Water PMF for predicting the properties of water molecules in protein binding site

Water is an important component in living systems and deserves better understanding in chemistry and biology. However, due to the difficulty of investigating the water functions in protein structures, it is usually ignored in computational modeling, especially in the field of computer‐aided drug design. Here, using the potential of mean forces (PMFs) approach, we constructed a water PMF (wPMF) based on 3946 non‐redundant high resolution crystal structures. The extracted wPMF potential was first used to investigate the structure pattern of water and analyze the residue hydrophilicity. Then, the relationship between wPMF score and the B factor value of crystal waters was studied. It was found that wPMF agrees well with some previously reported experimental observations. In addition, the wPMF score was also tested in parallel with 3D‐RISM to measure the ability of retrieving experimentally observed waters, and showed comparable performance but with much less computational cost. In the end, we proposed a grid‐based clustering scheme together with a distance weighted wPMF score to further extend wPMF to predict the potential hydration sites of protein structure. From the test, this approach can predict the hydration site at the accuracy about 80% when the calculated score lower than ?4.0. It also allows the assessment of whether or not a given water molecule should be targeted for displacement in ligand design. Overall, the wPMF presented here provides an optional solution to many water related computational modeling problems, some of which can be highly valuable as part of a rational drug design strategy. © 2012 Wiley Periodicals, Inc.     

TargetATPsite: A template‐free method for ATP‐binding sites prediction with residue evolution image sparse representation and classifier ensemble

Understanding the interactions between proteins and ligands is critical for protein function annotations and drug discovery. We report a new sequence‐based template‐free predictor (TargetATPsite) to identify the Adenosine‐5′‐triphosphate (ATP) binding sites with machine‐learning approaches. Two steps are implemented in TargetATPsite: binding residues and pockets predictions, respectively. To predict the binding residues, a novel image sparse representation technique is proposed to encode residue evolution information treated as the input features. An ensemble classifier constructed based on support vector machines (SVM) from multiple random under‐samplings is used as the prediction model, which is effective for dealing with imbalance phenomenon between the positive and negative training samples. Compared with the existing ATP‐specific sequence‐based predictors, TargetATPsite is featured by the second step of possessing the capability of further identifying the binding pockets from the predicted binding residues through a spatial clustering algorithm. Experimental results on three benchmark datasets demonstrate the efficacy of TargetATPsite. © 2013 Wiley Periodicals, Inc.     

A Correlation of the Drag Force Coefficient on a Sphere with Interface Slip at Low and Intermediate Reynolds Numbers

The hydrodynamics of a sphere with interface slip has been numerically investigated for flows of Reynolds number ranging 0 < Re ≤ 75. A simple correlation of the drag force coefficient in the present of interface slip has been derived based on our numerical simulations. The correlation takes the slip coefficient and Reynolds number as two input parameters. By comparing results found in the literature, we believe that the present correlation is more accurate; it provides a source for future experiment study and for numerical simulations of large multi-particle system where the interface slip is important.     

INDUSTRIAL NEWS

Interactions between monolayers of trilaurylamine (TLA) and various water-soluble corrosion, hydrate and scale inhibitors, as well as acetic acid and FeCl₂, have been studied by means of the Langmuir technique, The water-soluble compounds were present in the subphase before TLA was spread. Their influence on the monolayer properties were measured by means of surface pressure-area ( k-A) isotherms and constant surface pressure-area relaxation measurements. All the added water soluble species gave rise to monolayer expansion. The monolayer expansion observed for TLA at pH 1, increased when FeCl₂ was added to the subphase at the same pH. Polyethyleneglycols with molecular weight higher than 200 destabilized totally the TLA-monolayer, probably due to bending and folding into multilayers. Monolayer expansion and film instability increased with increased acetic acid concentrations. The destabilization mechanism in this case was most likely due to a combination of nucleation and dissolution of film components into the subphase. The corrosion inhibitor Dyno KI 384 had a higher surface activity than TLA. Hence the monolayer     

Molecular structural investigations of quinoxaline derivatives through 3D-QSAR,molecular docking,ADME prediction and pharmacophore modeling studies for the search of novel antimalarial agent

In the present article, a dataset of 63 quinoxaline derivatives were taken for antimalarial activity and pharmacophore were developed. Atom based method was used to develop a three dimensional quantitative structure activity relationship (3D-QSAR) model. On comparison of all statistical parameters, model AHRRR23 was found to be the most effective and predictive QSAR model as it satisfied all statistical parameters of a good model. The model AHRRR23 showed an adequate R² value for the training set 0.9446, good predictive power with Q² of 0.6409, good F- value, low SD 0.1218 value and outstanding Pearson-R values and low RMSE 0.2779 values of the model. The docking studies also gives very good results with good RMSD values. 3D QSAR, docking and ADME studies exhibits that the developed model could be employed as a potential lead for further study as antimalarial drug.     

Theoretical Perspectives in Organocatalysis

It is clear that the field of organocatalysis is continuously expanding during the last decades. With increasing computational capacity and new techniques, computational methods have provided a more economic approach to explore different chemical systems. This review offers a broad yet concise overview of current state-of-the-art studies that have employed novel strategies for catalyst design. The evolution of the all different theoretical approaches most commonly used within organocatalysis is discussed, from the traditional approach, manual-driven, to the most recent one, machine-driven.     

Dynamic Effects in Intramolecular Schmidt Reactions: Entropy,Electrostatic Drag,and Selectivity Prediction

Electrostatic drag in the intramolecular Schmidt reactions of azidopropylcyclohexanones is characterized using density functional theory (DFT) calculations and direct dynamics simulations. Despite resulting from enthalpically favorable interactions, electrostatic drag slows down N₂ loss during formation of bridged lactam products, an effect with implications for controlling product selectivity.