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Mohane Selvaraj Coumar

Bio: Mohane Selvaraj Coumar is an academic researcher from Pondicherry University. The author has contributed to research in topics: Aurora inhibitor & Virtual screening. The author has an hindex of 26, co-authored 100 publications receiving 2126 citations. Previous affiliations of Mohane Selvaraj Coumar include Panjab University, Chandigarh & Central University, India.


Papers
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Journal ArticleDOI
TL;DR: Despite the growing amount of knowledge related to survivin in the last ten years, the development of survivin inhibitors or survivin-related molecular therapies is surprisingly and relatively slow as compared to other therapeutic inhibitors for cancer treatment.

170 citations

Journal ArticleDOI
TL;DR: Preliminary mechanistic studies suggest that these compounds act as anti-influenza agents by inhibiting ribonucleoprotein (RNP) complex associated activity and have the potential to be developed further, which could form the basis for developing additional defense against influenza pandemics.
Abstract: By using a cell-based high throughput screening campaign, a novel angelicin derivative 6a was identified to inhibit influenza A (H1N1) virus induced cytopathic effect in Madin-Darby canine kidney cell culture in low micromolar range. Detailed structure-activity relationship studies of 6a revealed that the angelicin scaffold is essential for activity in pharmacophore B, while meta-substituted phenyl/2-thiophene rings are optimal in pharmacophore A and C. The optimized lead 4-methyl-9-phenyl-8-(thiophene-2-carbonyl)-furo[2,3-h]chromen-2-one (8g, IC(50) = 70 nM) showed 64-fold enhanced activity compared to the high throughput screening (HTS) hit 6a. Also, 8g was found effective in case of influenza A (H3N2) and influenza B virus strains similar to approved anti-influenza drug zanamivir (4). Preliminary mechanistic studies suggest that these compounds act as anti-influenza agents by inhibiting ribonucleoprotein (RNP) complex associated activity and have the potential to be developed further, which could form the basis for developing additional defense against influenza pandemics.

130 citations

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TL;DR: HTS hit 7 was modified through hybrid design strategy to introduce a chiral side chain followed by introduction of Michael acceptor group to obtain potent EGFR kinase inhibitors 11 and 19, which inhibited gefitinib-resistant double mutant (DM, T790M/L858R) EGFRKinase at nanomolar concentration.
Abstract: HTS hit 7 was modified through hybrid design strategy to introduce a chiral side chain followed by introduction of Michael acceptor group to obtain potent EGFR kinase inhibitors 11 and 19. Both 11 and 19 showed over 3 orders of magnitude enhanced HCC827 antiproliferative activity compared to HTS hit 7 and also inhibited gefitinib-resistant double mutant (DM, T790M/L858R) EGFR kinase at nanomolar concentration. Moreover, treatment with 19 shrinked tumor in nude mice xenograft model.

106 citations

Journal ArticleDOI
01 Feb 2015
TL;DR: Various tools using evolutionary algorithm, a soft computing technique for multi-objective optimization to find novel molecules for drug development are surveyed and analyzed in detail, with particular emphasis on the computational aspects.
Abstract: In de novo drug design multiple pharmaceutically important parameters need to be optimized. Various tools using evolutionary algorithm, a soft computing technique for multi-objective optimization to find novel molecules for drug development are surveyed. De novo drug design supplies novel molecules for drug development.In de novo drug design multiple parameters are optimized.Evolutionary algorithms are used for multi-objective optimization.Evolutionary algorithms used in de novo drug design tools are analyzed here. The process of drug design and discovery demands several man years and huge investment. Computer-aided drug design (CADD) technique is an aid to speed up the drug discovery process. De novo drug design, a CADD technique to identify drug-like novel chemical structures from a huge chemical search space, helps to find new drugs by the optimization of multiple pharmaceutically relevant parameters required for a successful drug. As the search space is very large in the case of de novo drug design, evolutionary algorithm (EA), a soft computing technique can be used to find an optimal solution, which in this case is a novel drug. In this paper, various EA techniques used in de novo drug design tools are surveyed and analyzed in detail, with particular emphasis on the computational aspects.

95 citations

Journal ArticleDOI
TL;DR: Considering the fact that aurora kinase plays an important role in the mitosis process and is involved in tumorigenesis, development of aurora Kinase inhibitors for the treatment of cancer, either as a single agent or in combination with existing cancer treatment is warranted.
Abstract: Background: Mitosis is a key step in the cell cycle governing the distribution of genetic material to the daughter cells. Any aberration in this process could lead to genomic instability. Aurora A, B and C, are members of the serine/threonine kinase family. Aurora kinases are essential for spindle assembly, centrosome maturation, chromosomal segregation and cytokinesis during mitosis. Abnormalities in the mitotic process through overexpression/amplification of aurora kinase have been linked to genomic instability leading to tumorigenesis. Hence, use of aurora kinase small molecule inhibitors as potential molecular-targeted therapeutic intervention for cancer is being pursued by various researchers. Objective: To review the literature of aurora kinase inhibitors in clinical and preclinical testing. Method: Pubmed, Scifinder® and www.clinicaltrials.gov databases were used to search the literature for aurora kinase. Conclusion/results: Approximately 13 aurora kinase inhibitors are under Phase I/II evaluation...

95 citations


Cited by
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Journal ArticleDOI
TL;DR: These findings reflect the critical influences of the σ orbital and metal-oxygen covalency on the competition between O(2)(2-)/OH(-) displacement and OH(-) regeneration on surface transition-metal ions as the rate-limiting steps of the ORR, and highlight the importance of electronic structure in controlling oxide catalytic activity.
Abstract: The prohibitive cost and scarcity of the noble-metal catalysts needed for catalysing the oxygen reduction reaction (ORR) in fuel cells and metal-air batteries limit the commercialization of these clean-energy technologies. Identifying a catalyst design principle that links material properties to the catalytic activity can accelerate the search for highly active and abundant transition-metal-oxide catalysts to replace platinum. Here, we demonstrate that the ORR activity for oxide catalysts primarily correlates to σ-orbital (e(g)) occupation and the extent of B-site transition-metal-oxygen covalency, which serves as a secondary activity descriptor. Our findings reflect the critical influences of the σ orbital and metal-oxygen covalency on the competition between O(2)(2-)/OH(-) displacement and OH(-) regeneration on surface transition-metal ions as the rate-limiting steps of the ORR, and thus highlight the importance of electronic structure in controlling oxide catalytic activity.

2,241 citations

Journal ArticleDOI
TL;DR: A new class of Pt-Co nanocatalysts composed of ordered Pt(3)Co intermetallic cores with a 2-3 atomic-layer-thick platinum shell with high activity and stability are described, providing a new direction for catalyst performance optimization for next-generation fuel cells.
Abstract: To enhance and optimize nanocatalyst performance and durability for the oxygen reduction reaction in fuel-cell applications, we look beyond Pt-metal disordered alloys and describe a new class of Pt-Co nanocatalysts composed of ordered Pt(3)Co intermetallic cores with a 2-3 atomic-layer-thick platinum shell. These nanocatalysts exhibited over 200% increase in mass activity and over 300% increase in specific activity when compared with the disordered Pt(3)Co alloy nanoparticles as well as Pt/C. So far, this mass activity for the oxygen reduction reaction is the highest among the Pt-Co systems reported in the literature under similar testing conditions. Stability tests showed a minimal loss of activity after 5,000 potential cycles and the ordered core-shell structure was maintained virtually intact, as established by atomic-scale elemental mapping. The high activity and stability are attributed to the Pt-rich shell and the stable intermetallic Pt(3)Co core arrangement. These ordered nanoparticles provide a new direction for catalyst performance optimization for next-generation fuel cells.

1,689 citations

Journal ArticleDOI
TL;DR: The screening of a range of botanical species and marine organisms has yielded promising new antitubulin agents with novel properties, and the three main objectives are enhanced tumour specificity, reduced neurotoxicity and insensitivity to chemoresistance mechanisms.
Abstract: Microtubules are dynamic filamentous cytoskeletal proteins composed of tubulin and are an important therapeutic target in tumour cells. Agents that bind to microtubules have been part of the pharmacopoeia of anticancer therapy for decades and until the advent of targeted therapy, microtubules were the only alternative to DNA as a therapeutic target in cancer. The screening of a range of botanical species and marine organisms has yielded promising new antitubulin agents with novel properties. In the current search for novel microtubule-binding agents, enhanced tumour specificity, reduced neurotoxicity and insensitivity to chemoresistance mechanisms are the three main objectives.

1,450 citations

Journal ArticleDOI
TL;DR: Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades and theory behind the most important methods and recent successful applications are discussed.
Abstract: Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.

1,362 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

1,129 citations