From owner-chemistry@ccl.net Wed Mar 25 08:16:01 2015 From: "Barbara Sandhoefer bs12_._princeton.edu" To: CCL Subject: CCL: Quantum Chemistry Survey Message-Id: <-51196-150325054554-5146-A/2FHtp624j48+qwa8LWuA{}server.ccl.net> X-Original-From: "Barbara Sandhoefer" Date: Wed, 25 Mar 2015 05:45:52 -0400 Sent to CCL by: "Barbara Sandhoefer" [bs12:-:princeton.edu] Dear CCL-Subscriber, Many excellent quantum chemistry packages are out there, but only very few experienced researchers know about the specialties and expertise of all of them. I am trying to collect information that would allow a comparison between the different programs, regarding technical features as well as user preferences. With this aim I am conducting a survey that you can find here: http://goo.gl/vZwa1V The survey takes less than 5 minutes, and it is anonymous (unless you want to provide further information on yourself). I would be grateful if you filled out the survey. Of course you are free to forward the survey to interested coworkers and colleagues. Great numbers make great statistics. Thanks, Barbara Sandhoefer Barbara Sandhoefer, Ph.D. Postdoctoral Researcher | Chan Group Department of Chemistry | Princeton University From owner-chemistry@ccl.net Wed Mar 25 10:49:00 2015 From: "Simon Cross simon__moldiscovery.com" To: CCL Subject: CCL: FLAP 2.1 released Message-Id: <-51197-150325104739-12216-F/SoSQF/3yivQlzTQSGa0Q(-)server.ccl.net> X-Original-From: Simon Cross Content-Transfer-Encoding: 7bit Content-Type: text/plain; charset=utf-8; format=flowed Date: Wed, 25 Mar 2015 15:47:25 +0100 MIME-Version: 1.0 Sent to CCL by: Simon Cross [simon:moldiscovery.com] Dear Colleagues, we are happy to announce the release of FLAP 2.1 for virtual screening, pharmacophore modelling, 3D-QSAR, docking, and water prediction. FLAP is based on GRID Molecular Interaction Fields, in combination with pharmacophoric quadruplet fingerprints, and enables candidate similarity to be calculated to a template in both ligand-based and structure-based approaches. FLAP has been validated against a number of prospective targets to find adenosine receptor antagonists, folate cycle inhibitors, NorA inhibitors, and influenza viruses. FLAP 2.1 contains an enhanced approach to docking with optional water molecules predicted by WaterFLAP, including a water displaceability score and identifying bridging waters. Additionally, many incremental improvements have been made to the graphical interface including a streamlined protein preparation workflow, better water handling and subset selection, hydrogen bond display, residue labelling and improved sequence viewer, a virtual screening workflow using FLAPdock, and bookmarking of selected compounds for further analysis and export. Key features include: - Fast ligand-based and structure-based virtual screening using FLAP fingerprints - Improved virtual screening accuracy using FLAP alignment and GRID MIF scoring - Optional user-specified pharmacophoric feature constraints - Ligand-based alignment and structure-based pose prediction using GRID MIFs - Pharmacophore elucidation and screening - Automatic pocket detection for structure-based design - GRID MIF calculation using all standard GRID probes - Electron density visualisation - Linear Discriminant Analysis enables the training of target focused scoring functions - Enrichment plot analysis enables screening approach validation prior to prospective screening - Fuzzy maximal common substructure alignment - 3D-QSAR analysis - WaterFLAP water prediction, scoring, and analysis - FLAPdock docking using GRID MIFs and WaterFLAP waters - MoKa integration for automatic protonation and tautomer enumeration and selection (requires FLAP-Suite edition or separate MoKa license) - VolSurf+ integration to enable virtual screening that includes pharmacokinetic properties (requires a separate VolSurf+ license) FLAP is available for both Windows and Linux operating systems. More information about FLAP can be found here: http://www.moldiscovery.com/soft_flap.php Kind regards, Simon Dr. Simon Cross Snr Scientist & Product Manager Molecular Discovery Ltd Email: simon[at]moldiscovery[dot]com Molecular Discovery provides robust, high-quality and innovative computational methods addressing pharmaceutical needs in the field of drug discovery, including methods for virtual screening, lead optimisation, ADME modelling and metabolism research. Molecular Discovery software products offer calculation of accurate Molecular Interaction Fields for structure-based design (GRID), water prediction for structure-based design (FLAP), ligand-based and structure-based virtual screening (FLAP), pharmacophore elucidation (FLAP), metabolism prediction (MetaSite), metabolite identification (Mass-MetaSite), scaffold hopping (SHOP), pKa prediction (MoKa), 3D-QSAR modeling (FLAP, Pentacle), and ADME modelling (VolSurf+) to improve efficiency in modern drug discovery. More information can be found on the main page: http://www.moldiscovery.com/ From owner-chemistry@ccl.net Wed Mar 25 13:09:01 2015 From: "Partha Sengupta anapspsmo]=[gmail.com" To: CCL Subject: CCL: TD spectra of [ Fe(CN)6]3- Message-Id: <-51198-150325130528-1902-jaEmQoKaxaNeptGDzKHjhA]*[server.ccl.net> X-Original-From: Partha Sengupta Content-Type: multipart/alternative; boundary=001a11c36d74a1386d05121fe7e2 Date: Wed, 25 Mar 2015 22:35:22 +0530 MIME-Version: 1.0 Sent to CCL by: Partha Sengupta [anapspsmo-#-gmail.com] --001a11c36d74a1386d05121fe7e2 Content-Type: text/plain; charset=UTF-8 Friends, I found TD-DFT of [ Fe(CN)6]3- a straight line. Why? -- Dr. Partha Sarathi Sengupta Associate Professor Vivekananda Mahavidyalaya, Burdwan --001a11c36d74a1386d05121fe7e2 Content-Type: text/html; charset=UTF-8
Friends, I found TD-DFT of [ Fe(CN)6]3- a straight line. Why?

--
Dr. Partha Sarathi Sengupta
Associate Professor
Vivekananda Mahavidyalaya, Burdwan
--001a11c36d74a1386d05121fe7e2-- From owner-chemistry@ccl.net Wed Mar 25 16:52:01 2015 From: "Timur I Madzhidov tmadzhidov,,gmail.com" To: CCL Subject: CCL: Second Kazan Summer School in Chemoinformatics, Kazan, Russia Message-Id: <-51199-150325105751-18957-a6J80qY9t0/CxAyrLbHK/g[#]server.ccl.net> X-Original-From: "Timur I Madzhidov" Date: Wed, 25 Mar 2015 10:57:50 -0400 Sent to CCL by: "Timur I Madzhidov" [tmadzhidov\a/gmail.com] Dear colleagues, Abstract submission for Kazan Summer School in Chemoinformatics to be held July 6-9, 2015, is still possible. The deadline for abstract submission is April 1, 2015. Summer School on Chemoinformatics is a regular event, aiming to create the conditions for training specialists of Chemoinformatics, as well as to create educational and scientific network of scientists, pharmaceutical and chemical industry representatives, IT specialists and software developers. In this school special attention will be paid to material design and new applications of chemoinformatics. Scientific program of the School covers: - Basics of chemoinformatics and QSAR approaches, - Sources of chemical information, its storage and retrieval, - SAR/QSAR/QSPR modeling, - Structure-based drug design. The program of the School includes: - Lectures by leading scientists devoted to different aspects of Chemoinformatics and computer-aided materials and drug design - Key-note research lectures - Oral presentations of the School participants - Tutorials with modern software - Poster session - Contest for young scientists for the best poster and oral presentation The list of lecturers include: - Johann Gasteiger (University of Erlangen, Germany): Solved and Unsolved Problems in Chemoinformatics - Alexandre Varnek (University of Strasbourg, France): Chemical space basis concept of chemoinformatics - Igor Tetko (Helmholtz Zentrum Mnchen, Germany): Prediction-driven Matched Molecular Pairs to interpret and compare QSPR/QSRR models - Alex Tropsha (University of North Carolina, USA): Current trends in QSAR Modeling - Artem Oganov (State University of New York at Stony Brook, USA): "Computational materials discovery: latest breakthroughs" - Thierry Langer (University of Vienna, Austria): Pharmacophores: Efficient Tools for Medicinal Chemistry Decision Support - Joao Aires de Sousa (Universidade Nova de Lisboa, Portugal): Machine learning with large datasets of quantum chemistry calculations - Vladimir Poroikov (Institute of Biomedical Chemistry, Russia): Drug Discovery: Science, Art, Business - Igor Baskin (Moscow State University, Russia): 3D QSAR approaches - Vladimir Tsirelson (Mendeleev University of Chemical Technology, Russia): In Search of Up-To-Date Bonding Descriptors Based on Electron Density - Hanoch Senderowich (Bar-Ilan University, Israel): Statistical Modeling in Material Sciences - Valery Tkachenko (Royal Society of Chemistry, UK): Chemical databasing. State of the art and current challenges - Benoit Creton (IFP Energies nouvelles, France): Structure-Property modelling in the oil industry - Dragos Horvath (CNRS, France): Conformational Sampling & Docking: State-of-the-art and Challenges - Pavel Polishchuk (Bogatsky Physico-Chemical Institute, Ukraine): QSAR modelling of mixtures - Vitaly Solov'ev (Institute of Physical Chemistry and Electrochemistry, Russia): Prediction of Halogen-Bond Strength by Ensemble QSPR - Vladimir Palyulin (Lomonosov Moscow State University, Russia): "Molecular Field Topology Analysis (MFTA) as an Advanced Tool for QSAR Studies" - Timur Madzhidov (Kazan Federal University, Russia): Reaction mining basics: database search and structure-reactivity modeling See details at www.kpfu.ru/kssci2015.html Abstracts for poster and oral presentations should be sent to scientific secretary, Dr. Timur MADZHIDOV Timur.Madzhidov%x%kpfu.ru. Best regards, Dr. Timur Madzhidov