Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RalGDS complexes

Binding Selectivity of Inhibitors toward Bromodomains BAZ2A and BAZ2B Uncovered by Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

Two Bromodomain-Containing proteins BAZ2A and BAZ2B are responsible for remodeling chromatin and regulating noncoding RNAs. As for our current studies, integration of multiple short molecular dynamics simulations (MSMDSs) with molecular mechanics generalized Born surface area (MM-GBSA) method is adopted for insights into binding selectivity of three small molecules D8Q, D9T and UO1 to BAZ2A against BAZ2B. The calculations of MM-GBSA unveil that selectivity of inhibitors toward BAZ2A and BAZ2B highly depends on the enthalpy changes and the details uncover that D8Q has better selectivity toward BAZ2A than BAZ2B, D9T more favorably bind to BAZ2B than BAZ2A, and UO1 does not show obvious selectivity toward these two proteins. The analysis of interaction network between residues and inhibitors indicates that seven residues are mainly responsible for the selectivity of D8Q, six residues for D9T and four residues provide significant contributions to associations of UO1 with two proteins. Moreover the analysis of interaction network not only reveals warm spots of inhibitor bindings to BAZ2A and BAZ2B but also unveils that common residue pairs, including (W1816, W1887), (P1817, P1888), (F1818, F1889), (V1822, V1893), (N1823, N1894),(L1826, L1897), (V1827, V1898), (F1872, F1943), (N1873, N1944) and (V1879, I1950) belonging to (BAZ2A, BAZ2B), induce mainly binding differences of inhibitors to BAZ2A and BAZ2B. Hence, insights from our current studies offer useful dynamics information relating with conformational alterations and structure-affinity relationship at atomistic levels for novel therapeutic strategies toward BAZ2A and BAZ2B.

Binding mechanism of inhibitors to p38α MAP kinase deciphered by using multiple replica Gaussian accelerated molecular dynamics and calculations of binding free energies

The p38α MAP Kinase has been an important target of drug design for treatment of inflammatory diseases and cancers. This work applies multiple replica Gaussian accelerated molecular dynamics (MR-GaMD) simulations and the molecular mechanics generalized Born surface area (MM-GBSA) method to probe the binding mechanism of inhibitors L51, R24 and 1AU to p38α. Dynamics analyses show that inhibitor bindings exert significant effect on conformational changes of the active helix α2 and the conserved DFG loop. The rank of binding free energies calculated with MM-GBSA not only agrees well with that determined by the experimental IC50 values but also suggests that mutual compensation between the enthalpy and entropy changes can improve binding of inhibitors to p38α. The analyses of free energy landscapes indicate that the L51, R24 and 1AU bound p38α display a DFG-out conformation. The residue-based free energy decomposition method is used to evaluate contributions of separate residues to the inhibitor-p38α binding and the results imply that residues V30, V38, L74, L75, I84, T106, H107, L108, M109, L167, F169 and D168 can be utilized as efficient targets of potent inhibitors toward p38α.

A comprehensive characterization of novel CYP-BM3 homolog (CYP-BA) from Bacillus aryabhattai

Functionalizing C-H bond poses one of the most significant challenges for chemists providing them with very few substrate-specific synthetic routes. Despite being incredibly plastic in their enzymatic ability, they are confined with deficient enzymatic action and limited explicitness of the substrates. In this study, we have endeavored to characterize novel cytochrome P450 from Bacillus aryabhattai (CYP-BA), a homolog of CYP P450-BM3, by taking interdisciplinary approaches. We conducted structure and sequence comparison to understand the conservation pattern for active site residues, conserved fold, evolutionary relationships among others. Molecular dynamics simulations were performed to understand the dynamic nature and interaction with the substrates. CYP-BA was successfully cloned, purified, and characterized. The enzyme's stability toward various physicochemical parameters was evaluated by UV-vis spectroscopy and Circular Dichroism (CD) spectroscopy. Various saturated fatty acids being the natural cytochrome P450 substrates were evaluated as catalytic efficiency of substrate oxidation by CYP-BA. The binding affinity of these natural substrates was monitored against CYP-BA by isothermal titration calorimetry (ITC). The catalytic performance of CYP-BA was satisfactory enough to proceed to the next step, that is, engineering to expand the substrate range to include polycyclic aromatic hydrocarbons (PAH). This is the first evidence of cloning, purifying and characterizing a novel homolog of CYP-BM3 to enable a better understanding of this novel biocatalyst and to provide a platform toward expanding its catalytic process through enzyme engineering.

Insight into the drug resistance mechanisms of GS-9669 caused by mutations of HCV NS5B polymerase via molecular simulation

GS-9669 is a non-nucleos(t)ide inhibitor (NNI) binding to the thumb site II of the Hepatitis C virus (HCV) NS5B polymerase and has advanced into phase II trials. To clarify the drug resistance mechanisms of GS-9669 caused by M423T/I/V, L419M, R422K, and I482L mutations of NS5B polymerase (GT1b) and the receptor-ligand interactions during the binding process, a series of molecular simulation methods including molecular dynamics (MD) simulations and adaptive steered molecular dynamics (ASMD) simulations were performed for the wild-type (WT) and six mutant NS5B/GS-9669 complexes. The calculated results indicate that the binding free energies of the mutant systems are less negative than that of the WT system, indicating that these mutations will indeed cause NS5B to produce different degrees of resistance to GS-9669. The mutation-induced drug resistances are mainly caused by the loss of binding affinities of Leu419 and Trp528 with GS-9669 or the formation of multiple solvent bridges. Moreover, the ASMD calculations show that GS-9669 binds to the thumb II sites of the seven NS5B polymerases in distinct pathways without any obvious energy barriers. Although the recognition methods and binding pathways are distinct, the binding processes of GS-9669 with the WT and mutant NS5B polymerases are basically controlled thermodynamically. This study clearly reveals the resistance mechanisms of GS-9669 caused by M423T/I/V, L419M, R422K, and I482L mutations of HCV NS5B polymerase and provides some valuable clues for further optimization and design of novel NS5B inhibitors.

An Effective MM/GBSA Protocol for Absolute Binding Free Energy Calculations: A Case Study on SARS-CoV-2 Spike Protein and the Human ACE2 Receptor

The binding free energy calculation of protein-ligand complexes is necessary for research into virus-host interactions and the relevant applications in drug discovery. However, many current computational methods of such calculations are either inefficient or inaccurate in practice. Utilizing implicit solvent models in the molecular mechanics generalized Born surface area (MM/GBSA) framework allows for efficient calculations without significant loss of accuracy. Here, GBNSR6, a new flavor of the generalized Born model, is employed in the MM/GBSA framework for measuring the binding affinity between SARS-CoV-2 spike protein and the human ACE2 receptor. A computational protocol is developed based on the widely studied Ras-Raf complex, which has similar binding free energy to SARS-CoV-2/ACE2. Two options for representing the dielectric boundary of the complexes are evaluated: one based on the standard Bondi radii and the other based on a newly developed set of atomic radii (OPT1), optimized specifically for protein-ligand binding. Predictions based on the two radii sets provide upper and lower bounds on the experimental references: -14.7(ΔGbindBondi)<-10.6(ΔGbindExp.)<-4.1(ΔGbindOPT1) kcal/mol. The consensus estimates of the two bounds show quantitative agreement with the experiment values. This work also presents a novel truncation method and computational strategies for efficient entropy calculations with normal mode analysis. Interestingly, it is observed that a significant decrease in the number of snapshots does not affect the accuracy of entropy calculation, while it does lower computation time appreciably. The proposed MM/GBSA protocol can be used to study the binding mechanism of new variants of SARS-CoV-2, as well as other relevant structures.

Influence of the gallate moiety on the interactions between green tea polyphenols and lipid membranes elucidated by molecular dynamics simulations

Previous studies suggested that naturally occurring EGCG primarily acted on the bacterial cell membrane then damaged the membrane and the gallate moiety in EGCG was very important to its anti-bacterial activity. However, the detailed mechanisms were still poorly understood. In this paper, EGCG and EGC were selected to study the great contribution of gallate moiety on the anti-bacterial activities of polyphenols. The results indicated that EGCG could penetrate deeper into the POPG lipid bilayer and possess more potent structure-perturbing potency on the POPG lipid bilayer than EGC. We also found that EGCG had the ability to form hydrogen bonds with the deeper inside oxygen atoms in the POPG lipid bilayer and the gallate moiety was the key functional group for EGCG forming hydrogen bonds with the POPG lipid bilayer. Moreover, results from the binding free energy analysis demonstrated that the gallate moiety made great contribution to the high affinity between EGCG and the POPG lipid bilayer. We believed that these findings could yield useful insights into the influence mechanisms of gallate moiety on the anti-bacterial activities of polyphenols.

Design and identification of a new farnesoid X receptor (FXR) partial agonist by computational structure-activity relationship analysis: Ligand-induced H8 helix fluctuation in the ligand-binding domain of FXR may lead to partial agonism

Farnesoid X receptor (FXR) controls gene-expression relevant to various diseases including nonalcoholic steatohepatitis and has become a drug target to regulate metabolic aberrations. However, some side effects of FXR agonists reported in clinical development such as an increase in blood cholesterol levels incentivize the development of partial agonists to minimize side effects. In this study, to identify a new partial agonist, we analyzed the computational structure-activity relationship (SAR) of FXR agonists previously developed in our laboratories using molecular dynamics simulations. SAR analysis showed that fluctuations in the H8 helix, by ligand binding, of the ligand-binding domain (LBD) of FXR may influence agonistic activity. Based on this observation, 6 was newly designed as a partial agonist and synthesized. As a result of biological evaluations, 6 showed weak agonistic activity (40.0% relative agonistic activity to the full-agonist GW4064) and a potent EC₅₀ value (55.5 nM). The successful identification of the new potent partial agonist 6 suggested that helix fluctuation in the LBD induced by ligands could be one way to develop partial agonists.

Molecular Dynamics Simulations Based on 1-Phenyl-4-Benzoyl-1-Hydro-Triazole ERRα Inverse Agonists

Estrogen-related receptor α (ERRα), which is overexpressed in a variety of cancers has been considered as an effective target for anticancer therapy. ERRα inverse agonists have been proven to effectively inhibit the migration and invasion of cancer cells. As few crystalline complexes have been reported, molecular dynamics (MD) simulations were carried out in this study to deepen the understanding of the interaction mechanism between inverse agonists and ERRα. The binding free energy was analyzed by the MM-GBSA method. The results show that the total binding free energy was positively correlated with the biological activity of an inverse agonist. The interaction of the inverse agonist with the hydrophobic interlayer composed of Phe328 and Phe495 had an important impact on the biological activity of inverse agonists, which was confirmed by the decomposition of energy on residues. As Glu331 flipped and formed a hydrogen bond with Arg372 in the MD simulation process, the formation of hydrogen bond interaction with Glu331 was not a necessary condition for the compound to act as an inverse agonist. These rules provide guidance for the design of new inverse agonists.

Binding thermodynamics and interaction patterns of human purine nucleoside phosphorylase-inhibitor complexes from extensive free energy calculations

Human purine nucleoside phosphorylase (hPNP) plays a significant role in the catabolism of deoxyguanosine. The trimeric protein is an important target in the treatment of T-cell cancers and autoimmune disorders. Experimental studies on the inhibition of the hPNP observe that the first ligand bound to one of three subunits effectively inhibits the protein, while the binding of more ligands to the subsequent sites shows negative cooperativities. In this work, we performed extensive end-point and alchemical free energy calculations to determine the binding thermodynamics of the trimeric protein-ligand system. 13 Immucillin inhibitors with experimental results are under calculation. Two widely accepted charge schemes for small molecules including AM1-BCC and RESP are adopted for ligands. The results of RESP are in better agreement with the experimental reference. Further investigations of the interaction networks in the protein-ligand complexes reveal that several residues play significant roles in stabilizing the complex structure. The most commonly observed ones include PHE200, GLU201, MET219, and ASN243. The conformations of the protein in different protein-ligand complexes are observed to be similar. We expect these insights to aid the development of potent drugs targeting hPNP.

DeepBAR: A Fast and Exact Method for Binding Free Energy Computation

The fast and accurate calculation of standard binding free energy has many important applications. Existing methodologies struggle at balancing accuracy and efficiency. We introduce a new method to compute binding free energy using deep generative models and the Bennett acceptance ratio method (DeepBAR). Compared to the rigorous potential of mean force (PMF) approach that requires sampling from intermediate states, DeepBAR is an order-of-magnitude more efficient as demonstrated in a series of host-guest systems. Notably, DeepBAR is exact and does not suffer from approximations for entropic contributions used in methods such as the molecular mechanics energy combined with the generalized Born and surface area continuum solvation (MM/GBSA). We anticipate DeepBAR to be a valuable tool for computing standard binding free energy used in drug design.

Raf promotes dimerization of the Ras G-domain with increased allosteric connections

Ras dimerization is critical for Raf activation. Here we show that the Ras binding domain of Raf (Raf-RBD) induces robust Ras dimerization at low surface densities on supported lipid bilayers and, to a lesser extent, in solution as observed by size exclusion chromatography and confirmed by SAXS. Community network analysis based on molecular dynamics simulations shows robust allosteric connections linking the two Raf-RBD D113 residues located in the Galectin scaffold protein binding site of each Raf-RBD molecule and 85 Å apart on opposite ends of the dimer complex. Our results suggest that Raf-RBD binding and Ras dimerization are concerted events that lead to a high-affinity signaling complex at the membrane that we propose is an essential unit in the macromolecular assembly of higher order Ras/Raf/Galectin complexes important for signaling through the Ras/Raf/MEK/ERK pathway.

Unraveling the mechanism of arbidol binding and inhibition of SARS-CoV-2: Insights from atomistic simulations

The COVID-19 pandemic has spread rapidly and poses an unprecedented threat to the global economy and human health. Broad-spectrum antivirals are currently being administered to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). China's prevention and treatment guidelines suggest the use of an anti-influenza drug, arbidol, for the clinical treatment of COVID-19. Reports indicate that arbidol could neutralize SARS-CoV-2. Monotherapy with arbidol is superior to lopinavir-ritonavir or favipiravir for treating COVID-19. In SARS-CoV-2 infection, arbidol acts by interfering with viral binding to host cells. However, the detailed mechanism by which arbidol induces the inhibition of SARS-CoV-2 is not known. Here, we present atomistic insights into the mechanism underlying membrane fusion inhibition of SARS-CoV-2 by arbidol. Molecular dynamics (MD) simulation-based analyses demonstrate that arbidol binds and stabilizes at the receptor-binding domain (RBD)/ACE2 interface with a high affinity. It forms stronger intermolecular interactions with the RBD than ACE2. Analyses of the detailed decomposition of energy components and binding affinities revealed a substantial increase in the affinity between the RBD and ACE2 in the arbidol-bound RBD/ACE2 complex, suggesting that arbidol generates favorable interactions between them. Based on our MD simulation results, we propose that the binding of arbidol induces structural rigidity in the viral glycoprotein, thus restricting the conformational rearrangements associated with membrane fusion and virus entry. Furthermore, key residues of the RBD and ACE2 that interact with arbidol were identified, opening the door for developing therapeutic strategies and higher-efficacy arbidol derivatives or lead drug candidates.

Discovery of novel heterocyclic amide-based inhibitors: an integrative in-silico approach to targeting soluble epoxide hydrolase

Inhibition of soluble epoxide hydrolase (sEH) is considered as an emerging druggable target to reduce blood pressure, improve insulin sensitivity, and decrease inflammation. Despite the availability of different classes of sEH small molecule inhibitors for the potential treatment of hypertension, only a few candidates have reached clinical trials, making the optimal control of blood pressure presently unattainable. This necessity motivated us to explore a series of novel quinazoline-4(3H)-one and 4,6-disubstituted pyridin-2(1H)-one derivatives targeting sEH enzyme. Herein, comprehensive computational investigations were performed to probe the inhibition efficacy of these potent compounds in terms of inhibitor-enzyme interactions against sEH. In this study, the 39 in-house with a focused library comprising 39 in-house synthesized compounds were selected. The structure-based pharmacophore modeling was developed based on the crystal structure of sEH with its co-crystallized biologically active inhibitor. The generated hypotheses were applied for virtual screening-based PHASE fitness scores. Docking-based virtual screening workflows were used to generate lead compounds using HTVS, SP and XP based GLIDE G-score values. The candidate leads were filtered using ADMET pharmacological and physicochemical properties screening. A 100-ns of molecular dynamics simulations with Molecular dynamics simulations (100 ns) were performed to explore the binding affinities of the considered compounds. Our study identified four best candidates from quinazoline-4(3H)-one derivatives, which indicated that a quinazolinone ring serves as a suitable scaffold to develop novel small molecule sEH inhibitors.

An atomistic investigation on the interaction of distamycin A and its derivative with the telomeric G-Quadruplex as anticancer agents by molecular dynamics simulation

Human telomerase that activates within cancer cells has a telomeric sequence at the 3' end. Each factor that stabilizes the G-quadruplex in guanine-rich telomeric sequences can inhibit the regular telomerase activity. Therefore, the telomeric G-quadruplex is known as a promising target in cancer treatment. In this work, we studied the binding of positively charged distamycin A and its uncharged derivative to the G-quadruplex in a solution environment by Molecular Dynamics (MD) simulation. The binding mechanism and subtle conformational changes were investigated as a result of the ligand attachment. Moreover, binding free energy and clustering analysis describe the stability and flexibility of G-quadruplexes upon ligand binding. Structural analyses displayed that the favorable binding of both ligands imposes significant stability and rigidity in G-quadruplex conformation compared to free G-quadruplex, especially charged distamycin. Hydration pattern and ion distribution were different for free G-quadruplex and both of the ligand complexes. Energy decomposition reveals the electrostatic effect on the stability of G-quadruplex. The radial distribution function displayed the solvent shell and ion moving away from the groove. The hydrogen bond played an essential role in the binding of both ligands, especially for the charged derivative. van der Waals interaction is the only factor that is more important in binding uncharged distamycin into G-quadruplex than the charged one. The calculated ΔG_bind showed the stability of both ligands within grooves and good agreement with the experimental binding free energy data. Finally, the results suggest that ligand modification improves the binding mode toward stabilizing G-quadruplexes.

Understanding the molecular interactions of inhibitors against Bla1 beta-lactamase towards unraveling the mechanism of antimicrobial resistance

This study evaluated the inhibitory potential of various beta-lactamase inhibitors such as mechanism-based inhibitors (MBIs), carbapenems, monobactam, and non-beta-lactam inhibitors against Bla1, a class-A beta-lactamase encoded by Bacillus anthracis. The binding potential of different inhibitors was estimated using competitive kinetic assay, isothermal titration calorimetry, and Biolayer interferometry. We observed that tazobactam has better inhibition among other MBIs with a characteristics inhibition dissociation constant of 0.51 ± 0.13 μM. Avibactam was also identified as good inhibitor with an inhibition efficiency of 0.6 ± 0.04 μM. All the MBIs (K_D = 1.90E-04 M, 2.05E-05 M, 3.55E-04 M for clavulanate, sulbactam and tazobactam) showed significantly better binding potential than carbapenems (K_D = 1.02E-03 M, 2.74E-03 M, 1.24E-03 M for ertapenem, imipenem and biapenem respectively). Molecular dynamics simulations were carried out using Bla1-inhibitor complexes to understand the dynamics and stability. The minimum inhibitory concentration (MIC) was carried out by taking various substrates and inhibitors, and later it was followed by cell viability assay. Together, our study helps develop a proper understanding of Bla1 beta-lactamase and its interaction with inhibitory molecules. This study would facilitate comprehending the catalytic divergence of beta-lactamases and the newly emergent resistant strains, focusing on the new generation of therapeutics being less prone to antimicrobial resistance.

Mechanistic insights into the effect of phosphorylation on Ras conformational dynamics and its interactions with cell signaling proteins

Ras undergoes interconversion between the active GTP-bound state and the inactive GDP-bound state. This GTPase cycle, which controls the activities of Ras, is accelerated by Ras GTPase-activating proteins (GAPs) and guanine nucleotide exchange factors (SOS). Oncogenic Ras mutations could affect the GTPase cycle and impair Ras functions. Additionally, Src-induced K-Ras Y32/64 dual phosphorylation has been reported to disrupt GTPase cycle and hinder Ras downstream signaling. However, the underlying mechanisms remain unclear. To address this, we performed molecular dynamics simulations (~30 μs in total) on unphosphorylated and phosphorylated K-Ras4B in GTP- and GDP-bound states, and on their complexes with GTPase cycle regulators (GAP and SOS) and the effector protein Raf. We found that K-Ras4B dual phosphorylation mainly alters the conformation at the nucleotide binding site and creates disorder at the catalytic site, resulting in the enlargement of GDP binding pocket and the retard of Ras-GTP intrinsic hydrolysis. We observed phosphorylation-induced shift in the distribution of Ras-GTP inactive-active sub-states and recognized potential druggable pockets in the phosphorylated Ras-GTP. Moreover, decreased catalytic competence or signal delivery abilities due to reduced binding affinities and/or distorted catalytic conformations of GAP, SOS and Raf were observed. In addition, the allosteric pathway from Ras/Raf interface to the distal Raf L4 loop was compromised by Ras phosphorylation. These results reveal the mechanisms by which phosphorylation influences the intrinsic or GAP/SOS catalyzed transformations between GTP- and GDP-bound states of Ras and its signal transduction to Raf. Our findings project Ras phosphorylation as a target for cancer drug discovery.

Azole-Based Indoleamine 2,3-Dioxygenase 1 (IDO1) Inhibitors

The heme enzyme indoleamine 2,3-dioxygenase 1 (IDO1) plays an essential role in immunity, neuronal function, and aging through catalysis of the rate-limiting step in the kynurenine pathway of tryptophan metabolism. Many IDO1 inhibitors with different chemotypes have been developed, mainly targeted for use in anti-cancer immunotherapy. Lead optimization of direct heme iron-binding inhibitors has proven difficult due to the remarkable selectivity and sensitivity of the heme-ligand interactions. Here, we present experimental data for a set of closely related small azole compounds with more than 4 orders of magnitude differences in their inhibitory activities, ranging from millimolar to nanomolar levels. We investigate and rationalize their activities based on structural data, molecular dynamics simulations, and density functional theory calculations. Our results not only expand the presently known four confirmed chemotypes of sub-micromolar heme binding IDO1 inhibitors by two additional scaffolds but also provide a model to predict the activities of novel scaffolds.

Deciphering the T790M/L858R-Selective Inhibition Mechanism of an Allosteric Inhibitor of EGFR: Insights from Molecular Simulations

Allosteric inhibitors have lately received great attention because of their unique advantages, representing a more suitable choice for combinatory therapeutics targeting resistance-relevant signaling cascades. Among the various inhibitors, an allosteric small-molecule inhibitor, JBJ-04-125-02, has been proven to be effective against EGFR^T790M/L858R mutant in vivo and in vitro. Herein, an in silico approach was adopted to shed light on the deep understanding of the higher selectivity of JBJ-04-125-02 against EGFR^T790M/L858R mutant than wild-type EGFR. Our results indicate that JBJ-04-125-02 prefers to bind with the EGFR^T790M/L858R mutant, stabilizes the inactive conformation, and further allosterically affects the conformations and dynamics of the interlobe cleft, including both the allosteric site and the ATP-binding site. Furthermore, docking results confirm that the binding of JBJ-04-125-02 at the allosteric site decreases the binding affinity of ANP (an ATP analogue) at the orthosteric site, especially for the Mut-holo one, which might further inhibit the function of EGFR. The present work provides a clear picture of the mutant-selective inhibition mechanism of an allosteric inhibitor of EGFR. The findings might pave the way for designing allosteric drugs targeting EGFR mutant lung cancer patients, which also takes a step forward in terms of drug resistance caused by protein mutations.

Repurposing potential of Ayurvedic medicinal plants derived active principles against SARS-CoV-2 associated target proteins revealed by molecular docking, molecular dynamics and MM-PBSA studies

All the plants and their secondary metabolites used in the present study were obtained from Ayurveda, with historical roots in the Indian subcontinent. The selected secondary metabolites have been experimentally validated and reported as potent antiviral agents against genetically-close human viruses. The plants have also been used as a folk medicine to treat cold, cough, asthma, bronchitis, and severe acute respiratory syndrome in India and across the globe since time immemorial. The present study aimed to assess the repurposing possibility of potent antiviral compounds with SARS-CoV-2 target proteins and also with host-specific receptor and activator protease that facilitates the viral entry into the host body. Molecular docking (MDc) was performed to study molecular affinities of antiviral compounds with aforesaid target proteins. The top-scoring conformations identified through docking analysis were further validated by 100 ns molecular dynamic (MD) simulation run. The stability of the conformation was studied in detail by investigating the binding free energy using MM-PBSA method. Finally, the binding affinities of all the compounds were also compared with a reference ligand, remdesivir, against the target protein RdRp. Additionally, pharmacophore features, 3D structure alignment of potent compounds and Bayesian machine learning model were also used to support the MDc and MD simulation. Overall, the study emphasized that curcumin possesses a strong binding ability with host-specific receptors, furin and ACE2. In contrast, gingerol has shown strong interactions with spike protein, and RdRp and quercetin with main protease (M^pro) of SARS-CoV-2. In fact, all these target proteins play an essential role in mediating viral replication, and therefore, compounds targeting aforesaid target proteins are expected to block the viral replication and transcription. Overall, gingerol, curcumin and quercetin own multitarget binding ability that can be used alone or in combination to enhance therapeutic efficacy against COVID-19. The obtained results encourage further in vitro and in vivo investigations and also support the traditional use of antiviral plants preventively.

Molecular Modelling Studies on Pyrazole Derivatives for the Design of Potent Rearranged during Transfection Kinase Inhibitors

RET (rearranged during transfection) kinase, one of the receptor tyrosine kinases, plays a crucial role in the development of the human nervous system. It is also involved in various cell signaling networks responsible for the normal cell division, growth, migration, and survival. Previously reported clinical studies revealed that deregulation or aberrant activation of RET signaling can cause several types of human cancer. For example, medullary thyroid carcinoma (MTC) and multiple endocrine neoplasia (MEN2A, MEN2B) occur due to sporadic mutation or germline RET mutation. A number of RET kinase inhibitors have been approved by the FDA for the treatment of cancer, such as cabozantinib, vandetanib, lenvatinib, and sorafenib. However, each of these drugs is a multikinase inhibitor. Hence, RET is an important therapeutic target for cancer drug design. In this work, we have performed various molecular modelling studies, such as molecular docking and dynamics simulation for the most active compound of the pyrazole series as RET kinase inhibitors. Furthermore, molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) free energy calculation and 3-dimensional quantitative structure-activity relationship (3D-QSAR) were performed using g_mmpbsa and SYBYL-X 2.1 package. The results of this study revealed the crucial binding site residues at the active site of RET kinase and contour map analysis showed important structural characteristics for the design of new highly active inhibitors. Therefore, we have designed ten RET kinase inhibitors, which showed higher inhibitory activity than the most active compound of the series. The results of our study provide insights to design more potent and selective RET kinase inhibitors.

Targeting ebola virus VP40 protein through novel inhibitors: exploring the structural and dynamic perspectives on molecular landscapes

Ebola filovirus (EBOV) is one of the deadliest known infectious agents, and a cause of Western African epidemics from 2013 to 2016. The virus has infected nearly 3000 humans and almost 1900 have died. In the past few years, various small molecules have been discovered to display efficiency against EBOV and some of them have progressed towards clinical trials. Even though continuous attempts have been made to find antiEBOV therapeutics, no potential drugs are yet approved against this viral infection. The development of small antiviral inhibitors has gained tremendous attention in the attempt to overcome EVD. With this background, we seek to offer molecular insights into EBOV VP40 protein inhibition, using all atom molecular mechanics methodology and binding free energy calculations. We have selected five novel reported inhibitors against VP40 protein, namely Comp1, Comp2, Comp3, Comp4, and Comp5, and explored their binding against the same target. It was evident from the analysis that all the inhibitors displayed stability in complex with VP40 protein; however, Comp1 exhibited enhanced stability and compactness. Comp1 unveiled favorable binding, which accounted for positive correlation motions in the active site residues. Likewise, Comp1 revealed the most promising binding (ΔG_bind - 40.3504 kcal/mol) as compared to the other four inhibitors, which disclosed relatively less favorable ΔG_bind. The highest binding energy of Comp1 to VP40 protein can be primarily endorsed to the upsurge in van der Waals energy by ΔE_vdW - 37.1609 kcal/mol and Coulomb energy by ΔE_ele - 52.7332 kcal/mol. Also, the hydrogen bond network is robust in Comp1-VP40 complex, with four hydrogen bonds, whilst it is less in other inhibitors. The outcomes from this report may assist in the advancement of novel VP40 inhibitors with high selectivity and potency for EVD therapeutics.

Mining of Ebola virus genome for the construction of multi-epitope vaccine to combat its infection

Ebola virus is the primary causative agent of viral hemorrhagic fever that is an epidemic disease and responsible for the massive premature deaths in humans. Despite knowing the molecular mechanism of its pathogenesis, to date, no commercial or FDA approved multiepitope vaccine is available against Ebola infection. The current study focuses on designing a multi-epitope subunit vaccine for Ebola using a novel immunoinformatic approach. The best predicted antigenic epitopes of Cytotoxic-T cell (CTL), Helper-T cells (HTL), and B-cell epitopes (BCL) joined by various linkers were selected for the multi-epitope vaccine designing. For the enhanced immune response, two adjuvants were also added to the construct. Further analysis showed the vaccine to be immunogenic and non-allergenic, forming a stable and energetically favorable structure. The stability of the unbound vaccine construct and vaccine/TLR4 was elucidated via atomistic molecular dynamics simulations. The binding free energy analysis (ΔG_Bind = -194.2 ± 0.5 kcal/mol) via the molecular mechanics Poisson-Boltzmann docking scheme revealed a strong association and thus can initiate the maximal immune response. Next, for the optimal expression of the vaccine construct, its gene construct was cloned in the pET28a + vector system. In summary, the Ebola viral proteome was screened to identify the most potential HTLs, CTLs, and BCL epitopes. Along with various linkers and adjuvants, a multi-epitope vaccine is constructed that showed a high binding affinity with the immune receptor, TLR4. Thus, the current study provides a highly immunogenic multi-epitope subunit vaccine construct that may induce humoral and cellular immune responses against the Ebola infection.Communicated by Ramaswamy H. Sarma.

Cheminformatics-Based Identification of Potential Novel Anti-SARS-CoV-2 Natural Compounds of African Origin

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome virus 2 (SARS-CoV-2) has impacted negatively on public health and socioeconomic status, globally. Although, there are currently no specific drugs approved, several existing drugs are being repurposed, but their successful outcomes are not guaranteed. Therefore, the search for novel therapeutics remains a priority. We screened for inhibitors of the SARS-CoV-2 main protease and the receptor-binding domain of the spike protein from an integrated library of African natural products, compounds generated from machine learning studies and antiviral drugs using AutoDock Vina. The binding mechanisms between the compounds and the proteins were characterized using LigPlot+ and molecular dynamics simulations techniques. The biological activities of the hit compounds were also predicted using a Bayesian-based approach. Six potential bioactive molecules NANPDB2245, NANPDB2403, fusidic acid, ZINC000095486008, ZINC0000556656943 and ZINC001645993538 were identified, all of which had plausible binding mechanisms with both viral receptors. Molecular dynamics simulations, including molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) computations revealed stable protein-ligand complexes with all the compounds having acceptable free binding energies <-15 kJ/mol with each receptor. NANPDB2245, NANPDB2403 and ZINC000095486008 were predicted as antivirals; ZINC000095486008 as a membrane permeability inhibitor; NANPDB2403 as a cell adhesion inhibitor and RNA-directed RNA polymerase inhibitor; and NANPDB2245 as a membrane integrity antagonist. Therefore, they have the potential to inhibit viral entry and replication. These drug-like molecules were predicted to possess attractive pharmacological profiles with negligible toxicity. Novel critical residues identified for both targets could aid in a better understanding of the binding mechanisms and design of fragment-based de novo inhibitors. The compounds are proposed as worthy of further in vitro assaying and as scaffolds for the development of novel SARS-CoV-2 therapeutic molecules.

Interplay among Structural Stability, Plasticity, and Energetics Determined by Conformational Attuning of Flexible Loops in PD-1

The dynamics and plasticity of the PD-1/PD-L1 axis are the bottlenecks for the discovery of small-molecule antagonists to perturb this interaction interface significantly. Understanding the process of this protein-protein interaction (PPI) is of fundamental biological interest in structure-based drug designing. Food and Drug Administration (FDA)-approved anti-PD-1 monoclonal antibodies (mAbs) are the first-in-class with distinct binding modes to access this axis clinically; however, their mechanistic aspects remain elusive. Here, we have unveiled the interactive interfaces with PD-L1 and mAbs to investigate the native plasticity of PD-1 at global (structural and dynamical) and local (residue side-chain orientations) levels. We found that the structural stability and coordinated C_α movements are increased in the presence of PD-1's binding partners. The rigorous analysis of these PPIs using computational biophysical approaches revealed PD-1's intrinsic plasticity, its concerted loops' movement (BC, FG, and CC'), distal side-chain motions, and the thermodynamic landscape, which are perturbed remarkably from its unbound to bound states. Based on intra-/inter-residues' contact networks and energetics, the hot-spots have been identified that were found to be essential to arrest the dynamical motions of PD-1 significantly for the rational design of therapeutic agents by mimicking the mAbs mechanism.

Structure-Based Identification of Potential Drugs Against FmtA of Staphylococcus aureus: Virtual Screening, Molecular Dynamics, MM-GBSA, and QM/MM

Staphylococcus aureus is resistant to β-lactam antibiotics and causes several skin diseases to life-threatening diseases. FmtA is found to be one of the main factors involved in methicillin resistance in S. aureus. FmtA exhibits an esterase activity that removes the D-Ala from teichoic acid. Teichoic acids played a significant role in cell wall synthesis, cell division, colonization, biofilm formation, virulence, antibiotic resistance, and pathogenesis. The virtual screening of drug molecules against the crystal structure of FmtA was performed and the binding affinities of top three molecules (ofloxacin, roflumilast, and furazolidone) were predicted using molecular docking. The presence of positive potential and electron affinity regions in screened drug molecules by DFT analysis illustrated that these molecules are reactive in nature. The protein-ligand complexes were subjected to molecular dynamics simulation. Molecular dynamics analysis such as RMSD, RMSF, Rg, SASA, PCA, and FEL results suggested that FmtA-drug(s) complexes are stable. MM-GBSA binding affinity and QM/MM results (ΔG, ΔH, and ΔS) revealed that active site residues (Ser127, Lys130, Tyr211, Asp213, and Asn343) of FmtA played an essential for the binding of the drug(s) to form a lower energy stable protein-ligand complexes. FmtA^Δ42 was purified using cation exchange and gel filtration chromatography. Fluorescence spectroscopy and circular dichroism results showed that interactions of drugs with FmtA^Δ42 affect the tertiary structure and increase the thermostability of the protein. The screened molecules need to be tested and could be further modified to develop the antimicrobial compounds against S. aureus.

ABBV-744 as a potential inhibitor of SARS-CoV-2 main protease enzyme against COVID-19

A new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide and become pandemic with thousands new deaths and infected cases globally. To address coronavirus disease (COVID-19), currently no effective drug or vaccine is available. This necessity motivated us to explore potential lead compounds by considering drug repurposing approach targeting main protease (M^pro) enzyme of SARS-CoV-2. This enzyme considered to be an attractive drug target as it contributes significantly in mediating viral replication and transcription. Herein, comprehensive computational investigations were performed to identify potential inhibitors of SARS-CoV-2 M^pro enzyme. The structure-based pharmacophore modeling was developed based on the co-crystallized structure of the enzyme with its biological active inhibitor. The generated hypotheses were applied for virtual screening based PhaseScore. Docking based virtual screening workflow was used to generate hit compounds using HTVS, SP and XP based Glide GScore. The pharmacological and physicochemical properties of the selected lead compounds were characterized using ADMET. Molecular dynamics simulations were performed to explore the binding affinities of the considered lead compounds. Binding energies revealed that compound ABBV-744 binds to the M^pro with strong affinity (ΔG_bind -45.43 kcal/mol), and the complex is more stable in comparison with other protein-ligand complexes. Our study classified three best compounds which could be considered as promising inhibitors against main protease SARS-CoV-2 virus.

Can natural products stop the SARS-CoV-2 virus? A docking and molecular dynamics study of a natural product database

Background: The SARS-CoV-2 3CLpro is one of the primary targets for designing new and repurposing known drugs. Methodology: A virtual screening of molecules from the Natural Product Atlas was performed, followed by molecular dynamics simulations of the most potent inhibitor bound to two conformations of the protease and into two binding sites. Conclusion: Eight molecules with appropriate ADMET properties are suggested as potential inhibitors. The greatest benefit of this study is the demonstration that these ligands can bind in the catalytic site but also to the groove between domains II and III, where they interact with a series of residues which have an important role in the dimerization and the maturation process of the enzyme.

Molecular Dynamics Protocols for the Study of Cyclodextrin Drug Delivery Systems

Hypertension treatment is a current therapeutic priority as there is a constantly increasing part of the population that suffers from this risk factor, which may lead to cardiovascular and encephalic episodes and eventually to death. A number of marketed medicines consist of active ingredients that may be relatively potent; however, there is plenty of room to enhance their pharmacological profile and therapeutic index by improving specific physicochemical properties. In this work, we focus on a class of blood pressure regulators, called sartans, and we present the computational scheme for the pharmacological improvement of irbesartan (IRB) as a representative example. IRB has been shown to exert increased pharmacological action compared with other sartans, but it appears to be highly lipophilic and violates Lipinski rule (MLogP >4.15). To circumvent this drawback, proper hydrophilic molecules, such as cyclodextrins, can be used as drug carriers. This chapter describes the combinatory use of computational methods, namely molecular docking, quantum mechanics, molecular dynamics, and free energy calculations, to study the interactions and the energetic contributions that govern the IRB:cyclodextrin association. We provide a detailed computational protocol, which aims to assist the improvement of the pharmacological properties of sartans. This protocol can also be applied to any other drug molecule with diminished hydrophilic character.

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

Small molecule stabilization of non-native protein-protein interactions of SARS-CoV-2 N protein as a mechanism of action against COVID-19

The outbreak of COVID-19, the disease caused by SARS-CoV-2, continues to affect millions of people around the world. The absence of a globally distributed effective treatment makes the exploration of new mechanisms of action a key step to address this situation. Stabilization of non-native Protein-Protein Interactions (PPIs) of the nucleocapsid protein of MERS-CoV has been reported as a valid strategy to inhibit viral replication. In this study, the applicability of this unexplored mechanism of action against SARS-CoV-2 is analyzed. During our research, we were able to find three inducible interfaces of SARS-CoV-2 N protein NTD, compare them to the previously reported MERS-CoV stabilized dimers, and identify those residues that are responsible for their formation. A drug discovery protocol implemented consisting of docking, molecular dynamics and MM-GBSA enabled us to find several compounds that might be able to exploit this mechanism of action. In addition, a common catechin skeleton was found among many of these molecules, which might be useful for further drug design. We consider that our findings could motivate future research in the fields of drug discovery and design towards the exploitation of this previously unexplored mechanism of action against COVID-19.

Communicated by Ramaswamy H. Sarma

Binding selectivity of inhibitors toward the first over the second bromodomain of BRD4: theoretical insights from free energy calculations and multiple short molecular dynamics simulations

Bromodomain-containing protein 4 (BRD4) plays an important role in mediating gene transcription involved in cancers and non-cancer diseases such as acute heart failure and inflammatory diseases. In this work, multiple short molecular dynamics (MSMD) simulations are integrated with a molecular mechanics generalized Born surface area (MM-GBSA) approach to decipher binding selectivity of three inhibitors 8NS, 82Y, and 837 toward two domains BD1 and BD2 of BRD4. The results demonstrate that the enthalpy effects play critical roles in selectivity identification of inhibitors toward BD1 and BD2, determining that 8NS has better selectivity toward BD2 than BD1, while 82Y and 837 more favorably bind to BD1 than BD2. A residue-based free-energy decomposition method was used to calculate an inhibitor-residue interaction spectrum and unveil contributions of separate residues to binding selectivity. The results identify six common residues, containing (P82, P375), (V87, V380), (L92, L385), (L94, L387), (N140, N433), and (I146, V439) individually belonging to (BD1, BD2) of BRD4, and yield a considerable binding difference of inhibitors to BD1 and BD2, suggesting that these residues play key roles in binding selectivity of inhibitors toward BD1 and BD2 of BRD4. Therefore, these results provide useful dynamics information and a structure affinity relationship for the development of highly selective inhibitors targeting BD1 and BD2 of BRD4.

Structural evidence for pheromone discrimination by the pheromone binding protein 3 from Plutella xylostella

Insect pheromone binding proteins (PBPs) are believed to have a high degree of pheromone selectivity, acting as the first filter to discriminate specific pheromones from other volatile compounds. Herein, we provide evidence using homology-based model for the pheromone discrimination of Plutella xylostella pheromone binding protein 3 (PxPBP3). Combining molecular dynamics simulations and in vitro binding assays, two dominant sites are determined to be essential for the PxPBP3 to discriminate (Z)-11-hexadecenyl acetate (Hexadecenyl) from (Z)-11-hexadecenal (Hexadecenal). As the first key site for pheromone discrimination, Arg111 is indispensable to the PxPBP3-Hexadecenyl interaction. However, its importance in the binding of Hexadecenal to PxPBP3 is greatly reduced. A second site where pheromone discrimination occurs is a small loop (residues 34-38) in PxPBP3. It is shown that the hydrophobic strength provided by three hydrophobic residues (Phe34, Tyr37, and Trp38) in the small loop is significantly biased in the two complexes formed by PxPBP3 and the two pheromones. The discrimination capacity of PxPBP3 indicates that the P. xylostella pheromones may not share the same peri-receptor pathway, although they both show high affinity to PxPBP3.

Identification of FDA approved drugs and nucleoside analogues as potential SARS-CoV-2 A1pp domain inhibitor: An in silico study

Coronaviruses are known to infect respiratory tract and intestine. These viruses possess highly conserved viral macro domain A1pp having adenosine diphosphate (ADP)-ribose binding and phosphatase activity sites. A1pp inhibits adenosine diphosphate (ADP)-ribosylation in the host and promotes viral infection and pathogenesis. We performed in silico screening of FDA approved drugs and nucleoside analogue library against the recently reported crystal structure of SARS-CoV-2 A1pp domain. Docking scores and interaction profile analyses exhibited strong binding affinity of eleven FDA approved drugs and five nucleoside analogues NA1 (−13.84), nadide (−13.65), citicholine (−13.54), NA2 (−12.42), and NA3 (−12.27). The lead compound NA1 exhibited significant hydrogen bonding and hydrophobic interaction at the natural substrate binding site. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface (SASA), hydrogen bond formation, principle component analysis, and free energy landscape calculations for NA1 bound protein displayed stable complex formation in 100 ns molecular dynamics simulation, compared to unbound macro domain and natural substrate adenosine-5-diphosphoribose bound macro domain that served as a positive control. The molecular mechanics Poisson–Boltzmann surface area analysis of NA1 demonstrated binding free energy of −175.978 ± 0.401 kJ/mol in comparison to natural substrate which had binding free energy of −133.403 ± 14.103 kJ/mol. In silico analysis by modelling tool ADMET and prediction of biological activity of these compounds further validated them as putative therapeutic molecules against SARS-CoV-2. Taken together, this study offers NA1 as a lead SARS-CoV-2 A1pp domain inhibitor for future testing and development as therapeutics against human coronavirus.

The Effect of Deuteration on the H2 Receptor Histamine Binding Profile: A Computational Insight into Modified Hydrogen Bonding Interactions

We used a range of computational techniques to reveal an increased histamine affinity for its H₂ receptor upon deuteration, which was interpreted through altered hydrogen bonding interactions within the receptor and the aqueous environment preceding the binding. Molecular docking identified the area between third and fifth transmembrane α-helices as the likely binding pocket for several histamine poses, with the most favorable binding energy of −7.4 kcal mol⁻¹ closely matching the experimental value of −5.9 kcal mol⁻¹. The subsequent molecular dynamics simulation and MM-GBSA analysis recognized Asp98 as the most dominant residue, accounting for 40% of the total binding energy, established through a persistent hydrogen bonding with the histamine −NH₃⁺ group, the latter further held in place through the N–H∙∙∙O hydrogen bonding with Tyr250. Unlike earlier literature proposals, the important role of Thr190 is not evident in hydrogen bonds through its −OH group, but rather in the C–H∙∙∙π contacts with the imidazole ring, while its former moiety is constantly engaged in the hydrogen bonding with Asp186. Lastly, quantum-chemical calculations within the receptor cluster model and utilizing the empirical quantization of the ionizable X–H bonds (X = N, O, S), supported the deuteration-induced affinity increase, with the calculated difference in the binding free energy of −0.85 kcal mol⁻¹, being in excellent agreement with an experimental value of −0.75 kcal mol⁻¹, thus confirming the relevance of hydrogen bonding for the H₂ receptor activation.

Targeting phosphatidylinositol 3-kinase gamma (PI3Kγ): Discovery and development of its selective inhibitors

Phosphatidylinositol 3-kinase gamma (PI3Kγ) has been regarded as a promising drug target for the treatment of advanced solid tumors, leukemia, lymphoma, and inflammatory and autoimmune diseases. However, the high level of structural conservation among the members of the PI3K family and the diverse physiological roles of Class I PI3K isoforms (α, β, δ, and γ) highlight the importance of isoform selectivity in the development of PI3Kγ inhibitors. In this review, we provide an overview of the structural features of PI3Kγ that influence γ-isoform selectivity and discuss the structure-selectivity-activity relationship of existing clinical PI3Kγ inhibitors. Additionally, we summarize the experimental and computational techniques utilized to identify PI3Kγ inhibitors. The insights gained so far could be used to overcome the main challenges in development and accelerate the discovery of PI3Kγ-selective inhibitors.

Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation

Computational studies play an increasingly important role in chemistry and biophysics, mainly thanks to improvements in hardware and algorithms. In drug discovery and development, computational studies can reduce the costs and risks of bringing a new medicine to market. Computational simulations are mainly used to optimize promising new compounds by estimating their binding affinity to proteins. This is challenging due to the complexity of the simulated system. To assess the present and future value of simulation for drug discovery, we review key applications of advanced methods for sampling complex free-energy landscapes at near nonergodicity conditions and for estimating the rate coefficients of very slow processes of pharmacological interest. We outline the statistical mechanics and computational background behind this research, including methods such as steered molecular dynamics and metadynamics. We review recent applications to pharmacology and drug discovery and discuss possible guidelines for the practitioner. Recent trends in machine learning are also briefly discussed. Thanks to the rapid development of methods for characterizing and quantifying rare events, simulation's role in drug discovery is likely to expand, making it a valuable complement to experimental and clinical approaches.

Hybrid Quinazoline 1,3,5-Triazines as Epidermal Growth Factor Receptor (EGFR) Inhibitors with Anticancer Activity: Design, Synthesis, and Computational Study

We report a series of hybrid quinazoline-1,3,5-triazine derivatives as EGFR inhibitors, which were synthesised and tested by using a variety of in vitro, in silico, and in vivo techniques. The derivatives were found to be active against different cancer cell lines and nontoxic against normal ones, with compounds 7 c, 7 d, 7 e, and 7 j being the most potent ones. The derivatives were also evaluated for angiogenesis inhibition potency in chicken eggs, and molecular docking and dynamics simulation studies were carried out to elucidate the fundamental substituent groups essential for their bioactivity. Additionally, a SAR study of the derivatives was performed for future compound optimisation. These studies suggested that the derivatives have a high affinity towards EGFR with favourable pharmacological properties. The most active compound (7 e) was further evaluated for in vivo anticancer activity against DMBA-induced tumours in female Sprague-Dawley rats as well as its effects on plasma antioxidant status, biotransformation enzymes, and lipid profile. The study suggested that 7 e has lead properties against breast cancer and can serve as a starting compound for further development of anti-EGFR compounds.

Computational Investigation of Structural Dynamics of SARS-CoV-2 Methyltransferase-Stimulatory Factor Heterodimer nsp16/nsp10 Bound to the Cofactor SAM

Recently, a highly contagious novel coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has emerged, posing a global threat to public health. Identifying a potential target and developing vaccines or antiviral drugs is an urgent demand in the absence of approved therapeutic agents. The 5'-capping mechanism of eukaryotic mRNA and some viruses such as coronaviruses (CoVs) are essential for maintaining the RNA stability and protein translation in the virus. SARS-CoV-2 encodes S-adenosyl-L-methionine (SAM) dependent methyltransferase (MTase) enzyme characterized by nsp16 (2'-O-MTase) for generating the capped structure. The present study highlights the binding mechanism of nsp16 and nsp10 to identify the role of nsp10 in MTase activity. Furthermore, we investigated the conformational dynamics and energetics behind the binding of SAM to nsp16 and nsp16/nsp10 heterodimer by employing molecular dynamics simulations in conjunction with the Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) method. We observed from our simulations that the presence of nsp10 increases the favorable van der Waals and electrostatic interactions between SAM and nsp16. Thus, nsp10 acts as a stimulator for the strong binding of SAM to nsp16. The hydrophobic interactions were predominately identified for the nsp16-nsp10 interactions. Also, the stable hydrogen bonds between Ala83 (nsp16) and Tyr96 (nsp10), and between Gln87 (nsp16) and Leu45 (nsp10) play a vital role in the dimerization of nsp16 and nsp10. Besides, Computational Alanine Scanning (CAS) mutagenesis was performed, which revealed hotspot mutants, namely I40A, V104A, and R86A for the dimer association. Hence, the dimer interface of nsp16/nsp10 could also be a potential target in retarding the 2'-O-MTase activity in SARS-CoV-2. Overall, our study provides a comprehensive understanding of the dynamic and thermodynamic process of binding nsp16 and nsp10 that will contribute to the novel design of peptide inhibitors based on nsp16.

Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery

Predicting protein-ligand binding affinities and the associated thermodynamics of biomolecular recognition is a primary objective of structure-based drug design. Alchemical free energy simulations offer a highly accurate and computationally efficient route to achieving this goal. While the AMBER molecular dynamics package has successfully been used for alchemical free energy simulations in academic research groups for decades, widespread impact in industrial drug discovery settings has been minimal because of the previous limitations within the AMBER alchemical code, coupled with challenges in system setup and postprocessing workflows. Through a close academia-industry collaboration we have addressed many of the previous limitations with an aim to improve accuracy, efficiency, and robustness of alchemical binding free energy simulations in industrial drug discovery applications. Here, we highlight some of the recent advances in AMBER20 with a focus on alchemical binding free energy (BFE) calculations, which are less computationally intensive than alternative binding free energy methods where full binding/unbinding paths are explored. In addition to scientific and technical advances in AMBER20, we also describe the essential practical aspects associated with running relative alchemical BFE calculations, along with recommendations for best practices, highlighting the importance not only of the alchemical simulation code but also the auxiliary functionalities and expertise required to obtain accurate and reliable results. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative BFE simulations in AMBER20, with a focus on real-world drug discovery applications.

Computational Investigation of the Binding Dynamics of Oligo p-Phenylene Ethynylene Fluorescence Sensors and Aβ Oligomers

Amyloid protein aggregates are pathological hallmarks of neurodegenerative disorders such as Alzheimer's (AD) and Parkinson's (PD) diseases and are believed to be formed well before the onset of neurodegeneration and cognitive impairment. Monitoring the course of protein aggregation is thus vital to understanding and combating these diseases. We have recently demonstrated that a novel class of fluorescence sensors, oligomeric p-phenylene ethynylene (PE)-based electrolytes (OPEs) selectively bind to and detect prefibrillar and fibrillar aggregates of AD-related amyloid-β (Aβ) peptides over monomeric Aβ. In this study, we investigated the binding between two OPEs, anionic OPE12- and cationic OPE24+, and to two different β-sheet rich Aβ oligomers using classical all-atom molecular dynamics simulations. Our simulations have revealed a number of OPE binding sites on Aβ oligomer surfaces, and these sites feature hydrophobic amino acids as well as oppositely charged amino acids. Binding energy calculations show energetically favorable interactions between both anionic and cationic OPEs with Aβ oligomers. Moreover, OPEs bind as complexes as well as single molecules. Compared to free OPEs, Aβ protofibril bound OPEs show backbone planarization with restricted rotations and reduced hydration of the ethyl ester end groups. These characteristics, along with OPE complexation, align with known mechanisms of binding induced OPE fluorescence turn-on and spectral shifts from a quenched, unbound state in aqueous solutions. This study thus sheds light on the molecular-level details of OPE-Aβ protofibril interactions and provides a structural basis for fluorescence turn-on sensing modes of OPEs.

Identification of saquinavir as a potent inhibitor of dimeric SARS-CoV2 main protease through MM/GBSA

Among targets selected for studies aimed at identifying potential inhibitors against COVID-19, SARS-CoV2 main proteinase (M^pro) is highlighted. M^pro is indispensable for virus replication and is a promising target of potential inhibitors of COVID-19. Recently, monomeric SARS-CoV2 M^pro, drug repurposing, and docking methods have facilitated the identification of several potential inhibitors. Results were refined through the assessment of dimeric SARS-CoV2 M^pro, which represents the functional state of enzyme. Docking and molecular dynamics (MD) simulations combined with molecular mechanics/generalized Born surface area (MM/GBSA) studies indicated that dimeric M^pro most significantly impacts binding affinity tendency compared with the monomeric state, which suggests that dimeric state is most useful when performing studies aimed at identifying drugs targeting M^pro. In this study, we extend previous research by performing docking and MD simulation studies coupled with an MM/GBSA approach to assess binding of dimeric SARS-CoV2 M^pro to 12 FDA-approved drugs (darunavir, indinavir, saquinavir, tipranavir, diosmin, hesperidin, rutin, raltegravir, velpatasvir, ledipasvir, rosuvastatin, and bortezomib), which were identified as the best candidates for the treatment of COVID-19 in some previous dockings studies involving monomeric SARS-CoV2 M^pro. This analysis identified saquinavir as a potent inhibitor of dimeric SARS-CoV2 M^pro; therefore, the compound may have clinical utility against COVID-19.

X-ray Structure, Bioinformatics Analysis, and Substrate Specificity of a 6-Phospho-β-glucosidase Glycoside Hydrolase 1 Enzyme from Bacillus licheniformis

In bacteria, mono- and disaccharides are phosphorylated during the uptake processes through the vastly spread transport system phosphoenolpyruvate-dependent phosphotransferase. As an initial step in the phosphorylated disaccharide metabolism pathway, 6-phospho-β-glucosidases and 6-phospho-β-galactosidases play a crucial role by releasing phosphorylated and nonphosphorylated monosaccharides. However, structural determinants for the specificity of these enzymes still need to be clarified. Here, an X-ray structure of a glycoside hydrolase family 1 enzyme from Bacillus licheniformis, hereafter known as BlBglH, was determined at 2.2 Å resolution, and its substrate specificity was investigated. The sequence of BlBglH was compared to the sequences of 58 other GH1 enzymes using sequence alignments, sequence identity calculations, phylogenetic analysis, and motif discovery. Through these various analyses, BlBglH was found to have sequence features characteristic of the 6-phospho-β-glucosidase activity enzymes. Motif and structural observations highlighted the importance of loop L8 in 6-phospho-β-glucosidase activity enzymes. To further affirm enzyme specificity, molecular docking and molecular dynamics simulations were performed using the crystallographic structure of BlBglH. Docking was carried out with a 6-phospho-β-glucosidase enzyme activity positive and negative control ligand, followed by 400 ns of MD simulations. The positive and negative control ligands were PNP6Pglc and PNP6Pgal, respectively. PNP6Pglc maintained favorable interactions within the active site until the end of the MD simulation, while PNP6Pgal exhibited instability. The favorable binding of substrate stabilized the loops that surround the active site. Binding free energy calculations showed that the PNP6Pglc complex had a substantially lower binding energy compared to the PNP6Pgal complex. Altogether, the findings of this study suggest that BlBglH possesses 6-phospho-β-glucosidase enzymatic activity and revealed sequence and structural differences between bacterial GH1 enzymes of various activities.

Pathway enrichment analysis of virus-host interactome and prioritization of novel compounds targeting the spike glycoprotein receptor binding domain-human angiotensin-converting enzyme 2 interface to combat SARS-CoV-2

SARS-CoV-2 has become a pandemic causing a serious global health concern. The absence of effective drugs for treatment of the disease has caused its rapid spread on a global scale. Similarly to the SARS-CoV, the SARS-CoV-2 is also involved in a complex interplay with the host cells. This infection is characterized by a diffused alveolar damage consistent with the Acute Respiratory Disease Syndrome (ARDS). To explore the complex mechanisms of the disease at the system level, we used a network medicine tools approach. The protein-protein interactions (PPIs) between the SARS-CoV and the associated human cell proteins are crucial for the viral pathogenesis. Since the cellular entry of SARS-CoV-2 is accomplished by binding of the spike glycoprotein binding domain (RBD) to the human angiotensin-converting enzyme 2 (hACE2), a molecule that can bind to the spike RDB-hACE2 interface could block the virus entry. Here, we performed a virtual screening of 55 compounds to identify potential molecules that can bind to the spike glycoprotein and spike-ACE2 complex interface. It was found that the compound ethyl 1-{3-[(2,4-dichlorobenzyl) carbamoyl]-1-ethyl-6-fluoro-4-oxo-1,4-dihydro-7-quinolinyl}-4-piperidine carboxylate (the S54 ligand) and ethyl 1-{3-[(2,4-dichlorobenzyl) carbamoyl]-1-ethyl-6-fluoro-4-oxo-1,4-dihydro-7-quinolinyl}-4 piperazine carboxylate (the S55 ligand) forms hydrophobic interactions with Tyr41A, Tyr505B and Tyr553B, Leu29A, Phe495B, respectively of the spike glycoprotein, the hotspot residues in the spike glycoprotein RBD-hACE2 binding interface. Furthermore, molecular dynamics simulations and free energy calculations using the MM-GBSA method showed that the S54 ligand is a stronger binder than a known SARS-CoV spike inhibitor SSAA09E3 (N-(9,10-dioxo-9, 10-dihydroanthracen-2-yl) benzamide).

Communicated by Ramaswamy H. Sarma

Structure dynamics reveal key residues essential for the sense of 1-dodecanol by Cydia pomonella pheromone binding protein 2 (CpomPBP2)

BACKGROUND

Cydia pomonella, a worldwide quarantine fruit pest, causes great damage to fruit production every year. Sex pheromone-mediated control of C. pomonella has been widely used. As an indispensable ingredient of commercial sex attractants, 1-dodecanol (Dod) works to synergize the effect of codlemone in attracting male moths of C. pomonella. The interactions between Dod and its transporter protein, C. pomonella pheromone-binding protein 2 (CpomPBP2), provide inspiration for chemical optimizations to improve the synergistic effects of Dod.

RESULTS

In this research, molecular simulations and biological verifications were used in combination to uncover key residues in CpomPBP2 essential for sensing Dod. After performing 150 ns molecular dynamics (MD) simulations, the C1-C12 chain of Dod was found to be locked by the van der Waals energy contributed by the hydrophobic residues Phe12, Leu68, and Ile113, whereas the -OH part of Dod was anchored by the H-bond derived from Glu98 and the salt-bridge derived from Arg109. Because of the importance of these two electrostatic interactions, Glu98 and Arg109 were further verified as key residues in determining the binding affinity between Dod and CpomPBP2. In addition, interactions unfavorable to the binding of Dod were described.

CONCLUSION

The research detailed the discovery of key residues involved in CpomPBP2-Dod interactions. Our results provide guidance and caution for the prospective discovery, optimization, and design of novel chemicals with a similar or stronger synergistic effect to codlemone in controlling C. pomonella.