Molecular basis for short-chain thioester hydrolysis by acyl hydrolase domains in trans -acyltransferase polyketide synthases.

Polyketide synthases (PKSs) are multi-domain enzymatic assembly lines that biosynthesise a wide selection of bioactive natural products from simple building blocks. In contrast to their cis -acyltransferase (AT) counterparts, trans -AT PKSs rely on stand-alone AT domains to load extender units onto acyl carrier protein (ACP) domains embedded in the core PKS machinery. Trans -AT PKS gene clusters also encode acyl hydrolase (AH) domains, which are predicted to share the overall fold of AT domains, but hydrolyse aberrant acyl chains from ACP domains, thus ensuring efficient polyketide biosynthesis. How such domains specifically target short acyl chains, in particular acetyl groups, tethered as thioesters to the substrate-shuttling ACP domains, with hydrolytic rather than acyl transfer activity, has remained unclear. To answer these questions, we solved the first structure of an AH domain and performed structure-guided activity assays on active site variants. Our results offer key insights into chain length control and selection against coenzyme A-tethered substrates, and clarify how the interaction interface between AH and ACP domains contributes to recognition of cognate and non-cognate ACP domains. Combining our experimental findings with molecular dynamics simulations allowed for the production of a data-driven model of an AH:ACP domain complex. Our results advance the currently incomplete understanding of polyketide biosynthesis by trans -AT PKSs, and provide foundations for future bioengineering efforts.

Investigating carbohydrate based ligands for galectin-3 with docking and molecular dynamics studies.

Galectin-3 (Gal-3) is a carbohydrate binding protein that is overexpressed in several types of cancers, including pancreatic cancer, which makes it a good target for both imaging and therapeutic drug design. A ligand library specialized for 18F positron emission tomography (PET) has been investigated with molecular dynamics (MD) and free energy methods to determine the relative binding energies of various potential ligands. Our results suggest that traditional docking methods can give good results when complemented by molecular dynamics and free energy methods for these types of ligands. Available experimental binding affinities for a small number of the tested compounds show very good agreement with the calculated energies and provide the rational approach for design of Gal-3 ligands with even higher affinity.

LICHEM: A QM/MM program for simulations with multipolar and polarizable force fields.

We introduce an initial implementation of the LICHEM software package. LICHEM can interface with Gaussian, PSI4, NWChem, TINKER, and TINKER-HP to enable QM/MM calculations using multipolar/polarizable force fields. LICHEM extracts forces and energies from unmodified QM and MM software packages to perform geometry optimizations, single-point energy calculations, or Monte Carlo simulations. When the QM and MM regions are connected by covalent bonds, the pseudo-bond approach is employed to smoothly transition between the QM region and the polarizable force field. A series of water clusters and small peptides have been employed to test our initial implementation. The results obtained from these test systems show the capabilities of the new software and highlight the importance of including explicit polarization. © 2016 Wiley Periodicals, Inc.

Hypothesis driven single nucleotide polymorphism search (HyDn-SNP-S).

The advent of complete-genome genotyping across phenotype cohorts has provided a rich source of information for bioinformaticians. However the search for SNPs from this data is generally performed on a study-by-study case without any specific hypothesis of the location for SNPs that are predictive for the phenotype. We have designed a method whereby very large SNP lists (several gigabytes in size), combining several genotyping studies at once, can be sorted and traced back to their ultimate consequence in protein structure. Given a working hypothesis, researchers are able to easily search whole genome genotyping data for SNPs that link genetic locations to phenotypes. This allows a targeted search for correlations between phenotypes and potentially relevant systems, rather than utilizing statistical methods only. HyDn-SNP-S returns results that are less data dense, allowing more thorough analysis, including haplotype analysis. We have applied our method to correlate DNA polymerases to cancer phenotypes using four of the available cancer databases in dbGaP. Logistic regression and derived haplotype analysis indicates that ~80SNPs, previously overlooked, are statistically significant. Derived haplotypes from this work link POLL to breast cancer and POLG to prostate cancer with an increase in incidence of 3.01- and 9.6-fold, respectively. Molecular dynamics simulations on wild-type and one of the SNP mutants from the haplotype of POLL provide insights at the atomic level on the functional impact of this cancer related SNP. Furthermore, HyDn-SNP-S has been designed to allow application to any system. The program is available upon request from the authors.