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Using the Cambridge Structural Database to Introduce Important Inorganic Concepts
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Tiana V. Davis, M. Shahzad Zaveer, and Marc Zimmer* Chemistry Department, Connecticut College, New London, CT 06320; *
[email protected] Data and structure correlation analysis is an increasingly important area in science (1). This is particularly true in biology where genomic and proteonomic studies are generating vast amounts of data. In order to expose our students to chemoinformatics and introduce them to an important resource in chemistry, the Cambridge Structural Database, we have devised a simple series of inorganic exercises that can be done in introductory inorganic classes. The latest version of the Cambridge Structural Database (CSD), version 5.22, contains the CSD database with 245,392 structures, ConQuest (an interface to CSD), Mercury (a visualization program), Isostar (software for superimposing molecular fragments) and Vista (a statistics package designed for use with the CSD). CSD has 245,392 X-ray and neutron diffraction structures of organocarbon compounds (2, 3).1 All the compounds in the CSD have less than 1,000 atoms. Peptides with up to 24 residues are covered (4), while larger peptides and proteins are in the Protein Database.2 The CSD has 109,349 structures that contain one or more transition metal ions. Classroom ConQuest comes with a reduced database of 11,300 entries. Anyone with at least one normal ConQuest license can install as many copies of Classroom ConQuest as required.3 The CSD is a treasure trove of information that has been underutilized in teaching. More than 200 systematic structural correlations employing the CSD have been published. Many of these analyses have investigated inorganic complexes (5). There are numerous structures in the CSD that have a common backbone (e.g., porphyrins or 14-membered macrocycles), often referred to as congeneric families. Analyses
of congeneric families are useful as they can reveal the different backbone conformations the structure can adopt in the different crystals environments. These analyses, in turn, can provide information about conformations available to the backbone, interconversions of the conformers, and environmental factors responsible for certain conformations (6). The release of a new user-friendly graphics interface called ConQuest, easy to use tutorials, a Windows PC and Linux version, and a classroom edition have prompted us to develop some inorganic laboratory exercises utilizing the database. The purpose of these exercises is to expose the students to database analyses, and to demonstrate inorganic structural properties and structure correlation. Four example exercises are outlined below; all the structures used in the exercises are shown in Table 1. The exercises can be presented as open-ended discovery assignments or as more traditional problems. As the tutorials are complete, easy to understand, and instructive, the students need no assistance in doing ConQuest searches. The resultant data can easily be exported to Isostar, Vista, or Excel. Back-Bonding Pi-acceptor ligands that have empty orbitals with the correct symmetry to overlap with the filled dπ orbitals of metal ions can accept electron density from the metal. This interaction is called π back-bonding. For example, carbon monoxide has empty π* orbitals which can accept electron density from the filled metal d orbitals. Because the metal donates density to the empty carbon π* orbitals, the metal–carbon
Table 1. A List of All the Substructures Used in the Exercises Substructure
Hits
3D Parameters
Restrictions
Ru(CO)x
1239
Ru⫺C, C⬅O
Ru 6-coordinate
Ru(CO)1L5
123
Ru⫺C, C⬅O
Ru 6-coordinate, L ≠ organometallic
Ru(CO)2L4
275
Ru⫺C, C⬅O
Ru 6-coordinate, L ≠ organometallic
Ru(CO)3L3
350
Ru⫺C, C⬅O
Ru 6-coordinate, L ≠ organometallic
Ru(CO)4L2
192
Ru⫺C, C⬅O
Ru 6-coordinate, L ≠ organometallic
Ni(LN)
1062
Ni⫺N
Ni any coordinate, LN ligand binding through N(sp3)
Ni(LN)
672
Ni⫺N
Ni 6-coordinate, LN ligand binding through N(sp3)
Ni(LN)
246
Ni⫺N
Ni 4-coordinate, LN ligand binding through N(sp3)
Cp⫺Fe⫺Cp
35
none
none
Cp⫺V⫺Cp
51
none
none
CuN6
22
All 6 Cu⫺N
Cu bound to 6 N(sp3), Distance 1: Cu⫺Neq 0.00–2.14 Å, Distance 2: Cu⫺Nax 2.30–2.80 Å, Nax⫺Cu⫺Nax 170° ± 10°
Note: All searches discarded structures with R-factors greater than 0.10 or that were disordered or for which no coordinates were available.
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Journal of Chemical Education • Vol. 79 No. 10 October 2002 • JChemEd.chem.wisc.edu
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bond length will get shorter as the metal and ligand share more electron density. However, the carbon–oxygen bond length will increase with increasing back donation because the electrons are being placed in the π* orbitals of CO, which −O bond are antibonding. An analysis of the Ru–C and C= lengths in ruthenium–carbonyl complexes can be used to illustrate these effects or to serve as a starting point for a discovery assignment designed to conceptualize back-bonding. −O bond lengths substantiates A plot of the Ru–C versus C= an inverse correlation. Separate searches can be conducted for mono-, di-, tri-, and tetracarbonyl ruthenium complexes. All four sets of structures demonstrate that an increase in −O back-bonding results in a shorter Ru–C and longer C= bond lengths. Figure 1 shows the inverse relationship between −O bond lengths for the monocarbonyl– the Ru–C and C= ruthenium complexes. The correlation coefficients for all the plots discussed in this paper vary between ᎑.8 and ᎑.5. It is not surprising that the correlations are not much better since there are no restrictions on the identities of the ligands that are not part of the substructures being used in the CSD searches. In fact, it is surprising that the correlations are as good as they are, given the large differences in steric bulk of the ligands. In addition, a plot of the mean Ru–C distance for the mono-, di-, tri- and tetracarbonyl ruthenium complexes versus the number of carbonyl ligands shows an increase in the Ru–C distance (i.e., decrease in back-bonding) with each additional carbonyl ligand.
Search Hints To find monocarbonyl–ruthenium complexes draw a substructure with a six-coordinate ruthenium atom bound to carbon monoxide and five other ligands that are not organometallic (non-organometallic ligands are defined by draw → more → other elements → multipick → any → carbon).
Jahn–Teller Effect Copper(II), a d9 metal ion, has an orbitally degenerate ground state. The degeneracy can be removed by tetragonal distortion. This phenomenon is called the Jahn–Teller effect. There are 22 hexaammine copper(II) complexes in the CSD with a substantial Jahn–Teller distortion. All 22 complexes have two long axial bonds and four short equatorial bonds. Although Jahn–Teller distortions with two short axial bonds and four long equatorial bonds are theoretically possible, they are rarely found. A plot of the Cu–Naxial versus the Cu– Nequatorial distance shows a rough inverse correlation between the two distances.
Search Hints In order to find Jahn–Teller distorted copper(II) complexes, and to define the axial and equatorial ligands, a search was conducted for a copper ion bound to six nitrogen atoms that are each bound to three other atoms. One of the Cu–N distances was limited to be between 2.30 and 2.80 Å and another had to be between 0.00 and 2.14 Å. The nitrogen atom trans to the long Cu–N distance was chosen as the other axial ligand by defining the Naxial–Cu–Naxial angle as 170° ± 10°. High-Spin versus Low-Spin Nickel(II), a d8 system, can adopt both high-spin and low-spin forms. High-spin nickel(II) can adopt six-coordinate (octahedral), five-coordinate (trigonal-bipyramidal and square-pyramidal), and four-coordinate (tetrahedral) geometries; while low-spin complexes have been found in five-coordinate (trigonal-bipyramidal and square-pyramidal) and four-coordinate (square-planar) geometries. Crystal-field sta-
2.1
Ru-C Distance / Å
2.0
1.9
1.8
1.7
1.6 0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
C O Distance / Å Figure 1. Relationship between the ruthenium–carbon distance and the carbon–oxygen distance in 141 Ru(CO)1Lx complexes.
Figure 2. Distribution of the nickel–nitrogen distance in 1062 Ni(LN) complexes. Inset left: Nickel(II) low-spin complexes. Inset right: Nickel(II) high-spin complexes.
JChemEd.chem.wisc.edu • Vol. 79 No. 10 October 2002 • Journal of Chemical Education
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Information • Textbooks • Media • Resources
X θmean = 138°
θmean = 179°
V
Fe
X
an analogous search for a vanadium ion will find complexes in which the vanadium ion binds additional ligands in order to obtain an 18e count. The additional binding of ligands to the vanadium ion results in a bent complex. The mean angle between the centroids of the cyclopentadienyl rings and the metal is 179° for all the ferrocene complexes found in the CSD search, while it is 138° for all the vanadocenes (see Figure 3).
Search Hints The quickest way to draw ferrocenes is to choose the cyclopentadienyl anion (cp) from the groups menu and pi bond it to the metal ion. Figure 3. The Cp centroid-Fe-Cp centroid angles vary from 165º to 180º with a mean value of 179º, while the Cp centroid-V-Cp centroid angles vary from 131º to 180º with a mean value of 138º.
bilization-energy diagrams can be used to account for these coordination geometries. A plot of the nickel–nitrogen distances for all the structures, found in a search of compounds that have at least one sp3-hybridized nitrogen atom bound to a nickel ion, is bimodal (see Figure 2). The majority of Ni–N distances are between 2.02 and 2.20 Å; these are the high-spin complexes. The low-spin complexes have Ni–N distances between 1.83 and 2.10 Å and are slightly less common. This observation was confirmed by repeating the search while constraining the nickel ion to a six-coordinate geometry (high-spin). A mean distance of 2.117 Å was found. A similar search with a square-planar constrained nickel ion (low-spin) had a mean Ni–N(sp3) distance of 1.945 Å.
Search Hints Nitrogen atoms with sp3 hybridization were defined by requiring that the nitrogen atom was bound to a nickel ion as well three other atoms. Square-planar nickel(II) complexes were found by constraining the nickel ion to be four-coordinate and selecting only structures that have a L–Ni–N angle within 5° of 90°, where L could be any atom. Eighteen-Electron Rule Low-valent transition metal organometallic complexes that obey the eighteen-electron rule are stable species. Just as the octet rule is based on completely filling the valence s and p orbitals (8e), the eighteen-electron rule is based on completely filling the s, p, and d orbitals (18e). Ferrocene is an 18-electron complex, while its vanadium analog is a 15electron species. Consequently a search for an iron ion bound to two cyclopentadienyl anions will only find iron ion that is 5 bound to the two cyclopentadienyls. On the other hand
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Acknowledgments Marc Zimmer is a Henry Dreyfus Teacher Scholar. Tiana Davis was supported by the Howard Hughes Medical Institute Undergraduate Biological Sciences Education Program. W
Supplemental Material
A list of all the refcodes in the classroom ConQuest database are available in this issue of JCE Online. Notes 1. Non-organocarbon inorganic compounds are not listed in the CSD. 2. Protein Database, http://www.rcsb.org/pdb (accessed July 2002). 3. A list of national and regional CSD affiliates through which the CSD can be purchased is located at http://www.ccdc.cam.ac.uk/ conts/nac_list.html (accessed July 2002). The cost for a normal annual CSD license is $400 in the USA. Unix, Windows PC, and Linux versions are available.
Literature Cited 1. Gutterman, L. Chronicle Higher Educ. 2001, 47, A14. 2. Allen, F. H.; Davies, J. E.; Galloy, J. J.; Johnson, O.; Kennard, O.; Macrae, C. F.; Mitchell, E. M.; Mitchell, G. F.; Smith J. M.; Watson, D. G. J. Chem. Inf. Comput. Sci. 1991, 31, 187. 3. Allen F. H.; Kennard, O. Chem. Design Automation News 1993, 1, 31. 4. Bernstein, F. C.; Koetzle, T. F.; Williams, J. G. B.; Meyer, E. F.; Brice, M. R.; Rodgers, J. R.; Kennard, O.; Shimanouchi T.; Tasumi, M. J. Mol. Biol. 1977, 122, 535. 5. Zimmer, M. Coord. Chem. Rev. 2001, 212, 133. 6. Orpen, A. J. J.Chem. Soc., Dalton Trans. 1993, 1993, 191.
Journal of Chemical Education • Vol. 79 No. 10 October 2002 • JChemEd.chem.wisc.edu
