Rerun of MD and FF

1. Rerun of MD and FF Force fields for MD and beyond

2. Force Field A force field is a set of parameters with the associated rules that together can be used to describe a situation and to simulate its future. The main problem you will encounter while studying FF is that there are very many, radically different FF. Actually, FF are everywhere around us, and touch us every day.

3. FF are everywhere AH uses FF to make us buy more than we intend The water flow in the Waal Stock market swings Fire exist usage in theatres Use of electrical power throughout the country Secondary structure of proteins Molecular dynamics Etcetera

4. FF for MD The force field for MD and EM holds about 5 terms. These are still the ones that were understood in the 60’s. Other terms either are poorly understood, or too hard to calculate. The present ~5 terms are optimised to also capture information related to all the terms not yet in use.

5. FF for MD You better look up those five terms, and understand them deeply. All five terms in the force field are used on all atom combinations every step of the simulation. Most CPU time is spent on water interactions… In MD s=v*t, F=m*a, etc. So atoms can only fly in a straight line. Therefore the time step (time before we calculate new v) is short (1-5 fs).

6. Here YASARA movies

7. Multiple minima problem And in a high-dimensional space this problem gets very, very much worse.

8. The other FF If I throw 2 dice and 1 coin inside a small coffee cup, one could expect any asymmetry in the dices to show up much stronger (I also don’t know why, but I needed a simple example). How do we check if the dices are honest?

9. The other FF How did they ever find out how the DNA code translates into protein? And how would we do it today?

10. How do we predict RNA binding loops?

11. How do we predict RNA binding loops? 1) Datasets

12. How do we predict RNA binding loops? 1) Datasets 2) Counting

13. How do we predict RNA binding loops? 1) Datasets 2) Counting 3) ΔG

14. How do we predict RNA binding loops? 1) Datasets 2) Counting 3) ΔG 4) Algorithm

15. How do we predict RNA binding loops? 1) Datasets 2) Counting 3) ΔG 4) Algorithm 5) Validate

16. And now… FF to predict secondary structure FF to predict how ruthenium oxide binds to photographic plate FF to predict which methionines are good to click a reactive group onto? FF to predict how a ligand binds to a receptor FF to predict TM helices.