Discovery of small molecules through pharmacophore modeling, docking and molecular dynamics simulation against Plasmodium vivax Vivapain-3 (VP-3)

Drug Development Strategies for Malaria: With the Hope for New Antimalarial Drug Discovery—An Update

Malaria continued to be a deadly situation for the people of tropical and subtropical countries. Although there has been a marked reduction in new cases as well as mortality and morbidity rates in the last two decades, the reporting of malaria caused 247 million cases and 619000 deaths worldwide in 2021, according to the WHO (2022). The development of drug resistance and declining efficacy against most of the antimalarial drugs/combination in current clinical practice is a big challenge for the scientific community, and in the absence of an effective vaccine, the problem becomes worse. Experts from various research organizations worldwide are continuously working hard to stop this disaster by employing several strategies for the development of new antimalarial drugs/combinations. The current review focuses on the history of antimalarial drug discovery and the advantages, loopholes, and opportunities associated with the common strategies being followed for antimalarial drug development.

Data mining and network analysis reveals C-X-C chemokine receptor type 5 is involved in the pathophysiology of age-related macular degeneration

Our previous studies found that the C-X-C motif chemokine receptor 5 (CXCR5) loss leads to retinal pigment epithelium (RPE) dysfunction and AMD pathogenesis. The current study aimed to characterize the G protein-coupled receptor (GPCR) structure of CXCR5 and analyze its interactions with AMD-related risk genes. The sequence alignments, homology model of CXCR5 and structural assessment analysis were performed. Data and text mining were then performed to identify AMD-related risk genes and their interaction with CXCR5 using statistical and mathematical algorithms. Sequence alignment and phylogenetic tree analysis revealed that human CXCR5 was highly similar (85.4839%) to the rabbit. The least similarity (33.871%) was found to be in zebrafish compared to the other species. The CXCR5 model structural assessment and secondary structure analysis exhibited an excellent model. Network analysis revealed that IL10, TNF, ICAM1, CXCL1, CXCL8, APP, TLR4, SELL, C3, IL17A and CCR2 were the most connected genes CXCR5. These findings suggest that CXCR5 signaling may regulate the biological function of RPE and modulate AMD pathophysiology via GPCR signaling and interacting with identified AMD risk genes. In summary, the data presented here provide novel and crucial insights into the molecular mechanisms of CXCR5 involvement in AMD.Communicated by Ramaswamy H. Sarma.

Structure- and ligand-based drug design methods for the modeling of antimalarial agents: a review of updates from 2012 onwards

Malaria still persists as one of the deadliest infectious disease having a huge morbidity and mortality affecting the higher population of the world. Structure and ligand-based drug design methods like molecular docking and MD simulations, pharmacophore modeling, QSAR and virtual screening are widely used to perceive the accordant correlation between the antimalarial activity and property of the compounds to design novel dominant and discriminant molecules. These modeling methods will speed-up antimalarial drug discovery, selection of better drug candidates for synthesis and to achieve potent and safer drugs. In this work, we have extensively reviewed the literature pertaining to the use and applications of various ligand and structure-based computational methods for the design of antimalarial agents. Different classes of molecules are discussed along with their target interactions pattern, which is responsible for antimalarial activity. Communicated by Ramaswamy H. Sarma.

Anti-Candida albicans Activity of Ononin and Other Secondary Metabolites from Platonia Insignis MART

Candida albicans is a human pathogen that is part of the healthy microbiome. However, it is often associated with opportunistic fungal infections. The treatment of these infections is challenging because prolonged exposure to antifungal drugs can culminate in fungal resistance during therapy, and there is a limited number of available drugs. Therefore, this study investigated the antifungal activity of ononin by in silico and in vitro assays, and in Tenebrio molitor as an alternative in vivo model of infection caused by C. albicans. Ononin is an isoflavone glycoside derived from formononetin that has various biological activities. According in silico evaluation, ononin showed the best electron affinity in molecular docking with CaCYP51, with a binding free energy of -10.89 kcal/mol, superior to that of the antifungal drugs fluconazole and posaconazole. The ononin + CaCYP51 complex formed hydrogen bonds with Tyr132, Ser378, Phe380, and Met508, as well as hydrophobic connections with Tyr118, Leu121, Phe126, Leu131, Ile304, and Leu309, and interactions with the heme group. Ononin exerted anti-Candida albicans activity, with MIC between 3.9 and 7.8 µg/mL, and inhibited young and mature biofilms, with a reduction in cell density and metabolic activity of 50 to 80%. The compound was not cytotoxic to sheep red blood cells at concentrations up to 1000 µg/mL. Larvae of the mealworm T. molitor were used as an alternative in vivo model of C. albicans infection. Ononin was able to prolong larval survival at concentrations of 0.5, 1, and 5 mg/kg, and was not toxic up to a concentration of 20 mg/kg. Moreover, ononin reduced the fungal charge in treated animals. In conclusion, our results suggest that ononin has anti-Candida albicans activity and is a potential candidate for the development of new therapeutic alternatives.

Identification of Potent and Selective JAK1 Lead Compounds Through Ligand-Based Drug Design Approaches

JAK1 plays a significant role in the intracellular signaling by interacting with cytokine receptors in different types of cells and is linked to the pathogenesis of various cancers and in the pathology of the immune system. In this study, ligand-based pharmacophore modeling combined with virtual screening and molecular docking methods was incorporated to identify the potent and selective lead compounds for JAK1. Initially, the ligand-based pharmacophore models were generated using a set of 52 JAK1 inhibitors named C-2 methyl/hydroxyethyl imidazopyrrolopyridines derivatives. Twenty-seven pharmacophore models with five and six pharmacophore features were generated and validated using potency and selectivity validation methods. During potency validation, the Guner-Henry score was calculated to check the accuracy of the generated models, whereas in selectivity validation, the pharmacophore models that are capable of identifying selective JAK1 inhibitors were evaluated. Based on the validation results, the best pharmacophore models ADHRRR, DDHRRR, DDRRR, DPRRR, DHRRR, ADRRR, DDHRR, and ADPRR were selected and taken for virtual screening against the Maybridge, Asinex, Chemdiv, Enamine, Lifechemicals, and Zinc database to identify the new molecules with novel scaffold that can bind to JAK1. A total of 4,265 hits were identified from screening and checked for acceptable drug-like properties. A total of 2,856 hits were selected after ADME predictions and taken for Glide molecular docking to assess the accurate binding modes of the lead candidates. Ninety molecules were shortlisted based on binding energy and H-bond interactions with the important residues of JAK1. The docking results were authenticated by calculating binding free energy for protein–ligand complexes using the MM-GBSA calculation and induced fit docking methods. Subsequently, the cross-docking approach was carried out to recognize the selective JAK1 lead compounds. Finally, top five lead compounds that were potent and selective against JAK1 were selected and validated using molecular dynamics simulation. Besides, the density functional theory study was also carried out for the selected leads. Through various computational studies, we observed good potency and selectivity of these lead compounds when compared with the drug ruxolitinib. Compounds such as T5923555 and T5923531 were found to be the best and can be further validated using in vitro and in vivo methods.

Inhibition of GSK_3β by Iridoid Glycosides of Snowberry (Symphoricarpos albus) Effective in the Treatment of Alzheimer's Disease Using Computational Drug Design Methods

The inhibition of glycogen synthase kinase-3β (GSK-3β) activity prevents tau hyperphosphorylation and binds it to the microtubule network. Therefore, a GSK-3β inhibitor may be a recommended drug for Alzheimer's treatment. In silico methods are currently considered as one of the fastest and most cost-effective available alternatives for drug/design discovery in the field of treatment. In this study, computational drug design was conducted to introduce compounds that play an effective role in inhibiting the GSK-3β enzyme by molecular docking and molecular dynamics simulation. The iridoid glycosides of the common snowberry (Symphoricarpos albus), including loganin, secologanin, and loganetin, are compounds that have an effect on improving memory and cognitive impairment and the results of which on Alzheimer's have been studied as well. In this study, in the molecular docking phase, loganin was considered a more potent inhibitor of this protein by establishing a hydrogen bond with the ATP-binding site of GSK-3β protein and the most negative binding energy to secologanin and loganetin. Moreover, by molecular dynamics simulation of these ligands and GSK-3β protein, all structures were found to be stable during the simulation. In addition, the protein structure represented no change and remained stable by binding ligands to GSK-3β protein. Furthermore, loganin and loganetin have higher binding free energy than secologanin; thus, these compounds could effectively bind to the active site of GSK-3β protein. Hence, loganin and loganetin as iridoid glycosides can be effective in Alzheimer's prevention and treatment, and thus, further in vitro and in vivo studies can focus on these iridoid glycosides as an alternative treatment.

Genome-Based Drug Target Identification in Human Pathogen Streptococcus gallolyticus

Streptococcus gallolysticus (Sg) is an opportunistic Gram-positive, non-motile bacterium, which causes infective endocarditis, an inflammation of the inner lining of the heart. As Sg has acquired resistance with the available antibiotics, therefore, there is a dire need to find new therapeutic targets and potent drugs to prevent and treat this disease. In the current study, an in silico approach is utilized to link genomic data of Sg species with its proteome to identify putative therapeutic targets. A total of 1,138 core proteins have been identified using pan genomic approach. Further, using subtractive proteomic analysis, a set of 18 proteins, essential for bacteria and non-homologous to host (human), is identified. Out of these 18 proteins, 12 cytoplasmic proteins were selected as potential drug targets. These selected proteins were subjected to molecular docking against drug-like compounds retrieved from ZINC database. Furthermore, the top docked compounds with lower binding energy were identified. In this work, we have identified novel drug and vaccine targets against Sg, of which some have already been reported and validated in other species. Owing to the experimental validation, we believe our methodology and result are significant contribution for drug/vaccine target identification against Sg-caused infective endocarditis.

Progress and challenges in the use of fluorescence-based flow cytometric assays for anti-malarial drug susceptibility tests

Drug-resistant Plasmodium is a frequent global threat in malaria eradication programmes, highlighting the need for new anti-malarial drugs and efficient detection of treatment failure. Plasmodium falciparum culture is essential in drug discovery and resistance surveillance. Microscopy of Giemsa-stained erythrocytes is common for determining anti-malarial effects on the intraerythrocytic development of cultured Plasmodium parasites. Giemsa-based microscopy use is conventional but laborious, and its accuracy depends largely on examiner skill. Given the availability of nucleic acid-binding fluorescent dyes and advances in flow cytometry, the use of various fluorochromes has been frequently attempted for the enumeration of parasitaemia and discrimination of P. falciparum growth in drug susceptibility assays. However, fluorochromes do not meet the requirements of being fast, simple, reliable and sensitive. Thus, this review revisits the utility of fluorochromes, notes previously reported hindrances, and highlights the challenges and opportunities for using fluorochromes in flow cytometer-based drug susceptibility tests. It aims to improve drug discovery and support a resistance surveillance system, an essential feature in combatting malaria.

Recent advances in quantitative structure-activity relationship models of antimalarial drugs

INTRODUCTION

Due to emerging resistance to the first-line artemisinin-based antimalarials and lack of efficient vaccines and limited chemotherapeutic alternatives, there is an urgent need to develop new antimalarial compounds. In this regard, quantitative structure-activity relationship (QSAR) modeling can provide essential information about required physicochemical properties and structural parameters of antimalarial drug candidates.

AREAS COVERED

The authors provide an overview of recent advances of QSAR models covering different classes of antimalarial compounds as well as molecular docking studies of compounds acting on different antimalarial targets reported in the last 5 years (2015-2019) to explore the mode of interactions between the molecules and the receptors. We have tried to cover most of the QSAR models of antimalarials (along with results from some other related computational methods) reported during 2015-2019.

EXPERT OPINION

Many QSAR reports for antimalarial compounds are based on small number of data points. This review infers that most of the present work deals with analog-based QSAR approach with a limited applicability domain (a very few cases with wide domain) whereas novel target-based computational approach is reported in very few cases, which leads to huge voids of computational work based on novel antimalarial targets.

Molecular modeling, docking and dynamic simulations of growth hormone receptor (GHR) of Labeo rohita

Growth hormones (GH) have diverse functions like growth promotion, metabolism, appetite, reproduction and social behavior in vertebrates, which is mediated through the growth hormone receptor (GHR). This work was aimed to analyze structural features, homology modeling and molecular docking of Labeo rohita GHR protein. A physicochemical characteristic, like molecular weight was 67.2 kDa and hydropathicity was 0.336. Protein modeling and structure confirmation of L. rohita GHR protein showed 92.7% residues are in the favored region. Selection of ligands and molecular docking shown Melengestrol and Riboflavin ligand showed uppermost binding energy values -7.8 and -7.3 kcal/mol. Molecular interactions describe conventional hydrogen bonding of Melengestrol was observed with VAL94, GLU97, GLU95, TRP57, PHE33, THR34, PRO35, ASP36, PRO37, ARG49, GLY292, LYS291, ILE290, ALA287, LYS289 residues. Riboflavin hydrogen bonds interaction was at PRO37, ASP36, PRO35, THR34, ARG49, SER144, VAL443, GLN442, PRO284, ASP294, ILE285, PRO286, SER408, ALA287, GLY292, LYS291, ILE290, PRO288, LYS287. Molecular dynamics simulation outcomes revealed that complex 2 (Riboflavin and GHR protein) is better than complex1 (Melengestrol and GHR protein). Overall, the results of the present work lead identification of novel molecules that may be agonistic of growth hormone receptor protein and can be used to surge growth in fish. Communicated by Ramaswamy H. Sarma.

Discovery of novel L-type voltage-gated calcium channel blockers and application for the prevention of inflammation and angiogenesis

BACKGROUND

The ways in which microglia activate and promote neovascularization (NV) are not fully understood. Recent in vivo evidence supports the theory that calcium is required for the transition of microglia from a surveillance state to an active one. The objectives of this study were to discover novel L-type voltage-gated channel (L-VGCC) blockers and investigate their application for the prevention of inflammation and angiogenesis.

METHODS

Pharmacophore-based computational modeling methods were used to screen for novel calcium channel blockers (CCBs) from the ZINC compound library. The effects of CCBs on calcium blockade, microglial pro-inflammatory activation, and cell toxicity were validated in BV-2 microglial cell and freshly isolated smooth muscle cell (SMC) cultures. Laser-induced choroidal neovascularization (NV) and the suture-induced inflammatory corneal NV models of angiogenesis were used for in vivo validation of the novel CCBs. CX3CR1^gfp/+ mice were used to examine the infiltration of GFP-labeled microglial cells.

RESULTS

We identified three compounds from the ZINC database (Zinc20267861, Zinc18204217, and Zinc33254827) as new blockers of L-type voltage-gated calcium channels (L-VGCC) using a structure-based pharmacophore approach. The effects of the three CCBs on Ca²⁺ influx into cells were verified in BV-2 microglial cells using Fura-2 fluorescent dye and in freshly isolated SMCs using the voltage-patch clamp. All three CCBs reduced microglial cell migration, activation stimulated by lipopolysaccharide (LPS), and reduced the expression of the inflammatory markers NF-κB (phospho-IκBα) and cyclooxygenase-2 (COX-2) as well as reactive oxygen species. Of the three compounds, we further examined the in vivo activity of Zinc20267861. Topical treatment with Zinc20267861 in a rat model of suture-induced inflammatory cornea neovascularization demonstrated efficacy of the compound in reducing monocyte infiltration and overall corneal NV response. Subconjunctival administration of the compound in the choroidal NV mouse model effectively prevented CNV and microglial infiltration.

CONCLUSIONS

Our findings suggest that the novel CCBs identified here are effective anti-inflammatory agents that can be further evaluated for treating NV disorders and can be potentially applied in the treatment of ocular inflammatory and pathological angiogenetic disorders.

Discovery of Small-Molecule Activators for Glucose-6-Phosphate Dehydrogenase (G6PD) Using Machine Learning Approaches

Glucose-6-Phosphate Dehydrogenase (G6PD) is a ubiquitous cytoplasmic enzyme converting glucose-6-phosphate into 6-phosphogluconate in the pentose phosphate pathway (PPP). The G6PD deficiency renders the inability to regenerate glutathione due to lack of Nicotine Adenosine Dinucleotide Phosphate (NADPH) and produces stress conditions that can cause oxidative injury to photoreceptors, retinal cells, and blood barrier function. In this study, we constructed pharmacophore-based models based on the complex of G6PD with compound AG1 (G6PD activator) followed by virtual screening. Fifty-three hit molecules were mapped with core pharmacophore features. We performed molecular descriptor calculation, clustering, and principal component analysis (PCA) to pharmacophore hit molecules and further applied statistical machine learning methods. Optimal performance of pharmacophore modeling and machine learning approaches classified the 53 hits as drug-like (18) and nondrug-like (35) compounds. The drug-like compounds further evaluated our established cheminformatics pipeline (molecular docking and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis). Finally, five lead molecules with different scaffolds were selected by binding energies and in silico ADMET properties. This study proposes that the combination of machine learning methods with traditional structure-based virtual screening can effectively strengthen the ability to find potential G6PD activators used for G6PD deficiency diseases. Moreover, these compounds can be considered as safe agents for further validation studies at the cell level, animal model, and even clinic setting.

Design and Selection of Novel C1s Inhibitors by In Silico and In Vitro Approaches

The complement system is associated with various diseases such as inflammation or auto-immune diseases. Complement-targeted drugs could provide novel therapeutic intervention against the above diseases. C1s, a serine protease, plays an important role in the CS and could be an attractive target since it blocks the system at an early stage of the complement cascade. Designing C1 inhibitors is particularly challenging since known inhibitors are restricted to a narrow bioactive chemical space in addition selectivity over other serine proteases is an important requirement. The typical architecture of a small molecule inhibitor of C1s contains an amidine (or guanidine) residue, however, the discovery of non-amidine inhibitors might have high value, particularly if novel chemotypes and/or compounds displaying improved selectivity are identified. We applied various virtual screening approaches to identify C1s focused libraries that lack the amidine/guanidine functionalities, then the in silico generated libraries were evaluated by in vitro biological assays. While 3D structure-based methods were not suitable for virtual screening of C1s inhibitors, and a 2D similarity search did not lead to novel chemotypes, pharmacophore model generation allowed us to identify two novel chemotypes with submicromolar activities. In three screening rounds we tested altogether 89 compounds and identified 20 hit compounds (<10 μM activities; overall hit rate: 22.5%). The highest activity determined was 12 nM (1,2,4-triazole), while for the newly identified chemotypes (1,3-benzoxazin-4-one and thieno[2,3-d][1,3]oxazin-4-one) it was 241 nM and 549 nM, respectively.