Harnessing conformational drivers in drug design.

This review article explores the pivotal role of conformational drivers in the discovery of drug-like molecules and illustrates their significance through real-life examples. Understanding molecular conformation is paramount to drug hunting as it can impact on- and off-target potency, metabolism, permeability, and solubility. Each conformational driver or effector is described and exemplified in a separate section. The final section is dedicated to NMR spectroscopy and illustrates its utility as an essential tool for conformational design.

Unveiling the "invisible" druggable conformations of GDP-bound inactive Ras.

The prevalent view on whether Ras is druggable has gradually changed in the recent decade with the discovery of effective inhibitors binding to cryptic sites unseen in the native structures. Despite the promising advances, therapeutics development toward higher potency and specificity is challenged by the elusive nature of these binding pockets. Here we derive a conformational ensemble of guanosine diphosphate (GDP)-bound inactive Ras by integrating spin relaxation-validated atomistic simulation with NMR chemical shifts and residual dipolar couplings, which provides a quantitative delineation of the intrinsic dynamics up to the microsecond timescale. The experimentally informed ensemble unequivocally demonstrates the preformation of both surface-exposed and buried cryptic sites in Ras•GDP, advocating design of inhibition by targeting the transient druggable conformers that are invisible to conventional experimental methods. The viability of the ensemble-based rational design has been established by retrospective testing of the ability of the Ras•GDP ensemble to identify known ligands from decoys in virtual screening.

Scrutinising the Conformational Ensemble of the Intrinsically Mixed-Folded Protein Galectin-3.

Galectin-3 is a protein involved in many intra- and extra-cellular processes. It has been identified as a diagnostic or prognostic biomarker for certain types of heart disease, kidney disease and cancer. Galectin-3 comprises a carbohydrate recognition domain (CRD) and an N-terminal domain (NTD), which is unstructured and contains eight collagen-like Pro-Gly-rich tandem repeats. While the structure of the CRD has been solved using protein crystallography, current knowledge about conformations of full-length galectin-3 is limited. To fill in this knowledge gap, we performed molecular dynamics (MD) simulations of full-length galectin-3. We systematically re-scaled the solute-solvent interactions in the Martini 3 force field to obtain the best possible agreement between available data from SAXS experiments and the ensemble of conformations generated in the MD simulations. The simulation conformations were found to be very diverse, as reflected, e.g., by (i) large fluctuations in the radius of gyration, ranging from about 2 to 5 nm, and (ii) multiple transient contacts made by amino acid residues in the NTD. Consistent with evidence from NMR experiments, contacts between the CRD and NTD were observed to not involve the carbohydrate-binding site on the CRD surface. Contacts within the NTD were found to be made most frequently by aromatic residues. Formation of fuzzy complexes with unspecific stoichiometry was observed to be mediated mostly by the NTD. Taken together, we offer a detailed picture of the conformational ensemble of full-length galectin-3, which will be important for explaining the biological functions of this protein at the molecular level.

Breaking the conformational ensemble barrier: Ensemble structure modeling challenges in CASP15.

For the first time, the 2022 CASP (Critical Assessment of Structure Prediction) community experiment included a section on computing multiple conformations for protein and RNA structures. There was full or partial success in reproducing the ensembles for four of the nine targets, an encouraging result. For protein structures, enhanced sampling with variations of the AlphaFold2 deep learning method was by far the most effective approach. One substantial conformational change caused by a single mutation across a complex interface was accurately reproduced. In two other assembly modeling cases, methods succeeded in sampling conformations near to the experimental ones even though environmental factors were not included in the calculations. An experimentally derived flexibility ensemble allowed a single accurate RNA structure model to be identified. Difficulties included how to handle sparse or low-resolution experimental data and the current lack of effective methods for modeling RNA/protein complexes. However, these and other obstacles appear addressable.

Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins.

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights. Determining conformational ensembles usually involves the integration of biophysical experiments and computational models. In this review, we discuss current approaches to determine conformational ensembles of IDPs and multidomain proteins, including the choice of biophysical experiments, computational models used to sample protein conformations, models to calculate experimental observables from protein structure, and methods to refine ensembles against experimental data. We also provide examples of recent applications of integrative conformational ensemble determination to study IDPs and multidomain proteins and suggest future directions for research in the field.

Generation of the configurational ensemble of an intrinsically disordered protein from unbiased molecular dynamics simulation.

Intrinsically disordered proteins (IDPs) are abundant in eukaryotic proteomes, play a major role in cell signaling, and are associated with human diseases. To understand IDP function it is critical to determine their configurational ensemble, i.e., the collection of 3-dimensional structures they adopt, and this remains an immense challenge in structural biology. Attempts to determine this ensemble computationally have been hitherto hampered by the necessity of reweighting molecular dynamics (MD) results or biasing simulation in order to match ensemble-averaged experimental observables, operations that reduce the precision of the generated model because different structural ensembles may yield the same experimental observable. Here, by employing enhanced sampling MD we reproduce the experimental small-angle neutron and X-ray scattering profiles and the NMR chemical shifts of the disordered N terminal (SH4UD) of c-Src kinase without reweighting or constraining the simulations. The unbiased simulation results reveal a weakly funneled and rugged free energy landscape of SH4UD, which gives rise to a heterogeneous ensemble of structures that cannot be described by simple polymer theory. SH4UD adopts transient helices, which are found away from known phosphorylation sites and could play a key role in the stabilization of structural regions necessary for phosphorylation. Our findings indicate that adequately sampled molecular simulations can be performed to provide accurate physical models of flexible biosystems, thus rationalizing their biological function.

Dynamically encoded reactivity of Ras enzymes: opening new frontiers for drug discovery.

Decoding molecular flexibility in order to understand and predict biological processes-applying the principles of dynamic-structure-activity relationships (DSAR)-becomes a necessity when attempting to design selective and specific inhibitors of a protein that has overlapping interaction surfaces with its upstream and downstream partners along its signaling cascade. Ras proteins are molecular switches that meet this definition perfectly. The close-lying P-loop and the highly flexible switch I and switch II regions are the site of nucleotide-, assisting-, and effector-protein binding. Oncogenic mutations that also appear in this region do not cause easily characterized overall structural changes, due partly to the inherent conformational heterogeneity and pliability of these segments. In this review, we present an overview of the results obtained using approaches targeting Ras dynamics, such as nuclear magnetic resonance (NMR) measurements and experiment-based modeling calculations (mostly molecular dynamics (MD) simulations). These methodologies were successfully used to decipher the mutant- and isoform-specific nature of certain transient states, far-lying allosteric sites, and the internal interaction networks, as well as the interconnectivity of the catalytic and membrane-binding regions. This opens new therapeutic potential: the discovered interaction hotspots present hitherto not targeted, selective sites for drug design efforts in diverse locations of the protein matrix.

Analytical and functional aspects of protein-ligand interactions: Beyond induced fit and conformational selection.

Ligand-dependent changes in protein conformation are foundational to biology. Historical mechanistic models for substrate-specific proteins are induced fit (IF) and conformational selection (CS), which invoke a change in protein conformation after ligand binds or before ligand binds, respectively. These mechanisms have important, but rarely discussed, functional relevance because IF vs. CS can differentially affect a protein's substrate specificity or promiscuity, and its regulatory properties. The modern view of proteins as conformational ensembles in both ligand free and bound states, together with the realization that most proteins exhibit some substrate promiscuity, demands a deeper interpretation of the historical models and provides an opportunity to improve mechanistic analyses. Here we describe alternative analytical strategies for distinguishing the historical models, including the more complex expanded versions of IF and CS. Functional implications of the different models are described. We provide an alternative perspective based on protein ensembles interacting with ligand ensembles that clarifies how a single protein can 'apparently' exploit different mechanisms for different ligands. Mechanistic information about protein ensembles can be optimized when they are probed with multiple ligands.

Structural ensemble and biological activity of DciA intrinsically disordered region.

DciA is a newly discovered bacterial protein involved in loading the replicative helicase DnaB onto DNA at the initiation step of chromosome replication. Its three-dimensional structure is composed of a folded N-terminal domain (residues 1-111) resembling K Homology domains and a long disordered C-terminal tail (residues 112-157) which structure-activity relationship remains to be elucidated. In the present study on Vibrio cholerae DciA, we emphasize the importance of its disordered region to load DnaB onto DNA using surface plasmon resonance (SPR) and isothermal titration microcalorimetry (ITC). Then we characterize the conformational ensemble of the full-length protein using a combination of circular dichroism (CD), small angle X-ray scattering (SAXS), and molecular dynamics (MD) simulations. The atomic-level structural ensemble generated by MD simulations is in very good agreement with SAXS data. From initial conformations of the C-terminal tail without any secondary structure, our simulations bring to light several transient helical structures in this segment, which might be molecular recognition features (MoRFs) for the binding to DnaB and its recruitment and loading onto DNA.

Computational methods for exploring protein conformations.

Proteins are dynamic molecules that can transition between a potentially wide range of structures comprising their conformational ensemble. The nature of these conformations and their relative probabilities are described by a high-dimensional free energy landscape. While computer simulation techniques such as molecular dynamics simulations allow characterisation of the metastable conformational states and the transitions between them, and thus free energy landscapes, to be characterised, the barriers between states can be high, precluding efficient sampling without substantial computational resources. Over the past decades, a dizzying array of methods have emerged for enhancing conformational sampling, and for projecting the free energy landscape onto a reduced set of dimensions that allow conformational states to be distinguished, known as collective variables (CVs), along which sampling may be directed. Here, a brief description of what biomolecular simulation entails is followed by a more detailed exposition of the nature of CVs and methods for determining these, and, lastly, an overview of the myriad different approaches for enhancing conformational sampling, most of which rely upon CVs, including new advances in both CV determination and conformational sampling due to machine learning.

Conformational Characterization and Classification of Intrinsically Disordered Proteins by Native Mass Spectrometry and Charge-State Distribution Analysis.

Intrinsically disordered proteins (IDPs) are systematically under-represented in structural proteomics studies. Their structural characterization implies description of the dynamic conformational ensembles populated by these polymers in solution, posing major challenges to biophysical methods. "Native" MS (native-MS) has emerged as a central tool in this field, conjugating the unique MS analytical power with structurally meaningful descriptors, like solvent-accessible surface area (SASA) and collisional cross section (CCS). This review summarizes recently published papers comparing native-MS and solution methods, with a focus on charge-state-distribution (CSD) analysis for IDP conformational analysis. The results point to substantial agreement, supporting structural interpretation of native-MS spectra of IDPs. The discussion is integrated with data from our group on "synthetic" IDPs, obtained by reduction and alkylation of natively folded proteins, whose fold is stabilized by disulfide bridges. Finally, an MS-based compaction index (CI) is introduced, evaluating SASA with reference to globular and fully disorder proteins. Such a parameter can be calculated for single conformers or the whole conformational ensemble, offering a continuous index for IDP comparison and classification.

Hyperpolarized MAS NMR of unfolded and misfolded proteins.

In this article we give an overview over the use of DNP-enhanced solid-state NMR spectroscopy for the investigation of unfolded, disordered and misfolded proteins. We first provide an overview over studies in which DNP spectroscopy has successfully been applied for the structural investigation of well-folded amyloid fibrils formed by short peptides as well as full-length proteins. Sample cooling to cryogenic temperatures often leads to severe line broadening of resonance signals and thus a loss in resolution. However, inhomogeneous line broadening at low temperatures provides valuable information about residual dynamics and flexibility in proteins, and, in combination with appropriate selective isotope labeling techniques, inhomogeneous linewidths in disordered proteins or protein regions may be exploited for evaluation of conformational ensembles. In the last paragraph we highlight some recent studies where DNP-enhanced MAS-NMR-spectroscopy was applied to the study of disordered proteins/protein regions and inhomogeneous sample preparations.

CAMERRA: An analysis tool for the computation of conformational dynamics by evaluating residue-residue associations.

A computational method which extracts the dominant motions from an ensemble of biomolecular conformations via a correlation analysis of residue-residue contacts is presented. The algorithm first renders the structural information into contact matrices, then constructs the collective modes based on the correlated dynamics of a selected set of dynamic contacts. Associated programs can bridge the results for further visualization using graphics software. The aim of this method is to provide an analysis of conformations of biopolymers from the contact viewpoint. It may assist a systematical uncovering of conformational switching mechanisms existing in proteins and biopolymer systems in general by statistical analysis of simulation snapshots. In contrast to conventional correlation analyses of Cartesian coordinates (such as distance covariance analysis and Cartesian principal component analysis), this program also provides an alternative way to locate essential collective motions in general. Herein, we detail the algorithm in a stepwise manner and comment on the importance of the method as applied to decoding allosteric mechanisms. © 2018 Wiley Periodicals, Inc.

To be disordered or not to be disordered: is that still a question for proteins in the cell?

There is ample evidence that many proteins or regions of proteins lack a well-defined folded structure under native-like conditions. These are called intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). Whether this intrinsic disorder is also their main structural characteristic in living cells has been a matter of intense debate. The structural analysis of IDPs became an important challenge also because of their involvement in a plethora of human diseases, which made IDPs attractive targets for therapeutic development. Therefore, biophysical approaches are increasingly being employed to probe the structural and dynamical state of proteins, not only in isolation in a test tube, but also in a complex biological environment and even within intact cells. Here, we survey direct and indirect evidence that structural disorder is in fact the physiological state of many proteins in the proteome. The paradigmatic case of α-synuclein is used to illustrate the controversial nature of this topic.

Efficacy of independence sampling in replica exchange simulations of ordered and disordered proteins.

Recasting temperature replica exchange (T-RE) as a special case of Gibbs sampling has led to a simple and efficient scheme for enhanced mixing (Chodera and Shirts, J. Chem. Phys., 2011, 135, 194110). To critically examine if T-RE with independence sampling (T-REis) improves conformational sampling, we performed T-RE and T-REis simulations of ordered and disordered proteins using coarse-grained and atomistic models. The results demonstrate that T-REis effectively increase the replica mobility in temperatures space with minimal computational overhead, especially for folded proteins. However, enhanced mixing does not translate well into improved conformational sampling. The convergences of thermodynamic properties interested are similar, with slight improvements for T-REis of ordered systems. The study re-affirms the efficiency of T-RE does not appear to be limited by temperature diffusion, but by the inherent rates of spontaneous large-scale conformational re-arrangements. Due to its simplicity and efficacy of enhanced mixing, T-REis is expected to be more effective when incorporated with various Hamiltonian-RE protocols. © 2017 Wiley Periodicals, Inc.

Ligand- and mutation-induced conformational selection in the CCR5 chemokine G protein-coupled receptor.

We predicted the structural basis for pleiotropic signaling of the C-C chemokine type 5 (CCR5) G protein-coupled receptor (GPCR) by predicting the binding of several ligands to the lower-energy conformations of the CCR5 receptor and 11 mutants. For each case, we predicted the ∼ 20 most stable conformations for the receptor along with the binding sites for four anti-HIV ligands. We found that none of the ligands bind to the lowest-energy apo-receptor conformation. The three ligands with a similar pharmacophore (Maraviroc, PF-232798, and Aplaviroc) bind to a specific higher-energy receptor conformation whereas TAK-779 (with a different pharmacophore) binds to a different high-energy conformation. This result is in agreement with the very different binding-site profiles for these ligands obtained by us and others. The predicted Maraviroc binding site agrees with the recent structure of CCR5 receptor cocrystallized with Maraviroc. We performed 11 site-directed mutagenesis experiments to validate the predicted binding sites. Here, we independently predicted the lowest 10 mutant protein conformations for each of the 11 mutants and then docked the ligands to these lowest conformations. We found the predicted binding energies to be in excellent agreement with our mutagenesis experiments. These results show that, for GPCRs, each ligand can stabilize a different protein conformation, complicating the use of cocrystallized structures for ligand screening. Moreover, these results show that a single-point mutation in a GPCR can dramatically alter the available low-energy conformations, which in turn alters the binding site, potentially altering downstream signaling events. These studies validate the conformational selection paradigm for the pleiotropic function and structural plasticity of GPCRs.

Osmolyte-Like Stabilizing Effects of Low GdnHCl Concentrations on d-Glucose/d-Galactose-Binding Protein.

The ability of d-glucose/d-galactose-binding protein (GGBP) to reversibly interact with its ligands, glucose and galactose, makes this protein an attractive candidate for sensing elements of glucose biosensors. This potential is largely responsible for attracting researchers to study the conformational properties of this protein. Previously, we showed that an increase in the fluorescence intensity of the fluorescent dye 6-bromoacetyl-2-dimetylaminonaphtalene (BADAN) is linked to the holo-form of the GGBP/H152C mutant in solutions containing sub-denaturing concentrations of guanidine hydrochloride (GdnHCl). It was hypothesized that low GdnHCl concentrations might lead to compaction of the protein, thereby facilitating ligand binding. In this work, we utilize BADAN fluorescence spectroscopy, intrinsic protein UV fluorescence spectroscopy, and isothermal titration calorimetry (ITC) to show that the sub-denaturing GdnHCl concentrations possess osmolyte-like stabilizing effects on the structural dynamics, conformational stability, and functional activity of GGBP/H152C and the wild type of this protein (wtGGBP). Our data are consistent with the model where low GdnHCl concentrations promote a shift in the dynamic distribution of the protein molecules toward a conformational ensemble enriched in molecules with a tighter structure and a more closed conformation. This promotes the increase in the configurational complementarity between the protein and glucose molecules that leads to the increase in glucose affinity in both GGBP/H152C and wtGGBP.

Structure-fluctuation-function relationships of seven pro-angiogenic isoforms of VEGFA, important mediators of tumorigenesis.

Vascular endothelial growth factor A (VEGFA) has different biological activities and plays a central role in tumor proliferation, angiogenesis and metastasis. Different VEGFA isoforms are generated by alternative splice site selection of exons 6, 7 and 8. In this paper, we analyzed the physical and chemical properties of the VEGFA exon 6 sequence, and modeled the three-dimensional structures of the regions corresponding to exons 6, 7 and 8 of six different pro-angiogenic isoforms of VEGFA in comparison to the experimental structure of VEGFA_165 by a combined approach of fold recognition and comparative modeling strategies and molecular dynamics simulations. Our results showed that i) exon 6 is a very flexible polycation with high disordered propensity, features well conserved in all mammals, ii) the structures of all the isoforms are stabilized by H-bond sub-networks organized around HUB residues and, iii) the charge content of exon 6 modulates the intrinsic structural preference of its flexible backbone, which can be described as an ensemble of conformations. Moreover, complexes between NRP-1 and VEGFA isoforms were modeled by molecular docking to study what isoforms are able to bind NRP-1. The analysis of complexes evidenced that VEGFA_121, VEGFA_145, VEGFA_183, VEGFA_189 and VEGFA_206, containing exons 7 and 8a, are able to interact with NRP-1 because they have the key regions of exons 7b and/or 8a. An overview of the isoforms shows how the fluctuations are the main guidance of their biological function. MD simulations also provide insights into factors that stabilize the binding regions of isoforms.

Thermal expansivities of peptides, polypeptides and proteins as measured by pressure perturbation calorimetry.

The main goal of this work was to provide direct experimental evidence that the expansivity of peptides, polypeptides and proteins as measured by pressure perturbation calorimetry (PPC), can serve as a proxy to characterize relative compactness of proteins, especially the denatured state ensemble. This is very important as currently only small angle X-ray scattering (SAXS), intrinsic viscosity and, to a lesser degree, fluorescence resonance transfer (FRET) experiments are capable of reporting on the compactness of denatured state ensembles. We combined the expansivity measurements with other biophysical methods (far-UV circular dichroism spectroscopy, differential scanning calorimetry, and small angle X-ray scattering). Three case studies of the effects of conformational changes on the expansivity of polypeptides in solution are presented. We have shown that expansivity appears to be insensitive to the helix-coil transition, and appears to reflect the changes in hydration of the side-chains. We also observed that the expansivity is sensitive to the global conformation of the polypeptide chain and thus can be potentially used to probe hydration of different collapsed states of denatured or even intrinsically disordered proteins.

Cyclopropane derivatives as potential human serine racemase inhibitors: unveiling novel insights into a difficult target.

d-Serine is the co-agonist of NMDA receptors and binds to the so-called glycine site. d-Serine is synthesized by human serine racemase (SR). Over activation of NMDA receptors is involved in many neurodegenerative diseases and, therefore, the inhibition of SR might represent a novel strategy for the treatment of these pathologies. SR is a very difficult target, with only few compounds so far identified exhibiting weak inhibitory activity. This study was aimed at the identification of novel SR inhibitor by mimicking malonic acid, the best-known SR inhibitor, with a cyclopropane scaffold. We developed, synthesized, and tested a series of cyclopropane dicarboxylic acid derivatives, complementing the synthetic effort with molecular docking. We identified few compounds that bind SR in high micromolar range with a lack of significant correlation between experimental and predicted binding affinities. The thorough analysis of the results can be exploited for the development of more potent SR inhibitors.