Binding of small molecules at interface of protein-protein complex - A newer approach to rational drug design

Peptides as multifunctional players in cancer therapy

Peptides exhibit lower affinity and a shorter half-life in the body than antibodies. Conversely, peptides demonstrate higher efficiency in tissue penetration and cell internalization than antibodies. Regardless of the pros and cons of peptides, they have been used as tumor-homing ligands for delivering carriers (such as nanoparticles, extracellular vesicles, and cells) and cargoes (such as cytotoxic peptides and radioisotopes) to tumors. Additionally, tumor-homing peptides have been conjugated with cargoes such as small-molecule or chemotherapeutic drugs via linkers to synthesize peptide-drug conjugates. In addition, peptides selectively bind to cell surface receptors and proteins, such as immune checkpoints, receptor kinases, and hormone receptors, subsequently blocking their biological activity or serving as hormone analogs. Furthermore, peptides internalized into cells bind to intracellular proteins and interfere with protein-protein interactions. Thus, peptides demonstrate great application potential as multifunctional players in cancer therapy.

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.

Pathogen-driven cancers from a structural perspective: Targeting host-pathogen protein-protein interactions

Host-pathogen interactions (HPIs) affect and involve multiple mechanisms in both the pathogen and the host. Pathogen interactions disrupt homeostasis in host cells, with their toxins interfering with host mechanisms, resulting in infections, diseases, and disorders, extending from AIDS and COVID-19, to cancer. Studies of the three-dimensional (3D) structures of host-pathogen complexes aim to understand how pathogens interact with their hosts. They also aim to contribute to the development of rational therapeutics, as well as preventive measures. However, structural studies are fraught with challenges toward these aims. This review describes the state-of-the-art in protein-protein interactions (PPIs) between the host and pathogens from the structural standpoint. It discusses computational aspects of predicting these PPIs, including machine learning (ML) and artificial intelligence (AI)-driven, and overviews available computational methods and their challenges. It concludes with examples of how theoretical computational approaches can result in a therapeutic agent with a potential of being used in the clinics, as well as future directions.

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.

Traversing through the Dynamic Protein-Protein Interaction Landscape and Conformational Plasticity of PD-1 for Small-Molecule Discovery

Monoclonal antibodies (mAbs) blocking the PD-1/PD-L1 interface have shown remarkable success in treating malignancies, but they may also initiate lethal immune-related adverse events. Small molecules may circumvent the mAb limitations; however, none has entered clinical trials targeting PD-1. Its complex protein-protein interaction interfaces necessitate an atomic-level understanding of recognition and binding mechanisms. Hence, we have aimed to highlight the PD-1's sequence-structure-dynamic-function link with its cognate ligands and diversely reported inhibitors. We focus primarily on the anti-PD-1 mAbs, their mode of actions, and interactions with PD-1 epitopes. The comparison of co-crystals showed that these ligands/inhibitors harness the PD-1's conformational plasticity and structural determinants differentially. The relationship between modulator binding patterns and biological activity is demonstrated using interaction fingerprinting of all reported human PD-1 co-crystals. The significant dynamical events and hot-spot residues underpinned from crystallographic wealth and computational studies have been highlighted to expedite small-molecule discovery.

Challenges in Discovering Drugs That Target the Protein-Protein Interactions of Disordered Proteins

Protein–protein interactions (PPIs) outnumber proteins and are crucial to many fundamental processes; in consequence, PPIs are associated with several pathological conditions including neurodegeneration and modulating them by drugs constitutes a potentially major class of therapy. Classically, however, the discovery of small molecules for use as drugs entails targeting individual proteins rather than targeting PPIs. This is largely because discovering small molecules to modulate PPIs has been seen as extremely challenging. Here, we review the difficulties and limitations of strategies to discover drugs that target PPIs directly or indirectly, taking as examples the disordered proteins involved in neurodegenerative diseases.

Exploring the chemical space of protein-protein interaction inhibitors through machine learning

Although protein-protein interactions (PPIs) have emerged as the basis of potential new therapeutic approaches, targeting intracellular PPIs with small molecule inhibitors is conventionally considered highly challenging. Driven by increasing research efforts, success rates have increased significantly in recent years. In this study, we analyze the physicochemical properties of 9351 non-redundant inhibitors present in the iPPI-DB and TIMBAL databases to define a computational model for active compounds acting against PPI targets. Principle component analysis (PCA) and k-means clustering were used to identify plausible PPI targets in regions of interest in the active group in the chemical space between active and inactive iPPI compounds. Notably, the uniquely defined active group exhibited distinct differences in activity compared with other active compounds. These results demonstrate that active compounds with regions of interest in the chemical space may be expected to provide insights into potential PPI inhibitors for particular protein targets.

Substrate-induced modulation of protein-protein interactions within human mitochondrial cytochrome P450-dependent system

Steroidogenesis is strictly regulated at multiple levels, as produced steroid hormones are crucial to maintain physiological functions. Cytochrome P450 enzymes are key players in adrenal steroid hormone biosynthesis and function within short redox-chains in mitochondria and endoplasmic reticulum. However, mechanisms regulating supply of reducing equivalents in the mitochondrial CYP-dependent system are not fully understood. In the present work, we aimed to estimate how the specific steroids, substrates, intermediates and products of multistep reactions modulate protein-protein interactions between adrenodoxin (Adx) and mitochondrial CYP11 s. Using the SPR technology we determined that steroid substrates affect affinity and stability of CYP11s-Adx complexes in an isoform-specific mode. In particular, cholesterol induces a 4-fold increase in the rate of CYP11A1 - Adx complex formation without significant effect on dissociation (koff decreased ∼1.5-fold), overall increasing complex affinity. At the same time steroid substrates decrease the affinity of both CYP11B1 - Adx and CYP11B2 - Adx complexes, predominantly reducing their stability (4-7 fold). This finding reveals differentiation of protein-protein interactions within the mitochondrial pool of CYPs, which have the same electron donor. The regulation of electron supply by the substrates might affect the overall steroid hormones production. Our experimental data provide further insight into protein-protein interactions within CYP-dependent redox chains involved in steroidogenesis.

Identification of potential SARS-CoV-2 entry inhibitors by targeting the interface region between the spike RBD and human ACE2

Coronavirus disease 2019 (COVID-19) is a fatal infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The virus infection is initiated upon recognition and binding of the spike (S) protein receptor-binding domain (RBD) to the host cell surface receptor, angiotensin-converting enzyme 2 (ACE2). Blocking the interaction between S protein and ACE2 receptor is a novel approach to prevent the viral entry into the host cell. The present study is aimed at the identification of small molecules which can disrupt the interaction between SARS-CoV-2 S protein and human ACE2 receptor by binding to the interface region. A chemical library consisting of 1,36,191 molecules were screened for drug-like compounds based on Lipinski's rule of five, Verber's rule and in silico toxicity parameters. The filtered drug-like molecules were next subjected to molecular docking in the interface region of RBD. The best three hits viz; ZINC64023823, ZINC33039472 and ZINC00991597 were further taken for molecular dynamics (MD) simulation studies and binding free energy evaluations using Molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) and Molecular mechanics-Generalized Born surface area (MM-GBSA). The protein-ligand complexes showed stable trajectories throughout the simulation time. ZINC33039472 exhibited binding free energy value lower as compared to the control (emodin) with a higher contribution by gas-phase energy and van der Waals energy to the total binding free energy. Thus, ZINC33039472 is identified to be a promising interfacial binding molecule which can inhibit the interaction between the viral S protein and human ACE2 receptor which would consequently help in the management of the disease.

Interaction of Isocitrate Lyase with Proteins Involved in the Energetic Metabolism in Paracoccidioides lutzii

Background: Systemic mycosis is a cause of death of immunocompromised subjects. The treatment directed to evade fungal pathogens shows severe limitations, such as time of drug exposure and side effects. The paracoccidioidomycosis (PCM) treatment depends on the severity of the infection and may last from months to years. Methods: To analyze the main interactions of Paracoccidioides lutzii isocitrate lyase (ICL) regarding the energetic metabolism through affinity chromatography, we performed blue native PAGE and co-immunoprecipitation to identify ICL interactions. We also performed in silico analysis by homology, docking, hot-spot prediction and contact preference analysis to identify the conformation of ICL complexes. Results: ICL interacted with 18 proteins in mycelium, 19 in mycelium-to-yeast transition, and 70 in yeast cells. Thirty complexes were predicted through docking and contact preference analysis. ICL has seven main regions of interaction with protein partners. Conclusions: ICL seems to interfere with energetic metabolism of P. lutzii, regulating aerobic and anaerobic metabolism as it interacts with proteins from glycolysis, gluconeogenesis, TCA and methylcitrate cycles, mainly through seven hot-spot residues.

Small molecules that inhibit TNF signalling by stabilising an asymmetric form of the trimer

Tumour necrosis factor (TNF) is a cytokine belonging to a family of trimeric proteins; it has been shown to be a key mediator in autoimmune diseases such as rheumatoid arthritis and Crohn’s disease. While TNF is the target of several successful biologic drugs, attempts to design small molecule therapies directed to this cytokine have not led to approved products. Here we report the discovery of potent small molecule inhibitors of TNF that stabilise an asymmetrical form of the soluble TNF trimer, compromising signalling and inhibiting the functions of TNF in vitro and in vivo. This discovery paves the way for a class of small molecule drugs capable of modulating TNF function by stabilising a naturally sampled, receptor-incompetent conformation of TNF. Furthermore, this approach may prove to be a more general mechanism for inhibiting protein–protein interactions.

While biologics have been successfully applied in TNF antagonist treatments, there are no clinically approved small molecules that target TNF. Here, the authors discover potent small molecule inhibitors of TNF, elucidate their molecular mechanism, and demonstrate TNF inhibition in vitro and in vivo.

PIDD interaction with KEAP1 as a new mutation-independent mechanism to promote NRF2 stabilization and chemoresistance in NSCLC

Chemotherapy resistance is a major problem in non-small cell lung cancer (NSCLC) treatment. A major mechanism of chemoresistance involves stabilization of the NRF2 transcription factor. NRF2 levels are normally tightly regulated through interaction with KEAP1, an adaptor that targets NRF2 to the CUL3 E3 ubiquitin ligase for proteolysis. In NSCLC, aberrant NRF2 stabilization is best understood through mutations in NRF2, KEAP1, or CUL3 that disrupt their interaction. Biochemical studies, however, have revealed that NRF2 can also be stabilized through expression of KEAP1-interacting proteins that competitively sequester KEAP1 away from NRF2. Here, we have identified PIDD, as a novel KEAP1-interactor in NSCLC that regulates NRF2. We show that this interaction allows PIDD to reduce NRF2 ubiquitination and increase its stability. We also demonstrate that PIDD promotes chemoresistance in NSCLC cells both in vitro and in vivo, and that this effect is dependent on NRF2. Finally, we report that NRF2 protein expression in a NSCLC cohort exceeds the typical incidence of combined NRF2, KEAP1, and CUL3 mutations, and that NRF2 expression in this cohort is correlated with PIDD levels. Our data identify PIDD as a new NRF2 regulator, and suggest that variations in PIDD levels contribute to differential chemosensitivities among NSCLC patients.

Exploiting endogenous opioids: Lessons learned from endomorphin 2 in the female rat

Effective management of chronic pain is demanded by ethical as well as medical considerations. Although opioid analgesics remain among the most effective pharmacotherapies for ameliorating many types of pain, their use is clouded by concerns regarding their addictive properties, underscored by the current epidemic of prescription opioid abuse and attendant deaths. Medicinal harnessing of endogenous opioid antinociception could provide a strategy for continuing to take advantage of the powerful antinociceptive properties of opioids while avoiding their abuse potential. Based on our studies of endogenous mechanism that suppress and facilitate spinal endomorphin 2 antinociception over the rat reproductive cycle, we identified multiple signaling molecules that could serve as targets for activating endogenous opioid analgesia for chronic pain management in women. Our findings emphasize the need for a precision medicine approach that includes stage of menstrual cycle as an important determinant of drug targets for (activating/harnessing) endogenous opioid antinociceptive systems/ capabilities. Utilization of drugs that harness endogenous opioid antinociception in accordance with varying physiological states represents a novel approach for effective pain management.

Methods for Discovering and Targeting Druggable Protein-Protein Interfaces and Their Application to Repurposing

Drug repurposing is a creative and resourceful approach to increase the number of therapies by exploiting available and approved drugs. However, identifying new protein targets for previously approved drugs is challenging. Although new strategies have been developed for drug repurposing, there is broad agreement that there is room for further improvements. In this chapter, we review protein-protein interaction (PPI) interface-targeting strategies for drug repurposing applications. We discuss certain features, such as hot spot residue and hot region prediction and their importance in drug repurposing, and illustrate common methods used in PPI networks to identify drug off-targets. We also collect available online resources for hot spot prediction, binding pocket identification, and interface clustering which are effective resources in polypharmacology. Finally, we provide case studies showing the significance of protein interfaces and hot spots in drug repurposing.

Allosteric binding sites in Rab11 for potential drug candidates

Rab11 is an important protein subfamily in the RabGTPase family. These proteins physiologically function as key regulators of intracellular membrane trafficking processes. Pathologically, Rab11 proteins are implicated in many diseases including cancers, neurodegenerative diseases and type 2 diabetes. Although they are medically important, no previous study has found Rab11 allosteric binding sites where potential drug candidates can bind to. In this study, by employing multiple clustering approaches integrating principal component analysis, independent component analysis and locally linear embedding, we performed structural analyses of Rab11 and identified eight representative structures. Using these representatives to perform binding site mapping and virtual screening, we identified two novel binding sites in Rab11 and small molecules that can preferentially bind to different conformations of these sites with high affinities. After identifying the binding sites and the residue interaction networks in the representatives, we computationally showed that these binding sites may allosterically regulate Rab11, as these sites communicate with switch 2 region that binds to GTP/GDP. These two allosteric binding sites in Rab11 are also similar to two allosteric pockets in Ras that we discovered previously.

Disrupting VEGF-VEGFR1 Interaction: De Novo Designed Linear Helical Peptides to Mimic the VEGF13-25 Fragment

The interaction between vascular endothelial growth factor (VEGF) and its receptors (VEGFR) has important implications in angiogenesis and cancer, which moved us to search for peptide derivatives able to block this protein–protein interaction. In a previous work we had described a collection of linear 13-mer peptides specially designed to adopt helical conformations (Ac-SSEEX⁵ARNX⁹AAX¹²N-NH₂), as well as the evaluation of seven library components for the inhibition of the interaction of VEGF with its Receptor 1 (VEGFR1). This study led to the discovery of some new, quite potent inhibitors of this protein–protein system. The results we found prompted us to extend the study to other peptides of the library. We describe here the evaluation of a new selection of peptides from the initial library that allow us to identify new VEGF-VEGFR1 inhibitors. Among them, the peptide sequence containing F, W, and I residues at the 5, 9, and 12 positions, show a very significant nanomolar IC₅₀ value, competing with VEGF for its receptor 1, VEGFR1 (Flt-1), which could represent a new tool within the therapeutic arsenal for cancer detection and therapy.