Fragment approaches in structure-based drug discovery

Fragment-based methods are successfully generating novel and selective drug-like inhibitors of protein targets, with a number of groups reporting compounds entering clinical trials. This paper summarizes the key features of the approach as one of the tools in structure-guided drug discovery

sgTarget: a target selection resource for structural genomics

sgTarget () is a web-based resource to aid the selection and prioritization of candidate proteins for structure determination. The system annotates user submitted gene or protein sequences, identifying sequence families with no homologues of known structure, and characterizing each protein according to a range of physicochemical properties that may affect its expression, solubility and likelihood to crystallize. Summaries of these analyses are available for individual sequences, as well as whole datasets. This type of analysis enables structural biologists to iteratively select targets from their genomic sequences of interest and according to their research needs. All sequence datasets submitted to sgTarget are available for users to select and rank using their choice of criteria. sgTarget was developed to support individual laboratories collaborating in structural and functional genomics projects and should be valuable to structural biologists wishing to employ the wealth of available genome sequences in their structural quests

Exploring idp–ligand interactions : Tau k18 as a test case

Over the past decade intrinsically disordered proteins (IDPs) have emerged as a biologically important class of proteins, many of which are of therapeutic relevance. Here, we investigated the interactions between a model IDP system, tau K18, and nine literature compounds that have been reported as having an effect on tau in order to identify a robust IDP–ligand system for the optimization of a range of biophysical methods. We used NMR, surface plasmon resonance (SPR) and microscale thermophoresis (MST) methods to investigate the binding of these compounds to tau K18; only one showed unambiguous interaction with tau K18. Several near neighbors of this compound were synthesized and their interactions with tau K18 characterized using additional NMR methods, including 1D ligand-observed NMR, diffusion-ordered spectroscopy (DOSY) and19F NMR. This study demonstrates that it is possible to detect and characterize IDP–ligand interactions using biophysical methods. However, care must be taken to account for possible artefacts, particularly the impact of compound solubility and where the protein has to be immobilized

Predicting how drug molecules bind to their protein targets

There have been substantial advances in the application of molecular modelling and simulation to drug discovery in recent years, as massive increases in computer power are coupled with continued development in the underlying methods and understanding of how to apply them. Here, we survey recent advances in one particular area — predicting how a known ligand binds to a particular protein. We focus on the four contributing classes of calculation: predicting where a binding site is on a protein; characterizing where chemical functional groups will bind to that site; molecular docking to generate a binding mode for a ligand and dynamics simulations to refine that pose and allow for protein conformation change. Examples of successful application are provided for each class

Correction to : 1H, 13C, 15N backbone and IVL methyl group resonance assignment of the fungal β-glucosidase from Trichoderma reesei (Biomolecular NMR Assignments, (2020), 10.1007/s12104-020-09959-2)

In the original publication of the article, the name of one of the authors is incorrect. The author's name is Eiso AB, but was modified to A. B. Eiso. The correct name is given in this Correction

1H, 13C, 15N backbone and IVL methyl group resonance assignment of the fungal β-glucosidase from Trichoderma reesei

β-glucosidases have received considerable attention due to their essential role in bioethanol production from lignocellulosic biomass. β-glucosidase can hydrolyse cellobiose in cellulose degradation and its low activity has been considered as one of the main limiting steps in the process. Large-scale conversions of cellulose therefore require high enzyme concentration which increases the cost. β-glucosidases with improved activity and thermostability are therefore of great commercial interest. The fungus Trichoderma reseei expresses thermostable cellulolytic enzymes which have been widely studied as attractive targets for industrial applications. Genetically modified β-glucosidases from Trichoderma reseei have been recently commercialised. We have developed an approach in which screening of low molecular weight molecules (fragments) identifies compounds that increase enzyme activity and are currently characterizing fragment-based activators of TrBgl2. A structural analysis of the 55 kDa apo form of TrBgl2 revealed a classical (α/β)8-TIM barrel fold. In the present study we present a partial assignment of backbone chemical shifts, along with those of the Ile (I)-Val (V)-Leu (L) methyl groups of TrBgl2. These data will be used to characterize the interaction of TrBgl2 with the small molecule activators

Biophysics in drug discovery : impact, challenges and opportunities

Over the past 25 years, biophysical technologies such as X-ray crystallography, nuclear magnetic resonance spectroscopy, surface plasmon resonance spectroscopy and isothermal titration calorimetry have become key components of drug discovery platforms in many pharmaceutical companies and academic laboratories. There have been great improvements in the speed, sensitivity and range of possible measurements, providing high-resolution mechanistic, kinetic, thermodynamic and structural information on compound-target interactions. This Review provides a framework to understand this evolution by describing the key biophysical methods, the information they can provide and the ways in which they can be applied at different stages of the drug discovery process. We also discuss the challenges for current technologies and future opportunities to use biophysical methods to solve drug discovery problems

Engineering Collaborations in Medical Modeling and Simulation

Fifty years ago computer science was just beginning to see common acceptance as a growing discipline and very few universities had a computer science department although other departments were utilizing computers and software to enhance their methodologies. We believe modeling and simulation (M&S) is on a similar path. Many other disciplines utilize M&S to enhance their methodologies but we also believe that M&S fundamentals can be essential in making better decisions by utilizing the appropriate model for the problem at hand, expanding the solution space through simulation, and understanding it through visualization and proper analyses. After our students learn these fundamentals, we offer the opportunity to apply them to varied application areas. One such application area is medical M&S, which is a broad area involving anatomical modeling, planning and training simulations, image-guided procedures and more. In this paper, we share several research projects involving M&S and the collaborations that make them possible

P-Rex1 Controls Sphingosine 1-Phosphate Receptor Signalling, Morphology, and Cell-Cycle Progression in Neuronal Cells.

P-Rex1 is a guanine-nucleotide exchange factor (GEF) that activates Rac-type small G proteins in response to the stimulation of a range of receptors, particularly G protein-coupled receptors (GPCRs), to control cytoskeletal dynamics and other Rac-dependent cell responses. P-Rex1 is mainly expressed in leukocytes and neurons. Whereas its roles in leukocytes have been studied extensively, relatively little is known about its functions in neurons. Here, we used CRISPR/Cas9-mediated P-Rex1 deficiency in neuronal PC12 cells that stably overexpress the GPCR S1PR1, a receptor for sphingosine 1-phosphate (S1P), to investigate the role of P-Rex1 in neuronal GPCR signalling and cell responses. We show that P-Rex1 is required for the S1P-stimulated activation of Rac1 and Akt, basal Rac3 activity, and constitutive cAMP production in PC12-S1PR1 cells. The constitutive cAMP production was not due to increased expression levels of major neuronal adenylyl cyclases, suggesting that P-Rex1 may regulate adenylyl cyclase activity. P-Rex1 was required for maintenance of neurite protrusions and spreading in S1P-stimulated PC12-S1PR1 cells, as well as for cell-cycle progression and proliferation. In summary, we identified novel functional roles of P-Rex1 in neuronal Rac, Akt and cAMP signalling, as well as in neuronal cell-cycle progression and proliferation

Thermo-mechanically-consistent phase-field modeling of thin film flows

We use phase-field techniques coupled with a Coleman-Noll type procedure to derive a family of thermomechanically consistent models for predicting the evolution of a non volatile thin liquid film on a flat substrate starting from mass conservation laws and the second law of thermodynamics, and provide constraints which must be met when modeling the dependent variables within a constitutive class to ensure dissipation of the free energy. We show that existing models derived using different techniques and starting points fit within this family. We regularise a classical model derived using asymptotic techniques to obtain a model which better handles film rupture, and perform numerical simulations in 2 and 3 dimensions using linear finite elements in space and a convex splitting method in time to investigate the evolution of a flat thin film undergoing rupture and dewetting on a flat solid substrate