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Peptide design plays a pivotal role in therapeutics, allowing brand new possibility to leverage target binding sites that are previously undruggable.
A general method applicable to the search for similarities in the amino acid sequence of two proteins
S. B. Needleman and C. D. Wunsch · 1970
Earlier work this paper cites.
Principles of protein–protein recognition
C. Chothia and J. Janin · 1975
Earlier work this paper cites.
The x-pro peptide bond as an nmr probe for conformational studies of flexible linear peptides
C. Grathwohl and K. Wüthrich · 1976
Earlier work this paper cites.
Correlation between stability of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence
K. Guruprasad, B. B. Reddy, and M. W. Pandit · 1990
Earlier work this paper cites.
Amino acid substitution matrices from protein blocks
S. Henikoff and J. G. Henikoff · 1992
Earlier work this paper cites.
Mathematical methods of statistics , volume 26
H. Cramér · 1999
Earlier work this paper cites.
The protein data bank
H. M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov, and P. E. Bourne · 2000
Earlier work this paper cites.
Biopython: freely available python tools for computational molecular biology and bioinformatics
P. J. Cock, T. Antao, J. T. Chang, B. A. Chapman, C. J. Cox, A. Dalke, I. Friedberg, T. Hamelryck, F. Kauff, B. Wilczynski, et al · 2009
Earlier work this paper cites.
The structural basis of peptide-protein binding strategies
N. London, D. Movshovitz-Attias, and O. Schueler-Furman · 2010
Earlier work this paper cites.
Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, P.-A. Manzagol, and L. Bottou · 2010
Earlier work this paper cites.
Rosetta flexpepdock web server—high resolution modeling of peptide–protein interactions
N. London, B. Raveh, E. Cohen, G. Fathi, and O. Schueler-Furman · 2011
Earlier work this paper cites.
Computational design of peptide ligands
P. Vanhee, A. M. van der Sloot, E. Verschueren, L. Serrano, F. Rousseau, and J. Schymkowitz · 2011
Earlier work this paper cites.
Matrix computations
G. H. Golub and C. F. Van Loan · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2013
Earlier work this paper cites.
Peptide therapeutics: current status and future directions
K. Fosgerau and T. Hoffmann · 2015
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
J. Sohl-Dickstein, E. Weiss, N. Maheswaranathan, and S. Ganguli · 2015
Earlier work this paper cites.
Dockq: a quality measure for protein-protein docking models
S. Basu and B. Wallner · 2016
Earlier work this paper cites.
Accurate de novo design of hyperstable constrained peptides
G. Bhardwaj, V. K. Mulligan, C. D. Bahl, J. M. Gilmore, P. J. Harvey, O. Cheneval, G. W. Buchko, S. V. Pulavarti, Q. Kaas, A. Eletsky, et al · 2016
Earlier work this paper cites.
Freesasa: An open source c library for solvent accessible surface area calculations
S. Mitternacht · 2016
Earlier work this paper cites.
The rosetta all-atom energy function for macromolecular modeling and design
R. F. Alford, A. Leaver-Fay, J. R. Jeliazkov, M. J. O’Meara, F. P. DiMaio, H. Park, M. V. Shapovalov, P. D. Renfrew, V. K. Mulligan, K. Kappel, et al · 2017
Earlier work this paper cites.
Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
M. Steinegger and J. Söding · 2017
Earlier work this paper cites.
Rosettaantibodydesign (rabd): A general framework for computational antibody design
J. Adolf-Bryfogle, O. Kalyuzhniy, M. Kubitz, B. D. Weitzner, X. Hu, Y. Adachi, W. R. Schief, and R. L. Dunbrack Jr · 2018
Earlier work this paper cites.
Recurrent neural network model for constructive peptide design
A. T. Muller, J. A. Hiss, and G. Schneider · 2018
Earlier work this paper cites.
Generative models for graph-based protein design
J. Ingraham, V. Garg, R. Barzilay, and T. Jaakkola · 2019
Earlier work this paper cites.
A comprehensive review on current advances in peptide drug development and design
A. C.-L. Lee, J. L. Harris, K. K. Khanna, and J.-H. Hong · 2019
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Generative modeling by estimating gradients of the data distribution
Y. Song and S. Ermon · 2019
Cited alongside, same era.
Pepbdb: a comprehensive structural database of biological peptide–protein interactions
Z. Wen, J. He, H. Tao, and S.-Y. Huang · 2019
Cited alongside, same era.
Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
Cited alongside, same era.
Macromolecular modeling and design in rosetta: recent methods and frameworks
J. K. Leman, B. D. Weitzner, S. M. Lewis, J. Adolf-Bryfogle, N. Alam, R. F. Alford, M. Aprahamian, D. Baker, K. A. Barlow, P. Barth, et al · 2020
Cited alongside, same era.
Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations
Pocket2mol: Efficient molecular sampling based on 3d protein pockets
X. Peng, S. Luo, J. Guan, Q. Xie, J. Peng, and J. Ma · 2022
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High-resolution image synthesis with latent diffusion models
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2022
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Tertiary motifs as building blocks for the design of protein-binding peptides
S. Swanson, V. Sivaraman, G. Grigoryan, and A. E. Keating · 2022
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Diffusion probabilistic modeling of protein backbones in 3d for the motif-scaffolding problem
B. L. Trippe, J. Yim, D. Tischer, T. Broderick, D. Baker, R. Barzilay, and T. Jaakkola · 2022
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Harnessing protein folding neural networks for peptide–protein docking
T. Tsaban, J. K. Varga, O. Avraham, Z. Ben-Aharon, A. Khramushin, and O. Schueler-Furman · 2022
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P. Das, T. Sercu, K. Wadhawan, I. Padhi, S. Gehrmann, F. Cipcigan, V. Chenthamarakshan, H. Strobelt, C. Dos Santos, P.-Y. Chen, et al · 2021
Cited alongside, same era.
Diffusion models beat gans on image synthesis
P. Dhariwal and A. Nichol · 2021
Cited alongside, same era.
Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites
P. Hosseinzadeh, P. R. Watson, T. W. Craven, X. Li, S. Rettie, F. Pardo-Avila, A. K. Bera, V. K. Mulligan, P. Lu, A. S. Ford, et al · 2021
Cited alongside, same era.
Iterative refinement graph neural network for antibody sequence-structure co-design
W. Jin, J. Wohlwend, R. Barzilay, and T. Jaakkola · 2021
Cited alongside, same era.
Highly accurate protein structure prediction with alphafold
J. Jumper, R. Evans, A. Pritzel, T. Green, M. Figurnov, O. Ronneberger, K. Tunyasuvunakool, R. Bates, A. Žídek, A. Potapenko, et al · 2021
Cited alongside, same era.
A deep-learning framework for multi-level peptide–protein interaction prediction
Y. Lei, S. Li, Z. Liu, F. Wan, T. Tian, S. Li, D. Zhao, and J. Zeng · 2021
Cited alongside, same era.
A 3d generative model for structure-based drug design
S. Luo, J. Guan, J. Ma, and J. Peng · 2021
Cited alongside, same era.
D. Wang, Z. Wen, F. Ye, H. Zhou, and L. Li · 2022
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Geodiff: A geometric diffusion model for molecular conformation generation
M. Xu, L. Yu, Y. Song, C. Shi, S. Ermon, and J. Tang · 2022
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Se (3)-stochastic flow matching for protein backbone generation
J. Bose, T. Akhound-Sadegh, K. FATRAS, G. Huguet, J. Rector-Brooks, C.-H. Liu, A. C. Nica, M. Korablyov, M. M. Bronstein, and A. Tong · 2023
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A hitchhiker’s guide to geometric gnns for 3d atomic systems
A. Duval, S. V. Mathis, C. K. Joshi, V. Schmidt, S. Miret, F. D. Malliaros, T. Cohen, P. Lio, Y. Bengio, and M. Bronstein · 2023
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Illuminating protein space with a programmable generative model
J. B. Ingraham, M. Baranov, Z. Costello, K. W. Barber, W. Wang, A. Ismail, V. Frappier, D. M. Lord, C. Ng-Thow-Hing, E. R. Van Vlack, et al · 2023
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End-to-end full-atom antibody design
X. Kong, W. Huang, and Y. Liu · 2023
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Abdiffuser: Full-atom generation of in-vitro functioning antibodies
K. Martinkus, J. Ludwiczak, K. Cho, W.-C. Lian, J. Lafrance-Vanasse, I. Hotzel, A. Rajpal, Y. Wu, R. Bonneau, V. Gligorijevic, et al · 2023
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Abode: Ab initio antibody design using conjoined odes
Y. Verma, M. Heinonen, and V. Garg · 2023
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De novo design of protein structure and function with rfdiffusion
J. L. Watson, D. Juergens, N. R. Bennett, B. L. Trippe, J. Yim, H. E. Eisenach, W. Ahern, A. J. Borst, R. J. Ragotte, L. F. Milles, et al · 2023
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Computational prediction of mhc anchor locations guides neoantigen identification and prioritization
H. Xia, J. McMichael, M. Becker-Hapak, O. C. Onyeador, R. Buchli, E. McClain, P. Pence, S. Supabphol, M. M. Richters, A. Basu, et al · 2023
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Helixgan a deep-learning methodology for conditional de novo design of α \alpha -helix structures
X. Xie, P. A. Valiente, and P. M. Kim · 2023
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Geometric latent diffusion models for 3d molecule generation
M. Xu, A. S. Powers, R. O. Dror, S. Ermon, and J. Leskovec · 2023
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Se (3) diffusion model with application to protein backbone generation
J. Yim, B. L. Trippe, V. De Bortoli, E. Mathieu, A. Doucet, R. Barzilay, and T. Jaakkola · 2023
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Diffpack: A torsional diffusion model for autoregressive protein side-chain packing
Y. Zhang, Z. Zhang, B. Zhong, S. Misra, and J. Tang · 2023
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A latent diffusion model for protein structure generation
C. Fu, K. Yan, L. Wang, W. Y. Au, M. C. McThrow, T. Komikado, K. Maruhashi, K. Uchino, X. Qian, and S. Ji · 2024
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Full-atom peptide design based on multi-modal flow matching
J. Li, C. Cheng, Z. Wu, R. Guo, S. Luo, Z. Ren, J. Peng, and J. Ma · 2024
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Protein structure generation via folding diffusion
K. E. Wu, K. K. Yang, R. van den Berg, S. Alamdari, J. Y. Zou, A. X. Lu, and A. P. Amini · 2024
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Helixdiff, a score-based diffusion model for generating all-atom α \alpha -helical structures
X. Xie, P. A. Valiente, J. Kim, and P. M. Kim · 2024
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