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440 V. C. Santos et al.
hydroxylamine pentanamide inhibitor (compound 1; Fig. 15.2d). This analysis
revealed that the carbonyl moieties maintained alignment with the water molecule,
even with the incorporation of an amine into the backbone—denoted by the substitution of Phe and tert-but yl carbamate moieties with the decahydroisoquinoline tertbutylamide.
Studies with compound 1 showed a better pharmacokinetic profile than the
hydroxyethylene isostere inhibitor. However, compound 1 exhibited moderate
potency against viral dissemination in infected human T cells with cell culture
inhibitory concentration (CIC
) values of 400 nM. Thus, considering the informa-
95
tion obtained from molecular modeling studies, structural modifications were
explored, leading to the development of indinavir (Fig. 15.2e ), which exhibited a
CIC
of 50 nM and an oral bioavailability of approximately 63% [26]. Indinavir,
95
under the brand Crixivan
®
, was approved in 1996 as a treatment for HIV/AIDS [32].
Finally, it is important to emphasize that other first-generation HIV-1 protease
inhibitors were developed and approved, such as ritonavir, nelfinavir, and
amprenavir. However, the emergence of HIV-resistant strains led to the development
of the so-called second-generation inhibitors.
2.3 Drug Resistance and Second-Generation HIV Protease
Inhibitors
The development of ritonavir, a first-generation inhibitor, provided relevant information for developing lopinavir. Ritonavir is a potent inhibitor (K
of 0.015 nM),
i
which was approved by the FDA in 1996 (Fig. 15.3a). Studies conducted with
ritonavir-treated patients revealed substitutions at nine different codons in the
protease gene, with mutants at Val82* being the first to emerge in infected patients
[33]. This information motivated the search for inhibitors that would not interact
with Val82*, making mutations at this position less likely to induce drug resistance.
The synthesis of DNA from a viral RNA is catalyzed by the viral reverse
transcriptase. This process has a high error propensity, mainly attributable to the
enzyme’s elevated mismatch error rate (10
-3
–10-5nucleotide bases per cycle) and
its absence of proofreading activity. Thus, this phenomenon allows the emergence of
polymorphic mutations within HIV-1 genome [34]. Several factors, such as deleterious mutations, natural selection, and the host immune response, constrict the
proliferation of mutated strains within a specified timeframe [35]. The introduction
of antiretroviral treatment exerts novel selection pressures that may contribute to the
proliferation of drug-resistant strains.
Primary mutations frequently occur in residues near the active site involved in
substrate binding. These mutations affect electrostatic and van der Waals interactions between the enzyme and the inhibitor, frequently reducing binding affinity
15 Molecular Modeling Strategies in Drug Design, Development, and... 441
[36]. Importantly, these modifications can also undermine the proficiency of substrate processing, adversely impacting virus replication [37]. Conversely, secondary
mutations are located outside the active site and may compensate for the deleterious
effects of primary mutations on substrate processing while maintaining drug resistance [38, 39].
Many specific primary and secondary mutations in HIV protease are associated
with different inhibitors, and strategies have been developed to design inhibitors that
interact with the HIV protease in a way that creates a higher barrier to resistance.
Here we discuss the development process of two second-generation inhibitors,
lopinavir, and darunavir.
2.3.1 Lopinavir
Structural analysis, based on the X-ray crystal structure of wild-type HIV-1 protease,
revealed an interaction between ritonavir’s P3 isopropylthiazolyl group and the
Fig. 15.3 Structure-based development of lopinavir. Chemical structure of ritonavir (a) and its
binding mode (PDB ID: 1HXW) in the HIV-1 protease active site (b). Chemical structures of the
cyclic urea compound, A-155564 (c), lopinavir (d), and the binding mode of lopinavir (PDB ID:
1MUI) in the HIV-1 protease active site (e). The isopropylthiazolyl group of ritonavir and the
Val82* residues are highlighted by black dashed lines. The same region is highlighted for the HIV-1
protease structure bound to lopinavir. Residues in chain B are identified by the letter and number
followed by *. Hydrogen bonds are shown as yellow dashed lines. Important residues and
compounds are represented as sticks and colored by atom. Carbons are colored gray in the enzyme
and green or cyan in the compounds. (Figure produced using ChemDraw and PyMOL)
442 V. C. Santos et al.
Val82* residue (Fig. 15.3b)[40]. To develop an inhibitor with activity less depen-
dent on an interaction with Val82*, researchers removed the P3 isopropylthiazolyl
group from ritonavir. However, this reduction decreased the protease affinity,
resulting in a 30-fold lower anti-HIV activity (EC
(EC
= 0.06 μM). A conformation constraint introduced by a cyclic urea compound
50
= 1.8 μM) compared to ritonavir
50
(compound A-155564; Fig. 15.3c) resulted in improved anti-HIV activity
(EC
= 0.15 μM), and the substitution of the P2’ group with a dimethyl phenoxy
50
acetyl group in lopinavir (Fig. 15.3d), which exhibited an EC50of 0.01 μM and a K
of 1.3 pM for the wild-type protease compared to ritonavir ’ s Kiof 10 pM. Moreover,
lopinavir demonstrated higher potency than ritonavir against proteases with mutations in Val82*, such as a K
of 3.7 pM for the V82F mutant HIV protease compared
i
to ritonavir’s Ki of 520 pM [10].
To comprehend the enhanced binding affinity of lopinavir towards both wild-type
and mutant proteases, researchers modeled the inhibitor within the active site of the
protease based on a crystal structure of the complex with ritonavir. In this model, the
2,6-dimethylphenoxy group was positioned in the S2’ subsite to fill the available
space, while the valinyl-cyclic urea moiety was rotated within the S2 subsite to
ensure optimal hydrogen bonding with Asp29 or Asp30 [10, 41]. As expected, the
model suggested that the P3 region of lopinavir engaged in minimal interactions with
Val82*, as later confirmed by X-ray crystallography (Fig. 15.3e)[41].
Ritonavir, originally approved in 1996, was later found to be a potent inhibitor of
cytochrome P450 3A, a key metabolic enzyme for protease inhibitors. Taking
advantage of this property, lopinavir and ritonavir were combined into a single pill
marketed as Kaletra
®
, approved in 2000 for the treatment of HIV infections [42].
i
2.3.2 Darunavir
Moreover, considering the approaches to avoid or overcome resistance, the “backbone binding” strategy has also been adopted. In this approach, the goal is to design
inhibitors that maximize inhibitor-backbone hydrogen-bonding interactions. This
concept arose from a structural analysis comparing X-ray structures of diverse
mutant HIV proteases with those of the wild-type HIV protease, revealing only
minimal distortions on the backbone conformation within the active site
[43, 44]. The backbone binding strategy guided the structure-based design of
darunavir—a non-peptidic inhibitor. To improve water solubility and bioavailability,
research focused on designing non-peptidic cyclic or heterocyclic structures, particularly cyclic ether or polyether-derived ligands.
Initially, researchers developed a cyclic ether-derived ligand (compound 2,
Fig. 15.4a) based on the X-ray structure of saquinavir , which exhibited an IC
of
50
132 nM against the enzyme. Subsequently, an X-ray crystal structure of this ligand
revealed a potential weak interaction between the oxygen atom of the tetrahydrofuran ring and the backbone nitrogen atoms of residues Asp29 and Asp30 [45]. To
strengthen the interacti on with these residues, researchers synthesized compounds
featuring bicyclic tetrahydrofuran rings (bis-THF), resulting in a higher potency
15 Molecular Modeling Strategies in Drug Design, Development, and... 443
Fig. 15.4 The development of darunavir. Chemical structures of a cyclic ether-derived ligand,
compound 2 (a), TMC-126 (b), and darunavir (c). Binding mode of darunavir (PDB ID: 2IEO) to
the HIV-1 protease mutant I84V active site (d). Water molecules are represented as red spheres, and
the hydrogen bonds are shown as yellow dashed lines. Residues in chain B are identified by the
letter and number followed by *. Important residues and compounds are represented as sticks and
colored by atom. Carbons are colored gray in the enzyme and green in the compound.
(Figure produced using ChemDraw and PyMOL)
against the enzyme (IC50= 1.8 nM) and enhanced water solubility [46]. The impact
of bis-THF on potency enhancement was further investigated in the context of other
isosteres [47], culminating in the development of TMC-126, with a K
of 14 pM
i
(Fig. 15.4b). To better understand the potential interactions with this inhibitor,
researchers conducted structural modeling of the HIV-1 protease complexed with
TMC-126. They utilized published crystal structures of HIV-1 protease complexed
with amprenavir, as well as with various inhibitors containing bis-THF, followed by
minimization of the active site using the Sybyl force field [48]. Consistent with
previous studies demonstrating higher potency with the substitution of THF by a
bis-THF group, the model suggests this heightened potency to be linked to hydrogen
bonding interactions between the oxygen atoms of the bis-THF moiety and the mainchain amides of Asp29* and Asp30* residues.
Subsequently, incorporating bis-THF into a p-amino sulfonamide isostere led to
the development of darunavir (Fig. 15.4c). X-ray crystallography studies involving
darunavir complexed with mutant proteases revealed that the interactions between
the bis- THF group and the amides of Asp29* and Asp30* remained intact, while
444 V. C. Santos et al.
new polar interactions were also observed with the side-chain carboxylate of Asp30
(Fig. 15.4d)[49].
In addition to the backbone strategy, another approach to avoid drug resistance is
based on the substrate-envelope hypothesis. Viral polyproteins, subject to processing
by HIV protease, undergo adaptive changes that culminate in forming a conserved
substrate envelope upon binding with the enzyme’s active site [39]. The substrateenvelope hypothesis suggests that the overall substrate conformation is pivotal in
achieving effective binding, not just the amino acid sequence. Mutations near this
substrate envelope significantly diminish the protease‘saffinity for its substrates,
rendering them unfavorable. Consequently, developing protease inhibitors strategically aligned with the substrate envelope should prevent the emergence of drugresistance mutations.
Although the development of darunavir was not based on the substrate-envelope
hypothesis, subsequent studies have shown that it fits the consensus substrate
volume [50]. As expected for a drug complying both with the backbone-binding
strategy and the substrate-envelope hypothesis, darunavir is a non-peptidic inhibitor
of HIV-1 protease with high potency against drug-resistant HIV variants
[11, 51]. Darunavir, sold under the brand name Prezista
2006, and it is part of antiretroviral therapy for people infected with HIV. Another
virus disease for which antiviral drugs were developed with the aid of molecular
modeling techniques is hepatitis C and it will be discussed in the following section.
®
, was first approved in
3 Structure-Based Drug Design of Grazoprevir
and Voxilaprevir as Hepatitis C Virus (HCV) NS3/4a
Protease Inhibitors
In 1989, scientists isolated the so-called non-A and non-B hepatitis agents
[52]. HCV infection occurs mainly in the liver and has an incubation period of
2–12 weeks, which is followed by an acute asymptomatic phase that is often
undiagnosed. When symptoms appear, they can be fever, tiredness, loss of appetite,
nausea and vomiting, abdominal pain, dark urine, pale feces, joint pain, and jaundice
[53]. The infection follows two courses: spontaneous clearance (18–34%) of
infected individuals or progression to chronic infection [54]. HCV can be found
worldwide, and the WHO estimated in 2024 that 50 million people were chronically
infected with the virus [53].
Two FDA-approved drugs targeting the HCV non-structural (NS) proteins
NS3/4a protease were developed using computational methods. NS3 is a
non-structural protein with two domains: N-terminal serine protease and
C-terminal RNA helicase [55]. NS4a is a polypeptide co-factor for the protease
activity of NS3. The NS3/4a complex processes the HCV polyprotein, releasing
among the cleavage products, the non-structural proteins required for virus replication [56]. HCV is phylogenetically classified into eight genotypes, named 1 to 8,
15 Molecular Modeling Strategies in Drug Design, Development, and... 445
Fig. 15.5 Structure-based development of grazoprevir. Chemical representation of BILN-2061 (a);
crystal structure of the full-length NS3/4A (protease domain with residues in green; helicase domain
with residues in pink, the enzyme is colored in gray) (PDB ID: 1CU1) (b); and chemical structure of
grazoprevir (c). The P4–P1 positions of each compound are labeled. Important residues and the
compounds are represented as sticks and colored by atom. (Figure produced using ChemDraw and
PyMOL)
according to the date when they were discovered [57]. Most of the hepatitis C cases
involve GT1 (44%), GT3 (25%), and GT4 (15%) [58]. The first drugs developed
targeted GT1, and as the other genotypes were being described, resistance emer ged,
making necessary the genotyping of patients’ samples to select the best treatment
option; however, this was only sometimes possible. Thus, the discovery of
pan-genotypic anti-HCV compounds represented a significant advance in hepatitis
C treatment, and nowadays, these compounds are used across the globe, and the
countries adopting them are released from the need for sample genotyping [59 ].
The development of grazoprevir and voxilaprevir will be discussed here and they
have the same starting point. The first macrocyclic inhibitors designed were based on
NMR data of subst rate-like peptide inhibitors of NS3/4a protease and were rigid to
ensure the trans geometry of the P2-P3 amide bond [60]. Later, the macrocyclic
inhibitor BILN-2061 (Fig. 15.5a) was modeled into the active site of the apo crystal
structure of NS3/4a protease (PDB ID 1CU1) [61, 62]. Considering that the P2 and
thiazolyl quinoline portions of BILN-2061 lie on pockets formed between the
protease and helicase domains of NS3/4a, more analogs were designed and modeled
to the same crystal structure. This modeling led to the design of compounds with a
P2–P4 macrocyclic constraint active against genotypes GT1 and GT2 of NS3/4a
protease [63]. However, analogs with a large substituent to the P2 heterocycle and
fused ring were more active against the GT3 genotype enzyme when compared to
GT1. After modeling these analogs [14], a cyclopropyl constraint was added to the
P2–P4 macrocyclic linker, improving the electrostatic interactions with the residue
156 (Fig. 15.5b), probably leaving room to accommodate the A156T/V substitutions
observed in resistant HCV populations, also resulting in increased the lipophilicity to
enhance the liver exposure (since HCV infects the liver), and a quinoxaline was
added to improve the compound’s solubility. All of these resulted in the discovery of
grazoprevir (Fig. 15.5c), approved in 2016 by the FDA under the name Zepartier
®
,a
single-oral dose pill also containing the NS5a inhibitor elbasvir [64].
446 V. C. Santos et al.
Fig. 15.6 Structure-based development of voxilaprevir. Chemical representations of compound
3 and voxilaprevir (a). Crystal structure of voxilaprevir complexed with GT1 D168Q (GT3
surrogate) NS3/4A protease (PDB ID 6NZT) (b). Water molecules are represented as red spheres,
and the polar contacts are shown in yellow dashed lines. The P4–P1 positions of each compound are
labeled. Important residues and compounds are represented as sticks and colored by atom. Carbons
are colored gray in the enzyme and green in the compound. (Figure produced using ChemDraw and
PyMOL)
Patients treated with grazoprevir had their serum alanine transaminase elevated, a
potential biomarker for hepatotoxicity, resulting in a reduction in the clinical dosage
and warnings on the prescription label [15]. Another issue that emerged with the
description of new HCV genotypes was that grazoprevir shows higher activity
against GT1 than GT3 [65]. Therefore, researchers focused on improving the activity
of the molecules against HCV genotypes targeting the catalytic triad residues
(Ser139, His57, and Asp81) since they are conserved across the genotypes. This
led to the developed of compound 3 (Fig. 15.6a), with good antiviral [half-maximal
effective concentration (EC
) of 23 nM] and enzymatic (Kiof 165 pM) potency. An
50
X-ray crystallography structure of compound 3 with GT1 D168Q (GT3 surrogate)
NS3/4A protease (PDB ID 6NZV) showed the ethyl part of 3 in a van der Waals
interaction with His57.
Additionally to the improvements in potency against GT3, efforts were made to
improve the compound’s pharmacokinetics and liver distribution to reduce the
hepatotoxicity. The search for compounds with superior metabolic stability and
reduced formation of protein adducts eventually led to the development of
voxilaprevir (Fig. 15.6a)[15, 66]. Voxilaprevir is more potent than 3 in GT3
enzymatic (K
of 63 pM) and antiviral (EC50of 6.1 nM) assays. This higher potency
i
might be explained by hydrophobic contact between the difluoro methylene on the
macrocycle and the alkyl portion of R155, as observed in the co-crystal with GT1
15 Molecular Modeling Strategies in Drug Design, Development, and... 447
D168Q (GT3 surrogate) NS3/4A protease (PDB ID 6NZT) (Fig. 15.6b). Overall, the
activity of Voxilaprevir against common GT1–6 ranged between an EC
6.6 nM. Voxilaprevir, together with sofosbuvir (inhibitor of the HCV NS5B polymerase) and velpatasvir (HCV NS5A inhibitor), is a component of Vosevi
of 1.5 and
50
®
approved in 2017 as a pan-genotypic treatment for patients who failed previous
therapies for hepatitis C [15].
,
4 Structure-Based Drug Design of Nirmatrelvir
pro
and Ensitrelvir as SARS-CoV-2 M
Since 2020, in response to the COVID-19 pandemic, there have been remarkable
efforts to design drugs targeting proteases. The description of COVID-19 was
quickly followed by the identification of its causing agent, the severe acute respiratory syndrome-related Coronavirus 2 (SARS-CoV-2), which was classified in the
Coronaviridae family by the Coronaviridae Study Group (CSG) of the International
Committee on Taxonomy of Viruses, based on the recognized similarity to bat
coronaviruses and human coronaviruses [67]. The first cases of the disease were
reported initially as pneumonia of unknown origin, in November 2019, in Wuhan
(China). Just 4 months later, in March 2020, COVID-19 had spread throughout the
globe, and a pandemic situation was declared. By that point, the SARS-CoV-2
genome had been sequenced [ 68 ], revealing high similarity to other coronaviruses,
and there were already crystallographic structures of SARS-CoV-2 main protease
pro
(M
, also known as chymotrypsin-like protease, 3CL
like protease (PL
pro
M
and PL
viral polypeptides pp1a and pp1ab into 16 nonstructural viral proteins [70]. Thus,
these proteases were promptly targeted for drug design. Later, with a better understanding of the process of host cell infection by SARS-CoV-2, the human proteases
Cathepsin L and TMPRSS2 were also identified as targets for the development of
COVID-19 treatments [71, 72 ]. While there are numerous studies on each of these
four targe t proteases, the most successfully targeted is M
our discussion on this target. In addition to its importance for viral replication, M
is considered a good drug target due to its unique specificity for Gln at P1, which is
not found among human cysteine proteases, contributing to the developing specific
pro
M
inhibitors and improves drug safety. Also, its conser vation among coronavirus
creates the potential for developing broad-spectrum antiviral drugs.
Computational strategies employed toward the development of M
include docking-based virtual screening of FDA-approved drugs [73], in-house
libraries [74, 75], and ultra-large commercial libraries [76, 77] (see Chaps. 8
and 11). Free energy perturbation calculations (see Chap. 10) have also led to potent
pro
M
inhibitors with antiviral activity [78]. Machine learning models have also been
successfully employed to extract information from high-throughput structural data
pro
) deposited in the Protein Data Bank.
pro
are essential for SARS-CoV-2 multiplication, as they process the
Inhibitors
pro
, or NS5) [69 ] and papain-
pro
, and thus we will focus
pro
pro
inhibitors
448 V. C. Santos et al.
Fig. 15.7 Structure-based development of nirmatrelvir. Chemical structures of the PF-00835231
(lead compound) and PF-07321332 (nirmatrelvir) (a). Binding mode of nirmatrelvir (PDB ID:
7RFW) in the SARS-CoV-2 M
lines. The P4–P1 positions of each compound are labeled. Important residues and compounds are
represented as sticks and colored by atom. Carbons are colored gray in the enzyme and salmon in
the compound. (Figure produced using ChemDraw and PyMOL)
pro
active site (b). Hydrogen bonds are represented as yellow dashed
and benefit the design of inhibitors that reveal potent antiviral properties [79]. Altogether, efforts based on computer-aided techniques and experimental approaches
have yielded several class es of M
pro
inhibitors (reviewed by [ 80]), including
marketed drugs.
The active site conservation between SARS-CoV and SARS-CoV-2 was a key
factor contributing to the quick development of Paxlovid
the SARS-CoV-2 M
developing nirmatrelvir was the SARS-CoV M
pro
inhibitor nirmatrelvir and ritonavir. The starting point for
pro
®
, a medicine containing
inhibitor PF-00835231, previously developed in structure-based design efforts against SARS-CoV [81]. After the
outbreak of COVID-19, PF-00835231 was also shown to be potent against the
SARS-CoV-2 enzyme and in infected Vero E6 cells, showing stability in plasma,
adequate solubility, and clearance rates suitable for development as a COVID-19
treatment via intravenous infusion [81].
Nevertheless, the low passive absorptive permeability of PF-00835231 was an
important limitation that had to be overcome to obtain an orally administered drug.
Thus, PF-00835231 was the lead compound for structure-based efforts to optimize
its pharmacokinetic properties (Fig. 15.7a). Throughout optimization, molecular
modeling studies against SARS-CoV-2 M
pro
were employed to suggest compounds
that should simultaneously result in favorable pharmacokinetic properties and maintain high potency against the target [12]. Examples of modifications guided by
modeling studies include the removal of hydrogen bond donors to improve oral
absorption and the incorporation of a nitrile warhead to enhance solubility while also
introducing modifications to ensure the occupation of the S2 and S3 pockets and
performing hydrogen bond interactions with Gln189 and Glu166 (Fig. 15.7b, c).
15 Molecular Modeling Strategies in Drug Design, Development, and... 449
Among the compounds developed, PF-07321332 (nirmatrelv ir) was chosen as the
clinical candidate considering its potent activity against M
pro
, in antiviral assays and
animal models, the ease of synthetic scale-up, reduced propensity for epimerization,
and enhanced solubility. Additionally, it showed antiviral activity against multiple
coronaviruses and no inhibitory effects against a wide panel of mammalian proteases, G protein-coupled receptors, kinases, transporters, phospho diesterases, and
cardiac ion channels. One limitation in nirmatrelvir’s profile was its intense metabolism by CYP450, especially by CYP3A4. To overcome this hurdle,
co-administration with ritonavir, a potent CYP3A4 inhibitor, was proposed and
yielded an improved pharmacokinetic profile [12]. This combination demonstrates
how CYP450 inhibition, frequently considered an unfavorable property due to
associated drug–drug interactions, was explored positively. The nirmatrelvir/ritonavir combination, licensed as Paxlovid
®
, reduced hospitalization by 89% in
unvaccinated adults at high risk for progression to severe COVID-19 [82]. Paxlovid
was approved for emergency use by the FDA in December 2021, followed by
approval by several international agencies, and was fully approved in May 2023.
The development of ensitrelvir (Xocova
structure-based approaches [13]. Aiming to discover noncovalent and nonpeptidic
inhibitors of SARS-CoV-2 M
pro
, researchers performed a docking-based virtual
®
) was also highly supported by
screening of their in-house library. To filter the docking results, they also built a
pharmacophoric model based on the crystallographic structures of three ligands in
complex with M
pro
. The pharmacophore consisted of an acceptor site hydrogen
bonding with the side-chain NH donor of His163 in S1, a lipophilic site in S2, and
an acceptor site interacti ng with the Glu166 main-chain NH, all of which had to be
present. It is interesting to highlight that the definition of a pharmacophore was
supported by the large amount of structural data of complexes of ligands bound to
pro
M
, including those from important initiatives such as the COVID-19 Moonshot
[83]. After filtering to ensure the compounds met the proposed pharmacophore, the
top 300 compounds from the virtual screening were evaluated in biochemical assays
with M
optimization. While 4 had a moderate potency against the enzyme (IC
pro
. Among the hits with IC50under 10 μM, hit 4 was prioritized for
of
50
8.6 μM), it presented a favorable pharmacokinetic profile with in vitro metabolic
stability, high oral bioavailability, and low clearance in vivo in rats.
Co-crystallization of 4 with M
pro
confirmed the binding mode predicted by docking
and supported its structure-based optimization based on modifications in two regions
(Fig. 15.8a, b). First, to optimize interactions with the S1’ pocket, a cyclization was
performed in the P1’ motif while maintaining the hydrogen bond with Thr26,
resulting in compound 5. Remarkably, a 90-fold improvement in enzymatic inhibition (IC
of 0.096 μM) was obtained with this modification while keeping a
50
favorable pharmacokinetic profile. Then, ensitrelvir (a.k.a. S-217622) was designed
by an additional cyclization in the P1 motif and a modification in the pattern of
fluorine substitution in the P2 ring (Fig. 15.8a, c). Ensitrelvir showed high potency
against M
pro
(IC50of 0.013 μM) and in antiviral assays (EC50of 0.37 μM), high
metabolic stability in vitro, high oral absorption, and low clearance in rats, monkeys,
and dogs.
®