Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

<div>There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each protein-ligand complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of protein-</div><div>ligand complexes to predict binding parameters. We introduce the option to use multiple structures to describe each ligand-protein complex into COMBINE analysis and</div><div>apply this to study the effects of protein flexibility on the derivation of dissociation rate constants (k_off) for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression and allowed the computation of k_off values. The QSKR model obtained using single, energy minimized crystal structures for each ligand-protein complex had a higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, the incorporation of protein-ligand flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, like interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures. These results show that COMBINE analysis is a promising method to guide the design of compounds that bind to flexible proteins with improved binding kinetics. </div>

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

<div>There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each protein-ligand complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of protein-</div><div>ligand complexes to predict binding parameters. We introduce the option to use multiple structures to describe each ligand-protein complex into COMBINE analysis and</div><div>apply this to study the effects of protein flexibility on the derivation of dissociation rate constants (k_off) for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression and allowed the computation of k_off values. The QSKR model obtained using single, energy minimized crystal structures for each ligand-protein complex had a higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, the incorporation of protein-ligand flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, like interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures, showing that COMBINE analysis is a promising method to design leads with improved kinetic rates for flexible proteins.</div>

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

<div>There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each protein-ligand complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of protein-</div><div>ligand complexes to predict binding parameters. We introduce the option to use multiple structures to describe each ligand-protein complex into COMBINE analysis and</div><div>apply this to study the effects of protein flexibility on the derivation of dissociation rate constants (k_off) for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression and allowed the computation of k_off values. The QSKR model obtained using single, energy minimized crystal structures for each ligand-protein complex had a higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, the incorporation of protein-ligand flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, like interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures, showing that COMBINE analysis is a promising method to design leads with improved kinetic rates for flexible proteins.</div>

Training of automatic preclassification during operation – the way to create an autonomous automatic analyzer of complex morphology

The development of a microscopy combine designed to automate the analysis of complex morphological objects is presented. Automatic tecniques of combine analysis form the results of the “preclassification” class with the control of automatic results by the user. The harvester has means of automatic adaptation to the current slide and to the population of objects of analysis presented in the streams of slides served by the team of combines of laboratories. Local adaptation optimizes the quality and speed of the slide scanning. Adaptation to the population of objects of analysis is carried out by training neural networks of combine analyzers using a common database of automatic preclassification adjustments by qualified laboratory users. Training is used to increase the accuracy of preclassification with the ultimate goal of creating a stand-alone analyzer without user control.

Functional codeswitching and register in educated Negev Arabic interview style

The sociolinguistic phenomenon of codeswitching, both diglossic and bilingual (Arabic–Hebrew), is extremely pervasive in all varieties of Palestinian Arabic, including Negev Arabic. Surprisingly, neither of these types of codeswitching in Palestinian Arabic has received due scholarly attention; moreover, their interplay has not been studied for any type of Arabic. This article analyses quantitative and functional aspects of diglossic and bilingual codeswitching in the personal interview style of 11 Negev Bedouin female students, focusing on their functional interaction. In the five distinct registers analysed, ratios of both diglossic and bilingual codeswitching were found to rise from childhood narratives to recounts of the period of academic studies and expository sections, with the use of Hebraisms dropping in the more formal registers. Although mixed bilingual discourse with intensive codeswitching is the default style for in-group discourse of the young generation, I show that many switches are not random, but fulfil discourse-pragmatic, communicative, social and textual functions typical of each of the registers. For example, in the narrative registers, switching may mark evaluation (commenting, explaining, self-repair, sidetracking, repetition). In both narrative and non-narrative discourse it may mark quotations, rephrasing or paraphrasing, with or without a metalinguistic introducing particle such as ‘as they say’. The result is redundancy at the referential level, with pragmatic functions of emphasizing or elaborating at the discourse level. This is in keeping with functions identified for bilingual codeswitching in general and also for diglossic codeswitching in Arabic; but it is the first effort, as far as I know, to combine analysis of the two codeswitching dimensions in any given code; and, moreover, to study the interplay of this bi-dimensional switching with relation to the stylistic factors of genre and register.

Research on Reform Vietnamese Traditional Clothing for High Schoolgirls Uniform

Vietnam traditional clothing is Ao dai. Ao dai is one of Vietnamese culture, the symbol of Vietnamese women. In high school white Ao dai has become girls uniform. Although high school girls was fond of Ao dai, it was difficult for movement, especially for every day wear. Through investigation into schoolgirls about Ao dai. In this paper, we proposed to combine analysis data with traditional Ao dai design to research and reform Ao dai in such a way that it made schoolgirls wear to feel more comfortable. The samples which was made according to patterns data, one again was evaluated on fitting, appearance and comfort.