<h3>Title</h3>
<p><span style="color: #0000ff;">Taking bumpy rides on the energy landscape</span></p>
<p><strong><span style="text-decoration: underline;">Abstract</span> :</strong></p>
<p>During the last few decades, the energy landscape framework has emerged both as a conceptual and a computational tool to understand the intimate connections between biomolecular structure, dynamics, and function. Nonetheless, determining the global topography of the landscape, using standard computational techniques, such as molecular dynamics simulations, has proved challenging because of the computational cost. For many practical applications, it is often sufficient to consider a coarse-grained description of the landscape, in terms of stationary points (minima and transition states). This coarse-graining eliminates the need for dynamical sampling, and the stationary points can be located using tools of geometry optimization. In my talk, I will highlight how this approach makes it easier to take bumpy rides on energy landscapes, particularly for those systems that exhibit multiple competing structures. </p>
<p><br />I will discuss some recent applications of the energy landscape framework in the context of RNA folding, as well as the extremely slow conformational switching between DNA helix morphologies.</p>