Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Assay for lipid peroxides in animal tissues by thiobarbituric acid reaction

KEGG(Kyoto Encyclopedia of Genes and Genomes)〔和文〕 (特集 ゲノム医学の現在と未来--基礎と臨床) -- (データベース)

AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore

PL02-05 

All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

Patterns of Somatic Mutation in Human Cancer Genomes

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.

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

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.

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

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 individual's 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.

Molecular Dynamics: New Frontier in Personalized Medicine.

The coronavirus disease (COVID-19) pandemic, which originated in the city of Wuhan, China, has quickly spread to various countries, with many cases having been reported worldwide. As of May 8th, 2020, in India, 56,342 positive cases have been reported. India, with a population of more than 1.34 billion-the second largest population in the world-will have difficulty in controlling the transmission of severe acute respiratory syndrome coronavirus 2 among its population. Multiple strategies would be highly necessary to handle the current outbreak; these include computational modeling, statistical tools, and quantitative analyses to control the spread as well as the rapid development of a new treatment. The Ministry of Health and Family Welfare of India has raised awareness about the recent outbreak and has taken necessary actions to control the spread of COVID-19. The central and state governments are taking several measures and formulating several wartime protocols to achieve this goal. Moreover, the Indian government implemented a 55-days lockdown throughout the country that started on March 25th, 2020, to reduce the transmission of the virus. This outbreak is inextricably linked to the economy of the nation, as it has dramatically impeded industrial sectors because people worldwide are currently cautious about engaging in business in the affected regions.

/pdf/the-rise-and-impact-of-covid-19-in-india-4l8i16fieb.pdf

C. George Priya Doss

Papers

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

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

Molecular Dynamics: New Frontier in Personalized Medicine.

The Rise and Impact of COVID-19 in India

Identification and in silico analysis of functional SNPs of the BRCA1 gene.