chem B"},{"issue":"2","key":"2026011303365280500_pgaf408-B39","doi-asserted-by":"crossref","first-page":"020603","DOI":"10.1103\/PhysRevLett.100.020603","article-title":"Well-tempered metadynamics: a smoothly converging and tunable free-energy method","volume":"100","author":"Barducci","year":"2008","journal-title":"Phys Rev Lett"},{"issue":"23","key":"2026011303365280500_pgaf408-B40","doi-asserted-by":"crossref","first-page":"230602","DOI":"10.1103\/PhysRevLett.111.230602","article-title":"From metadynamics to dynamics","volume":"111","author":"Tiwary","year":"2013","journal-title":"Phys Rev Lett"},{"issue":"7","key":"2026011303365280500_pgaf408-B41","doi-asserted-by":"crossref","first-page":"2731","DOI":"10.1021\/acs.jpclett.0c00497","article-title":"Rethinking metadynamics: from bias potentials to probability distributions","volume":"11","author":"Invernizzi","year":"2020","journal-title":"J Phys Chem Lett"},{"issue":"17","key":"2026011303365280500_pgaf408-B42","doi-asserted-by":"crossref","first-page":"5731","DOI":"10.1021\/acs.jctc.3c00254","article-title":"Oneopes, a combined enhanced sampling method to rule them all","volume":"19","author":"Rizzi","year":"2023","journal-title":"J Chem Theory Comput"},{"key":"2026011303365280500_pgaf408-B43","doi-asserted-by":"publisher","author":"Izmailov","year":"2018","DOI":"10.48550\/arXiv.1803.05407"},{"key":"2026011303365280500_pgaf408-B44"},{"issue":"23","key":"2026011303365280500_pgaf408-B45","doi-asserted-by":"crossref","first-page":"5214","DOI":"10.1021\/acs.jpcb.3c02028","article-title":"Comprehensive approach to simulating large scale conformational changes in biological systems utilizing a path collective variable and new barrier restraint","volume":"127","author":"Kolossv\u00e1ry","year":"2023","journal-title":"J Phys Chem B"},{"issue":"2","key":"2026011303365280500_pgaf408-B46","doi-asserted-by":"crossref","first-page":"020601","DOI":"10.1103\/PhysRevLett.109.020601","article-title":"Path finding on high-dimensional free energy landscapes","volume":"109","author":"Leines","year":"2012","journal-title":"Phys Rev Lett"},{"issue":"7","key":"2026011303365280500_pgaf408-B47","doi-asserted-by":"crossref","first-page":"2247","DOI":"10.1021\/ct3002464","article-title":"Metadynamics with adaptive Gaussians","volume":"8","author":"Branduardi","year":"2012","journal-title":"J Chem Theory Comput"},{"issue":"3","key":"2026011303365280500_pgaf408-B48","doi-asserted-by":"crossref","first-page":"736","DOI":"10.1021\/jp504920s","article-title":"A time-independent free energy estimator for metadynamics","volume":"119","author":"Tiwary","year":"2015","journal-title":"J Phys Chem B"},{"issue":"12","key":"2026011303365280500_pgaf408-B49","doi-asserted-by":"crossref","first-page":"7179","DOI":"10.1021\/acs.jctc.2c00873","article-title":"Reweighted manifold learning of collective variables from enhanced sampling simulations","volume":"18","author":"Rydzewski","year":"2022","journal-title":"J Chem Theory Comput"},{"key":"2026011303365280500_pgaf408-B50","author":"Nguyen"},{"issue":"3","key":"2026011303365280500_pgaf408-B51","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1021\/jp506633n","article-title":"The adaptive biasing force method: everything you always wanted to know but were afraid to ask","volume":"119","author":"Comer","year":"2015","journal-title":"J Phys Chem B"},{"issue":"16","key":"2026011303365280500_pgaf408-B52","doi-asserted-by":"crossref","first-page":"4738","DOI":"10.1021\/acs.jpclett.8b01994","article-title":"Zooming across the free-energy landscape: shaving barriers, and flooding valleys","volume":"9","author":"Fu","year":"2018","journal-title":"J Phys Chem Lett"},{"issue":"11","key":"2026011303365280500_pgaf408-B53","doi-asserted-by":"crossref","first-page":"3254","DOI":"10.1021\/acs.accounts.9b00473","article-title":"Taming rugged free energy landscapes using an average force","volume":"52","author":"Fu","year":"2019","journal-title":"Acc Chem Res"},{"key":"2026011303365280500_pgaf408-B54","author":"Schwede"},{"issue":"16","key":"2026011303365280500_pgaf408-B55","doi-asserted-by":"crossref","first-page":"1668","DOI":"10.1002\/jcc.20290","article-title":"The amber biomolecular simulation programs","volume":"26","author":"Case","year":"2005","journal-title":"J Comput Chem"},{"issue":"2","key":"2026011303365280500_pgaf408-B56","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1002\/wcms.1121","article-title":"An overview of the amber biomolecular simulation package","volume":"3","author":"Salomon-Ferrer","year":"2013","journal-title":"Wiley Interdiscip Rev Comput Mol Sci"},{"issue":"8","key":"2026011303365280500_pgaf408-B57","doi-asserted-by":"crossref","first-page":"3696","DOI":"10.1021\/acs.jctc.5b00255","article-title":"ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB","volume":"11","author":"Maier","year":"2015","journal-title":"J Chem Theory Comput"},{"issue":"9","key":"2026011303365280500_pgaf408-B58","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1002\/jcc.20035","article-title":"Development and testing of a general amber force field","volume":"25","author":"Wang","year":"2004","journal-title":"J Comput Chem"},{"issue":"2","key":"2026011303365280500_pgaf408-B59","doi-asserted-by":"crossref","first-page":"926","DOI":"10.1063\/1.445869","article-title":"Comparison of simple potential functions for simulating liquid water","volume":"79","author":"Jorgensen","year":"1983","journal-title":"J Chem Phys"},{"issue":"20","key":"2026011303365280500_pgaf408-B60","doi-asserted-by":"crossref","first-page":"10096","DOI":"10.1063\/1.1808117","article-title":"A modified TIP3P water potential for simulation with Ewald summation","volume":"121","author":"Price","year":"2004","journal-title":"J Chem Phys"},{"issue":"4","key":"2026011303365280500_pgaf408-B61","doi-asserted-by":"crossref","first-page":"1864","DOI":"10.1021\/ct5010406","article-title":"Long-time-step molecular dynamics through hydrogen mass repartitioning","volume":"11","author":"Hopkins","year":"2015","journal-title":"J Chem Theory Comput"},{"issue":"12","key":"2026011303365280500_pgaf408-B62","doi-asserted-by":"crossref","first-page":"10089","DOI":"10.1063\/1.464397","article-title":"Particle mesh Ewald: an n log (n) method for Ewald sums in large systems","volume":"98","author":"Darden","year":"1993","journal-title":"J Chem Phys"},{"issue":"19","key":"2026011303365280500_pgaf408-B63","doi-asserted-by":"crossref","first-page":"8577","DOI":"10.1063\/1.470117","article-title":"A smooth particle mesh Ewald method","volume":"103","author":"Essmann","year":"1995","journal-title":"J Chem Phys"},{"issue":"7","key":"2026011303365280500_pgaf408-B64","doi-asserted-by":"crossref","first-page":"e1005659","DOI":"10.1371\/journal.pcbi.1005659","article-title":"OpenMM 7: rapid development of high performance algorithms for molecular dynamics","volume":"13","author":"Eastman","year":"2017","journal-title":"PLoS Comput Biol"},{"issue":"8","key":"2026011303365280500_pgaf408-B65","doi-asserted-by":"crossref","first-page":"670","DOI":"10.1038\/s41592-019-0506-8","article-title":"Promoting transparency and reproducibility in enhanced molecular simulations","volume":"16","author":"Bonomi","year":"2019","journal-title":"Nat Methods"},{"issue":"10","key":"2026011303365280500_pgaf408-B66","doi-asserted-by":"crossref","first-page":"1961","DOI":"10.1016\/j.cpc.2009.05.011","article-title":"Plumed: a portable plugin for free-energy calculations with molecular dynamics","volume":"180","author":"Bonomi","year":"2009","journal-title":"Comput Phys Commun"},{"issue":"2","key":"2026011303365280500_pgaf408-B67","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1016\/j.cpc.2013.09.018","article-title":"Plumed 2: new feathers for an old bird","volume":"185","author":"Tribello","year":"2014","journal-title":"Comput Phys Commun"},{"issue":"8","key":"2026011303365280500_pgaf408-B68","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1002\/jcc.540130805","article-title":"Settle: an analytical version of the shake and rattle algorithm for rigid water models","volume":"13","author":"Miyamoto","year":"1992","journal-title":"J Comput Chem"},{"issue":"5","key":"2026011303365280500_pgaf408-B69","doi-asserted-by":"crossref","first-page":"054103","DOI":"10.1063\/1.2432340","article-title":"From a to b in free energy space","volume":"126","author":"Branduardi","year":"2007","journal-title":"J Chem Phys"},{"key":"2026011303365280500_pgaf408-B70","unstructured":"Kolossv\u00e1ry I . 2025. rmd-autoencoder for reinforced molecular dynamics simulations (Zenodo). 10.5281\/zenodo.16459122"},{"issue":"15","key":"2026011303365280500_pgaf408-B71","doi-asserted-by":"crossref","first-page":"3676","DOI":"10.1021\/acs.jpcb.6b10055","article-title":"Smoothed biasing forces yield unbiased free energies with the extended-system adaptive biasing force method","volume":"121","author":"Lesage","year":"2017","journal-title":"J Phys Chem B"},{"issue":"22-23","key":"2026011303365280500_pgaf408-B72","doi-asserted-by":"crossref","first-page":"3345","DOI":"10.1080\/00268976.2013.813594","article-title":"Using collective variables to drive molecular dynamics simulations","volume":"111","author":"Fiorin","year":"2013","journal-title":"Mol Phys"},{"issue":"45","key":"2026011303365280500_pgaf408-B73","doi-asserted-by":"crossref","first-page":"11108","DOI":"10.1021\/acs.jpcb.4c05604","article-title":"Expanded functionality and portability for the colvars library","volume":"128","author":"Fiorin","year":"2024","journal-title":"J Phys Chem B"},{"key":"2026011303365280500_pgaf408-B74"},{"issue":"2","key":"2026011303365280500_pgaf408-B75","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1016\/j.jmb.2010.11.008","article-title":"Alternate states of proteins revealed by detailed energy landscape mapping","volume":"405","author":"Tyka","year":"2011","journal-title":"J Mol Biol"},{"issue":"47","key":"2026011303365280500_pgaf408-B76","doi-asserted-by":"crossref","first-page":"18949","DOI":"10.1073\/pnas.1115898108","article-title":"Algorithm discovery by protein folding game players","volume":"108","author":"Khatib","year":"2011","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"4","key":"2026011303365280500_pgaf408-B77","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1002\/prot.26030","article-title":"Perturbing the energy landscape for improved packing during computational protein design","volume":"89","author":"Maguire","year":"2021","journal-title":"Proteins"},{"issue":"5","key":"2026011303365280500_pgaf408-B78","doi-asserted-by":"crossref","first-page":"e63906","DOI":"10.1371\/journal.pone.0063906","article-title":"Serverification of molecular modeling applications: the Rosetta Online Server that Includes Everyone (ROSIE)","volume":"8","author":"Lyskov","year":"2013","journal-title":"PLoS One"}],"container-title":["PNAS Nexus"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/pnasnexus\/article-pdf\/5\/1\/pgaf408\/66326445\/pgaf408.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/pnasnexus\/article-pdf\/5\/1\/pgaf408\/66326445\/pgaf408.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T08:37:11Z","timestamp":1768293431000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/pnasnexus\/article\/doi\/10.1093\/pnasnexus\/pgaf408\/8418313"}},"subtitle":[],"editor":[{"given":"Ozlem","family":"Keskin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":78,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1,5]]}},"URL":"https:\/\/doi.org\/10.1093\/pnasnexus\/pgaf408","relation":{},"ISSN":["2752-6542"],"issn-type":[{"value":"2752-6542","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,1]]},"published":{"date-parts":[[2026,1]]},"article-number":"pgaf408"}}