Predictive immunoinformatics reveal promising safety and anti-onchocerciasis protective immune response profiles to vaccine candidates (Ov-RAL-2 and Ov-103) in anticipation of phase I clinical trials.

Onchocerciasis (river blindness) is a debilitating tropical disease that causes significant eye and skin damage, afflicting millions worldwide. As global efforts shift from disease management to elimination, vaccines have become crucial supplementary tools. The Onchocerciasis Vaccine for Africa (TOVA) Initiative was established in 2015, to advance at least one vaccine candidate initially targeting onchocerciasis in infants and children below 5 years of age, through Phase I human trials by 2025. Notably, Ov-RAL-2 and Ov-103 antigens have shown great promise during pre-clinical development, however, the overall success rate of vaccine candidates during clinical development remains relatively low due to certain adverse effects and immunogenic limitations. This study, thus, aimed at predicting the safety and immunogenicity of Ov-RAL-2 and Ov-103 potential onchocerciasis vaccine candidates prior to clinical trials. Advanced molecular simulation models and analytical immunoinformatics algorithms were applied to predict potential adverse side effects and efficacy of these antigens in humans. The analyses revealed that both Ov-RAL-2 and Ov-103 demonstrate favourable safety profiles as toxicogenic and allergenic epitopes were found to be absent within each antigen. Also, both antigens were predicted to harbour substantial numbers of a wide range of distinct epitopes (antibodies, cytokines, and T- Cell epitopes) associated with protective immunity against onchocerciasis. In agreement, virtual vaccination simulation forecasted heightened, but sustained levels of primary and secondary protective immune responses to both vaccine candidates over time. Ov-103 was predicted to be non-camouflageable, as it lacked epitopes identical to protein sequences in the human proteome. Indeed, both antigens were able to bind with high affinity and activate the innate immune TLR4 receptor, implying efficient immune recognition. These findings suggest that Ov-RAL-2 and Ov-103 can induce sufficient protective responses through diverse humoral and cellular mechanisms. Overall, our study provides additional layer of evidence for advancing the clinical development of both vaccine candidates against onchocerciasis.

A high-throughput, microplate reader-based method to monitor in vitro HIV latency reversal in the absence of flow cytometry.

J-Lat cells are derivatives of the Jurkat CD4+ T cell line that contain a non-infectious, inducible HIV provirus with a GFP tag. While these cells have substantially advanced our understanding of HIV latency, their use by many laboratories in low and middle-income countries is restricted by limited access to flow cytometry. To overcome this barrier, we describe a modified J-Lat assay using a standard microplate reader that detects HIV-GFP expression following treatment with latency-reversing agents (LRAs). We show that HIV reactivation by control LRAs like prostratin and romidepsin is readily detected with dose dependence and with significant correlation and sensitivity to standard flow cytometry. For example, 10 µM prostratin induced a 20.1 ± 3.3-fold increase in GFP fluorescence in the microplate reader assay, which corresponded to 64.2 ± 5.0% GFP-positive cells detected by flow cytometery. Similarly, 0.3 µM prostratin induced a 1.7 ± 1.2-fold increase compared to 8.7 ± 5.7% GFP-positive cells detected. Using this method, we screen 79 epigenetic modifiers and identify molibresib, quisinostat, and CUDC-101 as novel LRAs. This microplate reader-based method offers accessibility to researchers in resource-limited regions to work with J-Lat cells and more actively participate in global HIV cure research efforts. Highlights: J-Lat T-cell lines are important to HIV cure research but require flow cytometryWe describe a method to work with J-Lat cells using a standard microplate readerThis assay can detect control LRAs similar to flow cytometry and discover new LRAsThis assay allows low-resourced laboratories to contribute to HIV cure research.

In Vitro and In Silico Studies of the Biological Activities of Some Secondary Metabolites Belonging to Ficus sur Forssk (Moraceae): Towards Optimization of Wighteone Metabolite.

Based on ethnomedicinal and chemotaxonomic records of Ficus plants, Ficussur Forssk was studied in the search for bioactive compounds. Eleven known compounds including mixture α -amyrin acetate and ß -amyrin acetate (1 and 2), lupeol (3), 3ß-acetoxy-olean-12-en-11-one (4), lupenyl acetate (5), taraxastan-3,20-diol (6), 3'- (3-methylbut-2-enyl) biochanin A (7), derrone (8), quercetin (9), stigmasterol (10), and stigmasterol glycoside (11) were isolated from stem barks of Ficus sur Forssk. Their structures were obtained through analysis of spectroscopic data (1D and 2D NMR), mass spectrometry, and by comparison of these data with the literature. Nine isolated compounds (1-7, 10, 11) were tested as the active wighteone metabolite previously isolated from the roots of this plant against the human HepG2 hepatocellular carcinoma cells and a small panel of sensitive microbial strains for structure- activity relationship purpose. The compounds didn't show any activity. With the aim of understanding the impact of the structural difference between wighteone metabolite and its analogs, the former were cross-docked to evaluate their anticancer properties via the apoptosis pathway. Wighteone metabolite proved to be the best ligand confirming its previous bioassay result. Thus, the current study lays the framework for the further optimization of wighteone metabolite regarding its anticancer activity.

Identification of potential dipeptidyl peptidase IV inhibitors from the ConMedNP library by virtual screening, and molecular dynamics methods.

In this study, we screened novel dipeptidyl peptidase IV (DPP4) inhibitors from the ConMedNP library consisting of 3507 molecules. Interestingly, molecular docking, ADMET, and the anti-diabetic activity predictions suggest that three molecules, namely OTH_UD_XX06_1, GB19, and BMC_000104, have a high binding affinity toward DPP4. The molecular dynamics (MD) simulation results suggest that these hit molecules have a stable binding pose and occupy the binding pockets throughout the 200 ns simulation. The presence of intermolecular H-bonding between the ligands and DPP4 was observed throughout the simulation period. Thus, docking and MD results, predicted that the three compounds were the most potent DPP4 inhibitors that could putatively bind to the DPP4 active site via both conventional H-bonding and hydrophobic interactions. These results could aid the discovery of new drugs to treat type 2 diabetes.

Computational discovery of dual potential inhibitors of SARS-CoV-2 spike/ACE2 and Mpro: 3D-pharmacophore, docking-based virtual screening, quantum mechanics and molecular dynamics.

To find drugs against COVID-19, caused by the SARS-CoV-2, promising targets include the fusion of the viral spike with the human angiotensin-converting enzyme 2 (ACE2) as well as the main protease (Mpro). These proteins are responsible for viral entry and replication, respectively. We combined several state-of-the-art computational methods, including, protein-ligand interaction fingerprint, 3D-pharmacophores, molecular-docking, MM-GBSA, DFT, and MD simulations to explore two databases: ChEMBL and NANPDB to identify molecules that could both block spike/ACE2 fusion and inhibit Mpro. A total of 1,690,649 compounds from the two databases were screened using the pharmacophore model obtained from PLIF analysis. Five recent complexes of Mpro co-crystallized with different ligands were used to generate the pharmacophore model, allowing 4,829 compounds that passed this prefilter. These were then submitted to molecular docking against Mpro. The 5% top-ranked docking hits from docking result having scores < -8.32 kcal mol-1 were selected and then docked against spike/ACE2. Only four compounds: ChEMBL244958, ChEMBL266531, ChEMBL3680003, and 1-methoxy-3-indolymethyl glucosinolate (4) displayed binding energies < - 8.21 kcal mol-1 (for the native ligand) were considered as putative dual-target inhibitors. Furthermore, predictive ADMET, MM-GBSA and DFT/6-311G(d,p) were performed on these compounds and compared with those of well-known antivirals. DFT calculations showed that ChEMBL244958 and compound 4 had significant predicted reactivity values. Molecular dynamics simulations of the docked complexes were run for 100 ns and used to validate the stability docked poses and to confirm that these hits are putative dual binders of the spike/ACE2 and the Mpro.

A survey of isatin hybrids and their biological properties.

The emergence of diverse infections worldwide, which is a serious global threat to human existence, necessitates the urgent development of novel therapeutic candidates that can combat these diseases with efficacy. Molecular hybridization has been established as an efficient technique in designing bioactive molecules capable of fighting infections. Isatin, a core nucleus of an array of compounds with diverse biological properties can be modified at different positions leading to the creation of novel drug targets, is an active area of medicinal chemistry. This review containing published articles from 2005 to 2022 highlights isatin hybrids which have been synthesized and reported in the literature alongside a discussion on their biological properties. The enriched structure-activity relationship studies discussed provides insights for the rational design of novel isatin hybrids with tailored biological properties as effective therapeutic candidates inspired by nature.

Design, synthesis, and biochemical and computational screening of novel oxindole derivatives as inhibitors of Aurora A kinase and SARS-CoV-2 spike/host ACE2 interaction.

Isatin (indol-2,3-dione), a secondary metabolite of tryptophan, has been used as the core structure to design several compounds that have been tested and identified as potent inhibitors of apoptosis, potential antitumor agents, anticonvulsants, and antiviral agents. In this work, several analogs of isatin hybrids have been synthesized and characterized, and their activities were established as inhibitors of both Aurora A kinase and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike/host angiotensin-converting enzyme II (ACE2) interactions. Amongst the synthesized isatin hybrids, compounds 6a, 6f, 6g, and 6m exhibited Aurora A kinase inhibitory activities (with IC50 values < 5 µM), with GScore values of -7.9, -7.6, -8.2 and -7.7 kcal/mol, respectively. Compounds 6g and 6i showed activities in blocking SARS-CoV-2 spike/ACE2 binding (with IC50 values in the range < 30 µM), with GScore values of -6.4 and -6.6 kcal/mol, respectively. Compounds 6f, 6g, and 6i were both capable of inhibiting spike/ACE2 binding and blocking Aurora A kinase. Pharmacophore profiling indicated that compound 6g tightly fits Aurora A kinase and SARS-CoV-2 pharmacophores, while 6d fits SARS-CoV-2 and 6l fits Aurora A kinase pharmacophore. This work is a proof of concept that some existing cancer drugs may possess antiviral properties. Molecular modeling showed that the active compound for each protein adopted different binding modes, hence interacting with a different set of amino acid residues in the binding site. The weaker activities against spike/ACE2 could be explained by the small sizes of the ligands that fail to address the important interactions for binding to the ACE2 receptor site.

5-chloro-3-(2-(2,4-dinitrophenyl) hydrazono)indolin-2-one: synthesis, characterization, biochemical and computational screening against SARS-CoV-2.

Chemical prototypes with broad-spectrum antiviral activity are important toward developing new therapies that can act on both existing and emerging viruses. Binding of the SARS-CoV-2 spike protein to the host angiotensin-converting enzyme 2 (ACE2) receptor is required for cellular entry of SARS-CoV-2. Toward identifying new chemical leads that can disrupt this interaction, including in the presence of SARS-CoV-2 adaptive mutations found in variants like omicron that can circumvent vaccine, immune, and therapeutic antibody responses, we synthesized 5-chloro-3-(2-(2,4-dinitrophenyl)hydrazono)indolin-2-one (H2L) from the condensation reaction of 5-chloroisatin and 2,4-dinitrophenylhydrazine in good yield. H2L was characterised by elemental and spectral (IR, electronic, Mass) analyses. The NMR spectrum of H2L indicated a keto-enol tautomerism, with the keto form being more abundant in solution. H2L was found to selectively interfere with binding of the SARS-CoV-2 spike receptor-binding domain (RBD) to the host angiotensin-converting enzyme 2 receptor with a 50% inhibitory concentration (IC50) of 0.26 µM, compared to an unrelated PD-1/PD-L1 ligand-receptor-binding pair with an IC50 of 2.06 µM in vitro (Selectivity index = 7.9). Molecular docking studies revealed that the synthesized ligand preferentially binds within the ACE2 receptor-binding site in a region distinct from where spike mutations in SARS-CoV-2 variants occur. Consistent with these models, H2L was able to disrupt ACE2 interactions with the RBDs from beta, delta, lambda, and omicron variants with similar activities. These studies indicate that H2L-derived compounds are potential inhibitors of multiple SARS-CoV-2 variants, including those capable of circumventing vaccine and immune responses. Supplementary Information: The online version contains supplementary material available at 10.1007/s11696-023-03274-5.

Challenges in natural product-based drug discovery assisted with in silico-based methods.

The application of traditional medicine by humans for the treatment of ailments as well as improving the quality of life far outdates recorded history. To date, a significant percentage of humans, especially those living in developing/underprivileged communities still rely on traditional medicine for primary healthcare needs. In silico-based methods have been shown to play a pivotal role in modern pharmaceutical drug discovery processes. The application of these methods in identifying natural product (NP)-based hits has been successful. This is very much observed in many research set-ups that use rationally in silico-based methods in combination with experimental validation techniques. The combination has rendered the use of in silico-based approaches even more popular and successful in the investigation of NPs. However, identifying and proposing novel NP-based hits for experimental validation comes with several challenges such as the availability of compounds by suppliers, the huge task of separating pure compounds from complex mixtures, the quantity of samples available from the natural source to be tested, not to mention the potential ecological impact if the natural source is exhausted. Because most peer-reviewed publications are biased towards "positive results", these challenges are generally not discussed in publications. In this review, we highlight and discuss these challenges. The idea is to give interested scientists in this field of research an idea of what they can come across or should be expecting as well as prompting them on how to avoid or fix these issues.

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis.

BACKGROUND: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. METHODS: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. RESULTS AND CONCLUSION: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events.

Finding alternatives to 5-fluorouracil: application of ensemble-based virtual screening for drug repositioning against human thymidylate synthase.

5-fluorouracil and analogs are used in the treatment of many solid tumours. However, there are many cases of resistance and high toxicity associated with 5-fluorouracil chemotherapy. Repurposing FDA drugs against human thymidylate synthase revealed a number of FDA drugs that have a potential to be further developed for the treatment of various cancers for which 5-fluorouracil and analogs have been used for chemotherapy. Four FDA drugs prioritized for further validation included Erismodegib, Irinotecan, Conivaptan and Ergotamine. The role of water in mediating drug interactions and its contribution to the total binding energy was also shown. MM-PBSA calculations revealed that the binding affinity was the lowest for the hTS-Ergotamine complex (-66.702 ± 1.807 kJ/mol) suggesting moderate inhibition despite a large energetic contribution from van der Waal interactions (-190.889 ± 1.027 kJ/mol).Communicated by Ramaswamy H. Sarma.

Fragment-based virtual screening discovers potential new Plasmodium PI4KIIIß ligands.

Type III beta phosphatidylinositol 4-kinase (PI4KIIIß) is the only clinically validated drug target in Plasmodium kinases and therefore a critical target in developing novel drugs for malaria. Current PI4KIIIß inhibitors have solubility and off-target problems. Here we set out to identify new Plasmodium PI4K ligands that could serve as leads for the development of new antimalarial drugs by building a PPI4K homology model since there was no available three-dimensional structure of PfPI4K and virtually screened a small library of ~ 22 000 fragments against it. Sixteen compounds from the fragment-based virtual screening (FBVS) were selected based on ≤ - 9.0 kcal/mol binding free energy cut-off value. These were subjected to similarity and sub-structure searching after they had passed PAINS screening and the obtained derivatives showed improved binding affinity for PfPI4K (- 10.00 to - 13.80 kcal/mol). Moreover, binding hypothesis of the top-scoring compound (31) was confirmed in a 100 ns molecular dynamics simulation and its binding pose retrieved after the system had converged at about 10 ns into the evolution was described to lay foundation for a rationale chemical-modification to optimize binding to PfPI4K. Overall, compound 31 appears to be a viable starting point for the development of PPI4K inhibitors with antimalarial activity.

Natural Products as Potential Lead Compounds for Drug Discovery Against SARS-CoV-2.

For the past 2 years, the coronavirus responsible for the COVID-19 infection has become a world pandemic, ruining the lives and economies of several nations in the world. This has scaled up research on the virus and the resulting infection with the goal of developing new vaccines and therapies. Natural products are known to be a rich source of lead compounds for drug discovery, including against infectious diseases caused by microbes (viruses, bacteria and fungi). In this review article, we conducted a literature survey aimed at identifying natural products with inhibitory concentrations against the coronaviruses or their target proteins, which lie below 10 µM. This led to the identification of 42 compounds belonging to the alkaloid, flavonoid, terpenoid, phenolic, xanthone and saponin classes. The cut off concentration of 10 µM was to limit the study to the most potent chemical entities, which could be developed into therapies against the viral infection to make a contribution towards limiting the spread of the disease.

Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop.

We report the major conclusions of the online open-access workshop "Computational Applications in Secondary Metabolite Discovery (CAiSMD)" that took place from 08 to 10 March 2021. Invited speakers from academia and industry and about 200 registered participants from five continents (Africa, Asia, Europe, South America, and North America) took part in the workshop. The workshop highlighted the potential applications of computational methodologies in the search for secondary metabolites (SMs) or natural products (NPs) as potential drugs and drug leads. During 3 days, the participants of this online workshop received an overview of modern computer-based approaches for exploring NP discovery in the "omics" age. The invited experts gave keynote lectures, trained participants in hands-on sessions, and held round table discussions. This was followed by oral presentations with much interaction between the speakers and the audience. Selected applicants (early-career scientists) were offered the opportunity to give oral presentations (15 min) and present posters in the form of flash presentations (5 min) upon submission of an abstract. The final program available on the workshop website ( https://caismd.indiayouth.info/ ) comprised of 4 keynote lectures (KLs), 12 oral presentations (OPs), 2 round table discussions (RTDs), and 5 hands-on sessions (HSs). This meeting report also references internet resources for computational biology in the area of secondary metabolites that are of use outside of the workshop areas and will constitute a long-term valuable source for the community. The workshop concluded with an online survey form to be completed by speakers and participants for the goal of improving any subsequent editions.

Phytochemical and Ethnopharmacological Perspectives of Ehretia laevis.

Ehretia laevis Roxb. (Boraginaceae) has been extensively used as a traditional remedy for the treatment of a diverse range of ailments related to the respiratory system, the gastrointestinal tract, the reproductive system, and against several infections. This review critically assesses and documents, for the first time, the fragmented information on E. laevis, including its botanical description, folklore uses, bioactive phyto metabolites and pharmacological activities. The goal is to explore this plant therapeutically. Ethnomedicinal surveys reveal that E. laevis has been used by tribal communities in Asian countries for the treatment of various disorders. Quantitative and qualitative phytochemical investigations of E. laevis showed the presence of important phytoconstituents such as pentacyclic triterpenoids, phenolic acids, flavonoids, fatty acids, steroids, alkaloids, aliphatic alcohols, hydrocarbons, amino acids, carbohydrates, vitamins and minerals. Fresh plant parts, crude extracts, fractions and isolated compounds have been reported to exhibit broad spectrum of therapeutic activities viz., antioxidant, antiarthritic, antidiabetic, anti-inflammatory, antiulcer, antidiarrheal, antidysenteric, wound healing and anti-infective activities. E. laevis is shown to be an excellent potential source of drugs for the mitigation of jaundice, asthma, dysentery, ulcers, diarrhea, ringworm, eczema, diabetes, fissure, syphilis, cuts and wounds, inflammation, liver problems, venereal and infectious disorders. Although few investigations authenticated its traditional uses but employed uncharacterized crude extracts of the plant, the major concerns raised are reproducibility of therapeutic efficacy and safety of plant material. The outcomes of limited pharmacological screening and reported bioactive compounds of E. laevis suggest that there is an urgent need for in-depth pharmacological investigations of the plant.

A computational multi-targeting approach for drug repositioning for psoriasis treatment.

BACKGROUND: Psoriasis is an autoimmune inflammatory skin disease that affects 0.5-3% of the world's population and current treatment options are posed with limitations. The reduced risk of failure in clinical trials for repositioned drug candidates and the time and cost-effectiveness has popularized drug reposition and computational methods in the drug research community. RESULTS: The current study attempts to reposition approved drugs for the treatment of psoriasis by docking about 2000 approved drug molecules against fifteen selected and validated anti-psoriatic targets. The docking results showed that a good number of the dataset interacted favorably with the targets as most of them had - 11.00 to - 10.00 kcal/mol binding free energies across the targets. The percentage of the dataset with binding affinity higher than the co-crystallized ligands ranged from 34.76% (JAK-3) to 0.73% (Rac-1). It was observed that 12 out of the 0.73% outperformed all the co-crystallized ligands across the 15 studied proteins. All the 12 drugs identified are currently indicated as either antiviral or anticancer drugs and are of purine and pyrimidine nuclei. This is not surprising given that there is similarity in the mechanism of the mentioned diseases. CONCLUSION: This study, therefore, suggests that; antiviral and anticancer drugs could have anti-psoriatic effects, and molecules with purine and pyrimidine structural architecture are likely templates to consider in developing anti-psoriatic agents.

The use of minimal topological differences to inspire the design of novel tetrahydroisoquinoline analogues with antimalarial activity.

A quantitative structure-activity relationship (QSAR) study was conducted using nineteen previously synthesized, and tested 1-aryl-6-hydroxy-1,2,3,4-tetrahydroisoquinolines with proven in vitro activities against Plasmodium falciparum. In order to computationally design and screen potent antimalarial agents, these compounds with known biological activity ranging from 0.697 to 35.978 µM were geometry optimized at the B3LYP/6-311 + G(d,p) level of theory, using the Gaussian 09W software. To calculate the topological differences, the series of the nineteen compounds was superimposed and a hypermolecule obtained with s ¯ = 17 and 20 vertices. Other molecular descriptors were considered in order to build a highly predictive QSAR model. These include the minimal topological differences (MTD), LogP, two dimensional polarity surface area (TDPSA), dipole moment (µ), chemical hardness (η), electrophilicity (ω), potential energy (Ep), electrostatic energy (Eele) and number of rotatable bonds (NRB). By using a training set composed of 15 randomly selected compounds from this series, several QSAR equations were derived. The QSAR equations obtained were then used to attempt to predict the IC50 values of 4 remaining compounds in a test (or validation) set. Ten analogues were proposed by a fragment search of a fragment library containing the pharmacophore model of the active compounds contained in the training set. The most active proposed analogue showed a predicted activity within the lower micromolar range.

Editorial to Special Issue-"Structure-Activity Relationships (SAR) of Natural Products".

The topic of structure-activity-relationships (SAR) has recently drawn a lot of attention, and there is increasing interest in natural products (NPs) as a "source of inspiration" for the discovery of new lead compounds [...].

StreptomeDB 3.0: an updated compendium of streptomycetes natural products.

Antimicrobial resistance is an emerging global health threat necessitating the rapid development of novel antimicrobials. Remarkably, the vast majority of currently available antibiotics are natural products (NPs) isolated from streptomycetes, soil-dwelling bacteria of the genus Streptomyces. However, there is still a huge reservoir of streptomycetes NPs which remains pharmaceutically untapped and a compendium thereof could serve as a source of inspiration for the rational design of novel antibiotics. Initially released in 2012, StreptomeDB (http://www.pharmbioinf.uni-freiburg.de/streptomedb) is the first and only public online database that enables the interactive phylogenetic exploration of streptomycetes and their isolated or mutasynthesized NPs. In this third release, there are substantial improvements over its forerunners, especially in terms of data content. For instance, about 2500 unique NPs were newly annotated through manual curation of about 1300 PubMed-indexed articles, published in the last five years since the second release. To increase interoperability, StreptomeDB entries were hyperlinked to several spectral, (bio)chemical and chemical vendor databases, and also to a genome-based NP prediction server. Moreover, predicted pharmacokinetic and toxicity profiles were added. Lastly, some recent real-world use cases of StreptomeDB are highlighted, to illustrate its applicability in life sciences.