MolTaut: A Tool for the Rapid Generation of Favorable Tautomer in Aqueous Solution.

Fast and proper treatment of the tautomeric states for drug-like molecules is critical in computer-aided drug discovery since the major tautomer of a molecule determines its pharmacophore features and physical properties. We present MolTaut, a tool for the rapid generation of favorable states of drug-like molecules in water. MolTaut works by enumerating possible tautomeric states with tautomeric transformation rules, ranking tautomers with their relative internal energies and solvation energies calculated by AI-based models, and generating preferred ionization states according to predicted microscopic pKa. Our test shows that the ranking ability of the AI-based tautomer scoring approach is comparable to the DFT method (wB97X/6-31G*//M062X/6-31G*/SMD) from which the AI models try to learn. We find that the substitution effect on tautomeric equilibrium is well predicted by MolTaut, which is helpful in computer-aided ligand design. The source code of MolTaut is freely available to researchers and can be accessed at https://github.com/xundrug/moltaut. To facilitate the usage of MolTaut by medicinal chemists, we made a free web server, which is available at http://moltaut.xundrug.cn. MolTaut is a handy tool for investigating the tautomerization issue in drug discovery.

MolHyb: A Web Server for Structure-Based Drug Design by Molecular Hybridization.

Molecular hybridization is a widely used ligand design method in drug discovery. In this study, we present MolHyb, a web server for structure-based ligand design by molecular hybridization. The input of MolHyb is a protein file and a seed compound file. MolHyb tries to generate novel ligands through hybridizing the seed compound with helper compounds that bind to the same protein target or similar proteins. To facilitate the job of getting helper compounds, we compiled a modeled protein-ligand structure database as an extension to crystal structures in the PDB database by placing the bioactive compounds in ChEMBL into their corresponding 3D protein binding pocket properly. MolHyb works by searching for helper compounds from the protein-ligand structure database and migrating chemical moieties from helper compounds to the seed compound efficiently. Hybridization is performed at both cyclic and acyclic bonds. The users can also input their own helper compounds to MolHyb. We hope that MolHyb will be a useful tool for rational drug design. MolHyb is freely available at http://molhyb.xundrug.cn/.

AA-Score: a New Scoring Function Based on Amino Acid-Specific Interaction for Molecular Docking.

The protein-ligand scoring function plays an important role in computer-aided drug discovery and is heavily used in virtual screening and lead optimization. In this study, we developed a new empirical protein-ligand scoring function with amino acid-specific interaction components for hydrogen bond, van der Waals, and electrostatic interactions. In addition, hydrophobic, π-stacking, π-cation, and metal-ligand interactions are also included in the new scoring function. To better evaluate the performance of the AA-Score, we generated several new test sets for evaluation of scoring, ranking, and docking performances, respectively. Extensive tests show that AA-Score performs well on scoring, docking, and ranking as compared to other widely used traditional scoring functions. The performance improvement of AA-Score benefits from the decomposition of individual interaction into amino acid-specific types. To facilitate applications, we developed an easy-to-use tool to analyze protein-ligand interaction fingerprint and predict binding affinity using the AA-Score. The source code and associated running examples can be found at https://github.com/xundrug/AA-Score-Tool.

Stereochemically altered cephalosporins as potent inhibitors of New Delhi metallo-ß-lactamases.

Antibiotic resistance caused by ß-lactamases, particularly metallo-ß-lactamases, has been a major threat to public health globally. New Delhi metallo-ß-lactamase-1 (NDM-1) represents one of the most important metallo-ß-lactamases; the production of NDM-1 in bacterial pathogen significantly reduces the efficacy of ß-lactam antibiotics, including life-saving carbapenems. Herein, we have demonstrated stereochemically altered cephalosporins as potent inhibitors against NDM-1, as well as mutants of NDM. The structure and activity relationship (SAR) study on over twenty cephalosporin analogues discloses the stereochemistry and the substituents on 7-position and 3'-position of cephalosporin are critical to suppress the activity of NDM-1 and the optimal compound 1u exhibited an IC50 of 0.13 µM. Furthermore, a crystal complex of NDM-1 and 1u has been obtained, suggesting this cephalosporin derivative inhibits enzyme activity by the formation of a relatively stable hydrolytic product-NDM-1 intermediate. The discovery in this study may pave the way to turn cephalosporin, a natural substrate of ß-lactamase, into an effective NDM-1 inhibitor to combat antibiotic resistance.

HobPre: accurate prediction of human oral bioavailability for small molecules.

Human oral bioavailability (HOB) is a key factor in determining the fate of new drugs in clinical trials. HOB is conventionally measured using expensive and time-consuming experimental tests. The use of computational models to evaluate HOB before the synthesis of new drugs will be beneficial to the drug development process. In this study, a total of 1588 drug molecules with HOB data were collected from the literature for the development of a classifying model that uses the consensus predictions of five random forest models. The consensus model shows excellent prediction accuracies on two independent test sets with two cutoffs of 20% and 50% for classification of molecules. The analysis of the importance of the input variables allowed the identification of the main molecular descriptors that affect the HOB class value. The model is available as a web server at www.icdrug.com/ICDrug/ADMET for quick assessment of oral bioavailability for small molecules. The results from this study provide an accurate and easy-to-use tool for screening of drug candidates based on HOB, which may be used to reduce the risk of failure in late stage of drug development.

MolGpka: A Web Server for Small Molecule pKa Prediction Using a Graph-Convolutional Neural Network.

pKa is an important property in the lead optimization process since the charge state of a molecule in physiologic pH plays a critical role in its biological activity, solubility, membrane permeability, metabolism, and toxicity. Accurate and fast estimation of small molecule pKa is vital during the drug discovery process. We present MolGpKa, a web server for pKa prediction using a graph-convolutional neural network model. The model works by learning pKa related chemical patterns automatically and building reliable predictors with learned features. ACD/pKa data for 1.6 million compounds from the ChEMBL database was used for model training. We found that the performance of the model is better than machine learning models built with human-engineered fingerprints. Detailed analysis shows that the substitution effect on pKa is well learned by the model. MolGpKa is a handy tool for the rapid estimation of pKa during the ligand design process. The MolGpKa server is freely available to researchers and can be accessed at https://xundrug.cn/molgpka.

Molecular basis of SMAC-XIAP binding and the effect of electrostatic polarization.

X-chromosome-linked inhibitor of apoptosis (XIAP) inhibits cell apoptosis. Overexpression of XIAP is widely found in human cancers. Second mitochondria-derived activator of caspase (SMAC) protein inhibits XIAP through binding with Baculovirus Inhibitor of apoptosis protein Repeat (BIR) 3 or BIR2 domain of XIAP. In this study, molecular dynamics (MD) simulations and the alanine scanning calculations by MM-GBSA_IE method were used to investigate the protein-peptide interaction between BIR3 and BIR2 domains of XIAP and SMAC peptide. Energetic contribution of each binding residue is calculated and hotspots on both XIAP and SMAC were identified using computational alanine scanning with interaction entropy method. We found that electrostatic polarization is important in stabilizing the protein-protein complex structure in MD simulation. By using polarized protein-specific charges, much better agreement with experimental result is obtained for calculated binding free energies compared to those using standard (nonpolarizable) AMBER force field. In particular, excellent correlation between calculated binding free energies in alanine scanning with mutational experimental data was obtained for BIR3/SMAC binding.Communicated by Ramaswamy H. Sarma.

FragRep: A Web Server for Structure-Based Drug Design by Fragment Replacement.

The design of efficient computational tools for structure-guided ligand design is essential for the drug discovery process. We hereby present FragRep, a new web server for structure-based ligand design by fragment replacement. The input is a protein and a ligand structure, either from protein data bank or from molecular docking. Users can choose specific substructures they want to modify. The server tries to find suitable fragments that not only meet the geometric requirements of the remaining part of the ligand but also fit well with local protein environments. FragRep is a powerful computational tool for the rapid generation of ligand design ideas; either in scaffold hopping or bioisosteric replacing. The FragRep Server is freely available to researchers and can be accessed at http://xundrug.cn/fragrep.

MolOpt: A Web Server for Drug Design using Bioisosteric Transformation.

BACKGROUND: Bioisosteric replacement is widely used in drug design for lead optimization. However, the identification of a suitable bioisosteric group is not an easy task. METHODS: In this work, we present MolOpt, a web server for in silico drug design using bioisosteric transformation. Potential bioisosteric transformation rules were derived from data mining, deep generative machine learning and similarity comparison. MolOpt tries to assist the medicinal chemist in his/her search for what to make next. RESULTS AND DISCUSSION: By replacing molecular substructures with similar chemical groups, MolOpt automatically generates lists of analogues. MolOpt also evaluates forty important pharmacokinetic and toxic properties for each newly designed molecule. The transformed analogues can be assessed for possible future study. CONCLUSION: MolOpt is useful for the identification of suitable lead optimization ideas. The MolOpt Server is freely available for use on the web at http://xundrug.cn/molopt.

Developing an effective polarizable bond method for small molecules with application to optimized molecular docking.

Electrostatic interaction plays an essential role in protein-ligand binding. Due to the polarization effect, electrostatic interactions are largely impacted by their local environments. However, traditional force fields use fixed point charge-charge interactions to describe electrostatic interactions but is unable to include the polarization effect. The lack of the polarization effect in the force field representation can result in substantial error in biomolecular studies, such as molecular dynamics and molecular docking. Docking programs usually employ traditional force fields to estimate the binding energy between a ligand and a protein for pose selection or scoring. The intermolecular interaction energy mainly consists of van der Waals and electrostatic interaction in the force field representation. In the current study, we developed an Effective Polarizable Bond (EPB) method for small organic molecules and applied this EPB method to optimize protein-ligand docking in computational tests for a variety of protein-ligand systems. We tested the method on a set of 38 cocrystallized structures taken from the Protein Data Bank (PDB) and found that the maximum error was reduced from 7.98 Å to 2.03 Å when using EPB Dock, providing strong evidence that the use of EPB charges is important. We found that our optimized docking approach with EPB charges could improve the docking performance, sometimes dramatically, and the maximum error was reduced from 12.88 Å to 1.57 Å in Optimized Docking (in the case of 1fqx). The average RMSD decreased from 2.83 Å to 1.85 Å. Further investigations showed that the use of the EBP method could enhance intermolecular hydrogen bonding, which is a major contributing factor to improved docking performance. Developed tools for the calculation of the polarized ligand charge from a protein-ligand complex structure with the EPB method are freely available on GitHub (https://github.com/Xundrug/EPB).

A force consistent method for electrostatic energy calculation in fluctuating charge model.

A practical approach to include the polarization effect in a molecular force field is the fluctuating charge method in which atomic charges vary as the configuration of the molecular system changes. However, the use of the Coulomb formula to evaluate energy in a fluctuating charge method is theoretically inconsistent with the forces given by the fluctuating method. In this work, we propose a force-consistent method to correctly calculate electrostatic energies of molecular systems using a fluctuating charge model (Effective Polarizable Bond or EPB). In this protocol, the electrostatic energy is obtained by numerical interaction of the atomic forces along the MD trajectory, rather than using the default Coulomb formula in the EPB model. Test study on the benchmark Barnase-Barstar protein-protein interaction system demonstrates that although the total electrostatic energy of the system shows little deviation due to the averaging effect, specific residue-residue electrostatic interaction energy is affected and the level of the effect depends on the charges of the interacting residues with charged residues showing pronounced differences in calculated energies between using the current protocol and the standard Coulomb formula. It is recommended that the proposed numerical interaction method should be preferred in the calculation of electrostatic energy in fluctuating charge models used in molecular dynamics simulations.

Electrostatic Polarization Effect on Cooperative Aggregation of Full Length Human Islet Amyloid.

Amyloid aggregation initiates from a slow nucleation process, where the association of monomers is unfavorable in energetics. In principle, the enthalpy change for aggregation should compensate the entropy loss as new monomers attach to formed oligomers. However, the classical force fields with fixed point charges failed to yield the correct enthalpy change due to the lack of electrostatic polarization effect on amyloid aggregation. In this work, we performed molecular dynamics simulation for the full-length human islet amyloid using the polarized protein-specific charges and calculated the electrostatic interaction energy for amyloid oligomers. The results of molecular dynamics simulation show that the aggregates simulated with polarized charges have larger enthalpy change than that with fixed charges. The large enthalpy change mainly originates from the electrostatic polarization, which makes a significant contribution to the cooperative effect of aggregation and facilitates the nucleation process of amyloids.

eMolTox: prediction of molecular toxicity with confidence.

Summary: In this work, we present eMolTox, a web server for the prediction of potential toxicity associated with a given molecule. A total of 174 toxicology-related in vitro/vivo experimental datasets were used for model construction and Mondrian conformal prediction was used to estimate the confidence of the resulting predictions. Toxic substructure analysis is also implemented in eMolTox. eMolTox predicts and displays a wealth of information of potential molecular toxicities for safety analysis in drug development. Availability and implementation: The eMolTox Server is freely available for use on the web at http://xundrug.cn/moltox. Supplementary information: Supplementary data are available at Bioinformatics online.

ES2 enhances the efficacy of chemotherapeutic agents in ABCB1-overexpressing cancer cells in vitro and in vivo.

ES2 is a new type of jatrophane diterpenoid ester isolated from the fructus E. sororia, a traditional Uyghur medicine in China. Here we reported the multidrug resistance (MDR) reversal effect of ES2 in vitro and in vivo by modulating the function of ATP-binding cassette subfamily B member 1 (ABCB1). ES2 exhibited low cytotoxicity to ABCB1-overexpressing MDR cells and their parental sensitive cells, but sensitized the MDR cells and ABCB1-transfected HEK293 cells to chemotherapeutic drugs that are ABCB1 substrates. The reversal ability of ES2 was primarily due to the inhibition of the efflux function of ABCB1. Moreover, ES2 stimulated the ATPase activity of ABCB1 in a concentration-dependent manner. There was no change in the expression of ABCB1 in the presence of ES2. The molecular docking analysis indicated that ES2 bond to the drug-binding site of ABCB1 transporter. Importantly, ES2 significantly enhanced the anti-tumor effect of vinorelbine against KBv200 cell xenografts in nude mice. Overall, these findings demonstrate that ES2 inhibits the ABCB1 transporter function and consequently reverses ABCB1-mediated MDR, indicating the potential use of ES2 in combination therapy with conventional chemotherapeutic drugs for cancer treatment.

Protein-Ligand Empirical Interaction Components for Virtual Screening.

A major shortcoming of empirical scoring functions is that they often fail to predict binding affinity properly. Removing false positives of docking results is one of the most challenging works in structure-based virtual screening. Postdocking filters, making use of all kinds of experimental structure and activity information, may help in solving the issue. We describe a new method based on detailed protein-ligand interaction decomposition and machine learning. Protein-ligand empirical interaction components (PLEIC) are used as descriptors for support vector machine learning to develop a classification model (PLEIC-SVM) to discriminate false positives from true positives. Experimentally derived activity information is used for model training. An extensive benchmark study on 36 diverse data sets from the DUD-E database has been performed to evaluate the performance of the new method. The results show that the new method performs much better than standard empirical scoring functions in structure-based virtual screening. The trained PLEIC-SVM model is able to capture important interaction patterns between ligand and protein residues for one specific target, which is helpful in discarding false positives in postdocking filtering.

Direct folding simulation of helical proteins using an effective polarizable bond force field.

We report a direct folding study of seven helical proteins (, Trpcage, , C34, N36, , ) ranging from 17 to 53 amino acids through standard molecular dynamics simulations using a recently developed polarizable force field-Effective Polarizable Bond (EPB) method. The backbone RMSDs, radius of gyrations, native contacts and native helix content are in good agreement with the experimental results. Cluster analysis has also verified that these folded structures with the highest population are in good agreement with their corresponding native structures for these proteins. In addition, the free energy landscape of seven proteins in the two dimensional space comprised of RMSD and radius of gyration proved that these folded structures are indeed of the lowest energy conformations. However, when the corresponding simulations were performed using the standard (nonpolarizable) AMBER force fields, no stable folded structures were observed for these proteins. Comparison of the simulation results based on a polarizable EPB force field and a nonpolarizable AMBER force field clearly demonstrates the importance of polarization in the folding of stable helical structures.

Activatable Near-Infrared Probe for Fluorescence Imaging of γ-Glutamyl Transpeptidase in Tumor Cells and In Vivo.

γ-Glutamyl transpeptidase (GGT) is a cell-membrane-bound enzyme that is involved in various physiological and pathological processes and is regarded as a potential biomarker for many malignant tumors, precise detection of which is useful for early cancer diagnosis. Herein, a new GGT-activatable near-infrared (NIR) fluorescence imaging probe (GANP) by linking of a GGT-recognitive substrate γ-glutamate (γ-Glu) and a NIR merocyanine fluorophore (mCy-Cl) with a self-immolative linker p-aminobenzyl alcohol (PABA) is reported. GANP was stable under physiological conditions, but could be efficiently activated by GGT to generate ≈100-fold enhanced fluorescence, enabling high sensitivity (detection limit of ≈3.6 mU L-1 ) and specificity for the real-time imaging of GGT activity as well as rapid evaluation of the inhibition efficacy of GGT inhibitors in living tumor cells. Notably, the deep tissue penetration ability of NIR fluorescence could further allow GANP to image GGT in frozen tumor tissue slices with large penetration depth (>100 µm) and in xenograft tumors in living mice. This GGT activatable NIR fluorescence imaging probe could facilitate the study and diagnosis of other GGT-correlated diseases in vivo.

Computational Study of PCSK9-EGFA Complex with Effective Polarizable Bond Force Field.

Inhibiting of Proprotein Convertase Subtilisin/Kexin-type 9 (PCSK9) and Low Density Lipoprotein Receptor (LDLR) binding is an effective way for reducing Low Density Lipoprotein cholesterol (LDL-C). Understanding the interaction between PCSK9 and LDLR is useful for PCSK9 inhibitor design. In this work, MD simulations with the standard (non-polarizable) AMBER force field and effective polarizable bond (EPB) force field were performed for wild type and four mutants of PCSK9 and EGFA (Epidermal Growth Factor-like repeat A) domain of LDLR complexes. These four mutants are gain-of-function mutants. The analysis of hydrogen bond dynamics and the relative binding free energy indicates that EPB is more reliable in simulating protein dynamics and predicting relative binding affinity. Structures sampled from MD simulations with the standard AMBER force field deviate too far away from crystal structures. Many important interaction components between of PCSK9 and EGFA no longer exist in the simulation with the Amber force field. For comparison, simulation using EPB force field gives more stable structures as shown by hydrogen bond analysis and produced relative binding free energies that are consistent with experimental results. Our study suggests that inclusion of polarization effects in MD simulation is important for studying the protein-protein interaction.

Effect of mismatch on binding of ADAR2/GluR-2 pre-mRNA complex.

RNA editing plays an important role in realizing the full potential of a given genome. Different from RNA splicing, RNA editing fine-tunes the sequence of RNA by changing only one or two nucleotides. A-I editing [deamination of adenosine (A) to create inosine (I)] is best characterized in mammals and occurs in the regions of double-stranded RNA (dsRNA). Adenosine deaminases acting on RNA (ADARs) are members of a family of enzymes involved in A-I deamination editing in numerous mRNA and pre-mRNA transcripts. Experimental study shows that ADAR2 selectively edits the R/G site, while ADAR1 edits more promiscuously at several other adenosines. How ADAR2 selects specific sites for deamination is poorly understood. Mismatches have been suggested to be important factors that allow the ADAR2 to achieve specific deamination. Using molecular dynamic simulation, we studied the effect of mismatch on binding stability of the dsRNA/ADAR2 complex. By comparison of two binding domains of ADAR2, we found that ADAR2 dsRBM2 (second binding domain of ADAR2) does not bind well with mismatch reversed GluR-2 RNA. When mismatch is reversed, dsRBM2 of ADAR2 slides along the RNA duplex in the simulation. Detailed structural analysis indicates that the minor groove width of dsRNA and global shape of RNA may play an important role in the specific reading mechanism of ADAR2.

Functional loop dynamics of the streptavidin-biotin complex.

Accelerated molecular dynamics (aMD) simulation is employed to study the functional dynamics of the flexible loop(3-4) in the strong-binding streptavidin-biotin complex system. Conventional molecular (cMD) simulation is also performed for comparison. The present study reveals the following important properties of the loop dynamics: (1) The transition of loop(3-4) from open to closed state is observed in 200 ns aMD simulation. (2) In the absence of biotin binding, the open-state streptavidin is more stable, which is consistent with experimental evidences. The free energy (ΔG) difference is about 5 kcal/mol between two states. But with biotin binding, the closed state is more stable due to electrostatic and hydrophobic interactions between the loop(3-4) and biotin. (3) The closure of loop(3-4) is concerted to the stable binding of biotin to streptavidin. When the loop(3-4) is in its open-state, biotin moves out of the binding pocket, indicating that the interactions between the loop(3-4) and biotin are essential in trapping biotin in the binding pocket. (4) In the tetrameric streptavidin system, the conformational change of the loop(3-4) in each monomer is independent of each other. That is, there is no cooperative binding for biotin bound to the four subunits of the tetramer.