Binding Affinity Values Research Articles

Development of Potent SARS-CoV 3CL Protease Inhibitors: In silico Analogues Designing of Darunavir, Molecular Modelling and Molecular Dynamic Simulation

COVID pandemic initiated in early 2019 and the origin from where it initiated was Wuhan city of China. It changed the whole world. A huge population died due to COVID-19 in spite of taking precautions. New treatments and vaccines are introduced for the treatment and prevention. Among successful treatments, antivirals were found effective against COVID-19. But there is a need to find derivatives, which could be more effective for the treatment of COVID-19. The current research is focused on computational studies on one of the antiviral, darunavir. A computational strategy, molecular docking and molecular dynamic simulation techniques is presented to discover the potent analogues of darunavir for inhibiting protease 3CLpro of SARS-CoV2. The newly discovered X-ray structure (PDB ID: 6LU7) was selected for docking study and generated analogues were docked. The docking results showed that the compounds were bound in the active site of receptor with good binding affinity. It was concluded that compounds D8 and D15 were have good binding affinity value of -9.85 and -8.95 kcal/mol, respectively and these compounds were selected for molecular dynamic simulation (MDS) study to check their stability in pocket of receptor.

In silico Study on the Promising Active Components of Terpenoid and Fucoidon from Sargassum sp. in Inhibiting CGRP and TNF-α

Introduction: The new discovery of the active substance in Sargassum sp marks the new era for drug industry as it is very effective as the new migraine medication compared to analgesics which have already been popular previously in treating migraine. By using the in silico methods, this study intended to identify the preventive effect of the active substance in Sargassum sp within the stage of pain and inflammation development in migraine. In migraine pathophysiology, the clinical findings would build and verify the role of CGRP and TNF-α. Methods: This research applied a one-shot experimental study and by employing the potential test through PubChem (https://pubchem.ncbi.nlm.nih.gov/), the result of this study proved that tannins, terpenoids and fucoidone were contained in the active substance of Sargassum sp leading to the possession of potential as the drug to treat migraine. Results: Terpenoids and tannin binding affinity value is higher than other substances. Terpenoids and fucoidon had similar amino acid residues with controls. Seaweed metabolites have great potential as inhibitors of CGRP and TNF-α because the binding affinity score is close to control. Conclusion: The active substance in Sargassum sp has an inhibitory effect on the occurrence of CGRP and TNF-α in migraine based on in silico studies.

In-silico study of some natural plant phyto-compounds for the identification of novel potent cholinesterase inhibitors against Alzheimer's Disease

The main aim of this study is to identify inhibitory binding potent of the available commercially alkaloids, against the crystal structure of acetylcholinesterase (AChE) protein by in silico studies. The inhibitory data of the compounds should be compared with the internal ligand as well as standard AChE inhibitor Aricept (which is used for the treatment of all stages of Alzheimer’s disease). AutoDock 4.0 is used for the docking study, conformational orientation site analysis, and, with the help of docking, we have calculated parameters like binding energy and inhibition constant. Docking's study showed that Glabridin, Isorosmanol, Quercetin, Honokiol, Eckol, Sargaquinoic acid, and Ginsedosides revealed strong binding affinity with the enzyme. Moreover, The ADMET profiling and physicochemical properties of the selected compounds are evaluated using the Molinspiration and Data warrior software. By showing a strong binding affinity value, positive bioactivity score, and good pharmacokinetic properties, the top compound was determined. After evaluation with all parameters, the compound Glabridin and Ginsedosides show the most potent inhibitory effect towards the acetylcholinesterase, so this compound could be used as a novel is required to treat Alzheimer's disease.

Virtual Screening, Docking, ADMET and Molecular Dynamics: A Study to Find Novel Inhibitors of Mycobacterium tuberculosis Targeting QcrB

Abstract: A major difficulty in the treatment of mycobacterial infection is its resistance against anti-mycobacterial drugs. Exploration of diverse targets, the search for novel chemical scaffolds and different methods of tuberculosis treatment are all basic measures needed in this perspective. In the same context, mycobacterial oxidative phosphorylation has received a lot of interest. It includes the electron transport system, which encompasses the cytochrome B component of the cytochrome bc1 complex (QcrB) which is a promising therapeutic target. The anti-tubercular drug Q203 (Telacebec), which is currently in phase 2 clinical trial, inhibits cytochrome B. The present study includes virtual screening studies from the ‘Zinc15’ chemical database, taking Q203 as a reference molecule, the creation of protein using homology modeling, molecular docking as well as simulation studies. The constructed protein showed considerable reliability, as results of the Ramachandran plot showed 92.8% amino acid residues in the favoured region, ERRAT score (overall quality factor) of 92.48% with ProSA (Z score) of –5.78. The hit molecules identified by structure-based virtual screening follow the Lipinski rule of five. The docking results indicated binding affinity values ranging from –7.19 to –9.10 kcal/mol. The top three compounds were ZINC64033452, ZINC3816287 and ZINC3830215, each having a higher docking score than the reference ligand (–7.70 kcal/mol). Leu174, Pro306, Ser304, Leu180, Glu314 and Thr313 are among the residues that cover the protein’s active site. The H-bond was observed in docking studies for Q203 and top three molecules from amino acid residues Glu314 and Thr313 and was consistent throughout dynamics studies. In a dynamics run of 20 ns, a stable RMSD was found after 8 ns for hit-molecules and Q203. Based on potential findings, we report that selected candidates are more likely to be used as anti-mycobacterial agents or as starting leads for the development of novel and potent anti-tubercular agents.

Antioxidant Potency of Cassumunin A-C Compounds from Bangle Rhizome (Zingiber cassumunar) by Molecular Docking on Human ROS-1 kinase Receptors

<p>Antioxidants play an role in human health by fighting oxidative stress and preventing chronic disease. Nowadays, molecular docking is used Bangle rhizome (<em>Zingiber cassumunar</em>) has a derivative of curcuminoid, cassumunin A, cassumunin B, and cassumunin C. This study was designed to determine the value of binding affinities between cassumunins ligands on human ROS1 kinase receptors, related to their antioxidant activity with ascorbic acid and tocopherol. One set of computational programs is Autodock Tools, Biovia Discovery Studio, and Command Prompt has prepared. These docking results presented the binding affinity values of cassumunin A, cassumunin B, cassumunin C, ascorbic acid, and tocopherol were -9.4 kcal/mol, -9.7 kcal/mol, -9.0 kcal/mol, -5.2 kcal/mol, and -8.1 kcal/mol respectively. RMSD value for the five ligands was ≤ 2Å, showed the validity of the docking results. Cassumunin A-C compound higher affinity compared to ascorbic acid and tocopherol. Based on this computational study, cassumunin A-C the potential compounds to be developed as potent antioxidant agents from natural resources.</p>

Synthesis, antibacterial and antioxidant activities of Thiazole-based Schiff base derivatives: a combined experimental and computational study

BackgroundThiazole-based Schiff base compounds display significant pharmacological potential with an ability to modulate the activity of many enzymes involved in metabolism. They also demonstrated to have antibacterial, antifungal, anti-inflammatory, antioxidant, and antiproliferative activities. In this work, conventional and green approaches using ZnO nanoparticles as catalyst were used to synthesize thiazole-based Schiff base compounds.ResultsAmong the synthesized compounds, 11 showed good activities towards Gram-negative E. coli (14.40 ± 0.04), and Gram-positive S. aureus (15.00 ± 0.01 mm), respectively, at 200 μg/mL compared to amoxicillin (18.00 ± 0.01 mm and 17.00 ± 0.04). Compounds 7 and 9 displayed better DPPH radical scavenging potency with IC50 values of 3.6 and 3.65 μg/mL, respectively, compared to ascorbic acid (3.91 μg/mL). The binding affinity of the synthesized compounds against DNA gyrase B is within − 7.5 to − 6.0 kcal/mol, compared to amoxicillin (− 6.1 kcal/mol). The highest binding affinity was achieved for compounds 9 and 11 (− 6.9, and − 7.5 kcal/mol, respectively). Compounds 7 and 9 displayed the binding affinity values of − 5.3 to − 5.2 kcal/mol, respectively, against human peroxiredoxin 5. These values are higher than that of ascorbic acid (− 4.9 kcal/mol), in good agreement with the experimental findings. In silico cytotoxicity predictions showed that the synthesized compounds Lethal Dose (LD50) value are class three (50 ≤ LD50 ≤ 300), indicating that the compounds could be categorized under toxic class. Density functional theory calculations showed that the synthesized compounds have small band gap energies ranging from 1.795 to 2.242 eV, demonstrating that the compounds have good reactivities.ConclusionsThe synthesized compounds showed moderate to high antibacterial and antioxidant activities. The in vitro antibacterial activity and molecular docking analysis showed that compound 11 is a promising antibacterial therapeutics agent against E. coli, whereas compounds 7 and 9 were found to be promising antioxidant agents. Moreover, the green synthesis approach using ZnO nanoparticles as catalyst was found to be a very efficient method to synthesize biologically active compounds compared to the conventional method.

Combined deep learning and molecular docking simulations approach identifies potentially effective FDA approved drugs for repurposing against SARS-CoV-2

The ongoing pandemic of Coronavirus Disease 2019 (COVID-19) has posed a serious threat to global public health. Drug repurposing is a time-efficient approach to finding effective drugs against SARS-CoV-2 in this emergency. Here, we present a robust experimental design combining deep learning with molecular docking experiments to identify the most promising candidates from the list of FDA-approved drugs that can be repurposed to treat COVID-19. We have employed a deep learning-based Drug Target Interaction (DTI) model, called DeepDTA, with few improvements to predict drug-protein binding affinities, represented as KIBA scores, for 2440 FDA-approved and 8168 investigational drugs against 24 SARS-CoV-2 viral proteins. FDA-approved drugs with the highest KIBA scores were selected for molecular docking simulations. We ran around 50,000 docking simulations for 168 selected drugs against 285 total predicted and/or experimentally proven active sites of all 24 SARS-CoV-2 viral proteins. A list of 49 most promising FDA-approved drugs with the best consensus KIBA scores and binding affinity values against selected SARS-CoV-2 viral proteins was generated. Most importantly, 16 drugs including anidulafungin, velpatasvir, glecaprevir, rifapentine, flavin adenine dinucleotide (FAD), terlipressin, and selinexor demonstrated the highest predicted inhibitory potential against key SARS-CoV-2 viral proteins. We further measured the inhibitory activity of 5 compounds (rifapentine, velpatasvir, glecaprevir, anidulafungin, and FAD disodium) on SARS-CoV-2 PLpro using Ubiquitin-Rhodamine 110 Gly fluorescent intensity assay. The highest inhibition of PLpro activity was seen with rifapentine (IC50: 15.18 μM) and FAD disodium (IC50: 12.39 μM), the drugs with high predicted KIBA scores and binding affinities.

Investigation of the electronic properties of solvents (water, benzene, methanol) using IEFPCM model, spectroscopic investigation with docking and MD simulations of a thiadiazole derivative with anti-tumor activities

6-(4-Chlorophenyl)-3-(thiophen-2-yl)-[1,2,4]triazolo[3,4-b][1,3,4]-thiadiazole (CLP) was synthesized and spectroscopic investigations have been made experimentally and theoretically. The electrostatic potential maps showed the reactive sites in CLP compound and its halogenated derivatives. The various chemical descriptors and NLO properties are predicted and compared for CLP with its halogenated derivatives. The stability of CLP was studied with NBO analysis. For diverse solvents (water, benzene, and methanol) and gas phase, UV–vis spectra are being used to assess the electronic transition. Binding affinities with target protein were carried out which gave the effects of bio-efficiency due to the halogen substitution. The binding affinity values were increasing from that of the parent molecule and are high for meta substitutions (with chlorine positional changes). The MD simulations and docking studies suggested inhibitory activity against CDK2 and could be considered as anticancer candidates.

TSSF-hERG: A machine-learning-based hERG potassium channel-specific scoring function for chemical cardiotoxicity prediction

The human ether-à-go-go-related gene (hERG) encodes the Kv11.1 voltage-gated potassium ion (K+) channel that conducts the rapidly activating delayed rectifier current (IKr) in cardiomyocytes to regulate the repolarization process. Some drugs, as blockers of hERG potassium channels, cannot be marketed due to prolonged QT intervals, as well known as cardiotoxicity. Predetermining the binding affinity values between drugs and hERG through in silico methods can greatly reduce the time and cost required for experimental verification. In this study, we collected 9,215 compounds with AutoDock Vina’s docking structures as training set, and collected compounds from four references as test sets. A series of models for predicting the binding affinities of hERG blockers were built based on five machine learning algorithms and combinations of interaction features and ligand features. The model built by support vector regression (SVR) using the combination of all features achieved the best performance on both tenfold cross-validation and external verification, which was selected and named as TSSF-hERG (target-specific scoring function for hERG). TSSF-hERG is more accurate than the classic scoring function of AutoDock Vina and the machine-learning-based generic scoring function RF-Score, with a Pearson’s correlation coefficient (Rp) of 0.765, a Spearman’s rank correlation coefficient (Rs) of 0.757, a root-mean-square error (RMSE) of 0.585 in a tenfold cross-validation study. All results demonstrated that TSSF-hERG would be useful for improving the power of binding affinity prediction between hERG and compounds, which can be further used for prediction or virtual screening of the hERG-related cardiotoxicity of drug candidates.

Identification of Potent Natural Resource Small Molecule Inhibitor to Control Vibrio cholera by Targeting Its Outer Membrane Protein U: An In Silico Approach.

Vibrio cholerae causes the diarrheal disease cholera which affects millions of people globally. The outer membrane protein U (OmpU) is the outer membrane protein that is most prevalent in V. cholerae and has already been recognized as a critical component of pathogenicity involved in host cell contact and as being necessary for the survival of pathogenic V. cholerae in the host body. Computational approaches were used in this study to screen a total of 37,709 natural compounds from the traditional Chinese medicine (TCM) database against the active site of OmpU. Following a sequential screening of the TCM database, we report three lead compounds—ZINC06494587, ZINC85510056, and ZINC95910434—that bind strongly to OmpU, with binding affinity values of −8.92, −8.12, and −8.78 kcal/mol, which were higher than the control ligand (−7.0 kcal/mol). To optimize the interaction, several 100 ns molecular dynamics simulations were performed, and the resulting complexes were shown to be stable in their vicinity. Additionally, these compounds were predicted to have good drug-like properties based on physicochemical properties and ADMET assessments. This study suggests that further research be conducted on these compounds to determine their potential use as cholera disease treatment.

In Silico Identification and Validation of Organic Triazole Based Ligands as Potential Inhibitory Drug Compounds of SARS-CoV-2 Main Protease.

The SARS-CoV-2 virus is highly contagious to humans and has caused a pandemic of global proportions. Despite worldwide research efforts, efficient targeted therapies against the virus are still lacking. With the ready availability of the macromolecular structures of coronavirus and its known variants, the search for anti-SARS-CoV-2 therapeutics through in silico analysis has become a highly promising field of research. In this study, we investigate the inhibiting potentialities of triazole-based compounds against the SARS-CoV-2 main protease (Mpro). The SARS-CoV-2 main protease (Mpro) is known to play a prominent role in the processing of polyproteins that are translated from the viral RNA. Compounds were pre-screened from 171 candidates (collected from the DrugBank database). The results showed that four candidates (Bemcentinib, Bisoctrizole, PYIITM, and NIPFC) had high binding affinity values and had the potential to interrupt the main protease (Mpro) activities of the SARS-CoV-2 virus. The pharmacokinetic parameters of these candidates were assessed and through molecular dynamic (MD) simulation their stability, interaction, and conformation were analyzed. In summary, this study identified the most suitable compounds for targeting Mpro, and we recommend using these compounds as potential drug molecules against SARS-CoV-2 after follow up studies.

Synthesis, crystal structure, Hirshfeld surface analysis, spectral characterizations and quantum computational assessments of 1‑hydroxy-3-methyl-11H-pyrido[2,1-b] quinazolin-11-one

In this manuscript, a newly synthesized 1‑hydroxy-3-methyl-11H-pyrido[2,1-b] quinazolin-11-one molecule was analyzed in details for structural clarification by X-Ray crystallographic and FT-IR spectral data along with theoretical quantum chemical computations. The theoretical computations were performed by DFT/B3LYP method and 6–311++G(d,p) basis set in gas phase, and Potential Energy Distribution (PED) analysis of the DFT/B3LYP calculated IR spectrum of the compound was carried out by VEDA4 program. Hirshfeld surface analysis of the compound was performed to determine the most important contributions for the crystal packing. The 1H- and 13C- NMR chemical shift analyses were theoretically and experimentally studied for the compound. The existence of the n(O)→σ*(OH) hyperconjugative interaction resulted from the intra-molecular OH···O hydrogen bonding in the title compound were analyzed with NBO (Natural Bond Orbital) study. Additionally, the highest occupied molecular orbital (HOMO) - the lowest unoccupied molecular orbital (LUMO), the molecular electrostatic potential (MEP) and the non-linear optic values for the compound were found. Finally, the molecular docking study between the compound and macromolecule PDB:1EVE was done, and from the binding affinity value and the presence of inter-molecular interactions it was concluded that the title ligand compound may serve as a smart drug with nootropic property.

Solid-state and solution characterizations of [(TMPA)Cu(II)(SO3)] and [(TMPA)Cu(II)(S2O3)] complexes: Application to sulfite and thiosulfate fast detection

Sulfite (SO32−) and thiosulfate (S2O32−) ions are used as food preservative and antichlor agent respectively. To detect low levels of such anions we used Cu(II) complex of the Tris-Methyl Pyridine Amine (TMPA) ligand, denoted L. Formation of [LCu(SO3)] (1) and [LCu(S2O3)] (2) in solution were monitored using UV–Vis, EPR and cyclic voltammetry, while the solid-state X-ray structures of both complexes were solved. In addition, we also evaluated the pH range in which the complexes are stable, and the anions binding affinity values for the [LCu(solvent)]2+ (3) parent complex. As a matter of illustration, we determined the sulfite content in a commercial crystal sugar.

Characterization of green synthesis, in silico docking and biological activity studies of N, N′-BIS (3-aminopropyl) piperazine derivatives

Novel bioactive piperazine derivatives are synthesised and charecterised by IR, NMR, UV, and elemental analysis techniques. The biological activity of the synthesised materials is investigated by using In vitro and docking experiments. The novel imines were prepared in quantitative yield using the microwave technique. The compound 2a and 3a are charecterised IR, NMR, UV, and elemental analysis techniques and confirm the formation of the desired product. The antimicrobial activity of the synthesised compounds showed excellent activity with compound 2a and 3a having the highest activity of about 6 µg/ml against Enterococcus Faecalis and Pseudomonas aeruginosa, respectively. The antioxidant properties of the synthesised compounds were investigated and the compound 2a has the smallest LC50 value (9 µg/ml). In silico docking of the BRCA1 protein in breast cancer cells confirmed an excellent binding affinity value of −7.10 kcal/mol. Similarly, invitro anticancer analysis on the MDA MB-231 breast cancer cell line indicate that the drug-treated cells have a uniform structure with few abnormalities.

Study of novel bioactive n, n'-bis (3-aminopropyl) piperazine derivatives: Green synthesis, spectral characterization, in silico docking and biological activity

Bioactive properties of piperazine derivatives are well known for its biological applications. In general, synthesis of bioactive compound is laborious and time consuming process. In the present investigation, the Microwave was used to synthesise two imines compounds using piperazine and various aldehydes in a quantitative yield. IR, NMR, UV, and elemental analysis techniques were used to characterise the compound 2a and 3a. In vitro method and docking experiments were used to investigate biological activities novel piperazines compounds. The antimicrobial activity of the synthesised compounds showed better results against Pseudomonas aeruginosa, with a MIC of 11.9 µg/ml. The antioxidant properties of the synthesised compounds were found to be high with the compound 2a has the smallest LC50 value (15 µg/ml). In silico docking of the BRCA1 protein in breast cancer cells confirmed an excellent binding affinity value of −7.10 kcal/mol. The findings of the anticancer analysis on the MDA MB-231 breast cancer cell line indicate that the drug-treated cells have a uniform structure with few abnormalities. Therefore, the synthesised compounds can be used in different biological applications.

Synthesis, crystal structure, DFT, docking and biological activity studies of (NZ,N’Z)-3,3’-(piperazine-1,4-diyl)bis(N-(-4-methyl benzylidene)propane-1-amine)

The title compound (NZ,N’Z)-3,3’-(piperazine-1,4-diyl)bis(N-(-4-methyl benzylidene)propane-1-amine) (PMP) was synthesized by reacting N,N′-bis(3-aminopropyl)piperazine and 4- methyl benzaldehyde using microwave energy. The formed compound is characterized using FTIR, 1H and 13C NMR, UV–visible and elemental analysis techniques. Single crystal X-ray diffraction confirms that the title compound crystallizes in a monoclinic crystal system with space group of P21/c. The unusual C–H…π interaction facilitate the crystal packing proved by the Density Functional Theory (DFT) and Hirshfeld surface analysis. The PMP showed an excellent result against Enterococcus Faecalis with the value of 3.125 μg/ml. The antioxidant behavior of PMP showed strong antioxidant property. The in silico docking studies on breast cancer cell BRCA1 protein confirms that the PMP showed excellent binding affinity value of −6.80 kcal/mol. The lipophilicity of the molecule is high due to the non polar nature of the PMP. The in vitro anticancer studies on the breast cancer cell line MDA MB-231 showed promising results.

Organomagnesium Crown Ethers and Their Binding Affinities with Li+, Na+, K+, Be2+, Mg2+, and Ca2+ Ions – A Theoretical Study

AbstractNovel organomagnesium crown ether molecules have been computationally characterized using density functional theory (DFT). Monomer units of MgC6 are used as building blocks. Isomers of MgC6H2 have been extensively explored using both DFT and coupled‐cluster methods in the past by some of us. It had been concluded that the seven‐membered ring isomer, 1‐magnesacyclohept‐4‐en‐2,6‐diyne, was the thermodynamically most stable molecule at all levels. Thus, the latter has been used as the building block for designing new organomagnesium crown ethers. Both alkali (Li+, Na+, and K+) and alkaline‐earth (Be2+, Mg2+, and Ca2+) metal ions selective complexes have been theoretically identified. Theoretical binding energies (▵E at 0 K) and thermally corrected Gibbs free energies (▵G at 298.15 K) have been computed for these molecules with MgC6‐6‐crown‐2, MgC6‐9‐crown‐3, and MgC6‐12‐crown‐4 hosts. Higher binding affinity values obtained for Be2+ indicate that these new crown ether molecules could effectively be used for Be2+ encapsulation.

Drug-target continuous binding affinity prediction using multiple sources of information

Drug-target binding affinity prediction has a significant role in the search for new drugs or novel targets for existing drugs. The vast majority of recent computational approaches, presented for the task of drug-target binding affinity prediction, make use of a single source to measure drug-drug or protein-protein similarities. Incorporating various information sources is of the essence for improving the accuracy of drug-target prediction. The main objective of this research is to propose a method for combining the information provided from various similarity measures for drug-drug and protein-protein similarities and to show that this leads to better prediction performance. For this purpose, we propose a method that makes use of five drug-drug and five protein-protein similarity measures simultaneously to predict the binding affinity value of an input query drug-protein interaction. In the proposed method, using each pair of drug-drug and protein-protein similarity measures, k-nearest neighbor algorithm is used to find k drug-protein pairs most similar to the input interaction. The information regarding the binding affinity values of neighbors and their similarities are fed as features to a gradient boosting machine to construct the regression model. To assess the performance of our method in comparison with state-of-the-art methods in the literature, three related benchmark datasets were used. The experimental results in various settings (pairwise, new drug, and new target scenarios) indicate the superiority of the proposed method in comparison with other methods proposed in the literature.

Effect of Organosulfur Compounds from Different Garlic Preparations on Hyperlipidemia: An in-silico Approach

Garlic is one of the most well-known medicinal plants in terms of hypolipidemic activities. Its organosulfur compounds (OSCs) are probably one of the major groups of potentially active compounds for treating hyperlipidemia. However, the hypolipidemic activities of many garlic OCSs have not been investigated. This study was conducted to predict the potential of garlic OSCs to interact with hyperlipidemia targets and to evaluate their pharmacokinetic properties. 25 OSCs were selected to interact with four major targets of hyperlipidemia named pancreatic lipase, HMG-CoA reductase, PPAR-α, and NPC1L1 using the AutoDock Vina program. The pharmacokinetic properties of OSCs were also evaluated by the SwissADME website. The best binding affinity values were obtained for γ-glutamyl-S-alk(en)ylcysteines. Other OSCs, such as S-alk(en)ylcysteine sulfoxides and ajoenes, presented a moderate to high affinity for the studied targets. However, in-silico evaluation of pharmacokinetic properties showed that γ-glutamyl-S-alk(en)ylcysteines have low absorption. The results displayed that γ-glutamyl-S-alk(en)ylcysteines can potentially be considered antihyperlipidemic agents mainly influencing the intestinal lumen. Therefore, it seems that fresh whole garlic, thermal dehydrated garlic, and freeze-dried garlic products are probably more potent antihyperlipidemic agents due to their higher levels of γ-glutamyl-S-alk(en)ylcysteines.

In silico studies of isatinyl-2-aminobenzoylhydrazone transition metal complexes against cyclin-dependent kinase 6 (CDK6)

Cyclin-dependent kinase 6 (CDK6) is an important member of protein kinases, involving in many cellular pathways especialy cell cycle progression. Thus, CDK6 is a promising target in cancer therapy. This report aims to predict inhibiton of CDK6 by some complex compounds by using molecular docking and pharmacological properties analysis. Those compounds are isatinyl-2-aminobenzoylhydrazone (ISABH) and cobalt (II), nickel (II), copper (II), and zinc (II) transition metal complexes. The molecular docking against CDK6 (PDB code: 3NUP) revealed that ISABH/ISABH-transition metal complexes established ligand-protein interaction as expressed by negative binding affinity values. Drug-likeness by SwissADME indicated that ISABH and Ni-ISABH met the Lipinski’s rule of five. Both compounds also showed reasonable pharmacological criteria by admetSAR.