The peptide biological screening represents a difficult task due to the complexity of the amino-acid sequences. One solution is the encoding of the molecular information using complex networks or graphs of the peptides into QSAR-like models in Web tools. Bio-AIMS contains free Web tools on an Artificial Intelligence Model Server in Biosciences: http://bio-aims.udc.es/TargetPred.php. These in silico peptide screening tools are implementing models to predict different protein activities, drug – protein and protein – protein interactions. The inputs are using 3D protein structures or 1D peptide amino acid sequences and the SMILES formulas for drugs, and the classification models are based on Machine Learning techniques. The Web tools are implemented using Python, PHP and XHTML programming languages.

Single-walled carbon nanotubes (SWNTs) are group of new substances with specific cylindrical architecture of their molecules. The dispersion of SWNTs in different organic solvents is parameter that can be valuable information for development of nanomaterials. The CORAL software is a tool to build up model for different endpoints using the Monte Carlo technique. In this work, the ability of the CORAL software to be a tool to predict dispersion of SWCTs in different organic solvents demonstrated.

A fresh wave of Dengue infection, particularly Dengue serotype 1and 3, have been observed all across India in recent times and has led to several fatalities. Since the surface situated envelope protein of the dengue virion is responsible for virus entry into the host cell, we have laid special emphasis on its characterization and analyses of the envelope gene with an aim to eventually develop inhibitors of the dengue virus. There are four serotypes of the dengue virus of which types 1 and 3 are the most widely prevalent in India. 2D graphical representations of the envelope gene from various countries show that the gene from an Indian dengue type 1 virus bears a strong resemblance to the gene from Malayasia, whereas in the case of dengue type 3, the Indian strain representation shows strong likeness to strains from North America. Phylogenetic trees using alignment procedures also bear this out, implying an inherent cross-national spread of the dengue virus. Moreover, hydropathy analysis shows that amino acid compositional changes are tending to increase hydrophobic residues in the dengue type 3 viruses leading to morphologtical changes that may explain, in part, the higher pathogenicity of the dengue virus in India in recent times. These exercises serve to show the urgency of comprehensive genetic surveillance of the dengue virus to anticipate further damaging changes in the viral sequence.

Hub proteins in interaction networks involved in signaling pathways are known to have more disordered residues than non-hubs. Since the signaling mechanisms involving PPI are regulated by phosphorylation, disordered interfaces could be thought to be extremely phosphorylated. In the present study we sought to map the phosphorylated sites onto disordered regions on interacting proteins-Interactomes and non-interacting proteins-Negatomes. Dataset of non-interacting protein included 784 proteins retrieved from Negatome database 2.0. 2252 interacting proteins were retrieved from “GeneMania”. Intrinsically disordered regions were predicted with “Disopred” program. The binding interfaces were defined by “PDBePISA” server, while, phosphorylation sites were derived from “NetPhos” program. All phosphorylation sites were mapped onto protein structures using alignments calculated by the MUSCLE program. As anticipated, the extent of phosphorylation in interactomes were significantly higher in disordered regions to its ordered counter parts (p=0.04). Insights revealed that the disordered regions in negatome were sparse in comparison to those in interactomes (p<0.0024). Declined phosphorylated sites were observed in negatomes. The widespread non-flexible and ordered regions in the negatomes confer the non interacting nature of the protein in turn makes it poor participant in signal transduction that involves phosphorylation. Our study sheds light on the importance of phosphorylated sites on disordered regions as a mark to decide whether protein would possibly interact or not.

Genetic algorithms are search and optimization techniques which have their origin and inspiration in the world of biology. They provide very good results in different kind of problems, but they are not free of problems. One of the most common problems that may arise with these techniques is that, despite a few generations obtain an approximation to the solution of the problem, they need considerably more to adjust to the final solution. To solve this problem Nature gives us, another time, a valid option. Fine Tuning techniques can model this transmission of knowledge between generations making slight variations in offspring before inserting it into the next generation. For its implementation, a new individual is generated from a solution (non best), changing slightly their genes. It can be performed by means a new Genetic Algorithm, with a lower number of individuals and its own configuration. On this way, solutions avoid local minima and introduce more variability in the global population that increase the possibilities to achieve the best solution. The developed solution uses this approach within a generic tool that makes possible that the user provides their own fitness functions to add any kind of problems. The software will allow to parametrize the execution and will show several graphics to control the evolution. Furthermore, to minimize the time for obtaining solutions the assessment of individuals is made under a distributed scheme. The control of the implementation of Genetic Algorithm will be made from a master computer, which delegated to other slave devices for evaluation and, if necessary, apply fine tuning.

Background: Streblusol E, a phenolic phytoconstituents of Streblus asper is a potential antihepatitis B viral agent. Objective: Current study is to mechanistically analyze the probable site of action for streblusol E. Material and methods: Streblusol E has been docked with EF3-CaM adenylyl cyclase(1PK0), deoxycytidine kinase(2NOA), human nucleoside diphosphate kinase(3FKB), human Hepatitis B Viral Capsid(1QGT) and hepatitis B X-interacting protein(3MSH) proteins using GRIP docking methodology. Results: Results revealed its preferential intractability towards 1PK0 i.e. EF3-CaM adenylyl cyclase and 1QGT i.e. human hepatitis B viral capsid(HBCAG) compared with reference ligand like adefovir diphosphate(active metabolite of adefovir), lamivudine, tenofovir monophosphate(active metabolite of tenofovir) and tenofovir diphosphate(active metabolite of tenofovir). Drug metabolism and pharmacokinetics studies did affirm that Streblusol E possessed all the desired drug Likeness potential. According to Derek Nexus predictions, Streblusol E did not carry potential toxicities like carcinogenicity, mutagenicity genotoxicity and developmental toxicity, providing further impetus for discovery and clinical development of semi-synthetic analogs of Streblusol E. Conclusion: The present study successfully denotes the docking studies and ADMET profile of streblusol E from Streblus asper.

Sirtuin type-1(SIRT1) is a regulator of various biosynthetic pathways via activation of peroxisome proliferator-activated receptor-γ and interacting with adenosine-mono-phosphate kinase. SIRT1 is the important target for various neurodegenerative, cancer and metabolic disorders as well as aging medicine. Keeping in view of the above fact, we considered novel 1,3,4-thiadiazole derivatives series for SIRT1 screening, which was performed through virtual screening,  homological modeling, docking and computational studies. On the basis of available molecular structure in protein data bank of SIRT1 protein, we calculated the interaction energy designed molecules. The interaction energy of designed compound VR3 closely better than resveratrol (̴ 6.4 kcal/mol). Among of them the VR 3 shown the best conformation fitting stability in the binding site of SIRT1 predicted by MD (Molecular dynamics) simulation for 2.5ns. Therefore, the designed compounds have good binding affinities to SIRT1 target, would serve better lead compound for antiaging screening for future drug design perspective.  

In this communication we summarized our previous in-depth review (Current Topics in Medicinal Chemistry, 2008, Vol. 8, No. 18.) on the legal aspects of the use of software and computational models in Chemoinformatics. An overview of relevant international tax issues on the use of software is also presented.

Abstract: In this work, we developed a multi-target model for neuroprotective compounds reported in the CHEMBL database. The model predicted correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80-90% in training and external validation series. This is model can different outcomes for >30 experimental measures in >400 different experimental protocols and related to >150 molecular and cellular targets present in 11 different organisms (including human). After that, we reported by the first time, the synthesis, characterization, and experimental assays of new series of chiral 1,2-rasagiline carbamate derivatives; not reported in previous works. This work is a synopsis of the results presented in our previous paper: Int J Mol Sci. 2014 Sep 24;15(9):17035-64. doi: 10.3390/ijms150917035.

A combination of experimental and theoretical approaches is proposed to determine the best template and conditions to synthesized a bio-active open mesopore structure material with a 3D- sponge-like network similar than those existed in trabecular bone with a consequent saving of time and products. Specifically, we discuss the possibility of combining experimental methods with theoretical methods that have been published in J Mater Sci 2012, 47, 2837-2844 and Langmuir 2015, doi: 10.1021/acs.langmuir.5b03074, respectively. The strategy proposed opens a new gate to the rational design of 3D hierarchically scaffolds for bone repair in the future.