Use of molecular docking computational tools in drug discovery

Stanzione, Francesca; Giangreco, Ilenia; Cole, Jason C.

doi:10.1016/bs.pmch.2021.01.004

Cited by 320 publications

(177 citation statements)

References 238 publications

Supporting

Mentioning

176

Contrasting

Unclassified

Order By: Relevance

“…In the research phase for phytochemicals with activity against S. mutans, carried out in the present study, no specific research was carried out for the classes of phytoconstituents. However, surprisingly, all isolated and identified chemical structures (24 compounds) belonged to the class of phenolic compounds, more specifically the class of flavonoids (2,3,4,5,6,7,8,9,12,13,14,15,16,17,18,19,20,21,23,24) and isoflavonoid derivatives (1, 10, 11, and 22). Five phytocompounds evaluated were elected as one of the three best ligands for at least three target proteins, highlighting the following compounds: 11 (erystagallin) (highlighted for 6 targets), 10 (erycristagallin) (highlighted for 5 targets), 1 (methoxyficifonilol) (highlighted for 4 targets), 20 (malvidin-3,5-diglucoside), and 2 (sophoraflavanone G), which provided indications of a possible and desirable multi-target action of these compounds.…”

Section: Discussionmentioning

confidence: 99%

“…With the evolution of bioinformatics, biotechnology, and molecular biology, including the determination of protein structures by using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy, it has become increasingly easier to use in silico tools to predict functioning drugs. Thus, in the last 20 years, more than 60 different molecular docking software were developed by universities and companies [16].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Molecular Docking of Phytochemicals against Streptococcus mutans Virulence Targets: A Proteomic Insight into Drug Planning

Silva¹,

Deps²,

Sakaguchi³

et al. 2022

Dentistry

View full text Add to dashboard Cite

Streptococcus mutans (S. mutans) is the most prevalent and most associated with dental caries. Here we aim to identify, through an in silico study, potential bioactive molecules against S. mutans. Twenty-four bioactive molecules with proven action against S. mutans were selected: 1-methoxyficifolinol; 5,7,2′,4′-tetrahydroxy-8-lavandulylflavanone (sophoraflavanone G); 6,8-diprenylgenistein; apigenin; artocarpesin; artocarpin; darbergioidin; dihydrobiochanin A; dihydrocajanin (5,2′,4′-trihydroxy-7-methoxyisoflavanone); erycristagallin; Erystagallin; ferreirin; fisetin; kaempferol; licoricidin; licorisoflavan A; licorisoflavan C; licorisoflavan E; luteolin (3′,4′,5,7-tetrahydroxyflavone); malvidin-3,5-diglucoside; myricetin; orientanol B; quercetin; and quercitrin. Moreover, we selected nine important target proteins for the virulence of this microorganism to perform as drug targets: antigen I/II (region V) (PDB: 1JMM); Antigen I/II (carbox-terminal region) (PDB: 3QE5); Spap (PDB: 3OPU); UA159sp signaling peptide (PDB: 2I2J); TCP3 signaling peptide (PDB: 2I2H); ATP-binding protein ComA (PDB: 3VX4); glucanosucrase (PDB: 3AIC); dextranase (PDB: 3VMO), and Hemolysin (PDB: 2RK5). Five molecules were revealed to be the best ligands for at least three target proteins, highlighting the following compounds: 11 (erystagallin), 10 (erycristagallin), 1 (methoxyficifonilol), 20 (malvidin-3,5-diglucoside), and 2 (sophoraflavanone G), which indicates a possible multi-target action of these compounds. Therefore, based on these findings, in vitro and in vivo tests should be performed to validate the effectiveness of these compounds in inhibiting S. mutans virulence factors. Furthermore, the promising results of these assays will allow the incorporation of these phytoconstituents in products for oral use for the control of tooth decay.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Molecular Docking of Phytochemicals against Streptococcus mutans Virulence Targets: A Proteomic Insight into Drug Planning

Silva¹,

Deps²,

Sakaguchi³

et al. 2022

Dentistry

View full text Add to dashboard Cite

show abstract

“…This method effectively makes up for the inadequacy of traditional methods and can obtain detailed results quickly. To date, the interaction between proteins and small molecules by molecular docking has been widely used in food [ 22 ], bioengineering [ 23 ], medicine and other industries [ 24 ], and molecular docking technology has made great progress [ 25 ]. The evaluation of the results of docking prediction mainly analyzes the RMSD value of the docking compound.…”

Section: Discussionmentioning

confidence: 99%

A combined application of molecular docking technology and indirect ELISA for the serodiagnosis of bovine tuberculosis

et al. 2022

View full text Add to dashboard Cite

Background There is an urgent need to find reliable and rapid bovine tuberculosis (bTB) diagnostics in response to the rising prevalence of bTB worldwide. Toll-like receptor 2 (TLR2) recognizes components of bTB and initiates antigen-presenting cells to mediate humoral immunity. Evaluating the affinity of antigens with TLR2 can form the basis of a new method for the diagnosis of bTB based on humoral immunity. Objectives To develop a reliable and rapid strategy to improve diagnostic tools for bTB. Methods In this study, we expressed and purified the sixteen bTB-specific recombinant proteins in Escherichia coli . The two antigenic proteins, MPT70 and MPT83, which were most valuable for serological diagnosis of bTB were screened. Molecular docking technology was used to analyze the affinity of MPT70, MPT83, dominant epitope peptide of MPT70 (M1), and dominant epitope peptide MPT83 (M2) with TLR2, combined with the detection results of enzyme-linked immunosorbent assay to evaluate the molecular docking effect. Results The results showed that interaction surface Cα-atom root mean square deviation of proteins (M1, M2, MPT70, MPT83)-TLR2 protein are less than 2.5 A, showing a high affinity. It is verified by clinical serum samples that MPT70, MPT83, MPT70-MPT83 showed good diagnostic potential for the detection of anti-bTB IgG and M1, M2 can replace the whole protein as the detection antigen. Conclusions Molecular docking to evaluate the affinity of bTB protein and TLR2 combined with ELISA provides new insights for the diagnosis of bTB.

show abstract

“…In the current study, two targets, such as β1- and β2-AR, were considered for molecular docking with PubChem compounds using ADV [ 70 ]. ADV is a freely available open-source molecular docking tool and has been highly cited since its availability from 2010 [ 74 ]. ADV is an excellent choice as a widely used docking tool to determine accurate and rapid binding affinity prediction between the protein and ligand [ 75 ].…”

Section: Methodsmentioning

confidence: 99%

Screening of β1- and β2-Adrenergic Receptor Modulators through Advanced Pharmacoinformatics and Machine Learning Approaches

Islam¹,

Rallabandi²,

Mohammed³

et al. 2021

IJMS

View full text Add to dashboard Cite

Cardiovascular diseases (CDs) are a major concern in the human race and one of the leading causes of death worldwide. β-Adrenergic receptors (β1-AR and β2-AR) play a crucial role in the overall regulation of cardiac function. In the present study, structure-based virtual screening, machine learning (ML), and a ligand-based similarity search were conducted for the PubChem database against both β1- and β2-AR. Initially, all docked molecules were screened using the threshold binding energy value. Molecules with a better binding affinity were further used for segregation as active and inactive through ML. The pharmacokinetic assessment was carried out on molecules retained in the above step. Further, similarity searching of the ChEMBL and DrugBank databases was performed. From detailed analysis of the above data, four compounds for each of β1- and β2-AR were found to be promising in nature. A number of critical ligand-binding amino acids formed potential hydrogen bonds and hydrophobic interactions. Finally, a molecular dynamics (MD) simulation study of each molecule bound with the respective target was performed. A number of parameters obtained from the MD simulation trajectories were calculated and substantiated the stability between the protein-ligand complex. Hence, it can be postulated that the final molecules might be crucial for CDs subjected to experimental validation.

show abstract

Use of molecular docking computational tools in drug discovery

Cited by 320 publications

References 238 publications

Molecular Docking of Phytochemicals against Streptococcus mutans Virulence Targets: A Proteomic Insight into Drug Planning

Molecular Docking of Phytochemicals against Streptococcus mutans Virulence Targets: A Proteomic Insight into Drug Planning

A combined application of molecular docking technology and indirect ELISA for the serodiagnosis of bovine tuberculosis

Screening of β1- and β2-Adrenergic Receptor Modulators through Advanced Pharmacoinformatics and Machine Learning Approaches

Contact Info

Product

Resources

About