R116C mutation of cationic trypsinogen in a Turkish family with recurrent pancreatitis illustrates genetic microheterogeneity of hereditary pancreatitis

Hereditary pancreatitis is due to heterozygosity for gain-of-function mutations in the cationic trypsinogen gene which result in increased levels of active trypsin within pancreatic acinar cells and autodigestion of the pancreas. The number of disease-causing defects is generally considered to be low. To gain further insight into the molecular basis of this disorder, DNA sequence analysis of all five exons was performed in 109 unrelated patients with idiopathic chronic pancreatitis in order to determine the variability of the underlying mutations. Two German females and one German male were carriers of the most common N291 and R122H mutations (trypsinogen numbering system). In a Turkish proband, an arginine (CGT) to cysteine (TGT) substitution at amino acid position 116 was identified. Family screening demonstrated that the patient had inherited the mutation from his asymptomatic father and that he had transmitted it to both of his children, his daughter being symptomatic since the age of 3 years. In addition, a German male was found to be a heterozygote for a D100H (GAC-->CAC) amino acid replacement. Our data provide evidence for genetic heterogeneity of hereditary pancreatitis. The growing number of cationic trypsinogen mutations is expected to change current mutation screening practices for this disease

The age of randomized clinical trials: three important aspects of randomized clinical trials in cardiovascular pharmacotherapy with examples from lipid, diabetes, and antithrombotic trials.

This review article aims to explain the important issues that data safety monitoring boards (DSMB) face when considering early termination of a trial and is specifically addressed to the needs of clinical and research cardiologists. We give an insight into the overall background and then focus on the three principal reasons for stopping trials, i.e. efficacy, futility, and harm. The statistical essentials are also addressed to familiarize clinicians with the key principles. The topic is further highlighted by numerous examples from lipid trials and antithrombotic trials. This is followed by an overview of regulatory aspects, including an insight into industry–investigator interactions. To conclude, we summarize the key elements that are the basis for a decision to stop a randomized clinical trial (RCT)

Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery

GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects

Using the fragment molecular orbital method to investigate agonist–orexin-2 receptor interactions

The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity and is essential for an efficient structure-based drug discovery (SBDD) process. Clearly, to begin SBDD, a structure is needed, and although there has been fantastic progress in solving G-protein-coupled receptor (GPCR) crystal structures, the process remains quite slow and is not currently feasible for every GPCR or GPCR-ligand complex. This situation significantly limits the ability of X-ray crystallography to impact the drug discovery process for GPCR targets in 'real-time' and hence there is still a need for other practical and cost-efficient alternatives. We present here an approach that integrates our previously described hierarchical GPCR modelling protocol (HGMP) and the fragment molecular orbital (FMO) quantum mechanics (QM) method to explore the interactions and selectivity of the human orexin-2 receptor (OX2R) and its recently discovered nonpeptidic agonists. HGMP generates a 3D model of GPCR structures and its complexes with small molecules by applying a set of computational methods. FMO allowsab initioapproaches to be applied to systems that conventional QM methods would find challenging. The key advantage of FMO is that it can reveal information on the individual contribution and chemical nature of each residue and water molecule to the ligand binding that normally would be difficult to detect without QM. We illustrate how the combination of both techniques provides a practical and efficient approach that can be used to analyse the existing structure-function relationships (SAR) and to drive forward SBDD in a real-world example for which there is no crystal structure of the complex available

First principles-based calculations of free energy of binding: application to ligand binding in a self-assembling superstructure

The accurate prediction of ligand binding affinities to a protein remains a desirable goal of computational biochemistry. Many available methods use molecular mechanics (MM) to describe the system, however, MM force fields cannot fully describe the complex interactions involved in binding, specifically electron transfer and polarization. First principles approaches can fully account for these interactions, and with the development of linear-scaling first principles programs, it is now viable to apply first principles calculations to systems containing tens of thousands of atoms. In this paper, a quantum mechanical Poisson?Boltzmann surface area approach is applied to a model of a protein?ligand binding cavity, the “tennis ball” dimer. Results obtained from this approach demonstrate considerable improvement over conventional molecular mechanics Poisson?Boltzmann surface area due to the more accurate description of the interactions in the system. For the first principles calculations in this study, the linear-scaling density functional theory program ONETEP is used, allowing the approach to be applied to receptor?ligand complexes of pharmaceutical interest that typically include thousands of atoms.<br/

GPCR structure, function, drug discovery and crystallography: report from Academia-Industry International Conference (UK Royal Society) Chicheley Hall, 1-2 September 2014

G-protein coupled receptors (GPCRs) are the targets of over half of all prescribed drugs today. The UniProt database has records for about 800 proteins classified as GPCRs, but drugs have only been developed against 50 of these. Thus, there is huge potential in terms of the number of targets for new therapies to be designed. Several breakthroughs in GPCRs biased pharmacology, structural biology, modelling and scoring have resulted in a resurgence of interest in GPCRs as drug targets. Therefore, an international conference, sponsored by the Royal Society, with world-renowned researchers from industry and academia was recently held to discuss recent progress and highlight key areas of future research needed to accelerate GPCR drug discovery. Several key points emerged. Firstly, structures for all three major classes of GPCRs have now been solved and there is increasing coverage across the GPCR phylogenetic tree. This is likely to be substantially enhanced with data from x-ray free electron sources as they move beyond proof of concept. Secondly, the concept of biased signalling or functional selectivity is likely to be prevalent in many GPCRs, and this presents exciting new opportunities for selectivity and the control of side effects, especially when combined with increasing data regarding allosteric modulation. Thirdly, there will almost certainly be some GPCRs that will remain difficult targets because they exhibit complex ligand dependencies and have many metastable states rendering them difficult to resolve by crystallographic methods. Subtle effects within the packing of the transmembrane helices are likely to mask and contribute to this aspect, which may play a role in species dependent behaviour. This is particularly important because it has ramifications for how we interpret pre-clinical data. In summary, collaborative efforts between industry and academia have delivered significant progress in terms of structure and understanding of GPCRs and will be essential for resolving problems associated with the more difficult targets in the future.ISSN:0028-1298ISSN:1432-191