Rational design of protein–protein interaction inhibitors

C-Terminal Decarboxylation of Proline-Derived Building Blocks for Protein-Binding Peptides

Using a set of conformationally restricted Proline-derived Modules (ProMs), our group has recently succeeded in developing inhibitors for the enabled/vasodilator-stimulated phosphoprotein homology 1 (EVH1) domain, which is a key mediator of cell migration and plays an important role in tumor metastasis. While these (formally) pentapeptidic compounds show nanomolecular binding affinities towards EVH1, their drug-like properties and cell permeability need to be further optimized before they can be clinically tested as therapeutic agents against metastasis. In this study, we sought to improve these properties by removing the C-terminal carboxylic acid function of our peptoids, either by late-stage decarboxylation or by direct synthesis. For late-stage decarboxylation of ProM-like systems, a method for reductive halo decarboxylation was optimized and applied to several proline-derived substrates. In this way, a series of new decarboxy ProMs suitable as building blocks for decarboxy EVH1 inhibitors were obtained. In addition, we incorporated decarboxy-ProM-1 into the pentapeptide-like compound Ac[2ClF][ProM-2][Decarb-ProM-1], which showed similar affinity towards EVH1 as the methyl ester derivative (Ac[2Cl-F][ProM-2][ProM1]OMe). However, despite better calculated drug-like properties, this compound did not inhibit chemotaxis in a cellular assay.

Molecular Dynamics as a Tool for Virtual Ligand Screening

Rational drug design is essential for new drugs to emerge, especially when the structure of a target protein or nucleic acid is known. To that purpose, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to modulate particular biomolecular interactions or biological activities, related to a disease process. The structure-based virtual ligand screening process primarily relies on docking methods which allow predicting the binding of a molecule to a biological target structure with a correct conformation and the best possible affinity. The docking method itself is not sufficient as it suffers from several and crucial limitations (lack of full protein flexibility information, no solvation and ion effects, poor scoring functions, and unreliable molecular affinity estimation).At the interface of computer techniques and drug discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein-drug complexes in the presence of water, ions, and even in membrane-like environments, describing more precisely the temporal evolution of the biological complex and ranking these complexes with more accurate binding energy calculations. In this chapter, we describe the up-to-date MD, which plays the role of supporting tools in the virtual ligand screening (VS) process.Without a doubt, using docking in combination with MD is an attractive approach in structure-based drug discovery protocols nowadays. It has proved its efficiency through many examples in the literature and is a powerful method to significantly reduce the amount of required wet experimentations (Tarcsay et al, J Chem Inf Model 53:2990-2999, 2013; Barakat et al, PLoS One 7:e51329, 2012; De Vivo et al, J Med Chem 59:4035-4061, 2016; Durrant, McCammon, BMC Biol 9:71-79, 2011; Galeazzi, Curr Comput Aided Drug Des 5:225-240, 2009; Hospital et al, Adv Appl Bioinforma Chem 8:37-47, 2015; Jiang et al, Molecules 20:12769-12786, 2015; Kundu et al, J Mol Graph Model 61:160-174, 2015; Mirza et al, J Mol Graph Model 66:99-107, 2016; Moroy et al, Future Med Chem 7:2317-2331, 2015; Naresh et al, J Mol Graph Model 61:272-280, 2015; Nichols et al, J Chem Inf Model 51:1439-1446, 2011; Nichols et al, Methods Mol Biol 819:93-103, 2012; Okimoto et al, PLoS Comput Biol 5:e1000528, 2009; Rodriguez-Bussey et al, Biopolymers 105:35-42, 2016; Sliwoski et al, Pharmacol Rev 66:334-395, 2014).

Site-directed modification of multifunctional lignocellulose-degrading enzymes of straw based on homologous modeling

Studying the straw lignocellulose strengthening mechanism during simultaneous degradation has important practical significance for improving resource utilization and reducing environmental pollution. In this paper, the degradation ability of four straw lignocellulose-degrading enzymes was evaluated by molecular docking and molecular dynamics. Using the significantly binds to straw lignocellulose-degrading enzyme as a template, a multifunctional lignocellulose-degrading enzyme 3CBH-1KS5-4XQD-1B85 was constructed based on amino acid recombination and homologous modeling. Five efficient degrading enzymes (3CBH-1, 3CBH-2, 3CBH-3, 3CBH-4, and 3CBH-5) were designed by site-directed mutagenesis of 3CBH-1KS5-4XQD-1B85 amino acid at position 346. Molecular dynamics showed that the degradation ability of 3CBH-1 was significant and it was 1.45 times higher than 3CBH-1KS5-4XQD-1B85. Moreover, the mechanism of enhanced degradability and the stability of the enzymes were explored. With the aid of Taguchi experiments, the suitable external environment for degrading straw was determined. In the presence of inhibitors (organic acids and phenolic compounds), the binding energy of 3CBH-1 (238.46 ± 30.96 kJ/mol) is 36.42% higher than that of 3CBH-1KS5-4XQD-1B85 (174.79 ± 20.35 kJ/mol) without external environmental stimulation. Based on homology modeling, this paper constructed a site-directed mutagenesis scheme of multifunctional enzymes, and the aim was to obtain multifunctional and efficient straw lignocellulose-degrading enzymes through protein engineering, which provided a feasible scheme for straw biodegradation.

Selected Approaches to Disrupting Protein-Protein Interactions within the MAPK/RAS Pathway

Within the MAPK/RAS pathway, there exists a plethora of protein-protein interactions (PPIs). For many years, scientists have focused efforts on drugging KRAS and its effectors in hopes to provide much needed therapies for patients with KRAS-mutant driven cancers. In this review, we focus on recent strategies to inhibit RAS-signaling via disrupting PPIs associated with SOS1, RAF, PDEδ, Grb2, and RAS.

Passive Membrane Permeability of Sizable Acyclic β-Hairpin Peptides

The recent shift toward increasingly larger drug modalities has created a significant demand for novel classes of compounds with high membrane permeability that can inhibit intracellular protein-protein interactions (PPIs). While major advances have been made in the design of cell-permeable helices, stapled β-sheets, and cyclic peptides, the development of large acyclic β-hairpins lags far behind. Therefore, we investigated a series of 26 β-hairpins (MW > 1.6 kDa) belonging to a chemical space far beyond the Lipinski "rule of five" (fbRo5) and showed that, in addition to their innate plasticity, the lipophilicity of these peptides (log D 7.4 ≈ 0 ± 0.7) can be tuned to drastically improve the balance between aqueous solubility and passive membrane permeability.

Targeting KRAS in PDAC: A New Way to Cure It?

Pancreatic cancer is one of the most intractable malignant tumors worldwide, and is known for its refractory nature and poor prognosis. The fatality rate of pancreatic cancer can reach over 90%. In pancreatic ductal carcinoma (PDAC), the most common subtype of pancreatic cancer, KRAS is the most predominant mutated gene (more than 80%). In recent decades, KRAS proteins have maintained the reputation of being “undruggable” due to their special molecular structures and biological characteristics, making therapy targeting downstream genes challenging. Fortunately, the heavy rampart formed by KRAS has been broken down in recent years by the advent of KRASG12C inhibitors; the covalent inhibitors bond to the switch-II pocket of the KRASG12C protein. The KRASG12C inhibitor sotorasib has been received by the FDA for the treatment of patients suffering from KRASG12C-driven cancers. Meanwhile, researchers have paid close attention to the development of inhibitors for other KRAS mutations. Due to the high incidence of PDAC, developing KRASG12D/V inhibitors has become the focus of attention. Here, we review the clinical status of PDAC and recent research progress in targeting KRASG12D/V and discuss the potential applications.

A Computational Study on the Interaction of NSP10 and NSP14: Unraveling the RNA Synthesis Proofreading Mechanism in SARS-CoV-2, SARS-CoV, and MERS-CoV

The interaction of exoribonuclease (ExoN) nonstructural protein (NSP14) with NSP10 co-factors is crucial for high-fidelity proofreading activity of coronavirus replication and transcription. Proofreading function is critical for maintaining the large genomes to ensure replication proficiency; therefore, while maintaining the viral replication fitness, quick resistance has been reported to the nucleotide analogue (NA) drugs. Therefore, targeting the NSP14 and NSP10 interacting interface with small molecules or peptides could be a better strategy to obstruct replication processes of coronaviruses (CoVs). A comparative study on the binding mechanism of NSP10 with the NSP14 ExoN domain of SARS-CoV-2, SARS-CoV, MERS-CoV, and four SARS-CoV-2 NSP14mutant complexes has been carried out. Protein-protein interaction (PPI) dynamics, per-residue binding free energy (BFE) analyses, and the identification of interface hotspot residues have been studied using molecular dynamics simulations and various computational tools. The BFE of the SARS-CoV NSP14-NSP10 complex was higher when compared to novel SARS-CoV-2 and MERS. However, SARS-CoV-2 NSP14mutant systems display a higher BFE as compared to the wild type (WT) but lower than SARS-CoV and MERS. Despite the high BFE, the SARS-CoV NSP14-NSP10 complex appears to be structurally more flexible in many regions especially the catalytic site, which is not seen in SARS-CoV-2 and its mutant or MERS complexes. The significantly high residue energy contribution of key interface residues and hotspots reveals that the high binding energy between NSP14 and NSP10 may enhance the functional activity of the proofreading complex, as the NSP10-NSP14 interaction is essential in maintaining the stability of the ExoN domain for the replicative fitness of CoVs. The factors discussed for SARS-CoV-2 complexes may be responsible for NSP14 ExoN having a high replication proficiency, significantly leading to the evolution of new variants of SARS-CoV-2. The NSP14 residues V66, T69, D126, and I201and eight residues of NSP10 (L16, F19, V21, V42, M44, H80, K93, and F96) are identified as common hotspots. Overall, the interface area, hotspot locations, bonded/nonbonded contacts, and energies between NSP14 and NSP10 may pave a way in designing potential inhibitors to disrupt NSP14-NSP10 interactions of CoVs especially SARS-CoV-2.

Adaptor-Specific Antibody Fragment Inhibitors for the Intracellular Modulation of p97 (VCP) Protein-Protein Interactions

Protein-protein interactions (PPIs) form complex networks to drive cellular signaling and cellular functions. Precise modulation of a target PPI helps explain the role of the PPI in cellular events and possesses therapeutic potential. For example, valosin-containing protein (VCP/p97) is a hub protein that interacts with more than 30 adaptor proteins involved in various cellular functions. However, the role of each p97 PPI during the relevant cellular event is underexplored. The development of small-molecule PPI modulators remains challenging due to a lack of grooves and pockets in the relatively large PPI interface and the fact that a common binding groove in p97 binds to multiple adaptors. Here, we report an antibody fragment-based modulator for the PPI between p97 and its adaptor protein NSFL1C (p47). We engineered these antibody modulators by phage display against the p97-interacting domain of p47 and minimizing binding to other p97 adaptors. The selected antibody fragment modulators specifically disrupt the intracellular p97/p47 interaction. The potential of this antibody platform to develop PPI inhibitors in therapeutic applications was demonstrated through the inhibition of Golgi reassembly, which requires the p97/p47 interaction. This study presents a unique approach to modulate specific intracellular PPIs using engineered antibody fragments, demonstrating a method to dissect the function of a PPI within a convoluted PPI network.

Protein-protein interaction of RdRp with its co-factor NSP8 and NSP7 to decipher the interface hotspot residues for drug targeting: A comparison between SARS-CoV-2 and SARS-CoV

In this study we explored the molecular mechanism of RdRp (Non-Structural Protein, NSP12) interaction with its co-factors NSP7 and NSP8 which is the main toolbox for RNA replication and transcription of SARS-CoV-2 and SARS-CoV. The replication complex is a heterotetramer consists of one NSP12, one NSP7 and two NSP8. Extensive molecular dynamics (MD) simulations were applied on both the heterotetramer complexes to generate the conformations and were used to estimate the MMPBSA binding free energy (BFE) and per-residue energy decomposition of NSP12-NSP8 and NSP12-NSP7 and NSP7-NSP8 complexes. The BFE of SARS-CoV-2 heterotetramer complex with its corresponding partner protein was significantly higher as compared to SARS-CoV. Interface hotspot residues were predicted using different methods implemented in KFC (Knowledge-based FADA and Contracts), HotRegion and Robetta web servers. Per-residue energy decomposition analysis showed that the predicted interface hotspot residues contribute more energy towards the formation of complexes and most of the predicted hotspot residues are clustered together. However, there is a slight difference in the residue-wise energy contribution in the interface NSPs on heterotetramer viral replication complex of both coronaviruses. While the overall replication complex of SARS-CoV-2 was found to be slightly flexible as compared to SARS-CoV. This difference in terms of structural flexibility/stability and energetic characteristics of interface residues including hotspots at PPI interface in the viral replication complexes may be the reason of higher rate of RNA replication of SARS-CoV-2 as compared to SARS-CoV. Overall, the interaction profile at PPI interface such as, interface area, hotspot residues, nature of bonds and energies between NSPs, may provide valuable insights in designing of small molecules or peptide/peptidomimetic ligands which can fit into the PPI interface to disrupt the interaction.

Identification of potential interleukin-8 inhibitors acting on the interactive site between chemokine and CXCR2 receptor: A computational approach

Interactions between interleukin (IL)-8 and its receptors, CXCR1, and CXCR2, serve crucial roles in inflammatory conditions and various types of cancers. Inhibition of this signaling pathway has been exploited as a promising strategy in treating these diseases. However, most studies only focused on the design of allosteric antagonists-bound receptors on the intracellular side of IL-8 receptors. Recently, the first cryo-EM structures of IL-8-CXCR2-Gi complexes have been solved, revealing the unique binding and activation modes of the endogenous chemokine IL-8. Hence, we set to identify small molecule inhibitors for IL-8 using critical protein-protein interaction between IL-8 and CXCR2 at the orthosteric binding site. The pharmacophore models and molecular docking screened compounds from DrugBank and NCI databases. The oral bioavailability of the top 23 ligands from the screening was then predicted by the SwissAMDE tool. Molecular dynamics simulation and free binding energy calculation were performed for the best compounds. The result indicated that DB14770, DB12121, and DB03916 could form strong interactions and stable protein-ligand complexes with IL-8. These three candidates are potential IL-8 inhibitors that can be further evaluated by in vitro experiments in the next stage.

Peptides and peptidomimetics as therapeutic agents for Covid-19

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Covid-19 pandemic has caused high morbidity and mortality rates worldwide. Virus entry into cells can be blocked using several strategies, including inhibition of protein-protein interactions (PPIs) between the viral spike glycoprotein and cellular receptors, as well as blocking of spike protein conformational changes that are required for cleavage/activation and fusogenicity. The spike-mediated viral attachment and entry into cells via fusion of the viral envelope with cellular membranes involve PPIs mediated by short peptide fragments exhibiting particular secondary structures. Thus, peptides that can inhibit these PPIs may be used as potential antiviral agents preventing virus entry and spread. This review is focused on peptides and peptidomimetics as PPI modulators and protease inhibitors against SARS-CoV-2.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Interaction between a Novel Oligopeptide Fragment of the Human Neurotrophin Receptor TrkB Ectodomain D5 and the C-Terminal Fragment of Tetanus Neurotoxin

This article presents experimental evidence and computed molecular models of a potential interaction between receptor domain D5 of TrkB with the carboxyl-terminal domain of tetanus neurotoxin (Hc-TeNT). Computational simulations of a novel small cyclic oligopeptide are designed, synthesized, and tested for possible tetanus neurotoxin-D5 interaction. A hot spot of this protein-protein interaction is identified in analogy to the hitherto known crystal structures of the complex between neurotrophin and D5. Hc-TeNT activates the neurotrophin receptors, as well as its downstream signaling pathways, inducing neuroprotection in different stress cellular models. Based on these premises, we propose the Trk receptor family as potential proteic affinity receptors for TeNT. In vitro, Hc-TeNT binds to a synthetic TrkB-derived peptide and acts similar to an agonist ligand for TrkB, resulting in phosphorylation of the receptor. These properties are weakened by the mutagenesis of three residues of the predicted interaction region in Hc-TeNT. It also competes with Brain-derived neurotrophic factor, a native binder to human TrkB, for the binding to neural membranes, and for uptake in TrkB-positive vesicles. In addition, both molecules are located together in vivo at neuromuscular junctions and in motor neurons.

Synthesis and Evaluation of Arylamides with Hydrophobic Side Chains for Insulin Aggregation Inhibition

Insulin, a peptide hormone, forms fibrils under aberrant physiological conditions leading to a reduction in its biological activity. To ameliorate insulin aggregation, we have synthesized a small library of oligopyridylamide foldamers decorated with different combination of hydrophobic side chains. Screening of these compounds for insulin aggregation inhibition using a Thioflavin-T assay resulted in the identification of a few hit molecules. The best hit molecule, BPAD2 inhibited insulin aggregation with an IC₅₀ value of 0.9 μM. Mechanistic analyses suggested that BPAD2 inhibited secondary nucleation and elongation processes during aggregation. The hit molecules worked in a mechanistically distinct manner, thereby underlining the importance of structure-activity relationship studies in obtaining a molecular understanding of protein aggregation.

Scanning Protein Surfaces with DNA-Encoded Libraries

Understanding the ligandability of a target protein, defined as the capability of a protein to bind drug-like compounds on any site, can give important stimuli to drug-development projects. For instance, inhibition of protein-protein interactions usually depends on the identification of protein surface binders. DNA-encoded chemical libraries (DELs) allow scanning of protein surfaces with large chemical space. Encoded library selection screens uncovered several protein-protein interaction inhibitors and compounds binding to the surface of G protein-coupled receptors (GPCRs) and kinases. The protein surface-binding chemotypes from DELs are predominantly chemically modified and cyclized peptides, and functional small-molecule peptidomimetics. Peptoid libraries and structural peptidomimetics have been less studied in the DEL field, hinting at hitherto less populated chemical space and suggesting alternative library designs. Roughly a third of bioactive molecules evolved from smaller, target-focused libraries. They showcase the potential of encoded libraries to identify more potent molecules from weak, for example, fragment-like, starting points.

Overcoming challenges in developing small molecule inhibitors for GPVI and CLEC-2

GPVI and CLEC-2 have emerged as promising targets for long-term prevention of both arterial thrombosis and thrombo-inflammation with a decreased bleeding risk relative to current drugs. However, while there are potent blocking antibodies of both receptors, their protein nature comes with decreased bioavailability, making formulation for oral medication challenging. Small molecules are able to overcome these limitations, but there are many challenges in developing antagonists of nanomolar potency, which is necessary when considering the structural features that underlie the interaction of CLEC-2 and GPVI with their protein ligands. In this review, we describe current small-molecule inhibitors for both receptors and strategies to overcome such limitations, including considerations when it comes to in silico drug design and the importance of complex compound library selection.

Molecular drug targets for scabies: a medicinal chemistry perspective

Sarcoptes scabiei is a causative organism for scabies that affects an estimated global population of 300 million and remains a disease of significant concern. Recently, a number of potential drug targets were identified for scabies, including hydrolytic enzymes, inactivated paralogues of hydrolytic enzymes, inhibitors of host proteolytic enzymes and other proteins of interest. These discoveries remain confined to academic laboratories and institutions, failing to attract interest from researchers in commercial drug development. Here, we summarize the latest developments in the scabies mite biology and the drug targets that were subsequently identified, and we propose several peptide and nonpeptide ligands targeting the hot spots for protein-protein interactions. We also identify gaps in the development of ligands as inhibitors or modulators of these macromolecules.

Identification of a New Heterocyclic Scaffold for Inhibitors of the Polo-Box Domain of Polo-like Kinase 1

As a mitotic-specific target widely deregulated in various human cancers, polo-like kinase 1 (Plk1) has been extensively explored for anticancer activity and drug discovery. Although multiple catalytic domain inhibitors were tested in preclinical and clinical studies, their efficacies are limited by dose-limiting cytotoxicity, mainly from off-target cross reactivity. The C-terminal noncatalytic polo-box domain (PBD) of Plk1 has emerged as an attractive target for generating new protein-protein interaction inhibitors. Here, we identified a 1-thioxo-2,4-dihydro-[1,2,4]triazolo[4,3-a]quinazolin-5(1H)-one scaffold that efficiently inhibits Plk1 PBD but not its related Plk2 and Plk3 PBDs. Structure-activity relationship studies led to multiple inhibitors having ≥10-fold higher inhibitory activity than the previously characterized Plk1 PBD-specific phosphopeptide, PLHSpT (Kd ∼ 450 nM). In addition, S-methyl prodrugs effectively inhibited mitotic progression and cell proliferation and their metabolic stability was determined. These data describe a novel class of small-molecule inhibitors that offer a promising avenue for future drug discovery against Plk1-addicted cancers.

Discovery of novel immunopharmacological ligands targeting the IL-17 inflammatory pathway

Interleukin 17 (IL-17) is a proinflammatory cytokine that acts as an immune checkpoint for several autoimmune diseases. Therapeutic neutralizing antibodies that target this cytokine have demonstrated clinical efficacy in psoriasis. However, biologics have limitations such as their high cost and their lack of oral bioavailability. Thus, it is necessary to expand the therapeutic options for this IL-17A/IL-17RA pathway, applying novel drug discovery methods to find effective small molecules. In this work, we combined biophysical and cell-based assays with structure-based docking to find novel ligands that target this pathway. First, a virtual screening of our chemical library of 60000 compounds was used to identify 67 potential ligands of IL-17A and IL-17RA. We developed a biophysical label-free binding assay to determine interactions with the extracellular domain of IL-17RA. Two molecules (CBG040591 and CBG060392) with quinazolinone and pyrrolidinedione chemical scaffolds, respectively, were confirmed as ligands of IL-17RA with micromolar affinity. The anti-inflammatory activity of these ligands as cytokine-release inhibitors was evaluated in human keratinocytes. Both ligands inhibited the release of chemokines mediated by IL-17A, with an IC₅₀ of 20.9 ± 12.6 μM and 23.6 ± 11.8 μM for CCL20 and an IC₅₀ of 26.7 ± 13.1 μM and 45.3 ± 13.0 μM for CXCL8. Hence, they blocked IL-17A proinflammatory activity, which is consistent with the inhibition of the signalling of the IL-17A receptor by ligand CBG060392. Therefore, we identified two novel immunopharmacological ligands targeting the IL-17A/IL-17RA pathway with antiinflammatory efficacy that can be promising tools for a drug discovery program for psoriasis.

Structure-based virtual screening, biological evaluation and biophysical study of novel Mcl-1 inhibitors

Aim: Targeting the protein-protein interactions (PPIs) associated with Mcl-1 has become a promising therapeutic approach for cancer. Herein, we reported the discovery of novel Mcl-1 inhibitors using an integrated computational approach. Results: Among 30 virtual screening hits, five compounds show inhibitory activities against Mcl-1. The most potent inhibitors M02 (K _i  = 5.4 μM) and M08 (K_i = 0.53 μM) exhibit good selectivity against Bcl-2 and Bcl-xL. Compound M08 exhibits anti-proliferation activity and induces caspase-3 activation in Jurkat cancer cells. Moreover, ¹H⁄¹⁵N HSQC NMR experiments suggested that compound M08 likely binds in the P2 pocket of Mcl-1 and engages R263 in a salt bridge. Conclusion: Our study provides a good starting point for future discovery of more potent Mcl-1 selective inhibitors.

Rational modulator design by exploitation of protein-protein complex structures

The horizon of drug discovery is currently expanding to target and modulate protein-protein interactions (PPIs) in globular proteins and intrinsically disordered proteins that are involved in various diseases. To either interrupt or stabilize PPIs, the 3D structure of target protein-protein (or protein-peptide) complexes can be exploited to rationally design PPI modulators (inhibitors or stabilizers) through structure-based molecular design. In this review, we present an overview of experimental and computational methods that can be used to determine 3D structures of protein-protein complexes. Several approaches including rational and in silico methods that can be applied to design peptides, peptidomimetics and small compounds by utilization of determined 3D protein-protein/peptide complexes are summarized and illustrated.

Synthesis and biological evaluation of a library of hybrid derivatives as inhibitors of influenza virus PA-PB1 interaction

The limited treatment options against influenza virus along with the growing public health concerns regarding the continuous emergence of drug-resistant viruses make essential the development of new anti-flu agents with novel mechanisms of action. One of the most attractive targets is the interaction between two subunits of the RNA-dependent RNA polymerase, PA and PB1. Herein we report the rational design of hybrid compounds starting from a 3-cyano-4,6-diphenylpyridine scaffold recently identified as disruptor of PA-PB1 interactions. Guided by the previously reported SAR data, a library of amino acid derivatives was synthesized. The biological evaluation led to the identification of new PA-PB1 inhibitors, that do not show appreciable toxicity. Molecular modeling shed further lights on the inhibition mechanism of these compounds.

Small molecule inhibitors of RAS-effector protein interactions derived using an intracellular antibody fragment

Targeting specific protein–protein interactions (PPIs) is an attractive concept for drug development, but hard to implement since intracellular antibodies do not penetrate cells and most small-molecule drugs are considered unsuitable for PPI inhibition. A potential solution to these problems is to select intracellular antibody fragments to block PPIs, use these antibody fragments for target validation in disease models and finally derive small molecules overlapping the antibody-binding site. Here, we explore this strategy using an anti-mutant RAS antibody fragment as a competitor in a small-molecule library screen for identifying RAS-binding compounds. The initial hits are optimized by structure-based design, resulting in potent RAS-binding compounds that interact with RAS inside the cells, prevent RAS-effector interactions and inhibit endogenous RAS-dependent signalling. Our results may aid RAS-dependent cancer drug development and demonstrate a general concept for developing small compounds to replace intracellular antibody fragments, enabling rational drug development to target validated PPIs.

Intracellular antibodies can inhibit disease-relevant protein interactions, but inefficient cellular uptake limits their utility. Using a RAS-targeting intracellular antibody as a screening tool, the authors here identify small molecules that inhibit RAS-effector interactions and readily penetrate cells.

Modeling and simulating networks of interdependent protein interactions

Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of these systems emerge not only from the protein interactions themselves but also from the dependencies between these interactions, as generated by allosteric effects or mutual exclusion due to steric hindrance. Therefore, formal models for integrating and utilizing information about interaction dependencies are of high interest. Here, we describe an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining constrained protein interaction networks ("constrained networks"). The construction of these networks is based on public interaction databases as well as text-mined information about interaction dependencies. We present an efficient data structure and algorithm to simulate protein complex formation in constrained networks. The efficiency of the model allows fast simulation and facilitates the analysis of many proteins in large networks. In addition, this approach enables the simulation of perturbation effects, such as knockout of single or multiple proteins and changes of protein concentrations. We illustrate how our model can be used to analyze a constrained human adhesome protein network, which is responsible for the formation of diverse and dynamic cell-matrix adhesion sites. By comparing protein complex formation under known interaction dependencies versus without dependencies, we investigate how these dependencies shape the resulting repertoire of protein complexes. Furthermore, our model enables investigating how the interplay of network topology with interaction dependencies influences the propagation of perturbation effects across a large biochemical system. Our simulation software CPINSim (for Constrained Protein Interaction Network Simulator) is available under the MIT license at http://github.com/BiancaStoecker/cpinsim and as a Bioconda package (https://bioconda.github.io).

Molecular Dynamics as a Tool for Virtual Ligand Screening

Rational drug design is essential for new drugs to emerge, especially when the structure of a target protein or catalytic enzyme is known experimentally. To that purpose, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to inhibit a particular protein interaction or biological activity. The virtual ligand screening process often relies on docking methods which allow predicting the binding of a molecule into a biological target structure with a correct conformation and the best possible affinity. The docking method itself is not sufficient as it suffers from several and crucial limitations (lack of protein flexibility information, no solvation effects, poor scoring functions, and unreliable molecular affinity estimation).At the interface of computer techniques and drug discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein-drug complexes in the presence of water, ions and even in membrane-like environments, and ranking complexes with more accurate binding energy calculations. In this chapter we describe the up-to-date MD protocols that are mandatory supporting tools in the virtual ligand screening (VS) process. Using docking in combination with MD is one of the best computer-aided drug design protocols nowadays. It has proved its efficiency through many examples, described below.

In silico structure-based approaches to discover protein-protein interaction-targeting drugs

A core concept behind modern drug discovery is finding a small molecule that modulates a function of a target protein. This concept has been successfully applied since the mid-1970s. However, the efficiency of drug discovery is decreasing because the druggable target space in the human proteome is limited. Recently, protein-protein interaction (PPI) has been identified asan emerging target space for drug discovery. PPI plays a pivotal role in biological pathways including diseases. Current human interactome research suggests that the number of PPIs is between 130,000 and 650,000, and only a small number of them have been targeted as drug targets. For traditional drug targets, in silico structure-based methods have been successful in many cases. However, their performance suffers on PPI interfaces because PPI interfaces are different in five major aspects: From a geometric standpoint, they have relatively large interface regions, flat geometry, and the interface surface shape tends to fluctuate upon binding. Also, their interactions are dominated by hydrophobic atoms, which is different from traditional binding-pocket-targeted drugs. Finally, PPI targets usually lack natural molecules that bind to the target PPI interface. Here, we first summarize characteristics of PPI interfaces and their known binders. Then, we will review existing in silico structure-based approaches for discovering small molecules that bind to PPI interfaces.

Mimicking Intermolecular Interactions of Tight Protein-Protein Complexes for Small-Molecule Antagonists

Tight protein-protein interactions (K_d <100 nm) that occur over a large binding interface (>1000 Ų ) are highly challenging to disrupt with small molecules. Historically, the design of small molecules to inhibit protein-protein interactions has focused on mimicking the position of interface protein ligand side chains. Here, we explore mimicry of the pairwise intermolecular interactions of the native protein ligand with residues of the protein receptor to enrich commercial libraries for small-molecule inhibitors of tight protein-protein interactions. We use the high-affinity interaction (K_d =1 nm) between the urokinase receptor (uPAR) and its ligand urokinase (uPA) to test our methods. We introduce three methods for rank-ordering small molecules docked to uPAR: 1) a new fingerprint approach that represents uPA's pairwise interaction energies with uPAR residues; 2) a pharmacophore approach to identify small molecules that mimic the position of uPA interface residues; and 3) a combined fingerprint and pharmacophore approach. Our work led to small molecules with novel chemotypes that inhibited a tight uPAR⋅uPA protein-protein interaction with single-digit micromolar IC₅₀ values. We also report the extensive work that identified several of the hits as either lacking stability, thiol reactive, or redox active. This work suggests that mimicking the binding profile of the native ligand and the position of interface residues can be an effective strategy to enrich commercial libraries for small-molecule inhibitors of tight protein-protein interactions.

Peptide-Directed Binding for the Discovery of Modulators of α-Helix-Mediated Protein-Protein Interactions: Proof-of-Concept Studies with the Apoptosis Regulator Mcl-1

Targeting PPIs with small molecules can be challenging owing to large, hydrophobic binding surfaces. Herein, we describe a strategy that exploits selective α-helical PPIs, transferring these characteristics to small molecules. The proof of concept is demonstrated with the apoptosis regulator Mcl-1, commonly exploited by cancers to avoid cell death. Peptide-directed binding uses few synthetic transformations, requires the production of a small number of compounds, and generates a high percentage of hits. In this example, about 50 % of the small molecules prepared showed an IC50 value of less than 100 μm, and approximately 25 % had IC50 values below 1 μm to Mcl-1. Compounds show selectivity for Mcl-1 over other anti-apoptotic proteins, possess cytotoxicity to cancer cell lines, and induce hallmarks of apoptosis. This approach represents a novel and economic process for the rapid discovery of new α-helical PPI modulators.

Specificity and stability of transient protein-protein interactions

Remarkable features that are achieved in a protein-protein complex to precise levels are stability and specificity. Deviation from the normal levels of specificity and stability, which is often caused by mutations, could result in disease conditions. Chemical nature, 3-D arrangement and dynamics of interface residues code for both specificity and stability. This article reviews roles of interfacial residues in transient protein-protein complexes. It is proposed that aside from hotspot residues conferring stability to the complex, a small set of 'rigid' residues at the interface that maintain conformation between complexed and uncomplexed forms, play a major role in conferring specificity. Exceptionally, 'super hotspot' residues, which confer both stability and specificity, are attractive sites for interaction with small molecule inhibitors.

The Influenza Virus Polymerase Complex: An Update on Its Structure, Functions, and Significance for Antiviral Drug Design

Influenza viruses cause seasonal epidemics and pandemic outbreaks associated with significant morbidity and mortality, and a huge cost. Since resistance to the existing anti‐influenza drugs is rising, innovative inhibitors with a different mode of action are urgently needed. The influenza polymerase complex is widely recognized as a key drug target, given its critical role in virus replication and high degree of conservation among influenza A (of human or zoonotic origin) and B viruses. We here review the major progress that has been made in recent years in unravelling the structure and functions of this protein complex, enabling structure‐aided drug design toward the core regions of the PA endonuclease, PB1 polymerase, or cap‐binding PB2 subunit. Alternatively, inhibitors may target a protein–protein interaction site, a cellular factor involved in viral RNA synthesis, the viral RNA itself, or the nucleoprotein component of the viral ribonucleoprotein. The latest advances made for these diverse pharmacological targets have yielded agents in advanced (i.e., favipiravir and VX‐787) or early clinical testing, besides several experimental inhibitors in various stages of development, which are all covered here.

Recent progress in the development of protein-protein interaction inhibitors targeting androgen receptor-coactivator binding in prostate cancer

The androgen receptor (AR) is a key regulator for the growth, differentiation and survival of prostate cancer cells. Identified as a primary target for the treatment of prostate cancer, many therapeutic strategies have been developed to attenuate AR signaling in prostate cancer cells. While frontline androgen-deprivation therapies targeting either the production or action of androgens usually yield favorable responses in prostate cancer patients, a significant number acquire treatment resistance. Known as the castration-resistant prostate cancer (CRPC), the treatment options are limited for this advanced stage. It has been shown that AR signaling is restored in CRPC due to many aberrant mechanisms such as AR mutations, amplification or expression of constitutively active splice-variants. Coregulator recruitment is a crucial regulatory step in AR signaling and the direct blockade of coactivator binding to AR offers the opportunity to develop therapeutic agents that would remain effective in prostate cancer cells resistant to conventional endocrine therapies. Structural analyses of the AR have identified key surfaces involved in protein-protein interaction with coregulators that have been recently used to design and develop promising AR-coactivator binding inhibitors. In this review we will discuss the design and development of small-molecule inhibitors targeting the AR-coactivator interactions for the treatment of prostate cancer.

Polymerase Acidic Protein-Basic Protein 1 (PA-PB1) Protein-Protein Interaction as a Target for Next-Generation Anti-influenza Therapeutics

The limited therapeutic options against the influenza virus (flu) and increasing challenges in drug resistance make the search for next-generation agents imperative. In this context, heterotrimeric viral PA/PB1/PB2 RNA-dependent RNA polymerase is an attractive target for a challenging but strategic protein-protein interaction (PPI) inhibition approach. Since 2012, the inhibition of the polymerase PA-PB1 subunit interface has become an active field of research following the publication of PA-PB1 crystal structures. In this Perspective, we briefly discuss the validity of flu polymerase as a drug target and its inhibition through a PPI inhibition strategy, including a comprehensive analysis of available PA-PB1 structures. An overview of all of the reported PA-PB1 complex formation inhibitors is provided, and approaches used for identification of the inhibitors, the hit-to-lead studies, and the emerged structure-activity relationship are described. In addition to highlighting the strengths and weaknesses of all of the PA-PB1 heterodimerization inhibitors, we analyze their hypothesized binding modes and alignment with a pharmacophore model that we have developed.

Structure-Based Virtual Ligand Screening on the XRCC4/DNA Ligase IV Interface

The association of DNA Ligase IV (Lig4) with XRCC4 is essential for repair of DNA double-strand breaks (DSBs) by Non-homologous end-joining (NHEJ) in humans. DSBs cytotoxicity is largely exploited in anticancer therapy. Thus, NHEJ is an attractive target for strategies aimed at increasing the sensitivity of tumors to clastogenic anticancer treatments. However the high affinity of the XRCC4/Lig4 interaction and the extended protein-protein interface make drug screening on this target particularly challenging. Here, we conducted a pioneering study aimed at interfering with XRCC4/Lig4 assembly. By Molecular Dynamics simulation using the crystal structure of the complex, we first delineated the Lig4 clamp domain as a limited suitable target. Then, we performed in silico screening of ~95,000 filtered molecules on this Lig4 subdomain. Hits were evaluated by Differential Scanning Fluorimetry, Saturation Transfer Difference-NMR spectroscopy and interaction assays with purified recombinant proteins. In this way we identified the first molecule able to prevent Lig4 binding to XRCC4 in vitro. This compound has a unique tripartite interaction with the Lig4 clamp domain that suggests a starting chemotype for rational design of analogous molecules with improved affinity.

Structure-Based Design of Peptidic Inhibitors of the Interaction between CC Chemokine Ligand 5 (CCL5) and Human Neutrophil Peptides 1 (HNP1)

Protein-protein interactions (PPIs) are receiving increasing interest, much sparked by the realization that they represent druggable targets. Recently, we successfully developed a peptidic inhibitor, RRYGTSKYQ ("SKY" peptide), that shows high potential in vitro and in vivo to interrupt a PPI between the platelet-borne chemokine CCL5 and the neutrophil-derived granule protein HNP1. This PPI plays a vital role in monocyte adhesion, representing a key mechanism in acute and chronic inflammatory diseases. Here, we present extensive and detailed computational methods applied to develop the SKY peptide. We combined experimentally determined binding affinities (KD) of several orthologs of CCL5 with HNP1 with in silico studies to identify the most likely heterodimeric CCL5-HNP1 complex which was subsequently used as a starting structure to rationally design peptidic inhibitors. Our method represents a fast and simple approach that can be widely applied to determine other protein-protein complexes and moreover to design inhibitors or stabilizers of protein-protein interaction.

Design, Synthesis and Evaluation of 2,5-Diketopiperazines as Inhibitors of the MDM2-p53 Interaction

The transcription factor p53 is the main tumour suppressor in cells and many cancer types have p53 mutations resulting in a loss of its function. In tumours that retain wild-type p53 function, p53 activity is down-regulated by MDM2 (human murine double minute 2) via a direct protein-protein interaction. We have designed and synthesised two series of 2,5-diketopiperazines as inhibitors of the MDM2-p53 interaction. The first set was designed to directly mimic the α-helical region of the p53 peptide, containing key residues in the i, i+4 and i+7 positions of a natural α-helix. Conformational analysis indicated that 1,3,6-trisubstituted 2,5-diketopiperazines were able to place substituents in the same spatial orientation as an α-helix template. The key step of the synthesis involved the cyclisation of substituted dipeptides. The other set of tetrasubstituted 2,5-diketopiperazines were designed based on structure-based docking studies and the Ugi multicomponent reaction was used for the synthesis. This latter set comprised the most potent inhibitors which displayed micromolar IC50-values in a biochemical fluorescence polarisation assay.

Turning Peptide Ligands into Small-Molecule Inhibitors of Protein-Protein Interactions

Proline makeover: Truncation and extensive chemical modification of a peptide ligand yielded a biologically active, cell-permeable, peptidomimetic, small-molecule inhibitor of a protein-protein interaction. A key step in this transformation was the replacement of a tetraproline motif by two conformationally constrained diproline units that retain the molecule's PPII helix.

In silico design of low molecular weight protein-protein interaction inhibitors: Overall concept and recent advances

Protein-protein interactions (PPIs) are carrying out diverse functions in living systems and are playing a major role in the health and disease states. Low molecular weight (LMW) "drug-like" inhibitors of PPIs would be very valuable not only to enhance our understanding over physiological processes but also for drug discovery endeavors. However, PPIs were deemed intractable by LMW chemicals during many years. But today, with the new experimental and in silico technologies that have been developed, about 50 PPIs have already been inhibited by LMW molecules. Here, we first focus on general concepts about protein-protein interactions, present a consensual view about ligandable pockets at the protein interfaces and the possibilities of using fast and cost effective structure-based virtual screening methods to identify PPI hits. We then discuss the design of compound collections dedicated to PPIs. Recent financial analyses of the field suggest that LMW PPI modulators could be gaining momentum over biologics in the coming years supporting further research in this area.