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Molecular docking and molecular dynamics (MD) are powerful tools used to investigate protein-ligand interactions. Molecular docking programs predict the binding pose and affinity of a protein-ligand complex, while MD can be used to incorporate flexibility into docking calculations and gain further information on the kinetics and stability of the protein-ligand bond. This review covers state-of-the-art methods of using molecular docking and MD to explore protein-ligand interactions, with emphasis on application to drug discovery. We also call for further research on combining common molecular docking and MD methods.

Computational enzyme design has made great strides over the last five years. Traditional methods of enzyme design require synthesis and evaluation of many mutations. Computational enzyme design has emerged as a powerful tool to predict how specific mutations modify a protein’s activity, stability, and/or selectivity. Such computational approaches can evaluate many mutations and reduce the load of in vitro work by identifying mutations likely to accomplish design objectives. Computational approaches can explore mutational spaces inaccessible in traditional mutagenesis. Computational methods reduce cost and time compared with experimental approaches. We review the efficacy and key differences of computational enzyme design methods as published in recent studies. The included articles used computational methods to design enzymes, were published no earlier than 2015, met design objectives, and verified results in vitro.

High-Throughput Sequencing on a Next Generation Sequencer to Identify Specific Binders from a Phage Library

Antibody Solution Viscosity and Intermolecular Interactions: Considerations for Development of Highly Concentrated Formulations

Display of Membrane Proteins on a Viral Envelope for Antibody Generation

Sequence and Structural Determinants of Antigen Binding in Antibody CDR Loops

Enhancement of the Stability of Single Chain Fv Molecules with the Amino Acid Substitutions Predicted by High-Performance Computer

Thermal Stability of Camelid Single Domain VHH Antibody

Exogenous enzymes, signaling peptides, and other classes of nonhuman proteins represent a potentially massive but largely untapped pool of biotherapeutic agents. Adapting a foreign protein for therapeutic use poses numerous design challenges. We focus here on one significant problem: modifying the protein to mitigate the immune response mounted against "non-self" proteins, while not adversely affecting the protein's stability or therapeutic activity. In order to propose such variants suitable for experimental evaluation, this paper develops a computational method to select sets of mutations predicted to delete immunogenic T-cell epitopes, as evaluated by a 9-mer potential, while simultaneously maintaining important residues and residue interactions, as evaluated by one- and two-body potentials. While this design problem is NP-hard, we develop an integer programming approach that works very well in practice. We demonstrate the effectiveness of our approach by developing plans for biotherapeutic proteins that, in previous studies, have been partially deimmunized via extensive experimental characterization and modification of limited segments. In contrast, our global optimization technique considers an entire protein and accounts for all residues, residue interactions, and epitopes in proposing candidates worth subjecting to experimental evaluation.

Gene targeting to selected chromosomal loci is greatly stimulated when free DNA ends are created that initiate double-strand break repair. Gene therapy reagents can be developed by engineering DNA endonucleases that cleave genomes at desired target sequences. Homing endonucleases are naturally occurring rare-cutting enzymes that have well understood DNA binding and DNA cleavage properties. Rational design methods as well as directed evolution strategies that involve genetic selections and screens using combinatorial libraries generate homing endonucleases with altered sequence specificities. Molecular switches are being introduced into these enzymes to regulate their activity. This article reviews the progress that has been made in constructing homing endonucleases for gene therapy and genome engineering, and discusses the challenges that remain.

A central challenge in the field of metabolic engineering is the efficient identification of a metabolic pathway genotype that maximizes specific productivity over a robust range of process conditions. Here we review current methods for optimizing specific productivity of metabolic pathways in living cells. New tools for library generation, computational analysis of pathway sequence-flux space, and high-throughput screening and selection techniques are discussed.

Here we present a model to estimate the interaction free energy contribution of each amino acid residue of a given protein. Protein interaction energy is described in terms of per-residue interaction factors, $\mu$. Multibody interactions are implicitly captured in $\mu$ through the combination of amino acid terms ($\gamma$) guided by local conformation indices ($\sigma$). The model enables construction of an interaction factor heat map for a protein in a given fold, allows prima facie assessment of the degree of residue–residue interaction, and facilitates a qualitative and quantitative evaluation of protein association properties. The model was used to compute thermal stability of T4 bacteriophage lysozyme mutants across seven sites. Qualitative assessment of mutational effects provides a straightforward rationale regarding whether a particular site primarily perturbs native or non-native states, or both. The presented model was found to be in good agreement with experimental mutational data ($R^2=0.73$) and suggests an approach by which to convert structure space into energy space.

Homing endonucleases (HEs) are highly site-specific endonucleases that induce homologous recombination or gene conversion in vivo by cleaving long (typically >18bp) DNA target sites. Homing endonucleases are under development as tools for targeted genetic engineering applications, ranging from therapeutic gene correction to metabolic and population engineering. The first structures of homing endonucleases were reported 10 years ago. Since that time, representative structures from each of the known families of homing endonucleases have been determined, and the corresponding details of their mechanisms of DNA recognition and cleavage have been elucidated. Using this information, the LAGLIDADG homing endonuclease family has been identified as the most tractable for further modification by structure-based selection and/or engineering approaches. Most recently, successful redesign of the I-CreI endonuclease has led to the development of reagents that recognize and act on genes associated with monogenic diseases, including the human RAG1 and XPC genes. These studies demonstrate the feasibility of using engineered homing endonucleases to promote efficient and target site-specific modification of chromosomal loci. Current studies are rapidly improving the throughput and efficiency of homing endonuclease design and selection, and aim to optimize the specificity and activity of the resulting endonucleases for targeted genomic applications in medicine and biotechnology.