3D-QSAR and docking studies on piperidine-substituted diarylpyrimidine analogues as HIV-1 reverse transcriptase inhibitors

Hybrid 2D/3D-quantitative structure-activity relationship studies on the bioactivities and molecular mechanism of antibacterial peptides

Antimicrobial peptide (AMP) is the polypeptide, which protects the organism avoiding attack from pathogenic bacteria. Studies have shown that there were some antimicrobial peptides with molecular action mechanism involved in crossing the cell membrane without inducing severe membrane collapse, then interacting with cytoplasmic target-nucleic acid, and exerting antibacterial activity by interfacing the transmission of genetic information of pathogenic microorganisms. However, the relationship between the antibacterial activities and peptide structures was still unclear. Therefore, in the present work, a series of AMPs with a sequence of 20 amino acids was extracted from DBAASP database, then, quantitative structure-activity relationship (QSAR) methods were conducted on these peptides. In addition, novel antimicrobial peptides with  stronger antimicrobial activities were designed according to the information originated from the constructed models. Hence, the outcome of this study would lay a solid foundation for the in-silico design and exploration of novel antibacterial peptides with improved activity activities.

3D-QSAR and Docking Studies on Pyrimidine Derivatives of Second-Generation ALK Inhibitors

Anaplastic lymphoma kinase (ALK) is a promising target for the treatment of non-small cell lung cancer. Under crizotinib treatment, drug resistance and progressive disease appeared after the point mutations arising in the kinase domain of ALK. Second-generation ALK inhibitors can solve the deficiencies of the first generation, especially the drug resistance in cancer chemotherapy. Ceritinib (LDK378), a pyrimidine derivative, for example, can inhibit the activity of ALK with an IC50 value of 40.7 nmol/L, and can experience disease progression after initial treatment with crizotinib. Unfortunately, clear structure–activity relationships have not been identified to date, impeding the rational design of future compounds possessing ALK inhibition activity. To explore interesting insights into the structures of pyrimidine derivatives that influence the activities of the second-generation ALK inhibitors, three-dimensional quantitative structure–activity relationship (3D-QSAR) and molecular docking were performed on a total of 45 derivatives of pyrimidine. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques were used to generate 3D-QSAR models. CoMFA and CoMSIA were performed using the Sybyl X 2.0 package. Molecular docking analysis was performed using the Surflex-Dock module in SYBYL-X 2.0 package. We found in the CoMFA model that the non-cross-validated r2 value was 0.998, the cross-validated q 2 value was 0.663, and the F statistic value was 2,401.970, while the r2 value was 0.988; q 2 value was 0.730, and F value was 542.933 in CoMSIA models, suggesting the good predictability of the CoMFA and CoMSIA models. 3D contour maps and docking results suggested that different groups on the core parts of the compounds could enhance the biological activities. Based on these results, the established 3D-QSAR models and the binding structures of ALK inhibitors obtained favor the prediction of the activity of new inhibitors and will be helpful in the reasonable design of ALK inhibitors in the future.

An Overview of Antiretroviral Agents for Treating HIV Infection in Paediatric Population

Paediatric Acquired ImmunoDeficiency Syndrome (AIDS) is a life-threatening and infectious disease in which the Human Immunodeficiency Virus (HIV) is mainly transmitted through Mother-To- Child Transmission (MTCT) during pregnancy, labour and delivery, or breastfeeding. This review provides an overview of the distinct therapeutic alternatives to abolish the systemic viral replication in paediatric HIV-1 infection. Numerous classes of antiretroviral agents have emerged as therapeutic tools for downregulation of different steps in the HIV replication process. These classes encompass Non- Nucleoside Analogue Reverse Transcriptase Inhibitors (NNRTIs), Nucleoside/Nucleotide Analogue Reverse Transcriptase Inhibitors (NRTIs/NtRTIs), INtegrase Inhibitors (INIs), Protease Inhibitors (PIs), and Entry Inhibitors (EIs). Co-administration of certain antiretroviral drugs with Pharmacokinetic Enhancers (PEs) may boost the effectiveness of the primary therapeutic agent. The combination of multiple antiretroviral drug regimens (Highly Active AntiRetroviral Therapy - HAART) is currently the standard therapeutic approach for HIV infection. So far, the use of HAART offers the best opportunity for prolonged and maximal viral suppression, and preservation of the immune system upon HIV infection. Still, the frequent administration of high doses of multiple drugs, their inefficient ability to reach the viral reservoirs in adequate doses, the development of drug resistance, and the lack of patient compliance compromise the complete HIV elimination. The development of nanotechnology-based drug delivery systems may enable targeted delivery of antiretroviral agents to inaccessible viral reservoir sites at therapeutic concentrations. In addition, the application of Computer-Aided Drug Design (CADD) approaches has provided valuable tools for the development of anti-HIV drug candidates with favourable pharmacodynamics and pharmacokinetic properties.

Docking-based 3D-QSAR and pharmacophore studies on diarylpyrimidines as non-nucleoside inhibitors of HIV-1 reverse transcriptase

Diarylpyrimidines (DAPYs), a type of effective HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs), have been considered as one of the most successful agents for treating AIDS. A number of structurally diverse DAPYs have been designed and synthesized in the past decade, and most of them exhibited potent anti-HIV-1 activities; however, the structure-activity relationships of recently reported DAPYs and their pharmacophore features that interacted with HIV-1 reverse transcriptase (RT) remain to be studied. In the present study, molecular docking studies were first performed on three novel classes of DAPYs to study their binding pattern in the HIV-1 RT. Based on the docking conformations of these DAPYs, 3D-QSAR models were constructed using CoMSIA and Topomer CoMFA methods, and pharmacophore models were also built using distance comparison technique. All selected DAPYs presented preferred U- or L-shaped conformations while being docked into the non-nucleoside inhibitor-binding pocket of the HIV-1 RT. The best CoMSIA model exhibited powerful predictivity, with satisfactory statistical parameters such as a q² of 0.572, an r² of 0.952, and an [Formula: see text] of 0.728. Contour maps of the best CoMSIA model were in accordance with those of the Topomer CoMFA model, giving the insight into the feature requirements of DAPYs for the anti-HIV-1 activity. Three potential pharmacophore models were constructed, and each of them was consisted of five hypothesis features. All results suggested that the aromatic ring on the left wing of DAPYs and the central pyrimidine ring contained key pharmacophore features for the anti-HIV-1 activity, and also indicated that the right wing of DAPYs had potential for further structural modification to improve activity. Eight novel DAPY molecules with potential anti-HIV-1 activities were designed on the basis of the obtained results. The findings in this study might provide important information for further design and development of novel HIV-1 NNRTIs.

Quantitative structure-activity relationship of anti-HIV integrase and reverse transcriptase inhibitors using norm indexes

The development of new and safe anti-human immunodeficiency virus (anti-HIV) drugs has been an urgent task for medical research recently. Herein, based on the norm-index descriptors proposed in this work and previous works, a couple of models were developed for investigating the quantitative structure-activity/toxicity relationship (QSAR/QSTR) of dual-target anti-HIV integrase (IN) and reverse transcriptase (RT) inhibitors. The validation results proved that the developed models were stable and reliable, both in statistical quality and predictive capacity. Moreover, potential dual-target inhibitors with high activity and low toxicity were deduced from the developed models; molecular docking results indicated that these inhibitors could interact with some important residues of HIV IN and RT through H-bonding. Accordingly, the norm indexes descriptors proposed by this work might be helpful for the research and development of dual-target anti-HIV drugs.

Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking

DNA repair enzyme O⁶-methylguanine-DNA methyltransferase (MGMT), which plays an important role in inducing drug resistance against alkylating agents that modify the O⁶ position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O⁶-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR) study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment) were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Q_cv² = 0.672 and R_ncv² = 0.997) and CoMSIA (Q_cv² = 0.703 and R_ncv² = 0.946) models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Q_ext² = 0.691, R_pred² = 0.738 and slope k = 0.91) was observed with acceptable external test-set validation values rather than the CoMSIA model (Q_ext² = 0.307, R_pred² = 0.4 and slope k = 0.719). Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity.

3D-QSAR (CoMFA, CoMFA-RG, CoMSIA) and molecular docking study of thienopyrimidine and thienopyridine derivatives to explore structural requirements for aurora-B kinase inhibition

Aurora-B kinase plays a crucial role in cell cycle events and is identified as an important factor in regulation of spindle check point assembly. Thus, it can be proved as an important target in the field of oncology. 3D-QSAR model was generated using 54 molecules reported in literature containing thienopyrimidine and thienopyridine as scaffolds. All molecules were aligned using Distill function in Sybyl X1.2. This generated best model of CoMFA-RG (Region focusing) and CoMSIA were statistically significant with correlation coefficient r(2)ncv of 0.97, for both & Leave one out coefficient (LOO) q(2) of 0.70 and 0.72, respectively. Best CoMSIA model was built up using various combination of descriptors and proved statistical significant among all models. Best CoMFA-RG and CoMSIA models were validated by 12 test set molecules giving satisfactory prediction (r(2)pred) values of 0.86 and 0.88, respectively. External test set validation was performed using 20 molecules and satisfactory prediction of their biological activity was found. Active compounds were docked on protein (PDB ID: 4C2V) by GOLD module and revealed important interactions with amino acids at ATP-binding region. These data explored insight requirements for Aurora-B inhibition which might be fruitful for understanding mechanisms with kinase ligand interactions.