LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Simple, yet Efficient Conformational Sampling Methods for Reproducing/Predicting Biologically Rare Events of Proteins

Photo from wikipedia

The biological functions of proteins are strongly related to their conformational transitions. To elucidate the essential dynamics, molecular dynamics (MD) simulation has become a powerful tool. However, it might still… Click to show full abstract

The biological functions of proteins are strongly related to their conformational transitions. To elucidate the essential dynamics, molecular dynamics (MD) simulation has become a powerful tool. However, it might still be difficult to address the relevant conformational transitions of proteins with the conventional MD (CMD) because the accessible time scales of CMD are far from those of the biological functions. Furthermore, the essential transitions are induced as stochastic processes in the long time scales, i.e. the conformational transitions are regarded as biologically relevant rare events. To reproduce/predict the rare events, we have proposed several enhanced conformational sampling methods. Our strategy to detect the rare events is based on cycles of the following conformational resampling consisting of two steps. (1) Selections of essential initial structures. (2) Restarting of short-time MD simulations from the initial structures. The cycles of conformational resampling increase the transition p...

Keywords: sampling methods; rare events; conformational sampling; conformational transitions; simple yet

Journal Title: Bulletin of the Chemical Society of Japan
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.