Similarity-Based Virtual Screening to Find Antituberculosis Agents Based on Novel Scaffolds: Design, Syntheses and Pharmacological Assays
Abstract
:1. Introduction
2. Results and Discussion
2.1. Antituberculosis Activity Modelling
2.2. Similarity-Based Virtual Screening
2.3. Chemistry
3. Materials and Methods
3.1. Antituberculosis Activity Modelling
3.2. Similarity-Based Virtual Screening
3.3. Chemical Methods
3.4. Microbiological Methods
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Symbol | Name | Definition | Reference |
---|---|---|---|
N | Molecular size | Number of non-hydrogen atoms. | [68] |
Vk k = 3, 4 | Vertices of degree k | Number of atoms having k bonds, σ or π, to non-hydrogen atoms. | [68] |
R | Ramification | Number of single structural branches. | [68] |
W | Wiener path number | Sum of the distances between any two atoms in terms of bonds. | [100] |
L | Length | Maximal distance between atoms in terms of bonds. | [68] |
PRk k = 0–3 | Pairs of ramifications at distance k | Number of pairs of single branches at distance k in terms of bonds. | [68] |
kχt k = 0–4 t = p, c, pc | Randić-like indices of order k and type path (p), cluster (c) and path-cluster (pc) | δi, number of bonds, σ or π, of the atom i to non-hydrogen atoms. Sj, jth sub-structure of order k and type t. | [71,81,82] |
kχtv k = 0–4 t = p, c, pc | Kier-Hall indices of order k and type path (p), cluster (c) and path-cluster (pc) | δiv, Kier-Hall valence of the atom i. Sj,jth sub-structure of order k and type t. | [71,81,82] |
Gk k = 1–5 | Topological charge indices of order k | , product of the adjacency and inverse squared distance matrices for the hydrogen-depleted molecular graph. D, distance matrix. δ, Kronecker delta. | [68,101] |
Gkv k = 1–5 | Valence topological charge indices of order k | product of the electronegativity-modified adjacency and inverse squared distance matrices for the hydrogen-depleted molecular graph. D, distance matrix. δ, Kronecker delta. | [68,101] |
Jk k = 1–5 | Pondered topological charge indices of order k | [68,101] | |
Jkv k = 1–5 | Pondered valence topological charge indices of order k | [68,101] | |
kDt k = 0–4 t = p, c, pc | Connectivity differences of order k and type path (p), cluster (c) and path-cluster (pc) | [68] | |
Ek k = 1–5 | Topological charge differences of order k | [102] | |
Fk k = 1–5 | Pondered topological charge differences of order k | [102] | |
kCt k = 0–4 t = p, c, pc | Connectivity quotients of order k and type path (p), cluster (c) and path-cluster (pc) | [68] | |
kQt k = 0–4 t = p, c, pc | Inverse connectivity quotients of order k and type path (p), cluster (c) and path-cluster (pc) | [102] | |
CGk k = 1–5 | Topological charge quotients of order k | [102] | |
QGk k = 1–5 | Inverse topological charge quotients of order k | [102] |
Active Group | Inactive Group | ||||||
---|---|---|---|---|---|---|---|
Compound | DF | Prob. a Active | Predicted Activity b | Compound | DF | Prob. a Inactive | Predicted Activity b |
Streptonicozid | 3.14 | 1.000 | + | Butibufen | −3.14 | 1.000 | − |
Tobramycin | 3.49 | 1.000 | + | Aldicarb | −2.74 | 1.000 | − |
Kanamycin | 3.88 | 1.000 | + | Antrafenine | −2.55 | 1.000 | − |
Amikacin | 4.14 | 1.000 | + | Carprofen | −1.89 | 0.997 | − |
Dihydrostreptomycin | 2.80 | 0.999 | + | Beclobrate | −1.84 | 0.997 | − |
Streptomycin | 2.32 | 0.997 | + | Benzoctamine | −1.77 | 0.996 | − |
Ethambutol | 2.23 | 0.996 | + | Carmofur | −1.77 | 0.996 | − |
Pyrazinamide | 1.97 | 0.992 | + | Aminothiazole | −1.73 | 0.996 | − |
Enviomycin | 1.92 | 0.991 | + | Acifran | −1.72 | 0.996 | − |
Ofloxacin | 1.82 | 0.988 | + | Brilliant Blue | −1.72 | 0.996 | − |
Moxifloxacin | 1.66 | 0.982 | + | Amitraz | −1.68 | 0.995 | − |
Gatifloxacin | 1.66 | 0.981 | + | Clofibrate | −1.62 | 0.994 | − |
Rifampin | 1.60 | 0.978 | + | Paraoxon | −1.52 | 0.992 | − |
Azithromycin | 1.49 | 0.971 | + | Piroxicam | −1.39 | 0.989 | − |
Verazide | 1.44 | 0.967 | + | Carmustine | −1.11 | 0.977 | − |
Isoniazid | 1.20 | 0.938 | + | Ornithine | −1.11 | 0.977 | − |
Capreomycin | 1.16 | 0.930 | + | Alpidem | −1.10 | 0.976 | − |
Sparfloxacin | 0.98 | 0.889 | + | Alprazolam | −1.04 | 0.972 | − |
Clarithromycin | 0.93 | 0.874 | + | Bixin | −1.04 | 0.972 | − |
Salinazid | 0.92 | 0.871 | + | Benzoic Acid | −1.03 | 0.971 | − |
Tuberin | 0.91 | 0.869 | + | Amsacrine | −0.98 | 0.967 | − |
Clofazimine | 0.13 | 0.432 | NC | Azaserine | −0.96 | 0.965 | − |
Imipenem | 0.09 | 0.404 | NC | Theofibrate | −0.88 | 0.957 | − |
Ph−Aminosalicylate | −0.200 | 0.230 | − | Azacosterol | −0.83 | 0.951 | − |
PAS | −1.000 | 0.031 | − | Allicin | −0.77 | 0.943 | − |
Prazepam | −0.77 | 0.943 | − | ||||
Camazepam | −0.71 | 0.933 | − | ||||
Aminopromazine | −0.57 | 0.904 | − | ||||
Bromazepam | −0.45 | 0.870 | − | ||||
Carnitine | −0.32 | 0.824 | − | ||||
Acipimox | −0.28 | 0.809 | − | ||||
Buspirone | −0.03 | 0.677 | − | ||||
Azapicyl | 0.03 | 0.640 | − | ||||
Acronine | 0.11 | 0.588 | NC | ||||
Captodiamine | 0.28 | 0.470 | NC |
Run No. | λ | Training Group | Test Group | ||
---|---|---|---|---|---|
(+) | (−) | (+) | (−) | ||
1 | 0.28 | 90% (18/2) | 100% (0/26) | 60% (3/2) | 100% (0/9) |
2 | 0.31 | 87% (20/3) | 96% (1/27) | 50% (1/1) | 100% (0/7) |
3 | 0.35 | 86% (19/3) | 89% (3/24) | 100% (3/0) | 75% (2/6) |
4 | 0.33 | 82% (14/3) | 100% (0/27) | 88% (7/1) | 100% (0/8) |
5 | 0.33 | 91% (20/2) | 96% (1/27) | 100% (3/0) | 86% (1/6) |
Average | - | 87% | 96% | 80% | 92% |
DF | 0.34 | 84% (21/4) | 97% (1/34) | No | No |
Active Group | Inactive Group | ||||||
---|---|---|---|---|---|---|---|
Compound | DF | Prob. a Active | Predicted Activity b | Compound | DF | Prob. a Inactive | Predicted Activity b |
Morphazinamide | 4.32 | 1.000 | + | Canthaxanthin | −3.46 | 1.000 | − |
Neomycin | 5.02 | 1.000 | + | Genite | −2.57 | 1.000 | − |
Tubercidin | 2.85 | 0.999 | + | Altretamine | −1.91 | 0.997 | − |
Ciprofloxacin | 2.15 | 0.995 | + | Etifoxin | −1.86 | 0.997 | − |
Viomycin | 1.75 | 0.986 | + | Dichlone | −1.78 | 0.996 | − |
Rifabutin | 0.73 | 0.799 | + | Feprazone | −1.47 | 0.991 | − |
Ethionamide | −1.30 | 0.014 | − | Antipyrine | −0.44 | 0.868 | − |
Benorylate | −0.25 | 0.792 | − | ||||
Chloropal | 0.19 | 0.526 | NC | ||||
Glucosamine | 1.77 | 0.014 | + |
Chemical Scaffolds | R1 | R2 |
---|---|---|
Compound | MIC Range/mg/L | MIC50/mg/L | MIC90/mg/L | Molecular Mass/Da | MIC50/μM | MIC90/μM |
---|---|---|---|---|---|---|
Ethambutol | 1–8 | 4.0 | 4.0 | 204.3 | 19.6 | 19.6 |
Isoniazid | 0.05–0.2 | 0.05 | 0.05 | 137.1 | 0.4 | 0.4 |
Rifampin | 0.125–1 | 0.125 | 0.5 | 823.0 | 0.2 | 0.6 |
Streptomycin | 0.125–0.5 | 0.25 | 0.5 | 581.6 | 0.4 | 0.9 |
Compound | MIC Range/mg/L | MIC50/mg/L | MIC90/mg/L | Molecular Mass/Da | MIC50/μM | MIC90/μM |
---|---|---|---|---|---|---|
6a | 64 | 64 | 64 | 438.5 | 146.0 | 146.0 |
7 | 32 | 32 | 32 | 392.4 | 81.5 | 81.5 |
9c | 64 | 64 | 64 | 381.4 | 167.8 | 167.8 |
11b | 16 - 64 | 32 | 64 | 399.8 | 80.0 | 160.1 |
12 | 32 | 32 | 32 | 264.3 | 121.1 | 121.1 |
13 | 32 - 64 | 64 | 64 | 485.6 | 131.8 | 131.8 |
14 | >128 | >128 | >128 | 414.5 | >308.8 | >308.8 |
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García-García, Á.; Julián-Ortiz, J.V.d.; Gálvez, J.; Font, D.; Ayats, C.; Guna Serrano, M.d.R.; Muñoz-Collado, C.; Borrás, R.; Villalgordo, J.M. Similarity-Based Virtual Screening to Find Antituberculosis Agents Based on Novel Scaffolds: Design, Syntheses and Pharmacological Assays. Int. J. Mol. Sci. 2022, 23, 15057. https://doi.org/10.3390/ijms232315057
García-García Á, Julián-Ortiz JVd, Gálvez J, Font D, Ayats C, Guna Serrano MdR, Muñoz-Collado C, Borrás R, Villalgordo JM. Similarity-Based Virtual Screening to Find Antituberculosis Agents Based on Novel Scaffolds: Design, Syntheses and Pharmacological Assays. International Journal of Molecular Sciences. 2022; 23(23):15057. https://doi.org/10.3390/ijms232315057
Chicago/Turabian StyleGarcía-García, Ángela, Jesus Vicente de Julián-Ortiz, Jorge Gálvez, David Font, Carles Ayats, María del Remedio Guna Serrano, Carlos Muñoz-Collado, Rafael Borrás, and José Manuel Villalgordo. 2022. "Similarity-Based Virtual Screening to Find Antituberculosis Agents Based on Novel Scaffolds: Design, Syntheses and Pharmacological Assays" International Journal of Molecular Sciences 23, no. 23: 15057. https://doi.org/10.3390/ijms232315057