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Performance of the new hybrid scoring function performance evaluated on the training set: N = 2412 protein–ligand complexes, R = 0.60, root-mean-square error = 1.61, mean absolute error = 1.27.
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Automated docking is one of the most important tools for structure-based drug design that allows prediction of ligand binding poses and also provides an estimate of how well small molecules fit in the binding site of a protein. A new scoring function based on AutoDock and AutoDock Vina has been introduced. The new hybrid scoring function is a linea...
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... All docking investigations used the Auto Dock Vina program in PyRx to perform molecular docking [34]. One of the most well-known and widely used open-source molecular coupling methods is AutoDock Vina [35]. The lowest binding energy docking data were finally shown in 3D and 2D using the Biovia Discovery Studio Visualizer. ...
Abstract
Pancreatic cancer (PC) is a devastating malignancy with intricate genetic underpinnings and a complex etiology. Emerging evidence suggests the presence of lynch syndrome (LS) and type 2 diabetes (T2D) associated susceptibility to PC. This study presents integrated computational and systems biology approaches to identify the genetic risk factors underlying the association between PC, LS, and T2D. Patient data for these three diseases have been collected from NCBI and differentially expressed genes (DEGs) identified by the GREIN web platform. Furthermore, protein-protein interaction (PPI), gene ontology (GO), and signaling pathway networks were analyzed through STRING and DAVID databases, respectively. Autodock Vina has been used for prospective analysis of ligand-protein interaction. About 60 unique common DEGs were identified by statistical analysis. In addition to the utilization of five distinct algorithms within the Cytoscape framework, we have reported three potential target candidates: TNF, CXCL1, and TNFSF10. In particular, the immune and inflammatory response, the chemokine-mediated signaling pathway, rheumatoid arthritis, and IL-17 signaling pathways emerged as prominently enriched pathways. Furthermore, the interaction of 162 phytochemicals from Nigella sativa was assessed with the identified hub proteins. Among these, thujopsene emerged as a notable ligand candidate, demonstrating the most favorable binding energy against the TNF (−9.6 kca/mol TNFSF10 (−8.5 kcal/mol), and CXCL1 (−9.1 kcal/mol) proteins. Besides, pharmacokinetics, toxicity, and drug-likeness properties of the thujopsene ligand showed an acceptable range for selection of a drug candidate. Collectively, these findings shed light on the intricate interplay of genes, pathways, and potential therapeutic compounds, providing a basis for further exploration and validation in the context of relevant diseases.
... The energy range was set to 5.0 kcal/mol, and the exhaustiveness parameter was configured as 22 (Agarwal and Smith, 2023). The optimal pose with the best scores within multiple iterations of the docking process was selected as the initial structure for the subsequent MD simulation, according to the affinity assessment through scoring function and binding mode analysis (Tanchuk et al., 2016). ...
Polygonatum sibiricum (P. sibiricum), recognized as a precious nourishing Chinese traditional medicine, exhibits the pharmacological effect of anti-aging. In this work, we proposed a novel mechanism underlying this effect related to the less studied bioactive compounds fructooligosaccharides in P. sibiricum (PFOS) to identify the inhibition effect of the small glycosyl molecules on the age-related zinc metalloprotease carbonic anhydrase II (CA II). Molecular docking and molecular dynamics simulation were used to investigate the structural and energetic properties of the complex systems consisting of the CA II enzyme and two possible structures of PFOS molecules (PFOS-A and PFOS-B). The binding affinity of PFOS-A (−7.27 ± 1.02 kcal/mol) and PFOS-B (−8.09 ± 1.75 kcal/mol) shows the spontaneity of the binding process and the stability of the combination in the solvent. Based on the residue energy decomposition and nonbonded interactions analysis, the C-, D- and G-sheet fragments of the CA II were found to be crucial in binding process. Van der Waals interactions form on the hydrophobic surface of CAII mainly with 131PHE and 135VAL, while hydrogen bonds form on the hydrophilic surface mainly with 67ASN and 92GLN. The binding of PFOS results in the blocking of the zinc ions pocket and then inhibiting its catalytic activity, the stability of which has been further demonstrated by free energy landscape. These findings provide evidence of the effective inhibition of PFOS to CA II enzyme, which leads to a novel direction for exploring the mechanism of traditional Chinese medicine focused on small molecule fructooligosaccharides.
... The program's default settings were then used for running the docking analysis. Through force-field scoring, the obtained scoring function was used to analyze the binding affinity between the drug molecules and transcription factors (Tanchuk et al., 2016). The compound with the highest negative binding score was proposed as the drug model candidate to deal with prostate cancer disease. ...
Cancer is a deadly disease that has accounted for hundreds of thousands of deaths each year around the globe. Prostate cancer is a type of cancer with a high prevalence among men in their sixties. One of the possible causes of this cancer is the mutations in the critical transcriptional factors (TFs) associated with the androgen receptors (ARs), such as FOXA1 and GATA2, which some studies have found to increase the risk of prostate cancer. TFs are one of the most direct and potential targets for treating cancer. However, TFs are very small and have no stable binding sites, which makes it hard to target using small compounds. Furthermore, limited studies have been conducted to determine the target sites of TFs to treat prostate cancer. This chapter aimed to recount a study approaching natural compound screening against TFs using the conventional molecular docking method. From the molecular docking results and KNApSAcK database, it was found that the natural compound (MolPort-001-742-110_ZINC000059779788) with a binding energy of around-9.6 kcal/mol was present in several herbs containing 2,3-Dihydroamentoflavone. However, there are still limited studies of the anticancer ability of the herbs. Hence, advanced in-silico studies and further wet lab activities, including in-vitro and in-vivo studies, are required to evaluate and expand these findings.
... Nowadays, many proteins simulation software has become mature with Leal et al. (2018) higher simulation accuracy. For example, protein simulation software such as Schrodinger and Autodock can perform molecular docking to predict the key amino acids at the binding sites of substrate molecules and target proteins (Tanchuk et al. 2016), thereby conducting alanine scanning and amino acid saturation mutations on a smaller scale, which can also screen out enzymes with higher enzyme activity. At present, there is still no breakthrough in the bottleneck of D-glucuronic acid yield (Arewång et al. 2007), further research is essential for biological methods, including strain improvement, detection optimization, and enzyme modification (Laisne et al. 2011), the scaffold of protein engineering and mutation of enzyme engineering are a very important research direction (Jaime-Acuña et al. 2021). ...
D-glucuronic acid is a kind of glucose derivative, which has excellent properties such as anti-oxidation, treatment of liver disease and hyperlipidemia, and has been widely used in medicine, cosmetics, food and other fields. The traditional production methods of D-glucuronic acid mainly include natural extraction and chemical synthesis, which can no longer meet the growing market demand. The production of D-glucuronic acid by biocatalysis has become a promising alternative method because of its high efficiency and environmental friendliness. This review describes different production methods of D-glucuronic acid, including single enzyme catalysis, multi-enzyme cascade, whole cell catalysis and co-culture, as well as the intervention of some special catalysts. In addition, some feasible enzyme engineering strategies are provided, including the application of enzyme immobilized scaffold, enzyme mutation and high-throughput screening, which provide good ideas for the research of D-glucuronic acid biocatalysis.
... Consensus functions are similar to the hybridized scoring functions (Maia et al., 2020). As an example, Tanchuk et al. (2016) combined physics and machine learning scoring functions. This method is very useful for the calculation of food protein-ligand interactions as it promotes calculation accuracy and speed on complex food docking systems. ...
In recent years, investigations on molecular interaction mechanisms between food proteins and ligands have attracted much interest. The interaction mechanisms can supply much useful information for many fields in the food industry, including nutrient delivery, food processing, auxiliary detection, and others. Molecular simulation has offered extraordinary insights into the interaction mechanisms. It can reflect binding conformation, interaction forces, binding affinity, key residues, and other information that physicochemical experiments cannot reveal in a fast and detailed manner. The simulation results have proven to be consistent with the results of physicochemical experiments. Molecular simulation holds great potential for future applications in the field of food protein–ligand interactions. This review elaborates on the principles of molecular docking and molecular dynamics simulation. Besides, their applications in food protein–ligand interactions are summarized. Furthermore, challenges, perspectives, and trends in molecular simulation of food protein–ligand interactions are proposed. Based on the results of molecular simulation, the mechanisms of interfacial behavior, enzyme‐substrate binding, and structural changes during food processing can be reflected, and strategies for hazardous substance detection and food flavor adjustment can be generated. Moreover, molecular simulation can accelerate food development and reduce animal experiments. However, there are still several challenges to applying molecular simulation to food protein–ligand interaction research. The future trends will be a combination of international cooperation and data sharing, quantum mechanics/molecular mechanics, advanced computational techniques, and machine learning, which contribute to promoting food protein–ligand interaction simulation. Overall, the use of molecular simulation to study food protein–ligand interactions has a promising prospect.
... We used AutoDock Vina [39][40][41] as molecular docking software to obtain EED protein Complexes with the six Inhibitors we studied. Since these are all competitive Inhibitors [30], we selected the binding pocket of the natural substrate as the docking area, the aromatic cage area mentioned in the introduction. ...
Inhibition of the Embryonic Ectoderm Development (EED) subunit in Polycomb Repressive Complex 2 (PRC2) can inhibit tumor growth. In this paper, we selected six experimentally designed EED competitive Inhibitors of the triazolopyrimidine derivatives class. We investigated the difference in the binding mode of the natural substrate to the Inhibitors and the effects of differences in the parent nuclei, heads, and tails of the Inhibitors on the inhibitory capacity. The results showed that the binding free energy of this class of Inhibitors was close to or lower compared to the natural substrate, providing an energetic basis for competitive inhibition. For the Inhibitors, the presence of a strong negatively charged group at the 6-position of the parent nucleus or the 8′-position of the head would make the hydrogen atom on the head imino group prone to flip, resulting in the vertical movement of the parent nucleus, which significantly decreased the inhibitory ability. When the 6-position of the parent nucleus was a nonpolar group, the parent nucleus would move horizontally, slightly decreasing the inhibitory ability. When the 8′-position of the head was methylene, it formed an intramolecular hydrophobic interaction with the benzene ring on the tail, resulting in a significant increase in inhibition ability.
... 52 The ligand molecule that has been chosen for performing simulation is in the most stable state that corresponds to the lowest energy found at the ground state, and the partial charges have been calculated using the Geistiger technique. [53][54][55] Different classes of bacteria were selected as target proteins and their PDB files were obtained from RCSB protein data. 56 ...
The present study deals with the application of ab initio method using
density functional theory (DFT) at M06-2X/6-311þþG(d,p) to characterize
the considered molecule completely. Though the anti-bacterial activity of
the 3-(amino thiazolyl)quinolone derivatives was studied, the effects of
intermolecular hydrogen bonding on chemical and biological processes
remain unexplored or have not been thoroughly investigated so far.
Investigations into non-covalent interactions were carried out using the
reduced density gradient methodology and the quantum theory of atoms
in molecules. An electron localization function was used to investigate the
electronic vicinity of each atom in a molecule. Natural bond orbital analysis
was used to determine the correlated stabilization energies for the intermolecular
hydrogen bonds (H-bonds) that are responsible for the molecular stability
of the dimer structure. The electrophilic and nucleophilic sites were
predicted using the molecular electrostatic potential. The density of states
and partial density of states were also used to represent the frontier molecular
orbitals. The inhibitory activities of the compound with different classes
of bacteria were also investigated using molecular docking simulation.
... manual.html) [69]. Bortezomib docks with the corresponding protein receptor via AutoDock Vina, and compound-target pairs with docking fraction less than −5 kcal/mol are considered as binding pairs [70]. ...
The drug therapy for non-small cell lung cancer (NSCLC) have always been issues of poisonous side effect, acquired drug resistance and narrow applicable population. In this study, we built a novel network analysis method (difference- correlation- enrichment- causality- node), which was based on the difference analysis, Spearman correlation network analysis, biological function analysis and Bayesian causality network analysis to discover new therapeutic target of NSCLC in the sequencing data of BEAS-2B and 7 NSCLC cell lines. Our results showed that, as a proteasome subunit coding gene in the central of cell cycle network, PSMD2 was associated with prognosis and was an independent prognostic factor for NSCLC patients. Knockout of PSMD2 inhibited the proliferation of NSCLC cells by inducing cell cycle arrest, and exhibited marked increase of cell cycle blocking protein p21, p27 and decrease of cell cycle driven protein CDK4, CDK6, CCND1 and CCNE1. IPA and molecular docking suggested bortezomib has stronger affinity to PSMD2 compared with reported targets PSMB1 and PSMB5. In vitro and In vivo experiments demonstrated the inhibitory effect of bortezomib in NSCLC with different driven mutations or with tyrosine kinase inhibitors resistance. Taken together, bortezomib could target PSMD2, PSMB1 and PSMB5 to inhibit the proteasome degradation of cell cycle check points, to block cell proliferation of NSCLC, which was potential optional drug for NSCLC patients.
... 26 Its scoring function is better and derived from pairwise interactions between atoms based on surface distance. 27 For molecular docking, ligands and proteins were prepared by molecular graphics library tools (MGL tools). The details of various steps of preparations for docking of ligands with proteins are as follows. ...
Cancer is a mechanistically complex and diverse disease with a plethora of fundamental genetic and epigenetic factors. Signal transducer and activator of transcription-3 (STAT3) is a transcription factor, and its constitutive activation executes promotion of cellular proliferation, cell cycle, angiogenesis, metastasis, immunosuppression, and chemo-resistance in cancer cells. Here, we aimed to design natural potential STAT3 inhibitors. For this purpose, we investigated 92 phytochemical compounds by molecular docking studies because they are diversified, multitargeted, affordable, easily available, and less- or non-toxic. We selected only 6 compounds such as sarsasapogenin (L3), peiminine (L9), solasodine (L10), tormentic acid (L23), obacunone (L29), and echinocystic acid (L34) due to their greater binding affinity than reference STAT3 inhibitor (S3I-201) with STAT3. The study was further continued by molecular dynamic (MD) simulations and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The results of molecular docking showed that all selected ligands exhibited binding affinity range from -9.3 Kcal/mol to -7.9 Kcal/mol and predicted inhibition constant [Formula: see text] values range from 0.14 [Formula: see text]M to 1.5 [Formula: see text]M. These compounds showed effective hydrogen bonding and hydrophobic interactions with DNA binding domain as well as SH2-domain of STAT3. The MD simulations performed by nanoscale molecular dynamics (NAMD) calculated root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration ([Formula: see text]), solvent accessible surface area (SASA) and number of hydrogen bond dynamics. All selected ligands with protein exhibited stability over 120 ns by MD simulation. Moreover, these ligands showed favorable ADMET profiling and drug likeness. So, our current computational investigations showed that these novel drug candidates can be potential STAT3 inhibitors and evoke the scientific interest for their further verification by in vitro and in vivo studies.
... AutoDock Vina 1.1.2 was performed for molecular docking to explore the binding arrangement between ECH and SrtA [35]. The crystal structure of SrtA (PDB ID: 1T2P) was retrieved from the protein database (http:// www. ...
Methicillin-resistant Staphylococcus aureus (MRSA) is a pathogenic bacterium responsible for a range of severe infections, such as skin infections, bacteremia, and pneumonia. Due to its antibiotic-resistant nature, current research focuses on targeting its virulence factors. Sortase A (SrtA) is a transpeptidase that anchors surface proteins to the bacterial cell wall and is involved in adhesion and invasion to host cells. Through fluorescence resonance energy transfer (FRET), we identified echinacoside (ECH), a natural polyphenol, as a potential SrtA inhibitor with an IC50 of 38.42 μM in vitro. It was demonstrated that ECH inhibited SrtA-mediated S. aureus fibrinogen binding, surface protein A anchoring, and biofilm formation. The fluorescence quenching assay determined the binding mode of ECH to SrtA and calculated the KA-binding constant of 3.09 × 10⁵ L/mol, demonstrating the direct interaction between the two molecules. Molecular dynamics simulations revealed that ECH–SrtA interactions occurred primarily at the binding sites of A92G, A104G, V168A, G192A, and R197A. Importantly, the combination of ECH and vancomycin offered protection against murine models of MRSA-induced pneumonia. Therefore, ECH may serve as a potential antivirulence agent against S. aureus infections, either alone or in combination with vancomycin.
