martini workshop 2021 introduction to martini 3

PAULO C. T. SOUZA

Martini Workshop 2021

Introduction to Martini 3

Overview of the presentation

• Basic CG modeling principles

• Revisiting Martini 2

• Problems of the previous

model

• Introduction to Martini 3

• Beads

• Validation

• Improvements2

van Gunsteren et al, Angew. Chem. 2006, 45, 4064 – 4092

Degrees of freedom

Boundary Conditions:

Temperature

Pressure

Walls or periodic

boundaries

External forces

Methods to generate

configurations

Forces between particles

Bonded interactions

Non-bonded interactions

MOLECULAR

MODEL

Electrons and Nucleus

United or All-atom

Coarse-grained

Implicit model

- Unbiased MD

-Biased methods

-Monte Carlo

-Docking, etc.

Four essential ingredients for molecular modeling:Choice depends of the problem studied

3

When should

we use CG?

When/Why use coarse-graining methods?

Connecting all-atom to continuum scale

-“toy model” for ideas

- get more sampling

CG for

smaller scales?

Tutorial

backward

Tutorial

TS2CG

Tutorial

Protein-small

molecule Binding

4

Different ways of coarse-graining

Experimental data

Atomistic

Models

Coarse-Grained

Models

• Pragmatic approach

• Reproduce faithfully certain experimental properties

• Developed with certain application area in mind

Examples:Go models

SIRAH model

• Hierarchical approach

• Interactions at CG level from the collective interactions at

atomistic level

• General method applicable to any system

Examples: - Iterative Boltzmann inversion potentials

- Force matching

BOTTOM-UP

TOP-DOWN

5

• Build block approach (“Lego”).

• Chemical specificity

• Fast (102 - 103 speed-up)

• Implementation in atomistic MD

codes.

• Compatibility and versatility

• Parameterization combining

Bottom-Up and Top-Down

approaches

The Martini Model: Key features

Approximately 4:1 mapping of

non-hydrogen atoms

6

From beads to complex systems

Parametrization with

atomistic simulations

Bottom-up

Building blocks

Simple systems

Complex Systems

Top-down

Calibration with

thermodynamics datanon-bonded

interaction

bonded

interactions

Insights of

collective

processes

Characterizaton

of assembles

and materials

Extensive

tests in model

systems

Comparison

with atomistic

data

7

MARTINI 2: THE BEADS TYPES

C = non-polar

N = intermediate

P = polar

Q = charged

(+1/-1)

C1

C2

C3

C4

C5

Nda

Nd /Na

N0

P1

P2

P3

P4

P5

Qda

Qd/ Qa

Q0

18 Bead Chemical Types 3 Bead Sizes

R = Regular

0.47 nm

S=Small

0.43 nmT=Tiny

0.32 nm

- +

R-S

0.47 nm

R-T

0.47 nm

S-T

0.43 nm

Linear/

Branched

molecules

Ringsnucleobases

- +

Marrink et. al JPCB,2007

Hyd

rop

ho

bic

ity s

ca

le

8Uusitalo et. al JCTC,2015

THE HEART OF MARTINI 2: THE INTERACTION MATRIX

9

MAPPING AND BONDED POTENTIALS

• Where the beads were placed?

• Center of mass: general rule

• Exceptions:

• Corrections in bond lenghts to improve

certain properties.

• Cα for proteins (Elnedyn approach)

• Fuzzy approach: a CG model can represent

more than one molecule. Example: lipids

• Bonded potentials: the ones

typically used in atomistic MD

codesTutorial

Parametrization new CG models10

Huge success of Martini 2 during 14 years

Google scholar: ~ 4500 citations only for the main paper:

S.J. Marrink at al. JPCB, 111:7812-7824, 2007.

Two recent high-impact examples of applications:

1) PIP2 stabilizes active states of

GPCRs and enhances selectivity of

G-protein couplingof GPCR .Yen et al, Nature 2018.

2) Reversible Self-Assembly of

Superstructured Networks.Freeman et al, Science 2018.

11

There are some limitations …

• Missing entropy, compensated by reduced enthalpy

• Driving forces may be wrong in some cases

• Temperature dependence and hydrophobic effect.

• Be careful with time scales

Fundamental problems related with CG approach

Coarse-grained Atomistic 12

AND there were also unexpected problems

Solu

ble

pro

tein

Sugars

Schmalhorst et al, JCTC, 2017

Stark et tal, JCTC, 2013

Javanainen et al, Plos One, 2017

TM

pro

tein

s

No internal cavities

and limited flexibility

apo-rhodopsin

Wrong partitions Dissociation barriers

Bereau and Kremer, JCTC, 2015 Uusitalo et al, JCTC, 2015

Issues in miscibility

Cyclohexane/Benzene

Alessandri et al, to be published 2021

Excessive aggregation

Limited chemical space

slightly soluble miscibleinsoluble

ON OO OOCH3

OC

O

slightly soluble

And others…Thanks for Martini

Community!

Kanekal and Bereau , JCP, 2019

13

Solution? Full reparametrization of Martini

Lego in ~1980

Lego today

Easy-to-use versus Accuracy?

First Lego ~1949

Martini 1:

for lipids

Marrink et. al JPCB,2004

Martini 2:

for biomolecules

Marrink et. al JPCB,2007.

Martini 3:

for general purpose

Souza et. al Nature Methods,2021.

14

Martini 3: what is new?

1) Improved interactions and packingReparametrized all bead sizes and types, cross interactions and bonds

2) Better Coverage of Chemical SpaceNew beads and ways to modify them.

Kanekal and Bereau , JCP, 2019

4) Embracing Gō models for proteins

Poma et al, JCTC, 2017

Alessandri,Souza et al, JCTC, 2019

3) Reformulation of charged beads

Jungwirth and Cremer, Nature Chemistry, 2014

15

How did we get the new model/parameters?

Defining the interaction matrix and interaction levels

Mainly Calibration Mainly Validation

Multiscaling

- Water/oil partitioning

- Miscibility

- Densities

- Trends in solvation

- Trends in vap. enthalpy

Quality control

- quick simulation tests

- Yes/No answers.

- avoid parameters with

clear problems

Quantitative tests

- expensive tests.

- big/complex systems

- taskforces and external

collaborators

Defining your

universe

- # of types and sizes

- # of interaction levels

- Rules for mapping

- Rules for bonds

- Bead assignments

- Interaction matrix

Tier 0 Tier 1 Tier 2


16

MARTINI 3: THE BEAD CHEMICAL TYPES

C = non-polar

N = intermediate

P = polar

Q=charged

X = halo compounds

C1

C2

C3

C4

C5

C6

N1

N2

N3

N4

N5

N6

P1

P2

P3

P4

P5

P6

Q1

Q2

Q3

Q4

Q5

Total of 29 Bead Chemical Types

- 1 +1


Hyd

rop

ho

bic

ity a

nd

mis

cib

ility s

ca

le

W= Specific beads for water

Expansion of bead subtypes

X1

X2

X3

X4

-2 +2 D = divalent charged

molecules

New beads!

17

NEW INTERACTION MATRIX OF MARTINI 3

LJ and Reaction-field (or PME)

Souza et. al Nature Methods,2021.18

MARTINI 3: THE BEAD SIZES

3 Bead Sizes

Regular

0.47 nm

Small

0.41 nmTiny

0.34 nm

R-S

0.43 nm

R-T

0.395 nm

S-T

0.365 nm

3-12-1

4-1


4-1 3-1 2-1

- Well-balanced sizes- Improved

partitioning

- Improved barriers

for dissociation

19

WELL-DEFINED MAPPING RULES


Lecture and Tutorial:

Parametrization new CG models

20

MARTINI 3: THE BEAD LABELS

d a


Electron poor (v) / Electron rich (e)

v e

H-donor (d) / H-acceptor (a)Credits: Vishal Maingi

Hydrogen bonding Electron polarizability

- The can be added to all P and N beads.

- Example: P1d, P1a beads use in

nucleobses .

- They can be added to all C and X beads.

- Example: C5e and C5v beads use in aedamers.

- A total of 9 new labels

are available.

- Considering:

Martini 2 Martini 3

Beads 54 843

Pair interactions 1,485 355,746

Parameters ~60 ~1,301chemical

types sizes labelsX X

21

MARTINI 3 PROTEIN MODELS: STILL UNDER DEVELOPMENT

1) Models for side chains

• New models for all

side chains.

• No over or under-

mapping.

• Side chain dihedral

corrections

• Bead type does not

depends of the

secondary structure.

• Default bead is P2

• Exceptions: certain

residues as glycine

and proline.

• Mapping and bonded

parameters are still

based on Martini 2.

2) Model for

backbone

22Protein tutorials and Lecturer about

Elastic and Go Models

3) Bias to keep tertiary structure

Some examples of improvements in proteins

Souza et. al Nature Methods, 2021.

Improved protein-protein

interactions

Predicting binding modes

Proteins have cavities and pores now!

Coarse-graining and Martini

- Simple models that allow affordable, but

meaningful MD simulations.

Martini 3, a general purpose force-field:

- Improved interactions and packing

- Better coverage of chemical space

- Improvements in Martini 3

- Proteins are less sticky

- Cavities and channels are there now.

- New applications of Martini 3?

Take-home message

Lecturer

Siewert J. Marrink

Thanks!

Acknowledgements

Alex de VriesUniversity of Groningen

Riccardo AlessandriUniversity of Chicago

Jonathan BarnoudUniversity of Bristol

Sebastian ThallmairFrankfurt Institute for Advanced Studies

Siewert J. MarrinkUniversity of Groningen

Acknowledgements

University of Groningen

Ignacio Faustino

Fabian Grunewald

Ilias Patmanidis

Haleh Abdizadeh

Bart M.H. Bruininks

Tsjerk Wassenaar

Peter C. Kroon

Josef Melcr

Weria Pezeshkian

Melanie Konig

Petteri Vainikka

Carlos Ramírez-Palacios

Maria Tsanai.

University of Calgary

Valentina Corradi

D. Peter Tieleman

University of Bergen

Hanif M. Khan

Nathalie Reuter

Czech Academy of Sciences

Matti Javanainen

Hector Martinez-Seara

University of Helsinki

Ilpo Vattulainen

NIH – US

Jan Domanski (also Oxford)

Robert B. Best

PharmCADD

Sangwook Wu

CNRS/ University of Lyon

Vincent Nieto

Luca Monticelli

University of Auckland

Xavier Periole

Case Western Reserve University

Amita Sahoo

Matthias Buck

Polish Academy of Sciences

Rodrigo Moreira

Adolfo Poma

Università della Svizzera italiana

Paolo Conflitti

Stefano Raniolo

Vittorio Limongelli

Universidad de Santiago de Chile

Raúl Mera-Adasme

University of California San Diego

Clarisse Gravina Ricci

ITQB NOVA

Manuel Nuno Melo

martini workshop 2021 introduction to martini 3

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