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Lactoferrin (Lf) was shown to exhibit its antiviral activity at an early phase of viral infection and a mechanism whereby the protein interacts with host cell surface molecules has been suggested. In this study, human Lf (HLf) and seven HLf-derived synthetic peptides (HLP) corresponding to the N-terminal domain of the native protein (1-47 amino acids sequence) were assayed for their capacity to prevent hepatitis B virus (HBV) infection and replication using the HepaRG and HepG2.2.2.15 cell lines. Of the series tested, four peptides showed 40-75% inhibition of HBV infection in HepaRG cells, HLP1-23, containing the GRRRR cationic cluster, being the most potent. Interestingly, this cluster is one of the two glycosaminoglycan binding sites of the native HLf involved in its antiviral activity; however, the mechanism of the HLP1-23 action was different from that of the full-length protein, the peptide inhibiting HBV infection when pre-incubated with the virus, while no effect was observed on the target cells. It is suggested that the cationic cluster is sufficient for the peptide to interact stably with negatively charged residues on the virion envelope, while the absence of the second glycosaminoglycan binding site prevents its efficient attachment to the cells. In conclusion, this peptide may constitute a non-toxic approach for potential clinical applications in inhibiting HBV entry by neutralizing the viral particles. J. Med. Virol. 85:780-788, 2013. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Most crystallized homo-oligomeric ion channels are highly symmetric, which dramatically decreases conformational space and facilitates building homology models (HMs). However, in molecular dynamics (MD) simulations channels deviate from ideal symmetry and accumulate thermal defects, which complicate the refinement of HMs using MD. In this work we evaluate the ability of symmetry constrained MD simulations to improve HMs accuracy, using an approach conceptually similar to Critical Assessment of techniques for protein Structure Prediction (CASP) competition: build HMs of channels with known structure and evaluate the efficiency of proposed methods in improving HMs accuracy (measured as deviation from experimental structure). Results indicate that unrestrained MD does not improve the accuracy of HMs, instantaneous symmetrization improves accuracy but not stability of HMs during subsequent unrestrained MD, while gradually imposing symmetry constraints improves both accuracy (by 5-50%) and stability of HMs. Moreover, accuracy and stability are strongly correlated, making stability a reliable criterion in predicting the accuracy of new HMs. Proteins 2010. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Brain presents very complex advanced protective mechanisms. However, these mechanisms occasionally fail due to risk factors represented by genetic, environmental or social stress and consequently, severe psychiatric disorders such as depression, schizophrenia or psychotic depression are induced. Under such circumstances, latest strategies in experimental and in silico neuroscience consider essential to identify new applications of already clinically-approved drugs for the treatment of psychiatric disorders but also as promoters of neurogenesis and neurites outgrowth. Results of recent studies suggested that antidepressants are able to induce neurogenesis and neurites outgrowth by their agonistic effects on 5-hydroxytryptamine receptor (5-HT), especially 5-HT 1A, and sigma1 receptor (σ1R), but many molecular aspects of these processes are still unclear. Here we present structural aspects of molecular complexes (5-HT 1A and σ1R and their ligands) revealed by experimental and in silico studies. Here we present the chemical structures-biological activity relationship (SAR) of these molecules revealed by recent experimental and in silico studies, offering a new perspective on the antidepressants mechanism as neurogenesis and neurites outgrowth promoters.

Xanthine-based molecules such as serine protease dipeptidyl peptidase 4 (DPP4) inhibitors are compounds often used in improving glycemic control in type 2 diabetic patients and also used for their effects as mild stimulants and as bronchodilators, notably in treating asthma symptoms. Here, we aim to better understand the molecular features affecting activity of xanthine-based DPP4 inhibitors such as sitagliptin and related compounds and use these features to de novo predict improved sitagliptin derivatives. To this end, we performed a clinical study to examine the efficacy and safety of once-daily 100 mg oral sitagliptin as monotherapy in Romanian patients with type 2 diabetes. This study indicates that sitagliptin effectively decreases the glycemic level and provides very good glycemic equilibrium. To predict putative new drugs with identical pharmacological effects at lower dosages, we generate QSAR models based on compound series containing 35 DPP4 inhibitors. We establish that the physicochemical parameters critical for DPP4 inhibitory activity are: hydrophobicity described by the logarithm of the octanol/water partition coefficient, counts of rotatable bonds, hydrogen bond donor and acceptor atoms, and topological polar surface area. The predictive power of our QSAR models is indicated by significant values of statistical coefficients: cross-validated correlation q2 (0.77), fitted correlation coefficient r2 (0.85) and standard error of prediction (0.34). Based on the established QSAR equations, we propose and analyse 19 new sitagliptin derivatives with possibly improved pharmacological effect as DPP4 inhibitors.