Molecular simulations integrated with experiments for probing the interaction dynamics and binding mechanisms of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) exploit their plasticity to deploy a rich panoply of soft interactions and binding phenomena. Advances in tailoring molecular simulations for IDPs combined with experimental cross-validation offer an atomistic view of the mechanisms that control IDP binding, function, and dysfunction. The emerging theme is that unbound IDPs autonomously form transient local structures and self-interactions that determine their binding behavior. Recent results have shed light on whether and how IDPs fold, stay disordered or drive condensation upon binding; how they achieve binding specificity and select among competing partners. The disorder-binding paradigm is now being proactively used by researchers to target IDPs for rational drug design and engineer molecular responsive elements for biosensing applications.

Insights into next generation sequencing guided antibody selection strategies.

Therapeutic antibody discovery often relies on in-vitro display methods to identify lead candidates. Assessing selected output diversity traditionally involves random colony picking and Sanger sequencing, which has limitations. Next-generation sequencing (NGS) offers a cost-effective solution with increased read depth, allowing a comprehensive understanding of diversity. Our study establishes NGS guidelines for antibody drug discovery, demonstrating its advantages in expanding the number of unique HCDR3 clusters, broadening the number of high affinity antibodies, expanding the total number of antibodies recognizing different epitopes, and improving lead prioritization. Surprisingly, our investigation into the correlation between NGS-derived frequencies of CDRs and affinity revealed a lack of association, although this limitation could be moderately mitigated by leveraging NGS clustering, enrichment and/or relative abundance across different regions to enhance lead prioritization. This study highlights NGS benefits, offering insights, recommendations, and the most effective approach to leverage NGS in therapeutic antibody discovery.

A modular approach to map out the conformational landscapes of unbound intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) fold upon binding to select/recruit multiple partners, morph around the partner's structure, and exhibit allostery. However, we do not know whether these properties emerge passively from disorder, or rather are encoded into the IDP's folding mechanisms. A main reason for this gap is the lack of suitable methods to dissect the energetics of IDP conformational landscapes without partners. Here we introduce such an approach that we term molecular LEGO, and apply it to NCBD, a helical, molten globule­like IDP, as proof of concept. The approach entails the experimental and computational characterization of the protein, its separate secondary structure elements (LEGO building blocks), and their supersecondary combinations. Comparative analysis uncovers specific, yet inconspicuous, energetic biases in the conformational/folding landscape of NCBD, including 1) strong local signals that define the three native helices, 2) stabilization of helix­helix interfaces via soft pairwise tertiary interactions, 3) cooperative stabilization of a heterogeneous three-helix bundle fold, and 4) a dynamic exchange between sets of tertiary interactions (native and nonnative) that recapitulate the different structures NCBD adopts in complex with various partners. Crucially, a tug of war between sets of interactions makes NCBD gradually shift between structural subensembles as a conformational rheostat. Such conformational rheostatic behavior provides a built-in mechanism to modulate binding and switch/recruit partners that is likely at the core of NCBD's function as transcriptional coactivator. Hence, the molecular LEGO approach emerges as a powerful tool to dissect the conformational landscapes of unbound IDPs and rationalize their functional mechanisms.

Molecular Simulations of Intrinsically Disordered Proteins and Their Binding Mechanisms.

Intrinsically disordered proteins (IDPs) lack well-defined secondary or tertiary structures in solution but are found to be involved in a wide range of critical cellular processes that highlight their functional importance. IDPs usually undergo folding upon binding to their targets. Such binding coupled to folding behavior has widened our perspective on the protein structure-dynamics-function paradigm in molecular biology. However, characterizing the folding upon binding mechanism of IDPs experimentally remains quite challenging. Molecular simulations emerge as a potentially powerful tool that offers information complementary to experiments. Here we present a general computational framework for the molecular simulations of IDP folding upon binding processes that combines all-atom molecular dynamics (MD) and coarse-grained simulations. The classical all-atom molecular dynamics approach using GPU acceleration allows the researcher to explore the properties of the IDP conformational ensemble, whereas coarse-grained structure-based models implemented with parameters carefully calibrated to available experimental measurements can be used to simulate the entire folding upon binding process. We also discuss a set of tools for the analysis of MD trajectories and describe the details of the computational protocol to follow so that it can be adapted by the user to study any IDP in isolation and in complex with partners.

Downhill (Un)Folding Coupled to Binding as a Mechanism for Engineering Broadband Protein Conformational Transducers.

Canonical proteins fold and function as conformational switches that toggle between their folded (on) and unfolded (off) states, a mechanism that also provides the basis for engineering transducers for biosensor applications. One of the limitations of such transducers, however, is their relatively narrow operational range, limited to ligand concentrations 20-fold below or above their C50. Previously, we discovered that certain fast-folding proteins lose/gain structure gradually (downhill folding), which led us to postulate their operation as conformational rheostats capable of processing inputs/outputs in analog fashion. Conformational rheostats could make transducers with extended sensitivity. Here we investigate this hypothesis by engineering pH transducing into the naturally pH insensitive, downhill folding protein gpW. Particularly, we engineered histidine grafts into its hydrophobic core to induce unfolding via histidine ionization. We designed and tested the effects of ionization via computational modeling and studied experimentally the four most promising single grafts and two double grafts. All tested mutants become reversible pH transducers in the 4-9 range, and their response increases proportionally to how buried the histidine graft is. Importantly, the pH-dependent reversible (un)folding occurs in rheostatic fashion, so the engineered transducers can detect up to 6 orders of magnitude in [H+] for single grafts, and even more for double grafts. Our results demonstrate that downhill (un)folding coupled to binding produces the gradual, analog responses to the ligand (here H+) that are expected of conformational rheostats, and which make them a powerful mechanism for engineering transducers with sensitivity over many orders of magnitude in ligand concentration (broadband).

Glutton: a tool for generating structural ensembles of partly disordered proteins from chemical shifts.

MOTIVATION: Many proteins are partially disordered in physiological conditions and only fold, fully or partially, upon binding. Their structural analysis is challenging because the accessible information, typically chemical shifts (CS) from nuclear magnetic resonance experiments, are averages over broad ensembles of conformations. We aim to develop a database for the analysis of such data in terms of conformational distributions of the protein backbone rather than of individual high-resolution structures. RESULTS: Glutton is the largest available database linking CS and protein 3D structures (5270 entries organized in three levels) and is searchable via a python script. It generates statistical distributions of ϕ-ψ dihedral angles based on CS or vice versa. Such ϕ-ψ distributions are used to calculate structural ensembles of partially disordered proteins from their CS. For folded proteins, such ensembles are excellent starting points for further refinement with additional experimental restraints (structure determination) or computational methods (structure prediction). AVAILABILITY AND IMPLEMENTATION: Glutton is freely available at https://github.com/YeeHo/Glutton. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Decoding Structural Properties of a Partially Unfolded Protein Substrate: En Route to Chaperone Binding.

Many proteins comprising of complex topologies require molecular chaperones to achieve their unique three-dimensional folded structure. The E.coli chaperone, GroEL binds with a large number of unfolded and partially folded proteins, to facilitate proper folding and prevent misfolding and aggregation. Although the major structural components of GroEL are well defined, scaffolds of the non-native substrates that determine chaperone-mediated folding have been difficult to recognize. Here we performed all-atomistic and replica-exchange molecular dynamics simulations to dissect non-native ensemble of an obligate GroEL folder, DapA. Thermodynamics analyses of unfolding simulations revealed populated intermediates with distinct structural characteristics. We found that surface exposed hydrophobic patches are significantly increased, primarily contributed from native and non-native ß-sheet elements. We validate the structural properties of these conformers using experimental data, including circular dichroism (CD), 1-anilinonaphthalene-8-sulfonic acid (ANS) binding measurements and previously reported hydrogen-deutrium exchange coupled to mass spectrometry (HDX-MS). Further, we constructed network graphs to elucidate long-range intra-protein connectivity of native and intermediate topologies, demonstrating regions that serve as central "hubs". Overall, our results implicate that genomic variations (or mutations) in the distinct regions of protein structures might disrupt these topological signatures disabling chaperone-mediated folding, leading to formation of aggregates.