Recent simulation methods for resolving molecular details in thermodynamics and kinetics

Molecular dynamics (MD) simulations are increasingly powerful tools for augmented thinking about molecular-level phenomena and their links to macroscopic properties. Fundamentally, MD propagates atomic positions and velocities by numerical integration of equations of motion subject to forces representing interatomic interactions. Unfortunately, even with present day computational power, it is nearly impossible to directly observe phenomena that have natural timescales of greater than about a microsecond or length scales greater than a few tens of nanometers using MD. This is because the ceaseless thermal agitation resolved by MD only very rarely and unpredictably rectifies itself along productive directions in some more macroscopically meaningful variable space. Our group is devoted to overcoming this issue with novel methods that provide access to these “rare events” with the ultimate aim being a full description of the equilibrium distributions and transition rates in some state space of interest. In this talk, I will highlight the development and application of some of these modern MD techniques, including temperature-acceleration and Markovian milestoning. Applications to be touched on include ligand entry and exit kinetics in enzymes and transmembrane ion transport. I will close with some highlights of future directions in method developments that involve hybrid approaches

All‐atom structural models of insulin binding to the insulin receptor in the presence of a tandem hormone‐binding element

Insulin regulates blood glucose levels in higher organisms by binding to and activating insulin receptor (IR), a constitutively homodimeric glycoprotein of the receptor tyrosine kinase (RTK) superfamily. Therapeutic efforts in treating diabetes have been significantly impeded by the absence of structural information on the activated form of the insulin/IR complex. Mutagenesis and photo‐crosslinking experiments and structural information on insulin and apo‐IR strongly suggest that the dual‐chain insulin molecule, unlike the related single‐chain insulin‐like growth factors, binds to IR in a very different conformation than what is displayed in storage forms of the hormone. In particular, hydrophobic residues buried in the core of the folded insulin molecule engage the receptor. There is also the possibility of plasticity in the receptor structure based on these data, which may in part be due to rearrangement of the so‐called CT‐peptide, a tandem hormone‐binding element of IR. These possibilities provide opportunity for large‐scale molecular modeling to contribute to our understanding of this system. Using various atomistic simulation approaches, we have constructed all‐atom structural models of hormone/receptor complexes in the presence of CT in its crystallographic position and a thermodynamically favorable displaced position. In the “displaced‐CT” complex, many more insulin–receptor contacts suggested by experiments are satisfied, and our simulations also suggest that R‐insulin potentially represents the receptor‐bound form of hormone. The results presented in this work have further implications for the design of receptor‐specific agonists/antagonists. Proteins 2013; © 2012 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98204/1/PROT_24255_sm_SuppInfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/98204/2/24255_ftp.pd

Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking (version 1)

Screening already approved drugs for activity against a novel pathogen can be an important part of global rapid-response strategies in pandemics. Such high-throughput repurposing screens have already identified several existing drugs with potential to combat SARS-CoV-2. However, moving these hits forward for possible development into drugs specifically against this pathogen requires unambiguous identification of their corresponding targets, something the high-throughput screens are not typically designed to reveal. We present here a new computational inverse-docking protocol that uses all-atom protein structures and a combination of docking methods to rank order targets for each of several existing drugs for which a plurality of recent hight-hroughput screens detected anti-SARS-CoV-2 activity. We demonstrate validation of this method with known drug-target pairs, including both non-antiviral and antiviral compounds. We subjected 152 distinct drugs potentially suitable for repurposing to the inverse docking procedure. The most common preferential targets were the human enzymes TMPRSS2 and PIKfyve, followed by the viral enzymes Helicase and PLpro. All compounds that selected TMPRSS2 are known serine protease inhibitors, and those that selected PIKfyve are known tyrosine kinase inhibitors. Detailed structural analysis of the docking poses revealed important insights into why these selections arose, and could potentially lead to more rational design of new drugs against these targets.Fil: Ribone, Sergio P. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Ciencias Farmacéuticas; Argentina.Fil: Ribone, Sergio P. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica; Argentina.Fil: Paz; S. Alexis. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas; Argentina.Fil: Paz, S. Alexis. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina.Fil: Abrams, Cameron F. Drexel University. Department of Chemical and Biological Engineering, Philadelphia; United States.Fil: Villarreal Marcos A. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas; Argentina.Fil: Villarreal Marcos A. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina.Fil: Paz; S. Alexis. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas; Argentina

To what extent is behaviour a problem in English schools?:Exploring the scale and prevalence of deficits in classroom climate

The working atmosphere in the classroom is an important variable in the process of education in schools, with several studies suggesting that classroom climate is an important influence on pupil attainment. There are wide differences in the extent to which classroom climate is considered to be a problem in English schools. Some ‘official’ reports suggest that behaviour in schools is ‘satisfactory or better’ in the vast majority of schools; other sources have pointed to behaviour being a serious and widespread problem. The paper details four studies conducted over the past decade which aimed to explore these disparities. The aim of the research was to gain a more accurate insight into the extent to which deficits in classroom climate limit educational attainment and equality of educational opportunity in English schools. The findings question the suggestion that behaviour is satisfactory or better in 99.7% of English schools and the concluding section suggests ways in which deficits in classroom climate might be addressed. Although the study is limited to classrooms in England, OECD studies suggest that deficits in the working atmosphere in classrooms occur in many countries. The study therefore has potential relevance for education systems in other countries

"Best fit" framework synthesis: refining the method

Background Following publication of the first worked example of the “best fit” method of evidence synthesis for the systematic review of qualitative evidence in this journal, the originators of the method identified a need to specify more fully some aspects of this particular derivative of framework synthesis. Methods and Results We therefore present a second such worked example in which all techniques are defined and explained, and their appropriateness is assessed. Specified features of the method include the development of new techniques to identify theories in a systematic manner; the creation of an a priori framework for the synthesis; and the “testing” of the synthesis. An innovative combination of existing methods of quality assessment, analysis and synthesis is used to complete the process. This second worked example was a qualitative evidence synthesis of employees’ views of workplace smoking cessation interventions, in which the “best fit” method was found to be practical and fit for purpose. Conclusions The method is suited to producing context-specific conceptual models for describing or explaining the decision-making and health behaviours of patients and other groups. It offers a pragmatic means of conducting rapid qualitative evidence synthesis and generating programme theories relating to intervention effectiveness, which might be of relevance both to researchers and policy-makers

A Multiscale Model Evaluates Screening for Neoplasia in Barrett's Esophagus

National Cancer Institute grants U01 CA152926 (CISNET) (to EGL, JJ, and WDH) and U01 CA182940 (BG-U01) (to EGL and WDH). National Science Foundation (www.nsf.gov) under grant no. DGE-0718124 (to KC

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac