In Silico

Newcastle disease virus (NDV) is negative sense single stranded RNA belongs to the Avulavirus genus of the Paramyxoviridae family which can be transmitted by inhalation or ingestion. Birds infected shed these viruses in feces as well as respiratory secretions. The aim of this study is to analyze fusion (F) protein of all virulent Newcastle strains reported in NCBI database using in silico approaches to select all possible epitopes that can be used as a therapeutic peptide vaccine. A total of 56 virulent NDV fusion protein variants retrieved from NCBI database. The conserved regions were introduced into IEDB analysis resource to predict B and T cell epitopes, as well as predicting the binding affinity of the conserved epitopes with BF2 21:01, from the predominantly expressed chicken MHC I molecule. Epitopes with high scores in both B and T cell epitopes predicting tools were suggested. Peptide vaccine against virulent NDV is strongly supersedes the conventional vaccines, as it design...

reconstructionists often determine pre-collision conditions based on post-collision evidence. Energy-based speed calculations for skidding vehicles are commonly used and have been the basis for numerous theoretical and experimental works. The simplest analysis technique, "skid-to-stop" is fairly well understood, however the more complex circumstance of a spinning trajectory is less well understood. This paper will describe a series of experiments conducted to evaluate the frictional values applicable to a spinning vehicle as it rotates and translates without brake application.

Mutations in the beta-amyloid precursor protein gene (APP) have been found in familial early-onset Alzheímer’s disease (AD). DNA variants at several genes have been linked to the risk of developing the most common late-onset form of AD (LOAD). A few studies analyzed the contribution of APP variants to LOAD, with negative or conflicting results. We determined the variation in the 18 APP exons and flanking intronic sequences in a total of 350 LOAD patients from Spain. A total of 13 nucleotide changes were found and 6 were new and not found among 340 healthy controls, including the only missense change (D243N). The in silico analysis suggested that none of them would have an effect on pre-mRNA splicing or protein folding (D243N). Patients and controls were also genotyped for three APP promoter polymorphisms, and none of them was significantly associated with LOAD. We concluded that APP variants would not contribute to the risk of developing LOAD in our population.

In the current investigation, the selected phytocompounds of Cocculus hirsutus were screened for potent tau aggregation inhibitors for Alzheimer’s disease through in silico molecular docking. Approximately 19 phytocompounds from Cocculus hirsutus were selected and assessed for their drug likeness based on rule-of-five using Swiss ADME. The phytocompounds that passed rule-of-five were subjected to in silico analysis through molecular docking on Cyclin-dependent kinase 5 (CDK5) and Glycogen synthase kinase 3 beta (GSK3B) using Molegro Virtual Docker v6.0. Molecular docking studies. The molecular interaction on CDK5 and GSK3B enzymes indicate their role in the tau protein aggregation inhibitory activity of the phytocompounds. In silico analysis showed that hirsutine and cohirsinine bind effectively at the active site of target proteins with a MolDock score of -115.08 and -107.29 respectively. The MolDock scores, ReRank scores and interaction poses of the phytocompounds were compared with the known inhibitors of CDK5 and GSK3B enzymes. The present research created a new perspective in understanding hirsutine and cohirsinine phytocompounds as effective inhibitors of tau aggregation and further research in vitro and in vivo may confirm their therapeutic potential in Alzheimer’s.

Abstract: We develop a simulation tool to support policy-decisions about healthcare for chronic diseases in defined populations. Incident disease-cases are generated in-silico from an age-sex characterised general population using standard epidemiological approaches. A novel disease-treatment model then simulates continuous life courses for each patient using discrete event simulation. Ideally, the discrete event simulation model would be inferred from complete longitudinal healthcare data via a likelihood or Bayesian approach. Such data is ...

This chapter presents a particular cascade of computational steps in order to build a workflow for an in silico protein engineering approach. In this respect, all available information, in order to choose and computationally implement mutations, is described, employed and monitored. Some of the prerequisites of in silico protein engineering are access to various sequence and structure molecular biology databases, software tools for three dimensional molecular visualization and manipulation, sequence and structure alignment and comparison, molecular modelling and molecular docking. The implementation of these steps is demonstrated in the context of performing mutations of particular residues on the ligand pocket of a lipocalin protein family member, to derive the desired ligand binding properties. The example chosen for inclusion introduces the reader to all of the essentials of computational protein engineering experiments. More importantly, it provides insight into understanding an...

Synthetic biology is an emerging field that strives to build increasingly complex biological networks through the integration of molecular biology and engineering. The growth of the field has been supported by progress in the design and construction of synthetic genetic and protein networks. This has led to the possibility of assembling modular components to attain novel biological functions and tools. In addition, these synthetic networks give rise to insights that facilitate the investigation of interactions and phenomena in naturally-occurring networks. Integration of well-characterized biological components into higher order networks requires computational modeling approaches to rationally construct systems that are directed towards a desired outcome. A computational approach would improve the predictability of the underlying mechanisms that would otherwise be difficult to deduce through experimentation alone. The analysis and interpretation of both qualitative and quantitative ...

Ketoprofen is a widespread non-steroidal anti-inflammatory agent used in treatment of acute pain and chronic arthritis. On the other hand, isoquinoline alkaloids are very well known with their wide range of biological activities. From this point of view it is of interest to us to obtain new isoquinolines containing a ketoprofen residue in their structure as new substances with potential biological activity. To estimate general efficacy and safety of the newly obtained compounds, their biological potential has been evaluated.

Two or more proteins interact in vivo to perform complex molecular functions including catalysis, regulation, assembly, immunity and inhibition through the formation of stable interfaces. This interaction is governed by several factors that are selective, sensitive and specific in nature. Several interface features has been documented since 1975. The study of these interface features of proteins and their dynamicity during interaction with different proteins help understanding the mechanisms underlying diverse molecular functions and its biological processes. Computational tools greatly assist in studying such interface features that determine the interaction between two or more proteins, and in this context, this review enumerates the different interface features reported thus far along with the tools that aid in deciphering protein features (physicochemical characteristics, binding site and interface residue prediction and hotspot residues) along with their approaches that are emp...

Sex determination in domestic animals is of potential value to livestock breeding programs. The aim of this study was to develop a simple and accurate PCR-based sex determination protocol, which can be applicable to 6 major domesticated species of the family Bovidae,viz. Bos frontalis, B. grunniens, B. indicus, Bubalus bubalis, Capra hircus, andOvis aries. In silico analysis was done to identify conserved DNA sequence in the HMG box region of the sex-determining region of the Y-chromosome (SRY gene) across the bovids. Duplex PCR assay, including theSRY gene and theGAPDH housekeeping gene, was optimized by using genomic DNA extracted from blood samples of known sex. It was possible to identify the sex of animals by amplifying both gender-specific (SRY) and autosomal (GAPDH) genes simultaneously in the duplex reaction, with the male yielding two bands and the female one band. The protocol was subjected to a blind test that showed a 100 percent specificity and accuracy, thus it can be used in sex determination in livestock breeding programs.

It is essential, in order to minimise expensive drug failures due to toxicity being found in late development or even in clinical trials, to determine potential toxicity problems as early as possible. In view of the large libraries of compounds now being handled by combinatorial chemistry and high-throughput screening, identification of putative toxicity is advisable even before synthesis. Thus the use of predictive toxicology is called for. A number of in silico approaches to toxicity prediction are discussed. Quantitative structure-activity relationships (QSARs), relating mostly to specific chemical classes, have long been used for this purpose, and exist for a wide range of toxicity endpoints. However, QSARs also exist for the prediction of toxicity of very diverse libraries, although often such QSARs are of the classification type; that is, they predict simply whether or not a compound is toxic, and do not give an indication of the level of toxicity. Examples are given of all of...

African Swine Fever Virus (ASFV) is a dsDNA virus causative of the African Swine Fever (ASF) in wild and domestic hogs. ASF is characterized by hemorrhagic fever, high mortality, and transmissibility. The binding of the DNA to the pA104R protein mediates viral replication and genome packaging. In the present study, we generated nine (9) reference compounds that exhibited high docking affinities through de novo computeraided drug design (CADD). These compounds were then used as query molecules to find commercially available drug-like compounds using ligand-based virtual screening (VS). We were able to retrieve 900 hit compounds that exhibited the same pharmacophoric activities. Then, these hit compounds were subjected to drug-likeness filtration to identify the most likely to be developed as commercial drugs based on established parameters. We identified sixty-two (62) drug-like molecules. Molecular docking was then performed to determine the top five compounds with the highest binding affinities against the target protein. ADME/T profiling was done on these compounds to assess their pharmacokinetic properties. Compound 8.45 performed best based on our devised scoring system. This paper shall serve as a good reference in the discovery and development of anti-ASFV therapeutics.

Breast cancer is the second most frequent cancer affecting women worldwide after lung cancer. The toxicity factor associated with synthetic drugs has turned the attention toward natural compounds as the primary focus of interest as anticancer agents. Vitamin E derivatives consisting of the well-established tocopherols and their analogs namely tocotrienols have been extensively studied due to their remarkable biological properties. While tocopherols have failed to offer protection, tocotrienols, in particular, α-, δ-, and γ-tocotrienols alone and in combination have demonstrated anticancer properties. The discovery of the antiangiogenic, antiproliferative, and apoptotic effects of tocotrienols, as well as their role as an inducer of immunological functions, not only reveals a new horizon as a potent antitumor agent but also reinforces the notion that tocotrienols are indeed more than antioxidants. On the basis of a transcriptomic platform, we have recently demonstrated a novel mechanism for tocotrienol activity that involves estrogen receptor (ER) signaling. In silico simulations and in vitro binding analyses indicate a high affinity of specific forms of tocotrienols for ERβ, but not for ERα. Moreover, we have demonstrated that specific tocotrienols increase ERβ translocation into the nucleus which, in turn, activates the expression of estrogen-responsive genes (MIC-1, EGR-1 and Cathepsin D) in breast cancer cells only expressing ERβ cells (MDA-MB-231) and in cells expressing both ER isoforms (MCF-7). The binding of specific tocotrienol forms to ERβ is associated with the alteration of cell morphology, caspase-3 activation, DNA fragmentation, and apoptosis. Furthermore, a recently concluded clinical trial seems to suggest that tocotrienols in combination with tamoxifen may have the potential to extend breast cancer-specific survival.