&lt;i&gt;In silico&lt;/i&gt; elucidation of potential drug target sites of the Thumb Index Fold Protein, Wnt-8b

Sehgal, Sheikh Arslan; Kanwal, Sonia; Tahir, Rana Adnan; Khalid, Zunera; Mirza, Ahmed Hammad

doi:10.4314/tjpr.v17i3.15

Cited by 11 publications

(8 citation statements)

References 15 publications

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“…Computational approaches have shown considerable success in research methodologies to solve biological problems [27]. After the successful identification of computational drugs and drug targets in neurological disorders [27][28][29][30][31][32] and cancer [33][34][35][36], researchers also utilized the computational approaches to design epitope-based peptide vaccines through immunoinformatic approaches [37]. The 3D model was built by using homology modeling and threading based approaches followed by the Molecular Dynamic (MD) simulations to optimize and analyze the structural features of a model for protein-peptide docking analyses.…”

Section: Introductionmentioning

confidence: 99%

In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1

Tahir¹,

Bashir²,

Yousaf³

et al. 2020

PLoS ONE

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Hypertension is considered as one of the most common diseases that affect human beings (both male and female) due to its high prevalence and also extending widely to both industrialize and developing countries. Angiotensin-converting enzyme (ACE) has a significant role in the regulation of blood pressure and ACE inhibition with inhibitory peptides is considered as a major target to prevent hypertension. In the current study, a blood pressure regulating honey protein (MRJP1) was examined to identify the ACE inhibitory peptides. The 3D structure of MRJP1 was predicted by utilizing the threading approach and further optimized by performing molecular dynamics simulation for 30 nanoseconds (ns) to improve the quality factor up to 92.43%. Root mean square deviation and root mean square fluctuations were calculated to evaluate the structural features and observed the fluctuations in the timescale of 30 ns. AHTpin server based on scoring vector machine of regression models, proteolysis and structural characterization approaches were implemented to identify the potential inhibitory peptides. The anti-hypertensive peptides were scrutinized based on the QSAR models of anti-hypertensive activity and the molecular docking analyses were performed to explore the binding affinities and potential interacting residues. The peptide "EALPHVPIFDR" showed the strong binding affinity and higher anti-hypertensive activity along with the global energy of-58.29 and docking score of 9590. The aromatic amino acids especially Tyr was observed as the key residue to design the dietary peptides and drugs like ACE inhibitors.

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Section: Introductionmentioning

confidence: 99%

In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1

Tahir¹,

Bashir²,

Yousaf³

et al. 2020

PLoS ONE

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“…Various biological fields including biotechnology, bioinformatics, microbiology, biochemistry and molecular biology are trying to solve serious biological issues of health including the removal of organic wastes from the environment (Sehgal et al 2018a;Tahir and Sehgal 2018;Tahir et al 2019). Bioinformatics plays a significant role to solve biological problems (Sehgal et al 2018b).…”

Section: Vegetable Oilsmentioning

confidence: 99%

Pesticide Concerns in Pakistan and Strategies to Mitigate Pesticide Residual Effects

Shamun

2022

Agric. Sci. J.

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Unrestrained pesticide usage has a negative impact on the ecosystem and also harms the health of other organisms, threatening biodiversity. The organophosphates and organochlorine cause convulsions, irritability and tumours which compel us to remove them from the ecosystem for the sustainability of life. The process of cleaning up pesticide-polluted regions is difficult and requires innovative eco-friendly strategies i.e. bioremediation, bio-stimulation and natural attenuation. Bioremediation is the method that biologically degrades the organic wastes under controlled conditions to the levels of less concentration of organic materials. The current study intends to investigate effective and environmentally acceptable ways for removing pesticide contamination and residues from our ecosystem, with a particular emphasis on bioremediation processes including bacteria, fungus, and other forms of life.

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“…The achievement of immuno-informatics research and computerized drug design has significantly increased during the preceding fifteen years. The in silico, bioinformatics, and immunoinformatic techniques have been used to answer numerous biological problems [6][7][8][9][10][11][12][13][14]. The molecular docking analyses were used in the current in silico effort to identify the novel molecules against ADA.…”

Section: Introductionmentioning

confidence: 99%

Computational 3D structure prediction followed by molecular docking to reveal the novel drug targets against ADA

2023

Biomed. Lett.

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Adenosine deaminase (ADA) is a functional enzyme that transforms deoxyadenosine and adenosine into deoxyinosine and inosine respectively. ADA deficiency causes toxic purine degradation byproducts to build up in the body, which has a particularly negative impact on lymphocytes and results in adenosine deaminase-deficient severe combined immunodeficiency. Different in silico techniques including threading, ab initio and homology modeling for 3D structure prediction were applied for the prediction of ADA structures. Following the three-dimensional structure prediction analyses, an extensive computational assessment of all predicted structures for reliability was performed. The overall quality factor of the predicted ADA structures was observed 62.45% in the predicted 3D models. A Ramachandran plot was created, and 94.80% of the residues were found in the allowed and favored regions of the protein structure plot. The molecular docking analyses were performed in order to identify the potential therapeutic medication targets against ADA. The virtually examined molecules through a virtually high throughput screening may have the ability the regulation the ADA activity. The least binding energy was calculated through the molecular docking analyses and the energy values were observed -8.7 Kcal/mol. The binding residues (Lys-367, Glu-424, Asp-422, Phe-381, Ile-377, Ser-430 and Glu-374) were conserved in all the interactional analyses of the docked complexes. Finding the effective binding domain in a protein three-dimensional structure is crucial for understanding of its structural makeup and determining its functions.

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<i>In silico</i> elucidation of potential drug target sites of the Thumb Index Fold Protein, Wnt-8b

Cited by 11 publications

References 15 publications

In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1

In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1

Pesticide Concerns in Pakistan and Strategies to Mitigate Pesticide Residual Effects

Computational 3D structure prediction followed by molecular docking to reveal the novel drug targets against ADA

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