From chemistry-request@ccl.net Sun Apr 19 01:25:30 1992 Date: Sun, 19 Apr 1992 12:29:01 GMT From: B_DUKE@DARWIN.NTU.EDU.AU (Brian Duke) Subject: Survey on comp chem. To: chemistry@ccl.net Status: R 19 April 1992. Dear Computational Chemistry list subscribers, Almost 12 months ago last May, my colleague, Brian O'Leary from the Chemistry Department of the University of Alabama at Birmingham, and I started to survey university chemistry departments to determine the extent of teaching of computational chemistry at all levels. As part of that survey, we sent a message to the computational chemistry list. Our letter and questionaire was sent to Chairmen or Heads of Chemistry Departments in several countries - Canada, New Zealand, Australia and the United Kingdom. In the event, a number of factors, including the onset of the summer vacation, prevented us from sending out the survey to departments in the US. Nevertheless, we did receive a few responses from the US. However, learning from our mistakes, we designed what we believe is a much better survey. This was sent to chemistry departments throughout the US towards the end of 1991 and we have received many replies. If your department has not replied, or if through some mistake, it did not receive our survey, would you please consider responding now? If you did not receive a copy of the survey or if you have misplaced it, a copy can be obtained by e-mail from:- b_duke@darwin.ntu.edu.au or from the Ohio archives using either ftp as follows:- ftp www.ccl.net (or ftp 128.146.36.48) login: anonymous password: your e-mail_address (please!) ftp> cd pub/chemistry ftp> get survey ftp> quit or by sending a single line message:- send survey from chemistry to oscpost@ccl.net or oscpost@ohstpy.bitnet It would also be pleasing if those in the US who responded to the original survey could respond to the new, improved model. The prime purpose of this posting to the list is to remind US Chemistry Departments about our survey and to seek further responses. For this reason, the survey available by e-mail or from the Ohio archives is identical to the one sent out last year, and it is obviously directed at the American market. Nevertheless, we would welcome responses from people outside the US, if you can be patient and translate the obvious americanisms. Thank you for your cooperation. Brian Duke School of Chemistry and Earth Sciences, Northern Territory University GPO Box 40146, Casuarina, NT 0811, Australia. Phone 089-466702 FAX 089-410460 E-mail B_DUKE@DARWIN.NTU.EDU.AU From chemistry-request@ccl.net Sun Apr 19 02:30:56 1992 Date: 18 Apr 92 15:57 LCL From: PA13808%UTKVM1.BITNET@OHSTVMA.ACS.OHIO-STATE.EDU Subject: BITNET mail follows To: CHEMISTRY@ccl.net Status: R TOXICITY I believe has been some interest recently on the network on software using QSAR methods to predict toxicity. I would like to make a tardy contribution which did not come up at the time. I receive a free pamphlett TOXICOLOGY Newsletter from HDI,183 E. Main street Rochester NY 14604 USA.These people have a number of software packages TOPKAT specifically designed for toxicity prediction.One for example interactively produces validated estimates of toxicity which are in compliance with US govt regs.(see the NEWSLETTERvol 14 nov 1991) See alsoQSAR studies using electronic descriptors calculated from topol ogical and MO methods. Quantitative Structure Activity Relationships vol9 325(1990). The company usually has a booth at American Chem soc meetings. (John E. Bloor,PA13808 AT UTKVM1) From chemistry-request@ccl.net Sun Apr 19 05:24:01 1992 Date: Sun, 19 Apr 92 00:06:34 PDT From: burger@violet.berkeley.EDU Subject: Re: Semiempirical optimizations To: AHOLDER@VAX1.UMKC.EDU, CHEMISTRY@ccl.net Status: R Is there any particular reason to use AMPAC instead of MOPAC and if not why do 2 programs of this type exist? There is something mentioned in the MOPAC manual but I didn't get the point Peter --------------------------------------------------------------- Peter Burger postdoctoral fellow UC Berkeley burger@violet.berkeley.edu From chemistry-request@ccl.net Sun Apr 19 12:30:30 1992 Date: Sun, 19 Apr 92 09:17:07 EDT From: m10!frisch@uunet.UU.NET (Michael Frisch) Subject: Semiempirical optimizations in MOPAC To: chemistry@ccl.net Status: R There seems to be some confusion about what Gaussian does during semi-empirical optimizations. Here are some details: 1. Gaussian defaults to accuracy comparable to that produced by the PRECISE keyword in MOPAC. 2. The step-size used in numerically differentiating the integrals as part of the gradient calculation is small in Gaussian, because a smaller step can be taken reliably if it is known in advance that PRECISE is always turned on. This provides somewhat greater accuracy in the derivatives. I think something like this (but with different values for the step size) is done in MOPAC version 6 but not in earlier versions. 3. Only the energy and cartesian gradient are computed using code from MOPAC; the rest of the optimization uses the standard Gaussian routines in exactly the same manner as an ab initio optimization would. 4. The cartesian forces are converted to internal coordinates using different algorithms. I don't know the details of how MOPAC does the conversion, but this appears to make a difference. Gaussian uses analytic expressions and doesn't suffer from the sensitivity to internal coordinate definition that MOPAC apparently does, since MOPAC gives the warning message about small changes in internal coordinates causing large displacements for cases where Gaussian does not have difficulties. 5. Gaussian's default optimizer is not the same as either EF in Gaussian or EF in MOPAC. It does use an RFO (Rational Function Optimization) step for the quadratic portion of the step as in the EF method, but it also does gradient-based linear corrections at every step as suggested by Schlegel, and it uses an improved version of Schlegel's update scheme for the Hessian. EF (Baker's algorithm) is available as an option, but is usually inferior to the default, since the default is a mixture of the best parts of Baker's and Schlegel's methods. Michael Frisch Gaussian, Inc. -------