C. George Priya Doss

Therapeutic miRNA and siRNA: Moving from Bench to Clinic as Next Generation Medicine

In the past few years, therapeutic microRNA (miRNA) and small interfering RNA (siRNA) are some of the most important biopharmaceuticals that are in commercial space as future medicines. This review summarizes the patents of miRNA- and siRNA-based new drugs, and also provides a snapshot about significant biopharmaceutical companies that are investing for the therapeutic development of miRNA and siRNA molecules. An insightful view about individual siRNA and miRNA drugs has been depicted with their present status, which is gaining attention in the therapeutic landscape. The efforts of the biopharmaceuticals are discussed with the status of their preclinical and/or clinical trials. Here, some of the setbacks have been highlighted during the biopharmaceutical development of miRNA and siRNA as individual therapeutics. Finally, a snapshot is illustrated about pharmacokinetics, pharmacodynamics with absorption, distribution, metabolism, and excretion (ADME), which is the fundamental development process of these therapeutics, as well as the delivery system for miRNA- and siRNA-based drugs.

Influence of miRNA in insulin signaling pathway and insulin resistance: micro-molecules with a major role in type-2 diabetes

The prevalence of type‐2 diabetes (T2D) is increasing significantly throughout the globe since the last decade. This heterogeneous and multifactorial disease, also known as insulin resistance, is caused by the disruption of the insulin signaling pathway. In this review, we discuss the existence of various miRNAs involved in regulating the main protein cascades in the insulin signaling pathway that affect insulin resistance. The influence of miRNAs (miR‐7, miR‐124a, miR‐9, miR‐96, miR‐15a/b, miR‐34a, miR‐195, miR‐376, miR‐103, miR‐107, and miR‐146) in insulin secretion and beta (β) cell development has been well discussed. Here, we highlight the role of miRNAs in different significant protein cascades within the insulin signaling pathway such as miR‐320, miR‐383, miR‐181b with IGF‐1, and its receptor (IGF1R); miR‐128a, miR‐96, miR‐126 with insulin receptor substrate (IRS) proteins; miR‐29, miR‐384‐5p, miR‐1 with phosphatidylinositol 3‐kinase (PI3K); miR‐143, miR‐145, miR‐29, miR‐383, miR‐33a/b miR‐21 with AKT/protein kinase B (PKB) and miR‐133a/b, miR‐223, miR‐143 with glucose transporter 4 (GLUT4). Insulin resistance, obesity, and hyperlipidemia (high lipid levels in the blood) have a strong connection with T2D and several miRNAs influence these clinical outcomes such as miR‐143, miR‐103, and miR‐107, miR‐29a, and miR‐27b. We also corroborate from previous evidence how these interactions are related to insulin resistance and T2D. The insights highlighted in this review will provide a better understanding on the impact of miRNA in the insulin signaling pathway and insulin resistance‐associated diagnostics and therapeutics for T2D. WIREs RNA 2014, 5:697–712. doi: 10.1002/wrna.1240

A novel computational and structural analysis of nsSNPs in CFTR gene

Single Nucleotide Polymorphisms (SNPs) are being intensively studied to understand the biological basis of complex traits and diseases. The Genetics of human phenotype variation could be understood by knowing the functions of SNPs. In this study using computational methods, we analyzed the genetic variations that can alter the expression and function of the CFTR gene responsible candidate for causing cystic fibrosis. We applied an evolutionary perspective to screen the SNPs using a sequence homology-based SIFT tool, which suggested that 17 nsSNPs (44%) were found to be deleterious. The structure-based approach PolyPhen server suggested that 26 nsSNPS (66%) may disrupt protein function and structure. The PupaSuite tool predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Structure analysis was carried out with the major mutation that occurred in the native protein coded by CFTR gene, and which is at amino acid position F508C for nsSNP with id (rs1800093). The amino acid residues in the native and mutant modeled protein were further analyzed for solvent accessibility, secondary structure and stabilizing residues to check the stability of the proteins. The SNPs were further subjected to iHAP analysis to identify htSNPs, and we report potential candidates for future studies on CFTR mutations.

Applications of computational algorithm tools to identify functional SNPs

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variations in humans. Understanding the functions of SNPs can greatly help to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. The method to identify functional SNPs from a pool, containing both functional and neutral SNPs is challenging by experimental protocols. To explore possible relationships between genetic mutation and phenotypic variation, different computational algorithm tools like Sorting Intolerant from Tolerant, Polymorphism Phenotyping, UTRscan, FASTSNP, and PupaSuite were used for prioritization of high-risk SNPs in coding region (exonic nonsynonymous SNPs) and noncoding regions (intronic and exonic 5’ and 3’-untranslated region (UTR) SNPs). In this work, we have analyzed the SNPs that can alter the expression and function of transcriptional factor TP53 as a pipeline and for providing a guide to experimental work. We identified the possible mutations and proposed modeled structure for the mutant proteins and compared them with the native protein. These nsSNPs play a critical role in cancer association studies aiming to explain the disparity in cancer treatment responses as well as to improve the effectiveness of the cancer treatments. Our results endorse the study with in vivo experimental protocols.

Investigating the Structural Impacts of I64T and P311S Mutations in APE1-DNA Complex: A Molecular Dynamics Approach

Background Elucidating the molecular dynamic behavior of Protein-DNA complex upon mutation is crucial in current genomics. Molecular dynamics approach reveals the changes on incorporation of variants that dictate the structure and function of Protein-DNA complexes. Deleterious mutations in APE1 protein modify the physicochemical property of amino acids that affect the protein stability and dynamic behavior. Further, these mutations disrupt the binding sites and prohibit the protein to form complexes with its interacting DNA. Principal Findings In this study, we developed a rapid and cost-effective method to analyze variants in APE1 gene that are associated with disease susceptibility and evaluated their impacts on APE1-DNA complex dynamic behavior. Initially, two different in silico approaches were used to identify deleterious variants in APE1 gene. Deleterious scores that overlap in these approaches were taken in concern and based on it, two nsSNPs with IDs rs61730854 (I64T) and rs1803120 (P311S) were taken further for structural analysis. Significance Different parameters such as RMSD, RMSF, salt bridge, H-bonds and SASA applied in Molecular dynamic study reveals that predicted deleterious variants I64T and P311S alters the structure as well as affect the stability of APE1-DNA interacting functions. This study addresses such new methods for validating functional polymorphisms of human APE1 which is critically involved in causing deficit in repair capacity, which in turn leads to genetic instability and carcinogenesis.

Studies on flexibility and binding affinity of Asp25 of HIV-1 protease mutants.

We have investigated and highlighted the behavior of binding residue, Asp25 by computational analysis, which play an important role in understanding docking process with drug molecule, Ritonavir (Norvir) and the flexibility nature of the Human Immunodeficiency Virus-1 (HIV-1) protease enzyme. It is well known that Ritonavir is a potent and a selective HIV-1 protease inhibitor. Molecular dockings were performed in order to gain insights regarding the binding mode of this inhibitor. In our analysis, we observed Ritonavir had different rank orders of scores against different mutant of this enzyme. Asp25 of the enzyme was found to be the active site for all the mutants. The results clearly suggest that Ritonavir is not able to appropriately bind at the active site of each HIV-1 protease mutant due to RMSD difference of the amino acid (Asp) at the position 25 of all mutants. These findings support the concept that 3D space of active site is a qualitative assessment for binding affinity of inhibitor with an enzyme. The investigation on the flexibility nature of Asp25 by normal mode analysis, show that binding residue posses less flexibility due to its solvation potential. The overall analysis of our study brings clarity to the binding behavior with respect to the different mutants with Ritonavir on the basis RMSD and also on the flexible nature of HIV-1 protease enzyme with respect to Asp25 position.

Effect of deleterious nsSNP on the HER2 receptor based on stability and binding affinity with herceptin: a computational approach.

In this study, we identified the most deleterious non-synonymous SNP of ERBB2 (HER2) receptors by its stability and investigated its binding affinity with herceptin. Out of 135 SNPs, 10 are nsSNPs in the coding region, in which one of the nsSNP (SNPid rs4252633) is commonly found to be damaged by I-Mutant 2.0, SIFT and PolyPhen servers. With this effort, we modelled the mutant HER2 protein based on this deleterious nsSNP (rs4252633). The modeled mutant showed less stability than native HER 2 protein, based on both total energy of the mutant and stabilizing residues in the mutant protein. This is due to a deviation between the mutant and the native HER2, having an RMSD of about 2.81 A. Furthermore, we compared the binding efficiency of herceptin with native and mutant HER2 receptors. We found that herceptin has a high binding affinity with mutant HER2 receptor, with a binding energy of -24.40 kcal/mol, as compared to the native type, which has a binding energy of -15.26 kcal/mol due to six-hydrogen bonding and two salt bridges exist between herceptin and the mutant type, whereas the native type establishes four hydrogen bonds and two salt bridges with herceptin. This analysis portrays that mutant type has two additional hydrogen bonds with herceptin compared with the native type. Normal mode analysis also showed that the two amino acids, namely Asp596 and Glu598 of mutant HER2, forming additional hydrogen bonding with herceptin, had a slightly higher flexibility than the native type. Based on our investigations, we propose that SNPid rs4252633 could be the most deleterious nsSNP for HER2 receptor, and that herceptin could be the best drug for mutant compared to the native HER2 target.

Computational Refinement of Functional Single Nucleotide Polymorphisms Associated with ATM Gene

Background Understanding and predicting molecular basis of disease is one of the major challenges in modern biology and medicine. SNPs associated with complex disorders can create, destroy, or modify protein coding sites. Single amino acid substitutions in the ATM gene are the most common forms of genetic variations that account for various forms of cancer. However, the extent to which SNPs interferes with the gene regulation and affects cancer susceptibility remains largely unknown. Principal findings We analyzed the deleterious nsSNPs associated with ATM gene based on different computational methods. An integrative scoring system and sequence conservation of amino acid residues was adapted for a priori nsSNP analysis of variants associated with cancer. We further extended our approach on SNPs that could potentially influence protein Post Translational Modifications in ATM gene. Significance In the lack of adequate prior reports on the possible deleterious effects of nsSNPs, we have systematically analyzed and characterized the functional variants in both coding and non coding region that can alter the expression and function of ATM gene. In silico characterization of nsSNPs affecting ATM gene function can aid in better understanding of genetic differences in disease susceptibility.

Structural signature of the G719S-T790M double mutation in the EGFR kinase domain and its response to inhibitors

Some individuals with non-small-cell lung cancer (NSCLC) benefit from therapies targeting epidermal growth factor receptor (EGFR), and the characterization of a new mechanism of resistance to the EGFR-specific antibody gefitinib will provide valuable insight into how therapeutic strategies might be designed to overcome this particular resistance mechanism. The G719S and T790M mutations and their combination were involved in causing different conformational redistribution of EGFR. In the present computational study, we analyzed the impact and structural influence of G719S/T790M double mutation (DM) in EGFR with ligand (gefitinib) through molecular dynamic simulation (50 ns) and docking analysis. We observed the escalation in distance between the functional loop and activation loop with respect to T790M mutation compared to the G719S mutation. Furthermore, we confirmed that the G719S mutation causes the ligand to move closer to the hinge region, whereas T790M makes the ligand escape from the binding pocket. Obtained results provide with an explanation for the resistance induced by T790M and a vital clue for the design of drugs to combat gefitinib resistance.

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.