ReviewGlobal heart2017
Role of Structural Bioinformatics in Drug Discovery by Computational SNP Analysis: Analyzing Variation at the Protein Level.
Review in Global heart, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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.
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.
Who cites it
21 citing papers in PubMed.
- AI-derived comparative assessment of the performance of pathogenicity prediction tools on missense variants of breast cancer genes.Human genomics · 2024Article
- Understanding the impact of structural modifications at the NNAT gene's post-translational acetylation site: in silico approach for predicting its drug-interaction role in anorexia nervosa.Eating and weight disorders : EWD · 2023Article
- NFX1-123: A potential therapeutic target in cervical cancer.Journal of medical virology · 2023Article
- Impact of highly deleterious non-synonymous polymorphisms on GRIN2A protein's structure and function.PloS one · 2023Article
- An in silico analysis of rpoB mutations to affect Chlamydia trachomatis sensitivity to rifamycin.Journal, genetic engineering & biotechnology · 2022Article
- Computer-Aided (In Silico) Modeling of Cytochrome P450-Mediated Food-Drug Interactions (FDI).International journal of molecular sciences · 2022Review
- Deciphering Isoniazid Drug Resistance Mechanisms on DimericACS omega · 2022Article
- Connecting the dots: A practical evaluation of web-tools for describing protein dynamics as networks.Frontiers in bioinformatics · 2022Review
- KEAP1 Cancer Mutants: A Large-Scale Molecular Dynamics Study of Protein Stability.International journal of molecular sciences · 2021Article
- Decoding the Molecular Effects of Atovaquone Linked Resistant Mutations onInternational journal of molecular sciences · 2021Article
- MDM-TASK-web: MD-TASK and MODE-TASK web server for analyzing protein dynamics.Computational and structural biotechnology journal · 2021Article
- Allosteric pockets and dynamic residue network hubs of falcipain 2 in mutations including those linked to artemisinin resistance.Computational and structural biotechnology journal · 2021Article
- Sequence Characterization and Molecular Modeling of Clinically Relevant Variants of the SARS-CoV-2 Main Protease.Biochemistry · 2020Article
- Rhapsody: predicting the pathogenicity of human missense variants.Bioinformatics (Oxford, England) · 2020Article
- Delving into the Characteristic Features of "Menace" Mycobacterium tuberculosis Homologs: A Structural Dynamics and Proteomics Perspectives.The protein journal · 2020Article
- Integrated Computational Approaches and Tools forAllosteric Drug Discovery.International journal of molecular sciences · 2020Review
- Mechanism of Action of Non-Synonymous Single Nucleotide Variations Associated withMolecules (Basel, Switzerland) · 2019Article
- Modulation of Human Hsp90α Conformational Dynamics by Allosteric Ligand Interaction at the C-Terminal Domain.Scientific reports · 2019Article
- Characterizing early drug resistance-related events using geometric ensembles from HIV protease dynamics.Scientific reports · 2018Article
- HUMA: A platform for the analysis of genetic variation in humans.Human mutation · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
With the completion of the human genome project at the beginning of the 21st century, the biological sciences entered an unprecedented age of data generation, and made its first steps toward an era of personalized medicine. This abundance of sequence data has led to the proliferation of numerous sequence-based techniques for associating variation with disease, such as genome-wide association studies and candidate gene association studies. However, these statistical methods do not provide an understanding of the functional effects of variation. Structure-based drug discovery and design is increasingly incorporating structural bioinformatics techniques to model and analyze protein targets, perform large scale virtual screening to identify hit to lead compounds, and simulate molecular interactions. These techniques are fast, cost-effective, and complement existing experimental techniques such as high throughput sequencing. In this paper, we discuss the contributions of structural bioinformatics to drug discovery, focusing particularly on the analysis of nonsynonymous single nucleotide polymorphisms. We conclude by suggesting a protocol for future analyses of the structural effects of nonsynonymous single nucleotide polymorphisms on proteins and protein complexes.
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Registered trials
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.