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\n  \n 2021\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n PDBrenum: A webserver and program providing Protein Data Bank files renumbered according to their UniProt sequences.\n \n \n \n\n\n \n Faezov, B.; and Dunbrack, R.\n\n\n \n\n\n\n PLoS ONE, 16(7 July). 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{\n title = {PDBrenum: A webserver and program providing Protein Data Bank files renumbered according to their UniProt sequences},\n type = {article},\n year = {2021},\n volume = {16},\n id = {63684916-7b6d-3735-9ed2-64197390c318},\n created = {2022-04-14T19:22:42.189Z},\n file_attached = {false},\n profile_id = {15907a83-415d-372c-9535-a6ff3937b322},\n last_modified = {2022-04-14T19:22:42.189Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n private_publication = {true},\n abstract = {The Protein Data Bank (PDB) was established at Brookhaven National Laboratories in 1971 as an archive for biological macromolecular crystal structures. In mid 2021, the database has almost 180,000 structures solved by X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and other methods. Many proteins have been studied under different conditions, including binding partners such as ligands, nucleic acids, or other proteins; mutations, and post-Translational modifications, thus enabling extensive comparative structure-function studies. However, these studies are made more difficult because authors are allowed by the PDB to number the amino acids in each protein sequence in any manner they wish. This results in the same protein being numbered differently in the available PDB entries. For instance, some authors may include N-Terminal signal peptides or the N-Terminal methionine in the sequence numbering and others may not. In addition to the coordinates, there are many fields that contain structural and functional information regarding specific residues numbered according to the author. Here we provide a webserver and Python3 application that fixes the PDB sequence numbering problem by replacing the author numbering with numbering derived from the corresponding UniProt sequences. We obtain this correspondence from the SIFTS database from PDBe. The server and program can take a list of PDB entries or a list of UniProt identifiers (e.g., "P04637"or "P53-HUMAN") and provide renumbered files in mmCIF format and the legacy PDB format for both asymmetric unit files and biological assembly files provided by PDBe.},\n bibtype = {article},\n author = {Faezov, B. and Dunbrack, R.L.},\n doi = {10.1371/journal.pone.0253411},\n journal = {PLoS ONE},\n number = {7 July}\n}
\n
\n\n\n
\n The Protein Data Bank (PDB) was established at Brookhaven National Laboratories in 1971 as an archive for biological macromolecular crystal structures. In mid 2021, the database has almost 180,000 structures solved by X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and other methods. Many proteins have been studied under different conditions, including binding partners such as ligands, nucleic acids, or other proteins; mutations, and post-Translational modifications, thus enabling extensive comparative structure-function studies. However, these studies are made more difficult because authors are allowed by the PDB to number the amino acids in each protein sequence in any manner they wish. This results in the same protein being numbered differently in the available PDB entries. For instance, some authors may include N-Terminal signal peptides or the N-Terminal methionine in the sequence numbering and others may not. In addition to the coordinates, there are many fields that contain structural and functional information regarding specific residues numbered according to the author. Here we provide a webserver and Python3 application that fixes the PDB sequence numbering problem by replacing the author numbering with numbering derived from the corresponding UniProt sequences. We obtain this correspondence from the SIFTS database from PDBe. The server and program can take a list of PDB entries or a list of UniProt identifiers (e.g., \"P04637\"or \"P53-HUMAN\") and provide renumbered files in mmCIF format and the legacy PDB format for both asymmetric unit files and biological assembly files provided by PDBe.\n
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\n \n\n \n \n \n \n \n Musashi-2 (MSI2) regulates epidermal growth factor receptor (EGFR) expression and response to EGFR inhibitors in EGFR-mutated non-small cell lung cancer (NSCLC).\n \n \n \n\n\n \n Makhov, P.; Bychkov, I.; Faezov, B.; Deneka, A.; Kudinov, A.; Nicolas, E.; Brebion, R.; Avril, E.; Cai, K.; Kharin, L.; Voloshin, M.; Frantsiyants, E.; Karnaukhov, N.; Kit, O.; Topchu, I.; Fazliyeva, R.; Nikonova, A.; Serebriiskii, I.; Borghaei, H.; Edelman, M.; Dulaimi, E.; Golemis, E.; and Boumber, Y.\n\n\n \n\n\n\n Oncogenesis, 10(3). 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{\n title = {Musashi-2 (MSI2) regulates epidermal growth factor receptor (EGFR) expression and response to EGFR inhibitors in EGFR-mutated non-small cell lung cancer (NSCLC)},\n type = {article},\n year = {2021},\n volume = {10},\n id = {67e56ced-1b53-3027-8e41-193e6a7b0439},\n created = {2022-04-14T19:22:42.242Z},\n file_attached = {false},\n profile_id = {15907a83-415d-372c-9535-a6ff3937b322},\n last_modified = {2022-04-14T19:22:42.242Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n private_publication = {true},\n abstract = {Non-small cell lung cancer (NSCLC) has limited treatment options. Expression of the RNA-binding protein (RBP) Musashi-2 (MSI2) is elevated in a subset of non-small cell lung cancer (NSCLC) tumors upon progression, and drives NSCLC metastasis. We evaluated the mechanism of MSI2 action in NSCLC to gain therapeutically useful insights. Reverse phase protein array (RPPA) analysis of MSI2-depleted versus control KrasLA1/+; Trp53R172HΔG/+ NSCLC cell lines identified EGFR as a MSI2-regulated protein. MSI2 control of EGFR expression and activity in an NSCLC cell line panel was studied using RT-PCR, Western blots, and RNA immunoprecipitation. Functional consequences of MSI2 depletion were explored for cell growth and response to EGFR-targeting drugs, in vitro and in vivo. Expression relationships were validated using human tissue microarrays. MSI2 depletion significantly reduced EGFR protein expression, phosphorylation, or both. Comparison of protein and mRNA expression indicated a post-transcriptional activity of MSI2 in control of steady state levels of EGFR. RNA immunoprecipitation analysis demonstrated that MSI2 directly binds to EGFR mRNA, and sequence analysis predicted MSI2 binding sites in the murine and human EGFR mRNAs. MSI2 depletion selectively impaired cell proliferation in NSCLC cell lines with activating mutations of EGFR (EGFRmut). Further, depletion of MSI2 in combination with EGFR inhibitors such as erlotinib, afatinib, and osimertinib selectively reduced the growth of EGFRmut NSCLC cells and xenografts. EGFR and MSI2 were significantly co-expressed in EGFRmut human NSCLCs. These results define MSI2 as a direct regulator of EGFR protein expression, and suggest inhibition of MSI2 could be of clinical value in EGFRmut NSCLC.},\n bibtype = {article},\n author = {Makhov, P. and Bychkov, I. and Faezov, B. and Deneka, A. and Kudinov, A. and Nicolas, E. and Brebion, R. and Avril, E. and Cai, K.Q. and Kharin, L.V. and Voloshin, M. and Frantsiyants, E. and Karnaukhov, N. and Kit, O.I. and Topchu, I. and Fazliyeva, R. and Nikonova, A.S. and Serebriiskii, I.G. and Borghaei, H. and Edelman, M. and Dulaimi, E. and Golemis, E.A. and Boumber, Y.},\n doi = {10.1038/s41389-021-00317-y},\n journal = {Oncogenesis},\n number = {3}\n}
\n
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\n Non-small cell lung cancer (NSCLC) has limited treatment options. Expression of the RNA-binding protein (RBP) Musashi-2 (MSI2) is elevated in a subset of non-small cell lung cancer (NSCLC) tumors upon progression, and drives NSCLC metastasis. We evaluated the mechanism of MSI2 action in NSCLC to gain therapeutically useful insights. Reverse phase protein array (RPPA) analysis of MSI2-depleted versus control KrasLA1/+; Trp53R172HΔG/+ NSCLC cell lines identified EGFR as a MSI2-regulated protein. MSI2 control of EGFR expression and activity in an NSCLC cell line panel was studied using RT-PCR, Western blots, and RNA immunoprecipitation. Functional consequences of MSI2 depletion were explored for cell growth and response to EGFR-targeting drugs, in vitro and in vivo. Expression relationships were validated using human tissue microarrays. MSI2 depletion significantly reduced EGFR protein expression, phosphorylation, or both. Comparison of protein and mRNA expression indicated a post-transcriptional activity of MSI2 in control of steady state levels of EGFR. RNA immunoprecipitation analysis demonstrated that MSI2 directly binds to EGFR mRNA, and sequence analysis predicted MSI2 binding sites in the murine and human EGFR mRNAs. MSI2 depletion selectively impaired cell proliferation in NSCLC cell lines with activating mutations of EGFR (EGFRmut). Further, depletion of MSI2 in combination with EGFR inhibitors such as erlotinib, afatinib, and osimertinib selectively reduced the growth of EGFRmut NSCLC cells and xenografts. EGFR and MSI2 were significantly co-expressed in EGFRmut human NSCLCs. These results define MSI2 as a direct regulator of EGFR protein expression, and suggest inhibition of MSI2 could be of clinical value in EGFRmut NSCLC.\n
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\n\n\n
\n \n\n \n \n \n \n \n PDBrenum: A webserver and program providing Protein Data Bank files renumbered according to their UniProt sequences.\n \n \n \n\n\n \n Faezov, B.; and Dunbrack, R.\n\n\n \n\n\n\n 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@misc{\n title = {PDBrenum: A webserver and program providing Protein Data Bank files renumbered according to their UniProt sequences},\n type = {misc},\n year = {2021},\n source = {bioRxiv},\n id = {656ec7a0-cc36-35d1-8a21-c6b7b85aa35b},\n created = {2022-04-14T19:22:42.258Z},\n file_attached = {false},\n profile_id = {15907a83-415d-372c-9535-a6ff3937b322},\n last_modified = {2022-04-14T19:22:42.258Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n private_publication = {true},\n abstract = {The Protein Data Bank (PDB) was established at Brookhaven National Laboratories in 1971 as an archive for biological macromolecular crystal structures. In the beginning the archive held only seven structures but in early 2021, the database has more than 170,000 structures solved by X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and other methods. Many proteins have been studied under different conditions (e.g., binding partners such as ligands, nucleic acids, or other proteins; mutations and post-translational modifications), thus enabling comparative structure-function studies. However, these studies are made more difficult because authors are allowed by the PDB to number the amino acids in each protein sequence in any manner they wish. This results in the same protein being numbered differently in the available PDB entries. In addition to the coordinates, there are many fields that contain information regarding specific residues in the sequence of each protein in the entry. Here we provide a webserver and Python3 application that fixes the PDB sequence numbering problem by replacing the author numbering with numbering derived from the corresponding UniProt sequences. We obtain this correspondence from the SIFTS database from PDBe. The server and program can take a list of PDB entries and provide renumbered files in mmCIF format and the legacy PDB format for both asymmetric unit files and biological assembly files provided by PDBe. The server can also take a list of UniProt identifiers (“P04637” or “P53_HUMAN”) and return the desired files. Availability: Source code is freely available at https://github.com/Faezov/PDBrenum. The webserver is located at: http://dunbrack3.fccc.edu/PDBrenum. Contact: bulat.faezov@fccc.edu or roland.dunbrack@fccc.edu.},\n bibtype = {misc},\n author = {Faezov, B. and Dunbrack, R.L.},\n doi = {10.1101/2021.02.14.431128}\n}
\n
\n\n\n
\n The Protein Data Bank (PDB) was established at Brookhaven National Laboratories in 1971 as an archive for biological macromolecular crystal structures. In the beginning the archive held only seven structures but in early 2021, the database has more than 170,000 structures solved by X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and other methods. Many proteins have been studied under different conditions (e.g., binding partners such as ligands, nucleic acids, or other proteins; mutations and post-translational modifications), thus enabling comparative structure-function studies. However, these studies are made more difficult because authors are allowed by the PDB to number the amino acids in each protein sequence in any manner they wish. This results in the same protein being numbered differently in the available PDB entries. In addition to the coordinates, there are many fields that contain information regarding specific residues in the sequence of each protein in the entry. Here we provide a webserver and Python3 application that fixes the PDB sequence numbering problem by replacing the author numbering with numbering derived from the corresponding UniProt sequences. We obtain this correspondence from the SIFTS database from PDBe. The server and program can take a list of PDB entries and provide renumbered files in mmCIF format and the legacy PDB format for both asymmetric unit files and biological assembly files provided by PDBe. The server can also take a list of UniProt identifiers (“P04637” or “P53_HUMAN”) and return the desired files. Availability: Source code is freely available at https://github.com/Faezov/PDBrenum. The webserver is located at: http://dunbrack3.fccc.edu/PDBrenum. Contact: bulat.faezov@fccc.edu or roland.dunbrack@fccc.edu.\n
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