A dynamic target-based pharmacophoric model mapping the CD4 binding site on HIV-1 gp120 to identify new inhibitors of gp120-CD4 protein-protein interactions

Predicting the Likelihood of Molecules to Act as Modulators of Protein-Protein Interactions

Targeting protein-protein interactions (PPIs) by small molecule modulators (iPPIs) is an attractive strategy for drug therapy, and some iPPIs have already been introduced into the clinic. Blocking PPIs is however considered to be a more difficult task than inhibiting enzymes or antagonizing receptor activity. In this paper, we examine whether it is possible to predict the likelihood of molecules to act as iPPIs. Using our in-house iterative stochastic elimination (ISE) algorithm, we constructed two classification models that successfully distinguish between iPPIs from the iPPI-DB database and decoy molecules from either the Enamine HTS collection (ISE 1) or the ZINC database (ISE 2). External test sets of iPPIs taken from the TIMBAL database and decoys from Enamine HTS or ZINC were screened by the models: the area under the curve for the receiver operating characteristic curve was 0.85-0.89, and the Enrichment Factor increased from an initial 1 to as much as 66 for ISE 1 and 57 for ISE 2. Screening of the Enamine HTS and ZINC data sets through both models results in a library of ∼1.3 million molecules that pass either one of the models. This library is enriched with iPPI candidates that are structurally different from known iPPIs, and thus, it is useful for target-specific screenings and should accelerate the discovery of iPPI drug candidates. The entire library is available in Table S6.

Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interactions

Protein-protein interactions play crucial and subtle roles in many biological processes and modifications of their fine mechanisms generally result in severe diseases. Peptide derivatives are very promising therapeutic agents for modulating protein-protein associations with sizes and specificities between those of small compounds and antibodies. For the same reasons, rational design of peptide-based inhibitors naturally borrows and combines computational methods from both protein-ligand and protein-protein research fields. In this chapter, we aim to provide an overview of computational tools and approaches used for identifying and optimizing peptides that target protein-protein interfaces with high affinity and specificity. We hope that this review will help to implement appropriate in silico strategies for peptide-based drug design that builds on available information for the systems of interest.

Targeting protein-protein interaction interfaces in COVID-19 drug discovery

To date, the COVID-19 pandemic has claimed over 1 million human lives, infected another 50 million individuals and wreaked havoc on the global economy. The crisis has spurred the ongoing development of drugs targeting its etiological agent, the SARS-CoV-2. Targeting relevant protein-protein interaction interfaces (PPIIs) is a viable paradigm for the design of antiviral drugs and enriches the targetable chemical space by providing alternative targets for drug discovery. In this review, we will provide a comprehensive overview of the theory, methods and applications of PPII-targeted drug development towards COVID-19 based on recent literature. We will also highlight novel developments, such as the successful use of non-native protein-protein interactions as targets for antiviral drug screening. We hope that this review may serve as an entry point for those interested in applying PPIIs towards COVID-19 drug discovery and speed up drug development against the pandemic.

Mimicking Strategy for Protein-Protein Interaction Inhibitor Discovery by Virtual Screening

As protein–protein interactions (PPIs) are highly involved in most cellular processes, the discovery of PPI inhibitors that mimic the structure of the natural protein partners is a promising strategy toward the discovery of PPI inhibitors. In this review, we discuss recent advances in the application of virtual screening for identifying mimics of protein partners. The classification and function of the mimicking protein partner inhibitor discovery by virtual screening are described. We anticipate that this review would be of interest to medicinal chemists and chemical biologists working in the field of protein–protein interaction inhibitors or probes.

Computational design, synthesis and evaluation of new sulphonamide derivatives targeting HIV-1 gp120

Attachment of envelope glycoprotein gp120 to the host cell receptor CD4 is the first step during the human immunodeficiency virus-1 (HIV-1) entry into the host cells that makes it a promising target for drug design. To elucidate the crucial three dimensional (3D) structural features of reported HIV-1 gp120 CD4 binding inhibitors, 3D pharmacophores were generated and receptor based approach was employed to quantify these structural features. A four-partial least square factor model with good statistics and predictive ability was generated for the dataset of 100 molecules. To further ascertain the structural requirement for gp120-CD4 binding inhibition, molecular interaction studies of inhibitors with gp120 was carried out by performing molecular docking using Glide 5.6. Based on these studies, structural requirements were drawn and new molecules were designed accordingly to yield new sulphonamides derivatives. A water based green synthetic approach was adopted to obtain these compounds which were evaluated for their HIV-1 gp120 CD4 binding inhibition. The newly synthesized compounds exhibited remarkable activity (10-fold increase) when compared with the standard BMS 806. Further the stability of newly synthesized derivatives with HIV-1 gp120 was also investigated through molecular dynamics simulation studies. This provides a proof of concept for molecular modeling based design of new inhibitors for inhibition of HIV-1 gp120 CD4 interaction.

Computer-aided design of amino acid-based therapeutics: a review

During the last two decades, the pharmaceutical industry has progressed from detecting small molecules to designing biologic-based therapeutics. Amino acid-based drugs are a group of biologic-based therapeutics that can effectively combat the diseases caused by drug resistance or molecular deficiency. Computational techniques play a key role to design and develop the amino acid-based therapeutics such as proteins, peptides and peptidomimetics. In this study, it was attempted to discuss the various elements for computational design of amino acid-based therapeutics. Protein design seeks to identify the properties of amino acid sequences that fold to predetermined structures with desirable structural and functional characteristics. Peptide drugs occupy a middle space between proteins and small molecules and it is hoped that they can target "undruggable" intracellular protein-protein interactions. Peptidomimetics, the compounds that mimic the biologic characteristics of peptides, present refined pharmacokinetic properties compared to the original peptides. Here, the elaborated techniques that are developed to characterize the amino acid sequences consistent with a specific structure and allow protein design are discussed. Moreover, the key principles and recent advances in currently introduced computational techniques for rational peptide design are spotlighted. The most advanced computational techniques developed to design novel peptidomimetics are also summarized.

Profiling the interaction mechanism of indole-based derivatives targeting the HIV-1 gp120 receptor

A glycoprotein exposed on a viral surface, human immunodeficiency virus type 1 (HIV-1) gp120 is essential for virus entry into cells as it plays a vital role in seeking out specific cell surface receptors for entry.

2-Aminothiazolones as anti-HIV agents that act as gp120-CD4 inhibitors

We report here the synthesis of 2-aminothiazolones along with their biological properties as novel anti-HIV agents. Such compounds have proven to act through the inhibition of the gp120-CD4 protein-protein interaction that occurs at the very early stage of the HIV-1 entry process. No cytotoxicity was found for these compounds, and broad antiviral activities against laboratory strains and pseudotyped viruses were documented. Docking simulations have also been applied to predict the mechanism, at the molecular level, by which the inhibitors were able to interact within the Phe43 cavity of HIV-1 gp120. Furthermore, a preliminary absorption, distribution, metabolism, and excretion (ADME) evaluation was performed. Overall, this study led the basis for the development of more potent HIV entry inhibitors.

Structure-based design of small-molecule protein–protein interaction modulators: the story so far

As the pivotal role of protein–protein interactions in cell growth, transcriptional activity, intracellular trafficking, signal transduction and pathological conditions has been assessed, experimental and in silico strategies have been developed to design protein–protein interaction modulators. State-of-the-art structure-based design methods, mainly pharmacophore modeling and docking, which have succeeded in the identification of enzyme inhibitors, receptor agonists and antagonists, and new tools specifically conceived to target protein–protein interfaces (e.g., hot-spot and druggable pocket prediction methods) have been applied in the search for small-molecule protein–protein interaction modulators. Many successful applications of structure-based design approaches that, despite the challenge of targeting protein–protein interfaces with small molecules, have led to the identification of micromolar and submicromolar hits are reviewed here.

Rational design of HIV-1 entry inhibitors

This chapter reviews studies that have used in silico techniques to design or identify potential HIV-1 entry inhibitors targeting cellular receptors CD4, CCR5, and CXCR4 and envelope glycoproteins, gp120 and gp41 of HIV-1. Both structure- and ligand-based design techniques have been used in those studies by applying diverse modeling techniques such as quantitative structure-activity relationship analysis, conformational analysis, molecular dynamics, pharmacophore generation, docking, virtual screening (using docking software and also shape-based ROCS techniques), and fragment-based design.

LIM kinases are attractive targets with many macromolecular partners and only a few small molecule regulators

The LIM kinases 1 and 2 (LIMK1 and LIMK2) are dual specificity (serine/threonine and tyrosine) kinases. Although they show significant structural similarity, LIMK1 and LIMK2 show different expression, subcellular localization, and functions. They are involved in many cellular functions, such as migration, cycle, and neuronal differentiation and also have a role in pathological processes, such as cancer cell invasion and metastatis, as well as in neurodevelopmental disorders (namely, the William's syndrome). LIM kinases have a relevant number of known partners that are able to induce or limit the ability of LIMK1 and LIMK2 to phosphorylate and inactivate their major substrate, cofilin. On the contrary, only a limited number of small molecules that interact with the two proteins to modulate their kinase activity have been identified. In this review, the most important partners of LIM kinases and their modulating activity toward LIMKs are described. The small compounds identified as LIMK1 and LIMK2 modulators are also reported, as well as their role as possible therapeutic agents for LIMK-induced diseases.

Molecular dynamics and DFT study on HIV-1 nucleocapsid protein-7 in complex with viral genome

The HIV-1 nucleocapsid protein-7 (NCp7) is a highly basic, small zinc-binding protein involved in both deoxyribonucleic (DNA) and ribonucleic (RNA) acids annealing and in viral particle maturation including genome encapsidation, with an additional chaperoning activity toward reverse transcriptase by promoting the two obligatory strand transfers during reverse transcription. Because of its interaction with highly conserved sequences of the HIV-1 genome, NCp7 is being considered a new potential drug target, resistant to mutation, for antiviral activity. The high flexibility of this protein has, however, limited the identification of structural determinants involved in the interaction with stranded sequences of DNA and RNA. Here, we provide a quantum mechanics (density functional theory) study of the zinc-binding motifs and a molecular dynamics simulation of the protein in complex with RNA and DNA, starting from available nuclear magnetic resonance (NMR) structures. Results show that the interaction between the NCp7 and the viral genome is probably based on electrostatic interactions due to a cluster of basic residues, which is reinforced by the exploitation of nonelectrostatic contacts that further stabilize the complexes. Moreover, a possible mechanism for DNA destabilization that involves amino acids T24 and R26 is also hypothesized. Finally, a network of hydrophobic and hydrogen-bond interactions for the stabilization of complexes with DNA and, especially, with RNA is described here for the first time. The complexes between NCp7 and both DNA and RNA, resulting from computer simulations, showed structural properties that are in agreement with most of the currently available molecular biology evidence and could be considered as reliable models (better than NMR structures currently available) for subsequent structure-based ligand design approaches.

ADS-J1 inhibits HIV-1 entry by interacting with gp120 and does not block fusion-active gp41 core formation

We had shown that virus resistance to ADS-J1 was associated with amino acid changes in the envelope glycoprotein, mostly located in the gp120 coding region. Time-of-addition and endocytic virus transfer assays clearly demonstrated that ADS-J1 behaved as a gp120 inhibitor. ADS-J1-resistant virus was cross-resistant to the polyanion dextran sulfate, and recombination of gp120 recovered only the ADS-J1-resistant phenotype. In summary, ADS-J1 blocks an early step of virus entry that appears to be driven by gp120 alone.

Rational conversion of noncontinuous active region in proteins into a small orally bioavailable macrocyclic drug-like molecule: the HIV-1 CD4:gp120 paradigm

Rational conversion of noncontinuous active regions of proteins into a small orally bioavailable molecule is crucial for the discovery of new drugs based on inhibition of protein-protein interactions. We developed a method that utilizes backbone cyclization as an intermediate step for conversion of the CD4 noncontinuous active region into small macrocyclic molecules. We demonstrate that this method is feasible by preparing small inhibitor for human immunodeficiency virus infection. The lead compound, CG-1, proved orally available in the rat model.