Literature DB >> 24610240

The use of docking-based comparative intermolecular contacts analysis to identify optimal docking conditions within glucokinase and to discover of new GK activators.

Mutasem O Taha1, Maha Habash, Mohammad A Khanfar.   

Abstract

Glucokinase (GK) is involved in normal glucose homeostasis and therefore it is a valid target for drug design and discovery efforts. GK activators (GKAs) have excellent potential as treatments of hyperglycemia and diabetes. The combined recent interest in GKAs, together with docking limitations and shortages of docking validation methods prompted us to use our new 3D-QSAR analysis, namely, docking-based comparative intermolecular contacts analysis (dbCICA), to validate docking configurations performed on a group of GKAs within GK binding site. dbCICA assesses the consistency of docking by assessing the correlation between ligands' affinities and their contacts with binding site spots. Optimal dbCICA models were validated by receiver operating characteristic curve analysis and comparative molecular field analysis. dbCICA models were also converted into valid pharmacophores that were used as search queries to mine 3D structural databases for new GKAs. The search yielded several potent bioactivators that experimentally increased GK bioactivity up to 7.5-folds at 10 μM.

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Year:  2014        PMID: 24610240     DOI: 10.1007/s10822-014-9740-4

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  79 in total

1.  Scoring functions: a view from the bench.

Authors:  J R Tame
Journal:  J Comput Aided Mol Des       Date:  1999-03       Impact factor: 3.686

2.  Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening.

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Journal:  J Med Chem       Date:  2004-03-25       Impact factor: 7.446

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Authors:  Shashidhar N Rao; Martha S Head; Amit Kulkarni; Judith M LaLonde
Journal:  J Chem Inf Model       Date:  2007-11-07       Impact factor: 4.956

4.  Lessons in molecular recognition. 2. Assessing and improving cross-docking accuracy.

Authors:  Jeffrey J Sutherland; Ravi K Nandigam; Jon A Erickson; Michal Vieth
Journal:  J Chem Inf Model       Date:  2007-10-23       Impact factor: 4.956

Review 5.  Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes?

Authors:  Johannes Kirchmair; Patrick Markt; Simona Distinto; Gerhard Wolber; Thierry Langer
Journal:  J Comput Aided Mol Des       Date:  2008-01-15       Impact factor: 3.686

6.  Discovery of novel 2-(pyridine-2-yl)-1H-benzimidazole derivatives as potent glucokinase activators.

Authors:  Makoto Ishikawa; Katsumasa Nonoshita; Yoshio Ogino; Yoshikazu Nagae; Daisuke Tsukahara; Hideka Hosaka; Hiroko Maruki; Sumika Ohyama; Riki Yoshimoto; Kaori Sasaki; Yasufumi Nagata; Jun-Ichi Eiki; Teruyuki Nishimura
Journal:  Bioorg Med Chem Lett       Date:  2009-05-18       Impact factor: 2.823

7.  Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes.

Authors:  M D Eldridge; C W Murray; T R Auton; G V Paolini; R P Mee
Journal:  J Comput Aided Mol Des       Date:  1997-09       Impact factor: 3.686

8.  Ligand-based assessment of factor Xa binding site flexibility via elaborate pharmacophore exploration and genetic algorithm-based QSAR modeling.

Authors:  Mutasem O Taha; Amjad M Qandil; Dhia D Zaki; Murad A AlDamen
Journal:  Eur J Med Chem       Date:  2005-07       Impact factor: 6.514

9.  Hydration in drug design. 2. Influence of local site surface shape on water binding.

Authors:  C S Poornima; P M Dean
Journal:  J Comput Aided Mol Des       Date:  1995-12       Impact factor: 3.686

10.  WaterScore: a novel method for distinguishing between bound and displaceable water molecules in the crystal structure of the binding site of protein-ligand complexes.

Authors:  Alfonso T García-Sosa; Ricardo L Mancera; Philip M Dean
Journal:  J Mol Model       Date:  2003-05-17       Impact factor: 1.810

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  5 in total

1.  Combining molecular dynamics simulation and ligand-receptor contacts analysis as a new approach for pharmacophore modeling: beta-secretase 1 and check point kinase 1 as case studies.

Authors:  Ma'mon M Hatmal; Shadi Jaber; Mutasem O Taha
Journal:  J Comput Aided Mol Des       Date:  2016-10-08       Impact factor: 3.686

2.  Combining docking-based comparative intermolecular contacts analysis and k-nearest neighbor correlation for the discovery of new check point kinase 1 inhibitors.

Authors:  Nour Jamal Jaradat; Mohammad A Khanfar; Maha Habash; Mutasem Omar Taha
Journal:  J Comput Aided Mol Des       Date:  2015-05-09       Impact factor: 3.686

3.  Docking-generated multiple ligand poses for bootstrapping bioactivity classifying Machine Learning: Repurposing covalent inhibitors for COVID-19-related TMPRSS2 as case study.

Authors:  Ma'mon M Hatmal; Omar Abuyaman; Mutasem Taha
Journal:  Comput Struct Biotechnol J       Date:  2021-08-19       Impact factor: 7.271

4.  Discovery of new Cdc2-like kinase 4 (CLK4) inhibitors via pharmacophore exploration combined with flexible docking-based ligand/receptor contact fingerprints and machine learning.

Authors:  Mai Fayiz Al-Tawil; Safa Daoud; Ma'mon M Hatmal; Mutasem Omar Taha
Journal:  RSC Adv       Date:  2022-04-05       Impact factor: 3.361

5.  Improved machine learning scoring functions for identification of Electrophorus electricus's acetylcholinesterase inhibitors.

Authors:  Ankit Ganeshpurkar; Ravi Singh; Shalini Shivhare; Devendra Kumar; Gopichand Gutti; Ravibhushan Singh; Ashok Kumar; Sushil Kumar Singh
Journal:  Mol Divers       Date:  2021-07-30       Impact factor: 2.943

  5 in total

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