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Biomedical subjects

John R Desjarlais

Publications and source records attributed to John R Desjarlais.

9 recordsLinked to original sources
PubMed2006

A molecular immunology approach to antibody humanization and functional optimization.

We introduce a new method of humanization based on a novel and immunologically relevant metric of antibody humanness, termed human string content (HSC), that quantifies a sequence at the level of potential MHC/T-cell epitopes. Use of this quantity rather than global identity as an optimization goal enables the sampling of human diversity from distinct human germline sequences across the framework and CDR regions, and allows for the generation of multiple diverse candidate sequences. As a result engineering is carried out at finer sequence resolution relative to standard CDR grafting methods, providing for the optimization of antibody properties beyond immunogenicity such as antigen affinity and solution behavior. We have applied this method to the humanization of four antibodies with different antigen specificities. The resulting variable domains differ fundamentally from CDR-grafted antibodies in that they are immunologically more human and their humanness is derived from several discrete germline sequences. Furthermore, these antibodies bind their respective antigens better than or comparable to those of the parent antibodies without the need for affinity maturation.

Animals↗
PubMed2005

Rational design of intercellular adhesion molecule-1 (ICAM-1) variants for antagonizing integrin lymphocyte function-associated antigen-1-dependent adhesion.

The interaction between integrin lymphocyte function-associated antigen-1 (LFA-1) and its ligand intercellular adhesion molecule-1 (ICAM-1) is critical in immunological and inflammatory reactions but, like other adhesive interactions, is of low affinity. Here, multiple rational design methods were used to engineer ICAM-1 mutants with enhanced affinity for LFA-1. Five amino acid substitutions 1) enhance the hydrophobicity and packing of residues surrounding Glu-34 of ICAM-1, which coordinates to a Mg2+ in the LFA-1 I domain, and 2) alter associations at the edges of the binding interface. The affinity of the most improved ICAM-1 mutant for intermediate- and high-affinity LFA-1 I domains was increased by 19-fold and 22-fold, respectively, relative to wild type. Moreover, potency was similarly enhanced for inhibition of LFA-1-dependent ligand binding and cell adhesion. Thus, rational design can be used to engineer novel adhesion molecules with high monomeric affinity; furthermore, the ICAM-1 mutant holds promise for targeting LFA-1-ICAM-1 interaction for biological studies and therapeutic purposes.

Cell Adhesion↗
PubMed2003

Inactivation of TNF signaling by rationally designed dominant-negative TNF variants.

Tumor necrosis factor (TNF) is a key regulator of inflammatory responses and has been implicated in many pathological conditions. We used structure-based design to engineer variant TNF proteins that rapidly form heterotrimers with native TNF to give complexes that neither bind to nor stimulate signaling through TNF receptors. Thus, TNF is inactivated by sequestration. Dominant-negative TNFs represent a possible approach to anti-inflammatory biotherapeutics, and experiments in animal models show that the strategy can attenuate TNF-mediated pathology. Similar rational design could be used to engineer inhibitors of additional TNF superfamily cytokines as well as other multimeric ligands.

Amino Acid Substitution↗
PubMed2003

Increased detection of structural templates using alignments of designed sequences.

Protein structure prediction by comparative modeling benefits greatly from the use of multiple sequence alignment information to improve the accuracy of structural template identification and the alignment of target sequences to structural templates. Unfortunately, this benefit is limited to those protein sequences for which at least several natural sequence homologues exist. We show here that the use of large diverse alignments of computationally designed protein sequences confers many of the same benefits as natural sequences in identifying structural templates for comparative modeling targets. A large-scale massively parallelized application of an all-atom protein design algorithm, including a simple model of peptide backbone flexibility, has allowed us to generate 500 diverse, non-native, high-quality sequences for each of 264 protein structures in our test set. PSI-BLAST searches using the sequence profiles generated from the designed sequences ("reverse" BLAST searches) give near-perfect accuracy in identifying true structural homologues of the parent structure, with 54% coverage. In 41 of 49 genomes scanned using reverse BLAST searches, at least one novel structural template (not found by the standard method of PSI-BLAST against PDB) is identified. Further improvements in coverage, through optimizing the scoring function used to design sequences and continued application to new protein structures beyond the test set, will allow this method to mature into a useful strategy for identifying distantly related structural templates.

Algorithms↗
PubMed2003

Rational design and engineering of therapeutic proteins.

An increasing number of engineered protein therapeutics are currently being developed, tested in clinical trials and marketed for use. Many of these proteins arose out of hit-and-miss efforts to discover specific mutations, fusion partners or chemical modifications that confer desired properties. Through these efforts, several useful strategies have emerged for rational optimization of therapeutic candidates. The controlled manipulation of the physical, chemical and biological properties of proteins enabled by structure-based simulation is now being used to refine established rational engineering approaches and to advance new strategies. These methods provide clear, hypothesis-driven routes to solve problems that plague many proteins and to create novel mechanisms of action. We anticipate that rational protein engineering will shape the field of protein therapeutics dramatically by improving existing products and enabling the development of novel therapeutic agents.

Animals↗
PubMed2003

Designing proteins for therapeutic applications.

Protein design is becoming an increasingly useful tool for optimizing protein drugs and creating novel biotherapeutics. Recent progress includes the engineering of monoclonal antibodies, cytokines, enzymes and viral fusion inhibitors.

Animals↗
PubMed2003

A de novo redesign of the WW domain.

We have used a sequence prediction algorithm and a novel sampling method to design protein sequences for the WW domain, a small beta-sheet motif. The procedure, referred to as SPANS, designs sequences to be compatible with an ensemble of closely related polypeptide backbones, mimicking the inherent flexibility of proteins. Two designed sequences (termed SPANS-WW1 and SPANS-WW2), using only naturally occurring L-amino acids, were selected for study and the corresponding polypeptides were prepared in Escherichia coli. Circular dichroism data suggested that both purified polypeptides adopted secondary structure features related to those of the target without the aid of disulfide bridges or bound cofactors. The structure exhibited by SPANS-WW2 melted cooperatively by raising the temperature of the solution. Further analysis of this polypeptide by proton nuclear magnetic resonance spectroscopy demonstrated that at 5 degrees C, it folds into a structure closely resembling a natural WW domain. This achievement constitutes one of a small number of successful de novo protein designs through fully automated computational methods and highlights the feasibility of including backbone flexibility in the design strategy.

Algorithms↗
PubMed2002

Thoroughly sampling sequence space: large-scale protein design of structural ensembles.

Modeling the inherent flexibility of the protein backbone as part of computational protein design is necessary to capture the behavior of real proteins and is a prerequisite for the accurate exploration of protein sequence space. We present the results of a broad exploration of sequence space, with backbone flexibility, through a novel approach: large-scale protein design to structural ensembles. A distributed computing architecture has allowed us to generate hundreds of thousands of diverse sequences for a set of 253 naturally occurring proteins, allowing exciting insights into the nature of protein sequence space. Designing to a structural ensemble produces a much greater diversity of sequences than previous studies have reported, and homology searches using profiles derived from the designed sequences against the Protein Data Bank show that the relevance and quality of the sequences is not diminished. The designed sequences have greater overall diversity than corresponding natural sequence alignments, and no direct correlations are seen between the diversity of natural sequence alignments and the diversity of the corresponding designed sequences. For structures in the same fold, the sequence entropies of the designed sequences cluster together tightly. This tight clustering of sequence entropies within a fold and the separation of sequence entropy distributions for different folds suggest that the diversity of designed sequences is primarily determined by a structure's overall fold, and that the designability principle postulated from studies of simple models holds in real proteins. This has important implications for experimental protein design and engineering, as well as providing insight into protein evolution.

Amino Acid Sequence↗