SlideShare a Scribd company logo
1 of 28
Download to read offline
- The Physics of Drug Discovery -




           Shourjya Sanyal
Table of Content

        Topic          No Of Slides
Introduction To Drug        5
Designing
Molecular Dynamics          5
(MD) Simulation
Free Energy                 5
Calculations
Hands on Training :
MD Simulation Setup        10
and Run
Rational Drug Designing
Rational Drug Designing
Rational Drug Designing
Rational Drug Designing
Rational Drug Designing


Absorption
Distribution
Metabolism
Elimination
MD Simulations

Dynamics: calculating trajectories

• Trajectory: positions as function of time: r i (t)
• How does one determine r i (t) from Fi = mi . ai ?
      Fi = mi . Ai = mi . dvi /dti = mi . d2 ri /dti 2
• Simple case where acceleration is constant
              a = dv/dt         v = at + vo
MD Simulations

      Treatment of solvent

• Implicit: The macromolecule
interacts only with itself, but the
electrostatic   interactions    are
modified to account for the solvent
•    Explicit  representation   The
macromolecule is surrounded by
solvent molecules (water, ions) with
which the macromolecule interacts.
Specific nonbond interactions are
calculated
MD Simulations

   Periodic boundary
       conditions

For explicit representation of
solvent the boundaries of the
system must be represented
for periodic system.

Permits the modeling of very
large systems, but introduces
a level of periodicity not
present in nature.
MD Simulations
MD Simulations

  Timescale Limitations



             Molecular dynamics:
      Integration timestep - 1 fs, set by
      fastest varying force.

      Accessible timescale: about 10
      nanoseconds.
Free Energy Calculations

Energy of binding ∆H must become more negative
The energetic interactions between ligand and
receptor have to become more favorable
Free Energy Calculations

The energy terms can be calculated according to
force fields
Free Energy Calculations
Dispersive interactions: London forces and van der Waals
Free Energy Calculations
Free Energy Calculations




         Energy Surface
    Exploration by Simulation..
MD Simulation Setup
Methods for Determining Atomic Structures

NMR (nuclear magnetic resonance) : Absorption of electromagnetic waves
MD Simulation Setup

Obtaining X-Ray structures
The arrangement of atoms in the crystal gives rise to a
diffraction pattern.
MD Simulation Setup
MD Simulation Setup
MD Simulation Setup

Step One: Prepare the Protein Topology

> For this tutorial, we will utilize T4 lysozyme L99A/M102Q
(PDB code 3HTB). Go to the RCSB website and download the
PDB text for the crystal structure.

> Seperate out Ligand and Parent Molecule.
grep JZ4 3HTB_clean.pdb > JZ4.pdb

> Create Topology File for Molecule.
pdb2gmx -f 3HTB_clean.pdb -o 3HTB_processed.gro -water spc
MD Simulation Setup

Step Two : Prepare the Ligand Topology

For this tutorial, we will use PRODRG to generate a starting
topology for our ligand, JZ4. Go to the PRODRG site and
upload your JZ4.pdb file. The server presents you with several
options for how to treat your ligand.

> Include topology of ligand
; Include ligand topology
#include "JZ4.itp"
MD Simulation Setup

Step Three : Solvate The System In Box

Define the box
editconf -f 3HTB_JZ4.gro -o 3HTB_JZ4_box.gro -bt cubic -d 1.0

Adding water ions to the box
genbox -cp 3HTB_JZ4_box.gro -cs spc216.gro -p 3HTB_JZ4.top -o
3HTB_JZ4_boxwater.gro
MD Simulation Setup

Step Four : Energy Minimization

Now that the system is assembled, create the binary input
using grompp using this input parameter file:
grompp -f enermin.mdp -c 3HTB_JZ4_boxwater.gro -p 3HTB_JZ4.top -o
em.tpr

We are now ready to invoke mdrun to carry out the EM:
mdrun -v -deffnm em
MD Simulation Setup

Step Five : Analysis

Energy Landscape
g_energy -f em.edr -o tot.xvg

Structural Analysis
g_rama -f em.trr -s em.tpr -o myrama.xvg
PRESENTATION
DEVELOPMENT


   Shourjya Sanyal
Academic : shourjya.sanyal@ucdconnect.ie
Business : shourjya@thinkbiosolution.com
Think Biosolution Pvt. Ltd. is a young startup aimed at providing low
cost solutions to enterprise ranging from biotechnology to bio-medical
instrumentation. We are a global team of young scientists and
technocrats who aims to serve towards making a better future, by
incorporating innovative technology within framework of current
operations for a given corporation.
It is our dream to accelerate technology growth and development
towards building a better tomorrow I welcome you all to be a part of
this dream.

             http://www.thinkbiosolution.com

More Related Content

What's hot

What's hot (20)

Energy minimization
Energy minimizationEnergy minimization
Energy minimization
 
Lab 07-sol
Lab 07-solLab 07-sol
Lab 07-sol
 
Tau14_7TeV
Tau14_7TeVTau14_7TeV
Tau14_7TeV
 
Tersoff Potential:Inter-atomic Potential for Semi-conductors
Tersoff Potential:Inter-atomic Potential for Semi-conductorsTersoff Potential:Inter-atomic Potential for Semi-conductors
Tersoff Potential:Inter-atomic Potential for Semi-conductors
 
Application of particle swarm optimization in 3 dimensional travelling salesm...
Application of particle swarm optimization in 3 dimensional travelling salesm...Application of particle swarm optimization in 3 dimensional travelling salesm...
Application of particle swarm optimization in 3 dimensional travelling salesm...
 
Molecular mechanics
Molecular mechanicsMolecular mechanics
Molecular mechanics
 
7.local and global minima
7.local and global minima7.local and global minima
7.local and global minima
 
Particle Swarm Optimization
Particle Swarm OptimizationParticle Swarm Optimization
Particle Swarm Optimization
 
Path compression
Path compressionPath compression
Path compression
 
Research on Chaotic Firefly Algorithm and the Application in Optimal Reactive...
Research on Chaotic Firefly Algorithm and the Application in Optimal Reactive...Research on Chaotic Firefly Algorithm and the Application in Optimal Reactive...
Research on Chaotic Firefly Algorithm and the Application in Optimal Reactive...
 
en_qu_sch
en_qu_schen_qu_sch
en_qu_sch
 
Term symbols
Term symbolsTerm symbols
Term symbols
 
Lab4 slides
Lab4 slidesLab4 slides
Lab4 slides
 
#26
#26#26
#26
 
Guided Modes Of Planer waveguide
Guided Modes Of Planer waveguideGuided Modes Of Planer waveguide
Guided Modes Of Planer waveguide
 
Advanced Molecular Dynamics 2016
Advanced Molecular Dynamics 2016Advanced Molecular Dynamics 2016
Advanced Molecular Dynamics 2016
 
Dft presentation
Dft presentationDft presentation
Dft presentation
 
Energy minimization
Energy minimizationEnergy minimization
Energy minimization
 
NANO266 - Lecture 3 - Beyond the Hartree-Fock Approximation
NANO266 - Lecture 3 - Beyond the Hartree-Fock ApproximationNANO266 - Lecture 3 - Beyond the Hartree-Fock Approximation
NANO266 - Lecture 3 - Beyond the Hartree-Fock Approximation
 
Potential Energy Surface Molecular Mechanics ForceField
Potential Energy Surface Molecular Mechanics ForceField Potential Energy Surface Molecular Mechanics ForceField
Potential Energy Surface Molecular Mechanics ForceField
 

Viewers also liked

Molecular dynamics and Simulations
Molecular dynamics and SimulationsMolecular dynamics and Simulations
Molecular dynamics and Simulations
Abhilash Kannan
 
Proteomics Processes and Applications
Proteomics Processes and ApplicationsProteomics Processes and Applications
Proteomics Processes and Applications
Khalid Hakeem
 
Proteomics analysis: Basics and Applications
Proteomics analysis: Basics and ApplicationsProteomics analysis: Basics and Applications
Proteomics analysis: Basics and Applications
COST action BM1006
 

Viewers also liked (14)

Some building blocks for Rational Drug Design
Some building blocks for Rational Drug Design Some building blocks for Rational Drug Design
Some building blocks for Rational Drug Design
 
What can we learn from molecular dynamics simulations of carbon nanotube and ...
What can we learn from molecular dynamics simulations of carbon nanotube and ...What can we learn from molecular dynamics simulations of carbon nanotube and ...
What can we learn from molecular dynamics simulations of carbon nanotube and ...
 
Rational drug design
Rational drug designRational drug design
Rational drug design
 
Molecular dynamics and Simulations
Molecular dynamics and SimulationsMolecular dynamics and Simulations
Molecular dynamics and Simulations
 
Proteomics Processes and Applications
Proteomics Processes and ApplicationsProteomics Processes and Applications
Proteomics Processes and Applications
 
Proteomics
Proteomics Proteomics
Proteomics
 
Proteomics
ProteomicsProteomics
Proteomics
 
Proteomics ppt
Proteomics pptProteomics ppt
Proteomics ppt
 
Proteomics
ProteomicsProteomics
Proteomics
 
Proteomics analysis: Basics and Applications
Proteomics analysis: Basics and ApplicationsProteomics analysis: Basics and Applications
Proteomics analysis: Basics and Applications
 
Techniques in proteomics
Techniques in proteomicsTechniques in proteomics
Techniques in proteomics
 
2015 Upload Campaigns Calendar - SlideShare
2015 Upload Campaigns Calendar - SlideShare2015 Upload Campaigns Calendar - SlideShare
2015 Upload Campaigns Calendar - SlideShare
 
What to Upload to SlideShare
What to Upload to SlideShareWhat to Upload to SlideShare
What to Upload to SlideShare
 
Getting Started With SlideShare
Getting Started With SlideShareGetting Started With SlideShare
Getting Started With SlideShare
 

Similar to The physics of computational drug discovery

Energy Minimization Using Gromacs
Energy Minimization Using GromacsEnergy Minimization Using Gromacs
Energy Minimization Using Gromacs
Rajendra K Labala
 
Jacob Kleine undergrad. Thesis
Jacob Kleine undergrad. ThesisJacob Kleine undergrad. Thesis
Jacob Kleine undergrad. Thesis
Jacob Kleine
 
Quantative Structure-Activity Relationships (QSAR)
Quantative Structure-Activity Relationships (QSAR)Quantative Structure-Activity Relationships (QSAR)
Quantative Structure-Activity Relationships (QSAR)
Atai Rabby
 
SAIP2015 presentation_v5
SAIP2015 presentation_v5SAIP2015 presentation_v5
SAIP2015 presentation_v5
Thembelani Gina
 
A simplex nelder mead genetic algorithm for minimizing molecular potential en...
A simplex nelder mead genetic algorithm for minimizing molecular potential en...A simplex nelder mead genetic algorithm for minimizing molecular potential en...
A simplex nelder mead genetic algorithm for minimizing molecular potential en...
Aboul Ella Hassanien
 

Similar to The physics of computational drug discovery (20)

Energy Minimization Using Gromacs
Energy Minimization Using GromacsEnergy Minimization Using Gromacs
Energy Minimization Using Gromacs
 
Md simulation
Md simulationMd simulation
Md simulation
 
Docking
DockingDocking
Docking
 
Monte Carlo Simulations & Membrane Simulation and Dynamics
Monte Carlo Simulations & Membrane Simulation and DynamicsMonte Carlo Simulations & Membrane Simulation and Dynamics
Monte Carlo Simulations & Membrane Simulation and Dynamics
 
Jacob Kleine undergrad. Thesis
Jacob Kleine undergrad. ThesisJacob Kleine undergrad. Thesis
Jacob Kleine undergrad. Thesis
 
FINAL VERSION sss.pptx
FINAL VERSION sss.pptxFINAL VERSION sss.pptx
FINAL VERSION sss.pptx
 
An Improved Adaptive Multi-Objective Particle Swarm Optimization for Disassem...
An Improved Adaptive Multi-Objective Particle Swarm Optimization for Disassem...An Improved Adaptive Multi-Objective Particle Swarm Optimization for Disassem...
An Improved Adaptive Multi-Objective Particle Swarm Optimization for Disassem...
 
Kobeworkshop pubchemqc project
Kobeworkshop pubchemqc projectKobeworkshop pubchemqc project
Kobeworkshop pubchemqc project
 
Molecular maodeling and drug design
Molecular maodeling and drug designMolecular maodeling and drug design
Molecular maodeling and drug design
 
Bio Linux
Bio LinuxBio Linux
Bio Linux
 
Qsar
QsarQsar
Qsar
 
Quantative Structure-Activity Relationships (QSAR)
Quantative Structure-Activity Relationships (QSAR)Quantative Structure-Activity Relationships (QSAR)
Quantative Structure-Activity Relationships (QSAR)
 
SAIP2015 presentation_v5
SAIP2015 presentation_v5SAIP2015 presentation_v5
SAIP2015 presentation_v5
 
MastersThesis
MastersThesisMastersThesis
MastersThesis
 
A simplex nelder mead genetic algorithm for minimizing molecular potential en...
A simplex nelder mead genetic algorithm for minimizing molecular potential en...A simplex nelder mead genetic algorithm for minimizing molecular potential en...
A simplex nelder mead genetic algorithm for minimizing molecular potential en...
 
Molecular modelling
Molecular modelling Molecular modelling
Molecular modelling
 
The PubChemQC Project
The PubChemQC ProjectThe PubChemQC Project
The PubChemQC Project
 
LSSC2011 Optimization of intermolecular interaction potential energy paramete...
LSSC2011 Optimization of intermolecular interaction potential energy paramete...LSSC2011 Optimization of intermolecular interaction potential energy paramete...
LSSC2011 Optimization of intermolecular interaction potential energy paramete...
 
Short Presentation: Mohamed abuella's Research Highlights
Short Presentation: Mohamed abuella's Research HighlightsShort Presentation: Mohamed abuella's Research Highlights
Short Presentation: Mohamed abuella's Research Highlights
 
Evolutionary Symbolic Discovery for Bioinformatics, Systems and Synthetic Bi...
Evolutionary Symbolic Discovery for Bioinformatics,  Systems and Synthetic Bi...Evolutionary Symbolic Discovery for Bioinformatics,  Systems and Synthetic Bi...
Evolutionary Symbolic Discovery for Bioinformatics, Systems and Synthetic Bi...
 

Recently uploaded

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Victor Rentea
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
 

Recently uploaded (20)

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelMcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptx
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 

The physics of computational drug discovery

  • 1. - The Physics of Drug Discovery - Shourjya Sanyal
  • 2. Table of Content Topic No Of Slides Introduction To Drug 5 Designing Molecular Dynamics 5 (MD) Simulation Free Energy 5 Calculations Hands on Training : MD Simulation Setup 10 and Run
  • 8. MD Simulations Dynamics: calculating trajectories • Trajectory: positions as function of time: r i (t) • How does one determine r i (t) from Fi = mi . ai ? Fi = mi . Ai = mi . dvi /dti = mi . d2 ri /dti 2 • Simple case where acceleration is constant a = dv/dt v = at + vo
  • 9. MD Simulations Treatment of solvent • Implicit: The macromolecule interacts only with itself, but the electrostatic interactions are modified to account for the solvent • Explicit representation The macromolecule is surrounded by solvent molecules (water, ions) with which the macromolecule interacts. Specific nonbond interactions are calculated
  • 10. MD Simulations Periodic boundary conditions For explicit representation of solvent the boundaries of the system must be represented for periodic system. Permits the modeling of very large systems, but introduces a level of periodicity not present in nature.
  • 12. MD Simulations Timescale Limitations Molecular dynamics: Integration timestep - 1 fs, set by fastest varying force. Accessible timescale: about 10 nanoseconds.
  • 13. Free Energy Calculations Energy of binding ∆H must become more negative The energetic interactions between ligand and receptor have to become more favorable
  • 14. Free Energy Calculations The energy terms can be calculated according to force fields
  • 15. Free Energy Calculations Dispersive interactions: London forces and van der Waals
  • 17. Free Energy Calculations Energy Surface Exploration by Simulation..
  • 18. MD Simulation Setup Methods for Determining Atomic Structures NMR (nuclear magnetic resonance) : Absorption of electromagnetic waves
  • 19. MD Simulation Setup Obtaining X-Ray structures The arrangement of atoms in the crystal gives rise to a diffraction pattern.
  • 22. MD Simulation Setup Step One: Prepare the Protein Topology > For this tutorial, we will utilize T4 lysozyme L99A/M102Q (PDB code 3HTB). Go to the RCSB website and download the PDB text for the crystal structure. > Seperate out Ligand and Parent Molecule. grep JZ4 3HTB_clean.pdb > JZ4.pdb > Create Topology File for Molecule. pdb2gmx -f 3HTB_clean.pdb -o 3HTB_processed.gro -water spc
  • 23. MD Simulation Setup Step Two : Prepare the Ligand Topology For this tutorial, we will use PRODRG to generate a starting topology for our ligand, JZ4. Go to the PRODRG site and upload your JZ4.pdb file. The server presents you with several options for how to treat your ligand. > Include topology of ligand ; Include ligand topology #include "JZ4.itp"
  • 24. MD Simulation Setup Step Three : Solvate The System In Box Define the box editconf -f 3HTB_JZ4.gro -o 3HTB_JZ4_box.gro -bt cubic -d 1.0 Adding water ions to the box genbox -cp 3HTB_JZ4_box.gro -cs spc216.gro -p 3HTB_JZ4.top -o 3HTB_JZ4_boxwater.gro
  • 25. MD Simulation Setup Step Four : Energy Minimization Now that the system is assembled, create the binary input using grompp using this input parameter file: grompp -f enermin.mdp -c 3HTB_JZ4_boxwater.gro -p 3HTB_JZ4.top -o em.tpr We are now ready to invoke mdrun to carry out the EM: mdrun -v -deffnm em
  • 26. MD Simulation Setup Step Five : Analysis Energy Landscape g_energy -f em.edr -o tot.xvg Structural Analysis g_rama -f em.trr -s em.tpr -o myrama.xvg
  • 27. PRESENTATION DEVELOPMENT Shourjya Sanyal Academic : shourjya.sanyal@ucdconnect.ie Business : shourjya@thinkbiosolution.com
  • 28. Think Biosolution Pvt. Ltd. is a young startup aimed at providing low cost solutions to enterprise ranging from biotechnology to bio-medical instrumentation. We are a global team of young scientists and technocrats who aims to serve towards making a better future, by incorporating innovative technology within framework of current operations for a given corporation. It is our dream to accelerate technology growth and development towards building a better tomorrow I welcome you all to be a part of this dream. http://www.thinkbiosolution.com