Predicting the bioactive conformations of macrocycles: a molecular dynamics-based docking procedure with DynaDock

Uğur, İlke; Schroft, Maja; Marion, Antoine; Glaser, Manuel; Antes, Iris

doi:10.1007/s00894-019-4077-5

Cited by 15 publications

(21 citation statements)

References 52 publications

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“…This group of compounds are emerging as promising leads which offer high bioavailability with enhanced affinity and selectivity for drug targets (Driggers et al, 2008;Mallinson & Collins, 2012;Heinis, 2014). Although large cyclic compounds are generally difficult to model using docking tools, their active conformations could be obtained with higher confidence when molecular dynamics-based computation methods are employed (Sindhikara et al, 2017;Ugur et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Identification of a novel inhibitor of SARS-CoV-2 3CL-PRO through virtual screening and molecular dynamics simulation

Bepari¹,

Reza²

2021

PeerJ

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Background The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has ravaged lives across the globe since December 2019, and new cases are still on the rise. Peoples’ ongoing sufferings trigger scientists to develop safe and effective remedies to treat this deadly viral disease. While repurposing the existing FDA-approved drugs remains in the front line, exploring drug candidates from synthetic and natural compounds is also a viable alternative. This study employed a comprehensive computational approach to screen inhibitors for SARS-CoV-2 3CL-PRO (also known as the main protease), a prime molecular target to treat coronavirus diseases. Methods We performed 100 ns GROMACS molecular dynamics simulations of three high-resolution X-ray crystallographic structures of 3CL-PRO. We extracted frames at 10 ns intervals to mimic conformational diversities of the target protein in biological environments. We then used AutoDock Vina molecular docking to virtual screen the Sigma–Aldrich MyriaScreen Diversity Library II, a rich collection of 10,000 druglike small molecules with diverse chemotypes. Subsequently, we adopted in silico computation of physicochemical properties, pharmacokinetic parameters, and toxicity profiles. Finally, we analyzed hydrogen bonding and other protein-ligand interactions for the short-listed compounds. Results Over the 100 ns molecular dynamics simulations of 3CL-PRO’s crystal structures, 6LZE, 6M0K, and 6YB7, showed overall integrity with mean Cα root-mean-square deviation (RMSD) of 1.96 (±0.35) Å, 1.98 (±0.21) Å, and 1.94 (±0.25) Å, respectively. Average root-mean-square fluctuation (RMSF) values were 1.21 ± 0.79 (6LZE), 1.12 ± 0.72 (6M0K), and 1.11 ± 0.60 (6YB7). After two phases of AutoDock Vina virtual screening of the MyriaScreen Diversity Library II, we prepared a list of the top 20 ligands. We selected four promising leads considering predicted oral bioavailability, druglikeness, and toxicity profiles. These compounds also demonstrated favorable protein-ligand interactions. We then employed 50-ns molecular dynamics simulations for the four selected molecules and the reference ligand 11a in the crystallographic structure 6LZE. Analysis of RMSF, RMSD, and hydrogen bonding along the simulation trajectories indicated that S51765 would form a more stable protein-ligand complexe with 3CL-PRO compared to other molecules. Insights into short-range Coulombic and Lennard-Jones potentials also revealed favorable binding of S51765 with 3CL-PRO. Conclusion We identified a potential lead for antiviral drug discovery against the SARS-CoV-2 main protease. Our results will aid global efforts to find safe and effective remedies for COVID-19.

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Section: Discussionmentioning

confidence: 99%

Identification of a novel inhibitor of SARS-CoV-2 3CL-PRO through virtual screening and molecular dynamics simulation

Bepari¹,

Reza²

2021

PeerJ

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“…In fact, the conformational analysis of macrocycles still remains a highly challenging problem and there needs to be further research, method developments and experimental validations in that area. We actually encourage interested readers to consult further studies regarding specific macrocyclic structures and their conformational arrangements such as the conformational control of macrocycles by remote structural modification by Appavoo et al [34], the prediction of the bioactive conformations of macrocycles using molecular dynamics and docking by Ugur et al [35], or the conformational exploration study of dissymmetric macrolides antibiotics by Belaidi et al [36]. SIME generates macrolide structures in SMILES format that can be further processed to generate 3D conformations by using cheminformatics tools (e.g., Prime macrocycle conformational sampling [27], ConfBuster [28]).…”

Section: Discussionmentioning

confidence: 99%

SIME: synthetic insight-based macrolide enumerator to generate the V1B library of 1 billion macrolides

2020

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We report on a new cheminformatics enumeration technology-SIME, synthetic insight-based macrolide enumerator-a new and improved software technology. SIME can enumerate fully assembled macrolides with synthetic feasibility by utilizing the constitutional and structural knowledge extracted from biosynthetic aspects of macrolides. Taken into account by the software are key information such as positions in macrolide structures at which chemical components can be inserted, and the types of structural motifs and sugars of interest that can be synthesized and incorporated at those positions. Additionally, we report on the chemical distribution analysis of the newly SIME-generated V1B (virtual 1 billion) library of macrolides. Those compounds were built based on the core of the Erythromycin structure, 13 structural motifs and a library of sugars derived from eighteen bioactive macrolides. This new enumeration technology can be coupled with cheminformatics approaches such as QSAR modeling and molecular docking to aid in drug discovery for rational designing of next generation macrolide therapeutics with desirable pharmacokinetic properties.

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“…Computational studies : For all modeling studies the X‐ray structure PDB ID: 5VZ2 ((ClpP from S. aureus + acyldepsipeptide)) of the Sa ClpP protein with bound ADEP was used. The modeling procedure applied is based on a molecular dynamics‐based docking pipeline, which was previously developed and optimized specifically for the docking of macrocyclic compounds . It contains the following steps: I) Conformational sampling of the compounds in aqueous solution, clustering and extraction of the most prominent conformations of the macrocycle.…”

Section: Methodsmentioning

confidence: 99%

Acyldepsipeptide Probes Facilitate Specific Detection of Caseinolytic Protease P Independent of Its Oligomeric and Activity State

et al. 2020

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Caseinolytic protease P (ClpP) is a tetradecameric peptidase that assembles with chaperones such as ClpX to gain proteolytic activity. Acyldepsipeptides (ADEPs) are small‐molecule mimics of ClpX that bind into hydrophobic pockets on the apical site of the complex, thereby activating ClpP. Detection of ClpP has so far been facilitated with active‐site‐directed probes which depend on the activity and oligomeric state of the complex. To expand the scope of ClpP labeling, we took a stepwise synthetic approach toward customized ADEP photoprobes. Structure–activity relationship studies with small fragments and ADEP derivatives paired with modeling studies revealed the design principles for suitable probe molecules. The derivatives were tested for activation of ClpP and subsequently applied in labeling studies of the wild‐type peptidase as well as enzymes bearing mutations at the active site and an oligomerization sensor. Satisfyingly, the ADEP photoprobes provided a labeling readout of ClpP independent of its activity and oligomeric state.

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Predicting the bioactive conformations of macrocycles: a molecular dynamics-based docking procedure with DynaDock

Cited by 15 publications

References 52 publications

Identification of a novel inhibitor of SARS-CoV-2 3CL-PRO through virtual screening and molecular dynamics simulation

Identification of a novel inhibitor of SARS-CoV-2 3CL-PRO through virtual screening and molecular dynamics simulation

SIME: synthetic insight-based macrolide enumerator to generate the V1B library of 1 billion macrolides

Acyldepsipeptide Probes Facilitate Specific Detection of Caseinolytic Protease P Independent of Its Oligomeric and Activity State

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