Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features

Cited by (152)

Items 101–152 of 152

1. Comparative Analysis of Homology Models of the Ah Receptor Ligand Binding Domain: Verification of Structure–Function Predictions by Site-Directed Mutagenesis of a Nonfunctional Receptor
   Fraccalvieri, Domenico, Soshilov, Anatoly A., Karchner, Sibel I., Franks, Diana G., Pandini, Alessandro, Bonati, Laura, Hahn, Mark E., Denison, Michael S. · 2013 · Biochemistry
2. Tadpole-like conformations of Huntingtin Exon 1 are characterized by conformational heterogeneity that persists regardless of polyglutamine length
   Newcombe, Estella A., Ruff, Kiersten M., Sethi, Ashish, Ormsby, Angelique R., Ramdzan, Yasmin M., Fox, Archa, Purcell, Anthony W., Gooley, Paul R., Pappu, Rohit V., Hatters, Danny M. · 2018 · Journal of Molecular Biology
3. The crystal structure of the periplasmic domain of the Escherichia coli membrane protein insertase YidC contains a substrate binding cleft.
   Ravaud, Stephanie, Stjepanovic, Goran, Wild, Klemens, Sinning, Irmgard · 2008 · Journal of Biological Chemistry
4. Structural basis for the recruitment of glycogen synthase by glycogenin
   Zeqiraj, Elton, Tang, Xiaojing, Hunter, Roger W., García-Rocha, Mar, Judd, Andrew, Deak, Maria, von Wilamowitz-Moellendorff, Alexander, Kurinov, Igor, Guinovart, Joan J., Tyers, Mike et al. · 2014 · Proceedings of the National Academy of Sciences
5. Structural Conservation of Components in the Amino Acid Sensing Branch of the TOR Pathway in Yeast and Mammals
   Kogan, Konstantin, Spear, Eric D., Kaiser, Chris A., Fass, Deborah · 2010 · Journal of Molecular Biology
6. The Plasma Membrane as a Competitive Inhibitor and Positive Allosteric Modulator of KRas4B Signaling
   Neale, Chris, García, Angel E. · 2020 · Biophysical Journal
7. Genome-wide prediction of pathogenic gain- and loss-of-function variants from ensemble learning of a diverse feature set
   Stein, David, Kars, Meltem Ece, Wu, Yiming, Bayrak, Çiğdem Sevim, Stenson, Peter D., Cooper, David N., Schlessinger, Avner, Itan, Yuval · 2023 · Genome Medicine
8. High-resolution crystal structure of the restriction-modification controller protein C.AhdI from Aeromonas hydrophila
   McGeehan, J.E., Streeter, S.D., Papapanagiotou, I., Fox, G.C., Kneale, G.G. · 2005 · Journal of Molecular Biology
9. Model for Substrate Interactions in C5a Peptidase from Streptococcus pyogenes: a 1.9 Å Crystal Structure of the Active Form of ScpA.
   Kagawa, Todd F., O'Connell, Maurice R., Mouat, Pania, Paoli, Max, O'Toole, Paul W., Cooney, Jakki C. · 2009 · Journal of Molecular Biology
10. Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon
    Rosenberg, Aviv A., Marx, Ailie, Bronstein, Alex M. · 2022 · Nature Communications
11. Structural insight into the lactoferrin receptors from pathogenic Neisseria
    Noinaj, Nicholas, Cornelissen, Cynthia Nau, Buchanan, Susan K. · 2013 · Journal of Structural Biology
12. Accurate prediction of protein assembly structure by combining AlphaFold and symmetrical docking
    Jeppesen, Mads, André, Ingemar · 2023 · Nature Communications
13. Solution Structure, Dimerization, and Dynamics of a Lipophilic α/3₁₀-Helical, C^α-Methylated Peptide. Implications for Folding of Membrane Proteins
    Dehner, Alexander, Planker, Eckart, Gemmecker, Gerd, Broxterman, Quirinus B., Bisson, William, Formaggio, Fernando, Crisma, Marco, Toniolo, Claudio, Kessler, Horst · 2001 · Journal of the American Chemical Society
14. Structural stability of proteins in aqueous and nonpolar environments
    Yasuda, Satoshi, Oshima, Hiraku, Kinoshita, Masahiro · 2012 · The Journal of Chemical Physics
15. Genetic interaction mapping informs integrative structure determination of protein complexes
    Braberg, Hannes, Echeverria, Ignacia, Bohn, Stefan, Cimermancic, Peter, Shiver, Anthony, Alexander, Richard, Xu, Jiewei, Shales, Michael, Dronamraju, Raghuvar, Jiang, Shuangying et al. · 2020 · Science
16. DEGRONOPEDIA: a web server for proteome-wide inspection of degrons
    Szulc, Natalia A, Stefaniak, Filip, Piechota, Małgorzata, Soszyńska, Anna, Piórkowska, Gabriela, Cappannini, Andrea, Bujnicki, Janusz M, Maniaci, Chiara, Pokrzywa, Wojciech · 2024 · Nucleic Acids Research
17. Interpreting the molecular mechanisms of disease variants in human transmembrane proteins
    Tiemann, Johanna Katarina Sofie, Zschach, Henrike, Lindorff-Larsen, Kresten, Stein, Amelie · 2023 · Biophysical Journal
18. The <i> <scp>L</scp> egionella pneumophila kai </i> operon is implicated in stress response and confers fitness in competitive environments
    Loza‐Correa, Maria, Sahr, Tobias, Rolando, Monica, Daniels, Craig, Petit, Pierre, Skarina, Tania, Gomez Valero, Laura, Dervins‐Ravault, Delphine, Honoré, Nadine, Savchenko, Aleksey et al. · 2014 · Environmental Microbiology
19. Crystal structure of human T-protein of glycine cleavage system at 2.0 A resolution and its implication for understanding non-ketotic hyperglycinemia
    Okamura-Ikeda, Kazuko, Hosaka, Harumi, Yoshimura, Masato, Yamashita, Eiki, Toma, Sachiko, Nakagawa, Atsushi, Fujiwara, Kazuko, Motokawa, Yutaro, Taniguchi, Hisaaki · 2005 · Journal of Molecular Biology
20. Structure and Non-Structure of Centrosomal Proteins
    Dos Santos, Helena G., Abia, David, Janowski, Robert, Mortuza, Gulnahar, Bertero, Michela G., Boutin, Maïlys, Guarín, Nayibe, Méndez-Giraldez, Raúl, Nuñez, Alfonso, Pedrero, Juan G. et al. · 2013 · PLoS ONE
21. The Statistical Trends of Protein Evolution: A Lesson from AlphaFold Database
    Tang, Qian-Yuan, Ren, Weitong, Wang, Jun, Kaneko, Kunihiko · 2022 · Molecular Biology and Evolution
22. ATP-induced asymmetric pre-protein folding as a driver of protein translocation through the Sec machinery.
    Corey, Robin A, Ahdash, Zainab, Shah, Anokhi, Pyle, Euan, Allen, William J, Fessl, Tomas, Lovett, Janet E, Politis, Argyris, Collinson, Ian · 2019 · eLife
23. A model for hydrophobic protrusions on peripheral membrane proteins
    Fuglebakk, Edvin, Reuter, Nathalie · 2018 · PLOS Computational Biology
24. Protein multiple conformations prediction using multi-objective evolution algorithm
    Hou, Ming-Hua, Jin, Si-Rong, Cui, Xin-Yue, Peng, Chun-Xiang, Zhao, Kai-Long, Song, Le, Zhang, Gui-Jun · 2023
25. <scp>P</scp> albociclib can overcome mutations in cyclin dependent kinase 6 that break hydrogen bonds between the drug and the protein
    Hernandez Maganhi, Stella, Jensen, Patrizia, Caracelli, Ignez, Zukerman Schpector, Julio, Fröhling, Stefan, Friedman, Ran · 2017 · Protein Science
26. Phosphorylation of the retinoic acid receptor alpha induces a mechanical allosteric regulation and changes in internal dynamics
    Chebaro, Yassmine, Amal, Ismail, Rochel, Natacha, Rochette-Egly, Cécile, Stote, Roland H., Dejaegere, Annick · 2013 · PLoS Computational Biology
27. Critical assessment of coiled-coil predictions based on protein structure data
    Simm, Dominic, Hatje, Klas, Waack, Stephan, Kollmar, Martin · 2021 · Scientific Reports
28. OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors
    Xu, Gang, Wang, Qinghua, Ma, Jianpeng · 2022 · Briefings in Bioinformatics
29. Protein dynamics at Eph receptor-ligand interfaces as revealed by crystallography, NMR and MD simulations
    Qin, Haina, Lim, Liangzhong, Song, Jianxing · 2012 · BMC Biophysics
30. Non-canonical Shedding of TNFα by SPPL2a Is Determined by the Conformational Flexibility of Its Transmembrane Helix
    Spitz, Charlotte, Schlosser, Christine, Guschtschin-Schmidt, Nadja, Stelzer, Walter, Menig, Simon, Götz, Alexander, Haug-Kröper, Martina, Scharnagl, Christina, Langosch, Dieter, Muhle-Goll, Claudia et al. · 2020 · iScience
31. ‘Asynchronous reciprocal coupling of Martini 2.2 coarse-grained and CHARMM36 all-atom simulations in an automated multiscale framework’
    López, Cesar A., Zhang, Xiaohua, Aydin, Fikret, Shrestha, Rebika, Van, Que N., Stanley, Christopher B., Carpenter, Timothy S., Nguyen, Kien, Patel, Lara A., Chen, De et al. · 2022 · Journal of Chemical Theory and Computation
32. Predicting the conformational flexibility of antibody and T-cell receptor CDRs
    Spoendlin, Fabian C., Fernández-Quintero, Monica L., Raghavan, Sai S. R., Turner, Hannah L., Gharpure, Anant, Loeffler, Johannes R., Wong, Wing K., Bujotzek, Alexander, Georges, Guy, Ward, Andrew B. et al. · 2025
33. A novel sequence alignment algorithm based on deep learning of the protein folding code
    Gao, Mu, Skolnick, Jeffrey · 2021 · Bioinformatics
34. Hidden information on protein function in censuses of proteome foldedness
    Cox, Dezerae, Ang, Ching-Seng, Nillegoda, Nadinath B., Reid, Gavin E., Hatters, Danny M. · 2022 · Nature Communications
35. Understanding the good and poor cell targeting activity of gold nanostructures functionalized with molecular units for the epidermal growth factor receptor
    Mazzuca, Claudia, Di Napoli, Benedetta, Biscaglia, Francesca, Ripani, Giorgio, Rajendran, Senthilkumar, Braga, Andrea, Benna, Clara, Mocellin, Simone, Gobbo, Marina, Meneghetti, Moreno et al. · 2019 · Nanoscale Advances
36. PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context
    Zhong, Guojie, Zhao, Yige, Zhuang, Demi, Chung, Wendy K., Shen, Yufeng · 2025 · Nature Communications
37. Relative Stabilities of Conserved and Non-Conserved Structures in the OB-Fold Superfamily
    Guardino, Kaitlyn M., Sheftic, Sarah R., Slattery, Robert E., Alexandrescu, Andrei T. · 2009 · International Journal of Molecular Sciences
38. Systematic investigation of machine learning on limited data: A study on predicting protein-protein binding strength
    Zheng, Feifan, Jiang, Xin, Wen, Yuhao, Yang, Yan, Li, Minghui · 2024 · Computational and Structural Biotechnology Journal
39. Can Peptide Folding Simulations Provide Predictive Information for Aggregation Propensity?
    Lin, Edmund I., Shell, M. Scott · 2010 · The Journal of Physical Chemistry B
40. High-throughput Selection of Human <i>de novo</i> -emerged sORFs with High Folding Potential
    Aubel, Margaux, Buchel, Filip, Heames, Brennen, Jones, Alun, Honc, Ondrej, Bornberg-Bauer, Erich, Hlouchova, Klara · 2024 · Genome Biology and Evolution
41. <scp> CC ⁺ </scp> : A searchable database of validated coiled coils in <scp>PDB</scp> structures and <scp>AlphaFold2</scp> models
    Kumar, Prasun, Petrenas, Rokas, Dawson, William M., Schweke, Hugo, Levy, Emmanuel D., Woolfson, Derek N. · 2023 · Protein Science
42. Severe deviation in protein fold prediction by advanced AI: a case study
    López-Sagaseta, Jacinto, Urdiciain, Alejandro · 2025 · Scientific Reports
43. Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterised proteins
    Kandathil, Shaun M, Greener, Joe G, Lau, Andy M, Jones, David T · 2020
44. AlphaFold2 SLiM screen for LC3-LIR interactions in autophagy
    Stuke, Jan Felix Maximilian, Hummer, Gerhard · 2025 · Autophagy
45. A unified analysis of evolutionary and population constraint in protein domains highlights structural features and pathogenic sites
    MacGowan, Stuart A., Madeira, Fábio, Britto-Borges, Thiago, Barton, Geoffrey J. · 2024 · Communications Biology
46. Exploring the Knowledge of an Outstanding Protein to Protein Interaction Transformer
    Yang, Sen, Cheng, Peng, Liu, Yang, Feng, Dawei, Wang, Shengqi · 2024 · IEEE/ACM Transactions on Computational Biology and Bioinformatics
47. Unifying Constraints Linking Protein Folding and Native Dynamics Decoded from AlphaFold
    Zhang, Zecheng, Ren, Weitong, Xie, Liangxu, Zheng, Yuxiang, Guan, Xingyue, Wang, Jun, Li, Wenfei, Tang, Qian-Yuan · 2026 · Physical Review Letters
48. NAStructuralDB : Structural database to facilitate computational studies of molecular modeling and recognition of proteins with special focus on antibody-antigen interactions
    Chomicz, Dawid, Dudzic, Paweł, Wrobel, Sonia, Gawłowski, Tomasz, Demharter, Samuel, Spreafico, Roberto, Minoux, Hervé, Phillips, Andrew, Krawczyk, Konrad · 2025
49. An interpretable molecular framework for predicting cancer driver missense mutations
    Yang, Yan, Sun, Weikang, Liu, Yang, Zhang, Jian, Li, Minghui · 2026 · Proceedings of the National Academy of Sciences
50. AlphaMut: A Deep Reinforcement Learning Model to Suggest Helix-Disrupting Mutations
    Bhargav, Prathith, Mukherjee, Arnab · 2025 · Journal of Chemical Theory and Computation
51. ECOD: Classification of domains in AFDB Swiss-Prot structure predictions
    Schaeffer, R. Dustin, Zhang, Jing, Cong, Qian, Grishin, Nick V. · 2026 · PLOS Computational Biology
52. Data‐driven evaluation of suitable immunogens for improved antibody selection
    Waury, Katharina, Kvartsberg, Hlin, Zetterberg, Henrik, Blennow, Kaj, Teunissen, Charlotte E., Abeln, Sanne · 2025 · Protein Science