Ho Ki Fung

Discovery of Entry Inhibitors for HIV-1 via a New De Novo Protein Design Framework

A new (to our knowledge) de novo design framework with a ranking metric based on approximate binding affinity calculations is introduced and applied to the discovery of what we believe are novel HIV-1 entry inhibitors. The framework consists of two stages: a sequence selection stage and a validation stage. The sequence selection stage produces a rank-ordered list of amino-acid sequences by solving an integer programming sequence selection model. The validation stage consists of fold specificity and approximate binding affinity calculations. The designed peptidic inhibitors are 12-amino-acids-long and target the hydrophobic core of gp41. A number of the best-predicted sequences were synthesized and their inhibition of HIV-1 was tested in cell culture. All peptides examined showed inhibitory activity when compared with no drug present, and the novel peptide sequences outperformed the native template sequence used for the design. The best sequence showed micromolar inhibition, which is a 3-15-fold improvement over the native sequence, depending on the donor. In addition, the best sequence equally inhibited wild-type and Enfuvirtide-resistant virus strains.

De Novo Peptide Design with C3a Receptor Agonist and Antagonist Activities: Theoretical Predictions and Experimental Validation

Targeting the complement component 3a receptor (C3aR) with selective agonists or antagonists is believed to be a viable therapeutic option for several diseases such as stroke, heart attack, reperfusion injuries, and rheumatoid arthritis. We designed a number of agonists, partial agonists, and antagonists of C3aR using our two-stage de novo protein design framework. Of the peptides tested using a degranulation assay in C3aR-transfected rat basophilic leukemia cells, two were prominent agonists (EC(50) values of 25.3 and 66.2 nM) and two others were partial agonists (IC(50) values of 15.4 and 26.1 nM). Further testing of these lead compounds in a calcium flux assay in U937 cells yielded similar results although with reduced potencies compared to transfected cells. The partial agonists also displayed full antagonist activity when tested in a C3aR inhibition assay. In addition, the electrostatic potential profile was shown to potentially discriminate between full agonists and partial agonists.

Novel formulations for the sequence selection problem in de novo protein design with flexible templates

This paper presents two novel formulations for solving the sequence selection problem in de novo protein design with highly flexible templates, each of which exhibits a crystal or NMR, structure. The first formulation applies weighted average energy parameters to incorporate information about every structure, with the weights, which are parameters dependent on a pair of Cα positions and a particular distance bin, given by the probability that the distance between the two positions is found to belong to that distance bin in any of the structures. The second formulation allows the distance between the two positions considered to fall into any distance bin that all the structures span over, but imposes novel linear constraints to ensure a physically consistent structure. Both formulations were tested on redesigning Compstatin, the template of which has 21 NMR structures from the protein data bank.

New Compstatin Variants through Two De Novo Protein Design Frameworks

Two de novo protein design frameworks are applied to the discovery of new compstatin variants. One is based on sequence selection and fold specificity, whereas the other approach is based on sequence selection and approximate binding affinity calculations. The proposed frameworks were applied to a complex of C3c with compstatin variant E1 and new variants with improved binding affinities are predicted and experimentally validated. The computational studies elucidated key positions in the sequence of compstatin that greatly affect the binding affinity. Positions 4 and 13 were found to favor Trp, whereas positions 1, 9, and 10 are dominated by Asn, and position 11 consists mainly of Gln. A structural analysis of the C3c-bound peptide analogs is presented.

Computational comparison studies of quadratic assignment like formulations for the in silico sequence selection problem in de novo protein design

In this paper an O(n2) mathematical formulation for in silico sequence selection in de novo protein design proposed by Klepeis et al. (2003, 2004), in which the number of additional variables and linear constraints scales with the square of the number of binary variables, is compared to three O(n) formulations. It is found that the O(n2) formulation is superior to the O(n) formulations on most sequence search spaces. The superiority of the O(n2) formulation is due to the reformulation linearization techniques (RLTs), since the O(n2) formulation without RLTs is found to be computationally less efficient than the O(n) formulations. In addition, new algorithmic enhancing components of RLTs with inequality constraints, triangle inequalities, and Dead-End Elimination (DEE) type preprocessing are added to the O(n2) formulation. The current best O(n2) formulation, which is the original formulation from Klepeis et al. (2003, 2004) plus DEE type preprocessing, is proposed for in silico sequence search. For a test problem with a search space of 3.4×1045 sequences, this new improved model is able to reduce the required CPU time by 67%.

Computational design of the lasso peptide antibiotic microcin J25

Microcin J25 (MccJ25) is a 21 amino acid (aa) ribosomally synthesized antimicrobial peptide with an unusual structure in which the eight N-terminal residues form a covalently cyclized macrolactam ring through which the remaining 13 aa tail is fed. An open question is the extent of sequence space that can occupy such an extraordinary, highly constrained peptide fold. To begin answering this question, here we have undertaken a computational redesign of the MccJ25 peptide using a two-stage sequence selection procedure based on both energy minimization and fold specificity. Eight of the most highly ranked sequences from the design algorithm, each of which contained two or three amino acid substitutions, were expressed in Escherichia coli and tested for production and antimicrobial activity. Six of the eight variants were successfully produced by E.coli at production levels comparable with that of the wild-type peptide. Of these six variants, three retain detectable antimicrobial activity, although this activity is reduced relative to wild-type MccJ25. The results here build upon previous findings that even rigid, constrained structures like the lasso architecture are amenable to redesign. Furthermore, this work provides evidence that a large amount of amino acid variation is tolerated by the lasso peptide fold.

Overcoming the Key Challenges in De Novo Protein Design: Enhancing Computational Efficiency and Incorporating True Backbone Flexibility

De novo protein design is initiated with a postulated or known flexible threedimensional protein structure and aims at identifying amino acid sequences compatible with such a structure. The problem was first denoted as the “inverse folding problem” [4, 5] since protein design has intimate links to the well-known protein folding problem [6]. While the protein folding problem aims at determining the single structure for a sequence, the de novo protein design problem exhibits a high level of degeneracy; that is, a large number of sequences are always found to share a common fold, although the sequences will vary with respect to properties such as activity and stability.

A new de novo approach for optimizing peptides that inhibit HIV-1 entry

Abstract A new de novo protein design framework and its application to the redesign of an HIV-1 entry peptide inhibitor is presented.