MCDCalc: Markov Chain Molecular Descriptors Calculator for Medicinal Chemistry

Paula       Carracedo-Reboredo; Ramiro       Corona; Mikel       Martinez-Nunes; Carlos       Fernandez-Lozano; Georgia       Tsiliki; Haralambos       Sarimveis; Eider       Aranzamendi; Sonia       Arrasate; Nuria       Sotomayor; Esther       Lete; Cristian    Robert    Munteanu; Humbert       González-Díaz

Abstract

Aims: Cheminformatics models are able to predict different outputs (activity, property, chemical reactivity) in single molecules or complex molecular systems (catalyzed organic synthesis, metabolic reactions, nanoparticles, etc.).

Background: Cheminformatics models are able to predict different outputs (activity, property, chemical reactivity) in single molecules or complex molecular systems (catalyzed organic synthesis, metabolic reactions, nanoparticles, etc.).

Objective: Cheminformatics prediction of complex catalytic enantioselective reactions is a major goal in organic synthesis research and chemical industry. Markov Chain Molecular Descriptors (MCDs) have been largely used to solve Cheminformatics problems. There are different types of Markov chain descriptors such as Markov-Shannon entropies (Shk), Markov Means (Mk), Markov Moments (πk), etc. However, there are other possible MCDs that have not been used before. In addition, the calculation of MCDs is done very often using specific software not always available for general users and there is not an R library public available for the calculation of MCDs. This fact, limits the availability of MCMDbased Cheminformatics procedures.

Methods: We studied the enantiomeric excess ee(%)[Rcat] for 324 α-amidoalkylation reactions. These reactions have a complex mechanism depending on various factors. The model includes MCDs of the substrate, solvent, chiral catalyst, product along with values of time of reaction, temperature, load of catalyst, etc. We tested several Machine Learning regression algorithms. The Random Forest regression model has R2 > 0.90 in training and test. Secondly, the biological activity of 5644 compounds against colorectal cancer was studied.

Result: We developed very interesting model able to predict with Specificity and Sensitivity 70-82% the cases of preclinical assays in both training and validation series.

Conclusion: The work shows the potential of the new tool for computational studies in organic and medicinal chemistry.

Keywords: Molecular descriptors, Markov chains, Singular values, Online tool, R-script, Chiral catalyst, Enantioselectivity, α-Amidoalkylation reactions, Biological activity, Colorectal cancer.

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Graphical Abstract

[1] 
Diez-Alarcia, R.; Yáñez-Pérez, V.; Muneta-Arrate, I.; Arrasate, S.; Lete, E.; Meana, J.J.; González-Díaz, H. Big data challenges targeting proteins in gpcr signaling pathways; combining ptml-chembl models and [35s]gtpγs binding assays. ACS Chem. Neurosci.,  2019, 10(11), 4476-4491.
[http://dx.doi.org/10.1021/acschemneuro.9b00302] 
[2] 
Santana, R.; Zuluaga, R.; Gañan, P.; Arrasate, S.; Onieva, E.; Gonzalez-Diaz, H. Designing nanoparticle release systems for drug-vitamin cancer co-therapy with multiplicative perturbation-theory machine learning (PTML) models. Nanoscale,  2019, 3(45), 21811-21823.
[http://dx.doi.org/10.1039/c9nr05070a] 
[3] 
Santiago, C.B.; Guo, J.Y.; Sigman, M.S. Predictive and mechanistic multivariate linear regression models for reaction development. Chem. Sci.,  2018, 9(9), 2398-2412.
[http://dx.doi.org/10.1039/c7sc04679k] 
[4] 
Harper, K.C.; Bess, E.N.; Sigman, M.S. Multidimensional steric parameters in the analysis of asymmetric catalytic reactions. Nat. Chem.,  2012, 4(5), 366-374.
[http://dx.doi.org/10.1038/nchem.1297] 
[5] 
Harper, K.C.; Sigman, M.S. Using physical organic parameters to correlate asymmetric catalyst performance. J. Org. Chem.,  2013, 78(7), 2813-2818.
[http://dx.doi.org/10.1021/jo4002239] 
[6] 
Bess, E.N.; Bischoff, A.J.; Sigman, M.S.; Jacobsen, E.N. Designer substrate library for quantitative, predictive modeling of reaction performance. Proc. Natl. Acad. Sci. U.S.A,  2014, 111(41), 14698-14703.
[http://dx.doi.org/10.1073/pnas.1409522111] 
[7] 
Huang, H.; Zong, H.; Bian, G.; Song, L. Constructing a quantitative correlation between n-substituent sizes of chiral ligands and enantioselectivities in asymmetric addition reactions of diethylzinc with benzaldehyde. J. Org. Chem.,  2012, 77(22), 10427-10434.
[http://dx.doi.org/10.1021/jo3016715] 
[8] 
Huang, H.; Zong, H.; Shen, B.; Yue, H.; Bian, G.; Song, L. QSAR analysis of the catalytic asymmetric ethylation of ketone using physical steric parameters of chiral ligand substituents. Tetrahedron,  2014, 70(6), 1289-1297.
[http://dx.doi.org/10.1016/j.tet.2013.12.054] 
[9] 
Harper, K.C.; Sigman, M.S. Predicting and optimizing asymmetric catalyst performance using the principles of experimental design and steric parameters. Proc. Natl. Acad. Sci. U.S.A,  2011, 108(6), 2179-2183.
[http://dx.doi.org/10.1073/pnas.1013331108] 
[10] 
Harper, K.C.; Sigman, M.S. Three-dimensional correlation of steric and electronic free energy relationships guides asymmetric propargylation. Science,  2011, 333(6051), 1875-1878.
[http://dx.doi.org/10.1126/science.1206997] 
[11] 
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.,  2013, 135(7), 2482-2485.
[http://dx.doi.org/10.1021/ja4001807] 
[12] 
Munteanu, C.R.; Dorado, J.; Pazos-Sierra, A.; Prado-Prado, F.; Pérez-Montoto, L.G.; Vilar, S.; Ubeira, F.M.; Sanchez-Gonzaléz, A.; Cruz-Monteagudo, M.; Arrasate, S. Markov entropy centrality:
chemical, biological, crime, and legislative networks. In: towards
an information theory of complex networks: statistical methods and
applications; Dehmer, M.; Emmert-Streib, F.; Mehler, A., Eds.; Birkhäuser Boston: Boston, 2011; pp. 199-258.
[http://dx.doi.org/10.1007/978-0-8176-4904-3_9] 
[13] 
Zhang, C.; Santiago, C.B.; Crawford, J.M.; Sigman, M.S. Enantioselective dehydrogenative heck arylations of trisubstituted alkenes with indoles to construct quaternary stereocenters. J. Am. Chem. Soc.,  2015, 137(50), 15668-15671.
[http://dx.doi.org/10.1021/jacs.5b11335] 
[14] 
Zhang, C.; Santiago, C.B.; Kou, L.; Sigman, M.S. Alkenyl carbonyl derivatives in enantioselective redox relay heck reactions: accessing α,β-unsaturated systems. J. Am. Chem. Soc.,  2015, 137(23), 7290-7293.
[http://dx.doi.org/10.1021/jacs.5b04289] 
[15] 
Milo, A.; Neel, A.J.; Toste, F.D.; Sigman, M.S. A data-intensive approach to mechanistic elucidation applied to chiral anion catalysis. Science,  2015, 347(6223), 737-743.
[http://dx.doi.org/10.1126/science.1261043] 
[16] 
Park, Y.; Niemeyer, Z.L.; Yu, J.Q.; Sigman, M.S. Quantifying structural effects of amino acid ligands in pd(ii)-catalyzed enantioselective c-h functionalization reactions. Organometallics,  2018, 37(2), 203-210.
[http://dx.doi.org/10.1021/acs.organomet.7b00751] 
[17] 
Blázquez-Barbadillo, C.; Aranzamendi, E.; Coya, E.; Lete, E.; Sotomayor, N.; González-Díaz, H. Perturbation theory model of reactivity and enantioselectivity of palladium-catalyzed heck-heck cascade reactions. RSC Advances,  2016, 6(45), 38602-38610.
[http://dx.doi.org/10.1039/c6ra08751e] 
[18] 
Aguado-Ullate, S.; Urbano-Cuadrado, M.; Villalba, I.; Pires, E.; García, J.I.; Bo, C.; Carbó, J.J. Predicting the enantioselectivity of the copper-catalysed cyclopropanation of alkenes by using quantitative quadrant-diagram representations of the catalysts. Chem- A Eur. J.,  2012, 18(44), 14026-14036.
[http://dx.doi.org/10.1002/chem.201201135] 
[19] 
Huang, H.; Zong, H.; Bian, G.; Yue, H.; Song, L. Correlating the effects of the n-substituent sizes of chiral 1,2-amino phosphinamide ligands on enantioselectivities in catalytic asymmetric henry reaction using physical steric parameters. J. Org. Chem.,  2014, 79(20), 9455-9464.
[http://dx.doi.org/10.1021/jo500982j] 
[20] 
Riihimaki, M.; Hemminki, A.; Sundquist, J.; Hemminki, K. Patterns of metastasis in colon and rectal cancer. Sci. Rep.,  2016, 6, 1-9.
[http://dx.doi.org/10.1038/srep29765] 
[21] 
Jhanwar, B.; Sharma, V.; Singla, R.K.; Shrivastava, B. QSAR - hansch analysis and related approaches in drug design. Pharmacol. Online Newsl.,  2011, 1, 306-344.
[22] 
Riera-Fernández, I.; Martín-Romalde, R.; Prado-Prado, F.J.; Escobar, M.; Munteanu, C.R.; Concu, R.; Duardo-Sanchez, A.; González-Díaz, H. From QSAR models of drugs to complex networks: state-of-art review and introduction of new markov-spectral moments indices. Curr. Top. Med. Chem.,  2012, 8, 927-960.
[23] 
Hull, R.D.; Fluder, E.M.; Singh, S.B.; Nachbar, R.B.; Kearsley, S.K.; Sheridan, R.P. (LaSSI) and comparison to TOPOSIM. Society,  2001, 1185-1191.
[24] 
Aranzamendi, E.; Sotomayor, N.; Lete, E. Brønsted acid catalyzed enantioselective α-amidoalkylation in the synthesis of isoindoloisoquinolines. J. Org. Chem.,  2012, 77(6), 2986-2991.
[http://dx.doi.org/10.1021/jo3000223] 
[25] 
Aranzamendi, E.; Arrasate, S.; Sotomayor, N.; González-Díaz, H.; Lete, E. Chiral brønsted acid-catalyzed enantioselective α-amidoalkylation reactions: a joint experimental and predictive study. ChemistryOpen,  2016, 5(6), 540-549.
[http://dx.doi.org/10.1002/open.201600120] 
[26] 
Guo, Q.X.; Peng, Y.G.; Zhang, J.W.; Song, L.; Feng, Z.; Gong, L.Z. Highly enantioselective alkylation reaction of enamides by bronsted-acid catalysis. Org. Lett.,  2009, 11(20), 4620-4623.
[http://dx.doi.org/10.1021/ol901892s] 
[27] 
Xie, Y.; Zhao, Y.; Qian, B.; Yang, L.; Xia, C.; Huang, H. Enantioselective N-H functionalization of indoles with α,β- unsaturated γ-lactams catalyzed by chiral brønsted acids. Angew. Chem. Int. Ed.,  2011, 50(25), 5682-5686.
[http://dx.doi.org/10.1002/anie.201102046] 
[28] 
Yu, X.; Lu, A.; Wang, Y.; Wu, G.; Song, H.; Zhou, Z.; Tang, C. Chiral phosphoric acid catalyzed asymmetric friedel-crafts alkylation of indole with 3-hydroxyisoindolin-1-one: enantioselective synthesis of 3-indolyl-substituted isoindolin-1-ones. Eur. J. Org. Chem.,  2011, 2011(5), 892-897.
[http://dx.doi.org/10.1002/ejoc.201001408] 
[29] 
Guo, C.; Song, J.; Huang, J.Z.; Chen, P.H.; Luo, S.W.; Gong, L.Z. Core-Structure-Oriented Asymmetric Organocatalytic Substitution of 3-Hydroxyoxindoles: Application in the Enantioselective Total Synthesis of (+)-Folicanthine. Angew. Chem. Int. Ed.,  2012, 51(4), 1046-1050.
[http://dx.doi.org/10.1002/anie.201107079] 
[30] 
Yin, Q.; Wang, S.G.; You, S.L. Asymmetric synthesis of tetrahydro-β-carbolines via chiral phosphoric acid catalyzed transfer hydrogenation reaction. Org. Lett.,  2013, 15(11), 2688-2691.
[http://dx.doi.org/10.1021/ol400995c] 
[31] 
Courant, T.; Kumarn, S.; He, L.; Retailleau, P.; Masson, G. Chiral phosphoric acid-catalyzed enantioselective aza-friedel-crafts alkylation of indoles with γ-hydroxy-γ-lactams. Adv. Synth. Catal.,  2013, 355(5), 836-840.
[http://dx.doi.org/10.1002/adsc.201201008] 
[32] 
González-Díaz, H.; Pérez-Montoto, L.G.; Ubeira, F.M. Model for vaccine design by prediction of b-epitopes of iedb given perturbations in peptide sequence, in vivo process, experimental techniques, and source or host organisms. J. Immunol. Res.,  2014, 2014
[http://dx.doi.org/10.1155/2014/768515] 
[33] 
Gonzalez-Diaz, H.; Arrasate, S.; Gomez-SanJuan, A.; Sotomayor, N.; Lete, E.; Besada-Porto, L.; Ruso, J.M. General theory for multiple input-output perturbations in complex molecular systems. 1. linear qspr electronegativity models in physical, organic, and medicinal chemistry. Curr. Top. Med. Chem.,  2013, 13(14), 1713-1741.
[http://dx.doi.org/10.2174/1568026611313140011] 
[34] 
Martínez-Arzate, S.G.; Tenorio-Borroto, E.; Barbabosa Pliego, A.; Díaz-Albiter, H.M.; Vázquez-Chagoyán, J.C.; González-Díaz, H. PTML model for proteome mining of b-cell epitopes and theoretical-experimental study of bm86 protein sequences from colima, mexico. J. Proteome Res.,  2017, 16(11), 4093-4103.
[http://dx.doi.org/10.1021/acs.jproteome.7b00477] 
[35] 
Casanola-Martin, G.M.; Le-Thi-Thu, H.; Perez-Gimenez, F.; Marrero-Ponce, Y.; Merino-Sanjuan, M.; Abad, C.; Gonzalez-Diaz, H. Multi-output model with box-jenkins operators of quadratic indices for prediction of malaria and cancer inhibitors targeting ubiquitin- proteasome Pathway (UPP) proteins. Curr. Protein Pept. Sci.,  2016, 17(3), 220-227.
[http://dx.doi.org/10.2174/1389203717999160226173500] 
[36] 
Romero-Durán, F.J.; Alonso, N.; Yañez, M.; Caamaño, O.; García-Mera, X.; González-Díaz, H. Brain-inspired cheminformatics of drug-target brain interactome, synthesis, and assay of tvp1022 derivatives. Neuropharmacology,  2016, 103, 270-278.
[http://dx.doi.org/10.1016/j.neuropharm.2015.12.019] 
[37] 
Kleandrova, V.V.; Luan, F.; González-Díaz, H.; Ruso, J.M.; Speck-Planche, A.; Cordeiro, M.N.D.S. Computational tool for risk assessment of nanomaterials: novel qstr-perturbation model for simultaneous prediction of ecotoxicity and cytotoxicity of uncoated and coated nanoparticles under multiple experimental conditions. Environ. Sci. Technol.,  2014, 48(24), 14686-14694.
[http://dx.doi.org/10.1021/es503861x] 
[38] 
Luan, F.; Kleandrova, V.V.; González-Díaz, H.; Ruso, J.M.; Melo, A.; Speck-Planche, A.; Cordeiro, M.N.D.S. Computer-aided nanotoxicology: assessing cytotoxicity of nanoparticles under diverse experimental conditions by using a novel qstr-perturbation approach. Nanoscale,  2014, 6(18), 10623-10630.
[http://dx.doi.org/10.1039/c4nr01285b] 
[39] 
Alonso, N.; Caamaño, O.; Romero-Duran, F.J.; Luan, F.D.S.; Cordeiro, M.N.; Yañez, M.; González-Díaz, H.; García-Mera, X. Model for high-throughput screening of multitarget drugs in chemical neurosciences: synthesis, assay, and theoretic study of rasagiline carbamates. ACS Chem. Neurosci.,  2013, 4(10), 1393-1403.
[http://dx.doi.org/10.1021/cn400111n] 
[40] 
Hill, T.; Lewicki, P.; Lewicki, P. Statistics: methods and applications : a comprehensive reference for science, industry, and data mining; StatSoft, 2006. 
[41] 
Speckamp, W.N.; Moolenaar, M.J. New developments in the chemistry of n-acyliminium ions and related intermediates. Tetrahedron,  2000, 56(24), 3817-3856.
[http://dx.doi.org/10.1016/S0040-4020(00)00159-9] 
[42] 
Yazici, A.; Pyne, S.G. Intermolecular addition reactions of a-acyliminium ions (Part I). Synthesis (Stuttg),  2009, 3, 339-368.
[http://dx.doi.org/10.1055/s-0028-1083325] 
[43] 
Yazici, A.; Pyne, S.G. Intermolecular addition reactions of a-acyliminium ions (Part II). Synthesis (Stuttg),  2009, 4, 513-541.
[http://dx.doi.org/10.1055/s-0028-1083346] 
[44] 
Martínez-Estibalez, U.; Gõmez-Sanjuan, A.; García-Calvo, O.; Aranzamendi, E.; Lete, E.; Sotomayor, N. Strategies based on aryllithium and n-acyliminium ion cyclizations for the stereocontrolled synthesis of alkaloids and related systems. Eur. J. Org. Chem.,  2011, 20-21, 3610-3633.
[http://dx.doi.org/10.1002/ejoc.201100123] 
[45] 
Nielsen, T.E.; Meldal, M. Solid-phase synthesis of complex and pharmacologically interesting heterocycles. Curr. Opin. Drug Discov. Devel.,  2009, 12(6), 798-810.
[http://dx.doi.org/10.1002/chin.201019251] 
[46] 
Avendaño López, C.; de la Cuesta, E. Synthetic chemistry with n-acyliminium ions derived from piperazine-2,5-diones and related compounds. Curr. Org. Synth.,  2009, 6, 143-168.
[http://dx.doi.org/10.2174/157017909788167310] 
[47] 
Merad, J.; Lalli, C.; Bernadat, G.; Maury, J.; Masson, G. Enantioselective brønsted acid catalysis as a tool for the synthesis of natural products and pharmaceuticals. Chem - A Eur. J.,  2018, 24(16), 3925-3943.
[http://dx.doi.org/10.1002/chem.201703556] 
[48] 
Osante, I.; Collado, M.I.; Lete, E.; Sotomayor, N. Cheminform abstract: stereodivergent synthesis of hetero-fused isoquinolines by acyliminium and metalation methods. ChemInform,  2010, 33(13)
[http://dx.doi.org/10.1002/chin.200213151] 
[49] 
González-Temprano, I.; Osante, I.; Lete, E.; Sotomayor, N. Enantiodivergent synthesis of pyrrolo[2,1-α]isoquinolines based on diastereoselective parham cyclization and α-amidoalkylation reactions. J. Org. Chem.,  2004, 69(11), 3875-3885.
[http://dx.doi.org/10.1021/jo049672o] 
[50] 
Abdullah, M.N.; Arrasate, S.; Lete, E.; Sotomayor, N. Stereoselective synthesis of thiaerythrinanes based on an α-amidoalkylation/rcm approach. Tetrahedron,  2008, 64(7), 1323-1332.
[http://dx.doi.org/10.1016/j.tet.2007.11.053] 
[51] 
Lee, Y.S.; Alam, M.M.; Keri, R.S. Enantioselective reactions of n-acyliminium ions using chiral organocatalysts. Chem. An Asian J.,  2013, 8(12), 2906-2919.
[http://dx.doi.org/10.1002/asia.201300814] 
[52] 
Akiyama, T. Science of Synthesis: Asymmetric Organocatalysis. In: Bronsted Base and Acid Catalysts, and Additional Topics; List, B; Maruoka, K., Ed.; Georg Thieme Verlag: New York, 2012; pp. 169-217.
[53] 
Terada, M.; Momiyama, N. Asymmetric Organocatalysis. In: Brønsted Base and Acid Catalysts, and Additional Topics; Maruoka, K., Ed.; Georg Thieme VerlagL New York, 2012; Vol. 2, pp. 219-278.
[54] 
Dalpozzo, R. Strategies for the asymmetric functionalization of indoles: an update. Chem. Soc. Rev.,  2015, 44(3), 742-778.
[http://dx.doi.org/10.1039/c4cs00209a] 
[55] 
Akiyama, T. Stronger Bronsted Acids. Chem. Rev.,  2007, 107(12), 5744-5758.
[56] 
Akiyama, T.; Mori, K. Stronger Brønsted Acids: Recent Progress. Chem. Rev.,  2015, 115(17), 9277-9306.
[http://dx.doi.org/10.1021/acs.chemrev.5b00041] 
[57] 
Parmar, D.; Sugiono, E.; Raja, S.; Rueping, M. Complete field guide to asymmetric binol-phosphate derived brønsted acid and metal catalysis: history and classification by mode of activation; brønsted acidity, hydrogen bonding, ion pairing, and metal phosphates. Chem. Rev.,  2014, 114(18), 9047-9153.
[http://dx.doi.org/10.1021/cr5001496] 
[58] 
Parmar, D.; Sugiono, E.; Raja, S.; Rueping, M. Erratum: complete field guide to asymmetric binol-phosphate derived brønsted acid and metal catalysis: history and classification by mode of activation; brønsted acidity, hydrogen bonding, ion pairing, and metal phosphates (chemical reviews (2014) 114:18. Chem. Rev.,  2017, 117(15), 10608-10620.
[http://dx.doi.org/10.1021/acs.chemrev.7b00197] 
[59] 
Takemoto, Y. Recognition and activation by ureas and thioureas: stereoselective reactions using ureas and thioureas as hydrogen-bonding donors. Org. Biomol. Chem.,  2005, 3(24), 4299-4306.
[http://dx.doi.org/10.1039/b511216h] 
[60] 
Doyle, A.G.; Jacobsen, E.N. Small-molecule h-bond donors in asymmetric catalysis. Chem. Rev.,  2007, 107(12), 5713-5743.
[http://dx.doi.org/10.1021/cr068373r] 
[61] 
Knowles, R. R.; Jacobsen, E. N. Attractive noncovalent interactions in asymmetric catalysis: links between enzymes and small molecule catalysts. Proc. Natl. Acad. Sci.,  2010, 107(48), 20678 LP-20685.
[http://dx.doi.org/10.1073/pnas.1006402107] 
[62] 
Jakab, G.; Schreiner, P.R. Comprehensive Enantioselective Organocatalysis; Dalpozzo, R., Ed.; Wiley-VCH: Weinheim, 2013, Vol. 2, pp. 315-341.
[63] 
Terrasson, V.; De Figueiredo, R.M.; Campagne, J.M. Organocatalyzed Asymmetric Friedel-Crafts Reactions. Eur. J. Org. Chem.,  2010, 14, 2635-2655.
[http://dx.doi.org/10.1002/ejoc.200901492] 
[64] 
Zeng, M.; You, S.L. Asymmetric friedel-crafts alkylation of indoles: the control of enantio- and regioselectivity. Synlett,  2010, 9, 1289-1301.
[http://dx.doi.org/10.1055/s-0029-1219929] 
[65] 
de Figueiredo, R.M.; Campagne, J.M. Comprehensive Enantioselective Organocatalysis In: ; Dalko, P. I., Ed.; Wiley-VCH: Weinheim, 2013; 3, pp. 1043-1066.
[66] 
P. Beletskaya, I.; D. Averin, A. Asymmetric friedel-crafts reactions of indole and its derivatives. Curr. Organocatal.,  2015, 3(1), 60-83.
[http://dx.doi.org/10.2174/2213337202666150505230013] 
[67] 
Mazurkiewicz, R.; Październiok-Holewa, A.; Adamek, J.; Zielińska, K. α-Amidoalkylating Agents: Structure, Synthesis, Reactivity
and Application; Elsevier: Amsterdam,  2014. 
[http://dx.doi.org/10.1016/B978-0-12-420160-6.00002-1] 
[68] 
Marrero-Ponce, Y.; Siverio-Mota, D.; Gálvez-Llompart, M.; Recio, M.C.; Giner, R.M.; García-Domnech, R.; Torrens, F.; Arán, V.J.; Cordero-Maldonado, M.L.; Esguera, C.V. Discovery of novel anti-inflammatory drug-like compounds by aligning in silico and in vivo screening: the nitroindazolinone chemotype. Eur. J. Med. Chem.,  2011, 46(12), 5736-5753.
[http://dx.doi.org/10.1016/j.ejmech.2011.07.053] 
[69] 
Speck-Planche, A.; Cordeiro, M.N.D.S. Erratum to: Fragment-based in silico modeling of multi-target inhibitors against breast cancer-related proteins. Mol. Divers.,  2017, 21(3), 525.
[http://dx.doi.org/10.1007/s11030-017-9766-3] 
[70] 
Speck-Planche, A.; Cordeiro, M.N.D.S. Fragment-based in silico modeling of multi-target inhibitors against breast cancer-related proteins. Mol. Divers.,  2017, 21(3), 511-523.
[http://dx.doi.org/10.1007/s11030-017-9731-1] 
[71] 
Speck-Planche, A.; Kleandrova, V.V.; Luan, F.; Cordeiro, M.N.D.S. Unified multi-target approach for the rational in silico design of anti-bladder cancer agents. Anticancer. Agents Med. Chem.,  2013, 13(5), 791-800.
[http://dx.doi.org/10.2174/1871520611313050013] 
[72] 
Speck-Planche, A.V.; Kleandrova, V.; Luan, F.; Natalia, D.S.; Cordeiro, M. Chemoinformatics in multi-target drug discovery for anti-cancer therapy: in silico design of potent and versatile anti-brain tumor agents. Anticancer. Agents Med. Chem.,  2012, 12(6), 678-685.
[http://dx.doi.org/10.2174/187152012800617722] 
[73] 
Speck-Planche, A.; Kleandrova, V.V.; Luan, F.; Cordeiro, M.N.D.S. Rational drug design for anti-cancer chemotherapy: multi-target qsar models for the in silico discovery of anti-colorectal cancer agents. Bioorg. Med. Chem.,  2012, 20(15), 4848-4855.
[http://dx.doi.org/10.1016/j.bmc.2012.05.071] 
[74] 
Speck-Planche, A.; Kleandrova, V.V.; Luan, F.; Cordeiro, M.N.D.S. Chemoinformatics in anti-cancer chemotherapy: multi-target qsar model for the in silico discovery of anti-breast cancer agents. Eur. J. Pharm. Sci.,  2012, 47(1), 273-279.
[http://dx.doi.org/10.1016/j.ejps.2012.04.012] 
[75] 
D.S. Cordeiro, M. N.; Speck-Planche, A. Editorial: computer-aided drug design, synthesis and evaluation of new anti-cancer drugs. Curr. Top. Med. Chem.,  2012, 12(24), 2703-2704.
[http://dx.doi.org/10.2174/15680266112129990082] 
[76] 
Speck-Planche, A. Multiple perspectives in anti-cancer drug discovery: from old targets and natural products to innovative computational approaches. Anticancer. Agents Med. Chem.,  2019, 19(2), 146-147.
[http://dx.doi.org/10.2174/187152061902190418105054] 
[77] 
Speck-Planche, A.; Kleandrova, V.V.; Luan, F.; Cordeiro, M.N.D.S. Multi-target drug discovery in anti-cancer therapy: fragment-based approach toward the design of potent and versatile anti-prostate cancer agents. Bioorg. Med. Chem.,  2011, 19(21), 6239-6244.
[http://dx.doi.org/10.1016/j.bmc.2011.09.015] 

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DOI https://dx.doi.org/10.2174/1568026620666191226092431	Print ISSN 1568-0266
Publisher Name Bentham Science Publisher	Online ISSN 1873-4294

Current Topics in Medicinal Chemistry

MCDCalc: Markov Chain Molecular Descriptors Calculator for Medicinal Chemistry

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