Markov State Models. Gregory R. Bowman Miller Fellow University of California, Berkeley

Similar documents
Supplementary Figures:

The Morse Potential. ChE Reactive Process Engineering. Let s have a look at a very simple model reaction :

Application of the Markov State Model to Molecular Dynamics of Biological Molecules. Speaker: Xun Sang-Ni Supervisor: Prof. Wu Dr.

Computational Biochemistry in the New Era of HPC. Imran Haque Department of Computer Science Stanford University

Lecture 21 (11/3/17) Protein Stability, Folding, and Dynamics Hydrophobic effect drives protein folding

Biology Chemistry & Physics of Biomolecules. Examination #1. Proteins Module. September 29, Answer Key

Modeling Background; Donald J. Jacobs, University of North Carolina at Charlotte Page 1 of 8

GCE A level 1326/01-D PHYSICS PH6 Data Analysis Task

Many proteins spontaneously refold into native form in vitro with high fidelity and high speed.

Supporting Information. RNA hairpin

AQA Physics A-level Section 1: Measurements and Their Errors

ELECTRONICS. EE 42/100 Lecture 2: Charge, Current, Voltage, and Circuits. Revised 1/18/2012 (9:04PM) Prof. Ali M. Niknejad

Introduce Professors Chidsey and Dai, Dr. Schwartz, Marissa Caldwell and the rest of the instructional team.

Identification and Analysis of Transition and Metastable Markov States

clustq: Efficient Protein Decoy Clustering Using Superposition-free Weighted Internal Distance Comparisons

Protein Folding experiments and theory

Energetics and Thermodynamics

Proton Acidity. (b) For the following reaction, draw the arrowhead properly to indicate the position of the equilibrium: HA + K + B -

Accelerating Rosetta with OpenMM. Peter Eastman. RosettaCon, August 5, 2010

Hybrid Vigor. Using Heterogeneous HPC to Accelerate Chemical Biology. Imran Haque Department of Computer Science Stanford University

Molecular Mechanics, Dynamics & Docking

STRUCTURAL BIOINFORMATICS I. Fall 2015

Matter is made of atoms and molecules

Nanobiotechnology. Place: IOP 1 st Meeting Room Time: 9:30-12:00. Reference: Review Papers. Grade: 40% midterm, 60% final report (oral + written)

PHOTO-DISSOCIATION OF CO 2 GAS BY USING TWO LASERS

Chemical symbols for elements appear on the periodic table; only the first letter is capitalized.

Enhanced Modeling via Network Theory: Adaptive Sampling of Markov State Models

5th CCPN Matt Crump. Thermodynamic quantities derived from protein dynamics

Can a continuum solvent model reproduce the free energy landscape of a β-hairpin folding in water?

Energy Landscapes and Accelerated Molecular- Dynamical Techniques for the Study of Protein Folding

Experimental Methods in Kinetics (2014)

The Structure of Small Protonated Peptides Containing Arginine and the Effect of Hydration

Computational Studies of the Photoreceptor Rhodopsin. Scott E. Feller Wabash College

CISC 636 Computational Biology & Bioinformatics (Fall 2016)

A Stochastic Roadmap Method to Model Protein Structural Transitions

8/17/2016. Summary. Summary. Summary. Chapter 1 Quantities and Units. Passive Components. SI Fundamental Units. Some Important Electrical Units

Short Announcements. 1 st Quiz today: 15 minutes. Homework 3: Due next Wednesday.

Physics- using a small number of basic concepts, equations, and assumptions to describe the physical world

Lecture 34 Protein Unfolding Thermodynamics

Laying down deep roots: Molecular models of plant hormone signaling towards a detailed understanding of plant biology

General Chemistry Exam 2/3 Chem 210 Section 02, Fall 2017

Cecilia Clementi s research group.

CHEM 109A Organic Chemistry

BIOCHEMISTRY Unit 2 Part 4 ACTIVITY #6 (Chapter 5) PROTEINS

110 Spring 2018 Exam 1 Version A Name: No cell phones or electronic devices (except scientific calculators). = 4 3 = = =

Molecular Modelling for Medicinal Chemistry (F13MMM) Room A36

Assignment 2 Atomic-Level Molecular Modeling

Introduction to Machine learning

Influence of Chemical Chaperone Hexylresorcinol on Lysozyme. Changes of Structure, Dynamics and Functional Activity.

Design of a Novel Globular Protein Fold with Atomic-Level Accuracy

UNIVERSITY OF TECHNOLOGY Laser & Opto-Electronic Eng. Dept rd YEAR. The Electromagnetic Waves

Course Introduction. SASSIE CCP-SAS Workshop. January 23-25, ISIS Neutron and Muon Source Rutherford Appleton Laboratory UK

Distance Constraint Model; Donald J. Jacobs, University of North Carolina at Charlotte Page 1 of 11

Hands-on Course in Computational Structural Biology and Molecular Simulation BIOP590C/MCB590C. Course Details

PY1007: Physics for Engineers I

QUANITY NAME OF UNIT ABBREVIATION length meter m mass kilogram kg time second s

What is the role of simulation in nanoscience research?

SECTION 3.1: What is a Rational

Lecture 2-3: Review of forces (ctd.) and elementary statistical mechanics. Contributions to protein stability

Outline. The ensemble folding kinetics of protein G from an all-atom Monte Carlo simulation. Unfolded Folded. What is protein folding?

Physics 11. Unit 1 Mathematical Toolkits

Protein Structure Prediction

Topics Covered in This Chapter:

Advances in Experimental Medicine and Biology 797

161 Spring 2018 Exam 1 Version A Name: No cell phones or electronic devices (except scientific calculators). = 4 3 = = =

Lattice protein models

Chapter 1: Quantities and Units

Secondary structure stability, beta-sheet formation & stability

Chapter 1 Introduction: Matter and Measurement Honors Chemistry Lecture Notes. 1.1 The Study of Chemistry: The study of and the it undergoes.

Finding slow modes and accessing very long timescales in molecular dynamics. Frank Noé (FU Berlin)

PHYSICS 149: Lecture 2

Protein structure prediction. CS/CME/BioE/Biophys/BMI 279 Oct. 10 and 12, 2017 Ron Dror

The lecture notes and homework will be posted on the Web

Giri Narasimhan. CAP 5510: Introduction to Bioinformatics. ECS 254; Phone: x3748

Using Spectral Clustering to Sample Molecular States and Pathways

This semester. Books

Homology modeling. Dinesh Gupta ICGEB, New Delhi 1/27/2010 5:59 PM

Computing Reaction Rates Using Macro-states

GCE AS/A level 1321/01 PHYSICS PH1 Motion, Energy and Charge

Introduction to CMOS VLSI Design Lecture 1: Introduction

General Chemistry (Chem110) Dr. Rima Alharthy

Final Morphology of Complex Materials

Protein Structure Determination from Pseudocontact Shifts Using ROSETTA

1.1 - Scientific Theory

High-Resolution Free-Energy Landscape Analysis of α Helical Protein Folding: HP35 and Its Double Mutant

A Molecular Interpretation of 2D IR Protein Folding Experiments with Markov State Models

PROTEIN EVOLUTION AND PROTEIN FOLDING: NON-FUNCTIONAL CONSERVED RESIDUES AND THEIR PROBABLE ROLE

StructuralBiology. October 18, 2018

974 Biophysical Journal Volume 107 August Dynamical Phase Transitions Reveal Amyloid-like States on Protein Folding Landscapes

Lesson 1.1 MEASUREMENT, UNITS, SCIENTIFIC NOTATION, AND PRECISION

THE UNIVERSITY OF MANITOBA. PAPER NO: 409 LOCATION: Fr. Kennedy Gold Gym PAGE NO: 1 of 6 DEPARTMENT & COURSE NO: CHEM 4630 TIME: 3 HOURS

Principal Component Analysis (PCA)

Computer Simulation of Lignocellulosic Biomass

Biological Thermodynamics

Presenter: She Zhang

Two-Metal Ion Catalysis by Ribonuclease H

Designing Metal-Templated de novo Protein Complexes

Protein structure prediction. CS/CME/BioE/Biophys/BMI 279 Oct. 10 and 12, 2017 Ron Dror

Energy Barriers and Rates - Transition State Theory for Physicists

Protein Structure Analysis

Transcription:

Markov State Models Gregory R. Bowman Miller Fellow University of California, Berkeley Tuesday, August 16, 2011

Defining The Protein Folding Problem

Defining The Protein Folding Problem

Why Mechanism?

Why Mechanism?

Why Mechanism?

The Sampling Challenge Bond vibration Isomerization Water dynamics Helix forms Fast folding Slow conf change protein oligomerization 10-15 femto 10-12 pico 10-9 nano 10-6 micro 10-3 milli 10 0 seconds 10 3 seconds MD step long MD run where we d love to be time on 1 fast CPU 1 day 3 years 3,000 years 3,000,000 years ~age of the earth Tuesday, August 16, 2011

The Sampling Challenge Bond vibration Isomerization Water dynamics Helix forms Fast folding Slow conf change protein oligomerization 10-15 femto 10-12 pico 10-9 nano 10-6 micro 10-3 milli 10 0 seconds 10 3 seconds MD step long MD run where we d love to be time on 1 fast CPU 1 day 3 years 3,000 years 3,000,000 years ~age of the earth Tuesday, August 16, 2011

The Sampling Challenge Bond vibration Isomerization Water dynamics Helix forms Fast folding Slow conf change protein oligomerization 10-15 femto 10-12 pico 10-9 nano 10-6 micro 10-3 milli 10 0 seconds 10 3 seconds MD step long MD run where we d love to be time on 1 fast CPU 1 day 3 years 3,000 years 3,000,000 years ~age of the earth Tuesday, August 16, 2011

The Sampling Challenge Bond vibration Isomerization Water dynamics Helix forms Fast folding Slow conf change protein oligomerization 10-15 femto 10-12 pico 10-9 nano 10-6 micro 10-3 milli 10 0 seconds 10 3 seconds MD step long MD run where we d love to be time on 1 fast CPU 1 day 3 years 3,000 years 3,000,000 years ~age of the earth Tuesday, August 16, 2011

Markov State Models (MSMs)

Markov State Models (MSMs)

Markov State Models (MSMs)

How to Build an MSM

How to Build an MSM

How to Build an MSM

Sample

Sample

Sample

Sample

Clustering Gives a High- resolution Model (this is a cartoon, since it s hard to draw 10,000 states in a talk) Tuesday, August 16, 2011

Lumping Provides Human Intuition

Under the Hood!"# $!"!% $!"& $'$ T(! t) =!"& $!"( $!"& $'$! $ $!"!) $!"* $'$ ' $ $' $ $' $ $'$!"#$%&#'&(&)"%&#'!"#'& Tuesday, August 16, 2011

Free Energy (kt) Modeling Experiments native state prediction Bowman, Beauchamp, Boxer, and Pande. JCP 2009. Bowman, Voelz, and Pande. JACS 2011. Tuesday, August 16, 2011

Free Energy (kt) Modeling Experiments native state prediction Bowman, Beauchamp, Boxer, and Pande. JCP 2009. Bowman, Voelz, and Pande. JACS 2011. Tuesday, August 16, 2011

Free Energy (kt) Modeling Experiments native state prediction!"#$%&#'&(&)"%&#'!"#'& Bowman, Beauchamp, Boxer, and Pande. JCP 2009. Bowman, Voelz, and Pande. JACS 2011. *+,"#'&(&!"#'!*+,& Tuesday, August 16, 2011

One Area Where We Need Help...

One Area Where We Need Help...

One Area Where We Need Help...

Jump- starting an MSM with Rosetta

Jump- starting an MSM with Rosetta

Jump- starting an MSM with Rosetta

What Can We Do For You?

What Can We Do For You? Dynamics in Design Tuesday, August 16, 2011

What Can We Do For You? Dynamics in Design Sampling Tuesday, August 16, 2011

What Can We Do For You? Dynamics in Design Sampling Force Field Assessment Tuesday, August 16, 2011

What Can We Do For You? Dynamics in Design Sampling Force Field Assessment? Tuesday, August 16, 2011

Conclusions

Conclusions Mechanism is important Tuesday, August 16, 2011

Conclusions Mechanism is important Markov state models are a powerful way of capturing the mechanisms of conformational change Tuesday, August 16, 2011

Conclusions Mechanism is important Markov state models are a powerful way of capturing the mechanisms of conformational change There s lots of room for collaboration! Tuesday, August 16, 2011

Thanks!

Conclusions Mechanism is important Markov state models are a powerful way of capturing the mechanisms of conformational change There s lots of room for collaboration! Tuesday, August 16, 2011