Advances in Pharmacophore Modeling and Its Role in Drug Designing

Swaminathan, Priya

doi:10.1007/978-981-15-6815-2_10

Cited by 3 publications

(1 citation statement)

References 47 publications

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“…The nature and three-dimensional conformation of compound functionalities in ligands essential for molecular interactions with macromolecular targets can be ascertained using 3D pharmacophores. Compounds' activities must be categorized into more general pharmacophore features, such as hydrogen donors, hydrophobic areas, aromatic ring systems, acceptors of hydrogen bonds, and negatively and positively ionizable groups [49].…”

Section: Pharmacophore Modelingmentioning

confidence: 99%

Glycine-Conjugated α-Mangostins as Potential Estrogen Receptor Alpha (ERα) Antagonists through Pharmacophore Modeling, Docking Analysis, and Molecular Dynamics Simulations

Arifian,

Maharani,

Megantara

et al. 2024

Applied Sciences

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Natural compounds have demonstrated good biological activity when combined with certain amino acids. For example, a glycine-conjugated glycyrrhetinic acid exhibits heightened efficiency against MCF7 cancer cells. Consequently, a molecular modeling analysis is conducted to construct glycine-conjugated α-mangostins and investigate their potential. According to pharmacophore modeling using the ligand-based drug design technique, only two glycine-conjugated α-mangostins conform to the pharmacophore features. The docking simulation results show that the Am1Gly conjugate can interact with the estrogen receptor-α (ERα) with a binding energy of −10.91 kcal/mol. This interaction is further supported by molecular dynamics simulations performed over a 200 ns timeframe. Based on molecular dynamics modeling using the MMPBSA method, the binding affinity of Am1Gly (ΔGTotal = −48.79 kcal/mol) is determined. The results of this analysis indicate that Am1Gly might function as an antagonist to estrogen receptors.

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Section: Pharmacophore Modelingmentioning

confidence: 99%

Glycine-Conjugated α-Mangostins as Potential Estrogen Receptor Alpha (ERα) Antagonists through Pharmacophore Modeling, Docking Analysis, and Molecular Dynamics Simulations

Arifian,

Maharani,

Megantara

et al. 2024

Applied Sciences

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From Traditional Herbal Medicine to Rational Drug Discovery: Strategies, Challenges, and Future Perspectives

Singh

Pathak

Rai

2022

Rev. Bras. Farmacogn.

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Pharmacophore Mapping: An Important Tool in Modern Drug Design and Discovery

Pathak,

Vyas,

Sagar

et al. 2023

Applied Computer-Aided Drug Design: Models and Methods

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Computer-Aided Drug Design (CADD) has become an integral part of drug discovery and development efforts in the pharmaceutical and biotechnology industry. Since the 1980s, structure-based design technology has evolved, and today, these techniques are being widely employed and credited for the discovery and design of most of the recent drug products in the market. Pharmacophore-based drug design provides fundamental approach strategies for both structure-based and ligand-based pharmacophore approaches. The different programs and methodologies enable the implementation of more accurate and sophisticated pharmacophore model generation and application in drug discovery. Commonly used programmes are GALAHAD, GASP, PHASE, HYPOGEN, ligand scout etc. In modern computational chemistry, pharmacophores are used to define the essential features of one or more molecules with the same biological activity. A database of diverse chemical compounds can then be searched for more molecules which share the same features located at a similar distance apart from each other. Pharmacophore requires knowledge of either active ligands and/or the active site of the target receptor. There are a number of ways to build a pharmacophore. It can be done by common feature analysis to find the chemical features shared by a set of active compounds that seem commonly important for receptor interaction. Alternately, diverse chemical structures for certain numbers of training set molecules, along with the corresponding IC50 or Ki values, can be used to correlate the three-dimensional arrangement of their chemical features with the biological activities of training set molecules. There are many advantages in pharmacophore based virtual screening as well as pharmacophore based QSAR, which exemplify the detailed application workflow. Pharmacophore based drug design process includes pharmacophore modelling and validation, pharmacophore based virtual screening, virtual hits profiling, and lead identification. The current chapter on pharmacophores also describes case studies and applications of pharmacophore mapping in finding new drug molecules of specific targets.

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Advances in Pharmacophore Modeling and Its Role in Drug Designing

Cited by 3 publications

References 47 publications

Glycine-Conjugated α-Mangostins as Potential Estrogen Receptor Alpha (ERα) Antagonists through Pharmacophore Modeling, Docking Analysis, and Molecular Dynamics Simulations

Glycine-Conjugated α-Mangostins as Potential Estrogen Receptor Alpha (ERα) Antagonists through Pharmacophore Modeling, Docking Analysis, and Molecular Dynamics Simulations

From Traditional Herbal Medicine to Rational Drug Discovery: Strategies, Challenges, and Future Perspectives

Pharmacophore Mapping: An Important Tool in Modern Drug Design and Discovery

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