Energy Minimization

The energetic state of a protein is one of the most important representative parameters of its stability. The energy of a protein can be defined as a function of its atomic coordinates. This energy function consists of several components: 1. Bond energy and angle energy, representative of the covalent bonds, bond angles. 2. Dihedral energy, due to the dihedral angles. 3. A van der Waals term (also called Leonard-Jones potential) to ensure that atoms do not have steric clashes. 4. Electrostatic energy accounting for the Coulomb’s Law m protein structure, i.e. the long-range forces between charged and partially charged atoms. All these quantitative terms have been parameterized and are collectively referred to as the ‘force-field’, for e.g. CHARMM, AMBER, AMBERJOPLS and GROMOS. The goal of energy Minimization is to find a set of coordinates representing the minimum energy conformation for the given structure. Various algorithms have been formulated by varying the use of derivatives. Three common algorithms used for this optimization are steepest descent, conjugate gradient and Newton–Raphson. Although energy Minimization is a tool to achieve the nearest local minima, it is also an indispensable tool in correcting structural anomalies, viz. bad stereo-chemistry and short contacts. An efficient optimization protocol could be devised from these methods in conjunction with a larger space exploration algorithm, e.g. molecular dynamics

Insight into trichomonas vaginalis genome evolution through metabolic pathways comparison

Trichomonas vaginalis causes the trichomoniasis, in women and urethritis and prostate cancer in men. Its genome draft published by TIGR in 2007 presents many unusual genomic and biochemical features like, exceptionally large genome size, the presence of hydrogenosome, gene duplication, lateral gene transfer mechanism and the presence of miRNA. To understand some of genomic features we have performed a comparative analysis of metabolic pathways of the T. vaginalis with other 22 significant common organisms. Enzymes from the biochemical pathways of T. vaginalis and other selected organisms were retrieved from the KEGG metabolic pathway database. The metabolic pathways of T. vaginalis common in other selected organisms were identified. Total 101 enzymes present in different metabolic pathways of T. vaginalis were found to be orthologous by using BLASTP program against the selected organisms. Except two enzymes all identified orthologous enzymes were also identified as paralogous enzymes. Seventy-five of identified enzymes were also identified as essential for the survival of T. vaginalis, while 26 as non-essential. The identified essential enzymes also represent as good candidate for novel drug targets. Interestingly, some of the identified orthologous and paralogous enzymes were found playing significant role in the key metabolic activities while others were found playing active role in the process of pathogenesis. The N-acetylneuraminate lyase was analyzed as the candidate of lateral genes transfer. These findings clearly suggest the active participation of lateral gene transfer and gene duplication during evolution of T. vaginalis from the enteric to the pathogenic urogenital environment

<span style="font-size:11.0pt;font-family: "Times New Roman";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: Mangal;mso-ansi-language:EN-GB;mso-fareast-language:EN-US;mso-bidi-language: HI" lang="EN-GB">Analyzing time course microarray data of <i style="mso-bidi-font-style: normal">Toxoplasma gondii</i> and study the impact on host transcript levels using Bioconductor</span>

46-51Toxoplasma gondii is an obligate, intracellular, apicomplexan parasite that can infect a wide range of warm-blooded animals including humans. In humans and other intermediate hosts, Toxoplasma develops into chronic infection that cannot be eliminated by host’s immune response or by currently used drugs. The ability of the parasite to convert to the bradyzoite stage and to live inside slow-growing cysts that can go unnoticed by the host immune system allows for the persistence of parasite throughout the life of the infected host. Little is known, however, about how bradyzoites manipulate their host cell. Large scale microarray experiments are becoming increasingly routine, particularly those which track a number of different cell lines through time. This time course information provides valuable insight into dynamics of various biological processes. The proper statistical analysis, however, requires the use of more sophisticated tools and complex statistical models. In the current study, the open-source R programming environment in conjunction with the open-source Bioconductor software was used to analyze microarray data of T. gondii. Several statistical analysis procedures like (log) fold changes in conjunction with ordinary and moderated t-statistics were used to determine differentially expressed genes. The differentially expressed genes were subjected to cluster analysis, followed by the annotation of the up and down regulated genes based on the gene ontology. The findings in the present study suggest the overall effect of the gene expression changes is to modulate the key metabolic pathways leading to compromised host immune response, enhancement in programmed cell death, depression in cell proliferation process and induction of various diseases

Hypothesis Volume 8(3) Metabolic pathway analysis and molecular docking analysis for identification of putative drug targets in Toxoplasma gondii: novel approach

Abstract: Toxoplasma gondii is an obligate intracellular apicomplexan parasite that can infect a wide range of warm-blooded animals including humans. In humans and other intermediate hosts, toxoplasma develops into chronic infection that cannot be eliminated by host&apos;s immune response or by currently used drugs. In most cases, chronic infections are largely asymptomatic unless the host becomes immune compromised. Thus, toxoplasma is a global health problem and the situation has become more precarious due to the advent of HIV infections and poor toleration of drugs used to treat toxoplasma infection, having severe side effects and also resistance have been developed to the current generation of drugs. The emergence of these drug resistant varieties of T. gondii has led to a search for novel drug targets. We have performed a comparative analysis of metabolic pathways of the host Homo sapiens and the pathogen T. gondii. The enzymes in the unique pathways of T. gondii, which do not show similarity to any protein from the host, represent attractive potential drug targets. We have listed out 11 such potential drug targets which are playing some important work in more than one pathway. Out of these, one important target is Glutamate dehydrogenase enzyme; it plays crucial part in oxidation reduction, metabolic process and amino acid metabolic process. As this is also present in the targets of tropical diseases of TDR (Tropical disease related Drug) target database and no PDB and MODBASE 3D structural model is available, homology models for Glutamate dehydrogenase enzyme were generated using MODELLER9v6. The model was further explored for the molecular dynamics simulation study with GROMACS, virtual screening and docking studies with suitable inhibitors against the NCI diversity subset molecules from ZINC database, by using AutoDock-Vina. The best ten docking solutions were selected (ZINC01690699, ZINC17465979, ZINC17465983, ZINC18141294_03, ZINC05462670, ZINC01572309, ZINC18055497_01, ZINC18141294, ZINC05462674 and ZINC13152284_01). Further the Complexes were analyzed through LIGPLOT. On the basis of Complex scoring and binding ability it is deciphered that these NCI diversity set II compounds, specifically ZINC01690699 (as it has minimum energy score and one of the highest number of interactions with the active site residue), could be promising inhibitors for T. gondii using Glutamate dehydrogenase as Drug target