A steered molecular dynamics mediated hit discovery for histone deacetylases.

The inhibitors of class I histone deacetylases (HDACIs) have gained significant interest in cancer therapeutics. Virtual high throughput screening (vHTS) is one of the popular approaches used in the identification of novel scaffolds of HDACIs. However, an accurate description of ligand-protein flexibilities in the vHTS remains challenging. In this work, we implement an integrated approach, which combines the vHTS with the 'state-of-the-art' steered molecular dynamics (SMD). This approach serves as an efficient tool to identify potential hits and characterize their binding potencies against the class I HDACs in a flexible solvent environment. A hybrid pharmacophore-based and structure-based vHTS method identifies the hits with more favourable physico-chemical features against the class I HDACs. Our pharmacophore-based screening enhanced the quality of the vHTS outcomes. Further, the molecular interactions between the hits and the HDACs are investigated using the SMD-driven force profiles, which in turn resulted in filtering the hits with higher binding potencies against the HDACs. Our results, therefore, reveal that vHTS and SMD can be a complementary and effective analytical tool for accelerating the hit identification phase in structure-based drug design.

[1]  Matthew P. Repasky,et al.  Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. , 2006, Journal of medicinal chemistry.

[2]  Lei Zhang,et al.  Discovery of a novel histone deacetylase 8 inhibitor by virtual screening , 2010, Medicinal Chemistry Research.

[3]  M. Dokmanovic,et al.  Prospects: Histone deacetylase inhibitors , 2005, Journal of cellular biochemistry.

[4]  Gisbert Schneider,et al.  Virtual screening: an endless staircase? , 2010, Nature Reviews Drug Discovery.

[5]  Alexander D. MacKerell,et al.  All-atom empirical potential for molecular modeling and dynamics studies of proteins. , 1998, The journal of physical chemistry. B.

[6]  Mai Suan Li,et al.  Neuraminidase inhibitor R-125489--a promising drug for treating influenza virus: steered molecular dynamics approach. , 2011, Biochemical and biophysical research communications.

[7]  Satoshi Inoue,et al.  Inhibition of histone deacetylase class I but not class II is critical for the sensitization of leukemic cells to tumor necrosis factor-related apoptosis-inducing ligand-induced apoptosis. , 2006, Cancer research.

[8]  Ruth Nussinov,et al.  A Method for Biomolecular Structural Recognition and Docking Allowing Conformational Flexibility , 1998, J. Comput. Biol..

[9]  Xue-Ru Wu,et al.  The histone deacetylase inhibitor belinostat (PXD101) suppresses bladder cancer cell growth in vitro and in vivo , 2007, Journal of Translational Medicine.

[10]  K. Schulten,et al.  Molecular dynamics study of unbinding of the avidin-biotin complex. , 1997, Biophysical journal.

[11]  Brian K. Shoichet,et al.  ZINC - A Free Database of Commercially Available Compounds for Virtual Screening , 2005, J. Chem. Inf. Model..

[12]  Subha Kalyaanamoorthy,et al.  Energy based pharmacophore mapping of HDAC inhibitors against class I HDAC enzymes. , 2013, Biochimica et biophysica acta.

[13]  Y Z Chen,et al.  Identifying Novel Type ZBGs and Nonhydroxamate HDAC Inhibitors Through a SVM Based Virtual Screening Approach , 2010, Molecular informatics.

[14]  W. L. Jorgensen,et al.  Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids , 1996 .

[15]  A. Laio,et al.  Equilibrium free energies from nonequilibrium metadynamics. , 2006, Physical Review Letters.

[16]  P. Bertrand Inside HDAC with HDAC inhibitors. , 2010, European journal of medicinal chemistry.

[17]  Ray Luo,et al.  Virtual screening using molecular simulations , 2011, Proteins.

[18]  S. Vadivelan,et al.  Pharmacophore modeling and virtual screening studies to design some potential histone deacetylase inhibitors as new leads. , 2008, Journal of molecular graphics & modelling.

[19]  O. Witt,et al.  HDAC family: What are the cancer relevant targets? , 2009, Cancer letters.

[20]  Daniel Cappel,et al.  Generation of structure-based pharmacophores using energetic analysis – application on fragment docking , 2011, J. Cheminformatics.

[21]  A. Cavalli,et al.  Single-molecule pulling simulations can discern active from inactive enzyme inhibitors. , 2010, Journal of the American Chemical Society.

[22]  A. Leach,et al.  Ligand docking to proteins with discrete side-chain flexibility. , 1994, Journal of molecular biology.

[23]  P. Marks,et al.  Histone Deacetylase Inhibitors: Overview and Perspectives , 2007, Molecular Cancer Research.

[24]  K. Schulten,et al.  Single-Molecule Experiments in Vitro and in Silico , 2007, Science.

[25]  Yi-Ping Phoebe Chen,et al.  Quantum polarized ligand docking investigation to understand the significance of protonation states in histone deacetylase inhibitors. , 2013, Journal of molecular graphics & modelling.

[26]  Keun Woo Lee,et al.  Dynamic Structure-Based Pharmacophore Model Development: A New and Effective Addition in the Histone Deacetylase 8 (HDAC8) Inhibitor Discovery , 2011, International journal of molecular sciences.

[27]  Ricky W. Johnstone,et al.  Histone-deacetylase inhibitors: novel drugs for the treatment of cancer , 2002, Nature Reviews Drug Discovery.

[28]  Woody Sherman,et al.  Energetic analysis of fragment docking and application to structure-based pharmacophore hypothesis generation , 2009, J. Comput. Aided Mol. Des..

[29]  Mai Suan Li,et al.  Top Leads for Swine Influenza A/H1N1 Virus Revealed by Steered Molecular Dynamics Approach , 2010, J. Chem. Inf. Model..

[30]  S. Sakkiah,et al.  Ligand and structure based pharmacophore modeling to facilitate novel histone deacetylase 8 inhibitor design. , 2010, European journal of medicinal chemistry.

[31]  Ruibo Wu,et al.  Zinc chelation with hydroxamate in histone deacetylases modulated by water access to the linker binding channel. , 2011, Journal of the American Chemical Society.

[32]  Qing-Chuan Zheng,et al.  Molecular Dynamics Simulations Suggest Ligand’s Binding to Nicotinamidase/Pyrazinamidase , 2012, PloS one.

[33]  P. Marks,et al.  Histone deacetylases and cancer: causes and therapies , 2001, Nature Reviews Cancer.

[34]  C. Abrams,et al.  Ligand escape pathways and (un)binding free energy calculations for the hexameric insulin-phenol complex. , 2008, Biophysical journal.

[35]  Difei Wang,et al.  Computational studies on the histone deacetylases and the design of selective histone deacetylase inhibitors. , 2009, Current topics in medicinal chemistry.

[36]  Yi-Ping Phoebe Chen,et al.  Structure-based drug design to augment hit discovery. , 2011, Drug discovery today.

[37]  M. Navre,et al.  Exploration of the HDAC2 foot pocket: Synthesis and SAR of substituted N-(2-aminophenyl)benzamides. , 2010, Bioorganic & medicinal chemistry letters.

[38]  Simona Distinto,et al.  Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection—What can we learn from earlier mistakes? , 2008, J. Comput. Aided Mol. Des..

[39]  A. Oyelere,et al.  Synthesis and structure-activity relationship of histone deacetylase (HDAC) inhibitors with triazole-linked cap group. , 2008, Bioorganic & medicinal chemistry.

[40]  Andreas Bender,et al.  Recognizing Pitfalls in Virtual Screening: A Critical Review , 2012, J. Chem. Inf. Model..

[41]  R C Wade,et al.  How do substrates enter and products exit the buried active site of cytochrome P450cam? 2. Steered molecular dynamics and adiabatic mapping of substrate pathways. , 2000, Journal of molecular biology.

[42]  Laxmikant V. Kalé,et al.  Scalable molecular dynamics with NAMD , 2005, J. Comput. Chem..

[43]  Walter Cabri,et al.  Azetidinones as Zinc‐Binding Groups to Design Selective HDAC8 Inhibitors , 2009, ChemMedChem.

[44]  David E. Gloriam,et al.  G Protein- and Agonist-Bound Serotonin 5-HT2A Receptor Model Activated by Steered Molecular Dynamics Simulations , 2011, J. Chem. Inf. Model..

[45]  P. Marks,et al.  Structures of a histone deacetylase homologue bound to the TSA and SAHA inhibitors , 1999, Nature.

[46]  Jaakko Akola,et al.  Steered molecular dynamics simulations of ligand–receptor interaction in lipocalins , 2011, European Biophysics Journal.

[47]  Hao Tang,et al.  Novel Inhibitors of Human Histone Deacetylase (HDAC) Identified by QSAR Modeling of Known Inhibitors, Virtual Screening, and Experimental Validation , 2009, J. Chem. Inf. Model..

[48]  Jianwei He,et al.  Steered molecular dynamics simulations on the binding of the appendant structure and helix-β2 in domain-swapped human cystatin C dimer , 2012, Journal of biomolecular structure & dynamics.

[49]  Y. Sugita,et al.  Replica-exchange molecular dynamics method for protein folding , 1999 .

[50]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings , 1997 .

[51]  Christopher I. Bayly,et al.  Evaluating Virtual Screening Methods: Good and Bad Metrics for the "Early Recognition" Problem , 2007, J. Chem. Inf. Model..

[52]  Yi-Ping Phoebe Chen,et al.  Exploring Inhibitor Release Pathways in Histone Deacetylases Using Random Acceleration Molecular Dynamics Simulations , 2012, J. Chem. Inf. Model..

[53]  Yong-Jun Jiang,et al.  Identification of ligand features essential for HDACs inhibitors by pharmacophore modeling. , 2008, Journal of molecular graphics & modelling.

[54]  J. Schwabe,et al.  Structure of HDAC3 bound to corepressor and inositol tetraphosphate , 2011, Nature.

[55]  J. R. Somoza,et al.  Structural snapshots of human HDAC8 provide insights into the class I histone deacetylases. , 2004, Structure.

[56]  W. L. Jorgensen,et al.  Comparison of simple potential functions for simulating liquid water , 1983 .

[57]  S. Kim,et al.  "Soft docking": matching of molecular surface cubes. , 1991, Journal of molecular biology.

[58]  Delong Liu,et al.  Novel histone deacetylase inhibitors in clinical trials as anti-cancer agents , 2010, Journal of hematology & oncology.

[59]  J. Bradner,et al.  On the inhibition of histone deacetylase 8. , 2010, Bioorganic & medicinal chemistry.

[60]  David E. Shaw,et al.  PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results , 2006, J. Comput. Aided Mol. Des..

[61]  David S Goodsell,et al.  The Molecular Perspective: Histone Deacetylase , 2003, Stem cells.

[62]  Hege S. Beard,et al.  Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. , 2004, Journal of medicinal chemistry.

[63]  Michele Pallaoro,et al.  HDACs, histone deacetylation and gene transcription: from molecular biology to cancer therapeutics , 2007, Cell Research.

[64]  Syam B. Nair,et al.  Computational identification of novel histone deacetylase inhibitors by docking based QSAR , 2012, Comput. Biol. Medicine.

[65]  P. Marks,et al.  Histone deacetylase inhibitors: from target to clinical trials , 2002, Expert opinion on investigational drugs.

[66]  N. L. La Thangue,et al.  HDAC inhibitor-based therapies and haematological malignancy. , 2009, Annals of oncology : official journal of the European Society for Medical Oncology.

[67]  D. E. Clark,et al.  Outstanding challenges in protein–ligand docking and structure‐based virtual screening , 2011 .

[68]  M. K. Pflum,et al.  Isoform-selective histone deacetylase inhibitors. , 2008, Chemical Society reviews.

[69]  I. Kuntz,et al.  Molecular docking to ensembles of protein structures. , 1997, Journal of molecular biology.