From owner-chemistry@ccl.net Sun May 8 10:56:00 2011 From: "Rodolfo Gomez rgbccl/./gmail.com" To: CCL Subject: CCL: chemoinformatics Message-Id: <-44585-110508013238-7088-WS5oSwDEm5oVnQ30WBzhUw++server.ccl.net> X-Original-From: Rodolfo Gomez Content-Type: multipart/alternative; boundary=000e0cd1469669c38304a2bd0b82 Date: Sun, 8 May 2011 00:32:10 -0500 MIME-Version: 1.0 Sent to CCL by: Rodolfo Gomez [rgbccl*gmail.com] --000e0cd1469669c38304a2bd0b82 Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable Dear CCLrs, Recently my faculty is considering to offer an undergraduate course on Chemoinformatics, for chemistry students. Though I=B4ve been working a bit = on computational chemistry, I do not feel I have the proper vision to built up a syllabus proposal, or even for giving a reasonable criticism of anyone else proposal. I would really appreciate your opinion on what should be included in a course of such a level? Thanks in advance for your kind reply. Rodolfo G=F3mez --000e0cd1469669c38304a2bd0b82 Content-Type: text/html; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable
Dear CCLrs,
=A0
Recently my faculty is considering to offer an undergraduate course on= Chemoinformatics, for chemistry students. Though I=B4ve been working a bit= on computational chemistry, I do not feel I have the proper vision=A0to bu= ilt up a syllabus proposal, or even=A0for giving a reasonable=A0criticism o= f anyone else proposal.
=A0
I would really appreciate your opinion on what=A0should be included in= a course of such a level?
=A0
Thanks in advance for your kind reply.
=A0
Rodolfo G=F3mez
--000e0cd1469669c38304a2bd0b82-- From owner-chemistry@ccl.net Sun May 8 11:31:00 2011 From: "Ben Webb ben*o*salilab.org" To: CCL Subject: CCL: Program language in Quantum Chemistry: C++ or FORTRAN? Message-Id: <-44586-110507235107-10687-43h8eXmuNQNdqi/yCtRj2g^-^server.ccl.net> X-Original-From: Ben Webb Content-Transfer-Encoding: 7bit Content-Type: text/plain; charset=ISO-8859-1; format=flowed Date: Sat, 07 May 2011 20:50:55 -0700 MIME-Version: 1.0 Sent to CCL by: Ben Webb [ben^_^salilab.org] On 5/7/11 3:20 AM, Michel Petitjean petitjean.chiral!=!gmail.com wrote: > 2011/5/7 uekstrom[a]gmail.com uekstrom[a]gmail.com: >> Also, since the Fortran market is >> so small the C++ compilers are much less buggy, > > Is there data to support that ? > I would be delighted to know about bugs for actual fortran compilers. One data point for you: MODELLER (http://salilab.org/modeller/) is a Fortran 95 application which we build with ifort. We still build this with version 10.1.022 on Linux and 10.1.017 on 32-bit Mac, since no release of the compiler since then has been able to both compile the application and result in a binary which passes our test suite (there has never been an ifort release which will successfully build MODELLER on 64-bit Mac, so we have to rely on slower gfortran builds). (Yes, we have bug reports open with Intel.) Until comparatively recently gfortran would not compile the code correctly either. We haven't used the NAG or Absoft compilers for a while, but when we did a few years ago we certainly had to disable optimization when compiling some modules to work around internal compiler errors. That said, we have occasionally run into MSVC bugs and the odd g++ bug with C++ code, so I'd be reluctant to say that one language's compilers are "less buggy" than the other. Ben -- ben],[salilab.org http://salilab.org/~ben/ "It is a capital mistake to theorize before one has data." - Sir Arthur Conan Doyle From owner-chemistry@ccl.net Sun May 8 12:06:00 2011 From: "Frank Neese neese-,-thch.uni-bonn.de" To: CCL Subject: CCL: Program language in Quantum Chemistry: C++ or FORTRAN? Message-Id: <-44587-110508101010-1010-BkHH/lMjD7Z4aERGWsahEg,,server.ccl.net> X-Original-From: Frank Neese Content-Type: multipart/signed; boundary=Apple-Mail-1-112157959; protocol="application/pkcs7-signature"; micalg=sha1 Date: Sun, 8 May 2011 08:41:12 +0200 Mime-Version: 1.0 (Apple Message framework v1084) Sent to CCL by: Frank Neese [neese=thch.uni-bonn.de] --Apple-Mail-1-112157959 Content-Transfer-Encoding: quoted-printable Content-Type: text/plain; charset=us-ascii Maybe a few words from a developper of a large code:=20 when i started the ORCA program in the late 90s we decided to use C++ = because i felt that it would be much=20 easier to keep the code well structured and organized in manageable = pieces.=20 Now, 10-15 years later i find this to be true (the program has well over = a million lines of code now). And i still pretend=20 that the program is relatively easy to read and extend. At least, no = student who entered the group has ever needed more than a few weeks (1-2) before being able to productively contribute to = the program.=20 Please, I am not saying that it is not possible to write a well = structured big program in Frontran but i do think that it is much easier in C++. Of course, = modern Fortran has all these extensions but they don't mix well with existing quantum chemistry programs and i don't feel that = they are much used.Maybe i am wrong, but whenever i see a Fortran based quantum chemistry code, they seem to dominantly be = very traditional Fortran 77 style codes. It is the unity of code and data that i find particularly attractive = with object oriented programing. In my own experience, this is the most important feature - being easily able to define complex = data structures together with the code that works on them. I don't feel that virtual functions have a high potential = in quantum chemistry as these programs are not event oriented. It would also be a performance killer in any time = critical program part.=20 Concerning performance - in our experience it is very well possible to = have C++ perform as good or better than any Fortran. Maybe one has to help the compiler a bit, but by and large this seems to = be argument from that past that is no longer valid. Many efficient algorithms rely on matrix multiplications = anyways and then it is just a matter of the available BLAS library. Of the time critical steps, it is mainly integral code that = needs to be compiled in a way that performs well.=20 The rest is more or less a matter of organizational convenience. Present = day multicore machines also appear to be rather limited by=20 memory bandwidth than by floating point performance.=20 Concerning the whole argument with 1-based arrays - i don't get that. = What is the virtue of having arrays start at 1 other than=20 that some people got used to it. After a short while one is just used to = zero based arrays and there is no problem.=20 When you call a BLAS routine you don't see it anyways. Really, it is a = non-issue in my opinion.=20 I can say from experience that we had hardore developpers from other = Fortran based quantum chemistry codes entering the group with a strong aversion against C/C++. And after learning the = language and starting to develop they all agreed that it is much more convenient to use the ORCA C++ infrastructure compared = to the Fortran codes they were used to. Please don't take that the wrong way - i have the highest respect for all = developpers of other codes and i don't want to say that=20 everybody should switch to C/C++. I am just reporting experience.=20 Concerning compilers our experiences are mixed. C++ compilers are so = complex that it is not unusual to find that they are buggy. Very often when a new computer architecture comes = up, the compiler producers need threee or four=20 updates before it generates correct code on the highest optimization = level. Years of experience with Intel compilers has been=20 particularly frustrating in this respect. The consistently most reliable = has been the gnu compiler, which, however, one has to work a bit harder to make it produces highly efficient code.=20 Concerning external libraries, i have very mixed feelings. They come and = go and are sometimes platform dependent. Our choice has been to rigorously minimize the depence on external code and = platform dependence.=20 The little that is unavoidable (BLAS, MPI, a little Lapack) is being = connected via wrappers tha don't depend on the=20 external programs calling conventions (that are maybe subject to = change). The reward is that the program compiles out of the box on any platform = that has a reasonable C++ compiler. Although this is a=20 maximally conservative strategy, we found this empirically to be a wise = choice if your goal is to produce a code that is being able to grow for decades and still stay maintainable. I don't mean to take = away anything from the developpers of wonderful libraries. it is just a question how much i can rely on that these things are = around in, say, 10 years from now when computer platforms have yet again drastically changed and the developpers of the library have = lost interest or opportunity.=20 For the same reason i am maximally reluctant to write hardware specific = code. Too many ingenious ideas and their associated programs have died in quantum chemistry with = the computers that they were bound to.=20 I don't know if these thoughts are useful to anybody. I just thought = would share them. 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<-44588-110508122139-16228-UD4WOf3lUC3XjU5Y/GXvvA#,#server.ccl.net> X-Original-From: jaleel uc Content-Type: multipart/alternative; boundary=0003255579766491f404a2c61d11 Date: Sun, 8 May 2011 21:51:27 +0530 MIME-Version: 1.0 Sent to CCL by: jaleel uc [jaleel.uc^^^gmail.com] --0003255579766491f404a2c61d11 Content-Type: text/plain; charset=windows-1252 Content-Transfer-Encoding: quoted-printable *d*ear all following syllabus can be used as a starting point jaleel * * * * * * *Paper-I Basics of Cheminformatics* *UNIT I - Basic Mathematics and Statistics * Graph theory and molecular numerology; Logic, sets and functions; Algorithms, integers and matrices; Mathematical reasoning, induction and recursion; Counting; graphs, trees and sets, basic probability and statistics; Markov processes *UNIT II - Foundations of Chemistry and Biology* Basic Stereochemistry, Group Theory, Amino acids and Proteins and Properties; pKa, pH and ionization of acids and bases; Protein structure - Primary structure, Secondary structure - helix & sheet; Tertiary structure; Quaternary structure; covalent and non-covalent forces that maintain structures. Physical properties of proteins - charge, size, hydrophobic, protein binding =96 structural aspects; antibodies; transport; nucleotide binding; catalytic enzymes; basic concepts of combinatorial chemistry. Introduction to drug action, pro drug design and applications *UNIT III - Chemical information sources* History of scientific information communication-chemical literature-chemical information-chemical information search-chemical information sources-chemical name and formula searching-analytical chemistry-chemical history-biography-directories and industry sources *UNIT IV - Bioinformatics * Introduction; Experimental sources of biological data; Publicly available databases; Gene expression monitoring; Genomics and Proteomics; Metabolomics; Visualisation of sequence data; Visualization of structures using Rasmol or SPDB Viewer or CHIME; Genetic basis of disease; Personalised medicine and gene-based diagnostics; Legal, ethical and commercial ramifications of bioinformatics *UNIT V - Pharmaceutical applications of molecular modeling * Introduction to drugs, structure-based drug design. QSAR and 3D-QSAR Methods. Pharmacophore Design, Ligand-Based Design and *De Novo* Drug Design Virtual sreening/docking of ligands. Protein structure. Drug action enzymes. Drug action receptors. Drug design target interaction. Prediction of Binding Modes, Protein=96ligand binding free energies, Fragment-Based Drug Design; Absorption, Distribution, Metabolism, Excretion & Toxicology (ADMET) prediction; Calculation of Physico-Chemical Properties, Biological and Physico-Chemical Predictive Model Building * * * * *PAPER II Computer Programming and NETWORKING FOR CHEMINFORMATICS* *UNIT-I* Operating systems =96 Human interface, Algorithms-genetic algorithms- neural networks- Artificial intelligence, Grid & high-performance computing, Software, Open source*. Document mark up languages:* HTML,XHTML, *XML:* Key terminology, Characters and escaping,Well-formedness and error-handling, Schemas and validation Related specifications, Use on the Internet, Programming interfaces, *Chemical Markup Language* *UNIT II* =96 *Basics of C & C++* : Basic Syntax - Variables, Constants an= d Built-in Types - Operators and Basic Expressions - Flow Control and Statement Blocks - Functions and Arguments - Modules and Scope =96 Arrays - Character Strings =96 Pointers - Defining New Types - Classes and Objects = =96 Casts =96 Preprocessor The Programming Process - Writing Source Code *UNIT III* - *JAVA Programming* -Introduction to Java - *JavaScript for Cheminformatics: *Basic Syntax - Variables, Constants and Built-in Types - Operators and Basic Expressions - Flow Control and Statement Blocks - Functions and Arguments - Modules and Scope =96 Arrays - Character Strings =96 Pointers - Defining New Types - Classes and Objects =96 Casts =96 Preprocessor The Programming Process - Writing Source Code *UNIT IV - Programming in PERL and PYTHON* :* PERL:* Introduction, Basic operators and control structures, Scalars, Lists, Hashes, File Manipulation, Pattern Matching and Regular Expressions, Subroutines, Text and string Processing *Python Programming: *Overview-Data structures-control flow-modules-basic I/O, Exception Handling, Regular expressions, File manipulation, classes, standard library *UNIT V* - *Computer networking*: Introduction *Network classification:* Connection method- Scale- Functional relationship (network architecture)-Network topology *Types of networks:* Personal area network-Local area network-Campus area network- Metropolitan area network-Wide area network- Global area network- Virtual private network *Internetwork:* Intranet- Extranet-Internet* Basic hardware components:* Network interface cards, Repeaters, Hubs,Bridges,Switches, Routers * * * * *Paper =96III CHEMINFORMATICS DATABASE design and their management* *UNIT I* - *Database Concepts*: Relational Databases-Object Databases-Basic SQL- Data types- Operators *Advanced Queries:* Joins, Built-in Functions, Improving Query Performance, Group by,Stored Procedures *Views, Catalogs and Integrity:* Creating tables- Verifying Integrity- Creating Views- Database Catalog E-R Model and Normalization - Entity and entity sets; Relations and relationship sets; E-R diagrams; Reducing E-R Diagrams to tables; *Security, Backup and Recovery:* Creating users- Encrypting traffic- Backup of the database- Recovery *Popular Databases and differences:* Oracle- SQL Server- DB2 *Unit II* - *Network Data Model*: Basic concepts; Hierarchical Data Model: Basic Concepts; Multimedia Databases - Basic Concepts and Applications; Indexing and Hashing; Basic concepts (ISAM, B+ Tree indexed files, B Tree indexed files, Static Hash functions, Dynamic Hash functions); Text Databases; Introduction to Distributed Database Processing, Data Security. Interfacing programs with databases; Data interoperability using XML. *UNIT III - Database Design:* Introduction to Schema Refinement- Functional Dependencies-Normal Forms-First , Second, Third, Boyce code, Fourth and Fifth Normal forms- Multivalued Dependencies. *UNIT IV - chemical databases* Introduction-chemical databases- types- chemical database design-Bio Catalysis Database. The MOS Database, reaction databases, The Failed Reaction Database. Protecting groups database-solid-phase synthesis database- Sequence Databases, Spectra. Databases, (Bio) Activity/Prop. Databases, Toxicology Databases. *Unit** V - High Throughput Data Processing and Data Mining* Introduction; Data visualization, Non-linear mapping Data mining methods, Substructural analysis, Discriminant Analysis, Neural networks, Decision Trees; Software for Chemical Data Mining. Data Mining and human genome. Combinatorial Chemistry Technologies and Libraries. Chemistry Libraries: Design of Focused, Diverse and Thematic Libraries. Biological Libraries, Bio planning, Peptide Display Libraries design and construction. * * *Paper IV - Computational chemistry* *UNIT I -* Introduction to computational chemistry -*Force fields and molecular representations of matter Intramolecular* (bonding) interactions-Non-bonded interactions -Hydrogen bonds-Constraints and Restraints-United atom and other coarse-grained approaches-Non-pairwise interactions*Methods for Simulating Large systems*:*Non-bonded Cutoffs *Shi= fted potential and shifted force-Switching functions-Neighbor lists*Boundaries -*Periodic Boundary conditions-Stochastic forces at spherical boundary*Long-range interactions -*The Ewald Sum-The Reaction field method *UNIT II -* *Energy Minimization and related analysis techniques* Steepest descent-Conjugate gradient-Newton-Raphson-Comparison of methods-Advanced techniques: Simulated Annealing, Branch-and-bound, simplex-What's the big deal about the minimum anyway? *Free Energy* :Perturbation methods,Thermodynamic integration *UNIT III - Introduction to Equilibrium Statistical Mechanics *Phase space, ergodicity, and Liouville's theorem-Ensemble theory, thermodynamic averages -Statistical mechanics of fluids *Monte Carlo -*MC integration and Markov chains:The Metropolis method,Biased MC *Molecular Dynamics *Classical mechanics: equations of motion,Finite Difference methods :Verlet algorithm,Velocity verlet,The Time step: practical issues,Multiple time-ste= p algorithms-Constraint Dynamics :Fundamental concepts ,SHAKE and RATTLE *Brownian dynamics and the Langevin Equation* *UNIT IV - Temperature:* Maxwell-Boltzmann distribution of velocities *Temperature control* Velocity scaling,Andersen's method,Nose-Hoover dynamics *Calculati= ng properties from MD trajectories, Hybrid MC* *UNIT V - Chemometrics -Introduction- Origins-Techniques : *Multivariate calibration,Classification, pattern recognition, clustering,Multivariate Curve resolution,Other Techniques*, Commercial Softwares* * * *References:* * * *Paper-V STRUCTURAL BIOLOGY* *UNIT I - *Introduction to protein structure: Physical and chemical properties of amino acids and polypeptides. Conformational properties of proteins, Ramachandarn Plot, Secondary, Super Secondary, tertiary and quaternary structure of proteins. *UNIT II - Functional classification of proteins: *Cell surface receptors, GPCR=92s, Kinases, Channel proteins, Ubiquitin *UNIT III - Biophysical Techniques: *Principles, Process and Applications of Thin layer chromatography, Column chromatography ( ion exchange and affinity only) , HPLC, *UNIT IV - *x-ray generation ; its application; unit cell and x-ray ,anomalous scattering; lattices, Bragg=92s Law; atomic scattering factor an= d structure factor; phase problem; intensity data collection and reduction; *UNIT V - *Isolation and purification of protein (chromatography, electrophoresis), crystallization (sitting and hanging drop method). Protei= n structure determination-molecular replacement technique; multiple isomorphous replacement method, synchrotron radiation and its uses; multi wavelength anomalous diffraction method. Calculation of electron density map, interpretation of electron density map. Refinement of the structure. Structure validation methods. * * * * * * *Paper-VI Molecular modeling techniques* *UNIT I: Introduction to Molecular Modelling* Introduction to Molecular Modelling. What are models used for? Areas of application =96 Single molecule calculation, assemblies of molecules. Reaction of the molecules. Drawbacks of mechanical models as compared to graphical models. Co-ordinate systems two = =96 matrix, potential energy surface. *UNIT II =96 Quantum Mechanics* Postulates of quantum mechanics, electronic structure calculations, ab initio, semi-empirical and density functional theory calculations, molecular size versus accuracy. Approximate molecular orbital theories. *UNIT III =96 Comparative protein modeling* Modelling by Homology-the alignment, construction of frame work, selecting variable regions, side chain placement and refinement, validation of protein models =96Ramchandran plot, threading and ab initio modeling. *PAPER VII - PHARMACEUTICAL CHEMISTRY* *UNIT I - Molecular basis of drug action: Receptor*: Drug Receptor Interaction: Basic ligand concept, agonist, antagonist, partial agonist, inverse agonist, receptor Theories - Occupancy, Rate & Activation Theories, receptor Binding Assays, determination of B-max and Kd by transforming data with Hill plot and Scatchered plot., above concepts with special reference to Opioid , Histaminergic , Adrenergic and GABA nergic receptors.* Enzyme Inhibition* =96 Enzyme, enzyme Kinetics, enzyme Inhibitors - reversible, irreversible, Kcat inhibitors.Transition state analogs, enzyme Inhibitors a= s drugs - ACE, leukotrienes,Lipoxygenase, Cycloxygenase, Aromatase, Xanthine oxidase, DNA PolymeraseInhibitors, HIV - Protease / Reverse Transcriptase, Integrase and Cytochrome P-450 Inhibitors. *Drug binding to nucleic acid* -= - Antimalarial, anti-cancer, antiviral.. *UNIT II- Synthon approach:* Definition of terms - disconnection, synthon, functional group interconversion (FGI), Basic rules in Disconnection, Use of synthon approac= h in synthesis of compounds: Trimethoprim, erfenadine, lbuprofen, Propanolol, Fentanyl,Ciprofloxacin, Cimetidine, Piroxicam,osiglitazone, Diclofenac, Captopryl, Nifedipine, Losartan. *UNIT III- Combinatorial Chemistry* Introduction, combinatorial approaches, chemical Peptide and small molecule libraries, applications, methodology, combinatorial organic synthesis, assays and screening of combinatorial libraries, i6ntroduction to High Throughputs Screening (HTS) *UNIT IV- Nanochemistry* Physical chemistry related to nanoparticles such as colloids and clusters: different equilibrium structures, quantum effects, conductivity and enhance= d catalytic activity compared to the same materials in the macroscopic state.Exploitation of self-assembly and self-organization to design functional structures in 1D, 2D or 3D structures.Role of polymers in lithography resists, as well as self-organization of more complicated polymer architectures such as block copolymers and polymer brushes. * Nanomaterials*: (Nanoparticles, nanoclusters, quantum dots synthesis): Top-down techniques: photolithography, other optical lithography (EUV, X-Ray, LIL), particle-beam lithographies (e-beam, FIB, shadow mask evaporation), probe lithographies, Bottom-up techniques: self-assembly, self-assembled monolayers, directed assembly, layer-by-layer assembly. Pattern replication techniques: soft lithography, nano imprint lithography. Pattern transfer and enhancement techniques: dry etching, wet etching, pattern growth techniques *UNIT V - Microwave synthesis- *fundamentals of microwave synthesis- Microw= aves Are Energy- Microwaves Can Interact with Matter- Two Principal Mechanisms for Interaction With Matter- *Microwave Heating Differs from Conventional Means: *Conventional Heating Methods- Microwave Heating - The Microwave Effect with examples - Single-Mode and Multimode Microwave Cavities * * *Paper-VIII ANALOG and stucture based drug designing* *UNIT I -* Drug discovery-Strategies and historical developments - Introduction =96conventional strategies to drug discovery-molecular mimetic= - first and second generation rational approach-Rational drug design-assessment of drug activity- future prospects-examples of successful applications of CAD *UNIT II -* Basic principle of drug design: Introduction-old QSAR-Use of physiochemical descriptors-use of electronic descriptors-use of molecular descriptors-Use of thermodynamic descriptors-use of receptor descriptors-success and limitations of old QSAR *UNIT III Analog based drug design** * *Developing and using QSAR*- Introduction-classical QSA-Freem and Wilson=92= s method-topliss method-use of statistical methods in QSAR-validation methods-3D QSAR approach-QSAR descriptors*3D QSAR-*Introduction-Pharmacore identification-binding site modeling of unknown receptor-receptor mapping-structural alignment and superposition-molecular field analysis (MFA) *Unit iv ** Structure based drug design* 3D pharmacophores, De novo Ligand design-introduction-approaches to de novo drug design problem-some current methods for de novo design.3D data base searching and virtual screening,. Sources of data, molecular similarity and similarity searching, prediction of binding energy of ligand-receptor complex-Free energies and salvation-electrostatic and non-electrostatic contribution to free energies combinatorial libraries =96 generation and utility, *UNIT V- Molecular docking: Introduction* *Docking approaches: *Shape complementarity- Simulation* Mechanics of docking - *Search algorithm-Scoring function-*Applications* * * * * * * * * * * *PRACTICAL I Computer programming and RDBMS * * C++, JAVA, CML, Perl, Perl Mol, Python, Visual Basic, ORACLE * *PRACTICAL II* *Chemical databases - *ChemBank-ChemBioFinder =96 CSChemoffice - ZINC *Molecular dynamics - *GROMACS- NAMD-VEGA ZZ* * *Structural chemistry - *NWChem =96GAMESS *Docking - *Autodock, DOCK -VEGA- FlexX JALEEL MCC On Sun, May 8, 2011 at 11:02 AM, Rodolfo Gomez rgbccl/./gmail.com < owner-chemistry]![ccl.net> wrote: > Dear CCLrs, > > Recently my faculty is considering to offer an undergraduate course on > Chemoinformatics, for chemistry students. Though I=B4ve been working a bi= t on > computational chemistry, I do not feel I have the proper vision to built = up > a syllabus proposal, or even for giving a reasonable criticism of anyone > else proposal. > > I would really appreciate your opinion on what should be included in a > course of such a level? > > Thanks in advance for your kind reply. > > Rodolfo G=F3mez > --=20 Dr UCA JALEEL Asst Professor in cheminformatics UGC AIDED Centre for cheminformatics MCC calicut phone --0003255579766491f404a2c61d11 Content-Type: text/html; charset=windows-1252 Content-Transfer-Encoding: quoted-printable

dear=A0 all


following syllabus=A0 can be used as a starting point

jaleel





Paper-I=A0=A0 Basics of Cheminformatics

UNIT I - Basic Mathematics =
and Statistics=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0 
Graph theory and molecular num=
erology; Logic, sets and functions; Algorithms, integers and matrice=
s; Mathematical reasoning, induction and recursion; Counting; graphs, trees and sets, basic probability and statist=
ics; Markov processes
UNIT II - Foundations of Ch=
emistry and Biology
Basic Stereochemistry, Group Theory, Amino acids and Prote=
ins and Properties; pKa, pH and ionization of acids and bases; Protein stru=
cture - Primary structure, Secondary structure - helix & sheet; Tertiar=
y structure; Quaternary structure; covalent and non-covalent forces that ma=
intain structures. Physical properties of proteins - charge, size, hydropho=
bic, protein binding =96 structural aspects; antibodies; transport; nucleot=
ide binding; catalytic enzymes; basic concepts of combinatorial chemistry. =
Introduction to drug action, pro drug design and applications
UNIT III - Chemical information sources
History of scientific information communication-chemical l=
iterature-chemical information-chemical information search-chemical informa=
tion sources-chemical name and formula searching-analytical chemistry-chemi=
cal history-biography-directories and industry sources
UNIT IV - Bioinformatics
Introduction; Experimental sources of = biological data; Publicly available databases; Gene expression monitoring; = Genomics and Proteomics; Metabolomics; Visualisation of sequence data; Visu= alization of structures using Rasmol or SPDB Viewer or CHIME;=A0=A0 Genetic basis of disease; Personalised medicine and gene-b= ased diagnostics; Legal, ethical and commercial ramifications of bioinforma= tics 
UNIT V - Pharmaceutical applications of molecular model=
ing 
Introduction to drugs, structure-based drug design. QSAR a=
nd 3D-QSAR Methods. Pharmacophore Design, Ligand-Based Design and De Nov=
o Drug Design Virtual sreening/docking of ligands. Protein structure. D=
rug action enzymes. Drug action receptors. Drug design target interaction. =
Prediction of Binding Modes, Protein=96ligand binding free energies, Fragme=
nt-Based Drug Design; Absorption, Distribution, Metabolism, Excretion &=
 Toxicology (ADMET) prediction; Calculation of Physico-Chemical Properties,=
 Biological and Physico-Chemical Predictive Model Building
=A0
=A0
PAPER II Computer Programmin=
g and NETWORKING FOR CHEMINFORMATICS
UNIT-I Operating systems =96 Human interface, Algorithms-genetic algori=
thms- neural networks- Artificial intelligence, Grid & high-performance=
 computing, Software, Open source. Document mark up languages=
: HTML,XHTML, XML: =A0Key ter=
minology, Characters and escaping,Well-formedness and error-handling, Schem=
as and validation Related specifications, Use on the Internet, Programming =
interfaces, Chemi=
cal Markup Language

UNIT II =96 Basics of C & C++ :=A0 Basic Syntax - Variables, Constan= ts and Built-in Types - Operators and Basic Expressions - Flow Control and Statement Blocks - Funct= ions and Arguments - Modules and Scope =96 Arrays - Character Strings =96 Pointe= rs - Defining New Types - Classes and Objects =96 Casts =96 Preprocessor The Pro= gramming Process - Writing Source Code

UNIT III - JAVA Programming -Introduction to Java - <=
/span>JavaScript for =A0Cheminformatics: Basic Syntax - Variables, Constants and Built-in Types - Operators and B=
asic Expressions - Flow Control and Statement Blocks - Functions and Argume=
nts - Modules and Scope =96 Arrays - Character Strings =96 Pointers - Defin=
ing New Types - Classes and Objects =96 Casts =96 Preprocessor The Programm=
ing Process - Writing Source Code 
UNIT IV - Programming in PERL and PYTHON : PERL: =A0Introduction, Basic operators and control structures=
, Scalars, Lists, Hashes, File Manipulation, Pattern Matching and Regular E=
xpressions, Subroutines, Text and string Processing Python Pr=
ogramming: Overview-Data structures-control flow-modules-basic I/O, Exc=
eption Handling, Regular expressions, File manipulation, classes, standard =
library 
UNIT V - Computer networking: Introduction =A0Network classification: Connection metho=
d-=A0 Scale- Functional relationship (network archi=
tecture)-Network topology Types of networks: Personal are=
a network-Local area network-Campus area network- Metropolitan area network=
-Wide area network- Global area network- Virtual private network Internetwork: Intranet- Extranet-Internet Basic har=
dware components: Network interface cards, Repeaters, Hubs,Bridges,Swit=
ches, Routers
=A0

=A0

Paper =96III CHEMINFORMATICS DATA= BASE design and their management

UNIT I - Database Concepts: Relational Databases-Obje=
ct Databases-Basic SQL- Data types-=A0 Operators Advanced Queries: Joins, Built-in Functions, Improving Quer=
y Performance, Group by,Stored Procedures Views, Catalogs and=
 Integrity: Creating tables- Verifying Integrity- Creating Views- Datab=
ase Catalog E-R Model and Normalization - Entity and entity sets; Relations=
 and relationship sets; E-R diagrams; Reducing E-R Diagrams to tables; Security, Backup and Recovery: Creating users- Encrypting tra=
ffic- Backup of the database- Recovery
Popular Databases and differences: Oracle- SQL Server- DB2
Unit II - Network Data Model: Basic concepts; Hierarc=
hical Data Model: Basic Concepts; Multimedia Databases - Basic Concepts and=
 Applications; Indexing and Hashing; Basic concepts (ISAM, B+ Tree indexed =
files, B Tree indexed files, Static Hash functions, Dynamic Hash functions)=
; Text Databases; Introduction to Distributed Database Processing, Data Sec=
urity.=A0=A0 Interfacing programs with databases; D=
ata interoperability using XML. 
UNIT III - Database Design: Introduction to Schema Refinement- Function=
al Dependencies-Normal Forms-First , Second, Third, Boyce code, Fourth and =
Fifth Normal forms- Multivalued Dependencies.
=A0
UNIT IV - chemical datab=
ases
Introduction-chemical databases- type=
s- chemical database design-Bio Catalysis Database. The MOS Database, react=
ion databases, The Failed Reaction Database. Protecting groups database-sol=
id-phase synthesis database- Sequence Databases, Spectra. Databases, (Bio) =
Activity/Prop. Databases, Toxicology Databases.
Unit V - High=
 Throughput Data Processing and Data Mining
Introduction; Data visualization, Non-linear mapping
Data mining methods, Substructural analysis, Discriminant =
Analysis, Neural networks, Decision Trees; Software for Chemical Data Minin=
g. Data Mining and human genome.
Combinatorial Chemistry Technologies and Libraries. Chemis=
try Libraries: Design of Focused, Diverse and Thematic Libraries. Biologica=
l Libraries, Bio planning, Peptide Display Libraries design and constructio=
n.
=A0

=A0

Paper IV - Computational chemistr= y

U= NIT I - Introduction to com= putational chemistry -Force fields and molecular representations of matter Intramolecular (bonding) interactions-Non-bon= ded interactions -Hydrogen bonds-Constraints and Restraints-United atom and oth= er coarse-grained approaches-Non-pairwise interactionsMethods fo= r Simulating Large systems:Non-bonded Cutoffs Shifted= potential and shifted force-Switching functions-Neighbor listsBoundaries -Periodic Boundary conditions-Stochastic forces at spherical boundaryLo= ng-range interactions -The Ewald Sum-The Reaction field method <= /p>

=A0

=A0

U= NIT II - Ener= gy Minimization and related analysis techniques Steepest descent-Conjugate gradient-Newton-Raphson-Comparison of methods-Advanced techniques: Simulated Annealing, Branch-and-bound, simplex-What's the b= ig deal about the minimum anyway? Free Energy :Perturbation methods,Thermodynamic integration

U= NIT III - Introduction to Equilibrium Statistical Mechanics Phase space, ergodicity, and Liouville's theorem-Ensemble theory, thermodynamic averages -Statistical mechanics of fluids Monte Carlo -MC integration and Markov chains:The Metropolis method,Biased MC Molecular Dynamics Classical mechanics: equations of motion,Finite Difference met= hods :Verlet algorithm,Velocity verlet,The Time step: practical issues,Multiple time-step algorithms-Constraint Dynamics :Fundamental concepts ,SHAKE and RATTLE Brownian dynamics and the Langevin Equation

=A0

U= NIT IV - Temperature: Maxwe= ll-Boltzmann distribution of velocities Temperature control Velocity scaling,Andersen's method,Nose-Hoover dynamics C= alculating properties from MD trajectories, Hybrid MC

U= NIT V - Chemometrics -Introduction- Origins-Techniques : Multiv= ariate

calibration,Cla= ssification, pattern recognition, clustering,Multivariate Curve resolution,Other<= /p>

=A0Techniques, Commercial Softwares

= =A0

R= eferences:

=A0

Paper-V STRUCTURAL BIOLOGY

U= NIT I - Introduction to protein structure: Physical and chemical properties of amino acids and p= olypeptides. Conformational properties of proteins, Ramachandarn Plot, Secondary, Super Secondary, tertiary and quaternary structure of proteins.

U= NIT II - Functional classification of proteins: Cell surface receptors, GPCR=92s, Kinases, Channel proteins, Ubiquitin

UNIT=A0 III - Biophysical Techniques: Principles, Process and Applications of Thin layer chromatography, Column chromatograph= y ( ion exchange and affinity only) , HPLC,

UNIT=A0 IV - x-= ray generation ; its application; unit cell and x-ray ,anomalous scattering; lattices, Bragg=92s= Law; atomic scattering factor and structure factor; phase problem; intensity dat= a collection and reduction;

UNIT V - Isolation and purification of protein (chromatography, electrophoresis), crystallizat= ion (sitting and hanging drop method). Protein structure determination-molecula= r replacement technique; multiple isomorphous replacement method, synchrotron radiation and its uses; multi wavelength anomalous diffraction method. Calculation of electron density map, interpretation of electron density map= . Refinement of the structure. Structure validation methods.

=A0

= =A0

= =A0

Paper-VI =A0Molecular modeling techniques

U= NIT I: Introduction to Molecular Modelling

Introduction to= Molecular Modelling. What are models used for? Areas of application =96 Single
molecule calculation, assemblies of molecules. Reaction of the molecules. Drawbacks of
mechanical models as compared to graphical models. Co-ordinate systems two = =96 matrix,
potential energy surface.

U= NIT II =96 Quantum Mechanics

Postulates of q= uantum mechanics, electronic structure calculations, ab initio, semi-empirical
and density functional theory calculations, molecular size versus accuracy. Approximate
molecular orbital theories.

=A0

=A0

<= br>

U= NIT III =96 Comparative protein modeling

Modelling by Ho= mology-the alignment, construction of frame work, selecting variable regions,
side chain placement and refinement, validation of protein models =96Ramcha= ndran plot,
threading and ab initio modeling.

=A0

PAPER VII - PHARMACEUTICAL CHEMISTRY

U= NIT I - Molecular basis of drug action: Receptor: Drug Rece= ptor Interaction: Basic ligand concept, agonist, antagonist, partial agonist, inverse agonist, rece= ptor Theories - Occupancy, Rate & Activation Theories, receptor Binding Assa= ys, determination of B-max and Kd by transforming data with Hill plot and Scatchered plot., above concepts with special reference to Opioid , Histami= nergic , Adrenergic and GABA nergic receptors. Enzyme Inhibition =96 Enzyme, enzyme Kinetics, enzyme Inhibitors - reversible, irreversible, Kcat inhibitors.Transition state analogs, enzyme = Inhibitors as drugs - ACE, leukotrienes,Lipoxygenase, Cycloxygenase, Aromatase, Xanthi= ne oxidase, DNA PolymeraseInhibitors, HIV - Protease / Reverse Transcriptase, Integrase and Cytochrome P-450 Inhibitors. Drug binding to nucleic acid -- Antimalarial, anti-cancer, antiviral..

U= NIT II- Synthon approach:

Definition of terms - disconnection, synthon, functional group interconversion (FGI), Basic rules in Disconnection, Use of synthon approach in synthesis of compounds: Trimethoprim, erfenadine, lbuprofen, Propanolol, Fentanyl,Ciprofloxacin, Cimetidine, Piroxicam,osiglitazone, Diclofenac, Captopryl, Nifedipine, Losartan.

=A0

U= NIT III- Combinatorial Chemistry

Introduction, combinatorial approaches, chemical Peptide and small molecule libraries, applications, methodology, combinatorial organic synthesis, assays and scre= ening of combinatorial libraries, i6ntroduction to High Throughputs Screening (HT= S)

U= NIT IV- Nanochemistry=A0=A0=A0=A0=A0=A0=A0=A0=A0= =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0

Physical chemistry related to nanoparticles such as colloids and clusters: different equilibrium structures, quantum effects, conductivity and enhanced catalyti= c activity compared to the same materials in the macroscopic state.Exploitati= on of self-assembly and self-organization to design functional structures in 1= D, 2D or 3D structures.Role of polymers in lithography resists, as well as self-organization of more complicated polymer architectures such as block copolymers and polymer brushes. Nanomaterials: (Nanoparticles, nanoclusters, quantum dots synthesis): Top-down techniques: photolithography, other optical lithography (EUV, X-Ray, LIL), particle-bea= m lithographies (e-beam, FIB, shadow mask evaporation), probe lithographies, Bottom-up techniques: self-assembly, self-assembled monolayers, directed assembly, layer-by-layer assembly. Pattern replication techniques: soft lithography, nano imprint lithography. Pattern transfer and enhancement techniques: dry etching, wet etching, pattern growth techniques

U= NIT V - Microwave synthesis- Microwaves Are Energy- Microwaves Can Interact with Matter- Two Principal Mechanisms for Interaction With Matter- Microwave Heating Differs from Conventional Means: Conventional Heating Methods- Microw= ave Heating - The Microwave Effect with examples - Single-Mode and Multimode Microwave Cavities

=A0

= =A0

Paper-VIII ANALOG and stucture ba= sed drug designing

U= NIT I - Drug discovery-Strategies and historical developments - Introduction =96conventional strategies to drug discovery-molecular mimetic- first and s= econd generation rational approach-Rational drug design-assessment of drug activi= ty- future prospects-examples of successful applications of CAD

U= NIT II - Basic principle of drug design: Introduction-old QSAR-Use of physiochemical descriptors-use of electronic descriptors-use of molecular descriptors-Use = of thermodynamic descriptors-use of receptor descriptors-success and limitatio= ns of old QSAR

UNIT III Analog based drug design

D= eveloping and using QSAR- Introductio= n-classical QSA-Freem and Wilson=92s method-topliss method-use of statistical methods in QSAR-validation methods-3D QSAR approach-QSAR descriptors3D QSAR-Introduction-Pharmacore identification-binding site modeling of unknown receptor-receptor mapping-structural alignment and superposition-molecular field analysis (MF= A)

Unit iv=A0 =A0= Structure based drug design

3D pharmacophor= es, De novo Ligand design-introduction-approaches to de novo drug design problem-some current methods for de novo design.3D data base searching and virtual screening,. Sources of data, molecular similarity and similarity searching, prediction = of binding energy of ligand-receptor complex-Free energies and salvation-electrostatic and non-electrostatic contribution to free energies combinatorial libraries =96 generation and utility,

U= NIT V- Molecular docking: Introduction Docking approaches: Shape complementarity- Simula= tion Mechanics of docking - Search algorithm-Scoring function-Applications

= =A0

= =A0

= =A0

= =A0

= =A0

P= RACTICAL I Computer programming and RDBMS

<= span style=3D"">=A0C++, JAVA, CML, Perl, Perl Mol, Python, Visual Basic, ORACLE

=A0

P= RACTICAL II

C= hemical databases - ChemBank-ChemBi= oFinder =96 CSChemoffice - ZINC

M= olecular dynamics - GROMACS- NAMD-VE= GA ZZ

S= tructural chemistry - NWChem =96GAMES= S

D= ocking - Autodock, DOCK -VEGA- FlexX

=A0

=A0

=A0

=A0

=A0

=A0

=A0JALEEL
<= /span>

=A0MCC

=A0

=A0

=A0



On Sun, May 8, 2011 at 11:02 AM, Rodolfo= Gomez rgbccl/./gmail.com <owner-chemistry]![ccl.net> wrote:
Dear CCLrs,<= /div>
=A0
Recently my faculty is considering to offer an undergraduate course on= Chemoinformatics, for chemistry students. Though I=B4ve been working a bit= on computational chemistry, I do not feel I have the proper vision=A0to bu= ilt up a syllabus proposal, or even=A0for giving a reasonable=A0criticism o= f anyone else proposal.
=A0
I would really appreciate your opinion on what=A0should be included in= a course of such a level?
=A0
Thanks in advance for your kind reply.
=A0
Rodolfo G=F3mez



--
=A0Dr UCA JALEEL
=A0= Asst Professor in cheminformatics
=A0UGC AIDED Centre for cheminformati= cs
=A0MCC calicut
phone

--0003255579766491f404a2c61d11-- From owner-chemistry@ccl.net Sun May 8 13:21:00 2011 From: "uekstrom[#]gmail.com uekstrom[#]gmail.com" To: CCL Subject: CCL: Program language in Quantum Chemistry: C++ or FORTRAN? Message-Id: <-44589-110508131932-5437-59G+DNnuzv/WVZ3Bmt9D9A^^^server.ccl.net> X-Original-From: "uekstrom- -gmail.com" Content-Type: text/plain; charset=ISO-8859-1 Date: Sun, 8 May 2011 19:19:26 +0200 MIME-Version: 1.0 Sent to CCL by: "uekstrom~~gmail.com" [uekstrom~~gmail.com] Professor Neese, thank you very much for your comments! I like Orca because it shows that better software is really possible. I am very curious about the programming techniques you have used in Orca, would you consider publishing some representative source files or some older version of the code online? Or did you already publish some paper or school material on this? I feel that some people are hesitant to try C++ because there is the initial "hump" of designing good BLAS wrappers etc, here I think it's important with success stories, such as Orca, to motivate people to overcome this hump. Regards, Ulf Ekstrom From owner-chemistry@ccl.net Sun May 8 16:41:00 2011 From: "Michel Petitjean petitjean.chiral|a|gmail.com" To: CCL Subject: CCL: Program language in Quantum Chemistry: C++ or FORTRAN? Message-Id: <-44590-110508163819-2922-V8JH3SUPrV32opiEGI462Q.@.server.ccl.net> X-Original-From: Michel Petitjean Content-Transfer-Encoding: 8bit Content-Type: text/plain; charset=ISO-8859-1 Date: Sun, 8 May 2011 22:38:07 +0200 MIME-Version: 1.0 Sent to CCL by: Michel Petitjean [petitjean.chiral-*-gmail.com] Hi, You got several replies to your post, including to some who choosed C++. C/C++ dominates the market in general (and in the Univ. curus), but fortran resists, at least for numerical applications. It was mentioned that it is difficult to find a good quality fortran compiler on Windows (well, I am not sure that most numericians like Windows). The lack of fortran programmers was evoked. Every year many people predicts the death of fortran, although it is the oldest language which survived. Some explains that by the existence of libraries, but fortran routines can be called in C (if not C++), sometimes through an interface (calling C from fortran is possible, too). So, why the beast is still alive ? Probably because programmers are able to learn several languages (and they like to learn several language), and then many haved tried fortran, soon or later. Then, they find useful to declare variable dimension arguments in subroutines such as tab(n) or tab(*), tab being declared with the dimension(s) you like in the calling routine: a major requirement for most developpers. They also like to save time (and decrease the risk or error) with the array indexing from 1 (from 0 or other is authorized !!). The backspace instruction is sometimes very useful. Entries and alternate returns can be useful, too. Formatted I/O ("column alignments" in files) are easy. Etc. Yes all that can be done in C/C++, but it is not so easy ! The major defect of f77 was the lack of dynamic allocation, but f90 solved that. I would recommand C as a jacknife for programming (and C++ is close to C, at least syntactically), but really f95 is nice for numerical analysis, and good compilers are available on the unix family platforms (Windows cannot be recommended for serious applications). The day when fortran compilers become unavailable, fortran will die. Before that, we will hear again about fortran on the CCL forum. Sincerely, Michel Petitjean MTi, INSERM UMR-S 973, University Paris 7 CNRS SNC 9079 35 rue Helene Brion, 75205 Paris Cedex 13, France. Phone: +331 5727 8434; Fax: +331 5727 8372 E-mail: petitjean.chiral!A!gmail.com (preferred), michel.petitjean!A!univ-paris-diderot.fr http://petitjeanmichel.free.fr/itoweb.petitjean.html 2011/5/7 Jun Zhang coolrainbow()yahoo.cn : > > Sent to CCL by: Jun Zhang [coolrainbow]*[yahoo.cn] > Hello Everyone: > > Many new developed quantum chemistry software have been written in C++ rather than FORTRAN. Although the compilers for C++ are developing, however, due to C++'s inherent complexity, I don't think it is easier to optimize a C++ code than FORTRAN code for compilers. So why so many have chosen C++? Is it due to developing efficiency? Any suggestions will be appreciated. > > Jun Zhang > Nankai University > coolrainbow- -yahoo.cn From owner-chemistry@ccl.net Sun May 8 22:03:01 2011 From: "Susan R. Atlas susie(!)sapphire.phys.unm.edu" To: CCL Subject: CCL: Program language in Quantum Chemistry: C++ or FORTRAN? Message-Id: <-44591-110508215249-26738-oiVVbgUq5mRy/5YzCcHa4g]*[server.ccl.net> X-Original-From: "Susan R. Atlas" Content-Type: multipart/alternative; boundary="------------030505090108060202050504" Date: Sun, 08 May 2011 19:52:28 -0600 MIME-Version: 1.0 Sent to CCL by: "Susan R. Atlas" [susie^^sapphire.phys.unm.edu] This is a multi-part message in MIME format. --------------030505090108060202050504 Content-Type: text/plain; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: 7bit Hi, Two words: FORmula TRANslation. For small-scale/single research group scientific programming in chemical and materials physics, I strongly recommend Fortran, since it leads to much more readable code where it is easy to match the code to the original mathematical equations. This facilitates extensibility, particularly across generations of graduate students. (Incidentally, with Fortran I would advise against using its "full" object-oriented features they can perform poorly, make the code unreadable, and if you want to go true OO, you should be using C++ anyway since that is what it was designed for. The OO features of F90 are an ugly hack in my opinion.) None of the departments at our university really teach scientific programming anymore (everything is Java, Python, etc.--- no Fortran, C, or C++!) so if I am going to have to give new research students a crash course in a high-level language anyway, I figure I may as well teach them Fortran, if that is the best tool for the job.) For any string handling or pre/post processing, which Fortran does *not *do well, I use perl scripting. By contrast, for computational biology type applications, I recommend C or C++ since compbio codes typically require a lot of string/text processing, pattern matching, etc., and Fortran is not the right tool for that. Finally, if you are working as part of a large-scale (multi-group, multi-institutional) collaboration, I think there is a good argument to be made for C++, since C++'s OO and attendant modularity are more important issues. Nevertheless, I myself would probably still prefer to use Fortran (implemented with a highly modular programming style), because its advantages with respect to clarity and readability are still so powerful. A language like MATLAB is fine for small-scale prototyping, but not appropriate for large-scale production computing, since it will be at least 10x slower than a well-written code in Fortran, C, or C++. Good luck, - Susan ------------------------------------------------------------------------ > I think Ulf's criteria are more on point here. When you are deciding > on the right > language to use it is generally pointless to argue which language is > better in > the abstract. If all of your graduate students know C,C++,python, > none of them > know fortran 90, and in the future you will be even less likely to > find fortran programmers > then that is a way more important fact than whether you like your > arrays to start at 1. > If you were going to do ab initio development then fortran might be > the no-brainer > choice over C because most ab initio code is still developed in fortran. > > Tom > > Thomas Stockfisch, Ph.D. > tom[-]tstockfisch.com > http://www.tstockfisch.com > http://www.linkedin.com/pub/tom-stockfisch/3/948/4b3 > 760-497-4108 > > On May 7, 2011, at 3:46 AM, uekstrom++gmail.com uekstrom++gmail.com wrote: > >> >> Sent to CCL by: "uekstrom,+,gmail.com" [uekstrom,+,gmail.com] >>> Plese read some f95 manual, and try to programme some numerical >>> algorithm (not too simple) in C or C++ and then in f95 or even in f77. >>> What about variable dimension arguments, arrays indiced from 1 rather >>> than 0, etc. >> >> I would say that for this exercise Matlab is 10x more productive >> compared to Fortran, C or C++, but that doesn't mean that Matlab is >> the right choice for making a large quantum chemistry program. The >> array index thing is a trivial point in a large program, more >> important is how adaptable the program will be in the future, and how >> fast new development can take place. There's nothing wrong with using >> different languages for different programs, or different languages for >> parts of the same program. >> >> The problem with Fortran is not that Fortran 77 had some issues, those >> issues were often also found in early C implementations. The problem >> with Fortran is that the language is evolving extremely slowly and >> that new features cannot be used because they are inefficient (i.e. >> MATMUL with ifort, the "best" Fortran compiler) or because compilers >> are still not, in 2011, supporting Fortran 2003. Being on the Fortran >> standardization committee must be the most maddening experience ever. >> >> Ulf>> the strange characters on the top line to the [-] sign. You can also>> >> E-mail to subscribers: CHEMISTRY[-]ccl.net >> or use:>> >> E-mail to administrators: CHEMISTRY-REQUEST[-]ccl.net >> or use>> >> > -- ------------------------------------------------------------------ Susan R. Atlas Research Associate Professor, Physics and Astronomy Director, Center for Advanced Research Computing Director, University of New Mexico Cancer Center Shared Resource for Bioinformatics and Computational Biology Department of Physics & Astronomy MSC07 4220 p: 505.277.1509 1 University of New Mexico e: susie . sapphire.phys.unm.edu Albuquerque, NM 87131-0001 n: www.phys.unm.edu/CompMaterials --------------030505090108060202050504 Content-Type: text/html; charset=ISO-8859-1 Content-Transfer-Encoding: 7bit Hi,

Two words:  FORmula TRANslation.

For small-scale/single research group scientific programming in chemical and materials physics, I strongly recommend Fortran, since it leads to much more readable code where it is easy to match the code to the original mathematical equations. This facilitates extensibility, particularly across generations of graduate students.  (Incidentally, with Fortran I would advise against using its "full" object-oriented features they can perform poorly, make the code unreadable, and if you want to go true OO, you should be using C++ anyway since that is what it was designed for.  The OO features of F90 are an ugly hack in my opinion.)  None of the departments at our university really teach scientific programming anymore (everything is Java, Python, etc.--- no Fortran, C, or C++!) so if I am going to have to give new research students a crash course in a high-level language anyway, I figure I may as well teach them Fortran, if that is the best tool for the job.)  For any string handling or pre/post processing, which Fortran does not do well, I use perl scripting.

By contrast, for computational biology type applications, I recommend C or C++ since compbio codes typically require a lot of string/text processing, pattern matching, etc., and Fortran is not the right tool for that.

Finally, if you are working as part of a large-scale (multi-group, multi-institutional) collaboration, I think there is a good argument to be made for C++, since C++'s OO and attendant modularity are more important issues.  Nevertheless, I myself would probably still prefer to use Fortran (implemented with a highly modular programming style), because its advantages with respect to clarity and readability are still so powerful.

A language like MATLAB is fine for small-scale prototyping, but not appropriate for large-scale production computing, since it will be at least 10x slower than a well-written code in Fortran, C, or C++.

Good luck,

  - Susan



I think Ulf's criteria are more on point here.  When you are deciding on the right
language to use it is generally pointless to argue which language is better in
the abstract.  If all of your graduate students know C,C++,python, none of them
know fortran 90, and in the future you will be even less likely to find fortran programmers
then that is a way more important fact than whether you like your arrays to start at 1.
If you were going to do ab initio development then fortran might be the no-brainer
choice over C because most ab initio code is still developed in fortran.

Tom
On May 7, 2011, at 3:46 AM, uekstrom++gmail.com uekstrom++gmail.com wrote:


Sent to CCL by: "uekstrom,+,gmail.com" [uekstrom,+,gmail.com]
Plese read some f95 manual, and try to programme some numerical
algorithm (not too simple) in C or C++ and then in f95 or even in f77.
What about variable dimension arguments, arrays indiced from 1 rather
than 0, etc.

I would say that for this exercise Matlab is 10x more productive
compared to Fortran, C or C++, but that doesn't mean that Matlab is
the right choice for making a large quantum chemistry program.  The
array index thing is a trivial point in a large program, more
important is how adaptable the program will be in the future, and how
fast new development can take place. There's nothing wrong with using
different languages for different programs, or different languages for
parts of the same program.

The problem with Fortran is not that Fortran 77 had some issues, those
issues were often also found in early C implementations. The problem
with Fortran is that the language is evolving extremely slowly and
that new features cannot be used because they are inefficient (i.e.
MATMUL with ifort, the "best" Fortran compiler) or because compilers
are still not, in 2011, supporting Fortran 2003. Being on the Fortran
standardization committee must be the most maddening experience ever.

Ulf



the strange characters on the top line to the [-] sign. You can also



-- 
------------------------------------------------------------------
 Susan R. Atlas
 Research Associate Professor, Physics and Astronomy
 Director, Center for Advanced Research Computing
 Director, University of New Mexico Cancer Center Shared Resource
    for Bioinformatics and Computational Biology
 
 Department of Physics & Astronomy
 MSC07 4220                       p: 505.277.1509
 1 University of New Mexico       e: susie . sapphire.phys.unm.edu
 Albuquerque, NM 87131-0001       n: www.phys.unm.edu/CompMaterials
--------------030505090108060202050504-- From owner-chemistry@ccl.net Sun May 8 23:53:00 2011 From: "Jun Zhang coolrainbow#,#yahoo.cn" To: CCL Subject: CCL: Program language in Quantum Chemistry: C++ or FORTRAN? Message-Id: <-44592-110508234625-1462-Yxw+TbICoolYACzTpYLSPQ||server.ccl.net> X-Original-From: Jun Zhang Content-Transfer-Encoding: 8bit Content-Type: text/plain; charset=utf-8 Date: Mon, 9 May 2011 11:46:11 +0800 (CST) MIME-Version: 1.0 Sent to CCL by: Jun Zhang [coolrainbow#%#yahoo.cn] Hello Everyone: I am very appreciate to get so many replies and participate this productive discussion. I have some program experience, although very limited, in both Fortran and C++. Software developing is indeed an elegant project with so many issues to consider. I want to share my experience. Performance - Although there are not systimatic data, some of my colleagues reported that with the same optimization strategies and algorithm, for integer computation Fortran seems to be faster and for floating computation Fortran shows no advantages. Obviously in quantum chemistry not too many integer operations are involved, so performance is not an issue. Of course, in C++ there are some "performance killers" such as object destructions during running and virtual functions, but all of them can be avoided by carefully coding. Taste - I agree that many Fortran coders, like me, do not like C++: Maybe this is because it involves too many program arts rather than scientific thoughts. Some C++ programmers are pursuing the "beautiful realization", forgetting the topic of the project. Fortran is more simple, and in f95 the new features such as dynamic allocation or implicit vector operations have made the fortran codes much more readable and beautiful that f77. One female coder states "I like FORTRAN77 forever", although I hate f77 but like f95. One in atmospheric science field say "In our field we cannot abandon Fortran". Which laguague is favorite depends on individual. In an inorganic group in my university they are still using BASIC! For large scale commencial codes - in science community or other fields - more and more are adopting C++. Maybe when the old softwares disappear, fortran will die. Maybe I have to admit this. Jun Zhang Nankai University coolrainbow],[yahoo.cn > Jun Zhang coolrainbow()yahoo.cn > CCL: Program language in Quantum Chemistry: C++ or FORTRAN? > "Zhang, Jun " > > Sent to CCL by: Jun Zhang [coolrainbow]*[yahoo.cn] > Hello Everyone: > > Many new developed quantum chemistry software have been > written in C++ rather than FORTRAN. Although the compilers > for C++ are developing, however, due to C++'s inherent > complexity, I don't think it is easier to optimize a C++ > code than FORTRAN code for compilers. So why so many have > chosen C++? Is it due to developing efficiency? Any > suggestions will be appreciated. > > Jun Zhang > Nankai University > coolrainbow- -yahoo.cn