The Benefits of
            <i>In Silico</i>
            Modeling to Identify Possible Small-Molecule Drugs and Their Off-Target Interactions

Zloh, Mire; Kirton, Stewart B.

doi:10.4155/fmc-2017-0151

Cited by 30 publications

(17 citation statements)

References 84 publications

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“…For example, off-targets like hERG, 5-HT 2b or PPARγ, which are known to be associated with safety liabilities, are often used in lead optimization stage counter-screens. Given the current limitations, in silico off-target prediction approaches have been receiving more attention in the past few years, mostly to understand polypharmacology and target engagement associated with preclinical and clinical toxicities (Lavecchia and Cerchia, 2016;Van Vleet et al, 2018;Zloh and Kirton, 2018). These in silico methods are now actively implemented at the early discovery and preclinical drug development stages for rapid generation of off-target binding hypotheses.…”

Section: Discussionmentioning

confidence: 99%

Novel Computational Approach to Predict Off-Target Interactions for Small Molecules

et al. 2019

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with MW > 700 and MW<200 for both categories. In addition, 15 internal small molecules with known off-target interactions were evaluated. For these compounds, the OTSA framework not only captured about 56.8% of in vitro confirmed off-target interactions, but also identified the right pharmacological targets for 14 compounds as one of the top scoring targets. In conclusion, the OTSA process demonstrates good predictive performance characteristics and represents an additional tool with utility during the lead optimization stage of the drug discovery process. Additionally, the computed physiochemical properties such as clogP (i.e., lipophilicity), molecular weight, pKa and logS (i.e., solubility) were found to be statistically different between the approved and discontinued drugs, but the internal compounds were close to the approved drugs space in most part.

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Section: Discussionmentioning

confidence: 99%

Novel Computational Approach to Predict Off-Target Interactions for Small Molecules

et al. 2019

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“…Therefore, these techniques are widely applied in the studies aiming to develop molecules characterized by a high affinity to a specific molecular target, with minimal side effects and promising pharmacokinetic parameters (ADME). Therefore, a combination of ligand- and structure-based approaches can be implemented to obtain reliable predictions useful in the identification of novel drug-like molecules [ 82 ]. In this part, we would like to focus on virtual screening approach, that sheds a light of hope on the rapid development of new, potentially valuable for the treatment of depression medication.…”

Section: In Silico Methods Aiming To Identify Novel 5-ht 2a Receptor Ligandsmentioning

confidence: 99%

Overcoming Depression with 5-HT2A Receptor Ligands

Zięba

Stępnicki

Matosiuk

et al. 2021

IJMS

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Depression is a multifactorial disorder that affects millions of people worldwide, and none of the currently available therapeutics can completely cure it. Thus, there is a need for developing novel, potent, and safer agents. Recent medicinal chemistry findings on the structure and function of the serotonin 2A (5-HT2A) receptor facilitated design and discovery of novel compounds with antidepressant action. Eligible papers highlighting the importance of 5-HT2A receptors in the pathomechanism of the disorder were identified in the content-screening performed on the popular databases (PubMed, Google Scholar). Articles were critically assessed based on their titles and abstracts. The most accurate papers were chosen to be read and presented in the manuscript. The review summarizes current knowledge on the applicability of 5-HT2A receptor signaling modulators in the treatment of depression. It provides an insight into the structural and physiological features of this receptor. Moreover, it presents an overview of recently conducted virtual screening campaigns aiming to identify novel, potent 5-HT2A receptor ligands and additional data on currently synthesized ligands acting through this protein.

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“…The application of in-silico methods on the interactions of biomolecules has tremendously promoted the analysis of biological systems, providing valuable information for predicting the activity of biomolecules or understanding biomolecular processes. In-silico approaches are commonly used in drug discovery and development [ 18 , 19 ], protein–protein interaction [ 20 , 21 ], aptamer–protein interaction [ 22 , 23 , 24 ], etc. Compared with empirical methods, computational in-silico methods have several advantages, such as low cost, a simple process, and queries that can be investigated irrespective of practical limitations that hinder experiments.…”

Section: Introductionmentioning

confidence: 99%

In-Silico Selection of Aptamer Targeting SARS-CoV-2 Spike Protein

Lin

Chen

Hwu

et al. 2022

IJMS

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Aptamers are single-stranded, short DNA or RNA oligonucleotides that can specifically bind to various target molecules. To diagnose the infected cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in time, numerous conventional methods are applied for viral detection via the amplification and quantification of DNA or antibodies specific to antigens on the virus. Herein, we generated a large number of mutated aptamer sequences, derived from a known sequence of receptor-binding domain (RBD)-1C aptamer, specific to the RBD of SARS-CoV-2 spike protein (S protein). Structural similarity, molecular docking, and molecular dynamics (MD) were utilized to screen aptamers and characterize the detailed interactions between the selected aptamers and the S protein. We identified two mutated aptamers, namely, RBD-1CM1 and RBD-1CM2, which presented better docking results against the S protein compared with the RBD-1C aptamer. Through the MD simulation, we further confirmed that the RBD-1CM1 aptamer can form the most stable complex with the S protein based on the number of hydrogen bonds formed between the two biomolecules. Based on the experimental data of quartz crystal microbalance (QCM), the RBD-1CM1 aptamer could produce larger signals in mass change and exhibit an improved binding affinity to the S protein. Therefore, the RBD-1CM1 aptamer, which was selected from 1431 mutants, was the best potential candidate for the detection of SARS-CoV-2. The RBD-1CM1 aptamer can be an alternative biological element for the development of SARS-CoV-2 diagnostic testing.

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The Benefits of In Silico Modeling to Identify Possible Small-Molecule Drugs and Their Off-Target Interactions

Cited by 30 publications

References 84 publications

Novel Computational Approach to Predict Off-Target Interactions for Small Molecules

Novel Computational Approach to Predict Off-Target Interactions for Small Molecules

Overcoming Depression with 5-HT2A Receptor Ligands

In-Silico Selection of Aptamer Targeting SARS-CoV-2 Spike Protein

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