Dataset Information

In Silico Insights towards the Identification of NLRP3 Druggable Hot Spots.

ABSTRACT: NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) activation has been linked to several chronic pathologies, including atherosclerosis, type-II diabetes, fibrosis, rheumatoid arthritis, and Alzheimer's disease. Therefore, NLRP3 represents an appealing target for the development of innovative therapeutic approaches. A few companies are currently working on the discovery of selective modulators of NLRP3 inflammasome. Unfortunately, limited structural data are available for this target. To date, MCC950 represents one of the most promising noncovalent NLRP3 inhibitors. Recently, a possible region for the binding of MCC950 to the NLRP3 protein was described but no details were disclosed regarding the key interactions. In this communication, we present an in silico multiple approach as an insight useful for the design of novel NLRP3 inhibitors. In detail, combining different computational techniques, we propose consensus-retrieved protein residues that seem to be essential for the binding process and for the stabilization of the protein-ligand complex.

SUBMITTER: Mekni N

PROVIDER: S-EPMC6834175 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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In Silico Insights towards the Identification of NLRP3 Druggable Hot Spots.

Mekni Nedra N De Rosa Maria M Cipollina Chiara C Gulotta Maria Rita MR De Simone Giada G Lombino Jessica J Padova Alessandro A Perricone Ugo U

International journal of molecular sciences 20191009 20

NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) activation has been linked to several chronic pathologies, including atherosclerosis, type-II diabetes, fibrosis, rheumatoid arthritis, and Alzheimer's disease. Therefore, NLRP3 represents an appealing target for the development of innovative therapeutic approaches. A few companies are currently working on the discovery of selective modulators of NLRP3 inflammasome. Unfortunately, limited structural data are available for this t ...[more]

PMID: 31600880

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Project description:Policy Points: Health care complaints contain valuable data on quality and safety; however, there is no reliable method of analysis to unlock their potential. We demonstrate a method to analyze health care complaints that provides reliable insights on hot spots (where harm and near misses occur) and blind spots (before admissions, after discharge, systemic and low-level problems, and errors of omission). Systematic analysis of health care complaints can improve quality and safety by providing patient-centered insights that localize issues and shed light on difficult-to-monitor problems.ContextThe use of health care complaints to improve quality and safety has been limited by a lack of reliable analysis tools and uncertainty about the insights that can be obtained. The Healthcare Complaints Analysis Tool, which we developed, was used to analyze a benchmark national data set, conceptualize a systematic analysis, and identify the added value of complaint data.MethodsWe analyzed 1,110 health care complaints from across England. "Hot spots" were identified by mapping reported harm and near misses onto stages of care and underlying problems. "Blind spots" concerning difficult-to-monitor aspects of care were analyzed by examining access and discharge problems, systemic problems, and errors of omission.FindingsThe tool showed moderate to excellent reliability. There were 1.87 problems per complaint (32% clinical, 32% relationships, and 34% management). Twenty-three percent of problems entailed major or catastrophic harm, with significant regional variation (17%-31%). Hot spots of serious harm were safety problems during examination, quality problems on the ward, and institutional problems during admission and discharge. Near misses occurred at all stages of care, with patients and family members often being involved in error detection and recovery. Complaints shed light on 3 blind spots: (1) problems arising when entering and exiting the health care system; (2) systemic failures pertaining to multiple distributed and often low-level problems; and (3) errors of omission, especially failure to acknowledge and listen to patients raising concerns.ConclusionsThe analysis of health care complaints reveals valuable and uniquely patient-centered insights on quality and safety. Hot spots of harm and near misses provide an alternative data source on adverse events and critical incidents. Analysis of entry-exit, systemic, and omission problems provides insight on blind spots that may otherwise be difficult to monitor. Benchmark data and analysis scripts are downloadable as supplementary files.

Dataset Information

In Silico Insights towards the Identification of NLRP3 Druggable Hot Spots.

Publications

In Silico Insights towards the Identification of NLRP3 Druggable Hot Spots.

Similar Datasets

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