Development of decision trees to discriminate HDAC8 inhibitors and non-inhibitors using recursive partitioning

Development of novel ALOX15 inhibitors combining dual machine learning filtering and fragment substitution optimisation approaches, molecular docking and dynamic simulation methods

The oxidation of unsaturated lipids, facilitated by the enzyme Arachidonic acid 15-lipoxygenase (ALOX15), is an essential element in the development of ferroptosis. This study combined a dual-score exclusion strategy with high-throughput virtual screening, naive Bayesian and recursive partitioning machine learning models, the already established ALOX15 inhibitor i472, and a docking-based fragment substitution optimisation approach to identify potential ALOX15 inhibitors, ultimately leading to the discovery of three FDA-approved drugs that demonstrate optimal inhibitory potential against ALOX15. Through fragment substitution-based optimisation, seven new inhibitor structures have been developed. To evaluate their practicality, ADMET predictions and molecular dynamics simulations were performed. In conclusion, the compounds found in this study provide a novel approach to combat conditions related to ferroptosis-related injury by inhibiting ALOX15.

Identification of structural fingerprints among natural inhibitors of HDAC1 to accelerate nature-inspired drug discovery in cancer epigenetics

Histone deacetylase 1 (HDAC1), a class I HDAC enzyme, is crucial for histone modification. Currently, it is emerged as one of the important biological targets for designing small molecule drugs through cancer epigenetics. Along with synthetic inhibitors different natural inhibitors are showing potential HDAC1 inhibitions. In order to gain insights into the relationship between the molecular structures of the natural inhibitors and HDAC1, different molecular modelling techniques (Bayesian classification, recursive partitioning, molecular docking and molecular dynamics simulations) have been applied on a dataset of 155 HDAC1 nature-inspired inhibitors with diverse scaffolds. The Bayesian study showed acceptable ROC values for both the training set and test sets. The Recursive partitioning study produced decision tree 1 with 6 leaves. Further, molecular docking study was processed for generating the protein ligand complex which identified some potential amino acid residues such as F205, H28, L271, P29, F150, Y204 for the binding interactions in case of natural inhibitors. Stability of these HDAC1-natutal inhibitors complexes has been also evaluated by molecular dynamics simulation study. The current modelling study is an attempt to get a deep insight into the different important structural fingerprints among different natural compounds modulating HDAC1 inhibition.Communicated by Ramaswamy H. Sarma.

Unveiling critical structural features for effective HDAC8 inhibition: a comprehensive study using quantitative read-across structure-activity relationship (q-RASAR) and pharmacophore modeling

Histone deacetylases constitute a group of enzymes that participate in several biological processes. Notably, inhibiting HDAC8 has become a therapeutic strategy for various diseases. The current inhibitors for HDAC8 lack selectivity and target multiple HDACs. Consequently, there is a growing recognition of the need for selective HDAC8 inhibitors to enhance the effectiveness of therapeutic interventions. In our current study, we have utilized a multi-faceted approach, including Quantitative Structure-Activity Relationship (QSAR) combined with Quantitative Read-Across Structure-Activity Relationship (q-RASAR) modeling, pharmacophore mapping, molecular docking, and molecular dynamics (MD) simulations. The developed q-RASAR model has a high statistical significance and predictive ability (Q2F1:0.778, Q2F2:0.775). The contributions of important descriptors are discussed in detail to gain insight into the crucial structural features in HDAC8 inhibition. The best pharmacophore hypothesis exhibits a high regression coefficient (0.969) and a low root mean square deviation (0.944), highlighting the importance of correctly orienting hydrogen bond acceptor (HBA), ring aromatic (RA), and zinc-binding group (ZBG) features in designing potent HDAC8 inhibitors. To confirm the results of q-RASAR and pharmacophore mapping, molecular docking analysis of the five potent compounds (44, 54, 82, 102, and 118) was performed to gain further insights into these structural features crucial for interaction with the HDAC8 enzyme. Lastly, MD simulation studies of the most active compound (54, mapped correctly with the pharmacophore hypothesis) and the least active compound (34, mapped poorly with the pharmacophore hypothesis) were carried out to validate the observations of the studies above. This study not only refines our understanding of essential structural features for HDAC8 inhibition but also provides a robust framework for the rational design of novel selective HDAC8 inhibitors which may offer insights to medicinal chemists and researchers engaged in the development of HDAC8-targeted therapeutics.

Exploring molecular fingerprints of different drugs having bile interaction: a stepping stone towards better drug delivery

Bile acids are amphiphilic substances produced naturally in humans. In the context of drug delivery and dosage form design, it is critical to understand whether a drug interacts with bile inside the gastrointestinal (GI) tract or not. This study focuses on the identification of structural fingerprints/features important for bile interaction. Molecular modelling methods such as Bayesian classification and recursive partitioning (RP) studies are executed to find important fingerprints/features for the bile interaction. For the Bayesian classification study, the ROC score of 0.837 and 0.950 are found for the training set and the test set compounds, respectively. The fluorine-containing aliphatic/aromatic group, the branched chain of the alkyl group containing hydroxyl moiety and the phenothiazine ring etc. are identified as good fingerprints having a positive contribution towards bile interactions, whereas, the bad fingerprints such as free carboxylate group, purine, and pyrimidine ring etc. have a negative contribution towards bile interactions. The best tree (tree ID: 1) from the RP study classifies the bile interacting or non-interacting compounds with a ROC score of 0.941 for the training and 0.875 for the test set. Additionally, SARpy and QSAR-Co analyses are also been performed to classify compounds as bile interacting/non-interacting. Moreover, forty-six recently FDA-approved drugs have been screened by the developed SARpy and QSAR-Co models to assess their bile interaction properties. Overall, this attempt may facilitate the researchers to identify bile interacting/non-interacting molecules in a faster way and help in the design of formulations and target-specific drug development.

A fragment-based exploration of diverse MMP-9 inhibitors through classification-dependent structural assessment

Matrix metalloproteinases (MMPs) are belonging to the Zn2+-dependent metalloenzymes. These can degenerate the extracellular matrix (ECM) that is entailed with various biological processes. Among the MMP family members, MMP-9 is associated with several pathophysiological circumstances. Apart from wound healing, remodeling of bone, inflammatory mechanisms, and rheumatoid arthritis, MMP-9 has also significant roles in tumor invasion and metastasis. Therefore, MMP-9 has been in the spotlight of anticancer drug discovery programs for more than a decade. In this present study, classification-based QSAR techniques along with fragment-based data mining have been carried out on divergent MMP-9 inhibitors to point out the important structural attributes. This current study may be able to elucidate the importance of several pivotal molecular fragments such as sulfonamide, hydroxamate, i-butyl, and ethoxy functions for imparting potential MMP-9 inhibition. These observations are in correlation with the ligand-bound co-crystal structures of MMP-9. Therefore, these findings are beneficial for the design and discovery of effective MMP-9 inhibitors in the future.

In Silico molecular docking and dynamic analysis of natural compounds against major non-structural proteins of SARS-COV-2

COVID-19 has infected millions and significantly affected the global economy and healthcare systems. Despite continuous lockdowns, symptomatic management with currently available medications, and numerous vaccination drives, it is still far more difficult to control. Against COVID-19 infection, the pressure to develop vaccines and drugs has led to using some currently available medications like remdesivir, azithromycin, hydroxychloroquine and ritonavir. Understanding the importance and potential of harmless molecules to tackle SARS-COV-2, we designed the present study to identify potential natural phytocompounds. In the present study, we docked natural compounds and standard drugs against SARS-COV-2 proteins: papain-like protease, main protease and helicase. ADME/T and ProTox-II analyses were used to determine the toxicity of phytocompounds and drugs. The docking analysis revealed that podophyllotoxin gave the highest binding affinity scores of -8.1, -7.1 and -7.4 kcal/mol against PLpro, Mpro and helicase, respectively. Among the control drugs, doxycycline hydrochloride showed the highest binding affinity of -10.5, -8.4 and -8.8 kcal/mol against PLpro, Mpro and helicase. The results of this study revealed that podophyllotoxin and doxycycline hydrochloride could be promising inhibitors against SARS-Cov-2. Molecular dynamic simulations were executed for the best docked (PLpro-podophyllotoxin) complex, and the results displayed stable conformation and convergence. Energy plot results predicted a global minima average energy of -95 kcal/mol and indicated podophyllotoxin's role in stabilizing protein and making it compact and complex. FarPPI server used MM/GBSA approach to determine free binding affinity, and helicase-gallic acid complex showed the highest affinity, respectively. Therefore, it can be concluded that there is still a need for in vitro and in vivo studies to support further and validate these findings and validate these findings.Communicated by Ramaswamy H. Sarma.

Antichagasic evaluation, molecular docking and ADMET properties of the chalcone (2E)-3-(2-fluorophenyl)-1-(2-hydroxy- 3,4,6-trimethoxyphenyl)prop-2-en-1-one against Trypanosoma cruzi

Characterized as a neglected disease, Chagas disease is an infection that, in the current scenario, affects about 8 million people per year, with a higher incidence in underdeveloped countries, Chagas is responsible for physiological disabilities that result in impacts that are slightly reflected in world socioeconomic stability. Although treatments are based on drugs such as Benznidazole, the pathology lacks a continuous treatment method with low toxicological incidence. The present study estimates the anti-chagasic activity of the synthetic chalcone CPN2F based on the alignment between in vitro tests and structural classification in silico studies, molecular docking and ADMET studies. The in vitro tests showed a reduction in the protozoan metabolism in host cells (LLC-MK2). At the same time, the molecular docking models evaluate this growth inhibition through the synergistic effect associated with Benznida- zole against validated therapeutic target key stages (Cruzaine TcGAPDH and Trypanothione reductase) of the Trypanosoma cruzi development cycle. The in silico prediction results reveal an alignment between pharmacokinetic attributes, such as renal absorption and release, which allow the preparation of CPN2F as an antichagasic drug with a low incidence of organic toxicity.Communicated by Ramaswamy H. Sarma.

Potential Phytochemicals for Prevention of Familial Breast Cancer with BRCA Mutations

Breast cancer has remained a global challenge and the second leading cause of cancer mortality in women and family history. Hereditary factors are some of the major risk factors associated with breast cancer. Out of total breast cancer cases, 5-10% account only for familial breast cancer, and nearly 50% of all hereditary breast cancer are due to BRCA1/BRCA2 germline mutations. BRCA1/2 mutations play an important role not only in determining the clinical prognosis of breast cancer but also in the survival curves. Since this risk factor is known, a significant amount of the healthcare burden can be reduced by taking preventive measures among people with a known history of familial breast cancer. There is increasing evidence that phytochemicals of nutrients and supplements help in the prevention and cure of BRCA-related cancers by different mechanisms such as limiting DNA damage, altering estrogen metabolism, or upregulating expression of the normal BRCA allele, and ultimately enhancing DNA repair. This manuscript reviews different approaches used to identify potential phytochemicals to mitigate the risk of familial breast cancer with BRCA mutations. The findings of this review can be extended for the prevention and cure of any BRCAmutated cancer after proper experimental and clinical validation of the data.

Theaflavin 3-gallate inhibits the main protease (Mpro) of SARS-CoV-2 and reduces its count in vitro

The main protease (M^pro) of SARS-CoV-2 has been recognized as an attractive drug target because of its central role in viral replication. Our previous preliminary molecular docking studies showed that theaflavin 3-gallate (a natural bioactive molecule derived from theaflavin and found in high abundance in black tea) exhibited better docking scores than repurposed drugs (Atazanavir, Darunavir, Lopinavir). In this study, conventional and steered MD-simulations analyses revealed stronger interactions of theaflavin 3-gallate with the active site residues of M^pro than theaflavin and a standard molecule GC373 (a known inhibitor of M^pro and novel broad-spectrum anti-viral agent). Theaflavin 3-gallate inhibited M^pro protein of SARS-CoV-2 with an IC₅₀ value of 18.48 ± 1.29 μM. Treatment of SARS-CoV-2 (Indian/a3i clade/2020 isolate) with 200 μM of theaflavin 3-gallate in vitro using Vero cells and quantifying viral transcripts demonstrated reduction of viral count by 75% (viral particles reduced from Log10^6.7 to Log10^6.1). Overall, our findings suggest that theaflavin 3-gallate effectively targets the M^pro thus limiting the replication of the SARS-CoV-2 virus in vitro.

Molecular dynamics simulations reveal the inhibitory mechanism of Withanolide A against α-glucosidase and α-amylase

Diabetes mellitus (DM) is a global chronic disease characterized by hyperglycemia and insulin resistance. The unsavory severe gastrointestinal side-effects of synthetic drugs to regulate hyperglycemia have warranted the search for alternative treatments to inhibit the carbohydrate digestive enzymes (e.g. α-amylase and α-glucosidase). Certain phytochemicals recently captured the scientific community's attention as carbohydrate digestive enzyme inhibitors due to their low toxicity and high efficacy, specifically the Withanolides-loaded extract of Withania somnifera. That said, the present study evaluated in silico the efficacy of Withanolide A in targeting both α-amylase and α-glucosidase in comparison to the synthetic drug Acarbose. Protein-ligand interactions, binding affinity, and stability were characterized using pharmacological profiling, high-end molecular docking, and molecular-dynamic simulation. Withanolide A inhibited the activity of α-glucosidase and α-amylase better, exhibiting good pharmacokinetic properties, absorption, and metabolism. Also, Withanolide A was minimally toxic, with higher bioavailability. Interestingly, Withanolide A bonded well to the active site of α-amylase and α-glucosidase, yielding the lowest binding free energy of -82.144 ± 10.671 kcal/mol and -102.1043 ± 11.231 kcal/mol compared to the Acarbose-enzyme complexes (-63.220 ± 13.283 kcal/mol and -82.148 ± 10.671 kcal/mol). Hence, the findings supported the therapeutic potential of Withanolide A as α-amylase and α-glucosidase inhibitor for DM treatment.Communicated by Ramaswamy H. Sarma.

Toxicologic Concerns with Current Medical Nanoparticles

Nanotechnology is one of the scientific advances in technology. Nanoparticles (NPs) are small materials ranging from 1 to 100 nm. When the shape of the supplied nanoparticles changes, the physiological response of the cells can be very different. Several characteristics of NPs such as the composition, surface chemistry, surface charge, and shape are also important parameters affecting the toxicity of nanomaterials. This review covered specific topics that address the effects of NPs on nanomedicine. Furthermore, mechanisms of different types of nanomaterial-induced cytotoxicities were described. The distributions of different NPs in organs and their adverse effects were also emphasized. This review provides insight into the scientific community interested in nano(bio)technology, nanomedicine, and nanotoxicology. The content may also be of interest to a broad range of scientists.

3β-Acetoxy-21α-H-hop-22(29)ene, a novel multitargeted phytocompound against SARS-CoV-2: in silico screening

The present pandemic disease COVID-19 demands an urgent need for more efficient antiviral drugs against SARS-CoV-2. Computational drug designing and discovery enable us to explore ethnomedicinal plants as a source of various lead molecules that can be used against present and future pathogens. Adiantum latifolium Lam., a common fern, is resistant to pathogens mainly due to the presence of various phytochemicals having antimicrobial properties. In our previous study, 3β-acetoxy-21α-H-hop-22(29)ene, a terpenoid has been characterized from the methanol extract of leaves of A. latifolium. The manuscript evaluates the antiviral potency of the compound against SARS-CoV-2 through molecular docking method. Proteins essential for SARS-CoV-2 multiplication in host cells are the target sites. The study revealed strong binding affinity of the compound for all the ten proteins selected, including seven nonstructural proteins, two structural proteins and one receptor protein, with a binding energy of -4.67 to -8.76 kcal/mol. MDS and MMPBSA analysis of the best ranked complex further confirmed the results. The multitargeted compound can be considered as a natural lead molecule in drug designing against COVID-19, but requires wet-lab experimentation and clinical trials.Communicated by Ramaswamy H. Sarma.

Matairesinol, an active constituent of HC9 polyherbal formulation, exhibits HDAC8 inhibitory and anticancer activity

Histone deacetylase 8 (HDAC8) has emerged as a promising drug target for cancer therapeutics development. HDAC8 has been reported to regulate cancer cell proliferation, invasion and promote metastasis through modulation of cell cycle associated proteins. Of late, phytocompounds have been demonstrated to exhibit anticancer and anti-HDAC8 activity. Here, we have shown the HDAC8 inhibitory potential of an active phytocompound from HC9 (herbal composition-9), a polyherbal anticancer formulation based on the traditional Ayurvedic drug, Stanya Shodhan Kashaya. HC9 was recently reported to exhibit anticancer activity against breast cancer cells through induction of cell cycle arrest, decrease in migration and invasion as well as regulation of inflammation and chromatin modulators. In silico studies such as molecular docking, molecular dynamics (MD) simulation and binding free energy analyses showed greater binding energy values and interaction stability of MA with HDAC8 compared to other phytocompounds of HC9. Interestingly, in vitro validation confirmed the anti-HDAC8 activity of MA. Further, in vitro studies showed that MA significantly decreased the viability of breast and prostate cancer cell lines, thereby confirming its anticancer potential.

Discriminations of active from inactive HDAC8 inhibitors Part II: Bayesian classification study to find molecular fingerprints

In continuation of our earlier work (Doi: 10.1080/07391102.2019.1661876), a statistically validated and robust Bayesian model was developed on a large diverse set of HDAC8 inhibitors. The training set comprised of 676 small molecules and 293 compounds were considered as test set molecules. The findings of this analysis will help to explore some major directions regarding the HDAC8 inhibitor designing approach. Acrylamide (G1-G3, G9), N-substituted 2-phenylimidazole (G4-G8, G9, G12-G13, G16-G19), benzimidazole (G10-G11), piperidine substituted pyrrole (G13-G14) groups, alkyl/aryl amide (G15) and aryloxy carboxamide (G20) fingerprints were found to play a crucial role in HDAC8 inhibitory activity whereas -CH-N=CH- (B1, B4-B6, B14) motif, benzamide (B2-B3, B9-B13, B16-B17) groups and heptazepine (B7-B8, B15, B18-B20) group were found to influence negatively the HDAC8 inhibitory activity. The importance of such fingerprints was further validated by the HDAC8 enzyme and related inhibitor interactions at the receptor level. These results are in close agreement with those of our previous work that validate each other. Moreover, this comparative learning may enrich future endeavours regarding the designing strategy of HDAC8 inhibitors.

Identification of HDAC6 selective inhibitors: pharmacophore based virtual screening, molecular docking and molecular dynamics simulation

HDAC6 regulates the expression and activity of various tumor-related proteins, but currently there is no selective inhibitor targeting HDAC6 for clinical application. In order to discover novel HDAC6 inhibitors, virtual screening methods comprised of pharmacophore based virtual screening, molecular docking and molecular dynamics (MD) simulations were employed. 15 molecules were obtained after virtual screening. After in vitro bioassays, two of the hits showed inhibition activity against HDAC6, among which the inhibition activity of G1 to HDAC6 reached 81% at concentration of 20 μM. In addition, the inhibitory activity against HDAC1 and HDAC10 demonstrated that G1 and G10 were highly selective to HDAC6. The analysis of the binding modes of G1 and G10 provides a reference for further development of highly active HDAC6 inhibitors. Communicated by Ramaswamy H. Sarma.