Systematic Studies on the Protocol and Criteria for Selecting a Covalent Docking Tool

Wen, Chang; Yan, Xin; Gu, Qiong; Du, Jiewen; Wu, Di; Lu, Yutong; Zhou, Huihao; Xu, Jing

doi:10.3390/molecules24112183

Cited by 24 publications

(34 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Though many covalent docking tools have been developed, covalent docking is still rarely used in virtual screening since it is quite timeconsuming in comparison to noncovalent docking. 32 A recent study demonstrated that covalent docking does not perform significantly better than noncovalent docking. Conversely, noncovalent docking successfully predicts correct binding conformations for many covalent complexes that are failed in covalent docking.…”

Section: ■ Resultsmentioning

confidence: 99%

“…Virtual screening is performed against the selected binding pocket using the covalent NP database. Though many covalent docking tools have been developed, covalent docking is still rarely used in virtual screening since it is quite time-consuming in comparison to noncovalent docking . A recent study demonstrated that covalent docking does not perform significantly better than noncovalent docking.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Discovery of Targeted Covalent Natural Products against PLK1 by Herb-Based Screening

Hao

Liu

Kuang

et al. 2020

J. Chem. Inf. Model.

View full text Add to dashboard Cite

Natural products (NPs) are a rich source of drug discovery, and some of them act by covalently binding to the targets. Recently, targeted covalent natural product (TCNP) design has gained considerable attention since this approach offers significant benefits in improving biological efficacy and decreasing the off-target side effects. However, most of the known TCNPs were discovered by chance. Rational approaches for a systematic screen of TCNPs are much needed. Here, we developed a combined computational and experimental approach to carry out herb-based screening to identify TCNPs against proper cysteine residues in the target proteins. The herb-based TCNP screening approach (HB-TCNP) starts from a druggable pocket and cysteine residue prediction, followed by virtual screening of a covalent NP database and herb-based mapping to identify candidate herbs for experimental validation. Herbs with time-dependent activity are selected, and their NPs are experimentally tested to further screen covalent NPs. We have successfully applied HB-TCNP to screen anti-PLK1 herbs and NPs with high efficacy. Cys67 and Cys133 in the ATP binding pocket of PLK1 were used in the search. Five herbs were tested and exhibited PLK1 inhibition activity to some extent, among which Scutellaria baicalensis showed the most potent activity with time dependency. Further experimental studies showed that the main active compounds in Scutellaria baicalensis, baicalein and baicalin, covalently bind PLK1 through Cys133. Our study provided an efficient way to rationally design TCNPs and to make better use of herb medicines. The Cys133 residue in PLK1 serves as a novel covalent site for further drug discovery against PLK1.

show abstract

Section: ■ Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Discovery of Targeted Covalent Natural Products against PLK1 by Herb-Based Screening

Hao

Liu

Kuang

et al. 2020

J. Chem. Inf. Model.

View full text Add to dashboard Cite

show abstract

“…It has been suggested that for an ideal covalent-docking tool, the success rate should not be dependent on protein classes, ligand warhead classes, residue types, and reaction mechanisms [ 93 ]. However, the performance of the present covalent-docking tools is largely dependent on these aforementioned criteria.…”

Section: Selecting An Ideal Covalent-docking Program For Virtual-scre...mentioning

confidence: 99%

Docking covalent targets for drug discovery: stimulating the computer-aided drug design community of possible pitfalls and erroneous practices

et al. 2022

View full text Add to dashboard Cite

The continuous approval of covalent drugs in recent years for the treatment of diseases has led to an increased search for covalent agents by medicinal chemists and computational scientists worldwide. In the computational parlance, molecular docking which is a popular tool to investigate the interaction of a ligand and a protein target, does not account for the formation of covalent bond, and the increasing application of these conventional programs to covalent targets in early drug discovery practice is a matter of utmost concern. Thus, in this comprehensive review, we sought to educate the docking community about the realization of covalent docking and the existence of suitable programs to make their future virtual-screening events on covalent targets worthwhile and scientifically rational. More interestingly, we went beyond the classical description of the functionality of covalent-docking programs down to selecting the ‘best’ program to consult with during a virtual-screening campaign based on receptor class and covalent warhead chemistry. In addition, we made a highlight on how covalent docking could be achieved using random conventional docking software. And lastly, we raised an alert on the growing erroneous molecular docking practices with covalent targets. Our aim is to guide scientists in the rational docking pursuit when dealing with covalent targets, as this will reduce false-positive results and also increase the reliability of their work for translational research. Graphical abstract

show abstract

“…Protein docking-based methods directly predict the interaction between host receptor protein and the spike protein of SARS-CoV-2. The protein docking algorithms are divided into rigid and flexible ones (Sable and Jois, 2015;Lensink et al, 2016;Xu et al, 2018;Wen et al, 2019). Rigid docking methods like ZDOCK (Pierce et al, 2014) and MEGADOCK (Ohue et al, 2014) are usually simple and less time-consuming.…”

Section: Introductionmentioning

confidence: 99%

Systematic Tracing of Susceptible Animals to SARS-CoV-2 by a Bioinformatics Framework

Sun

Wang²,

Wang³

et al. 2022

Front. Microbiol.

View full text Add to dashboard Cite

Since the outbreak of SARS-CoV-2 in 2019, the Chinese horseshoe bats were considered as a potential original host of SARS-CoV-2. In addition, cats, tigers, lions, mints, and ferrets were naturally or experimentally infected with SARS-CoV-2. For the surveillance and control of this highly infectious disease, it is critical to trace susceptible animals and predict the consequence of potential mutations at the binding region of viral spike protein and host ACE2 protein. This study proposed a novel bioinformatics framework to systematically trace susceptible animals to SARS-CoV-2 and predict the binding affinity between susceptible animals’ mutated/un-mutated ACE2 receptors. As a result, we identified a few animals posing a potential risk of infection with SARS-CoV-2 using the docking analysis of ACE2 protein and viral spike protein. The binding affinity of some of these species is weaker than that of humans but more potent than that of Chinese horseshoe bats. We also found that a few point mutations in human ACE2 protein or viral spike protein could significantly enhance their binding affinity, posing an enormous potential threat to public health. The ancestors of the Omicron may evolve rapidly through the accumulation of mutations in infecting the host and jumped into human beings. These findings indicate that if the epidemic expands, there may be a human-animal-human transmission route, which will increase the difficulty of disease prevention and control.

show abstract

Systematic Studies on the Protocol and Criteria for Selecting a Covalent Docking Tool

Cited by 24 publications

References 49 publications

Discovery of Targeted Covalent Natural Products against PLK1 by Herb-Based Screening

Discovery of Targeted Covalent Natural Products against PLK1 by Herb-Based Screening

Docking covalent targets for drug discovery: stimulating the computer-aided drug design community of possible pitfalls and erroneous practices

Systematic Tracing of Susceptible Animals to SARS-CoV-2 by a Bioinformatics Framework

Contact Info

Product

Resources

About