scholarly journals Virtual screening for high affinity guests for synthetic supramolecular receptors

2015 ◽  
Vol 6 (5) ◽  
pp. 2790-2794 ◽  
Author(s):  
William Cullen ◽  
Simon Turega ◽  
Christopher A. Hunter ◽  
Michael D. Ward
Keyword(s):  
Virtual Screening ◽  
Ligand Docking ◽  
High Affinity

The protein/ligand docking programme ‘GOLD’ can be used to identify new strongly-binding guests for a synthetic coordination cage host.

scholarly journals Identification of New Potential Inhibitors of Quorum Sensing through a Specialized Multi-Level Computational Approach

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2600
Author(s):  
Fábio G. Martins ◽  
André Melo ◽  
Sérgio F. Sousa
Keyword(s):  
Virtual Screening ◽  
Quorum Sensing ◽  
In Silico ◽  
Bacterial Infections ◽  
Extracellular Polymeric Substances ◽  
Free Energy Calculations ◽  
Ligand Docking ◽  
Screening Tests ◽  
Scoring Functions ◽  
Potential Inhibitors

Biofilms are aggregates of microorganisms anchored to a surface and embedded in a self-produced matrix of extracellular polymeric substances and have been associated with 80% of all bacterial infections in humans. Because bacteria in biofilms are less amenable to antibiotic treatment, biofilms have been associated with developing antibiotic resistance, a problem that urges developing new therapeutic options and approaches. Interfering with quorum-sensing (QS), an important process of cell-to-cell communication by bacteria in biofilms is a promising strategy to inhibit biofilm formation and development. Here we describe and apply an in silico computational protocol for identifying novel potential inhibitors of quorum-sensing, using CviR—the quorum-sensing receptor from Chromobacterium violaceum—as a model target. This in silico approach combines protein-ligand docking (with 7 different docking programs/scoring functions), receptor-based virtual screening, molecular dynamic simulations, and free energy calculations. Particular emphasis was dedicated to optimizing the discrimination ability between active/inactive molecules in virtual screening tests using a target-specific training set. Overall, the optimized protocol was used to evaluate 66,461 molecules, including those on the ZINC/FDA-Approved database and to the Mu.Ta.Lig Virtual Chemotheca. Multiple promising compounds were identified, yielding good prospects for future experimental validation and for drug repurposing towards QS inhibition.

Discovery of High-Affinity Ligands of σ1Receptor, ERG2, and Emopamil Binding Protein by Pharmacophore Modeling and Virtual Screening

2005 ◽  
Vol 48 (15) ◽  
pp. 4754-4764 ◽  
Author(s):  
Christian Laggner ◽  
Claudia Schieferer ◽  
Birgit Fiechtner ◽  
Gloria Poles ◽  
Rémy D. Hoffmann ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Binding Protein ◽  
Pharmacophore Modeling ◽  
Affinity Ligands ◽  
High Affinity

Structure-based virtual screening of novel, high-affinity BRD4 inhibitors

2014 ◽  
Vol 10 (9) ◽  
pp. 2384 ◽  
Author(s):  
Charuvaka Muvva ◽  
E. R. Azhagiya Singam ◽  
S. Sundar Raman ◽  
V. Subramanian
Keyword(s):  
Virtual Screening ◽  
High Affinity

scholarly journals PSOVina: The hybrid particle swarm optimization algorithm for protein–ligand docking

2015 ◽  
Vol 13 (03) ◽  
pp. 1541007 ◽  
Author(s):  
Marcus C. K. Ng ◽  
Simon Fong ◽  
Shirley W. I. Siu
Keyword(s):  
Particle Swarm Optimization ◽  
Virtual Screening ◽  
Particle Swarm ◽  
Ligand Docking ◽  
Conformational Search ◽  
Search Problem ◽  
Data Set ◽  
Swarm Optimization ◽  
Screening Experiments ◽  
Hybrid Particle Swarm Optimization

Protein–ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden–Fletcher–Goldfarb–Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein–ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51–60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein–ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo .

Virtual Screening Using Protein−Ligand Docking:  Avoiding Artificial Enrichment

2004 ◽  
Vol 44 (3) ◽  
pp. 793-806 ◽  
Author(s):  
Marcel L. Verdonk ◽  
Valerio Berdini ◽  
Michael J. Hartshorn ◽  
Wijnand T. M. Mooij ◽  
Christopher W. Murray ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Ligand Docking

Virtual Screening Using Protein—Ligand Docking: Avoiding Artificial Enrichment.

ChemInform ◽  
2004 ◽  
Vol 35 (30) ◽  
Author(s):  
Marcel L. Verdonk ◽  
Valerio Berdini ◽  
Michael J. Hartshorn ◽  
Wijnand T. M. Mooij ◽  
Christopher W. Murray ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Ligand Docking

Virtual Screening of Inhibitors Against Spike Glycoprotein of SARS-CoV-2: A Drug Repurposing Approach

2020 ◽  
Author(s):  
Kanishka Senathilake ◽  
Sameera Samarakoon ◽  
Kamani Tennekoon
Keyword(s):  
Virtual Screening ◽  
Drug Repurposing ◽  
Homology Model ◽  
Respiratory Illness ◽  
Receptor Interaction ◽  
S Protein ◽  
Surface Receptors ◽  
High Affinity ◽  
Food Dye ◽  
Novel Coronavirus

The novel coronavirus (SARS-CoV-2) is a human pathogen recently emerged in China, causing a global pandemic of severe respiratory illness (COVID19). SARS-CoV-2 makes entry into human cells through its spike (S) protein that binds to cell surface receptors. Widespread of SARS-CoV-2 has been attributed to high affinity of S protein to its receptor. A homology model of the receptor binding domain of SARS-CoV-2 S protein (RBD) was built. RBD- receptor docking and published molecular dynamics data were used to map the key RBD-receptor interaction hotspot (RBDhp) on the RBD. Primary virtual screening was carried out against RBDhp using more than 3300 compounds approved by U.S Food and Drug Administration (FDA) and other authorities for human use. Compounds that bind to hpRBD with a binding energy ≤ - 6.5 kcal/mol were subjected to secondary screening using a recently published cryo EM (2.9 Å) structure of RBD. A cardiac glycoside (dgitoxin), two anthracyclines (zorubicin and aclarubicin), a tetracycline derivative (rolitetracycline), a cephalosporin (cefoperazone) and a food dye (E-155) were predicted to be most potent inhibitors of RBD – receptor interaction. An anti-asthmatic drug (zafirlukast) and several other drugs (itrazol, fazadinium, troglitazone, gliquidone, Idarubicin, Oxacillin) were found to be high affinity binders that may have a potential to inhibit RBD – receptor interaction.

Sign in / Sign up

Export Citation Format

Share Document