Answer Set Programming with External Sources

Answer Set Programming (ASP) is a well-known problem solving approach based on nonmonotonic logic programs and efficient solvers. To enable access to external information, HEX-programs extend programs with external atoms, which allow for a bidirectional communication between the logic program and external sources of computation (e.g., description logic reasoners and Web resources). Current solvers evaluate HEX-programs by a translation to ASP itself, in which values of external atoms are guessed and verified after the ordinary answer set computation. This elegant approach does not scale with the number of external accesses in general, in particular in presence of nondeterminism (which is instrumental for ASP). Hence, there is a need for genuine algorithms which handle external atoms as first-class citizens, which is the main focus of this PhD project. In the first phase of the project, state-of-the-art conflict driven algorithms were already integrated into the prototype system dlvhex and extended to external sources. In particular, the evaluation of external sources may trigger a learning procedure, such that the reasoner gets additional information about the internals of external sources. Moreover, problems on the second level of the polynomial hierarchy were addressed by integrating a minimality check, based on unfounded sets. First experimental results show already clear improvements

Exploiting Unfounded Sets for HEX-Program Evaluation

HEX programs extend logic programs with external computations through external atoms, whose answer sets are the minimal models of the Faber-Leone-Pfeifer-reduct. As already reasoning from Horn programs with nonmonotonic external atoms of polynomial complexity is on the second level of the polynomial hierarchy, answer set checking needs special attention; simply computing reducts and searching for smaller models does not scale well. We thus extend an approach based on unfounded sets to HEX and integrate it in a Conflict Driven Clause Learning framework for HEX program evaluation. It reduces the check to a search for unfounded sets, which is more efficiently implemented as a SAT problem. We give a basic encoding for HEX and show optimizations by additional clauses. Experiments show that the new approach significantly decreases runtime

Nanoparticular Inhibitors of Flavivirus Proteases from Zika, West Nile and Dengue Virus Are Cell-Permeable Antivirals

Viral proteases have been established as drug targets in several viral diseases including human immunodeficiency virus and hepatitis C virus infections due to the essential role of these enzymes in virus replication. In contrast, no antiviral therapy is available to date against flaviviral infections including those by Zika virus (ZIKV), West Nile virus (WNV), or dengue virus (DENV). Numerous potent inhibitors of flaviviral proteases have been reported; however, a huge gap remains between the in vitro and intracellular activities, possibly due to low cellular uptake of the charged compounds. Here, we present an alternative, nanoparticular approach to antivirals. Conjugation of peptidomimetic inhibitors and cell-penetrating peptides to dextran yielded chemically defined nanoparticles that were potent inhibitors of flaviviral proteases. Peptide-dextran conjugates inhibited viral replication and infection in cells at nontoxic, low micromolar or even nanomolar concentrations. Thus, nanoparticular antivirals might be alternative starting points for the development of broad-spectrum antiflaviviral drugs.C.N. thanks the Australian Research Council for a Discovery Early Career Research Award (DE190100015) and the Freie Universität Berlin for a Rising Star fellowship