Literature DB >> 25373478

Statistical analysis, optimization, and prioritization of virtual screening parameters for zinc enzymes including the anthrax toxin lethal factor.

Kimberly M Maize, Xia Zhang, Elizabeth Ambrose Amin1.   

Abstract

The anthrax toxin lethal factor (LF) and matrix metalloproteinase-3 (MMP-3, stromelysin-1) are popular zinc metalloenzyme drug targets, with LF primarily responsible for anthrax-related toxicity and host death, while MMP-3 is involved in cancer- and rheumatic disease-related tissue remodeling. A number of in silico screening techniques, most notably docking and scoring, have proven useful for identifying new potential drug scaffolds targeting LF and MMP-3, as well as for optimizing lead compounds and investigating mechanisms of action. However, virtual screening outcomes can vary significantly depending on the specific docking parameters chosen, and systematic statistical significance analyses are needed to prioritize key parameters for screening small molecules against these zinc systems. In the current work, we present a series of chi-square statistical analyses of virtual screening outcomes for cocrystallized LF and MMP-3 inhibitors docked into their respective targets, evaluated by predicted enzyme-inhibitor dissociation constant and root-mean-square deviation (RMSD) between predicted and experimental bound configurations, and we present a series of preferred parameters for use with these systems in the industry-standard Surflex-Dock screening program, for use by researchers utilizing in silico techniques to discover and optimize new scaffolds.

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Year:  2014        PMID: 25373478      PMCID: PMC4631255          DOI: 10.2174/1568026614666141106163011

Source DB:  PubMed          Journal:  Curr Top Med Chem        ISSN: 1568-0266            Impact factor:   3.295


  32 in total

Review 1.  Virtual screening in lead discovery and optimization.

Authors:  Ajay N Jain
Journal:  Curr Opin Drug Discov Devel       Date:  2004-07

2.  Parameter estimation for scoring protein-ligand interactions using negative training data.

Authors:  Tuan A Pham; Ajay N Jain
Journal:  J Med Chem       Date:  2006-10-05       Impact factor: 7.446

3.  Membrane-type I matrix metalloproteinase-dependent regulation of rheumatoid arthritis synoviocyte function.

Authors:  Farideh Sabeh; David Fox; Stephen J Weiss
Journal:  J Immunol       Date:  2010-05-05       Impact factor: 5.422

4.  A preliminary in silico lead series of 2-phthalimidinoglutaric acid analogues designed as MMP-3 inhibitors.

Authors:  Elizabeth A Amin; William J Welsh
Journal:  J Chem Inf Model       Date:  2006 Sep-Oct       Impact factor: 4.956

5.  Highly predictive CoMFA and CoMSIA models for two series of stromelysin-1 (MMP-3) inhibitors elucidate S1' and S1-S2' binding modes.

Authors:  Elizabeth A Amin; William J Welsh
Journal:  J Chem Inf Model       Date:  2006 Jul-Aug       Impact factor: 4.956

6.  Novel and selective DNA methyltransferase inhibitors: Docking-based virtual screening and experimental evaluation.

Authors:  Dirk Kuck; Narender Singh; Frank Lyko; Jose L Medina-Franco
Journal:  Bioorg Med Chem       Date:  2009-11-27       Impact factor: 3.641

7.  Novel inhibitors of human histone deacetylase (HDAC) identified by QSAR modeling of known inhibitors, virtual screening, and experimental validation.

Authors:  Hao Tang; Xiang S Wang; Xi-Ping Huang; Bryan L Roth; Kyle V Butler; Alan P Kozikowski; Mira Jung; Alexander Tropsha
Journal:  J Chem Inf Model       Date:  2009-02       Impact factor: 4.956

8.  Identification of novel non-hydroxamate anthrax toxin lethal factor inhibitors by topomeric searching, docking and scoring, and in vitro screening.

Authors:  Ting-Lan Chiu; Jonathan Solberg; Satish Patil; Todd W Geders; Xia Zhang; Subhashree Rangarajan; Rawle Francis; Barry C Finzel; Michael A Walters; Derek J Hook; Elizabeth A Amin
Journal:  J Chem Inf Model       Date:  2009-12       Impact factor: 4.956

9.  Discovery of geranylgeranyltransferase-I inhibitors with novel scaffolds by the means of quantitative structure-activity relationship modeling, virtual screening, and experimental validation.

Authors:  Yuri K Peterson; Xiang S Wang; Patrick J Casey; Alexander Tropsha
Journal:  J Med Chem       Date:  2009-07-23       Impact factor: 7.446

10.  Development of a novel virtual screening cascade protocol to identify potential trypanothione reductase inhibitors.

Authors:  Rolando Perez-Pineiro; Asdrubal Burgos; Deuan C Jones; Lena C Andrew; Hortensia Rodriguez; Margarita Suarez; Alan H Fairlamb; David S Wishart
Journal:  J Med Chem       Date:  2009-03-26       Impact factor: 7.446

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  1 in total

1.  Optimizing culture conditions for production of intra and extracellular inulinase and invertase from Aspergillus niger ATCC 20611 by response surface methodology (RSM).

Authors:  Mojdeh Dinarvand; Malahat Rezaee; Majid Foroughi
Journal:  Braz J Microbiol       Date:  2017-02-10       Impact factor: 2.476

  1 in total

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