Next Generation Protein Structure Predictions and Genetic Variant Interpretation

Basic local alignment search tool

Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669 · see citing works

VMD: visual molecular dynamics

Humphrey, W., Dalke, A., & Schulten, K. (1996) · Journal of Molecular Graphics · doi:10.1016/0263-7855(96)00018-5 · Cited by 66,952 · see citing works

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

Initial sequencing and analysis of the human genome

International Human Genome Sequencing Consortium, Whitehead Institute for Biomedical Research, C. F. G. R., Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C., Zody, M. C., Baldwin, J., Devon, K., Dewar, K., et al. (2001) · Nature · doi:10.1038/35057062 · Cited by 24,216 · see citing works

The sequence of the human genome

Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., Yandell, M., Evans, C. A., Holt, R. A., et al. (2001) · Science · doi:10.1126/science.1058040 · Cited by 13,909 · see citing works

A method and server for predicting damaging missense mutations.

Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194 · see citing works

SWISS-MODEL: homology modelling of protein structures and complexes

Waterhouse, A. M., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F. T., de Beer, T., Rempfer, C., Bordoli, L., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky427 · Cited by 13,005 · see citing works

Predicting transmembrane protein topology with a hidden markov model: application to complete genomes11Edited by F. Cohen

Krogh, A., Larsson, B., von Heijne, G., & Sonnhammer, E. L. L. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2000.4315 · Cited by 12,654 · see citing works

UniProt: a worldwide hub of protein knowledge

The UniProt Consortium (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1049 · Cited by 7,698 · see citing works

Pfam: The protein families database in 2021

Mistry, J., Chuguransky, S., Williams, L., Qureshi, M., Salazar, G. A., Sonnhammer, E. L. L., Tosatto, S. C. E., Paladin, L., Raj, S., Richardson, L. J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa913 · Cited by 7,452 · see citing works

COSMIC: the Catalogue Of Somatic Mutations In Cancer

Tate, J. G., Bamford, S., Jubb, H. C., Sondka, Z., Beare, D. M., Bindal, N., Boutselakis, H., Cole, C. G., Creatore, C., Dawson, E., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1015 · Cited by 4,867 · see citing works

SignalP 5.0 improves signal peptide predictions using deep neural networks

Armenteros, J. J. A., Tsirigos, K. D., Sønderby, C. K., Petersen, T. N., Winther, O., Brunak, S., von HEIJNE, G., & Nielsen, H. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0036-z · Cited by 4,206 · see citing works

Genetic effects on gene expression across human tissues

GTEx Consortium (2017) · Nature · doi:10.1038/nature24277 · Cited by 4,036 · see citing works

Predicting Functional Effect of Human Missense Mutations Using PolyPhen‐2

Adzhubei, I., Jordan, D. M., & Sunyaev, S. R. (2013) · Current Protocols in Human Genetics · doi:10.1002/0471142905.hg0720s76 · Cited by 3,705 · 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

Highly accurate protein structure prediction for the human proteome

Tunyasuvunakool, K., Adler, J., Wu, Z., Green, T., Zielinski, M., Žídek, A., Bridgland, A., Cowie, A., Meyer, C., Laydon, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03828-1 · Cited by 3,025 · see citing works

A Completely Reimplemented MPI Bioinformatics Toolkit with a New HHpred Server at its Core

Zimmermann, L., Stephens, A., Nam, S.-Z., Rau, D., Kübler, J., Lozajic, M., Gabler, F., Söding, J., Lupas, A. N., & Alva, V. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2017.12.007 · Cited by 2,522 · see citing works

SIFT web server: predicting effects of amino acid substitutions on proteins

Sim, N.-L., Kumar, P. N., Hu, J., Henikoff, S., Schneider, G., & Ng, P. C. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks539 · Cited by 2,419 · see citing works

HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment

Remmert, M., Biegert, A., Hauser, A., & Söding, J. (2012) · Nature Methods · doi:10.1038/nmeth.1818 · Cited by 2,288 · see citing works

Predicting the functional impact of protein mutations: application to cancer genomics

Reva, B. A., Antipin, Y., & Sander, C. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr407 · Cited by 1,987 · see citing works

Mass-spectrometry-based draft of the human proteome

Wilhelm, M., Schlegl, J., Hahne, H., Gholami, A. M., Lieberenz, M., Savitski, M. M., Ziegler, E., Butzmann, L., Gessulat, S., Marx, H., et al. (2014) · Nature · doi:10.1038/nature13319 · Cited by 1,820 · see citing works

UniRef: comprehensive and non-redundant UniProt reference clusters

Suzek, B. E., Huang, H., McGarvey, P., Mazumder, R., & Wu, C. H. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm098 · Cited by 1,613 · see citing works

Ensembl 2021

Howe, K. L., Achuthan, P., Allen, J. E., Allen, J., Álvarez-Jarreta, J., Amode, M., Armean, I., Azov, A., Bennett, R., Bhai, J., et al. (2020) · Nucleic Acids Res. · doi:10.1093/nar/gkaa942 · Cited by 1,355 · see citing works

HH-suite3 for fast remote homology detection and deep protein annotation

Steinegger, M., Meier, M., Mirdita, M., Vöhringer, H., Haunsberger, S. J., & Söding, J. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3019-7 · Cited by 1,145 · see citing works

ALSCRIPT: a tool to format multiple sequence alignments

Barton, G. J. (1993) · Protein Engineering Design and Selection · doi:10.1093/protein/6.1.37 · Cited by 1,144 · see citing works

ModBase, a database of annotated comparative protein structure models, and associated resources

Pieper, U., Webb, B., Barkan, D. T., Schneidman‐Duhovny, D., Schlessinger, A., Braberg, H., Yang, Z., Meng, E., Pettersen, E. F., Huang, C. C., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1091 · Cited by 1,069 · see citing works

Intrinsically Disordered Proteins and Intrinsically Disordered Protein Regions

Oldfield, C. J., & Dunker, A. K. (2014) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-072711-164947 · Cited by 1,057 · see citing works

One thousand families for the molecular biologist

Chothia, C. (1992) · Nature · doi:10.1038/357543a0 · Cited by 1,012 · see citing works

Single-particle cryo-EM at atomic resolution

Nakane, T., Kotecha, A., Sente, A., McMullan, G., Masiulis, S., Brown, P. M. G. E., Grigoras, I. T., Malinauskaitė, L., Malinauskas, T., Miehling, J., et al. (2020) · Nature · doi:10.1038/s41586-020-2829-0 · Cited by 881 · see citing works

Dissecting the genomic complexity underlying medulloblastoma

Jones, D. T. W., Jäger, N., Kool, M., Zichner, T., Hutter, B., Sultan, M., Cho, Y.-J., Pugh, T. J., Hovestadt, V., Stütz, A. M., et al. (2012) · Nature · doi:10.1038/nature11284 · Cited by 839 · see citing works

Multiple protein sequence alignment from tertiary structure comparison: Assignment of global and residue confidence levels

Russell, R. B., & Barton, G. J. (1992) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340140216 · Cited by 642 · see citing works

Attributes of short linear motifs

Davey, N. E., Roey, K. V., Weatheritt, R. J., Toedt, G., Uyar, B., Altenberg, B., Budd, A., Diella, F., Dinkel, H., & Gibson, T. J. (2011) · Molecular BioSystems · doi:10.1039/c1mb05231d · Cited by 626 · see citing works

Protein structure prediction from sequence variation

Marks, D. S., Hopf, T. A., & Sander, C. (2012) · Nature Biotechnology · doi:10.1038/nbt.2419 · Cited by 622 · see citing works

Green Algorithms: Quantifying the Carbon Footprint of Computation

Lannelongue, L., Grealey, J., & Inouye, M. (2021) · Advanced Science · doi:10.1002/advs.202100707 · Cited by 604 · see citing works

IUPred3: prediction of protein disorder enhanced with unambiguous experimental annotation and visualization of evolutionary conservation

Erdős, G., Pajkos, M., & Dosztányi, Z. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab408 · Cited by 588 · see citing works

Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study

Dewey, F. E., Murray, M. F., Overton, J. D., Habegger, L., Leader, J. B., Fetterolf, S. N., O’Dushlaine, C. T., Hout, C. V. V., Staples, J. C., Gonzaga-Jauregui, C. G., et al. (2016) · Science · doi:10.1126/science.aaf6814 · Cited by 533 · see citing works

‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures

Callaway, E. (2020) · Nature · doi:10.1038/d41586-020-03348-4 · Cited by 499 · see citing works

ELM--the database of eukaryotic linear motifs

Dinkel, H., Michael, S., Weatheritt, R. J., Davey, N. E., Roey, K. V., Altenberg, B., Toedt, G., Uyar, B., Seiler, M., Budd, A., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1064 · Cited by 439 · see citing works

Recurrent mutation of the ID3 gene in Burkitt lymphoma identified by integrated genome, exome and transcriptome sequencing

the ICGC MMML-Seq Project (2012) · Nature Genetics · doi:10.1038/ng.2469 · Cited by 435 · see citing works

Structural Aspects of the Fibrinogen to Fibrin Conversion

Doolittle, R. F. (1973) · Advances in protein chemistry · doi:10.1016/s0065-3233(08)60446-5 · Cited by 391 · see citing works

Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life

Peng, Z., Yan, J. R., Fan, X., Mizianty, M. J., Xue, B., Wang, K., Hu, G., Uversky, V. N., & Kurgan, L. (2014) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-014-1661-9 · Cited by 382 · see citing works

ModBase, a database of annotated comparative protein structure models and associated resources

Pieper, U., Webb, B., Dong, G. Q., Schneidman‐Duhovny, D., Fan, H., Kim, S. J., Khuri, N., Spill, Y. G., Weinkam, P., Hammel, M., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1144 · Cited by 323 · see citing works

The revolution will not be crystallized: a new method sweeps through structural biology

Callaway, E. (2015) · Nature · doi:10.1038/525172a · Cited by 291 · see citing works

Biophysical experiments and biomolecular simulations: A perfect match?

Bottaro, S., & Lindorff‐Larsen, K. (2018) · Science · doi:10.1126/science.aat4010 · Cited by 285 · see citing works

Correction: Corrigendum: TCTEX1D2 mutations underlie Jeune asphyxiating thoracic dystrophy with impaired retrograde intraflagellar transport

Schmidts, M., Hou, Y., Cortés, C. R., et al. (2016) · Nature Communications · doi:10.1038/ncomms11270 · Cited by 260 · see citing works

SIFTS: updated Structure Integration with Function, Taxonomy and Sequences resource allows 40-fold increase in coverage of structure-based annotations for proteins

Dana, J., Gutmanas, A., Tyagi, N., Qi, G., O'Donovan, C., Martin, M., & Velankar, S. (2018) · Nucleic Acids Res. · doi:10.1093/nar/gky1114 · Cited by 258 · see citing works

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

Boldt, K., van Reeuwijk, J., Lu, Q., Koutroumpas, K., Nguyen, T.-M. T., Texier, Y., van Beersum, S. E. C., Horn, N., Willer, J. R., Mans, D. A., et al. (2016) · Nature Communications · doi:10.1038/ncomms11491 · Cited by 240 · see citing works

Phylogenetic patterns of emergence of new genes support a model of frequent de novo evolution

Neme, R., & Tautz, D. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-117 · Cited by 220 · see citing works

Critical assessment of methods of protein structure prediction (CASP)—round IX

Moult, J., Fidelis, K. A., Kryshtafovych, A., & Tramontano, A. L. (2011) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.23200 · Cited by 211 · see citing works

Ten thousand interactions for the molecular biologist

Aloy, P., & Russell, R. B. (2004) · Nature Biotechnology · doi:10.1038/nbt1018 · Cited by 191 · see citing works

Processing and evaluation of predictions in CASP4

Zemla, A. T., Venclovas, ?., Moult, J., & Fidelis, K. A. (2001) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10052 · Cited by 156 · see citing works

Evolution of modular intraflagellar transport from a coatomer-like progenitor

van Dam, T. J. P., Townsend, M. J., Turk, M., Schlessinger, A., Šali, A., Field, M. C., & Huynen, M. A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1221011110 · Cited by 152 · see citing works

Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma

López, C., Kleinheinz, K., Aukema, S., Rohde, M., Bernhart, S. H., Hübschmann, D., Wagener, R., Toprak, U. H., Raimondi, F., Kreuz, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08578-3 · Cited by 151 · see citing works

3did: identification and classification of domain-based interactions of known three-dimensional structure

Stein, A., Ceol, A. G. M., & Aloy, P. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq962 · Cited by 142 · see citing works

Towards the prediction of protein interaction partners using physical docking

Wass, M., Fuentes, G., Pons, C., Pazos, F., & Valencia, A. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.3 · Cited by 129 · see citing works

Shining a light on structural genomics

Kim, S. H. (1998) · Nature Structural Biology · doi:10.1038/1334 · Cited by 120 · see citing works

The pathway to GTPase activation of elongation factor SelB on the ribosome

Fischer, N., Neumann, P., Bock, L. V., Maracci, C., Wang, Z., Paleskava, A., Konevega, A. L., Schroeder, G. F., Grubmüller, H., Ficner, R., et al. (2016) · Nature · doi:10.1038/nature20560 · Cited by 116 · see citing works

The Many Faces of Protein–Protein Interactions: A Compendium of Interface Geometry

Kim, W., Henschel, A., Winter, C., & Schroeder, M. (2006) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0020124 · Cited by 112 · see citing works

Architectures and Functional Coverage of Protein–Protein Interfaces

Tunçbağ, N., Gürsoy, A., Güney, E., Nussinov, R., & Keskin, Ö. (2008) · Journal of Molecular Biology · doi:10.1016/j.jmb.2008.04.071 · Cited by 109 · see citing works

Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions

Betts, M. J., Lu, Q., Jiang, Y., Drusko, A., Wichmann, O., Utz, M., Valtierra-Gutiérrez, I. A., Schlesner, M., Jäger, N., Jones, D., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1094 · Cited by 90 · see citing works

Proteome-wide analysis of human disease mutations in short linear motifs: neglected players in cancer?

Uyar, B., Weatheritt, R. J., Dinkel, H., Davey, N. E., & Gibson, T. J. (2014) · Molecular BioSystems · doi:10.1039/c4mb00290c · Cited by 87 · see citing works

Defining clinical subgroups and genotype–phenotype correlations in NBAS-associated disease across 110 patients

Staufner, C., Peters, B., Wagner, M., et al. (2019) · Genetics in Medicine · doi:10.1038/s41436-019-0698-4 · Cited by 70 · see citing works

The impact of structural genomics: the first quindecennial

Grabowski, M., Niedzialkowska, E., Zimmerman, M., & Minor, W. (2016) · Journal of Structural and Functional Genomics · doi:10.1007/s10969-016-9201-5 · Cited by 67 · see citing works

Rare, functional, somatic variants in gene families linked to cancer genes: GPCR signaling as a paradigm

Raimondi, F., Inoue, A., Kadji, F. M. N., Ni, S., González‐Sánchez, J. C., Singh, G., de la Vega, A. A., Sotillo, R., Fischer, B., Aoki, J., et al. (2019) · Oncogene · doi:10.1038/s41388-019-0895-2 · Cited by 30 · see citing works

A New Wave of Genomics for All

Crow, D. (2019) · Cell · doi:10.1016/j.cell.2019.02.041 · Cited by 20 · see citing works

Genetic variants affecting equivalent protein family positions reflect human diversity

Raimondi, F., Betts, M. J., Lu, Q., Inoue, A., Gutkind, J. S., & Russell, R. B. (2017) · Scientific Reports · doi:10.1038/s41598-017-12971-7 · Cited by 14 · see citing works

The carbon footprint of bioinformaticsPreprint

Grealey, J., Lannelongue, L., Saw, W., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.08.434372 · Cited by 9 · see citing works

Mechnetor: a web server for exploring protein mechanism and the functional context of genetic variants

González‐Sánchez, J. C., Ibrahim, M. F. R., Leist, I. C., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab399 · Cited by 6 · see citing works

Structural genomics in the Spotlight

Gabanyi, M. J. (2009) · PSI Structural Genomics Knowledgebase · doi:10.1038/nw_psisgkb.2009.62 · Cited by 2 · see citing works

Structural genomics in the spotlight

(2008) · Nature Methods · doi:10.1038/nmeth0208-115 · Cited by 1 · see citing works

AlphaFold, Artificial Intelligence (AI), and Allostery

Nussinov, R., Zhang, M., Liu, Y., & Jang, H. (2022) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.2c04346 · Cited by 190 · see citing works

AlphaFold heralds a data-driven revolution in biology and medicine

Thornton, J. M., Laskowski, R. A., & Borkakoti, N. (2021) · Nature Medicine · doi:10.1038/s41591-021-01533-0 · Cited by 185 · see citing works

The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins

Agarwal, V., & McShan, A. C. (2024) · Nature Chemical Biology · doi:10.1038/s41589-024-01638-w · Cited by 155 · see citing works

Predicting the pathogenicity of missense variants using features derived from AlphaFold2

Schmidt, A., Röner, S., Mai, K., Klinkhammer, H., Kircher, M., & Ludwig, K. U. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad280 · Cited by 79 · see citing works

The X-ray crystallography phase problem solved thanks to <i>AlphaFold</i> and <i>RoseTTAFold</i> models: a case-study report

Barbarin-Bocahu, I., & Graille, M. (2022) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798322002157 · Cited by 52 · see citing works

A high-stringency blueprint of the human proteome

Adhikari, S., Nice, E. C., Deutsch, E. W., Lane, L., Omenn, G. S., Pennington, S. R., Paik, Y.-K., Overall, C. M., Corrales, F. J., Cristea, I. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19045-9 · Cited by 210 · see citing works

The human eye proteome project

Omenn, G. S. (2013) · PROTEOMICS · doi:10.1002/pmic.201300255 · Cited by 9 · see citing works

Human Proteome Project and Current Bioinformatics Status in Disease Diagnosis and Treatment

Anwar, P., Javed, A., Amjad, I., Arif, I., Sadiqa, A., Akram, H., & Azhar, L. (2018) · Journal of Proteomics and Genomics research · doi:10.14302/issn.2326-0793.jpgr-18-2004 · Cited by 1 · see citing works

Indian proteomics efforts and human proteome project

Sirdeshmukh, R. (2015) · Journal of Proteomics · doi:10.1016/j.jprot.2015.03.018 · Cited by 4 · see citing works

HICL table can manipulate all proteins in human complete proteomePreprint

Xie, Z. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/093971