Identification of potential AChE inhibitors through combined machine-learning and structure-based design approaches-Supplementary data

Alzheimer’s disease (AD) is an irreversible, progressive neurodegenerative disease characterised by dementia.The depletion of acetylcholine (ACh) is involved the synaptic cleft is responsible for dementia due to neuronal loss. The acetylcholinesterase (AChE) enzyme isinvolved in the hydrolytic degradation of ACh and its inhibition is therapeutically beneficial for the treatment in memory loss.The use of machine learning (ML) for the identification of enzyme inhibitors has recently become popular. It identifies important patterns in the reported inhibitors to predict the new molecules. Hence, in this study, a set of support vector classifier-based ML models were developed,validated and employed to predict AChE inhibitors. Further, 247 predicted compounds obtained through PAINS and molecular property filters were docked on the AChE enzyme. The docking study identified compounds AAM132011183, ART21232619 and LMG16204648 as AChE inhibitors with suitable ADME properties. The selected compounds produced stable interactions with enzymes in molecular dynamics studies. The novel inhibitors obtained from the study may be proposed as active leads for AChE inhibition.

Identification of potential AChE inhibitors through combined machine-learning and structure-based design approaches-Supplementary data

Alzheimer’s disease (AD) is an irreversible, progressive neurodegenerative disease characterised by dementia.The depletion of acetylcholine (ACh) is involved the synaptic cleft is responsible for dementia due to neuronal loss. The acetylcholinesterase (AChE) enzyme isinvolved in the hydrolytic degradation of ACh and its inhibition is therapeutically beneficial for the treatment in memory loss.The use of machine learning (ML) for the identification of enzyme inhibitors has recently become popular. It identifies important patterns in the reported inhibitors to predict the new molecules. Hence, in this study, a set of support vector classifier-based ML models were developed,validated and employed to predict AChE inhibitors. Further, 247 predicted compounds obtained through PAINS and molecular property filters were docked on the AChE enzyme. The docking study identified compounds AAM132011183, ART21232619 and LMG16204648 as AChE inhibitors with suitable ADME properties. The selected compounds produced stable interactions with enzymes in molecular dynamics studies. The novel inhibitors obtained from the study may be proposed as active leads for AChE inhibition.

Identification of potential AChE inhibitors through combined machine-learning and structure-based design approaches

Alzheimer’s disease (AD) is an irreversible, progressive neurodegenerative disease characterised by dementia.The depletion of acetylcholine (ACh) is involved the synaptic cleft is responsible for dementia due to neuronal loss. The acetylcholinesterase (AChE) enzyme isinvolved in the hydrolytic degradation of ACh and its inhibition is therapeutically beneficial for the treatment in memory loss.The use of machine learning (ML) for the identification of enzyme inhibitors has recently become popular. It identifies important patterns in the reported inhibitors to predict the new molecules. Hence, in this study, a set of support vector classifier-based ML models were developed,validated and employed to predict AChE inhibitors. Further, 247 predicted compounds obtained through PAINS and molecular property filters were docked on the AChE enzyme. The docking study identified compounds AAM132011183, ART21232619 and LMG16204648 as AChE inhibitors with suitable ADME properties. The selected compounds produced stable interactions with enzymes in molecular dynamics studies. The novel inhibitors obtained from the study may be proposed as active leads for AChE inhibition.

Molecular docking studies of natural and synthetic compounds against human secretory PLA2 in therapeutic intervention of inflammatory diseases and analysis of their pharmacokinetic properties

Literature survey reveals that there are several natural and synthetic anti-inflammatory compounds reported till date. As a therapeutic drug target, PLA2 inhibition is preferred over other anti-inflammatory drug targets. The pro-inflammatory effects of group X sPLA2 are acquired from multiple pathways. This study aims to identify the best anti-inflammatory compound among 22 compounds reported in literature using in silico approach. The compound ligands are subjected to docking against the target protein human sPLA2 [PDB ID: 5G3M] at the active site using AutoDock 4.2.6. Based on the ? binding free energy and hydrogen bonding interactions, it was observed that ten compounds fit at the active site. Out of these, compound 1 (14-deoxyandrographolide) was selected as the best compound. Absorption, distribution, metabolism, and excretion (ADME) properties of the ligands are analyzed using pkCSM software available online. Compound 1 exhibited the best conformational fit when compared to the co-crystal inhibitor 4-Benzylbenzamide.

Molecular Docking Of Selected Bioactive Compounds From Azadirachta Indica For The Inhibition Of Covid19 Protease

Objective: COVID-19 caused by novel SARS-coronavirus 2 belonging to family Coronaviridae, is a global public health emergency infecting many people all around the world, especially in India with more than 2,98,000 cases. Hence there is a need for a novel drug that counters SARS-CoV2 is the prime requirement at this time. Methods: The present study aimed to assess bioactive compounds found in Azadirachta indica as a potential inhibitor of COVID-19 Mpr °(6Y2E, 6LU7, and 2GTB) by Autodock 4.2, with the Lamarckian Genetic Algorithm. COVID-19 Mpr ° was docked with thirteen bioactive compounds, and docking was analyzed by Autodock 4.2 and Pymol. Nelfinavir and Saquinavir were used as positive standards for comparison. Results: Azadirachtanin, Azadirachtol, and Salannolide, were left out because of the violation of Lipinski’s rule. The binding energies obtained from the docking of 6Y2E with a native ligand, Azadiradione, Beta-sitosterol, Epiazadiradione, Epoxyazadiradione, Kaempferol, Meldenin, Myricetin, Nimbaflavone, Nimbinene, Nimbione, Nimbocinolide, Quercitrin, Vepnin, Saquinavir, and Nelfinavir were-7.32,-6.63,-6.69,-7.52,-5.27,-4.54,-6.07,-4.19,-5.02,-5.58,-6.23,-4.71, -3.72,-6.4,-7.14 and-4.67 kcal/mol respectively. The binding energies obtained from the docking of 6LU7 with the native ligand, Azadiradione, Nimbione, Vepnin, and Saquinavir were-6.14,-6.48,-6.79 and-6.49 kcal/mol correspondingly. The binding energies obtained from the docking of 2GTB with the native ligand, Azadiradione, Epiazadiradione, Epoxyazadiradione, Kaempferol, Meldenin, Myricetin, Nimbaflavone, Nimbione, Nimbocinolide, Quercitrin, Vepnin, Saquinavir, and Nelfinavir were-6.96,-7.13,-6.69,-5.22,-6.44,-5.06,-5.93,-6.66,-5.3,-5.63,-7.11,-6.89 and-5.42kcal/mol, respectively. Conclusion: Azadiradione, Epiazadiradione, Nimbione, and Vepnin seemed to have the greatest potential to act as COVID-19 protease inhibitors. However, further research is necessary to explore their prospective medicinal use in vitro and in vivo conditions.

Investigating Drug Properties Of Bioactive Compounds Of Cymbopogon Citratus By Absorption, Distribution, Metabolism, Excretion/Toxicity And Molecular Docking Analysis Against Apolipoprotein N-Acyl Transferase

Delivering a potential drug is a predominant challenge in medicinal chemistry.in this study, bio organic compounds of Cymbopogon citratus was screened by analysing physiochemical properties like solubility, permeability, efficacy, toxicity, and metabolic stability. The optimization of drug potential against virulent protein was calculated by using docking algorithm Autodock 4.2.3. Structure based ligand docking reveals that the compounds having better inhibition potential against virulent enzymes with insoluble and impermeable activities. The organic compounds of Cymbopogon citratus were screened using Lipinski rule of five and ADME/T prediction for drug likeliness. The structure based ligand docking was done between bioactive compounds of plant and virulent protein that cause diseases. The interaction was visualized using Discovery studio and was studies. The molecular docking of bioactive compounds resulted in better inhibition potential with controlled lipophilicity level, without causing toxicity that harms the natural habitat of humans. The compounds, 1,3,4-trimethyl -3cyclohexene-1-carboxaldehyde exhibit binding energy -4.70 Kcal/mol followed by β-myrcene – 4.35 Kcal/mol and Geraniol -4.35 Kcal/mol. Hence, structure based ligand docking and in silico ADME/T studies revealed that the compounds have better inhibition potential against Apolipoprotein by improving the prediction of drug compounds.

In silico molecular docking and ADME/T analysis of plant compounds against IL17A and IL18 targets in gouty arthritis

Accumulation of urate crystals and subsequent inflammation are the major cause of pathogenesis of gout. Twopro inflammatory cytokines IL17A and IL18 are upregulated in the serum of gout patients and plays a major rolein promoting inflammation. Inhibition of these cytokines by plant phytochemicals would reduce the severity ofinflammation in gout. In the present study, in silico analysis of inhibition of IL17A and IL18 by 10 plant phytochemicalswere studied using the AutoDock 4.2 based on the principles of Lamarckian genetic algorithm. The results revealed abinding energy in the range of −6.32 kcal/mol to −3.5 kcal/mol and interacted with the amino acids in active pocketof IL17A and IL18. Among all the compounds, syringaresinol showing the least binding energy of −6.05 kcal/molwith IL17A and −6.32 kcal/mol with IL18. The control drug, allopurinol showed a binding energy of −3.32 and −3.18kcal/mol with IL17A and IL18, respectively. In addition, ADME/T properties of the compounds were also analyzed topredict their drug likeliness. This docking study can be used for developing potent inhibitors of IL17A and IL18 forthe treatment of gout.

Insights into cytochrome bc1 complex binding mode of antimalarial 2-hydroxy-1, 4-naphthoquinones through molecular modelling

BACKGROUND Malaria persists as a major public health problem. Atovaquone is a drug that inhibits the respiratory chain of Plasmodium falciparum, but with serious limitations like known resistance, low bioavailability and high plasma protein binding. OBJECTIVES The aim of this work was to perform molecular modelling studies of 2-hydroxy-1,4-naphthoquinones analogues of atovaquone on the Qo site of P. falciparum cytochrome bc1 complex (Pfbc1) to suggest structural modifications that could improve their antimalarial activity. METHODS We have built the homology model of the cytochrome b (CYB) and Rieske iron-sulfur protein (ISP) subunits from Pfbc1 and performed the molecular docking of 41 2-hydroxy-1,4-naphthoquinones with known in vitro antimalarial activity and predicted to act on this target. FINDINGS Results suggest that large hydrophobic R2 substituents may be important for filling the deep hydrophobic Qo site pocket. Moreover, our analysis indicates that the H-donor 2-hydroxyl group may not be crucial for efficient binding and inhibition of Pfbc1 by these atovaquone analogues. The C1 carbonyl group (H-acceptor) is more frequently involved in the important hydrogen bonding interaction with His152 of the Rieske ISP subunit. MAIN CONCLUSIONS Additional interactions involving residues such as Ile258 and residues required for efficient catalysis (e.g., Glu261) could be explored in drug design to avoid development of drug resistance by the parasite.

Potential activity of some natural products compounds as Neuraminidase inhibitors based on molecular docking simulation and in vitro test.

Neuraminidase (NA) plays an important role in replication and the release of a new avian influenza virion. In consequence, NA has been considered as a valid target in drug design against influenza virus. The aim of this study was to identify the new neuraminidase inhibitors using molecular docking simulation based on virtual screening from natural products compounds. The X-ray crystal structure of neuraminidase type N1 (PDB id: 3B7E) and N1 mutant (PDB id: 3NNS) using Autodock 4.2 program. Zanamivir was used as the control ligand and docked against neuraminidase type N1, further plotted between log IC50 value experiments of sialic acid derivatives compound versus log of Ki value of molecular docking. Molecular docking simulation was performed on 113 herb compounds along with zanamivir and oseltamivir as the control ligands. The result showed that the best interaction against of neuraminidase N1 and N1 mutant from herbs compound is katsumadain-A withfree energy value -7,54 kcal/mol and -7,46 kkal/mol, respectively. Katsumadain-Aformed hydrogen bond with amino acid residue Arg118 and Arg371 on neuraminidase and neuraminidase N1 mutant Katsumadain-A was also connected with Arg118 through hydrogen binding interaction. This in silico results also was proved by in vitro MUNANA assay.

Potential interaction of components from essential oils with dengue virus proteins / Potencial interacción de componentes de aceites esenciales con proteínas del virus del dengue

An antiviral drug for treatment of dengue is an urgent necessity. In this study in silico activities of essential oils components on dengue virus (DENV) were evaluated, and beta-Caryophyllene was subjected to biological examination to assess inhibition of DENV-2 replication. Components previously optimized were coupled with viral proteins prepared, using AutoDock Vina. Theoretical affinity values varied between -4.0 and -7.3 kcal/mol. alpha-copaene, beta-bourbonene, germacrene D, spathulenol, beta-caryophyllene, caryophyllene oxide and (+)- epi-bicyclosesquiphellandrene showed the greatest interaction with viral proteins. beta-caryophyllene inhibits DENV-2 in vitro (50 percent inhibitory concentration [IC50] = 22.5 +/- 5.6 uM [4.6 +/- 1.1 ug/mL] and resulted non-cytostatic with a selectivity index value of 71.1. The in silico results permit infer that DENV proteins are potential targets for the concomitant docking of various essential oils components. Biological examination suggest that beta-caryophyllene acts on very early steps of the viral replication cycle and it might prove virucidal.

Una droga antiviral para tratamiento del dengue es una necesidad urgente. En este estudio se evaluó la actividad in silico de componentes de aceites esenciales sobre el virus del dengue (VDEN) y el beta-cariofileno se seleccionó para evaluar la inhibición sobre la replicación in vitro del VDEN-2. Los componentes previamente optimizados fueron acoplados con proteínas virales preparadas, utilizando AutoDock Vina. Los valores de afinidad variaron entre -4.0 and -7.3 kcal/mol. alfa-Copaeno, beta-bourboneno, germacreno D, spatulenol, beta- cariofileno, óxido de cariofileno y (+)-epi-biciclosesquifellandreno presentaron la mayor interacción con las proteínas virales. beta-Cariofileno inhibió VDEN-2 in vitro (Concentración inhibitoria 50 [IC50] = 22.5 +/- 5.6 uM [4.6 +/- 1.1 ug/mL] y resultó no-citostático con índice de selectividad de 71.1. Los resultados in silico indican que proteínas del VDEN son blancos potenciales para varios componentes. El análisis biológico sugiere que el beta-cariofileno actúa en etapas tempranas de la replicación viral y podría ser virucida.

Molecular Docking Study on Dipeptidyl Peptidase-4 Inhibitors.

Dipeptidyl peptidase (DPP)-IV inhibitors are a new approach to the treatment of type 2 diabetes. DPP-IV is a member of a family of serine peptidases that includes quiescent cell proline dipeptidase (QPP), DPP8, and DPP9. DPP-IV is a key regulator of incretin hormones, but the functions of other family members are unknown. To determine the importance of selective DPP-IV inhibition for the treatment of diabetes, we conducted molecular docking studies on clinical inhibitors of DPP-IV.

Molecular docking study of 3,6 bis(3’substituted propoxy) and 3,6 bis (5’substituted pentyloxy) xanthone derivatives as PGHS- 2 inhibitors.

The primary effect of the NSAIDs is to inhibit cyclooxygenase (COX or prostaglandin synthase), thereby impairing the ultimate transformation of arachidonic acid to prostaglandins, prostacyclin, and thromboxanes. Two related isoforms of the COX enzyme have been described, COX-1 and COX-2. Identification of this cyclooxygenase-2 (COX-2) isoform resulted in the development of selective COX-2 inhibitors, with the hope of producing a safer analgesic and anti-inflammatory agent. The principal benefit with the selective COX-2 inhibitors is the production of comparable analgesia and antiinflammatory effects to the nonselective NSAIDs, but with fewer symptomatic gastric and duodenal ulcers and a decrease in gastrointestinal symptoms. In the present work, twelve novel series of xanthone derivatives (A1-A6 and B1-B6) were allowed to dock against PGHS-2(prostaglandin endoperoxide synthase-2) protein (PDB ID: 3LN1) to evaluate their comparative efficacy in terms of docking performance. The results are discussed on the basis of binding energy value.

Método acoplado Autodock-PM6 para seleccionar la mejor pose en estudios de acoplamiento molecular / Autodock-PM6 method to choose the better pose in molecular docking studies / A Autodock-PM6 metodo pra seleccionar o melhor pose en estudios de acoplamiento molecular

El acoplamiento molecular (conocido como docking) es una técnica de mecánica molecular ampliamente utilizada para predecir energías y modos de enlace entre ligandos y proteínas, información de gran utilidad en el estudio de nuevos compuestos con efectos terapéuticos. No obstante, los resultados obtenidos mediante esta técnica tienden a la subjetividad, debido a que los programas utilizados para llevarla a cabo proporcionan más de un criterio de selección de la mejor pose. En la presente investigación se aplicó el método semiempírico PM6 a los resultados del acoplamiento, obteniendo con ello mejorías en el proceso de selección de la mejor pose pues se obtuvieron poses con alta probabilidad de unión al sitio activo de su receptor y con energías de unión menores a las reportadas por los criterios de selección ofrecidos por el programa de docking.

The acoplamiento molecular (conocido como docking) es una técnica de mecánica molecular ampliamente utilizada para predecir energías y modos de enlace entre ligandos y proteínas, lo que proporciona información de gran utilidad para el estudio de nuevos compuestos con efectos terapéuticos. No obstante, los resultados obtenidos mediante esta técnica tienden a la subjetividad, debido a que los programas utilizados para llevarla a cabo proporcionan más de un criterio de selección de la mejor pose. En la presente investigación, se aplicó el método semiempírico PM6 a los resultados del acoplamiento, obteniendo con ello mejorías en el proceso de selección de la mejor pose al observarse finalmente poses con alta probabilidad de unión al sitio activo de su receptor y con energías de unión menores a las reportadas por los criterios de selección ofrecidos por el programa de docking.

El acoplamiento molecular (conocido como docking) es una técnica de mecánica molecular ampliamente utilizada para predecir energías y modos de enlace entre ligandos y proteínas, lo que proporciona información de gran utilidad para el estudio de nuevos compuestos con efectos terapéuticos. No obstante, los resultados obtenidos mediante esta técnica tienden a la subjetividad, debido a que los programas utilizados para llevarla a cabo proporcionan más de un criterio de selección de la mejor pose. En la presente investigación, se aplicó el método semiempírico PM6 a los resultados del acoplamiento, obteniendo con ello mejorías en el proceso de selección de la mejor pose al observarse finalmente poses con alta probabilidad de unión al sitio activo de su receptor y con energías de unión menores a las reportadas por los criterios de selección ofrecidos por el programa de docking.

Molecular docking based inhibition of Trypanothione reductase activity by Taxifolin novel target for antileishmanial activity.

The theoretical docking study, conducted on a sample of previously reported for anti-inflammatory and antioxidant activities of Taxifolin at the binding site of Leishmania infantum trypanothione reductase (Try R) examine interaction energy. Taxifolin is widely used in the traditional medicine have been investigated for their putative chemo preventive and antileishmanial properties for the last few decades. A theoretical docking study, the evaluation of Taxifolin as inhibitor of trypanothione reductase a validated drug target enzyme of the Leishmania parasite. Taxifolin was found to bind at active site of L. infantum TryR with lowest binding energy and RMSD values to be -8.82 Kcal/Mol and 2.0 Å respectively. Docking analysis of TryR with ligand enabled us to identify specific residues viz. Ser-14, Ala-47, Ser-162, Thr-336 and Arg-286, within the TryR binding pocket to play an important role in ligand binding affinity. The availability of TryR built model, together with insights gained from docking analysis will promote the rational design of potent and selective TryR inhibitor as antileishmanial therapeutic. The study contributes towards understanding mechanism of antileshmanial effect of the Taxifolin. This compound has shown promising biological activity in preliminary studies by targeting multiple signaling pathways. Thus on the basis of our in silico studies we hypothesize that this compound into Taxifolin can be inhibitory effect on against leishmaniasis.

Synthesis and anticancer activity study of diosgenin derivatives / 中国药学杂志

OBJECTIVE: To synthesize diosgenin derivatives and investigate their anti-tumor activities in vitro. METHODS: Designed and docked by AutoDock4.2, a series of diosgenin derivatives were selectively prepared from diosgenin. Their anti-tumor activities in vitro were evaluated for human malignant melanoma A375 cells, human lung adenocarcinoma A549 cells, human hepatoma HepG-2 cells and human myeloid leukemia K562 cells by MTT assay. RESULTS: Twelve novel compounds were synthesized and the basic structures were characterized by 1H-NMR and 13C-NMR. MTT assay showed that most of the diosgenin derivatives exhibited some anti-tumor activities. CONCLUSION: Most of the synthesized compounds had certain antitumor activity and showed no or little toxicity against the normal cells. Copyright 2012 by the Chinese Pharmaceutical Association.