modelling protein tertiary structure ram samudrala university of washington

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Modelling protein tertiary structure Ram Samudrala University of Washington

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Page 1: Modelling protein tertiary structure Ram Samudrala University of Washington

Modelling protein tertiary structureRam Samudrala

University of Washington

Page 2: Modelling protein tertiary structure Ram Samudrala University of Washington

Outline

1. Introduction to protein structure (15 minutes) - de novo prediction - comparative modelling

2. Introduction to RAMP software (10 minutes)

3. Installation/set up of RAMP software (5 minutes)

4. Comparative modelling using RAMP software (45 minutes) - template selection (web) (10 minutes) - alignment (web) (10 minutes) - scgen_mutate to create initial model (10 minutes) - mcgen_semfold_loop to build loops (10 minutes) - refinement (5 minutes)

5. Ab initio modelling using RAMP software (45 minutes) - secondary structure prediction (5 minutes) - setting up simulation on a cluster (10 minutes) - running the simulation (10-20 minutes) * - break/questions - energy minimisation (5 minutes) - scoring using functions from RAMP (10 minutes) - final selection of native-like conformations (5 minutes)

Page 3: Modelling protein tertiary structure Ram Samudrala University of Washington

Comparative modelling of protein structure

KDHPFGFAVPTKNPDGTMNLMNWECAIPKDPPAGIGAPQDN----QNIMLWNAVIP** * * * * * * * **

… …

scanalign

refine

physical functions

build initial model

minimum perturbation

construct non-conservedside chains and main chains

graph theory, semfold

Page 4: Modelling protein tertiary structure Ram Samudrala University of Washington

De novo prediction of protein structure

sample conformational space such thatnative-like conformations are found

astronomically large number of conformations5 states/100 residues = 5100 = 1070

select

hard to design functionsthat are not fooled by

non-native conformations(“decoys”)

Page 5: Modelling protein tertiary structure Ram Samudrala University of Washington

Semi-exhaustive segment-based foldingEFDVILKAAGANKVAVIKAVRGATGLGLKEAKDLVESAPAALKEGVSKDDAEALKKALEEAGAEVEVK

generatefragments from database14-state , model

… …

minimisemonte carlo with simulated annealingconformational space annealing, GA

… …

filter all-atom pairwise interactions, bad contactscompactness, secondary structure

Page 6: Modelling protein tertiary structure Ram Samudrala University of Washington

Ab initio prediction at CASPConsistently predicted correct topology (~ 4 to 6 Å) for 60-100+ residues

T172 – 5.9 Å for 74 aa T187 – 5.1 Å for 66 aa

T129 – 5.8 Å for 68 aa

T170/sfrp3 – 4.8 Å for all 69 aa

T138 – 4.6 Å for 84 aa T146 – 5.6 Å for 67 aa

Page 7: Modelling protein tertiary structure Ram Samudrala University of Washington

Comparative modelling at CASPOverall model accuracy ranging from 1 to 6 Å for 50-10% sequence identity

T160 – 2.5 Å (125 aa; 22%) T133 – 6.0 Å (260 aa; 14%)

T137 – 1.0 Å (133 aa; 57% id)

T185 – 6.0 Å (428 aa; 24% id)

T182 – 1.0 Å (249 aa; 41% id) T150 – 2.7 Å (99aa; 32% id)