The Importance of Retrosynthesis in Organic Synthesis
Keywords:
Disconnections strategies, Organic synthesis, Retrosynthesis, Synthetic plan, Target molecule.1Abstract
The process of designing- an-effective synthesis plan for a target molecule remains a signifi1cant challenge in organic synthesis. Synthesis planning involves determining the steps to synthesize a desired molecule. Retrosynthesis, developed by Elias James Corey and recognized with a Nobel Prize in 1990, is a systematic approach that involves working backwards from- the target-molecule to identify the -starting materials-. Retrosynthetic analysis is a– valuable technique but requires a comprehensive understanding of chemical substances, compound classes, reactions, and reaction conditions. This understanding enables chemists to effectively plan and analyze the synthesis of the target molecule. Through analyzing the target molecule and identifying possible disconnections, chemists can think creatively and devise innovative solutions for complex synthetic problems. This article serves as an introduction to retrosynthesis, highlighting its importance and fundamental theoretical concepts (strategies) that can be combined to plan the synthesis of organic compounds.
References
N. C. Deno, H. G. Richey, J. S. Liu, D. N. Lincoln, J. O. Turner (1965) J. Am. Chem. Soc.. 87, 4533–4538.
E. J. Corey (1988) Retrosynthetic Thinking - Essentials and Examples. 17, 111–133.
J. Walker (2014) Retrosynthetic Analysis and Synthetic Planning Life's Perspectives. 1-33.
R. O. M. A. de Souza, L. S. M. Miranda, U. T. Bornscheuer (2017) A Retrosynthesis Approach for Biocatalysis in Organic Synthesis. 23(50), 12040–12063.
E. J. Corey (1988) Robert Robinson lecture. Retrosynthetic thinking - Essentials and examples. 17((April)), 111–133.
G. Fray (1983) The disconnection approaches. 7, 157 p..
D. Seyferth (1979) Organic chemistry. 205((4405)), 487–488. http://www.ncbi.nlm.nih.gov/pubmed/17758787
B. M. Trost (1991) Times to The Atom Economy A Search for Synthetic Efficiency. 254, 1471–1477. www.sciencemag.org
M. H. Todd (2005) Computer-aided organic synthesis. 34((3)), 247–266.
(1986) Synth. Org. Chem..
U. De Barcelona (2004) Design of Organic Synthesis Part I. Strategies.
F. Z. Dörwald (2006) Side Reactions in Organic Synthesis: A Guide to Successful Synthesis Design. 389 p..
S. Mondal (2021) Unit V: Synthon Approach and Retrosynthesis Applications. ((March)).
L. K. G. Ackerman-Biegasiewicz, D. M. Arias-Rotondo, K. F. Biegasiewicz, E. Elacqua, M. R. Golder, L. V. Kayser (2020) Organic Chemistry: A Retrosynthetic Approach to a Diverse Field. 6((11)), 1845–1850.
J. Wiley (2010) Designing Organic Syntheses. 30((50)), 16766–16776. http://www.ncbi.nlm.nih.gov/pubmed/21159948
R. Breinbauer (2013) Chemical Synthesis of Hormones, Pheromones and Other Bioregulators. 45((07)), 978–978.
(2007) Strategy of synthesis. 232–300.
P. P. Plehiers, C. W. Coley, H. Gao, F. H. Vermeire, M. R. Dobbelaere, C. V. Stevens (2020) Artificial Intelligence for Computer-Aided Synthesis in Flow: Analysis and Selection of Reaction Components. 2((August)).
E. J. Corey, W. Wipke Todd (1969) Computer-assisted design of complex organic syntheses. 166((3902)), 178–192.
M. B. Smith, J. March (2006) March's Advanced Organic Chemistry.
H Bromides Summary of First Semester Reactions Useful in Synthesis. 1–13.
E. J. Corey, X.-M. Cheng (1989) Structure-Based and Topological Strategies. 33–46 p.. [Internet]
J Wang, H Lundberg, S Asai, P Martín-Acosta, J. S. Chen, S Brown, W Farrell, R. G. Dushin, C. J. O'Donnell, A. S. Ratnayake, P Richardson, Z Liu, T Qin, D. G. Blackmond, P. S. Baran (2018) Kinetically Guided Radical-Based Synthesis of C(sp^3)–C(sp^3) Linkages on DNA. 115(28), E6404–E6410.
R. C. H. Oh, C Oh (1990) Unit III: Synthetic Approaches Retrosynthesis and Retrosynthetic Analysis; Terminologies used in Retrosynthesis. (2).
P. A. Wender, V. A. Verma, T. J. Paxton, T. H. Pillow (2008) Function-oriented synthesis, step economy, and drug design. 41(1), 40–49.
A. J. Waldman, T. L. Ng, P Wang, E. P. Balskus (2017) Heteroatom – Heteroatom Bond Formation in Natural Product Biosynthesis.
H Paulsen (1982) International Edition in English. 21(3), 155–173.
Umpolung Synthons - Planning Organic Syntheses Organic Chemistry.
J Alleva (2014) Strategies in Synthetic Planning: Modern Stylistic Points in Retrosynthetic Analysis.
D. A. Evans, J Bartroli, T. L. Shih (1981) Enantioselective Aldol Condensations. 2. Erythro-Selective Chiral Aldol Condensations via Boron Enolates. 103(8), 2127–2129.
J. M. Smith, S. J. Harwood, P. S. Baran (2018) Radical Retrosynthesis. 51(8), 1807–17.
S. W. M. Crossley, C Obradors, R. M. Martinez, R. A. Shenvi (2016) Mn-, Fe-, and Co-Catalyzed Radical Hydrofunctionalizations of Olefins. 116(15), 8912–9000.
T Ishii, K Ota, K Nagao, H Ohmiya (2019) N-Heterocyclic Carbene-Catalyzed Radical Relay Enabling Vicinal Alkylacylation of Alkenes. 141(36), 14073–7.
W Kong, C Yu, H An, Q Song (2018) Photoredox-Catalyzed Decarboxylative Alkylation of Silyl Enol Ethers to Synthesize Functionalized Aryl Alkyl Ketones. 20(2), 349–52.
M. C. Fu, R. Shang, B. Wang, Y. Fu (2019) Photocatalytic Decarboxylative Alkylations Mediated by Triphenylphosphine and Sodium Iodide. 363(6434), 1429–34.
G. Landelle, A. Panossian, S. Pazenok, J. P. Vors, F. R. Leroux (2013) Recent Advances in Transition Metal-Catalyzed Csp2-Monofluoro-, Difluoro-, Perfluoromethylation and Trifluoromethylthiolation. 9, 2476–536.
C. Bi, G. Che, D. Bao, W. Qiao, L. Sun, M. R. Collins (2018) Modular Radical Cross-Coupling with Sulfones Enables Access to sp^3-Rich (Fluoro)alkylated Scaffolds. 80(April), 75–80.
D. A. Pensak, E. J. Corey (1977) LHASA—Logic and Heuristics Applied to Synthetic Analysis. 1–32.
Z. Wang, W. Zhang, B. Liu (2021) Computational Analysis of Synthetic Planning: Past and Future. 39(11), 3127–43.
P. Murray-Rust, H. S. Rzepa (1999) Chemical Markup, XML, and the Worldwide Web. 1. Basic Principles. 39(6), 928–42.
G. L. Holliday, P. Murray-Rust, H. S. Rzepa (2006) Chemical markup, XML, and the world wide web. 6. CMLReact, an XML vocabulary for chemical reactions. 46(1), 145–57.
D. Rogers, M. Hahn (2010) Extended-Connectivity Fingerprints. 742–54.
S. Heller (2014) InChI – the worldwide chemical structure standard. 6(S1), 1–9.
C. W. Coley, W. H. Green, F. Jensen (2018) Machine Learning in Computer-Aided Synthesis Planning. 51(5), 1281–9.
R. Gómez-Bombarelli, J. N. Wei, D. Duvenaud, J. M. Hernández-Lobato, B. Sánchez-Lengeling, D. Sheberla (2018) Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules. 4(2), 268–76.
N. Schneider, D. M. Lowe, R. A. Sayle, G. A. Landrum (2015) Development of a novel fingerprint for chemical reactions and its application to large-scale reaction classification and similarity. 55(1), 39–53.
P. Carbonell, A. J. Jervis, C. J. Robinson, C. Yan, M. Dunstan, N. Swainston (2018) An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals. 1(1), 1–10.
S. Szymkuć, E. P. Gajewska, T. Klucznik, K. Molga, P. Dittwald, M. Startek (2016) Computer-Assisted Synthetic Planning: The End of the Beginning. 55, 5904–5937.
P Schwaller, T Gaudin, D Lányi, C Bekas, T Laino (2018) Found in Translation: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models. 9(28), 6091–8.
M. A. Kayala, P Baldi (2012) ReactionPredictor: Prediction of complex chemical reactions at the mechanistic level using machine learning. 52(10), 2526–2540.
A Bøgevig, H J Federsel, F Huerta, M G Hutchings, H Kraut, T Langer (2015) Route design in the 21st century: The IC SYNTH software tool as an idea generator for synthesis prediction. 19(2), 357–368.
E S Blurock (1990) Computer-Aided Synthesis Design at RISC-Linz: Automatic Extraction and Use of Reaction Classes. 30(4), 505–510.
C W Coley, L Rogers, W H Green, K F Jensen (2017) Computer-Assisted Retrosynthesis Based on Molecular Similarity. 3(12), 1237–1245.
M H S Segler, M P Waller (2017) Neural-Symbolic Machine Learning for Retrosynthesis and Reaction Prediction. 23(25), 5966–5971.
P Schwaller, T Laino, T Gaudin, P Bolgar, C A Hunter, C Bekas (2019) Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction. 5(9), 1572–1583.
C W Coley, W H Green, K F Jensen (2019) RDChiral: An RDKit Wrapper for Handling Stereochemistry in Retrosynthetic Template Extraction and Application. 59, 2529–2537.
H Dai, C Li, C W Coley, B Dai, L Song (2019) Retrosynthesis prediction with conditional graph logic network. 32(NeurIPS), 1–11.
K Lin, Y Xu, J Pei, L Lai (2020) Automatic retrosynthetic route planning using template-free models. 11(12), 3355–3364.
W Jin, C W Coley, R Barzilay, T Jaakkola (2017) Predicting organic reaction outcomes with weisfeiler-lehman network. 2017-Decem(Nips), 2608–2617.
V R Somnath, C Bunne, C W Coley, A Krause, R Barzilay (2021) Learning Graph Models for Retrosynthesis Prediction. 12(NeurIPS), 9405–9415.
C Yan, Q Ding, P Zhao, S Zheng, J Yang, Y Yu (2020) RetroXpert: Decompose retrosynthesis prediction like a chemist. 2020-Decem(NeurIPS).
B. Liu, B. Ramsundar, P. Kawthekar, J. Shi, J. Gomes, Q. Luu Nguyen, et al (2017) Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models. 3(10), 1103–1113.
I. Sutskever, O. Vinyals, Q. V. Le (2014) Sequence to sequence learning with neural networks. (January), 3104–31.
M. A. Kayala, C.-A. Azencott, J. H. Chen, P. Baldi (2011) Learning to Predict Chemical Reactions. 51, 2209–2222.
A. F. de Almeida, R. Moreira, T. Rodrigues (2019) Synthetic organic chemistry driven by artificial intelligence. 3(10), 589–604.
O. Engkvist, P. O. Norrby, N. Selmi, Y. H. Lam, Z. Peng, E. C. Sherer, et al (2018) Computational prediction of chemical reactions: current status and outlook. 23(6), 1203–1218.
F. Feng, L. Lai, J. Pei (2018) Computational chemical synthesis analysis and pathway design. 6(JUN).
J. Savage, A. Kishimoto, B. Buesser, E. Diaz-Aviles, C. Alzate (2017) Chemical reactant recommendation using a network of organic chemistry. 210–214.
D. Lowe (2018) AI Designs of organic synthesis. (29), 593.
T. Maimone, P. S. Baran (2005) Computer-Assisted Organic Synthesis (CAOS). 1–20.
T. Ching, D. S. Himmelstein, B. K. Beaulieu-Jones, A. A. Kalinin, B. T. Do, G. P. Way, et al (2018) Opportunities and obstacles for deep learning in biology and medicine. 15.
R. Konieczny, R. Idczak (2016) Mössbauer study of Fe-Re alloys prepared by mechanical alloying. 237(1), 1–8.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Authors and Global Journals Private Limited

This work is licensed under a Creative Commons Attribution 4.0 International License.
