Evidence map›Paper›PMID 39599762›Full record

ArticleViruses2024

Identification and Ranking of Binding Sites from Structural Ensembles: Application to SARS-CoV-2.

Maria Lazou, Ayse A Bekar-Cesaretli, Sandor Vajda, Diane Joseph-McCarthy

Abstract read
In one paragraph

Article in Viruses, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Maria LazouDepartment of Biomedical Engineering, Boston University, Boston, MA 02215, USA.ORCID 0009-0003-6443-8060
Ayse A Bekar-CesaretliDepartment of Chemistry, Boston University, Boston, MA 02215, USA.ORCID 0000-0001-9122-4955
Sandor VajdaDepartment of Biomedical Engineering, Boston University, Boston, MA 02215, USA.ORCID 0000-0003-1540-8220
Diane Joseph-McCarthyDepartment of Biomedical Engineering, Boston University, Boston, MA 02215, USA.ORCID 0000-0001-9685-6177

Funding

Analysis and Prediction of Molecular InteractionsR35GM118078 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI SANDOR VAJDA · 2016 to 2026
$6.5M
NIGMS NIH HHS R35 GM118078NIH HHS R35GM118078NSF NSF-2200052
6 · The paper itself

Abstract

Target identification and evaluation is a critical step in the drug discovery process. Although time-intensive and complex, the challenge becomes even more acute in the realm of infectious disease, where the rapid emergence of new viruses, the swift mutation of existing targets, and partial effectiveness of approved antivirals can lead to outbreaks of significant public health concern. The COVID-19 pandemic, caused by the SARS-CoV-2 virus, serves as a prime example of this, where despite the allocation of substantial resources, Paxlovid is currently the only effective treatment. In that case, significant effort pre-pandemic had been expended to evaluate the biological target for the closely related SARS-CoV. In this work, we utilize the computational hot spot mapping method, FTMove, to rapidly identify and rank binding sites for a set of nine SARS-CoV-2 drug/potential drug targets. FTMove takes into account protein flexibility by mapping binding site hot spots across an ensemble of structures for a given target. To assess the applicability of the FTMove approach to a wide range of drug targets for viral pathogens, we also carry out a comprehensive review of the known SARS-CoV-2 ligandable sites. The approach is able to identify the vast majority of all known sites and a few additional sites, which may in fact be yet to be discovered as ligandable. Furthermore, a UMAP analysis of the FTMove features for each identified binding site is largely able to separate predicted sites with experimentally known binders from those without known binders. These results demonstrate the utility of FTMove to rapidly identify actionable sites across a range of targets for a given indication. As such, the approach is expected to be particularly useful for assessing target binding sites for any emerging pathogen, as well as for indications in other disease areas, and providing actionable starting points for structure-based drug design efforts.

Indexed as

Antiviral AgentsSARS-CoV-2Binding SitesCOVID-19COVID-19 Drug TreatmentDrug DiscoveryHumansProtein BindingAntiviral Agentsbinding site assessmentFTMovehotspot mappingligandabilitySARS-CoV-2 drug targetstarget evaluation

Identifiers

PMID39599762
PMCPMC11599001

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.