Abstract
The engineering of catalysts with desirable properties can be accelerated by computer-aided design. To achieve this aim, features of molecular catalysts can be condensed into numerical descriptors that can then be used to correlate reactivity and structure. Based on such descriptors, we have introduced topographic steric maps that provide a three-dimensional image of the catalytic pocket—the region of the catalyst where the substrate binds and reacts—enabling it to be visualized and also reshaped by changing various parameters. These topographic steric maps, especially when used in conjunction with density functional theory calculations, enable catalyst structural modifications to be explored quickly, making the online design of new catalysts accessible to the wide chemical community. In this Perspective, we discuss the application of topographic steric maps either to rationalize the behaviour of known catalysts—from synthetic molecular species to metalloenzymes—or to design improved catalysts.
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Code availability
The source code calculating buried volumes and steric maps is downloadable from the SambVca 2.1 web server, https://www.molnac.unisa.it/OMtools/sambvca2.1/index.html.
References
Chemistry for Tomorrow’s World (Royal Society of Chemistry, 2009); https://go.nature.com/31AWVup
Basic Research Needs for Catalysis Science (US Department of Energy, 2017); https://go.nature.com/2yU0iR1
Placzek, S. et al. BRENDA in 2017: new perspectives and new tools in BRENDA. Nucleic Acids Res. 45, D380–D388 (2017).
Porter, C. T., Bartlett, G. J. & Thornton, J. M. The catalytic site atlas: a resource of catalytic sites and residues identified in enzymes using structural data. Nucleic Acids Res. 32, D129–D133 (2004).
Neurath, H. Evolution of proteolytic enzymes. Science 224, 350–357 (1984).
Holzwarth, A., Schmidt, H.-W. & Maier, W. F. Detection of catalytic activity in combinatorial libraries of heterogeneous catalysts by IR thermography. Angew. Chem. Int. Ed. 37, 2644–2647 (1998).
Boussie, T. R. et al. A fully integrated high-throughput screening methodology for the discovery of new polyolefin catalysts: Discovery of a new class of high temperature single-site group (IV) copolymerization catalysts. J. Am. Chem. Soc. 125, 4306–4317 (2003).
Taylor, S. J. & Morken, J. P. Thermographic selection of effective catalysts from an encoded polymer-bound library. Science 280, 267–270 (1998).
Babin, V., Leforestier, C. & Paesani, F. Development of a “first principles” water potential with flexible monomers: Dimer potential energy surface, VRT spectrum, and second virial coefficient. J. Chem. Theory Comput. 9, 5395–5403 (2013).
Todeschini, R. & Viviana Consonni, V. Handbook of Molecular Descriptors (Wiley, 2000).
Foscato, M., Occhipinti, G., Venkatraman, V., Alsberg, B. K. & Jensen, V. R. Automated design of realistic organometallic molecules from fragments. J. Chem. Inf. Model. 54, 767–780 (2014).
Fey, N., Orpen, A. G. & Harvey, J. N. Building ligand knowledge bases for organometallic chemistry: Computational description of phosphorus(III)-donor ligands and the metal–phosphorus bond. Coord. Chem. Rev. 253, 704–722 (2009).
Fey, N. The contribution of computational studies to organometallic catalysis: Descriptors, mechanisms and models. Dalton Trans. 39, 296–310 (2010).
Hammett, L. P. The effect of structure upon the reactions of organic compounds. Benzene derivatives. J. Am. Chem. Soc. 59, 96–103 (1937).
Tolman, C. A. Steric effects of phosphorus ligands in organometallic chemistry and homogeneous catalysis. Chem. Rev. 77, 313–348 (1977).
Crabtree, R. H. The Organometallic Chemistry of the Transition Metals (Wiley, 2014).
Hansch, C., Leo, A. & Taft, R. W. A survey of Hammett substituent constants and resonance and field parameters. Chem. Rev. 91, 165–195 (1991).
Charton, M. & Charton, B. Steric effects. v. barriers to internal-rotation. J. Am. Chem. Soc. 97, 6472–6473 (1975).
Charton, M. Linear free-energy relationships. II. Proximity effects. Chem. Tech. 5, 245–255 (1975).
Verloop, A., Hoogenstraaten, W. & Tipker, J. Development and Application of New Steric Substituent Parameters in Drug Design, Vol. 7, 165–207 (Academic Press, 1976).
Verloop, A. The STERIMOL approach to drug design (Marcel Dekker, 1987).
Poater, A. et al. SambVca: A web application for the calculation of the buried volume of N-heterocyclic carbene ligands. Eur. J. Inorg. Chem. https://doi.org/10.1002/ejic.200801160 (2009).
Cavallo, L., Correa, A., Costabile, C. & Jacobsen, H. Steric and electronic effects in the bonding of N-heterocyclic ligands to transition metals. J. Organomet. Chem. 690, 5407–5413 (2005).
Poater, A. et al. Thermodynamics of N-heterocyclic carbene dimerization: The balance of sterics and electronics. Organometallics 27, 2679–2681 (2008).
Hillier, A. C. et al. A combined experimental and theoretical study examining the binding of N-heterocyclic carbenes (NHC) to the Cp*RuCl (Cp* = η5-C5Me5) moiety: insight into stereoelectronic differences between unsaturated and saturated NHC ligands. Organometallics 22, 4322–4326 (2003).
Billow, B. S., McDaniel, T. J. & Odom, A. L. Quantifying ligand effects in high-oxidation-state metal catalysis. Nat. Chem. 9, 837–842 (2017).
Wu, K. & Doyle, A. G. Parameterization of phosphine ligands demonstrates enhancement of nickel catalysis via remote steric effects. Nat. Chem. 9, 779–784 (2017).
Lipkowitz, K. B., D’Hue, C. A., Sakamoto, T. & Stack, J. N. Stereocartography: a computational mapping technique that can locate regions of maximum stereoinduction around chiral catalysts. J. Am. Chem. Soc. 124, 14255–14267 (2002).
Angermund, K. et al. Complexes (P2)Rh(hfacac) as model compounds for the fragment (P2)Rh and as highly active catalysts for CO2 hydrogenation: The accessible molecular surface (AMS) model as an approach to quantifying the intrinsic steric properties of chelating ligands in homogeneous catalysis. Chem. Eur. J. 3, 755–764 (1997).
Harper, K. C., Vilardi, S. C. & Sigman, M. S. Prediction of catalyst and substrate performance in the enantioselective propargylation of aliphatic ketones by a multidimensional model of steric effects. J. Am. Chem. Soc. 135, 2482–2485 (2013).
Harper, K. C. & Sigman, M. S. Using physical organic parameters to correlate asymmetric catalyst performance. J. Org. Chem. 78, 2813–2818 (2013).
Fischer, E. Einfluss der configuration auf die wirkung der enzyme. Berichte Deutsch. Chem. Gesell. 27, 2985–2993 (1894).
Pauling, L. & Corey, R. B. The structure of fibrous proteins of the collagen-gelatin group. Proc. Natl Acad. Sci. USA 37, 272–281 (1951).
Pauling, L., Corey, R. B. & Branson, H. R. The structure of proteins: Two hydrogen-bonded helical configurations of the polypeptide chain. Proc. Natl Acad. Sci. USA 37, 205–211 (1951).
Poater, A., Ragone, F., Mariz, R., Dorta, R. & Cavallo, L. Comparing the enantioselective power of steric and electrostatic effects in transition-metal-catalyzed asymmetric synthesis. Chem. Eur. J. 16, 14348–14353 (2010).
Falivene, L. et al. SambVca 2. A web tool for analyzing catalytic pockets with topographic steric maps. Organometallics 35, 2286–2293 (2016).
Liu, P., Montgomery, J. & Houk, K. N. Ligand steric contours to understand the effects of N-heterocyclic carbene ligands on the reversal of regioselectivity in Ni-catalyzed reductive couplings of alkynes and aldehydes. J. Am. Chem. Soc. 133, 6956–6959 (2011).
Wang, H. et al. NHC ligands tailored for simultaneous regio- and enantiocontrol in Nickel-catalyzed reductive couplings. J. Am. Chem. Soc. 139, 9317–9324 (2017).
Yoon, T. P. & Jacobsen, E. N. Privileged chiral catalysts. Science 299, 1691–1693 (2003).
Weinstein, C. M. et al. Highly ambiphilic room temperature stable six-membered cyclic (alkyl)(amino)carbenes. J. Am. Chem. Soc. 140, 9255–9260 (2018).
Zhang, W. et al. Electron-rich metal cations enable synthesis of high molecular weight, linear functional polyethylenes. J. Am. Chem. Soc. 140, 8841–8850 (2018).
Deng, L., Woo, T. K., Cavallo, L., Margl, P. M. & Ziegler, T. The role of bulky substituents in Brookhart-type Ni(II) diimine catalyzed olefin polymerization: a combined density functional theory and molecular mechanics study. J. Am. Chem. Soc. 119, 6177–6186 (1997).
Talarico, G., Busico, V. & Cavallo, L. “Living” propene polymerization with bis(phenoxyimine) group 4 metal catalysts: New strategies and old concepts. Organometallics 23, 5989–5993 (2004).
Schwizer, F. et al. Artificial metalloenzymes: reaction scope and optimization strategies. Chem. Rev. 118, 142–231 (2018).
Rothlisberger, D. et al. Kemp elimination catalysts by computational enzyme design. Nature 453, 190–195 (2008).
Choroba, O. W., Williams, D. H. & Spencer, J. B. Biosynthesis of the vancomycin group of antibiotics: involvement of an unusual dioxygenase in the pathway to (S)-4-hydroxyphenylglycine. J. Am. Chem. Soc. 122, 5389–5390 (2000).
Hubbard, B. K., Thomas, M. G. & Walsh, C. T. Biosynthesis of L-p-hydroxyphenylglycine, a non-proteinogenic amino acid constituent of peptide antibiotics. Chem. Biol. 7, 931–942 (2000).
Pratter, S. M. et al. Inversion of enantioselectivity of a mononuclear non-heme iron(II)-dependent hydroxylase by tuning the interplay of metal-center geometry and protein structure. Angew. Chem. Int. Ed. 52, 9677–9681 (2013).
Brownlee, J., He, P., Moran, G. R. & Harrison, D. H. Two roads diverged: the structure of hydroxymandelate synthase from amycolatopsis orientalis in complex with 4-hydroxymandelate. Biochem. 47, 2002–2013 (2008).
Zahrt, A. F. et al. Prediction of higher-selectivity catalysts by computer-driven workflow and machine learning. Science 363, eaau5631 (2019).
Falivene, L. et al. SambVca 2. A web tool for analyzing catalytic pockets with topographic steric maps. Organometallics 35, 2286–2293 (2016).
GNU v.3 (Free Software Foundation, 2007).
Hubbard, S. J., Campbell, S. F. & Thornton, J. M. Molecular recognition: conformational analysis of limited proteolytic sites and serine proteinase protein inhibitors. J. Mol. Biol. 220, 507–530 (1991).
Hostaš, J. & Řezáč, J. Accurate DFT-D3 calculations in a small basis set. J. Chem. Theory Comput. 13, 3575–3585 (2017).
Brandenburg, J. G., Bannwarth, C., Hansen, A. & Grimme, S. B97-3c: A revised low-cost variant of the B97-D density functional method. J. Chem. Phys. 148, 064104 (2018).
Bannwarth, C., Ehlert, S. & Grimme, S. GFN2-xTB—an accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions. J. Chem. Theory Comput. 15, 1652–1671 (2019).
Mühlbach, A. H., Vaucher, A. C. & Reiher, M. Accelerating wave function convergence in interactive quantum chemical reactivity studies. J. Chem. Theory Comput. 12, 1228–1235 (2016).
Wu, D., Rosen, D. W., Wang, L. & Schaefer, D. Cloud-based design and manufacturing: a new paradigm in digital manufacturing and design innovation. Comput. Aided Des. 59, 1–14 (2015).
Santiago, C. B., Guo, J.-Y. & Sigman, M. S. Predictive and mechanistic multivariate linear regression models for reaction development. Chem. Sci. 9, 2398–2412 (2018).
Sigman, M. S., Harper, K. C., Bess, E. N. & Milo, A. The development of multidimensional analysis tools for asymmetric catalysis and beyond. Acc. Chem. Res. 49, 1292–1301 (2016).
Harper, K. C. & Sigman, M. S. Three-dimensional correlation of steric and electronic free energy relationships guides asymmetric propargylation. Science 333, 1875–1878 (2011).
Ahneman, D. T., Estrada, J. G., Lin, S., Dreher, S. D. & Doyle, A. G. Predicting reaction performance in C–N cross-coupling using machine learning. Science 360, 186–190 (2018).
Acknowledgements
L.C. thanks the King Abdullah University of Science and Technology (KAUST). This research used resources of the Core Labs and of the KAUST Supercomputing Laboratory. A.P. is a Serra Húnter fellow and thanks the Spanish MICINN for the project PGC2018-097722-B-I00. R.O. thanks University Parthenope ‘Finanziamento per il Sostegno alla Ricerca Individuale di Ateneo – Annualità 2017’ for funding.
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L.C. conceived and designed the project. L.F. and A.P. provided the DFT calculations and the buried volume and steric maps analyses. Z.C. wrote the SambVca source code. R.O. provided the analysis of the biomolecules. A.P., L.S. and V.S designed and implemented the SambVca web application. All authors contributed to the discussion, L.C. and R.O. wrote the manuscript and all authors commented on the manuscript.
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Falivene, L., Cao, Z., Petta, A. et al. Towards the online computer-aided design of catalytic pockets. Nat. Chem. 11, 872–879 (2019). https://doi.org/10.1038/s41557-019-0319-5
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DOI: https://doi.org/10.1038/s41557-019-0319-5
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