gambling on protein promiscuity, polypharmacology and exploratory

Dirty simula,ons: gambling on protein promiscuity, polypharmacology and exploratory toxicology Domenico Alberga, Domenico Gadaleta, Andrea Gissi, Gianluca La<anzi, Giuseppe Felice Mangiatordi and Orazio NicoloB (Laboratory of Virtual Molecular Experiments-­‐ Drug Oriented) LoVME-­‐ DO Università degli Studi di Bari ‘Aldo Moro’ DiparFmento di Farmacia – Scienze del Farmaco Research day, Bari, 27 Feb 2014 1 2 Hann M., Oprea T.I. Pursuing the leadlikeness concept in pharmaceuFcal research. Curr. Opin. Chem. Biol. 8, 255, 263, 2004 Visual naviga,on from Chemical to Biology and Medicine Spaces via Principal Component Analysis 3 DUD: Directory of Useful Decoys Extracted from ZINC, a database of commercially available compounds complying the Lipinsky’s Rule of Five, a filter based on empirical analyses of drug aeer FDA approval A total of 2,950 acFve compounds (red) against a total of 40 targets. For each acFve, 36 decoys (blue) with similar physical properFes (e.g. molecular weight, calculated LogP) but dissimilar topology. A total of 109150 compounds (acFve and decoys). 4 2006 Huang N, Shoichet BK, Irwin JJ. Benchmarking Sets for Molecular Docking, J. Med. Chem. 49,6789-­‐680, Principal Component Analysis: Score plot of the DUD database Different therapeuFc classes look at different space regions, however overlaps and voids can occur 5 Principal Component Analysis: Loadings plot of the DUD database Polarity • accptHB • donorHB • FISA • PSA • N and O • QPlogPw Size • 
• 
• 
• 
mol MW volume SASA nonHatoms Hydrohobicity •  QPlogPo/w •  QPlogKhsa Solubility •  QPlogS •  CIQPlogS Permeability •  QPlogKp •  HumanOralAbsorpFon •  QPlogBB •  QPPCaco •  QPPMDCK Lovering F, Bikker J, Humblet C. Escape from Flatland: Increasing SaturaFon as an Approach to Improving Clinical Success J. Med. Chem., 52, 6752–6767, 2009 6 Bickerton GR,Paolini GV, Besnard J,Muresan S, Hopkins AL. QuanFfying the chemical beauty of drugs Nat Chem.4, 90-­‐98, 2012 Principal Component Analysis: 3D score plot of the DUD database Target (red) an off-­‐target (white) space 7 NavigaFng from chemical to biology and medicine spaces relationship between the continuum of chemical space (blue) and the discrete areas
of chemical space that are occupied by target / off-target compounds (red and
green) 8 C. Lipinski and A. Hopkins, NavigaFng chemical space for biology and medicine Nature 432, 855-­‐861, 2004 Design and development of mul,-­‐target compounds to approach cancer and cancer resistance Proge<o IDEA 2011 Study on the pathophysiological role of D184E muta,on in Aquaporin-­‐4 gene Proge<o FIRB 2012 Predic,ve toxicology models complying REACH requirements Is,tuto Superiore di Sanità 2012
9 10 β
α
Dama-Colchicine
11 Sketch-­‐shelf plakorm Commercial Compound CollecFon (CoCoCo database) 7×106 shape pharmacophore 65 compounds in-­‐vitro test …in progress… docking 12 Human AQP4: structure PDB code 3GD8
M23-‐‑‒AQP4
Heterotetrameric units
M1-‐‑‒AQP4
Orthogonal arrays of particles (OAPs)
13 STUDY ON THE PATHOPHYSIOLOGICAL
ROLE OF D184E MUTATION IN
AQUAPORIN-4 GENE
q 
Elucidating the role of D184E mutation in AQP4 gene on AQP4 plasma
membrane stability and/or on its dynamic interaction with cell cytoskeleton and
on important physiological functions of excitable tissues, related to a correct
functionality of the water channel AQP4 for the increased susceptibility of
individuals with this mutation, in developing pathological situations, such as
deafness, neuromyelitis optica (NMO) and probably others not yet known. 14 Druggable or undruggable, that is the quesFon! Selectivity filter (ar/R region)
Asparagine-Proline-Alanine
Electrostatic barrier / proton exclusion
!
15 Where have we been? Where are we going to? •  Extracting relevant information from protein structures gives the opportunity to use the biological space for many purposes •  ‘Similar entities show similar function’ à several methods to compare proteins 1970
1980
1990
2000
2013
Sequence comparison 3D structure comparison 16 “the function of a protein does not necessarily depend by the folding or the sequence” Journal of Structural Biology 134, 145–165 (2001) Cavity characterization Something like… Find the differences!
Slight differences (selectivity, drug side effects) Separated at
birth !
Unexpected similaritites (multi-­‐target, drug repositioning, 17 Large scale analysis) Cavity characterizaFon Common Reference Framework Structure of quadruplets 18 Evaluation of the type, strength and direction of the interactions that a cavity is capable of making Data analysis Virtual screening where cavities in the database are ranked accordingly with their degree of similarity against a template (query cavity). Similarity scores can be used to perform a Principal Component Analysis (PCA). 19 REACH – DefiniFons q REACH indicates guidelines
q REACH is the new European for collecting and assessing,
Community RegulaFon (EC by June 2018, all
1907/2006) concerning information on the
Registra,on, Evalua,on, Authoriza,on and Restric,on of properties and hazards of
over 100,000 substances
chemicals. REACH has entered into force on June 2007 imported/manifactured into
European Union, exceeding
1 ton per year q REACH has been adopted to improve the protec,on of human health and the environment from the risks that can be posed by chemicals 20 BioconcentraFon factor q BCF values are used to relate pollutant residues in aquaFc organisms to the pollutant concentraFon in ambient water q The BCF is one of the most relevant endpoints under REACH, as well as one of the most complex, expensive and ,me consuming q REACH describes and
promotes alternative
methods for the BCF
assessment 21 Credits Domenico Alberga, Dipar,mento di Fisica Angelo Caroq Marco Caro Saverio Cellamare Nunzio Denora Roberta Farina, Dipar,mento di Farmacia-­‐Scienze del Farmaco Antonio Frigeri, DiparFmento di Bioscienze, Biotecnologie e BiofarmaceuFca Domenico Gadaleta, Dipar,mento di Farmacia-­‐Scienze del Farmaco Ilenia Giangreco, Cambridge Cristallographic Data Centre Sabrina Giordano, Is,tuto di Ricerche Farmacologiche “Mario Negri” Andrea Gissi, European Chemical Agency Antonellina Introcaso Gianluca Laranzi, DiparFmento di Fisica Francesco Leoneq Giuseppe Felice Mangiatordi, Dipar,mento di Farmacia-­‐Scienze del Farmaco Fabiola Teresa Miscioscia, Colosseum Combinatorial Chemistry Centre for Technology Grazia Paola Nicchia, DiparFmento di Bioscienze, Biotecnologie e BiofarmaceuFca Leonardo Pisani, Dipar,mento di Farmacia-­‐Scienze del Farmaco Lydia Siragusa, Molecular Discovery Angela Stefanachi Diana Antonella Stolfa, Dipar,mento di Farmacia-­‐Scienze del Farmaco