Ligand-Based Virtual Screening and Molecular Docking Studies to Identify the Critical Chemical Features of Potent Cathepsin D Inhibitors

Computer-aided drug design for virtual-screening and active-predicting of main protease (Mpro) inhibitors against SARS-CoV-2

Introduction: SARS-CoV-2 is a novel coronavirus with highly contagious and has posed a significant threat to global public health. The main protease (Mpro) is a promising target for antiviral drugs against SARS-CoV-2. Methods: In this study, we have used pharmacophore-based drug design technology to identify potential compounds from drug databases as Mpro inhibitors. Results: The procedure involves pharmacophore modeling, validation, and pharmacophore-based virtual screening, which identifies 257 compounds with promising inhibitory activity. Discussion: Molecular docking and non-bonding interactions between the targeted protein Mpro and compounds showed that ENA482732 was the best compound. These results provided a theoretical foundation for future studies of Mpro inhibitors against SARS-CoV-2.

Computer-aided drug design for the pain-like protease (PLpro) inhibitors against SARS-CoV-2

A new coronavirus, known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a highly contagious virus and has caused a massive worldwide health crisis. While large-scale vaccination efforts are underway, the management of population health, economic impact and asof-yet unknown long-term effects on physical and mental health will be a key challenge for the next decade. The papain-like protease (PL^pro) of SARS-CoV-2 is a promising target for antiviral drugs. This report used pharmacophore-based drug design technology to identify potential compounds as PL^pro inhibitors against SARS-CoV-2. The optimal pharmacophore model was fully validated using different strategies and then was employed to virtually screen out 10 compounds with inhibitory. Molecular docking and non-bonding interactions between the targeted protein PL^pro and compounds showed that UKR1129266 was the best compound. These results provided a theoretical foundation for future studies of PL^pro inhibitors against SARS-CoV-2.

Potential of Pueraria tuberosa (Willd.) DC. to rescue cognitive decline associated with BACE1 protein of Alzheimer's disease on Drosophila model: An integrated molecular modeling and in vivo approach

The indispensable role of Beta-site amyloid precursor protein cleaving enzyme-1 (BACE1) in Amyloid beta (Aβ) plaques generation and Aβ-mediated synaptic dysfunctions makes it a crucial target for therapeutic intervention in Alzheimer's disease (AD). In order to find out the potential inhibitors of BACE1, the present study focused on five phytochemicals from Pueraria tuberosa, namely, daidzin, genistin, mangiferin, puerarin, and tuberosin. A molecular docking study showed that all five phytochemicals presented the strongest BACE1 inhibition. Integrated molecular dynamics simulations and free energy calculations demonstrated that all five natural compounds have stable and favorable energies causing strong binding with the pocket site of BACE1 on 50 ns. All these molecules also passed Lipinski's rule of five. To validate the molecular modeling based findings, we primarily targeted the cognitive decline associated with BACE1 expression in AD flies with P. tuberosa. Significant improvement in cognitive decline was observed in AD flies in different behavioral assays such as Larval crawling assay (16.38%), Larval light preference assay (26.39%), Climbing assay (32.97%), Cold sensitivity assay (43.6%), and Thermal sensitivity assay (44.42%). The present findings suggest that P. tuberosa may be considered as a promising dietary supplement that can significantly ameliorate cognitive decline caused by BACE1 in Alzheimer's disease (AD).

The Discovery of Novel BCR-ABL Tyrosine Kinase Inhibitors Using a Pharmacophore Modeling and Virtual Screening Approach

Chronic myelogenous leukemia (CML) typically results from a reciprocal translocation between chromosomes 9 and 22 to produce the bcr-abl oncogene that when translated, yields the p210 BCR-ABL protein in more than 90% of all CML patients. This protein has constitutive tyrosine kinase activity that activates numerous downstream pathways that ultimately produces uncontrolled myeloid proliferation. Although the use of the BCR-ABL tyrosine kinase inhibitors (TKIs), such as imatinib, nilotinib, dasatinib, bosutinib, and ponatinib have increased the overall survival of CML patients, their use is limited by drug resistance and severe adverse effects. Therefore, there is the need to develop novel compounds that can overcome these problems that limit the use of these drugs. Therefore, in this study, we sought to find novel compounds using Hypogen and Hiphip pharmacophore models based on the structures of clinically approved BCR-ABL TKIs. We also used optimal pharmacophore models such as three-dimensional queries to screen the ZINC database to search for potential BCR-ABL inhibitors. The hit compounds were further screened using Lipinski’s rule of five, ADMET and molecular docking, and the efficacy of the hit compounds was evaluated. Our in vitro results indicated that compound ZINC21710815 significantly inhibited the proliferation of K562, BaF3/WT, and BaF3/T315I leukemia cells by inducing cell cycle arrest. The compound ZINC21710815 decreased the expression of p-BCR-ABL, STAT5, and Crkl and produced apoptosis and autophagy. Our results suggest that ZINC21710815 may be a potential BCR-ABL inhibitor that should undergo in vivo evaluation.

Potential natural inhibitors of xanthine oxidase and HMG-CoA reductase in cholesterol regulation: in silico analysis

Background

Hypercholesterolemia has posed a serious threat of heart diseases and stroke worldwide. Xanthine oxidase (XO), the rate-limiting enzyme in uric acid biosynthesis, is regarded as the root of reactive oxygen species (ROS) that generate atherosclerosis and cholesterol crystals. β-Hydroxy β-methylglutaryl-coenzyme A reductase (HMGR) is a rate-limiting enzyme in cholesterol biosynthesis. Although some commercially available enzyme inhibiting drugs have effectively reduced cholesterol levels, most of them have failed to meet potential drug candidates’ requirements. Here, we have carried out an in-silico analysis of secondary metabolites that have already shown good inhibitory activity against XO and HMGR in a wet lab setup.

Methods

Out of 118 secondary metabolites reviewed, sixteen molecules inhibiting XO and HMGR were selected based on the IC₅₀ values reported in in vitro assays. Further, receptor-based virtual screening was carried out against secondary metabolites using GOLD Protein-Ligand Docking Software, combined with subsequent post-docking, to study the binding affinities of ligands to the enzymes. In-silico ADMET analysis was carried out to explore their pharmacokinetic properties, followed by toxicity prediction through ProTox-II.

Results

The molecular docking of amentoflavone (GOLD score 70.54, ∆G _calc. = − 10.4 Kcal/mol) and ganomycin I (GOLD score 59.61, ∆G _calc. = − 6.8 Kcal/mol) displayed that the drug has effectively bound at the competitive site of XO and HMGR, respectively. Besides, 6-paradol and selgin could be potential drug candidates inhibiting XO. Likewise, n-octadecanyl-O-α-D-glucopyranosyl (6′ → 1″)-O-α-D-glucopyranoside could be potential drug candidates to maintain serum cholesterol. In-silico ADMET analysis has shown that these sixteen metabolites were optimal within the categorical range compared to commercially available XO and HMGR inhibitors, respectively. Toxicity analysis through ProTox-II revealed that 6-gingerol, ganoleucoin K, and ganoleucoin Z are toxic for human use.

Conclusion

This computational analysis supports earlier experimental evidence towards the inhibition of XO and HMGR by natural products. Further study is necessary to explore the clinical efficacy of these secondary molecules, which might be alternatives for the treatment of hypercholesterolemia.

Structure-Based Scaffold Repurposing toward the Discovery of Novel Cholinesterase Inhibitors

Cholinesterases (ChE) are well-known drug targets for the treatment of Alzheimer's disease (AD). In continuation of work to develop novel cholinesterase inhibitors, we utilized a structure-based scaffold repurposing approach and discovered six novel ChE inhibitors from our recently developed DNA gyrase inhibitor library. Among the identified hits, two compounds (denoted 3 and 18) were found to be the most potent inhibitor of acetylcholinesterase (AChE, IC₅₀ = 6.10 ± 1.01 μM) and butyrylcholinesterase (BuChE, IC₅₀ = 5.50 ± 0.007 μM), respectively. Compound 3 was responsible for the formation of H-bond and π-π stacking interactions within the active site of AChE. In contrast, compound 18 was well fitted in the choline-binding pocket and catalytic site of BuChE. Results obtained from in vitro cytotoxicity assays and in silico derived physicochemical and absorption, distribution, metabolism, and excretion (ADME) properties indicate that repurposed scaffold 3 and 18 could be potential drug candidates for further development as novel ChE inhibitors.

Computational Simulations Identified Two Candidate Inhibitors of Cdk5/p25 to Abrogate Tau-associated Neurological Disorders

Deregulation of Cdk5 is a hallmark in neurodegenerative diseases and its complex with p25 forms Cdk5/p25, thereby causes severe neuropathological insults. Cdk5/p25 abnormally phosphorylates tau protein, and induces tau-associated neurofibrillary tangles in neurological disorders. Therefore, the pharmacological inhibition of Cdk5/p25 alleviates tau-associated neurological disorders. Herein, computational simulations probed two candidate inhibitors of Cdk5/p25. Structure-based pharmacophore investigated the essential complementary chemical features of ATP-binding site of Cdk5 in complex with roscovitine. Resultant pharmacophore harbored polar interactions with Cys83 and Asp86 residues and non-polar interactions with Ile10, Phe80, and Lys133 residues of Cdk5. The chemical space of selected pharmacophore was comprised of two hydrogen bond donors, one hydrogen bond acceptor, and three hydrophobic features. Decoy test validation of pharmacophore obtained highest Guner-Henry score (0.88) and enrichment factor score (7.23). The screening of natural product drug-like databases by validated pharmacophore retrieved 1126 compounds as candidate inhibitors of Cdk5/p25. The docking of candidate inhibitors filtered 10 molecules with docking score >80.00 and established polar and non-polar interactions with the ATP-binding site residues of Cdk5/p25. Finally, molecular dynamics simulation and binding free energy analyses identified two candidate inhibitors of Cdk5/p25. During 30 ns simulation, the candidate inhibitors established <3.0 Å root mean square deviation and stable hydrogen bond interactions with the ATP-binding site residues of Cdk5/p25. The final candidate inhibitors obtained lowest binding free energies of -122.18 kJ/mol and - 117.26 kJ/mol with Cdk5/p25. Overall, we recommend two natural product candidate inhibitors to target the pharmacological inhibition of Cdk5/p25 in tau-associated neurological disorders.

Smart, Innovative and Intelligent Technologies Used in Drug Designing

Smart and intelligent computational methods are essential nowadays for designing, manufacturing and optimizing new drugs. New and innovative computational tools and algorithms are consistently developed and applied for the development of novel therapeutic compounds in many research projects. Rapid developments in the architecture of computers have also provided complex calculations to be performed in a smart, intelligent and timely manner for desired quality outputs. Research groups worldwide are developing drug discovery platforms and innovative tools following smart manufacturing ideas using highly advanced biophysical, statistical and mathematical methods for accelerated discovery and analysis of smaller molecules. This chapter discusses novel innovative applications in drug discovery involving use of structure-based drug design which utilizes geometrical knowledge of the three-dimensional protein structures. It discusses statistical and physics based methods such as quantum mechanics and classical molecular dynamics which can also play a major role in improving the performance and in prediction of computational drug discovery. Lastly, the authors provide insights on recent developments in cloud computing with significant increase in smart and intelligent computational power thus allowing larger data sets to be analyzed simultaneously on multi processor cloud systems. Future directions for the research are outlined.

Cathepsin D inhibitors as potential therapeutics for breast cancer treatment: Molecular docking and bioevaluation against triple-negative and triple-positive breast cancers

The main aim of this study was to discover small molecule inhibitors against Cathepsin D (CatD) (EC.3.4.23.5), a clinically proven prognostic marker for breast cancer, and to explore the mechanisms by which CatD could be a useful therapeutic target for triple-positive and triple-negative breast cancers (TPBC & TNBC). The crystal structure of CatD at 2.5 Å resolution (PDB: 1LYB), which was complexed with Pepstatin A, was selected for computer-aided molecular modeling. The methods used in our study were pharmacophore modeling and molecular docking. Virtual screening was performed to identify small molecules from an in-house database and a large commercial chemical library. Cytotoxicity studies were performed on human normal cell line HEK293T and growth inhibition studies on breast adenocarcinoma cell lines, namely MCF-7, MDA-MB-231, SK-BR-3, and MDA-MB-468. Furthermore, RT-PCR analysis, in vitro enzyme assay, and cell cycle analysis ascertained the validity of the selected molecules. A set of 28 molecules was subjected to an in vitro fluorescence-based inhibitory activity assay, and among them six molecules exhibited >50 % inhibition at 25μM. These molecules also exhibited good growth inhibition against TPBC and TNBC cancer types. Among them, molecules 1 and 17 showed single-digit micromolar GI50 values against MCF-7 and MDA-MB-231 cell lines.

Inhibition of Paracoccidioides lutzii Pb01 isocitrate lyase by the natural compound argentilactone and its semi-synthetic derivatives

The dimorphic fungus Paracoccidioides spp. is responsible for paracoccidioidomycosis, the most prevalent systemic mycosis in Latin America, causing serious public health problems. Adequate treatment of mycotic infections is difficult, since fungi are eukaryotic organisms with a structure and metabolism similar to those of eukaryotic hosts. In this way, specific fungus targets have become important to search of new antifungal compound. The role of the glyoxylate cycle and its enzymes in microbial virulence has been reported in many fungal pathogens, including Paracoccidioides spp. Here, we show the action of argentilactone and its semi-synthetic derivative reduced argentilactone on recombinant and native isocitrate lyase from Paracoccidioides lutzii Pb01 (PbICL) in the presence of different carbon sources, acetate and glucose. Additionally, argentilactone and its semi-synthetic derivative reduced argentilactone exhibited relevant inhibitory activity against P. lutzii Pb01 yeast cells and dose-dependently influenced the transition from the mycelium to yeast phase. The other oxygenated derivatives tested, epoxy argentilactone and diol argentilactone-, did not show inhibitory action on the fungus. The results were supported by in silico experiments.

Bioinformatics opportunities for identification and study of medicinal plants

Plants have been used as a source of medicine since historic times and several commercially important drugs are of plant-based origin. The traditional approach towards discovery of plant-based drugs often times involves significant amount of time and expenditure. These labor-intensive approaches have struggled to keep pace with the rapid development of high-throughput technologies. In the era of high volume, high-throughput data generation across the biosciences, bioinformatics plays a crucial role. This has generally been the case in the context of drug designing and discovery. However, there has been limited attention to date to the potential application of bioinformatics approaches that can leverage plant-based knowledge. Here, we review bioinformatics studies that have contributed to medicinal plants research. In particular, we highlight areas in medicinal plant research where the application of bioinformatics methodologies may result in quicker and potentially cost-effective leads toward finding plant-based remedies.