From owner-chemistry@ccl.net Thu Jul 30 12:38:01 2020 From: "jaleel uc jaleeluc##ospfound.org" To: CCL Subject: CCL:G: Drug Repurposing Message-Id: <-54151-200730062051-11633-giWUCTk6E8jPt53X4PjtiQ**server.ccl.net> X-Original-From: jaleel uc Content-Type: multipart/mixed; boundary="0000000000007c073805aba606b3" Date: Thu, 30 Jul 2020 15:49:53 +0530 MIME-Version: 1.0 Sent to CCL by: jaleel uc [jaleeluc[A]ospfound.org] --0000000000007c073805aba606b3 Content-Type: multipart/alternative; boundary="0000000000007c073405aba606b1" --0000000000007c073405aba606b1 Content-Type: text/plain; charset="UTF-8" On August 5th, join the Open Source Pharma community and NIH Director Christopher Austin to learn more about drug repurposing amid unprecedented pandemic times. Register here >> https://zoom.us/meeting/register/tJMtcuurrTwpE9Tk9mVHbji8HBIUYO21ED7W. _ --0000000000007c073405aba606b1 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable
On August 5th, join the Open Source Pharma community and = NIH Director Christopher Austin to learn more about drug repurposing amid u= nprecedented pandemic times. Register here >> https://zoom.us/= meeting/register/tJMtcuurrTwpE9Tk9mVHbji8HBIUYO21ED7W. _
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oopSiiiilKKKKKUorLftQ+wP0z6+plao04lnSetlgr+kI7X+LTl+kppPcn/pU4Xzk7wAmiipWXVs rCkGDWi0JWmFCvx/1Vp2bpDUt10rcnWHZdomOwn1sKKm1LbWUqKSoAkZHGQD8qa6KK9qNRXAO9FF FFZrFFFFFKUUUUUpX//Z --0000000000007c073805aba606b3-- From owner-chemistry@ccl.net Thu Jul 30 22:22:00 2020 From: "Thomas Manz thomasamanz : gmail.com" To: CCL Subject: CCL: bond order calculation method Message-Id: <-54152-200730214204-28847-A8j/J+9wtVmfy9LV7yZdKw ~ server.ccl.net> X-Original-From: Thomas Manz Content-Type: multipart/alternative; boundary="000000000000f9ae3205abb2e4cf" Date: Thu, 30 Jul 2020 19:41:46 -0600 MIME-Version: 1.0 Sent to CCL by: Thomas Manz [thomasamanz[A]gmail.com] --000000000000f9ae3205abb2e4cf Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable Dear colleagues, One of my graduate students is in the process of preparing a YouTube video on the topic of computing bond orders using the method introduced in the following paper: T. A. Manz, "Introducing DDEC6 atomic population analysis: part 3. Comprehensive method to compute bond orders," RSC Advances, 7 (2017) 45552-45581 (open access) DOI: 10.1039/c7ra07400j The video will be a less technical presentation, emphasizing chemical concepts with less focus on mathematics. Were any of the concepts presented in the above paper unclear to you? If so, could you please explain which of those concepts you did not understand? If there is a pattern of some aspects being unclear, then I would like to know so that it can be explained in a more understandable way= . If any of you have not taken the time to carefully read that paper, I believe it would be worth your while to do so. Bond order is a foundational chemical concept that has wide-ranging impacts and numerous applications throughout the chemical sciences. The above paper presents the first comprehensive and computationally efficient method to compute accurate bond orders across an extremely wide range of material types. This method to compute bond orders enabled the first study of quantum-mechanically computed bond orders for a large number of diatomic molecules: T. Chen and T. A. Manz, "Bond orders of the diatomic molecules," RSC Advances, 9 (2019) 17072-17092 (open access) DOI: 10.1039/c9ra00974d In this work, bond orders were quantum-mechanically computed for 288 diatomic molecules and ions, which is >10 times the number of diatomics for which bond orders were quantum-mechanically computed in each prior work. Because diatomic molecules are the smallest molecules containing a chemical bond, they are natural textbook examples for studying bond order. Therefore, I view the accurate bond orders for diatomic molecules as foundational to chemical theory. Even among the diatomic molecules, there are many interesting effects that you may not be familiar with yet. These can often provide insights that are helpful to understand larger materials with more atoms. In two recent papers, the above bond order method was applied to identify misbonded atoms in the experimentally-derived crystal structures of metal-organic frameworks: T. Chen and T. A. Manz, "Identifying misbonded atoms in the 2019 CoRE metal=E2=80=93organic framework database," RSC Advances, 10 (2020) 26944-26= 951 (open access) DOI: 10.1039/d0ra02498h T. Chen and T. A. Manz, "A collection of forcefield precursors for metal-organic frameworks," RSC Advances, 9 (2019) 36492-36507 (open access) DOI: 10.1039/c9ra07327b For example, carbon atoms in organic compounds often have a sum of bond orders (SBOs) of approximately 4, because they have four electrons to share in covalent bonding. Therefore, in the above two studies, carbon atoms having abnormally low or abnormally high SBOs were flagged as misbonded. (A low carbon SBO might be caused by a missing hydrogen atom that was not reported in the crystal structure.) This kind of screening would have been much harder or perhaps infeasible without the above method to compute bond orders. Another important application of these bond orders is to understand changes that occur during chemical reactions. For example, several studies reported changes in these bond orders during catalytic reactions. Finally, last year an interesting paper explored correlations between these bond orders and crystal orbital Hamilton populations (a bond energy projection method): R.Y. Rohling, I.C. Tranca, E.J.M. Henen, and E.A. Pidko, "Correlations between density-based bond orders and orbital-based bond energies for chemical bonding analysis," J. Phys. Chem. C, 123 (2019) 2843-2854 DOI: 10.1021/acs.jpcc.8b08934 Within the same material class, the bond order between two specific chemical elements was shown to be proportional to the COHP. The bond order is easier to interpret than the COHP. An encouraging sign is this bond order method is starting to gain some traction in VASP and CP2K calculations (using the Chargemol code for post-processing), which going back >3 years bond order calculations using those codes were nearly unheard of. I believe the impact could be even much larger, which is why I'm reaching out to try to highlight some of the use cases for this method as well as to give you an opportunity to explain to me what aspects of the method you are having trouble understanding. Sincerely, Tom Manz --000000000000f9ae3205abb2e4cf Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable
Dear colleagues,

One of my graduate students is in = the process of preparing a YouTube video on the topic of computing bond ord= ers using the method introduced in the following paper:

T. A. Manz, = "Introducing DDEC6 atomic population analysis: part 3. Comprehensive m= ethod to compute bond orders," RSC Advances, 7 (2017) 45552-45581 (ope= n access) DOI: 10.1039/c7ra07400j

The video will be a less technical= presentation, emphasizing chemical concepts with less focus on mathematics= .

Were any of the concepts presented in the above paper unclear to y= ou? If so, could you please explain which of those concepts you did not und= erstand? If there is a pattern of some aspects being unclear, then I would = like to know so that it can be explained in a more understandable way.
<= br>If any of you have not taken the time to carefully read that paper, I be= lieve it would be worth your while to do so. Bond order is a foundational c= hemical concept that has wide-ranging impacts and numerous applications thr= oughout the chemical sciences. The above paper presents the first comprehen= sive and computationally efficient method to compute accurate bond orders a= cross an extremely wide range of material types.

This method to comp= ute bond orders enabled the first study of quantum-mechanically computed bo= nd orders for a large number of diatomic molecules:

T. Chen and T. A= . Manz, "Bond orders of the diatomic molecules," RSC Advances, 9 = (2019) 17072-17092 (open access) DOI: 10.1039/c9ra00974d

In this wor= k, bond orders were quantum-mechanically computed for 288 diatomic molecule= s and ions, which is >10 times the number of diatomics for which bond or= ders were quantum-mechanically computed in each prior work.

Because = diatomic molecules are the smallest molecules containing a chemical bond, t= hey are natural textbook examples for studying bond order. Therefore, I vie= w the accurate bond orders for diatomic molecules as foundational to chemic= al theory. Even among the diatomic molecules, there are many interesting ef= fects that you may not be familiar with yet. These can often provide insigh= ts that are helpful to understand larger materials with more atoms.

= In two recent papers, the above bond order method was applied to identify m= isbonded atoms in the experimentally-derived crystal structures of metal-or= ganic frameworks:

T. Chen and T. A. Manz, "Identifying misbonde= d atoms in the 2019 CoRE metal=E2=80=93organic framework database," RS= C Advances, 10 (2020) 26944-26951 (open access) DOI: 10.1039/d0ra02498h =C2= =A0

T. Chen and T. A. Manz, "A collection of forcefield precurs= ors for metal-organic frameworks," RSC Advances, 9 (2019) 36492-36507 = (open access) DOI: 10.1039/c9ra07327b

For example, carbon atoms in o= rganic compounds often have a sum of bond orders (SBOs) of approximately 4,= because they have four electrons to share in covalent bonding. Therefore, = in the above two studies, carbon atoms having abnormally low or abnormally = high SBOs were flagged as misbonded. (A low carbon SBO might be caused by a= missing hydrogen atom that was not reported in the crystal structure.) Thi= s kind of screening would have been much harder or perhaps infeasible witho= ut the above method to compute bond orders.

Another important applic= ation of these bond orders is to understand changes that occur during chemi= cal reactions. For example, several studies reported changes in these bond = orders during catalytic reactions.

Finally, last year an interesting= paper explored correlations between these bond orders and crystal orbital = Hamilton populations (a bond energy projection method):

R.Y. Rohling= , I.C. Tranca, E.J.M. Henen, and E.A. Pidko, "Correlations between den= sity-based bond orders and orbital-based bond energies for chemical bonding= analysis," J. Phys. Chem. C, 123 (2019) 2843-2854 DOI: 10.1021/acs.jp= cc.8b08934

Within the same material class, the bond order between tw= o specific chemical elements was shown to be proportional to the COHP. The = bond order is easier to interpret than the COHP.

An encouraging sign= is this bond order method is starting to gain some traction in VASP and CP= 2K calculations (using the Chargemol code for post-processing), which going= back >3 years bond order calculations using those codes were nearly unh= eard of.

I believe the impact could be even much larger, which is wh= y I'm reaching out to try to highlight some of the use cases for this m= ethod as well as to give you an opportunity to explain to me what aspects o= f the method you are having trouble understanding.

Sincerely,
Tom Manz
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