Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking

One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we te...
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Autor*in:	Mateusz Zalewski [verfasserIn] Sebastian Kmiecik [verfasserIn] Michał Koliński [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	model scoring protein–peptide docking molecular dynamics CABS-dock coarse-grained docking

Übergeordnetes Werk:	In: Molecules - MDPI AG, 2003, 26(2021), 11, p 3293
Übergeordnetes Werk:	volume:26 ; year:2021 ; number:11, p 3293

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/molecules26113293

Katalog-ID:	DOAJ068873816

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520			\|a One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures.
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allfields	10.3390/molecules26113293 doi (DE-627)DOAJ068873816 (DE-599)DOAJ609adcd00fdd46d8a9923ee5225ff2b7 DE-627 ger DE-627 rakwb eng QD241-441 Mateusz Zalewski verfasserin aut Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures. model scoring protein–peptide docking molecular dynamics CABS-dock coarse-grained docking Organic chemistry Sebastian Kmiecik verfasserin aut Michał Koliński verfasserin aut In Molecules MDPI AG, 2003 26(2021), 11, p 3293 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:26 year:2021 number:11, p 3293 https://doi.org/10.3390/molecules26113293 kostenfrei https://doaj.org/article/609adcd00fdd46d8a9923ee5225ff2b7 kostenfrei https://www.mdpi.com/1420-3049/26/11/3293 kostenfrei https://doaj.org/toc/1420-3049 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 26 2021 11, p 3293
spelling	10.3390/molecules26113293 doi (DE-627)DOAJ068873816 (DE-599)DOAJ609adcd00fdd46d8a9923ee5225ff2b7 DE-627 ger DE-627 rakwb eng QD241-441 Mateusz Zalewski verfasserin aut Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures. model scoring protein–peptide docking molecular dynamics CABS-dock coarse-grained docking Organic chemistry Sebastian Kmiecik verfasserin aut Michał Koliński verfasserin aut In Molecules MDPI AG, 2003 26(2021), 11, p 3293 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:26 year:2021 number:11, p 3293 https://doi.org/10.3390/molecules26113293 kostenfrei https://doaj.org/article/609adcd00fdd46d8a9923ee5225ff2b7 kostenfrei https://www.mdpi.com/1420-3049/26/11/3293 kostenfrei https://doaj.org/toc/1420-3049 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 26 2021 11, p 3293
allfields_unstemmed	10.3390/molecules26113293 doi (DE-627)DOAJ068873816 (DE-599)DOAJ609adcd00fdd46d8a9923ee5225ff2b7 DE-627 ger DE-627 rakwb eng QD241-441 Mateusz Zalewski verfasserin aut Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures. model scoring protein–peptide docking molecular dynamics CABS-dock coarse-grained docking Organic chemistry Sebastian Kmiecik verfasserin aut Michał Koliński verfasserin aut In Molecules MDPI AG, 2003 26(2021), 11, p 3293 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:26 year:2021 number:11, p 3293 https://doi.org/10.3390/molecules26113293 kostenfrei https://doaj.org/article/609adcd00fdd46d8a9923ee5225ff2b7 kostenfrei https://www.mdpi.com/1420-3049/26/11/3293 kostenfrei https://doaj.org/toc/1420-3049 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 26 2021 11, p 3293
allfieldsGer	10.3390/molecules26113293 doi (DE-627)DOAJ068873816 (DE-599)DOAJ609adcd00fdd46d8a9923ee5225ff2b7 DE-627 ger DE-627 rakwb eng QD241-441 Mateusz Zalewski verfasserin aut Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures. model scoring protein–peptide docking molecular dynamics CABS-dock coarse-grained docking Organic chemistry Sebastian Kmiecik verfasserin aut Michał Koliński verfasserin aut In Molecules MDPI AG, 2003 26(2021), 11, p 3293 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:26 year:2021 number:11, p 3293 https://doi.org/10.3390/molecules26113293 kostenfrei https://doaj.org/article/609adcd00fdd46d8a9923ee5225ff2b7 kostenfrei https://www.mdpi.com/1420-3049/26/11/3293 kostenfrei https://doaj.org/toc/1420-3049 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 26 2021 11, p 3293
allfieldsSound	10.3390/molecules26113293 doi (DE-627)DOAJ068873816 (DE-599)DOAJ609adcd00fdd46d8a9923ee5225ff2b7 DE-627 ger DE-627 rakwb eng QD241-441 Mateusz Zalewski verfasserin aut Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures. model scoring protein–peptide docking molecular dynamics CABS-dock coarse-grained docking Organic chemistry Sebastian Kmiecik verfasserin aut Michał Koliński verfasserin aut In Molecules MDPI AG, 2003 26(2021), 11, p 3293 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:26 year:2021 number:11, p 3293 https://doi.org/10.3390/molecules26113293 kostenfrei https://doaj.org/article/609adcd00fdd46d8a9923ee5225ff2b7 kostenfrei https://www.mdpi.com/1420-3049/26/11/3293 kostenfrei https://doaj.org/toc/1420-3049 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 26 2021 11, p 3293
language	English
source	In Molecules 26(2021), 11, p 3293 volume:26 year:2021 number:11, p 3293
sourceStr	In Molecules 26(2021), 11, p 3293 volume:26 year:2021 number:11, p 3293
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	model scoring protein–peptide docking molecular dynamics CABS-dock coarse-grained docking Organic chemistry
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container_title	Molecules
authorswithroles_txt_mv	Mateusz Zalewski @@aut@@ Sebastian Kmiecik @@aut@@ Michał Koliński @@aut@@
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callnumber-first	Q - Science
author	Mateusz Zalewski
spellingShingle	Mateusz Zalewski misc QD241-441 misc model scoring misc protein–peptide docking misc molecular dynamics misc CABS-dock misc coarse-grained docking misc Organic chemistry Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking
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topic_title	QD241-441 Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking model scoring protein–peptide docking molecular dynamics CABS-dock coarse-grained docking
topic	misc QD241-441 misc model scoring misc protein–peptide docking misc molecular dynamics misc CABS-dock misc coarse-grained docking misc Organic chemistry
topic_unstemmed	misc QD241-441 misc model scoring misc protein–peptide docking misc molecular dynamics misc CABS-dock misc coarse-grained docking misc Organic chemistry
topic_browse	misc QD241-441 misc model scoring misc protein–peptide docking misc molecular dynamics misc CABS-dock misc coarse-grained docking misc Organic chemistry
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title	Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking
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title_full	Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking
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title_sort	molecular dynamics scoring of protein–peptide models derived from coarse-grained docking
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title_auth	Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking
abstract	One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures.
abstractGer	One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures.
abstract_unstemmed	One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures.
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title_short	Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking
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Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking

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