Application of Molecular Dynamics Simulations to the Design of Nucleotide Inhibitors Binding to Norovirus Polymerase

Freedman, Holly; Kundu, Joydeb Kumar; Tchesnokov, Egor P.; Law, John Lok Man; Nieman, James A.; Schinazi, Raymond F.; Tyrrell, D. Lorne; Götte, Matthias; Houghton, Michael

doi:10.1021/acs.jcim.0c00742

Cited by 8 publications

(5 citation statements)

References 67 publications

(123 reference statements)

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“…R f = 0.50 (5% MeOH in EtOAc) was a single spot when visualized with 10% phosphomolybdic acid in ethanol. 1 N 2 -(tert-Butoxycarbonyl)-N-{(2S)-4-chloro-3-oxo-1-[(3S)-2-oxopyrrolidin-3-yl]butan-2-yl}-L-leucinamide (12). This material was prepared using procedures in refs 11 and 39.…”

Section: ■ Experimental Sectionmentioning

confidence: 99%

“…We also thank the DMPK group at WuXi AppTech for performing the ADME experiments reported in Table 3. We thank the staff at SSRL beamline 12…”

Section: Notesmentioning

confidence: 99%

“…10,11 In 2017, the Li Ka Shing Applied Virology Institute (LKSAVI) began to explore direct acting antivirals to treat norovirus infections. Different viral targets were examined, including the polymerase 12 and peptidomimetic cysteine 3CLP inhibitors. Utilizing the literature at the time, various compounds were generated as part of the 3CLP portion of that program.…”

Section: ■ Introductionmentioning

confidence: 99%

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Peptidomimetic α-Acyloxymethylketone Warheads with Six-Membered Lactam P1 Glutamine Mimic: SARS-CoV-2 3CL Protease Inhibition, Coronavirus Antiviral Activity, and in Vitro Biological Stability

et al. 2021

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Recurring coronavirus outbreaks, such as the current COVID-19 pandemic, establish a necessity to develop direct-acting antivirals that can be readily administered and are active against a broad spectrum of coronaviruses. Described in this Article are novel α-acyloxymethylketone warhead peptidomimetic compounds with a six-membered lactam glutamine mimic in P1. Compounds with potent SARS-CoV-2 3CL protease and in vitro viral replication inhibition were identified with low cytotoxicity and good plasma and glutathione stability. Compounds 15e , 15h , and 15l displayed selectivity for SARS-CoV-2 3CL protease over CatB and CatS and superior in vitro SARS-CoV-2 antiviral replication inhibition compared with the reported peptidomimetic inhibitors with other warheads. The cocrystallization of 15l with SARS-CoV-2 3CL protease confirmed the formation of a covalent adduct. α-Acyloxymethylketone compounds also exhibited antiviral activity against an alphacoronavirus and non-SARS betacoronavirus strains with similar potency and a better selectivity index than remdesivir. These findings demonstrate the potential of the substituted heteroaromatic and aliphatic α-acyloxymethylketone warheads as coronavirus inhibitors, and the described results provide a basis for further optimization.

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Section: ■ Experimental Sectionmentioning

confidence: 99%

“…We also thank the DMPK group at WuXi AppTech for performing the ADME experiments reported in Table 3. We thank the staff at SSRL beamline 12…”

Section: Notesmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

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Peptidomimetic α-Acyloxymethylketone Warheads with Six-Membered Lactam P1 Glutamine Mimic: SARS-CoV-2 3CL Protease Inhibition, Coronavirus Antiviral Activity, and in Vitro Biological Stability

et al. 2021

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“…There are numerous studies that report the successful application of FEP+ in live drug discovery projects [17][18][19][20][21][22][23][24][25] . Although physics-based affinity prediction methods are intrinsically computationally expensive, large clusters of graphical processing units and cloud computing enable the evaluation of relative binding free energies for potentially thousands of pairs of compounds within the typical time-constraints of medicinal chemistry deadlines.…”

mentioning

confidence: 99%

The maximal and current accuracy of rigorous protein-ligand binding free energy calculations

Ross,

Lu,

Scarabelli

et al. 2023

Commun Chem

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Computational techniques can speed up the identification of hits and accelerate the development of candidate molecules for drug discovery. Among techniques for predicting relative binding affinities, the most consistently accurate is free energy perturbation (FEP), a class of rigorous physics-based methods. However, uncertainty remains about how accurate FEP is and can ever be. Here, we present what we believe to be the largest publicly available dataset of proteins and congeneric series of small molecules, and assess the accuracy of the leading FEP workflow. To ascertain the limit of achievable accuracy, we also survey the reproducibility of experimental relative affinity measurements. We find a wide variability in experimental accuracy and a correspondence between binding and functional assays. When careful preparation of protein and ligand structures is undertaken, FEP can achieve accuracy comparable to experimental reproducibility. Throughout, we highlight reliable protocols that can help maximize the accuracy of FEP in prospective studies.

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“…There are numerous studies that report the successful application of FEP+ in live drug discovery projects [13][14][15][16][17][18][19][20] . Although physics-based affinity prediction methods are intrinsically computationally expensive, large clusters of graphical processing units and cloud computing enable the evaluation of relative binding free energies for potentially thousands of pairs of compounds within the typical time-constraints of medicinal chemistry deadlines.…”

Section: Introductionmentioning

confidence: 99%

The maximal and current accuracy of rigorous protein-ligand binding free energy calculations

Ross

Lü

Scarabelli

et al. 2022

Preprint

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It is well recognized that computational techniques can speed up the identification of hits and accelerate the optimization of such hits to lead series and development candidate molecules. A class of rigorous physics-based methods known as free energy perturbation (FEP) have emerged as the most consistently accurate relative affinity prediction tool available to support such efforts. Yet, there remains uncertainty about how accurate these techniques are and how accurate they can ever be. Here, we assemble what we believe to be the largest publicly available dataset of proteins and congeneric series of small molecules and assess the accuracy of the leading FEP workflow in predicting relative binding affinities. To ascertain the limit of achievable accuracy, we survey the reproducibility of experimental relative affinity measurements by comparing chemical series that have been assayed by two or more different techniques. We find a wide variability in experimental accuracy and a general correspondence between binding and functional assays. When the protein and ligand structures are prepared with care, we find that FEP can achieve a level of accuracy close to what we find in our experimental survey. Throughout, we highlight reliable protocols that can help maximize the accuracy of FEP in prospective studies.

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Application of Molecular Dynamics Simulations to the Design of Nucleotide Inhibitors Binding to Norovirus Polymerase

Cited by 8 publications

References 67 publications

Peptidomimetic α-Acyloxymethylketone Warheads with Six-Membered Lactam P1 Glutamine Mimic: SARS-CoV-2 3CL Protease Inhibition, Coronavirus Antiviral Activity, and in Vitro Biological Stability

Peptidomimetic α-Acyloxymethylketone Warheads with Six-Membered Lactam P1 Glutamine Mimic: SARS-CoV-2 3CL Protease Inhibition, Coronavirus Antiviral Activity, and in Vitro Biological Stability

The maximal and current accuracy of rigorous protein-ligand binding free energy calculations

The maximal and current accuracy of rigorous protein-ligand binding free energy calculations

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