Effect of novel leukemia mutations (K75E &amp; E222K) on interferon regulatory factor 1 and its interaction with DNA: insights from molecular dynamics simulations and docking studies

Kamaraj, Balu; Al‐Subaie, Abeer M.; Ahmad, Fazil; Surapaneni, Krishna Mohan; Alsamman, Khaldoon

doi:10.1080/07391102.2020.1784790

Cited by 26 publications

(18 citation statements)

References 53 publications

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“…The stabilizing nonsynonymous mutations (H49Y, S50L, N501Y, D614G, A845V, and P1143L) of S-protein and ACE2 complexes show more binding free energy native complex ( Table 4 b). Hydrogen bonds are the essential interactions in biological identification processes and vital for establishing the binding specificity [ [57] , [58] , [59] , [60] ]. The intermolecular hydrogen bonds can provide favorable binding energy [ 77 , 78 ].…”

Section: Discussionmentioning

confidence: 99%

“…The collected binding residues in S-protein together with the binding residues in the partner ACE-2 receptor were used as active residues, and the neighboring ones were used as passive residues. The default parameters we applied in our previous studies were also considered for the docking studies [ [57] , [58] , [59] , [60] ]. The HADDOCK scoring function was executed based on the weighted aggregate of the various energy terms de-solvation (Desolv) and restraints energy, Van der Waals (vdw), electrostatic (Elec), and buried surface area (BSA).…”

Section: Methodsmentioning

confidence: 99%

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Investigation of nonsynonymous mutations in the spike protein of SARS-CoV-2 and its interaction with the ACE2 receptor by molecular docking and MM/GBSA approach

Aljindan

Al‐Subaie

Al-Ohali

et al. 2021

Computers in Biology and Medicine

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COVID-19 is an infectious and pathogenic viral disease caused by SARS-CoV-2 that leads to septic shock, coagulation dysfunction, and acute respiratory distress syndrome. The spreading rate of SARS-CoV-2 is higher than MERS-CoV and SARS-CoV. The receptor-binding domain (RBD) of the Spike-protein (S-protein) interacts with the human cells through the host angiotensin-converting enzyme 2 (ACE2) receptor. However, the molecular mechanism of pathological mutations of S-protein is still unclear. In this perspective, we investigated the impact of mutations in the S-protein and their interaction with the ACE2 receptor for SAR-CoV-2 viral infection. We examined the stability of pathological nonsynonymous mutations in the S-protein, and the binding behavior of the ACE2 receptor with the S-protein upon nonsynonymous mutations using the molecular docking and MM_GBSA approaches. Using the extensive bioinformatics pipeline, we screened the destabilizing (L8V, L8W, L18F, Y145H, M153T, F157S, G476S, L611F, A879S, C1247F, and C1254F) and stabilizing (H49Y, S50L, N501Y, D614G, A845V, and P1143L) nonsynonymous mutations in the S-protein. The docking and binding free energy (ddG) scores revealed that the stabilizing nonsynonymous mutations show increased interaction between the S-protein and the ACE2 receptor compared to native and destabilizing S-proteins and that they may have been responsible for the virulent high level. Further, the molecular dynamics simulation (MDS) approach reveals the structural transition of mutants (N501Y and D614G) S-protein. These insights might help researchers to understand the pathological mechanisms of the S-protein and provide clues regarding mutations in viral infection and disease propagation. Further, it helps researchers to develop an efficient treatment approach against this SARS-CoV-2 pandemic.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Investigation of nonsynonymous mutations in the spike protein of SARS-CoV-2 and its interaction with the ACE2 receptor by molecular docking and MM/GBSA approach

Aljindan

Al‐Subaie

Al-Ohali

et al. 2021

Computers in Biology and Medicine

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“…The interaction pattern of the corresponding protein is altered when amino acid residues are changed, especially the formation of H bonds [ 49 , 50 ]. Formations of hydrogen bonds in protein structure affect its conformational flexibility [ 51 , 52 , 53 , 54 , 55 ]. Hence, the number of hydrogen bonds (NH bond) is calculated in our analysis for native and mutant FLT3 structures during the simulation time.…”

Section: Discussionmentioning

confidence: 99%

The Structural Effect of FLT3 Mutations at 835th Position and Their Interaction with Acute Myeloid Leukemia Inhibitors: In Silico Approach

Al‐Subaie

Kamaraj

2021

IJMS

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FMS-like tyrosine kinase 3 (FLT3) gene mutations have been found in more than one-third of Acute Myeloid Leukemia (AML) cases. The most common point mutation in FLT3 occurs at the 835th residue (D835A/E/F/G/H/I/N/V/Y), in the activation loop region. The D835 residue is critical in maintaining FLT3 inactive conformation; these mutations might influence the interaction with clinically approved AML inhibitors used to treat the AML. The molecular mechanism of each of these mutations and their interactions with AML inhibitors at the atomic level is still unknown. In this manuscript, we have investigated the structural consequence of native and mutant FLT-3 proteins and their molecular mechanisms at the atomic level, using molecular dynamics simulations (MDS). In addition, we use the molecular docking method to investigate the binding pattern between the FLT-3 protein and AML inhibitors upon mutations. This study apparently elucidates that, due to mutations in the D835, the FLT-3 structure loses its conformation and becomes more flexible compared to the native FLT3 protein. These structural changes are suggested to contribute to the relapse and resistance responses to AML inhibitors. Identifying the effects of FLT3 at the molecular level will aid in developing a personalized therapeutic strategy for treating patients with FLT-3-associated AML.

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“…Due to the high cost of experimental methods, in silico methods are required for interpretation and classifying the SNPs more accurately and quickly. [46][47][48][49][50][51][52] The combination of various stability algorithms such as iStable, iMutant2.0, MuPro, Dynamut, mCSM, SDM, and Duet was used to compute the FTO protein's stability that makes a result accurate and reliable. Only three missense mutations, G187A, M223V, and I492V, were predicted to be destabilizing by all the stability prediction tools used in this study.…”

Section: Discussionmentioning

confidence: 99%

“…At the structural level, understanding the disease's molecular basis using experimental methods needs a great deal of time and effort. Due to the high cost of experimental methods, in silico methods are required for interpretation and classifying the SNPs more accurately and quickly 46–52 . The combination of various stability algorithms such as iStable, iMutant2.0, MuPro, Dynamut, mCSM, SDM, and Duet was used to compute the FTO protein's stability that makes a result accurate and reliable.…”

Section: Discussionmentioning

confidence: 99%

Comparison of potential inhibitors and targeting fat mass and obesity‐associated protein causing diabesity through docking and molecular dynamics strategies

Kumar

Rajan

Kumar

et al. 2021

J of Cellular Biochemistry

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Genome-wide association studies (GWAS) have identified an association between polymorphisms in the FTO gene and obesity. The FTO: rs9939609, an intronic variant, is considered a risk allele for developing diabesity in homozygous and heterozygous forms. This study aimed to investigate the molecular structure of the available inhibitors specific to the FTO mutations along with the rs9939609 variant. We identified the best-suited inhibitor molecules for each mutant type containing the rs9939609 risk allele. Missense mutations unique to obesity and containing the risk allele of rs9939609 were retrieved from dbSNP for this study. Further stability testing for the mutations were carried out using DynaMut and iStable tools. Three mutations (G187A, M223V, and I492V) were highly destabilizing the FTO structure. These three mutants and native FTO were docked with each of the nine-inhibitor molecules collected from literature studies with the help of PyRx and AutoDock.Further structural behavior of the mutants and native FTO were identified with molecular dynamics simulations and MM-PBSA analyses, along with the 19complex inhibitor compound. We found the compound 19complex exhibited better binding interactions and is the top candidate inhibitor for the M223V and I492V mutants. This study provided insights into the structural changes caused due to mutations in FTO, and the binding mechanism of the inhibitor molecules. It could aid in developing antiobesity drugs for treating patients with mutations and risk alleles predisposing to obesity.

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Effect of novel leukemia mutations (K75E & E222K) on interferon regulatory factor 1 and its interaction with DNA: insights from molecular dynamics simulations and docking studies

Cited by 26 publications

References 53 publications

Investigation of nonsynonymous mutations in the spike protein of SARS-CoV-2 and its interaction with the ACE2 receptor by molecular docking and MM/GBSA approach

Investigation of nonsynonymous mutations in the spike protein of SARS-CoV-2 and its interaction with the ACE2 receptor by molecular docking and MM/GBSA approach

The Structural Effect of FLT3 Mutations at 835th Position and Their Interaction with Acute Myeloid Leukemia Inhibitors: In Silico Approach

Comparison of potential inhibitors and targeting fat mass and obesity‐associated protein causing diabesity through docking and molecular dynamics strategies

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