De novo approach was applied to design single chain fragment variable (scFv) for BmR1, a recombinant antigen from Bm17DIII gene which is the primary antigen used for the detection of anti-BmR1 IgG4 antibodies in the diagnostic of lymphatic filariasis. Three epitopes of the BmR1 was previously predicted form an ab initio derived three-dimensional structure. A collection of energetically favourable conformations was generated via hot-spot-centric approach. This resulted in a set of three different scFv scaffolds used to compute the high shape complementary conformations via dock-and-design approach with the predicted epitopes of BmR1. A total of 4227 scFv designs were generated where 200 scFv designs produced binding energies of less than -20 R.E.U with shape complementarity higher than 0.5. We further selected the design with at least one hydrogen bond and one salt bridge with the epitope, thus resulted in a total of 10, 1 and 19 sFv designs for epitope 1, 2 and 3, respectively. The results thus showed that de novo design can be an alternative approach to yield high affinity in silico scFv designs as a starting point for antibody or specific binder discovery processes.
Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically <1.5 Å) model can be built via comparative modelling. However, when confronted with low sequence similarity of the target protein (also known as twilight-zone protein, sequence identity with available templates is less than 30%), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.
Brugia malayi is a filarial nematode, which causes lymphatic filariasis in humans. In 1995, the disease has been identified by the World Health Organization (WHO) as one of the second leading causes of permanent and long-term disability and thus it is targeted for elimination by year 2020. Therefore, accurate filariasis diagnosis is important for management and elimination programs. A recombinant antigen (BmR1) from the Bm17DIII gene product was used for antibody-based filariasis diagnosis in "Brugia Rapid". However, the structure and dynamics of BmR1 protein is yet to be elucidated. Here we study the three dimensional structure and dynamics of BmR1 protein using comparative modeling, threading and ab initio protein structure prediction. The best predicted structure obtained via an ab initio method (Rosetta) was further refined and minimized. A total of 5 ns molecular dynamics simulation were performed to investigate the packing of the protein. Here we also identified three epitopes as potential antibody binding sites from the molecular dynamics average structure. The structure and epitopes obtained from this study can be used to design a binder specific against BmR1, thus aiding future development of antigen-based filariasis diagnostics to complement the current diagnostics.