Ron Levy group

Exploring
molecular
landscapes

Structural Bioinformatics II

Chemistry 5412

Spring 2016

Time and Location:

  • 5:30PM - 7:50OM, SERC 456

Instrcutors:

Description

This course is designed to provide a basic introduction to computational methods used in protein structure determination and molecular modeling. The course emphasis will be on the use of computational methods for protein structure prediction to understand protein structures through modelling and on structure based drug design. The course will provide practical training in the application of modeling techniques in drug discovery

Reference Texts

  • Gregory A. Petsko, Dagmar Ringe, Protein Structure and Function, New Science Press, 2004
  • Thomas E. Creighton, Protein: Structure and Function , Freeman. W. H. & Company. 1992
  • Andrew Leach, Molecular Modelling: principles and Applications, Prentice Hall, 2001
  • Alan Hinchliffe, Molecular Modelling for Beginners, John Wiley & Sons, 2008
  • Hans-Dieter Holtje, Wolfgang Sippl, Didier Rognan, Gerd Folkers, Molecular Modeling: Basic Principles and Applications, Wiley-VCH Verlga GmbH, 2008
  • Daan Frenkel, Berend Smit, Understanding Molecular Simulation From Algorithms to Applications, Academic Press, 2001

Syllabus:

pdf

I. Protein Structure Modelling

Dates Topics Lecturer Lecture Slides
1/11 Lecture:1
General overview on protein structure prediction
Strategies: ab initio vs knowledge-based
Secondary structure prediction
Community-wide assessment of protein structure
prediction CASP and CAMEO
Vijayan Ramaswamy ppt
1/25 Lecture:2
Identifying templates for protein modelling:
Sequence alignment with BLAST and
position specific substitution matrices(PSI-BLAST)
Vincenzo Carnevale ppt
2/1 Lecture:3
Building a profile HMM from an alignment and
aligning sequences to it:
Formal definition of HMMs
Most probable state path: the Viterbi algorithm
The forward algorithm
Parameter estimation for HMMs
Vincenzo Carnevale ppt
2/8 Lecture:4
Template based protein modelling
Homology modeling
Threading or Fold recognition
"Loop modelling"
Template Based and Non-Template Based Techniques
Roland Dunbrack ppt
2/15 Lecture:5
Protein side chain modellingi
Graph based, Tree Decomposition, DEE, SCMF
Refinement of comparative models
Model quality assessment
Errors in protein modelling
Roland Dunbrack ppt
2/22 Lecture:6(Protein Modelling Lab)
Hands on session in Protein Modelling(Rosetta/Modeller)
Roland & Vincenzo pdf

II. Molecular Modelling

Dates Topics Lecturer Lecture Slides
3/7 Lecture:7
Molecular Mechanics
General features of molecular mechanics force fields,
bonded terms, non-bonded terms.
Force field parameterization strategy, commonly used force
field transferability of force field parameters
Hands-on session: Basic model building, editing,
visualization and MM based energy minimization using
Maestro (Schrodinger)
Nanjie Deng ppt
3/14 Lecture:8
Potential Energy Surface and Optimization methods
Basics of Molecular Dynamics simulations.
Integrators of equation of motion: Verlet, Leap-frog.
Treatment of electrostatics, cut-off, Ewald, PME.
Hands-on session: Conformational analysis using Macromodel
Vincenzo Carnevale pdf
3/21 Lecture:9
Conformational sampling methods in Molecular Dynamics:
NVT, NPT ensembles.
Non-canonical sampling and importance sampling methods:
Umbrella sampling, metadynamics.
Vincenzo Carnevale pdf
3/28 lecture:10(Molecular Dynamics Lab)
Hands on session of MD simulation of a small protein
Crambin in water, using Desmond (Schrodinger).
Analyze the RMS fluctuation as a function of amino acid
residues, and RMSD as a function of simulation time.
Nanjie/Vincenzo

III. Structual Based Drug design

Dates Topics Lecturer Lecture Slides
4/4 Lecture;11
Virtual screening in Drug Discovery
Overview of ligand-based and structure-based screening,
basics of Molecular Docking.
Success stories form structure based drug design:
HIV-1 protease inhibitor.
Nanjie Deng ppt
4/11 Lecture:12
Ligand-based screening:
pharmacophore based screening, Shape Based Screening
Eleonora Gianti pdf
4/18 Lecture:13
Best practices in Virtual Screening:
ligand preparation, protein preparation, benchmarking using
various evaluation metrics(ROC enrichment, RMSD for pose prediction)
Binding Free energy methods in Structure Based Drug Design:
the computation of binding affinities,
relative and absolute binding Free energy methods.
4/25 Lecture;14(Docking and Binding Free Energy Calculation Lab)
Virtual Screening: Docking using Glide (Schrodinger)
Binding Free energy calculation using the BEDAM workflow.
The protein receptor will be HIV-1 Integrase, and two ligands,
one binder and one non-binder will be used for ligands.