DESIGN OF INORGANIC BINDING PROTEINS

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DESIGN OF INORGANIC BINDING PROTEINS RAM
SAMUDRALA ASSOCIATE PROFESSOR UNIVERSITY OF
WASHINGTON How can we design peptides and
proteins capable of binding to inorganic
substrates with specific selectivity and affinity?
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MOTIVATION
The functions necessary for life are undertaken
by proteins. Protein function is mediated by
protein three-dimensional structure. A vast
number of computational methodologies have been
developed for the analysis and modelling of the
sequences and structures of naturally occurring
proteins. We can harness these knowledge- and
biophysics-based computational methodologies to
design peptides and proteins capable of binding
to inorganic substrates with specific affinity
and selectivity. Goal is to develop generalised
computational techniques to construct molecular
building blocks based on peptides and proteins
that can be easily assembled to design higher
order structures. Applications in the area of
medicine, nanotechnology, and biological
computing.
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KNOWLEDGE-BASED DESIGN
Proteins that are evolutionarily related
generally have similar sequences, structures, and
functions. We hypothesised that this applies to
experimentally discovered peptides capable of
binding to inorganic substrates. We then
examined similarity of sequences between
experimentally discovered peptides and random
peptide sequences using standard sequence
comparison tools. Random peptide sequences most
similar to a particular group of experimentally
discovered peptides were considered to possess
the same functional property. Some examples of
experimentally discovered peptides (from Mehmet
Sarikaya)
Platinum binders DRTSTWR TSPGQKQ IGSSLKP
Quartz binders RLNPPSQMDPPF QTWPPPLWFSTS LTPHQTTM
AHFL
Hydroxyapatite binders MLPHHGA TTTPNRA PVAMPHW
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SIMILARITY ANALYSIS
The similarity of two protein or peptide
sequences is determined by their optimal
alignment score (PSS) according to a scoring
matrix
PSS12
The scoring matrix determines the similarity of
any two amino acids based on their evolutionary
and biophysical preferences. BLOSUM and PAM are
two popular scoring matrices derived from amino
acid preferences observed in representative sets
of proteins
The optimal alignment and score is determined
using dynamic programming.
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SIMILARITY ANALYSIS
Our goal is to determine to the total similarity
score (TSS) of one set of sequences (which may
contain only one member) to another set of
sequences. The total similarity score is
effectively a normalised sum of pairwise
similarity scores between sequences in the two
sets
Initial studies were done by Ersin Emre Oren
using the BLOSUM and PAM matrices on a set of 39
strong (10), moderate (14) and weak (15) quartz
binding sequences provided by Mehmet Sarikaya.
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PRIMARY HYPOTHESIS VERIFICATION
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BACKTESTING PREDICTIVE POWER
The total similarity score of each quartz binder
to the set of strong quartz binders were
calculated and used as an indicator of binding
affinity.
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OPTIMISATION OF SCORING MATRICES
We perturbed the PAM 250 scoring matrix
systematically to produce a higher strong-strong
self-similarity and lower strong-weak
cross-similarity score, and backtested the
predictive power of the new QUARTZ I matrix.
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OPTIMISATION OF SCORING MATRICES
We perturbed the PAM 250 scoring matrix
systematically to produce a higher strong-strong
self-similarity and lower strong-weak
cross-similarity score, and backtested the
predictive power of the new QUARTZ I matrix.
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KNOWLEDGE-BASED PEPTIDE DESIGN
We hypothesised that random sequences similar to
a set of sequences with a particular functional
property must also possess that property. We
calculated the TSS of 1,000,000 random sequences
(12,000,000 aa) to the set of experimentally
determined strong quartz binding sequences.
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EXPERIMENTAL VERIFICATION
Three sets of experiments were performed by
Mehmet Sarikayas group to validate the
computationally designed sequences.
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DESIGN OF SECOND GENERATION MATRICES
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DESIGN OF CROSS-SPECIFIC BINDERS
Quartz matrix scores
Hydroxapatite matrix scores
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DESIGN OF CROSS-SPECIFIC BINDERS
This procedure can be generalized to any number
of inorganic substrates as long as there is
enough initial data to calculate the TSS.
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CHARACTERISTICS OF SCORING MATRICES
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CHARACTERISTICS OF SEQUENCES
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CHARACTERISTICS OF SEQUENCES
Strong quartz binding peptides likely have
extended conformations since the bulky
hydrophobic side chains of Tryptophan (W) or
Phenlyalanine (F) in a small peptide require
adequate spacing, and the Proline (P) residue
reduces conformational flexibility. Weak quartz
binding peptides have residues that may allow for
collapse of the peptides either directly (through
the formation of disulphide and salt bridges or
collapse of the smaller hydrophobes) or
indirectly (Glycine (G), which increases
conformational flexibility).
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BIOPHYSICS-BASED DESIGN
Characterise sequences and structures of
naturally occurring proteins in terms of their
total similarity scores using different scoring
matrices. This will produce a database of
sequences with predicted and known structures
with specific selectivity and affinity to
different inorganics. This database can be
analysed for atom-atom preferences, torsion angle
preferences, and other characteristics to define
energy functions and move sets for performing
protein structure simulations. We will combine
this with our all-atom energy function capable of
handling inorganics and our protein structure
simulation software. Design higher order
protein-like scaffolds with specific
functionalities
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ACKNOWLEDGEMENTS
People Ersin Emre Oren Mehmet Sarikaya and his
group Candan Tamerler-Behar Samudrala
group Primary support from Defense University
Research Initiative on NanoTechnology Genetically
Engineered Materials Science and Engineering
Center Other support from National Institutes
of Health National Science Foundation Kinship
Foundation