Dev Bukhsh Singh

Docking and in silico ADMET studies of noraristeromycin, curcumin and its derivatives with Plasmodium falciparum SAH hydrolase: A molecular drug target against malaria

The Plasmodium falciparum S-adenosyl-L-homocysteine hydrolase (pfSAHH) enzyme has been considered as a potential chemotherapeutic target against malaria due to the amino acid differences found on binding sites of pfSAHH related to human SAHH. It has been reported that noraristeromycin and some curcumin derivatives have potential binding with the largest cavity of pfSAHH, which is also related to the binding with Nicotinamide-Adenine-Dinucleotide (NAD) and Adenosine (ADN). Our present work focuses on docking and ADMET studies to select potential inhibitors of pfSAHH. The binding of the selected inhibitor of the PfSAHH active site was analyzed using Molegro Virtual Docker. In this study, curcumin and its derivatives have been found to have higher binding affinity with pfSAHH than noraristeromycin. Seven amino acid residues Leu53, His54, Thr56, Lys230, Gly397, His398 and Phe407 of pfSAHH involved in binding with curcumin, are the same as those for noraristeromycin, which reveals that curcumin and noraristeromycin bind in the same region of pfSAHH. Curcumin has shown a strong interaction with hydrophobic amino acid residues of pfSAHH. Molecular Docking and ADMET predictions suggest that curcumin can be a potent inhibitor of pfSAHH with ability to modulate the target in comparatively smaller dose. Therefore, curcumin is likely to become a good lead molecule for the development of effective drug against malaria.

Identification of potential inhibitors of Fasciola gigantica thioredoxin1: computational screening, molecular dynamics simulation, and binding free energy studies

Fasciola gigantica is the causative organism of fascioliasis and is responsible for major economic losses in livestock production globally. F. gigantica thioredoxin1 (FgTrx1) is an important redox-active enzyme involved in maintaining the redox homeostasis in the cell. To identify a potential anti-fasciolid compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,740) against the FgTrx1 structure. The ligands were docked against FgTrx1 and 309 ligands were found to have better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 30 compounds were found to fit well for re-docking studies. After refinement by molecular docking and drug-likeness analysis, three potential inhibitors (ZINC15970091, ZINC9312362, and ZINC9312661) were identified. These three ligands were further subjected to molecular dynamics simulation (MDS) to compare the dynamics and stability of the protein structure after binding of the ligands. The binding free energy analyses were calculated to determine the intermolecular interactions. The results suggested that the two compounds had a binding free energy of –82.237, and –109.52 kJ.mol−1 for compounds with IDs ZINC9312362 and ZINC9312661, respectively. These predicted compounds displayed considerable pharmacological and structural properties to be drug candidates. We concluded that these two compounds could be potential drug candidates to fight against F. gigantica parasites.

Molecular drug targets and therapies for Alzheimer’s disease

Alzheimer’s disease (AD) is a neurodegenerative disorder that is characterized by normal memory loss and cognitive impairment in humans. Many drug targets and disease-modulating therapies are available for treatment of AD, but none of these are effective enough in reducing problems associated with recognition and memory. Potential drug targets so far reported for AD are β-secretase, Γ-secretase, amyloid beta (Aβ) and Aβ fibrils, glycogen synthase kinase-3 (GSK-3), acyl-coenzyme A: cholesterol acyl-transferase (ACAT) and acetylcholinesterase (AChE). Herbal remedies (antioxidants) and natural metal-chelators have shown a very significant role in reducing the risk of AD, as well as lowering the effect of Aβ in AD patients. Researchers are working in the direction of antisense and stem cell-based therapies for a cure for AD, which mainly depends on the clearance of misfolded protein deposits — including Aβ, tau, and alpha-synuclein. Computational approaches for inhibitor designing, interaction analysis, principal descriptors and an absorption, distribution, metabolism, excretion and toxicity (ADMET) study could speed up the process of drug development with higher efficacy and less chance of failure. This paper reviews the known drugs, drug targets, and existing and future therapies for the treatment of AD.

A comprehensive metabolic modeling of thyroid pathway in relation to thyroid pathophysiology and therapeutics.

The thyroid pathway represents a complex interaction of different glands for thyroid hormone synthesis. Thyrotropin releasing hormone is synthesized in the hypothalamus and regulates thyrotropin stimulating hormone gene expression in the pituitary gland. In order to understand the complexity of the thyroid pathways, and using experimental data retrieved from the biomedical literature (e.g., NCBI, HuGE Navigator, Protein Data Bank, and KEGG), we constructed a metabolic map of the thyroid hormone pathway at a molecular level and analyzed it topologically. A total of five hub nodes were predicted in regards to the transcription thyroid receptor (TR), cAMP response element-binding protein (CREB), signal transducer and activator of transcription 3 (STAT 3), nuclear factor kappa-light-chain-enhancer of activated B cells (NFkB), and activator protein 1 (AP-1) as being potentially important in study of thyroid disorders and as novel putative therapeutic drug targets. Notably, the thyroid receptor is a highly connected hub node and currently used as a therapeutic target in hypothyroidism. Our analysis represents the first comprehensive description of the thyroid pathway, which pertains to understanding the function of the protein and gene interaction networks. The findings from this study are therefore informative for pathophysiology and rational therapeutics of thyroid disorders.

Functional classification and biochemical characterization of a novel rho class glutathione S-transferase in Synechocystis PCC 6803

We report a novel class of glutathioneS‐transferase (GST) from the model cyanobacteriumSynechocystis PCC 6803 (sll1545) which catalyzes the detoxification of the water pollutant dichloroacetate and also shows strong glutathione‐dependent peroxidase activity representing the classical activities of zeta and theta/alpha class respectively. Interestingly, sll1545 has very low sequence and structural similarity with these classes. This is the first report of dichloroacetate degradation activity by any bacterial GST. Based on these results we classify sll1545 to a novel GST class, rho. The present data also indicate potential biotechnological and industrial applications of cyanobacterial GST in dichloroacetate‐polluted areas.

An Approach for Identification of Novel Drug Targets in Streptococcus pyogenes SF370 Through Pathway Analysis

Streptococcus pyogenes is one of the most important pathogens as it is involved in various infections affecting upper respiratory tract and skin. Due to the emergence of multidrug resistance and cross-resistance, S. Pyogenes is becoming more pathogenic and dangerous. In the present study, an in silico comparative analysis of total 65 metabolic pathways of the host (Homo sapiens) and the pathogen was performed. Initially, 486 paralogous enzymes were identified so that they can be removed from possible drug target list. The 105 enzymes of the biochemical pathways of S. pyogenes from the KEGG metabolic pathway database were compared with the proteins from the Homo sapiens by performing a BLASTP search against the non-redundant database restricted to the Homo sapiens subset. Out of these, 83 enzymes were identified as non-human homologous while 30 enzymes of inadequate amino acid length were removed for further processing. Essential enzymes were finally mined from remaining 53 enzymes. Finally, 28 essential enzymes were identified in S. pyogenes SF370 (serotype M1). In subcellular localization study, 18 enzymes were predicted with cytoplasmic localization and ten enzymes with the membrane localization. These ten enzymes with putative membrane localization should be of particular interest. Acyl-carrier-protein S-malonyltransferase, DNA polymerase III subunit beta and dihydropteroate synthase are novel drug targets and thus can be used to design potential inhibitors against S. pyogenes infection. 3D structure of dihydropteroate synthase was modeled and validated that can be used for virtual screening and interaction study of potential inhibitors with the target enzyme.

Exploring Medicinal Plant Legacy for Drug Discovery in Post-genomic Era

Plants are a valuable source of pharmacologically important compounds since these are traditionally important in medicinal systems. Medicinal plant-based ancient wisdom could serve as a powerful tool to facilitate focused research on natural compounds for the drug discovery process. Medicinal plants are more important sources for drug discovery, specifically lead molecules as these offer several advantages over the synthetic molecules. Since in post genomic era, molecular targets for most diseases are known, conventional bioscreening strategies for medicinal plants are not sufficient to fulfill the present demand. It makes the role of medicinal plants more significant than ever before. The rich heritage of Indian medicinal plants can be explored utilizing various computational approaches for bioprospecting in the post-genomic era. In this review, the authors explore how Indian medicinal plant legacy can be utilized in post-genomic era utilizing the computational, bioinformatics, chemo-informatics, genomics and systems biology approaches. This approach shall make possible the systematic analysis integrating traditional and modern data in order to validate medicinal plant based knowledge.

Pharmacogenomics: Clinical Perspective, Strategies, and Challenges

Pharmacogenomics (PGx) defines the genetic basis of variability among individuals in response to drugs. It is an emerging discipline of medical science and is now a challenging and applied area of medical research. Several factors influence the efficacy and toxicity of drugs such as environmental factors, age, weight, gender, liver and kidney function, and applied drug therapy. Another crucial factor that influences the drug response of a patient is the genetic makeup of the patient. Polymorphism affects the drug efficacy, bioavailability, and toxicity. Human Genome Project (HGP) has provided a foundation for PGx study by identifying genes related to a disease. PGx knowledge derived from genetic profiling and associated drug response must be translated into clinical applications. A drug label contains information about PGx biomarker and drug related to a therapeutic area and also provides specific information for safe and effective medication based on a biomarker. PGx drugs have improved therapeutic response and also avoid events of adverse drug reactions (ADRs). There are some important ethical, social justice, and economic issues related to PGx which create hurdles in the drug development via PGx. The objective of this chapter is to discuss the basic principle of PGx and its application and also to put forward the ethical, social, technological, and economic challenges in the way of PGx. In spite of many challenges, it is expected that PGx may offer significant promises toward the goal of personalized medicine in the future.

A Quantitative Measure of Conformational Changes in Apo, Holo and Ligand-Bound Forms of Enzymes.

Determination of the native geometry of the enzymes and ligand complexes is a key step in the process of structure-based drug designing. Enzymes and ligands show flexibility in structural behavior as they come in contact with each other. When ligand binds with active site of the enzyme, in the presence of cofactor some structural changes are expected to occur in the active site. Motivation behind this study is to determine the nature of conformational changes as well as regions where such changes are more pronounced. To measure the structural changes due to cofactor and ligand complex, enzyme in apo, holo and ligand-bound forms is selected. Enzyme data set was retrieved from protein data bank. Fifteen triplet groups were selected for the analysis of structural changes based on selection criteria. Structural features for selected enzymes were compared at the global as well as local region. Accessible surface area for the enzymes in entire triplet set was calculated, which describes the change in accessible surface area upon binding of cofactor and ligand with the enzyme. It was observed that some structural changes take place during binding of ligand in the presence of cofactor. This study will helps in understanding the level of flexibility in protein–ligand interaction for computer-aided drug designing.