Homology modeling is one of the computational structure prediction methods that are used to determine protein 3D structure from its amino acid sequence. It is considered to be the most accurate of the computational structure prediction methods. It consists of multiple steps that are straightforward and easy to apply. There are many tools and servers that are used for homology modeling. There is no single modeling program or server which is superior in every aspect to others. Since the functionality of the model depends on the quality of the generated protein 3D structure, maximizing the quality of homology modeling is crucial. Homology modeling has many applications in the drug discovery process. Since drugs interact with receptors that consist mainly of proteins, protein 3D structure determination, and thus homology modeling is important in drug discovery. Accordingly, there has been the clarification of protein interactions using 3D structures of proteins that are built with homology modeling. This contributes to the identification of novel drug candidates. Homology modeling plays an important role in making drug discovery faster, easier, cheaper, and more practical. As new modeling methods and combinations are introduced, the scope of its applications widens.

A pharmacophore describes the framework of molecular features that are vital for the biological activity of a compound. Pharmacophore models are built by using the structural information about the active ligands or targets. The pharmacophore models developed are used to identify novel compounds that satisfy the pharmacophore requirements and thus expected to be biologically active. Drug discovery process is a challenging task that requires the contribution of multidisciplinary approaches. Pharmacophore modeling has been used in various stages of the drug discovery process. The major application areas are virtual screening, docking, drug target fishing, ligand profiling, and ADMET prediction. There are several pharmacophore modeling programs in use. The user must select the right program for the right purpose carefully. There are new developments in pharmacophore modeling with the involvement of the other computational methods. It has been integrated with molecular dynamics simulations. The latest computational approaches like machine learning have also played an important role in the advances achieved. Moreover, with the rapid advance in computing capacity, data storage, software and algorithms, more advances are anticipated. Pharmacophore modeling has contributed to a faster, cheaper, and more effective drug discovery process. With the integration of pharmacophore modeling with the other computational methods and advances in the latest algorithms, programs that have better perfomance are emerging. Thus, improvements in the quality of the phamacophore models generated have been achieved with this new developments.

The tumorigenic properties of prostate cancer are regulated by advanced hormonal regulation‐mediated complex molecular signals. Therefore, characterizing the regulation of these signal transduction systems is crucial for understanding prostate cancer biology. Recent studies have shown that endoplasmic reticulum (ER)‐localized protein quality control mechanisms, including ER‐associated degradation (ERAD) and unfolded protein response (UPR) signaling contribute to prostate carcinogenesis and to the development of drug resistance. It has also been determined that these systems are tightly regulated by androgens. However, the role of estrogenic signaling in prostate cancer and its effects on protein quality control mechanisms is not fully understood. Herein, we investigated the regulatory effects of estrogens on ERAD and UPR and their impacts on prostate carcinogenesis. We found that estrogens strongly regulated the ERAD components and IRE1⍺ branch of UPR by Er⍺/β/AR axis. Besides, estrogenic signaling rigorously regulated the tumorigenicity of prostate cancer cells by promoting c‐Myc expression and epithelial‐mesenchymal transition (EMT). Moreover, estrogenic signal blockage significantly decreased the tumorigenic features of prostate cancer cells. Additionally, simultaneous inhibition of androgenic/estrogenic signals more efficiently inhibited tumorigenicity of prostate cancer cells, including proliferation, migration, invasion and colonial growth. Furthermore, computational‐based molecular docking, molecular dynamics simulations and MMPBSA calculations supported the estrogenic stimulation of AR. Present findings suggested that ERAD components and IRE1⍺ signaling are tightly regulated by estrogen‐stimulated AR and Er⍺/β. Our data suggest that treatment approaches targeting the co‐inhibition of androgenic/estrogenic signals may pave the way for new treatment approaches to be developed for prostate cancer.

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Background: The need for the development of novel antimicrobial agents is apparent as infectious diseases are increasing and resistance is rapidly developing against the drugs used in the treatment. Objective: This study aimed at the synthesis, antimicrobial susceptibility testing, and computational elucidation of the mechanism of action of benzoxazole derivatives. It also aimed at comparing the results obtained in this study with the previous studies by our group. This would pave the way for designing novel molecules with better antimicrobial activity. The other goal was pharmacophore analysis and in silico ADMET analysis of them. Methods: In this study, synthesis, antimicrobial susceptibility testing, molecular docking, pharmacophore analysis, and ADMET prediction were carried out. Results: The antimicrobial activity studies demonstrated that the synthesized compounds were active against standard strains and clinical isolates at high concentrations. Then, the antimicrobial testing results were compared to similar benzoxazoles tested by our group previously. Benzoxazole derivatives without methylene bridge between oxazole and phenyl ring were found to be more active than those with the methylene bridge. This was also confirmed by molecular modeling undertaken in this study. The computational results indicated that the antibacterial activity could be achieved by DNA gyrase inhibition. Pharmacophore analysis showed that hydrogen bond acceptor (HBA), hydrogen bond donor (HBD), and hydrophobicity features would contribute to the inhibition. In addition, in silico ADMET property investigation of the compounds exhibited that they had the desired pharmacokinetics. Conclusion: Although antibacterial activity by inhibiting DNA gyrase is selective, the synthesized compounds were active at much higher concentrations than the standards. Therefore, in prospective antimicrobial studies, it is better to focus on benzoxazole derivatives without the methylene bridge. Since the compounds had suitable in silico ADMET properties, screening them against the other pharmacologic activities should be carried out. It is recommended to support the molecular modeling results with in vitro or in vivo studies.

Essential oils (EO), as new bioactive compounds, have been used for pharmaceutical applications. In this study, EO of Niaouli was found to have a high content in 1,8-cineole (58.53%). Furthermore, pinene, α-terpineol, nerolidol and ledene were found to be its components with an abundance of above 2%. Niaouli EO also had effects as inhibitor of Pseudomonas aeruginosa PAO1 biofilm formation (p<0.05). In the molecular docking study, this effect was explored. The natural ligand OdDHL, the bound ligand TP-1 (Triphenyl-1), the major component 1,8-cineole and the other components with significant abundance were docked against the binding region of the LasR protein. The docking study exhibited that 1,8-cineole together with the other components investigated could inhibit LasR competitively. Its effect on cell viability was also HIGHLIGHTS• Essential oil (EO) of Niaouli is an inhibitor on biofilm formation of P. aeruginosa.• The main components of Niaouli EO act as possible inhibitors of LasR.• The inhibition effect of these molecules on LasR is verified by molecular docking.• Niaouli EO has effects on cell viability of fibroblast cells at high concentrations.• Niaouli is a valuable essential oil for pharmaceutical applications.Onem, E; et al.

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