Evolution- and structure-based computational strategy reveals the impact of deleterious missense mutations on MODY 2 (maturity-onset diabetes of the young, type 2)

Targeting decaprenylphosphoryl-β-D-ribose 2'-epimerase for Innovative Drug Development Against Mycobacterium Tuberculosis Drug-Resistant Strains

Tuberculosis (TB) remains a global health challenge with the emergence of drug-resistant Mycobacterium tuberculosis variants, necessitating innovative drug molecules. One potential target is the cell wall synthesis enzyme decaprenylphosphoryl-β-D-ribose 2'-epimerase (DprE1), crucial for virulence and survival. This study employed virtual screening of 111 Protein Data Bank (PDB) database molecules known for their inhibitory biological activity against DprE1 with known IC50 values. Six compounds, PubChem ID: 390820, 86287492, 155294899, 155522922, 162651615, and 162665075, exhibited promising attributes as drug candidates and validated against clinical trial inhibitors BTZ043, TBA-7371, PBTZ169, and OPC-167832. Concurrently, this research focused on DprE1 mutation effects using molecular dynamic simulations. Among the 10 mutations tested, C387N significantly influenced protein behavior, leading to structural alterations observed through root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and solvent-accessible surface area (SASA) analysis. Ligand 2 (ID: 390820) emerged as a promising candidate through ligand-based pharmacophore analysis, displaying enhanced binding compared with reference inhibitors. Molecular dynamic simulations highlighted ligand 2's interaction with the C387N mutation, reducing fluctuations, augmenting hydrogen bonding, and influencing solvent accessibility. These collective findings emphasize ligand 2's efficacy, particularly against severe mutations, in enhancing protein-ligand complex stability. Integrated computational and pharmacophore methodologies offer valuable insights into drug candidates and their interactions within intricate protein environments. This research lays a strategic foundation for targeted interventions against drug-resistant TB, highlighting ligand 2's potential for advanced drug development strategies.

Computational refinement identifies functional destructive single nucleotide polymorphisms associated with human retinoid X receptor gene

Alterations in the nuclear retinoid X receptor (RXRs) signalling have been implicated in neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, stroke, multiple sclerosis and glaucoma. Single nucleotide polymorphisms (SNPs) are the main cause underlying single nucleic acid variations which in turn determine heterogeneity within various populations. These genetic polymorphisms have been suggested to associate with various degenerative disorders in population-wide analysis. This bioinformatics study was designed to investigate, search, retrieve and identify deleterious SNPs which may affect the structure and function of various RXR isoforms through a computational and molecular modelling approach. Amongst the 1,813 retrieved SNPs several were found to be deleterious with rs140464195_G139R, rs368400425_R358W and rs368586400_L383F RXRα mutant variants being the most detrimental ones causing changes in the interatomic interactions and decreasing the flexibility of the mutant proteins. Molecular genetics analysis identified seven missense mutations in RXRα/β/γ isoforms. Two novel mutations SNP IDs (rs1588299621 and rs1057519958) were identified in RXRα isoform. We used several in silico prediction tools such as SIFT, PolyPhen, I-Mutant, Protein Variation Effect Analyzer (PROVEAN), PANTHER, SNP&Go, PhD-SNP and SNPeffect to predict pathogenicity and protein stability associated with RXR mutations. The structural assessment by DynaMut tool revealed that hydrogen bonds were affected along with hydrophobic and carbonyl interactions resulting in reduced flexibility at the mutated residue positions but ultimately stabilizing the molecule as a whole. Summarizing, analysis of the missense mutations in RXR isoforms showed a mix of conclusive and inconclusive genotype-phenotype correlations suggesting the use of sophisticated computational analysis tools for studying RXR variants.Communicated by Ramaswamy H. Sarma.

In silico protein engineering shows that novel mutations affecting NAD+ binding sites may improve phosphite dehydrogenase stability and activity

Pseudomonas stutzeri phosphite dehydrogenase (PTDH) catalyzes the oxidation of phosphite to phosphate in the presence of NAD, resulting in the formation of NADH. The regeneration of NADH by PTDH is greater than any other enzyme due to the substantial change in the free energy of reaction (G°' = - 63.3 kJ/mol). Presently, improving the stability of PTDH is for a great importance to ensure an economically viable reaction process to produce phosphite as a byproduct for agronomic applications. The binding site of NAD⁺ with PTDH includes thirty-four residues; eight of which have been previously mutated and characterized for their roles in catalysis. In the present study, the unexplored twenty-six key residues involved in the binding of NAD⁺ were subjected to in silico mutagenesis based on the physicochemical properties of the amino acids. The effects of these mutations on the structure, stability, activity, and interaction of PTDH with NAD⁺ were investigated using molecular docking, molecular dynamics simulations, free energy calculations, and secondary structure analysis. We identified seven novel mutations, A155I, G157I, L217I, P235A, V262I, I293A, and I293L, that reduce the compactness of the protein while improving PTDH stability and binding to NAD⁺.

Facing Antitubercular Resistance: Identification of Potential Direct Inhibitors Targeting InhA Enzyme and Generation of 3D-pharmacophore Model by in silico Approach

Purpose

The enoyl-acyl carrier protein reductase (InhA) is one of the important key enzymes employed in mycolic acids biosynthesis pathway and an important component of mycobacterial cell walls. This enzyme has also been identified as major target of isoniazid drug, except that isoniazid needs to be activated first by the catalase peroxidase (KatG) protein to form the isonicotinoyl-NAD (INH-NAD) adduct that inhibits the action of InhA enzyme. However, this activation becomes more difficult and unreachable with the problem of mutation-related resistance caused mainly by acquired mutations in KatG and InhA protein. Our main interest in this study is to identify direct InhA inhibitors using computer-aided drug design.

Methods

Computer-aided drug design was used to solve this problem by applying three different approaches including mutation impact modelling, virtual screening and 3D-pharmacophore search.

Results

A total of 15 mutations were collected from the literature, then a 3D model was generated for each of them and their impact was predicted. Of the 15 mutations, 10 were found to be deleterious and have a direct effect on flexibility, stability and SASA of the protein. In virtual screening, from 1,000 similar INH-NAD analogues obtained by the similarity search method, 823 compounds passed toxicity filter and drug likeness rules, which were then docked to the wild-type of InhA protein. Subsequently, 34 compounds with binding energy score better than that of INH-NAD were selected and docked against the 10 generated mutated models of InhA. Only three leads showed a lower binding affinity better than the reference. The 3D-pharmacophore model approach was used to identify the common features between those three compounds by generating a pharmacophoric map.

Conclusion

The result of this study may pave the way to develop more potent mutant-specific inhibitors to overcome this resistance.

Mutations in GCK May Lead to MODY2 by Reducing Glycogen Synthesis

Dysfunction of glucokinase (GCK) caused by mutations in the GCK gene is the main cause of maturity-onset diabetes of the young type-2 (MODY2, also known as GCK-MODY), which is usually present in adolescence or young adulthood. MODY2 is characterized by mild, stable fasting hyperglycemia that presents at birth, usually 5.4-8.3 mmol L^-1 , and rarely develops complications from diabetes. The treatment of MODY2 prefers a manageable diet rather than the use of insulin. Previous studies have identified GCK mutations only by online software prediction or enzyme kinetic analysis and thermolability assays which are complicated to be conducted. In this study, six mutations in the GCK gene, including four novel mutations and two mutations that are previously reported, are identified. All the six locations are highly conserved according to the sequencing alignment. Moreover, missense mutations are strongly predicted to be pathogenic using online programs. Functional studies show that mutations in GCK mutation do not affect insulin secretion but affect glycogen synthesis. These findings demonstrate that GCK mutations decrease glycogen synthesis, which leads to hyperglycemia in MODY2. Meanwhile, this study provides a new perspective and methods for identifying pathogenic mutations in GCK.

Maturity-Onset Diabetes of the Young: Mutations, Physiological Consequences, and Treatment Options

Maturity-Onset Diabetes of the Young (MODY) is a rare form of diabetes which affects between 1% and 5% of diagnosed diabetes cases. Clinical characterizations of MODY include onset of diabetes at an early age (before the age of 30), autosomal dominant inheritance pattern, impaired glucose-induced secretion of insulin, and hyperglycemia. Presently, 14 MODY subtypes have been identified. Within these subtypes are several mutations which contribute to the different MODY phenotypes. Despite the identification of these 14 subtypes, MODY is often misdiagnosed as type 1 or type 2 diabetes mellitus due to an overlap in clinical features, high cost and limited availability of genetic testing, and unfamiliarity with MODY outside of the medical profession. The primary aim of this review is to investigate the genetic characterization of the MODY subtypes. Additionally, this review will elucidate the link between the genetics, function, and clinical manifestations of MODY in each of the 14 subtypes. In providing this knowledge, we hope to assist in the accurate diagnosis of MODY patients and, subsequently, in ensuring they receive appropriate treatment.

Unraveling the structures, functions and mechanisms of epithelial membrane protein family in human cancers

Peripheral myelin protein 22 (PMP22) and epithelial membrane proteins (EMP-1, -2, and -3) belong to a small hydrophobic membrane protein subfamily, with four transmembrane structures. PMP22 and EMPs are widely expressed in various tissues and play important roles in cell growth, differentiation, programmed cell death, and metastasis. PMP22 presents its highest expression in the peripheral nerve and participates in normal physiological and pathological processes of the peripheral nervous system. The progress of molecular genetics has shown that the genetic changes of the PMP22 gene, including duplication, deletion, and point mutation, are behind various hereditary peripheral neuropathies. EMPs have different expression patterns in diverse tissues and are closely related to the risk of malignant tumor progression. In this review, we focus on the four members in this protein family which are related to disease pathogenesis and discuss gene mutations and post-translational modification of them. Further research into the interactions between structural alterations and function of PMP22 and EMPs will help understand their normal physiological function and role in diseases and might contribute to developing novel therapeutic tools.

Potential Acetylcholinesterase Inhibitor Acting on the Pesticide Resistant and Susceptible Cotton Pests

Gossypium spp., produces economically important cotton fiber, and its yield is highly affected due to pest attacks. Insecticidal target site mutation is one of the reasons behind insecticide resistance to a wide range of pesticides. Acetylcholinesterase (AChE) protein sequences from major pests of cotton were analyzed to assess various physicochemical properties, presence of motifs, and understand evolutionary relationship. The impact of three mutant AChE1, A. lucorum A216S, B. tabaci F392W, and A. gossypii A302S, on the strucutral stability was assessed, and F392W_AChE1 was selected based on 100 ns molecular dynamics simulation. Virtual screening of the zinc database and high-throughput virtual screening, standard precision, and extra precision docking resulted in the identification of six compounds. The six identified compounds and six known commercial pesticdes were docked with three mutant and three wild type AChE1, and one (C1) was selected based on Tice criteria. The conformational and interaction stability of the AChE1-C1 and F392W_AChE1-C1 complexes were monitored at 100 ns Gromacs simulation and were found to be thermodynamically favorable. Therefore, C1 may have the potential to bind to the resistant and susceptible strains of cotton pest, and the resistance developed by insects could be arrested. Furthermore, synthesis and field study of C1 will lead us to a better understanding of the efficacy of the identified compound.

Modeling and Molecular Dynamic Simulation of F(ab')2 Fragment of Nimotuzumab for Lung Cancer Diagnostics

Lung cancer is one of the leading causes of cancer-related deaths in the world among both men and women. Several studies in the literature report that overexpression and mutation of the epidermal growth factor receptor (EGFR) are implicated in the pathogenesis of some lung cancers. Nimotuzumab is a humanized monoclonal antibody (mAb) that inhibits EGF binding because it binds to the extracellular domain of the EGFR. Nimotuzumab requires bivalent binding for stable attachment to cellular surface, which leads to nimotuzumab selectively binding to cells that express mAbs of moderate to high EGFR levels, and this could explain its low toxicity. This property has an advantage for development of nimotuzumab as a therapeutic and diagnostic agent. Monoclonal antibodies are large in size (150 kDa), thus penetrating slowly and residing in the blood for extended periods of time (from days to weeks); their use in imaging studies can result in low signal-to-background ratios and poor image quality. A reduction in the size of the immunoglobulin molecule has also been proposed as a means for increasing tumor penetration by mAbs. Nevertheless, it is known that the penetration of mAb into tumor cell is slow, due to its high molecular weight. Therefore, mAb is not very attractive to be used for imaging diagnostic purpose because of its kinetics and potential to elicit antibody response. The objective of this research was to study the homology modeling of a simpler functional molecule based on nimotuzumab, which consists of 2 antigen-binding fragments (Fab), namely, F(ab′)₂, using MODELER. The crystal structure of Fab of nimotuzumab from protein data bank was used as a template to construct the model of F(ab′)₂. Molecular dynamic simulation was performed to evaluate the stability of F(ab′)₂ and conformational changes of F(ab′)₂ in simulation. The result showed the dynamic behavior of antigen-binding site region of F(ab′)₂ throughout simulation. This result is expected to be useful in the further development of F(ab′)₂ fragment nimotuzumab as a lung cancer diagnostic.

In silico screening and analysis of nonsynonymous SNPs in human CYP1A2 to assess possible associations with pathogenicity and cancer susceptibility

Cytochrome P450 1A2 (CYP1A2) is one of the main hepatic CYPs involved in metabolism of carcinogens and clinically used drugs. Nonsynonymous single nucleotide polymorphisms (nsSNPs) of this enzyme could affect cancer susceptibility and drug efficiency. Hence, identification of human CYP1A2 pathogenic nsSNPs could be of great importance in personalized medicine and pharmacogenetics. Here, 176 nsSNPs of human CYP1A2 were evaluated using a variety of computational tools, of which 18 nsSNPs were found to be associated with pathogenicity. Further analysis suggested possible association of 9 nsSNPs (G73R, G73W, R108Q, R108W, E168K, E346K, R431W, F432S and R456H) with the risk of hepatocellular carcinoma. Molecular dynamics simulations revealed higher overall flexibility, decreased intramolecular hydrogen bonds and lower content of regular secondary structures for both cancer driver variants G73W and F432S when compared to the wild-type structure. In case of F432S, loss of the conserved hydrogen bond between Arg137 and heme propionate oxygen may affect heme stability and the observed significant rise in fluctuation of the CD loop could modify CYP1A2 interactions with its redox partners. Together, these findings propose CYP1A2 as a possible candidate for hepatocellular carcinoma and provide structural insights into how cancer driver nsSNPs could affect protein structure, heme stability and interaction network.

Structural insight into mutations at 155 position of valosin containing protein (VCP) linked to inclusion body myopathy with Paget disease of bone and frontotemporal Dementia

Mutations in Valosin-containing protein (VCP) have been implicated in the pathology linked to inclusion body myopathy, paget disease of bone and frontotemporal dementia (IBMPFD). VCP is an essential component of AAA-ATPase superfamily involved in various cellular functions. Advanced In-silico analysis was performed using prediction based servers to determine the most deleterious mutation. Molecular dynamics simulation was used to study the protein dynamics at atomic level. Molecular docking was used to study the effect of mutation on ATP/ADP transition in the kinase domain. This ATPase of 806 amino acids has four domains: N-terminal domain, C-terminal domain and two ATPase domains D1 and D2 and each of these domains have a distinct role in its functioning. The mutations in VCP protein are distributed among regions known as hotspots, one such hotspot is codon 155. Three missense mutations reported in this hotspot are R155C, R155H and R155P. Potentiality of the deleteriousness calculated using server based prediction models reveal R155C mutation to be the most deleterious. The atomic insight into the effect of mutation by molecular dynamics simulation revealed major conformational changes in R155C variants ATP binding site in D1 domain. The nucleotide-binding mode at the catalytic pocket of VCP and its three variants at codon 155 showed change in the structure, which affects the ATP-ADP transition kinetics in all the three variants.

The Mutation Spectrum of Maturity Onset Diabetes of the Young (MODY)-Associated Genes among Western Siberia Patients

Maturity onset diabetes of the young (MODY) is a congenital form of diabetes characterized by onset at a young age and a primary defect in pancreatic-β-cell function. Currently, 14 subtypes of MODY are known, and each is associated with mutations in a specific gene: HNF4A, GCK, HNF1A, PDX1, HNF1B, NEUROD1, KLF11, CEL, PAX4, INS, BLK, KCNJ11, ABCC8, and APPL1. The most common subtypes of MODY are associated with mutations in the genes GCK, HNF1A, HNF4A, and HNF1B. Among them, up to 70% of cases are caused by mutations in GCK and HNF1A. Here, an analysis of 14 MODY genes was performed in 178 patients with a MODY phenotype in Western Siberia. Multiplex ligation-dependent probe amplification analysis of DNA samples from 50 randomly selected patients without detectable mutations did not reveal large rearrangements in the MODY genes. In 38 patients (37% males) among the 178 subjects, mutations were identified in HNF4A, GCK, HNF1A, and ABCC8. We identified novel potentially causative mutations p.Lys142*, Leu146Val, Ala173Glnfs*30, Val181Asp, Gly261Ala, IVS7 c.864 -1G>T, Cys371*, and Glu443Lys in GCK and Ser6Arg, IVS 2 c.526 +1 G>T, IVS3 c.713 +2 T>A, and Arg238Lys in HNF1A.

Tunisian Maturity-Onset Diabetes of the Young: A Short Review and a New Molecular and Clinical Investigation

INTRODUCTION/AIMS

Maturity-Onset Diabetes of the Young (MODY) is a monogenic non-autoimmune diabetes with 14 different genetic forms. MODY-related mutations are rarely found in the Tunisian population. Here, we explored MODY related genes sequences among seventeen unrelated Tunisian probands qualifying the MODY clinical criteria.

MATERIALS AND METHODS

The GCK and HNF1A genes were systematically analyzed by direct sequencing in all probands. Then, clinical exome sequencing of 4,813 genes was performed on three unrelated patients. Among them, 130 genes have been reported to be involved in the regulation of glucose metabolism, β-cell development, differentiation and function. All identified variants were analyzed according to their frequencies in the GnomAD database and validated by direct sequencing.

RESULTS

We identified the previously reported GCK mutation (rs1085307455) in one patient. The clinical features of the MODY2 proband were similar to previous reports. In this study, we revealed rare and novel alterations in GCK (rs780806456) and ABCC8 (rs201499958) genes with uncertain significance. We also found two likely benign alterations in HNF1A (rs1800574) and KLF11 (rs35927125) genes with minor allele frequencies similar to those depicted in public databases. No pathogenic variants have been identified through clinical exome analysis.

CONCLUSIONS

The most appropriate patients were selected, following a strict clinical screening approach, for genetic testing. However, the known MODY1-13 genes could not explain most of the Tunisian MODY cases, suggesting the involvement of unidentified genes in the majority of Tunisian affected families.

Molecular Genetic Study in a Cohort of Iranian Families Suspected to Maturity-Onset Diabetes of the Young, Reveals a Recurrent Mutation and a High-Risk Variant in the CEL Gene

Background

Diabetes mellitus (DM) is a group of metabolic disorders in the body, accompanied with increasing blood sugar levels. Diabetes is classified into three groups: Type 1 DM (T1DM), Type 2 DM (T2DM), and monogenic diabetes. Maturity-onset diabetes of the young (MODY) is a monogenic diabetes that is frequently mistaken for T1D or T2D. The aim of this study was to diagnose MODY and its subtype frequency in a diabetic population in Iran.

Materials and Methods

In this study among ten diabetic families that were highly suspected to MODY by nongenetic biomarkers and without any pathogenic mutation in GCK and HNF1A genes, two patients from two unrelated families were examined via whole-exome sequencing (WES) in order to detect the causative gene of diabetes. Co-segregation analysis of the identified variant was performed using Sanger sequencing.

Results

In this study, no pathogenic variant was found in GCK and HNF1A genes (MODY2 and MODY3), while these two types of MODY were introduced as the most frequent in other studies. By using WES, a pathogenic variant (p.I488T) was found in one of the patients in CEL gene causing MODY8 that its frequency is very rare in other studied populations. A high-risk variant associated with diabetes was found in another patient.

Conclusion

WES was applied in this study to reveal the cause of MODY in 1 family. This pathogenic mutation was previously reported as a disease causing mutation.

Lys694Arg polymorphism leads to blunted responses to LPS by interfering TLR4 with recruitment of MyD88

TLR4 polymorphisms such as Asp299Gly and Thr399Ile related to Gram-negative sepsis have been reported to result in significantly blunted responsiveness to LPS. Our study group previously screened other TLR4 polymorphic variants by checking the NF-κB activation in comparison to wild type (WT) TLR4 in human embryonic kidney 293T cells. In this study, we found that the Lys694Arg (K694R) polymorphism reduced the activation of NF-κB, and the production of downstream inflammatory factors IL-1, TNF-α and IL-6, representing the K694R polymorphism, led to blunted responsiveness to LPS. Then, we examined the influence of the K694R polymorphism on total and cell-surface TLR4 expression by Western blotting and flow cytometry, respectively, but observed no differences between the K694R polymorphism and WT TLR4. We also used co-immunoprecipitation to determine the interaction of the K694R polymorphism and WT TLR4 with their co-receptor myeloid differentiation factor 2 (MD2) and their downstream signal adaptor MyD88. We found that K694R reduced the recruitment of MyD88 in TLR4 signalling but had no impact on the interaction with MD2.

Identification of nsSNPs of transcription factor E2F1 predisposing individuals to lung cancer and head and neck cancer

E2Fs transcription factors family is involved in the G1/S transition and DNA replication and their deregulated expression have been reported in various human cancers. Studies have shown that the genetic variants of E2F1 family members play an important role in head and neck carcinogenesis. In this study, we predicted six highly deleterious nsSNPs (C227F, R252H, V295D, C298Y, R56W, and Y59C) of E2F1 gene through in silico analyses. The latter was based on protein structure, function, and amino acid conservation. Molecular dynamics studies showed a deviation of the structures of the mutant proteins from the global protein parameters. Further, a case-control study that included total 535 samples (305 cancer patients and 230 controls) was conducted to find the association of the predicted SNPs with the susceptibility to lung cancer (LC) and head and neck cancer (HNC). The genotyping was done applying in-house artificial-RFLP method. Statistical analysis showed that the mutant alleles/genotypes of rs3213172 (R252H) were found to increase ∼ 2-5 fold risk of LC and HNC in all the genetic models. These results suggest that the rs3213172C/T polymorphism of the E2F1 gene could be used as an effective biomarker for genetic susceptibility to LC and HNC in our population.

Comprehensive in silico screening and molecular dynamics studies of missense mutations in Sjogren-Larsson syndrome associated with the ALDH3A2 gene

Sjögren-Larsson syndrome (SLS) is an autoimmune disorder inherited in an autosomal recessive pattern. To date, 80 missense mutations have been identified in association with the Aldehyde Dehydrogenase 3 Family Member A2 (ALDH3A2) gene causing SLS. Disruption of the function of ALDH3A2 leads to excessive accumulation of fat in the cells, which interferes with the normal function of protective membranes or materials that are necessary for the body to function normally. We retrieved 54 missense mutations in the ALDH3A2 from the OMIM, UniProt, dbSNP, and HGMD databases that are known to cause SLS. These mutations were examined with various in silico stability tools, which predicted that the mutations p.S308N and p.R423H that are located at the protein-protein interaction domains are the most destabilizing. Furthermore, to determine the atomistic-level differences within the protein-protein interactions owing to mutations, we performed macromolecular simulation (MMS) using GROMACS to validate the motion patterns and dynamic behavior of the biological system. We found that both mutations (p.S380N and p.R423H) had significant effects on the protein-protein interaction and disrupted the dimeric interactions. The computational pipeline provided in this study helps to elucidate the potential structural and functional differences between the ALDH3A2 native and mutant homodimeric proteins, and will pave the way for drug discovery against specific targets in the SLS patients.

Functional investigation of the BRCA1 Val1714Gly and Asp1733Gly variants by computational tools and yeast transcription activation assay

Mutations in the BRCA1 gene are known to be a major cause of hereditary breast cancer. However, characterizing the point mutations associated with cancer in BRCA1 is challenging because the functional impact of most of them is still unknown. Nowadays, a variety of methods are employed to identify cancer-associated mutations in BRCA1. This study is aimed to assess the functional effects of two mutations, Asp1733Gly and Val1714Gly, using a combination of insilico tools and yeast functional transcription activator assay. Our computational analysis showed that theVal1714Gly mutation was deleterious, while the other one, Asp1733Gly, predicted as neutral. Also using yeast functional transcription activator assay, we found that the Asp1733Gly mutation displayed similar ability with positive controls. In contrast, the Val1714Gly mutation completely abrogated transcriptional activity in the yeast. These results suggested that Val1714Gly and Asp1733Gly can be classified as pathogenic and benign mutations for the BRCA1, respectively.

Structural bioinformatics analysis of variants on GPCR function

G protein-coupled receptors (GPCRs) are key membrane-embedded receptor proteins, with critical roles in cellular signal transduction. In the era of precision medicine, understanding the role of natural variants on GPCR function is critical, especially from a pharmacogenomics viewpoint. Studies involved in mapping variants to GPCR structures are briefly reviewed here. The endocannabinoid system involving the central nervous system (CNS), the human cannabinoid receptor 1 (CB1), is an important drug target and its variability has implications for disease susceptibility and altered drug and pain response. We have carried out a computational study to map deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) to CB1. CB1 mutations were computationally evaluated from neutral to deleterious, and the top twelve deleterious mutations, with structural information, were found to be either close to the ligand binding region or the G-protein binding site. We have mapped these to the active and inactive CB1 X-ray crystallographic structures to correlate variants with available phenotypic information. We have also carried out molecular dynamics simulations to functionally characterize four selected mutants.

Genetic characterization of suspected MODY patients in Tunisia by targeted next-generation sequencing

AIMS

Maturity Onset Diabetes of the Young (MODY) is a monogenic form of diabetes with autosomal dominant inheritance pattern. The diagnosis of MODY and its subtypes is based on genetic testing. Our aim was investigating MODY by means of next-generation sequencing in the Tunisian population.

METHODS

We performed a targeted sequencing of 27 genes known to cause monogenic diabetes in 11 phenotypically suspected Tunisian patients. We retained genetic variants passing filters of frequency in public databases as well as their probable effects on protein structures and functions evaluated by bioinformatics prediction tools.

RESULTS

Five heterozygous variants were found in four patients. They include two mutations in HNF1A and GCK that are the causative genes of the two most prevalent MODY subtypes described in the literature. Other possible mutations, including novel frameshift and splice-site variants were identified in ABCC8 gene.

CONCLUSIONS

Our study is the first to investigate the clinical application of targeted next-generation sequencing for the diagnosis of MODY in Africa. The combination of this approach with a filtering/prioritization strategy made a step towards the identification of MODY mutations in the Tunisian population.

[A novel mutation W257R in GCK gene discovered from a Chinese patient with maturity onset diabetes of the young]

Maturity onset diabetes of the young (MODY) is a monogenic autosomal dominant inherited disease. Its clinical manifestations are asymptomatic with slightly elevated fasting blood glucose and few complications. This paper reports a novel mutation W257R in glucokinase (GCK) gene from a Chinese patient with MODY. Heterozygous mutation c.769T>C (p.W257R) in exon 7 of GCK gene (Chr744187343) was found in the proband, her father and brother. This W257R mutation was first reported in Chinese population.

Identification and structural characterization of deleterious non-synonymous single nucleotide polymorphisms in the human SKP2 gene

In SCF (Skp, Cullin, F-box) ubiquitin-protein ligase complexes, S-phase kinase 2 (SKP2) is one of the major players of F-box family, that is responsible for the degradation of several important cell regulators and tumor suppressor proteins. Despite of having significant evidence for the role of SKP2 on tumorgenesis, there is a lack of available data regarding the effect of non-synonymous polymorphisms. In this communication, the structural and functional consequences of non-synonymous single nucleotide polymorphisms (nsSNPs) of SKP2 have been reported by employing various computational approaches and molecular dynamics simulation. Initially, several computational tools like SIFT, PolyPhen-2, PredictSNP, I-Mutant 2.0 and ConSurf have been implicated in this study to explore the damaging SNPs. In total of 172 nsSNPs, 5 nsSNPs were identified as deleterious and 3 of them were predicted to be decreased the stability of protein. Guided from ConSurf analysis, P101L (rs761253702) and Y346C (rs755010517) were categorized as the highly conserved and functional disrupting mutations. Therefore, these mutations were subjected to three dimensional model building and molecular dynamics simulation study for the detailed structural consequences upon the mutations. The study revealed that P101L and Y346C mutations increased the flexibility and changed the structural dynamics. As both these mutations are located in the most functional regions of SKP2 protein, these computational insights might be helpful to consider these nsSNPs for wet-lab confirmatory analysis as well as in rationalizing future population based studies and structure based drug design against SKP2.

Impact of missense mutations in survival motor neuron protein (SMN1) leading to Spinal Muscular Atrophy (SMA): A computational approach

Spinal muscular atrophy (SMA) is a neuromuscular disorder caused by the mutations in survival motor neuron 1 gene (SMN1). The molecular pathology of missense mutations in SMN1 is not thoroughly investigated so far. Therefore, we collected all missense mutations in the SMN1 protein, using all possible search terms, from three databases (PubMed, PMC and Google Scholar). All missense mutations were subjected to in silico pathogenicity, conservation, and stability analysis tools. We used statistical analysis as a QC measure for validating the specificity and accuracy of these tools. PolyPhen-2 demonstrated the highest specificity and accuracy. While PolyPhen-1 showed the highest sensitivity; overall, PolyPhen2 showed better measures in comparison to other in silico tools. Three mutations (D44V, Y272C, and Y277C) were identified as the most pathogenic and destabilizing. Further, we compared the physiochemical properties of the native and the mutant amino acids and observed loss of H-bonds and aromatic stacking upon the cysteine to tyrosine substitution, which led to the loss of aromatic rings and may reduce protein stability. The three mutations were further subjected to Molecular Dynamics Simulation (MDS) analysis using GROMACS to understand the structural changes. The Y272C and Y277C mutants exhibited maximum deviation pattern from the native protein as compared to D44V mutant. Further MDS analysis predicted changes in the stability that may have been contributed due to the loss of hydrogen bonds as observed in intramolecular hydrogen bond analysis and physiochemical analysis. A loss of function/structural impact was found to be severe in the case of Y272C and Y277C mutants in comparison to D44V mutation. Correlating the results from in silico predictions, physiochemical analysis, and MDS, we were able to observe a loss of stability in all the three mutants. This combinatorial approach could serve as a platform for variant interpretation and drug design for spinal muscular dystrophy resulting from missense mutations.

Structural analysis of missense mutations in galactokinase 1 (GALK1) leading to galactosemia type-2

Galactosemia type 2 is an autosomal recessive disorder characterized by the deficiency of galactokinase (GALK) enzyme due to missense mutations in GALK1 gene, which is associated with various manifestations such as hyper galactosemia and formation of cataracts. GALK enzyme catalyzes the adenosine triphosphate (ATP)-dependent phosphorylation of α-d-galactose to galactose-1-phosphate. We searched 4 different literature databases (Google Scholar, PubMed, PubMed Central, and Science Direct) and 3 gene-variant databases (Online Mendelian Inheritance in Man, Human Gene Mutation Database, and UniProt) to collect all the reported missense mutations associated with GALK deficiency. Our search strategy yielded 32 missense mutations. We used several computational tools (pathogenicity and stability, biophysical characterization, and physiochemical analyses) to prioritize the most significant mutations for further analyses. On the basis of the pathogenicity and stability predictions, 3 mutations (P28T, A198V, and L139P) were chosen to be tested further for physicochemical characterization, molecular docking, and simulation analyses. Molecular docking analysis revealed a decrease in interaction between the protein and ATP in all the 3 mutations, and molecular dynamic simulations of 50 ns showed a loss of stability and compactness in the mutant proteins. As the next step, comparative physicochemical changes of the native and the mutant proteins were carried out using essential dynamics. Overall, P28T and A198V were predicted to alter the structure and function of GALK protein when compared to the mutant L139P. This study demonstrates the power of computational analysis in variant classification and interpretation and provides a platform for developing targeted therapeutics.

Combined pharmacophore, virtual screening and molecular dynamics studies to identify Bruton's tyrosine kinase inhibitors

Bruton's tyrosine Kinase (BTK) is a cytoplasmic, non-receptor tyrosine kinase expressed in hematopoietic cells. BTK plays a critical role in many cellular signalling pathways making it a potential target to treat autoimmune diseases and cancer. BTK signalling is important for the production of arthritis-associated antibodies, and inhibiting BTK will help the system to block the production of disease-associated antibodies. In this study, we have implemented ligand-based pharmacophore modelling and virtual screening against natural compounds followed by molecular docking, density functional theory and molecular dynamics studies for 50 ns. Four compounds with high affinity towards BTK were identified, and it could be used as a potent lead molecule for designing BTK inhibitor.

Probing the Protein-Protein Interaction Network of Proteins Causing Maturity Onset Diabetes of the Young

Protein-protein interactions (PPIs) play vital roles in various cellular pathways. Most of the proteins perform their responsibilities by interacting with an enormous number of proteins. Understanding these interactions of the proteins and their interacting partners has shed light toward the field of drug discovery. Also, PPIs enable us to understand the functions of a protein by understanding their interacting partners. Consequently, in the current study, PPI network of the proteins causing MODY (Maturity Onset Diabetes of the Young) was drawn, and their correlation in causing a disease condition was marked. MODY is a monogenic type of diabetes caused by autosomal dominant inheritance. Extensive research on transcription factor and their corresponding genetic pathways have been studied over the last three decades, yet, very little is understood about the molecular modalities of highly dynamic interactions between transcription factors, genomic DNA, and the protein partners. The current study also reveals the interacting patterns of the various transcription factors. Consequently, in the current work, we have devised a PPI analysis to understand the plausible pathway through which the protein leads to a deformity in glucose uptake.

Evidence-based tailoring of bioinformatics approaches to optimize methods that predict the effects of nonsynonymous amino acid substitutions in glucokinase

Computational methods that allow predicting the effects of nonsynonymous substitutions are an integral part of exome studies. Here, we validated and improved their specificity by performing a comprehensive bioinformatics analysis combined with experimental and clinical data on a model of glucokinase (GCK): 8835 putative variations, including 515 disease-associated variations from 1596 families with diagnoses of monogenic diabetes (GCK-MODY) or persistent hyperinsulinemic hypoglycemia of infancy (PHHI), and 126 variations with available or newly reported (19 variations) data on enzyme kinetics. We also proved that high frequency of disease-associated variations found in patients is closely related to their evolutionary conservation. The default set prediction methods predicted correctly the effects of only a part of the GCK-MODY-associated variations and completely failed to predict the normoglycemic or PHHI-associated variations. Therefore, we calculated evidence-based thresholds that improved significantly the specificity of predictions (≤75%). The combined prediction analysis even allowed to distinguish activating from inactivating variations and identified a group of putatively highly pathogenic variations (EVmutation score <−7.5 and SNAP2 score >70), which were surprisingly underrepresented among MODY patients and thus under negative selection during molecular evolution. We suggested and validated the first robust evidence-based thresholds, which allow improved, highly specific predictions of disease-associated GCK variations.

Prediction of functionally significant single nucleotide polymorphisms in PTEN tumor suppressor gene: An in silico approach

The phosphatase and tensin homolog (PTEN) gene plays a crucial role in signal transduction by negatively regulating the PI3K signaling pathway. It is the most frequent mutated gene in many human-related cancers. Considering its critical role, a functional analysis of missense mutations of PTEN gene was undertaken in this study. Thirty five nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of the PTEN gene were selected for our in silico investigation, and five nsSNPs (G129E, C124R, D252G, H61D, and R130G) were found to be deleterious based on combinatorial predictions of different computational tools. Moreover, molecular dynamics (MD) simulation was performed to investigate the conformational variation between native and all the five mutant PTEN proteins having predicted deleterious nsSNPs. The results of MD simulation of all mutant models illustrated variation in structural attributes such as root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and total energy; which depicts the structural stability of PTEN protein. Furthermore, mutant PTEN protein structures also showed a significant variation in the solvent accessible surface area and hydrogen bond frequencies from the native PTEN structure. In conclusion, results of this study have established the deleterious effect of the all the five predicted nsSNPs on the PTEN protein structure. Thus, results of the current study can pave a new platform to sort out nsSNPs that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case of control studies.

Identification of Maturity-Onset Diabetes of the Young Caused by Glucokinase Mutations Detected Using Whole-Exome Sequencing

Glucokinase maturity-onset diabetes of the young (GCK-MODY) represents a distinct subgroup of MODY that does not require hyperglycemia-lowering treatment and has very few diabetes-related complications. Three patients from two families who presented with clinical signs of GCK-MODY were evaluated. Whole-exome sequencing was performed and the effects of the identified mutations were assessed using bioinformatics tools, such as PolyPhen-2, SIFT, and in silico modeling. We identified two mutations: p.Leu30Pro and p.Ser383Leu. In silico analyses predicted that these mutations result in structural conformational changes, protein destabilization, and thermal instability. Our findings may inform future GCK-MODY diagnosis; furthermore, the two mutations detected in two Korean families with GCK-MODY improve our understanding of the genetic basis of the disease.

Structural Analysis of G1691S Variant in the Human Filamin B Gene Responsible for Larsen Syndrome: A Comparative Computational Approach

Larsen syndrome (LRS) is a rare genetic disease associated with variable manifestations including skeletal malformations, dislocations of the large joints, and notable changes in facial and limb features. Genetic variants in the Filamin B (FLNB) gene are associated with the development of LRS. We searched two literature databases (OMIM and PubMed) and three gene variant databases (HGMD, UniProt, & dbSNP) to capture all the possible variants associated with LRS phenotype, which may have an impact on the FLNB function. Our search yielded 77 variants that might impact the FLNB protein function in patients with LRS. We performed rigorous computational analysis such as conservational, biochemical, pathogenicity, and structural computational analyses to understand the deleterious effect of the G1691S variant. Further, the structural changes of the G1691S variant was compared with a null variant (G1691A) and the native protein through a molecular dynamic simulation study of 50 ns. We found that the variant G1691S was highly deleterious and destabilize the protein when compared to the native and variant G1691A. This might be due to the physicochemical changes in the variant G1691S when compared to the native and variant G1691A. The destabilization was further supported by transformation of bend to coil in variant G1691S whereas bend was retained in native and variant G1691A through molecular dynamics analysis. Our study shed light on the importance of computational methods to understand the molecular nature of genetic variants and structural insights on the function of the FLNB protein. J. Cell. Biochem. 118: 1900-1910, 2017. © 2017 Wiley Periodicals, Inc.

TBCD may be a causal gene in progressive neurodegenerative encephalopathy with atypical infantile spinal muscular atrophy

Spinal muscular atrophy (SMA) is an autosomal recessive neurodegenerative disorder caused by survival motor neuron gene mutations. Variant forms of SMA accompanied by additional clinical presentations have been classified as atypical SMA and are thought to be caused by variants in as yet unidentified causative genes. Here, we presented the clinical findings of two siblings with an SMA variant followed by progressive cerebral atrophy, and the results of whole-exome sequencing analyses of the family quartet that was performed to identify potential causative variants. We identified two candidate homozygous missense variants, R942Q in the tubulin-folding cofactor D (TBCD) gene and H250Q in the bromo-adjacent homology domain and coiled-coil containing 1 (BAHCC1) gene, located on chromosome 17q25.3 with an interval of 1.4 Mbp. The in silico analysis of both variants suggested that TBCD rather than BAHCC1 was likely the pathogenic gene (TBCD sensitivity, 0.68; specificity, 0.97; BAHCC1 sensitivity, 1.00; specificity, 0.00). Thus, our results show that TBCD is a likely novel candidate gene for atypical SMA with progressive cerebral atrophy. TBCD is predicted to have important functions on tubulin integrity in motor neurons as well as in the central nervous system.

Genetic Epidemiology of Glucose-6-Phosphate Dehydrogenase Deficiency in the Arab World

A systematic search was implemented using four literature databases (PubMed, Embase, Science Direct and Web of Science) to capture all the causative mutations of Glucose-6-phosphate dehydrogenase (G6PD) deficiency (G6PDD) in the 22 Arab countries. Our search yielded 43 studies that captured 33 mutations (23 missense, one silent, two deletions, and seven intronic mutations), in 3,430 Arab patients with G6PDD. The 23 missense mutations were then subjected to phenotypic classification using in silico prediction tools, which were compared to the WHO pathogenicity scale as a reference. These in silico tools were tested for their predicting efficiency using rigorous statistical analyses. Of the 23 missense mutations, p.S188F, p.I48T, p.N126D, and p.V68M, were identified as the most common mutations among Arab populations, but were not unique to the Arab world, interestingly, our search strategy found four other mutations (p.N135T, p.S179N, p.R246L, and p.Q307P) that are unique to Arabs. These mutations were exposed to structural analysis and molecular dynamics simulation analysis (MDSA), which predicting these mutant forms as potentially affect the enzyme function. The combination of the MDSA, structural analysis, and in silico predictions and statistical tools we used will provide a platform for future prediction accuracy for the pathogenicity of genetic mutations.

Pharmacology-based toxicity assessment: towards quantitative risk prediction in humans

Despite ongoing efforts to better understand the mechanisms underlying safety and toxicity, ~30% of the attrition in drug discovery and development is still due to safety concerns. Changes in current practice regarding the assessment of safety and toxicity are required to reduce late stage attrition and enable effective development of novel medicines. This review focuses on the implications of empirical evidence generation for the evaluation of safety and toxicity during drug development. A shift in paradigm is needed to (i) ensure that pharmacological concepts are incorporated into the evaluation of safety and toxicity; (ii) facilitate the integration of historical evidence and thereby the translation of findings across species as well as between in vitro and in vivo experiments and (iii) promote the use of experimental protocols tailored to address specific safety and toxicity questions. Based on historical examples, we highlight the challenges for the early characterisation of the safety profile of a new molecule and discuss how model-based methodologies can be applied for the design and analysis of experimental protocols. Issues relative to the scientific rationale are categorised and presented as a hierarchical tree describing the decision-making process. Focus is given to four different areas, namely, optimisation, translation, analytical construct and decision criteria. From a methodological perspective, the relevance of quantitative methods for estimation and extrapolation of risk from toxicology and safety pharmacology experimental protocols, such as points of departure and potency, is discussed in light of advancements in population and Bayesian modelling techniques (e.g. non-linear mixed effects modelling). Their use in the evaluation of pharmacokinetics (PK) and pharmacokinetic-pharmacodynamic relationships (PKPD) has enabled great insight into the dose rationale for medicines in humans, both in terms of efficacy and adverse events. Comparable benefits can be anticipated for the assessment of safety and toxicity profile of novel molecules.

Rising Strengths Hong Kong SAR in Bioinformatics

Hong Kong's bioinformatics sector is attaining new heights in combination with its economic boom and the predominance of the working-age group in its population. Factors such as a knowledge-based and free-market economy have contributed towards a prominent position on the world map of bioinformatics. In this review, we have considered the educational measures, landmark research activities and the achievements of bioinformatics companies and the role of the Hong Kong government in the establishment of bioinformatics as strength. However, several hurdles remain. New government policies will assist computational biologists to overcome these hurdles and further raise the profile of the field. There is a high expectation that bioinformatics in Hong Kong will be a promising area for the next generation.

Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants

Protein stability is the free energy difference between unfolded and folded states of a protein, which lies in the range of 5-25 kcal/mol. Experimentally, protein stability is measured with circular dichroism, differential scanning calorimetry, and fluorescence spectroscopy using thermal and denaturant denaturation methods. These experimental data have been accumulated in the form of a database, ProTherm, thermodynamic database for proteins and mutants. It also contains sequence and structure information of a protein, experimental methods and conditions, and literature information. Different features such as search, display, and sorting options and visualization tools have been incorporated in the database. ProTherm is a valuable resource for understanding/predicting the stability of proteins and it can be accessed at http://www.abren.net/protherm/ . ProTherm has been effectively used to examine the relationship among thermodynamics, structure, and function of proteins. We describe the recent progress on the development of methods for understanding/predicting protein stability, such as (1) general trends on mutational effects on stability, (2) relationship between the stability of protein mutants and amino acid properties, (3) applications of protein three-dimensional structures for predicting their stability upon point mutations, (4) prediction of protein stability upon single mutations from amino acid sequence, and (5) prediction methods for addressing double mutants. A list of online resources for predicting has also been provided.

Value of predictive bioinformatics in inherited metabolic diseases

Typically, inherited metabolic diseases arise from point mutations in genes encoding metabolic enzymes. Although some of these mutations directly affect amino acid residues in the active sites of these enzymes, the majority do not. It is now well accepted that the majority of these disease-associated mutations exert their effects through alteration of protein stability, which causes a reduction in enzymatic activity. This finding suggests a way to predict the severity of newly discovered mutations. In silico prediction of the effects of amino acid sequence alterations on protein stability often correlates with disease severity. However, no stability prediction tool is perfect and, in general, better results are obtained if the predictions from a variety of tools are combined and then interpreted. In addition to predicted alterations to stability, the degree of conservation of a particular residue can also be a factor which needs to be taken into account: alterations to highly conserved residues are more likely to be associated with severe forms of the disease. The approach has been successfully applied in a variety of inherited metabolic diseases, but further improvements are necessary to enable robust translation into clinically useful tools.

Analysing the Effect of Mutation on Protein Function and Discovering Potential Inhibitors of CDK4: Molecular Modelling and Dynamics Studies

The cyclin-dependent kinase 4 (CDK4)-cyclin D1 complex plays a crucial role in the transition from the G1 phase to S phase of the cell cycle. Among the CDKs, CDK4 is one of the genes most frequently affected by somatic genetic variations that are associated with various forms of cancer. Thus, because the abnormal function of the CDK4-cyclin D1 protein complex might play a vital role in causing cancer, CDK4 can be considered a genetically validated therapeutic target. In this study, we used a systematic, integrated computational approach to identify deleterious nsSNPs and predict their effects on protein-protein (CDK4-cyclin D1) and protein-ligand (CDK4-flavopiridol) interactions. This analysis resulted in the identification of possible inhibitors of mutant CDK4 proteins that bind the conformations induced by deleterious nsSNPs. Using computational prediction methods, we identified five nsSNPs as highly deleterious: R24C, Y180H, A205T, R210P, and R246C. From molecular docking and molecular dynamic studies, we observed that these deleterious nsSNPs affected CDK4-cyclin D1 and CDK4-flavopiridol interactions. Furthermore, in a virtual screening approach, the drug 5_7_DIHYDROXY_ 2_ (3_4_5_TRI HYDROXYPHENYL) _4H_CHROMEN_ 4_ONE displayed good binding affinity for proteins with the mutations R24C or R246C, the drug diosmin displayed good binding affinity for the protein with the mutation Y180H, and the drug rutin displayed good binding affinity for proteins with the mutations A205T and R210P. Overall, this computational investigation of the CDK4 gene highlights the link between genetic variation and biological phenomena in human cancer and aids in the discovery of molecularly targeted therapies for personalized treatment.

CoagVDb: a comprehensive database for coagulation factors and their associated SAPs

The current state of the art in medical genetics is to identify and classify the functional (deleterious) or non-functional (neutral) single amino acid substitutions (SAPs), also known as non-synonymous SNPs (nsSNPs). The primary goal is to elucidate the mechanisms through which functional SAPs exert their effects, and ultimately interrogating this information for association with complex phenotypes. This work focuses on coagulation factors involved in the coagulation cascade pathway which plays a vital role in the maintenance of homeostasis in the human system. We developed an integrated coagulation variation database, CoagVDb, which makes use of the biological information from various public databases such as NCBI, OMIM, UniProt, PDB and SAPs (rsIDs/variant). CoagVDb enriched with computational prediction scores classify SAPs as either deleterious or tolerated. Also, various other properties are incorporated such as amino acid composition, secondary structure elements, solvent accessibility, ordered/disordered regions, conservation, and the presence of disulfide bonds. This specialized database provides integration of various prediction scores from different computational methods along with gene, protein, and disease information. We hope our database will act as a useful reference resource for hematologists to reveal protein structure–function relationship and disease genotype–phenotype correlation.

Atomic Insight into the Altered O6-Methylguanine-DNA Methyltransferase Protein Architecture in Gastric Cancer

O⁶-methylguanine-DNA methyltransferase (MGMT) is one of the major DNA repair protein that counteracts the alkalyting agent-induced DNA damage by replacing O⁶-methylguanine (mutagenic lesion) back to guanine, eventually suppressing the mismatch errors and double strand crosslinks. Exonic alterations in the form of nucleotide polymorphism may result in altered protein structure that in turn can lead to the loss of function. In the present study, we focused on the population feared for high exposure to alkylating agents owing to their typical and specialized dietary habits. To this end, gastric cancer patients pooled out from the population were selected for the mutational screening of a specific error prone region of MGMT gene. We found that nearly 40% of the studied neoplastic samples harbored missense mutation at codon¹⁵¹ resulting into Serine to Isoleucine variation. This variation resulted in bringing about the structural disorder, subsequently ensuing into a major stoichiometric variance in recognition domain, substrate binding and selectivity loop of the active site of the MGMT protein, as observed under virtual microscope of molecular dynamics simulation (MDS). The atomic insight into MGMT protein by computational approach showed a significant change in the intra molecular hydrogen bond pattern, thus leading to the observed structural anomalies. To further examine the mutational implications on regulatory plugs of MGMT that holds the protein in a DNA-Binding position, a MDS based analysis was carried out on, all known physically interacting amino acids essentially clustered into groups based on their position and function. The results generated by physical-functional clustering of protein indicated that the identified mutation in the vicinity of the active site of MGMT protein causes the local and global destabilization of a protein by either eliminating the stabilizing salt bridges in cluster C3, C4, and C5 or by locally destabilizing the “protein stabilizing hing” mapped on C3-C4 cluster, preceding the active site.