The traditional nutritional and medical hemp(Cannabis sativa L.)seed protein were explored for the discovery and directional preparation of new xanthine oxidase inhibitory(XOI)peptides by structure-based virtual scree...The traditional nutritional and medical hemp(Cannabis sativa L.)seed protein were explored for the discovery and directional preparation of new xanthine oxidase inhibitory(XOI)peptides by structure-based virtual screening,compound synthesis,in vitro bioassay and proteolysis.Six subtypes of hemp seed edestin and albumin were in silico hydrolyzed by 29 proteases,and 192 encrypted bioactive peptides were screened out.Six peptides showed to be XOI peptides,of which four(about 67%)were released by elastase hydrolysis.The peptide DDNPRRFY displayed the highest XOI activity(IC50=(2.10±0.06)mg/mL),acting as a mixed inhibitor.The pancreatic elastase directionally prepared XOI hemp seed protein hydrolysates,from which 6 high-abundance XOI peptides encrypted 3 virtually-screened ones including the DDNPRRFY.The novel outstanding hemp seed protein-derived XOI peptides and their virtual screening and directed preparation methods provide a promising and applicable approach to conveniently and efficiently explore food-derived bioactive peptides.展开更多
Current biodegradation timelines show that polyesters take over 200 years to break down. A crucial component of several industries, polyesters are relied upon for materials development and thus require sustainable alt...Current biodegradation timelines show that polyesters take over 200 years to break down. A crucial component of several industries, polyesters are relied upon for materials development and thus require sustainable alternatives. Recent works in generative modeling have made it possible to produce large sets of chemical structures, but current molecular screening methods are expensive, not scalable, and are oversimplified. This work evaluates whether a molecule’s biodegradability potential can be accurately predicted by training a model on recent experimental data. Additionally, three chemical descriptors were evaluated on the final molecules for their effects on biodegradability: molecular structure, bond types, and solubility. A Gradient Boosted Machine was trained on a dataset of 600 molecules and their binary labels on biodegradability. The classification model effectively captured the biodegradability property, yielding an Area Under the Receiver Operating Characteristics, AUROC, of 84% and an Area Under the Precision Recall Curve, or AUPRC, of 87%. Additionally, an existing amortized synthetic tree generation model, SynNet, validated each molecule by showing chemical synthesizability and producing simple and interpretable synthesis pathways. This approach of filtering by prediction and chemical rule interpretation is inexpensive, highly scalable and can capture the necessary complexity. Using this method, novel polyester candidates can be polymerized and produced into sustainable fabrics, reducing environmental stress from textile-reliant industries.展开更多
As a type II or III transmembrane glycoprotein, human CD38 is ubiquitously expressed in all mammalian tissues. CD38 is a multi-functional enzyme and a member of the ADP-ribosyl cyclase family, and it catalyzes nicotin...As a type II or III transmembrane glycoprotein, human CD38 is ubiquitously expressed in all mammalian tissues. CD38 is a multi-functional enzyme and a member of the ADP-ribosyl cyclase family, and it catalyzes nicotinamide adenine dinucleotide （NAD^＋） and nicotinamide adenine dinucleotide phosphate （NADP＋） to two distinct Ca^2＋ messengers as follows： cyclic ADP-ribose （cADPR） and nicotinic acid adenine dinucleotide phosphate （NAADP）, respectively. Moreover, both cADPR and NAADP mediate mobilization of intracellular Ca^2＋ targeting endoplasmic stores and the lysosomes, respectively. In this study, we combined ligand-based and structure-based virtual screening strategies to compare the inhibitor discovery efficacy based on natural substrates and the known inhibitors. The similarity queries towards SPECS database were carried out using ROCS and EON modules of OpenEye software. The hits were further docked to CD38 using AutoDock 4.05 program. In addition, ADME studies were also processed considering solubility in water and membrane permeability. Finally, we identified 17 compotmds-based on natural substrates and 10 compounds based on known inhibitor models. The results showed that the known inhibitor H2-based model was more efficient in virtual screening of CD38 non-covalent inhibitors.展开更多
To discover new lead compounds for M1 agonists. Ten typical M1 agonists were superimposed to build a M1 agonists 3D-pharmacophore model using distance-comparisons （DISCO） method without the previous knowledge of the...To discover new lead compounds for M1 agonists. Ten typical M1 agonists were superimposed to build a M1 agonists 3D-pharmacophore model using distance-comparisons （DISCO） method without the previous knowledge of the three-dimensional structure of M1 receptor. Virtual screening strategy was used to analyze the Available Chemicals Directory-Screening Compounds （ACD-SC） to identify possible new hits. Twenty-two compounds which fit the pharmacophore model well and are not similar with known M1 agonists were purchased in order to evaluate their M1 receptor agonist activity. One of them shows M1 receptor agonist activity with EC50 of 4.90 μmol/L and maximum response. Multiple of 10.0 which shows it worthy of further study as a new lead compound for M1 agonists.展开更多
Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and...Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and experiments is presented for accelerating the discovery of novel energetic materials.A high-throughput virtual screening(HTVS)system integrating on-demand molecular generation and machine learning models covering the prediction of molecular properties and crystal packing mode scoring is established.With the proposed HTVS system,candidate molecules with promising properties and a desirable crystal packing mode are rapidly targeted from the generated molecular space containing 25112 molecules.Furthermore,a study of the crystal structure and properties shows that the good comprehensive performances of the target molecule are in agreement with the predicted results,thus verifying the effectiveness of the proposed methodology.This work demonstrates a new research paradigm for discovering novel energetic materials and can be extended to other organic materials without manifest obstacles.展开更多
Angiotensin I converting enzyme （ACE） plays an important physiological role in the regulation of hypertension. In this study, we applied virtual screening to discover a novel angiotensin I converting enzyme inhibito...Angiotensin I converting enzyme （ACE） plays an important physiological role in the regulation of hypertension. In this study, we applied virtual screening to discover a novel angiotensin I converting enzyme inhibitory peptides from milk casein. One potential hit was identified based on docking scores, subsequently confirmed by activity studies in vitro （IC50=20.85 μmol L-1）. The proposed peptide in this study contains a unique sequence, Lys-Val-Leu-Ile-Leu-Ala. Moreover, we performed the docking studies to understand the binding mode between the enzyme and peptide hit.展开更多
O-GlcNAc transferase （OGT） is one of essential mammalian enzymes, which catalyze the transfer of N-acetylglucosamine from UDP-N-acetylglucosamine （UDP-GlcNAc） to hydroxyl groups of serines and threonines （Ser/Thr...O-GlcNAc transferase （OGT） is one of essential mammalian enzymes, which catalyze the transfer of N-acetylglucosamine from UDP-N-acetylglucosamine （UDP-GlcNAc） to hydroxyl groups of serines and threonines （Ser/Thr） in proteins. Dysregulations of cellular O-GlcNAc have been implicated in diabetes, neurodegenerative disease, and cancer, which brings great interest in developing potent and specific small-molecular OGT inhibitors. In this work, we performed virtual screening on OGT catalytic site to identify potential inhibitors. 7134792 drug-like compounds from ZINC （a free database of commercially available compounds for virtual screening） and 4287550 compounds generated by FOG （fragment optimized growth program） were screened and the top 116 compounds ranked by docking score were analyzed. By comparing the screening results, we found FOG program can generate more compounds with better docking scores than ZINC. The top ZINC compounds ranked by docking score were grouped into two classes, which held the binding positions of UDP and GlcNAc of UDP- GlcNAc. Combined with individual fragments in binding pocket, de novo compounds were designed and proved to have better docking score. The screened and designed compounds may become a starting point for developing new drugs.展开更多
The serotonin 2A（5-HT2A） receptor has been implicated in several neurological conditions and potent 5-HT2A antagonists have therapeutic effects in the treatment of schizo phrenia and depression.In this study,a poten...The serotonin 2A（5-HT2A） receptor has been implicated in several neurological conditions and potent 5-HT2A antagonists have therapeutic effects in the treatment of schizo phrenia and depression.In this study,a potent novel 5-HT2A inhibitor 05245768 with a Ki value of （593.89±34.10） nmol/L was discovered by integrating a set of computational approaches and experiments（protein structure prediction,pharmacophore-based virtual screening,automated molecular docking and pharmacological bioassay）.The 5-HT2A receptor showed a negatively charged bin-ding pocket.The binding mode of compound 05245768 with 5-HT2A was obtained by GOLD docking procedure,which revealed the conserved interaction between protonated nitrogen in compound 05245768 and carboxylate group of D3.32 at the active site of 5-HT2A.展开更多
The interaction between Amyloid β(Aβ) peptide and acetylcholine receptor is the key for our understanding of how Aβ fragments block the ion channels within the synapses and thus induce Alzheimer’s disease.Here,mol...The interaction between Amyloid β(Aβ) peptide and acetylcholine receptor is the key for our understanding of how Aβ fragments block the ion channels within the synapses and thus induce Alzheimer’s disease.Here,molecular docking and molecular dynamics(MD)simulations were performed for the structural dynamics of the docking complex consisting of Aβ and α7-n ACh R(α7 nicotinic acetylcholine receptor),and the inter-molecular interactions between ligand and receptor were revealed.The results show that Aβ_(25-35) is bound toα7-n ACh R through hydrogen bonds and complementary shape,and the Aβ_(25-35) fragments would easily assemble in the ion channel of α7-n ACh R,then block the ion transfer process and induce neuronal apoptosis.The simulated amide-I band of Aβ_(25-35) in the complex is located at 1650.5 cm^(-1),indicating the backbone of Aβ_(25-35) tends to present random coil conformation,which is consistent with the result obtained from cluster analysis.Currently existing drugs were used as templates for virtual screening,eight new drugs were designed and semi-flexible docking was performed for their performance.The results show that,the interactions between new drugs and α7-n ACh R are strong enough to inhibit the aggregation of Aβ_(25-35) fragments in the ion channel,and also be of great potential in the treatment of Alzheimer’s disease.展开更多
As a zinc-dependent enzyme, metal-β-lactamase L1 contributes to the development of β-lactam antibiotic resistance. The metal-β-lactamase inhibitor can restore the efficacy of β-lactam antibiotics, and its developm...As a zinc-dependent enzyme, metal-β-lactamase L1 contributes to the development of β-lactam antibiotic resistance. The metal-β-lactamase inhibitor can restore the efficacy of β-lactam antibiotics, and its development has attracted much attention. In the present study, we used four widely-used virtual screening programs to screen 7035 small molecules to identify potential L1 inhibitors, and a high-throughput experimental model of L1 inhibitors was established. In this high-throughput testing model, the inhibition rate of 163 compounds on L1 exceeded 40%. The results of virtual screening of 7035 small molecules using the following four programs showed that among the top 1.35% of the compounds, their hit rates were ranked as Schr?dinger’s(5.26%), DS(1.05%), and Sybyl-x 2.0(1.05%), and Smina(2.11%).展开更多
Triple-negative breast cancer is an aggressive subtype that frequently develops resistance to chemotherapy. It is expected to develop new anti-tumor drugs through targeting the structure of G-quadruplexes of the genes...Triple-negative breast cancer is an aggressive subtype that frequently develops resistance to chemotherapy. It is expected to develop new anti-tumor drugs through targeting the structure of G-quadruplexes of the genes associated with this tumor. In this work, by targeting the 21-mer telomere G-quadruplex structure, compounds VB07 and VC02 were identified to stabilize the telomere G-quadruplex through structure-based high-throughput virtual screening. Cell cytotoxicity assay showed that VB07 and VC02 exhibited inhibitory effect on triple-negative breast cancer cells at the concentration of 5 μM. This study showed that structure-based high-throughput virtual screening was able to successfully identify the proper compounds targeting the telomere G-quadruplex, which exhibited inhibitory effects against the triple-negative breast cancer cells.展开更多
BRAF has been recognized as a promising target for cancer therapy. A number of crystal structures have been published. Molecular docking is one of the most effective techniques in the field of computer-aided drug des...BRAF has been recognized as a promising target for cancer therapy. A number of crystal structures have been published. Molecular docking is one of the most effective techniques in the field of computer-aided drug design（CADD）. Appropriate protein conformation and docking method are essential for the successful virtual screening experiments. One approach considering protein flexibility and multiple docking methods was proposed in this study. Six DFG-in/αC-helix-out crystal structures of BRAF, three docking programs（Glide, GOLD and Ligand Fit） and 12 scoring functions were applied for the best combination by judging from the results of pose prediction and retrospective virtual screening（VS）. The most accurate results（mean RMSD of about 0.6 A） of pose prediction were obtained with two complex structures（PDB： 3 C4 C and 3 SKC） using Glide SP. From the retrospective VS, the most active compounds were identified by using the complex structure of 3 SKC, indicated by a ROC/AUC score of 0.998 and an EF of 20.6 at 5% of the database screen with Glide-SP. On the whole, PDB 3 SKC could achieve a higher rate of correct reproduction, a better enrichment and more diverse compounds. A comparison of 3 SKC and the other X-ray crystal structures led to a rationale for the docking results. PDB 3 SKC could achieve a broad range of sulfonamide substitutions through an expanded hydrophobic pocket formed by a further shift of the αC-helix. Our study emphasized the necessity and significance of protein flexibility and scoring functions in both ligand docking and virtual screening.展开更多
The drug development process takes a long time since it requires sorting through a large number of inactive compounds from a large collection of compounds chosen for study and choosing just the most pertinent compound...The drug development process takes a long time since it requires sorting through a large number of inactive compounds from a large collection of compounds chosen for study and choosing just the most pertinent compounds that can bind to a disease protein.The use of virtual screening in pharmaceutical research is growing in popularity.During the early phases of medication research and development,it is crucial.Chemical compound searches are nowmore narrowly targeted.Because the databases containmore andmore ligands,thismethod needs to be quick and exact.Neural network fingerprints were created more effectively than the well-known Extended Connectivity Fingerprint(ECFP).Only the largest sub-graph is taken into consideration to learn the representation,despite the fact that the conventional graph network generates a better-encoded fingerprint.When using the average or maximum pooling layer,it also contains unrelated data.This article suggested the Graph Convolutional Attention Network(GCAN),a graph neural network with an attention mechanism,to address these problems.Additionally,it makes the nodes or sub-graphs that are used to create the molecular fingerprint more significant.The generated fingerprint is used to classify drugs using ensemble learning.As base classifiers,ensemble stacking is applied to Support Vector Machines(SVM),Random Forest,Nave Bayes,Decision Trees,AdaBoost,and Gradient Boosting.When compared to existing models,the proposed GCAN fingerprint with an ensemble model achieves relatively high accuracy,sensitivity,specificity,and area under the curve.Additionally,it is revealed that our ensemble learning with generated molecular fingerprint yields 91%accuracy,outperforming earlier approaches.展开更多
CDK<span style="white-space:nowrap;"><sub><sub><span style="font-family:Verdana;">2<span style="white-space:nowrap;"></sub></sub><span style=&...CDK<span style="white-space:nowrap;"><sub><sub><span style="font-family:Verdana;">2<span style="white-space:nowrap;"></sub></sub><span style="font-family:Verdana;"> is one of the most important members of Cyclin-dependent kinases. It is a critical modulator of various oncogenic signaling pathways, and its activity is vital for <span style="font-family:Verdana;">loss<span style="font-family:Verdana;"> of proliferative control during oncogenesis. This work has focused on developing a pharmacophore model for CDK<span style="white-space:nowrap;"><sub><sub><span style="font-family:Verdana;">2<span style="white-space:nowrap;"></sub></sub><span style="font-family:Verdana;"> inhibitors by using a dataset of known inhibitors as a pre-filter throughout the virtual screening and docking process. Consequently, the best pharmacophore model was made of one hydrogen bond acceptor, and two aromatic ring features with <span style="font-family:Verdana;">a <span style="font-family:Verdana;">high<span style="font-family:""><span style="font-family:Verdana;"> correlation value of 0.906. The validation findings proved out that the selected model can be used as a filter to screen new molecules like Enamine kinase hinge region directed library against CDK<span style="white-space:nowrap;"><sub><sub><span style="font-family:Verdana;">2<span style="white-space:nowrap;"></sub></sub><span style="font-family:Verdana;">. As a result, 69 hits were subjected to molecular docking studies. Eventually, three compounds<span style="font-family:Verdana;"> (<span style="font-family:""><span style="font-family:Verdana;">5909, 701 <span style="font-family:Verdana;">and<span style="font-family:Verdana;"> 8397<span style="font-family:Verdana;">) <span style="font-family:""><span style="font-family:Verdana;">scored good interaction energy values and strong molecular interactions. Hence, they were identified as leads for novel CDK<span style="white-space:nowrap;"><sub><sub><span style="font-family:Verdana;">2<span style="white-space:nowrap;"></sub></sub><span style="font-family:Verdana;"> inhibitors as anticancer drugs.展开更多
Chitosanases EAG1 is a classical glycoside hydrolase from Bacillus ehimensis. The previous researches showed that this Chitosanases can not only hydrolyze the b1,4-glycosidic bonds of chitosan to COS in different size...Chitosanases EAG1 is a classical glycoside hydrolase from Bacillus ehimensis. The previous researches showed that this Chitosanases can not only hydrolyze the b1,4-glycosidic bonds of chitosan to COS in different sizes but also keep a high catalytic activity in organic, which was useful for producing chitooligosaccharides and GlcN for use in the food and pharmacological industries. While it is instable in the liquid state. This shortcoming seriously restricts its industrial application. Here we used the modeled structure of EAG1 and the molecular modeling software package to screen the free chemical database ZINC. Moreover, the strategies including “initial filter” and consensus scoring were applied to accelerate the process and improve the success rate of virtual screening. Finally, five compounds were screened and they were purchased or synthetized to test their binding affinity against EAG1. The test results showed that one of them could inhibit the enzyme with an apparent Ki of 1.5 μM. The result may take the foundation for further inhibitor screening and design against EAG1 and the screened compound may also help to improve the liquid stability of EAG1 and expand its industrial application.展开更多
The aberrant overexpression of cyclin-dependent kinase 9 (CDK9) in cancer cells results in the loss of proliferative control, making it an attractive therapeutic target for various cancers. However, the highly structu...The aberrant overexpression of cyclin-dependent kinase 9 (CDK9) in cancer cells results in the loss of proliferative control, making it an attractive therapeutic target for various cancers. However, the highly structural similarity between CDK9 and CDK2 makes the development of novel selective CDK9 inhibitors a challenging task and thus limits their clinical applications. Here, an effective two-stage virtual screening strategy was developed to identify novel CDK9 inhibitors with better inhibitory activity and higher selectivity. The first screening stage aims to select potential compounds with better inhibitory activity than Roniciclib, one of the most effective CDK9 inhibitors, through reliable structure-based pharmacophoric virtual screening and accurate molecular docking analyses. The second stage employs a very detailed visual inspection process, in which several structural criteria describing the major difference between the binding pockets of CDK9 and CDK2 are taken into consideration, to identify compounds with higher selectivity than CAN508, one of the CDK9 inhibitors with distinguished selectivity. Finally, three compounds (NCI207113 from NCI database and TCM0004 and TCM3282 from TCM database) with better inhibitory activity and higher selectivity were successfully identified as novel CDK9 inhibitors. These three compounds also display excellent binding stabilities, great pharmacokinetic properties and low toxicity in MD simulations and ADMET predictions. Besides, the results of binding free energy calculations suggest that enhancing van der Waals interaction and nonpolar solvation energy and/or reducing polar solvation energy can significantly improve the binding affinity of these CDK9 inhibitors. Their clinical potentials to serve as anticancer drug candidates can be further evaluated through a series of <em>in vitro/in vivo</em> bioassays in the future. To the best of our knowledge, this is the first attempt to identify novel CDK9 inhibitors with both better inhibitory activity and higher selectivity through an effective two-stage virtual screening strategy.展开更多
Background: Dengue is a Neglected tropical disease (NTDs) with high incidence in Brazil. This disease is caused by Dengue virus and is transmitted by Aedes aegypti mosquito. The search for new approaches for controlli...Background: Dengue is a Neglected tropical disease (NTDs) with high incidence in Brazil. This disease is caused by Dengue virus and is transmitted by Aedes aegypti mosquito. The search for new approaches for controlling of this disease is the subject of numerous studies. The aaNAT is a key enzyme in the metabolism of A. aegypti and is crucial in the sclerotization process, as well as regulation of circadian rhythm and inactivation of neurotransmitters. Computational techniques applied to studies of biological systems become an effective weapon in the mapping and management of 3D data structures, giving direction and guidance of potential ligands that can form stable complexes with targets of interest, using a Molecular Docking approach. The present study was conducted by a virtual screening, followed by docking calculations, in order to find molecules that could inhibit aaNAT. In this study, we used available compounds in SAM database (Bioinformatics and Medicinal Chemistry Laboratory—Southwest Bahia State University, Jequié-Bahia, Brazil), PubChem and ZINC. Results: The result of dockings with selected ligands showed good energy affinities, presenting potential inhibitory interactions with the enzyme active site. Conclusions: The Coa-S-acetyl-tryptamine and 3-indoleacriloil-coenzyme-A showed the same binding energies -8.9 Kcal/Mol and were described as possible inhibitors of aaNAT.展开更多
Background:Many short peptides have proved to exhibit potential anti-hypertensive activity through the inhibition of the Angiotensin I-converting enzyme(ACE)activity and the regulation of blood pressure.However,the tr...Background:Many short peptides have proved to exhibit potential anti-hypertensive activity through the inhibition of the Angiotensin I-converting enzyme(ACE)activity and the regulation of blood pressure.However,the traditional experimental screening method for ACE inhibitory peptides is time consuming and costly,accompanied with the limitations as incomplete hydrolysis and peptides loss during purification process.Virtual methods with the aid of computer can break such bottle-neck of experimental work.In this study,an attempt was made to establish a library of di-and tri-peptides derived from proteins of Phascolosoma esculenta,a kind of seafood,through BIOPEP(http://www.uwm.edu.pl/biochemia/index.php/pl/biopep),and to screen highly active ACE inhibitory peptides by molecular docking with the help of LibDock module of Discovery Studio 3.5 software.Results:Two hundred and eighty four(284)di-and tri-peptides,derived from P.esculenta proteins after a virtual hydrolysis with pepsin,trypsin and a mixture of pepsin and trypsin,were predicted to possess ACE inhibitory activity,among which there are 99 ACE inhibitory peptides with estimated IC_(50) less than 50μM.Nine peptides were synthesized for the comparison between the estimated and the experimentally determined IC_(50).The results indicated that errors between the estimated and measured log(1/IC_(50))are all less than 1.0 unit.Conclusions:Virtual method for peptide library construction and ACE inhibitory peptides screening efficiently demonstrated that P.esculenta proteins are prospect resource for food-origin ACE inhibitory peptide.展开更多
The utilization of phosphorescent metal complexes as emissive dopants for organic light-emitting diodes(OLEDs)has been the subject of intense research.Cyclometalated Pt(Ⅱ)complexes are particularly popular triplet em...The utilization of phosphorescent metal complexes as emissive dopants for organic light-emitting diodes(OLEDs)has been the subject of intense research.Cyclometalated Pt(Ⅱ)complexes are particularly popular triplet emitters due to their color-tunable emissions.To make them viable for practical applications as OLED emitters,it is essential to develop Pt(Ⅱ)complexes with high radiative decay rate constants(k_(r))and photoluminescence quantum yields(PLQY).To this end,an efficient and accurate prediction tool is highly desirable.In this work,we propose a general yet powerful protocol achieving metal complex generation,high throughput virtual screening(HTVS),and fast predictions with high accuracy.More than 3600 potential structures are generated in a synthesis-friendly manner.Moreover,three HTVS-machine learning(ML)models are established using different algorithms with carefully designed features that are suitable for metal complexes.Specifically,30 potential candidates are filtered out by HTVS-ML models with a three-tier screening rule and put into accurate predictions with experimental calibrationΔ-learning method.The highly accurate prediction approach further reduces the stress of experiments and inspires greater confidence in identifying the most promising complexes as excellent emitters.As a result,12 promising complexes(k_(r)>10^(5) s^(−1) and PLQY>0.6)with the same superior core structures are confirmed from over 3600 Pt-complexes.Experiments revealed that two very close complexes have excellent emission properties and are consistent with the prediction results,providing strong evidence for the efficacy of the proposed protocol.We expect this protocol will become a valuable tool,expediting the rational design and rapid development of novel OLED materials with desired properties.展开更多
Objective To investigate endothelial cell heterogeneity in diabetic cardiomyopathy (DCM) and identify potential therapeutic targets of dapagliflozin in cardiac vascular endothelial cells.Methods ePharmaLib reverse vir...Objective To investigate endothelial cell heterogeneity in diabetic cardiomyopathy (DCM) and identify potential therapeutic targets of dapagliflozin in cardiac vascular endothelial cells.Methods ePharmaLib reverse virtual screening was performed on 15 148 protein crystals to identify the binding interactions between humanderived proteins and dapagliflozin.展开更多
基金funded by National Natural Science Foundation of China(21868003)Bama County Program for Talents in Science and Technology(BaRenKe20210045).
文摘The traditional nutritional and medical hemp(Cannabis sativa L.)seed protein were explored for the discovery and directional preparation of new xanthine oxidase inhibitory(XOI)peptides by structure-based virtual screening,compound synthesis,in vitro bioassay and proteolysis.Six subtypes of hemp seed edestin and albumin were in silico hydrolyzed by 29 proteases,and 192 encrypted bioactive peptides were screened out.Six peptides showed to be XOI peptides,of which four(about 67%)were released by elastase hydrolysis.The peptide DDNPRRFY displayed the highest XOI activity(IC50=(2.10±0.06)mg/mL),acting as a mixed inhibitor.The pancreatic elastase directionally prepared XOI hemp seed protein hydrolysates,from which 6 high-abundance XOI peptides encrypted 3 virtually-screened ones including the DDNPRRFY.The novel outstanding hemp seed protein-derived XOI peptides and their virtual screening and directed preparation methods provide a promising and applicable approach to conveniently and efficiently explore food-derived bioactive peptides.
文摘Current biodegradation timelines show that polyesters take over 200 years to break down. A crucial component of several industries, polyesters are relied upon for materials development and thus require sustainable alternatives. Recent works in generative modeling have made it possible to produce large sets of chemical structures, but current molecular screening methods are expensive, not scalable, and are oversimplified. This work evaluates whether a molecule’s biodegradability potential can be accurately predicted by training a model on recent experimental data. Additionally, three chemical descriptors were evaluated on the final molecules for their effects on biodegradability: molecular structure, bond types, and solubility. A Gradient Boosted Machine was trained on a dataset of 600 molecules and their binary labels on biodegradability. The classification model effectively captured the biodegradability property, yielding an Area Under the Receiver Operating Characteristics, AUROC, of 84% and an Area Under the Precision Recall Curve, or AUPRC, of 87%. Additionally, an existing amortized synthetic tree generation model, SynNet, validated each molecule by showing chemical synthesizability and producing simple and interpretable synthesis pathways. This approach of filtering by prediction and chemical rule interpretation is inexpensive, highly scalable and can capture the necessary complexity. Using this method, novel polyester candidates can be polymerized and produced into sustainable fabrics, reducing environmental stress from textile-reliant industries.
基金National Natural Science Foundation of China(Grant No.21272017 and 81172917)
文摘As a type II or III transmembrane glycoprotein, human CD38 is ubiquitously expressed in all mammalian tissues. CD38 is a multi-functional enzyme and a member of the ADP-ribosyl cyclase family, and it catalyzes nicotinamide adenine dinucleotide （NAD^＋） and nicotinamide adenine dinucleotide phosphate （NADP＋） to two distinct Ca^2＋ messengers as follows： cyclic ADP-ribose （cADPR） and nicotinic acid adenine dinucleotide phosphate （NAADP）, respectively. Moreover, both cADPR and NAADP mediate mobilization of intracellular Ca^2＋ targeting endoplasmic stores and the lysosomes, respectively. In this study, we combined ligand-based and structure-based virtual screening strategies to compare the inhibitor discovery efficacy based on natural substrates and the known inhibitors. The similarity queries towards SPECS database were carried out using ROCS and EON modules of OpenEye software. The hits were further docked to CD38 using AutoDock 4.05 program. In addition, ADME studies were also processed considering solubility in water and membrane permeability. Finally, we identified 17 compotmds-based on natural substrates and 10 compounds based on known inhibitor models. The results showed that the known inhibitor H2-based model was more efficient in virtual screening of CD38 non-covalent inhibitors.
基金National Natural Science Foundation of China (Grant No. 30271538)985 program,Ministry of Education of China
文摘To discover new lead compounds for M1 agonists. Ten typical M1 agonists were superimposed to build a M1 agonists 3D-pharmacophore model using distance-comparisons （DISCO） method without the previous knowledge of the three-dimensional structure of M1 receptor. Virtual screening strategy was used to analyze the Available Chemicals Directory-Screening Compounds （ACD-SC） to identify possible new hits. Twenty-two compounds which fit the pharmacophore model well and are not similar with known M1 agonists were purchased in order to evaluate their M1 receptor agonist activity. One of them shows M1 receptor agonist activity with EC50 of 4.90 μmol/L and maximum response. Multiple of 10.0 which shows it worthy of further study as a new lead compound for M1 agonists.
基金the Science Challenge Project(TZ2018004)the National Natural Science Foundation of China(21875228 and 21702195)for financial support。
文摘Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and experiments is presented for accelerating the discovery of novel energetic materials.A high-throughput virtual screening(HTVS)system integrating on-demand molecular generation and machine learning models covering the prediction of molecular properties and crystal packing mode scoring is established.With the proposed HTVS system,candidate molecules with promising properties and a desirable crystal packing mode are rapidly targeted from the generated molecular space containing 25112 molecules.Furthermore,a study of the crystal structure and properties shows that the good comprehensive performances of the target molecule are in agreement with the predicted results,thus verifying the effectiveness of the proposed methodology.This work demonstrates a new research paradigm for discovering novel energetic materials and can be extended to other organic materials without manifest obstacles.
基金supported by the National High Technology Research and Development Program of China(863 Program, 2008AA10Z313)the Foundation for Sciand Tech Research Project of Zhejiang Province, China(2006C12096)Natural Science Foundation of Zhejiang Province, China (Y3090026)
文摘Angiotensin I converting enzyme （ACE） plays an important physiological role in the regulation of hypertension. In this study, we applied virtual screening to discover a novel angiotensin I converting enzyme inhibitory peptides from milk casein. One potential hit was identified based on docking scores, subsequently confirmed by activity studies in vitro （IC50=20.85 μmol L-1）. The proposed peptide in this study contains a unique sequence, Lys-Val-Leu-Ile-Leu-Ala. Moreover, we performed the docking studies to understand the binding mode between the enzyme and peptide hit.
文摘O-GlcNAc transferase （OGT） is one of essential mammalian enzymes, which catalyze the transfer of N-acetylglucosamine from UDP-N-acetylglucosamine （UDP-GlcNAc） to hydroxyl groups of serines and threonines （Ser/Thr） in proteins. Dysregulations of cellular O-GlcNAc have been implicated in diabetes, neurodegenerative disease, and cancer, which brings great interest in developing potent and specific small-molecular OGT inhibitors. In this work, we performed virtual screening on OGT catalytic site to identify potential inhibitors. 7134792 drug-like compounds from ZINC （a free database of commercially available compounds for virtual screening） and 4287550 compounds generated by FOG （fragment optimized growth program） were screened and the top 116 compounds ranked by docking score were analyzed. By comparing the screening results, we found FOG program can generate more compounds with better docking scores than ZINC. The top ZINC compounds ranked by docking score were grouped into two classes, which held the binding positions of UDP and GlcNAc of UDP- GlcNAc. Combined with individual fragments in binding pocket, de novo compounds were designed and proved to have better docking score. The screened and designed compounds may become a starting point for developing new drugs.
基金Supported by the National High Technology Research and Development Program of China(No.2009AA02Z308)the Major State Basic Research Development Program of China(No.2010CB912601)the National Natural Science Foundation of China (No.20702009)
文摘The serotonin 2A（5-HT2A） receptor has been implicated in several neurological conditions and potent 5-HT2A antagonists have therapeutic effects in the treatment of schizo phrenia and depression.In this study,a potent novel 5-HT2A inhibitor 05245768 with a Ki value of （593.89±34.10） nmol/L was discovered by integrating a set of computational approaches and experiments（protein structure prediction,pharmacophore-based virtual screening,automated molecular docking and pharmacological bioassay）.The 5-HT2A receptor showed a negatively charged bin-ding pocket.The binding mode of compound 05245768 with 5-HT2A was obtained by GOLD docking procedure,which revealed the conserved interaction between protonated nitrogen in compound 05245768 and carboxylate group of D3.32 at the active site of 5-HT2A.
基金supported by the National Natural Science Foundation of China(No.21103021)the New Century Excellent Talent Project in University of Fujian Province,Opening Project of PCOSS,Xiamen University(No.201904)。
文摘The interaction between Amyloid β(Aβ) peptide and acetylcholine receptor is the key for our understanding of how Aβ fragments block the ion channels within the synapses and thus induce Alzheimer’s disease.Here,molecular docking and molecular dynamics(MD)simulations were performed for the structural dynamics of the docking complex consisting of Aβ and α7-n ACh R(α7 nicotinic acetylcholine receptor),and the inter-molecular interactions between ligand and receptor were revealed.The results show that Aβ_(25-35) is bound toα7-n ACh R through hydrogen bonds and complementary shape,and the Aβ_(25-35) fragments would easily assemble in the ion channel of α7-n ACh R,then block the ion transfer process and induce neuronal apoptosis.The simulated amide-I band of Aβ_(25-35) in the complex is located at 1650.5 cm^(-1),indicating the backbone of Aβ_(25-35) tends to present random coil conformation,which is consistent with the result obtained from cluster analysis.Currently existing drugs were used as templates for virtual screening,eight new drugs were designed and semi-flexible docking was performed for their performance.The results show that,the interactions between new drugs and α7-n ACh R are strong enough to inhibit the aggregation of Aβ_(25-35) fragments in the ion channel,and also be of great potential in the treatment of Alzheimer’s disease.
基金Natural Sciences Foundation of China (Grant No. 81872913)National High-tech R&D Program (863 Program, Grant No. 2015AA020911)。
文摘As a zinc-dependent enzyme, metal-β-lactamase L1 contributes to the development of β-lactam antibiotic resistance. The metal-β-lactamase inhibitor can restore the efficacy of β-lactam antibiotics, and its development has attracted much attention. In the present study, we used four widely-used virtual screening programs to screen 7035 small molecules to identify potential L1 inhibitors, and a high-throughput experimental model of L1 inhibitors was established. In this high-throughput testing model, the inhibition rate of 163 compounds on L1 exceeded 40%. The results of virtual screening of 7035 small molecules using the following four programs showed that among the top 1.35% of the compounds, their hit rates were ranked as Schr?dinger’s(5.26%), DS(1.05%), and Sybyl-x 2.0(1.05%), and Smina(2.11%).
基金National Natural Science Foundation of China(Grant No.31701791,21732002,31672558 and 21502060)Huazhong Agricultural University Scientific&Technological Self-innovation Foundation(Grant No.2662017PY113,2015RC013 and 2662015PY208)Open fund of The State Key Laboratory of Bio-organic and Natural Products Chemistry,CAS(Grant No.SKLBNPC16343)。
文摘Triple-negative breast cancer is an aggressive subtype that frequently develops resistance to chemotherapy. It is expected to develop new anti-tumor drugs through targeting the structure of G-quadruplexes of the genes associated with this tumor. In this work, by targeting the 21-mer telomere G-quadruplex structure, compounds VB07 and VC02 were identified to stabilize the telomere G-quadruplex through structure-based high-throughput virtual screening. Cell cytotoxicity assay showed that VB07 and VC02 exhibited inhibitory effect on triple-negative breast cancer cells at the concentration of 5 μM. This study showed that structure-based high-throughput virtual screening was able to successfully identify the proper compounds targeting the telomere G-quadruplex, which exhibited inhibitory effects against the triple-negative breast cancer cells.
基金supported by the National Natural Science Foundation of China(21102181,81302634 and 21572273)
文摘BRAF has been recognized as a promising target for cancer therapy. A number of crystal structures have been published. Molecular docking is one of the most effective techniques in the field of computer-aided drug design（CADD）. Appropriate protein conformation and docking method are essential for the successful virtual screening experiments. One approach considering protein flexibility and multiple docking methods was proposed in this study. Six DFG-in/αC-helix-out crystal structures of BRAF, three docking programs（Glide, GOLD and Ligand Fit） and 12 scoring functions were applied for the best combination by judging from the results of pose prediction and retrospective virtual screening（VS）. The most accurate results（mean RMSD of about 0.6 A） of pose prediction were obtained with two complex structures（PDB： 3 C4 C and 3 SKC） using Glide SP. From the retrospective VS, the most active compounds were identified by using the complex structure of 3 SKC, indicated by a ROC/AUC score of 0.998 and an EF of 20.6 at 5% of the database screen with Glide-SP. On the whole, PDB 3 SKC could achieve a higher rate of correct reproduction, a better enrichment and more diverse compounds. A comparison of 3 SKC and the other X-ray crystal structures led to a rationale for the docking results. PDB 3 SKC could achieve a broad range of sulfonamide substitutions through an expanded hydrophobic pocket formed by a further shift of the αC-helix. Our study emphasized the necessity and significance of protein flexibility and scoring functions in both ligand docking and virtual screening.
文摘The drug development process takes a long time since it requires sorting through a large number of inactive compounds from a large collection of compounds chosen for study and choosing just the most pertinent compounds that can bind to a disease protein.The use of virtual screening in pharmaceutical research is growing in popularity.During the early phases of medication research and development,it is crucial.Chemical compound searches are nowmore narrowly targeted.Because the databases containmore andmore ligands,thismethod needs to be quick and exact.Neural network fingerprints were created more effectively than the well-known Extended Connectivity Fingerprint(ECFP).Only the largest sub-graph is taken into consideration to learn the representation,despite the fact that the conventional graph network generates a better-encoded fingerprint.When using the average or maximum pooling layer,it also contains unrelated data.This article suggested the Graph Convolutional Attention Network(GCAN),a graph neural network with an attention mechanism,to address these problems.Additionally,it makes the nodes or sub-graphs that are used to create the molecular fingerprint more significant.The generated fingerprint is used to classify drugs using ensemble learning.As base classifiers,ensemble stacking is applied to Support Vector Machines(SVM),Random Forest,Nave Bayes,Decision Trees,AdaBoost,and Gradient Boosting.When compared to existing models,the proposed GCAN fingerprint with an ensemble model achieves relatively high accuracy,sensitivity,specificity,and area under the curve.Additionally,it is revealed that our ensemble learning with generated molecular fingerprint yields 91%accuracy,outperforming earlier approaches.
文摘CDK<span style="white-space:nowrap;"><sub><sub><span style="font-family:Verdana;">2<span style="white-space:nowrap;"></sub></sub><span style="font-family:Verdana;"> is one of the most important members of Cyclin-dependent kinases. It is a critical modulator of various oncogenic signaling pathways, and its activity is vital for <span style="font-family:Verdana;">loss<span style="font-family:Verdana;"> of proliferative control during oncogenesis. This work has focused on developing a pharmacophore model for CDK<span style="white-space:nowrap;"><sub><sub><span style="font-family:Verdana;">2<span style="white-space:nowrap;"></sub></sub><span style="font-family:Verdana;"> inhibitors by using a dataset of known inhibitors as a pre-filter throughout the virtual screening and docking process. Consequently, the best pharmacophore model was made of one hydrogen bond acceptor, and two aromatic ring features with <span style="font-family:Verdana;">a <span style="font-family:Verdana;">high<span style="font-family:""><span style="font-family:Verdana;"> correlation value of 0.906. The validation findings proved out that the selected model can be used as a filter to screen new molecules like Enamine kinase hinge region directed library against CDK<span style="white-space:nowrap;"><sub><sub><span style="font-family:Verdana;">2<span style="white-space:nowrap;"></sub></sub><span style="font-family:Verdana;">. As a result, 69 hits were subjected to molecular docking studies. Eventually, three compounds<span style="font-family:Verdana;"> (<span style="font-family:""><span style="font-family:Verdana;">5909, 701 <span style="font-family:Verdana;">and<span style="font-family:Verdana;"> 8397<span style="font-family:Verdana;">) <span style="font-family:""><span style="font-family:Verdana;">scored good interaction energy values and strong molecular interactions. Hence, they were identified as leads for novel CDK<span style="white-space:nowrap;"><sub><sub><span style="font-family:Verdana;">2<span style="white-space:nowrap;"></sub></sub><span style="font-family:Verdana;"> inhibitors as anticancer drugs.
文摘Chitosanases EAG1 is a classical glycoside hydrolase from Bacillus ehimensis. The previous researches showed that this Chitosanases can not only hydrolyze the b1,4-glycosidic bonds of chitosan to COS in different sizes but also keep a high catalytic activity in organic, which was useful for producing chitooligosaccharides and GlcN for use in the food and pharmacological industries. While it is instable in the liquid state. This shortcoming seriously restricts its industrial application. Here we used the modeled structure of EAG1 and the molecular modeling software package to screen the free chemical database ZINC. Moreover, the strategies including “initial filter” and consensus scoring were applied to accelerate the process and improve the success rate of virtual screening. Finally, five compounds were screened and they were purchased or synthetized to test their binding affinity against EAG1. The test results showed that one of them could inhibit the enzyme with an apparent Ki of 1.5 μM. The result may take the foundation for further inhibitor screening and design against EAG1 and the screened compound may also help to improve the liquid stability of EAG1 and expand its industrial application.
文摘The aberrant overexpression of cyclin-dependent kinase 9 (CDK9) in cancer cells results in the loss of proliferative control, making it an attractive therapeutic target for various cancers. However, the highly structural similarity between CDK9 and CDK2 makes the development of novel selective CDK9 inhibitors a challenging task and thus limits their clinical applications. Here, an effective two-stage virtual screening strategy was developed to identify novel CDK9 inhibitors with better inhibitory activity and higher selectivity. The first screening stage aims to select potential compounds with better inhibitory activity than Roniciclib, one of the most effective CDK9 inhibitors, through reliable structure-based pharmacophoric virtual screening and accurate molecular docking analyses. The second stage employs a very detailed visual inspection process, in which several structural criteria describing the major difference between the binding pockets of CDK9 and CDK2 are taken into consideration, to identify compounds with higher selectivity than CAN508, one of the CDK9 inhibitors with distinguished selectivity. Finally, three compounds (NCI207113 from NCI database and TCM0004 and TCM3282 from TCM database) with better inhibitory activity and higher selectivity were successfully identified as novel CDK9 inhibitors. These three compounds also display excellent binding stabilities, great pharmacokinetic properties and low toxicity in MD simulations and ADMET predictions. Besides, the results of binding free energy calculations suggest that enhancing van der Waals interaction and nonpolar solvation energy and/or reducing polar solvation energy can significantly improve the binding affinity of these CDK9 inhibitors. Their clinical potentials to serve as anticancer drug candidates can be further evaluated through a series of <em>in vitro/in vivo</em> bioassays in the future. To the best of our knowledge, this is the first attempt to identify novel CDK9 inhibitors with both better inhibitory activity and higher selectivity through an effective two-stage virtual screening strategy.
文摘Background: Dengue is a Neglected tropical disease (NTDs) with high incidence in Brazil. This disease is caused by Dengue virus and is transmitted by Aedes aegypti mosquito. The search for new approaches for controlling of this disease is the subject of numerous studies. The aaNAT is a key enzyme in the metabolism of A. aegypti and is crucial in the sclerotization process, as well as regulation of circadian rhythm and inactivation of neurotransmitters. Computational techniques applied to studies of biological systems become an effective weapon in the mapping and management of 3D data structures, giving direction and guidance of potential ligands that can form stable complexes with targets of interest, using a Molecular Docking approach. The present study was conducted by a virtual screening, followed by docking calculations, in order to find molecules that could inhibit aaNAT. In this study, we used available compounds in SAM database (Bioinformatics and Medicinal Chemistry Laboratory—Southwest Bahia State University, Jequié-Bahia, Brazil), PubChem and ZINC. Results: The result of dockings with selected ligands showed good energy affinities, presenting potential inhibitory interactions with the enzyme active site. Conclusions: The Coa-S-acetyl-tryptamine and 3-indoleacriloil-coenzyme-A showed the same binding energies -8.9 Kcal/Mol and were described as possible inhibitors of aaNAT.
基金supported by‘National Natural Science Foundation of China(No.31301413)’‘National Major Science and Technology Projects of China(No.2012ZX09304009)’the‘Fundamental Research Funds for the Central Universities’,People's Republic of China.
文摘Background:Many short peptides have proved to exhibit potential anti-hypertensive activity through the inhibition of the Angiotensin I-converting enzyme(ACE)activity and the regulation of blood pressure.However,the traditional experimental screening method for ACE inhibitory peptides is time consuming and costly,accompanied with the limitations as incomplete hydrolysis and peptides loss during purification process.Virtual methods with the aid of computer can break such bottle-neck of experimental work.In this study,an attempt was made to establish a library of di-and tri-peptides derived from proteins of Phascolosoma esculenta,a kind of seafood,through BIOPEP(http://www.uwm.edu.pl/biochemia/index.php/pl/biopep),and to screen highly active ACE inhibitory peptides by molecular docking with the help of LibDock module of Discovery Studio 3.5 software.Results:Two hundred and eighty four(284)di-and tri-peptides,derived from P.esculenta proteins after a virtual hydrolysis with pepsin,trypsin and a mixture of pepsin and trypsin,were predicted to possess ACE inhibitory activity,among which there are 99 ACE inhibitory peptides with estimated IC_(50) less than 50μM.Nine peptides were synthesized for the comparison between the estimated and the experimentally determined IC_(50).The results indicated that errors between the estimated and measured log(1/IC_(50))are all less than 1.0 unit.Conclusions:Virtual method for peptide library construction and ACE inhibitory peptides screening efficiently demonstrated that P.esculenta proteins are prospect resource for food-origin ACE inhibitory peptide.
基金supported by the RGC General Research Fund under Grant No.17309620Hong Kong Quantum AI Lab Limited and Air@InnoHK of Hong Kong Government+4 种基金the support from National Natural Science Foundation of China(Grant Nos.22073007 and 22473022)Shenzhen Basic Research Key Project Fund(Grant No.JCYJ20220818103200001)National Natural Science Foundation of China(No.22273010)Department of Science and Technology of Jilin Province(20210402075GH)C-M C and F-F H acknowledge Guangdong Major Project of Basic and Applied Basic Research(Grant No.2019B030302009).
文摘The utilization of phosphorescent metal complexes as emissive dopants for organic light-emitting diodes(OLEDs)has been the subject of intense research.Cyclometalated Pt(Ⅱ)complexes are particularly popular triplet emitters due to their color-tunable emissions.To make them viable for practical applications as OLED emitters,it is essential to develop Pt(Ⅱ)complexes with high radiative decay rate constants(k_(r))and photoluminescence quantum yields(PLQY).To this end,an efficient and accurate prediction tool is highly desirable.In this work,we propose a general yet powerful protocol achieving metal complex generation,high throughput virtual screening(HTVS),and fast predictions with high accuracy.More than 3600 potential structures are generated in a synthesis-friendly manner.Moreover,three HTVS-machine learning(ML)models are established using different algorithms with carefully designed features that are suitable for metal complexes.Specifically,30 potential candidates are filtered out by HTVS-ML models with a three-tier screening rule and put into accurate predictions with experimental calibrationΔ-learning method.The highly accurate prediction approach further reduces the stress of experiments and inspires greater confidence in identifying the most promising complexes as excellent emitters.As a result,12 promising complexes(k_(r)>10^(5) s^(−1) and PLQY>0.6)with the same superior core structures are confirmed from over 3600 Pt-complexes.Experiments revealed that two very close complexes have excellent emission properties and are consistent with the prediction results,providing strong evidence for the efficacy of the proposed protocol.We expect this protocol will become a valuable tool,expediting the rational design and rapid development of novel OLED materials with desired properties.
文摘Objective To investigate endothelial cell heterogeneity in diabetic cardiomyopathy (DCM) and identify potential therapeutic targets of dapagliflozin in cardiac vascular endothelial cells.Methods ePharmaLib reverse virtual screening was performed on 15 148 protein crystals to identify the binding interactions between humanderived proteins and dapagliflozin.
