Development and Characterization of an In Silico Database of In Vitro Tested Antiviral Compounds

Authors

DOI:

https://doi.org/10.53805/lads.v3i2.61

Keywords:

In Silico Database, Antiviral compounds, computational biology, structural data, classical research and development

Abstract

Antivirals are substances that inhibit viral infection or virus replication, acting as drugs to treat viral diseases. However, due the diversity of pathogens, it is important to seek new antivirals. Among the options, repositioning already approved drugs is a cheaper and faster strategy when compared to classical research and development methods. Since there is a lack of compiled and standardized data on these drugs, this work aims to build a database of in vitro antiviral tests. Thus, the compounds and their information were obtained through publications of in vitro methods for testing antiviral drugs, we created six databases covering SMILES, MOL, SDF 2D, MOL2, PDB and PDBQT extensions, classified by the presence and/or absence of antiviral activity. Each file contains its IUPAC name and structural data in up to three dimensions.

References

CHEOHEN, C. F. A.; ANDRIOLO, B. V.; DA SILVA, M. L. Database of Active Pharmaceutical Ingredients (APIs) present in the Brazilian Pharmacopeia. Latin American Data in Science, v. 2, n. 1, p. 7-12, 2022. DOI: 10.53805/lads.v2i1.35.

EGAN, W. J.; MERZ, K. M. Jr.; BALDWIN, J. J. Prediction of drug absorption using multivariate statistics. J Med Chem. 2000 Oct 19;43(21):3867-77. DOI: 10.1021/jm000292e.

GHOSE, A. K.; VISWANADLHAN, V. N.; WENDOLOSKII, J. J. 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. 1999 Jan;1(1):55-68. DOI: 10.1021/cc9800071.

IRWIN, J. J.; SHOICHET, B. K. ZINC− a free database of commercially available compounds for virtual screening. Journal of chemical information and modeling, v. 45, n. 1, p. 177-182, 2005. DOI: 10.1021/ci049714+.

LIPINSKI C. A. et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 2001 Mar 1;46(1-3):3-26. DOI: 10.1016/s0169-409x(00)00129-0.

MORRIS, G. M.; LIM-WILBY, M. Molecular Docking. In: KUKOL, A. (Ed.). Methods in Molecular Biology. Totowa: [s.n.]. v. 443p. 365–382, 2008.DOI: 10.1007/978-1-59745-177-2_19.

MUEGGE I.; HEALD S. L.; BRITTELLI D. Simple selection criteria for drug-like chemical matter. J Med Chem. 2001 Jun 7;44(12):1841-6. DOI: 10.1021/jm015507e.

O’BOYLE, N. M. et al. Open Babel: An open chemi.cal toolbox. Journal of Cheminformatics, v. 3, n. 33, p. 1– 14, 2011.DOI: 10.1186/1758-2946-3-33.

OPENBABEL. Obabel and babel:Convert, Filter and Manipulate Chemical Data documentation.2011.Available:https://openbabel.org/docs/dev/Command-line_tools/babel.html

RUCHAWAPOL, C. et al. Natural Products and Their Derivatives against Human Herpesvirus Infection. Molecules. v. 26, n. 20, 1 out. 2021.DOI: 10.3390/molecules26206290.

SANDER, T. et al. DataWarrior: an open-source program for chemistry aware data visualization and analysis. Journal of chemical information and modeling, v. 55, n. 2, p. 460-473, 2015. DOI: 10.1021/ci500588j.

VEBER, D. F. et al. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem. 2002 Jun 6;45(12):2615-23. DOI: 10.1021/jm020017n.

Downloads

Additional Files

Published

13-10-2023

How to Cite

FELIX, N. P. .; CHEOHEN, C. .; ESTEVES, M. E. A. .; DA SILVA, M. L. . Development and Characterization of an In Silico Database of In Vitro Tested Antiviral Compounds. Latin American Data in Science, [S. l.], v. 3, n. 2, p. 2–7, 2023. DOI: 10.53805/lads.v3i2.61. Disponível em: https://ojs.datainscience.com.br/index.php/lads/article/view/61. Acesso em: 15 jul. 2024.