Efforts aimed to reduce attrition in antimalarial drug discovery: A

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Efforts aimed to reduce attrition in antimalarial drug discovery: A systematic evaluation of current antimalarial targets portfolio María Jesus Chaparro, Felix Calderon, Pablo Castañeda, Elena Fernandez Alvaro, Raquel Gabarro, Francisco-Javier Gamo, María G. Gómez-Lorenzo, Julio Martín, and Esther Fernandez ACS Infect. Dis., Just Accepted Manuscript • DOI: 10.1021/acsinfecdis.7b00211 • Publication Date (Web): 10 Jan 2018 Downloaded from http://pubs.acs.org on January 11, 2018

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ACS Infectious Diseases

Efforts aimed to reduce attrition in antimalarial drug discovery: A systematic evaluation of current antimalarial targets portfolio

María Jesús Chaparro, Félix Calderón, Pablo Castañeda, Elena Fernández-Alvaro, Raquel Gabarró, Francisco Javier Gamo, María G. Gómez-Lorenzo, Julio Martín, and Esther Fernández* Tres Cantos Medicines Development Campus, DDW, GlaxoSmithKline, Severo Ochoa, 2, 28760 Tres Cantos, Madrid, Spain *corresponding author email: [email protected]

Malaria remains a major global health problem. In 2015 alone, more than 200 million cases of malaria were reported, and more than 400,000 deaths occurred. Since 2010, emerging resistance to current front-line ACTs (Artemisinin Combination Therapies) has been detected in endemic countries. Therefore, there is an urgency for new therapies based on novel modes of action, able to relieve symptoms as fast as the artemisinins and/or block malaria transmission. During the past few years, the antimalarial community has focused their efforts on phenotypic screening as a pragmatic approach to identify new hits. Optimization efforts on several chemical series have been successful, and clinical candidates have been identified. In addition, recent advances in genetics and proteomics have led to the target deconvolution of phenotypic clinical candidates. New mechanisms of action will also be critical to overcome resistance and reduce attrition. Therefore, a complementary strategy focused on identifying well-validated targets to start hit

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identification programs is essential to reinforce the clinical pipeline. Leveraging published data, we have assessed the status-quo of the current antimalarial target portfolio with a focus on the blood stage clinical disease. From an extensive list of reported Plasmodium targets we have defined a triage criteria. These criteria consider

genetic,

pharmacological

and

chemical

validation,

as

well

as

tractability/do-ability, and safety implications. These criteria have provided a quantitative score that has led us to prioritize those targets with the highest probability to deliver successful and differentiated new drugs. KEYWORDS Malaria, malaria targets, target based screenings, new chemical space Malaria is still a major global health problem. Half of the world's population is at risk of malaria and in 2015 alone more than 200 million cases of malaria were reported and more than 400,000 deaths occurred. At the beginning of 2016, 91 countries and territories were malaria endemic although sub-Saharan Africa continues to be the region with the highest malaria burden. In fact 90% of the total cases and 92% of the reported deaths occurring in this area were in children under 5 years of age and pregnant women.1 Recently WHO Global Technical Strategy for Malaria 2016-2030 has been endorsed as a 15-year malaria framework for all countries working to control and eliminate malaria. The awareness of governments, public health systems and funding agencies gives a timely chance to change the course of this disease, achieve control of the spread of the disease and eventually eradicate it. A variety of

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approaches are being followed to achieve this objective of eradicating malaria with vaccines,

vector

control

and

chemotherapy

as

different,

complementary

strategies.2 The vaccine, RTS,S, also known as Mosquirix®, was created by scientists at GSK in 1987. It was developed in a public-private partnership with the PATH (formerly the Program for Appropriate Technology in Health), Malaria Vaccine Initiative (MVI) and with support from the Bill and Melinda Gates Foundation along with local health organizations from Africa. Encouraging Phase III results for vaccine RTS,S have shown it to provide partial protection in children. As a next step, WHO in coordination with GSK, will be piloting the use of the vaccine in 3 African countries.3-5 The use of bed nets and insecticides continue to be very effective protective measures despite the constant increase in insecticide resistance remaining a concern. Finally, Tafenoquine is being developed by GSK in collaboration with MMV (Medicines for Malaria Venture) as a single-dose treatment to prevent relapse of Plasmodium vivax malaria and it has been submitted for FDA approval at the end of 2017.6 Nevertheless, the effectiveness of the current antimalarial therapy is under continuous threat through the spread of resistant Plasmodium strains. Emerging resistance is starting to be seen in SouthEast Asia to the most recent class of antimalarial drugs used in the current standard-of-care

regimens

(ACT:

artemisinin-combination-therapies)

.7,8

Consequently, there is a clear and urgent need to identify new therapies with a novel mechanism of action. Such new treatments must be efficacious against current resistant strains, display a rapid onset of antimalarial effects and demonstrate activity against different stages of parasite lifecycle.9

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Traditionally, different strategies have been followed to develop new antimalarial treatments and target based drug discovery approaches were the focus over the last decades.10,

11

This strategy has not delivered the expected wave of new

antimalarial agents with lack of whole cell activity being the main cause of failure due to the absence of validated targets in most cases.12-14 The current late stage antimalarial pipeline lacks new assets with an identified, novel mode of action. DSM265 (DHODH inhibitor, Takeda), currently in Phase II, and P218 (DHFR inhibitor, Janssen), currently in Phase I, both developed in partnership with MMV (Medicines for Malaria Venture), are the only late stage antimalarial assets discovered through a traditional target based program (Figure 1).15-18

Figure 1. Antimalarial clinical compounds (Phase I-III) and their corresponding mode of action (new chemical entities).

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During the last few years, the antimalarial community has focused their efforts on phenotypic screenings as a pragmatic approach to identify new compounds able to cure blood stage clinical disease. The use of this strategy avoids potential permeability issues of compounds, can lead to the identification of hits that act through multitarget mechanisms as well as new hits with unknown modes of action. In the period 2008-2010 more than 21,000 compounds were identified through different phenotypic screens and their structures were made public in an effort to accelerate the identification of new promising antimalarial clinical candidates.19-22 Since the release of this huge amount of information, extensive work has been carried out by the antimalarial community on different structural chemical classes and some of them have become successful, delivering the expected outcome.23 As a consequence, phenotypic screens have delivered nearly all potential new drugs in the global antimalarial clinical pipeline and the majority of them are being developed in partnership with MMV: KAE609 (PfATP4, Phase II, Novartis),24-26 KAF156 (undetermined MoA, Phase II, Novartis),27-29 MMV390048 (Pi4K, Phase I, UCT),30,31 SJ557733 (PfATP4, Phase I, Kentucky/Eisai),32,33 ACT451840 (unknown MoA, Phase I, Actelion),34 GSK030 (PfATP4, preclinical, GSK),35 GSK607 (PfATP4, preclinical, GSK),36 and DDD107498 (EF2, preclinical, Merck) (Figure 12).37 Interestingly, 8 of these clinical or preclinical candidates exploit only 3 distinct modes of action, with 2 modes of action yet to be defined. This can be explained by different reasons such as availability of biased screening collections, usage of similar criteria in the identification of hits from screening or use of identical phenotypic assay conditions that tend to select the same kind of chemotypes to provide the desired biological phenotype. Several clinical candidates sharing the

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same mode of action affords a strong antimalarial pipeline that assures that at least one molecule per mode of action will be successfully launched and therefore reduce attrition. On the contrary, this decreases the diversity of new mechanisms of action that are critical to overcome resistance. In addition, during this last decade, the clear majority of the identified quality hits in the phenotypic screens have been already explored, leading to the exhaustion of the available chemical libraries. Furthermore, there is a big overlap in the available screening collections that makes the search for new chemical diversity a great challenge.38

Figure 2. Pre-clinical and clinical candidates under development originating from phenotypic hits.

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New chemical libraries to screen that can provide differential molecules to overcome the potential failure of existing assets as well as filling the current gaps in the clinical pipeline is clearly needed. Exploration of new chemical diversity such as natural products that traditionally have delivered many anti-infective drugs represents a promising opportunity as well as the development of new phenotypic assays having different readouts that could identify yet unexplored chemical space.39-41 Finally, a complementary strategy focusing on identifying and/or leveraging knowledge of well validated targets to start hit identification programs is essential to strengthen the malaria pipeline. We refer to new validated targets as those having evidence for essentiality either by genetic method, using pharmacology data with validated tool compounds (in vitro, in vivo or in the clinic) and/or there is a biochemical rationale for the target/pathway. New target based screens can provide a route to novel assay modalities to unveil new chemical space which has remained dark to phenotypic screens. This is a risky approach based on previous experience from the antibacterial field and will require taking learnings from past target based programs.

42

This means just

selecting those targets for screening with enough validation data. In addition, these new target based screens will use the already available chemical library collections. Therefore, this will lead to the identification of hits lacking whole cell activity as, theoretically, those having whole cell activity were already identified in the phenotypic assays. This will imply that whole cell activity could be designed in during the progression of the drug discovery programs.43,44

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Leveraging published data, we at GSK have assessed the status-quo of the current antimalarial target portfolio with a focus on the blood stage clinical disease. We have also considered those targets involved in sexual and liver stages able to block transmission, although not as our main objective as usually less knowledge is available. We have done a comprehensive exercise to select those targets with the highest probability of delivering successful and differentiated new drugs based on an exhaustive assessment as is described below. From an extensive list of previously reported Plasmodium targets, we have defined the key requirements that a potential successful target should meet. For these, we have built some criteria and defined a score that considers genetic, pharmacological and chemical validation, tractability/do-ability as well as novelty, and safety implications. These criteria have provided a rating that has led us to prioritize the most promising targets to initiate medicinal chemistry programs. RESULTS AND DISCUSSION The complete Plasmodium falciparum genome sequence was published in 2002 and revealed more than 5,000 genes encoding the corresponding proteins that could potentially be considered as therapeutic targets.20,45,46 We have then followed a systematic approach that includes: a definition of the desired phenotype our ideal target should provide; generation of a comprehensive list of antimalarial targets to be evaluated; a definition of the critical requirements to be considered; assigning a numerical score to each one, and finally a target prioritization based on the final ratings.

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Before starting our evaluation, we decided to define the phenotype that an ideal antimalarial target should provide. A new target should be essential, validated and tractable, that means target screening would have a reasonable chance of delivering viable and high quality starting points. It should provide a desired therapeutic profile, that includes a fast acting profile, i.e. compounds acting through the target should have a killing/clearance profile like artemisinin or chloroquine, and activity against all parasite stages. Finally, if a human homolog exists, it is critical to have evidence that selectivity can be achieved. The number of known antimalarial validated targets is quite low so we have considered those targets with some degree of previously published information as well as targets where GSK have generated internal information and knowledge.47-51 In addition we have decided to include in our exercise not only targets but also pathways that would provide higher probabilities of success of achieving the required and desired phenotype. Those pathways selected for evaluation have been chosen based on published information and/or when very little information is available for the individual target. As described in Table 1, our selected targets/pathways are categorized depending on the subcellular localization and/or cellular function. We have evaluated targets distributed in all Plasmodium organelles and have not limited our selection to Plasmodium falciparum. We have considered in our analysis other human Plasmodium species such as P. vivax, although we have not considered rodent species. Our exercise has covered many published malaria targets and pathways, although we have left some of them out such as host targets. Those already known targets that cause a delayed phenotype like most of the antibacterials targeting the apicoplast have also not been included

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as GSK is not considering this phenotype as a main priority. We have included very well-known targets such as DHODH or bc1 and others with less available knowledge like PfATP4. Lastly, in those cases in which very little information was available for some targets, we decided to evaluate them as a target class group. For example, that was the case of several epigenetic targets such as most HDACs (histone deacetylases) or HKMTs (histone lysine methyltransferases). Another example has been aminoacyl t-RNA synthetases: from the 36 potential targets, we have only chosen those with the most knowledge in the literature. After the total compilation, more than 50 different targets and/or pathways were finally considered (Table 1).

Table 1. List of targets and pathways (green) evaluated.a Transporters

Kinases

Gene expression

Protein and DNA/RNA synthesis

Proteases

Ubiquitin Proteasome System

Organelles

Others

ATP6

PK6

HKMTs

DHODH

DPAP1

Proteasome

Cytbc1 (mitochondria)

NMT (post-translational modifications)

ATP4

PK7

HDAC1

EF2

DPAP3

DUBs

Heme polimerization (digestive vacuole)

Palmitoyl transferase (posttranslational modifications)

ABCl3

FIKK kinases

HDAC2

Pro-tRNA synthetase

Methionyl Aminopeptidase

E3 ligases

Isoprenoid biosynthesis (apicoplast)

Farnesyl transferase (posttranslational modifications)

FIKK8

Lys-tRNA synthetase

Glutamate dehydrogenase (redox reactions)

MAPK2

Met-tRNA synthetase

Thioredoxin reductase

CDPK1

Phe-tRNA-synthetase

Hsp90

PKG

Thr-tRNA-synthetase

PDEs

PI3K

mRNA capping (3 activities)

ERAD pathway

PI4K

dUTPase (nucleotide metabolism)

G6PD (pentose pathway)

DHFR (folate pathway)

ACS10&11

GSK3

DHFR-TS (Thymidylate synthase)

a

ABCl3, ATP binding cassette transporter I family member 1; ACS10&11, acyl-CoA synthetases 10&11; ATP4, P-type ATPase 4; ATP6, Sarco/endoplasmic reticulum calciumdependent ATPase; CDPK1, calcium-dependent protein kinase; Cytbc1, cytochrome bc1 complex; DHODH, dihydroorotate dehydrogenase; DHFR, dihydrofolate reductase; DPAP, DiPeptidyl AminoPeptidase; DUB, DeUBiquitinase; dUTPase, deoxyuridine 5’triphosphate nucleotidohydrolase; EF2, elongation factor 2; ERAD, Endoplasmic

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Reticulum Associated Degradation pathway; FIKK, Serine/threonine protein kinase, FIKK family; FT, farnesyl transferase; G6PD, glucose-6-phosphate dehydrogenase; GSK3, glycogen synthase-3; HDACs, histone deacetylases; HKMT, histone lysine methyl transferases; Hsp90, heat shock protein 90; MAPK2, mitogen-associated protein kinase 2; NMT, N-myristoyltransferase; PDEs, phosphodiesterases; Pi3K, Phosphatidylinositol-3kinase; Pi4K, phosphatidylinositol-4-OH kinase; PK6, protein kinase 6; PK7, protein kinase 7; PKG, cGMP-dependent protein kinase; TS, thymidylate synthetase.

Selecting the highest ranked targets to increase the probability of success of delivering clinical candidates is the main objective of this exercise. As such, before starting to evaluate our final list of targets in depth, we defined the critical parameters to be considered that would help in assessing the most relevant target properties while making it possible to triage them. We have first included the different validation aspects: genetic, biochemical and pharmacological (in vivo and/or clinical). These validation aspects have been evaluated and scored based on the available knowledge for the intraerythrocytic stages of the disease. If information is available for sexual and liver stages, we have also considered them although the focus has been on blood stages of the disease. We also have taken into consideration what was known in terms of the mode of action and potential therapeutic profile (or target candidate profiles, TCPs) provided for every target. Another important aspect that we have considered is the selectivity versus human homologs and the safety implications that a lack of selectivity would imply. We have considered selectivity mainly based on degree of homology although we acknowledge that this is not the only criterion. However, for many targets it is the only available information. Tractability and do-ability of a target are essential parameters mainly referring to target druggability or the likelihood of identifying good quality chemotypes and the availability of a medium-high throughput assay. ACS Paragon Plus Environment

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Finally, the novelty and competitor landscape along with other available data were on our list of criteria to be considered. This last includes the evaluation of similar targets in Kinetoplastid organisms such as Trypanosoma and Leishmania that would help in considering repurposing opportunities within GSK. Details of what specific data should be considered under every parameter are described in Figure 3. Once all the required parameters were decided, the next step was to assign a score that would allow prioritization of our list of targets based on these ratings at the end of the process. Among the different options considered, ranging from a traffic light system to numerical values we finally decided on the system described in Figure 3 in which the score ranges from -1 to 3. With -1 being the score used when contradictory evidence is present, 3 for targets having the strongest evidence and using 0 when required information is unknown (Figure 3).

Strong: KO available/described or KO Evidences on genetic editing (3), moderate: KO essentiality of the target: not described but locus there is a relevant

Genetic Validation

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has been accessed (2), phenotype (parasite death) weak evidences (1), from loss or gain of function unknown (0), and of target gen evidences of no essentiality (-1) Tool compounds modify

Strong (3), moderate (2),

relevant mechanism and

weak (1) evidences, (0)

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Pharmacological

provide desired phenotype

unknown and (-1)

in vivo and/or show benefit

contradictory evidences

in human disease (clinic) Strong (3), moderate (2), Biochemical rationale for the

weak (1) evidences, (0)

target/pathway essentiality

unknown and (-1)

Biochemical contradictory evidences Fast (killing/clearance

profile like artemisinin or chloroquine) (3),

Speed of killing

Target/mechanism provide

moderate

compounds with a Fast,

(killing/clearance profile

Moderate or Slow profile

like mefloquine) (2), slow (killing/clearance profile like atovaquone (1), a

unknown (0), NA (-1)

MoA

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Parameter used for

Therapeutic

Target Candidate Profiles

Profile

(TCPs)

9

information as it is mainly defined by speed of killing and life cycle essentiality Target is expressed in

Life Cycle essentiality

Target is expressed in

blood, sexual and liver

blood, sexual and/or liver

stages (3), blood&sexual

stages

(2), blood (1), unknown a

(0), NA (-1)

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There is no human homolog (3), there is human homolog but there

Selectivity

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Evidence pointing at differential mechanisms for

is evidence of achieving

human vs. parasite target (e.g. different enzyme

selectivity (2), there is

requirements), or substantial difference in

human homolog but

homology or already available evidences that

evidence of achieving

selective compounds can be obtained

selectivity is weak (1), unknown (0), there is evidence that selectivity is not achievable (-1) Precedents of small molecules inhibiting the target and providing whole cell activity (3), robust evidence of binding

Tractability

Chances that target screen will identify quality hits

but no phenotype (2)

to initiate medicinal chemistry programs

there is 3D structure knowledge but nothing else (1), unknown (0), evidence that no quality hits will be identified Assay/screen already

Do-ability

Evidence that an assay/screen can be configured

developed in HTS format

for the target

plus reagents are available (3), robust assay available that needs optimization (2), purified

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protein and assay concept available (1), no assay available neither additional information (0), a

NA (-1) No competitors are working on the target (3), there are some competitors but there are no clinical candidates (2), target is not novel and Target is novel and

there are compounds

Competitor landscape

inhibiting that target in

Novelty and competitor landscape clinical stages (1), unknown (0), target is not novel, there are several clinical candidates and no issues in their development (-1)

Homology with other parasites

Supporting evidences on the

Strong (3), moderate (2)

existence and high degree

or weak (1), unknown (0),

of similarity of the target in

contradictory evidence (-

Leishmania and

1)

Trypanosomas

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a

NA, Not Applicable

Figure 3. Parameters considered for target evaluation along with the defined score.

After the definition of our critical parameters as well as the score was set up, we then initiated the process of deeply evaluating every single target from our list. We either used information available in the literature or internally generated at GSK. We assigned an individual score to each parameter for every target with a maximum of 3 and a minimum of -1 for every field. The only exception was the therapeutic profile in which we have assigned the corresponding TCP or 0 if unknown. All the results are summarized in Table S1 (Supplementary Material). Once the evaluation of the total list was finished, we then initiated a prioritization process. As we previously commented, different approaches could be considered and any of them would provide a different prioritization list. The simplest option was the sum of all the required parameters that would give us a total maximum score for every single target/pathway of 36 (12 parameters x maximum score of 3) and a minimum of -12 (12 parameters x minimum score of -1). Although this would give us a very good range of values that would help prioritization, it the convenience of

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giving every single parameter the same weight was discussed. Those parameters related to Validation, Tractability, MoA and Therapeutic Profile should be considered as our priority to select those targets with the highest probabilities of delivering new antimalarial drugs. We then evolved our scores to group validation and tractability together and MoA and therapeutic profile together. New resultant scores were a maximum value for Validation&Tractability of 15 and minimum of -5 and a maximum value of 6 and minimum of -2 for MoA&Therapeutic Profile. Remaining parameters have also been considered to make our final prioritization. The result is presented in Figure 4. Additional visualizations of our evaluation that would lead to different target prioritization are included in Supplementary Material (Figures S1-S3).

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Figure

4.

Visualization

of

all

evaluated

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malaria

targets:

y-axis:

Validation&Tractability; x-axis: MoA/Therapeutic Profile; colour by selectivity; shape by do-ability and size by Novelty&Competitor knowledge.

Based on these parameters it was easy to identify which targets had the highest scores. Using a first cut-off in which we only kept those targets having a Validation&Tractability score equal to or higher than 7 and a MoA&Therapeutic Profile equal to or higher than 3, 12 most preferred targets were selected (Figure 5). These included several aminoacyl t-RNA synthetases, general mechanisms such as haemoglobin degradation and isoprenoid biosynthesis, organelles like proteasome, kinases like Pi4K and PKG and finally some very well-known targets such as DHFR or others with a number of candidates already in the clinic like PfATP4. Additional parameters were also considered to further prioritize and novelty/competitor landscape was included in the evaluation as our third criteria. Considering this last parameter those well explored targets like PfATP4 and DHFR were deprioritized.

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Figure 5. Preferred targets space based on Validation&Tractability and MoA&Therapeutic profile. As we have previously discussed, this is a multiparameter exercise and there are different approaches that could be considered to select the most promising antimalarial targets. At GSK, we have prioritised validation and MoA but other selections are also providing interesting results. For instance, still considering validation as a main parameter along with Novelty&Competitor landscape provides a different and attractive picture. Figure 6 shows a selection of targets covering a wide range of validation status and high scores in the Novelty&Competitor landscape. Those in the upper right corner are very promising and some have not been previously identified in our first selection, such as NMT and FT. In the bottomright corner, selected targets representing excellent starting points as they would

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provide novel and differential clinical candidates have been identified. These have valuable profiles in terms of MoA and novelty however, they require some degree of biological validation work. Some examples are dUTPase, DHFR in its TS, PDEs or ERAD pathway.

Figure 6. Selection of targets with high Validation&Tractability values as well as Novelty&Competitor Landscape. CONCLUSION In summary, we describe in this work a comprehensive exercise of categorization and prioritization of the malaria target space as a tool to aid in the selection of new malarial target-based programs with an assessed degree of confidence proportional to the score obtained. Our analysis has provided a set of 12 of the most promising targets to identify new drug discovery programs with the highest probabilities of success of providing new clinical candidates. This is not a finished

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process but a live exercise as every new potential target or new further data of existing proteins could be included, evaluated and compared in a quick and easy way. In addition, we consider this a very useful exercise that can be applicable to other therapeutic areas. SUPPORTING INFORMATION Table including the complete list of targets evaluated along with all parameters and corresponding scores. Different Spotfire visualizations of the scoring and prioritization exercise. AUTHOR INFORMATION Corresponding author: *E-mail: [email protected] ORCID Esther Fernandez 0000-0002-0507-8507 Author contributions: E.F., F.C., F.J.G., M.G.G.L., E.F., M.J.C., R.G, J.M. and P.C. designed and developed the work and contributed equally. E.F. and M.J.C. wrote the paper and supplementary material. Notes: Authors declare no competing financial interest. ACKNOWLEDGEMENTS

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Authors thank Hannah Davies for her careful reading and editing of the manuscript as well as for the insightful comments and suggestions. ABBREVIATIONS ACT, Artemisinin Combination Therapies; FDA, Food and Drug Administration; GSK, GlaxoSmithKline; HTS, high throughput screening; MMV, Medicines for Malaria Venture; MoA, mode of action; PATH, Program for Appropriate Technology in Health; TCP, target candidate profile; TFQ, Tafenoquine; WHO, World Health Organization; REFERENCES (1)

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