P. Sneha

Molecular Dynamics: New Frontier in Personalized Medicine

The field of drug discovery has witnessed infinite development over the last decade with the demand for discovery of novel efficient lead compounds. Although the development of novel compounds in this field has seen large failure, a breakthrough in this area might be the establishment of personalized medicine. The trend of personalized medicine has shown stupendous growth being a hot topic after the successful completion of Human Genome Project and 1000 genomes pilot project. Genomic variant such as SNPs play a vital role with respect to inter individuals disease susceptibility and drug response. Hence, identification of such genetic variants has to be performed before administration of a drug. This process requires high-end techniques to understand the complexity of the molecules which might bring an insight to understand the compounds at their molecular level. To sustenance this, field of bioinformatics plays a crucial role in revealing the molecular mechanism of the mutation and thereby designing a drug for an individual in fast and affordable manner. High-end computational methods, such as molecular dynamics (MD) simulation has proved to be a constitutive approach to detecting the minor changes associated with an SNP for better understanding of the structural and functional relationship. The parameters used in molecular dynamic simulation elucidate different properties of a macromolecule, such as protein stability and flexibility. MD along with docking analysis can reveal the synergetic effect of an SNP in protein-ligand interaction and provides a foundation for designing a particular drug molecule for an individual. This compelling application of computational power and the advent of other technologies have paved a promising way toward personalized medicine. In this in-depth review, we tried to highlight the different wings of MD toward personalized medicine.

Influence of V54M mutation in giant muscle protein titin: a computational screening and molecular dynamics approach

Recent genetic studies have revealed the impact of mutations in associated genes for cardiac sarcomere components leading to dilated cardiomyopathy (DCM). The cardiac sarcomere is composed of thick and thin filaments and a giant muscle protein known as titin or connectin. Titin interacts with T-cap/telethonin in the Z-line region and plays a vital role in regulating sarcomere assembly. Initially, we screened all the variants associated with giant protein titin and analyzed their impact with the aid of pathogenicity and stability prediction methods. V54M mutation found in the hydrophobic core region of the protein associated with abnormal clinical phenotype leads to DCM was selected for further analysis. To address this issue, we mapped the deleterious mutant V54M, modeled the mutant protein complex, and deciphered the impact of mutation on binding with its partner telethonin in the titin crystal structure of PDB ID: 1YA5 with the aid of docking analysis. Furthermore, two run molecular dynamics simulation was initiated to understand the mechanistic action of V54M mutation in altering the protein structure, dynamics, and stability. According to the results obtained from the repeated 50 ns trajectory files, the overall effect of V54M mutation was destabilizing and transition of bend to coil in the secondary structure was observed. Furthermore, MMPBSA elucidated that V54M found in the Z-line region of titin decreases the binding affinity of titin to Z-line proteins T-cap/telethonin thereby hindering the protein–protein interaction.

Molecular dynamics-based analyses of the structural instability and secondary structure of the fibrinogen gamma chain protein with the D356V mutation.

Mutations in the fibrinogen gamma chain (FGG) gene have been associated with various disorders, such as dysfibrinogenemia, thrombophilia, and hypofibrinogenemia. A literature survey showed that a residue exchange in fibrinogen Milano I from γ Asp to Val at position 330 impairs fibrin polymerization. The D356V (D330V) mutation located in the C-terminus was predicted to be highly deleterious and to affect the function of the protein. The pathogenicity of the altered gene and changes in protein functions were predicted using in silico methods, such as SIFT, PolyPhen 2, I-Mutant 3.0, Align GV–GD, PhD–SNP, and SNPs&GO. The secondary structure of the mutant protein was unwound by the end of the 50-ns simulation period, and a structural change in the helix-turn transition of the alpha-helical (352–356) region residues was observed. Moreover, a change in the length of the helical region was visualized in the mutant trajectory file, indicating the local transient unfolding of the protein. The obtained computational results suggest that the substitution of the neutral amino acid valine for the acidic amino acid aspartic acid at position 356 results in an unwound conformation within 50 ns, which might contribute to defective polymerization. Our analysis also provides insights into the effect of the conformational change in the D356V (D330V) mutant on protein structure and function.

Genetic Epidemiology of Glucose-6-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.

Gliptins in managing diabetes - Reviewing computational strategy

The pace of anti-diabetic drug discovery is very slow in spite of increasing rate of prevalence of Type 2 Diabetes which remains a major public health concern. Though extensive research steps are taken in the past decade, yet craves for better new treatment strategies to overcome the current scenario. One such general finding is the evolution of gliptins which discriminately inhibits DPP4 (Dipeptidyl peptidase-4) enzyme. Although the mechanism of action of gliptin is highly target oriented and accurate, still its long-term use stands unknown. This step calls for a fast, flexible, and cost-effective strategies to meet the demands of producing arrays of high-content lead compounds with improved efficiency for better clinical success. The present review highlights the available gliptins in the market and also other naturally occurring DPP4 enzyme inhibitors. Along with describing the known inhibitors and their origin in this review, we attempted to identify a probable new lead compounds using advanced computational techniques. In this context, computational methods that integrate the knowledge of proteins and drug responses were utilized in prioritizing targets and designing drugs towards clinical trials with better efficacy. The compounds obtained as a result of virtual screening were compared with the commercially available gliptin in the market to have better efficiency in the identification and validation of the potential DPP4 inhibitors. The combinatorial computational methods used in the present study identified Compound 1: 25022354 as promising inhibitor.

Determining the role of missense mutations in the POU domain of HNF1A that reduce the DNA-binding affinity: A computational approach

Maturity-onset diabetes of the young type 3 (MODY3) is a non-ketotic form of diabetes associated with poor insulin secretion. Over the past years, several studies have reported the association of missense mutations in the Hepatocyte Nuclear Factor 1 Alpha (HNF1A) with MODY3. Missense mutations in the POU homeodomain (POUH) of HNF1A hinder binding to the DNA, thereby leading to a dysfunctional protein. Missense mutations of the HNF1A were retrieved from public databases and subjected to a three-step computational mutational analysis to identify the underlying mechanism. First, the pathogenicity and stability of the mutations were analyzed to determine whether they alter protein structure and function. Second, the sequence conservation and DNA-binding sites of the mutant positions were assessed; as HNF1A protein is a transcription factor. Finally, the biochemical properties of the biological system were validated using molecular dynamic simulations in Gromacs 4.6.3 package. Two arginine residues (131 and 203) in the HNF1A protein are highly conserved residues and contribute to the function of the protein. Furthermore, the R131W, R131Q, and R203C mutations were predicted to be highly deleterious by in silico tools and showed lower binding affinity with DNA when compared to the native protein using the molecular docking analysis. Triplicate runs of molecular dynamic (MD) simulations (50ns) revealed smaller changes in patterns of deviation, fluctuation, and compactness, in complexes containing the R131Q and R131W mutations, compared to complexes containing the R203C mutant complex. We observed reduction in the number of intermolecular hydrogen bonds, compactness, and electrostatic potential, as well as the loss of salt bridges, in the R203C mutant complex. Substitution of arginine with cysteine at position 203 decreases the affinity of the protein for DNA, thereby destabilizing the protein. Based on our current findings, the MD approach is an important tool for elucidating the impact and affinity of mutations in DNA-protein interactions and understanding their function.

Chapter Nine – Elucidating the Mutational Landscape in Hepatocyte Nuclear Factor 1β (HNF1B) by Computational Approach

Transcription factors are the major gene-regulatory proteins that recognize specific nucleotide sequences and bind to them. Missense mutations in transcription factors play a significant role in misregulation of gene expression contributing to various diseases and disorders. Understanding their structural and functional impact of the disease-causing mutations becomes prime importance in treating a disease. Commonly associated defect with the mutations of hepatocyte nuclear factor 1 beta (HNF1B) protein, a transcription factor results in maturity-onset diabetes of the young-5 (MODY-5) leading to loss of function. In the study presented, we applied a series of computational strategies to analyze the effect of mutations on protein structure or function in protein-DNA complex. The mutations from publicly available databases were retrieved and subjected to an array of in silico prediction methods. Key implementation of the present study consists of a pipeline drawn using well established in silico prediction methods of different algorithms to explain the biochemical changes impaired upon mutations in the binding sites of protein-DNA complex using HNF1B. Prediction scores obtained from the in silico tools suggested H153N and A241T as the major nsSNPs involved in destabilizing the protein. Further, high-end microscopic computational study, such as molecular dynamics simulations was utilized to relate the structural and functional effects upon mutations. Although, both the mutations exhibited similar structural differences, we observed A241T with higher destabilizing effect on the protein. The presented work is a step toward understanding the genotype-phenotype relationships in transcription factor genes using fast and accurate computational approach.

Structural insights into the binding mode and conformational changes of BSA induced by bixin and crocin

Bixin and crocin are natural apocarotenoids utilized as food colorants and additives in food industries worldwide. For safety assessment, it is necessary to understand the biological interaction of food colorants. In our present study, we report the interaction of two apocarotenoids with bovine serum albumin (BSA) at physiological pH using spectroscopic techniques and in silico tools. The binding constant and the mode of binding sites have been studied. The enthalpic and entropic contribution to the intermolecular binding event was analyzed and it was found that the contribution of hydrogen bonding and hydrophobic interactions was dominant. The adverse temperature dependence in the unusual static quenching is found to be a reasonable consequence of the large activation energy requirement in the binding process, which is required to overcome the fundamental block and is a direct result of the unique microstructure of the binding sites. To confirm the experimental analysis, we investigated the binding patterns using different in silico tools. A combination of molecular docking, molecular dynamics, and toxicity analysis was performed, and the obtained results revealed that both the apocarotenoids had high binding affinity with a binding energy of −5.44 and −5.93 kcal/mol for bixin and crocin, respectively, with no toxic effects and are in accordance with our experimental analysis. The results directly revealed the flexibility of the protein toward bixin and crocin which has a great impact on the interaction. Thus bixin and crocin can guardedly be used as food colorants in food industries.

Structural analysis of missense mutations in galactokinase 1 (GALK1) leading to galactosemia type-2: P et al.

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.

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

Scientific Reports 6: Article number: 37284; published online: 17 November 2016; updated: 03 January 2017 The original version of this Article contained an error in the title of the paper, where “Genetic Epidemiology of Glucose-6-Phosphate Dehydrogenase Deficiency in the Arab World” was incorrectly given as “Genetic Epidemiology of Glucose-6-Dehydrogenase Deficiency in the Arab World”.