scholarly journals Highly Conserved Homotrimer Cavity Formed by the SARS-CoV-2 Spike Glycoprotein: A Novel Binding Site

2020 ◽  
Vol 9 (5) ◽  
pp. 1473 ◽  
Author(s):  
Umesh Kalathiya ◽  
Monikaben Padariya ◽  
Marcos Mayordomo ◽  
Małgorzata Lisowska ◽  
Judith Nicholson ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Binding Site ◽  
Protein Interactions ◽  
Mammalian Target Of Rapamycin ◽  
Md Simulations ◽  
Cell Receptor ◽  
Spike Protein ◽  
Heptad Repeat ◽  
Central Helix ◽  
Future Drug

An important stage in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) life cycle is the binding of the spike (S) protein to the angiotensin converting enzyme-2 (ACE2) host cell receptor. Therefore, to explore conserved features in spike protein dynamics and to identify potentially novel regions for drugging, we measured spike protein variability derived from 791 viral genomes and studied its properties by molecular dynamics (MD) simulation. The findings indicated that S2 subunit (heptad-repeat 1 (HR1), central helix (CH), and connector domain (CD) domains) showed low variability, low fluctuations in MD, and displayed a trimer cavity. By contrast, the receptor binding domain (RBD) domain, which is typically targeted in drug discovery programs, exhibits more sequence variability and flexibility. Interpretations from MD simulations suggest that the monomer form of spike protein is in constant motion showing transitions between an “up” and “down” state. In addition, the trimer cavity may function as a “bouncing spring” that may facilitate the homotrimer spike protein interactions with the ACE2 receptor. The feasibility of the trimer cavity as a potential drug target was examined by structure based virtual screening. Several hits were identified that have already been validated or suggested to inhibit the SARS-CoV-2 virus in published cell models. In particular, the data suggest an action mechanism for molecules including Chitosan and macrolides such as the mTOR (mammalian target of Rapamycin) pathway inhibitor Rapamycin. These findings identify a novel small molecule binding-site formed by the spike protein oligomer, that might assist in future drug discovery programs aimed at targeting the coronavirus (CoV) family of viruses.

scholarly journals Highly Conserved Homotrimer Cavity Formed by the SARS-CoV-2 Spike Glycoprotein: A Novel Binding Site

2020 ◽  
Author(s):  
Umesh Kalathiya ◽  
Monikaben Padariya ◽  
Marcos Mayordomo ◽  
Małgorzata Lisowska ◽  
Judith Nicholson ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Binding Site ◽  
Protein Interactions ◽  
Drug Target ◽  
Md Simulation ◽  
Cell Receptor ◽  
S Protein ◽  
Viral Genomes ◽  
Host Cell Receptor ◽  
Future Drug

An important stage in SARS-CoV-2 life cycle is the fusion of spike(S) protein with the ACE2 host-cell receptor. Therefore, to explore conserved features in S protein dynamics and to identify potentially novel regions for drugging, we measured variability derived from 791 viral genomes and studied its properties by MD simulation. The findings indicated that S2 subunit (HR1, CH, and CD domains) showed low variability, low fluctuations in MD, and displayed a trimer cavity. By contrast, the RBD domain, which is typically targeted in drug discovery programmes, exhibits more sequence variability and flexibility. Interpretations from MD suggest that the monomer is in constant motion showing transitions up-to-down state, and the trimer cavity may function as a 'bouncing spring' that may facilitates S protein interactions with ACE2. Feasibility of trimer cavity for potential drug target was examined by SBVS screening. Several hits that have already been validated or suggested to inhibit the SARS-CoV-2 virus in cell systems were identified; in particular, the data suggest an action mechanism for such molecules including Chitosan and macrolide types. These findings identify a novel binding-site formed by the S protein, that might assist in future drug discovery programmes aimed at targeting the CoV family of viruses.

scholarly journals How does a small molecule bind at a cryptic binding site?

2021 ◽  
Author(s):  
Yibing Shan ◽  
Venkatesh P. Mysore ◽  
Abba E. Leffler ◽  
Eric T. Kim ◽  
Shiori Sagawa ◽  
...  
Keyword(s):  
Small Molecules ◽  
Binding Site ◽  
Small Molecule ◽  
Protein Interactions ◽  
Binding Sites ◽  
Rational Design ◽  
Structural Information ◽  
Interleukin 2 ◽  
Md Simulations ◽  
Drug Binding

Protein-protein interactions (PPIs) are ubiquitous biomolecular processes that are central to virtually all aspects of cellular function. Identifying small molecules that modulate specific disease-related PPIs is a strategy with enormous promise for drug discovery. The design of drugs to disrupt PPIs is challenging, however, because many potential drug-binding sites at PPI interfaces are "cryptic": When unoccupied by a ligand, cryptic sites are often flat and featureless, and thus not readily recognizable in crystal structures, with the geometric and chemical characteristics of typical small-molecule binding sites only emerging upon ligand binding. The rational design of small molecules to inhibit specific PPIs would benefit from a better understanding of how such molecules bind at PPI interfaces. To this end, we have conducted unbiased, all-atom MD simulations of the binding of four small-molecule inhibitors (SP4206 and three SP4206 analogs) to interleukin 2 (IL2)—which performs its function by forming a PPI with its receptor—without incorporating any prior structural information about the ligands' binding. In multiple binding events, a small molecule settled into a stable binding pose at the PPI interface of IL2, resulting in a protein–small-molecule binding site and pose virtually identical to that observed in an existing crystal structure of the IL2-SP4206 complex. Binding of the small molecule stabilized the IL2 binding groove, which when the small molecule was not bound emerged only transiently and incompletely. Moreover, free energy perturbation (FEP) calculations successfully distinguished between the native and non-native IL2–small-molecule binding poses found in the simulations, suggesting that binding simulations in combination with FEP may provide an effective tool for identifying cryptic binding sites and determining the binding poses of small molecules designed to disrupt PPI interfaces by binding to such sites.

scholarly journals A repurposed drug screen identifies compounds that inhibit the binding of the COVID-19 spike protein to ACE2

2021 ◽  
Author(s):  
Kaleb B Tsegay ◽  
Christiana M Adeyemi ◽  
Edward P Gniffke ◽  
D. Noah E.P. Sather ◽  
John K Walker ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Spike Protein ◽  
Regulatory Agencies ◽  
Drug Screen ◽  
Effective Screening ◽  
Screening Approach ◽  
Binding Inhibition ◽  
Future Drug ◽  
Repurposed Drugs ◽  
Potential Inhibitors

Repurposed drugs that block the interaction between the SARS-CoV-2 spike protein and its receptor ACE2 could offer a rapid route to novel COVID-19 treatments or prophylactics. Here, we screened 2701 compounds from a commercial library of drugs approved by international regulatory agencies for their ability to inhibit the binding of recombinant, trimeric SARS-CoV-2 spike protein to recombinant human ACE2. We identified 56 compounds that inhibited binding by <90%, measured the EC50 of binding inhibition, and computationally modeled the docking of the best inhibitors to both Spike and ACE2. These results highlight an effective screening approach to identify compounds capable of disrupting the Spike-ACE2 interaction as well as identifying several potential inhibitors that could serve as templates for future drug discovery efforts.

scholarly journals Enrichments of Ensemble Docking Strategy Based on the Bayesian Model

2021 ◽  
Author(s):  
Yu Lei ◽  
Sheng Guo ◽  
Yi Liu ◽  
Zhili Zuo
Keyword(s):  
Drug Discovery ◽  
Binding Site ◽  
Crystal Structures ◽  
Bayesian Model ◽  
Protein Flexibility ◽  
Md Simulations ◽  
Ensemble Docking ◽  
Single Receptor

Abstract MotivationChallenges remained in structure-based drug discovery which include protein flexibility in binding site. Thus, concerning the flexibility of proteins, docking into an ensemble of rigid conformations (ensemble docking) have been proposed with incorporation into protein flexibility with expects that it could provide higher enrichments than rigid single receptor. Here we have developed the ensemble docking strategy by using Bayesian Model algorithms, and this method is validated by three proteins: BTK, JAK and PARP. The Bayesian Model was used to integrate independent docking runs of an ensemble of rigid crystal structures and MD simulations. ResultsThe structure of MD simulations outperforms the crystal structures in separating inhibitors from decoys in BTK and PARP. Further, the results demonstrated that the ensemble docking strategy has better performance than rigid single conformation.

scholarly journals COVID-19 Spike-host cell receptor GRP78 binding site prediction

2020 ◽  
Author(s):  
Ibrahim Ibrahim ◽  
Doaa Abdelmalek ◽  
Mohamed Elshahat ◽  
Abdo Elfiky
Keyword(s):  
Binding Site ◽  
Host Cell ◽  
Driving Force ◽  
Cell Receptor ◽  
Binding Domain ◽  
Cell Surface Receptor ◽  
Spike Protein ◽  
Cell Recognition ◽  
Host Cell Receptor ◽  
Host Cell Recognition

Abstract Coronaviruses have been circulating between animals and humans repeatedly. A novel human coronavirus, named COVID-19, has recently emerged in Hubei Province, China. Within the first two months, more than 2200 deaths have been confirmed, and there have been more than 79,000 hospitalized patients, mainly in China. Understanding the virus mode of host cell recognition may help to fight the disease and save lives. The spike protein of coronaviruses is the main driving force for host cell recognition. In this study, the COVID-19 corona viral spike binding site to the cell-surface receptor (Glucose Regulated Protein 78 (GRP78)) is predicted using combined molecular modeling docking and structural bioinformatics. The cyclic peptide Pep42 (CTVALPGGYVRVC) was reported earlier to be the docking platform of GRP78 in cancer cells. The COVID-19 spike protein is modeled using its counterpart, the SARS spike. Sequence and structural alignments show that four regions, in addition to its cyclic nature (the S-S bond), have sequence and physicochemical similarities to the cyclic Pep42. Protein-protein docking was performed to test the four regions of the spike that fit tightly in the GRP78 Substrate Binding Domain β (SBDβ). The docking pose revealed the involvement of the SBDβ of GRP78 and the receptor-binding domain of the coronavirus spike protein in recognition of the host cell receptor. We reveal that the binding is more favorable between regions III (C391-C525) and IV (C480-C488) of the spike protein model and GRP78. Region IV is the main driving force for GRP78 binding with the predicted binding affinity of -9.8 kcal/mol. These nine residues (region IV) of the spike can be used to develop therapeutics specific against COVID-19.

Sitagliptin: a potential drug for the treatment of SARS-CoV-2?

2020 ◽  
Author(s):  
Sanaa Bardaweel
Keyword(s):  
Clinical Trials ◽  
Drug Discovery ◽  
Antimalarial Drug ◽  
Drug Repurposing ◽  
Spike Protein ◽  
Diabetic Patients ◽  
Potential Drug ◽  
Chemokine Production ◽  
Drug Discovery And Development ◽  
Sequence Identity

Recently, an outbreak of fatal coronavirus, SARS-CoV-2, has emerged from China and is rapidly spreading worldwide. As the coronavirus pandemic rages, drug discovery and development become even more challenging. Drug repurposing of the antimalarial drug chloroquine and its hydroxylated form had demonstrated apparent effectiveness in the treatment of COVID-19 associated pneumonia in clinical trials. SARS-CoV-2 spike protein shares 31.9% sequence identity with the spike protein presents in the Middle East Respiratory Syndrome Corona Virus (MERS-CoV), which infects cells through the interaction of its spike protein with the DPP4 receptor found on macrophages. Sitagliptin, a DPP4 inhibitor, that is known for its antidiabetic, immunoregulatory, anti-inflammatory, and beneficial cardiometabolic effects has been shown to reverse macrophage responses in MERS-CoV infection and reduce CXCL10 chemokine production in AIDS patients. We suggest that Sitagliptin may be beneficial alternative for the treatment of COVID-19 disease especially in diabetic patients and patients with preexisting cardiovascular conditions who are already at higher risk of COVID-19 infection.

Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes

2019 ◽  
Vol 26 (21) ◽  
pp. 3890-3910 ◽  
Author(s):  
Branislava Gemovic ◽  
Neven Sumonja ◽  
Radoslav Davidovic ◽  
Vladimir Perovic ◽  
Nevena Veljkovic
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Experimental Studies ◽  
Protein Protein Interactions ◽  
Web Based ◽  
Prediction Tools ◽  
Physiological Processes ◽  
Modern Drug ◽  
Ppi Prediction

Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology. Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions. Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions. Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs. Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.

Protein Interaction Domains and Post-Translational Modifications: Structural Features and Drug Discovery Applications

2020 ◽  
Vol 27 (37) ◽  
pp. 6306-6355 ◽  
Author(s):  
Marian Vincenzi ◽  
Flavia Anna Mercurio ◽  
Marilisa Leone
Keyword(s):  
Drug Discovery ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Structural Information ◽  
Protein Complexes ◽  
Structural Features ◽  
Protein Protein Interactions ◽  
Modular Architecture ◽  
Post Translational Modifications ◽  
Interaction Domains

Background:: Many pathways regarding healthy cells and/or linked to diseases onset and progression depend on large assemblies including multi-protein complexes. Protein-protein interactions may occur through a vast array of modules known as protein interaction domains (PIDs). Objective:: This review concerns with PIDs recognizing post-translationally modified peptide sequences and intends to provide the scientific community with state of art knowledge on their 3D structures, binding topologies and potential applications in the drug discovery field. Method:: Several databases, such as the Pfam (Protein family), the SMART (Simple Modular Architecture Research Tool) and the PDB (Protein Data Bank), were searched to look for different domain families and gain structural information on protein complexes in which particular PIDs are involved. Recent literature on PIDs and related drug discovery campaigns was retrieved through Pubmed and analyzed. Results and Conclusion:: PIDs are rather versatile as concerning their binding preferences. Many of them recognize specifically only determined amino acid stretches with post-translational modifications, a few others are able to interact with several post-translationally modified sequences or with unmodified ones. Many PIDs can be linked to different diseases including cancer. The tremendous amount of available structural data led to the structure-based design of several molecules targeting protein-protein interactions mediated by PIDs, including peptides, peptidomimetics and small compounds. More studies are needed to fully role out, among different families, PIDs that can be considered reliable therapeutic targets, however, attacking PIDs rather than catalytic domains of a particular protein may represent a route to obtain selective inhibitors.

Decoding Protein-protein Interactions: An Overview

2020 ◽  
Vol 20 (10) ◽  
pp. 855-882
Author(s):  
Olivia Slater ◽  
Bethany Miller ◽  
Maria Kontoyianni
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Drug Repurposing ◽  
Protein Docking ◽  
Target Space ◽  
Protein Protein Interactions ◽  
X Ray Crystallography ◽  
Protein Protein Interaction ◽  
Interaction Sites ◽  
Long Time

Drug discovery has focused on the paradigm “one drug, one target” for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

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