ProTherm, version 4.0: thermodynamic database for proteins and mutants

Bava, K. Abdulla; Gromiha, M. Michael; Uedaira, Hatsuho; Kitajima, K.; Sarai, Akinori

doi:10.1093/nar/gkh082

Cited by 339 publications

(285 citation statements)

References 15 publications

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“…Similarly, the ΔG o U at 25°C for ecRBP mutants L62C and A188C, using ΔH m values of 81 AE 2 and 91 AE 4 kcal mol −1 , respectively, is 3.2 AE 0.1 kcal mol −1 and 4.1 AE 0.1 kcal mol −1 , whereas the stability of wild-type reported by chemical denaturation is 5.9 AE 0.4 kcal mol −1 (27). This decrease in stability caused by the introduction of cysteine is typical for mutations in the hydrophobic core of these (26,28) and other (29) proteins.…”

Section: Resultsmentioning

confidence: 91%

Picomole-scale characterization of protein stability and function by quantitative cysteine reactivity

Isom

Vardy

Oas

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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The Gibbs free energy difference between native and unfolded states ("stability") is one of the fundamental characteristics of a protein. By exploiting the thermodynamic linkage between ligand binding and stability, interactions of a protein with small molecules, nucleic acids, or other proteins can be detected and quantified. Determination of protein stability can therefore provide a universal monitor of biochemical function. Yet, the use of stability measurements as a functional probe is underutilized, because such experiments traditionally require large amounts of protein and special instrumentation. Here we present the quantitative cysteine reactivity (QCR) technique to determine protein stabilities rapidly and accurately using only picomole quantities of material and readily accessible laboratory equipment. We demonstrate that QCRderived stabilities can be used to measure ligand binding over a wide range of ligand concentrations and affinities. We anticipate that this technique will have broad applications in high-throughput protein engineering experiments and functional genomics. Macromolecular stability is therefore one of the most fundamental thermodynamic measures in biochemistry by quantitatively reporting on structure-function relationships to provide a universal monitor for biochemical function.There are two distinct approaches for determining protein stability (4). The first measures the free energy of protein (un)folding under equilibrium conditions by assessing the fraction of the native state using spectroscopy, hydrodynamic observations, functional assays, or calorimetry. The second exploits the relationship between protein dynamics and stability by monitoring the differential reactivity of internal chemical groups in native and unfolded states. This second approach measures conformational free energies, which under appropriate conditions corresponds to global protein stability. Amide proton exchange is used most commonly to monitor such differential reactivity (5-9), but its widespread use to assess biological function typically is limited by the need for specialized instrumentation and relatively large amounts of protein. Recently, cysteine reactivity (10-14) and proteolysis (15) have emerged as alternative means to determine rates of protein (un)folding and estimate protein stabilities. Here we present a method, quantitative cysteine reactivity (QCR), in which protein stability is determined by monitoring the reactivity of cysteine residues buried in the hydrophobic core of proteins. This approach has the advantage over more traditional methods for measuring protein stability in that it requires only picomoles (nanograms) of protein, uses simple instrumentation accessible to any lab, can be reasonably high throughput, and can provide site-specific thermodynamic information. QCR can be used to determine apparent protein stabilities rapidly and accurately, construct Gibbs-Helmholtz stability profiles, measure ligand binding over a large range of ligand concentrations and affinities, and infer e...

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Section: Resultsmentioning

confidence: 91%

Picomole-scale characterization of protein stability and function by quantitative cysteine reactivity

Isom

Vardy

Oas

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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“…4I). Computational modeling showed a decrease in protein stability with a high reliability index (≥3) in six DLC1 mutants, including these three mutants (SI Appendix, Table S16) (42). In addition, using three kinds of bioinformatics algorithms [SIFT (43), PolyPhen-2 (44), and MutationTaster (45)], we found that seven mutations showed "damaging" functional changes, as indicated in multiple analytic algorithms (SI Appendix, Table S17).…”

Section: Association Of Mutations Of Dlc1 With Sensitivity To a Rockmentioning

confidence: 87%

Genomic alterations in BCL2L1 and DLC1 contribute to drug sensitivity in gastric cancer

Park

Cho

Kim

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide. Recent high-throughput analyses of genomic alterations revealed several driver genes and altered pathways in GC. However, therapeutic applications from genomic data are limited, largely as a result of the lack of druggable molecular targets and preclinical models for drug selection. To identify new therapeutic targets for GC, we performed array comparative genomic hybridization (aCGH) of DNA from 103 patients with GC for copy number alteration (CNA) analysis, and whole-exome sequencing from 55 GCs from the same patients for mutation profiling. Pathway analysis showed recurrent alterations in the Wnt signaling [APC, CTNNB1, and DLC1 (deleted in liver cancer 1)], ErbB signaling (ERBB2, PIK3CA, and KRAS), and p53 signaling/apoptosis [TP53 and BCL2L1 (BCL2-like 1)] pathways. In 18.4% of GC cases (19/103), amplification of the antiapoptotic gene BCL2L1 was observed, and subsequently a BCL2L1 inhibitor was shown to markedly decrease cell viability in BCL2L1-amplified cell lines and in similarly altered patient-derived GC xenografts, especially when combined with other chemotherapeutic agents. In 10.9% of cases (6/55), mutations in DLC1 were found and were also shown to confer a growth advantage for these cells via activation of Rho-ROCK signaling, rendering these cells more susceptible to a ROCK inhibitor. Taken together, our study implicates BCL2L1 and DLC1 as potential druggable targets for specific subsets of GC cases.gastric cancer | copy number alteration | whole-exome sequencing | patient-derived xenograft | druggable target G astric cancer (GC) is a highly prevalent malignancy and is the third leading cause of cancer-related deaths in the world (1). In unresectable and metastatic cases, the clinical outcome for this disease remains poor (median survival is 10-14 mo) (2), and other treatment options are often limited because of the lack of effective therapeutic approaches and molecular prognostic markers (2, 3). To date, with the exception of the application of trastuzumab [ERBB2 (ErbB2 receptor tyrosine kinase 2) antagonist] or ramucirumab [VEGFR2 (Vascular endothelial growth factor receptor 2) antagonist] for advanced GC cases (4, 5), drugs that target GC on a molecular level are limited.Recent genomic studies have demonstrated the heterogeneous genomic characteristics of GC (6-10). In addition, previous studies of patients with GC by whole-genome and whole-exome sequencing (WES) have identified frequent somatic mutations in tumor suppressors such as TP53, ARID1A, APC, and FAT4, and oncogenes including PI3KCA, KRAS, and RHOA (6-10). However, these findings, although academically meaningful, are far from ready for clinical applications, largely because of the lack of identified druggable molecular targets and the availability of reliable preclinical models for validation of potential target inhibitors.To identify novel therapeutic targets for GC, we explored genomic alterations in GC through an integrated genomic data set from WE...

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“…Starting either from the protein structure or from the protein sequence, the predictions were done through IMutant2.0 (Capriotti et al, 2005). Here, a data set used derived from ProTherm (Bava et al, 2004) is the database considered when compared against others for thermodynamic experimental data of free energy changes concerning protein stability caused by mutations in various environment. The output files indicated the predicted free energy change value or sign (∆∆G), which was based on the calculation, the unfolding Gibbs free energy value of the mutated protein minus the unfolding Gibbs free energy value of the native protein (kcal/mol).…”

Section: Datasetsmentioning

confidence: 99%

A computational approach to analyze the missense mutations in human angiogenin variants leading to amyotrophic lateral sclerosis

Sreevishnupriya

Rajasekaran

2013

Bangladesh J Pharmacol

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A computational approach to analyze the missense mutations in human angiogenin variants leading to amyotrophic lateral sclerosis BJP IntroductionAmyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by selective destruction of motor neurons, resulting paralysis in stages and death within a few years from onset (Bruijin et al., 2004). In the past decade, a small number of genes involved in the etiology of the disease have been identified. Angiogenin (ANG), which encodes an angiogenic protein, has been recently identified as a candidate susceptibility gene for ALS in the Irish and Scottish population by Greenway et al (Greenway et al., 2004).The ANG gene provides instructions for making a protein called angiogenin. This protein promotes the formation of new blood vessels from pre-existing blood vessels through a process called angiogenesis. The ANG gene is located on the long (q) arm of chromosome 14 between positions 11.1 and 11.2. More precisely, the ANG gene is located from base pair 21,152,335 to base pair 21,162,344 on chromosome 14.The protein aggregation, defective axonal transport, oxidative stress, dysfunctional growth factor signaling, mitochondrial dysfunction and excitotoxicity are some of the factors found to be combined to the inception of ALS.Around 10% of ALS cases are inherited genetically, but the other 90% have no clear genetic cause (Dion et al., 2009 AbstractThe most deleterious missense mutations of angiogenin forming amyotrophic lateral sclerosis were identified computationally and the substrate binding efficiencies of these mutations were also analyzed. Out of 12 variants, IMutant2.0, SIFT and PolyPhen programs identified 3 variants that were less stable, deleterious and damaging respectively. These 3 variants were modeled to find their conformational changes in concern with native angiogenin through RMSD calculation and Total energy. Docking of native and 3 mutants with ribonuclease inhibitor was performed to describe the binding efficiencies of those detrimental missense mutations. By computing the binding amino acids' flexibility of angiogenin and computing the binding free energy (ΔG)between native and mutant complexes, the loss in binding affinity with their interacting protein namely ribonuclease inhibitor was investigated. This work is licensed under a Creative Commons Attribution 3.0 License. You are free to copy, distribute and perform the work. You must attribute the work in the manner specified by the author or licensor. Article Info

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ProTherm, version 4.0: thermodynamic database for proteins and mutants

Cited by 339 publications

References 15 publications

Picomole-scale characterization of protein stability and function by quantitative cysteine reactivity

Picomole-scale characterization of protein stability and function by quantitative cysteine reactivity

Genomic alterations in BCL2L1 and DLC1 contribute to drug sensitivity in gastric cancer

A computational approach to analyze the missense mutations in human angiogenin variants leading to amyotrophic lateral sclerosis

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