Computational platform Way2Drug: from the prediction of biological activity to drug repurposing

Investigating the potential of 6-substituted 3-formyl chromone derivatives as anti-diabetic agents using in silico methods

In exploring nature's potential in addressing diabetes-related conditions, this study investigates the therapeutic capabilities of 3-formyl chromone derivatives. Utilizing in silico methodologies, we focus on 6-substituted 3-formyl chromone derivatives (1-16) to assess their therapeutic potential in treating diabetes. The research examined the formyl group at the chromone's C-3 position. ADMET, biological activities, were conducted along with B3LYP calculations using 3 different basis sets. The analogues were analyzed based on their parent structure obtained from PubChem. The HOMO-LUMO gap confirmed the bioactive nature of the derivatives, NBO analysis was performed to understand the charge transfer. PASS prediction revealed that 3-formyl chromone derivatives are potent aldehyde oxidase inhibitors, insulin inhibitors, HIF1A expression inhibitors, and histidine kinase. Molecular docking studies indicated that the compounds had a strong binding affinity with proteins, including CAD, BHK, IDE, HIF-α, p53, COX, and Mpro of SARS-CoV2. 6-isopropyl-3-formyl chromone (4) displayed the highest affinity for IDE, with a binding energy of - 8.5 kcal mol-1. This result outperformed the affinity of the reference standard dapagliflozin (- 7.9 kcal mol-1) as well as two other compounds that target human IDE, namely vitexin (- 8.3 kcal mol-1) and myricetin (- 8.4 kcal mol-1). MD simulations were revealed RMSD value between 0.2 and 0.5 nm, indicating the strength of the protein-ligand complex at the active site.

Exploring the effectiveness of flavone derivatives for treating liver diseases: Utilizing DFT, molecular docking, and molecular dynamics techniques

In exploring nature's potential in addressing liver-related conditions, this study investigates the therapeutic capabilities of flavonoids. Utilizing in silico methodologies, we focus on flavone and its analogs (1-14) to assess their therapeutic potential in treating liver diseases. Molecular change calculations using density functional theory (DFT) were conducted on these compounds, accompanied by an evaluation of each analog's physiochemical and biochemical properties. The study further assesses these flavonoids' binding effectiveness and locations through molecular docking studies against six target proteins associated with human cancer. Tropoflavin and taxifolin served as reference drugs. The structurally modified flavone analogs (1-14) displayed a broad range of binding affinities, ranging from -7.0 to -9.4 kcal mol⁻¹, surpassing the reference drugs. Notably, flavonoid (7) exhibited significantly higher binding affinities with proteins Nrf2 (PDB:1 × 2 J) and DCK (PDB:1 × 2 J) (-9.4 and -8.1 kcal mol⁻¹) compared to tropoflavin (-9.3 and -8.0 kcal mol⁻¹) and taxifolin (-9.4 and -7.1 kcal mol⁻¹), respectively. Molecular dynamics (MD) simulations revealed that the docked complexes had a root mean square deviation (RMSD) value ranging from 0.05 to 0.2 nm and a root mean square fluctuation (RMSF) value between 0.35 and 1.3 nm during perturbation. The study concludes that 5,7-dihydroxyflavone (7) shows substantial promise as a potential therapeutic agent for liver-related conditions. However, further validation through in vitro and in vivo studies is necessary. Key insights from this study include:•Screening of flavanols and their derivatives to determine pharmacological and bioactive properties using ADMET, molinspiration, and pass prediction analysis.•Docking of shortlisted flavone derivatives with proteins having essential functions.•Analysis of the best protein-flavonoid docked complexes using molecular dynamics simulation to determine the flavonoid's efficiency and stability within a system.

Mechanism of Action of Isoflavone Derived from Soy-Based Tempeh as an Antioxidant and Breast Cancer Inhibitor via Potential Upregulation of miR-7-5p: A Multimodal Analysis Integrating Pharmacoinformatics and Cellular Studies

Breast cancer presents a significant global health challenge with rising incidence rates worldwide. Despite current efforts, it remains inadequately controlled. Functional foods, notably tempeh, have emerged as promising candidates for breast cancer prevention and treatment due to bioactive peptides and isoflavones exhibiting potential anticancer properties by serving as antioxidants, inducing apoptosis, and inhibiting cancer cell proliferation. This study integrates pharmacoinformatics and cellular investigations (i.e., a multifaceted approach) to elucidate the antioxidative and anti-breast cancer properties of tempeh-derived isoflavones. Methodologies encompass metabolomic profiling, in silico analysis, antioxidant assays, and in vitro experiments. Daidzein and genistein exhibited potential therapeutic options for breast cancer treatment and as antioxidant agents. In vitro studies also supported their efficacy against breast cancer and their ability to scavenge radicals, particularly in soy-based tempeh powder (SBT-P) and its isoflavone derivatives. Results have demonstrated a significant downregulation of breast cancer signaling proteins and increased expression of miR-7-5p, a microRNA with tumor-suppressive properties. Notably, the LD50 values of SBT-P and its derivatives on normal breast cell lines indicate their potential safety, with minimal cytotoxic effects on MCF-10A cells compared to control groups. The study underscores the favorable potential of SBT-P as a safe therapeutic option for breast cancer treatment, warranting further clinical exploration.

Novel Functional Food Properties of Forest Onion (Eleutherine bulbosa Merr.) Phytochemicals for Treating Metabolic Syndrome: New Insights from a Combined Computational and In Vitro Approach

Metabolic syndrome is a global health problem. The use of functional foods as dietary components has been increasing. One food of interest is forest onion extract (FOE). This study aimed to investigate the effect of FOE on lipid and glucose metabolism in silico and in vitro using the 3T3-L1 mouse cell line. This was a comprehensive study that used a multi-modal computational network pharmacology analysis and molecular docking in silico and 3T3-L1 mouse cells in vitro. The phytochemical components of FOE were analyzed using untargeted ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS). Next, an in silico analysis was performed to determine FOE's bioactive compounds, and a toxicity analysis, protein target identification, network pharmacology, and molecular docking were carried out. FOE's effect on pancreatic lipase, α-glucosidase, and α-amylase inhibition was determined. Finally, we determined its effect on lipid accumulation and MAPK8, PPARG, HMGCR, CPT-1, and GLP1 expression in the preadipocyte 3T3-L1 mouse cell line. We showed that the potential metabolites targeted glucose and lipid metabolism in silico and that FOE inhibited pancreatic lipase levels, α-glucosidase, and α-amylase in vitro. Furthermore, FOE significantly (p < 0.05) inhibits targeted protein expressions of MAPK8, PPARG, HMGCR, CPT-1, and GLP-1 in vitro in 3T3-L1 mouse cells in a dose-dependent manner. FOE contains several metabolites that reduce pancreatic lipase levels, α-glucosidase, α-amylase, and targeted proteins associated with lipid and glucose metabolism in vitro.

Structure-based virtual screening of mangiferin derivatives with antidiabetic action: a molecular docking and dynamics study and MPO-based drug-likeness approach

Extracts from Mangifera indica leaves and its main component, mangiferin, have proven antidiabetic activity. In this study, mangiferin and its natural derivatives Homomangiferin (HMF), Isomangiferin (IMF), Neomangiferin (NMF), Glucomangiferin (GMF), Mangiferin 6'-gallate (MFG), and Norathyriol (NRT) were compared regarding their action on Diabetes mellitus (DM), employing docking and molecular dynamics (MD) simulations to analyze interactions with the aldose reductase enzyme, the precursor to the conversion of glucose into sorbitol. Notably, HMF showed significant affinity to residues in the active site of the enzyme, including Trp 79, His 110, Trp 111, Phe 122, and Phe 300, with an energy of - 7.2 kcal/mol, observed in the molecular docking simulations. MD reinforced the formation of stable complexes for HMF and MFG with the aldose reductase, with interaction potential energies (IPE) in the order of - 300.812 ± 52 kJ/mol and - 304.812 ± 52 kJ/mol, respectively. The drug-likeness assessment, by multiparameter optimization (MPO), highlighted that HMF and IMF have similarities with polyphenols and glycosidic flavonoids recently patented as antidiabetics, revealing that high polarity (TPSA > 180 Å2) is a favorable property for subcutaneous administration, especially because of the gradual passive cell permeability values in biological tissues, with Papp values estimated at < 10 × 10-6 cm/s. These compounds are metabolically stable against metabolic enzymes, resulting in a low toxic incidence by metabolic activation, corroborating with a lethal dose (LD50) greater than 2000 mg/kg. In this way, HMF showed a systematic alignment between predicted pharmacokinetics and pharmacodynamics, characterizing it as the most favorable substance for inhibiting aldose reductase.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-03978-9.

Trichoplusia ni Transcriptomic Responses to the Phytosaponin Aglycone Hederagenin: Sex-Related Differences

Many plant species, particularly legumes, protect themselves with saponins. Previously, a correlation was observed between levels of oleanolic acid-derived saponins, such as hederagenin-derived compounds, in the legume Medicago truncatula and caterpillar deterrence. Using concentrations that reflect the foliar levels of hederagenin-type saponins, the sapogenin hederagenin was not toxic to 4th instar caterpillars of the cabbage looper Trichoplusia ni nor did it act as a feeding deterrent. Female caterpillars consumed more diet than males, presumably to obtain the additional nutrients required for oogenesis, and are, thus, exposed to higher hederagenin levels. When fed the hederagenin diet, male caterpillars expressed genes encoding trypsin-like proteins (LOC113500509, LOC113501951, LOC113501953, LOC113501966, LOC113501965, LOC113499659, LOC113501950, LOC113501948, LOC113501957, LOC113501962, LOC113497819, LOC113501946, LOC113503910) as well as stress-responsive (LOC113503484, LOC113505107) proteins and cytochrome P450 6B2-like (LOC113493761) at higher levels than females. In comparison, female caterpillars expressed higher levels of cytochrome P450 6B7-like (LOC113492289). Bioinformatic tools predict that cytochrome P450s could catalyze the oxygenation of hederagenin which would increase the hydrophilicity of the compound. Expression of a Major Facilitator Subfamily (MFS) transporter (LOC113492899) showed a hederagenin dose-dependent increase in gene expression suggesting that this transporter may be involved in sapogenin efflux. These sex-related differences in feeding and detoxification should be taken into consideration in insecticide evaluations to minimize pesticide resistance.

Molecular Property Diagnostic Suite for COVID-19 (MPDSCOVID-19): an open-source disease-specific drug discovery portal

Molecular Property Diagnostic Suite (MPDS) was conceived and developed as an open-source disease-specific web portal based on Galaxy. MPDSCOVID-19 was developed for COVID-19 as a one-stop solution for drug discovery research. Galaxy platforms enable the creation of customized workflows connecting various modules in the web server. The architecture of MPDSCOVID-19 effectively employs Galaxy v22.04 features, which are ported on CentOS 7.8 and Python 3.7. MPDSCOVID-19 provides significant updates and the addition of several new tools updated after six years. Tools developed by our group in Perl/Python and open-source tools are collated and integrated into MPDSCOVID-19 using XML scripts. Our MPDS suite aims to facilitate transparent and open innovation. This approach significantly helps bring inclusiveness in the community while promoting free access and participation in software development.

Availability & Implementation

The MPDSCOVID-19 portal can be accessed at https://mpds.neist.res.in:8085/.

Revealing Novel Source of Breast Cancer Inhibitors from Seagrass Enhalus acoroides: In Silico and In Vitro Studies

Enhalus arcoides is a highly beneficial type of seagrass. Prior studies have presented proof of the bioactivity of E. acoroides, suggesting its potential to combat cancer. Therefore, this study aims to delve deeper into E. acoroides bioactive molecule profiles and their direct biological anticancer activities potentials through the combination of in-silico and in-vitro studies. This study conducted metabolite profile analysis on E. acoroides utilizing HPLC-ESI-HRMS/MS analysis. Two extraction techniques, ethanol and hexane, were employed for the extraction process. Furthermore, the in-silico study was conducted using molecular docking simulations on the HER2, EGFR tyrosine kinase and HIF-1α protein receptor. Afterward, the antioxidant activity of E. acoroides metabolites was examined to ABTS, and the antiproliferative activity was tested using an MTT assay. An in-silico study revealed its ability to combat breast cancer by inhibiting the HER2/EGFR/HIF-1α pathway through molecular docking. In addition, the MTT assay demonstrated that higher dosages of metabolites from E. acoroides increased the effectiveness of toxicity against cancer cell lines. Additionally, the study demonstrated that the metabolites possess the ability to function as potent antioxidants, effectively inhibiting a series of carcinogenic mechanisms. Ultimately, this study showed a new approach to unveiling the E. acoroides metabolites' anticancer activity through inhibiting HER2/EGFR/HIF-1α receptors, with great cytotoxicity and a potent antioxidant property to prevent a carcinogenic cascade.

Inhibitors against New Delhi metallo-betalactamase-1 (NDM-1) and its variants endemic in Indian settings along with the laboratory functional gain mutant of NDM-1

PURPOSE

The emergence of NDM-1 producing bacteria has become common in both hospital and community settings, but no inhibitor has yet been available for clinical treatment. Hence, demanding the urgent need of NDM-1 inhibitors, we initiated to screen broad spectrum inhibitors against NDM natural variants and laboratory mutant.

METHODS

We used docking and molecular dynamics simulations, in silico pharmacokinetic investigations, and density functional theory calculation to characterize molecules. Furthermore, an in vitro study, including MIC, kinetics, and fluorescence study were carried out to confirm the efficacies of the selected compounds.

RESULTS

According to the findings of the computational studies, three compounds were effective against NDM variants. Fourfold reduction in MIC of imipenem and meropenem was observed when combined with inhibitors (D2573, D2148, and D63) against blaNDM-1, blaNDM-4, blaNDM-6, and blaNDM-1Q123A, while twofold reduction in MIC of imipenem and meropenem was observed against blaNDM-5 and blaNDM-7. Similarly in the presence of inhibitors (D2573, D2148, and D63) the efficiency of nitrocefin hydrolysis by NDM-4, NDM-6, and Q123A decreases to much more extent as compared to NDM-5 and NDM-7. These results showed that the efficacy of these broad spectrum inhibitors decreases with increasing resistance of NDM variants.

CONCLUSION

This is the first time inhibitors were tested against different NDM natural variants which are endemic in Indian settings. Moreover, a functional gain laboratory mutant was also checked for their efficacies. We may propose these molecules for the pre-clinical trial to further translate.

Integration of network pharmacology, molecular docking, and simulations to evaluate phytochemicals from Drymaria cordata against cervical cancer

Introduction: Cervical cancer is prevalent among women worldwide. It is a type of cancer that occurs in the cells of the cervix, the lower part of the uterus. Mostly, it is observed in developing nations due to limited access to screening tools. Natural products with anticancer properties and fewer side effects have gained attention. Therefore, this study evaluates the potential of Drymaria cordata as a natural source for treating cervical cancer. Methodology: Phytocompounds present in Drymaria cordata were screened for their molecular properties and drug-likeness. The selected compounds were studied using systems biology tools such as network pharmacology, molecular docking, and molecular dynamics simulations, including MMGBSA studies. Results: Through network pharmacology, molecular docking, and molecular dynamics simulations, quercetin 3-O-β-d-glucopyranosyl-(1→2)-rhamnopyranoside was identified as a hit compound targeting HRAS and VEGFA proteins. These proteins were found to be responsible for the maximum number of pathway modulations in cervical cancer. Conclusion: Drymaria cordata exhibits potential for treating cervical cancer due to the presence of quercetin 3-O-β-d-glucopyranosyl-(1→2)-rhamnopyranoside. Further validation of these findings through in vitro and in vivo studies is required.

Computational Design of Novel Griseofulvin Derivatives Demonstrating Potential Antibacterial Activity: Insights from Molecular Docking and Molecular Dynamics Simulation

In response to the urgent demand for innovative antibiotics, theoretical investigations have been employed to design novel analogs. Because griseofulvin is a potential antibacterial agent, we have designed novel derivatives of griseofulvin to enhance its antibacterial efficacy and to evaluate their interactions with bacterial targets using in silico analysis. The results of this study reveal that the newly designed derivatives displayed the most robust binding affinities towards PBP2, tyrosine phosphatase, and FtsZ proteins. Additionally, molecular dynamics (MD) simulations underscored the notable stability of these derivatives when engaged with the FtsZ protein, as evidenced by root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), and solvent-accessible surface area (SASA). Importantly, this observation aligns with expectations, considering that griseofulvin primarily targets microtubules in eukaryotic cells, and FtsZ functions as the prokaryotic counterpart to microtubules. These findings collectively suggest the promising potential of griseofulvin and its designed derivatives as effective antibacterial agents, particularly concerning their interaction with the FtsZ protein. This research contributes to the ongoing exploration of novel antibiotics and may serve as a foundation for future drug development efforts.

Design of Inhibitors That Target the Menin-Mixed-Lineage Leukemia Interaction

The prognosis of mixed-lineage leukemia (MLL) has remained a significant health concern, especially for infants. The minimal treatments available for this aggressive type of leukemia has been an ongoing problem. Chromosomal translocations of the KMT2A gene are known as MLL, which expresses MLL fusion proteins. A protein called menin is an important oncogenic cofactor for these MLL fusion proteins, thus providing a new avenue for treatments against this subset of acute leukemias. In this study, we report results using the structure-based drug design (SBDD) approach to discover potential novel MLL-mediated leukemia inhibitors from natural products against menin. The three-dimensional (3D) protein model was derived from Protein Databank (Protein ID: 4GQ4), and EasyModeller 4.0 and I-TASSER were used to fix missing residues during rebuilding. Out of the ten protein models generated (five from EasyModeller and I-TASSER each), one model was selected. The selected model demonstrated the most reasonable quality and had 75.5% of residues in the most favored regions, 18.3% of residues in additionally allowed regions, 3.3% of residues in generously allowed regions, and 2.9% of residues in disallowed regions. A ligand library containing 25,131 ligands from a Chinese database was virtually screened using AutoDock Vina, in addition to three known menin inhibitors. The top 10 compounds including ZINC000103526876, ZINC000095913861, ZINC000095912705, ZINC000085530497, ZINC000095912718, ZINC000070451048, ZINC000085530488, ZINC000095912706, ZINC000103580868, and ZINC000103584057 had binding energies of -11.0, -10.7, -10.6, -10.2, -10.2, -9.9, -9.9, -9.9, -9.9, and -9.9 kcal/mol, respectively. To confirm the stability of the menin-ligand complexes and the binding mechanisms, molecular dynamics simulations including molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) computations were performed. The amino acid residues that were found to be potentially crucial in ligand binding included Phe243, Met283, Cys246, Tyr281, Ala247, Ser160, Asn287, Asp185, Ser183, Tyr328, Asn249, His186, Leu182, Ile248, and Pro250. MI-2-2 and PubChem CIDs 71777742 and 36294 were shown to possess anti-menin properties; thus, this justifies a need to experimentally determine the activity of the identified compounds. The compounds identified herein were found to have good pharmacological profiles and had negligible toxicity. Additionally, these compounds were predicted as antileukemic, antineoplastic, chemopreventive, and apoptotic agents. The 10 natural compounds can be further explored as potential novel agents for the effective treatment of MLL-mediated leukemia.

Molecular insights into the anti-inflammatory activity of fermented pineapple juice using multimodal computational studies

Pineapple has been recognized for its potential to enhance health and well-being. This study aimed to gain molecular insights into the anti-inflammatory properties of fermented pineapple juice using multimodal computational studies. In this study, pineapple juice was fermented using Lactobacillus paracasei, and the solution underwent liquid chromatography-mass spectrometry analysis. Network pharmacology was applied to investigate compound interactions and targets. In silico methods assessed compound bioactivities. Protein-protein interactions, network topology, and enrichment analysis identified key compounds. Molecular docking explored compound-receptor interactions in inflammation regulation. Molecular dynamics simulations were conducted to confirm the stability of interactions between the identified crucial compounds and their respective receptors. The study revealed several compounds including short-chain fatty acids, peptides, dihydroxyeicosatrienoic acids, and glycerides that exhibited promising anti-inflammatory properties. Leucyl-leucyl-norleucine and Leu-Leu-Tyr exhibited robust and stable interactions with mitogen-activated protein kinase 14 and IκB kinase β, respectively, indicating their potential as promising therapeutic agents for inflammation modulation. This proposition is grounded in the pivotal involvement of these two proteins in inflammatory signaling pathways. These findings provide valuable insights into the anti-inflammatory potential of these compounds, serving as a foundation for further experimental validation and exploration. Future studies can build upon these results to advance the development of these compounds as effective anti-inflammatory agents.

Biological Activity of Hexaazaisowurtzitane Derivatives

Biologically active compounds of natural or synthetic origin have a complex structure and generally contain various structural groups among which polycyclic cage amines are found. Hexaazaisowurtzitanes are representatives of these amines and studies on their biological activity began less than two decades ago, starting with research on the environmental impact of CL-20. This research helped to evaluate the risks of potential pollution in the habitat environments of living organisms and determine whether the chemical compounds in question could be utilized in pesticides, herbicides, fungicides, or medicinal drugs. The nomenclature of hexaazaisowurtzitane compounds has recently been expanded significantly, and some of them have demonstrated promise in the design of medicinal drugs. This paper review studies the pharmacological activity of the acyl derivatives of hexaazaisowurtzitane. Most of the compounds have been found to possess a high analgesic activity, providing a solution to the pressing issue of pain management in current pharmacology. Analgesic drugs currently used in the clinical practice do not meet all of the efficacy and safety requirements (gastro-, nephro-, hepato-, haematotoxicity, etc.). The material presented in the seven sections of this paper highlights information about hexaazaisowurtzitane derivatives. Furthermore, they have been observed to exhibit anti-inflammatory, anticonvulsant, antihypoxic, and antimetastatic activities, which render them highly promising for evaluation in various fields of medicinal practice.

The anti-inflammatory activity of probiotic Dadiah to activate Sirtuin-1 in inhibiting diabetic nephropathy progression

Purpose

The activation of SIRT-1 in the kidney has become a new therapeutic target to increase resistance to many causal factors in DN development. Furthermore, antioxidative stress and anti-inflammation are essential to preventing renal fibrosis in DN. Therefore, finding "probiotic products" to treat and prevent DN is necessary. This study aimed to analyze the anti-inflammatory of probiotic dadiah to activate SIRT-1 in inhibiting DN progression.

Methods

This study is an experimental group designed with a post-test-only control group to observe the effect of dadiah, LAB, and bacteriocin on alloxan-induced nephropathy diabetic rats through two control groups and five intervention groups for eight weeks. The expression of antibodies SIRT-1 and TNF-α was examined using Immunohistochemistry and histopathology of kidney tissue. All data were analyzed using ANOVA test.

Results

The treatment of dadiah, lactic acid bacteria, and bacteriocin showed a higher expression of Sirtuin-1 than the positive control. They also, reduce TNF-α expression varies significantly between treatments. The highest average of interstitial fibrosis in the C + groups was substantially different from all groups, but all treatments showed decreased kidney fibrosis. Although all treatments showed a decrease in interstitial kidney fibrosis found in the control group, the treatment using dadiah showed the highest result.

Conclusions

Dadiah has the potential to the prevention of fibrosis on kidney tissue of alloxan-induced nephropathy diabetic rats. The findings could be to develop novel treatments for DN that aim to reduce the cascade of oxidative stress and inflammatory signals in kidney tissue.

Evaluation of the anti-infective potential of the seed endophytic fungi of Corchorus olitorius through metabolomics and molecular docking approach

BACKGROUND

Endophytic fungi are very rich sources of natural antibacterial and antifungal compounds. The main aim of this study is to isolate the fungal endophytes from the medicinal plant Corchorus olitorius seeds (F. Malvaceae), followed by antimicrobial screening against various bacterial and fungal strains.

RESULTS

Seven endophytic fungal strains belonging to different three genera were isolated, including Penicillium, Fusarium, and Aspergillus. The seven isolated endophytic strains revealed selective noticeable activity against Escherichia coli (ATCC25922) with varied IC50s ranging from 1.19 to 10 µg /mL, in which Aspergillus sp. (Ar 6) exhibited the strongest potency against E. coli (ATCC 25,922) and candida albicans (ATCC 10,231) with IC50s 1.19 and 15 µg /mL, respectively. Therefore, the chemical profiling of Aspergillus sp. (Ar 6) crude extract was performed using LC-HR-ESI-MS and led to the dereplication of sixteen compounds of various classes (1-16). In-silico analysis of the dereplicated metabolites led to highlighting the compounds responsible for the antimicrobial activity of Aspergillus sp. extract. Moreover, molecular docking showed the potential targets of the metabolites; Astellatol (5), Aspergillipeptide A (10), and Emericellamide C (14) against E. coli and C. albicans.

CONCLUSION

These results will expand the knowledge of endophytes and provide us with new approaches to face the global antibiotic resistance problem and the future production of undiscovered compounds different from the antibiotics classes.

Web Service for HIV Drug Resistance Prediction Based on Analysis of Amino Acid Substitutions in Main Drug Targets

Predicting viral drug resistance is a significant medical concern. The importance of this problem stimulates the continuous development of experimental and new computational approaches. The use of computational approaches allows researchers to increase therapy effectiveness and reduce the time and expenses involved when the prescribed antiretroviral therapy is ineffective in the treatment of infection caused by the human immunodeficiency virus type 1 (HIV-1). We propose two machine learning methods and the appropriate models for predicting HIV drug resistance related to amino acid substitutions in HIV targets: (i) k-mers utilizing the random forest and the support vector machine algorithms of the scikit-learn library, and (ii) multi-n-grams using the Bayesian approach implemented in MultiPASSR software. Both multi-n-grams and k-mers were computed based on the amino acid sequences of HIV enzymes: reverse transcriptase and protease. The performance of the models was estimated by five-fold cross-validation. The resulting classification models have a relatively high reliability (minimum accuracy for the drugs is 0.82, maximum: 0.94) and were used to create a web application, HVR (HIV drug Resistance), for the prediction of HIV drug resistance to protease inhibitors and nucleoside and non-nucleoside reverse transcriptase inhibitors based on the analysis of the amino acid sequences of the appropriate HIV proteins from clinical samples.

HDAC inhibition by Nigella sativa L. sprouts extract in hepatocellular carcinoma: an approach to study anti-cancer potential

A wide variety of natural products have been widely used in chemoprevention therapy because they have antioxidant, anti-inflammatory, and anticancer activity. In the present study, we shed light on the 5th day germinated sprouts of N. sativa seeds and evaluated them against HDAC inhibition and antioxidant activity. The extract from the seed and sprout was extracted and characterised by LC-MS/MS, FTIR, and NMR to reveal its chemical composition, especially thymol (THY) and thymoquinone (TQ). Hepatocellular carcinoma (HCC) is a global health concern as it is a major lifestyle disease. Hence, incorporating herbal-based therapeutic compounds into everyday routines has become an attractive alternative for preventing hepatic diseases. Histone deacetylase (HDAC) inhibition (HDACi) is emerging as a promising therapeutic strategy for managing various carcinomas including HCC. Therefore, the 5th day of N. sativa can be used as a potential anticancer agent by inhibiting HDAC activity, as it is reported to have an important role in the management of oxidative stress. The bioactive compound of N. sativa, i.e. thymoquinone, also showed a good binding affinity with the HDAC protein (3MAX) with a stable interaction in an in silico study as compared to the standard drug (Trichostatin A) and thymol.Communicated by Ramaswamy H. Sarma.

Cu(i)-catalysed 1,2,3-triazole stitched chalcomer assembly as Pb(ii) and Cu(ii) ion sensor: DFT and docking scrutiny

Herein, a 1,2,3-triazole derivative (CBT), synthesized using the Copper(i) catalyzed Alkyne Azide Cycloaddition (CuAAC) procedure, based on a chalcone skeleton has been reported, that was implemented as an effective sensor for Pb(ii) and Cu(ii) ions. The synthesized CBT was characterized using spectroscopic techniques such as FTIR, NMR (1H and 13C), and mass spectrometry. The sensing behaviour of CBT was analyzed using UV-Vis spectroscopy, demonstrating selective sensing for Pb(ii) and Cu(ii) ions, competitively. The correlation plot revealed the detection limit for Pb(ii) and Cu(ii) ions to be 100 μM and 110 μM respectively. In addition, DFT simulations and molecular electrostatic potential (MEP) studies scrutinized the binding strategy of the free CBT and its orientation towards the metal ions in the metal-ligand complex. The probe CBT was predicted via the online platform Way2drug for its pharmacological properties, investigating the possibility to inhibit early atherosclerosis. CBT was subsequently docked to the TRIB1 protein using AutoDock Vina and demonstrated a high binding affinity with a value of -6.2 kcal mol-1.

Molecular Property Diagnostic Suite Compound Library (MPDS-CL): a structure-based classification of the chemical space

Molecular Property Diagnostic Suite Compound Library (MPDS-CL) is an open-source Galaxy-based cheminformatics web portal which presents a structure-based classification of the molecules. A structure-based classification of nearly 150 million unique compounds, obtained from 42 publicly available databases and curated for redundancy removal through 97 hierarchically well-defined atom composition-based portions, has been done. These are further subjected to 56-bit fingerprint-based classification algorithm which led to the formation of 56 structurally well-defined classes. The classes thus obtained were further divided into clusters based on their molecular weight. Thus, the entire set of molecules was put into 56 different classes and 625 clusters. This led to the assignment of a unique ID, named as MPDS-AadharID, for each of these 149,169,443 molecules. MPDS-AadharID is akin to the unique number given to citizens in India (similar to SSN in the US and NINO in the UK). The unique features of MPDS-CL are (a) several search options, such as exact structure search, substructure search, property-based search, fingerprint-based search, using SMILES, InChIKey and key-in; (b) automatic generation of information for the processing for MPDS and other galaxy tools; (c) providing the class and cluster of a molecule which makes it easier and fast to search for similar molecules and (d) information related to the presence of the molecules in multiple databases. The MPDS-CL can be accessed at https://mpds.neist.res.in:8086/ .

Fungistatic Effect of Phthalide Lactones on Rhodotorula mucilaginosa

Currently, there is an increasing number of cases of fungal infections caused by opportunistic strains of the yeast Rhodotorula mucilaginosa, mainly in immunocompromised patients during hospitalization. The excessive use of antibiotics and azole compounds increases the risk of resistance to microorganisms. A new alternative to these drugs may be synthetic phthalide lactones with a structure identical to or similar to the natural ones found in celery plants, which show low toxicity and relatively high fungistatic activity. In the present study, the fungistatic activity of seven phthalide lactones was determined against R. mucilaginosa IHEM 18459. We showed that 3-n-butylidenephthalide, the most potent compound selected in the microdilution test, caused a dose-dependent decrease in dry yeast biomass. Phthalide accumulated in yeast cells and contributed to an increase in reactive oxygen species content. The synergistic effect of fluconazole resulted in a reduction in the azole concentration required for yeast inhibition. We observed changes in the color of the yeast cultures; thus, we conducted experiments to prove that the carotenoid profile was altered. The addition of lactones also triggered a decline in fatty acid methyl esters.

Microbial Metabolites of 3-n-butylphthalide as Monoamine Oxidase A Inhibitors

Novel compounds with antidepressant activity via monoamine oxidase inhibition are being sought. Among these, derivatives of 3-n-butylphthalide, a neuroprotective lactone from Apiaceae plants, may be prominent candidates. This study aimed to obtain the oxidation products of 3-n-butylphthalide and screen them regarding their activity against the monoamine oxidase A (MAO-A) isoform. Such activity of these compounds has not been previously tested. To obtain the metabolites, we used fungi as biocatalysts because of their high oxidative capacity. Overall, 37 strains were used, among which Penicillium and Botrytis spp. were the most efficient, leading to the obtaining of three main products: 3-n-butyl-10-hydroxyphthalide, 3-n-butylphthalide-11-oic acid, and 3-n-butyl-11-hydroxyphthalide, with a total yield of 0.38-0.82 g per g of the substrate, depending on the biocatalyst used. The precursor-3-n-butylphthalide and abovementioned metabolites inhibited the MAO-A enzyme; the most active was the carboxylic acid derivative of the lactone with inhibitory constant (K_i) < 0.001 µmol/L. The in silico prediction of the drug-likeness of the metabolites matches the assumptions of Lipinski, Ghose, Veber, Egan, and Muegge. All the compounds are within the optimal range for the lipophilicity value, which is connected to adequate permeability and solubility.

Machine learning based dynamic consensus model for predicting blood-brain barrier permeability

The blood-brain barrier (BBB) is an important defence mechanism that restricts disease-causing pathogens and toxins to enter the brain from the bloodstream. In recent years, many in silico methods were proposed for predicting BBB permeability, however, the reliability of these models is questionable due to the smaller and class-imbalance dataset which subsequently leads to a very high false positive rate. In this study, machine learning and deep learning-based predictive models were built using XGboost, Random Forest, Extra-tree classifiers and deep neural network. A dataset of 8153 compounds comprising both the BBB permeable and BBB non-permeable was curated and subjected to calculations of molecular descriptors and fingerprints for generating the features for machine learning and deep learning models. Three balancing techniques were then applied to the dataset to address the class-imbalance issue. A comprehensive comparison among the models showed that the deep neural network model generated on the balanced MACCS fingerprint dataset outperformed with an accuracy of 97.8% and a ROC-AUC score of 0.98 among all the models. Additionally, a dynamic consensus model was prepared with the machine learning models and validated with a benchmark dataset for predicting BBB permeability with higher confidence scores.

Cichorium intybus L. “hairy” roots as a rich source of antioxidants and anti-inflammatory compounds

The present study aimed to determine the bioactive profile of various extracts of Cichorium intybus L. "hairy" roots. In particular, the total content of flavonoids as well as the reducing power, antioxidant and anti-inflammatory activity of the aqueous and ethanolic (70%) extracts were evaluated. The total content of flavonoids the ethanolic extract of the dry "hairy" root reached up to 121.3 mg (RE)/g, which was twofold greater than in the aqueous one. A total of 33 diverse polyphenols were identified by the LC-HRMS method. The experimental results showed a high amount of gallic (6.103 ± 0.008 mg/g) and caffeic (7.001 ± 0.068 mg/g) acids. In the "hairy" roots, the presence of rutin, apigenin, kaempferol, quercetin, and its derivatives was found in concentrations of 0.201±0.003 - 6.710±0.052 mg/g. The broad spectrum of pharmacological activities (antioxidant, anti-inflammatory, antimutagenic, anticarcinogenic, etc.) of the key flavonoids identified in the chicory "hairy" root extract was predicted by the General Unrestricted Structure-Activity Relationships algorithm based on in the substances detected in the extract. The evaluation of the antioxidant activity showed that the EC₅₀ values of the ethanol and the aqueous extracts were 0.174 and 0.346 mg, respectively. Thus, the higher ability of the ethanol extract to scavenge the DPPH radical was observed. The calculated Michaelis and inhibition constants indicated that the ethanolic extract of C. intybus "hairy" roots is an efficient inhibitor of soybean 15-Lipoxygenase activity (IC₅₀ = 84.13 ± 7.22 μM) in a mixed mechanism. Therefore, the obtained extracts could be the basis of herbal pharmaceuticals for the therapy of human diseases accompanied by oxidative stress and inflammation, including the pandemic coronavirus disease COVID-19.

Synergic Effect of Phthalide Lactones and Fluconazole and Its New Analogues as a Factor Limiting the Use of Azole Drugs against Candidiasis

The resistance of Candida albicans and other pathogenic yeasts to azole antifungal drugs has increased rapidly in recent years and is a significant problem in clinical therapy. The current state of pharmacological knowledge precludes the withdrawal of azole drugs, as no other active substances have yet been developed that could effectively replace them. Therefore, one of the anti-yeast strategies may be therapies that can rely on the synergistic action of natural compounds and azoles, limiting the use of azole drugs against candidiasis. Synergy assays performed in vitro were used to assess drug interactions Fractional Inhibitory Concentration Index. The synergistic effect of fluconazole (1) and three synthetic lactones identical to those naturally occurring in celery plants-3-n-butylphthalide (2), 3-n-butylidenephthalide (3), 3-n-butyl-4,5,6,7-tetrahydrophthalide (4)-against Candida albicans ATCC 10231, C. albicans ATCC 2091, and C. guilliermondii KKP 3390 was compared with the performance of the individual compounds separately. MIC90 (the amount of fungistatic substance (in µg/mL) inhibiting yeast growth by 90%) was determined as 5.96-6.25 µg/mL for fluconazole (1) and 92-150 µg/mL for lactones 2-4. With the simultaneous administration of fluconazole (1) and one of the lactones 2-4, it was found that they act synergistically, and to achieve the same effect it is sufficient to use 0.58-6.73 µg/mL fluconazole (1) and 1.26-20.18 µg/mL of lactones 2-4. As fluconazole and phthalide lactones show synergy, 11 new fluconazole analogues with lower toxicity and lower inhibitory activity for CYP2C19, CYP1A2, and CYP2C9, were designed after in silico testing. The lipophilicity was also analyzed. A three-carbon alcohol with two rings was preserved. In all compounds 5-15, the 1,2,4-triazole rings were replaced with 1,2,3-triazole or tetrazole rings. The hydroxyl group was free or esterified with phenylacetic acid or thiophene-2-carboxylic acid chlorides or with adipic acid. In structures 11 and 12 the hydroxyl group was replaced with the fragment -CH2Cl or = CH2. Additionally, the difluorophenyl ring was replaced with unsubstituted phenyl. The structures of the obtained compounds were determined by 1H NMR, and 13C NMR spectroscopy. Molecular masses were established by GC-MS or elemental analysis. The MIC50 and MIC90 of all compounds 1-15 were determined against Candida albicans ATCC 10231, C. albicans ATCC 2091, AM 38/20, C. guilliermondii KKP 3390, and C. zeylanoides KKP 3528. The MIC50 values for the newly prepared compounds ranged from 38.45 to 260.81 µg/mL. The 90% inhibitory dose was at least twice as high. Large differences in the effect of fluconazole analogues 5-15 on individual strains were observed. A synergistic effect on three strains-Candida albicans ATCC 10231, C. albicans ATCC 2091, C. guilliermondii KKP 339-was observed. Fractional inhibitory concentrations FIC50 and FIC90 were tested for the most active lactone, 3-n-butylphthalide, and seven fluconazole analogues. The strongest synergistic effect was observed for the strain C. albicans ATCC 10231, FIC 0.04-0.48. The growth inhibitory amount of azole is from 25 to 55 µg/mL and from 3.13 to 25.3 µg/mL for 3-n-butylphthalide. Based on biological research, the influence of the structure on the fungistatic activity and the synergistic effect were determined.

Evaluation of Blood-Brain-Barrier Permeability, Neurotoxicity, and Potential Cognitive Impairment by Pseudomonas aeruginosa’s Virulence Factor Pyocyanin

Pyocyanin (PCN) is a redox-active secondary metabolite produced by Pseudomonas aeruginosa as its primary virulence factor. Several studies have reported the cytotoxic potential of PCN and its role during infection establishment and progression. Considering its ability to diffuse through biological membranes, it is hypothesized that PCN can gain entry into the brain and induce oxidative stress across the blood-brain barrier (BBB), ultimately contributing towards reactive oxygen species (ROS) mediated neurodegeneration. Potential roles of PCN in the central nervous system (CNS) have never been evaluated, hence the study aimed to evaluate PCN's probable penetration into CNS through blood-brain barrier (BBB) using both in silico and in vivo (Balb/c mice) approaches and the impact of ROS generation via commonly used tests: Morris water maze test, novel object recognition, elevated plus maze test, and tail suspension test. Furthermore, evidence for ROS generation in the brain was assessed using glutathione S-transferase assay. PCN demonstrated BBB permeability albeit in minute quantities. A significant hike was observed in ROS generation (P < 0.0001) along with changes in behavior indicating PCN permeability across BBB and potentially affecting cognitive functions. This is the first study exploring the potential role of PCN in influencing the cognitive functions of test animals.

Potential of the Compounds from Bixa orellana Purified Annatto Oil and Its Granules (Chronic®) against Dyslipidemia and Inflammatory Diseases: In Silico Studies with Geranylgeraniol and Tocotrienols

Some significant compounds present in annatto are geranylgeraniol and tocotrienols. These compounds have beneficial effects against hyperlipidemia and chronic diseases, where oxidative stress and inflammation are present, but the exact mechanism of action of such activities is still a subject of research. This study aimed to evaluate possible mechanisms of action that could be underlying the activities of these molecules. For this, in silico approaches such as ligand topology (PASS and SEA servers) and molecular docking with the software GOLD were used. Additionally, we screened some pharmacokinetic and toxicological parameters using the servers PreADMET, SwissADME, and ProTox-II. The results corroborate the antidyslipidemia and anti-inflammatory activities of geranylgeraniol and tocotrienols. Notably, some new mechanisms of action were predicted to be potentially underlying the activities of these compounds, including inhibition of squalene monooxygenase, lanosterol synthase, and phospholipase A₂. These results give new insight into new mechanisms of action involved in these molecules from annatto and Chronic^®.

Synthesis, Biological Evaluation and Molecular Docking Studies of 5-indolylmethylen-4-oxo-2-thioxothiazolidine Derivatives

Background: Infectious diseases represent a significant global strain on public health security and impact on socio-economic stability all over the world. The increasing resistance to the current antimicrobial treatment has resulted in the crucial need for the discovery and development of novel entities for the infectious treatment with different modes of action that could target both sensitive and resistant strains. Methods: Compounds were synthesized using the classical organic chemistry methods. Prediction of biological activity spectra was carried out using PASS and PASS-based web applications. Pharmacophore modeling in LigandScout software was used for quantitative modeling of the antibacterial activity. Antimicrobial activity was evaluated using the microdilution method. AutoDock 4.2® software was used to elucidate probable bacterial and fungal molecular targets of the studied compounds. Results: All compounds exhibited better antibacterial potency than ampicillin against all bacteria tested. Three compounds were tested against resistant strains MRSA, P.aeruginosa and E.coli and were found to be more potent than MRSA than reference drugs. All compounds demonstrated a higher degree of antifungal activity than the reference drugs bifonazole (6–17-fold) and ketoconazole (13–52-fold). Three of the most active compounds could be considered for further development of the new, more potent antimicrobial agents. Conclusion: Compounds 5b (Z)-3-(3-hydroxyphenyl)-5-((1-methyl-1H-indol-3-yl)methylene)-2-thioxothiazolidin-4-one and 5g (Z)-3-[5-(1H-Indol-3-ylmethylene)-4-oxo-2-thioxo-thiazolidin-3-yl]-benzoic acid as well as 5h (Z)-3-(5-((5-methoxy-1H-indol-3-yl)methylene)-4-oxo-2-thioxothiazolidin-3-yl)benzoic acid can be considered as lead compounds for further development of more potent and safe antibacterial and antifungal agents.

A possible potential COVID-19 drug candidate: Diethyl 2-(2-(2-(3-methyl-2-oxoquinoxalin-1(2H)-yl)acetyl)hydrazono)malonate: Docking of disordered independent molecules of a novel crystal structure, HSA/DFT/XRD and cytotoxicity

This study reports the synthesis, characterization and importance of a novel diethyl 2-(2-(2-(3-methyl-2-oxoquinoxalin-1(2H)-yl)acetyl)hydrazono)malonate (MQOAHM). Two independent molecular structures of the disordered MQOAHM have been established by XRD‑single‑crystal analysis in a ratio of 0.596(3)/0.404(3), MQOAHM (a) and MQOAHM (b), respectively. MQOAHM was characterized by means of various spectroscopic tools ESI-MS, IR, ¹H &¹³C NMR analyses. Density Functional Theory (DFT) method, B3LYP, 6-311++G(d,p) basis set was used to optimize MQOAHM molecule. The obtained theoretical structure and experimental structure were superimposed on each other, and the correlation between them was calculated. The Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) were created, and the energy gap between these orbitals was calculated. For analyzing intermolecular interactions, Molecular Electrostatic Potential (MEP) and Hirshfeld Surface Analysis were studied. For a fair comparative study, the two forms of the title compound were docked together with 18 approved drugs and N3 under precisely the same conditions. The disordered molecule structure's binding scores against 7BQY were -7.0 and -6.9 kcal/mol^-1 for MQOAHM (a) and MQOAHM (b), respectively. Both the forms show almost identical superimposed structures and scores indicating that the disorder of the molecule, in this study, has no obvious effect. The high binding score of the molecule was attributed to the multi-hydrogen bond and hydrophobic interactions between the ligand and the receptor's active amino acid residues. Worth pointing out here that the aim of using the free energy in Silico molecular docking approach is to rank the title molecule compared to the wide range of approved drugs and a well-established ligand N3. The binding scores of all the molecules used in this study are ranged from -9.9 to -4.5 kcal/mol^-1. These results and the supporting statistical analyses suggest that this malonate-based ligand merits further research in the context of possible therapeutic agents for COVID-19. Cheap computational techniques, PASS, Way2drug and ADMET, online software tools, were used in this study to uncover the title compound's potential biological activities and cytotoxicity.

Prediction of ITK inhibitor kinases activity based on posterior probabilistic weighted average based ensemble voting classification

ITK inhibitor is used for the treatment of asthma and activity of inhibitor prediction helps to provide better treatment. Few researches were carried out for the analysis and prediction of kinases activity. Existing methods applied for the inhibitor prediction have limitations of imbalance dataset and lower performance. In this research, the Posterior Probabilistic Weighted Average Based Ensemble voting (PPWAE)ensemble method is proposed with various classifier for effective prediction of kinases activity. The PPWAE model selects the most probable class from the classification method for prediction. The co-train model has two advantages: Features are trained together to increases the learning rate of model and probability is measured for each model to select the efficient classifier. Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Classification and Regression Tree (CART), and Nave Bayes were among the classifiers employed. The results suggest that the Probabilistic Co-train ensemble technique performs well in kinase activity prediction. In the prediction of ITK inhibitor activity, the suggested ensemble method has a 74.27 percent accuracy, while the conventional SVM method has a 60% accuracy.

Antiprotozoal and Antitumor Activity of Natural Polycyclic Endoperoxides: Origin, Structures and Biological Activity

Polycyclic endoperoxides are rare natural metabolites found and isolated in plants, fungi, and marine invertebrates. The purpose of this review is a comparative analysis of the pharmacological potential of these natural products. According to PASS (Prediction of Activity Spectra for Substances) estimates, they are more likely to exhibit antiprotozoal and antitumor properties. Some of them are now widely used in clinical medicine. All polycyclic endoperoxides presented in this article demonstrate antiprotozoal activity and can be divided into three groups. The third group includes endoperoxides, which show weak antiprotozoal activity with a reliability of up to 70%, and this group includes only 1.1% of metabolites. The second group includes the largest number of endoperoxides, which are 65% and show average antiprotozoal activity with a confidence level of 70 to 90%. Lastly, the third group includes endoperoxides, which are 33.9% and show strong antiprotozoal activity with a confidence level of 90 to 99.6%. Interestingly, artemisinin and its analogs show strong antiprotozoal activity with 79 to 99.6% confidence against obligate intracellular parasites which belong to the genera Plasmodium, Toxoplasma, Leishmania, and Coccidia. In addition to antiprotozoal activities, polycyclic endoperoxides show antitumor activity in the proportion: 4.6% show weak activity with a reliability of up to 70%, 65.6% show an average activity with a reliability of 70 to 90%, and 29.8% show strong activity with a reliability of 90 to 98.3%. It should also be noted that some polycyclic endoperoxides, in addition to antiprotozoal and antitumor properties, show other strong activities with a confidence level of 90 to 97%. These include antifungal activity against the genera Aspergillus, Candida, and Cryptococcus, as well as anti-inflammatory activity. This review provides insights on further utilization of polycyclic endoperoxides by medicinal chemists, pharmacologists, and the pharmaceutical industry.

Antioxidant and Antiproliferative Activity of The Ethanolic Extract of Equisetum Myriochaetum and Molecular Docking of Its Main Metabolites (Apigenin, Kaempferol, and Quercetin) on β-Tubulin

Equisetum myriochaetum is a semi-aquatic plant found on riverbanks that is commonly used in traditional medicine as a diuretic agent. Additionally, the genus Equisetum stands out for its content of the flavonoid kaempferol, a well-known antiproliferative agent. Therefore, in this study, E. myriochaetum ethanolic extract was tested in vitro against a cervical cancer cell line (SiHa). Additionally, the antioxidative activity was evaluated through a 2,2-diphenyl-1-picrilhidrazil (DPPH) assay. Finally, a molecular docking analysis of apigenin, kaempferol, and quercetin on the active site of β-tubulin was performed to investigate their potential mechanism of action. All fractions of E. myriochaetum ethanolic extract showed antioxidative activity. Fraction 14 displayed an antiproliferative capacity with a half maximal inhibitory concentration (IC₅₀) value of 6.78 μg/mL against SiHa cells.

Antibacterial activity of griseofulvin analogues as an example of drug repurposing

Griseofulvin is a well-known antifungal drug that was launched in 1962 by Merck & Co. for the treatment of dermatophyte infections. However, according to predictions using the Way2Drug computational drug repurposing platform, it may also have antibacterial activity. As no confirmation of this prediction was found in the published literature, this study estimated in-silico antibacterial activity for 42 griseofulvin derivatives. Antibacterial activity was predicted for 33 of the 42 compounds, which led to the conclusion that this activity might be considered as typical for this chemical series. Therefore, experimental testing of antibacterial activity was performed on a panel of Gram-positive and Gram-negative micro-organisms. Antibacterial activity was evaluated using the microdilution method detecting the minimal inhibitory concentration (MIC) and the minimal bactericidal concentration (MBC). The tested compounds exhibited potent antibacterial activity against all the studied bacteria, with MIC and MBC values ranging from 0.0037 to 0.04 mg/mL and from 0.01 to 0.16 mg/mL, respectively. Activity was 2.5-12 times greater than that of ampicillin and 2-8 times greater than that of streptomycin, which were used as the reference drugs. Similarity analysis for all 42 compounds with the (approximately) 470,000 drug-like compounds indexed in the Clarivate Analytics Integrity database confirmed the significant novelty of the antibacterial activity for the compounds from this chemical class. Therefore, this study demonstrated that by using computer-aided prediction of biological activity spectra for a particular chemical series, it is possible to identify typical biological activities which may be used for discovery of new applications (e.g. drug repurposing).

AntiBac-Pred: A Web Application for Predicting Antibacterial Activity of Chemical Compounds

Discovery of new antibacterial agents is a never-ending task of medicinal chemistry. Every new drug brings significant improvement to patients with bacterial infections, but prolonged usage of antibacterials leads to the emergence of resistant strains. Therefore, novel active structures with new modes of action are required. We describe a web application called AntiBac-Pred aimed to help users in the rational selection of the chemical compounds for experimental studies of antibacterial activity. This application is developed using antibacterial activity data available in ChEMBL and PASS software. It allows users to classify chemical structures of interest into growth inhibitors or noninhibitors of 353 different bacteria strains, including both resistant and nonresistant ones.

Spectral and quantum chemical analysis of ethyl 4-[3-(adamantan-1-yl)-4-phenyl-5-sulfanylidene-4,5-dihydro-1H-1,2,4-triazole-1-yl]methylpiperazine-1-carboxylate

The Fourier transform infrared and Raman spectra of the adamantane-based compound ethyl 4-[3-(adamantan-1-yl)-4-phenyl-5-sulfanylidene-4,5-dihydro-1H-1,2,4-triazol-1-yl]methylpiperazine-1-carboxylate were recorded in the ranges of 3200–650[Formula: see text]cm[Formula: see text] and 3200–150[Formula: see text]cm[Formula: see text], respectively. The UV/Vis spectrum of solution of the title compound in ethanol was measured in the range of 450–200[Formula: see text]nm. The DFT calculations at the B3LYP/cc-pVDZ and B3LYP/cc-pVTZ levels of the theory were performed to obtain the equilibrium geometric structure and to predict vibrational IR and Raman spectra of the title molecule. The TDDFT calculations at the CAM-B3LYP/cc-pVTZ level of the theory, as well as MRPT calculations at the CASSCF(4,5)/XMCQDPT2 level of the theory were carried out to reproduce the electronic absorption spectrum. The experimental IR, Raman and UV/Vis spectra were interpreted on the basis of results of quantum chemical modeling. Based on Mulliken and Löwdin atomic population analysis, it was established that the compound under study exhibits features of an intramolecular charge transfer.

Drug-drug interaction prediction using PASS

Simultaneous use of the drugs may lead to undesirable Drug-Drug Interactions (DDIs) in the human body. Many DDIs are associated with changes in drug metabolism that performed by Drug-Metabolizing Enzymes (DMEs). In this case, DDI manifests itself as a result of the effect of one drug on the biotransformation of other drug(s), its slowing down (in the case of inhibiting DME) or acceleration (in case of induction of DME), which leads to a change in the pharmacological effect of the drugs combination. We used OpeRational ClassificAtion (ORCA) system for categorizing DDIs. ORCA divides DDIs into five classes: contraindicated (class 1), provisionally contraindicated (class 2), conditional (class 3), minimal risk (class 4), no interaction (class 5). We collected a training set consisting of several thousands of drug pairs. Algorithm of PASS program was used for the first, second and third classes DDI prediction. Chemical descriptors called PoSMNA (Pairs of Substances Multilevel Neighbourhoods of Atoms) were developed and implemented in PASS software to describe in a machine-readable format drug substances pairs instead of the single molecules. The average accuracy of DDI class prediction is about 0.84. A freely available web resource for DDI prediction was developed (http://way2drug.com/ddi/).

Assessment of the cardiovascular adverse effects of drug-drug interactions through a combined analysis of spontaneous reports and predicted drug-target interactions

Adverse drug effects (ADEs) are one of the leading causes of death in developed countries and are the main reason for drug recalls from the market, whereas the ADEs that are associated with action on the cardiovascular system are the most dangerous and widespread. The treatment of human diseases often requires the intake of several drugs, which can lead to undesirable drug-drug interactions (DDIs), thus causing an increase in the frequency and severity of ADEs. An evaluation of DDI-induced ADEs is a nontrivial task and requires numerous experimental and clinical studies. Therefore, we developed a computational approach to assess the cardiovascular ADEs of DDIs. This approach is based on the combined analysis of spontaneous reports (SRs) and predicted drug-target interactions to estimate the five cardiovascular ADEs that are induced by DDIs, namely, myocardial infarction, ischemic stroke, ventricular tachycardia, cardiac failure, and arterial hypertension. We applied a method based on least absolute shrinkage and selection operator (LASSO) logistic regression to SRs for the identification of interacting pairs of drugs causing corresponding ADEs, as well as noninteracting pairs of drugs. As a result, five datasets containing, on average, 3100 potentially ADE-causing and non-ADE-causing drug pairs were created. The obtained data, along with information on the interaction of drugs with 1553 human targets predicted by PASS Targets software, were used to create five classification models using the Random Forest method. The average area under the ROC curve of the obtained models, sensitivity, specificity and balanced accuracy were 0.837, 0.764, 0.754 and 0.759, respectively. The predicted drug targets were also used to hypothesize the potential mechanisms of DDI-induced ventricular tachycardia for the top-scoring drug pairs. The created five classification models can be used for the identification of drug combinations that are potentially the most or least dangerous for the cardiovascular system.

Systematic Review on Cytotoxic and Anticancer Potential of N-Substituted Isatins as Novel Class of Compounds Useful in Multidrug-Resistant Cancer Therapy: In Silico and In Vitro Analysis

As the emergence of resistance to clinical cancer treatments poses a significant problem in cancer management, there is a constant need to explore novel anticancer agents which have the ability to overcome multidrug resistance (MDR) mechanisms. The search for the development of novel isatin-based antitumor agents accelerated after the approval by the Food and Drug Administration (FDA) of sunitinib malate, a C-3 isatin derivative, as a multitargeted receptor tyrosine kinase inhibitor. However, it is interesting to note that, over the last decade, various N-substituted analogs of isatin with intact carbonyl functionalities have been found to show more promising anticancer potential than its C-3 derivatives. Microtubule-targeting agents are a class of anticancer drugs which affect mitosis by targeting microtubules and suppressing their dynamic behavior. This review presents a systematic compilation of the in vitro cytotoxic and anticancer properties of various N-substituted isatins and illustrates their mechanism of action to overcome MDR by acting as microtubule-destabilizing agents. Predictions of the biological activities and cytotoxic effects of potential N-substituted isatins against various cancer cell lines have also been performed using the PASS computer-aided drug discovery program. Findings from such in vitro and in silico studies will act as a guide for the development of structure-activity relationship and will facilitate the design and exploration of more potent analogs of isatin with high potency and lower side effects for treatment of drug-resistant cancer. Mechanism of action of N-substituted isatin as microtubule-destabilizing agent on tumor cells. N-Substituted isatins bind to colchicine binding site on β-tubulin, which inhibits microtubule polymerization and thereby destabilizes microtubule dynamics, resulting in mitotic arrest leading to tumor cell growth suppression.

Structural, Vibrational and UV/Vis Studies of Adamantane-Containing Triazole Thiones by Spectral, DFT and Multi-reference ab initio Methods

The Fourier transform infrared and Raman spectra of two adamantane-containing triazole thiones, namely 3-(adamantan-1-yl)-1-[(4-benzylpiperazin-1-yl)methyl]-4-phenyl-1H-1,2,4-triazole-5(4H)-thione and 3-(adamantan-1-yl)-4-phenyl-1-[(4-phenylpiperazin-1-yl)methyl]-1H-1,2,4-triazole-5(4H)-thione, were examined in the ranges of 3200–650 cm−1 and 3200–150 cm−1, respectively. The density functional theory calculations were performed for the geometric structures and vibrational spectra for the title molecules. The accurate equilibrium geometry structures of the molecules were determined on the basis of full geometry optimization at the B3LYP/cc-pVDZ level of the theory. The IR and Raman vibrational spectra were calculated and compared with the experimental ones. The experimental vibrational FT-IR and Raman spectra were interpreted. Based on the structure of the molecules the biological activity indices were predicted. It is established that compounds under consideration are very likely to exhibit the analgesic activities. The UV/Vis spectra of solution of the compounds in ethanol were measured in the range of 450–200 nm. The UV/Vis spectra simulations at the Time-Dependent DFT and Multi-Reference Perturbation Theory levels of theory demonstrate unsuitability of the TDDFT for description of the experimental spectra of the title molecules. It is highly probable that this is a consequence of the intramolecular charge transfer. In contrast, the MRPT results are in a good agreement with the experimental spectra.

Naturally occurring aromatic steroids and their biological activities

The present review describes the distribution and biological activities of natural mono-, di-, and triaromatic steroids. It is shown that the producers of aromatic steroids are microorganisms, fungi, and marine invertebrates, and also they were found in plants, animals, marine sediments, and karst deposits. Eighty biologically active aromatic steroids likely have an anti-tumor, anti-inflammatory, and neuroprotection activity with a confidence of 78 to 92%. The structures and predicted biological activities of aromatic steroids are available. This review emphasizes the role of aromatic steroids as an important source and potential leads for drug discovery and they are of great interest to chemists, physicians, biologists, pharmacologists, and the pharmaceutical industry.

Computer-aided prediction of biological activity spectra for chemical compounds: opportunities and limitation

An essential characteristic of chemical compounds is their biological activity since its presence can become the basis for the use of the substance for therapeutic purposes, or, on the contrary, limit the possibilities of its practical application due to the manifestation of side action and toxic effects. Computer assessment of the biological activity spectra makes it possible to determine the most promising directions for the study of the pharmacological action of particular substances, and to filter out potentially dangerous molecules at the early stages of research. For more than 25 years, we have been developing and improving the computer program PASS (Prediction of Activity Spectra for Substances), designed to predict the biological activity spectrum of substance based on the structural formula of its molecules. The prediction is carried out by the analysis of structure-activity relationships for the training set, which currently contains information on structures and known biological activities for more than one million molecules. The structure of the organic compound is represented in PASS using Multilevel Neighborhoods of Atoms descriptors; the activity prediction for new compounds is performed by the naive Bayes classifier and the structure-activity relationships determined by the analysis of the training set. We have created and improved both local versions of the PASS program and freely available web resources based on PASS (http://www.way2drug.com). They predict several thousand biological activities (pharmacological effects, molecular mechanisms of action, specific toxicity and adverse effects, interaction with the unwanted targets, metabolism and action on molecular transport), cytotoxicity for tumor and non-tumor cell lines, carcinogenicity, induced changes of gene expression profiles, metabolic sites of the major enzymes of the first and second phases of xenobiotics biotransformation, and belonging to substrates and/or metabolites of metabolic enzymes. The web resource Way2Drug is used by over 18,000 researchers from more than 90 countries around the world, which allowed them to obtain over 600,000 predictions and publish about 500 papers describing the obtained results. The analysis of the published works shows that in some cases the interpretation of the prediction results presented by the authors of these publications requires an adjustment. In this work, we provide the theoretical basis and consider, on particular examples, the opportunities and limitations of computer-aided prediction of biological activity spectra.