Background
The understanding of the importance of RNA has dramatically changed over recent years. As in the case of proteins, the function of an RNA molecule is encoded in its tertiary structure, which in turn is determined by the molecule's sequence. The prediction of tertiary structures of complex RNAs is still a challenging task.
Results
Using the observation that RNA sequences from the same RNA family fold into conserved structure, we test herein whether parallel modeling of RNA homologs can improve ab initio RNA structure prediction method. EvoClustRNA is a multi-step modeling process, in which homologous sequences for the target sequence are selected using the Rfam database. Subsequently, independent folding simulations using Rosetta FARFAR and SimRNA are carried out. The model of the target sequence is selected based on the most common structural arrangement of the common helical fragments. As a test, on two blind RNA-Puzzles challenges, EvoClustRNA predictions ranked as the first of all submissions for the L-glutamine riboswitch and as the second for the ZMP riboswitch. Moreover, through a benchmark of known structures, we discovered several cases in which particular homologs were unusually amenable to structure recovery in folding simulations compared to the single original target sequence.
Conclusion
This work, for the first time to our knowledge, demonstrates how important is the selection of the target sequence from an alignment of an RNA family for the success of RNA 3D structure prediction. These observations prompt investigations into a new direction of research for checking 3D structure “foldability” or “predictability” of related RNA sequences to obtain accurate predictions. To support new research in this area, we provide all relevant scripts in a documented and ready-to-use form. By exploring new ideas and identification of limitations of the current RNA 3D structure prediction methods, this work is bringing us closer to the near-native computational RNA 3D models.

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This is a list of supplementary files associated with this preprint. Click to download.
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On 01 Oct, 2019
On 30 Sep, 2019
On 29 Sep, 2019
On 29 Sep, 2019
On 22 Sep, 2019
Invitations sent on 20 Sep, 2019
On 20 Sep, 2019
Received 20 Sep, 2019
On 19 Sep, 2019
On 18 Sep, 2019
On 18 Sep, 2019
Posted 20 Sep, 2019
On 04 Sep, 2019
Received 02 Sep, 2019
Invitations sent on 23 Aug, 2019
On 23 Aug, 2019
On 22 Aug, 2019
On 21 Aug, 2019
On 21 Aug, 2019
On 22 Jul, 2019
Received 18 Jul, 2019
Received 08 Jul, 2019
On 27 Jun, 2019
On 26 Jun, 2019
On 26 Jun, 2019
Invitations sent on 26 Jun, 2019
On 26 Jun, 2019
On 25 Jun, 2019
On 01 Oct, 2019
On 30 Sep, 2019
On 29 Sep, 2019
On 29 Sep, 2019
On 22 Sep, 2019
Invitations sent on 20 Sep, 2019
On 20 Sep, 2019
Received 20 Sep, 2019
On 19 Sep, 2019
On 18 Sep, 2019
On 18 Sep, 2019
Posted 20 Sep, 2019
On 04 Sep, 2019
Received 02 Sep, 2019
Invitations sent on 23 Aug, 2019
On 23 Aug, 2019
On 22 Aug, 2019
On 21 Aug, 2019
On 21 Aug, 2019
On 22 Jul, 2019
Received 18 Jul, 2019
Received 08 Jul, 2019
On 27 Jun, 2019
On 26 Jun, 2019
On 26 Jun, 2019
Invitations sent on 26 Jun, 2019
On 26 Jun, 2019
On 25 Jun, 2019
Background
The understanding of the importance of RNA has dramatically changed over recent years. As in the case of proteins, the function of an RNA molecule is encoded in its tertiary structure, which in turn is determined by the molecule's sequence. The prediction of tertiary structures of complex RNAs is still a challenging task.
Results
Using the observation that RNA sequences from the same RNA family fold into conserved structure, we test herein whether parallel modeling of RNA homologs can improve ab initio RNA structure prediction method. EvoClustRNA is a multi-step modeling process, in which homologous sequences for the target sequence are selected using the Rfam database. Subsequently, independent folding simulations using Rosetta FARFAR and SimRNA are carried out. The model of the target sequence is selected based on the most common structural arrangement of the common helical fragments. As a test, on two blind RNA-Puzzles challenges, EvoClustRNA predictions ranked as the first of all submissions for the L-glutamine riboswitch and as the second for the ZMP riboswitch. Moreover, through a benchmark of known structures, we discovered several cases in which particular homologs were unusually amenable to structure recovery in folding simulations compared to the single original target sequence.
Conclusion
This work, for the first time to our knowledge, demonstrates how important is the selection of the target sequence from an alignment of an RNA family for the success of RNA 3D structure prediction. These observations prompt investigations into a new direction of research for checking 3D structure “foldability” or “predictability” of related RNA sequences to obtain accurate predictions. To support new research in this area, we provide all relevant scripts in a documented and ready-to-use form. By exploring new ideas and identification of limitations of the current RNA 3D structure prediction methods, this work is bringing us closer to the near-native computational RNA 3D models.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8
This is a list of supplementary files associated with this preprint. Click to download.
Loading...