ArticleBioMed research international2014
Integrating in silico prediction methods, molecular docking, and molecular dynamics simulation to predict the impact of ALK missense mutations in structural perspective.
Article in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 54 citations in OpenAlex.
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- Theoretical aspects of interaction of the anticancer drug cytarabine with human serum albumin.Structural chemistry · 2023Article
- SHP-1 tyrosine phosphatase binding to c-Src kinase phosphor-dependent conformations: A comparative structural framework.PloS one · 2023Article
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- PSnpBind: a database of mutated binding site protein-ligand complexes constructed using a multithreaded virtual screening workflow.Journal of cheminformatics · 2022Article
- Analysis of SYK Gene as a Prognostic Biomarker and Suggested Potential Bioactive Phytochemicals as an Alternative Therapeutic Option for Colorectal Cancer: An In-Silico Pharmaco-Informatics Investigation.Journal of personalized medicine · 2021Article
- Development of Escherichia coli asparaginase II for the Treatment of Acute Lymphocytic Leukemia: In Silico Reduction of asparaginase II Side Effects by a Novel Mutant (V27F).Asian Pacific journal of cancer prevention : APJCP · 2021Article
- Estimation of drug-likeness properties of GC-MS separated bioactive compounds in rare medicinalNetwork modeling and analysis in health informatics and bioinformatics · 2021Article
- The SARS-Cov-2 Proliferation Blocked by a Novel and Potent Main Protease Inhibitor via Computer-aided Drug Design.Iranian journal of pharmaceutical research : IJPR · 2021Article
- ANS Interacts with the CaJournal of fluorescence · 2020Article
- Rhapsody: predicting the pathogenicity of human missense variants.Bioinformatics (Oxford, England) · 2020Article
- Mechanistic insights into the deleterious roles of Nasu-Hakola disease associated TREM2 variants.Scientific reports · 2020Article
- Computational insights of K1444N substitution in GAP-related domain of NF1 gene associated with neurofibromatosis type 1 disease: a molecular modeling and dynamics approach.Metabolic brain disease · 2018Article
- A profound computational study to prioritize the disease-causing mutations in PRPS1 gene.Metabolic brain disease · 2018Article
- In silico quest of selective naphthyl-based CREBBP bromodomain inhibitor.In silico pharmacology · 2018Article
- Exploring the crizotinib resistance mechanism of NSCLC with the L1196M mutation using molecular dynamics simulation.Journal of molecular modeling · 2017Article
- Molecular docking of Glycine max and Medicago truncatula ureases with urea; bioinformatics approaches.Molecular biology reports · 2016Article
Corrections and comments
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Authors and funding
4 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over the past decade, advancements in next generation sequencing technology have placed personalized genomic medicine upon horizon. Understanding the likelihood of disease causing mutations in complex diseases as pathogenic or neutral remains as a major task and even impossible in the structural context because of its time consuming and expensive experiments. Among the various diseases causing mutations, single nucleotide polymorphisms (SNPs) play a vital role in defining individual's susceptibility to disease and drug response. Understanding the genotype-phenotype relationship through SNPs is the first and most important step in drug research and development. Detailed understanding of the effect of SNPs on patient drug response is a key factor in the establishment of personalized medicine. In this paper, we represent a computational pipeline in anaplastic lymphoma kinase (ALK) for SNP-centred study by the application of in silico prediction methods, molecular docking, and molecular dynamics simulation approaches. Combination of computational methods provides a way in understanding the impact of deleterious mutations in altering the protein drug targets and eventually leading to variable patient's drug response. We hope this rapid and cost effective pipeline will also serve as a bridge to connect the clinicians and in silico resources in tailoring treatments to the patients' specific genotype.
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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.