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One bead per residue can describe all-atom protein structures

https://doi.org/10.1016/j.str.2023.10.013

Heo, Lim; Feig, Michael (November 2023, Structure)

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Modeling Concentration-dependent Phase Separation Processes Involving Peptides and RNA via Residue-Based Coarse-Graining

https://doi.org/10.1021/acs.jctc.2c00856

Valdes-Garcia, Gilberto; Heo, Lim; Lapidus, Lisa J.; Feig, Michael (January 2023, Journal of Chemical Theory and Computation)

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Characterizing Transient Protein–Protein Interactions by Trp-Cys Quenching and Computer Simulations

https://doi.org/10.1021/acs.jpclett.2c02723

Heo, Lim; Gamage, Kasun; Valdes-Garcia, Gilberto; Lapidus, Lisa J.; Feig, Michael (November 2022, The Journal of Physical Chemistry Letters)

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Protein assembly and crowding simulations

https://doi.org/10.1016/j.sbi.2022.102340

Heo, Lim; Sugita, Yuji; Feig, Michael (April 2022, Current Opinion in Structural Biology)

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ColabFold: making protein folding accessible to all

https://doi.org/10.1038/s41592-022-01488-1

Mirdita, Milot; Schütze, Konstantin; Moriwaki, Yoshitaka; Heo, Lim; Ovchinnikov, Sergey; Steinegger, Martin (June 2022, Nature Methods)

Abstract ColabFold offers accelerated prediction of protein structures and complexes by combining the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. ColabFold’s 40−60-fold faster search and optimized model utilization enables prediction of close to 1,000 structures per day on a server with one graphics processing unit. Coupled with Google Colaboratory, ColabFold becomes a free and accessible platform for protein folding. ColabFold is open-source software available at https://github.com/sokrypton/ColabFold and its novel environmental databases are available at https://colabfold.mmseqs.com .
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An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12

https://doi.org/10.1038/s41598-018-26812-8

Keasar, Chen; McGuffin, Liam J.; Wallner, Björn; Chopra, Gaurav; Adhikari, Badri; Bhattacharya, Debswapna; Blake, Lauren; Bortot, Leandro Oliveira; Cao, Renzhi; Dhanasekaran, B. K.; et al (December 2018, Scientific Reports)

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