Engineering of protein structures
 Overview of mutations
 Databases of mutations
 Missense mutations
 Prediction of mutational effects
 Rational design of proteins
Outline
2Engineering of protein structures
Overview of mutations
3Overview of mutations
 Mutations in DNA or RNA may occur
 Errors in DNA replication during cell division
 Exposure to mutagens (physical or chemical agents)
 Viral infections
 …Or scientist intervention 
 Can be harmful or not
Overview of mutations
4Overview of mutations
 Location in the DNA
 Non-coding region –> affect gene expression (transcriptional
regulation, mRNA stability, translation rates, location, etc.)
 Coding region –> may affect protein sequence
Overview of mutations
5Overview of mutations
 Types
 Point mutations – a single nucleotide is changed in DNA (or RNA)
 Substitutions
 Single nucleotide polymorphism (SNP – pronounced “snip”)
 Genetic variation; occurs in > 1 % of population
 About 10,000,000 in the human genome
 Insertions or deletions
 Codons have triple nature (3 nucleotides  1 amino acid)
 Potential for frameshift (change in the grouping of
codons, resulting in a different translation)
 Can be very deleterious
 Other types (duplications, translocations, inversions, etc.)
Point mutations at protein level
6Overview of mutations
 Types of point mutations
 Silent (synonymous SNP) – no effect on protein sequence
 Missense (non-synonymous SNP) – substitution of amino acid
 Nonsense – introduction of a stop codon -> protein truncation
Databases of mutations
7Databases of mutations
 Human Genome Variation Society
 http://www.hgvs.org
 Lists all the available databases of human mutations
 Central mutation databases (>20)
 Substitutions in all genes
 Variability in protein sequences
 Data mainly from literature
 Locus-specific databases (about 700)
 Substitutions in specific genes
 Typically manually annotated
Central mutation databases
8Databases of mutations
 Database of Single Nucleotide Polymorphisms - dbSNP
 http://www.ncbi.nlm.nih.gov/SNP/
 Repository for both SNP and short deletion and insertion
 For human genome
Central mutation databases
9Databases of mutations
 Online Mendelian Inheritance in Man – OMIM
 http://omim.org/
 Comprehensive database of human genes and genetic phenotypes
Central mutation databases
10Databases of mutations
 Human Gene Mutation Database - HGMD
 http://www.hgmd.cf.ac.uk/ac/index.php
 Comprehensive collection of mutations in nuclear genes
that underlie or are associated with human inherited disease
Central mutation databases
11Databases of mutations
 UniProtKB/Swiss-Prot
 http://www.uniprot.org/UniProtKB/
 High-quality manually annotated protein entries with partial lists of
known sequence variants
Locus-specific databases
12Databases of mutations
 For information on gene-specific databases
Missense mutations
13Missense mutations
 What are they?...
 How can they affect proteins?
Missense mutations
14Missense mutations
 Mutations affecting structure
 Stability & folding
 Aggregation
 Mutations affecting function
 Binding & catalysis
 Transport processes
 Protein dynamics
 Protein localization
Mutations affecting structure
15Missense mutations - structure
 Major pathogenic consequences of missense mutation
 Compromised folding – the protein has modified folds or
presents more unfolded states
 Decreased stability – the lifetime of the protein is decreased
 Increased aggregation
Mutations affecting structure
16Missense mutations - structure
 Molecular basis of mutations affecting folding & stability
 Introduced clashes – common for small to large mutations in
buried residues
 Loss of interactions – most pronounced effects related to H-bonds,
salt bridges and aromatic interactions
Mutations affecting structure
17Missense mutations - structure
 Molecular basis of mutations affecting folding & stability
 Altered conformation of protein backbone – mutations concerning
residues with specific backbone angles (especially glycine and proline)
 Changes in charge/hydrophobicity
 Introducing hydrophilic/charged residue into the protein core
 Introducing hydrophobic residue onto the protein surface
NOTE:
• Glycine – the most
flexible amino acid
• Proline – the most rigid
Mutations affecting structure
18Missense mutations - structure
 Mutations can reduce solubility or increase aggregation
 Alterations on the surface residues may affects the solubility
(ex: reduction of charge)
 Hydrophobic mutations can increase protein aggregation
 Aggregating proteins usually have high level of β-structures
 Aggregation modulated by short specific sequences
 Aggregation-prone regions (APRs) are sequences of 5-15
hydrophobic residues
 They tend to stack and form amyloid fibrils (cross-β spines)
 Some mutations can increase the propensity to form such
amyloid structures
Mutations affecting function
19Missense mutations - function
 Effect on binding and catalysis
 Binding sites are tuned to bind specific molecules and
stabilize transition states
 Mutations can improve or disrupt the binding and catalysis
 Example – drug-resistance of HIV-1 protease mutants
 Loss of interactions with inhibitors
Ile84Val
3x higher Ki
Ile50Val
37x higher Ki
Means: isoleucine in position 84
was mutated to valine
Mutations affecting function
20Missense mutations - function
 Effect on ligand transport
 Pathways are adjusted to permit transport of specific molecules
 Mutations can speed-up or disrupt their transport or allow the
transport of different molecules
Leu177Trp => tunnel
becomes almost closed
release of products 500x slower
Mutations affecting function
21Missense mutations - function
 Effect on protein dynamics
 Dynamics enables proteins to adapt to their binding partners and
interchanging between conformations
 Mutations can:
 Make regions more rigid (targeting hinge or very mobile regions,
ex.: loops ) -> reduced adaptability
 Increase flexibility of rigid regions (targeting residues with many
contacts in mobile elements) -> increased adaptability
 These change may affect activity, specificity or even recognition
Mutations affecting function
22Missense mutations - function
 Effect on protein localization
 After translation, the protein must be translocated to the appropriate
cellular compartment
 Translocation can be regulated by short sequences (Signal Peptides)
on the N-terminus, by Translocation Complexes, Chaperones, etc.
 Mutations can disrupt or alter the signal, or complex formation ->
protein fails to be transported to the correct subcellular location
 Missing protein -> inactive reaction pathways or unregulated
signaling cascades
 Mislocalized protein -> active in the wrong cellular
compartment, causing harmful effects
Prediction of mutational effects
23Prediction of mutational effects
 Identification of mutable residues
 Prediction of the effects on structure
 Prediction of pathogenicity
Identification of mutable residues
24Prediction of mutational effects - mutable residues
 What is it?
Identification of mutable residues
25Prediction of mutational effects - mutable residues
 The effect of mutations on the protein can be predicted
directly from the role of the modified residue
 Mutation of evolutionary conserved residues
 Residues important for protein function or stability tend to be
highly conserved over evolution
 Mutation of highly conserved residues -> often lead to
destabilization or loss of function
 Mutation of highly variable residues -> often neutral
26
 Mutations affecting stability & folding
 Mutation of residues with many contacts or with favorable
interaction energy -> often destabilizing or compromise folding
 Mutation of residues in protein core -> often destabilizing
 Small residue to large -> steric clashes
 Large to small -> loss of contacts (creation of a void)
 Polar to non-polar -> loss of H-bond
 Neutral to charged -> introduction of isolated charge
 Mutation of residues on protein surface (often neutral)
 Polar to hydrophobic -> desolvation penalty (destabilizing)
 Mutation involving proline or glycine -> altered conformation
Identification of mutable residues
Prediction of mutational effects - mutable residues
27
 Mutations affecting function
 Mutation of residues in binding or active sites -> modify binding
or catalysis
 Mutation of residues in transport pathways -> modify transport
 Mutation of hinge or mobile residues, residues on loops with many
contacts -> modify flexibility
 Mutation of residues directing protein localization -> mislocalization
of proteins
Identification of mutable residues
Prediction of mutational effects - mutable residues
28
 Tools for annotating (identifying) the role of residues
 Individual tools for specific analysis
 Evolutionary conservation – ex:. ConSurf, …
 Residue contacts – ex: Contact Map Web Viewer, …
 Residue interactions – ex: Protein Interaction Calculator, …
 Accessible surface area – ex: AsaView, Naccess, …
 Binding sites – ex: CASTp, metaPocket 2.0, meta-PPISP, …
 Transport pathways – ex: CAVER 3.0, POREWALKER, …
 Protein dynamics – ex: NMA, molecular dynamics, …
 Protein localization – ex: SignalP, TargetP, Phobius, TMHMM, …
Identification of mutable residues
Prediction of mutational effects - mutable residues
29
 HotSpot Wizard – meta-server combining several tools
 http://loschmidt.chemi.muni.cz/hotspotwizard/
 Homology modelling, MSA, conservation, correlation, pockets and
tunnels detection, docking, stability prediction, design of smart library
Identification of mutable residues
Prediction of mutational effects - mutable residues
Functional hot-spots Stability hot-spots (flexibility)
Stability hot-spots (evolution)
P
P
P
P
P
P
P
P
P
P
P
P
P P P
W
W
- - - -
G
G
G
G
G
G
G
G
G
G
GP
P
P
P
P
P
P
P
P
P
R
R
R
R
R
R
R
R
R
R
R
M
M
M
M
M
M
M
M
M
M
M
I
I
I
I
I
I
I
I
I
I
I
T
T
T
T
T
T
T
T
T
T
Y
Y
Y
Y
Y
Y
Y
Y
Y
A
A
A
A
A
A
A
A
A
A
A
S
S
S
S
S
S
S
S
S
S
W
W
W
W
W
W
W
W
W
W
W
W
C
C
C
C
C
C
C
C
H
H
H
H
H
H
H
H
S
S
S
S
S
S
S
S
S
S
S
L
L
L
L
L
L
L
L
L
L
L
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
L
L
L
L
L
L
L
L
L
L
LI
I
L
L
Y
Y
Y R
Correlated hot-spots
P
P
P
P
P
P
P
P
P
P
P
P
P P P
W
W
- - - -
G
G
G
G
G
G
G
G
G
G
GP
P
P
P
P
P
P
P
P
P
R
R
R
R
R
R
R
R
R
R
R
M
M
M
M
M
M
M
M
M
M
M
I
I
I
I
I
I
I
I
I
I
I
T
T
T
T
T
T
T
T
T
T
Y
Y
Y
Y
Y
Y
Y
Y
Y
A
A
A
A
A
A
A
A
A
A
A
S
S
S
S
S
S
S
S
S
S
W
W
W
W
W
W
W
W
W
W
W
W
C
C
C
C
C
C
C
C
H
H
H
H
H
H
H
H
S
S
S
S
S
S
S
S
S
S
S
L
L
L
L
L
L
L
L
L
L
L
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
L
L
L
L
L
L
L
L
L
L
LI
I
L
L
Y
Y
W
W
W
R
R
R
K
K
K
K
K
W
W
W
D
D
D
E
E
E
E
E
V
V
V
Identification of mutable residues
Prediction of mutational effects - mutable residues 30
Identification of mutable residues
Identification of mutable residues
Prediction of mutational effects - mutable residues 32
33
 Prediction of mutant structures – general workflow
 Mutated residue and its surroundings represented by rotamers
from rotamer library (conformations derived form X-ray structures)
 The best set of rotamers selected by Monte Carlo approach
 Optionally – energy minimization, backbone flexibility
 Comparing structures of mutant and native protein -> assessment
of the mutational effect (G = GMut - GNative)
 Available tools
 Geometric: PyMOL; WhatIF
 Energy-based: FOLDX, Rosetta-ddG
 Homology: Swiss Model, MODELLER, etc.
Prediction of effects on structure
Prediction of mutational effects - structure
34
 PyMOL
 https://pymol.org/
 Mutagenesis module
 User can choose rotamers and visualize potential clashes
 Very fast; fixed backbone; no mutational scoring
Prediction of effects on structure
Prediction of mutational effects - structure
35
 WHATIF
 https://swift.cmbi.umcn.nl/servers/html/index.html
 Web server for multiple purpose including mutagenesis
 Very fast
 Fixed backbone conformation
 Construction of single mutants only, or stabilizing Proline mutations
 No scoring function
Prediction of effects on structure
Prediction of mutational effects - structure
36
 FOLDX
 http://foldxsuite.crg.eu/
 Stand alone, with plug-in to Yasara modeling tool
 Fast (minutes)
 Fixed backbone conformation
 Construction of single or multiple mutants
 Empirical scoring function for calculation of stability change (ΔΔG)
Prediction of effects on structure
Prediction of mutational effects - structure
37
 FOLDX
Prediction of effects on structure
Prediction of mutational effects - structure
Prediction of effects on structure
38
 Rosetta-ddG
 Under https://www.rosettacommons.org/
 Stand alone with bash and python scripts available
 Slow (hours-days)
 Fixed or flexible backbone conformation
 Construction of single or multiple mutants
 Empirical force field for calculating structure and stability of
wild-type and mutant
 Construction of PDB and prediction of stability change (ΔΔG)
Prediction of mutational effects - structure
Prediction of pathogenicity
39
 Prediction of impact of mutation on protein function
 Tools employ machine learning approaches
 Trained on functional experimental data
 Predictions can be based on sequence only
 Qualitative results – i.e. deleterious versus neutral
 Primarily intended for pathogenicity prediction (leading to disease)
 Available tools
 MutPred, SNAP, PhD-SNP, SIFT, MAPP …
 PredictSNP – meta server combining many tools
Prediction of mutational effects - pathogenicity
40
 PredictSNP:
 http://loschmidt.chemi.muni.cz/predictsnp/
 Combines many tools for Protein or DNA assessment of SNPs
Prediction of pathogenicity
Prediction of mutational effects - pathogenicity
41
Prediction of pathogenicity
Prediction of mutational effects - pathogenicity
Prediction of pathogenicity
42
 There are many more tools out there
Prediction of mutational effects - pathogenicity
43Rational design of proteins
 Protein engineering: sometimes we can use mutagenesis to
rationally design proteins according to our needs
 Properties that can be modified by mutagenesis
 Such as?...
Rational design of proteins
44Rational design of proteins
 Protein engineering: sometimes we can use mutagenesis to
rationally design proteins according to our needs
 Properties that can be modified by mutagenesis
 Stability
 Function
 Binging site (catalytic activity or substrate specificity)
 Macromolecular interface
 Molecular tunnels/channels
 Solubility
Rational design of proteins
45
 Prediction of stability change upon mutation
 Structure of mutant protein may not be produced
 Tools often employ
 Empirical scoring functions
 Evolutionary conservation analysis (ex: back-to-consensus)
 Machine learning approaches
 Available tools
 Energy-based: Rosetta-ddG, FOLDX 
 Evolution-based: FireProtASR
 Hybrid approaches: FireProt, PROSS
Rational design of proteins - stability
Rational design: stability
46
 FireProt
 https://loschmidt.chemi.muni.cz/fireprotweb
 In silico analysis of all possible
mutations
 Energy- and evolution-based analyses
 Multiple-point mutants for
gene synthesis
Rational design of proteins - stability
Rational design: stability
47
 FireProt
Rational design of proteins - stability
Rational design: stability
48
 FireProt
Rational design of proteins - stability
Rational design: stability
49
 PROSS
 https://pross.weizmann.ac.il/step/pross-terms/
 Combination of mutations “allowed” by conservation analysis and
Rosetta calculations (energy)
Rational design of proteins - stability
Rational design: stability
50
 FireProtASR
 https://loschmidt.chemi.muni.cz/fireprotasr
 Ancestral sequence reconstruction (ASR)
 Automated ancestral inference & phylogenetic tree
 Useful to find stable ancestral enzymes
Rational design of proteins - stability
Rational design: stability
51
 FireProtASR
 https://loschmidt.chemi.muni.cz/fireprotasr
 Ancestral sequence reconstruction (ASR)
 Automated ancestral inference & phylogenetic tree
 Useful to find stable ancestral enzymes
Rational design of proteins - stability
Rational design: stability
 RosettaDesign
 http://rosettadesign.med.unc.edu/
 Monte Carlo sampling (random search) to predict minimum-energy
structure of mutants
 Predicts free energy changes upon mutations (G)
 Helps design mutations to optimize the binding site and increase
interactions with a ligand/substrate
52Rational design of proteins - function
Rational design: function
 PocketOptimizer
 https://github.com/Hoecker-Lab/pocketoptimizer/
 Aimed at maximizing the affinity of a binding site towards a ligand
 Modular pipeline with different tools
 Flexibility, docking, mutagenesis, energy calculation
 Predicts global minimum-energy designs
53
Rational design: function
Rational design of proteins - function
 FuncLib
 https://funclib.weizmann.ac.il
 To redesign and/or optimize binding site
 Utilizes evolution (conservation) and Rosetta calculations (energy)
to introduce multiple-point mutations to modify the properties of
the binding site
 Can be used to improve the binding affinity towards a ligand
 Outputs up to 50 multiple-point mutants for protein synthesis
54
Rational design: function
Rational design of proteins - function
 FuncLib
55
Rational design: function
Rational design of proteins - function
 AffiLib
 https://affilib.weizmann.ac.il
 To optimize protein-protein interface
 Utilizes evolution (conservation) and Rosetta (energy) to introduce
mutations and optimize macromolecular interface
 Suggests mutations on the interface residues to improve the
binding affinity
 Outputs up to 50 multiple-point mutants for protein synthesis
56Rational design of proteins - function
Rational design: function
57
 Mutation Cutoff Scanning Matrix (mCSM-PPI2)
 http://biosig.unimelb.edu.au/mcsm_ppi2/
 To optimize protein-protein interface
 Based on machine learning, evolutionary data and energy (FoldX)
 Provides mutational G
 Modes of calculations
 Single mutation – single point mutations on interface
 Mutation list – single mutations accordingly to a user
 Alanine scanning (all interface residues are mutated to alanine)
 Systematic – position saturation (all interface residues are
mutated to all other 19 amino acids)
Rational design of proteins - function
Rational design: function
 Aggrescan3D; SoluProt (see lecture 6 - Analysis of protein structures)
 SolubiS
 https://solubis.switchlab.org/
 To identify stabilizing mutations that reduce the aggregation tendency
of a protein
 1) Identifies exposed APRs
 2) Introduces “gatekeeper” residues (P, R, K, D and E) into APRs
 3) Assesses the stability changes of mutations (ΔΔG)
58Rational design of proteins - solubility
Rational design: solubility
References I
 Ng, P. C. & Henikoff, S. (2006) Predicting the effects of amino acid
substitutions on protein function. Annual Review of Genomics and
Human Genetics 7: 61-80.
 Thusberg, J. & Vihinen, M. (2009) Pathogenic or not? And if so, then
how? Studying the effects of missense mutations using bioinformatics
methods. Human Mutation 30: 703-714.
 Potapov, V. et al. (2009) Assessing computational methods for
predicting protein stability upon mutation: good on average but not in
the details. Protein Engineering, Design & Selection 22: 553-560.
References 59
References II
 Khan, S. & Vihinen, M. (2010) Performance of protein stability
predictors. Human Mutation 31: 675-684.
 Bendl, J. et al. (2016) PredictSNP2: A Unified Platform for Accurately
Evaluating SNP Effects by Exploiting the Different Characteristics of
Variants in Distinct Genomic Regions. PLOS Computational Biology 12:
e1004962.
 Musil, M. et al. (2019) Computational Design of Stable and Soluble
Biocatalysts. ACS Catalysis 9: 1033−1054.
 Planas-Iglesias, J. et al. (2021) Computational design of enzymes for
biotechnological applications. Biotechnology Advances 47:107696
References 60