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Introduction to Pharmaceutical Biotechnology, Volume 2 (Second Edition)
• Dihydrofolate reductase: In this enzyme, substitution of a single amino acid,
aspartic acid (Asp) by asparagine (Asn), results in a decrease in specific
activity by a thousand fold, signifying that aspartic acid is significant for the
active site. Other similar modifications were also examined.
• Human-13 interferon: Removal of the three cysteine residues led to an
improvement in stability of the enzyme.
• Insulin: Contains A and B chains connected by a C-peptide of 35 amino acids.
It was observed that a sequence of six amino C-peptides was satisfactory for
the connecting function.
• Lactose permease (product of ‘y’‘lac’ operon): This enzyme is involved in
delivery of lactose and, a cysteine to glycine replacement showed that this
amino acid was vital for delivery. Further, of four histidine residues, two at
positions 35 and 39 do not play any essential role in transport while the
mutation in any of the other two at positions 208 and 322 result in a transport
function.
• T4 lysozyme: A mutation of isoleucine to cysteine in this enzyme leads to
formation of a disulfide bridge, leading to thermal stability and a 200-fold
increase in enzyme activity even at 67 °C.
• Trypsin: This can be restructured to have modified substrate specificity.
• β-lactamase: This bacterial derived enzyme hydrolyzes and inactivates the β-
lactam ring of penicillin derivatives and allows delivery across the inner
membrane. In the course of transport a polypeptide (23 amino acids) is
cleaved off. Comprehensive examination suggests that transport and processing are not influenced by this polypeptide of 23 amino acids alone. An active
site comprising the amino acid serine has also been recognized, as its
substitution by cysteine results in a reduction in the activity of this enzyme.
• λ repressor: This protein could be engineered to develop a specific site for cro-
protein, since the alteration led to the development of a cro recognition site.
• Subtilisin: The serine protease subtilisin is an important industrial enzyme as well
as a model for understanding the enormous rate enhancements effected by
enzymes. Mutations in well over 50% of the 275 amino acids of subtilisin have
been reported in the scientific literature. Most subtilisin engineering has involved
catalytic amino acids, substrate binding regions and stabilizing mutations.
Additional effective modification of substrate specificity includes the subtilisin.
• Lactate dehydrogenase: A lactate dehydrogenase isolated from Bacillus
stearothermophilus was modified individually by each of the three substitu-
tions of amino acids.
10.14 Computational approaches in protein engineering
Computational methods in protein engineering seek to interpret, design, and finetune proteins for several uses. This may be achieved by utilizing the power of
computational tools and algorithms. These techniques enable the exploration of the
vast protein design, which would be difficult to explore experimentally due to time
and resource constraints [25].
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10.14.1 Molecular dynamics simulations
An effective theoretical tool for examining the atomic-scale characteristics of
proteins is a simulation of molecular dynamics (MD). MD simulations are critical
for investigating the structure–function relationships of proteins, which is necessary
to understand biological processes such as protein interactions and ligand binding.
MD simulations may convert protein dynamics data into meaningful statistics,
which can then be used to investigate thermodynamics and kinetics which are the
two concepts crucial to understanding biological systems [26]. Moreover, recent
improvements in simulation tools have allowed for the precise prediction and
characterization of these processes, which, correctly used in structure-based drug
design (SBDD) and are very helpful for accelerating the drug development process.
Because of significant improvements in simulation speed, accuracy, and accessibility, simulations have become more important in molecular biology and drug
development. The simulations capture the dynamics of proteins and other biomolecules with atomic precision at unprecedentedly high temporal resolutions.
Furthermore, throughout time, the simulations’ accessibility, accuracy, and speed
have all experienced notable increases [25]. A workflow of MD simulation from
preparation to analysis is shown in figure 10.7.
10.14.2 Quantum mechanical calculations
Quantum mechanical (QM) computations help understand and simulate protein
activities at a deeper level. They thoroughly understand protein electronic structure.
This is essential for a wide variety of uses, including ligand binding, protein–protein
interactions, and enzyme catalysis. One efficient computational tool for modeling
Figure 10.7. Molecular dynamics simulation process: setup, simulation, and analysis phases with detailed
steps.
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Figure 10.8. Flowchart illustrating the process of initiating a QM/MM calculation using crystal structure
coordinates and producing MD snapshots.
protein electrostatics uses static point-charge model distributions based on a
quantum mechanical technique termed electrostatically embedded generalized
molecular fractionation with conjugate caps (EE-GMFCC) [27]. Compared to
conventional molecular mechanics (MM) force fi elds, this method has shown a
notable improvement in modeling the electrostatic potential and solvation energy of
proteins by considering both polarization and charge transfer effects [27]. Correct
scoring in protein docking relies heavily on quantum mechanical calculations, which
are utilized to create docking protocols based on quantum mechanical/molecular
mechanical computations and use quantum mechanical energy as a scoring metric.
Several instances with a wide range of binding site characteristics have shown the
effectiveness of this unique docking approach [28]. A workflow of QM/MM
simulation including detailed steps is shown in figure 10.8.
10.14.3 Docking and ligand optimization
Docking and ligand optimization are crucial tools in SBDD, facilitating the
elucidation of protein–ligand (PL) interactions (PLIs), which is fundamental for
drug discovery and development. As a rapid and cheap alternative to traditional
experimental methods, PL docking is essential for predicting the binding orientations and affinities of small molecules inside the binding site of a given protein [29].
Pose prediction and docking are both crucial in virtual high-throughput screening
for optimizing leads. It has been noted that most docking systems pitched toward
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Figure 10.9. PL docking procedure: from target and ligand preparation to docking, scoring, and postprocessing analysis.
pose prediction focus on redocking to a previously determined co-crystallized
protein structure, while often overlooking structural flexibility [30]. Ligand optimization includes carefully creating or choosing ligands with optimum binding
properties. The development of PL binding poses and the prediction of PL binding
affinities rely heavily on this step [31]. Molecular optimization, also called ligand
optimization, requires the examination of PL complex files to measure specific
parameters that determine the relationship between protein structure and ligand.
Tools like CABS-flex 2.0 have been utilized for efficient protein flexibility modeling
in this domain [32]. The docking scheme having detailed steps is represented in
figure 10.9.
10.14.4 Machine learning algorithms in protein design
The combination of machine learning (ML) and deep learning (DL) algorithms in
protein design has significantly accelerated the optimization of protein functions by
rendering a data-driven mapping of sequences to functions without requiring a
detailed model of the underlying physics or biological pathways [33]. ML,
particularly through directed evolution, has been involved in protein engineering,
accurately predicting how sequence maps function [34]. DL is a subfield of ML that
is igniting scientific revolution by making use of massive amounts of data and highpowered computers. Protein structural modeling is used for structure prediction
from amino acid sequences and determined protein design [35]. The continuous
protein design issue may be transformed into a discrete one by using ML-based
algorithms, which may have an effect on the development of novel molecular
therapeutics for human diseases [36]. Various ML algorithms have been extensively
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applied in pharmaceutical protein development, creating a significant development
in therapeutic protein engineering [37].
10.15 Directed evolution techniques
Directed evolution is a robust methodology employed in protein engineering to
enhance or modify the attributes of biomolecules for diverse applications. The
process parallels natural evolution on a consolidated timescale, permitting rapid
selection of biomolecule variants with desirable traits for specific applications [38].
There are two main phases to this method: creating genetic variety (library creation)
and separating out interesting variations. Directed evolution is a powerful approach
for creating new or better biological functionalities because it accelerates the natural
evolution process of biological molecules and systems in a controlled setting via
repeated rounds of gene diversification and library screening and selection [39].
10.15.1 Error-prone PCR
Error-prone PCR (epPCR) is a pivotal technique within directed evolution, utilized
mainly to generate libraries of DNA molecules with a broad mutational spectrum,
thus operating the genetic diversification required for directed evolution. epPCR
introduces random mutations throughout a DNA sequence during the replication
process. This method is particularly effective in directed evolution for creating
diverse genetic variants from a given DNA sequence, which can then be screened or
selected for desired traits or functionalities. The process of error-prone PCR
represents the initial step in the directed evolution workflow, paving the way for
the subsequent screening or selection processes to isolate promising variants. By
employing epPCR, systematically exploring the genetic landscape and unveil novel
or enhanced biomolecule functionalities, thereby driving innovation in protein
engineering and other fields of molecular biology [25].
10.15.2 DNA shuffling
In directed evolution, DNA shuffling plays a crucial role by facilitating the in vitro
recombination of a single gene or pools of homologous genes to generate new gene
variants. The method involves cutting genes into pieces of varying sizes and then
using PCR to reassemble the pieces back into functional genes. Recombination
occurs as a result of this reassembly via self-priming because of PCR template
switching [ 40]. DNA shuffling has been likened to ‘sexual PCR’, allowing for the
recombination of homologous DNA sequences during in vitro molecular evolution,
thereby generating a diverse set of genetic variants. Applications of DNA shuffling
extend to enhancing metabolic pathways, modifying active site residues within
enzymes to boost catalytic rates, and creating synthetic operons, all of which are
essential for advancing molecular biology and protein engineering techniques [40].
Moreover, DNA shuffling has been utilized to develop new generation vaccines to
counter rapidly evolving pathogens by overcoming natural selection and environmental pressures [41].
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10.15.3 Saturation mutagenesis
The semi-rational protein engineering method known as saturation mutagenesis
involves the whole or partial replacement of a target residue with any other naturally
occurring amino acid. This method allows for the precise alteration of single or
multiple amino acid residues, thereby generating a library of single-residue substitutions for further analysis and selection [42]. Saturation mutagenesis is used to
identify sequence determinants of protein structure, stability, and function, particularly in situations where phenotypic readouts are easily accessible. A straightforward and productive approach to understanding protein structure and function is
saturation mutagenesis coupled with deep sequencing [43].
10.15.4 Phage display
It is possible to study protein–protein, protein–peptide, and protein–DNA interactions
with the use of a method called phage display. There is a direct link between the DNA
that makes up the genotype and the phenotype that is expressed as a protein on the
surface of bacteriophages via the expression of proteins or peptide sequences. Finding
peptides and antibodies with high affinity and specificity for their target relies heavily on
this link. Screening is performed by comparing a phage display library containing many
different peptide or protein sequences to a target molecule [44]. Phages are selected
based on the presence of peptides or proteins with a high affinity for the target. Next, we
sequence the DNA of these phages to identify the peptide or protein sequences that
exhibit the desired binding properties. After that, the phages are multiplied. Research
into protein–protein and protein–ligand interactions, as well as drug discovery and
vaccine development, has made extensive use of phage display. It is a useful technique in
modern molecular biology and protein engineering, having been used to find and
produce novel ligands, antibodies, and enzyme inhibitors, among other things [45].
10.16 Post-translational modifications
Proteins’ functional characteristics are altered by a series of chemical reactions known
as post-translational modifications (PTMs), which occur after proteins are synthesized.
These modifications significantly influence proteins’ behavior, activity, and interactions, thereby playing a vital role in regulating various biological processes [46].
10.16.1 Glycosylation engineering
Glycosylation engineering is a specialized domain focused on manipulating the
glycosylation patterns of proteins to enhance or modify their functionalities.
Glycosylation refers to the covalent attachment of glycans (sugars) to proteins, and it
is a common PTM with profound implications on protein stability, solubility,
immunogenicity, and bioactivity. The commercial demand for glycosylation engineering covers the biopharmaceutical sector, mainly for producing biological therapeutics
with defined glycosylation patterns [47]. Glycoengineering methodologies are developed
to modify glycan structures on proteins, thereby potentially improving their properties,
such as enhancing the therapeutic efficacy of biopharmaceuticals [48].
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10.16.2 Phosphorylation engineering
Phosphorylation is one of the most prevalent and new PTMs, regulating many
cellular signaling pathways that control cell proliferation, survival, and differentiation. Enzymes called kinases (which add phosphate groups) and phosphatases
(which remove phosphate groups) play essential roles in phosphorylation engineering (which remove phosphate groups). The phosphorylation state of proteins is
altered by these enzymes, which affects the proteins’ function and their interactions
with other biomolecules [49]. Phosphorylation engineering comprehends techniques
to analyze phosphorylation sites and their functional relevance, employing phosphoproteomic workflows to sove the complexities of phosphorylation networks
within the cellular environment [50].
10.16.3 Methylation and acetylation
Methylation and acetylation are prominent PTMs impacting gene expression
through epigenetic modifications. Histones may be methylated or acetylated,
respectively, with methylation adding a methyl group to DNA or histones. Both
acetylation and methylation are metabolically sensitive and may significantly impact
how genes express themselves. Acetylation usually increases gene expression while
methylation suppresses it [51]. Recently, studies have revealed that histone acetylation may operate as a DNA methylation target, suggesting a functional link
between both systems. This functional connection might be significant in pathological conditions like atherosclerosis [51].
10.16.4 PEGylation for enzyme stability
PEGylation is the covalent attachment of polyethylene glycol (PEG) to proteins and
is an essential strategy to increase the stability and solubility of therapeutic proteins.
Enhancing the pharmacokinetic characteristics of protein therapeutics requires
PEGylation since it has been associated with higher protein solubility, increased
proteolysis resistance, lower toxicity, and decreased protein aggregation [52].
Significant progress has been made over the last three decades in addressing poor
solubility, protein stability, shelf life, and bioactivity by developments in
PEGylation procedures. Successful therapeutic uses of proteins rely on their desired
qualities, which can only be guaranteed by preventing the formation of undesirable
protein aggregates. Enzyme stability engineering benefits from the precision and
efficacy of PEGylation conducted at specific sites on the protein [53].
10.17 Structural flexibility and allosteric regulation
The concepts of structural flexibility and allosteric regulation are closely related in
protein study. Structural flexibility is the ability of a protein to undergo conformational
changes. Conversely, the process by which a chemical interaction at one site on a
protein may affect the function at another site is known as allostery [52, 54].
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10.17.1 Intraprotein communication pathways
Intraprotein communication pathways are essential for proteins to function and be
appropriately regulated. Information (in the form of structural modifications to the
protein) may be sent from one part of the protein to another via these routes. The
protein’s structure may be altered in response to a stimulus, activating a functional
reaction at a new place. Understanding these pathways is crucial for unraveling the
complex mechanisms that run protein activity and regulation [55].
10.17.2 Allosteric site identification
One of the first steps in learning about and using allosteric control is identifying
allosteric sites on a protein where small molecules or other proteins interact to create
an allosteric response. Based on protein structure, approaches for predicting
allosteric sites have been developed. For instance, allosteric interactions may be
found in pockets and pathways that may be uncovered using computational
methods. Allosteric regulation is defined as the process that begins when a small
molecule effector or inhibitor binds to a location on a protein that is not the active
site. Allosteric regulation is discussed in terms of its efficacy and robustness in
controlling protein activity across various biological functions [56]. The relevance of
changes in protein conformation in allosteric regulation and function emphasizes
how crucial it is to think of proteins as conformational ensembles rather than static
structures to comprehend allosteric pathways [57]. Allostery occurs when a protein’s
active or main site is modified by binding a ligand or another protein at a different
position on the protein [ 58]. Govindara et al (2023) describe modern computational
approaches applied to allosteric communication, which contribute to the finding and
understanding of allosteric sites and pathways [58].
10.17.3 Modulator design
Modulator design, particularly allosteric modulators, is innovative in drug discovery
and protein engineering. Allosteric modulators bind to allosteric sites on proteins to
modulate their activity. Finding allosteric sites and creating compounds that can
bind to them is crucial for developing allosteric modulators that can cause the
required conformational changes in the target protein. Different methodologies have
been employed for the identification of allosteric binding sites and modulators,
including structure-based and ligand-based drug design methodologies [58]. There is
also a method called a structure-based allosteric modulator design which is proposed
to guide the design of allosteric modulators. Moreover, the discovery of allosteric
modulators can transition from chance to a more structured approach through
structure-based design [59].
10.17.4 Coupling allosteric regulation with catalytic function
The coupling of allosteric regulation with catalytic function is vital to many
enzymes’ operational efficiency and regulation. Allosteric regulation is a robust
mechanism employed by proteins for regulating activity and adaptability during
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processes such as catalysis, signal transduction, and gene regulation. Allosteric
regulation is responsible for the modifying of enzyme activity in living organisms,
and it has also been used to construct artificial switchable catalysts by embedding
catalytically active groups in allosteric scaffolds [60]. Allosteric crosstalk plays a
significant role in activity modulation and function modification of proteins, and
understanding allostery is crucial for advancing the discovery of allosteric drugs.
Additionally, multistate models of enzyme catalysis and enzyme allostery have been
developed to capture the large-scale conformational changes and the coupling
between allosteric regulation and catalytic function in enzymes [61].
10.18 Protein–protein and protein–ligand interactions
Protein interactions with other proteins or ligands are fundamental to the functioning of biological systems. These interactions dictate a variety of cellular processes
and understanding them is crucial in fields like drug discovery and molecular
biology. Protein–protein interactions (PPIs) are essential in life processes and are
associated with various diseases. Because of their association with cancer, infectious
diseases, and neurological disorders, irregular PPIs are promising therapeutic
development targets. PPI modulators, such as small compounds, peptides, and
antibodies, have been developed recently, with some entering clinical trials and
being licensed for sale [62].
10.18.1 Characterizing binding sites
Identifying and characterizing binding sites is critical for understanding protein
interactions. Binding sites are the specific regions on a protein where another
molecule, be it a protein or a ligand, interacts. Binding kinetics, thermodynamic
principles, and driving forces of binding are only some of the methodologies and
models created to comprehend the physicochemical processes underpinning PLIs
[63]. Techniques such as ligand-based methods are used to anticipate possible PLIs.
The conception is that chemically identical ligands are more likely to bind to
chemically identical protein targets [64].
10.18.2 Fine-tuning affinity and specificity
Techniques like ligand-based methods are used to anticipate possible PLIs. The idea
is that if two ligands are chemically similar, they will have a greater chance of
binding to a protein with the same chemical make-up [65].
10.18.3 Interaction networks
The intricate interactions between proteins and other macromolecules in cells may
be easier to understand within the context of an interaction network. These networks
may be seen and investigated to provide insight on cellular processes and molecular
dynamics. Biological networks, such those involving PPI, may be compared with the
help of network alignment. It takes into account the topological similarity of the
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surrounding biological nodes across networks as well as the biological linkages
between biological nodes. The behavior of molecular components may be better
understood as a result. PPI networks incorporate a variety of technologies that
might be used in drug development processes. These technologies consist of the yeast
two-hybrid system, local and global network alignment, and alignment [66].
10.18.4 Biophysical methods for interaction studies
Biophysical approaches are critical for researching the interactions of macromolecules such as proteins. These approaches may offer quantitative data on
binding affinity, kinetics, and other aspects of the interaction. The FRET (fluorescence resonance energy transfer) method is a strong tool for analyzing molecular
interactions. It may give real-time data on the distance between interaction partners
and how they are orientated in relation to one another. Surface plasmon resonance
(SPR) is a technique often used to investigate molecular interactions. However, from
the affinity of the interaction, it may give real-time information on the processes of
binding and dissociation. The thermodynamics of binding interactions may be
quantified using an isothermal titration calorimetry (ITC) technique [67]. It provides
data on the energetics of interactions regarding enthalpy, entropy, and binding
affinity. NMR spectroscopy and x-ray crystallography techniques are employed to
get high-resolution structural data on protein complexes. They can provide
thorough explanations of the chemical underpinnings of interactions. Protein
interaction analysis and prediction may be done using various software programs
and computational techniques. These techniques may give us a more profound
knowledge of interaction networks and supplement experimental data [68].
10.19 Applications in synthetic biology
Synthetic biology expands the spectrum of created creatures and valuable results by
applying engineering ideas to biological systems [69]. It demonstrates the field’s
adaptability by making possible situations outside of the laboratory, such as
bioproduction, biosensing, and others [70].
10.19.1 Metabolic pathway engineering
Metabolic pathway engineering (MPE) is about modifying organisms’ metabolic
pathways to enhance the production of desired compounds. It is connected with
synthetic biology, where it provides the necessary components and insights, and MPE
applies this knowledge for optimization [71]. Techniques involve the selection of
suitable host organisms, utilizing various genetic components and engineering tools for
pathway modification. Whole-cell and cell-free systems, for instance, are used in
bioproduction scenarios for the continuous and on-demand production of biochemical
therapies. These systems need genetically and environmentally robust field-deployable
platforms to keep metabolism going in a variety of environments [70].
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