Monitoring Ligand-Induced Protein Ordering in Drug Discovery

A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF-CBA to help users identify scenarios where the approach will be most useful. Given the method's speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification.

Sifting Through the Noise: A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners, but often include false positives. Furthermore, they provide no information about what the binding region is (e.g. the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competition Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment, along with the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies to AF and AF-CBA, to help users identify scenarios where the approach will be most useful. Given the speed and accuracy of the methodology, we expect it to be generally applicable to facilitate target selection for experimental verification starting from high-throughput protein libraries.

Computed Protein-Protein Enthalpy Signatures as a Tool for Identifying Conformation Sampling Problems

Understanding the thermodynamic signature of protein-peptide binding events is a major challenge in computational chemistry. The complexity generated by both components possessing many degrees of freedom poses a significant issue for methods that attempt to directly compute the enthalpic contribution to binding. Indeed, the prevailing assumption has been that the errors associated with such approaches would be too large for them to be meaningful. Nevertheless, we currently have no indication of how well the present methods would perform in terms of predicting the enthalpy of binding for protein-peptide complexes. To that end, we carefully assembled and curated a set of 11 protein-peptide complexes where there is structural and isothermal titration calorimetry data available and then computed the absolute enthalpy of binding. The initial "out of the box" calculations were, as expected, very modest in terms of agreement with the experiment. However, careful inspection of the outliers allows for the identification of key sampling problems such as distinct conformations of peptide termini not being sampled or suboptimal cofactor parameters. Additional simulations guided by these aspects can lead to a respectable correlation with isothermal titration calorimetry (ITC) experiments (R2 of 0.88 and an RMSE of 1.48 kcal/mol overall). Although one cannot know prospectively whether computed ITC values will be correct or not, this work shows that if experimental ITC data are available, then this in conjunction with computed ITC, can be used as a tool to know if the ensemble being simulated is representative of the true ensemble or not. That is important for allowing the correct interpretation of the detailed dynamics of the system with respect to the measured enthalpy. The results also suggest that computational calorimetry is becoming increasingly feasible. We provide the data set as a resource for the community, which could be used as a benchmark to help further progress in this area.

State of the Art of Pharmacological Activators of p53 in Ocular Malignancies

The pivotal role of p53 in the regulation of a vast array of cellular functions has been the subject of extensive research. The biological activity of p53 is not strictly limited to cell cycle arrest but also includes the regulation of homeostasis, DNA repair, apoptosis, and senescence. Thus, mutations in the p53 gene with loss of function represent one of the major mechanisms for cancer development. As expected, due to its key role, p53 is expressed throughout the human body including the eye. Specifically, altered p53 signaling pathways have been implicated in the development of conjunctival and corneal tumors, retinoblastoma, uveal melanoma, and intraocular melanoma. As non-selective cancer chemotherapies as well as ionizing radiation can be associated with either poor efficacy or dose-limiting toxicities in the eye, reconstitution of the p53 signaling pathway currently represents an attractive target for cancer therapy. The present review discusses the role of p53 in the pathogenesis of these ocular tumors and outlines the various pharmacological activators of p53 that are currently under investigation for the treatment of ocular malignancies.

Protein interactions: anything new?

How do proteins interact in the cellular environment? Which interactions stabilize liquid-liquid phase separated condensates? Are the concepts, which have been developed for specific protein complexes also applicable to higher-order assemblies? Recent discoveries prompt for a universal framework for protein interactions, which can be applied across the scales of protein communities. Here, we discuss how our views on protein interactions have evolved from rigid structures to conformational ensembles of proteins and discuss the open problems, in particular related to biomolecular condensates. Protein interactions have evolved to follow changes in the cellular environment, which manifests in multiple modes of interactions between the same partners. Such cellular context-dependence requires multiplicity of binding modes (MBM) by sampling multiple minima of the interaction energy landscape. We demonstrate that the energy landscape framework of protein folding can be applied to explain this phenomenon, opening a perspective toward a physics-based, universal model for cellular protein behaviors.

Classical and Machine Learning Methods for Protein - Ligand Binding Free Energy Estimation

Binding free energy estimation of drug candidates to their biomolecular target is one of the best quantitative estimators in computer-aided drug discovery. Accurate binding free energy estimation is still a challengeable task even after decades of research, along with the complexity of the algorithm, time-consuming procedures, and reproducibility issues. In this review, we have discussed the advantages and disadvantages of diverse free energy methods like Thermodynamic Integration (TI), Bennett's Acceptance Ratio (BAR), Free Energy Perturbation (FEP), alchemical methods. Moreover, we discussed the possible application of the machine learning method in protein-ligand binding free energy estimation.

Leveraging the multivalent p53 peptide-MdmX interaction to guide the improvement of small molecule inhibitors

Overexpressed Mdm2 and its 7homolog MdmX impair p53 activity in many cancers. Small molecules mimicking a p53 peptide can effectively inhibit Mdm2 but not MdmX. Here, we show a strategy for improving lead compounds for Mdm2 and MdmX inhibition based on the multivalency of the p53 peptide. Crystal structures of MdmX complexed with nutlin-3a, a strong Mdm2 inhibitor but a weak one for MdmX, reveal that nutlin-3a fits into the ligand binding pocket of MdmX mimicking the p53 peptide. However, due to distinct flexibility around the MdmX ligand binding pocket, the structures are missing many important intermolecular interactions that exist in the MdmX/p53 peptide and Mdm2/nultin-3a complexes. By targeting these flexible regions, we identify allosteric and additive fragments that enhance the binding affinity of nutlin-3a for MdmX, leading to potent Mdm2/MdmX inhibitors with anticancer activity. Our work provides a practical approach to drug design for signal transduction therapy.

Peptide fragments derived from the interfaces of protein-protein interactions (PPIs) provide useful templates for designing small molecule PPI inhibitors. Here, the authors utilize the multivalency of an MdmX-binding p53 peptide to develop a weak inhibitor of MdmX into potent Mdm2/MdmX inhibitors.

Therapeutic opportunities in cancer therapy: targeting the p53-MDM2/MDMX interactions

Ubiquitination is a key enzymatic post-translational modification that influences p53 stability and function. p53 protein regulates the expression of MDM2 (mouse double-minute 2 protein) E3 ligase and MDMX (double-minute 4 protein), through proteasome-based degradation. Exploration of targeting the ubiquitination pathway offers a potentially promising strategy for precision therapy in a variety of cancers. The p53-MDM2-MDMX pathway provides multiple molecular targets for small molecule screening as potential therapies for wild-type p53. As a result of its effect on molecular carcinogenesis, a personalized therapeutic approach based on the wild-type and mutant p53 protein is desirable. We highlighted the implications of p53 mutations in cancer, p53 ubiquitination mechanistic details, targeting p53-MDM2/MDMX interactions, significant discoveries related to MDM2 inhibitor drug development, MDM2 and MDMX dual target inhibitors, and clinical trials with p53-MDM2/MDMX-targeted drugs. We also investigated potential therapeutic repurposing of selective estrogen receptor modulators (SERMs) in targeting p53-MDM2/MDMX interactions. Molecular docking studies of SERMs were performed utilizing the solved structures of the p53/MDM2/MDMX proteins. These studies identified ormeloxifene as a potential dual inhibitor of p53/MDM2/MDMX interaction, suggesting that repurposing SERMs for dual targeting of p53/MDM2 and p53/MDMX interactions is an attractive strategy for targeting wild-type p53 tumors and warrants further preclinical research.

Elaboration of Non-naturally Occurring Helical Tripeptides as p53-MDM2/MDMX Interaction Inhibitors

Protein-protein interactions (PPIs) are often mediated by helical, strand and/or coil secondary structures at the interface regions. We previously showed that non-naturally occurring, stable helical trimers of bicyclic β-amino acids (Abh) with all-trans amide bonds can block the p53-MDM2/MDMX α-helix-helix interaction, which plays a role in regulating p53 function. Here, we conducted docking and molecular dynamics calculations to guide the structural optimization of our reported compounds, focusing on modifications of the C-terminal/N-terminal residues. We confirmed that the modified peptides directly bind to MDM2 by means of thermal shift assay, isothermal titration calorimetry, and enzyme-linked immunosorbent assay (ELISA) experiments. Biological activity assay in human osteosarcoma cell line SJSA-1, which has wild-type p53 and amplification of the Mdm2 gene, indicated that these peptides are membrane-permeable p53-MDM2/MDMX interaction antagonists that can rescue p53 function in the cells.

Tumor-Suppressor p53TAD1-60 Forms a Fuzzy Complex with Metastasis-Associated S100A4: Structural Insights and Dynamics by an NMR/MD Approach

Conformationally flexible protein complexes represent a major challenge for structural and dynamical studies. We present herein a method based on a hybrid NMR/MD approach to characterize the complex formed between the disordered p53TAD1-60 and the metastasis-associated S100A4. Disorder-to-order transitions of both TAD1 and TAD2 subdomains upon interaction is detected. Still, p53TAD1-60 remains highly flexible in the bound form, with residues L26, M40, and W53 being anchored to identical hydrophobic pockets of the S100A4 monomer chains. In the resulting "fuzzy" complex, the clamp-like binding of p53TAD1-60 relies on specific hydrophobic anchors and on the existence of extended flexible segments. Our results demonstrate that structural and dynamical NMR parameters (cumulative Δδ, SSP, temperature coefficients, relaxation time, hetNOE) combined with MD simulations can be used to build a structural model even if, due to high flexibility, the classical solution structure calculation is not possible.

Absolute Binding Free Energy Calculations for Highly Flexible Protein MDM2 and Its Inhibitors

Reliable prediction of binding affinities for ligand-receptor complex has been the primary goal of a structure-based drug design process. In this respect, alchemical methods are evolving as a popular choice to predict the binding affinities for biomolecular complexes. However, the highly flexible protein-ligand systems pose a challenge to the accuracy of binding free energy calculations mostly due to insufficient sampling. Herein, integrated computational protocol combining free energy perturbation based absolute binding free energy calculation with free energy landscape method was proposed for improved prediction of binding free energy for flexible protein-ligand complexes. The proposed method is applied to the dataset of various classes of p53-MDM2 (murine double minute 2) inhibitors. The absolute binding free energy calculations for MDMX (murine double minute X) resulted in a mean absolute error value of 0.816 kcal/mol while it is 3.08 kcal/mol for MDM2, a highly flexible protein compared to MDMX. With the integration of the free energy landscape method, the mean absolute error for MDM2 is improved to 1.95 kcal/mol.

AlphaSpace 2.0: Representing Concave Biomolecular Surfaces Using β-Clusters

Modern rational modulator design and structure-function characterization often concentrate on concave regions of biomolecular surfaces, ranging from well-defined small-molecule binding sites to large protein-protein interaction interfaces. Here, we introduce a β-cluster as a pseudomolecular representation of fragment-centric pockets detected by AlphaSpace [J. Chem. Inf. Model. 2015, 55, 1585], a recently developed computational analysis tool for topographical mapping of biomolecular concavities. By mimicking the shape as well as atomic details of potential molecular binders, this new β-cluster representation allows direct pocket-to-ligand shape comparison and can be used to guide ligand optimization. Furthermore, we defined the β-score, the optimal Vina score of the β-cluster, as an indicator of pocket ligandability and developed an ensemble β-cluster approach, which allows one-to-one pocket mapping and comparison among aligned protein structures. We demonstrated the utility of β-cluster representation by applying the approach to a wide variety of problems including binding site detection and comparison, characterization of protein-protein interactions, and fragment-based ligand optimization. These new β-cluster functionalities have been implemented in AlphaSpace 2.0, which is freely available on the web at http://www.nyu.edu/projects/yzhang/AlphaSpace2.

Multicomponent Peptide Stapling as a Diversity-Driven Tool for the Development of Inhibitors of Protein-Protein Interactions

Stapled peptides are chemical entities in-between biologics and small molecules, which have proven to be the solution to high affinity protein-protein interaction antagonism, while keeping control over pharmacological performance such as stability and membrane penetration. We demonstrate that the multicomponent reaction-based stapling is an effective strategy for the development of α-helical peptides with highly potent dual antagonistic action of MDM2 and MDMX binding p53. Such a potent inhibitory activity of p53-MDM2/X interactions was assessed by fluorescence polarization, microscale thermophoresis, and 2D NMR, while several cocrystal structures with MDM2 were obtained. This MCR stapling protocol proved efficient and versatile in terms of diversity generation at the staple, as evidenced by the incorporation of both exo- and endo-cyclic hydrophobic moieties at the side chain cross-linkers. The interaction of the Ugi-staple fragments with the target protein was demonstrated by crystallography.

Revealing binding selectivity of ligands toward murine double minute 2 and murine double minute X based on molecular dynamics simulations and binding free energy calculations

It is well known that the interactions of p53 with murine double minute 2 and murine double minute X, namely MDM2 and MDMX, have been significant targets of efficient anti-cancer drug design. In this study, molecular dynamics (MD) simulations, principal component (PC) analysis and binding free energy calculations are combined to recognize binding selectivity of three ligands to MDM2 and MDMX. The binding free energies were estimated by using molecular mechanics generalized Born surface area (MM-GBSA) method and the obtained results display that the increase in the binding enthalpy of three ligands to MDM2 relative to MDMX mainly drives the binding selectivity of them toward MDM2 and MDMX. The information obtained from PC analysis shows that the associations of ligands exert important impacts on internal dynamics of MDM2 and MDMX. Meanwhile, the calculations of residue-based free energy decomposition not only identify the hot interaction spots of ligands with MDM2 and MDMX, but also show the residues (L54, M53), (Y67, Y66), (V93, V92), (H96, P95), (I99, I98) and (Y100, Y99) in (MDM2, MDMX) are responsible for most contributions to the binding selectivity of three ligands toward MDM2 and MDMX. It is believed that this work can provide useful information for design of highly selective and dual inhibitors targeting MDM2 and MDMX.Communicated by Ramaswamy H. Sarma.

Proteasome-associated deubiquitinases and cancer

Maintenance of protein homeostasis is a crucial process for the normal functioning of the cell. The regulated degradation of proteins is primarily facilitated by the ubiquitin proteasome system (UPS), a system of selective tagging of proteins with ubiquitin followed by proteasome-mediated proteolysis. The UPS is highly dynamic consisting of both ubiquitination and deubiquitination steps that modulate protein stabilization and degradation. Deregulation of protein stability is a common feature in the development and progression of numerous cancer types. Simultaneously, the elevated protein synthesis rate of cancer cells and consequential accumulation of misfolded proteins drives UPS addiction, thus sensitizing them to UPS inhibitors. This sensitivity along with the potential of stabilizing pro-apoptotic signaling pathways makes the proteasome an attractive clinical target for the development of novel therapies. Targeting of the catalytic 20S subunit of the proteasome is already a clinically validated strategy in multiple myeloma and other cancers. Spurred on by this success, promising novel inhibitors of the UPS have entered development, targeting the 20S as well as regulatory 19S subunit and inhibitors of deubiquitinating and ubiquitin ligase enzymes. In this review, we outline the manner in which deregulation of the UPS can cause cancer to develop, current clinical application of proteasome inhibitors, and the (pre-)clinical development of novel inhibitors of the UPS.

The NMR2 Method to Determine Rapidly the Structure of the Binding Pocket of a Protein–Ligand Complex with High Accuracy

Structural characterization of complexes is crucial for a better understanding of biological processes and structure-based drug design. However, many protein–ligand structures are not solvable by X-ray crystallography, for example those with low affinity binders or dynamic binding sites. Such complexes are usually targeted by solution-state NMR spectroscopy. Unfortunately, structure calculation by NMR is very time consuming since all atoms in the complex need to be assigned to their respective chemical shifts. To circumvent this problem, we recently developed the Nuclear Magnetic Resonance Molecular Replacement (NMR2) method. NMR2 very quickly provides the complex structure of a binding pocket as measured by solution-state NMR. NMR2 circumvents the assignment of the protein by using previously determined structures and therefore speeds up the whole process from a couple of months to a couple of days. Here, we recall the main aspects of the method, show how to apply it, discuss its advantages over other methods and outline its limitations and future directions.

Fast NMR-Based Determination of the 3D Structure of the Binding Site of Protein-Ligand Complexes with Weak Affinity Binders

In early drug discovery approaches, screening hits are often weak affinity binders that are difficult to characterize in structural detail, particularly towards obtaining the 3D structure of protein-ligand complexes at atomic resolution. NMR is the outstanding technique to tackle such problems, yet suffers from a tedious structure calculation process. NMR² was recently developed to alleviate the laborious element of routine NMR structure calculation procedures and provides the structural information at protein-ligand interaction sites orders of magnitude faster than standard procedures. The NMR² method was extended to weak binders and applied to the oncoproteins HDM2 and MDMX. The structure of the MDMX-SJ212 complex is reported with a K_d of approximately 0.7 μm; the complex structure of HDM2 with the mm affinity ligand #845 exhibits a new scaffold.

Performance of a docking/molecular dynamics protocol for virtual screening of nutlin-class inhibitors of Mdmx

A virtual screening protocol involving docking and molecular dynamics has been tested against the results of fluorescence polarization assays testing the potency of a series of compounds of the nutlin class for inhibition of the interaction between p53 and Mdmx, an interaction identified as a driver of certain cancers. The protocol uses a standard docking method (AutoDock) with a cutoff based on the AutoDock score (ADscore), followed by molecular dynamics simulation with a cutoff based on root-mean-square-deviation (RMSD) from the docked pose. An analysis of the experimental and computational results shows modest performance of ADscore alone, but dramatically improved performance when RMSD is also used.

A Unique Mdm2-Binding Mode of the 3-Pyrrolin-2-one- and 2-Furanone-Based Antagonists of the p53-Mdm2 Interaction

The p53 pathway is inactivated in almost all types of cancer by mutations in the p53 encoding gene or overexpression of the p53 negative regulators, Mdm2 and/or Mdmx. Restoration of the p53 function by inhibition of the p53-Mdm2/Mdmx interaction opens up a prospect for a nongenotoxic anticancer therapy. Here, we present the syntheses, activities, and crystal structures of two novel classes of Mdm2-p53 inhibitors that are based on the 3-pyrrolin-2-one and 2-furanone scaffolds. The structures of the complexes formed by these inhibitors and Mdm2 reveal the dimeric protein molecular organization that has not been observed in the small-molecule/Mdm2 complexes described until now. In particular, the 6-chloroindole group does not occupy the usual Trp-23 pocket of Mdm2 but instead is engaged in dimerization. This entirely unique binding mode of the compounds opens new possibilities for optimization of the Mdm2-p53 interaction inhibitors.

p53 Proteoforms and Intrinsic Disorder: An Illustration of the Protein Structure-Function Continuum Concept

Although it is one of the most studied proteins, p53 continues to be an enigma. This protein has numerous biological functions, possesses intrinsically disordered regions crucial for its functionality, can form both homo-tetramers and isoform-based hetero-tetramers, and is able to interact with many binding partners. It contains numerous posttranslational modifications, has several isoforms generated by alternative splicing, alternative promoter usage or alternative initiation of translation, and is commonly mutated in different cancers. Therefore, p53 serves as an important illustration of the protein structure–function continuum concept, where the generation of multiple proteoforms by various mechanisms defines the ability of this protein to have a multitude of structurally and functionally different states. Considering p53 in the light of a proteoform-based structure–function continuum represents a non-canonical and conceptually new contemplation of structure, regulation, and functionality of this important protein.