Predicting drug–drug interactions through drug structural similarities and interaction networks incorporating pharmacokinetics and pharmacodynamics knowledge

Additional file 1. Table S1. Average structural similarity scores for the DDI/non–DDI pairs in the network of each De. Table S2-1. Top 10 predicted drugs with DDIs for warfarin. Table S2-2. Top 10 predicted drugs with DDIs for simvastatin. Table S3. Four-fold cross-validation test results. Text S1. Drugs that show DDI (DrugBank ID). Figure S1. Illustration of construction of training and test set for 4-fold cross validation. Figure S2. ROC curves using the models with score set 1 in a 4-fold validation

A knowledge-guided strategy for improving the accuracy of scoring functions in binding affinity prediction

<p>Abstract</p> <p>Background</p> <p>Current scoring functions are not very successful in protein-ligand binding affinity prediction albeit their popularity in structure-based drug designs. Here, we propose a general knowledge-guided scoring (KGS) strategy to tackle this problem. Our KGS strategy computes the binding constant of a given protein-ligand complex based on the known binding constant of an appropriate reference complex. A good training set that includes a sufficient number of protein-ligand complexes with known binding data needs to be supplied for finding the reference complex. The reference complex is required to share a similar pattern of key protein-ligand interactions to that of the complex of interest. Thus, some uncertain factors in protein-ligand binding may cancel out, resulting in a more accurate prediction of absolute binding constants.</p> <p>Results</p> <p>In our study, an automatic algorithm was developed for summarizing key protein-ligand interactions as a pharmacophore model and identifying the reference complex with a maximal similarity to the query complex. Our KGS strategy was evaluated in combination with two scoring functions (X-Score and PLP) on three test sets, containing 112 HIV protease complexes, 44 carbonic anhydrase complexes, and 73 trypsin complexes, respectively. Our results obtained on crystal structures as well as computer-generated docking poses indicated that application of the KGS strategy produced more accurate predictions especially when X-Score or PLP alone did not perform well.</p> <p>Conclusions</p> <p>Compared to other targeted scoring functions, our KGS strategy does not require any re-parameterization or modification on current scoring methods, and its application is not tied to certain systems. The effectiveness of our KGS strategy is in theory proportional to the ever-increasing knowledge of experimental protein-ligand binding data. Our KGS strategy may serve as a more practical remedy for current scoring functions to improve their accuracy in binding affinity prediction.</p

Adaptive dynamic disturbance strategy for differential evolution algorithm

To overcome the problems of slow convergence speed, premature convergence leading to local optimization and parameter constraints when solving high-dimensional multi-modal optimization problems, an adaptive dynamic disturbance strategy for differential evolution algorithm (ADDSDE) is proposed. Firstly, this entails using the chaos mapping strategy to initialize the population to increase population diversity, and secondly, a new weighted mutation operator is designed to weigh and combinemutation strategies of the standard differential evolution (DE). The scaling factor and crossover probability are adaptively adjusted to dynamically balance the global search ability and local exploration ability. Finally, a Gauss perturbation operator is introduced to generate a random disturbance variation, and to accelerate premature individuals to jump out of local optimization. The algorithm runs independently on five benchmark functions 20 times, and the results show that the ADDSDE algorithm has better global optimization search ability, faster convergence speed and higher accuracy and stability compared with other optimization algorithms, which provide assistance insolving high-dimensionaland complex problems in engineering and information science

Reaction Data in PubChem

A presentation at the enviPathPlus workshop (held online) on "Reaction Data in PubChem". Presented by E. Schymanski on behalf of all authors. See slides for details and many hyperlinks - thanks to Kathrin Fenner for the opportunity

Design of amplifying information metasurface for enhancing signal coverage

Traditional information metasurfaces can be used in wireless relay systems to control the propagation direction of electromagnetic waves due to their capability to control the amplitude and phase.However, owing to the lack of signal amplification function, these metasurfaces have a limited operating distance.Thus, a large size of metasurfaces is usually demanded to realize the signal coverage of dead zones.To solve this problem, an amplifying information metasurface was designed to realize the 2 bit phase manipulation and signal amplification function within the broad band from 2.7 to 3.1 GHz.Furthermore, a power dividing and combining network was introduced to combine the 1×8 metasurface elements into an array with only one amplifier, which greatly reduced the number of amplifiers, the hardware cost, and the power consumption.The simulation results indicate that the array can realize beamforming and signal amplification over a broad band.Therefore, the proposed amplifying information metasurface array may find important applications in wireless relay systems and provide a new solution to enhancing the signal coverage and reducing the size of the metasurface array

Regulatory Variants and Disease: The E-Cadherin −160C/A SNP as an Example

Single nucleotide polymorphisms (SNPs) occurring in noncoding sequences have largely been ignored in genome-wide association studies (GWAS). Yet, amounting evidence suggests that many noncoding SNPs especially those that are in the vicinity of protein coding genes play important roles in shaping chromatin structure and regulate gene expression and, as such, are implicated in a wide variety of diseases. One of such regulatory SNPs (rSNPs) is the E-cadherin (CDH1) promoter −160C/A SNP (rs16260) which is known to affect E-cadherin promoter transcription by displacing transcription factor binding and has been extensively scrutinized for its association with several diseases especially malignancies. Findings from studying this SNP highlight important clinical relevance of rSNPs and justify their inclusion in future GWAS to identify novel disease causing SNPs.</jats:p

Electromechanical Catastrophe

A transducer is a system that couples two loads. For example, an electromechanical transducer couples a mechanical force and an electrical voltage. A two-load, nonlinear system can exhibit rich behavior of bifurcation, which can be displayed in a three-dimensional space, with the horizontal plane representing the two loads, and the vertical axis representing the state of the system. In this three-dimensional space, a state of equilibrium at fixed loads corresponds to a point on a surface. The surface is smooth, but its projection to the load plane results in singularities of two types: fold and cusp. Here we identify the fold and cusp for a dielectric elastomer transducer by a combination of experiment and calculation. We conduct two kinds of experiment: electrical actuation under a constant force and mechanical pulling under a constant voltage. The theory and the experiment agree well. The fold and cusp are essential in the design of loading paths to avoid or harness the bifurcation.Engineering and Applied Science