Side chain similarity comparisons for integrated drug repositioning and potential toxicity assessments in epidemic response scenarios: The case for COVID-19

Ghani, Nur Syatila Ab; Emrizal, Reeki; Makmur, Haslina; Firdaus-Raih, Mohd

doi:10.1016/j.csbj.2020.10.013

Cited by 4 publications

(4 citation statements)

References 77 publications

(57 reference statements)

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“…The same principle that allows a compound to be repositioned for therapeutic outcomes is also applicable for causing toxicity or other side effects due to off-target binding. Therefore, the identification of such sites in human proteins could also provide insights into potential side-effects ( 18 ). This can be a useful tool to investigate the reported side-effects to known drugs and can be a useful aid for future clinical trials programs not only in the context of drug repurposing but also for the development of new drugs.…”

Section: Resultsmentioning

confidence: 99%

“…However, web server access only solutions may have limitations in terms of high-throughput processing capacity and programmatic access. For example the work reported for compiling the database of 3D sites that are similar to known drug binding sites for the purpose of drug repositioning ( 17 , 18 ) and the work reporting the discovery of novel base triples in RNA structures ( 19 , 20 ) were carried out by standalone versions of the ASSAM and NASSAM computer programs and not their respective web services. Stand-alone tools that are able to carry out high-throughput analysis fill a complementary gap in the scenarios presented above.…”

Section: Introductionmentioning

confidence: 99%

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GrAfSS: a webserver for substructure similarity searching and comparisons in the structures of proteins and RNA

Ghani

Emrizal

Moffit

et al. 2022

Nucleic Acids Research

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The GrAfSS (Graph theoretical Applications for Substructure Searching) webserver is a platform to search for three-dimensional substructures of: (i) amino acid side chains in protein structures; and (ii) base arrangements in RNA structures. The webserver interfaces the functions of five different graph theoretical algorithms – ASSAM, SPRITE, IMAAAGINE, NASSAM and COGNAC – into a single substructure searching suite. Users will be able to identify whether a three-dimensional (3D) arrangement of interest, such as a ligand binding site or 3D motif, observed in a protein or RNA structure can be found in other structures available in the Protein Data Bank (PDB). The webserver also allows users to determine whether a protein or RNA structure of interest contains substructural arrangements that are similar to known motifs or 3D arrangements. These capabilities allow for the functional annotation of new structures that were either experimentally determined or computationally generated (such as the coordinates generated by AlphaFold2) and can provide further insights into the diversity or conservation of functional mechanisms of structures in the PDB. The computed substructural superpositions are visualized using integrated NGL viewers. The GrAfSS server is available at http://mfrlab.org/grafss/.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

GrAfSS: a webserver for substructure similarity searching and comparisons in the structures of proteins and RNA

Ghani

Emrizal

Moffit

et al. 2022

Nucleic Acids Research

Self Cite

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“…An interesting aspect in drug repurposing is the binding site similarity between targets. Therefore, the similarity between pocket sequences can be used to identify new targets 70 , 71 .…”

Section: Resultsmentioning

confidence: 99%

KUALA: a machine learning-driven framework for kinase inhibitors repositioning

Simone

Sardina

Gulotta

et al. 2022

Sci Rep

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The family of protein kinases comprises more than 500 genes involved in numerous functions. Hence, their physiological dysfunction has paved the way toward drug discovery for cancer, cardiovascular, and inflammatory diseases. As a matter of fact, Kinase binding sites high similarity has a double role. On the one hand it is a critical issue for selectivity, on the other hand, according to poly-pharmacology, a synergistic controlled effect on more than one target could be of great pharmacological interest. Another important aspect of binding similarity is the possibility of exploit it for repositioning of drugs on targets of the same family. In this study, we propose our approach called Kinase drUgs mAchine Learning frAmework (KUALA) to automatically identify kinase active ligands by using specific sets of molecular descriptors and provide a multi-target priority score and a repurposing threshold to suggest the best repurposable and non-repurposable molecules. The comprehensive list of all kinase-ligand pairs and their scores can be found at https://github.com/molinfrimed/multi-kinases.

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“…Many studies about clinical diagnosis [6], transmission relationship [7], drug vaccine [8], spatiotemporal pattern [9], risk assessment [10], and epidemic transmission [11] of COVID-19 have been done by scholars since the breakout of the epidemic, which has made great contributions to the prevention and control of COVID-19. With the arrival of the post-epidemic period, the risk assessment of epidemic has gradually become the focus of attention [12,13].…”

Section: Introductionmentioning

confidence: 99%

COVID-19 Risk Assessment: Contributing to Maintaining Urban Public Health Security and Achieving Sustainable Urban Development

Zhang

Yuan

2021

Sustainability

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As the most infectious disease in 2020, COVID-19 is an enormous shock to urban public health security and to urban sustainable development. Although the epidemic in China has been brought into control at present, the prevention and control of it is still the top priority of maintaining public health security. Therefore, the accurate assessment of epidemic risk is of great importance to the prevention and control even to overcoming of COVID-19. Using the fused data obtained from fusing multi-source big data such as POI (Point of Interest) data and Tencent-Yichuxing data, this study assesses and analyzes the epidemic risk and main factors that affect the distribution of COVID-19 on the basis of combining with logistic regression model and geodetector model. What’s more, the following main conclusions are obtained: the high-risk areas of the epidemic are mainly concentrated in the areas with relatively dense permanent population and floating population, which means that the permanent population and floating population are the main factors affecting the risk level of the epidemic. In other words, the reasonable control of population density is greatly conducive to reducing the risk level of the epidemic. Therefore, the control of regional population density remains the key to epidemic prevention and control, and home isolation is also the best means of prevention and control. The precise assessment and analysis of the epidemic conducts by this study is of great significance to maintain urban public health security and achieve the sustainable urban development.

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Side chain similarity comparisons for integrated drug repositioning and potential toxicity assessments in epidemic response scenarios: The case for COVID-19

Abstract: Graphical abstract

Cited by 4 publications

References 77 publications

GrAfSS: a webserver for substructure similarity searching and comparisons in the structures of proteins and RNA

GrAfSS: a webserver for substructure similarity searching and comparisons in the structures of proteins and RNA

KUALA: a machine learning-driven framework for kinase inhibitors repositioning

COVID-19 Risk Assessment: Contributing to Maintaining Urban Public Health Security and Achieving Sustainable Urban Development

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