Proteins inherently fluctuate between conformations to perform functions in the cell. For example, they sample product‐binding, transition‐state‐stabilizing and product‐release states during ...catalysis, and they integrate signals from remote regions of the structure for allosteric regulation. However, there is a lack of understanding of how these dynamic processes occur at the basic atomic level. This gap can be at least partially addressed by combining variable‐temperature (instead of traditional cryogenic temperature) X‐ray crystallography with algorithms for modeling alternative conformations based on electron‐density maps, in an approach called multitemperature multiconformer X‐ray crystallography (MMX). Here, the use of MMX to reveal alternative conformations at different sites in a protein structure and to estimate the degree of energetic coupling between them is discussed. These insights can suggest testable hypotheses about allosteric mechanisms. Temperature is an easily manipulated experimental parameter, so the MMX approach is widely applicable to any protein that yields well diffracting crystals. Moreover, the general principles of MMX are extensible to other perturbations such as pH, pressure, ligand concentration etc. Future work will explore strategies for leveraging X‐ray data across such perturbation series to more quantitatively measure how different parts of a protein structure are coupled to each other, and the consequences thereof for allostery and other aspects of protein function.
Crystallography at multiple temperatures can reveal the collective shifts of alternative conformations that underlie allosteric communication through protein structures.
This paper describes the current update on macromolecular model validation services that are provided at the MolProbity website, emphasizing changes and additions since the previous review in 2010. ...There have been many infrastructure improvements, including rewrite of previous Java utilities to now use existing or newly written Python utilities in the open‐source CCTBX portion of the Phenix software system. This improves long‐term maintainability and enhances the thorough integration of MolProbity‐style validation within Phenix. There is now a complete MolProbity mirror site at http://molprobity.manchester.ac.uk. GitHub serves our open‐source code, reference datasets, and the resulting multi‐dimensional distributions that define most validation criteria. Coordinate output after Asn/Gln/His “flip” correction is now more idealized, since the post‐refinement step has apparently often been skipped in the past. Two distinct sets of heavy‐atom‐to‐hydrogen distances and accompanying van der Waals radii have been researched and improved in accuracy, one for the electron‐cloud‐center positions suitable for X‐ray crystallography and one for nuclear positions. New validations include messages at input about problem‐causing format irregularities, updates of Ramachandran and rotamer criteria from the million quality‐filtered residues in a new reference dataset, the CaBLAM Cα‐CO virtual‐angle analysis of backbone and secondary structure for cryoEM or low‐resolution X‐ray, and flagging of the very rare cis‐nonProline and twisted peptides which have recently been greatly overused. Due to wide application of MolProbity validation and corrections by the research community, in Phenix, and at the worldwide Protein Data Bank, newly deposited structures have continued to improve greatly as measured by MolProbity's unique all‐atom clashscore.
Proteins must move between different conformations of their native ensemble to perform their functions. Crystal structures obtained from high-resolution X-ray diffraction data reflect this ...heterogeneity as a spatial and temporal conformational average. Although movement between natively populated alternative conformations can be critical for characterizing molecular mechanisms, it is challenging to identify these conformations within electron density maps. Alternative side chain conformations are generally well separated into distinct rotameric conformations, but alternative backbone conformations can overlap at several atomic positions. Our model building program qFit uses mixed integer quadratic programming (MIQP) to evaluate an extremely large number of combinations of sidechain conformers and backbone fragments to locally explain the electron density. Here, we describe two major modeling enhancements to qFit: peptide flips and alternative glycine conformations. We find that peptide flips fall into four stereotypical clusters and are enriched in glycine residues at the n+1 position. The potential for insights uncovered by new peptide flips and glycine conformations is exemplified by HIV protease, where different inhibitors are associated with peptide flips in the "flap" regions adjacent to the inhibitor binding site. Our results paint a picture of peptide flips as conformational switches, often enabled by glycine flexibility, that result in dramatic local rearrangements. Our results furthermore demonstrate the power of large-scale computational analysis to provide new insights into conformational heterogeneity. Overall, improved modeling of backbone heterogeneity with high-resolution X-ray data will connect dynamics to the structure-function relationship and help drive new design strategies for inhibitors of biomedically important systems.
Most macromolecular X-ray structures are determined from cryocooled crystals, but it is unclear whether cryocooling distorts functionally relevant flexibility. Here we compare independently acquired ...pairs of high-resolution data sets of a model Michaelis complex of dihydrofolate reductase (DHFR), collected by separate groups at both room and cryogenic temperatures. These data sets allow us to isolate the differences between experimental procedures and between temperatures. Our analyses of multiconformer models and time-averaged ensembles suggest that cryocooling suppresses and otherwise modifies side-chain and main-chain conformational heterogeneity, quenching dynamic contact networks. Despite some idiosyncratic differences, most changes from room temperature to cryogenic temperature are conserved and likely reflect temperature-dependent solvent remodeling. Both cryogenic data sets point to additional conformations not evident in the corresponding room temperature data sets, suggesting that cryocooling does not merely trap preexisting conformational heterogeneity. Our results demonstrate that crystal cryocooling consistently distorts the energy landscape of DHFR, a paragon for understanding functional protein dynamics.
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•Two room temperature versus two cryogenic DHFR X-ray data sets differ consistently•Crystal cryocooling traps preexisting conformations and favors new ones•Solvent ordering drives surface changes in both multiconformer and ensemble models•Functionally important intramolecular networks are evident only at room temperature
Most protein crystal structures are based on data collected under cryogenic conditions. Keedy et al. compare two cryogenic datasets against two room temperature datasets for DHFR, and show that cryocooling perturbs molecular flexibility, which is likely important for protein function.
MolProbity is a structure‐validation web service that provides broad‐spectrum solidly based evaluation of model quality at both the global and local levels for both proteins and nucleic acids. It ...relies heavily on the power and sensitivity provided by optimized hydrogen placement and all‐atom contact analysis, complemented by updated versions of covalent‐geometry and torsion‐angle criteria. Some of the local corrections can be performed automatically in MolProbity and all of the diagnostics are presented in chart and graphical forms that help guide manual rebuilding. X‐ray crystallography provides a wealth of biologically important molecular data in the form of atomic three‐dimensional structures of proteins, nucleic acids and increasingly large complexes in multiple forms and states. Advances in automation, in everything from crystallization to data collection to phasing to model building to refinement, have made solving a structure using crystallography easier than ever. However, despite these improvements, local errors that can affect biological interpretation are widespread at low resolution and even high‐resolution structures nearly all contain at least a few local errors such as Ramachandran outliers, flipped branched protein side chains and incorrect sugar puckers. It is critical both for the crystallographer and for the end user that there are easy and reliable methods to diagnose and correct these sorts of errors in structures. MolProbity is the authors' contribution to helping solve this problem and this article reviews its general capabilities, reports on recent enhancements and usage, and presents evidence that the resulting improvements are now beneficially affecting the global database.
Due to their low binding affinities, detecting small-molecule fragments bound to protein structures from crystallographic datasets has been a challenge. Here, we report a trove of 65 new fragment ...hits for PTP1B, an “undruggable” therapeutic target enzyme for diabetes and cancer. These structures were obtained from computational analysis of data from a large crystallographic screen, demonstrating the power of this approach to elucidate many (∼50% more) “hidden” ligand-bound states of proteins. Our new structures include a fragment hit found in a novel binding site in PTP1B with a unique location relative to the active site, one that links adjacent allosteric sites, and, perhaps most strikingly, a fragment that induces long-range allosteric protein conformational responses. Altogether, our research highlights the utility of computational analysis of crystallographic data, makes publicly available dozens of new ligand-bound structures of a high-value drug target, and identifies novel aspects of ligandability and allostery in PTP1B.
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•Computational reanalysis of a crystallographic small-molecule fragment screen for PTP1B•Identification of 65 new fragment hits across 59 new liganded crystal structures•New fragments reveal novel aspects of ligandability and allostery in PTP1B
Mehlman et al. report 65 new small-molecule fragment hits for PTP1B, an “undruggable” therapeutic target enzyme for diabetes and cancer. These structures were obtained from computational reanalysis of data from a large crystallographic screen, demonstrating the power of this approach to elucidate many (∼50% more) “hidden” ligand-bound states of proteins.
Many proteins have small-molecule binding pockets that are not easily detectable in the ligand-free structures. These cryptic sites require a conformational change to become apparent; a cryptic site ...can therefore be defined as a site that forms a pocket in a holo structure, but not in the apo structure. Because many proteins appear to lack druggable pockets, understanding and accurately identifying cryptic sites could expand the set of drug targets. Previously, cryptic sites were identified experimentally by fragment-based ligand discovery and computationally by long molecular dynamics simulations and fragment docking. Here, we begin by constructing a set of structurally defined apo–holo pairs with cryptic sites. Next, we comprehensively characterize the cryptic sites in terms of their sequence, structure, and dynamics attributes. We find that cryptic sites tend to be as conserved in evolution as traditional binding pockets but are less hydrophobic and more flexible. Relying on this characterization, we use machine learning to predict cryptic sites with relatively high accuracy (for our benchmark, the true positive and false positive rates are 73% and 29%, respectively). We then predict cryptic sites in the entire structurally characterized human proteome (11,201 structures, covering 23% of all residues in the proteome). CryptoSite increases the size of the potentially “druggable” human proteome from ~40% to ~78% of disease-associated proteins. Finally, to demonstrate the utility of our approach in practice, we experimentally validate a cryptic site in protein tyrosine phosphatase 1B using a covalent ligand and NMR spectroscopy. The CryptoSite Web server is available at http://salilab.org/cryptosite.
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•Bona fide cryptic sites identified by comparison of apo and holo protein structures.•Features distinguishing cryptic sites and binding pockets identified.•Efficient and accurate prediction of cryptic sites developed.•Cryptic sites predicted for all human proteins of known structure.•The “druggable” human proteome may be larger than previously estimated.
Allostery is an inherent feature of proteins, but it remains challenging to reveal the mechanisms by which allosteric signals propagate. A clearer understanding of this intrinsic circuitry would ...afford new opportunities to modulate protein function. Here, we have identified allosteric sites in protein tyrosine phosphatase 1B (PTP1B) by combining multiple-temperature X-ray crystallography experiments and structure determination from hundreds of individual small-molecule fragment soaks. New modeling approaches reveal 'hidden' low-occupancy conformational states for protein and ligands. Our results converge on allosteric sites that are conformationally coupled to the active-site WPD loop and are hotspots for fragment binding. Targeting one of these sites with covalently tethered molecules or mutations allosterically inhibits enzyme activity. Overall, this work demonstrates how the ensemble nature of macromolecular structure, revealed here by multitemperature crystallography, can elucidate allosteric mechanisms and open new doors for long-range control of protein function.
Protein tyrosine phosphatase 1B (PTP1B) is a validated therapeutic target for obesity, diabetes, and certain types of cancer. In particular, allosteric inhibitors hold potential for therapeutic use, ...but an incomplete understanding of conformational dynamics and allostery in this protein has hindered their development. Here, we interrogate solution dynamics and allosteric responses in PTP1B using high‐resolution hydrogen‐deuterium exchange mass spectrometry (HDX‐MS), an emerging and powerful biophysical technique. Using HDX‐MS, we obtain a detailed map of backbone amide exchange that serves as a proxy for the solution dynamics of apo PTP1B, revealing several flexible loops interspersed among more constrained and rigid regions within the protein structure, as well as local regions that exchange faster than expected from their secondary structure and solvent accessibility. We demonstrate that our HDX rate data obtained in solution adds value to estimates of conformational heterogeneity derived from a pseudo‐ensemble constructed from ~200 crystal structures of PTP1B. Furthermore, we report HDX‐MS maps for PTP1B with active‐site versus allosteric small‐molecule inhibitors. These maps suggest distinct and widespread effects on protein dynamics relative to the apo form, including changes in locations distal (>35 Å) from the respective ligand binding sites. These results illuminate that allosteric inhibitors of PTP1B can induce unexpected changes in dynamics that extend beyond the previously understood allosteric network. Together, our data suggest a model of BB3 allostery in PTP1B that combines conformational restriction of active‐site residues with compensatory liberation of distal residues that aid in entropic balancing. Overall, our work showcases the potential of HDX‐MS for elucidating aspects of protein conformational dynamics and allosteric effects of small‐molecule ligands and highlights the potential of integrating HDX‐MS alongside other complementary methods, such as room‐temperature X‐ray crystallography, NMR spectroscopy, and molecular dynamics simulations, to guide the development of new therapeutics.
Proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is ...critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein–ligand states into X-ray data. Here, we designed a computational method, qFit-ligand, to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor–ligand complexes. In an analysis of the cancer related BRD4 domain, we found that up to 29% of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand–receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. Combining qFit-ligand with high-throughput screening or multitemperature crystallography could therefore augment the structure-based drug design toolbox.
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