CoMFA Study of Piperidine Analogues of Cocaine at the Dopamine Transporter: Exploring the Binding Mode of the 3  -Substituent of the Piperidine Ring Using.

Slides:



Advertisements
Similar presentations
Combinatorial computational method gives new picomolar ligands for a known enzyme Bartosz A. Grzybowski, Alexey V. Ishchenko, Chu- Young Kim, George Topalov,
Advertisements

Case Study: Dopamine D 3 Receptor Anthagonists Chapter 3 – Molecular Modeling 1.
AutoDock 4 and AutoDock Vina -Brief Intruction
Improving enrichment rates A practical solution to an impractical problem Noel O’Boyle Cambridge Crystallographic Data Centre
Jürgen Sühnel Institute of Molecular Biotechnology, Jena Centre for Bioinformatics Jena / Germany Supplementary Material:
Computational Drug Design Apr 2010 Postgrad course on Comp Chem Noel M. O’Boyle.
Molecular dynamics refinement and rescoring in WISDOM virtual screenings Gianluca Degliesposti University of Modena and Reggio Emilia Molecular Modelling.
 Structure-based drug design:  The macromolecular target can be isolated and crystallized…then the structure will be determined using X-ray crystallography.
1 PharmID: A New Algorithm for Pharmacophore Identification Stan Young Jun Feng and Ashish Sanil NISSMPDM 3 June 2005.
Recap: Intermolecular forces and binding Overview of classes of targets for drugs Quantitation of Drug activity (functional assay) EC 50, ED 50, IC 50.
Summary Molecular surfaces QM properties presented on surface Compound screening Pattern matching on surfaces Martin Swain Critical features Dave Whitley.
M. Wagener 3D Database Searching and Scaffold Hopping Markus Wagener NV Organon.
Quantative Structure- Activity Relationships. Why QSAR? The number of compounds required for synthesis in order to place 10 different groups in 4 positions.
Quantitative Structure-Activity Relationships (QSAR) Comparative Molecular Field Analysis (CoMFA) Gijs Schaftenaar.
Bioinformatics IV Quantitative Structure-Activity Relationships (QSAR) and Comparative Molecular Field Analysis (CoMFA) Martin Ott.
An Integrated Approach to Protein-Protein Docking
BL5203: Molecular Recognition & Interaction Lecture 5: Drug Design Methods Ligand-Protein Docking (Part I) Prof. Chen Yu Zong Tel:
Pharmacophore-based Molecular Docking Bert E. Thomas, Diane Joseph- McCarthy, Juan C.Avarez.
Molecular Docking Using GOLD Tommi Suvitaival Seppo Virtanen S Basics for Biosystems of the Cell Fall 2006.
Structural biology and drug design: An overview Olivier Taboureau Assitant professor Chemoinformatics group-CBS-DTU
Virtual Screening protein-ligand interactions, inhibitors, SBDD –kinetics, competitive, slow, aggregators –H-bonding, halogens, co-factors, metal ions.
Protein Structure and Drug Discovery Workshop To be held at Monash University, Mebourne, Australia October 3 rd to 4 th 2006 Molecular Visualization Learn.
Structure Based Drug Design
1 Data mining of toxic chemicals & database-based toxicity prediction Jiansuo Wang & Luhua Lai Institute of Physical Chemistry, Peking University P. R.
GGAGATTCTGGGCCACTTTGGTTCCCCATGAGCCAAGACGGCACTTCTAATTTGCATTCCCTACCGGAGTCCCTGTCTGTAGCCAGCCTGGCTTTCAGCTGGTGCCCAAAGTGACAAATGTATCTGCAATGACAAAGGTAC CCTGGAAGGGCTCGCCCTCTGCGGAATTTCAGTTCATGCAGGCCTTGGTGCTTCCACATCTGTCCAAGGGCCTTTCAAATGTGACTTTTAACTCTGTGGATTGATTTGCCCGG
Drug Design Process Discovery Phase. Tripos Software n SYBYL & its modules SYBYL, Concord, MOLCAD, SiteId, Advanced Computation, GASP, DISCOtech, HQSAR,
Computational Techniques in Support of Drug Discovery October 2, 2002 Jeffrey Wolbach, Ph. D.
Cédric Notredame (30/08/2015) Chemoinformatics And Bioinformatics Cédric Notredame Molecular Biology Bioinformatics Chemoinformatics Chemistry.
Computer-Assisted Drug Design (1) i)Random Screening ii)Lead Development and Optimization using Multivariate Statistical Analyses. iii)Lead Generation.
Molecular Modeling: Conformational Molecular Field Analysis (CoMFA)
DE NOVO DESIGN OF A THYMIDYLATE KINASE INHIBITOR.
Development of Novel Geometrical Chemical Descriptors and Their Application to the Prediction of Ligand-Protein Binding Affinity Shuxing Zhang, Alexander.
Modern Tools of Drug Discovery
3D- QSAR. QSAR A QSAR is a mathematical relationship between a biological activity of a molecular system and its physicochemical parameters. QSAR attempts.
“Emergency discovery” of novel antimicrobials among known drugs in response to new and re-emerging infectious threats A. Cherkasov UBC / VGH Infectious.
Physicochemical Properties of Drugs in relation to Drug Action Roselyn Aperocho Naranjo, RPh, MPH USPF, College of Pharmacy
QSAR Study of HIV Protease Inhibitors Using Neural Network and Genetic Algorithm Akmal Aulia, 1 Sunil Kumar, 2 Rajni Garg, * 3 A. Srinivas Reddy, 4 1 Computational.
Altman et al. JACS 2008, Presented By Swati Jain.
1 © Patrick An Introduction to Medicinal Chemistry 3/e Chapter 10 DRUG DESIGN: OPTIMIZING TARGET INTERACTIONS Part 2: Section 10.2.
Virtual Screening C371 Fall INTRODUCTION Virtual screening – Computational or in silico analog of biological screening –Score, rank, and/or filter.
Bioinformatics MEDC601 Lecture by Brad Windle Ph# Office: Massey Cancer Center, Goodwin Labs Room 319 Web site for lecture:
Hierarchical Database Screenings for HIV-1 Reverse Transcriptase Using a Pharmacophore Model, Rigid Docking, Solvation Docking, and MM-PB/SA Junmei Wang,
Pharmacophores Chapter 13 Part 2.
Computer-aided drug discovery (CADD)/design methods have played a major role in the development of therapeutically important small molecules for several.
R L R L L L R R L L R R L L water DOCKING SIMULATIONS.
Binding Free Energies of Water Molecules in Protein Active Sites A Case Study Using Pentothenate Synthetase, An Emerging TB target Michael Brunsteiner,
Surflex: Fully Automatic Flexible Molecular Docking Using a Molecular Similarity-Based Search Engine Ajay N. Jain UCSF Cancer Research Institute and Comprehensive.
Identification of structurally diverse Growth Hormone Secretagogue (GHS) agonists by virtual screening and structure-activity relationship analysis of.
Computational Approach for Combinatorial Library Design Journal club-1 Sushil Kumar Singh IBAB, Bangalore.
Molecular mechanics Classical physics, treats atoms as spheres Calculations are rapid, even for large molecules Useful for studying conformations Cannot.
Elon Yariv Graduate student in Prof. Nir Ben-Tal’s lab Department of Biochemistry and Molecular Biology, Tel Aviv University.
Molecular Modeling in Drug Discovery: an Overview
Nehad A. El Sayed, Amal A. H. Eissa, Reem K. Arafa and Ghada F. El Masry* Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Cairo University.
Page 1 Computer-aided Drug Design —Profacgen. Page 2 The most fundamental goal in the drug design process is to determine whether a given compound will.
Computational Docking Experiments to Find a Ligand that Will Bind to Xanthine Oxidase Lysengkeng Her and Thao Yang Department of Chemistry, University.
Computational Tools Seminar
Computational design of protein function
APPLICATIONS OF BIOINFORMATICS IN DRUG DISCOVERY
Computer-aided Drug Design
Virtual Screening.
Current Status at BioChemtek
“Structure Based Drug Design for Antidiabetics”
An Integrated Approach to Protein-Protein Docking
James Ricky Cox, Department of Chemistry, Murray State University
New Transition Metal Catalysts for Selective C-H Oxidation Chemistry
Derivation of preliminary three-dimensional pharmacophoric maps for chemically diverse intravenous general anaesthetics†   J.C. Sewell, J.W. Sear  British.
Mr.Halavath Ramesh 16-MCH-001 Dept. of Chemistry Loyola College University of Madras-Chennai.
Mr.Halavath Ramesh 16-MCH-001 Dept. of Chemistry Loyola College University of Madras-Chennai.
Mr.Halavath Ramesh 16-MCH-001 Dept. of Chemistry Loyola College University of Madras-Chennai.
Mr.Halavath Ramesh 16-MCH-001 Dept. of Chemistry Loyola College University of Madras-Chennai.
Presentation transcript:

CoMFA Study of Piperidine Analogues of Cocaine at the Dopamine Transporter: Exploring the Binding Mode of the 3  -Substituent of the Piperidine Ring Using Pharmacophore-Based Flexible Alignment Hongbin Yuan, Alan P. Kozikowski, and Pavel A. Petukhov* Department of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, University of Illinois at Chicago J. Med. Chem. 2004, 47,

outline Goal: to develop a model of the dopamine transporter (DAT) using QSAR analysis of cocaine analogues –No crystal structure of the DAT is available, but many piperidine analogues of cocaine have been synthesized and evaluated for binding affinity –A highly predictive model for the DAT would facilitate development of therapeutics for cocaine abuse Methods –Training set of 36 compounds, test set of 6 compounds –Genetic Algorithm Similarity Program (GASP) used to generate pharmacophore by comparing known ligands for DAT –Comparative molecular field analysis (CoMFA) calculates steric and electrostatic field energies –Refined with Flexible Superposition (FlexS)

Cocaine and analogues

Flow chart training set

Top two pharmacophores DS = H-bond donor AS = H-bond acceptor site AA = H-bond acceptor atom

Quantitative predictions are accurate

Conclusions Two pharmacophore models suggest multiple binding modes for ligands Good fit when QSAR applied to test set of 6 compounds Predictive power for new potential therapeutics