p.(L576P) -KIT mutation in GIST: Favorable prognosis and sensitive to imatinib?

Exon 11 KIT mutations are found in a majority of gastrointestinal stromal tumors (GIST) and are usually predictive of response to imatinib, a KIT, PDGFRA and ABL inhibitor. Exon 11 mutations with poor sensitivity to imatinib and poor outcome can be observed on rare occasions, including p.(L576P). In silico and in vitro studies suggested a decreased binding affinity for imatinib in p.(L576P) KIT mutations, thereby offering an explanation for their poor outcome and poor response to standard therapy. These observations were further corroborated with anecdotal case reports of refractoriness or non-durable response to imatinib therapy. However, we describe the favorable response to imatinib and outcome in 5 p.(L576P)-KIT mutant GIST patients treated at a tertiary sarcoma referral center. The sensitivity of p.(L576P)-KIT mutations to imatinib, and the prognostic impact of this mutation need to be further evaluated in a larger cohort. Based on our observations, p.(L576P) mutated GISTs should be treated with standard first line imatinib therapy.

Insight into determinants of substrate binding and transport in a multidrug efflux protein

Multidrug resistance arising from the activity of integral membrane transporter proteins presents a global public health threat. In bacteria such as Escherichia coli, transporter proteins belonging to the major facilitator superfamily make a considerable contribution to multidrug resistance by catalysing efflux of myriad structurally and chemically different antimicrobial compounds. Despite their clinical relevance, questions pertaining to mechanistic details of how these promiscuous proteins function remain outstanding, and the role(s) played by individual amino acid residues in recognition, binding and subsequent transport of different antimicrobial substrates by multidrug efflux members of the major facilitator superfamily requires illumination. Using in silico homology modelling, molecular docking and mutagenesis studies in combination with substrate binding and transport assays, we identified several amino acid residues that play important roles in antimicrobial substrate recognition, binding and transport by Escherichia coli MdtM, a representative multidrug efflux protein of the major facilitator superfamily. Furthermore, our studies suggested that 'aromatic clamps' formed by tyrosine and phenylalanine residues located within the substrate binding pocket of MdtM may be important for antimicrobial substrate recognition and transport by the protein. Such 'clamps' may be a structurally and functionally important feature of all major facilitator multidrug efflux proteins.

Reversibility Iteration Method to Understand Reaction Networks and to Solve Micro-Kinetics in Heterogeneous Catalysis

Solving microkinetics of catalytic systems, which bridges microscopic processes and macroscopic reaction rates, is currently vital for understanding catalysis in silico. However, traditional microkinetic solvers possess several drawbacks that make the process slow and unreliable for complicated catalytic systems. In this paper, a new approach, the so-called reversibility iteration method (RIM), is developed to solve microkinetics for catalytic systems. Using the chemical potential notation we previously proposed to simplify the kinetic framework, the catalytic systems can be analytically illustrated to be logically equivalent to the electric circuit, and the reaction rate and coverage can be calculated by updating the values of reversibilities. Compared to the traditional modified Newton iteration method (NIM), our method is not sensitive to the initial guess of the solution and typically requires fewer iteration steps. Moreover, the method does not require arbitrary-precision arithmetic and has a higher probability of successfully solving the system. These features make it ∼1000 times faster than the modified Newton iteration method for the systems we tested. Moreover, the derived concept and the mathematical framework presented in this work may provide new insight into catalytic reaction networks.

Prior knowledge transfer across transcriptional data sets and technologies using compositional statistics yields new mislabelled ovarian cell line

Here, we describe gene expression compositional assignment (GECA), a powerful, yet simple method based on compositional statistics that can validate the transfer of prior knowledge, such as gene lists, into independent data sets, platforms and technologies. Transcriptional profiling has been used to derive gene lists that stratify patients into prognostic molecular subgroups and assess biomarker performance in the pre-clinical setting. Archived public data sets are an invaluable resource for subsequent in silico validation, though their use can lead to data integration issues. We show that GECA can be used without the need for normalising expression levels between data sets and can outperform rank-based correlation methods. To validate GECA, we demonstrate its success in the cross-platform transfer of gene lists in different domains including: bladder cancer staging, tumour site of origin and mislabelled cell lines. We also show its effectiveness in transferring an epithelial ovarian cancer prognostic gene signature across technologies, from a microarray to a next-generation sequencing setting. In a final case study, we predict the tumour site of origin and histopathology of epithelial ovarian cancer cell lines. In particular, we identify and validate the commonly-used cell line OVCAR-5 as non-ovarian, being gastrointestinal in origin. GECA is available as an open-source R package.

Rational design of a (S)-selective-Transaminase for asymmetric synthesis of (1S)-1-(1,1'-biphenyl 2-yl)ethanamine

Amine transaminases offer an environmentally sustainable synthesis route for the production ofpure chiral amines. However, their catalytic efficiency towards bulky ketone substrates isgreatly limited by steric hindrance and therefore presents a great challenge for industrialsynthetic applications. Hereby we report an example of rational transaminase enzyme design tohelp alleviate these challenges. Starting from the Vibrio fluvialis amine transaminase that has nodetectable catalytic activity towards the bulky aromatic ketone 2-acetylbiphenyl, we employed arational design strategy combining in silico and in vitro studies to engineer the transaminaseenzyme with a minimal number of mutations, achieving an high catalytic activity and highenantioselectivity. We found that by introducing two mutations W57G/R415A detectableenzyme activity was achieved. The rationally designed best variant,W57F/R88H/V153S/K163F/I259M/R415A/V422A, showed an improvement in reaction rateby > 1716-fold towards the bulky ketone under study, producing the corresponding enantiomericpure (S)-amine (ee value of > 99%). 

Insight into the mechanism of galactokinase: role of a critical glutamate residue and helix/coil transitions

Galactokinase, the enzyme which catalyses the first committed step in the Leloir pathway, has attracted interest due to its potential as a biocatalyst and as a possible drug target in the treatment of type I galactosemia. The mechanism of the enzyme is not fully elucidated. Molecular dynamics (MD) simulations of galactokinase with the active site residues Arg-37 and Asp-186 altered predicted that two regions (residues 174-179 and 231-240) had different dynamics as a consequence. Interestingly, the same two regions were also affected by alterations in Arg-105, Glu-174 and Arg- 228. These three residues were identified as important in catalysis in previous computational studies on human galactokinase. Alteration of Arg-105 to methionine resulted in a modest reduction in activity with little change in stability. When Arg-228 was changed to methionine, the enzyme’s interaction with both ATP and galactose was affected. This variant was significantly less stable than the wild-type protein. Changing Glu-174 to glutamine (but not to aspartate) resulted in no detectable activity and a less stable enzyme. Overall, these combined in silico and in vitro studies demonstrate the importance of a negative charge at position 174 and highlight the critical role of the dynamics in to key regions of the protein. We postulate that these regions may be critical for mediating the enzyme’s structure and function.