Binding Mode Prediction Research Articles

DETERMINING THE ROLE OF GALECTIN1/HOXA5 INTERACTION AND REGULATION IN GLIOBLASTOMA DEVELOPMENT

Abstract LGALS1 is directly transcribed by STAT3, which promotes glioblastoma tumorigenesis via its interaction with HOXA5. However, the underling molecular mechanism of this interaction remains uninvestigated. In this study, we predicted the interacting mode between galectin1 and HOXA5 using a protein-protein docking method. Our analysis suggests that the interaction between Galectin1 monomer and the homeobox domain of HOXA5 impedes the interaction between the homeobox domain of HOXA5 and DNA. In contrast, the interaction of Galectin1 homodimer and the N-terminal region of HOXA5 facilitates or stabilizes the homeobox domain of HOXA5 to bind DNA. Based on this predicted binding mode, we hypothesized that HOXA5 transcriptional activity is regulated by phosphorylated HOXA5, which may impact the interaction by attenuating the binding of HOXA5 to negatively charged DNA. To validate this model, we generated a mutant Galectin1 that cannot form dimers by substituting Cys at position 2 with Ser and Val at position 5 with Asp. We also generated functional domain deletion mutants of HOXA5 to confirm the interaction of the N- terminal region of HOXA5 with Galectin1, according to the prediction on functional domains in HOXA5 by Pfam. Using wild type (dimer) and mutant (monomer) recombinant galectin1 proteins and deletion-mutant proteins of HOXA5, we are conducting a binding assay to validate this model. Next, we employed knock-in lines to explore the role of HOXA5 phosphorylation in tumorigenesis using a glioblastoma mouse model. The proposed models will help uncover the underlying regulatory mechanisms of HOXA5/Galectin1 on BTSC self-renewal and glioblastoma tumorigenesis.

Solvated interaction energy: from small-molecule to antibody drug design.

Scoring functions are ubiquitous in structure-based drug design as an aid to predicting binding modes and estimating binding affinities. Ideally, a scoring function should be broadly applicable, obviating the need to recalibrate and refit its parameters for every new target and class of ligands. Traditionally, drugs have been small molecules, but in recent years biologics, particularly antibodies, have become an increasingly important if not dominant class of therapeutics. This makes the goal of having a transferable scoring function, i.e., one that spans the range of small-molecule to protein ligands, even more challenging. One such broadly applicable scoring function is the Solvated Interaction Energy (SIE), which has been developed and applied in our lab for the last 15years, leading to several important applications. This physics-based method arose from efforts to understand the physics governing binding events, with particular care given to the role played by solvation. SIE has been used by us and many independent labs worldwide for virtual screening and discovery of novel small-molecule binders or optimization of known drugs. Moreover, without any retraining, it is found to be transferrable to predictions of antibody-antigen relative binding affinities and as accurate as functions trained on protein-protein binding affinities. SIE has been incorporated in conjunction with other scoring functions into ADAPT (Assisted Design of Antibody and Protein Therapeutics), our platform for affinity modulation of antibodies. Application of ADAPT resulted in the optimization of several antibodies with 10-to-100-fold improvements in binding affinity. Further applications included broadening the specificity of a single-domain antibody to be cross-reactive with virus variants of both SARS-CoV-1 and SARS-CoV-2, and the design of safer antibodies by engineering of a pH switch to make them more selective towards acidic tumors while sparing normal tissues at physiological pH.

Function and Structure of Lacticaseibacillus casei GH35 β-Galactosidase LBCZ_0230 with High Hydrolytic Activity to Lacto-N-biose I and Galacto-N-biose.

β-Galactosidase (EC 3.2.1.23) hydrolyzes β-D-galactosidic linkages at the non-reducing end of substrates to produce β-D-galactose. Lacticaseibacillus casei is one of the most widely utilized probiotic species of lactobacilli. It possesses a putative β-galactosidase belonging to glycoside hydrolase family 35 (GH35). This enzyme is encoded by the gene included in the gene cluster for utilization of lacto-N-biose I (LNB; Galβ1-3GlcNAc) and galacto-N-biose (GNB; Galβ1-3GalNAc) via the phosphoenolpyruvate: sugar phosphotransferase system. The GH35 protein (GnbG) from L. casei BL23 is predicted to be 6-phospho-β-galactosidase (EC 3.2.1.85). However, its 6-phospho-β-galactosidase activity has not yet been examined, whereas its hydrolytic activity against LNB and GNB has been demonstrated. In this study, L. casei JCM1134 LBCZ_0230, homologous to GnbG, was characterized enzymatically and structurally. A recombinant LBCZ_0230, produced in Escherichia coli, exhibited high hydrolytic activity toward o-nitrophenyl β-D-galactopyranoside, p-nitrophenyl β-D-galactopyranoside, LNB, and GNB, but not toward o-nitrophenyl 6-phospho-β-D-galactopyranoside. Crystal structure analysis indicates that the structure of subsite -1 of LBCZ_0230 is very similar to that of Streptococcus pneumoniae β-galactosidase BgaC and not suitable for binding to 6-phospho-β-D-galactopyranoside. These biochemical and structural analyses indicate that LBCZ_0230 is a β-galactosidase. According to the prediction of LNB's binding mode, aromatic residues, Trp190, Trp240, Trp243, Phe244, and Tyr458, form hydrophobic interactions with N-acetyl-D-glucosamine residue of LNB at subsite +1.

ACFIS 2.0: an improved web-server for fragment-based drug discovery via a dynamic screening strategy.

Drug discovery, which plays a vital role in maintaining human health, is a persistent challenge. Fragment-based drug discovery (FBDD) is one of the strategies for the discovery of novel candidate compounds. Computational tools in FBDD could help to identify potential drug leads in a cost-efficient and time-saving manner. The Auto Core Fragment in silico Screening (ACFIS) server is a well-established and effective online tool for FBDD. However, the accurate prediction of protein-fragment binding mode and affinity is still a major challenge for FBDD due to weak binding affinity. Here, we present an updated version (ACFIS 2.0), that incorporates a dynamic fragment growing strategy to consider protein flexibility. The major improvements of ACFIS 2.0 include (i) increased accuracy of hit compound identification (from 75.4% to 88.5% using the same test set), (ii) improved rationality of the protein-fragment binding mode, (iii) increased structural diversity due to expanded fragment librariesand (iv) inclusion of more comprehensive functionality for predicting molecular properties. Three successful cases of drug lead discovery using ACFIS 2.0 are described, including drugs leads to treat Parkinson's disease, cancer, and major depressive disorder. These cases demonstrate the utility of this web-based server. ACFIS 2.0 is freely available at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS2/.

Identification of Small Molecule Inhibitors of Human Cytomegalovirus pUL89 Endonuclease Using Integrated Computational Approaches.

Replication of Human Cytomegalovirus (HCMV) requires the presence of a metal-dependent endonuclease at the C-terminus of pUL89, in order to properly pack and cleave the viral genome. Therefore, pUL89 is an attractive target to design anti-CMV intervention. Herein, we used integrated structure-based and ligand-based virtual screening approaches in combination with MD simulation for the identification of potential metal binding small molecule antagonist of pUL89. In this regard, the essential chemical features needed for the inhibition of pUL89 endonuclease domain were defined and used as a 3D query to search chemical compounds from ZINC and ChEMBL database. Thereafter, the molecular docking and ligand-based shape screening were used to narrow down the compounds based on previously identified pUL89 antagonists. The selected virtual hits were further subjected to MD simulation to determine the intrinsic and ligand-induced flexibility of pUL89. The predicted binding modes showed that the compounds reside well in the binding site of endonuclease domain by chelating with the metal ions and crucial residues. Taken in concert, the in silico investigation led to the identification of potential pUL89 antagonists. This study provided promising starting point for further in vitro and in vivo studies.

Investigation of the Compatibility between Warheads and Peptidomimetic Sequences of Protease Inhibitors-A Comprehensive Reactivity and Selectivity Study.

Covalent peptidomimetic protease inhibitors have gained a lot of attention in drug development in recent years. They are designed to covalently bind the catalytically active amino acids through electrophilic groups called warheads. Covalent inhibition has an advantage in terms of pharmacodynamic properties but can also bear toxicity risks due to non-selective off-target protein binding. Therefore, the right combination of a reactive warhead with a well-suited peptidomimetic sequence is of great importance. Herein, the selectivities of well-known warheads combined with peptidomimetic sequences suited for five different proteases were investigated, highlighting the impact of both structure parts (warhead and peptidomimetic sequence) for affinity and selectivity. Molecular docking gave insights into the predicted binding modes of the inhibitors inside the binding pockets of the different enzymes. Moreover, the warheads were investigated by NMR and LC-MS reactivity assays against serine/threonine and cysteine nucleophile models, as well as by quantum mechanics simulations.

Simulation of uranyl-biomolecule interaction using a cationic dummy atom model

We report a multisite cationic dummy atom model of the uranyl cation, suitable for atomistic simulation of the interaction of this ion with water and biomolecules. This reproduces geometry of model complexes with typical ligands, interactions and diffusion coefficient in water, and the structure of an adduct with a uranyl binding protein. A protocol for prediction of binding mode and strength of complexes formed with small peptides is proposed.

The Crystal Structure of Engineered Nitroreductase NTR 2.0 and Impact of F70A and F108Y Substitutions on Substrate Specificity.

Bacterial nitroreductase enzymes that convert prodrugs to cytotoxins are valuable tools for creating transgenic targeted ablation models to study cellular function and cell-specific regeneration paradigms. We recently engineered a nitroreductase ("NTR 2.0") for substantially enhanced reduction of the prodrug metronidazole, which permits faster cell ablation kinetics, cleaner interrogations of cell function, ablation of previously recalcitrant cell types, and extended ablation paradigms useful for modelling chronic diseases. To provide insight into the enhanced enzymatic mechanism of NTR 2.0, we have solved the X-ray crystal structure at 1.85 Angstroms resolution and compared it to the parental enzyme, NfsB from Vibrio vulnificus. We additionally present a survey of reductive activity with eight alternative nitroaromatic substrates, to provide access to alternative ablation prodrugs, and explore applications such as remediation of dinitrotoluene pollutants. The predicted binding modes of four key substrates were investigated using molecular modelling.

FuzPred: a web server for the sequence-based prediction of the context-dependent binding modes of proteins.

Proteins form complex interactions in the cellular environment to carry out their functions. They exhibit a wide range of binding modes depending on the cellular conditions, which result in a variety of ordered or disordered assemblies. To help rationalise the binding behavior of proteins, the FuzPred server predicts their sequence-based binding modes without specifying their binding partners. The binding mode defines whether the bound state is formed through a disorder-to-order transition resulting in a well-defined conformation, or through a disorder-to-disorder transition where the binding partners remain conformationally heterogeneous. To account for the context-dependent nature of the binding modes, the FuzPred method also estimates the multiplicity of binding modes, the likelihood of sampling multiple binding modes. Protein regions with a high multiplicity of binding modes may serve as regulatory sites or hot-spots for structural transitions in the assembly. To facilitate the interpretation of the predictions, protein regions with different interaction behaviors can be visualised on protein structures generated by AlphaFold. The FuzPred web server (https://fuzpred.bio.unipd.it) thus offers insights into the structural and dynamical changes of proteins upon interactions and contributes to development of structure-function relationships under a variety of cellular conditions.

Bestatin analogs-4-quinolinone hybrids as antileishmanial hits: Design, repurposing rational, synthesis, in vitro and in silico studies

Amongst different forms of leishmaniasis, visceral leishmaniasis caused by L. donovani is highly mortal. Identification of new hit compounds might afford new starting points to develop novel therapeutics. In this lieu, a rationally designed small library of bestatin analogs-4-quinolone hybrids were prepared and evaluated. Analysis of SAR unveiled distinct profiles for hybrids type 1 and type 2, which might arise from their different molecular targets. Amongst type 1 bestatin analog-4-quinolone hybrids, hybrid 1e was identified as potential hit inhibiting growth of L. donovani promastigotes by 91 and 53% at 50 and 25 μM concentrations, respectively. Meanwhile, hybrid 2j was identified amongst type 2 bestatin analog-4-quinolone hybrids as potential hit compound inhibiting growth of L. donovani promastigotes by 50 and 38% at 50 and 25 μM concentrations, respectively. Preliminary safety evaluation of the promising hit compounds showed that they are 50–100 folds safer against human derived monocytic THP-1 cells relative to the drug erufosine. In silico study was conducted to predict the possible binding of hybrid 1e with methionine aminopeptidases 1 and 2 of L. donovani. Molecular dynamic simulations verified the predicted binding modes and provide more in depth understanding of the impact of hybrid 1e on LdMetAP-1 and LdMetAP-2.

Modified N-acyl-L-homoserine lactone compounds abrogate Las-dependent quorum-sensing response in human pathogen Pseudomonas aeruginosa.

Quorum sensing (QS) is a mode of cell-cell communication that bacteria use to sense population density and orchestrate collective behaviors. The common opportunistic human pathogen Pseudomonas aeruginosa employs QS to regulate a large set of genes involved in virulence and host-pathogen interactions. The Las circuit positioned on the top of the QS hierarchy in P. aeruginosa makes use of N-acyl-L-homoserine lactones (AHLs) as signal molecules, like N-3-oxo-dodecanoyl-L-homoserine lactone (3O-C12-HSL). Disabling QS circuits by certain small-molecule compounds, known as quorum-sensing inhibitors (QSIs), has been proposed as a strategy to attenuate bacterial pathogenicity. In this study, four new AHL analogs were designed by incorporating a tert-butoxycarbonyl Boc group in amide and β-keto (3-oxo) moiety. Compounds were evaluated on a molecular and phenotypic basis as a QSI using the screening strategy linked to the assignment of the Las QS system in P. aeruginosa. Using a LasR-based bioreporter, we found that the compounds decreased LasR-controlled light activity and competed efficiently with natural 3O-C12-HSL. The compounds reduced the production of the cognate 3O-C12-HSL and certain virulence traits, like total protease activity, elastase activity, pyocyanin production, and extracellular DNA release. Furthermore, a quantitative proteomic approach was used to study the effect of the compounds on QS-regulated extracellular proteins. Among the four compounds tested, one of them showed the most significant difference in the appearance of the 3O-C12-HSL-responsive reference proteins related to QS communication and virulence, i.e., a distinct activity as a QSI. Moreover, by combining experimental data with computational chemistry, we addressed the effect of LasR protein flexibility on docking precision and assessed the advantage of using a multi-conformational docking procedure for binding mode prediction of LasR modulators. Thus, the four new AHL compounds were tested for their interaction with the AHL-binding site in LasR to identify the key interferences with the activity of LasR. Our study provides further insight into molecular features that are required for small-molecule modulation of LasR-dependent QS communication in P. aeruginosa. This should facilitate rational design of the next generation of antivirulence tools to study and manipulate QS-controlled fitness in bacteria and, thereby, handle bacterial infections in a new way.

Structure-Based Virtual Screening of Natural Products and Optimization for the Design and Synthesis of Novel CeCht1 Inhibitors as Nematicide Candidates.

Nematode chitinases are critical components of the nematode life cycle, and CeCht1 is a potential target for developing novel nematicides. Herein, lunidonine, a natural quinoline alkaloid, was first discovered to have inhibitory activity against CeCht1, which was acquired from a library of over 16,000 natural products using a structure-based virtual screening methodology. A pocket-based lead optimization strategy was employed based on the predicted binding mode of lunidonine. Subsequently, a series of benzo[d][1,3]dioxole-5-carboxylate derivatives were designed and synthesized, and their inhibitory activities against CeCht1 as well as in vitro nematicidal activities against Caenorhabditis elegans were assessed. The analysis of structure-activity relationship and inhibitory mechanisms provided insights into their interactions with the CeCht1 active site, which could facilitate future research in improving the potency of the inhibitory activity. Especially, compound a12 interacted well with CeCht1 and exhibited excellent in vitro nematicidal activity against C. elegans with a LC50 value of 41.54 mg/L, suggesting that it could be a promising candidate for a novel chemical nematicide targeting CeCht1. The known binding modes and structural features of these inhibitors will contribute to the design of stronger CeCht1-based nematicides to control nematodes in agriculture.

Rational design, synthesis, and pharmacological evaluation of a cohort of novel beta-adrenergic receptors ligands enables an assessment of structure-activity relationships

Biomedical applications of molecules that are able to modulate β-adrenergic signaling have become increasingly attractive over the last decade, revealing that β-adrenergic receptors (β-ARs) are key targets for a plethora of therapeutic interventions, including cancer. Despite successes in β-AR drug discovery, identification of β-AR ligands that are useful as selective chemical tools in pharmacological studies of the three β-AR subtypes, or lead compounds for drug development is still a highly challenging task. This is mainly due to the intrinsic plasticity of β-ARs as G protein-coupled receptors in conjunction with the requirement for functional receptor subtype selectivity, tissue specificity and minimal off-target effects. With the aim to provide insight into structure-activity relationships for the three β-AR subtypes, we have synthesized and obtained the pharmacological profile of a series of structurally diverse compounds (named MC) that were designed based on the aryloxy-propanolamine scaffold of SR59230A. Comparative analysis of their predicted binding mode within the active and inactive states of the receptors in combination with their pharmacological profile revealed key structural elements that control their activity as agonists or antagonists, in addition to clues about substituents that mediate selectivity for one receptor subtype over the others. We anticipate that these results will facilitate selective β-AR drug development efforts.

Computational Analysis of Triazole-Based Kojic Acid Analogs as Tyrosinase Inhibitors by Molecular Dynamics and Free Energy Calculations

Molecular docking, molecular dynamics (MD) simulations and the linear interaction energy (LIE) method were used here to predict binding modes and free energy for a set of 1,2,3-triazole-based KA analogs as potent inhibitors of Tyrosinase (TYR), a key metalloenzyme of the melanogenesis process. Initially, molecular docking calculations satisfactorily predicted the binding mode of evaluated KA analogs, where the KA part overlays the crystal conformation of the KA inhibitor into the catalytic site of TYR. The MD simulations were followed by the LIE method, which reproduced the experimental binding free energies for KA analogs with an r2 equal to 0.97, suggesting the robustness of our theoretical model. Moreover, the van der Waals contributions performed by some residues such as Phe197, Pro201, Arg209, Met215 and Val218 are responsible for the binding recognition of 1,2,3-triazole-based KA analogs in TYR catalytic site. Finally, our calculations provide suitable validation of the combination of molecular docking, MD, and LIE approaches as a powerful tool in the structure-based drug design of new and potent TYR inhibitors.

Computational design, synthesis and biological evaluation of PDE5 inhibitors based on N2,N4-diaminoquinazoline and N2,N6-diaminopurine scaffolds

We report the synthesis, and characterization of twenty-nine new inhibitors of PDE5. Structure-based design was employed to modify to our previously reported 2,4-diaminoquinazoline series. Modification include scaffold hopping to 2,6-diaminopurine core as well as incorporation of ionizable groups to improve both activity and solubility. The prospective binding mode of the compounds was determined using 3D ligand-based similarity methods to inhibitors of known binding mode, combined with a PDE5 docking and molecular dynamics based-protocol, each of which pointed to the same binding mode. Chemical modifications were then designed to both increase potency and solubility as well as validate the binding mode prediction. Compounds containing a quinazoline core displayed IC50s ranging from 0.10 to 9.39 µM while those consisting of a purine scaffold ranging from 0.29 to 43.16 µM. We identified 25 with a PDE5 IC50 of 0.15 µM, and much improved solubility (1.77 mg/mL) over the starting lead. Furthermore, it was found that the predicted binding mode was consistent with the observed SAR validating our computationally driven approach.

Holo Protein Conformation Generation from Apo Structures by Ligand Binding Site Refinement.

An important part in structure-based drug design is the selection of an appropriate protein structure. It has been revealed that a holo protein structure that contains a well-defined binding site is a much better choice than an apo structure in structure-based drug discovery. Therefore, it is valuable to obtain a holo-like protein conformation from apo structures in the case where no holo structure is available. Meeting the need, we present a robust approach to generate reliable holo-like structures from apo structures by ligand binding site refinement with restraints derived from holo templates with low homology. Our method was tested on a test set of 32 proteins from the DUD-E data set and compared with other approaches. It was shown that our method successfully refined the apo structures toward the corresponding holo conformations for 23 of 32 proteins, reducing the average all-heavy-atom RMSD of binding site residues by 0.48 Å. In addition, when evaluated against all the holo structures in the protein data bank, our method can improve the binding site RMSD for 14 of 19 cases that experience significant conformational changes. Furthermore, our refined structures also demonstrate their advantages over the apo structures in ligand binding mode predictions by both rigid docking and flexible docking and in virtual screening on the database of active and decoy ligands from the DUD-E. These results indicate that our method is effective in recovering holo-like conformations and will be valuable in structure-based drug discovery.

Discovery of novel pyrazole and pyrazolo[1,5-a]pyrimidine derivatives as cyclooxygenase inhibitors (COX-1 and COX-2) using molecular modeling simulation.

Searching for effective and selective anti-inflammatory agents, our studyinvolved designing and synthesizing new pyrazole and pyrazolo[1,5-a]pyrimidine derivatives 4-11. The structures of the synthesized derivatives were confirmed using different spectroscopic techniques. Virtual screening was achieved for the newly designed derivatives using in silico docking simulation inside the active sites of four proteins classified as two cyclooxygenases (COX)-1 (PDB: 3KK6 and 4OIZ) and two COX-2 (PBD: 1CX2 and 3LN1). Among them, six derivatives 4c, 5b, 6a, 7a, 7b, and 10b displayed the highest binding energy. These derivatives were evaluated for their in vitro COX-1 and COX-2 inhibitory activities and their selectivity indexes were calculated. Additionally, these derivatives displayed IC50 values ranging between 4.909 ± 0.25 and 57.53 ± 2.91 µM, and 3.289 ± 0.14 and 124 ± 5.32 µM, against COX-1 and COX-2, respectively. Furthermore, the tested derivatives were found to have selective inhibitory activity on the COX-2 enzyme. Surprisingly, the two pyrazole derivatives 4c and 5b were found to be the most active, with IC50 values of 9.835 ± 0.50 and 4.909 ± 0.25 µM and 4.597 ± 0.20 and 3.289 ± 0.14 µM compared with meloxicam (1.879 ± 0.1 and 5.409 ± 0.23 µM) and celecoxib (5.439 ± 0.28 and 2.164 ± 0.09 µM) against COX-1/-2, respectively. Besides, two pyrazole derivatives, 4c and 5b, displayed a COX-1/COX-2 SI of 2.14 and 1.49. Computational techniques such as molecular docking, density function theory (DFT) calculation, and chemical absorption, distribution, metabolism, excretion, and toxicity evaluation were applied to explain the molecules' binding mode, chemical nature, drug likeness, and toxicity prediction.

(-)-Epigallocatechin Gallate is a Noncompetitive Inhibitor of NAD Kinase.

Nicotinamide adenine dinucleotide kinase (NADK) controls the intracellular NADPH content and provides reducing power for the synthesis of macromolecules and anti-ROS. Moreover, NADK is considered to be a synthetic lethal gene for KRAS mutations. To discover NADK-targeted probes, a high-throughput screening assay was established and optimized with a Z factor of 0.71. The natural product (-)-epigallocatechin gallate (EGCG) was found to be a noncompetitive inhibitor of NADK with K i = 3.28 ± 0.32 μΜ. The direct binding of EGCG to NADK was determined by several biophysical methods, including NMR spectroscopy, surface plasmon resonance (SPR) assay, and hydrogen-deuterium exchange mass spectrometry (HDX-MS). The SPR assay showed a K d of 1.78 ± 1.15 μΜ. The HDX-MS experiment showed that EGCG was bound at the non-substrate-binding sites of NADK. Besides, binding mode prediction and derivative activity analysis revealed a potential structure-activity relationship between EGCG and NADK. Furthermore, EGCG can specifically inhibit the proliferation of KRAS-mutated lung cancer cell lines without affecting KRAS wild-type lung cancer cell lines.

Discovery of novel anti-tumor compounds targeting PARP-1 with induction of autophagy through in silico and in vitro screening.

Poly (ADP-ribose) polymerase 1 (PARP-1) is a critical enzyme involved in DNA damage repair and recombination, and shows great potential for drug development in the treatment of cancers with defective DNA repair. The anti-tumor activities of PARP-1 inhibitors are regulated by both inhibition activities and allosteric mechanisms of PARP-1, and may also be involved in an autophagy-mediated process. Screening PARP-1 inhibitors with potential allosteric mechanisms and induced autophagy process could achieve elevated potency toward cancer cell killing. In this study, we tried to discover novel anti-tumor compounds targeting PARP-1 by computer simulations and in vitro screening. In order to filter PARP-1 inhibitors that could affect the folding state of the helix domain (HD) on PARP-1, the free energy contribution of key residues on HD were systematically analyzed using the ligand-binding crystal structures and integrated into in silico screening workflow for the selection of 20 pick-up compounds. Four compounds (Chemdiv codes: 8012-0567, 8018-6529, 8018-7168, 8018-7603) were proved with above 40% inhibitory ratio targeting PARP-1 under 20μM, and further performed binding mode prediction and dynamic effect evaluation by molecular dynamics simulation. Further in vitro assays showed that compounds 8018-6529 and 8018-7168 could inhibit the growth of the human colorectal cancer cell (HCT-116) with IC50 values of 4.30 and 9.29μM and were accompanied with an induced autophagy process. Taken together, we discover two novel anti-tumor compounds that target PARP-1 with an induced autophagy process and provide potential hit compounds for the anti-cancer drug development.

MDO: A Computational Protocol for Prediction of Flexible Enzyme-Ligand Binding Mode.

Developing a method for use in computer aided drug design Background: Predicting the structure of enzyme-ligand binding mode is essential for understanding the properties, functions, and mechanisms of the bio-complex, but is rather difficult due to the enormous sampling space involved. Accurate prediction of enzyme-ligand binding mode conformation. A new computational protocol, MDO, is proposed for finding the structure of ligand binding pose. MDO consists of sampling enzyme sidechain conformations via molecular dynamics simulation of enzyme-ligand system and clustering of the enzyme configurations, sampling ligand binding poses via molecular docking and clustering of the ligand conformations, and the optimal ligand binding pose prediction via geometry optimization and ranking by the ONIOM method. MDO is tested on 15 enzyme-ligand complexes with known accurate structures. The success rate of MDO predictions, with RMSD < 2 Å, is 67%, substantially higher than the 40% success rate of conventional methods. The MDO success rate can be increased to 83% if the ONIOM calculations are applied only for the starting poses with ligands inside the binding cavities. The MDO protocol provides high quality enzyme-ligand binding mode prediction with reasonable computational cost. The MDO protocol is recommended for use in the structure-based drug design.