Binding Site Flexibility Research Articles

A Computational Pipeline Observes the Flexibility and Dynamics of Plant Cytochrome P450 Binding Sites.

Binding site flexibility and dynamics strongly affect the ability of proteins to accommodate substrates and inhibitors. The significance of these properties is particularly pronounced for proteins that are inherently flexible, such as cytochrome P450 enzymes (CYPs). While the research on human CYPs provides detailed knowledge on both structural and functional level, such analyses are still lacking for their plant counterparts. This study aims to bridge this gap. We developed a novel computational pipeline consisting of two steps. Firstly, we use molecular dynamics (MD) simulations to capture the full conformational ensemble for a certain plant CYP. Subsequently, we developed and applied a comprehensive methodology to analyze a number of binding site properties-size, flexibility, shape, hydrophobicity, and accessibility-using the fpocket and mdpocket packages on MD-generated trajectories. The workflow was validated on human CYPs 1A2, 2A6, and 3A4, as their binding site characteristics are well known. Not only could we confirm known binding site properties, but we also identified and named previously unseen binding site channels for CYPs 1A2 and 2A6. The pipeline was then applied to plant CYPs, leading to the first categorization of 15 chosen plant CYPs based on their binding site's (dis)similarities. This study provides a foundation for the largely uncharted fields of plant CYP substrate specificity and facilitates a more precise understanding of their largely unknown specific biological functions. It offers new insights into the structural and functional dynamics of plant CYPs, which may facilitate a more accurate understanding of the fate of agrochemicals or the biotechnological design and exploitation of enzymes with specific functions. Additionally, it serves as a reference for future structural-functional analyses of CYP enzymes across various biological kingdoms.

Modeling of noncovalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-2 considering the protein flexibility by using molecular dynamics and cross-docking.

The papain-like protease (PLpro) found in coronaviruses that can be transmitted from animals to humans is a critical target in respiratory diseases linked to Severe Acute Respiratory Syndrome (SARS-CoV). Researchers have proposed designing PLpro inhibitors. In this study, a set of 89 compounds, including recently reported 2-phenylthiophenes with nanomolar inhibitory potency, were investigated as PLpro noncovalent inhibitors using advanced molecular modeling techniques. To develop the work with these inhibitors, multiple structures of the SARS-CoV-2 PLpro binding site were generated using a molecular sampling method. These structures were then clustered to select a group that represents the flexibility of the site. Subsequently, models of the protein-ligand complexes were created for the set of inhibitors within the chosen conformations. The quality of the complex models was assessed using LigRMSD software to verify similarities in the orientations of the congeneric series and interaction fingerprints to determine the recurrence of chemical interactions. With the multiple models constructed, a protocol was established to choose one per ligand, optimizing the correlation between the calculated docking energy values and the biological activities while incorporating the effect of the binding site's flexibility. A strong correlation (R2 = 0.922) was found when employing this flexible docking protocol.

Flexibility of Binding Site is Essential to the Ca2+ Selectivity in EF-Hand Calcium-Binding Proteins.

High binding affinity and selectivity of metal ions are essential to the function of metalloproteins. Thus, understanding the factors that determine these binding characteristics is of major interest for both fundamental mechanistic investigations and guiding of the design of novel metalloproteins. In this work, we perform QM cluster model calculations and quantum mechanics/molecular mechanics (QM/MM) free energy simulations to understand the binding selectivity of Ca2+ and Mg2+ in the wild-type carp parvalbumin and its mutant. While a nonpolarizable MM model (CHARMM36) does not lead to the correct experimental trend, treatment of the metal binding site with the DFTB3 model in a QM/MM framework leads to relative binding free energies (ΔΔGbind) comparable with experimental data. For the wild-type (WT) protein, the calculated ΔΔGbind is ∼6.6 kcal/mol in comparison with the experimental value of 5.6 kcal/mol. The good agreement highlights the value of a QM description of the metal binding site and supports the role of electronic polarization and charge transfer to metal binding selectivity. For the D51A/E101D/F102W mutant, different binding site models lead to considerable variations in computed binding affinities. With a coordination number of seven for Ca2+, which is shown by QM/MM metadynamics simulations to be the dominant coordination number for the mutant, the calculated relative binding affinity is ∼4.8 kcal/mol, in fair agreement with the experimental value of 1.6 kcal/mol. The WT protein is observed to feature a flexible binding site that accommodates a range of coordination numbers for Ca2+, which is essential to the high binding selectivity for Ca2+ over Mg2+. In the mutant, the E101D mutation reduces the flexibility of the binding site and limits the dominant coordination number of Ca2+ to be seven, thereby leading to reduced binding selectivity against Mg2+. Our results highlight that the binding selectivity of metal ions depends on both the structural and dynamical properties of the protein binding site.

Avian cryptochrome 4 binds superoxide

Flavin-binding cryptochromes are blue-light sensitive photoreceptors that have been implicated with magnetoreception in some species. The photocycle involves an intra-protein photo-reduction of the flavin cofactor, generating a magnetosensitive radical pair, and its subsequent re-oxidation. Superoxide (O2•−) is generated in the re-oxidation with molecular oxygen. The resulting O2•−-containing radical pairs have also been hypothesised to underpin various magnetosensitive traits, but due to fast spin relaxation when tumbling in solution would require immobilisation. We here describe our insights in the binding of superoxide to cryptochrome 4 from C. livia based on extensive all-atom molecular dynamics studies and density-functional theory calculations. The positively charged “crypt” region that leads to the flavin binding pocket transiently binds O2•− at 5 flexible binding sites centred on arginine residues. Typical binding times amounted to tens of nanoseconds, but exceptional binding events extended to several hundreds of nanoseconds and slowed the rotational diffusion, thereby realising rotational correlation times as large as 1 ns. The binding sites are particularly efficient in scavenging superoxide escaping from a putative generation site close to the flavin-cofactor, possibly implying a functional relevance. We discuss our findings in view of a potential magnetosensitivity of biological flavin semiquinone/superoxide radical pairs.

Deciphering insights into the binding mechanism and plasticity of Telacebec with M. tuberculosis cytochrome bcc-aa3 supercomplex through an unbiased molecular dynamics simulation, free-energy analysis, and DFT study

The cytochrome bcc-aa3 supercomplex, a key component in the electron transport chain pathway involved in bacterial energy production and homeostasis, is a clinically validated target for tuberculosis (TB), leading to Telacebec (Q203). Telacebec is a potent candidate drug under Phase II clinical development for the treatment of drug-sensitive and drug-resistant TB. Recently, the cryo-electron microscopy structure of this supercomplex from Mycobacterium tuberculosis (Mtb) complexed with Q203 was resolved at 6.9 Å resolution (PDB ID: 7E1W). To understand the binding site (QP site) flexibility and Q203’s stability at the QP site of the Mtb cytochrome bcc complex, we conducted molecular dynamics (MD) simulation and free energy analysis on this complex in an explicit hydrated lipid bilayer environment for 500 ns. Through this study, the persistence of a range of direct and indirect interactions was observed over the course of the simulation. The significance of the interactions with His375, Tyr161, Ala178, Ala179, Ile183, His355, Leu356, and Thr313 is underlined. Electrostatic energy was the primary source of the net binding free energy, regardless of the important interacting residues. The overall binding free energy for Q203 was −112.84 ± 7.73 kcal/mol, of which the electrostatic and lipophilic energy contributions were −116.31 ± 1.14 and −21.32 ± 2.35 kcal/mol, respectively. Meanwhile, DFT calculations were utilized to elucidate Q203’s molecular properties. Overall, this study deciphers key insights into the cytochrome bcc-aa3 supercomplex with Q203 on the ground of molecular mechanics and quantum mechanics that may facilitate structure-based drug design and optimization for the discovery of the next-generation antitubercular drug(s). Communicated by Ramaswamy H. Sarma

Cooperative Bimetallic Co−Mn Catalyst: Exploiting Metallo‐Organic and Hydrogen Bonded Interactions for Rechargeable C‐/N‐Alkylation

AbstractDespite the progress on cobalt and manganese catalyzed C−C and C−N bond‐forming methodologies, the associated catalyst reusability remains with some unresolved issue, which needs to be addressed. Disclosed herein, a flexible multidentate proton‐responsive ligand (L) bearing 2,6‐bis(1H‐benzo[d]imidazol‐2‐yl)pyridine (BBP), 6‐(1H‐benzo[d]imidazol‐2‐yl)picolinic acid (BPA), and benzene‐1,2‐diamine (BDA) for Co/Mn‐based mono‐ and bi‐metallic supramolecular materials for C‐/N‐alkylation of alcohols. The flexible binding sites and different hydrogen bond donor‐acceptor fragments of L brings the rigidity and self‐assembling to ordered crystalline supramolecular materials, which prevented the coordinatively saturated active sites and thus providing much higher reaction efficiency and selectivity, which is highly unlikely in the case of comparable individual components. The easy synthesis, efficient reactivity and selectivity through cooperativity, broad substrate scope, and efficient recycling via recharging of metals make the catalyst and the protocol economical and sustainable. Importantly, the design strategy based on metallo‐organic hydrogen bonded coordination assembly has the potential to contribute to the development of supramolecular materials for various advanced catalytic applications.

Improving the Modeling of Extracellular Ligand Binding Pockets in RosettaGPCR for Conformational Selection.

G protein-coupled receptors (GPCRs) are the largest class of drug targets and undergo substantial conformational changes in response to ligand binding. Despite recent progress in GPCR structure determination, static snapshots fail to reflect the conformational space of putative binding pocket geometries to which small molecule ligands can bind. In comparative modeling of GPCRs in the absence of a ligand, often a shrinking of the orthosteric binding pocket is observed. However, the exact prediction of the flexible orthosteric binding site is crucial for adequate structure-based drug discovery. In order to improve ligand docking and guide virtual screening experiments in computer-aided drug discovery, we developed RosettaGPCRPocketSize. The algorithm creates a conformational ensemble of biophysically realistic conformations of the GPCR binding pocket between the TM bundle, which is consistent with a knowledge base of expected pocket geometries. Specifically, tetrahedral volume restraints are defined based on information about critical residues in the orthosteric binding site and their experimentally observed range of Cα-Cα-distances. The output of RosettaGPCRPocketSize is an ensemble of binding pocket geometries that are filtered by energy to ensure biophysically probable arrangements, which can be used for docking simulations. In a benchmark set, pocket shrinkage observed in the default RosettaGPCR was reduced by up to 80% and the binding pocket volume range and geometric diversity were increased. Compared to models from four different GPCR homology model databases (RosettaGPCR, GPCR-Tasser, GPCR-SSFE, and GPCRdb), the here-created models showed more accurate volumes of the orthosteric pocket when evaluated with respect to the crystallographic reference structure. Furthermore, RosettaGPCRPocketSize was able to generate an improved realistic pocket distribution. However, while being superior to other homology models, the accuracy of generated model pockets was comparable to AlphaFold2 models. Furthermore, in a docking benchmark using small-molecule ligands with a higher molecular weight between 400 and 700 Da, a higher success rate in creating native-like binding poses was observed. In summary, RosettaGPCRPocketSize can generate GPCR models with realistic orthosteric pocket volumes, which are useful for structure-based drug discovery applications.

Increased flexibility of the SARS-CoV-2 RNA-binding site causes resistance to remdesivir.

Mutations continue to accumulate within the SARS-CoV-2 genome, and the ongoing epidemic has shown no signs of ending. It is critical to predict problematic mutations that may arise in clinical environments and assess their properties in advance to quickly implement countermeasures against future variant infections. In this study, we identified mutations resistant to remdesivir, which is widely administered to SARS-CoV-2-infected patients, and discuss the cause of resistance. First, we simultaneously constructed eight recombinant viruses carrying the mutations detected in in vitro serial passages of SARS-CoV-2 in the presence of remdesivir. We confirmed that all the mutant viruses didn't gain the virus production efficiency without remdesivir treatment. Time course analyses of cellular virus infections showed significantly higher infectious titers and infection rates in mutant viruses than wild type virus under treatment with remdesivir. Next, we developed a mathematical model in consideration of the changing dynamic of cells infected with mutant viruses with distinct propagation properties and defined that mutations detected in in vitro passages canceled the antiviral activities of remdesivir without raising virus production capacity. Finally, molecular dynamics simulations of the NSP12 protein of SARS-CoV-2 revealed that the molecular vibration around the RNA-binding site was increased by the introduction of mutations on NSP12. Taken together, we identified multiple mutations that affected the flexibility of the RNA binding site and decreased the antiviral activity of remdesivir. Our new insights will contribute to developing further antiviral measures against SARS-CoV-2 infection.

Dispersion Effect of Molecular Crowding on Ligand-Protein Surface Binding Sites of Escherichia coli RNase HI.

The molecular crowding effect on ligand-protein interactions, which plays several crucial roles in life processes, has been investigated using various models by adding crowding agents to mimic the intracellular environment. Several studies evaluating this effect have focused on the ligand-protein binding reaction of well-structured binding sites with rigid conformations. However, the crowding effect on flexible binding sites is not well-understood, especially in terms of the conformations. In this work, to elucidate the detailed molecular mechanism underlying the ligand-protein interactions with flexible binding sites on a protein surface, we studied the interaction between the basic protrusion of Escherichia coli ribonuclease HI (RNase HI) and 8-anilinonaphthalene-1-sulfonic acid (ANS). The RNase HI concentration-dependent measurement of ANS fluorescence combined with the multivariate analysis and the fluorescence vibronic structure analysis revealed an increase in the heterogeneous species with an increase in the protein concentration, which is a different behavior from that of proteins with rigid binding sites. This result indicates that ANS molecules bind to the additional binding sites because of the destabilization of the main sites by the excluded volume effect in a crowded environment. The fluorescence vibronic structure analysis yields a detailed molecular picture, indicating that the main species of ANS can have a distorted structure. On the other hand, some ANS molecules move to the minor binding sites of a different microenvironment to secure a stabilized structure. These spectroscopic analyses may show a hypothesis, suggesting that the decrease in the ΔG difference between the main and minor sites due to destabilization of the main binding site could lower the potential barrier between them, inducing the dispersion of binding pathways.

Binding pocket stabilization by high-throughput screening of yeast display libraries.

Protein dynamics have a great influence on the binding pockets of some therapeutic targets. Flexible protein binding sites can result in transient binding pocket formation which might have a negative impact on drug screening efforts. Here, we describe a protein engineering strategy with FK506-binding protein 51 (FKBP51) as a model protein, which is a promising target for stress-related disorders. High-throughput screening of yeast display libraries of FKBP51 resulted in the identification of variants exhibiting higher affinity binding of conformation-specific FKBP51 selective inhibitors. The gene libraries of a random mutagenesis and site saturation mutagenesis of the FK1 domain of FKBP51 encoding sequence were used to create a yeast surface display library. Fluorescence-activated cell sorting for FKBP51 variants that bind conformation-specific fluorescently labeled ligands with high affinity allowed for the identification of 15 different protein variants with improved binding to either, or both FKBP51-specific ligands used in the screening, with improved affinities up to 34-fold compared to the wild type. These variants will pave the way to a better understanding of the conformational flexibility of the FKBP51 binding pocket and may enable the isolation of new selective ligands that preferably and selectively bind the active site of the protein in its open conformation state.

Flexibility of flanking DNA is a key determinant of transcription factor affinity for the core motif

Selective gene regulation is mediated by recognition of specific DNA sequences by transcription factors (TFs). The extremely challenging task of searching out specific cognate DNA binding sites among several million putative sites within the eukaryotic genome is achieved by complex molecular recognition mechanisms. Elements of this recognition code include the core binding sequence, the flanking sequence context, and the shape and conformational flexibility of the composite binding site. To unravel the extent to which DNA flexibility modulates TF binding, in this study, we employed experimentally guided molecular dynamics simulations of ternary complex of closely related Hox heterodimers Exd-Ubx and Exd-Scr with DNA. Results demonstrate that flexibility signatures embedded in the flanking sequences impact TF binding at the cognate binding site. A DNA sequence has intrinsic shape and flexibility features. While shape features are localized, our analyses reveal that flexibility features of the flanking sequences percolate several basepairs and allosterically modulate TF binding at the core. We also show that lack of flexibility in the motif context can render the cognate site resistant to protein-induced shape changes and subsequently lower TF binding affinity. Overall, this study suggests that flexibility-guided DNA shape, and not merely the static shape, is a key unexplored component of the complex DNA-TF recognition code.

General Method for Pesticide Recognition Using Albumin-Based Host-Guest Ensembles.

The massive use of pesticides nowadays has led to serious consequences for the environment and public health. Fluorescence analytical methods for pesticides are particularly advantageous with respect to simplicity and portability; however, currently available fluorescence methods (enzyme-based assays and indicator displacement assays) with poor universality are only able to detect few specific pesticides (e.g., organophosphorus). Making use of the multiple flexible and asymmetrical binding sites in albumin, we herein report a set of multicolor albumin-based host-guest ensembles. These ensembles exhibit a universal but distinctive fluorescent response to most of the common pesticides and allow array-based identification of pesticides with high accuracy. Furthermore, the simplicity, portability, and visualization of this method enable on-site determination of pesticides in a practical setting. This albumin host strategy largely expands the toolbox of traditional indicator displacement assays (synthetic macrocycles as hosts), and we expect it to inspire a series of sensor designs for pesticide detection.

Importance of Binding Site Hydration and Flexibility Revealed When Optimizing a Macrocyclic Inhibitor of the Keap1-Nrf2 Protein-Protein Interaction.

Upregulation of the transcription factor Nrf2 by inhibition of the interaction with its negative regulator Keap1 constitutes an opportunity for the treatment of disease caused by oxidative stress. We report a structurally unique series of nanomolar Keap1 inhibitors obtained from a natural product-derived macrocyclic lead. Initial exploration of the structure-activity relationship of the lead, followed by structure-guided optimization, resulted in a 100-fold improvement in inhibitory potency. The macrocyclic core of the nanomolar inhibitors positions three pharmacophore units for productive interactions with key residues of Keap1, including R415, R483, and Y572. Ligand optimization resulted in the displacement of a coordinated water molecule from the Keap1 binding site and a significantly altered thermodynamic profile. In addition, minor reorganizations of R415 and R483 were accompanied by major differences in affinity between ligands. This study therefore indicates the importance of accounting both for the hydration and flexibility of the Keap1 binding site when designing high-affinity ligands.

Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy.

The binding of small-molecule ligands to protein or nucleic acid targets is important to numerous biological processes. Accurate prediction of the binding modes between a ligand and a macromolecule is of fundamental importance in structure-based structure-function exploration. When multiple ligands with different sizes are docked to a target receptor, it is reasonable to assume that the residues in the binding pocket may adopt alternative conformations upon interacting with the different ligands. In addition, it has been suggested that the entropic contribution to binding can be important. However, only a few attempts to include the side chain conformational entropy upon binding within the application of flexible receptor docking methodology exist. Here, we propose a new physics-based scoring function that includes both enthalpic and entropic contributions upon binding by considering the conformational variability of the flexible side chains within the ensemble of docked poses. We also describe a novel hybrid searching algorithm that combines both molecular dynamics (MD)-based simulated annealing and genetic algorithm crossovers to address the enhanced sampling of the increased search space. We demonstrate improved accuracy in flexible cross-docking experiments compared with rigid cross-docking. We test our developments by considering five protein targets, thrombin, dihydrofolate reductase(DHFR), T4 L99A, T4 L99A/M102Q, and PDE10A, which belong to different enzyme classes with different binding pocket environments, as a representative set of diverse ligands and receptors. Each target contains dozens of different ligands bound to the same binding pocket. We also demonstrate that this flexible docking algorithm may be applicable to RNA docking with a representative riboswitch example. Our findings show significant improvements in top ranking accuracy across this set, with the largest improvement relative to rigid, 23.64%, occurring for ligands binding to DHFR. We then evaluate the ability to identify lead compounds among a large chemical space for the proposed flexible receptor docking algorithm using a subset of the DUD-E containing receptor targets MCR, GCR, and ANDR. We demonstrate that our new algorithms show improved performance in modeling flexible binding site residues compared to DOCK. Finally, we select the T4 L99A and T4 L99A/M102Q decoy sets, containing dozens of binders and experimentally validated nonbinders, to test our approach in distinguishing binders from nonbinders. We illustrate that our new algorithms for searching and scoring have superior performance to rigid receptor CDOCKER as well as AutoDock Vina. Finally, we suggest that flexible CDOCKER is sufficiently fast to be utilized in high-throughput docking screens in the context of hierarchical approaches.

DynaBiS: A hierarchical sampling algorithm to identify flexible binding sites for large ligands and peptides.

Knowing the ligand or peptide binding site in proteins is highly important to guide drug discovery, but experimental elucidation of the binding site is difficult. Therefore, various computational approaches have been developed to identify potential binding sites in protein structures. However, protein and ligand flexibility are often neglected in these methods due to efficiency considerations despite the recognition that protein-ligand interactions can be strongly affected by mutual structural adaptations. This is particularly true if the binding site is unknown, as the screening will typically be performed based on an unbound protein structure. Herein we present DynaBiS, a hierarchical sampling algorithm to identify flexible binding sites for a target ligand with explicit consideration of protein and ligand flexibility, inspired by our previously presented flexible docking algorithm DynaDock. DynaBiS applies soft-core potentials between the ligand and the protein, thereby allowing a certain protein-ligand overlap resulting in efficient sampling of conformational adaptation effects. We evaluated DynaBiS and other commonly used binding site identification algorithms against a diverse evaluation set consisting of 26 proteins featuring peptide as well as small ligand binding sites. We show that DynaBiS outperforms the other evaluated methods for the identification of protein binding sites for large and highly flexible ligands such as peptides, both with a holo or apo structure used as input.

Prediction of the Drug–Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each ligand-protein complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of ligand-protein complexes to predict binding parameters. We introduce the option of using multiple structures to describe each ligand-protein complex in COMBINE analysis and apply this to study the effects of protein flexibility on the derivation of dissociation rate constants (koff) for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression, and they allowed for the computation of koff values. The QSKR model obtained using single, energy-minimized crystal structures for each ligand-protein complex had higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, incorporation of ligand-protein flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, such as interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures. These results show that COMBINE analysis is a promising method to guide the design of compounds that bind to flexible proteins with improved binding kinetics.

Tuning the Transglycosylation Reaction of a GH11 Xylanase by a Delicate Enhancement of its Thumb Flexibility

Glycoside hydrolases (GHs) are attractive tools for multiple biotechnological applications. In conjunction with their hydrolytic function, GHs can perform transglycosylation under specific conditions. In nature, oligosaccharide synthesis is performed by glycosyltransferases (GTs); however, the industrial use of GTs is limited by their instability in solution. A key difference between GTs and GHs is the flexibility of their binding site architecture. We have used the xylanase from Bacillus circulans (BCX) to study the interplay between active‐site flexibility and transglycosylation. Residues of the BCX “thumb” were substituted to increase the flexibility of the enzyme binding site. Replacement of the highly conserved residue P116 with glycine shifted the balance of the BCX enzymatic reaction toward transglycosylation. The effects of this point mutation on the structure and dynamics of BCX were investigated by NMR spectroscopy. The P116G mutation induces subtle changes in the configuration of the thumb and enhances the millisecond dynamics of the active site. Based on our findings, we propose the remodelling of the GH enzymes glycon site flexibility as a strategy to improve the transglycosylation efficiency of these biotechnologically important catalysts.

Mining Natural Products for Macrocycles to Drug Difficult Targets.

Lead generation for difficult-to-drug targets that have large, featureless, and highly lipophilic or highly polar and/or flexible binding sites is highly challenging. Here, we describe how cores of macrocyclic natural products can serve as a high-quality in silico screening library that provides leads for difficult-to-drug targets. Two iterative rounds of docking of a carefully selected set of natural-product-derived cores led to the discovery of an uncharged macrocyclic inhibitor of the Keap1-Nrf2 protein–protein interaction, a particularly challenging target due to its highly polar binding site. The inhibitor displays cellular efficacy and is well-positioned for further optimization based on the structure of its complex with Keap1 and synthetic access. We believe that our work will spur interest in using macrocyclic cores for in silico-based lead generation and also inspire the design of future macrocycle screening collections.

Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking.

The coronavirus disease 19 (COVID-19) is a rapidly growing pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its papain-like protease (SARS-CoV-2 PLpro) is a crucial target to halt virus replication. SARS-CoV PLpro and SARS-CoV-2 PLpro share an 82.9% sequence identity and a 100% sequence identity for the binding site reported to accommodate small molecules in SARS-CoV. The flexible key binding site residues Tyr269 and Gln270 for small-molecule recognition in SARS-CoV PLpro exist also in SARS-CoV-2 PLpro. This inspired us to use the reported small-molecule binders to SARS-CoV PLpro to generate a high-quality DEKOIS 2.0 benchmark set. Accordingly, we used them in a cross-benchmarking study against SARS-CoV-2 PLpro. As there is no SARS-CoV-2 PLpro structure complexed with a small-molecule ligand publicly available at the time of manuscript submission, we built a homology model based on the ligand-bound SARS-CoV structure for benchmarking and docking purposes. Three publicly available docking tools FRED, AutoDock Vina, and PLANTS were benchmarked. All showed better-than-random performances, with FRED performing best against the built model. Detailed performance analysis via pROC-Chemotype plots showed a strong enrichment of the most potent bioactives in the early docking ranks. Cross-benchmarking against the X-ray structure complexed with a peptide-like inhibitor confirmed that FRED is the best-performing tool. Furthermore, we performed cross-benchmarking against the newly introduced X-ray structure complexed with a small-molecule ligand. Interestingly, its benchmarking profile and chemotype enrichment were comparable to the built model. Accordingly, we used FRED in a prospective virtual screen of the DrugBank1 database. In conclusion, this study provides an example of how to harness a custom-made DEKOIS 2.0 benchmark set as an approach to enhance the virtual screening success rate against a vital target of the rapidly emerging pandemic.

Potential target identification for breast cancer and screening of small molecule inhibitors: A bioinformatics approach

In the current study, we investigated the role of PAK1 (P21 (RAC1) Activated Kinase 1) gene in breast cancer and to this end, we performed differential gene expression analysis of PAK1 in breast cancer tissues compared to the normal adjacent tissue. We also studied its significance in protein-protein interaction (PPI) network, and analysed biological pathways, cellular processes, and role of PAK1 in different diseases. We found PAK1 to have significant role in breast cancer pathways such as integrin signaling, axonal guidance signaling, signaling by Rho family GTPases, ERK5 signaling. Additionally, it has been found as hub gene in PPI network, suggesting its possible regulatory role in breast carcinogenesis. Moreover, PAK1 had role in progression of various diseases as neoplasia, tumorigenesis, lymphatic neoplasia. Thereby, PAK1 can be used as a therapeutic target in breast cancer. Further, we put our efforts in identification of potential small molecules inhibitors against PAK1 by developing a composite virtual screening protocol involving molecular dynamics (MD) and molecular docking. The chemical library of compounds from NCI diversity sets, Pubchem and eMolecules were screened against PAK1 protein and hits which showed good binding affinity were considered for MD simulation study. Moreover, to assess binding of selected hits, MMGBSA (Molecular Mechanics-Generalized Born Surface Area) analysis was performed using AMBER (Assisted Model Building with Energy Refinement) package. MMGBSA calculations exhibited that the identified ligands showed good binding affinity with PAK1. Highlights The PAK1 has been found to be upregulated in breast cancer samples and is a potential oncogene playing role in different cellular functions and processes. The molecular docking studies revealed ligands showed good binding affinity towards PAK1 protein. The residues Glu345, Leu347, Thr406, Asp299, Asp393 and Gly350 were found to make H-bond interactions with small molecule inhibitors. The residues Ile276, Val284, Ala297, Tyr346, Leu396 and Asp407 were found to make hydrophobic interactions. The RMSD analysis confirmed stability of complexes throughout 40 ns production period. The MD simulations studies revealed the binding site flexibility, binding free energy of complexes and per-residue contribution in ligand binding. Communicated by Ramaswamy H. Sarma