Under construction - 【Tutorial of Polyply for Beginners: using PEG-pLeu as an example】

[kurokawaikki]

This is a general tutorial of Polyply for beginners. PEG-pLeu wiil be used as an example.

In many cases, simulation of polymers is painful with all atom MD simulation. The cost of computational power is dramatic and lots of time. The development of coarse-grained MD simulation improved the situation. However, the parameterization of large polymers still hinders the ease use of CG simulation. The development of Marini CG [1] and Polyply [2] make the processes more delightful than before. In order to help beginners to have better understanding of Martini CG and Polyply, the present example tries to use as simple as possible methods to guide the beginners through the aching parameterization processes.

Here, a general tutorial for using Martini 3 CG and Polyply is presented. The PEG-pLeu is used as an example. You can feel free to change to any other molecules. With the power of Polyply, it is possible to just get the parameters for certain critical linkage in order to have a functional parameter for large polymers. Please give the most appreciation to the developers of Martini CG and Polyply.
This tutorial is originally based on the official Martini CG tutorial for parameterizing new small molecules (http://cgmartini.nl/index.php/2021-martini-online-workshop/tutorials/560-5-parametrization-of-a-new-small-molecule) and the Polyply github issues (#190). More details of how to combine the obtained parameters to Polyply is provided.

In this tutorial you will learn from the beginning including:

1. How to get parameter for new small molecules with available online servers.
2. How to parameterize the small molecules in Martini 3 CG force field with two ways:
   2.1 Bartender – A DFTB method for parametrization.
   2.2 Swarm CG – An automatic method for parametrization [3].
3. Obtaining required parameters for force field files (.ff) for Polyply.
4. Running CG simulation of a polymer with the parameters (.itp) from Polyply.

References:
1.
2.
3.

Special thanks to @fgrunewald.