Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking.

Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and machine-learning-based binding pocket detection with the ensemble-based ligand docking and binding free energy analysis to characterize the potential allosteric binding sites and determine structural and energetic determinants of allosteric inhibition for a series of experimentally validated allosteric molecules. The results demonstrate a good agreement between computational and experimental binding affinities, providing support to the predicted binding modes and suggesting key interactions formed by the allosteric ligands to elicit the experimentally observed inhibition. We establish structural and energetic determinants of allosteric binding for the experimentally known allosteric molecules, indicating a potential mechanism of allosteric modulation by targeting the hinges of the inter-protomer movements and blocking conformational changes between the closed and open spike trimer forms. The results of this study demonstrate that combining ensemble-based ligand docking with conformational states of spike protein and rigorous binding energy analysis enables robust characterization of the ligand binding modes, the identification of allosteric binding hotspots, and the prediction of binding affinities for validated allosteric modulators, which is consistent with the experimental data. This study suggested that the conformational adaptability of the protein allosteric sites and the diversity of ligand bound conformations are both in play to enable efficient targeting of allosteric binding sites and interfere with the conformational changes.

Computational insights into allosteric inhibition of focal adhesion kinase: A combined pharmacophore modeling and molecular dynamics approach.

Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase that modulates integrin and growth factor signaling pathways and is implicated in cancer cell migration, proliferation, and survival. Over the past decade various, FAK kinase, FERM, and FAT domain inhibitors have been reported and a few kinase domain inhibitors are under clinical consideration. However, few of them were identified as multikinase inhibitors. In kinase drug design selectivity is always a point of concern, to improve selectivity allosteric inhibitor development is the best choice. The current research utilized a pharmacophore modeling (PM) approach to identify novel allosteric inhibitors of FAK. The all-available allosteric inhibitor bound 3D structures with PDB ids 4EBV, 4EBW, and 4I4F were utilized for the pharmacophore modeling. The validated PM models were utilized to map a database of 770,550 compounds prepared from ZINC, EXIMED, SPECS, ASINEX, and InterBioScreen, aiming to identify potential allosteric inhibitors. The obtained compounds from screening step were forwarded to molecular docking (MD) for the prediction of binding orientation inside the allosteric site and the results were evaluated with the known FAK allosteric inhibitor (REF). Finally, 14 FAK-inhibitor complexes were selected from the docking study and were studied under molecular dynamics simulations (MDS) for 500 ns. The complexes were ranked according to binding free energy (BFE) and those demonstrated higher affinity for allosteric site of FAK than REF inhibitors were selected. The selected complexes were further analyzed for intermolecular interactions and finally, three potential allosteric inhibitor candidates for the inhibition of FAK protein were identified. We believe that identified scaffolds may help in drug development against FAK as an anticancer agent.

Allosteric Cholesterol Site in Glycine Receptors Characterized through Molecular Simulations.

Glycine receptors are pentameric ligand-gated ion channels that conduct chloride ions across postsynaptic membranes to facilitate fast inhibitory neurotransmission. In addition to gating by the glycine agonist, interactions with lipids and other compounds in the surrounding membrane environment modulate their function, but molecular details of these interactions remain unclear, in particular, for cholesterol. Here, we report coarse-grained simulations in a model neuronal membrane for three zebrafish glycine receptor structures representing apparent resting, open, and desensitized states. We then converted the systems to all-atom models to examine detailed lipid interactions. Cholesterol bound to the receptor at an outer-leaflet intersubunit site, with a preference for the open and desensitized versus resting states, indicating that it can bias receptor function. Finally, we used short atomistic simulations and iterative amino acid perturbations to identify residues that may mediate allosteric gating transitions. Frequent cholesterol contacts in atomistic simulations clustered with residues identified by perturbation analysis and overlapped with mutations influencing channel function and pathology. Cholesterol binding at this site was also observed in a recently reported pig heteromeric glycine receptor. These results indicate state-dependent lipid interactions relevant to allosteric transitions of glycine receptors, including specific amino acid contacts applicable to biophysical modeling and pharmaceutical design.

Py-CoMFA, docking, and molecular dynamics simulations of Leishmania (L.) amazonensis arginase inhibitors.

Leishmaniasis is a disease caused by a protozoan of the genus Leishmania, affecting millions of people, mainly in tropical countries, due to poor social conditions and low economic development. First-line chemotherapeutic agents involve highly toxic pentavalent antimonials, while treatment failure is mainly due to the emergence of drug-resistant strains. Leishmania arginase (ARG) enzyme is vital in pathogenicity and contributes to a higher infection rate, thus representing a potential drug target. This study helps in designing ARG inhibitors for the treatment of leishmaniasis. Py-CoMFA (3D-QSAR) models were constructed using 34 inhibitors from different chemical classes against ARG from L. (L.) amazonensis (LaARG). The 3D-QSAR predictions showed an excellent correlation between experimental and calculated pIC50 values. The molecular docking study identified the favorable hydrophobicity contribution of phenyl and cyclohexyl groups as substituents in the enzyme allosteric site. Molecular dynamics simulations of selected protein-ligand complexes were conducted to understand derivatives' interaction modes and affinity in both active and allosteric sites. Two cinnamide compounds, 7g and 7k, were identified, with similar structures to the reference 4h allosteric site inhibitor. These compounds can guide the development of more effective arginase inhibitors as potential antileishmanial drugs.

Gaining Insights into Key Structural Hotspots within the Allosteric Binding Pockets of Protein Kinases.

Protein kinases are essential regulators of cell function and represent one of the largest and most diverse protein families. They are particularly influential in signal transduction and coordinating complex processes like the cell cycle. Out of the 518 human protein kinases identified, 478 are part of a single superfamily sharing catalytic domains that are related in sequence. The dysregulation of protein kinases due to certain mutations has been associated with various diseases, including cancer. Although most of the protein kinase inhibitors identified as type I or type II primarily target the ATP-binding pockets of kinases, the structural and sequential resemblances among these pockets pose a significant challenge for selective inhibition. Therefore, targeting allosteric pockets that are beside highly conserved ATP pockets has emerged as a promising strategy to prevail current limitations, such as poor selectivity and drug resistance. In this article, we compared the binding pockets of various protein kinases for which allosteric (type III) inhibitors have already been developed. Additionally, understanding the structure and shape of existing ligands could aid in identifying key interaction sites within the allosteric pockets of kinases. This comprehensive review aims to facilitate the design of more effective and selective allosteric inhibitors.

Synthesis, In Vivo Anticonvulsant Activity Evaluation and In Silico Studies of Some Quinazolin-4(3H)-One Derivatives.

Two series, "a" and "b", each consisting of nine chemical compounds, with 2,3-disubstituted quinazolin-4(3H)-one scaffold, were synthesized and evaluated for their anticonvulsant activity. They were investigated as dual potential positive allosteric modulators of the GABAA receptor at the benzodiazepine binding site and inhibitors of carbonic anhydrase II. Quinazolin-4(3H)-one derivatives were evaluated in vivo (D1-3 = 50, 100, 150 mg/kg, administered intraperitoneally) using the pentylenetetrazole (PTZ)-induced seizure model in mice, with phenobarbital and diazepam, as reference anticonvulsant agents. The in silico studies suggested the compounds act as anticonvulsants by binding on the allosteric site of GABAA receptor and not by inhibiting the carbonic anhydrase II, because the ligands-carbonic anhydrase II predicted complexes were unstable in the molecular dynamics simulations. The mechanism targeting GABAA receptor was confirmed through the in vivo flumazenil antagonism assay. The pentylenetetrazole experimental anticonvulsant model indicated that the tested compounds, 1a-9a and 1b-9b, present a potential anticonvulsant activity. The evaluation, considering the percentage of protection against PTZ, latency until the onset of the first seizure, and reduction in the number of seizures, revealed more favorable results for the "b" series, particularly for compound 8b.

Structural Models for a Series of Allosteric Inhibitors of IGF1R Kinase.

The allosteric inhibition of insulin-like growth factor receptor 1 kinase (IGF1RK) is a potential strategy to overcome selectivity barriers for targeting receptor tyrosine kinases. We constructed structural models of a series of 12 indole-butyl-amine derivatives that have been reported as allosteric inhibitors of IGF1RK. We further studied the dynamics and interactions of each inhibitor in the allosteric pocket via all-atom explicit-solvent molecular dynamics (MD) simulations. We discovered that a bulky carbonyl substitution at the R1 indole ring is structurally unfavorable for inhibitor binding in the IGF1RK allosteric pocket. Moreover, we found that the most potent derivative (termed C11) acquires a distinct conformation: forming an allosteric pocket channel with better shape complementarity and interactions with the receptor. In addition to a hydrogen-bonding interaction with V1063, the cyano derivative C11 forms a stable hydrogen bond with M1156, which is responsible for its unique binding conformation in the allosteric pocket. Our findings show that the positioning of chemical substituents with different pharmacophore features at the R1 indole ring influences molecular interactions and binding conformations of indole-butyl-amine derivatives and, hence, dramatically affects their potencies. Our results provide a structural framework for the design of allosteric inhibitors with improved affinities and specificities against IGF1RK.

G protein-coupled receptors (GPCRs): advances in structures, mechanisms, and drug discovery.

G protein-coupled receptors (GPCRs), the largest family of human membrane proteins and an important class of drug targets, play a role in maintaining numerous physiological processes. Agonist or antagonist, orthosteric effects or allosteric effects, and biased signaling or balanced signaling, characterize the complexity of GPCR dynamic features. In this study, we first review the structural advancements, activation mechanisms, and functional diversity of GPCRs. We then focus on GPCR drug discovery by revealing the detailed drug-target interactions and the underlying mechanisms of orthosteric drugs approved by the US Food and Drug Administration in the past five years. Particularly, an up-to-date analysis is performed on available GPCR structures complexed with synthetic small-molecule allosteric modulators to elucidate key receptor-ligand interactions and allosteric mechanisms. Finally, we highlight how the widespread GPCR-druggable allosteric sites can guide structure- or mechanism-based drug design and propose prospects of designing bitopic ligands for the future therapeutic potential of targeting this receptor family.

[Computer-aided prediction and molecular mechanism investigation of active components in compound Kushen injection inhibiting p21-activated kinase 1].

Targeting p21-activated kinase 1 (PAK1) is a novel strategy for pancreatic cancer treatment. Compound Kushen injection contains many anti-pancreatic cancer components, but the specific targets are unknown. In this study, 14α-hydroxymatrine, an active component of Kushen injection, was found to possess high binding free energy with the allosteric site of PAK1 by molecular docking based virtual screening. Molecular dynamics simulations suggested that 14α-hydroxymatrine caused the α1 and α2 helices of the allosteric site of PAK1 to extend outward to form a deep allosteric regulatory pocket. Meanwhile, 14α-hydroxymatrine induced the ß-folding region at the adenosine triphosphate (ATP)-binding pocket of PAK1 to close inward, resulting in the ATP-binding pocket in a "semi-closed" state which caused the inactivation of PAK1. After removal of 14α-hydroxymatrine, PAK1 showed a tendency to change from the inactive conformation to the active conformation. We supposed that 14α-hydroxymatrine of compound Kushen injection might be a reversible allosteric inhibitor of PAK1. This study used modern technologies and methods to study the active components of traditional Chinese medicine, which laid a foundation for the development and utilization of natural products and the search for new treatments for pancreatic cancer.

Bitter taste receptor activation by cholesterol and an intracellular tastant.

Bitter taste sensing is mediated by type 2 taste receptors (TAS2Rs (also known as T2Rs)), which represent a distinct class of G-protein-coupled receptors1. Among the 26 members of the TAS2Rs, TAS2R14 is highly expressed in extraoral tissues and mediates the responses to more than 100 structurally diverse tastants2-6, although the molecular mechanisms for recognizing diverse chemicals and initiating cellular signalling are still poorly understood. Here we report two cryo-electron microscopy structures for TAS2R14 complexed with Ggust (also known as gustducin) and Gi1. Both structures have an orthosteric binding pocket occupied by endogenous cholesterol as well as an intracellular allosteric site bound by the bitter tastant cmpd28.1, including a direct interaction with the α5 helix of Ggust and Gi1. Computational and biochemical studies validate both ligand interactions. Our functional analysis identified cholesterol as an orthosteric agonist and the bitter tastant cmpd28.1 as a positive allosteric modulator with direct agonist activity at TAS2R14. Moreover, the orthosteric pocket is connected to the allosteric site via an elongated cavity, which has a hydrophobic core rich in aromatic residues. Our findings provide insights into the ligand recognition of bitter taste receptors and suggest activities of TAS2R14 beyond bitter taste perception via intracellular allosteric tastants.

Discovery and development of novel 10,12-disubstituted aloperine derivatives against HCoV-OC43 by targeting allosteric site of host TMPRSS2.

By inducing steric activation of the 10CH bond with a 12-acyl group to form a key imine oxime intermediate, 20 novel (10S)-10,12-disubstituted aloperine derivatives were successfully synthesized and assessed for their antiviral efficacy against HCoV-OC43. Of them, compound 3i exhibited the moderate activities against HCoV-OC43, as well as against the SARS-CoV-2 variant EG.5.1 with the comparable EC50 values of 4.7 and 4.1 µM. A mechanism study revealed that it inhibited the protease activity of host TMPRSS2 by binding to an allosteric site, rather than the known catalytic center, different from that of camostat. Also, the combination of compound 3i and molnupiravir, as an RdRp inhibitor, showed an additive antiviral effect against HCoV-OC43. The results provide a new binding mode and lead compound for targeting TMPRSS2, with an advantage in combating broad-spectrum coronavirus.

Identifying and Assessing Putative Allosteric Sites and Modulators for CXCR4 Predicted through Network Modeling and Site Identification by Ligand Competitive Saturation.

The chemokine receptor CXCR4 is a critical target for the treatment of several cancer types and HIV-1 infections. While orthosteric and allosteric modulators have been developed targeting its extracellular or transmembrane regions, the intramembrane region of CXCR4 may also include allosteric binding sites suitable for the development of allosteric drugs. To investigate this, we apply the Gaussian Network Model (GNM) to the monomeric and dimeric forms of CXCR4 to identify residues essential for its local and global motions located in the hinge regions of the protein. Residue interaction network (RIN) analysis suggests hub residues that participate in allosteric communication throughout the receptor. Mutual residues from the network models reside in regions with a high capacity to alter receptor dynamics upon ligand binding. We then investigate the druggability of these potential allosteric regions using the site identification by ligand competitive saturation (SILCS) approach, revealing two putative allosteric sites on the monomer and three on the homodimer. Two screening campaigns with Glide and SILCS-Monte Carlo docking using FDA-approved drugs suggest 20 putative hit compounds including antifungal drugs, anticancer agents, HIV protease inhibitors, and antimalarial drugs. In vitro assays considering mAB 12G5 and CXCL12 demonstrate both positive and negative allosteric activities of these compounds, supporting our computational approach. However, in vivo functional assays based on the recruitment of ß-arrestin to CXCR4 do not show significant agonism and antagonism at a single compound concentration. The present computational pipeline brings a new perspective to computer-aided drug design by combining conformational dynamics based on network analysis and cosolvent analysis based on the SILCS technology to identify putative allosteric binding sites using CXCR4 as a showcase.

Identification of two novel chemical classes of Autotaxin (ATX) inhibitors using Enalos Asclepios KNIME nodes.

Autotaxin is a secreted lysophospholipase D which is a member of the ectonucleotide pyrophosphatase/phosphodiesterase family converting extracellular lysophosphatidylcholine and other non-choline lysophospholipids, such as lysophosphatidylethanolamine and lysophosphatidylserine, to the lipid mediator lysophosphatidic acid. Autotaxin is implicated in various fibroproliferative diseases including interstitial lung diseases, such as idiopathic pulmonary fibrosis and hepatic fibrosis, as well as in cancer. In this study, we present an effort of identifying ATX inhibitors that bind to allosteric ATX binding sites using the Enalos Asclepios KNIME Node. All the available PDB crystal structures of ATX were collected, prepared, and aligned. Visual examination of these structures led to the identification of four crystal structures of human ATX co-crystallized with four known inhibitors. These inhibitors bind to five binding sites with five different binding modes. These five binding sites were thereafter used to virtually screen a compound library of 14,000 compounds to identify molecules that bind to allosteric sites. Based on the binding mode and interactions, the docking score, and the frequency that a compound comes up as a top-ranked among the five binding sites, 24 compounds were selected for in vitro testing. Finally, two compounds emerged with inhibitory activity against ATX in the low micromolar range, while their mode of inhibition and binding pattern were also studied. The two derivatives identified herein can serve as "hits" towards developing novel classes of ATX allosteric inhibitors.

Synergizing structure and function: Cinnamoyl hydroxamic acids as potent urease inhibitors.

The current investigation encompasses the structural planning, synthesis, and evaluation of the urease inhibitory activity of a series of molecular hybrids of hydroxamic acids and Michael acceptors, delineated from the structure of cinnamic acids. The synthesized compounds exhibited potent urease inhibitory effects, with IC50 values ranging from 3.8 to 12.8 µM. Kinetic experiments unveiled that the majority of the synthesized hybrids display characteristics of mixed inhibitors. Generally, derivatives containing electron-withdrawing groups on the aromatic ring demonstrate heightened activity, indicating that the increased electrophilicity of the beta carbon in the Michael Acceptor moiety positively influences the antiureolytic properties of this compounds class. Biophysical and theoretical investigations further corroborated the findings obtained from kinetic assays. These studies suggest that the hydroxamic acid core interacts with the urease active site, while the Michael acceptor moiety binds to one or more allosteric sites adjacent to the active site.

A three-level regulatory mechanism of the aldo-keto reductase subfamily AKR12D.

Modulation of protein function through allosteric regulation is central in biology, but biomacromolecular systems involving multiple subunits and ligands may exhibit complex regulatory mechanisms at different levels, which remain poorly understood. Here, we discover an aldo-keto reductase termed AKRtyl and present its three-level regulatory mechanism. Specifically, by combining steady-state and transient kinetics, X-ray crystallography and molecular dynamics simulation, we demonstrate that AKRtyl exhibits a positive synergy mediated by an unusual Monod-Wyman-Changeux (MWC) paradigm of allosteric regulation at low concentrations of the cofactor NADPH, but an inhibitory effect at high concentrations is observed. While the substrate tylosin binds at a remote allosteric site with positive cooperativity. We further reveal that these regulatory mechanisms are conserved in AKR12D subfamily, and that substrate cooperativity is common in AKRs across three kingdoms of life. This work provides an intriguing example for understanding complex allosteric regulatory networks.

Probe Substrate Dependencies in CYP3A4 Allosteric Inhibition: A Novel Molecular Mechanism Involving F-F' Loop Perturbations.

The biochemical basis for substrate dependences in apparent inhibition constant values (Ki) remains unknown. Our study aims to elucidate plausible structural determinants underpinning these observations. In vitro steady-state inhibition assays conducted using human recombinant CYP3A4 enzyme and testosterone substrate revealed that fibroblast growth factor receptor (FGFR) inhibitors erdafitinib and pemigatinib noncompetitively inhibited CYP3A4 with apparent Ki values of 10.2 ± 1.1 and 3.3 ± 0.9 µM, respectively. However, when rivaroxaban was adopted as the probe substrate, there were 2.0- and 3.2-fold decreases in its apparent Ki values. To glean mechanistic insights into this phenomenon, erdafitinib and pemigatinib were docked to allosteric sites in CYP3A4. Subsequently, molecular dynamics (MD) simulations of apo- and holo-CYP3A4 were conducted to investigate the structural changes induced. Comparative structural analyses of representative MD frames extracted by hierarchical clustering revealed that the allosteric inhibition of CYP3A4 by erdafitinib and pemigatinib did not substantially modulate its active site characteristics. In contrast, we discovered that allosteric binding of the FGFR inhibitors reduces the structural flexibility of the F-F' loop region, an important gating mechanism to regulate access of the substrate to the catalytic heme. We surmised that the increased rigidity of the F-F' loop engenders a more constrained entrance to the CYP3A4 active site, which in turn impedes access to the larger rivaroxaban molecule to a greater extent than testosterone and culminates in more potent inhibition of its CYP3A4-mediated metabolism. Our findings suggest a potential mechanism to rationalize probe substrate dependencies in Ki arising from the allosteric noncompetitive inhibition of CYP3A4.

Fragment-Based Discovery of Allosteric Inhibitors of SH2 Domain-Containing Protein Tyrosine Phosphatase-2 (SHP2).

The ubiquitously expressed protein tyrosine phosphatase SHP2 is required for signaling downstream of receptor tyrosine kinases (RTKs) and plays a role in regulating many cellular processes. Genetic knockdown and pharmacological inhibition of SHP2 suppresses RAS/MAPK signaling and inhibit the proliferation of RTK-driven cancer cell lines. Here, we describe the first reported fragment-to-lead campaign against SHP2, where X-ray crystallography and biophysical techniques were used to identify fragments binding to multiple sites on SHP2. Structure-guided optimization, including several computational methods, led to the discovery of two structurally distinct series of SHP2 inhibitors binding to the previously reported allosteric tunnel binding site (Tunnel Site). One of these series was advanced to a low-nanomolar lead that inhibited tumor growth when dosed orally to mice bearing HCC827 xenografts. Furthermore, a third series of SHP2 inhibitors was discovered binding to a previously unreported site, lying at the interface of the C-terminal SH2 and catalytic domains.

Computational insights into diverse binding modes of the allosteric modulator and their regulation on dopamine D1 receptor.

Allosteric drugs hold the promise of addressing many challenges in the current drug development of GPCRs. However, the molecular mechanism underlying their allosteric modulations remain largely elusive. The dopamine D1 receptor (DRD1), a member of Class A GPCRs, is critical for treating psychiatric disorders, and LY3154207 serves as its promising positive allosteric modulator (PAM). In the work, we utilized extensive Gaussian-accelerated molecular dynamics simulations (a total of 41µs) for the first time probe the diverse binding modes of the allosteric modulator and their regulation effects, based on the DRD1 and LY3154207 as representative. Our simulations identify four binding modes of LY3154207 (one boat mode, two metastable vertical modes and a novel cleft-anchored mode), in which the boat mode is the most stable while there three modes are similar in the stability. However, it is interesting to observed that the most stable boat mode inversely exhibits the weakest positive allosteric effect on influencing the orthosteric ligand binding and maintaining the activity of the transducer binding site. It should result from its induced weaker correlation between the allosteric site and the orthosteric site, and between the orthosteric site and the transducer binding site than the other three binding modes, as well as its weakened interaction between a crucial activation-related residue (S2025.46) and the orthosteric ligand (dopamine). Overall, the work offers atomic-level information to advance our understanding of the complex allosteric regulation on GPCRs, which is beneficial to the allosteric modulator design and development.

A comprehensive survey on protein-ligand binding site prediction.

Protein-ligand binding site prediction is critical for protein function annotation and drug discovery. Biological experiments are time-consuming and require significant equipment, materials, and labor resources. Developing accurate and efficient computational methods for protein-ligand interaction prediction is essential. Here, we summarize the key challenges associated with ligand binding site (LBS) prediction and introduce recently published methods from their input features, computational algorithms, and ligand types. Furthermore, we investigate the specificity of allosteric site identification as a particular LBS type. Finally, we discuss the prospective directions for machine learning-based LBS prediction in the near future.

NMR tools to detect protein allostery.

Allostery is a fundamental mechanism of cellular homeostasis by intra-protein communication between distinct functional sites. It is an internal process of proteins to steer interactions not only with each other but also with other biomolecules such as ligands, lipids, and nucleic acids. In addition, allosteric regulation is particularly important in enzymatic activities. A major challenge in structural and molecular biology today is unraveling allosteric sites in proteins, to elucidate the detailed mechanism of allostery and the development of allosteric drugs. Here we summarize the recently developed tools and approaches which enable the elucidation of regulatory hotspots and correlated motion in biomolecules, focusing primarily on solution-state nuclear magnetic resonance spectroscopy (NMR). These tools open an avenue towards a rational understanding of the mechanism of allostery and provide essential information for the design of allosteric drugs.