Influence of Stereochemistry in a Local Approach for Calculating Protein Conformations

Highly accurate protein structure prediction with AlphaFold

Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works

The Protein Data Bank

Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196 · see citing works

Crystallography & NMR System: A New Software Suite for Macromolecular Structure Determination

Brünger, A. T., Adams, P. D., Clore, G. M., DeLano, W. L., Gros, P., Grosse‐Kunstleve, R. W., Jiang, J., Kuszewski, J. J., Nilges, M., Pannu, N., et al. (1998) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444998003254 · Cited by 15,720 · see citing works

Accurate prediction of protein structures and interactions using a 3-track network

Baek, M., DiMaio, F., Anishchenko, I., Dauparas, J., Ovchinnikov, S., Lee, G. R., Wang, J., Cong, Q., Kinch, L. N., Schaeffer, R. D., et al. (2021) · doi:10.1101/2021.06.14.448402 · Cited by 5,542 · see citing works

Evolutionary-scale prediction of atomic level protein structure with a language model

Lin, Z., Akin, H., Rao, R., Hie, B., Zhu, Z., Lu, W., Smetanin, N., Verkuil, R., Kabeli, O., Shmueli, Y., et al. (2022) · doi:10.1101/2022.07.20.500902 · Cited by 5,523 · see citing works

Improved protein structure prediction using potentials from deep learning

Senior, A. W., Evans, R., Jumper, J., Kirkpatrick, J., Sifre, L., Green, T., Qin, C., Žídek, A., Nelson, A. W. R., Bridgland, A., et al. (2020) · Nature · doi:10.1038/s41586-019-1923-7 · Cited by 3,378 · see citing works

Database resources of the national center for biotechnology information

Sayers, E. W., Bolton, E. E., Brister, J. R., Canese, K., Chan, J., Comeau, D. C., Connor, R., Funk, K., Kelly, C., Kim, S., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1112 · Cited by 2,812 · see citing works

Knowledge‐based protein secondary structure assignment

Frishman, D., & Argos, P. (1995) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340230412 · Cited by 2,524 · see citing works

Accurate Bond and Angle Parameters for X-ray Protein Structure Refinement

Engh, R., & Huber, R. (1991) · Acta Crystallographica Section A Foundations of Crystallography · doi:10.1107/s0108767391001071 · Cited by 2,497 · see citing works

Scoring function for automated assessment of protein structure template quality

Zhang, Y., & Skolnick, J. (2004) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20264 · Cited by 2,392 · see citing works

PISCES: a protein sequence culling server

Wang, G., & Dunbrack, R. L. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg224 · Cited by 1,664 · see citing works

The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

Alford, R. F., Leaver-Fay, A., Jeliazkov, J. R., O’Meara, M. J., DiMaio, F. P., Park, H., Shapovalov, M. V., Renfrew, P. D., Mulligan, V. K., Kappel, K., et al. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00125 · Cited by 1,532 · see citing works

Improved protein structure prediction using predicted interresidue orientations

Yang, J., Anishchenko, I., Park, H., Peng, Z., Ovchinnikov, S., & Baker, D. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1914677117 · Cited by 1,421 · see citing works

Identification of direct residue contacts in protein–protein interaction by message passing

Weigt, M., White, R. A., Szurmant, H., Hoch, J. A., & Hwa, T. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0805923106 · Cited by 1,025 · see citing works

Advances in protein structure prediction and design

Kuhlman, B., & Bradley, P. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0163-x · Cited by 806 · see citing works

Euclidean Distance Geometry and Applications

Liberti, L., Lavor, C., Maculan, N., & Mucherino, A. (2014) · SIAM Review · doi:10.1137/120875909 · Cited by 531 · see citing works

A fresh look at the Ramachandran plot and the occurrence of standard structures in proteins

Hollingsworth, S. A., & Karplus, P. A. (2010) · BioMolecular Concepts · doi:10.1515/bmc.2010.022 · Cited by 429 · see citing works

Synonymous Codons Direct Cotranslational Folding toward Different Protein Conformations

Buhr, F., Jha, S., Thommen, M., Mittelstaet, J., Kutz, F., Schwalbe, H., Rodnina, M. V., & Komar, A. A. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.01.008 · Cited by 395 · see citing works

ARIA: automated NOE assignment and NMR structure calculation

Linge, J. P., Habeck, M., Rieping, W., & Nilges, M. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.315 · Cited by 391 · see citing works

An evolution-based model for designing chorismate mutase enzymes

Russ, W. P., Figliuzzi, M., Stocker, C., Barrat-Charlaix, P., Socolich, M., Kast, P., Hilvert, D., Monasson, R., Cocco, S., Weigt, M., et al. (2020) · Science · doi:10.1126/science.aba3304 · Cited by 313 · see citing works

A Pareto-Optimal Refinement Method for Protein Design Scaffolds

Nivón, L. G., Moretti, R., & Baker, D. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059004 · Cited by 310 · see citing works

Roles for Synonymous Codon Usage in Protein Biogenesis

Chaney, J. L., & Clark, P. L. (2015) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-060414-034333 · Cited by 306 · see citing works

Effect of Proline and Glycine Residues on Dynamics and Barriers of Loop Formation in Polypeptide Chains

Krieger, F., Möglich, A., & Kiefhaber, T. (2005) · Journal of the American Chemical Society · doi:10.1021/ja042798i · Cited by 261 · see citing works

MONSSTER: a method for folding globular proteins with a small number of distance restraints

Skolnick, J., Koliński, A., & Ortíz, Á. R. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0720 · Cited by 258 · see citing works

Synonymous but Not Silent: The Codon Usage Code for Gene Expression and Protein Folding

Liu, Y., Yang, Q., & Zhao, F. (2021) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-071320-112701 · Cited by 242 · see citing works

The Yin and Yang of codon usage

Komar, A. A. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw207 · Cited by 175 · see citing works

The influence of proline residues on α‐helical structure

Woolfson, D. N., & Williams, D. H. (1990) · FEBS Letters · doi:10.1016/0014-5793(90)80839-b · Cited by 158 · see citing works

Critical assessment of methods of protein structure prediction ( <scp>CASP</scp> )—Round <scp>XV</scp>

Kryshtafovych, A., Schwede, T., Topf, M., Fidelis, K., & Moult, J. (2023) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26617 · Cited by 148 · see citing works

The discretizable molecular distance geometry problem

Lavor, C., Liberti, L., Maculan, N., & Mucherino, A. (2011) · Computational Optimization and Applications · doi:10.1007/s10589-011-9402-6 · Cited by 142 · see citing works

The interval Branch-and-Prune algorithm for the discretizable molecular distance geometry problem with inexact distances

Lavor, C., Liberti, L., & Mucherino, A. (2011) · Journal of Global Optimization · doi:10.1007/s10898-011-9799-6 · Cited by 98 · see citing works

Protein Structure Prediction: Conventional and Deep Learning Perspectives

Jisna, V. A., & Jayaraj, P. B. (2021) · The Protein Journal · doi:10.1007/s10930-021-10003-y · Cited by 94 · see citing works

Improving fragment-based ab initio protein structure assembly using low-accuracy contact-map predictions

Mortuza, S. M., Zheng, W. H., Zhang, C., Li, Y., Pearce, R., & Zhang, Y. (2021) · Nature Communications · doi:10.1038/s41467-021-25316-w · Cited by 93 · see citing works

Universal similarity measure for comparing protein structures

Betancourt, M. R., & Skolnick, J. (2001) · Biopolymers · doi:10.1002/1097-0282(20011015)59:5 · Cited by 84 · see citing works

Weighting of experimental evidence in macromolecular structure determination

Habeck, M., Rieping, W., & Nilges, M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506412103 · Cited by 83 · see citing works

Inter-residue, inter-protein and inter-family coevolution: bridging the scales

Szurmant, H., & Weigt, M. (2018) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2017.10.014 · Cited by 81 · see citing works

Distance Geometry : Theory, Methods, and Applications

Mucherino, A., Lavor, C., Liberti, L., & Maculan, N. (2013) · HAL · doi:10.1007/978-1-4614-5128-0 · Cited by 74 · see citing works

Increasing the accuracy of single sequence prediction methods using a deep semi-supervised learning framework

Moffat, L., & Jones, D. T. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab491 · Cited by 69 · see citing works

The breakthrough in protein structure prediction

Lupas, A. N., Pereira, J., Alva, V., Merino, F., Coles, M. P., & Hartmann, M. D. (2021) · Biochemical Journal · doi:10.1042/bcj20200963 · Cited by 64 · see citing works

Reaching alignment-profile-based accuracy in predicting protein secondary and tertiary structural properties without alignment

Singh, J., Paliwal, K. K., Litfin, T., Singh, J., & Zhou, Y. (2022) · Scientific Reports · doi:10.1038/s41598-022-11684-w · Cited by 57 · see citing works

An algorithm to enumerate all possible protein conformations verifying a set of distance constraints

Cassioli, A., Bardiaux, B., Bouvier, G., Mucherino, A., Alves, R. S. D. O., Liberti, L., Nilges, M., Lavor, C., & Malliavin, T. E. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0451-1 · Cited by 53 · see citing works

Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon

Rosenberg, A. A., Marx, A., & Bronstein, A. M. (2022) · Nature Communications · doi:10.1038/s41467-022-30390-9 · Cited by 48 · see citing works

SPOT-1D-Single: improving the single-sequence-based prediction of protein secondary structure, backbone angles, solvent accessibility and half-sphere exposures using a large training set and ensembled deep learning

Singh, J., Litfin, T., Paliwal, K. K., Singh, J., Hanumanthappa, A. K., & Zhou, Y. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab316 · Cited by 47 · see citing works

Current approaches to flexible loop modeling

Barozet, A., Chacón, P., & Cortés, J. (2021) · Current Research in Structural Biology · doi:10.1016/j.crstbi.2021.07.002 · Cited by 41 · see citing works

Clifford Algebra and the Discretizable Molecular Distance Geometry Problem

Lavor, C., Alves, R. S. D. O., Figueiredo, W., Petraglia, A., & Maculan, N. (2015) · Advances in Applied Clifford Algebras · doi:10.1007/s00006-015-0532-2 · Cited by 39 · see citing works

Systematic Exploration of Protein Conformational Space Using a Distance Geometry Approach

Malliavin, T. E., Mucherino, A., Lavor, C., & Liberti, L. (2019) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.9b00215 · Cited by 39 · see citing works

A generic model of multi-class support vector machine

Guermeur, Y. (2012) · International Journal of Intelligent Information and Database Systems · doi:10.1504/ijiids.2012.050094 · Cited by 36 · see citing works

ProteinUnet —An efficient alternative to SPIDER3‐single for sequence‐based prediction of protein secondary structures

Kotowski, K., Smolarczyk, T., Roterman‐Konieczna, I., & Stąpor, K. (2020) · Journal of Computational Chemistry · doi:10.1002/jcc.26432 · Cited by 32 · see citing works

(φ,ψ)2 Motifs: A Purely Conformation-Based Fine-Grained Enumeration of Protein Parts at the Two-Residue Level

Hollingsworth, S. A., Lewis, M. C., Berkholz, D. S., Wong, W.-K., & Karplus, P. A. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2011.12.022 · Cited by 25 · see citing works

Bayesian estimation of NMR restraint potential and weight: A validation on a representative set of protein structures

Bernard, A., Vranken, W., Bardiaux, B., Nilges, M., & Malliavin, T. E. (2011) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22980 · Cited by 25 · see citing works

Revisiting Evaluation of Multiple Sequence Alignment Methods

Warnow, T. J. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-1036-7_17 · Cited by 21 · see citing works

New Error Measures and Methods for Realizing Protein Graphs from Distance Data

D’Ambrosio, C., Vu, K., Lavor, C., Liberti, L., & Maculan, N. (2017) · Discrete & Computational Geometry · doi:10.1007/s00454-016-9846-7 · Cited by 20 · see citing works

Tuning interval Branch-and-Prune for protein structure determination

Worley, B., Delhommel, F., Cordier, F., Malliavin, T. E., Bardiaux, B., Wolff, N., Nilges, M., Lavor, C., & Liberti, L. (2018) · Journal of Global Optimization · doi:10.1007/s10898-018-0635-0 · Cited by 19 · see citing works

An amino-domino model described by a cross-peptide-bond Ramachandran plot defines amino acid pairs as local structural units

Rosenberg, A. A., Yehishalom, N., Marx, A., & Bronstein, A. M. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2301064120 · Cited by 16 · see citing works

Structural and Dynamic Differences between Calreticulin Mutants Associated with Essential Thrombocythemia

Radjasandirane, R., & de Brevern, A. G. (2023) · Biomolecules · doi:10.3390/biom13030509 · Cited by 9 · see citing works

Local Backbone Geometry Plays a Critical Role in Determining Conformational Preferences of Amino Acid Residues in Proteins

Balasco, N., Esposito, L., Simone, A. D., & Vitagliano, L. (2022) · Biomolecules · doi:10.3390/biom12091184 · Cited by 7 · see citing works

PS4: A Next-Generation Dataset for Protein Single-Sequence Secondary Structure Prediction

Peracha, O. (2024) · BioTechniques · doi:10.2144/btn-2023-0024 · Cited by 7 · see citing works

Low-resolution description of the conformational space for intrinsically disordered proteins

Förster, G. D., Idier, J., Liberti, L., Mucherino, A., Lin, J., & Malliavin, T. E. (2022) · Scientific Reports · doi:10.1038/s41598-022-21648-9 · Cited by 6 · see citing works

Tandem domain structure determination based on a systematic enumeration of conformations

Malliavin, T. E. (2021) · Scientific Reports · doi:10.1038/s41598-021-96370-z · Cited by 6 · see citing works

Machine learning approaches demonstrate that protein structures carry information about their genetic coding

Ackerman-Schraier, L., Rosenberg, A. A., Marx, A., & Bronstein, A. M. (2022) · Scientific Reports · doi:10.1038/s41598-022-25874-z · Cited by 3 · see citing works

Exploration of Conformations for an Intrinsically Disordered Protein

Huang, S.-Y., Chang, C., Lin, J., & Malliavin, T. E. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-38299-4_55 · Cited by 1 · see citing works

FoldDoF: Utilizing the Primary Degrees of Freedom of Protein Backbone for Geometric Modeling and Generation

Zhu, Z., & Song, C. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c00617 · Cited by 1 · see citing works

Metabolomic Profiling and Bioactivity Evaluation of Rhodotorula Mucilaginosa Extract: Insights From In Vitro and In Silico Approaches

Soundararajan, S., Ranjan, J., Rosita, A. S., Prathiviraj, R., Sundararaju, M. P., Rajendran, D., Ashique, S., Sridhar, S. B., Panigrahy, U. P., Attar, J. R., et al. (2026) · Journal of Pharmaceutical Innovation · doi:10.1007/s12247-026-10832-3

Filtering Disordered Protein Conformations by NMR Residual Dipolar Couplings

Botnari, M., Sibille, N., Lin, J., & Malliavin, T. E. (2026) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.6c02007

Influence of the local amino acid sequence upon the zones of the torsional angles .phi. and .psi. adopted by residues in proteins

Gibrat, J.-F., Robson, B., & Garnier, J. (1991) · Biochemistry · doi:10.1021/bi00220a019 · Cited by 52 · see citing works

Prediction of protein structure from amino acid sequence.

Sternberg, M. J. E. (1986) · PubMed · Cited by 1 · see citing works

The prediction of protein structure from amino acid sequence

Sternberg, M. J. E., Cohen, F. E., & Taylor, W. R. (1981) · Acta Crystallographica Section A Foundations of Crystallography · doi:10.1107/s0108767381099017 · Cited by 12 · see citing works

A randomized algorithm for aligning DNA sequences to reference genomes

Rata, I., Wessells, K., & Li, Y. (2013)

Exploring the conformational space of proteins by enumeration in the frame of theDistance Geometry Problem

Malliavin, T. E. (2024) · HAL