KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 4 of 4

Some of the metrics are blocked by your
consent settings
StackHCV: a web-based integrative machine-learning framework for large-scale identification of hepatitis C virus NS5B inhibitors
(2021-10-01)
Malik, Aijaz Ahmad
;
Chotpatiwetchkul, Warot
;
Phanus-umporn, Chuleeporn
;
Nantasenamat, Chanin
;
Charoenkwan, Phasit
Fast and accurate identification of inhibitors with potency against HCV NS5B polymerase is currently a challenging task. As conventional experimental methods is the gold standard method for the design and development of new HCV inhibitors, they often require costly investment of time and resources. In this study, we develop a novel machine learning-based meta-predictor (termed StackHCV) for accurate and large-scale identification of HCV inhibitors. Unlike the existing method, which is based on single-feature-based approach, we first constructed a pool of various baseline models by employing a wide range of heterogeneous molecular fingerprints with five popular machine learning algorithms (k-nearest neighbor, multi-layer perceptron, partial least squares, random forest and support vectors machine). Secondly, we integrated these baseline models in order to develop the final meta-based model by means of the stacking strategy. Extensive benchmarking experiments showed that StackHCV achieved a more accurate and stable performance as compared to its constituent baseline models on the training dataset and also outperformed the existing predictor on the independent test dataset. To facilitate the high-throughput identification of HCV inhibitors, we built a web server that can be freely accessed at http://camt.pythonanywhere.com/StackHCV. It is expected that StackHCV could be a useful tool for fast and precise identification of potential drugs against HCV NS5B particularly for liver cancer therapy and other clinical applications.
Some of the metrics are blocked by your
consent settings
Preparation, biological & cheminformatics-based assessment of N2,N4-diphenylpyrimidine-2,4-diamine as potential Kinase-targeted antimalarials
(2021-09-15)
Toviwek, Borvornwat
;
Phuangsawai, Oraphan
;
Konsue, Adchatawut
;
Hannongbua, Supa
;
Riley, Jennifer
Twenty eight new N2,N4-diphenylpyrimidine-2,4-diamines have been prepared in order to expand our understanding of the anti-malarial SAR of the scaffold. The aim of the study was to make structural modifications to improve the overall potency, selectivity and solubility of the series by varying the anilino groups attached to the 2- and 4-position. We evaluated the activity of the compounds against Plasmodium falciparum (Pf) 3D7, cytotoxicity against HepG2, % inhibition at a panel of 10 human kinases, solubility, permeability and lipophilicity, and human and rat in vitro clearance. 11 was identified as a potent anti-malarial with an IC<inf>50</inf> of 0.66 µM at the 3D7 strain and a selectivity (SI) of ~ 40 in terms of cytotoxicity against the HepG2 cell line. It also displayed low experimental logD<inf>7.4</inf> (2.27), reasonable solubility (124 µg/ml), good metabolic stability, but low permeability. A proteo-chemometric workflow was employed to identify putative Pf targets of the most promising compounds. Ligand-based similarity searching of the ChEMBL database led to the identification of most probable human targets. These were then used as input for sequence-based searching of the Pf proteome. Homology modelling and molecular docking were used to evaluate whether compounds could indeed bind to these targets with valid binding modes. In vitro biological testing against close human analogs of these targets was subsequently undertaken. This allowed us to identify potential Pf targets and human anti-targets that could be exploited in future development.
Some of the metrics are blocked by your
consent settings
Towards reproducible computational drug discovery
(2020-01-28)
Schaduangrat, Nalini
;
Lampa, Samuel
;
Simeon, Saw
;
Gleeson, Matthew Paul
;
Spjuth, Ola
The reproducibility of experiments has been a long standing impediment for further scientific progress. Computational methods have been instrumental in drug discovery efforts owing to its multifaceted utilization for data collection, pre-processing, analysis and inference. This article provides an in-depth coverage on the reproducibility of computational drug discovery. This review explores the following topics: (1) the current state-of-the-art on reproducible research, (2) research documentation (e.g. electronic laboratory notebook, Jupyter notebook, etc.), (3) science of reproducible research (i.e. comparison and contrast with related concepts as replicability, reusability and reliability), (4) model development in computational drug discovery, (5) computational issues on model development and deployment, (6) use case scenarios for streamlining the computational drug discovery protocol. In computational disciplines, it has become common practice to share data and programming codes used for numerical calculations as to not only facilitate reproducibility, but also to foster collaborations (i.e. to drive the project further by introducing new ideas, growing the data, augmenting the code, etc.). It is therefore inevitable that the field of computational drug design would adopt an open approach towards the collection, curation and sharing of data/code.
Some of the metrics are blocked by your
consent settings
Elucidation of vasodilation response and structure activity relationships of N2,N4-disubstituted quinazoline 2,4-diamines in a rat pulmonary artery model
(2019-01-14)
Paracha, Tamkeen Urooj
;
Pobsuk, Nattakarn
;
Salaloy, Nattapas
;
Suphakun, Praphasri
;
Pekthong, Dumrongsak
Pulmonary arterial hypertension (PAH) is a rare and progressive disease arising from various etiologies and pathogenesis. PAH decreases life expectancy due to pulmonary vascular remodeling, elevation of mean pulmonary arterial pressure, and ultimately progresses to heart failure. While clinical treatments are available to reduce the associated symptoms, a complete cure has yet to be found. Phosphodiesterase-5 (PDE-5) inhibition has been identified as a possible intervention point in PAH treatment. The functional vasodilation response to N2,N4-diamino quinazoline analogues with differing PDE-5 inhibitory activities and varying physicochemical properties were assessed in both endothelium-intact and denuded rat pulmonary arteries to gain greater insight into their mode of action. All analogues produced vasorelaxant effects with EC50s ranging from 0.58 ± 0.22 µM to >30 µM. It was observed that vasodilation response in intact vessels was highly correlated with that of denuded vessels. The ~10% drop in activity is consistent with a loss of the nitric oxide mediated cyclic guanosine monophosphate (NO/cGMP) pathway in the latter case. A moderate correlation between the vasodilation response and PDE-5 inhibitory activity in the intact vessels was observed. Experimental protocol using the alpha-adrenergic (α<inf>1</inf>) receptor agonist, phenylephrine (PE), was undertaken to assess whether quinazoline derivatives showed competitive behavior similar to the α<inf>1</inf> receptor blocker, prazosin, itself a quinazoline derivative, or to the PDE-5 inhibitor, sildenafil. Competitive experiments with the α<inf>1</inf>-adrenergic receptor agonist point to quinazoline derivatives under investigation here act via PDE-5 inhibition and not the former. The pre-incubation of pulmonary arterial rings with quinazoline test compounds (10 µM) reduced the contractile response to PE around 40–60%. The most promising compound (9) possessed ~32 folds higher selectivity in terms of vasodilation to its mammalian A549 cell cytotoxicity. This study provides experimental basis for PDE-5 inhibition as the mode of action for vasodilation by N2,N4-diamino quinazoline analogues along with their safety studies that may be beneficial in the treatment of various cardiovascular pathologies.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results