Docking Methods Research Articles

Discovery of novel Akt1 inhibitors by an ensemble-based virtual screening method, molecular dynamics simulation, and in vitro biological activity testing.

Akt1, as an important member of the Akt family, plays a controlled role in cancer cell growth and survival. Inhibition of Akt1 activity can promote cancer cell apoptosis and inhibit tumor growth. Therefore, in this investigation, a multilayer virtual screening approach, including receptor-ligand interaction-based pharmacophore, 3D-QSAR, molecular docking, and deep learning methods, was utilized to construct a virtual screening platform for Akt1 inhibitors. 17 representative compounds with different scaffolds were identified as potential Akt1 inhibitors from three databases. Among these 17 compounds, the Hit9 exhibited the best inhibitory activity against Akt1 with inhibition rate of 33.08% at concentration of 1μM. The molecular dynamics simulations revealed that Hit9 and Akt1 could form a compact and stable complex. Moreover, Hit9 interacted with some key residues by hydrophobic, electrostatic, and hydrogen bonding interactions and induced substantial conformation changes in the hinge region of the Akt1 active site. The average binding free energies for the Akt1-CQU, Akt1-Ipatasertib, and Akt1-Hit9 systems were - 34.44, - 63.37, and - 39.14kJ mol-1, respectively. In summary, the results obtained in this investigation suggested that Hit9 with novel scaffold may be a promising lead compound for developing new Akt1 inhibitor for treatment of various cancers with Akt1 overexpressed.

Scientific Validation of Flavonoids for Effective Management of Pancreatitis: In-Silico Molecular Docking

When someone develops pancreatitis, their pancreas swells up in inflammation. Pancreatic damage happens when the digestive enzymes are activated before they are discharged into the small intestine and begin attacking the pancreas. There are two types of pancreatitis: acute and chronic. Alcohol consumption and gallstones are just two of the numerous potential causes of pancreatitis. Plant medicine is an effective way to cure pancreatitis. Citrus flavonoids may offer promising bioactive molecules for treating metabolic disorders, according to some research. Hesperidin is widely consumed in the Western diet in this regard, mostly through the consumption of orange juice. Furthermore, since refined hesperidin is easily extracted or produced and is highly purified industrially, it is inexpensively available commercially. The Western diet contains little eriodictoyl, which is mostly found in lemons and is commercially available. Method: In the current work, NF-kβ receptor inhibitors were sought after using a molecular docking approach. The binding was determined by the Auto Dock software utilizing a grid-based docking method. Compounds' 2D structures were constructed using the chem sketch, converted to 3D, and then energetically reduced up to an arms gradient of 0.01. (MMFF). Result: Hesperetin and Eriodictoyl found to be effective anti-pancreatitis agent effectively binds to be target protein NF-kβ receptor with binding energy -6.9 & -6.7 kcalmol-1 for hesperetin & eriodictoyl respectively. Conclusion: It was discovered through a computationally based docking analysis that both lead compounds exhibit strong NF-KB receptor inhibiting effects. The results demonstrated a promising docking score and lead molecule's pattern of binding to the target protein's active region with strong covalent bonding. The synergistic impact of hesperetin & eriodictoyl is ability to heal pancreatitis.

AI-based Virtual Screening of Traditional Chinese Medicine and the Discovery of Novel Inhibitors of TCTP.

Translationally controlled tumour protein (TCTP) is associated with tumor diseases, such as breast cancer, and its inhibitor can reduce the growth of tumor cells. Unfortunately, there is currently no effective medication available for treating TCTP-related breast cancer. The objective of this study was to explore the inhibitor candidates among natural compounds for the treatment of breast cancer related to TCTP protein. To explore the potential inhibitors of TCTP, we first screened out four potential inhibitors in the Traditional Chinese Medicine (TCM) for cancer based on AI virtual screening using the docking method, and then revealed the interaction mechanism of TCTP and four candidate inhibitors from TCM with molecular docking and molecular dynamics (MD) methods. Based on the conformational characteristics and the MD properties of the four leading compounds, we designed the new skeleton molecules with the AI method using MolAICal software. Our MD simulations have revealed that different small molecules bind to different sites of TCTP, but the flexible regions and the signaling pathways are almost the same, and the VDW and hydrophobic interactions are crucial in the interactions between TCTP and ligands. We have proposed the candidate inhibitor of TCTP. Our study has provided a potential new method for exploring inhibitors from Traditional Chinese Medicine (TCM).

Exploring the Infectious Drug Target Glutathione S-Transferase in Plasmodium falciparum with the Inhibitory Potential of Azadirachta indica Phytocompounds

Background. Neem compounds are being studied for their potential as new and effective antimalarial drugs, and there is mounting evidence that they may help treat malaria. The PfGST enzyme is crucial to the malaria parasite’s survival, making it a desirable target for new antimalarial drugs, and the study aims to examine the bark region compounds as PfGST inhibitors. Methods. The structure of PfGST is examined for quality analysis, the active site is predicted based on a web server, and the bark region compounds are docked for their binding potential. Final molecules are identified for the absorption, distribution, metabolism, and excretion (ADME) analysis to confirm the possible future leads that target malaria. Results. This study reports that IMPHY000093, IMPHY001448, and IMPHY005310 can be potential inhibitors, showing strong binding potential in hydrogen bonds, scoring values, and ADME analysis. Results are confirmed by the possible re-docking poses by the docking method, and the binding score is used for the evaluations. Conclusion. Neem’s active ingredients have shown promise as a new class of antimalarial medications. Neem compounds may boost the efficacy of other antimalarial drugs and the host immune system by inhibiting GST, which is involved in the metabolism of the malaria parasite.

Comprehensive In silico Analysis of Antibacterial Compounds in n-Hexane Fraction from Jeruju Leaf (Acanthus ilicifolius)

In an emergency, to identify the most promising Hesperidin, Kaempferol-3,4'-di-O-methyl ether (Ermanin); Myricetin-3-glucoside, Peonidine 3-(4’-arabinosylglucoside); Quercetin 3-(2G-rhamnosylrutinoside); and Rhamnetin 3-mannosyl-(1–2)-alloside as a lead compound from Jeruju to develop new drugs from flavonoid analog. The active compound's structure is derived from the PubChem database and improves the stability through ChemDraw v19. The Protein Data Bank website identified the protein macromolecule with PDB code 3VSL. Redocking was performed to ensure validation of 3VSL. The docking method was carried out using the IGEMDOCK software version v2.1. Also, the chimera-1.13.1 program is used to know the interaction profile. The web server pkCSM and Protox II online tool were used to determine the toxicity. 3,7,11,15-tetramethyl-2-hexadecen-1-ol is the juju leaf chemical with the most promise as an antibacterial and the one that shows the maximum binding affinity when taking into account toxicity.

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

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

Investigating the mechanism and efficacy material basis of Xiehuo Xiaoying decoction for treating Graves' disease via thyroid cell apoptosis based on proteomics and molecular docking techniques

Ethnopharmacological relevanceFor numerous years, the Xiehuo Xiaoying decoction (XHXY), a traditional Chinese medicine formula, has demonstrated substantial promise in treating Graves' disease (GD) in clinical settings, showcasing significant potential. However, the therapeutic mechanism and efficacy material basis of XHXY remains obscure. Aim of the studyThis work aims to investigate the underlying mechanisms and to study the efficacy material basis of XHXY in anti-GD effect using a combination of TMT quantitative proteomics and molecular docking method. Materials and methodsGD model was initiated by administering Ad-TSH289. Subsequently, the mice underwent a four-week regimen that included oral gavage of XHXY at doses of 17 g/kg·d and 34 g/kg·d, along with intraperitoneal injections of Gentiopicroside (GPS). Utilizing the principles of pharmacological chemistry in traditional Chinese medicine, we employed high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (HPLC-QTOF/MS) to discern prescribed prototype composition of XHXY in serum samples from mouse. TMT proteomics research provided evidence of XHXY's putative targets and important pathways in vivo. The binding activity of probable action targets and prototype composition was detected by molecular docking. Finally, Immunohistochemistry (IHC) and TUNEL staining were used to verify the mechanism of XHXY and GPS in anti-GD. ResultsXHXY and GPS alleviated GD by ameliorating the pathological changes and reducing thyroxine and TRAb levels. In mouse serum, a total of 31 prototypical XHXY ingredients were detected, and the majority of these components were from monarch and minister medicine. Proteomics study results indicated that the XHXY may mainly regulate targets including FAS-associated death domain protein (FADD), Apolipoprotein C-III, etc. and main pathways are Apoptosis, Cholesterol metabolism, TNF signalling pathway, etc. Strong binding activity of the prototypical active ingredient and GPS towards FADD, Caspase 8, and Caspase 3 was demonstrated by molecular docking. XHXY and its primary component, GPS, elevated the expression of FADD, Caspase 8, and Caspase 3, and enhance apoptosis in thyroid cells, as lastly validated by TUNEL and IHC staining. ConclusionsXHXY exhibits a favorable therapeutic effect in treating GD by promoting apoptosis in thyroid cells through the upregulation of FADD, Caspase 8, and Caspase 3 expression. And GPS is the main efficacy material basis for its therapeutic effect in anti-GD.

Exploring the potential mechanism and molecular targets of Taohong Siwu Decoction against deep vein thrombosis based on network pharmacology and analysis docking.

This study aims to investigate the mechanism of Taohong Siwu Decoction (THSWD) against deep vein thrombosis (DVT) using network pharmacology and molecular docking technology. We used the Traditional Chinese Medicine Systems Pharmacology database and reviewed literature to identify the main chemical components of THSWD. To find targets for DVT, we consulted GeneCards, Therapeutic Target Database, and PharmGKB databases. We used Cytoscape 3.8.2 software to construct herb-disease-gene-target networks. Additionally, we integrated drug targets and disease targets on the STRING platform to create a protein-protein interaction network. Then, we conducted Kyoto Encyclopedia of Genes and Genomes and gene ontology analysis. Finally, We employed the molecular docking method to validate our findings. We identified 56 potential targets associated with DVT and found 61 effective components. beta-sitosterol, quercetin, and kaempferol were the most prominent among these components. Our analysis of the protein-protein interaction network revealed that IL6, L1B, and AKT1 had the highest degree of association. Gene ontology analysis showed that THSWD treatment for DVT may involve response to inorganic substances, negative regulation of cell differentiation, plasma membrane protein complex, positive regulation of phosphorylation, and signaling receptor regulator activity. Kyoto Encyclopedia of Genes and Genomes analysis indicated that lipid and atherosclerosis, pathways in cancer, as well as the PI3K-Akt pathway are the main signal pathways involved. Molecular docking results demonstrated strong binding affinity between beta-sitosterol, quercetin, kaempferol, and AKT1 proteins as well as IL1B and IL6 proteins. The main targets for THSWD treatment of DVT may include AKT1, IL1B, and IL6. Beta-sitosterol, quercetin, and kaempferol may be the active ingredients responsible for producing this effect. These compounds may slow down the progression of DVT by regulating the inflammatory response through the PI3K/Akt pathway.

Cobdock: an accurate and practical machine learning-based consensus blind docking method

Probing the surface of proteins to predict the binding site and binding affinity for a given small molecule is a critical but challenging task in drug discovery. Blind docking addresses this issue by performing docking on binding regions randomly sampled from the entire protein surface. However, compared with local docking, blind docking is less accurate and reliable because the docking space is too largetly sampled. Cavity detection-guided blind docking methods improved the accuracy by using cavity detection (also known as binding site detection) tools to guide the docking procedure. However, it is worth noting that the performance of these methods heavily relies on the quality of the cavity detection tool. This constraint, namely the dependence on a single cavity detection tool, significantly impacts the overall performance of cavity detection-guided methods. To overcome this limitation, we proposed Consensus Blind Dock (CoBDock), a novel blind, parallel docking method that uses machine learning algorithms to integrate docking and cavity detection results to improve not only binding site identification but also pose prediction accuracy. Our experiments on several datasets, including PDBBind 2020, ADS, MTi, DUD-E, and CASF-2016, showed that CoBDock has better binding site and binding mode performance than other state-of-the-art cavity detector tools and blind docking methods.

Virtual screening and multi-synergism of inhibitory compounds against pancreatic lipase

In response to the adverse effects associated with chemically synthesized pancreatic lipase (PL) inhibitors and the limited efficacy of individual natural functional compounds, this investigation aims at virtually screening potential PL inhibitors from natural plant-sourced materials and evaluating their multi-synergism through molecular docking, SynergyFinder tool and spectroscopic methods. Luteolin (LUT), quercetin (QUE), and apigenin (API) have been virtually screened out as outstanding PL inhibitors with the IC50 values being 109.7, 190.0 and 276.9 μg/mL. Synergistic score analysis of the PL inhibition rates by SynergyFinder Plus showed that the tri-component synergistic scores were more significant than one- and two-component synergy scores and the inhibition rate could reach 96.8% with LUT: QUE: API of 2 : 3: 12. The inhibitory mechanism of the complex (L-Q-A) on PL is mixed inhibition. L-Q-A exhibits a more potent quenching effect on PL and exerts a more pronounced influence on the secondary structure of PL. The simultaneous muti-ligand molecule docking results further demonstrate the existence of multiple binding pockets of L-Q-A on the PL that can form more hydrogen bonding, hydrophobic interactions and π-π interactions. In conclusion, LUT, QUE, and API exhibit synergistic effects in inhibiting PL activity, holding promise as innovative dietary supplements for mitigating obesity-related symptoms.

Advancing Pyrrole Synthesis through DDQ Catalysis: A Comprehensive Research Incorporating DFT, ADMT, and Molecular Docking Analysis

AbstractThe construction of pyrroles is an important heterocyclic group comprising many compounds with interesting properties that have led to numerous applications in various fields. We delineate a new synthetic method for the rapid construction of tree‐substituted pyrroles from readily available ketoximes as starting materials and also a new mechanism and method has been proposed. It is presented that substituted pyrroles were efficiently synthesized in high yields (up to 81 % yield) through the cyclization reaction of starting ketoximes mediated by 2,3‐dichlor‐5,6‐dicyanobenzoquinone (DDQ). Utilizing this protocol various pyrrole derivatives were synthesized from diethyl acetylene dicarboxylate (DEAD). We then developed the dehydrogenation reaction mechanism of this formation, also studied in detail, also all synthesized compounds were analyzed in detail by spectroscopic techniques (FT‐IR, 1H NMR, 13CNMR) which were compared with the computational data estimated at B3LYP/6‐311G** level. The thermochemical and electronic properties of the pyrroles were evaluated after optimizing and then confirming the equilibrium structures. ADMT scores were also considered to estimate/elucidate the possible bioavailability tendencies as well as the toxicity. In addition, the interactions of the optimized molecules were evaluated by molecular docking methods against BSA “Bovine Serum Albumin” and LIF “Leukemia Inhibitory Factor”. The results obtained from this study will ideally provide a fundamental source in contemporary drug design in terms of both the key electronic properties underlying the possible reactivity features and toxicity.

Effects and mechanisms of Zhizi Chuanxiong herb pair against atherosclerosis: an integration of network pharmacology, molecular docking, and experimental validation

BackgroundThe Zhizi Chuanxiong herb pair (ZCHP) can delay pathological progression of atherosclerosis (AS); however, its pharmacological mechanism remains unclear because of its complex components. The purpose of current study is to systematically investigate the anti-AS mechanism of ZCHP.MethodsThe databases of TCMSP, STITCH, SwissTargetPrediction, BATMAN-TCM, and ETCM were searched to predict the potential targets of ZCHP components. Disease targets associated with AS was retrieved from the GEO database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analyses were executed using DAVID 6.8. Molecular docking method was employed to evaluate the core target binding to blood components, and animal experiments were performed to test action mechanism.ResultsA ZCHP-components-targets-AS network was constructed by using Cytoscape, included 11 main components and 52 candidate targets. Crucial genes were shown in the protein–protein interaction network, including TNF, IL-1β, IGF1, MMP9, COL1A1, CCR5, HMOX1, PTGS1, SELE, and SYK. KEGG enrichment illustrated that the NF-κB, Fc epsilon RI, and TNF signaling pathways were important for AS treatment. These results were validated by molecular docking. In ApoE−/− mice, ZCHP significantly reduced intima-media thickness, pulse wave velocity, plaque area, and serum lipid levels while increasing the difference between the end-diastolic and end-systolic diameters. Furthermore, ZCHP significantly decreased the mRNA and protein levels of TNF-α and IL-1β, suppressed NF-κB activation, and inhibited the M1 macrophage polarization marker CD86 in ApoE−/− mice.ConclusionThis study combining network pharmacology, molecular biology, and animal experiments showed that ZCHP can alleviate AS by suppressing the TNF/NF-κB axis and M1 macrophage polarization.Graphical

Computational analysis of anti-cancer drug hydroxyurea adsorption on nanocages of gold, silver and copper: SERS and DFT assessment

The use of nanostructures in targeted drug delivery is effective in decreasing anticancer drug toxicity. Here, we discuss the theoretically predicted adsorption and interaction behavior of hydroxyurea [HU] with nano metal cages (nmC). HU interact the nmC through the N4 in primary amine with energies of −29.776, −30.684 and −22.105 kcal/mol for Au, Ag and Cu cage, respectively. As a result of reactivity studies, HU complexes with nmC (Au/Ag/Cu) are becoming more electrophilic and this gives the nmC system their bioactivity. It is suggested that nanocage is going to change the FMO's energy levels by means of absorption, so that it is used in drug administration. DOS and MEP were accomplished to gain additional understandings into the reactivity of proposed complexes. Method for improving the Raman signal of biomolecules is surface enhanced Raman scattering (SERS), which uses nanosized metal substrates. Chemical enhancement is evidenced by Mulliken charge distributions of all systems for detection and chemical compositions and exerts a significant role in determining them. In HU complexes containing nmC (Au/Ag/Cu), electron density was detected via ELF and LOL calculations. Based on the results of a non-covalent interaction (NCI) analysis, Van der Waals/hydrogen bonds/repulsive steric – interactions have been found. The title compound will also be analyzed in order to determine its bioactivity and drug likeness parameters, as a result, we will able to create a molecule with a highly favorable pharmacological profile and use the docking method to determine the values of the interaction energies for drug delivery. This study suggests that adsorption of drugs on nanocage surface occurs physically and functionalizing the nanocage has increased adsorption energy.

Triangle codes and tracer lights based absolute positioning method for terminal visual docking of autonomous underwater vehicles

PurposeDocking technology plays a crucial role in enabling long-duration operations of autonomous underwater vehicles (AUVs). Visual positioning solutions alone are susceptible to abnormal drift values due to the challenging underwater optical imaging environment. When an AUV approaches the docking station, the absolute positioning method fails if the AUV captures an insufficient number of tracers. This study aims to to provide a more stable absolute position visual positioning method for underwater terminal visual docking.Design/methodology/approachThis paper presents a six-degree-of-freedom positioning method for AUV terminal visual docking, which uses lights and triangle codes. The authors use an extended Kalman filter to fuse the visual calculation results with inertial measurement unit data. Moreover, this paper proposes a triangle code recognition and positioning algorithm.FindingsThe authors conducted a simulation experiment to compare the underwater positioning performance of triangle codes, AprilTag and Aruco. The results demonstrate that the implemented triangular code reduces the running time by over 70% compared to the other two codes, and also exhibits a longer recognition distance in turbid environments. Subsequent experiments were carried out in Qingjiang Lake, Hubei Province, China, which further confirmed the effectiveness of the proposed positioning algorithm.Originality/valueThis fusion approach effectively mitigates abnormal drift errors stemming from visual positioning and cumulative errors resulting from inertial navigation. The authors also propose a triangle code recognition and positioning algorithm as a supplementary approach to overcome the limitations of tracer light positioning beacons.

Metabolomics and network pharmacology reveal the mechanism of Castanopsis honey against Streptococcus pyogenes

Streptococcus pyogenes (GAS) is one of the most virulent and infectious bacteria, severely threatening health and lives of people worldwide. Honey has been proven to have effective capability against GAS, but the underlying metabolites and mechanisms are still unclear. In this study, the Castanopsis honey (CH) showed significant antibacterial ability compared to other seven kinds of honey and artificial honey. Furthermore, the antibacterial metabolites and their targets in CH were screened by combined method of metabolomics, network pharmacology, and molecular docking. The results suggested that the activities of two antioxidant enzymes, glutathione peroxidase and tyrosyl tRNA synthetase identified as the primary targets, were significantly inhibited by CH, which significantly increased the level of oxidative stress in GAS. The results revealed a possibly novel mechanism regulating the oxidative stress and inhibits the growth in bacteria, providing strong experimental evidence to support the further development of CH as a novel antibacterial agent.

Investigating the binding of caffeic acid to human hemoglobin using multispectroscopic and molecular docking approaches

Caffeic acid (CA) is a hydroxycinnamic acid derivative that possess a wide variety of biological properties and is non-toxic to humans. The binding mechanism of CA with human hemoglobin (HHb) was studied for the first time using multispectroscopic and molecular docking methods. The UV–visible absorption spectra showed that CA interacts with HHb through the formation of ground state complex. The fluorescence studies revealed that CA quenches HHb fluorescence by the static mechanism and confirmed the presence of a single CA binding site on the HHb molecule. The negative values of thermodynamics parameters (ΔH,ΔSand ΔG) showed that the binding of CA to HHb is a spontaneous and exothermic process. Hydrogen bonds and van der Waal interactions are the major intermolecular forces that stabilize the HHb-CA complex. Synchronous fluorescence experiments showed that binding of CA altered the microenvironment around tryptophan residues of HHb. Fluorescence resonance energy transfer studies indicated a high propensity of energy transfer from tryptophan residues of HHb to CA. Circular dichroism spectra and catalytic esterase activity confirmed that only minor changes occur in the secondary structure of HHb in the presence of CA. Molecular docking study identified the HHb amino acid residues involved in binding to CA. Analysis of the binding mode of CA with HHb represents an important step in elucidating the molecular mechanism of the protection of HHb from oxidative damage. This will help in understanding the potential role of CA and related antioxidants as therapeutic agents in various blood-related diseases.

Multispectral analysis and molecular docking to predict the mechanism of molecular interactions of curcumin, zein and fucoidan complexes

Zein-fucoidan (Fuc) nanocarriers are used to deliver curcumin (Cur). However, the structural effects of Fuc and Cur ligand molecules on zein are still understudied. Therefore, multi-spectral analysis and molecular docking methods were used in this study to investigate the interaction of Cur and Fuc on zein. The UV–visible, synchronous, and endogenous fluorescence showed that Cur and Fuc influence the microenvironment of the chromogenic amino acids in zein. The FT-IR confirmed the effect of Cur and Fuc molecules on secondary structure changes in zein. Raman spectroscopy further analyzed the hydrophobic interactions and hydrogen bonding between Cur and Fuc on zein. And the fluorescence quenching of zein by Cur or Fuc was a single static quenching. Additionally, molecular docking showed that Fuc was attached to the outside of zein, while Cur was on the contrary. The findings of this study provide a theoretical basis for the further application of Fuc-zein nanocarriers.

A High-Quality Data Set of Protein-Ligand Binding Interactions Via Comparative Complex Structure Modeling.

High-quality protein-ligand complex structures provide the basis for understanding the nature of noncovalent binding interactions at the atomic level and enable structure-based drug design. However, experimentally determined complex structures are scarce compared with the vast chemical space. In this study, we addressed this issue by constructing the BindingNet data set via comparative complex structure modeling, which contains 69,816 modeled high-quality protein-ligand complex structures with experimental binding affinity data. BindingNet provides valuable insights into investigating protein-ligand interactions, allowing visual inspection and interpretation of structural analogues' structure-activity relationships. It can also be used for evaluating machine-learning-based scoring functions. Our results indicate that machine learning models trained on BindingNet could reduce the bias caused by buried solvent-accessible surface area, as we previously found for models trained on the PDBbind data set. We also discussed strategies to improve BindingNet and its potential utilization for benchmarking the molecular docking methods and ligand binding free energy calculation approaches. The BindingNet complements PDBbind in constructing a sufficient and unbiased protein-ligand binding data set and is freely available at http://bindingnet.huanglab.org.cn.

Predicting the biological activity of selected phytochemicals in Alsophila spinulosa leaves against 4-aminobutyrate-aminotransferase: A potential antiepilepsy agents

The use of medicinal plants as an alternative mean of treating various diseases has drawn the attention of several researchers. The desire to find lasting solutions to epilepsy among humans increases every day. Thus, this work was aimed at investigating the potential capacity of the studied phytochemicals in Alsophila spinulosa against human 4-aminobutyrate-aminotransferase as well as to predict the nonbonding interactions involved in the studied complexes. In this work, ten compounds with biological activities were selected and studied using molecular docking method. The molecules selected obtained from A. spinulosa leaves were optimized and various descriptors that described the anti-4-aminobutyrate-aminotransferase features were obtained. More so, 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5-trihydroxy-6-methyltetrahydro-2H-pyran-2-yl)oxy)-4H-chromen-4-one (compound 9) with highest binding affinity proved to have greater strength to inhibit 4-aminobutyrate-aminotransferase thereby downregulating epilepsy than other studied compounds and the reference drug (clobazam). The ADMET features of both compound 9 and clobazam were explored and reported.

Determination of the inhibition effect of hesperetin and its derivatives on Candida glabrata by molecular docking method

In the study, it was aimed to develop new candidate inhibitor molecules by targeting the AWP1 protein structure of Candida glabrata organism. Hesperetin molecule was taken as a reference and different substituted groups were attached to the determined ends of the molecule to increase the inhibition potential on the protein structure. A total of 100 molecules were designed and after conformer distribution using the Molecular Mechanics/MMFF method for each designed molecule, the area, volume, weight, energy, EHOMO, ELUMO, polarizability, dipole moment, log P values of these molecules were calculated using the Semi Empirical/PM6 method. Molecular docking studies of the optimized molecules were carried out through the Autodock Vina program. After the docking studies, the interactions of the designed molecules with the active site amino acids of the protein structure were analyzed by BIOVIA Discovery Studio Client software in case of possible mutation. As a result of the analysis, five molecules with higher binding energies than other designed molecules and currently used antifungal drugs were recommended.