Commit 7fe79c52 authored by Vladimir Reinharz's avatar Vladimir Reinharz
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results, capt im 6

parent c5c53b6c
......@@ -436,9 +436,9 @@ The adenine riboswitch belongs to family \texttt{RF00167} which has $133$ seed s
Experiments \texttt{Adenine\char`_4} which was done in absence of the ligand gave poor results, since the MaM experiment was done on the unbounded structure. Those additional results are shown in the Supp. Mat.
For each molecule, we present in Fig.~\ref{fig:shape}, for every position $i$, the disruption of the shape profile when a mutation occurs at that position (i.e. $\Delta(S, S_i)$), with the aligned \rfam consensus secondary structure below.
For each molecule, we present in Fig.~\ref{fig:shape}, for every position $i$, the disruption of the shape profile when a mutation occurs at that position (i.e. $\Delta(S, S_i)$), with the aligned \rfam consensus secondary structure below. We notice the rugged landscape and the sharp differences between the adenine riboswitch profile 4, where the MaM was done without the presence of adenine, and the other two. Additionally, the fact that the glycosine riboswitch sequence is mostly aligned to non structured part might be an additional reason for the poor results of our method.
}
\begin{figure*}[ht!]
......@@ -446,7 +446,7 @@ For each molecule, we present in Fig.~\ref{fig:shape}, for every position $i$, t
\colorbox{red}{
\includegraphics[width=0.96\textwidth]{Figure4.png}
}
\caption{{\bf Disruptive impact of mutations, as measured from MaM data.} On the $x$-axis the position of the mutation, and on the $y$-axis the value of the SHAPE profile distance $\Delta(S, S_i)$.}
\caption{{\bf Disruptive impact of mutations, as measured from MaM data.} On the $x$-axis the position of the mutation, and on the $y$-axis the value of the SHAPE profile distance $\Delta(S, S_i)$. {\color{red} The adenine\_4 MaM experiment was done in the absence of adenine.}}
\label{fig:shape}
\end{figure*}
......@@ -493,7 +493,7 @@ It is important to recall that the set of positives and negatives is influenced
\begin{figure*}[ht!]
\centering
\colorbox{red}{% \includegraphics[width=0.96\textwidth]{Figure5.png}
\colorbox{red}{
\begin{subfigure}{\textwidth}
\includegraphics[width=0.96\textwidth]{Figure5.png}
\caption{MaM}
......@@ -514,50 +514,41 @@ It is important to recall that the set of positives and negatives is influenced
%\begin{figure}[ht!]
% \centering
% \includegraphics[width=0.47\textwidth]{Figure5.png}
% \caption{AUC results for a range of values of $\gamma$ and $\delta$ averaged over the 4 RNA structures of 5S in the first row and those of c-di-GMP in the second row.
% The structural disruption is evaluated with Mutate and Map in the first column and \remu in the second.}
% \label{fig:auc}
%\end{figure}
\subsection{Evolutionary stabilization of {\itshape in vitro} disruptive mutations reveal molecular interfaces}
The ROC curves for the 4 PDB structures are shown on the same graph, for a specific \shape distance threshold $\delta$ and $\gamma$.
We illustrate in Fig.~\ref{fig:roc}a the results for the 5S RNA given $\delta$ at the $96^{\text{th}}$ percentile and a $\gamma$ of $23$.
In Fig.~\ref{fig:roc}b we show the result for the c-di-GMP riboswitch given a \shape distance threshold at the $93^{\text{th}}$
percentile and a $\gamma$ of $6$.
%
%\begin{figure}[t!]
% \centering
% \includegraphics[width=0.47\textwidth]{Figure6.png}
% \caption{{\bf Detailed discrimination power analysis of \soft.} ROC curves for 5S rRNA (a.) with $\gamma$ at $23$ and $\delta$ at $96\%$, and c-di-GMP (b.) with $\delta$ at $93\%$ and $\gamma$ at 6.}
% \label{fig:roc}
%\end{figure}
In the case of the 5S RNA,
we hypothesize that two main reasons explain the discrepancy between the different PDB models. A few nucleotides are missing from each,
creating regions without available information. More crucially, the four structures have been determined in different contexts.
\texttt{3OAS}, \texttt{3OFC} and \texttt{3ORB} are respectively bound to telithromycin, solithromycin,
and chloramphenicol while \texttt{2WWQ} is stalled during translation of the TNAC leader peptide.
{\color{red}
The results shown in Fig.~\ref{fig:auc} all follow the same trend
}
For the c-di-GMP riboswitch, the ROC curves discrepancy observed when comparing the results of 3MXH, 3MUV, 3MUT, and 3IWN can probably be explained by the fact that, although all four structures are bound to the U1 small nuclear ribonucleoprotein A, each are missing nucleotides in different regions due to incomplete 3D models. We recall that they are missing between $7\%$ and $21\%$ of the whole structure.
%The ROC curves for the 4 PDB structures are shown on the same graph, for a specific \shape distance threshold $\delta$ and $\gamma$.
%We illustrate in Fig.~\ref{fig:roc}a the results for the 5S RNA given $\delta$ at the $96^{\text{th}}$ percentile and a $\gamma$ of $23$.
%In Fig.~\ref{fig:roc}b we show the result for the c-di-GMP riboswitch given a \shape distance threshold at the $93^{\text{th}}$
%percentile and a $\gamma$ of $6$.
%In the case of the 5S RNA,
%we hypothesize that two main reasons explain the discrepancy between the different PDB models. A few nucleotides are missing from each,
%creating regions without available information. More crucially, the four structures have been determined in different contexts.
%\texttt{3OAS}, \texttt{3OFC} and \texttt{3ORB} are respectively bound to telithromycin, solithromycin,
%and chloramphenicol while \texttt{2WWQ} is stalled during translation of the TNAC leader peptide.
%For the c-di-GMP riboswitch, the ROC curves discrepancy observed when comparing the results of 3MXH, 3MUV, 3MUT, and 3IWN can probably be explained by the fact that, although all four structures are bound to the U1 small nuclear ribonucleoprotein A, each are missing nucleotides in different regions due to incomplete 3D models. We recall that they are missing between $7\%$ and $21\%$ of the whole structure.
%The set of parameters associated with the best average AUC correspond to 3 curves having AUC of $1$, plus another around $0.5$. We suggest that at high value of $\delta$ the region of interests is restrained to nucleotides that are not in the PDB models, resulting in a minimal validation case.
The set of parameters associated with the best average AUC correspond to 3 curves having AUC of $1$, plus another around $0.5$. We suggest that at high value of $\delta$ the region of interests is restrained to nucleotides that are not in the PDB models, resulting in a minimal validation case.
We conjecture that the differences in the influence of the $\gamma$ parameter are due to
structural differences. We present in Fig.~\ref{fig:dist} the distribution of path lengths (distance) between every pair of secondary structure elements, weighted by the number of combinations of positions that are not in the intersection of the secondary structure element. We observe that the 5S rRNA (Fig.~\ref{fig:dist}a) has a much more Normal-like distance distribution than the c-di-GMP (Fig.~\ref{fig:dist}b), which is highly skewed towards smaller distances. Moreover, these figures show that the expected distance in the 5S model is much larger than that of the c-di-GMP, a trend that is also observed in the respective optimal values of $\gamma$ for the two models.
We conjecture that the differences in the influence of the $\gamma$ parameter, minimal distance from the mutation, are due to
structural differences. We present in Fig.~\ref{fig:dist} the distribution of path lengths (distance) between every pair of secondary structure elements, weighted by the number of combinations of positions that are not in the intersection of the secondary structure element. We observe that the 5S rRNA has a much more Normal-like distance distribution, {\color{red} while the c-di-GMP (Fig.~\ref{fig:dist} and cobalamin riboswitch are more Poisson-like. In contrast, the three way junction in the tRNA and adenine riboswitch induce bimodal distributions.
Those distributions determine how smoothly the number of positions considered decreases as the parameter $\gamma$, minimal distance from the mutation, is increased.
}
\begin{figure}[htb!]
\begin{figure}[ht!]
\centering
\colorbox{red}{
\includegraphics[width=0.47\textwidth]{Figure6.png}
}
\caption{{\bf Distance distribution for pairs of secondary structure elements}, weighted by the numbers of non-shared nucleotides}
\caption{{\bf Distance distribution for pairs of secondary structure elements}, weighted by the numbers of non-shared nucleotides. {\color{red} The different distribution affect the quantity
of positions selected by the parameter $\gamma$, distance from the mutation.}}
\label{fig:dist}%
\end{figure}
......
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