Improved cytosine base editors generated from TadA variants.

Cytosine base editors (CBEs) enable programmable genomic C·G-to-T·A transition mutations and typically comprise a modified CRISPR-Cas enzyme, a naturally occurring cytidine deaminase, and an inhibitor of uracil repair. Previous studies have shown that CBEs utilizing naturally occurring cytidine deaminases may cause unguided, genome-wide cytosine deamination. While improved CBEs that decrease stochastic genome-wide off-targets have subsequently been reported, these editors can suffer from suboptimal on-target performance.

A proteomic platform to identify off-target proteins associated with therapeutic modalities that induce protein degradation or gene silencing.

Novel modalities such as PROTAC and RNAi have the ability to inadvertently alter the abundance of endogenous proteins. Currently available in vitro secondary pharmacology assays, which evaluate off-target binding or activity of small molecules, do not fully assess the off-target effects of PROTAC and are not applicable to RNAi. To address this gap, we developed a proteomics-based platform to comprehensively evaluate the abundance of off-target proteins.

Quantifying the nativeness of antibody sequences using long short-term memory networks.

Antibodies often undergo substantial engineering en route to the generation of a therapeutic candidate with good developability properties. Characterization of antibody libraries has shown that retaining native-like sequence improves the overall quality of the library. Motivated by recent advances in deep learning, we developed a bi-directional long short-term memory (LSTM) network model to make use of the large amount of available antibody sequence information, and use this model to quantify the nativeness of antibody sequences.

ClusPro PeptiDock: efficient global docking of peptide recognition motifs using FFT.

Summary: We present an approach for the efficient docking of peptide motifs to their free receptor structures. Using a motif based search, we can retrieve structural fragments from the Protein Data Bank (PDB) that are very similar to the peptide's final, bound conformation. We use a Fast Fourier Transform (FFT) based docking method to quickly perform global rigid body docking of these fragments to the receptor.

Detection of Peptide-Binding Sites on Protein Surfaces Using the Peptimap Server.

Peptide-mediated interactions are of primordial importance to the cell, and the structure of such interaction provides an important starting point for their further characterization. In many cases, the structure of the peptide-protein complex has not been solved by experiment, and modeling tools need to be applied to generate structural models of the interaction. PeptiMap is a protocol that identifies the peptide-binding site when only the structure of the receptor is known, but no information about where the peptide binds is available.

New additions to the ClusPro server motivated by CAPRI.

The heavily used protein-protein docking server ClusPro performs three computational steps as follows: (1) rigid body docking, (2) RMSD based clustering of the 1000 lowest energy structures, and (3) the removal of steric clashes by energy minimization. In response to challenges encountered in recent CAPRI targets, we added three new options to ClusPro. These are (1) accounting for small angle X-ray scattering data in docking; (2) considering pairwise interaction data as restraints; and (3) enabling discrimination between biological and crystallographic dimers.

A benchmark testing ground for integrating homology modeling and protein docking.

Protein docking procedures carry out the task of predicting the structure of a protein-protein complex starting from the known structures of the individual protein components. More often than not, however, the structure of one or both components is not known, but can be derived by homology modeling on the basis of known structures of related proteins deposited in the Protein Data Bank (PDB). Thus, the problem is to develop methods that optimally integrate homology modeling and docking with the goal of predicting the structure of a complex directly from the amino acid sequences of its component proteins.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank.

Focused grid-based resampling for protein docking and mapping.

The fast Fourier transform (FFT) sampling algorithm has been used with success in application to protein-protein docking and for protein mapping, the latter docking a variety of small organic molecules for the identification of binding hot spots on the target protein. Here we explore the local rather than global usage of the FFT sampling approach in docking applications. If the global FFT based search yields a near-native cluster of docked structures for a protein complex, then focused resampling of the cluster generally leads to a substantial increase in the number of conformations close to the native structure.

The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins.

FTMap is a computational mapping server that identifies binding hot spots of macromolecules-i.e., regions of the surface with major contributions to the ligand-binding free energy.

Evidence of conformational selection driving the formation of ligand binding sites in protein-protein interfaces.

Many protein-protein interactions (PPIs) are compelling targets for drug discovery, and in a number of cases can be disrupted by small molecules. The main goal of this study is to examine the mechanism of binding site formation in the interface region of proteins that are PPI targets by comparing ligand-free and ligand-bound structures. To avoid any potential bias, we focus on ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) techniques and deposited in the Protein Data Bank, rather than on ensembles specifically generated for this study.

Detection of peptide-binding sites on protein surfaces: the first step toward the modeling and targeting of peptide-mediated interactions.

Peptide-mediated interactions, in which a short linear motif binds to a globular domain, play major roles in cellular regulation. An accurate structural model of this type of interaction is an excellent starting point for the characterization of the binding specificity of a given peptide-binding domain. A number of different protocols have recently been proposed for the accurate modeling of peptide-protein complex structures, given the structure of the protein receptor and the binding site on its surface.

How good is automated protein docking?

The protein docking server ClusPro has been participating in critical assessment of prediction of interactions (CAPRI) since its introduction in 2004. This article evaluates the performance of ClusPro 2.0 for targets 46-58 in Rounds 22-27 of CAPRI.

Application of asymmetric statistical potentials to antibody-protein docking.

Motivation: An effective docking algorithm for antibody-protein antigen complex prediction is an important first step toward design of biologics and vaccines. We have recently developed a new class of knowledge-based interaction potentials called Decoys as the Reference State (DARS) and incorporated DARS into the docking program PIPER based on the fast Fourier transform correlation approach. Although PIPER was the best performer in the latest rounds of the CAPRI protein docking experiment, it is much less accurate for docking antibody-protein antigen pairs than other types of complexes, in spite of incorporating sequence-based information on the location of the paratope.

Computational mapping reveals dramatic effect of Hoogsteen breathing on duplex DNA reactivity with formaldehyde.

Formaldehyde has long been recognized as a hazardous environmental agent highly reactive with DNA. Recently, it has been realized that due to the activity of histone demethylation enzymes within the cell nucleus, formaldehyde is produced endogenously, in direct vicinity of genomic DNA. Should it lead to extensive DNA damage? We address this question with the aid of a computational mapping method, analogous to X-ray and nuclear magnetic resonance techniques for observing weakly specific interactions of small organic compounds with a macromolecule in order to establish important functional sites.

FTMAP: extended protein mapping with user-selected probe molecules.

Binding hot spots, protein sites with high-binding affinity, can be identified using X-ray crystallography or NMR by screening libraries of small organic molecules that tend to cluster at such regions. FTMAP, a direct computational analog of the experimental screening approaches, globally samples the surface of a target protein using small organic molecules as probes, finds favorable positions, clusters the conformations and ranks the clusters on the basis of the average energy. The regions that bind several probe clusters predict the binding hot spots, in good agreement with experimental results.