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The profound impact of in silico studies for a fast-paced drug discovery pipeline is undeniable for pharmaceutical community. The rational design of novel drug candidates necessitates considering optimization of their different aspects prior to synthesis and biological evaluations. The affinity prediction of small ligands to target of interest for rank-ordering the potential ligands is one of the most routinely used steps in the context of virtual screening. So, the end-point methods were employed for binding free energy estimation focusing on evaluating simulation time effect. Then, a set of human aldose reductase inhibitors were selected for molecular dynamics (MD)-based binding free energy calculations. A total of 100[Formula: see text]ns MD simulation time was conducted for the ligand-receptor complexes followed by prediction of binding free energies using MM/PB(GB)SA and LIE approaches under different simulation time. The results revealed that a maximum of 30[Formula: see text]ns simulation time is sufficient for determination of binding affinities inferred from steady trend of squared correlation values (R 2 ) between experimental and predicted [Formula: see text]G as a function of MD simulation time. In conclusion, the MM/PB(GB)SA algorithms performed well in terms of binding affinity prediction compared to LIE approach. The results provide new insights for large-scale applications of such predictions in an affordable computational cost.

Histamine H 3 receptors (H 3 R), belonging to G-protein coupled receptors (GPCR) class A superfamily, are responsible for modulating the release of histamine as well as of other neurotransmitters by a negative feedback mechanism mainly in the central nervous system (CNS). These receptors have gained increased attention as therapeutic target for several CNS related neurological diseases. In the current study, we aimed to identify novel H 3 R ligands using in silico virtual screening methods. To this end, a combination of ligand- and structure-based approaches was utilized for screening of ZINC database on the homology model of human H 3 R. Structural similarity- and pharmacophore-based approaches were employed to generate compound libraries. Various molecular modeling methodologies such as molecular docking and dynamics simulation along with different drug likeness filtering criteria were applied to select anti-H 3 R ligands as promising candidate molecules based on different known parent lead compounds. In vitro binding assays of the selected molecules demonstrated three of them being active within the micromolar and submicromolar K i range. The current integrated computational and experimental methods used in this work can provide new general insights for systematic hit identification for novel anti-H 3 R agents from large compound libraries., (© 2018 John Wiley & Sons A/S.)

RON (Recepteur d'Origine Nantais) tyrosine kinase receptor is a promising target for therapeutic intervention in cancer therapy. The aim of this work was identification of RON-binding peptides using phage display and computational modeling their mode of binding. A 12-mer peptide phage library was utilized to perform biopanning against RON. The RON-binding ability of the selected peptide-displaying phage and their possible binding sites were examined by ELISA. Binding modes and affinities were also predicted by docking and molecular dynamics (MD) simulation. The results of ELISA experiment showed that P6 peptide displaying phage has higher affinity for RON compared to others and its binding site is located out of ligand binding site. Docking and MD simulation results also indicated higher affinity of P6 to RON as well as its exosite-binding feature. Taken together, our data suggest a capacity for P6 peptide (FEHSLYKEMTHL) to be utilized as RON binding agent, and hence be used for various purposes, including design of drug delivery systems for transferring cytotoxic agents to RON-positive cancer cells, interfering with RON signaling, peptidomimetics design, and diagnostic imaging.

Aldehyde oxidase (AO), an important enzyme in the biotransformation of drugs and xenobiotics, is inhibited by flavonoids. This enzyme can metabolize both aldehydes and N-heterocycles. In this work, a set of 15 flavonoids was assessed for inhibitory activity on the AO oxidation of vanillin as an aldehyde substrate. Spectrophotometrically determined IC50 values showed that myricetin, quercetin, and epicatechin were the most potent inhibitors. The results also revealed that the inhibition of vanillin oxidation by flavonoids was stronger than that of phenanthridine oxidation (an N-heterocyclic substrate) as reported previously. In order to investigate the important structural features responsible for the inhibitory effects of the studied flavonoids, a quantitative structure-activity relationship (QSAR) analysis was performed. This study showed that the size of the flavonoids was the most important factor inversely affecting their potencies. The QSAR model can be used more broadly to predict the AO inhibitory activity of flavonoid-like structures for application in food-drug and drug-drug interaction studies., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: Despite tremendous efforts made by scientific community during the outbreak of COVID‐19 pandemic, this disease still remains as a public health concern. Although different types of vaccines were globally used to reduce the mortality, emergence of new variants of SARS‐CoV‐2 is a challenging issue in COVID‐19 pharmacotherapy. In this context, target therapy of SARS‐CoV‐2 by small ligands is a promising strategy. Methods: In this investigation, we applied ligand‐based virtual screening for finding novel molecules based on nirmatrelvir structure. Various criteria including drug‐likeness, ADME, and toxicity properties were applied for filtering the compounds. The selected candidate molecules were subjected to molecular docking and dynamics simulation for predicting the binding mode and binding free energy, respectively. Then the molecules were experimentally evaluated in terms of antiviral activity against SARS‐CoV‐2 and toxicity assessment. Results: The results demonstrated that the identified compounds showed inhibitory activity towards SARS‐CoV‐2 Mpro. Conclusion: In summary, the introduced compounds may provide novel scaffold for further structural modification and optimization with improved anti SARS‐CoV‐2 Mpro activity. [ABSTRACT FROM AUTHOR]

Purpose: DOF (DNA-binding with One Finger) proteins are plant-specific transcription factors which mediate numerous biological processes. The purpose of the current study is to report new naturally occurring mutations in the gene encoding for one of the members of DOF proteins named DOF 4.2. Methods: The expression of zinc finger domain of DOF 4.2 (DOF 4.2-ZF) was investigated by first synthesis of cDNA library using different parts of Arabidopsis thaliana plant. Then the coding sequence for zinc finger domain of DOF 4.2 protein was prepared using nested PCR experiment and cloned into pGEX-6P-1 expression vector. Finally, the prepared construct was used for protein expression. Furthermore, molecular dynamics (MD) simulation was carried out to predict DNA binding affinity of DOF 4.2-ZF using AMBER package. Results: For the first time a new variant of DOF 4.2-ZF protein with three mutations was detected. One of the mutations is silent while the other two mutations lead to amino acid replacement (S18G) as well as introduction of a stop codon ultimately resulting in a truncated protein production. In order to investigate whether the truncated form is able to recognize DNA binding motif, MD simulations were carried out and the results showed that the chance of binding of DOF 4.2-ZF protein to cognate DNA in its truncated form is very low. Conclusion: The findings demonstrated that the observed mutations adversely affect the DNA binding ability of the truncated form of DOF4.2 if it is expressed in the mutant variant of A. thaliana used in this study. [ABSTRACT FROM AUTHOR]

Recently, multi‐target directed ligands have been of research interest for multifactorial disorders such as Alzheimer's disease (AD). Since H3 receptors (H3Rs) and cholinesterases are involved in pathophysiology of AD, identification of dual‐acting compounds capable of improving cholinergic neurotransmission is of importance in AD pharmacotherapy. In the present study, H3R antagonistic activity combined with anticholinesterase properties of two previously computationally identified lead compounds, that is, compound 3 (6‐chloro‐N‐methyl‐N‐[3‐(4‐methylpiperazin‐1‐yl)propyl]‐1H‐indole‐2‐carboxamide) and compound 4 (7‐chloro‐N‐[(1‐methylpiperidin‐3‐yl)methyl]‐1,2,3,4‐tetrahydroisoquinoline‐2‐carboxamide), was tested. Moreover, molecular docking and binding free energy calculations were conducted for binding mode and affinity prediction of studied ligands toward cholinesterases. Biological evaluations revealed inhibitory activity of ligands in nanomolar (compound 3: H3R EC50 = 0.73 nM; compound 4: H3R EC50 = 31 nM) and micromolar values (compound 3: AChE IC50 = 9.09 µM, BuChE IC50 = 21.10 µM; compound 4: AChE IC50 = 8.40 µM, BuChE IC50 = 4.93 µM) for H3R antagonism and cholinesterase inhibition, respectively. Binding free energies yielded good consistency with cholinesterase inhibitory profiles. The results of this study can be used for lead optimization where dual inhibitory activity on H3R and cholinesterases is needed. Such ligands can exert their biological activity in a synergistic manner resulting in higher potency and efficacy. [ABSTRACT FROM AUTHOR]

Histamine H3 receptors (H3R), belonging to G‐protein coupled receptors (GPCR) class A superfamily, are responsible for modulating the release of histamine as well as of other neurotransmitters by a negative feedback mechanism mainly in the central nervous system (CNS). These receptors have gained increased attention as therapeutic target for several CNS related neurological diseases. In the current study, we aimed to identify novel H3R ligands using in silico virtual screening methods. To this end, a combination of ligand‐ and structure‐based approaches was utilized for screening of ZINC database on the homology model of human H3R. Structural similarity‐ and pharmacophore‐based approaches were employed to generate compound libraries. Various molecular modeling methodologies such as molecular docking and dynamics simulation along with different drug likeness filtering criteria were applied to select anti‐H3R ligands as promising candidate molecules based on different known parent lead compounds. In vitro binding assays of the selected molecules demonstrated three of them being active within the micromolar and submicromolar Ki range. The current integrated computational and experimental methods used in this work can provide new general insights for systematic hit identification for novel anti‐H3R agents from large compound libraries. [ABSTRACT FROM AUTHOR]

[Display omitted] • New scaffolds for histamine H3 receptor ligands. • High drug-likeness of newly designed compounds by computational methods. • Selection of ligands by toxicological and ADME screening in silico. • Synthesis and proof of concept with one ligand selected. • Combination of diverse computational methods to the design of novel compounds with new scaffolds. During the past decades, histamine H 3 receptors have received widespread attention in pharmaceutical research due to their involvement in pathophysiology of several diseases such as neurodegenerative disorders. In this context, blocking of these receptors is of paramount importance in progression of such diseases. In the current investigation, novel histamine H 3 receptor ligands were designed by exploiting scaffold-hopping drug-design strategy. We inspected the designed molecules in terms of ADME properties, drug-likeness, as well as toxicity profiles. Additionally molecular docking and dynamics simulation studies were performed to predict binding mode and binding free energy calculations, respectively. Among the designed structures, we selected compound d2 and its demethylated derivative as examples for synthesis and affinity measurement. In vitro binding assays of the synthesized molecules demonstrated that d2 has lower binding affinity (K i = 2.61 μM) in radioligand displacement assay to hH 3 R than that of demethylated form (K i = 12.53 μM). The newly designed compounds avoid of any toxicity predictors resulted from extended in silico and experimental studies, can offer another scaffold for histamine H 3 R antagonists for further structure–activity relationship studies. [ABSTRACT FROM AUTHOR]

• Virtual screening was used for identifying two novel ligands antagonizing PDGF-B. • Inhibitory activity of the ligands was evaluated using in vitro bioassay. • Binding free energies were calculated for the ligand-protein complexes. • The results of in silico calculations were in agreement with in vitro bioassay. • The results can be used for design of novel anti-PDGF-B drugs. Platelet-derived growth factor (PDGF) is a family of growth factors with mitogenic and chemotactic activity. However, uncontrolled and overactivated PDGF signaling has been implicated in a variety of diseases, such as cancers and atherosclerosis. In this context, inhibition of PDGF-PDGFR signaling is of paramount importance in progression of such diseases. The purpose of the current study was to identify novel PDGF-B inhibitors using virtual screening methods. To this end, a combination of molecular modeling techniques such as molecular docking and dynamics simulation, as well as drug likeness filtering criteria, was applied to select anti-PDGF peptidomimetic candidates based on crystallography solved structure of an anti-PDGF-B monoclonal antibody named, MOR8457. In vitro biological assays of the selected compounds revealed two of them being active at micromolar IC 50 concentrations. The presented work can provide a framework for systematic peptidomimetic identification for anti-PDGF-B agents from large chemical libraries. [ABSTRACT FROM AUTHOR]