We present here a case study of an antibody-engineering platform that selects, modifies, and assembles antibody parts to construct novel antibodies. A salient feature of this platform includes the role of amino acid networks in optimizing framework regions (FRs) and complementarity determining regions (CDRs) to engineer new antibodies with desired structure-function relationships. The details of this approach are described in the context of its utility in engineering ZAb_FLEP, a potent anti-Zika virus antibody. ZAb_FLEP comprises of distinct parts, including heavy chain and light chain FRs and CDRs, with engineered features such as loop lengths and optimal epitope-paratope contacts. We demonstrate, with different test antibodies derived from different FR-CDR combinations, that despite these test antibodies sharing high overall sequence similarity, they yield diverse functional readouts. Furthermore, we show that strategies relying on one dimensional sequence similarity-based analyses of antibodies miss important structural nuances of the FR-CDR relationship, which is effectively addressed by the amino acid networks approach of this platform.

Operations research is a well-established field that uses computational systems to support decisions in business and public life. Good solutions to operations research problems can make a large difference to the efficient running of businesses and organisations and so the field often searches for new methods to improve these solutions. The high school timetabling problem is an example of an operations research problem and is a challenging task which requires assigning events and resources to time slots subject to a set of constraints. In this article, a new sequence-based selection hyper-heuristic is presented that produces excellent results on a suite of high school timetabling problems. In this study, we present an easy-to-implement, easy-to-maintain, and effective sequence-based selection hyper-heuristic to solve high school timetabling problems using a benchmark of unified real-world instances collected from different countries. We show that with sequence-based methods, it is possible to discover new best known solutions for a number of the problems in the timetabling domain. Through this investigation, the usefulness of sequence-based selection hyper-heuristics has been demonstrated and the capability of these methods has been shown to exceed the state of the art.

In our previous work, a NAD(H)-dependent carbonyl reductase (GoCR) was identified from Gluconobacter oxydans, which showed moderate to high enantiospecificity for the reduction of different kinds of prochiral ketones. In the present study, the crystal structure of GoCR was determined at 1.65Å resolution, and a computational strategy concerning substrate-enzyme docking and all-atom molecular dynamics (MD) simulation was established to help understand the molecular basis of enantiopreference and enantiorecognition for GoCR, and to further guide the design and engineering of GoCR enantioselectivity. For the reduction of ethyl 2-oxo-4-phenylbutyrate (OPBE), three binding pocket residues, Cys93, Tyr149, and Trp193 were predicted to play a critical role in determining the enantioselectivity. Through site-directed mutagenesis, single-point mutant W193A was constructed and proved to reduce OPBE to ethyl (R)-2-hydroxy-4-phenylbutyrate (R-HPBE) with a significantly improved ee of >99% compared to 43.2% for the wild type (WT). Furthermore, double mutant C93V/Y149A was proved to even invert the enantioselectivity of GoCR to afford S-HPBE at 79.8% ee.