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High-throughput virtual screening with e-pharmacophore and molecular simulations study in the designing of pancreatic lipase inhibitors

Overview of attention for article published in Drug Design, Development and Therapy, August 2015
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Title
High-throughput virtual screening with e-pharmacophore and molecular simulations study in the designing of pancreatic lipase inhibitors
Published in
Drug Design, Development and Therapy, August 2015
DOI 10.2147/dddt.s84052
Pubmed ID
Authors

Ganesh Kumar Veeramachaneni, K Kranthi Raj, Leela Madhuri Chalasani, Jayakumar Singh Bondili, Venkateswara Rao Talluri

Abstract

Obesity is a progressive metabolic disorder in the current world population, and is characterized by the excess deposition of fat in the adipose tissue. Pancreatic lipase is one of the key enzymes in the hydrolysis of triglycerides into monoglycerides and free fatty acids, and is thus considered a promising target for the treatment of obesity. The present drugs used for treating obesity do not give satisfactory results, and on prolonged usage result in severe side effects. In view of the drastic increase in the obese population day-to-day, there is a greater need to discover new drugs with lesser side effects. High-throughput virtual screening combined with e-pharmacophore screening and ADME (absorption, distribution, metabolism, and excretion) and PAINS (pan-assay interference compounds) filters were applied to screen out the ligand molecules from the ZINC natural molecule database. The screened molecules were subjected to Glide XP docking to study the molecular interactions broadly. Further, molecular dynamic simulations were used to validate the stability of the enzyme-ligand complexes. Finally, the molecules with better results were optimized for in vitro testing. The screening protocols identified eight hits from the natural molecule database, which were further filtered through pharmacological filters. The final four hits were subjected to extra precision docking, and the complexes were finally studied with molecular dynamic simulations. The results pointed to the zinc 85893731 molecule as the most stable in the binding pocket, producing consistent H-bond interaction with Ser152 (G=-7.18). The optimized lead molecule exhibited good docking score, better fit, and improved ADME profile. The present study specifies zinc 85893731 as a lead molecule with higher binding score and energetically stable complex with pancreatic lipase. This lead molecule, along with its various analogs, can be further tested as a novel inhibitor against pancreatic lipase using in vitro protocols.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 14 19%
Student > Ph. D. Student 12 16%
Student > Master 9 12%
Researcher 6 8%
Professor 3 4%
Other 12 16%
Unknown 19 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 23%
Agricultural and Biological Sciences 9 12%
Chemistry 7 9%
Pharmacology, Toxicology and Pharmaceutical Science 5 7%
Medicine and Dentistry 3 4%
Other 10 13%
Unknown 24 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 April 2016.
All research outputs
#21,118,279
of 25,942,066 outputs
Outputs from Drug Design, Development and Therapy
#1,464
of 2,288 outputs
Outputs of similar age
#203,708
of 277,458 outputs
Outputs of similar age from Drug Design, Development and Therapy
#103
of 149 outputs
Altmetric has tracked 25,942,066 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,288 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 277,458 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 149 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.