Veracity through variety (of methods): Simulating dipeptides with little volume Tanja van Mourik.
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Transcript of Veracity through variety (of methods): Simulating dipeptides with little volume Tanja van Mourik.
Veracity through variety (of methods):Simulating dipeptides with little volume
Tanja van Mourik
Overview
• Why study peptides with computational methods?
• What is computational quantum chemistry?
1. Background
2. Application
• The shape of a small peptide
little “volume”
1. Background theory
Why study peptides with computational methods?
• the shape of biomolecules is important for their function
• it is difficult to deduce the shape unambiguously from experiments
• computational data can help experimental assignment
function
shape
?
What is computational quantum chemistry?
Quantum chemistry is based on quantum mechanics
Particles are completely characterised by their wavefunction
Wavefunction can be obtained from the Schrödinger equation:
H =E
H =E
However, the Schrödinger equation cannot be solved exactly
Need to use approximate methods
in general:
more precise methods == higher computational demand
larger basis sets => more precise results => higher computational demand
more precise methods == higher computational demand
Level of theory depends on method and basis set
Method: approximate way to solve the Schrödinger equation
Basis set: representation of the wavefunction
H =E
2. Application
The shape of the Tyr-Gly dipeptide
N
O
O
O-H
H H
C CCC
C
C = carbonO = oxygen
N = nitrogenH = hydrogen
N
H-OC
CC
CC
C
H
H
H
H
H-O
2 x 2 x 2 x 3 x 6 x 6 x 12 x 12 = 124416 conformers
single-pointcalculationsHF/3-21G*
33433
geometryoptimisationsHF/3-21G*
300
single-pointMP2/6-31+G*
20
Hierarchical Selection Scheme
geometry optimisationsMP2/6-31+G*
selected conformers:
create structures ofall possible conformers
sort according to their numberof H-bond interactions
124416
geometryoptimisations
B3LYP/6-31+G*20
0.0 3.4 3.6 3.9 4.2
4.5 5.6 5.6 5.7 5.8
6.5 6.5 7.0 7.1 7.1
7.4 10.5 10.5 10.6 11.0
conf 1 conf 2 conf 3
conf 4 conf 5 conf 6
Geometries from B3LYP/6-31+G(d)
Structures were computed with two different levels of theory:
• B3LYP/6-31+G*
• MP2/6-31+G*
method basis set
MP2 and B3LYP generally assumed to be of similar accuracy.However, the MP2 and B3LYP structures differ considerably!
fGly
B3LYP structure MP2 structure
missing dispersion?
BSSE?
Dispersion: physical attraction between atoms
BSSE: artificial attraction between atoms
B3LYP, MP2: two different quantum-chemical methods
rotationaround fGly
MP2/6-31+G*
B3LYP/6-31+G*
fGly
DE
[k
J/m
ol]
MP2 B3LYP
B3LYPminimum MP2
minimum
MP2minimum
Possible reasons for the different geometries obtainedwith B3LYP and MP2:
• MP2 results may be affected by BSSE (unphysical attraction)
• B3LYP results may be affected by missing dispersion (physical attraction)
We can reduce the BSSE in the MP2 calculationsby using larger basis sets
rotationaround fGly
MP2 B3LYP
B3LYPminimum MP2
minimum MP2
minimum
MP2/6-31+G*
B3LYP/6-31+G*MP2/6-31+G*MP2/avdzMP2/avtzMP2/avqz
fGly
DE
[k
J/m
ol]
veracity through variety
MP2/avdz
MP2/avtz
MP2/avqz
BSSE (kJ/mol)
BSSE not the same over the fGly range
Summary
Using computational quantum chemistry one canpredict almost any molecular property, withoutprior knowledge of the molecular system
But: to obtain reliable results, high levels of theoryneed to be used, requiring large computational resources
Results obtained with high-level methods can beused to verify/calibrate more approximate methods
Here: shape of a small peptide
“little volume”
=> “veracity through variety”
Static structures => no velocity
Problem
Hierarchical selection scheme is not guaranteedto select the most stable conformers
(Even high-level methods may miss conformers)
Can data science help to selectmost relevant conformers?
Acknowledgements
Engineering and Physical Sciences Research Council(EPSRC)
The Royal Society
EaStCHEM
Leo Holroyd (UCL and St Andrews)
Ashley Shields (St Andrews)
EaStCHEM Research Computing Facility
Dimitrios Toroz (UCL)
Jie Cao (St Andrews)
“Tyrosine-glycine revisited: Resolving the discrepancy between theory and experiment”Leo F. Holroyd and Tanja van Mourik, Phys. Chem. Lett. 621, 124-129 (2015).
“Performance of the M06-L density functional for a folded Tyr-Gly conformer”J. Cao and T. van Mourik, Chem. Phys. Lett. 485, 40-44 (2010).
“Insufficient description of dispersion in B3LYP and large basis set superposition errors in MP2 calculations can hide peptide conformers”L. F. Holroyd and T. van Mourik, Chem. Phys. Lett. 442, 42-46 (2007).
“The structure of the gas-phase tyrosine-glycine dipeptide”D. Toroz and T. van Mourik, Mol. Phys. 104, 559-570 (2006).
“Comparison of ab initio and DFT electronic structure methods for peptides containing an aromatic ring: The effect of dispersion and BSSE”A. E. Shields and T. van Mourik, J. Phys. Chem. A 111, 13272 – 13277 (2007).
“Conformational structure of tyrosine, tyrosyl-glycine and tyrosyl-glycyl-glycine by double resonance spectroscopy”A. Abo-Riziq, L. Grace, B. Crews, M.P. Callahan, T. van Mourik and M.S. de Vries, J. Phys. Chem. A 115, 6077-6087 (2011).
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