LigRMSD: a web server for automatic structure matching and RMSD calculations among identical and similar compounds in protein-ligand docking

Velázquez‐Libera, José Luis; Durán-Verdugo, Fabio; Valdés-Jiménez, Alejandro; Núñez-Vivanco, Gabriel; Caballero, Julio

doi:10.1093/bioinformatics/btaa018

Cited by 112 publications

(87 citation statements)

References 9 publications

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“…In order to validate the ligand superimposition procedure, RMSDs between the superimposed ligands (ligands 3-15, 17-18 and 34-36) and the reference ligand (ligand 16) were S19 computed using the heavy atoms of the maximum common substructure for the ligands compared and the web server ligRMSD. 55 Table S12 shows that the RMSD values are low, as expected.…”

Section: S18supporting

confidence: 76%

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Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

Nunes-Alves¹,

Ormersbach²,

Wade³

2021

Preprint

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<div>There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each protein-ligand complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of protein-</div><div>ligand complexes to predict binding parameters. We introduce the option to use multiple structures to describe each ligand-protein complex into COMBINE analysis and</div><div>apply this to study the effects of protein flexibility on the derivation of dissociation rate constants (k<sub>off</sub>) for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression and allowed the computation of k<sub>off</sub> values. The QSKR model obtained using single, energy minimized crystal structures for each ligand-protein complex had a higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, the incorporation of protein-ligand flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, like interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures, showing that COMBINE analysis is a promising method to design leads with improved kinetic rates for flexible proteins.</div>

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Section: S18supporting

confidence: 76%

“…Hydrogens were added using pdb2pqr 38,39 at pH 7.2 for the protein and Babel 40 for the ligands. All protein structures had a net charge of -7 e. and MDAnalysis 1.0.0 53,54 (details and validation using ligRMSD 55 are given in section S2).…”

Section: Modification Of Combine Software To Use Multiple Structures mentioning

confidence: 99%

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

Nunes-Alves¹,

Ormersbach²,

Wade³

2021

Preprint

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“…These compounds were then filtered by RMSD value [30], to evaluate experimental stability of the docked ligand conformers. RMSD values around 1.5 Å , are considered successful and stable while those beyond 2 Å indicate instability of ligand conformation and docking parameters [36]. For SARS-CoV-2 protein M pro , the binding energy observed for these compounds ranged from−7.950 to −0.339 kcal/mol while for spike glycoprotein, binding energy ranged from −8.088 to −5.437 kcal/mol.…”

Section: Structure-based Virtual Screening and Molecular Docking Of Amentioning

confidence: 99%

Identification of Potential SARS-CoV-2 Main Protease and Spike Protein Inhibitors from the Genus Aloe: An In Silico Study for Drug Development

et al. 2021

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Severe acute respiratory syndrome coronavirus (SARS-CoV-2) disease is a global rapidly spreading virus showing very high rates of complications and mortality. Till now, there is no effective specific treatment for the disease. Aloe is a rich source of isolated phytoconstituents that have an enormous range of biological activities. Since there are no available experimental techniques to examine these compounds for antiviral activity against SARS-CoV-2, we employed an in silico approach involving molecular docking, dynamics simulation, and binding free energy calculation using SARS-CoV-2 essential proteins as main protease and spike protein to identify lead compounds from Aloe that may help in novel drug discovery. Results retrieved from docking and molecular dynamics simulation suggested a number of promising inhibitors from Aloe. Root mean square deviation (RMSD) and root mean square fluctuation (RMSF) calculations indicated that compounds 132, 134, and 159 were the best scoring compounds against main protease, while compounds 115, 120, and 131 were the best scoring ones against spike glycoprotein. Compounds 120 and 131 were able to achieve significant stability and binding free energies during molecular dynamics simulation. In addition, the highest scoring compounds were investigated for their pharmacokinetic properties and drug-likeness. The Aloe compounds are promising active phytoconstituents for drug development for SARS-CoV-2.

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“…To verify the docking results reproducibility, we calculate the root-mean-square deviation (RMSD) between the ligand designed in silico, and LigHAO, our ligand reference discharged from the Protein Data Bank. RMSD calculations were performed using the LigRMSD server 1.0 program 54 . All docking figures were built using Pymol software version 1.8 [55][56][57] .…”

Section: Docking Experimentsmentioning

confidence: 99%

Insight Into the Binding Mode Knowledge of New Possible Anti-Hypertensive Compounds Designed in Silico Using Neutral Endopeptidase (NEP) As A Target.

Lamazares

Cañizares-Carmenate

Castillo-Garit

et al. 2021

Preprint

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Arterial hypertension is a health problem that affects millions of people around the world. Particularly in Chile, according to the last health survey in 2019, 28.7% of the population had this condition, and arterial hypertension complications cause one in three deaths per year. In this work, we have used molecular simulation tools to evaluate new compounds designed in silico by our group as possible anti-hypertensive agents, taking Neutral Endopeptidase (NEP) as a target, a key enzyme in the arterial hypertension regulation at the level kidney. We use docking experiments, molecular dynamics simulation, free energy decomposition calculations means of Molecular Mechanics Poisson–Boltzmann (MM-PBSA) method and ligand efficiency analysis. To identify the best anti-hypertensive agent we realized pharmacokinetic and toxicological predictions (ADME-Tox). The principal results obtained shown the ligands designed in silico were adequately oriented in the thermolysin active centre. The Lig783, Lig2177, and Lig3444 compounds were those with better dynamic behaviour. The energetic components that contribute to the complexes stability are the electrostatic and Van der Waals components; however, when the ADME-Tox properties were analyzed, we conclude that the best anti-hypertensive candidate agents are Lig783 and Lig3444, taking Neutra Endopeptidase as a target.

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LigRMSD: a web server for automatic structure matching and RMSD calculations among identical and similar compounds in protein-ligand docking

Cited by 112 publications

References 9 publications

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

Identification of Potential SARS-CoV-2 Main Protease and Spike Protein Inhibitors from the Genus Aloe: An In Silico Study for Drug Development

Insight Into the Binding Mode Knowledge of New Possible Anti-Hypertensive Compounds Designed in Silico Using Neutral Endopeptidase (NEP) As A Target.

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LigRMSD: a web server for automatic structure matching and RMSD calculations among identical and similar compounds in protein-ligand docking

Cited by 112 publications

References 9 publications

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

Identification of Potential SARS-CoV-2 Main Protease and Spike Protein Inhibitors from the Genus Aloe: An In Silico Study for Drug Development

Insight Into the Binding Mode Knowledge of New Possible Anti-Hypertensive Compounds Designed in Silico Using Neutral Endopeptidase&nbsp;(NEP) As A Target.

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Product

Resources

About

Insight Into the Binding Mode Knowledge of New Possible Anti-Hypertensive Compounds Designed in Silico Using Neutral Endopeptidase (NEP) As A Target.