M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER

Size: px
Start display at page:

Download "M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER"

Transcription

1 M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER CLASS : PGDCI SUBJECT :... PAPER : I- Basic of Chemoinformatics funsz'k %& 1- lhkh iz'u Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2- nksuksa l=h; iz'ui= gy djuk vfuok;z gsaa 3- l=h; dk;z mùkjiqflrdk ds vafre i`"b ij lacaf/kr fo"k; dh laiuu laidz d{kkvksa dh frffk;ksa,oa ijke'kznkrk ds uke,oa in dk vo'; myys[k djsaa 4- vafre frffk mijkar l=h; dk;z mùkjiqflrdkvksa dks eku; ugha djrs gq, ewy;kafdr ugha dh tkosxha 5- l=h; dk;z mùkjiqflrdk,a tek djus dh vafre frffk l=h; dk;z mùkjiqflrdk,a tek djus dh jlhn vo'; izkir dj ysaa vizsy 2010 gsa 7- nks l=h; dk;z izkirkadksa esa ls fdlh,d esa vf/kdre vad dh iwoz izpfyr O;oLFkk ds LFkku ij nksuksa l=h; dk;ksza ds izkirkadksa ds vkslr vad l=kar ijh{kk ifj.kke esa tksm+s tk,axsa lhkh iz'uksa ds vad leku gsaa First Assignment Max Marks - 30 Q.1 Explain in phase the integration and access. Or Discuss pharmacophore appearing. Q.2 Explain how is Medical Chemistry changing? Or Discuss the emergence of a discipline i.e.chemoinformatics. Q.3 Give traditional A& I services, embracing the future and leveraging the past. Or What are chemical information specialists actually do? Q.4 Give application of chemoinformatics with drug industry. Or How you will analyze and exploit the HTS data? Q.5 Explain Bio-Technology, Drug discovery and informatics. Or Explain the educational requirement in respect of chemoinformatics. Second Assignment Max Marks - 30

2 Q.1What are the Chemoinformatic techniques? Or What is docking referring physical the between a macromolecular target & a pharmaceuticals? Q.2 What was the situations in 1973, scientific millstones in predicting chemo informatics. Or Give milestones in the development of molecular modeling. Q.3 Give enzymes of A& C Services. Or Discuss complete generation & launching. Q.4 Explain combinational chemistry and chemoinformatics. Or Discuss rational drug discovery (Bio-Chemo informatics). Q.5 Explain revising gene annotations. Or Give prediction of drug and in vivo effects.

3 M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER CLASS : PGDCI SUBJECT :... PAPER : II- Medical Chemistry, receptor, Ligand interaction funsz'k %& 1- lhkh iz'u Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2- nksuksa l=h; iz'ui= gy djuk vfuok;z gsaa 3- l=h; dk;z mùkjiqflrdk ds vafre i`"b ij lacaf/kr fo"k; dh laiuu laidz d{kkvksa dh frffk;ksa,oa ijke'kznkrk ds uke,oa in dk vo'; myys[k djsaa 4- vafre frffk mijkar l=h; dk;z mùkjiqflrdkvksa dks eku; ugha djrs gq, ewy;kafdr ugha dh tkosxha 5- l=h; dk;z mùkjiqflrdk,a tek djus dh vafre frffk l=h; dk;z mùkjiqflrdk,a tek djus dh jlhn vo'; izkir dj ysaa vizsy 2010 gsa 7- nks l=h; dk;z izkirkadksa esa ls fdlh,d esa vf/kdre vad dh iwoz izpfyr O;oLFkk ds LFkku ij nksuksa l=h; dk;ksza ds izkirkadksa ds vkslr vad l=kar ijh{kk ifj.kke esa tksm+s tk,axsa lhkh iz'uksa ds vad leku gsaa First Assignment Max Marks - 30 Q.1 Discuss ligand based drug design method. Or Structural based virtual screening. Q.2 Give Pharmaco Kinetics in brief. Or Explain such types of antagonism. Q.3 What are abused drugs & their effects? Or Discuss antiinfective Antibiotic drugs. Q.4 Discuss the prospects in Medical Chemistry. Or What are the new places to look for Biodiversity? Q.5 Explain drug discovery process today. Or Discuss molecular approaches in drug discovery. Second Assignment Max Marks - 30 Q.1 Define ligand & receptor. Or Receptor discovery and characterization. Q.2 Give respiratory system drug therapy. Or What are natural sources of lead compounds? Q.3 Explain various aspects of anti-cancer therapy. Or What are challenges for new century for natural products?

4 Q.4 What are the drug discovery process today? Or Give ADME/PK as part of a rational approach drug discovery. Q.5 Explain extended therapeutic utility for ligands with affinities Or How is partition co-efficient in drug defined?

5 M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER CLASS : PGDCI SUBJECT :... PAPER : III- Modern Combinatorial Chemistry funsz'k %& 1- lhkh iz'u Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2- nksuksa l=h; iz'ui= gy djuk vfuok;z gsaa 3- l=h; dk;z mùkjiqflrdk ds vafre i`"b ij lacaf/kr fo"k; dh laiuu laidz d{kkvksa dh frffk;ksa,oa ijke'kznkrk ds uke,oa in dk vo'; myys[k djsaa 4- vafre frffk mijkar l=h; dk;z mùkjiqflrdkvksa dks eku; ugha djrs gq, ewy;kafdr ugha dh tkosxha 5- l=h; dk;z mùkjiqflrdk,a tek djus dh vafre frffk l=h; dk;z mùkjiqflrdk,a tek djus dh jlhn vo'; izkir dj ysaa vizsy 2010 gsa 7- nks l=h; dk;z izkirkadksa esa ls fdlh,d esa vf/kdre vad dh iwoz izpfyr O;oLFkk ds LFkku ij nksuksa l=h; dk;ksza ds izkirkadksa ds vkslr vad l=kar ijh{kk ifj.kke esa tksm+s tk,axsa lhkh iz'uksa ds vad leku gsaa First Assignment Max Marks - 30 Q.1 What are the synthesis principle of natural amino acids? Or Discuss spot synthesis of amino acids. Q.2 What are OBDC library methods (one bead one compound) (OBDC) library) Or Explain coupling chemistry in pharmeco kinetics. Q.3 What are phase derived intermediates? Or What are the challenges facing UHTH? Q.4 Name the new statistical methods. Or Give in order about the sited of metabolism. Q.5 Explain in short of the following (any two) (a) Liquid phase chemistry (b) Multiple parallel synthesis (c) Regent Efficiency (d) Solid-phase extraction Second Assignment Max Marks - 30 Q.1 Explain parallel synthesis on solid-phase. Or Give in short the identification of the active ligands.

6 Q.2 What are solid-phase supported regents. Or Explain in situ synthesis of peptides. Q.3 What are destructive techniques, give names? Or Explain in short solution & gel phase by MMR. Q.4 What are experimental model for coatings. Or Explain in short design based on natural products. Q.5 Explain in short any two of the following. a) Ladder synthesis c)re-synthesis b) Flourouse Synthesis d)phage display libraries

7 M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER CLASS : PGDCI SUBJECT :... PAPER : IV- Chimoinformatics Data base Design & Their Management funsz'k %& 1- lhkh iz'u Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2- nksuksa l=h; iz'ui= gy djuk vfuok;z gsaa 3- l=h; dk;z mùkjiqflrdk ds vafre i`"b ij lacaf/kr fo"k; dh laiuu laidz d{kkvksa dh frffk;ksa,oa ijke'kznkrk ds uke,oa in dk vo'; myys[k djsaa 4- vafre frffk mijkar l=h; dk;z mùkjiqflrdkvksa dks eku; ugha djrs gq, ewy;kafdr ugha dh tkosxha 5- l=h; dk;z mùkjiqflrdk,a tek djus dh vafre frffk l=h; dk;z mùkjiqflrdk,a tek djus dh jlhn vo'; izkir dj ysaa vizsy 2010 gsa 7- nks l=h; dk;z izkirkadksa esa ls fdlh,d esa vf/kdre vad dh iwoz izpfyr O;oLFkk ds LFkku ij nksuksa l=h; dk;ksza ds izkirkadksa ds vkslr vad l=kar ijh{kk ifj.kke esa tksm+s tk,axsa lhkh iz'uksa ds vad leku gsaa First Assignment Max Marks - 30 Q.1 Explain database management system. Or Give examples of data used in pharmaceutical industry. Q.2 What are different types of information rules. Or Explain set field properties of database. Q.3 What is customizing access of database? Or Explain fast and flexible chemistry Q.4 Explain SQL strength & weakness. Or What is nested SQL statements? Q.5 Give in short the following (any two) a) Digression on Map-ability. b) Array specifications c) Summary of basic techniques. d) failing database Chimoinformatics. Second Assignment Max Marks - 30 Q.1 What is database? Give its advantages. Or Give various types of database system.

8 Q.2 Explain database design examples. Or Give in short chemoinformatics database. Q.3 Describe in short the different normal forms. Or How will you setup a data base? Q.4 What is referential integrity, How you will use it? Q.5 Explain in short the followings (any two) a) Data definition communications. b) SQL's DML statements. c) Internet data structure. d) Any case study database design.

9 M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER CLASS : PGDCI SUBJECT :... PAPER : V- Chemical Information Sources funsz'k %& 1- lhkh iz'u Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2- nksuksa l=h; iz'ui= gy djuk vfuok;z gsaa 3- l=h; dk;z mùkjiqflrdk ds vafre i`"b ij lacaf/kr fo"k; dh laiuu laidz d{kkvksa dh frffk;ksa,oa ijke'kznkrk ds uke,oa in dk vo'; myys[k djsaa 4- vafre frffk mijkar l=h; dk;z mùkjiqflrdkvksa dks eku; ugha djrs gq, ewy;kafdr ugha dh tkosxha 5- l=h; dk;z mùkjiqflrdk,a tek djus dh vafre frffk l=h; dk;z mùkjiqflrdk,a tek djus dh jlhn vo'; izkir dj ysaa vizsy 2010 gsa 7- nks l=h; dk;z izkirkadksa esa ls fdlh,d esa vf/kdre vad dh iwoz izpfyr O;oLFkk ds LFkku ij nksuksa l=h; dk;ksza ds izkirkadksa ds vkslr vad l=kar ijh{kk ifj.kke esa tksm+s tk,axsa lhkh iz'uksa ds vad leku gsaa First Assignment Max Marks - 30 Q.1 Explain the future of the scientific internet. Or How you will distinguish scholarly journals from other periodicals. Q.2 What are the advantages of computer searching? Or Explain chemical safely & toxicology information. Q.3 Explain environmentally friendly analytical chemistry. Or Discuss the CIS: Chemical information system. Q.4 Discuss in short biographical information. Or Explain in short about access to patents. Q.5 What are the various sources by which you can get a detailed knowledge of a chemical world. Or What is trn news reader; How does it works? Second Assignment Max Marks - 30 Q.1 Discuss the importance of various types of publications. Or What is the purpose of searching chemical abstracts on line.

10 Q.2 What do you understand by primary literature, discuss any one of them? Or What are patents, their search & trade mark depository library? Q.3 What is visual molecular dynamics (VMD)? Or Give types of complex-readable sources. Q.4 How analytical chemistry is useful for obtaining informations? Or How the name reactions complications are solved? Q.1 What is the criteria of primary secondary and tertiary literature. Or What do you know about physical properties of organic solvent for database.

11 M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER CLASS : PGDCI SUBJECT :... PAPER : VII- Data Sequencing mining & Visualization funsz'k %& 1- lhkh iz'u Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2- nksuksa l=h; iz'ui= gy djuk vfuok;z gsaa 3- l=h; dk;z mùkjiqflrdk ds vafre i`"b ij lacaf/kr fo"k; dh laiuu laidz d{kkvksa dh frffk;ksa,oa ijke'kznkrk ds uke,oa in dk vo'; myys[k djsaa 4- vafre frffk mijkar l=h; dk;z mùkjiqflrdkvksa dks eku; ugha djrs gq, ewy;kafdr ugha dh tkosxha 5- l=h; dk;z mùkjiqflrdk,a tek djus dh vafre frffk l=h; dk;z mùkjiqflrdk,a tek djus dh jlhn vo'; izkir dj ysaa vizsy 2010 gsa 7- nks l=h; dk;z izkirkadksa esa ls fdlh,d esa vf/kdre vad dh iwoz izpfyr O;oLFkk ds LFkku ij nksuksa l=h; dk;ksza ds izkirkadksa ds vkslr vad l=kar ijh{kk ifj.kke esa tksm+s tk,axsa lhkh iz'uksa ds vad leku gsaa First Assignment Max Marks - 30 Q.1 What is data mining? Give suitable diagram and example? Or How will you select data mining products categories? Q.2 How data mining help in Biological data analysis? Or What is machine leaving? Q.3 Why is visualize a data mining model? OR What is CHILD, explain in short. Q.4 What are analytical technologies used in data mining? Or How is the space for clustering and nearest neighbor defined? Q.5 How can you compare different mining models using data visualization? Or Discuss the data mining software developments? Second Assignment Max Marks - 30 Q.1 Discuss predictive data mining and classification with terminology. Or Explain data mining process with examples. Q.2 How data mining works? Or Describe data mining architecture.

12 Q.3 What is Ontology understanding module? Or What are the characteristics of data? Q.4 What is decision tree for prediction? Or Write in short on data warehouse design for drug discovery. Q.5 What is difference between characterizing and near to neighbor prediction. Or Give current state of data mining software applications.

13 M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER CLASS : PGDCI SUBJECT :... PAPER : VIII- Drug Design and Discovery funsz'k %& 1- lhkh iz'u Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2- nksuksa l=h; iz'ui= gy djuk vfuok;z gsaa 3- l=h; dk;z mùkjiqflrdk ds vafre i`"b ij lacaf/kr fo"k; dh laiuu laidz d{kkvksa dh frffk;ksa,oa ijke'kznkrk ds uke,oa in dk vo'; myys[k djsaa 4- vafre frffk mijkar l=h; dk;z mùkjiqflrdkvksa dks eku; ugha djrs gq, ewy;kafdr ugha dh tkosxha 5- l=h; dk;z mùkjiqflrdk,a tek djus dh vafre frffk l=h; dk;z mùkjiqflrdk,a tek djus dh jlhn vo'; izkir dj ysaa vizsy 2010 gsa 7- nks l=h; dk;z izkirkadksa esa ls fdlh,d esa vf/kdre vad dh iwoz izpfyr O;oLFkk ds LFkku ij nksuksa l=h; dk;ksza ds izkirkadksa ds vkslr vad l=kar ijh{kk ifj.kke esa tksm+s tk,axsa lhkh iz'uksa ds vad leku gsaa First Assignment Max Marks - 30 Q.1 Describe database system for protein-ligand structures. Or Explain the evolution plays a role in deciphering protein functions. Q.2 What are the steps involved in docking? Or Discuss the role of computers in molecular modeling. Q.3 Explain phase-i & Phase-II metabolism of drugs. Or Discuss, How do hard drugs solve the problem of toxicity. Q.4 What are the physico-chemical texture that effect rate of absorption. Or Explain difference between genetics and pharmecogenetics. Q.5 How does virtual screening help drug design? Or What are rapid reversible inhibitors? Second Assignment Max Marks - 30 Q.1 Describe here a protein structure deciphers its function. Or What is the role of combination chemistry in drug design. Q.2 Distinguish between quantum mechanics and molecular mechanics. Or Write a note on enzyme induction & inhibition. P.T.O.

14 From Pre Page Q.3 What are soft drugs & how they function? Or Describe the role of solvent in ligand binding. Q.4 Explain the short coming of Lipinski's rule. Or What is proteomics and give its difference from genomics. Q.5 Define the term- (a) Pharmecophores (b) EST (C) SNP Or Write short note on Michaelis- menten equation.

M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER

M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER Paper - I - Quantum Mechanics Q.1 Explain Erhenfest theorem. (5) Q.2 Explain Fermi Golden rule. (5) Q.3 Discuss Wein - gorden equation & drive equation. (5) Q.4 Write a short note on Exchange degeneracy

More information

M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER

M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER CLASS : M.Sc. Final Year SUBJECT: Mathematics Paper - I - Integration theorey and Functional Analysis 1- lhkh iz- Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2- nksuksa l=h; iz-i= gy djuk vfuok;z gsa ds vkslr

More information

Assignment Question Paper I I

Assignment Question Paper I I 2012-13 Quantum Mechanics Max Marks - 30 Q.1 Explain Pauli's exclusion principle.. Q.2 Explain Fermi Golden rule. & Pauli's exclusion principle Q.3 Discuss Wein - gorden equation & drive equation. Q.4

More information

Principles of Drug Design

Principles of Drug Design Advanced Medicinal Chemistry II Principles of Drug Design Tentative Course Outline Instructors: Longqin Hu and John Kerrigan Direct questions and enquiries to the Course Coordinator: Longqin Hu I. Introduction

More information

Madhya Pradesh Bhoj (Open) University, Bhopal

Madhya Pradesh Bhoj (Open) University, Bhopal Subject- Cytology Genetics and Cytogenetics Maximum Marks: 30 5- l=h; dk;z tek djus dh vafre frffk 31 fnlecj 2012 gsa 6- l=h; dk;z mrrj iqflrdkvksa dks tek djus dh jlhn vo ; izkir dj ysaa Q. 1 Describe

More information

Receptor Based Drug Design (1)

Receptor Based Drug Design (1) Induced Fit Model For more than 100 years, the behaviour of enzymes had been explained by the "lock-and-key" mechanism developed by pioneering German chemist Emil Fischer. Fischer thought that the chemicals

More information

In silico pharmacology for drug discovery

In silico pharmacology for drug discovery In silico pharmacology for drug discovery In silico drug design In silico methods can contribute to drug targets identification through application of bionformatics tools. Currently, the application of

More information

Introduction to Chemoinformatics and Drug Discovery

Introduction to Chemoinformatics and Drug Discovery Introduction to Chemoinformatics and Drug Discovery Irene Kouskoumvekaki Associate Professor February 15 th, 2013 The Chemical Space There are atoms and space. Everything else is opinion. Democritus (ca.

More information

Chemoinformatics and information management. Peter Willett, University of Sheffield, UK

Chemoinformatics and information management. Peter Willett, University of Sheffield, UK Chemoinformatics and information management Peter Willett, University of Sheffield, UK verview What is chemoinformatics and why is it necessary Managing structural information Typical facilities in chemoinformatics

More information

Retrieving hits through in silico screening and expert assessment M. N. Drwal a,b and R. Griffith a

Retrieving hits through in silico screening and expert assessment M. N. Drwal a,b and R. Griffith a Retrieving hits through in silico screening and expert assessment M.. Drwal a,b and R. Griffith a a: School of Medical Sciences/Pharmacology, USW, Sydney, Australia b: Charité Berlin, Germany Abstract:

More information

JCICS Major Research Areas

JCICS Major Research Areas JCICS Major Research Areas Chemical Information Text Searching Structure and Substructure Searching Databases Patents George W.A. Milne C571 Lecture Fall 2002 1 JCICS Major Research Areas Chemical Computation

More information

October 6 University Faculty of pharmacy Computer Aided Drug Design Unit

October 6 University Faculty of pharmacy Computer Aided Drug Design Unit October 6 University Faculty of pharmacy Computer Aided Drug Design Unit CADD@O6U.edu.eg CADD Computer-Aided Drug Design Unit The development of new drugs is no longer a process of trial and error or strokes

More information

Structural biology and drug design: An overview

Structural biology and drug design: An overview Structural biology and drug design: An overview livier Taboureau Assitant professor Chemoinformatics group-cbs-dtu otab@cbs.dtu.dk Drug discovery Drug and drug design A drug is a key molecule involved

More information

Bachelor of Science (B.Sc) Final Year ( )

Bachelor of Science (B.Sc) Final Year ( ) Subject -- BOTANY Maximum Marks: 30 ------------------------------------------------------------------------------------------------------------------------------------------------ ---------------------------------------------------------------------------------------------------------------------------------------------

More information

Early Stages of Drug Discovery in the Pharmaceutical Industry

Early Stages of Drug Discovery in the Pharmaceutical Industry Early Stages of Drug Discovery in the Pharmaceutical Industry Daniel Seeliger / Jan Kriegl, Discovery Research, Boehringer Ingelheim September 29, 2016 Historical Drug Discovery From Accidential Discovery

More information

Principles of Drug Design

Principles of Drug Design (16:663:502) Instructors: Longqin Hu and John Kerrigan Direct questions and enquiries to the Course Coordinator: Longqin Hu For more current information, please check WebCT at https://webct.rutgers.edu

More information

Cheminformatics Role in Pharmaceutical Industry. Randal Chen Ph.D. Abbott Laboratories Aug. 23, 2004 ACS

Cheminformatics Role in Pharmaceutical Industry. Randal Chen Ph.D. Abbott Laboratories Aug. 23, 2004 ACS Cheminformatics Role in Pharmaceutical Industry Randal Chen Ph.D. Abbott Laboratories Aug. 23, 2004 ACS Agenda The big picture for pharmaceutical industry Current technological/scientific issues Types

More information

xf.kr MATHEMATICS Ñi;k tk p dj ysa fd bl iz'u&i= esa eqfnzr iz'u 20 gsaa Please make sure that the printed question paper are contains 20 questions.

xf.kr MATHEMATICS Ñi;k tk p dj ysa fd bl iz'u&i= esa eqfnzr iz'u 20 gsaa Please make sure that the printed question paper are contains 20 questions. CLASS : th (Sr. Secondary) Code No. 6 Series : SS-M/08 Roll No. SET : C f.kr MATHEMATICS [ Hindi and English Medium ] ACADEMIC/OPEN (Only for Fresh/Re-appear Candidates) Time allowed : hours ] [ Maimum

More information

Next Generation Computational Chemistry Tools to Predict Toxicity of CWAs

Next Generation Computational Chemistry Tools to Predict Toxicity of CWAs Next Generation Computational Chemistry Tools to Predict Toxicity of CWAs William (Bill) Welsh welshwj@umdnj.edu Prospective Funding by DTRA/JSTO-CBD CBIS Conference 1 A State-wide, Regional and National

More information

FRAUNHOFER IME SCREENINGPORT

FRAUNHOFER IME SCREENINGPORT FRAUNHOFER IME SCREENINGPORT Design of screening projects General remarks Introduction Screening is done to identify new chemical substances against molecular mechanisms of a disease It is a question of

More information

In Silico Investigation of Off-Target Effects

In Silico Investigation of Off-Target Effects PHARMA & LIFE SCIENCES WHITEPAPER In Silico Investigation of Off-Target Effects STREAMLINING IN SILICO PROFILING In silico techniques require exhaustive data and sophisticated, well-structured informatics

More information

Contents 1 Open-Source Tools, Techniques, and Data in Chemoinformatics

Contents 1 Open-Source Tools, Techniques, and Data in Chemoinformatics Contents 1 Open-Source Tools, Techniques, and Data in Chemoinformatics... 1 1.1 Chemoinformatics... 2 1.1.1 Open-Source Tools... 2 1.1.2 Introduction to Programming Languages... 3 1.2 Chemical Structure

More information

M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER

M P BHOJ (OPEN) UNIVERSITY, BHOPAL ASSIGNMENT QUESTION PAPER CLASS : B.Sc. First Year SUBJECT : Botany PAPER : I & II 1- lhkh iz'u Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2- nksuksa l=h; iz'ui= gy djuk vfuok;z gsa ds vkslr vad l=kar ijh{kk ifj.kke esa tksm+s tk,axsa

More information

Plan. Lecture: What is Chemoinformatics and Drug Design? Description of Support Vector Machine (SVM) and its used in Chemoinformatics.

Plan. Lecture: What is Chemoinformatics and Drug Design? Description of Support Vector Machine (SVM) and its used in Chemoinformatics. Plan Lecture: What is Chemoinformatics and Drug Design? Description of Support Vector Machine (SVM) and its used in Chemoinformatics. Exercise: Example and exercise with herg potassium channel: Use of

More information

Cross Discipline Analysis made possible with Data Pipelining. J.R. Tozer SciTegic

Cross Discipline Analysis made possible with Data Pipelining. J.R. Tozer SciTegic Cross Discipline Analysis made possible with Data Pipelining J.R. Tozer SciTegic System Genesis Pipelining tool created to automate data processing in cheminformatics Modular system built with generic

More information

Data Mining in the Chemical Industry. Overview of presentation

Data Mining in the Chemical Industry. Overview of presentation Data Mining in the Chemical Industry Glenn J. Myatt, Ph.D. Partner, Myatt & Johnson, Inc. glenn.myatt@gmail.com verview of presentation verview of the chemical industry Example of the pharmaceutical industry

More information

Plan. Day 2: Exercise on MHC molecules.

Plan. Day 2: Exercise on MHC molecules. Plan Day 1: What is Chemoinformatics and Drug Design? Methods and Algorithms used in Chemoinformatics including SVM. Cross validation and sequence encoding Example and exercise with herg potassium channel:

More information

Bioinformatics 2. Yeast two hybrid. Proteomics. Proteomics

Bioinformatics 2. Yeast two hybrid. Proteomics. Proteomics GENOME Bioinformatics 2 Proteomics protein-gene PROTEOME protein-protein METABOLISM Slide from http://www.nd.edu/~networks/ Citrate Cycle Bio-chemical reactions What is it? Proteomics Reveal protein Protein

More information

MSc Drug Design. Module Structure: (15 credits each) Lectures and Tutorials Assessment: 50% coursework, 50% unseen examination.

MSc Drug Design. Module Structure: (15 credits each) Lectures and Tutorials Assessment: 50% coursework, 50% unseen examination. Module Structure: (15 credits each) Lectures and Assessment: 50% coursework, 50% unseen examination. Module Title Module 1: Bioinformatics and structural biology as applied to drug design MEDC0075 In the

More information

Ñi;k iz'u dk mùkj fy[kuk 'kq: djus ls igys] iz'u dk Øekad vo'; fy[ksaa

Ñi;k iz'u dk mùkj fy[kuk 'kq: djus ls igys] iz'u dk Øekad vo'; fy[ksaa CLASS : 10th (Secondary) Code No. 3525 Series : Sec. M/2018 Roll No. AUTOMOBILE National Skills Qualification Framework (NSQF) Level 2 [ Hindi and English Medium ] (Only for Fresh/Re-appear Candidates)

More information

CH MEDICINAL CHEMISTRY

CH MEDICINAL CHEMISTRY CH 458 - MEDICINAL CHEMISTRY SPRING 2011 M: 5:15pm-8 pm Sci-1-089 Prerequisite: Organic Chemistry II (Chem 254 or Chem 252, or equivalent transfer course) Instructor: Dr. Bela Torok Room S-1-132, Science

More information

Introduction. OntoChem

Introduction. OntoChem Introduction ntochem Providing drug discovery knowledge & small molecules... Supporting the task of medicinal chemistry Allows selecting best possible small molecule starting point From target to leads

More information

Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining

Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining Samer Haidar 1, Zouhair Bouaziz 2, Christelle Marminon 2, Tiomo Laitinen 3, Anti Poso

More information

Using AutoDock for Virtual Screening

Using AutoDock for Virtual Screening Using AutoDock for Virtual Screening CUHK Croucher ASI Workshop 2011 Stefano Forli, PhD Prof. Arthur J. Olson, Ph.D Molecular Graphics Lab Screening and Virtual Screening The ultimate tool for identifying

More information

An Integrated Approach to in-silico

An Integrated Approach to in-silico An Integrated Approach to in-silico Screening Joseph L. Durant Jr., Douglas. R. Henry, Maurizio Bronzetti, and David. A. Evans MDL Information Systems, Inc. 14600 Catalina St., San Leandro, CA 94577 Goals

More information

Bioinformatics. Dept. of Computational Biology & Bioinformatics

Bioinformatics. Dept. of Computational Biology & Bioinformatics Bioinformatics Dept. of Computational Biology & Bioinformatics 3 Bioinformatics - play with sequences & structures Dept. of Computational Biology & Bioinformatics 4 ORGANIZATION OF LIFE ROLE OF BIOINFORMATICS

More information

Computational Chemistry in Drug Design. Xavier Fradera Barcelona, 17/4/2007

Computational Chemistry in Drug Design. Xavier Fradera Barcelona, 17/4/2007 Computational Chemistry in Drug Design Xavier Fradera Barcelona, 17/4/2007 verview Introduction and background Drug Design Cycle Computational methods Chemoinformatics Ligand Based Methods Structure Based

More information

FACULTY OF PHARMACY. M. Pharmacy I Semester (Suppl.) Examination, November 2015 (Common To All) Subject: Pharmaceutical Analytical Techniques

FACULTY OF PHARMACY. M. Pharmacy I Semester (Suppl.) Examination, November 2015 (Common To All) Subject: Pharmaceutical Analytical Techniques M. Pharmacy I Semester (Suppl.) Examination, November 2015 (Common To All) Subject: Pharmaceutical Analytical Techniques Code No. 6001 / S 1 a) Describe the instrumentation and applications of UV-visible

More information

Molecular modeling methods for novel health and environmental applications

Molecular modeling methods for novel health and environmental applications Molecular modeling methods for novel health and environmental applications ALIVE axis 16/08/2018 1 Novel Molecular Modeling Approaches > Model-based computational methods are an essential complement to

More information

Ignasi Belda, PhD CEO. HPC Advisory Council Spain Conference 2015

Ignasi Belda, PhD CEO. HPC Advisory Council Spain Conference 2015 Ignasi Belda, PhD CEO HPC Advisory Council Spain Conference 2015 Business lines Molecular Modeling Services We carry out computational chemistry projects using our selfdeveloped and third party technologies

More information

Advanced Medicinal Chemistry SLIDES B

Advanced Medicinal Chemistry SLIDES B Advanced Medicinal Chemistry Filippo Minutolo CFU 3 (21 hours) SLIDES B Drug likeness - ADME two contradictory physico-chemical parameters to balance: 1) aqueous solubility 2) lipid membrane permeability

More information

Madhya Pradesh Bhoj (Open) University, Bhopal B.Sc. Final Year

Madhya Pradesh Bhoj (Open) University, Bhopal B.Sc. Final Year B.Sc. Final Year -2018-19 Subject: Mathematics Maximum Marks: 30 ----------------- funsz'k%& 1 & lhkh iz'u Lo;a dh glrfyfi esa gy djuk vfuok;z gsa 2 & fo'ofo ky; }kjk iznk; l=h; mrrj iqflrdkvksa esa gy

More information

Machine learning for ligand-based virtual screening and chemogenomics!

Machine learning for ligand-based virtual screening and chemogenomics! Machine learning for ligand-based virtual screening and chemogenomics! Jean-Philippe Vert Institut Curie - INSERM U900 - Mines ParisTech In silico discovery of molecular probes and drug-like compounds:

More information

Virtual affinity fingerprints in drug discovery: The Drug Profile Matching method

Virtual affinity fingerprints in drug discovery: The Drug Profile Matching method Ágnes Peragovics Virtual affinity fingerprints in drug discovery: The Drug Profile Matching method PhD Theses Supervisor: András Málnási-Csizmadia DSc. Associate Professor Structural Biochemistry Doctoral

More information

Reaxys Medicinal Chemistry Fact Sheet

Reaxys Medicinal Chemistry Fact Sheet R&D SOLUTIONS FOR PHARMA & LIFE SCIENCES Reaxys Medicinal Chemistry Fact Sheet Essential data for lead identification and optimization Reaxys Medicinal Chemistry empowers early discovery in drug development

More information

ENZYME KINETICS. Medical Biochemistry, Lecture 24

ENZYME KINETICS. Medical Biochemistry, Lecture 24 ENZYME KINETICS Medical Biochemistry, Lecture 24 Lecture 24, Outline Michaelis-Menten kinetics Interpretations and uses of the Michaelis- Menten equation Enzyme inhibitors: types and kinetics Enzyme Kinetics

More information

Drug Informatics for Chemical Genomics...

Drug Informatics for Chemical Genomics... Drug Informatics for Chemical Genomics... An Overview First Annual ChemGen IGERT Retreat Sept 2005 Drug Informatics for Chemical Genomics... p. Topics ChemGen Informatics The ChemMine Project Library Comparison

More information

PROVIDING CHEMINFORMATICS SOLUTIONS TO SUPPORT DRUG DISCOVERY DECISIONS

PROVIDING CHEMINFORMATICS SOLUTIONS TO SUPPORT DRUG DISCOVERY DECISIONS 179 Molecular Informatics: Confronting Complexity, May 13 th - 16 th 2002, Bozen, Italy PROVIDING CHEMINFORMATICS SOLUTIONS TO SUPPORT DRUG DISCOVERY DECISIONS CARLETON R. SAGE, KEVIN R. HOLME, NIANISH

More information

Quantitative structure activity relationship and drug design: A Review

Quantitative structure activity relationship and drug design: A Review International Journal of Research in Biosciences Vol. 5 Issue 4, pp. (1-5), October 2016 Available online at http://www.ijrbs.in ISSN 2319-2844 Research Paper Quantitative structure activity relationship

More information

Syllabus BINF Computational Biology Core Course

Syllabus BINF Computational Biology Core Course Course Description Syllabus BINF 701-702 Computational Biology Core Course BINF 701/702 is the Computational Biology core course developed at the KU Center for Computational Biology. The course is designed

More information

COMBINATORIAL CHEMISTRY: CURRENT APPROACH

COMBINATORIAL CHEMISTRY: CURRENT APPROACH COMBINATORIAL CHEMISTRY: CURRENT APPROACH Dwivedi A. 1, Sitoke A. 2, Joshi V. 3, Akhtar A.K. 4* and Chaturvedi M. 1, NRI Institute of Pharmaceutical Sciences, Bhopal, M.P.-India 2, SRM College of Pharmacy,

More information

Proteomics. Yeast two hybrid. Proteomics - PAGE techniques. Data obtained. What is it?

Proteomics. Yeast two hybrid. Proteomics - PAGE techniques. Data obtained. What is it? Proteomics What is it? Reveal protein interactions Protein profiling in a sample Yeast two hybrid screening High throughput 2D PAGE Automatic analysis of 2D Page Yeast two hybrid Use two mating strains

More information

MDL Databases. Solutions At Every Stage in the R&D Process. MDL Databases. Information Systems, Inc.

MDL Databases. Solutions At Every Stage in the R&D Process. MDL Databases. Information Systems, Inc. MDL Databases Solutions At Every Stage in the R&D Process MDL Databases Information Systems, Inc. Solutions At Every Stage in the R&D Process MDL Databases Many of the problems scientists encounter during

More information

SUMMATIVE ASSESSMENT I, 2014

SUMMATIVE ASSESSMENT I, 2014 SUMMATIVE ASSESSMENT I (0) SUMMATIVE ASSESSMENT I, 04 MATHEMATICS Lakdfyr ijh{kk CLASS &I - IX MATHEMATICS / f.kr Class IX / & IX 4600 Time allowed: 3 hours Maimum Marks: 90 fu/kkzfjr le; % 3?k.Vs vf/kdre

More information

Madhya Pradesh Bhoj (Open) University, Bhopal Bachelor of Science (B.Sc) First Year ( )

Madhya Pradesh Bhoj (Open) University, Bhopal Bachelor of Science (B.Sc) First Year ( ) Subject -- BOTANY Maximum Marks: 30 ------------------------------------------------------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------------------------------------------------

More information

Structural Bioinformatics (C3210) Molecular Docking

Structural Bioinformatics (C3210) Molecular Docking Structural Bioinformatics (C3210) Molecular Docking Molecular Recognition, Molecular Docking Molecular recognition is the ability of biomolecules to recognize other biomolecules and selectively interact

More information

xf.kr MATHEMATICS Ñi;k tk p dj ysa fd bl iz'u&i= esa eqfnzr iz'u 20 gsaa Please make sure that the printed question paper are contains 20 questions.

xf.kr MATHEMATICS Ñi;k tk p dj ysa fd bl iz'u&i= esa eqfnzr iz'u 20 gsaa Please make sure that the printed question paper are contains 20 questions. CLASS : th (Sr. Secondary) Code No. 0 Series : SS-M/07 Roll No. SET : A f.kr MATHEMATICS [ Hindi and English Medium ] ACADEMIC/OPEN (Only for Fresh Candidates) (Evening Session) Time allowed : hours ]

More information

CHEMISTRY (CHE) CHE 104 General Descriptive Chemistry II 3

CHEMISTRY (CHE) CHE 104 General Descriptive Chemistry II 3 Chemistry (CHE) 1 CHEMISTRY (CHE) CHE 101 Introductory Chemistry 3 Survey of fundamentals of measurement, molecular structure, reactivity, and organic chemistry; applications to textiles, environmental,

More information

Dr. Sander B. Nabuurs. Computational Drug Discovery group Center for Molecular and Biomolecular Informatics Radboud University Medical Centre

Dr. Sander B. Nabuurs. Computational Drug Discovery group Center for Molecular and Biomolecular Informatics Radboud University Medical Centre Dr. Sander B. Nabuurs Computational Drug Discovery group Center for Molecular and Biomolecular Informatics Radboud University Medical Centre The road to new drugs. How to find new hits? High Throughput

More information

Product Guide. Thermo Scientific Cellomics HCS Solution

Product Guide. Thermo Scientific Cellomics HCS Solution Product Guide Thermo Scientific Cellomics HCS Solution Thermo Scientific Cellomics HCS Solution Your Complete HCS Solution The search for new therapies for human diseases is increasingly driven by the

More information

The Changing Requirements for Informatics Systems During the Growth of a Collaborative Drug Discovery Service Company. Sally Rose BioFocus plc

The Changing Requirements for Informatics Systems During the Growth of a Collaborative Drug Discovery Service Company. Sally Rose BioFocus plc The Changing Requirements for Informatics Systems During the Growth of a Collaborative Drug Discovery Service Company Sally Rose BioFocus plc Overview History of BioFocus and acquisition of CDD Biological

More information

Chemogenomic: Approaches to Rational Drug Design. Jonas Skjødt Møller

Chemogenomic: Approaches to Rational Drug Design. Jonas Skjødt Møller Chemogenomic: Approaches to Rational Drug Design Jonas Skjødt Møller Chemogenomic Chemistry Biology Chemical biology Medical chemistry Chemical genetics Chemoinformatics Bioinformatics Chemoproteomics

More information

Everyday NMR. Innovation with Integrity. Why infer when you can be sure? NMR

Everyday NMR. Innovation with Integrity. Why infer when you can be sure? NMR Everyday NMR Why infer when you can be sure? Innovation with Integrity NMR Only NMR gives you definitive answers, on your terms. Over the past half-century, scientists have used nuclear magnetic resonance

More information

Computational chemical biology to address non-traditional drug targets. John Karanicolas

Computational chemical biology to address non-traditional drug targets. John Karanicolas Computational chemical biology to address non-traditional drug targets John Karanicolas Our computational toolbox Structure-based approaches Ligand-based approaches Detailed MD simulations 2D fingerprints

More information

SUMMATIVE ASSESSMENT I (2011) Lakdfyr ijh{kk &I. MATHEMATICS / xf.kr Class IX / & IX

SUMMATIVE ASSESSMENT I (2011) Lakdfyr ijh{kk &I. MATHEMATICS / xf.kr Class IX / & IX SUMMATIVE ASSESSMENT I (0) Lakdfyr ijh{kk &I MATHEMATICS / xf.kr Class IX / & IX 46005 Time allowed: hours Maximum Marks: 90 fu/kkzfjr le; %?k.vs vf/kdre vad % 90 General Instructions: All questions are

More information

CHEMISTRY (CHEM) CHEM 5800 Principles Of Materials Chemistry. Tutorial in selected topics in materials chemistry. S/U grading only.

CHEMISTRY (CHEM) CHEM 5800 Principles Of Materials Chemistry. Tutorial in selected topics in materials chemistry. S/U grading only. Chemistry (CHEM) 1 CHEMISTRY (CHEM) CHEM 5100 Principles of Organic and Inorganic Chemistry Study of coordination compounds with a focus on ligand bonding, electron counting, molecular orbital theory,

More information

Structure-Based Drug Discovery An Overview

Structure-Based Drug Discovery An Overview Structure-Based Drug Discovery An Overview Edited by Roderick E. Hubbard University of York, Heslington, York, UK and Vernalis (R&D) Ltd, Abington, Cambridge, UK RSC Publishing Contents Chapter 1 3D Structure

More information

SUMMATIVE ASSESSMENT I (0) Lakdfyr ijh{kk &I MATHEMATICS / f.kr Class IX / & IX 46007 Time allowed: 3 hours Maimum Marks: 90 fu/kkzfjr le; % 3?k.Vs vf/kdre vad % 90 General Instructions: (i) All questions

More information

2009 (Odd) xzqi&a ds lhkh 20 ç'uksa ds mùkj nsaa ¼izR;sd ds 1 vad gsaa½

2009 (Odd) xzqi&a ds lhkh 20 ç'uksa ds mùkj nsaa ¼izR;sd ds 1 vad gsaa½ 009 (Odd) Time : Hrs. Full Marks : 80 Pass Marks : 6 SemI-G Engg. Math.-I GROUP-A.(A) Write down the most correct answer for the following question from four given alternatives : = Answer all 0 questions

More information

SUMMATIVE ASSESSMENT I (2011) Lakdfyr ijh{kk &I. MATHEMATICS / xf.kr Class IX / & IX

SUMMATIVE ASSESSMENT I (2011) Lakdfyr ijh{kk &I. MATHEMATICS / xf.kr Class IX / & IX SUMMATIVE ASSESSMENT I (011) Lakdfyr ijh{kk &I MATHEMATICS / xf.kr Class IX / & IX 46003 Time allowed: 3 hours Maximum Marks: 90 fu/kkzfjr le; % 3?k.Vs vf/kdre vad % 90 General Instructions: (i) All questions

More information

Integrated Cheminformatics to Guide Drug Discovery

Integrated Cheminformatics to Guide Drug Discovery Integrated Cheminformatics to Guide Drug Discovery Matthew Segall, Ed Champness, Peter Hunt, Tamsin Mansley CINF Drug Discovery Cheminformatics Approaches August 23 rd 2017 Optibrium, StarDrop, Auto-Modeller,

More information

Chemical Space. Space, Diversity, and Synthesis. Jeremy Henle, 4/23/2013

Chemical Space. Space, Diversity, and Synthesis. Jeremy Henle, 4/23/2013 Chemical Space Space, Diversity, and Synthesis Jeremy Henle, 4/23/2013 Computational Modeling Chemical Space As a diversity construct Outline Quantifying Diversity Diversity Oriented Synthesis Wolf and

More information

COMPARISON OF SIMILARITY METHOD TO IMPROVE RETRIEVAL PERFORMANCE FOR CHEMICAL DATA

COMPARISON OF SIMILARITY METHOD TO IMPROVE RETRIEVAL PERFORMANCE FOR CHEMICAL DATA http://www.ftsm.ukm.my/apjitm Asia-Pacific Journal of Information Technology and Multimedia Jurnal Teknologi Maklumat dan Multimedia Asia-Pasifik Vol. 7 No. 1, June 2018: 91-98 e-issn: 2289-2192 COMPARISON

More information

Computational methods for predicting protein-protein interactions

Computational methods for predicting protein-protein interactions Computational methods for predicting protein-protein interactions Tomi Peltola T-61.6070 Special course in bioinformatics I 3.4.2008 Outline Biological background Protein-protein interactions Computational

More information

Virtual Screening: How Are We Doing?

Virtual Screening: How Are We Doing? Virtual Screening: How Are We Doing? Mark E. Snow, James Dunbar, Lakshmi Narasimhan, Jack A. Bikker, Dan Ortwine, Christopher Whitehead, Yiannis Kaznessis, Dave Moreland, Christine Humblet Pfizer Global

More information

Virtual Libraries and Virtual Screening in Drug Discovery Processes using KNIME

Virtual Libraries and Virtual Screening in Drug Discovery Processes using KNIME Virtual Libraries and Virtual Screening in Drug Discovery Processes using KNIME Iván Solt Solutions for Cheminformatics Drug Discovery Strategies for known targets High-Throughput Screening (HTS) Cells

More information

Evidence for the Existence of Non-monotonic Dose-response: Does it or Doesn t it?

Evidence for the Existence of Non-monotonic Dose-response: Does it or Doesn t it? Evidence for the Existence of Non-monotonic Dose-response: Does it or Doesn t it? Scott M. Belcher, PhD University of Cincinnati Department of Pharmacology and Cell Biophysics Evidence for the Existence

More information

EMPIRICAL VS. RATIONAL METHODS OF DISCOVERING NEW DRUGS

EMPIRICAL VS. RATIONAL METHODS OF DISCOVERING NEW DRUGS EMPIRICAL VS. RATIONAL METHODS OF DISCOVERING NEW DRUGS PETER GUND Pharmacopeia Inc., CN 5350 Princeton, NJ 08543, USA pgund@pharmacop.com Empirical and theoretical approaches to drug discovery have often

More information

Priority Setting of Endocrine Disruptors Using QSARs

Priority Setting of Endocrine Disruptors Using QSARs Priority Setting of Endocrine Disruptors Using QSARs Weida Tong Manager of Computational Science Group, Logicon ROW Sciences, FDA s National Center for Toxicological Research (NCTR), U.S.A. Thanks for

More information

LigandScout. Automated Structure-Based Pharmacophore Model Generation. Gerhard Wolber* and Thierry Langer

LigandScout. Automated Structure-Based Pharmacophore Model Generation. Gerhard Wolber* and Thierry Langer LigandScout Automated Structure-Based Pharmacophore Model Generation Gerhard Wolber* and Thierry Langer * E-Mail: wolber@inteligand.com Pharmacophores from LigandScout Pharmacophores & the Protein Data

More information

Madhya Pradesh Bhoj Open University Bhopal CLASS-M.Sc. Zoology Final YEAR

Madhya Pradesh Bhoj Open University Bhopal CLASS-M.Sc. Zoology Final YEAR SUBJECT: COMPARATIVE ANATOMY OF VERTIBRATES MAXIMUM MARKS:30 Q.1 Describe the inter-relationship of Uro chords and cephalochordates and their relationship with other deuterostomes. Q.2 Describe origin,

More information

Simplifying Drug Discovery with JMP

Simplifying Drug Discovery with JMP Simplifying Drug Discovery with JMP John A. Wass, Ph.D. Quantum Cat Consultants, Lake Forest, IL Cele Abad-Zapatero, Ph.D. Adjunct Professor, Center for Pharmaceutical Biotechnology, University of Illinois

More information

Biologically Relevant Molecular Comparisons. Mark Mackey

Biologically Relevant Molecular Comparisons. Mark Mackey Biologically Relevant Molecular Comparisons Mark Mackey Agenda > Cresset Technology > Cresset Products > FieldStere > FieldScreen > FieldAlign > FieldTemplater > Cresset and Knime About Cresset > Specialist

More information

BEFORE TAKING THIS MODULE YOU MUST ( TAKE BIO-4013Y OR TAKE BIO-

BEFORE TAKING THIS MODULE YOU MUST ( TAKE BIO-4013Y OR TAKE BIO- 2018/9 - BIO-4001A BIODIVERSITY Autumn Semester, Level 4 module (Maximum 150 Students) Organiser: Dr Harriet Jones Timetable Slot:DD This module explores life on Earth. You will be introduced to the major

More information

PDB : 1ZTB Ligand : ZINC

PDB : 1ZTB Ligand : ZINC PDB : 1ZTB Ligand : ZINC00367031 Pantothenate biosynthesis Enzymes with invariant peptides : Pantothenate kinase (CoaA), Pantothenate Synthetase (PanC) Methyltransferase (PanB) Pathway3 Pathway2 E4 X X

More information

QSAR Modeling of ErbB1 Inhibitors Using Genetic Algorithm-Based Regression

QSAR Modeling of ErbB1 Inhibitors Using Genetic Algorithm-Based Regression APPLICATION NOTE QSAR Modeling of ErbB1 Inhibitors Using Genetic Algorithm-Based Regression GAINING EFFICIENCY IN QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS ErbB1 kinase is the cell-surface receptor

More information

Current Literature. Development of Highly Potent and Selective Steroidal Inhibitors and Degraders of CDK8

Current Literature. Development of Highly Potent and Selective Steroidal Inhibitors and Degraders of CDK8 Current Literature Development of ighly Potent and Selective Steroidal Inhibitors and Degraders of CDK8 ACS Med. Chem. Lett. 2018, ASAP Rational Drug Development simplification Cortistatin A 16-30 steps;

More information

Topology based deep learning for biomolecular data

Topology based deep learning for biomolecular data Topology based deep learning for biomolecular data Guowei Wei Departments of Mathematics Michigan State University http://www.math.msu.edu/~wei American Institute of Mathematics July 23-28, 2017 Grant

More information

DATA ANALYTICS IN NANOMATERIALS DISCOVERY

DATA ANALYTICS IN NANOMATERIALS DISCOVERY DATA ANALYTICS IN NANOMATERIALS DISCOVERY Michael Fernandez OCE-Postdoctoral Fellow September 2016 www.data61.csiro.au Materials Discovery Process Materials Genome Project Integrating computational methods

More information

SUMMATIVE ASSESSMENT I (2011) Lakdfyr ijh{kk &I. MATHEMATICS / xf.kr Class IX / & IX

SUMMATIVE ASSESSMENT I (2011) Lakdfyr ijh{kk &I. MATHEMATICS / xf.kr Class IX / & IX SUMMATIVE ASSESSMENT I (2011) Lakdfyr ijh{kk &I MATHEMATICS / xf.kr Class IX / & IX 460021 Time allowed: 3 hours Maximum Marks: 90 fu/kkzfjr le; % 3?k.Vs vf/kdre vad % 90 General Instructions: (i) All

More information

CHEMISTRY (CHEM) CHEM 208. Introduction to Chemical Analysis II - SL

CHEMISTRY (CHEM) CHEM 208. Introduction to Chemical Analysis II - SL Chemistry (CHEM) 1 CHEMISTRY (CHEM) CHEM 100. Elements of General Chemistry Prerequisite(s): Completion of general education requirement in mathematics recommended. Description: The basic concepts of general

More information

CSCE555 Bioinformatics. Protein Function Annotation

CSCE555 Bioinformatics. Protein Function Annotation CSCE555 Bioinformatics Protein Function Annotation Why we need to do function annotation? Fig from: Network-based prediction of protein function. Molecular Systems Biology 3:88. 2007 What s function? The

More information

MEDLINE Clinical Laboratory Sciences Journals

MEDLINE Clinical Laboratory Sciences Journals Source Type Publication Name ISSN Peer-Reviewed Academic Journal Acta Biochimica et Biophysica Sinica 1672-9145 Y Academic Journal Acta Physiologica 1748-1708 Y Academic Journal Aging Cell 1474-9718 Y

More information

SUMMATIVE ASSESSMENT I (0) Lakdfyr ijh{kk &I MATHEMATICS / xf.kr Class IX / & IX 46000 Time allowed: 3 hours Maximum Marks: 90 fu/kkzfjr le; % 3?k.Vs vf/kdre vad % 90 General Instructions: (i) All questions

More information

Chemical properties that affect binding of enzyme-inhibiting drugs to enzymes

Chemical properties that affect binding of enzyme-inhibiting drugs to enzymes Chemical properties that affect binding of enzyme-inhibiting drugs to enzymes Introduction The production of new drugs requires time for development and testing, and can result in large prohibitive costs

More information

Introduction to Computational Structural Biology

Introduction to Computational Structural Biology Introduction to Computational Structural Biology Part I 1. Introduction The disciplinary character of Computational Structural Biology The mathematical background required and the topics covered Bibliography

More information

FUNDAMENTALS of SYSTEMS BIOLOGY From Synthetic Circuits to Whole-cell Models

FUNDAMENTALS of SYSTEMS BIOLOGY From Synthetic Circuits to Whole-cell Models FUNDAMENTALS of SYSTEMS BIOLOGY From Synthetic Circuits to Whole-cell Models Markus W. Covert Stanford University 0 CRC Press Taylor & Francis Group Boca Raton London New York Contents /... Preface, xi

More information

Targeting protein-protein interactions: A hot topic in drug discovery

Targeting protein-protein interactions: A hot topic in drug discovery Michal Kamenicky; Maria Bräuer; Katrin Volk; Kamil Ödner; Christian Klein; Norbert Müller Targeting protein-protein interactions: A hot topic in drug discovery 104 Biomedizin Innovativ patientinnenfokussierte,

More information

Lecture 27. Transition States and Enzyme Catalysis

Lecture 27. Transition States and Enzyme Catalysis Lecture 27 Transition States and Enzyme Catalysis Reading for Today: Chapter 15 sections B and C Chapter 16 next two lectures 4/8/16 1 Pop Question 9 Binding data for your thesis protein (YTP), binding

More information

RATIONAL DRUG DESIGN

RATIONAL DRUG DESIGN RATIOAL DRUG DESIG Drug Design & Discovery: Introduction Drugs: Targets: atural sources Synthetic sources Ideal Drug 1) target: bio-molecule,involved in signaling or metabolic pathways, that are specific

More information