Post-Docking Refinement of Peptide or Protein-RNA Complexes Using Thermal Titration Molecular Dynamics (TTMD): A Stability Insight

被引:0
作者
Dodaro, Andrea [1 ]
Novello, Gianluca [1 ]
Menin, Silvia [1 ]
Strascia, Chiara Cavastracci [1 ]
Sturlese, Mattia [1 ]
Salmaso, Veronica [1 ]
Moro, Stefano [1 ]
机构
[1] Univ Padua, Dept Pharmaceut & Pharmacol Sci, Mol Modeling Sect MMS, I-35131 Padua, Italy
关键词
RESPONSE ELEMENT RRE; HK022 NUN PROTEIN; RIBOSOMAL-PROTEIN; BINDING; S8; RECOGNITION; MECHANISM; RELEVANT;
D O I
10.1021/acs.jcim.4c01393
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
RNA-protein interactions drive and regulate fundamental cellular processes like transcription and translation. Despite being still limited, the growing body of structural data significantly contributes to the characterization of these interactions. However, RNA complexes involving proteins or peptides are not always available due to the structural determination challenges that this biopolymer entails. Consequently, modeling approaches like molecular docking are exploited to generate complexes relevant to structural and pharmaceutical purposes, including analysis of putative drug targets. Docking methods, despite their widespread adoption, are often hindered by limitations in scoring accuracy, which affects the ranking of the generated poses. Postdocking refining methods, including molecular dynamics (MD) approaches, have been developed to tackle this issue. Thermal Titration Molecular Dynamics (TTMD) is an enhanced sampling molecular dynamics technique that has been previously effectively applied to refine protein or RNA-small-molecule docking poses. This study presents the first application of TTMD to RNA-peptide complexes, validating this method on more complex systems and extending its applicability domain. Our findings showcase the capability of this technique to refine peptide-RNA docking poses, correctly identifying native binding modes among decoys for different pharmaceutically relevant targets.
引用
收藏
页码:1441 / 1452
页数:12
相关论文
共 75 条
  • [1] Targeting Tat-TAR RNA Interaction for HIV-1 Inhibition
    Alanazi, Awadh
    Ivanov, Andrey
    Kumari, Namita
    Lin, Xionghao
    Wang, Songping
    Kovalskyy, Dmytro
    Nekhai, Sergei
    [J]. VIRUSES-BASEL, 2021, 13 (10):
  • [2] [Anonymous], BARNABA SOFTWARE ANA
  • [3] alpha helix-RNA major groove recognition in an HIV-1 Rev peptide RRE RNA complex
    Battiste, JL
    Mao, HY
    Rao, NS
    Tan, RY
    Muhandiram, DR
    Kay, LE
    Frankel, AD
    Williamson, JR
    [J]. SCIENCE, 1996, 273 (5281) : 1547 - 1551
  • [4] The Protein Data Bank
    Berman, HM
    Westbrook, J
    Feng, Z
    Gilliland, G
    Bhat, TN
    Weissig, H
    Shindyalov, IN
    Bourne, PE
    [J]. NUCLEIC ACIDS RESEARCH, 2000, 28 (01) : 235 - 242
  • [5] The role of nucleobase interactions in RNA structure and dynamics
    Bottaro, Sandro
    Di Palma, Francesco
    Bussi, Giovanni
    [J]. NUCLEIC ACIDS RESEARCH, 2014, 42 (21) : 13306 - 13314
  • [6] ProLIF: a library to encode molecular interactions as fingerprints
    Bouysset, Cedric
    Fiorucci, Sebastien
    [J]. JOURNAL OF CHEMINFORMATICS, 2021, 13 (01)
  • [7] Case D. A., 2022, AMBERTOOLS22
  • [8] The Amber biomolecular simulation programs
    Case, DA
    Cheatham, TE
    Darden, T
    Gohlke, H
    Luo, R
    Merz, KM
    Onufriev, A
    Simmerling, C
    Wang, B
    Woods, RJ
    [J]. JOURNAL OF COMPUTATIONAL CHEMISTRY, 2005, 26 (16) : 1668 - 1688
  • [9] Efficient conformational sampling and weak scoring in docking programs? Strategy of the wisdom of crowds
    Chaput, Ludovic
    Mouawad, Liliane
    [J]. JOURNAL OF CHEMINFORMATICS, 2017, 9
  • [10] Cyclization and Docking Protocol for Cyclic Peptide-Protein Modeling Using HADDOCK2.4
    Charitou, Vicky
    van Keulen, Siri C.
    Bonvin, Alexandre M. J. J.
    [J]. JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2022, 18 (06) : 4027 - 4040