New Halogenated Compounds from Halimeda macroloba Seaweed with Potential Inhibitory Activity against Malaria

Malaria is one of the most important infectious diseases worldwide. The causative of the most severe forms of malaria, Plasmodium falciparum, has developed resistances against all the available antimalarial drugs. In the present study, the phytochemical investigation of the green seaweed Halimeda macroloba has afforded two new compounds 1–2, along with 4 known ones 3–6. The structures of the compounds had been confirmed using 1& 2D-NMR and HRESIMS analyses. Extensive machine-learning-supported virtual-screening suggested cytochrome-C enzyme as a potential target for compound 2. Docking, absolute-binding-free-energy (ΔGbinding) and molecular-dynamics-simulation (MDS) of compound 2 revealed the strong binding interaction of this compound with cytochrome-C. In vitro testing for crude extract and isolated compounds revealed the potential in vitro inhibitory activity of both extract and compound 2 against P. falciparum. The crude extract was able to inhibit the parasite growth with an IC50 value of 1.8 ± 0.35 µg/mL. Compound 2 also showed good inhibitory activity with an IC50 value of 3.2 ± 0.23 µg/mL. Meanwhile, compound 6 showed moderate inhibitory activity with an IC50 value of 19.3 ± 0.51 µg/mL. Accordingly, the scaffold of compound 2 can be considered as a good lead compound for the future development of new antimalarial agents.


Introduction
Infectious diseases impose a significant burden on global public health and economic stability [1]. Malaria is a potentially life-threatening parasitic disease caused by Plasmodium protozoa and accounting for approximately 229 million cases and 409,000 fatalities in 2019 [2]. Currently, two antimalarial drugs are used to control infection: artemisinin, obtained from Artemisia annua L., and quinine, obtained from Cinchona sp. [2]. The emergence of resistance on the part of mosquitoes to these antimalarial drugs, the weak development of new antimalarial drugs, the logistical problems of these drugs in poor malaria-endemic countries, and the lack of efficient and safe vaccines might increase the complications of a diversity of secondary metabolites which are still not fully explored, with few reported compounds which proved activity against human, fish, and shrimp pathogenic bacteria [21]. Halimeda macroloba generally grows in complex environmental conditions (relatively high salinity of seawater, high heavy metal content, and much susceptibility to surrounding organisms) [21]. This green seaweed proved antioxidant, antibacterial, and cytotoxic efficacies but has never been investigated against malaria, while other related species such as H. gracilis were [22]. In silico techniques including machine learning and artificial intelligence have significantly advanced during the last 15 years, to the point where they have become an integrated tool in the discovery and development of new therapeutics. These techniques have also facilitated the investigation of natural crude extracts to find out the potential bioactive chemical entity's complex matrices [3,23].
Consequently, we aimed in the present work to explore the phytochemical profile of the green seaweed Halimeda macroloba and test its possible anti-plasmodial potential via virtual screening and physics-based molecular simulation.
Halimeda macroloba is a widespread green seaweed in wide marine habitats which is always associated with coral reefs and therefore contains high amounts of calcium carbonate, causing it to be classified as a calcified or calcareous algae [20]. Halimeda attains a diversity of secondary metabolites which are still not fully explored, with few reported compounds which proved activity against human, fish, and shrimp pathogenic bacteria [21]. Halimeda macroloba generally grows in complex environmental conditions (relatively high salinity of seawater, high heavy metal content, and much susceptibility to surrounding organisms) [21]. This green seaweed proved antioxidant, antibacterial, and cytotoxic efficacies but has never been investigated against malaria, while other related species such as H. gracilis were [22]. In silico techniques including machine learning and artificial intelligence have significantly advanced during the last 15 years, to the point where they have become an integrated tool in the discovery and development of new therapeutics. These techniques have also facilitated the investigation of natural crude extracts to find out the potential bioactive chemical entity's complex matrices [3,23].
Consequently, we aimed in the present work to explore the phytochemical profile of the green seaweed Halimeda macroloba and test its possible anti-plasmodial potential via virtual screening and physics-based molecular simulation.

Predicting Possible Biological Activity
In order to predict the probable biological activity of the isolated compounds, we subjected their modeled structures to a machine learning-based virtual screening platform called Prediction of Activity Spectra of Substances (PASS; http://www.way2drug. com/passonline/products.php, accessed on 16 August 2022). This platform utilizes a pharmacophore-based screening algorithm to score the biological activities of query struc- ture. Possible active score (Pa) > 0.5 indicates high probability of being active in the corresponding biological activity category [30]. After submitting all structures of the isolated compounds, compound 2 showed an interesting Pa score (0.892) for the cytochrome-C reductase inhibitor. This enzyme is involved in many essential biological processes in many eukaryotes, particularly in malaria [31,32]. Accordingly, this preliminary in silico screening directs our attention to test both the crude extract of H. macrolaba and the isolated compounds against P. falciparum in vitro. The results indicated that the extract inhibits the replication of P. falciparum in a dose-dependent manner with an IC 50 value of 1.8 ± 0.35 µg/mL. Moreover, compound 2 also showed good inhibitory activity with an IC 50 value of 3.2 ± 0.23 µg/mL, while compound 6 showed moderate inhibitory activity with an IC 50 value of 19.3 ± 0.51 µg/mL (Table 3).

Binding Mode Analysis and Absolute Binding Free Energy Calculation
According to the in vitro antimalarial inhibitory activity results, compound 2 is a potential antimalarial agent that probably targets and inhibits the parasite's cytochrome-C reductase.
To study the binding mode of compound 2 with cytochrome-C reductase, the modeled structure of this compound was docked into the atovaquone-binding site of cytochrome bc1 reductase (PDB code: 4PD4; atovaquone is a quinone-based antimalarial drug) [33]. The resulting binding poses (10 poses) were almost identical with docking poses ranging from −10.83 to −9.94 kcal/mol (Table S1). Subsequently, these poses were subjected to moleculardynamics simulation-based absolute binding free energy determination (∆G binding ) to assess the pose with the highest affinity toward the enzyme's binding site using the free energy perturbation method (FEP) [34]. The second binding pose, with a docking score of −10.52 kcal/mol, was the best in terms of affinity to the binding site, where it attained the lowest ∆G binding value of −8.33 kcal/mol. Regarding the co-crystalized inhibitor atovaquone, its modeled structure was re-docked into the enzyme active site, and similarly to compound 2, ten poses for the docked structure were generated with docking scores ranging from −9.76 to −9.23 kcal/mol (Table S1). The ∆G binding of these generated poses was also determined, where the first pose got the lowest value (−14.46 kcal/mol). The calculated RMSD of this pose with co-crystalized inhibitor atovaquone was 1.17 Å.
From the previous findings we can conclude that compound 2 has a comparable affinity with the co-crystalized ligand toward cytochrome-C reductase. Additionally, its lower affinity is comparable to the co-crystalized inhibitor, which might be attributed to its higher flexibility (i.e., higher number of rotatable bonds, 22 vs. 2 for atovaquone).
To study the dynamic binding mode of compound 2 and atovaquone inside the enzyme's active site, their binding poses in terms of ∆G binding were subjected to 50 ns long MDS. As shown in Figure 3, both structures achieved good binding stability over the course of simulation; however, atovaquone was more stable with an average RMSD of 1.34 Å (the average RMSD of compound 2 was 3.23 Å). The extracted top-populated binding poses of both structures revealed that both their binding and stability inside the binding pocket were achieved primarily via hydrophobic interactions. Atovaquone established hydrophobic interactions mainly with PHE-129, ILE-269, LEU-275, PHE-278, and TYR-279. Regarding compound 2, its structure was larger, more flexible, and richer in hydrophobic hydrocarbon moieties and attained two hydrophobic iodine atoms. Hence, it was able to establish more hydrophobic interactions inside the binding pocket, e.g., ILE-125, PHE-129, VAL-146, ILE-269, LEU-275, TYR-279, and LEU-282, moreover establishing a prominent single H-bond with TYR-279. Taken together, compound 2 can be considered a good scaffold for the future development of new antimalarial agents targeting cytochrome-C. However, this scaffold (i.e., compound 2) is not a drug-like molecule according to Lipinski's and Veber's rules of drug-likeness (Molecular weight > 500, LogP > 4.15, and the number of rotatable bonds > 10). The removal of one of the two long aliphatic sidechains can significantly improve the drugability of this scaffold. Accordingly, in our next stage of investigating this probable antimalarial molecule, its biological activity will be fully characterized and its essential structural features will be identified so that its structure can be modified synthetically to a drug-like molecule. Figure 3, both structures achieved good binding stability over the course of simulation; however, atovaquone was more stable with an average RMSD of 1.34 Å (the average RMSD of compound 2 was 3.23 Å). The extracted top-populated binding poses of both structures revealed that both their binding and stability inside the binding pocket were achieved primarily via hydrophobic interactions. Atovaquone established hydrophobic interactions mainly with PHE-129, ILE-269, LEU-275, PHE-278, and TYR-279. Regarding compound 2, its structure was larger, more flexible, and richer in hydrophobic hydrocarbon moieties and attained two hydrophobic iodine atoms. Hence, it was able to establish more hydrophobic interactions inside the binding pocket, e.g., ILE-125, PHE-129, VAL-146, ILE-269, LEU-275, TYR-279, and LEU-282, moreover establishing a prominent single H-bond with TYR-279. Taken together, compound 2 can be considered a good scaffold for the future development of new antimalarial agents targeting cytochrome-C. However, this scaffold (i. e., compound 2) is not a drug-like molecule according to Lipinski's and Veber's rules of drug-likeness (Molecular weight > 500, LogP > 4.15, and the number of rotatable bonds > 10). The removal of one of the two long aliphatic sidechains can significantly improve the drugability of this scaffold. Accordingly, in our next stage of investigating this probable antimalarial molecule, its biological activity will be fully characterized and its essential structural features will be identified so that its structure can be modified synthetically to a drug-like molecule. To the best of our knowledge, this is the first study investigating the phytochemical environment of H. macrolaba with a focus on its anti-plasmodium efficacy. The phytochemical analyses led to the identification of six compounds, with the predominance of aliphatic hydrocarbon moieties as well as strong antimalarial activity (IC50 1.8 ± 0.354 µg/mL). Since bioactive extracts are categorized to be potent as antimalarials when their IC50 values are less than 10 µg/mL, H. macrolaba extract can be considered as a potential source of potent antimalarial agents [35]. Interestingly, a previous machine-learning To the best of our knowledge, this is the first study investigating the phytochemical environment of H. macrolaba with a focus on its anti-plasmodium efficacy. The phytochemical analyses led to the identification of six compounds, with the predominance of aliphatic hydrocarbon moieties as well as strong antimalarial activity (IC 50 1.8 ± 0.354 µg/mL). Since bioactive extracts are categorized to be potent as antimalarials when their IC 50 values are less than 10 µg/mL, H. macrolaba extract can be considered as a potential source of potent antimalarial agents [35]. Interestingly, a previous machine-learning study reported that the most persuasive physicochemical factor for antimalarial drugs to penetrate red blood cells is protein binding. The less a drug is bound to protein, the more it is freely available to penetrate the red blood cell. Drugs with aromatic hydrocarbons and/or aliphatic hydrocarbons may have a higher amount of freely available drug in the plasma to penetrate the red blood cells, facilitating their pharmacodynamic activities [36]. That might explain why compound 2 [2,5-bis (6-iodo-10-methyltridecan-2-yl)-3,6-dimethylcyclohexa-2,5-diene-1,4-dione], with its high number of aliphatic hydrocarbons, attained the highest binding score toward cytochrome c reductase. Moreover, this compound attains a quinone moiety that strengthens the antimalarial activity, which was supported by the reports of many quinone-derived compounds with potent antimalarial efficacies [37]. In a previous study, physcion and emodin (aromatic quinone derivatives) proved strong antimalarial activities with IC 50 values of 0.9 and 1.9 µM, respectively [38]. Moreover, atovaquone is a well-known antimalarial quinone-based compound that is used in combination with proguanil (Malarone ® ) for the control of malaria infections worldwide [38]. Regarding compound 2, a new compound, this is the first report of a quinone-based aliphatic compound with potent antimalarial efficacy. Accordingly, and in addition to recent related published data, machine learning could be a powerful approach to be widely used in various scientific fields for finding valuable information from data. The aims of a machine-learning model progression can be employed to build a robust predictive model, especially as most antimalarial drugs are still orphan [36] and data about their safety are limited. More importantly, the target prediction software has become an integral part of the drug discovery platform, which reduces the time and effort required for screening huge libraries of chemical compounds to find out available drug candidates. Such in silico tools could be employed in drug discovery from natural sources, with the ability to prioritize possibly active metabolites in a natural extract; hence, isolation and identification efforts will be directed toward top-scoring candidates.

Seaweed Samples Collection and Identification
Specimens of the green seaweed Halimeda macroloba were collected during May 2021 from the littoral zone of shorelines in Savage City on the Red Sea coast, Egypt. The collected seaweed samples were washed well with seawater, then with tap water, and finally with distilled water to remove any impurities, sand particles, and salts on their surfaces. The samples were kept in sterile clean plastic bottles and transported chilled in an ice box to the laboratory. The specimens were kindly identified according to standard taxonomic keys, and a voucher specimen (2021-BuPD 82) was deposited at the Department of Pharmacognosy, Faculty of Pharmacy, Beni-Suef University, Egypt.

Spectral Analyses
Proton 1 H and Distortionless Enhancement by Polarization Transfer-Q (DEPT-Q) 13 C NMR spectra were recorded at 400 and 100 MHz, respectively. Tetramethylsilane (TMS) was used as an internal standard in CDCL 3 -d and CD 3 OD-d 4 , utilizing residual solvent peaks (δ H = 7.26; and δ C 77.2) and (δ H = 3.34; 4.78; and δ C 49.9) as references, respectively. Measurements were performed on a Bruker Advance III 400 MHz with BBFO Smart Probe and a Bruker 400 MHz EON Nitrogen-Free Magnet (Bruker AG, Billerica, MA, USA). Carbon multiplicities were determined using a DEPT-Q experiment. The ultraviolet radiation (UV) spectrum in methanol was obtained using a Shimadzu UV 2401PC spectrophotometer (Shimadzu Corporation-UV-2401PC/UV-2501PC, Kyoto, Japan). Infrared (IR) spectra were measured using a Jasco FTIR 300E infrared spectrophotometer. HRESIMS data were obtained using an Acquity Ultra Performance Liquid Chromatography system coupled with a Synapt G2 HDMS quadrupole time-of-flight hybrid mass spectrometer (Waters, Milford, MA, USA).

Extraction and Fractionation of Halimeda Macroloba
The Halimeda macroloba samples (0.25 kg) were collected and air-dried in the shade for one month, dried, then finely powdered using an OC-60B/60B grinding machine (60-120 mesh, Henan, Mainland China) [40,41]. The powder was extracted by maceration using 70% ethanol (5 L, 3×, seven days each) at room temperature and concentrated under vacuum at 45 • C using a rotary evaporator (Buchi Rotavapor R-300, Cole-Parmer, Vernon Hills, IL, USA) to afford 50 g crude extract [42,43]. The dry extract was suspended in 100 mL distilled water (H 2 O), and successively portioned with solvents of different polarities (n-Hex., DCM). The organic phase in each step was separately evaporated under reduced pressure to afford the corresponding fractions I (5.0 g) and II (25.0 g), respectively, while the remaining mother liquor was then concentrated down to give the aqueous fraction (20.0 g). All the resulting fractions were kept at 4 • C for biological and phytochemical investigations [44,45].

Antimalarial Assay
The anti-plasmodial effect of the seaweed extract on P. falciparum erythrocytic replication in vitro was investigated using the Malstat assay [3]. The details of this method can be found in the supplementary file.

Biological Activity Prediction
Prediction of the probable biological activities of the isolated compounds was carried out using the (www.way2drug.com, accessed on 16 August 2022) [46]. The full details of this virtual screening method are provided in the supplementary file.

Molecular Docking, ∆g binding Calculation, and Molecular Dynamics Simulation
Docking, ∆G binding calculation, and molecular dynamics simulation experiments were carried out as previously described [47]. The detailed methods can be found in the supplementary file.

Conclusions
Phytochemical investigation of the green seaweed Halimeda macroloba led to the isolation of two new compounds and four previously reported ones. The compounds' structures were confirmed using 1D, 2D NMR, and HRESIMS analyses. The cytochrome-C enzyme, the critical target for the malaria parasite, was identified as a possible target for compound 2 after a machine learning-based virtual screening. The mode of interaction of compound 2 s scaffold inside the active site of cytochrome-C was putatively determined using comprehensive molecular docking and MDS experiments. In addition, compound 2 s affinity to the active site was calculated in terms of absolute binding free energy (∆G binding = −14.46 kcal/mol). In vitro against P. falciparum showed the potential inhibitory activity of compound 2 against the parasite. Accordingly, compound 2's scaffold can be considered as a promising lead compound for future antimalarial drug development.