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Molecular Recognition of Azelaic Acid and Related Molecules with DNA Polymerase I Investigated by Molecular Modeling Calculations

Overview of attention for article published in Interdisciplinary Sciences: Computational Life Sciences, October 2016
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Title
Molecular Recognition of Azelaic Acid and Related Molecules with DNA Polymerase I Investigated by Molecular Modeling Calculations
Published in
Interdisciplinary Sciences: Computational Life Sciences, October 2016
DOI 10.1007/s12539-016-0186-3
Pubmed ID
Authors

Jakaria Shawon, Akib Mahmud Khan, Adhip Rahman, Mohammad Mazharol Hoque, Mohammad Abdul Kader Khan, Mohammed G. Sarwar, Mohammad A. Halim

Abstract

Molecular recognition has central role on the development of rational drug design. Binding affinity and interactions are two key components which aid to understand the molecular recognition in drug-receptor complex and crucial for structure-based drug design in medicinal chemistry. Herein, we report the binding affinity and the nonbonding interactions of azelaic acid and related compounds with the receptor DNA polymerase I (2KFN). Quantum mechanical calculation was employed to optimize the modified drugs using B3LYP/6-31G(d,p) level of theory. Charge distribution, dipole moment and thermodynamic properties such as electronic energy, enthalpy and free energy of these optimized drugs are also explored to evaluate how modifications impact the drug properties. Molecular docking calculation was performed to evaluate the binding affinity and nonbonding interactions between designed molecules and the receptor protein. We notice that all modified drugs are thermodynamically more stable and some of them are more chemically reactive than the unmodified drug. Promise in enhancing hydrogen bonds is found in case of fluorine-directed modifications as well as in the addition of trifluoroacetyl group. Fluorine participates in forming fluorine bonds and also stimulates alkyl, pi-alkyl interactions in some drugs. Designed drugs revealed increased binding affinity toward 2KFN. A1, A2 and A3 showed binding affinities of -8.7, -8.6 and -7.9 kcal/mol, respectively against 2KFN compared to the binding affinity -6.7 kcal/mol of the parent drug. Significant interactions observed between the drugs and Thr358 and Asp355 residues of 2KFN. Moreover, designed drugs demonstrated improved pharmacokinetic properties. This study disclosed that 9-octadecenoic acid and drugs containing trifluoroacetyl and trifluoromethyl groups are the best 2KFN inhibitors. Overall, these results can be useful for the design of new potential candidates against DNA polymerase I.

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Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Germany 1 2%
Unknown 48 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 22%
Student > Bachelor 9 18%
Student > Ph. D. Student 6 12%
Researcher 5 10%
Student > Doctoral Student 2 4%
Other 5 10%
Unknown 12 24%
Readers by discipline Count As %
Chemistry 15 30%
Biochemistry, Genetics and Molecular Biology 7 14%
Pharmacology, Toxicology and Pharmaceutical Science 4 8%
Medicine and Dentistry 3 6%
Agricultural and Biological Sciences 2 4%
Other 6 12%
Unknown 13 26%
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 06 October 2016.
All research outputs
#20,413,129
of 22,963,381 outputs
Outputs from Interdisciplinary Sciences: Computational Life Sciences
#207
of 297 outputs
Outputs of similar age
#281,843
of 324,788 outputs
Outputs of similar age from Interdisciplinary Sciences: Computational Life Sciences
#6
of 6 outputs
Altmetric has tracked 22,963,381 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 297 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 1st percentile – i.e., 1% 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 324,788 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.