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102 4 Bioisosteric Replacement for Drug Discovery Supported by the SwissBioisostere Database
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classical denition. Later denitions are going even further in practical sense, such
as the one of Thornber, who dened a form of non-classical isosterism characterized
by chemical and physical similarity and roughly similar biological eects [8].
4.1.2 Classical vs. Non-classical Bioisostere and Further Molecular
Replacements
The most recent denitions of bioisosterism relate to drug discovery in a pragmatic
sense, with the idea that all depend on the biological and chemical contexts of the
eld explored. Regarding biological context, the same pair of similar compounds
can display comparable pharmacological properties on a given protein target or
assay while showing divergent bioactivities on other targets or in other experimental
setups.
In addition, the eect produced by exchanginga molecular fragment in a molecule
is very dependent on the chemical context. For instance, replacing a methyl group
with a halogen atom can have dierent impacts on molecular and physicochemical
properties if it takes place as an aromatic substitution or at the end of a long alkyl
chain.
Echoing such ordinary problems of daily medicinal chemistry routine, experts in
the eld have clearly softened the criteria for alikenessin terms of both biological and
chemical contexts. Among the rened vocabulary employed, the distinction between
classical and non-classical bioisosteres is noteworthy.
As the name suggests, classical bioisosteres come from the initial denitions
of isosterism focusing on strict comparison at the atomic and electronic levels.
Atoms or groups are typically classied as monovalent, divalent, or trivalent
bioisosteres. Medicinal chemists apply such classical bioisosteric replacements
routinely. Typically, this denition applies, for example, between uorine and
hydrogen; amino and hydroxyl; thiol and hydroxyl; hydroxyl, amino, and methyl
groups (comply with Grimm’s Hydride Displacement Law); chloro, bromo, thiol,
and hydroxyl groups (relaxed criteria according to Erlenmeyer) [3]. Some modest
extensions of the concept can reasonably be seen as classical bioisosteres like
tetrasubstituted atoms (tetravalent carbon, tetrasubstituted silane, ammonium
exchanges) or very similar ring replacements (e.g. pyridine for phenyl).
Further extensions of the concept enter the territory of non-classical bioisosteres,
which can dier in molecular structures and properties, for instance in terms of
the number of atoms, or steric or electronic considerations. Well-known examples
include the replacement of carboxylic acid by tetrazole, as successfully applied for
designing nonpeptide oral angiotensin receptor antagonists and resultingin the antihypertensive drug Losartan (Figure 4.1a). In general, the tetrazole moiety shows an
acidity similar to carboxylic acid while improving other properties important for a
drug [13, 14]. In this biological and chemical context, the bioisosteric exchange also
produced stronger in vitro and in vivo activities due to better pharmacokinetics and
pharmacodynamics [9].
Although less strict than classical bioisoteres, such non-classical bioisosteric transformations still aim at mimicking some properties of a molecular fragment to be
(a)
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4.1 Introduction 103
(b)
(d)
Figure 4.1 Drug-related non-classical bioisosteres. (a) Both the bioactivity and the
bioavailability of angiotensin receptor antagonists were improved by switching from
carboxylic acid to tetrazole [9]; (b) and (c) examples of FDA-approved drugs involving
internal hydrogen bonds forming pseudo-cycles, possibly ring bioisosteres. Source: Adapted
from Refs. [10, 11]; (d) example of bioisosteric replacement of the central core of TNIK
inhibitor by cyclization [12].
(c)
replaced, even by a dierent means than sticking to an identical number of atoms
and electrons.
Conceptually, it is possible to go even further and apply molecular replacements of fragments without necessarily trying to mimic any property a priori.
The objective of retaining bioactivity is perforce linked to molecular recognition
at the target, and hence, any modication of small molecule ligand should be
meant not to alter the position in space of chemical features essential for the
recognition, a.k.a. the pharmacophore. Keeping the pharmacophoric points at
the correct location can be achieved by more subtle and sophisticated means
than exchanges of similar moieties as described previously. For instance, taking
advantage of intramolecular interactions to mimic a ring with a noncyclic moiety
104 4 Bioisosteric Replacement for Drug Discovery Supported by the SwissBioisostere Database
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is exemplied by the internal hydrogen bonds in amlodipine [10] or sildenal
[11] (Figure 4.1b, c, respectively). The reverse, i.e. cyclization, is also a valid
strategy, as described in a recent paper detailing the rational design of inhibitors
of TRAF2 and NCK-interacting protein kinase (TNIK) [12]. Dierent fused ring
systems were evaluated as bioisostere of o-methoxybenzamide that can form an
internal hydrogen bond between the methoxy oxygen and the amide nitrogen. The
tetrahydro-1,4-benzoxazepin-5-one was selected as a replacement, improving both
pharmacodynamic and pharmacokinetic proles (see Figure 4.1d).
Furthermore, not all regions of druglike compounds are part of a pharmacophore.
Some chemical groups are not making specic intermolecular interaction or even
not making any interaction at all with the targeted macromolecule. As an example,
physicochemical properties of kinase inhibitors were optimized by modifying a
long side chain attached by an ether to an aminoquinazoline core [15]. While the
latter is known nowadays as a typical scaold making specically interactions
with the hinge domain of kinases, the side chain is not part of the pharmacophore
stricto sensu and was used to modulate physicochemical properties while keeping
bioactivity. Terminal polar heterocycles were particularly eective in increasing
the solubility of the inhibitors. Morpholine was nally selected for the molecule,
which was ultimately developed as Getinib, an EGFR inhibitor and rst-line
therapy to treat non-small cell lung carcinoma. Resolved structures of Getinib
cocrystallized with dierent kinases have conrmed the position of morpholine
in the solvent (Figure 4.2, e.g. Getinib bound to an EGFR mutant, PDB entry:
Figure 4.2 Crystallized complex of EGFR with inhibitor Gefitinib. Screenshot of Mol*
Viewer [16] as embedded on Protein Data Bank in Europe portal (PDB ID: 2ITO, https://www
.ebi.ac.uk/pdbe/). EGFR is displayed as mauve cartoon and Gefitinib ligand in ball-and-stick
with carbon atoms in grey. The orange arrow points to the morpholine in the solvent.
4.1 Introduction 105
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2ITO). Grippingly, morpholine is the second most queried fragment inputted by
SwissBioisostere users (refer to Section 4.4.2).
Regardless of the medicinal chemistry strategy followed (if any), the fact remains
that replacing one part of a molecule only, while keeping the rest unchanged
generates a couple of compounds. In case of similar biological activity, we consider
the compounds as bioisosteres and the exchange of fragments as a bioisosteric
replacement.
To support medicinal chemists in choosing eective bioisosteric replacements,
this very pragmatic generalization of the concept stresses the need for tools not
limited to molecular or physicochemical descriptions but based on bioactivity
knowledge. Nowadays, the wealth of bioactivity data is sucient, both in quality and quantity, to enable such knowledge-based tools. The SwissBioisostere
database and its web interface are the examples we want to describe in this chapter.
4.1.3 Bioisosteric Replacement in Drug Discovery
Drug discovery can be dened as all the strategies and techniques aimed at nding
small molecules active on a dened biological target (i.e. hit compounds), selecting leads with most appropriate properties for chemical modications enabling
optimization, and ultimately promoting the drug candidates with the best chance
of success into the development phases. It is a long and costly workow involving
trial-and-error paths and empirical feedback loops – in fact, much more complex
than the idealized scheme often presented. For decades, substantial eorts have
been put to lower the attrition rate and accelerate the generation of hypotheses,
knowledge, or evidences to support decisions and nally to reduce the risks
associated with the even more time-consuming and expensive drug development
phases.
Such decision-making support can be successfully achieved by a bioisosteric
replacement strategy, routinely followed by medicinal chemists. The approach
consists in dening and applying the chemical modications that improve one or
several sub-optimal properties while keeping the bioactivity at least at the same level
[17]. Drug discovery is highly multi-objective, hence the large variety of properties
to be potentially corrected: toxicity or lack of specicity for the target, synthesis
or intellectual property issues, improper Absorption, Distribution, Metabolism,
and Excretion (ADME) or pharmacokinetic proles, to name the most obvious
ones [18].
In this section, we propose to describe and exemplify bioisosterism practices
applied to hit nding and lead optimization.
When a pharmacologically relevant target has been selected, chemical entities
showing activity must be identied with procedures grouped under the term hit
nding. In usual workows, high-throughput screening as well as literature and
patent analysis are the primary sources for hits. The most promising hits have to
be clearly detected, unambiguously dened chemically, biochemically validated
in diverse assays, and further evaluated as suitable or not for promotion as lead
compounds. These activities are of utmost importance to promote the best possible
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start of demanding medicinal chemistry programs. During hit nding, experts must
obviously address technical points, such as synthetic accessibility of a given scaold,
for instance, but also, more broadly, questions regarding the freedom to operate.
Intellectual property to avoid conict with already protected elds is critical.
The objective is to escape a given chemotype to overcome the specic issues of a
given chemical series. Consequently, one can expect the chemical space to be vast
and distant from the rst molecular hits. An ecient approach to explore new areas
of this broad space consists in exchanging the whole central core of a hit compound
but keeping the pharmacophoric points at the periphery of the molecule to retain
bioactivity [19]. In this methodology conceptualized and called scaold hopping by
Gisbert Schneider [20], bioisosteric replacements concern “linker” or “scaold” fragments, including multiple connection points to the constant part of bioisostere compounds (for technical aspects, see Section 4.2.3 and Figure 4.4).
Upon successful completion of all the hit-related processes described above, the
chemical entities are termed “lead compounds” and enter optimization, for which
bioisosteric replacements are also routinely and eciently conducted. During lead
optimization, a validated chemotype is subject to numerous modest structural modications [21]. The exploration of the chemical space allows to consider the relationship between the structure and the properties that need to be optimized to design
a drug candidate. Compared to the hit-nding step, the exploration of the space
remains within the vicinity of the lead compound. Structural modications are principally made at the periphery of the molecules, such as at the end of a chain or
at a substituent position. The bioisosteric replacement is mainly applied on “side
chains,” with exchanged fragments having a single connection point with the rest of
the molecule (for technical aspects, see Section 4.2.3, and Figure 4.4).
The motivation for proposing SwissBioisostere and the way it has been designed
was to meet the needs of medicinal chemists’ practice. This is exposed in detail in
Section 4.2.
4.2 Construction and Dissemination of SwissBioisostere
4.2.1 Intention and Requirements
As introduced in Section 4.1, bioisosterism is routinely used for drug discovery.
This intuitive approach cannot follow a generalized logical path since it depends
on the biological and chemical contexts of the explored domain. There are neither
universally applicable rules nor guidelines to support the important and daily
task of replacing parts of a template molecule with new chemical moieties. Often,
the practice of bioisosteric replacement relies solely on the expertise of medicinal
chemists.
The likelihood of success of bioisosteric replacement approaches increases when
applied in a systematic and rational manner [2, 3]. Medicinal chemists can benet
from computational support for bioisosteric drug design. However, the usefulness of
such tools depends on some requirements. First, the bioisosteric knowledge should
4.2 Construction and Dissemination of SwissBioisostere 107
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Figure 4.3 Construction of the SwissBioisostere database and web interface.
be primarily rooted in bioactivity data linked to the structure of compounds and
processed with an unbiased technique, without considering other molecular parameters like physicochemical properties, for instance (refer to Section 4.2.3). Second,
the bioactivity data itself should be of high quality and broad in terms of chemical
and biological spaces (refer to Section 4.2.2).
The physicochemical and molecular descriptors are not included in the denition
of molecular replacements, but, reversely, they are of great importance for the users
to estimate the impact of these replacements on such properties. This, together with
the dierence in bioactivity, should be organized for easy access to enable a global
assessment of the consequences of selected molecular replacements (refer to Section
4.2.4 and Section 2.5).
The general workow for the construction of SwissBioisostere is displayed in
Figure 4.3.
4.2.2 Bioactivity Data
The major data source for building SwissBioisostere is ChEMBL (https://www
.ebi.ac.uk/chembl/), a manually curated high-quality bioactivity database relying
mainly on medicinal chemistry literature and secondarily other sources, like
publicly available screening campaigns [22, 23]. It provides the possibility to
download the entire database in dierent formats. This allows to eciently link
the chemical context (molecular structure and descriptors) and the biological
context (bioactivity, target, and target class) to assays and publications, for a large
set of bioactive compounds. For the needs of SwissBioisostere, ChEMBL data were
ltered to keep only small molecules (molecular weight <800 g/mol), active in vitro
108 4 Bioisosteric Replacement for Drug Discovery Supported by the SwissBioisostere Database
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(IC50,EC50,Ki,orKd< 10 μM) in a binding or functional assay on a dened protein
target with enough curation condence (score >7). This dataset is rst organized
by classifying compounds tested on the same target in the same assay.
4.2.3 Nonsupervised Matched Molecular Pair Analysis
The bioactivity dataset organized by assay, obtained as described in Section 4.2.2,
is processed by a Matched Molecular Pair (MMP) algorithm. Such intuitive,
easy-to-use approach, proposed more than 40 years ago, heavily developed and
diversied [24], has demonstrated its value for analyzing public chemical databases
and especially in nding bioisostere molecules [25] by individualizing pairs of compounds that dier by a single structural fragment. For building SwissBioisostere
and dening truly unclassical bioisosteres, a single structural change is related to
variation in bioactivity and only to this property, without any bias of any kind.
One well-known example of such unbiased, unsupervised MMP [26] is the
fragment-based method described by Hussain and Rea [27]. We employed a
custom-made implementation of this algorithm, in particular by dening additional fragmentation rules (for details, please refer to [28]). In brief, the algorithm
cuts molecules tested in the same experimental assay into fragments with respect
to their bond types. Only single bonds may be cut if linking at least one carbon, no
hydrogen, and not being part of any cycle, chemical function, or simple sugar pattern (e.g. glucose or fructose). To generate fragments, no more than three bonds can
be cut at the same time. As such, three kinds of fragments are considered: side chain
fragments with one attachment point; linker fragments with two attachment points;
and scaold fragments with three attachment points (Figure 4.4a). All remaining
(one, two, or three) moieties are tagged “R-groups” and correspond to the constant
part of the molecule (Figure 4.4b). This allows nally to dene an occurrence as two
molecules tested on the same assay (and thus on the same target) diering only by
one fragmental exchange with the rest of the structure constant (R-groups). This
fragmental exchange is dened as the replacement (Figure 4.3).
4.2.4 Database
The MMP analysis on bioactivity data as described above enables the user to nd
possible bioisosteric replacements, for instance, if the majority of occurrences (pairs
of molecules) for a given replacement are showing similar bioactivity when tested
in the same assay. The analysis can be further rened thanks to attached data, such
as physicochemical properties, or biological and chemical contexts not employed to
guide the MMP but important for design actions to be applied in lead optimization
or hit nding. A relational database was built using MySQL (https://www.mysql
.com) with the aim of structuring the extensive wealth of knowledge and making
it straightforwardly searchable through a large variety of languages, including
web-oriented programs. As an example, the main and largest table contains more
than 65million data points, corresponding to all replacement occurrences. These
base data are linked to all additional knowledge, like molecular and physicochemical
properties or target classes, through several other interconnected tables.
4.2 Construction and Dissemination of SwissBioisostere 109
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(a)
(b)
Figure 4.4 Unsupervised Matched Molecular Pair (MMP) algorithm for building
SwissBioisostere. (a) Example of some fragmentations of Ponatinib (other cuts are
possible); our implementation of MMP can consider three kinds of fragments: side chain,
linker, and scaffold fragments with one, two, and three attachment points, respectively. This
allows (b) to define matched fragments (here replacements of linkers boxed in red) among
pairs of molecules tested on the same target in the same assay (here, two occurrences for
the same replacement from two different assays); all remaining (one, two, or three)
chemical moieties correspond to the constant part of the molecule (blue dashed boxes).
4.2.5 Web Interface
The SwissBioisostere database is openly accessible on the Web, freely browsable
and searchable by reaching www.swissbioisostere.ch. This login-free website has
been online since 2012 [29] and has undergone a major update (both frontend and
backend) in 2021 [28]. Users can perform their own requests and analyses within
the graphical web interface; they can also export results, access to related ChEMBL
and PubMed entries, and interoperate with other CADD web tools. Use cases and
examples are given in Section 4.4.3. Please refer to the reference [28] for the details
on how to take full advantage of all capabilities.
Importantly, like for our CADD web tools, the results generated by SwissBioisostere are under CC-BY license. This extends the freedom to operate, including
for commercial and for-prot usages. The current website is optimized for Firefox
(www.mozilla.org) or Google Chrome (www.google.com/chrome/). The best user
experience is obtained by using a recent version of either browser.
Detailed support to the user on all options regarding input, output, visualization,
analysis, ltering, export, access to databases of origin, and interoperability with
other CADD tools is obtained directly on the website through the main menu. Apart
from frequently asked questions (FAQ), the items “Tutorials”and “Help” give access
110 4 Bioisosteric Replacement for Drug Discovery Supported by the SwissBioisostere Database
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(a)
(b)
Figure 4.5 User support on SwissBioisostere website. Short video tutorials (a) and static
help page (b) are available to assist the user through all technical aspects of the graphical
interface.
to video tutorials and static help pages (see Figure 4.5). Particularly useful are the
short screen capture videos of about 1 to 2 minutes, which cover comprehensively
the most technical aspects of the graphical interface. As of today, the tutorials show
how to: (i) input a side chain fragment; (ii) analyze results of possible replacements of a fragment; (iii) analyze results of specic replacement occurrences;
(iv) input linker and scaold fragments; and (v) input a specic replacement.
The last two tutorials show users how they can benet from SwissDrugDesign
4.3 Content of SwissBioisostere 111
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environment interoperability: (vi) send any compound from SwissBioisostere to
other SwissDrugDesign tools in order to perform additional analyses (vii) send any
molecule from another SwissDrugDesign tool to SwissBioisostere. The static help
page acts as a checklist summarizing the input/output requirements and available
options. If a user has other concerns or a specic question, a contact form is also
provided.
The following few basic points are noteworthy. Users can input molecular
fragments directly from the input page using either one or both molecular sketchers. Twotypes of requests are available:(option 1) requests for possible replacements
of a molecular fragment with input in the left-hand sketchers; (option 2) requests
for occurrences of a specic replacement with input in both left- and right-hand
sketchers. Request options and display/undisplay of the right-hand sketcher are
available by clicking on the corresponding grey tabs above sketchers. When a query
of possible replacements (request type 1, see Figure 4.10a) is completed, results
are returned in a new browser tab as a rst output page containing the list of
candidate fragments sorted by default according to the dierence of bioactivity (see
Figure 4.10b). If the user clicks on a given candidate fragment, a second request is
performed for occurrences of the specic replacement. Upon completion, a new
browser tab displays a second output page, listing all occurrences for the specic
replacement (i.e. all pairs of molecules diering by this replacement and tested
in the same assay, see Figure 4.10c). As mentioned before, such a request for
occurrences can also be performed directly from the input page with an input in
both sketchers (request type 2).
4.3 Content of SwissBioisostere
4.3.1 Global Content
At the time of writing this chapter (early 2022), the chemoinformatic pipeline
described in Section 4.2 was applied to data extracted and ltered from ChEMBL
version 28 to analyze a total of 1,124,168 datapoints representing 483,927 compounds tested for bioactivity on 2036 protein targets of 35 classes through 61,199
assays. The workow that generated the database behind the production website
www.swissbioisostere.ch was able to describe 25,305,017 unique replacements,
implying 1,216,118 unique fragments [28]. Overall, the browsable replacement
space of SwissBioisostere is as vast as 65 million datapoints, of which more than
36 million are directly linked to a publication and straightforwardly accessible
in one click through a PubMed link (see Figures 4.10 and 4.11). The rest of the
replacement information originates from assays not published but curated by
ChEMBL, as well. Most are part of large high-throughput screening (HTS) public
campaigns, targeting neglected diseases or COVID-19, for instance. It is important
to understand that addition of new data in SwissBioisostere depends on ChEMBL
releases and SwissBioisostere updates. As such, SwissBioisostere must be seen as a
CADD tool to support drug discovery and certainly not as a means to track the very
latest communications in medicinal chemistry.
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