Preliminary in silico investigation of cox 2 selective inhibitors

We report herein an attempt to generate QSAR models for a large number of structurally diverse compounds (1078 compounds) whose affinities for cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2) were experimentally determined. Initially, individual QSAR models for COX-1 (M1) and COX-2 (M2) for biological activity were developed. A selectivity QSAR model, M3 was then developed using as dependent variable Y the differences in pIC50 values between COX-1 and COX-2. The statistical results for all three models showed a satisfactory to good statistical parameters where the values for squared correlation coefficient (coefficient of determination) for the training set are: M1: 0.872, M2: 0.797 respectively M3: 0.739. The predicted values of affinity in the case of all three models selected M1, M2 and respectively M3, are very good 84.88%, 91.12%, 79.59% which lead to very small diffrences between observed and predicted biological activity/selectivity (less than 0.5 logarithimic units)

Preliminary study of the blood brain barrier penetration of some organic compounds and drugs

Partial Least Squares (PLS) regression of blood–brain permeation data (logBB) including 348 diverse organic compounds and drugs was built using 903 Dragon descriptors. The prediction performance of the obtained PLS model is acceptable: the squared correlation coefficient (cumulative sum of squares of all the Y's explained by all extracted components) R 2 Y(CUM) = 0.822, the crossvalidated correlation coefficient (cumulative fraction of the total variation of the Y's that can be predicted by all the extracted components) Q 2 Y(CUM) = 0.640, the number of independent variables, X=487, for a dataset of 342 compounds (six compounds was outliers). The Y-randomization test demonstrated the absence of chance correlation which is confirmed by the lower values of regression line intercepts for R2 X(CUM) (0.307) and Q2 (CUM) (-0.320). The descriptors such as polar surface area (N,O and N,O,S,P polar contributions), octanol-water partition coefficient (Ghose-Crippen and Moriguchi), hydrophilic factor, complementary information content index and the number of H-bond donor atoms showed the largest Variables Importance in the Projection (VIP) values and can influence the logBB. The values of logBB predicted by our model display lower differences against experimental values of 342 compounds than logBB values predicted by QikProp

Preliminary investigation of common GSK3, PPARγ AND DPP IV chemical space

Cross-target biochemical experiments demonstrated that some molecules display an ample spectrum of biological activities which are therapeutically effective. In this regard we investigated the chemical space of the following targets GSK3, DPP IV and PPAR gamma since the DPP IV inhibitors, and PPAR gamma agonists are used to treat diabetes miellitus of type 2. Nevertheless, GSK-3 inhibitors have shown therapeutic potential for insulin resistant type-2 diabetes, the drug market does not register yet an inhibitor of GSK-2 for therapeutical use. The ChEMBL homo sapiens assay data for GSK-3, DPP IV and PPAR gamma were assembled into are database including 7599 compounds. GSK-3 assay comprise 2497 compounds, from which 1889 are unique divided into 428 chemotypes. DPP IV register 3482 compounds and 3026 were unique sharing 510 chemotypes. PPAR gamma incldes 1620 agonists from which 1333 are unique partitioned into 264 chemotypes. The chemical space of GSK3, DPP IV and PPAR gamma share 12 chemotypes, GSK3 and DPP IV share 30 chemotypes, DPP IV and PPAR gamma share 13 chemotypes, whereas GSK3 and PPAR gamma share 17 chemotypes. The 12 chemotypes active on all three proteins were superposed to develop a common pharmacophore which will be further used to identify novel chemotyes with potential biological activity

DFT study of long bonds in radical cations of sugar derivatives

We have performed DFT computations on radical cations of several monosaccharide derivatives, using the STO-3G and 3-21G basis sets. The obtained long bond lengths were compared with the values we have previously obtained using the RM1 and PM7 semi-empirical methods. The applied DFT methods offered smaller values for the long bond lengths, attaining only 1.6÷1.7 Å. Also, in contrast with the simple STO-3G basis set, which shows some exceptions, the more advanced 3-21G basis set always places the long bond in the correct C4-C5 position, as suggested by the EI-MS analyses

In Silico Study of Some Natural Flavonoids as Potential Agents against COVID-19: Preliminary Results

Flavonoids, widely distributed in fruits, vegetables, and medicinal herbs, are compounds with multiple biological benefits to human health from anti-inflammatory, antioxidant, anticancer, antibacterial to antiviral activity. Coronavirus disease 2019 (COVID-19), a serious concern in the world today, is a respiratory tract disease involving moderate to severe symptoms of pneumonia, with a major incidence in older people and patients having chronic diseases. This emergency health situation led us to evaluate the possible use of natural products to prevent respiratory diseases. The present study aims to report the potential of four natural flavonoids, known to have anti-inflammatory and antiviral activity, as anti-SARS-CoV-2 through their binding on the 6YNQ protein receptor. Molecular docking study with the FRED program was chosen as an appropriate tool to analyze the interaction of natural flavonoids, quercetin, luteolin, galangin, and naringenin, with the SARS-CoV-2 main protease and to rank the conformations through a scoring function to predict their binding affinity. Overall, our preliminary results indicate the potential of the titled natural flavonoids to fight the new coronavirus, COVID-19

COX Inhibition Profile and Molecular Docking Studies of Some 2-(Trimethoxyphenyl)-Thiazoles

Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used therapeutic agents that exhibit frequent and sometimes severe adverse effects, including gastrointestinal ulcerations and cardiovascular disorders. In an effort to obtain safer NSAIDs, we assessed the direct cyclooxygenase (COX) inhibition activity and we investigated the potential COX binding mode of some previously reported 2-(trimethoxyphenyl)-thiazoles. The in vitro COX inhibition assays were performed against ovine COX-1 and human recombinant COX-2. Molecular docking studies were performed to explain the possible interactions between the inhibitors and both COX isoforms binding pockets. Four of the tested compounds proved to be good inhibitors of both COX isoforms, but only compound A3 showed a good COX-2 selectivity index, similar to meloxicam. The plausible binding mode of compound A3 revealed hydrogen bond interactions with binding site key residues including Arg120, Tyr355, Ser530, Met522 and Trp387, whereas hydrophobic contacts were detected with Leu352, Val349, Leu359, Phe518, Gly526, and Ala527. Computationally predicted pharmacokinetic profile revealed A3 as lead candidate. The present data prove that the investigated compounds inhibit COX and thus confirm the previously reported in vivo anti-inflammatory screening results suggesting that A3 is a suitable candidate for further development as a NSAID

ColBioS-FlavRC: A Collection of Bioselective Flavonoids and Related Compounds Filtered from High-Throughput Screening Outcomes

Flavonoids, the vastest class of natural polyphenols, are extensively investigated for their multiple benefits on human health. Due to their physicochemical or biological properties, many representatives are considered to exhibit low selectivity among various protein targets or to plague high-throughput screening (HTS) outcomes. The aim of this study is to highlight reliable, bioselective compounds sharing flavonoidic scaffolds in HTS experiments. A filtering scheme was applied to remove undesired flavonoids (and related compounds) from confirmatory PubChem bioassays. A number of 433 compounds addressing various protein targets form the core of the collection of bioselective flavonoids and related compounds (ColBioS-FlavRC). With an additional set of 2908 inactive related compounds, ColBioS-FlavRC offers the grounds for method optimization and validation. We exemplified the use of ColBioS-FlavRC by pharmacophore modeling, subsequently (externally) validated for virtual screening purposes. The early enrichment capabilities of the pharmacophore hypotheses were measured by means of the median exponential retriever operating curve enrichment (MeROCE), a suited metric in comparative evaluations of virtual screening methods. ColBioS-FlavRC is available in the Supporting Information and is freely accessible for further studies