Skip to main content
SpringerLink
Log in

The Brazilian compound library (BraCoLi) database: a repository of chemical and biological information for drug design

  • Short Communication
  • Published:
Molecular Diversity Aims and scope Submit manuscript

Abstract

The Brazilian Compound Library (BraCoLi) is a novel open access and manually curated electronic library of compounds developed by Brazilian research groups to support further computer-aided drug design works, available on https://www.farmacia.ufmg.br/qf/downloads/. Herein, the first version of the database is described comprising 1176 compounds. Also, the chemical diversity and drug-like profiles of BraCoLi were defined to analyze its chemical space. A significant amount of the compounds fitted Lipinski and Veber’s rules, alongside other drug-likeness properties. A comparison using principal component analysis showed that BraCoLi is similar to other databases (FDA-approved drugs and NuBBEDB) regarding structural and physicochemical patterns. Furthermore, a scaffold analysis showed that BraCoLi presents several privileged chemical skeletons with great diversity. Despite the similar distribution in the structural and physicochemical spaces, Tanimoto coefficient values indicated that compounds present in the BraCoLi are generally different from the two other databases, where they showed different kernel distributions and low similarity. These facts show an interesting innovative aspect, which is a desirable feature for novel drug design purposes.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. Lin X, Li X, Lin X (2020) A review on applications of computational methods in drug screening and design. Molecules 25:1375. https://doi.org/10.3390/molecules25061375

    Article  CAS  PubMed Central  Google Scholar 

  2. Zhao L, Ciallella HL, Aleksunes LM, Zhu H (2020) Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling. Drug Discov Today 25:1624–1638. https://doi.org/10.1016/j.drudis.2020.07.005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Ferreira LLG, Andricopulo AD (2018) Chemoinformatics approaches to structure- and ligand-based drug design. Front Pharmacol. https://doi.org/10.3389/fphar.2018.01416

    Article  PubMed  PubMed Central  Google Scholar 

  4. Shoichet BK (2004) Virtual screening of chemical libraries. Nature 432:862–865. https://doi.org/10.1038/nature03197

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Brown N, Ertl P, Lewis R et al (2020) Artificial intelligence in chemistry and drug design. J Comput Aided Mol Des 34:709–715. https://doi.org/10.1007/s10822-020-00317-x

    Article  CAS  PubMed  Google Scholar 

  6. Nicola G, Liu T, Gilson MK (2012) Public domain databases for medicinal chemistry. J Med Chem 55:6987–7002. https://doi.org/10.1021/jm300501t

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Bajorath J (2016) Extending accessible chemical space for the identification of novel leads. Expert Opin Drug Discov 11:825–829. https://doi.org/10.1080/17460441.2016.1210126

    Article  PubMed  Google Scholar 

  8. Zhao L, Wang W, Sedykh A, Zhu H (2017) Experimental errors in QSAR modeling sets: what we can do and what we cannot do. ACS Omega 2:2805–2812. https://doi.org/10.1021/acsomega.7b00274

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Anuraj N (2020) Experimental and computational approaches to improve binding affinity in chemical biology and drug discovery. Curr Top Med Chem 20:1651–1660

    Article  Google Scholar 

  10. Martinez-Mayorga K, Madariaga-Mazon A, Medina-Franco JL, Maggiora G (2020) The impact of chemoinformatics on drug discovery in the pharmaceutical industry. Exp Opin Drug Discov 15:293–306. https://doi.org/10.1080/17460441.2020.1696307

    Article  CAS  Google Scholar 

  11. Fourches D, Muratov E, Tropsha A (2010) Trust, but verify: on the importance of chemical structure curation in cheminformatics and QSAR modeling research. J Chem Inf Model 50:1189–1204. https://doi.org/10.1021/ci100176x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hawkins PCD, Skillman AG, Warren GL et al (2010) Conformer generation with OMEGA: algorithm and validation using high quality structures from the protein databank and cambridge structural database. J Chem Inf Model 50:572–584. https://doi.org/10.1021/ci100031x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Halgren TA (1999) MMFF VI. MMFF94s option for energy minimization studies. J Comput Chem 20:720–729. https://doi.org/10.1002/(SICI)1096-987X(199905)20:7%3c720::AID-JCC7%3e3.0.CO;2-X

    Article  CAS  PubMed  Google Scholar 

  14. Yap CW (2011) PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints. J Comput Chem 32:1466–1474. https://doi.org/10.1002/jcc.21707

    Article  CAS  PubMed  Google Scholar 

  15. Sander T, Freyss J, von Korff M, Rufener C (2015) DataWarrior: an open-source program for chemistry aware data visualization and analysis. J Chem Inf Model 55:460–473. https://doi.org/10.1021/ci500588j

    Article  CAS  PubMed  Google Scholar 

  16. de Oliveira RB, Vaz ABM, Alves RO et al (2006) Arylfurans as potential trypanosoma cruzi trypanothione reductase inhibitors. Mem Inst Oswaldo Cruz 101:169–173. https://doi.org/10.1590/s0074-02762006000200009

    Article  PubMed  Google Scholar 

  17. de Oliveira RB, de Souza-Fagundes EM, Siqueira HAJ et al (2006) Synthesis and evaluation of cytotoxic activity of arylfurans. Eur J Med Chem 41:756–760. https://doi.org/10.1016/j.ejmech.2006.03.010

    Article  CAS  PubMed  Google Scholar 

  18. de Oliveira RB, Zani CL, Ferreira RS et al (2008) Síntese, avaliação biológica e modelagem molecular de arilfuranos como inibidores da enzima tripanotiona redutase. Quím Nova 31:261–267. https://doi.org/10.1590/S0100-40422008000200013

    Article  Google Scholar 

  19. de Oliveira RB, de Souza-Fagundes EM, Soares RPP et al (2008) Synthesis and antimalarial activity of semicarbazone and thiosemicarbazone derivatives. Eur J Med Chem 43:1983–1988. https://doi.org/10.1016/j.ejmech.2007.11.012

    Article  CAS  PubMed  Google Scholar 

  20. Lopes MS, de Souza Pietra RCC, Borgati TF et al (2011) Synthesis and evaluation of the anti parasitic activity of aromatic nitro compounds. Eur J Med Chem 46:5443–5447. https://doi.org/10.1016/j.ejmech.2011.09.002

    Article  CAS  PubMed  Google Scholar 

  21. Braga SFP, Alves ÉVP, Ferreira RS et al (2014) Synthesis and evaluation of the antiparasitic activity of bis-(arylmethylidene) cycloalkanones. Eur J Med Chem 71:282–289. https://doi.org/10.1016/j.ejmech.2013.11.011

    Article  CAS  PubMed  Google Scholar 

  22. Lopes MS, de Camila F, AS, Bruno LS, et al (2015) Synthesis of nitroaromatic compounds as potential anticancer agents. Anticancer Agents Med Chem 15:206–216

    Article  CAS  PubMed  Google Scholar 

  23. Pereira de Sá N, Lino CI, Fonseca NC et al (2015) Thiazole compounds with activity against Cryptococcus gattii and Cryptococcus neoformans in vitro. Eur J Med Chem 102:233–242. https://doi.org/10.1016/j.ejmech.2015.07.032

    Article  CAS  PubMed  Google Scholar 

  24. de Sá NP, de Lima CM, Lino CI et al (2017) Heterocycle thiazole compounds exhibit antifungal activity through increase in the production of reactive oxygen species in the cryptococcus neoformans-cryptococcus gattii species complex. Antimicrob Agents Chemother. https://doi.org/10.1128/AAC.02700-16

    Article  PubMed  PubMed Central  Google Scholar 

  25. Cruz LIB, Lopes LFF, De Camargo RF et al (2018) Anti-Candida albicans activity of thiazolylhydrazone derivatives in invertebrate and murine models. J Fungi 4:134. https://doi.org/10.3390/jof4040134

    Article  CAS  Google Scholar 

  26. Sá NP, Pôssa AP, Pilar P et al (2019) Antifungal activity directed toward the cell wall by 2-Cyclohexylidenhydrazo- 4-Phenyl-thiazole against candida albicans. Infect Disord Drug Targets 19:428–438

    Article  PubMed  Google Scholar 

  27. Lino CI, Gonçalves de Souza I, Borelli BM et al (2018) Synthesis, molecular modeling studies and evaluation of antifungal activity of a novel series of thiazole derivatives. Eur J Med Chem 151:248–260. https://doi.org/10.1016/j.ejmech.2018.03.083

    Article  CAS  PubMed  Google Scholar 

  28. Sá NP, Lima CM, dos Santos AJR et al (2018) A phenylthiazole derivative demonstrates efficacy on treatment of the cryptococcosis & candidiasis in animal models. Fut Sci OA. https://doi.org/10.4155/fsoa-2018-0001

    Article  Google Scholar 

  29. de Sá NP, de Barros PP, Junqueira JC et al (2019) Thiazole derivatives act on virulence factors of Cryptococcus spp. Med Mycol 57:84–91. https://doi.org/10.1093/mmy/myx158

    Article  CAS  PubMed  Google Scholar 

  30. de Sá NP, de Barros PP, Junqueira JC et al (2021) Antivirulence activity and in vivo efficacy of a thiazole derivative against candidiasis. J Med Mycol 31:101134. https://doi.org/10.1016/j.mycmed.2021.101134

    Article  Google Scholar 

  31. Franco PHC, Braga SFP, de Oliveira RB, César IC (2020) Purity determination of a new antifungal drug candidate using quantitative 1H NMR spectroscopy: method validation and comparison of calibration approaches. Magn Reson Chem 58:97–105. https://doi.org/10.1002/mrc.4936

    Article  CAS  PubMed  Google Scholar 

  32. Silva IR, Braga AV, de Gloria MBA et al (2020) Preclinical pharmacokinetic study of a new thiazolyl hydrazone derivative with antifungal activity in mice plasma by LC-MS/MS. J Chromatogr B 1149:122180. https://doi.org/10.1016/j.jchromb.2020.122180

    Article  CAS  Google Scholar 

  33. Tonholo DR, Maltarollo VG, Kronenberger T et al (2020) Preclinical toxicity of innovative molecules: in vitro, in vivo and metabolism prediction. Chem Biol Interact 315:108896. https://doi.org/10.1016/j.cbi.2019.108896

    Article  CAS  PubMed  Google Scholar 

  34. Franco PHC, Vieira JG, de Ramos CAO et al (2021) Stability-indicating method for the novel antifungal compound RI76: characterization and in vitro antifungal activity of its active degradation product. Biomed Chromatogr 35:e5014. https://doi.org/10.1002/bmc.5014

    Article  CAS  PubMed  Google Scholar 

  35. Silva IR, Kronenberger T, Gomes ECL et al (2021) Improving the solubility of an antifungal thiazolyl hydrazone derivative by cyclodextrin complexation. Eur J Pharm Sci 156:105575. https://doi.org/10.1016/j.ejps.2020.105575

    Article  CAS  PubMed  Google Scholar 

  36. Serafim MSM, Lavorato SN, Kronenberger T et al (2019) Antibacterial activity of synthetic 1,3-bis(aryloxy)propan-2-amines against Gram-positive bacteria. MicrobiologyOpen 8:e814. https://doi.org/10.1002/mbo3.814

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Lana DFD, Lavorato SN, Giuliani LM et al (2020) Discovery of a novel and selective fungicide that targets fungal cell wall to treat dermatomycoses: 1,3-bis(3,4-dichlorophenoxy)propan-2-aminium chloride. Mycoses 63:197–211. https://doi.org/10.1111/myc.13027

    Article  CAS  Google Scholar 

  38. Lavorato SN, Duarte MC, Lage DP et al (2017) 1,3-Bis(aryloxy)propan-2-ols as potential antileishmanial agents. Chem Biol Drug Des 90:981–986. https://doi.org/10.1111/cbdd.13024

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Lavorato SN, Duarte MC, Lage DP et al (2017) Synthesis and antileishmanial activity of 1,3-bis(aryloxy)propan-2-amines. Med Chem Res 26:1052–1072. https://doi.org/10.1007/s00044-017-1805-1

    Article  CAS  Google Scholar 

  40. Lavorato SN, Sales Júnior PA, Murta SMF et al (2015) In vitro activity of 1,3-bisaryloxypropanamines against Trypanosoma cruzi-infected L929 cultures. Mem Inst Oswaldo Cruz 110:566–568. https://doi.org/10.1590/0074-02760150007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Dalla Lana DF, Kaminski TFA, Lavorato SN et al (2021) In vitro pharmacokinetics/pharmacodynamics modeling and efficacy against systemic candidiasis in Drosophila melanogaster of a bisaryloxypropanamine derivative. Med Mycol 59:58–66. https://doi.org/10.1093/mmy/myaa030

    Article  CAS  PubMed  Google Scholar 

  42. Coelho EAF, Alves RJ, Romanha AJ, Lavorato SN (2014) Diarilaminas, composições farmacêuticas contendo as diarilaminas e usos

  43. Asse Junior LR, Kronenberger T, Magalhães Serafim MS et al (2019) Virtual screening of antibacterial compounds by similarity search of Enoyl-ACP reductase (FabI) inhibitors. Future Med Chem 12:51–68. https://doi.org/10.4155/fmc-2019-0158

    Article  CAS  PubMed  Google Scholar 

  44. Shultz MD (2019) Two decades under the influence of the rule of five and the changing properties of approved oral drugs. J Med Chem 62:1701–1714. https://doi.org/10.1021/acs.jmedchem.8b00686

    Article  CAS  PubMed  Google Scholar 

  45. Moriguchi I, Hirono S, Nakagome I, Hirano H (1994) Comparison of reliability of log P values for drugs calculated by several methods. Chem Pharm Bull 42:976–978. https://doi.org/10.1248/cpb.42.976

    Article  CAS  Google Scholar 

  46. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings1PII of original article: S0169–409X(96), 00423–1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3–25.1. Adv Drug Deliv Rev 46:3–26. https://doi.org/10.1016/S0169-409X(00)00129-0

    Article  CAS  PubMed  Google Scholar 

  47. Veber DF, Johnson SR, Cheng H-Y et al (2002) Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem 45:2615–2623. https://doi.org/10.1021/jm020017n

    Article  CAS  PubMed  Google Scholar 

  48. Ghose AK, Viswanadhan VN, Wendoloski JJ (1999) A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. J Comb Chem 1:55–68. https://doi.org/10.1021/cc9800071

    Article  CAS  PubMed  Google Scholar 

  49. Muegge I, Heald SL, Brittelli D (2001) Simple selection criteria for drug-like chemical matter. J Med Chem 44:1841–1846. https://doi.org/10.1021/jm015507e

    Article  CAS  PubMed  Google Scholar 

  50. Lipinski CA (2004) Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol 1:337–341. https://doi.org/10.1016/j.ddtec.2004.11.007

    Article  CAS  PubMed  Google Scholar 

  51. Pathania S, Singh PK (2020) Analyzing FDA-approved drugs for compliance of pharmacokinetic principles: should there be a critical screening parameter in drug designing protocols? Expert Opinion on Drug Metabolism & Toxicology 0:1–4. In press. https://doi.org/10.1080/17425255.2021.1865309

  52. Varma MVS, Obach RS, Rotter C et al (2010) Physicochemical space for optimum oral bioavailability: contribution of human intestinal absorption and first-pass elimination. J Med Chem 53:1098–1108. https://doi.org/10.1021/jm901371v

    Article  CAS  PubMed  Google Scholar 

  53. Giordanetto F, Kihlberg J (2014) Macrocyclic drugs and clinical candidates: What can medicinal chemists learn from their properties? J Med Chem 57:278–295. https://doi.org/10.1021/jm400887j

    Article  CAS  PubMed  Google Scholar 

  54. Lipinski CA (2016) Rule of five in 2015 and beyond: target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions. Adv Drug Deliv Rev 101:34–41. https://doi.org/10.1016/j.addr.2016.04.029

    Article  CAS  PubMed  Google Scholar 

  55. Furukawa A, Schwochert J, Pye CR et al (2020) Drug-like properties in macrocycles above MW 1000: backbone rigidity versus side-chain lipophilicity. Angew Chem 132:21755–21761. https://doi.org/10.1002/ange.202004550

    Article  Google Scholar 

  56. Protti ÍF, Rodrigues DR, Fonseca SK et al (2021) Do Drug-likeness rules apply to oral prodrugs? Chem Med Chem. https://doi.org/10.1002/cmdc.202000805

    Article  PubMed  Google Scholar 

  57. Jampilek J (2019) Heterocycles in medicinal chemistry. Molecules 24:3839. https://doi.org/10.3390/molecules24213839

    Article  CAS  PubMed Central  Google Scholar 

  58. Irwin JJ, Tang KG, Young J et al (2020) ZINC20—a free ultralarge-scale chemical database for ligand discovery. J Chem Inf Model 60:6065–6073. https://doi.org/10.1021/acs.jcim.0c00675

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Kim S, Chen J, Cheng T et al (2021) PubChem in 2021: new data content and improved web interfaces. Nucl Acids Res 49:D1388–D1395. https://doi.org/10.1093/nar/gkaa971

    Article  CAS  PubMed  Google Scholar 

  60. Davies M, Nowotka M, Papadatos G et al (2015) ChEMBL web services: streamlining access to drug discovery data and utilities. Nucl Acids Res 43:W612–W620. https://doi.org/10.1093/nar/gkv352

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Mendez D, Gaulton A, Bento AP et al (2019) ChEMBL: towards direct deposition of bioassay data. Nucl Acids Res 47:D930–D940. https://doi.org/10.1093/nar/gky1075

    Article  CAS  PubMed  Google Scholar 

  62. Gilson MK, Liu T, Baitaluk M et al (2016) BindingDB in 2015: a public database for medicinal chemistry, computational chemistry and systems pharmacology. Nucl Acids Res 44:D1045–D1053. https://doi.org/10.1093/nar/gkv1072

    Article  CAS  PubMed  Google Scholar 

  63. Chen CY-C (2011) TCM Database@Taiwan: the world’s largest traditional Chinese medicine database for drug screening in silico. PLoS ONE 6:e15939. https://doi.org/10.1371/journal.pone.0015939

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Wishart DS, Feunang YD, Guo AC et al (2018) DrugBank 5.0: a major update to the DrugBank database for 2018. Nucl Acids Res 46:D1074–D1082. https://doi.org/10.1093/nar/gkx1037

    Article  CAS  PubMed  Google Scholar 

  65. Corsello SM, Bittker JA, Liu Z et al (2017) The drug repurposing hub: a next-generation drug library and information resource. Nat Med 23:405–408. https://doi.org/10.1038/nm.4306

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Valli M, dos Santos RN, Figueira LD et al (2013) Development of a natural products database from the biodiversity of Brazil. J Nat Prod 76:439–444. https://doi.org/10.1021/np3006875

    Article  CAS  PubMed  Google Scholar 

  67. Pilon AC, Valli M, Dametto AC et al (2017) NuBBE DB : an updated database to uncover chemical and biological information from Brazilian biodiversity. Sci Rep 7:7215. https://doi.org/10.1038/s41598-017-07451-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Farrell LJ, Lo R, Wanford JJ et al (2018) Revitalizing the drug pipeline: AntibioticDB, an open access database to aid antibacterial research and development. J Antimicrob Chemother 73:2284–2297. https://doi.org/10.1093/jac/dky208

    Article  CAS  PubMed  Google Scholar 

  69. Ntie-Kang F, Zofou D, Babiaka SB et al (2013) AfroDb: a select highly potent and diverse natural product library from African medicinal plants. PLoS ONE 8:e78085. https://doi.org/10.1371/journal.pone.0078085

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Pilón-Jiménez BA, Saldívar-González FI, Díaz-Eufracio BI, Medina-Franco JL (2019) BIOFACQUIM: a Mexican compound database of natural products. Biomolecules 9:31. https://doi.org/10.3390/biom9010031

    Article  CAS  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Conselho Nacional de Desenvolvimento Científico e Tecnológico, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Fundação de Amparo à Pesquisa do Estado de Minas Gerais, and Pró-Reitoria de Pesquisa of Universidade Federal de Minas Gerais for financial support and scholarships. Also, we would like to thank OpenEye Scientific Software for OMEGA and QUACPAC academic licenses.

Author information

Author notes

  1. Gabriel Corrêa Veríssimo and Valtair Severino dos Santos Júnior have equally contributed to the manuscript (First authors).

Authors and Affiliations

  1. Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

    Gabriel Corrêa Veríssimo, Valtair Severino dos Santos Júnior, Ingrid Ariela do Rosário de Almeida, Marina Sant’Anna Mitraud Ruas, Lukas Galuppo Coutinho, Renata Barbosa de Oliveira, Ricardo José Alves & Vinícius Gonçalves Maltarollo

Authors
  1. Gabriel Corrêa Veríssimo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Valtair Severino dos Santos Júnior
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ingrid Ariela do Rosário de Almeida
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marina Sant’Anna Mitraud Ruas
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lukas Galuppo Coutinho
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Renata Barbosa de Oliveira
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ricardo José Alves
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Vinícius Gonçalves Maltarollo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vinícius Gonçalves Maltarollo.

Ethics declarations

Conflict of interest

The authors would like to declare that the manuscript has been posted on ChemRxiv according to the Springer Nature preprint policy and can be found in the following link: https://doi.org/10.33774/chemrxiv-2021-lwrcx-v2. As stated in the above-mentioned policy, posting a manuscript on a legal preprint server is not considered prior publication.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Veríssimo, G.C., dos Santos Júnior, V.S., de Almeida, I.A.d.R. et al. The Brazilian compound library (BraCoLi) database: a repository of chemical and biological information for drug design. Mol Divers 26, 3387–3397 (2022). https://doi.org/10.1007/s11030-022-10386-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11030-022-10386-9

Keywords

Search

Navigation