Multi-Target In-Silico modeling strategies to discover novel angiotensin converting enzyme and neprilysin dual inhibitors.

Cardiovascular diseases, including heart failure, stroke, and hypertension, affect 608 million people worldwide and cause 32% of deaths. Combination therapy is required in 60% of patients, involving concurrent Renin-Angiotensin-Aldosterone-System (RAAS) and Neprilysin inhibition. This study introduces a novel multi-target in-silico modeling technique (mt-QSAR) to evaluate the inhibitory potential against Neprilysin and Angiotensin-converting enzymes. Using both linear (GA-LDA) and non-linear (RF) algorithms, mt-QSAR classification models were developed using 983 chemicals to predict inhibitory effects on Neprilysin and Angiotensin-converting enzymes. The Box-Jenkins method, feature selection method, and machine learning algorithms were employed to obtain the most predictive model with ~ 90% overall accuracy. Additionally, the study employed virtual screening of designed scaffolds (Chalcone and its analogues, 1,3-Thiazole, 1,3,4-Thiadiazole) applying developed mt-QSAR models and molecular docking. The identified virtual hits underwent successive filtration steps, incorporating assessments of drug-likeness, ADMET profiles, and synthetic accessibility tools. Finally, Molecular dynamic simulations were then used to identify and rank the most favourable compounds. The data acquired from this study may provide crucial direction for the identification of new multi-targeted cardiovascular inhibitors.

DrugMetric: quantitative drug-likeness scoring based on chemical space distance.

The process of drug discovery is widely known to be lengthy and resource-intensive. Artificial Intelligence approaches bring hope for accelerating the identification of molecules with the necessary properties for drug development. Drug-likeness assessment is crucial for the virtual screening of candidate drugs. However, traditional methods like Quantitative Estimation of Drug-likeness (QED) struggle to distinguish between drug and non-drug molecules accurately. Additionally, some deep learning-based binary classification models heavily rely on selecting training negative sets. To address these challenges, we introduce a novel unsupervised learning framework called DrugMetric, an innovative framework for quantitatively assessing drug-likeness based on the chemical space distance. DrugMetric blends the powerful learning ability of variational autoencoders with the discriminative ability of the Gaussian Mixture Model. This synergy enables DrugMetric to identify significant differences in drug-likeness across different datasets effectively. Moreover, DrugMetric incorporates principles of ensemble learning to enhance its predictive capabilities. Upon testing over a variety of tasks and datasets, DrugMetric consistently showcases superior scoring and classification performance. It excels in quantifying drug-likeness and accurately distinguishing candidate drugs from non-drugs, surpassing traditional methods including QED. This work highlights DrugMetric as a practical tool for drug-likeness scoring, facilitating the acceleration of virtual drug screening, and has potential applications in other biochemical fields.

Investigation on molecular and biomolecular spectroscopy of the novel 2BCA molecule to analyse its biological activities and binding interaction with nipah viral protein.

The molecule of 2-Biphenyl Carboxylic Acid (2BCA), which contains peculiar features, was explored making use of density functional theory (DFT) and experimental approaches in the area of quantum computational research. The optimised structure, atomic charges, vibrational frequencies, electrical properties, electrostatic potential surface (ESP), natural bond orbital analysis and potential energy surface (PES) were obtained applying the B3LYP approach with the 6-311++ G (d,p) basis set.. The 2BCA molecule was examined for possible conformers using a PES scan. The methods applied for spectral analyses included FT-IR, FT-RAMAN, NMR, and UV-Vis results. Vibrational frequencies for all typical modes of vibration were found using the Potential Energy Distribution (PED) data. The UV-Vis spectrum was simulated using the TD-DFT technique, which is also seen empirically. The Gauge-Invariant Atomic Orbital (GIAO) approach was employed to model and study the 13C and 1H NMR spectra of the 2BCA molecule in a CDCL3 solution. The spectra were then exploited experimentally to establish their chemical shifts. To predict the donor and acceptor interaction, the NBO analysis was used. The electrostatic potential surface was employed to anticipate the locations of nucleophilic and electrophilic sites. Hirshfeld surfaces and their related fingerprint plots are exploited for the investigation of intermolecular interactions. Reduced Density Gradient (RDG) helps to measure and illustrate electron correlation effects, offering precise insights into chemical bonding, reactivity, and the electronic structure of 2BCA. According to Lipinski and Veber's drug similarity criteria, 2BCA exhibits the typical physicochemical and pharmacokinetic properties that make it a potential oral pharmaceutical candidate. According to the findings of a molecular docking study, the 2BCA molecule has promise as a treatment agent for the Nipah virus (PDB ID: 6 EB9), which causes severe respiratory and neurological symptoms in humans.

Synthesis of Thiazolidin-4-Ones Derivatives, Evaluation of Conformation in Solution, Theoretical Isomerization Reaction Paths and Discovery of Potential Biological Targets.

Thiazolin-4-ones and their derivatives represent important heterocyclic scaffolds with various applications in medicinal chemistry. For that reason, the synthesis of two 5-substituted thiazolidin-4-one derivatives was performed. Their structure assignment was conducted by NMR experiments (2D-COSY, 2D-NOESY, 2D-HSQC and 2D-HMBC) and conformational analysis was conducted through Density Functional Theory calculations and 2D-NOESY. Conformational analysis showed that these two molecules adopt exo conformation. Their global minimum structures have two double bonds (C=N, C=C) in Z conformation and the third double (C=N) in E. Our DFT results are in agreement with the 2D-NMR measurements. Furthermore, the reaction isomerization paths were studied via DFT to check the stability of the conformers. Finally, some potential targets were found through the SwissADME platform and docking experiments were performed. Both compounds bind strongly to five macromolecules (triazoloquinazolines, mglur3, Jak3, Danio rerio HDAC6 CD2, acetylcholinesterase) and via SwissADME it was found that these two molecules obey Lipinski's Rule of Five.

Neuroprotective Effect and Mechanism of Tanreqing Injection on Ischemic Stroke: Insights from Network Pharmacology and in vivo Experiments.

OBJECTIVE: To explore the neuroprotective effects and mechanism of Tanreqing Injection (TRQ) on treating ischemic stroke based on network pharmacology and in vivo experimental validation. METHODS: The chemical compounds of TRQ were retrieved based on published data, with targets retrieved from PubChem, Therapeutic Target Database and DrugBank. Network visualization and analysis were performed using Cytoscape, with protein-protein interaction networks derived from the STRING database. Enrichment analysis was performed using Kyoto Encyclopedia of Genes Genomes pathway and Gene Ontology analysis. In in vivo experiments, the middle cerebral artery occlusion (MCAO) model was used. Infarct volume was determined by 2,3,5-triphenyltetrazolium hydrochloride staining and protein expressions were analyzed by Western blot. Molecular docking was performed to predict ligand-receptor interactions. RESULTS: We screened 81 chemical compounds in TRQ and retrieved their therapeutic targets. Of the targets, 116 were therapeutic targets for stroke. The enrichment analysis showed that the apelin signaling pathway was a key pathway for ischemic stroke. Furthermore, in in vivo experiment we found that administering with intraperitoneal injection of 2.5 mL/kg TRQ every 6 h could significantly reduce the infarct volume of MCAO rats (P<0.05). In addition, protein levels of the apelin receptor (APJ)/phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) pathway were increased by TRQ (P<0.05). In addition, 41 chemical compounds in TRQ could bind to APJ. CONCLUSIONS: The neuroprotective effect of TRQ may be related to the APJ/PI3K/AKT signaling pathway. However, further studies are needed to confirm the findings.

Phytochemical analysis, physicochemical, pharmacokinetic properties and molecular docking studies of bioactive compounds in Ottelia alismoides (L.) pers. Against breast cancer proteins.

Plants provide compounds that can be used to treat diseases, and in silico methods help to expedite drug discovery while reducing costs. This study explored the phytochemical profile of methanol extract of O. alismoides using GC-MS to identify potential bioactive compounds. Autodock 4.2.6. was employed for molecular docking evaluation of the efficacy of these identified compounds against Estrogen Receptor Alpha (ERα), Human Epidermal Growth Factor Receptor 2 (HER2), and Epidermal Growth Factor Receptor (EGFR), proteins. Additionally, the ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties of the compounds were predicted using the SwissADME online tool. The preliminary phytochemical analysis revealed the presence of alkaloids, carbohydrates, glycosides, and steroids. During the GC-MS analysis, seven compounds were identified, and drug-likeness prediction of these compounds showed good pharmacokinetic properties having high gastrointestinal absorption, and orally bioavailable. The molecular docking studies exhibited promising binding affinities of bioactive compounds against all target proteins. Specifically, the compounds Tricyclo[5.2.1.0(2,6)]decan-10-ol and 2,2,6-Trichloro-7-oxabicyclo[4.1.0]heptane-1-carboxamide demonstrated the highest binding affinities with the ERα (-6.3 and - 6.0 k/cal), HER2 (-5.6 and - 6.1 k/cal), and EGFR (-5.4 and - 5.4 k/cal), respectively. These findings suggest the potential of O. alismoides as a source for developing new cancer therapeutics. The study highlights the effectiveness of in silico approaches for accelerating drug discovery from natural sources and paves the way for further exploration of these promising compounds. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00227-y.

Molecular docking of antidiabetic molecules of libas (Spondias pinnata) fruit and prediction of their pharmacokinetic properties.

Diabetes mellitus is one of the chronic metabolic disorders that affects more than 16 million Filipinos. Proper education, medical intervention, and a good lifestyle can help individuals control and manage this disease. Spondias pinnata is one of the underutilized crops in the Philippines that is well-known for its satisfactory flavor and medicinal properties, including its antidiabetic activity. The quest for a natural and effective drug to manage diseases is a continuous work in progress. Drug discovery and design is a tedious and expensive process. Computer-aided drug design guides the design and makes the process more efficient and less costly. Molecular docking was used to determine the potential antidiabetic compounds from the 48 reported compounds found in S. pinnata fruit. Seven compounds namely squalene (-9.1 kcal/mol), rutin (-9 kcal/mol), catechin (-8.7 kcal/mol), quercetin (-8.5 kcal/mol), tocopherol (-8.4 kcal/mol), myricetin (-8.4 kcal/mol), and ellagic acid (-8.3 kcal/mol) showed binding affinities comparable to those of pioglitazone, a standard drug, with peroxisome proliferator-activated receptor gamma (PPARγ). Tocopherol and catechin showed good ADMET properties. Among the two compounds, catechin passed the four filters for drug-likeness. Thus, catechin could be a potential compound for the development of antidiabetic drugs. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00230-3.

In Silico Analysis of Selective Bioactive Compounds from Acronychia Pedunculata as a Potential Inhibitor of HER2 in Colorectal Cancer.

Colorectal cancer (CRC) is a pervasive malignancy that stands as a prominent contributor to global cancer-related mortality. Among the numerous causative factors, the overexpression of human epidermal growth factor receptor 2 (HER2) is notably linked to CRC progression. Acronychia (A.) pedunculata has a longstanding history in folk medicine due to its multifaceted medicinal attributes. This study aimed to assess the potential of specific bioactive compounds derived from A. pedunculata for their inhibition of HER2 in CRC, utilizing in silico analysis. The compounds were systematically evaluated through a series of computational analyses. Drug-likeness assessment, pharmacokinetic evaluation, and toxicity analysis were conducted. Molecular docking studies were performed to investigate binding affinities with the HER2 target. Additionally, bioavailability radar analysis was employed to predict oral bioavailability, while molecular target prediction provided insights into potential protein interactions. All 12 compounds demonstrated favorable drug-likeness properties and adherence to Lipinski's rule of five, indicative of the potential for good oral bioavailability. Four compounds were found to have no toxicological endpoints. Molecular docking revealed two compounds, namely caryophylla-4 (14), 8 (15)-dien-5alpha-ol and (-)-globulol, which showed promising binding affinities between several compounds and HER2. From this study, two leads were identified from A. pedunculata. Further experimental studies are required to validate the action of leads.

5-Oxo-dihydropyranopyran derivatives as anti-proliferative agents; synthesis, biological evaluation, molecular docking, MD simulation, DFT, and in-silico pharmacokinetic studies.

A series of ethyl 2-amino-7-methyl-5-oxo-4-phenyl-4,5-dihydropyrano[4,3-b]pyran-3-carboxylate derivatives (4a-j) bearing different substitutions on the C4-phenyl ring was synthesized. The anti-proliferative activity of all the synthesized compounds was assessed against two human cancer-cell lines, including SW-480 and MCF-7, by using MTT method. Derivatives 4g, 4i, and 4j, possessing 4-NO2, 4-Cl, and 3,4,5-(OCH3)3 substitutions, were found to be the most potent compounds against both cell lines. The obtained IC50 values for 4g, 4i, and 4j were 34.6, 35.9, and 38.6 µM against SW-480 cells and 42.6, 34.2, and 26.6 µM against MCF-7 cells, respectively. Evaluation of the free radical scavenging potential of the compounds against DPPH radicals showed the highest result for compound 4j with an EC50 value of 580 µM. Molecular docking studies revealed the compounds were well accommodated within the binding site of cyclin-dependent kinase-2 (CDK2) with binding energies comparable to those of DTQ (the co-crystallized inhibitor) and BMS-265246 (a well-known CDK2 inhibitor). Molecular dynamics simulation studies confirmed the interactions and stability of the 4g-CDK2 complex. All derivatives, except 4g, were predicted to comply with the drug-likeness rules. Compound 4j may be proposed as an anti-cancer lead candidate for further studies due to the promising findings from in-silico pharmacokinetic studies, such as high GI absorption, not being a P-gp substrate, and being a P-gp inhibitor. Density functional theory (DFT) analysis was performed at the B3LYP/6-311++G (d,p) level of theory to examine the reactivity or stability descriptors of 4d, 4g, 4i, and 4j derivatives. The highest value of energy gap between HOMO and LUMO and thermochemical parameters were obtained for 4i and 4j.

New oxomethacrylate and acetamide: synthesis, characterization, and their computational approaches: molecular docking, molecular dynamics, and ADME analyses.

The compounds 2-chloro-N-(3-methoxyphenyl)acetamide (m-acetamide) and 2-(3-methoxyphenylamino)-2-oxoethyl methacrylate (3MPAEMA) were synthesized in this study for the first time in the literature. FTIR, 1H, and 13C NMR spectroscopic techniques were used to characterize it. Subsequently, computational techniques were used to assess various ADME factors, such as drug-likeness properties, bioavailability score, and adherence to Lipinski's rule. Finally, molecular docking experiments were conducted with the human topoisomerase α2 (TOP2A) protein to verify and validate the reliability and stability of the docking procedure. The results of the docking scores, which quantify binding affinity, indicated that these derivatives exhibited a stronger affinity for TOP2A.

Phthalazine Sulfonamide Derivatives as Carbonic Anhydrase Inhibitors. Synthesis, Biological and in silico Evaluation.

Carbonic Anhydrases (CAs) are a large family of zinc metalloenzymes that catalyze the reversible hydration of carbon dioxide involved in several biological processes. They show a wide diversity in tissue distribution and their subcellular localization. Twenty-two novel phthalazine derivatives were designed, synthesized, and evaluated against four human isoforms: hCA I, hCA II, hCA IX, and hCA XII. Compounds appeared to be very active mostly against hCA IX (7) and hCA I (6) isoforms being more potent than reference drug acetazolamide (AAZ). Some compounds appeared to be very selective with a selectivity index up to 13.8. Furthermore, docking was performed for some of these compounds on all isoforms to understand the possible interactions with the active site. Additionally, the most active compounds against hCA IX were subjected to cell viability assay. The anticancer activity of the compounds (3 a-d, 5 d, 5 i, and 5 m) was investigated using two human breast cancer cell lines, i. e. MCF-7 and MDA-MB-231 cells, and the normal counterpart, namely MCF10-A cells.

Unveiling the Potential of Ent-Kaurane Diterpenoids: Multifaceted Natural Products for Drug Discovery.

Natural products hold immense potential for drug discovery, yet many remain unexplored in vast libraries and databases. In an attempt to fill this gap and meet the growing demand for effective drugs, this study delves into the promising world of ent-kaurane diterpenoids, a class of natural products with huge therapeutic potential. With a dataset of 570 ent-kaurane diterpenoids obtained from the literature, we conducted an in silico analysis, evaluating their physicochemical, pharmacokinetic, and toxicological properties with a focus on their therapeutic implications. Notably, these natural compounds exhibit drug-like properties, aligning closely with those of FDA-approved drugs, indicating a high potential for drug development. The ranges of the physicochemical parameters were as follows: molecular weights-288.47 to 626.82 g/mol; number of heavy atoms-21 to 44; the number of hydrogen bond donors and acceptors-0 to 8 and 1 to 11, respectively; the number of rotatable bonds-0 to 11; fraction Csp3-0.65 to 1; and TPSA-20.23 to 189.53 Ų. Additionally, the majority of these molecules display favorable safety profiles, with only 0.70%, 1.40%, 0.70%, and 46.49% exhibiting mutagenic, tumorigenic, reproduction-enhancing, and irritant properties, respectively. Importantly, ent-kaurane diterpenoids exhibit promising biopharmaceutical properties. Their average lipophilicity is optimal for drug absorption, while over 99% are water-soluble, facilitating delivery. Further, 96.5% and 28.20% of these molecules exhibited intestinal and brain bioavailability, expanding their therapeutic reach. The predicted pharmacological activities of these compounds encompass a diverse range, including anticancer, immunosuppressant, chemoprotective, anti-hepatic, hepatoprotectant, anti-inflammation, antihyperthyroidism, and anti-hepatitis activities. This multi-targeted profile highlights ent-kaurane diterpenoids as highly promising candidates for further drug discovery endeavors.

Design, Synthesis, Computational Studies, and Anti-Proliferative Evaluation of Novel Ethacrynic Acid Derivatives Containing Nitrogen Heterocycle, Urea, and Thiourea Moieties as Anticancer Agents.

In the present work, the synthesis of new ethacrynic acid (EA) derivatives containing nitrogen heterocyclic, urea, or thiourea moieties via efficient and practical synthetic procedures was reported. The synthesised compounds were screened for their anti-proliferative activity against two different cancer cell lines, namely, HL60 (promyelocytic leukaemia) and HCT116 (human colon carcinoma). The results of the in vitro tests reveal that compounds 1-3, 10, 16(a-c), and 17 exhibit potent anti-proliferative activity against the HL60 cell line, with values of the percentage of cell viability ranging from 20 to 35% at 1 µM of the drug and IC50 values between 2.37 µM and 0.86 µM. Compounds 2 and 10 showed a very interesting anti-proliferative activity of 28 and 48% at 1 µM, respectively, against HCT116. Two PyTAP-based fluorescent EA analogues were also synthesised and tested, showing good anti-proliferative activity. A test on the drug-likeness properties in silico of all the synthetised compounds was performed in order to understand the mechanism of action of the most active compounds. A molecular docking study was conducted on two human proteins, namely, glutathione S-transferase P1-1 (pdb:2GSS) and caspase-3 (pdb:4AU8) as target enzymes. The docking results show that compounds 2 and 3 exhibit significant binding modes with these enzymes. This finding provides a potential strategy towards developing anticancer agents, and most of the synthesised and newly designed compounds show good drug-like properties.

PTSA-induced synthesis, in silico and nano study of novel ethylquinolin-thiazolo-triazole in cervical cancer.

Aim: p-Toluenesulfonic acid-(PTSA) and grinding-induced novel synthesis of ethylquinolin-thiazolo-triazole derivatives was performed using green chemistry. Materials & methods: Development of a nanoconjugate drug-delivery system of ethylquinolin-thiazolo-triazole was carried out with D-α-tocopheryl polyethylene glycol succinate (TPGS) and the formulation was further characterized by transmission electron microscopy, atomic force microscopy, dynamic light scattering and in vitro drug release assay. The effect of 3a nanoparticles was assessed against a cervical cancer cell line (HeLa) through the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, and the effect on apoptosis was determined. Results & discussion: The 3a nanoparticles triggered the apoptotic mode of cell death after increasing the intracellular reactive oxygen level by enhancing cellular uptake of micelles. Furthermore, in silico studies revealed higher absorption, distribution, metabolism, elimination and toxicity properties and bioavailability of the enzyme tyrosine protein kinase. Conclusion: The 3a nanoparticles enhanced the therapeutic potential and have higher potential for targeted drug delivery against cervical cancer.

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.

Synthesis, spectroscopic analysis, and computational-based investigations on 'azo-coumarin-Co(II)-galangin' hybrids exhibit multipotential activities.

The present study synthesized a series of cobalt (II) metal ion frame hybrid candidates (6a-6f) bearing phyto-flavonol galangin with substituted aryl diazenyl coumarins, and further structural confirmation was validated by various spectral techniques, including NMR, ATR-FTIR, UV-vis, HPLC, XRD, etc. Therapeutic potency was investigated via PASS (prediction of activity spectra for substances), molecular docking, molecular dynamics simulation, prediction of toxicity, pharmacokinetics, and drug-likeness scores, along with the highest occupied molecular orbital (HOMO), the lowest unoccupied molecular orbital (LUMO), with their energy gaps (ΔEH-L) to locate the most potential therapeutic candidates. The PASS prediction (Pa > Pi score) showed that proposed metal complexes have kinase inhibitors, antioxidative, and antischistosomal activities with potential molecular docking scores (> -7 kcal/mol) against selected targeted enzymes. Further, the MD-simulation (RMSD, RMSF, Rg, and H-bonds) of the most potential docking complex, 'HER2-6d', showed a minimum deviation similar to the standard drug (lapatinib) at 100 ns, indicating that 6d could be a potential noncovalent anticancer inhibitor. In addition, metal complexes possess a non-toxic and ideal drug-ability profiles, and positive electron space in an excited state increases the binding affinity towards target enzymes. Among all six ligands, 6c and 6d were the two most multipotent therapeutic agents from the above analyses. In summary, this could be a feasible approach towards the utilization of phytochemicals in mainstream therapeutic applications, where bioinformatics tools help to select a lead drug candidate at an early stage and guide for higher experimental success by proceeding with potential candidates.Communicated by Ramaswamy H. Sarma.

2,3-Dichloronaphthoquinone derivatives: Synthesis, antimicrobial activity, molecular modelling and ADMET studies.

In the present study, an intermediate namely 2-(3-bromopropylamino)-3-chloronaphthalene-1,4-dione was initially synthesized via the nucleophilic addition-elimination reaction between 2,3-dichloro-1,4-naphthoquinone and 3-bromo-1-aminopropane. Then a coupling reaction between the intermediate and piperazine derivatives yielded a number of 1,4-naphthoquinone derivatives. Spectroscopic analysis successfully characterized the products that were obtained in good yields. In vitro antibacterial properties of the compounds were examined against different bacterial strains. In vitro antibacterial properties of the compounds were examined against the bacterial strains S. Aureus, E. Faecalis, E. Coli and P. Aeruginosa. While compound 9 was found to be effective against all bacterial strains used, compound 12 was active against three strains and compounds 10 and 11 were effective against the two. None of the compounds are effective against C. albicans strain. In silico molecular docking studies revealed that all compounds had docking scores comparable to the antibacterial drugs ciprofloxacin and gentamicin and might be considered as DNA gyrase B inhibitors. Molecular dynamics simulations were also conducted for a better understanding of the stability and the selected docked complexes. Additionally, the drug similarity of the synthesized compounds and ADMET characteristics were examined in conjunction with the antibiotic ciprofloxacin, and drug potentials were then evaluated. Compatible predictions were found with the drug similarity and ADMET parameters.

Harnessing Brazilian biodiversity database: identification of flavonoids as potential inhibitors of SARS-CoV-2 main protease using computational approaches and all-atom molecular dynamics simulation.

SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is the etiological agent responsible for the global outbreak of COVID-19 (Coronavirus Disease 2019). The main protease of SARS-CoV-2, Mpro, is a key enzyme that plays a vital role in mediating viral replication and transcription. In this study, a comprehensive computational approach was employed to investigate the binding affinity, selectivity, and stability of natural product candidates as potential new antivirals acting on the viral polyprotein processing mediated by SARS-CoV-2 Mpro. A library of 288 flavonoids extracted from Brazilian biodiversity was screened to select potential Mpro inhibitors. An initial filter based on Lipinski's rule of five was applied, and 204 compounds that did not violate any of the Lipinski rules were selected. The compounds were then docked into the active site of Mpro using the GOLD program, and the poses were subsequently re-scored using MM-GBSA (Molecular Mechanics Generalized Born Surface Area) binding free energy calculations performed by AmberTools23. The top five flavonoids with the best MM-GBSA binding free energy values were selected for analysis of their interactions with the active site residues of the protein. Next, we conducted a toxicity and drug-likeness analysis, and non-toxic compounds were subjected to molecular dynamics simulation and free energy calculation using the MM-PBSA (Molecular Mechanics Poisson-Boltzmann Surface Area) method. It was observed that the five selected flavonoids had lower MM-GBSA binding free energy with Mpro than the co-crystal ligand. Furthermore, these compounds also formed hydrogen bonds with two important residues, Cys145 and Glu166, in the active site of Mpro. Two compounds that passed the drug-likeness filter showed stable conformations during the molecular dynamics simulations. Among these, NuBBE_867 exhibited the best MM-PBSA binding free energy value compared to the crystallographic inhibitor. Therefore, this study suggests that NuBBE_867 could be a potential inhibitor against the main protease of SARS-CoV-2 and may be further examined to confirm our results.

De Novo Drug Design Using Transformer-Based Machine Translation and Reinforcement Learning of an Adaptive Monte Carlo Tree Search.

The discovery of novel therapeutic compounds through de novo drug design represents a critical challenge in the field of pharmaceutical research. Traditional drug discovery approaches are often resource intensive and time consuming, leading researchers to explore innovative methods that harness the power of deep learning and reinforcement learning techniques. Here, we introduce a novel drug design approach called drugAI that leverages the Encoder-Decoder Transformer architecture in tandem with Reinforcement Learning via a Monte Carlo Tree Search (RL-MCTS) to expedite the process of drug discovery while ensuring the production of valid small molecules with drug-like characteristics and strong binding affinities towards their targets. We successfully integrated the Encoder-Decoder Transformer architecture, which generates molecular structures (drugs) from scratch with the RL-MCTS, serving as a reinforcement learning framework. The RL-MCTS combines the exploitation and exploration capabilities of a Monte Carlo Tree Search with the machine translation of a transformer-based Encoder-Decoder model. This dynamic approach allows the model to iteratively refine its drug candidate generation process, ensuring that the generated molecules adhere to essential physicochemical and biological constraints and effectively bind to their targets. The results from drugAI showcase the effectiveness of the proposed approach across various benchmark datasets, demonstrating a significant improvement in both the validity and drug-likeness of the generated compounds, compared to two existing benchmark methods. Moreover, drugAI ensures that the generated molecules exhibit strong binding affinities to their respective targets. In summary, this research highlights the real-world applications of drugAI in drug discovery pipelines, potentially accelerating the identification of promising drug candidates for a wide range of diseases.

Identification of dual-target isoxazolidine-isatin hybrids with antidiabetic potential: Design, synthesis, in vitro and multiscale molecular modeling approaches.

In the development of novel antidiabetic agents, a novel series of isoxazolidine-isatin hybrids were designed, synthesized, and evaluated as dual α-amylase and α-glucosidase inhibitors. The precise structures of the synthesized scaffolds were characterized using different spectroscopic techniques and elemental analysis. The obtained results were compared to those of the reference drug, acarbose (IC50 = 296.6 ± 0.825 µM for α-amylase & IC50 = 780.4 ± 0.346 µM for α-glucosidase). Among the title compounds, 5d exhibited impressive α-amylase and α-glucosidase inhibitory activity with IC50 values of 30.39 ± 1.52 µM and 65.1 ± 3.11 µM, respectively, followed by 5h (IC50 = 46.65 ± 2.3 µM; IC50 = 85.16 ± 4.25 µM) and 5f (IC50 = 55.71 ± 2.78 µM; IC50 = 106.77 ± 5.31 µM). Mechanistic studies revealed that the most potent derivative 5d bearing the chloro substituent attached to the oxoindolin-3-ylidene core, and acarbose, are a competitive inhibitors of α-amylase and α-glucosidase, respectively. Structure activity relationship (SAR) was examined to guide further structural optimization of the most appropriate substituent(s). Moreover, drug-likeness qualities and ADMET prediction of the most active analogue, 5d was also performed. Subsequently, 5d was subjected to molecular docking and dynamic simulation during the progression of 120 ns analysis to check the essential ligand-receptor patterns, and to estimate its stability. In silico studies were found in good agreement with the in vitro enzymatic inhibitions results. In conclusion, we demonstrated that most potent compound 5d could be exploited as dual potential inhibitor of α-amylase and α-glucosidase for possible management of diabetes.