Identification of irreversible protein splicing inhibitors as potential anti-TB drugs: insight from hybrid non-covalent/covalent docking virtual screening and molecular dynamics simulations

Identification of prospective covalent inhibitors for SARS-CoV-2 main protease using structure-based approach

The rapid global spread of SARS-CoV-2 has recently caused havoc and forced the world into a state of the pandemic causing respiratory, gastrointestinal, hepatic, and neurologic diseases. It persistently, through mutation, develops into new variants of the virus that have appeared over time. As main protease (Mpro) is involved in proteolysis of two overlapping polyproteins pp1a and pp1ab to produce 16 non-structural proteins having a paramount factor in the virus replication that have a cysteine-histidine catalytic dyad. A computational approach, guiding a covalent docking as it offers higher potency, long duration of action and decreased drug resistance advantages over the conventional docking of the ligands on a catalytic dyad, is applied for SARS-CoV-2 main protease (Mpro) in this manuscript to divulge better molecules. Mpro active site contains Cys145 residue which act as a nucleophile and can donate its electron to an electrophilic molecule by interacting covalently. Furthermore, the ligand-protein complexes are allowed to simulate their dynamic studies to look into their time-based interaction stability and also, a parallel study of ADME properties for the hit molecules is also performed. Important insights from the studies revealed that the interactions are persistent and molecules may be considered for further optimization in clinical investigation.Communicated by Ramaswamy H. Sarma.

Docking covalent targets for drug discovery: stimulating the computer-aided drug design community of possible pitfalls and erroneous practices

The continuous approval of covalent drugs in recent years for the treatment of diseases has led to an increased search for covalent agents by medicinal chemists and computational scientists worldwide. In the computational parlance, molecular docking which is a popular tool to investigate the interaction of a ligand and a protein target, does not account for the formation of covalent bond, and the increasing application of these conventional programs to covalent targets in early drug discovery practice is a matter of utmost concern. Thus, in this comprehensive review, we sought to educate the docking community about the realization of covalent docking and the existence of suitable programs to make their future virtual-screening events on covalent targets worthwhile and scientifically rational. More interestingly, we went beyond the classical description of the functionality of covalent-docking programs down to selecting the 'best' program to consult with during a virtual-screening campaign based on receptor class and covalent warhead chemistry. In addition, we made a highlight on how covalent docking could be achieved using random conventional docking software. And lastly, we raised an alert on the growing erroneous molecular docking practices with covalent targets. Our aim is to guide scientists in the rational docking pursuit when dealing with covalent targets, as this will reduce false-positive results and also increase the reliability of their work for translational research.

Advanced approaches of developing targeted covalent drugs

In recent years, the development of targeted covalent inhibitors has gained popularity around the world. Specific groups (electrophilic warheads) form irreversible bonds with the side chain of nucleophilic amino acid residues, thus changing the function of biological targets such as proteins. Since the first targeted covalent inhibitor was disclosed in the 1990s, great efforts have been made to develop covalent ligands from known reversible leads or drugs by addition of tolerated electrophilic warheads. However, high reactivity and "off-target" toxicity remain challenging issues. This review covers the concept of targeted covalent inhibition to diseases, discusses traditional and interdisciplinary strategies of cysteine-focused covalent drug discovery, and exhibits newly disclosed electrophilic warheads majorly targeting the cysteine residue. Successful applications to address the challenges of designing effective covalent drugs are also introduced.

Interaction of the new inhibitor paxlovid (PF-07321332) and ivermectin with the monomer of the main protease SARS-CoV-2: A volumetric study based on molecular dynamics, elastic networks, classical thermodynamics and SPT

The COVID-19 pandemic has accelerated the study of drugs, most notably ivermectin and more recently Paxlovid (PF-07321332) which is in phase III clinical trials with experimental data showing covalent binding to the viral protease M^pro. Theoretical developments of catalytic site-directed docking support thermodynamically feasible non-covalent binding to M^pro. Here we show that Paxlovid binds non-covalently at regions other than the catalytic sites with energies stronger than reported and at the same binding site as the ivermectin B1a homologue, all through theoretical methodologies, including blind docking. We volumetrically characterize the non-covalent interaction of the ivermectin homologues (avermectins B1a and B1b) and Paxlovid with the mM^pro monomer, through molecular dynamics and scaled particle theory (SPT). Using the fluctuation-dissipation theorem (FDT), we estimated the electric dipole moment fluctuations at the surface of each of complex involved in this study, with similar trends to that observed in the interaction volume. Using fluctuations of the intrinsic volume and the number of flexible fragments of proteins using anisotropic and Gaussian elastic networks (ANM+GNM) suggests the complexes with ivermectin are more dynamic and flexible than the unbound monomer. In contrast, the binding of Paxlovid to mM^pro shows that the mM^pro-PF complex is the least structurally dynamic of all the species measured in this investigation. The results support a differential molecular mechanism of the ivermectin and PF homologues in the mM^pro monomer. Finally, the results showed that Paxlovid despite beingbound in different sites through covalent or non-covalent forms behaves similarly in terms of its structural flexibility and volumetric behaviour.

Covalent Antiviral Agents

Nowadays, many viral infections have emerged and are taking a huge toll on human lives globally. Meanwhile, viral resistance to current drugs has drastically increased. Hence, there is a pressing need to design potent broad-spectrum antiviral agents to treat a variety of viral infections and overcome viral resistance. Covalent inhibitors have the potential to achieve both goals owing to their biochemical efficiency, prolonged duration of action, and the capability to inhibit shallow, solvent-exposed substrate-binding domains. In this chapter, we review the structures, activities, and inhibition mechanisms of covalent inhibitors against severe acute respiratory syndrome coronavirus 2, dengue virus, enterovirus, hepatitis C virus, human immunodeficiency virus, and influenza viruses. We also discuss the application of in silico study in covalent inhibitor design.

An in-silico layer-by-layer adsorption study of the interaction between Rebaudioside A and the T1R2 human sweet taste receptor: modelling and biosensing perspectives

The human sweet taste receptor (T1R2) monomer-a member of the G-protein coupled receptor family that detects a wide variety of chemically and structurally diverse sweet tasting molecules, is known to pose a significant threat to human health. Protein that lack crystal structure is a challenge in structure-based protein design. This study focused on the interaction of the T1R2 monomer with rebaudioside A (Reb-A), a steviol glycoside with potential use as a natural sweetener using in-silico and biosensing methods. Herein, homology modelling, docking studies, and molecular dynamics simulations were applied to elucidate the interaction between Reb-A and the T1R2 monomer. In addition, the electrochemical sensing of the immobilised T1R2-Reb-A complex with zinc oxide nanoparticles (ZnONPs) and graphene oxide (GO) were assessed by testing the performance of multiwalled carbon nanotube (MWCNT) as an adsorbent experimentally. Results indicate a strong interaction between Reb-A and the T1R2 receptor, revealing the stabilizing interaction of the amino acids with the Reb-A by hydrogen bonds with the hydroxyl groups of the glucose moieties, along with a significant amount of hydrophobic interactions. Moreover, the presence of the MWCNT as an anchor confirms the adsorption strength of the T1R2-Reb-A complex onto the GO nanocomposite and supported with electrochemical measurements. Overall, this study could serve as a cornerstone in the development of electrochemical immunosensor for the detection of Reb-A, with applications in the food industry.

Virtual screening-guided discovery of thioredoxin reductase inhibitors

The selenoprotein thioredoxin reductase (TXNRD) is a promising therapeutic target for cancer. To discover novel TXNRD inhibitors, a library of α, β-unsaturated carbonyl compounds were applied in structure-based virtual screening for the selection of hit compounds. Fifteen top-ranked compounds were further validated experimentally, exhibiting potent inhibition of TXNRD and remarkable cytotoxicity to cancer cells. The further binding mode analysis indicated that multiple noncovalent interactions between the inhibitors and the active pocket of TXNRD facilitated the formation of covalent bonds between the Sec498 on TXNRD and the α, β-unsaturated carbonyl groups on inhibitors. Results from both simulations and experiments demonstrated that Sec498 is the prime interaction site for the inhibition of TXNRD. Taking compound 7 as an example, the inhibition of TXNRD by compounds promoted oxidative stress-mediated apoptosis of cancer cells. Given these findings, novel TXNRD inhibitors may be discovered and introduced to the growing fields of small molecule drugs against TXNRD.

Covalent simulations of covalent/irreversible enzyme inhibition in drug discovery: a reliable technical protocol

Aim: Irreversible covalent inhibition of biological targets in disease pathogenesis is an emerging field in drug design. Computational techniques have assumed a critical role in understanding covalent enzyme inhibition. However, a gap currently exists with regards to the reliability and reproducibility of currently available protocols available in literature and open scientific forums. Methodology/results: Appropriate ligand and protein target are selected, docked covalently or noncovalently using respective docking tools. Both components are subjected to premolecular dynamic preparations. This was followed by parameterization of the ligand, protein and covalent complex, respectively. The production runs were initiated and the resulting trajectories are saved and analyzed. Conclusion: This protocol is reliable and reproducible, hence would advance the development of irreversible covalent inhibitors toward disease treatment.

Docking of Covalent Ligands: Challenges and Approaches

Covalent ligands have recently regained considerable attention in drug discovery. The rational design of such ligands, however, is still faced with particular challenges, mostly related to the fact that covalent bond formation is a quantum mechanical phenomenon which cannot adequately be handled by the force fields or empirical approaches typically used for noncovalent protein-ligand interactions. Although the necessity for quantum chemical approaches is clear, they cannot yet routinely be applied on large data sets of ligands or for a broader exploration of binding modes in docking calculations. On the other hand, technical solutions for performing docking calculations with covalent ligands are available, but their scope is normally quite limited. Scoring functions typically neglect the contribution from covalent bond formation completely. In this situation, the question arises how to approach covalent ligands and which methods to choose for their docking and design.

Road Map for the Structure-Based Design of Selective Covalent HCV NS3/4A Protease Inhibitors

Over the last 2 decades, covalent inhibitors have gained much popularity and is living up to its reputation as a powerful tool in drug discovery. Covalent inhibitors possess many significant advantages including increased biochemical efficiency, prolonged duration and the ability to target shallow, solvent exposed substrate-binding domains. However, rapidly mounting concerns over the potential toxicity, highly reactive nature and general lack of selectivity have negatively impacted covalent inhibitor development. Recently, a great deal of emphasis by the pharmaceutical industry has been placed toward the development of novel approaches to alleviate the major challenges experienced through covalent inhibition. This has unexpectedly led to the emergence of "selective" covalent inhibitors. The purpose of this review is not only to provide an overview from literature but to introduce a technical guidance as to how to initiate a systematic "road map" for the design of selective covalent inhibitors which we believe may assist in the design and development of optimized potential selective covalent HCV NS3/4A viral protease inhibitors.

Covalent inhibitors design and discovery

In the history of therapeutics, covalent drugs occupy a very distinct category. While representing a significant fraction of the drugs on the market, very few have been deliberately designed to interact covalently with their biological target. In this review, the prevalence of covalent drugs will first be briefly covered, followed by an introduction to their mechanisms of action and more detailed discussions of their discovery and the development of safe and efficient covalent enzyme inhibitors. All stages of a drug discovery program will be covered, from target considerations to lead optimization, strategies to tune reactivity and computational methods. The goal of this article is to provide an overview of the field and to outline good practices that are needed for the proper assessment and development of covalent inhibitors as well as a good understanding of the potential and limitations of current computational methods for the design of covalent drugs.

2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors

Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% by using independent set test. Then, in the 3D-QSAR model, the model with q² = 0.565 (cross-validated correlation coefficient) and r² = 0.888 (non-cross-validated correlation coefficient) was built to predict the activity of EGFR inhibitors. The mean absolute error (MAE) of the training set and test set was 0.308 log units and 0.526 log units, respectively. In addition, molecular docking was also employed to investigate the interaction between EGFR inhibitors and EGFR.

Theory and applications of covalent docking in drug discovery: merits and pitfalls

The present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed some significant advantages over non-covalent inhibitors such as covalent warheads can target rare, non-conserved residue of a particular target protein and thus led to development of highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with shallow binding cleavage which will led to development of novel inhibitors with increased potency than non-covalent inhibitors. Several computational approaches have been developed to simulate covalent interactions; however, this is still a challenging area to explore. Covalent molecular docking has been recently implemented in the computer-aided drug design workflows to describe covalent interactions between inhibitors and biological targets. In this review we highlight: (i) covalent interactions in biomolecular systems; (ii) the mathematical framework of covalent molecular docking; (iii) implementation of covalent docking protocol in drug design workflows; (iv) applications covalent docking: case studies and (v) shortcomings and future perspectives of covalent docking. To the best of our knowledge; this review is the first account that highlights different aspects of covalent docking with its merits and pitfalls. We believe that the method and applications highlighted in this study will help future efforts towards the design of irreversible inhibitors.

Discovery of novel covalent proteasome inhibitors through a combination of pharmacophore screening, covalent docking, and molecular dynamics simulations

The ubiquitin-proteasome pathway plays a pivotal role in the regulation of cellular protein processing and degradation. Proteasome inhibitors (PIs) have enormous potential to treat multiple myeloma, solid tumors, parasites, inflammation, and immune diseases, which is spurring the development of new types of PIs with enhanced efficacy, fewer side effects, and reduced drug resistance. Nevertheless, virtual screening for covalent PIs has rarely been reported because calculating the covalent binding energy is a challenging task. The aim of this study was to discover new covalent inhibitors of the 20S proteasome. The structures of PIs were manually divided into two parts: a noncovalent binding part resulting from virtual screening, and an epoxyketone group that was pre-selected as a covalent binding part. The SPECS database was screened by noncovalent docking and a pharmacophore model built with the 20S proteasome. After validating the covalent conjugation, 88 hits with epoxyketone were covalently docked into the 20S proteasome to analyze the intermolecular interactions. Four compounds were selected after multiple filtration and validations. Molecular dynamics simulations were performed to check the stability of the noncovalent and covalent docked ligand-enzyme complexes and investigate the interaction patterns of the screened inhibitors. Finally, two compounds with novel aromatic backbones, reasonable interactions, and stable covalent binding modes were retained. These compounds can serve as potential hits for further biological evaluation.