The Transporter-Mediated Cellular Uptake and Efflux of Pharmaceutical Drugs and Biotechnology Products: How and Why Phospholipid Bilayer Transport Is Negligible in Real Biomembranes

Abstract

Over the years, my colleagues and I have come to realise that the likelihood of pharmaceutical drugs being able to diffuse through whatever unhindered phospholipid bilayer may exist in intact biological membranes in vivo is vanishingly low. This is because (i) most real biomembranes are mostly protein, not lipid, (ii) unlike purely lipid bilayers that can form transient aqueous channels, the high concentrations of proteins serve to stop such activity, (iii) natural evolution long ago selected against transport methods that just let any undesirable products enter a cell, (iv) transporters have now been identified for all kinds of molecules (even water) that were once thought not to require them, (v) many experiments show a massive variation in the uptake of drugs between different cells, tissues, and organisms, that cannot be explained if lipid bilayer transport is significant or if efflux were the only differentiator, and (vi) many experiments that manipulate the expression level of individual transporters as an independent variable demonstrate their role in drug and nutrient uptake (including in cytotoxicity or adverse drug reactions). This makes such transporters valuable both as a means of targeting drugs (not least anti-infectives) to selected cells or tissues and also as drug targets. The same considerations apply to the exploitation of substrate uptake and product efflux transporters in biotechnology. We are also beginning to recognise that transporters are more promiscuous, and antiporter activity is much more widespread, than had been realised, and that such processes are adaptive (i.e., were selected by natural evolution). The purpose of the present review is to summarise the above, and to rehearse and update readers on recent developments. These developments lead us to retain and indeed to strengthen our contention that for transmembrane pharmaceutical drug transport “phospholipid bilayer transport is negligible”.

Full text

Molecules 2021, 26, 5629. https://doi.org/10.3390/molecules26185629 www.mdpi.com/journal/molecules
Article
The Transporter-Mediated Cellular Uptake and Efflux
of Pharmaceutical Drugs and Biotechnology Products: How
and Why Phospholipid Bilayer Transport Is Negligible
in Real Biomembranes
Douglas B. Kell 1,2,3
1 Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology,
University of Liverpool, Crown St, Liverpool L69 7ZB, UK; dbk@liv.ac.uk
2 Novo Nordisk Foundation Centre for Biosustainability, Technical University of Denmark, Building 220,
Kemitorvet, 2800 Kgs Lyngby, Denmark
3 Mellizyme Biotechnology Ltd., IC1, Liverpool Science Park, Mount Pleasant, Liverpool L3 5TF, UK
Abstract: Over the years, my colleagues and I have come to realise that the likelihood of pharma-
ceutical drugs being able to diffuse through whatever unhindered phospholipid bilayer may exist
in intact biological membranes in vivo is vanishingly low. This is because (i) most real biomembranes
are mostly protein, not lipid, (ii) unlike purely lipid bilayers that can form transient aqueous chan-
nels, the high concentrations of proteins serve to stop such activity, (iii) natural evolution long ago
selected against transport methods that just let any undesirable products enter a cell, (iv) transport-
ers have now been identified for all kinds of molecules (even water) that were once thought not to
require them, (v) many experiments show a massive variation in the uptake of drugs between dif-
ferent cells, tissues, and organisms, that cannot be explained if lipid bilayer transport is significant
or if efflux were the only differentiator, and (vi) many experiments that manipulate the expression
level of individual transporters as an independent variable demonstrate their role in drug and nu-
trient uptake (including in cytotoxicity or adverse drug reactions). This makes such transporters
valuable both as a means of targeting drugs (not least anti-infectives) to selected cells or tissues and
also as drug targets. The same considerations apply to the exploitation of substrate uptake and
product efflux transporters in biotechnology. We are also beginning to recognise that transporters
are more promiscuous, and antiporter activity is much more widespread, than had been realised,
and that such processes are adaptive (i.e., were selected by natural evolution). The purpose of the
present review is to summarise the above, and to rehearse and update readers on recent develop-
ments. These developments lead us to retain and indeed to strengthen our contention that for trans-
membrane pharmaceutical drug transport “phospholipid bilayer transport is negligible”.
Keywords: membrane transport; pharmaceuticals; drugs; energy coupling; biotechnology; ADME;
DMPK; transporter engineering
1. Introduction
Over the years, two main ideas have been used to explain the mechanisms by which
pharmaceutical drugs and/or substrates and products of biotechnological interest pass
through the plasma (or other) membranes of the relevant organism: in a more classical
analysis, it is assumed (and it really is purely an assumption [1]) that molecules can dif-
fuse through the core of the lipid bilayer by some means. In an alternative and really en-
tirely opposite view, which we refer to as PBIN for “phospholipid bilayer diffusion is
negligible” [2], we have argued [1–12] (and these constitute background that we mainly
do not rehearse again here) that this does not in fact occur in real biomembranes to any
Citation:
Kell, D.B. The Transporter-
Mediated Cellular Upt ake and Efflux
of Pharmaceutical Drugs and
Biotechnology Products: How and
Why Phospholipid Bilayer Transport
Is Negligible in Real Biomembranes.
Molecules
2021, 26, 5629.
https://doi.org/
10.3390/molecules26185629
Academic
Editors: Kristiina
Huttunen and Santosh Kumar Adla
Received:
17 August 2021
Accepted:
14 September 2021
Published:
16 September 2021
Publisher’s Note:
MDPI stays neu-
tral with regard to jurisdictional
claims in published maps and institu-
tional affiliations.
C
opyright: © 2021 by the author. Li-
censee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and con-
ditions of the Creative
Commons At-
tribution (CC BY) license (http://crea-
tivecommons.org/licenses/by/4.0/).

Molecules 2021, 26, 5629 2 of 39
significant extent at all. Some of this background material is also available in a webinar
(https://bit.ly/3yQJ1FG, accessed on 15 September 2021). The two modes are illustrated in
Figure 1. One may debate what is “significant” and/or “negligible”, but anything less than
5% of a total flux really is not much of a contribution, and plenty of evidence implies that
it is almost certainly less than 1%. In our view, the term “negligible” covers this more than
adequately. The purpose of this review and commentary is to provide an update on some
of the salient issues. Examples of the importance of transporters continue to grow apace,
while—whatever may or may not happen in artificial membranes—it remains the case
that the actual evidence for significant transmembrane transport solely through any bi-
layer portions of intact biological membranes is non-existent. We shall start by looking at
why this is the case, initially by focusing on some of the major differences between real
biomembranes and those artificial ones made from phospholipid bilayers.
Figure 1. A drug D might pass through a biological membrane in one of two main ways conceptually (we do not here
discuss endo- and exocytosis; the focus is only on cases where the drug is considered to cross through the membrane
barrier itself). On the left is illustrated transport through phospholipid bilayers, while on the right we illustrate the use of
proteinaceous solute carriers to effect entry and exit of the drug. The crux of this review is that the mode on the left does
not take place at any meaningful rate in intact biological membranes (since they have a high protein content).
1.1. Biological Membrane Structure
The textbook view of biological membranes is that they are to be seen as a “fluid
mosaic” [13,14] of proteins embedded within a phospholipid bilayer, along with other
small molecules such as sterols. The original article [13] featured a now iconic illustration
(shown in Figure 3 of said article) in which a small number of proteins were embedded in
How drugs might pass through
cellular membranes
OR
via
phospholipid
bilayer
via one or more
of hundreds of
transporters

Molecules 2021, 26, 5629 3 of 39
and on a “sea” of phospholipids, with the proteins representing (by eye) approximately
one-seventh of both the total mass and area. Unfortunately, this picture is very mislead-
ing, since biological membranes are commonly 3:1 protein:lipid by mass, and maybe 1:1
by area (not 1:7) [15–28] (see Figure 2). This widespread but erroneous mental picture, of
“proteins floating in a sea of phospholipids”, has led many to suppose that from a bio-
physical point of view biomembranes are thus essentially just like pure lipid bilayers, in
that the supposedly sparse proteins would do little or nothing to affect the kinds of prop-
erties that can be seen in purely phospholipid bilayers such as those studied in vitro [29–
31]. However, this is emphatically not the case.
Purely artificial (solely phospholipid) bilayer membranes are not terribly stable and
admit the passage of small molecules (and even ions) via transient aqueous pores or chan-
nels (e.g., [32–43]). This mode of transfer clearly has to be the case if ostensibly ‘transmem-
brane’ transport ‘through’ them is observed, as it can easily be calculated that the free
energy necessary for passing a small cation through a dielectric (such as that represented
by a membrane interior of phospholipid tails) with a permittivity of ca 2 is so great that it
would be unlikely to occur even over millions of years [44]. More specifically, the lateral
flexing of phospholipids needed to make such transient aqueous pores simply cannot oc-
cur when the phospholipids are either bound directly to a protein or are strongly influ-
enced thereby (as they are, e.g., [45–62]). This is likely reinforced by the well-established,
substantial and dynamic lipid asymmetry between the inner and outer halves of mem-
branes [63–65]. Note too that ABC transporters are responsible for moving lipids them-
selves around cells and within membranes [47,66–69]. In short, studying an aardvaark
tells you about an aardvark, not a langoustine. In a similar way, studying sodium chloride
tells you about sodium chloride, not strychnine chloride, even if they both contain chlo-
ride. Thus, in a similar way, studying pure phospholipid bilayers tells you about pure
phospholipid bilayers, and not biomembranes that may happen to contain relatively small
amounts phospholipids in a bilayer form. This may seem obvious when set out in this
way, which is why we do it.
Figure 2. Cartoon of a typical biomembrane indicating the relative paucity of phopholipid bilayer
that is uninfluenced by proteins. Taken from an Open Access animation covering some of this
ground and related transporter matters at https://www.youtube.com/watch?v=s23vNwLE-Jw.
Protein and lipid amounts as they
are in a typical biomembrane

Molecules 2021, 26, 5629 4 of 39
1.2. Transport of Drugs through Biological Membranes and the (Mis)Use of the Term “Passive”
It is now well-established that cells require proteinaceous transporters to effect the
transmembrane transport of the nutrients they need to survive and to grow. Since these
nutrients are mainly small molecules, it might be thought that a similar degree of ac-
ceptance would accord to the assumption that this held true for pharmaceutical drugs too,
as well as for the uptake and efflux of substances of interest to the biotechnology industry.
Surprisingly, as mooted above, and for some comparable reasons with bioenergetics more
generally [70], this has not largely been the case. Indeed, why these and other beliefs per-
sist despite the facts, and what to do about it, is of general philosophical and psychological
interest [71–76]. In this case, it seems from our experience that it is to do with culture and
education; those versed in physical organic chemistry (who are often predominant in the
DMPK/ADMET sections of pharmaceutical companies but also in more traditional phar-
macology schools in academia) tend not to know much about enzymology, while molec-
ular biologists—who tend to know little of physical organic chemistry—express extreme
surprise when told of the widespread belief of physical organic chemists that drugs
simply pass through the bilayer portions of biomembranes. There is clearly value for in-
dividuals from both backgrounds in learning a little of each topic.
The term “passive”, as employed for instance in the phrase “passive diffusion”, is
also widely misused, not least because it can be (and is) used to cover and then conflate
two separate concepts. The first represents a thermodynamic meaning, where “passive”
is used to mean “equilibrative”: the transporter requires no free energy and simply lets
molecules pass down their concentration gradients until their concentrations (strictly,
thermodynamic activities) are the same on each side of the membrane of interest (i.e., that
in which the transporter is embedded). Clearly, the thermodynamic usage can (or should)
have no mechanistic implications. The problem is that the same term (as in “passive dif-
fusion” or “passive permeability”) is also used to imply a mechanism, viz that such equili-
brative diffusion occurs through the phospholipid bilayer. In the worst cases, demonstra-
tion of the thermodynamic property is used to imply or even to claim the demonstration
of a mechanism as transbilayer diffusion. In our view, the term “passive” has acquired so
much baggage that the only solution to this (Figure 3 and reference [2]), in addition to
education, is to avoid the term “passive” completely, and thus be forced to be more ex-
plicit about precisely what it is that is being claimed in any particular case.
Figure 3. Suggested terminologies to avoid the use of the term “passive”, which is still widely mis-
used to conflate two entirely separate concepts, one thermodynamic (hence independent of mecha-
nism) and one mechanistic.
Means of transport
Purely lipoidal Transporter-mediated
Thermodynamics
Concentra�ve
Equilibra�ve
Concentra�ve
bilayer diffusion
(coupled e.g. to a
pH gradient)
Equilibra�ve
Bilayer diffusion
Facilitated
diffusion
The terminology of transport reac�ons
Ac�ve transport

Molecules 2021, 26, 5629 5 of 39
One feature of transport across membrane systems such as those of the popular Caco-
2 cell monolayers [77–84], that (like other human tissues [85,86]; https://www.proteinat-
las.org/search/slc), express hundreds of transporter proteins [87–91], is that the initial rate
of transport of a given substrate at the same initial concentration from side A → side B can
differ from that when the test is made from side B → side A, even when the transport is
purely equilibrative. This has no ready explanation by or for those schooled purely in
physico-chemical concepts and who believe that diffusion explains everything. By con-
trast, enzymologists have a perfectly straightforward explanation of this, which comes
from the well-known thermodynamic Haldane relationship relating the Km and Vmax val-
ues in the forward (Km,f and Vmax,f) and reverse (Km,r and Vmax,r) directions of a reaction to
its equilibrium constant Keq. While this can be found in any textbook of enzyme kinetics
(e.g., [92–94]), or even of biochemistry, we reproduce it below:
(Vmax,f · Km,r)/(Vmax,r · Km,f) = Keq (1
)
Thus, even for Keq values of unity, it is easily possible to have rates that differ
manyfold in the two directions for the same external concentration, just by manipulating
the other values in Equation (1) while keeping their ratios consistent with it. Of course,
and I stress this purposely, this is true only for enzyme- (transporter)-mediated transport,
not “diffusion” through lipid bilayers [5].
1.3. Untestability of Bilayer Transport Models in Real Biomembranes
Perhaps surprisingly, the view that molecules pass through phospholipid bilayers in
real biological membranes is presently untestable, because we do not have the ability to
image small molecules and membranes with the atomic resolution that would be neces-
sary to observe their transport directly. What is presently carried out most commonly is
to observe molecules on one side of a membrane and later on the other side, and simply
assume that they appeared there via transbilayer transport. This is a well-established and
classical logical fallacy known as “affirming the precedent” or “post hoc ergo propter hoc”
[1]. In a different vein, observing a molecule transferring from one side of a pure phos-
pholipid bilayer simply does not tell you what it might do in a real membrane where there
is very little bilayer that is not affected by the presence of protein. Similarly, changing the
type or amount of phospholipid does not “simply” do that, because the activities of mem-
brane proteins, including transporters [95], can vary quite substantially with changes in
their adjacent lipids. Consequently, any changes in transport induced by changing lipids
can perfectly well (and more accurately) be explained by their influences on the proteins
embedded in the membrane.
1.4. Testability of Transporter-Mediated Models in Real Biomembranes
By contrast, those of us who claim that bilayer transport is negligible in real biomem-
branes can easily change the expression levels or activities of transporters of interest (e.g.,
[96,97]) and observe the concomitant effects on the transport of the small molecules of
interest (as in Figure 4). (The same strategy can also be used to detect inhibitors of the
transporter, e.g., [98,99].) In the paper of Winter et al. [97], the uptake and toxicity of an
anticancer compound called YM155 or sepantronium bromide was decreased some 500-
fold when the single transporter SLC35F2 was knocked out, and the toxicity of the com-
pound correlated closely with that transporter’s expression level over some four orders of
magnitude when explored in some 15 separate cell lines (that, as for many transporters
[86,100], showed equivalently massively varying expression levels). The only reasonable
(one might say plausible) explanation is that the SLC35F2 transporter normally carried
some 99.5% of the flux of YM155 into the cell, and that consequently the transmembrane
flux occurring by any other means, including via bilayer transport, is indeed negligible.
This simple phenomenon served to explain entirely the highly variable efficacy of YM155
in a series of clinical trials.

Molecules 2021, 26, 5629 6 of 39
Figure 4. Principle of determining the substrate of a drug at toxic concentrations (e.g., [8,96,97,101,102]) by assessing the
ability of cells lacking a particular transporter gene to survive its presence, while the wild-type cells, or cells knocked out
for other genes not involved in the drug’s transport, are killed. Obviously, this is the extreme; there may also be degrees
of resistance.
Typically, the question of the interaction between substrates and transporters can be
phrased in two complementary ways: the transporter-centric question is “given a trans-
porter of interest X, what are its substrates?”. This is the problem of de-orphanisation
[103–109]. The complementary, substrate-centric, question is “given a substrate Y, which
transporter(s) is/are responsible for its cellular uptake and/or efflux?”. The latter is the
more important one for assessing the mechanisms of drug transport [8], and there are
many examples (e.g., [110–118]) where transporter activity has been identified but where
the transporters involved have not. Of course, while a known result is a partial answer to
each question, the strategies for tackling them are slightly different (for a recent overview
of cell-based assay methods for SLCs, see [119]). Note, in particular, that simple biophysics
plus the re-use of protein motifs in evolution means that most small molecules bind to
multiple targets, and most proteins can bind small molecules promiscuously (e.g.,
[8,9,120–130]).
As part of the EU-IMI ReSolute project [131] (https://re-solute.eu/), the CEMM group
studied 60 cytotoxic compounds. By using an SLC-focused CRISPR-Cas9 library, they
identified a series of transporters whose absence induced resistance to the drugs tested
[101], much as had been achieved in smaller numbers before [96,97]. This kind of sub-
strate-centric strategy clearly represents a potent means of identifying drug transporters,
and notably it also illuminated cases of interactions. Such interactions scale exponentially
with the number of candidates, but high-throughput CRISPR-Cas methods are enabling
the identification of all kinds of genes involved in complex biological processes (e.g., [132–
137]).
D
D
D
DEAD
Gene knockout -based strategy for
solute carrier identification
KO2
SURVIVES
D
LACKS CARRIER Y
KO1
KO3
KO4
Add toxic substrate t hat if transported kills ce lls

Molecules 2021, 26, 5629 7 of 39
1.5. Heterogeneity of Transport and Transporters in Different Cells and Tissues
If trans-bilayer permeability were significant in real biomembranes, the free concen-
trations of drugs inside cells and organelles (modulo pH and potential gradients) would
be more or less homogeneous. Of course, they are not, as is well-known (and as can easily
be determined by chemical imaging methods, e.g., [138–159]). A particularly well-estab-
lished case is that of the blood–brain barrier, where, despite the lipids not being noticeably
different from those in other cells, the permeability is negligible if specific transporters are
not involved [160–164]. What does differ greatly between different cells and tissues, of
course, is the expression of particular proteins such as transporter proteins [85,86,165],
with any number of large datasets now becoming available.
1.6. Role of Transporters in Biotechnology
In addition to activities mentioned in our previous reviews that were focused on
transporters and biotechnology [4,12,166], a number of other authors (as reviewed, e.g., in
[167–178]) have also highlighted the importance of transporters in the uptake of CO2 [179]
and in the biotechnological production of substances of interest in the BioEconomy. Some
recent examples include the production of amorphadiene [180], citrate [181], L-malate
[182–184], antibiotics [185], fatty acids [186], fatty alcohols [187], olefins [188], various or-
ganic acids [176], other dicarboxylic acids [189,190], sophorolipids [173,186,191,192], in
microbial fluorination (by removing a fluoride effluxer from E. coli [193]), and in the pro-
duction of a variety of hydrophobic substances [191,194]. Promiscuity can be quite signif-
icant for biotechnology [182,195–199]. In particular, here, the promiscuity of some trans-
porters, especially under biotechnological conditions of unphysiologically high intracel-
lular concentrations of small molecules, means that cells can have a tendency to leak path-
way intermediates with structural similarities (as judged by various means [200,201]) to
products, rather than simply just excreting the desired product; this too can be manipu-
lated via transporter engineering [171].
1.7. Adaptive Laboratory Evolution and Membrane Transporters
While some studies are more binary, looking for resistance to a toxic substrate via
survival or death “in one go”, other strategies (such as the very elegant “variable dose
analysis” [202]) are more graded. A particularly nice example is that of adaptive labora-
tory evolution (ALE), illustrated in Figure 5. While many very elegant examples of long-
term laboratory-based bacterial evolution exist (e.g., [203–210]), a more directed focus has
been where it is exploited for biotechnology (e.g., [190,211–223]). However, it is perfectly
applicable in drug transporter studies too. As with any phenotypic selection of this type
[224–231], it relies on the fact that, in a heterogeneous population, the faster-growing
strains will tend to become more prevalent at the expense of the slower-growing ones.
Sequencing those that take over indicates where favourable mutational events have oc-
curred, and essentially identifies the relevant genes. It can best be run as a hypothesis-free
strategy [232], given that some mutations cannot reasonably be predicted (e.g., the role of
ribosomal subunits in improving methanol tolerance in E. coli [233]). In one example in-
volving transporters [234], ALE was used to increase the tolerance to aromatic amino acids
of baker’s yeast. Here, [234], the major mutation was in a transcriptional activator called
Aro80, that served to increase the activity of an efflux transporter Espb6, a role (in efflux-
ing aromatic compounds) shared with the previously known Pdr12. In another example
[235], E. coli cells were made more tolerant to ionic liquids; in this case, the chief mutations
in tolerant clones occurred in transport processes in the shape of mdtJI, a multidrug efflux
pump, and yhdP, a largely uncharacterised transporter possibly involved [236,237] in
phospholipid transport to the outer membrane.

Molecules 2021, 26, 5629 8 of 39
Figure 5. Illustration of the principle of adaptive laboratory evolution (ALE). Cells are exposed to a toxic substance that
causes them to grow sub-optimally. Selection leads to strains that can revert to rates and extents of growth shown by the
wild type when inoculated into fresh cultures. The stress level is increased and the process continued. Sampling and
growth rate measurement can be completely automated.
As illustrated in Figure 5, the commonest means of performing ALE is in a “semi-
batch” type of mode in which small inocula are used to grow cells in batch mode, while
they are then sampled at the end of growth and a new inoculum introduced to a separate
batch culture. What is then selected, in part, is cells that as well as having a higher growth
rate also have lowered lag phases and the ability to survive better in stationary phase.
Truly continuous cultures provide for a much more stringent selection, especially when
carried out in a turbidostat. In a turbidostat (e.g., [227,238–245]), the growth medium is
arranged such that—unlike in a chemostat—cells can grow at the maximum rate they are
able to within it. The biomass in a fermentor of working volume V is controlled at a set
point via a suitable probe (see, e.g., [246–248]). As it exceeds this level, fresh growth me-
dium (including any inhibitors) is pumped in at an average rate over a period of v mL ·
min−1. Cells are washed out at the same rate. As usual [249], this rate is numerically equiv-
alent to the growth rate = the dilution rate = v/V min−1, and may be recorded continuously.
Rather surprisingly, the method has not been widely used, although McGeachy et al. [227]
give a nice example that illustrated selection of mutations in the Mep3p ammonium trans-
porter. We predict that these kinds of strategies may have much more impact in the future.
Principle of adaptive laboratory evolution
Periodically increase stress level as growth rate/ yield improves
Increase stress level

Molecules 2021, 26, 5629 9 of 39
1.8. Substrate Misannotations and the Importance of Antiporter Activity in Drug Influx and
Efflux
Most transporters are discovered via their effects on the uptake or efflux of a partic-
ular substrate of interest, and they are often codified accordingly. Our experience is that—
just as with enzyme annotation more generally [250]—this leads to misannotation in that
“any” activity discovered first is typically seen the main or even only activity. A classic
example is SLC22A4, previously known as OCTN1. It had been found to catalyse the up-
take of carnitine, and also that of the the non-physiological tetraethylammonium cation.
However, the rates were in fact quite miserable, and it was not until Gründemann and
colleagues used what was effectively an untargeted metabolomics approach [103] that it
was discovered that it was in fact “really” a concentrative, sodium-coupled transporter
for the nutraceutical ergothioneine [251,252] and also for the related stachydrine (proline
betaine) [103,253,254]. Equivalently, this example also serves to illustrate how finding a
transporter with one activity does not mean that it is the only such capability, and it is
now known that at least one more transporter, viz SLC22A15 [109], can also catalyse er-
gothioneine uptake.
Another means of misannotation is that based on an assumption of unidirectionality
(as an “influxer” or an “effluxer”) that is not warranted and follows from the fact that
most kinetic assays are set up to measure either only an influx or an efflux. At one level,
bidirectional transport is inevitably the case, in that most equilibrative transporters are
necessarily functionally perfectly reversible; if a transporter has two uniported substrates
A and B, both can pass in either direction depending on their relative concentration on
either side of the membrane. More significantly, however, is the case in which the trans-
porter is in fact an antiporter, where the transport of A in one direction is coupled to the
transport of B in the other direction, whether B is measured or not. In radioisotopic assays
for the uptake of A, B is usually unlabelled and hence unobserved. By contrast, so-called
“untargeted” [255–257] mass spectrometric methods show clearly that there is a massive
amount of efflux as well as influx when cells are exposed to new drug and nutrient sources
[258]. In addition, the energy coupling elements of concentrative or efflux transporters are
largely separate from those responsible for conducting the passage of the substrate
through the membrane or can be made so [259].
“Multi-drug transporters” (MDTs) represent a particularly clear example of this; of-
ten, a transporter is labelled as an MDT involved in efflux because lowering its activity
makes an organism more sensitive to a cytotoxic drug. However, in some cases (e.g.,
[260]), the removal of such a transporter actually makes the organism more sensitive to
some other substances! Only “omics” methods in which many substances are measured
simultaneously can easily disentangle this kind of behaviour.
1.9. Genome-Wide Analysis of Drug Uptake and Efflux in E. coli
In recent work [261–263], we have recognised that the existence of genome-wide
knockout (and overexpression) collections allows for the high-throughput assessment of
the uptake of small molecule substrates. Since fluorophores are perfectly good surrogates
for these purposes [264], and their uptake admits easy assessment using flow cytometry
[265–272], we have been able to assess the influence of the expression of individual trans-
porters on the uptake of various fluorophores. Figure 6 gives an example from E. coli [261],
using a wild type and some 530 knockouts, of the effect of such knockouts on the steady-
state uptake of two dyes, viz DiSC3(5), a carbocyanine dye responsive to membrane ener-
gisation [70], and SYBR Green, an intercalating dye whose fluorescence is massively en-
hanced upon binding to (especially double stranded [273]) DNA [274,275]. We here focus
on the so-called multidrug transporter genes of the mdt family. Although the effect of
knocking them out individually is, as expected [276], mainly (for mdt B,C,D,G,I, and J) to
increase the steady-state uptake of DiSC3(5), that of mdtH and mdtK has the opposite
effect, and uptake is very significantly decreased, indicating that normally these can act

Molecules 2021, 26, 5629 10 of 39
as influxers for this molecule. In a similar vein, the uptake of SYBR Green is lowered when
mdtF and mdtL are knocked out.
While one can never exclude the contribution of pleiotropic effects (e.g., [277]), the
obvious conclusion from these kinds of genome-wide study is that many individual trans-
porters can potentially contribute to the uptake and efflux of any stated substrate of inter-
est. Where this is the case, knocking a single one out may not have measurable effects,
since the others can “take up the slack” [276]; this does not of course then mean that the
gene knocked out did not catalyse the flux of the substrate of interest—absence of evi-
dence is not evidence of absence.
Figure 6. Dual roles of so-called multidrug transport proteins in E. coli. Data redrawn from those published with Open
Access at [261]. Plotted are the median uptakes of SYBR Green and DiSC3(5) by various knockout strains relative to the
Wild Type (WT). The ranges are, respectively, 70-fold and 36-fold. So-called y-genes (genes of nominally unknown func-
tion [278,279]) are encoded in red. Mdt gene knockouts are labelled (and have green symbols).
A convenient method for invoking genome-wide diversity via gene disruption is the
use of transposon insertion, but this has the disadvantage that the inactivation of essential
genes in haploid organisms is missed. Thus, Webber and colleagues [280] have developed
a system (TraDIS-Xpress) based on a transposon linked to an inducible promoter and used
this to determine transporters (and other genes) involved in resistance to triclosan [280]
and to fosfomycin [281]. This kind of strategy will be vital in further uncovering trans-
porter-mediated contributions to antimicrobial resistance (AMR).
Uptake of two dyes in E. coli gene knockouts
Median DiSC3(5) uptake
Median SYBR Green uptake

Molecules 2021, 26, 5629 11 of 39
1.10. Recent Approaches to the De-Orphanisation of Mammalian “Orphan” Transporters
Some 1000 genes in the human genome encode transporters [7], of which the largest
class, amounting to roughly half [282–288], is represented by the SoLute Carrier (SLC)
class (http://slc.bioparadigms.org/, accessed on 15 September 2021). As noted above, even
for those that have at least one known substrate, there are doubtless many more to be
found. More significantly, at this stage of knowledge, many of them are complete “or-
phans” in that not a single substrate is in fact known. One recent example of de-orphani-
sation is that of the mitochondrial transporter SLC25A51, which turns out [108,289] to be
an NAD+ importer. This de-orphanisation hinged upon a successful combination of ge-
nomics, metabolomics, CRISPR-Cas9-mediated gene editing, and genetics. Other strate-
gies include binding assays [107], the use of direct assays in Xenopus oocytes [290], and
others that are covered in a recent and comprehensive review [119].
1.11. Selectivity and Drug Targeting by the Use and Exploitation of Varying Expression Profiles
Given the need for transporters if drugs are to cross cell membranes, one can make a
virtue of necessity [284] by seeking either to exploit their natural expression profiles [291–
293] or to vary them explicitly [294], so as to target them to particular tissues [295]. The
latter has obvious benefits in oncology [296–300], where the necessary cytotoxicity of
many drugs, such as nucleoside analogues, is rather non-specific. The strategy can be used
for modifying both influx and efflux transporters, though the latter is likely to prove more
efficacious [276]. In one example [294] (Figure 7), the second drug in the “binary weapon”
strategy decreased the expression of a relevant efflux transporter some 12-fold, in a cell-
selective manner. This binary weapon strategy potentially holds much promise for target-
ing cytotoxic anti-cancer drugs.
Figure 7. “Binary weapons” based on drug transporters [294]. The cytotoxic drug gemcitabine
(GEM, a fluorinated cytosine nucleoside analogue) when added at a certain low concentration to
Panc1 pancreatic cancer cells was barely cytotoxic (left panel). However, when a second drug was
added, which was itself also non-toxic, the combination was substantially more toxic. What had
occurred was that, in response to the GEM, the cells had increased the expression of the efflux trans-
porter ABCC2 (MRP2) some 12-fold; the second drug inhibited this process, and in a cell-selective
manner.
The fact that expression levels of SLCs often vary considerably was illustrated by us
previously [86], using a publicly available dataset [85]. The Gini coefficient (see
[86,100,301,302]) (Figure 8) describes the heterogeneity of a distribution in a simple, non-
Drug 2 varies efflux
transport er
expression
increased toxicity
Drug 2
Drug 2
Proposed partial mode of action of ‘binary weapons’ in
enhancing gemcitabine toxicity in Panc1 cells
Panc1
GEM
GEM
Nucleoside
influx
transporter
GEM GEM
Influx/efflux transporter
expression ratio
insufficient for full toxicity
Dr ug 2
transporter
Nucleoside
efflux
transporters
GEM
GEM
GEM

Molecules 2021, 26, 5629 12 of 39
parametric manner, and takes values between zero and 1. Some of the cell line data are
replotted in Figure 9, where the Gini coefficient is plotted against their median expression
level as assessed by RNASeq. Specifically, we use these data to illustrate four points: (i)
the very fact that there are a great many uptake transporters (at least 400), that may or
may not be expressed in different cells; (ii) those transporters with the lowest Gini coeffi-
cient, indicating their relative homogeneity of expression between cell lines (which may
be referred to as GiniGenes [86,100]); (iii) an example (in the form of SLC18A2, a vesicular
monoamine transporter [303]) of a transporter with both a high Gini coefficient, indicating
a very restricted expression, and a reasonably high expression level; and (iv) the substan-
tial variation in Gini coefficient for the six members of the SLC35F family, with three being
quite selectively expressed (SLC35F1,3,4) while the others (SLC35F2,5,6) are expressed
over a very broad range of values, as shown explicitly elsewhere for SLC35F2 [97]. Over-
all, 61 of the 410 transporters (15%) plotted in Figure 9 have a Gini coefficient over 0.8, 105
(26%) exceed 0.7 and 173 (42%) exceed 0.5. By contrast, the Gini coefficient for income
inequality in different countries (its usual domain of application [304]) https://www.in-
dexmundi.com/facts/indicators/SI.POV.GINI/rankings shows only 14 countries/159 (9%)
with a Gini coefficient exceeding 0.5.
Figure 8. Illustration of the derivation of the non-parametric Gini coefficient for describing the inequality of a distribution
(here the variation of transcript levels between cell lines). This was achieved by rank ordering the value of the different
examples according to their expression levels, as indicated.
Derivation of the Gini coefficient (index)
and its application to absolute
transcriptomics
Cumul a�ve frac�on of total
transcripts when ordered from
lowest to highest expression levels
01
Cumula�ve frac�on of transcript
types in order of increasing
expression magnitude
Area A
Area B
G = A/(A + B)
1

Molecules 2021, 26, 5629 13 of 39
Figure 9. Variation of Gini coefficient and median expression for 410 SLC transporters in 56 cell lines. Data were obtained
from previous open access publications [85,86] and a subset replotted. A few transporters are labelled to illustrate some
of the SLCs with the lowest value of the Gini coefficient (lower right), one with a high value and a reasonable expression
(SLC18A2), and the six members of the SLC35F family. The transcript expression levels are expressed through a wide-
spread normalisation (see [305], but also [306,307]) as reads per kilobase million (RPKM).
1.12. Transporters and Prodrugs
Another strategy that has been widely used to improve cellular drug uptake is the
use of so-called prodrugs, in which a drug is modified by the addition of a moiety that,
although without direct pharmacological activity at a target receptor, assists the passage
of the drug to its target (e.g., [308–318]). These necessarily involve transporters, although
their identity is not always known. Several recent examples showing high efficacy are
based on the SLC7A5 (LAT1) transporter [319–324]. In one recent instance [321], the up-
take of the anti-inflammatory salicylic acid was enhanced more than five-fold by fusing it
with a phenylalanine moiety. Sometimes the prodrug is more lipophilic than its parent,
and this is taken in some quarters to mean that it therefore must be passing through bi-
layers. As pointed out before [8], however, “in actual practice, the reformulation of a water
soluble drug with lipidization modifications is difficult to execute successfully, and there
is not a single example of a drug presently sold whereby medicinal chemistry was suc-
cessfully used to convert a non-brain-penetrating drug into a molecule that crosses the
BBB {blood–brain barrier} in pharmacologically significant amounts” [325].
Variation of expression of SLC transporters in cell lines
Gini coefficient
Expression level / RPKM

Molecules 2021, 26, 5629 14 of 39
1.13. Transporters and Adverse Drug Reactions
Notwithstanding all the benefits of small molecule drugs, it remains the case that
they are also widely associated with various morbidities and mortalities, often referred to
as “adverse drug reactions” (ADRs) (e.g., [326–346]). Despite the lengthy and complex
regulatory hurdles that drugs must overcome before being marketed (and toxicity re-
mains a major cause of so-called “attrition” where drug candidates are pulled before they
even get to market [347–353]), ADRs are extremely common (and hard to anticipate, given
the huge genetic and phenotypic variation in human populations [354]). Due to non-line-
arities in biochemical kinetics, averaging across many cells or tissues necessarily hides the
true biology [267,355], and thus lumping heterogeneous cells into tissues will always miss
such problems [2]. Our contention is that in many cases these ADRs are mediated via
transporters, especially since when concentrative transporters can potentially cause mas-
sive accumulation in particular cells. Failure or inhibition of efflux transporters also has a
major role to play in drug toxicity.
Consequently, the involvement of transporters in ADRs and drug cytotoxicity is
well-established (see above and, e.g., [294,336,339,340,356–394]), providing further evi-
dence for the major roles of transporters in both pharmacokinetics and pharmacodynam-
ics.
1.14. Transporters, Antibiotics, and Antimicrobial Resistance (AMR)
Antimicrobial resistance (AMR) is a major human health problem (e.g., [272,395–
419]). Most pertinently, efflux transporters are well-recognised as a major source of AMR
(e.g., [276,397,420–457]). The outer membrane also contributes significantly to the perme-
ability barrier in Gram-negatives (e.g., [265,434,443,444,448,458–466]). However, another
specific area in which the role of transporters is largely unrecognised—albeit this is a spe-
cific subset of drug transport—pertains to the uptake transport of anti-infectives to their
sites of action [439,467]. This can involve both the targets within the microbe and the host’s
transporters when (as is common, e.g., [468–485]) the infective agents reside intracellu-
larly. A particularly clear example is given by Mycobacterium tuberculosis, the causative
agent of TB, where the very striking lack of correlation between in vivo and in vitro drug
potencies is easily and necessarily explained via transporter activities [139,151,486–488].
Many orally prescribed antibiotics enter the host via SLC15 family members [489,490],
while some of the relatively few known microbial uptake transporters for anti-infectives
are listed in Table 1. What evidence there is implies that there are multiple means of up-
take, which is why identifying individual transporters for successful antibiotics has
proven difficult [276]. On the flipside, of course, when we recognise the relevant trans-
porters and/or their structure–activity relationships governing cell permeability, we can
exploit them [437,444,491–495].

Molecules 2021, 26, 5629 15 of 39
Table 1. Some examples of differential resistance to anti-microbial drugs involving uptake trans-
porters.
Antibiotic
Transporter
Comments
Selected Reference(s)
Aminoglycosides
[496]
Chloramphenicol YdgR
E. coli. Proton-de-
pendent oligopeptide
transporter analogue
[497]
Cycloserine
[498]
5-fluocytosine
FCY2
Various Candida spp.
[499,500]
Fosfomycin
[501,502]
Pacidamycin
Opp
PA14
Pseudomonas aeru-
ginosa
[503]
[504]
Pentamidine
Three adenosine-
based transporters
[441,505]
Quinoline antimalari-
als
AAT1 [506]
Reviews
[441,507–509]
Tetracyclines
Two unknown trans-
porters
[510,511]
1.15. Molecular Dynamics of Transporter Reactions
Given, as mentioned, the present impossibility of detecting the molecular pathway
of drug transport directly, one alternative is to calculate it from first principles, which for
these purposes means via the use of molecular dynamics (MD). MD allows the calculation
“ab initio” of the molecular motions of molecules during their normal activity. Although
computationally demanding (something that becomes much less of an issue over time,
e.g., [512,513]), it is perfectly suited to calculating the mechanisms of substrates transport
across membranes [514]. We have discussed this in more detail elsewhere [2], and so we
simply include here some of the more recent developments. Thus, Jia et al. [515] could
mirror precisely the experimental findings underpinning the behaviours of a xylose trans-
porter. Other findings uncovered an electrostatic lock in emrE [516] (see also [517,518]),
established the molecular basis of sodium-coupled transporters [519], and illustrated the
mechanism of transporters as varied as acrB [520–522], the vitamin B12 importer BtuCD
[523], the maltose transporter ATPase MalK2 [524], McjD (an antibacterial peptide ABC
transporter from E. coli) [525], proton oligopeptide transporters [526], hexameric urea
transporter UreI from Helicobacter pylori [527], and the mammalian transporters SLC1A1
(excitatory amino acid transporter EAAT3) [528], SLC2A1 (glucose transporter GLUT1)
[529], SLC4A1 (“band 3” protein, bicarbonate/anion exchanger) [530], SLC6A4 [531],
SLC7A10 [532]. By contrast, studies of membrane-embedded molecules such as aqua-
porins, when conducted with high protein concentrations resembling those in biomem-
branes [533–536], show that even water molecules do not pass through the bilayer (see a
direct illustration at http://www3.mpibpc.mpg.de/groups/de_groot/gallery/aqp1_snap-
shot.jpg/). In several cases, the MD simulations are accompanied by confirmatory X-ray
structures (e.g., [530,535,536]).
1.16. Uptake Transporters as Drug Targets
Although our chief interest here relates mainly to the role of solute carriers in drug
disposition, we would be remiss not to mention that, largely because they have been seri-
ously understudied [288], SLCs themselves necessarily constitute potentially valuable and
novel drug targets [11,286,537–552]. It is reasonable that the technical improvements in
cryo-EM will contribute to the rational design of such drugs [553], as well as the many
other activities ongoing (e.g., as summarised in [131]).

Molecules 2021, 26, 5629 16 of 39
1.17. What Are the “Real” Substrates of Drug Uptake Transporters?
While some drugs that are SLC substrates are, or are semi-synthetic analogues of,
natural products, most modern drugs are entirely synthetic in nature, and so natural evo-
lution had no known exposure to them. It is then at least reasonable to enquire as to what
the “normal” substrates of these molecules are that happen also to allow them to transport
drugs. The principle of molecular similarity (e.g., [201,554–564]) suggests that molecules
that have similar structures should tend to have similar activities, so the question then
becomes “to which molecules are marketed drugs most similar”? This is a cheminformat-
ics question, and the answer depends in part on the nature of the structural encoding,
although most encodings of “actually” similar molecules show a Tanimoto similarity ex-
ceeding 0.8 or so, a number that may be used as a kind of benchmark. Our initial assump-
tion was that successful, marketed drug should bear structural similarities to endogenous
human metabolites [565–568], which have been catalogued in metabolic reconstructions
[569] and elsewhere (e.g., [570]). However, this accounts for only a small percentage (~15%
[83,200,568]), and the true answer—possibly unsurprisingly, post hoc—is that most drugs
actually bear similarities to natural products, whose uptake via SLCs may be assumed to
be, or to have been during natural selection, of some nutritional or medical benefit to the
host [200,264]. This also brings to the fore the important role of natural products in drug
discovery [9,571–586]. Natural products are, of course, famous for breaking [587–590]
many of the “rule of 5” [591] guidelines, and include many very clear examples of drugs
that cannot possibly diffuse through lipid bilayers in intact biological cells.
1.18. Why Do SOME Solvents Increase the Rate of Drug Uptake?
Anecdotally, there is a common assumption that because solvents such as DMSO can
increase the rate of drug uptake they must be doing so by solubilising the drug, or at least
by assisting its solubilisation, in the phospholipid bilayer part of biomembranes. This
would then be seen as some kind of evidence for the importance of bilayer transport, but
in fact this does not follow at all. The issue with insoluble drugs is that transporters require
their substrates to be bound, and that this normally happens via solubilisation in the aque-
ous phase. Rocks and crystals and amorphous solids are not direct substrates of drug
transporters; molecules are. All that solvents such as DMSO are then doing is increasing
the rate of solubilisation of drug solids and their presentation to the transporters as single
molecules (the necessarily preferred substrates) in solution.
2. Discussion
Real biological membranes possess a high protein:lipid ratio, often as much as 3:1 by
mass. Consequently, they do not remotely behave in a manner similar to pure, artificial,
phospholipid bilayers. Additionally, the transport of small organic molecules (including
drugs) across them commonly requires the intercession of proteinaceous transporters
(e.g., [2,3,6,8,101,287,370,592–620]), and there is in fact no actual evidence whatsoever for
any significant flux across native, undamaged biomembranes through whatever phospho-
lipid bilayer may be present. This contrasts with a widely held set of assumptions, based
in part (it is assumed) on what can be observed in pure phospholipid bilayers that admit
the transport of all kinds of small molecules, albeit through transient aqueous pores.
Identifying these transporters of small molecules can be performed (e.g.,
[96,97,99,101,171]) by manipulating their expression, including under conditions in which
their substrates are otherwise toxic. The idea is that removing (or otherwise inhibiting) a
transporter that normally helps a toxic drug to enter a cell should increase the host’s re-
sistance to it, while overexpressing the transporter would make the cells more sensitive.
More generally, understanding the co-variation between the uptake of a molecule and the
expression of its potential transporters gives a strong indication of which they are.

Molecules 2021, 26, 5629 17 of 39
The recognition that in real biological membranes the transbilayer transport through
phospholipids of small molecule drugs, nutrients, and biotechnology products is negligi-
ble also explains straightforwardly the following well-established facts:
• The negligible uptake of drugs and substrates in some tissues, including via the
blood–brain barrier (and equivalents in the retina, testes, and other tissues), where
relevant transporters are absent;
• The extreme heterogeneity of uptake of a given molecule in different organs, tissues,
and organisms despite little substantive variation in their lipid physical properties;
• The existence of transporters for all kinds of small molecules (even water, acetate,
ammonia, glycerol, etc., as well as entirely hydrophobic molecules such as alkanes
[621–623]) that had previously been assumed to lack them;
• A variety of cases in which individual defined transporters can be shown to account
for the overwhelming bulk of measured fluxes;
• The need for such transporters in order to effect drug uptake, mirroring the wide-
spread recognition that they can serve to efflux them (and thereby created resistance
to their activity);
• The role of transporters in drug-mediated toxicity (e.g., [366,624]);
• The poor correlation between the uptake of small molecules and simple physico-
chemical properties such as log P or log D (many examples, such as those in
[2,6,83,625–627]).
3. Looking to the Future
The two chief questions posed earlier (“what are the substrates for a given tra-
sporter?” and “what are the transporters for a given substrate?”) are normally addressed
experimentally, using a variety of the methods described above. As intimated above, the
exponential increase in computer power will eventually allow the methods of molecular
dynamics to admit these “measurements” entirely by calculations based on simple force
fields, de novo. In addition, given the success of so-called deep learning [628–630] methods
in predicting the structures of proteins [631–645], novel receptor–ligand interactions [646–
650], and a variety of other protein and small molecule properties (e.g., [201,651–665]), it
seems likely that we shall soon have available in silico methods for predicting transporter
substrates directly from protein sequences, and the likeliest transporters from candidate
substrate structures of interest.
4. Conclusions
On the basis of the present evidence, the transport of drugs and nutrients through
phospholipid bilayers in real biomembranes is negligible. Progress in understanding drug
distribution profiles is thus to be made by establishing which transporters they use, the
expression profiles of those transporters, and the kinetic rate equations that they obey.
Armed with these it will be possible to model, to analyse, to understand, and to exploit
our principled knowledge of drug distributions both mechanistically and with confidence.
Funding: DBK thanks the BBSRC (grant BB/R014426/1) and the Novo Nordisk Foundation (Grant
agreement No. NNF20CC0035580) for financial support.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments: I thank many colleagues for useful discussions.
Conflicts of Interest: The author declares no conflict of interest.
Sample Availability: Samples of the compounds are not available from the authors.

Molecules 2021, 26, 5629 18 of 39
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