HISNAPI: a bioinformatic tool for dynamic hot spot analysis in nucleic acid-protein interface with a case study.

Protein-nucleic acid interactions play essential roles in many biological processes, such as transcription, replication and translation. In protein-nucleic acid interfaces, hotspot residues contribute the majority of binding affinity toward molecular recognition. Hotspot residues are commonly regarded as potential binding sites for compound molecules in drug design projects. The dynamic property is a considerable factor that affects the binding of ligands. Computational approaches have been developed to expedite the prediction of hotspot residues on protein-nucleic acid interfaces. However, existing approaches overlook hotspot dynamics, despite their essential role in protein function. Here, we report a web server named Hotspots In silico Scanning on Nucleic Acid and Protein Interface (HISNAPI) to analyze hotspot residue dynamics by integrating molecular dynamics simulation and one-step free energy perturbation. HISNAPI is capable of not only predicting the hotspot residues in protein-nucleic acid interfaces but also providing insights into their intensity and correlation of dynamic motion. Protein dynamics have been recognized as a vital factor that has an effect on the interaction specificity and affinity of the binding partners. We applied HISNAPI to the case of SARS-CoV-2 RNA-dependent RNA polymerase, a vital target of the antiviral drug for the treatment of coronavirus disease 2019. We identified the hotspot residues and characterized their dynamic behaviors, which might provide insight into the target site for antiviral drug design. The web server is freely available via a user-friendly web interface at http://chemyang.ccnu.edu.cn/ccb/server/HISNAPI/ and http://agroda.gzu.edu.cn:9999/ccb/server/HISNAPI/.

Bioinformatics toolbox for exploring protein phosphorylation network.

A clear systematic delineation of the interactions between phosphorylation sites on substrates and their effector kinases plays a fundamental role in revealing cellular activities, understanding signaling modulation mechanisms and proposing novel hypotheses. The emergence of bioinformatics tools contributes to studying phosphorylation network. Some of them feature the visualization of network, enabling more effective trace of the underlying biological problems in a clear and succinct way. In this review, we aimed to provide a toolbox for exploring phosphorylation network. We first systematically surveyed 19 tools that are available for exploring phosphorylation networks, and subsequently comparatively analyzed and summarized these tools to guide tool selection in terms of functionality, data sources, performance, network visualization and implementation, and finally briefly discussed the application cases of these tools. In different scenarios, the conclusion on the suitability of a tool for a specific user may vary. Nevertheless, easily accessible bioinformatics tools are proved to facilitate biological findings. Hopefully, this work might also assist non-specialists, students, as well as computational scientists who aim at developing novel tools in the field of phosphorylation modification.

Cloud 3D-QSAR: a web tool for the development of quantitative structure-activity relationship models in drug discovery.

Effective drug discovery contributes to the treatment of numerous diseases but is limited by high costs and long cycles. The Quantitative Structure-Activity Relationship (QSAR) method was introduced to evaluate the activity of a large number of compounds virtually, reducing the time and labor costs required for chemical synthesis and experimental determination. Hence, this method increases the efficiency of drug discovery. To meet the needs of researchers to utilize this technology, numerous QSAR-related web servers, such as Web-4D-QSAR and DPubChem, have been developed in recent years. However, none of the servers mentioned above can perform a complete QSAR modeling and supply activity prediction functions. We introduce Cloud 3D-QSAR by integrating the functions of molecular structure generation, alignment, molecular interaction field (MIF) computing and results analysis to provide a one-stop solution. We rigidly validated this server, and the activity prediction correlation was R2 = 0.934 in 834 test molecules. The sensitivity, specificity and accuracy were 86.9%, 94.5% and 91.5%, respectively, with AUC = 0.981, AUCPR = 0.971. The Cloud 3D-QSAR server may facilitate the development of good QSAR models in drug discovery. Our server is free and now available at http://chemyang.ccnu.edu.cn/ccb/server/cloud3dQSAR/ and http://agroda.gzu.edu.cn:9999/ccb/server/cloud3dQSAR/.

AIMMS suite: a web server dedicated for prediction of drug resistance on protein mutation.

Drug resistance is one of the most intractable issues for successful treatment in current clinical practice. Although many mutations contributing to drug resistance have been identified, the relationship between the mutations and the related pharmacological profile of drug candidates has yet to be fully elucidated, which is valuable both for the molecular dissection of drug resistance mechanisms and for suggestion of promising treatment strategies to counter resistant. Hence, effective prediction approach for estimating the sensitivity of mutations to agents is a new opportunity that counters drug resistance and creates a high interest in pharmaceutical research. However, this task is always hampered by limited known resistance training samples and accurately estimation of binding affinity. Upon this challenge, we successfully developed Auto In Silico Macromolecular Mutation Scanning (AIMMS), a web server for computer-aided de novo drug resistance prediction for any ligand-protein systems. AIMMS can qualitatively estimate the free energy consequences of any mutations through a fast mutagenesis scanning calculation based on a single molecular dynamics trajectory, which is differentiated with other web services by a statistical learning system. AIMMS suite is available at http://chemyang.ccnu.edu.cn/ccb/server/AIMMS/.

PIIMS Server: A Web Server for Mutation Hotspot Scanning at the Protein-Protein Interface.

Protein-protein interactions (PPIs) play vital roles in regulating biological processes, such as cellular and signaling pathways. Hotspots are certain residues located at protein-protein interfaces that contribute more in protein-protein binding than other residues. Research on the mutational effects of hotspots is important for understanding basic aspects of protein association. Hence, various computational tools have been developed to explore the impact of mutation hotspots, which will allow a better understanding of the forces that drive PPIs. However, tools that may provide comprehensive substitutions at hotspots are still rare. Hence, there is a strong need for a new free web server to explore mutational effects of hotspots. Herein we introduce a web server named PIIMS that integrates molecular dynamics simulation and one-step free energy perturbation. It contains two main computational functions: (1) computational alanine scanning analysis to identify hotspots and (2) full mutation scanning analysis to evaluate the effects of hotspot mutations. We rigidly validated its ability to predict binding free energy changes by using large and diverse datasets including 1,341 mutations from 50 PPIs with the correlation coefficient R = 0.75. The difference from the existing tools is that PIIMS can perform further evaluation of hotspot residues with regard to their different mutations. The PIIMS web server (accessible at http://chemyang.ccnu.edu.cn/ccb/server/PIIMS/index.php) is free and open to all users without login requirements.

ACFIS: a web server for fragment-based drug discovery.

In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown 'chemical space' to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for 'chemical space', which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/.

Discovery of 3-pyrazolyl-substituted pyrazolo[1,5-a]pyrimidine derivatives as potent TRK inhibitors to overcome clinically acquired resistance.

Several secondary tropomyosin receptor kinase (TRK) mutations located in the solvent front, xDFG, and gatekeeper regions, are a common cause of clinical resistance. Mutations in the xDFG motif in particular limit sensitivity to second-generation TRK inhibitors, which represent an unmet clinical need. We designed a series of 3-pyrazolyl-substituted pyrazolo[1,5-a]pyrimidine derivatives toward these secondary mutations using ring-opening and scaffold-hopping strategies. Compound 5n was the most potent, with IC50 values of 2.3 nM, 0.4 nM, and 0.5 nM against TRKAG667C, TRKAF589L, and TRKAG595R, compared to selitrectinib with IC50 values of 12.6 nM, 5.8 nM, and 7.6 nM, respectively (approximately 5.4, 14.5, and 15.2-fold increases). Furthermore, 5n displayed favorable pharmacokinetic properties and satisfactory antitumor efficacy (tumor growth inhibition of 97% at 30 mg/kg and 73% at 100 mg/kg) in TRKAWT and TRKAG667C xenograft mouse models. Collectively, 5n is a promising TRK inhibitor lead compound for overcoming clinically acquired resistance to second-generation inhibitors, particularly for resistant tumors harboring the TRKAG667C mutation in the xDFG motif.

Green synthesis, structure optimization and biological evalution of Rhopaladins' analog 2-styryl-5-oxopyrrolidine-2- carboxamide RPDPRH on CaSki cells.

We have synthesized Rhopaladins' analog (2E,4E)-4-chlorobenzylidene-2-(4-chlorostyryl)-N-cyclohexyl-1-(4-fluorophenyl)-5-oxopyrrolidine-2-carboxamide (RPDPRH) via a highly facile, inexpensive and green approach and verified the structural superiority of compound RPDPRH through molecular docking. Moreover, we further detected the anti-proliferation, apoptosis and HPV E6/E7 effects of RPDPRH on CaSki cells. Finally, we confirmed that compared with the previous compound (E)-N-(tert-butyl)-2-(4-chlorobenzoyl)-4-(4-fluorobenzylidene)-1-isopropyl-5-oxopyrrolidine-2-carboxamide (RPDPB), RPDPRH could better inhibit proliferation, induce apoptosis, and down-regulate HPV E6/E7 mRNA expression on Caski cells. And preliminary RT-PCR experiments have demonstrated that RPDPRH also could affect the expression of Bcl-2, Bax and Caspase-3 mRNA in Caski cells. In summary, RPDPRH has potential as an effective agent against cervical cancer and will play an important role in our subsequent research.

Discovery of Next-Generation Tropomyosin Receptor Kinase Inhibitors for Combating Multiple Resistance Associated with Protein Mutation.

Tropomyosin receptor kinase (TRK) inhibition is an effective therapeutic approach for treatment of a variety of cancers. Despite the use of first-generation TRK inhibitor (TRKI) larotrectinib (1) resulting in significant therapeutic response in patients, acquired resistance develops invariably. The emergence of secondary mutations occurring at the solvent-front, xDFG, and gatekeeper regions of TRK represents a common mechanism for acquired resistance. However, xDFG mutations remain insensitive to second-generation macrocyclic TRKIs selitrectinib (3) and repotrectinib (4) designed to overcome the resistance mediated by solvent-front and gatekeeper mutations. Here, we report the structure-based drug design and discovery of a next-generation TRKI. The structure-activity relationship studies culminated in the identification of a promising drug candidate 8 that showed excellent in vitro potency on a panel of TRK mutants, especially TRKAG667C in the xDFG motif, and improved in vivo efficacy than 1 and 3 in TRK wild-type and mutant fusion-driven tumor xenograft models, respectively.

Structure-activity relationship study of novel quinazoline-based 1,6-naphthyridinones as MET inhibitors with potent antitumor efficacy.

As a privileged scaffold, the quinazoline ring is widely used in the development of EGFR inhibitors, while few quinazoline-based MET inhibitors are reported. In our ongoing efforts to develop new MET-targeted anticancer drug candidates, a series of quinazoline-based 1,6-naphthyridinone derivatives were designed, synthesized, and evaluated for their biological activities. The preliminary SARs studies indicate that the quinazoline scaffold was also acceptable for the block A of class II MET inhibitors. The further pharmacokinetic studies led to the identification of the most promising compound 22a with favorable in vitro potency (MET, IC50 = 9.0 nM), human microsomal metabolic stability (t1/2 = 621.2 min) and oral bioavailability (F = 42%). Moreover, 22a displayed good in vivo antitumor efficacy (IR of 81% in 75 mg/kg) in MET-positive human glioblastoma U-87 MG xenograft model. These positive results indicated that 22a is a potential new MET-targeted antitumor drug lead, which is worthy of further development.

Discovery of Novel Pyrazole-Quinazoline-2,4-dione Hybrids as 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors.

4-Hydroxyphenylpyruvate dioxygenase (HPPD, EC 1.13.11.27) has been identified as one of the most significant targets in herbicide discovery for resistant weed control. In a continuing effort to discover potent novel HPPD inhibitors, we adopted a ring-expansion strategy to design a series of novel pyrazole-quinazoline-2,4-dione hybrids based on the previously discovered pyrazole-isoindoline-1,3-dione scaffold. One compound, 3-(2-chlorophenyl)-6-(5-hydroxy-1,3-dimethyl-1H-pyrazole-4-carbonyl)-1,5-dimethylquinazoline-2,4(1H,3H)-dione (9bj), displayed excellent potency against AtHPPD, with an IC50 value of 84 nM, which is approximately 16-fold more potent than pyrasulfotole (IC50 = 1359 nM) and 2.7-fold more potent than mesotrione (IC50 = 226 nM). Furthermore, the co-crystal structure of the AtHPPD-9bj complex (PDB ID 6LGT) was determined at a resolution of 1.75 Å. Similar to the existing HPPD inhibitors, compound 9bj formed a bidentate chelating interaction with the metal ion and a π-π stacking interaction with Phe381 and Phe424. In contrast, o-chlorophenyl at the N3 position of quinazoline-2,4-dione with a double conformation was surrounded by hydrophobic residues (Met335, Leu368, Leu427, Phe424, Phe392, and Phe381). Remarkably, the greenhouse assay indicated that most compounds displayed excellent herbicidal activity (complete inhibition) against at least one of the tested weeds at the application rate of 150 g of active ingredient (ai)/ha. Most promisingly, compounds 9aj and 9bi not only exhibited prominent weed control effects with a broad spectrum but also showed very good crop safety to cotton, peanuts, and corn at the dose of 150 g of ai/ha.

Hydrophobicity-oriented drug design (HODD) of new human 4-hydroxyphenylpyruvate dioxygenase inhibitors.

Involved in the tyrosine degradation pathway, 4-hydroxyphenylpyruvate dioxygenase (HPPD) is an important target for treating type I tyrosinemia. To discover novel HPPD inhibitors, we proposed a hydrophobicity-oriented drug design (HODD) strategy based on the interactions between HPPD and the commercial drug NTBC. Most of the new compounds showed improved activity, compound d23 being the most active candidate (IC50 = 0.047 µM) with about 2-fold more potent than NTBC (IC50 = 0.085 µM). Therefore, compound d23 is a potential drug candidate to treat type I tyrosinemia.

ACID: a free tool for drug repurposing using consensus inverse docking strategy.

Drug repurposing offers a promising alternative to dramatically shorten the process of traditional de novo development of a drug. These efforts leverage the fact that a single molecule can act on multiple targets and could be beneficial to indications where the additional targets are relevant. Hence, extensive research efforts have been directed toward developing drug based computational approaches. However, many drug based approaches are known to incur low successful rates, due to incomplete modeling of drug-target interactions. There are also many technical limitations to transform theoretical computational models into practical use. Drug based approaches may, thus, still face challenges for drug repurposing task. Upon this challenge, we developed a consensus inverse docking (CID) workflow, which has a ~ 10% enhancement in success rate compared with current best method. Besides, an easily accessible web server named auto in silico consensus inverse docking (ACID) was designed based on this workflow (http://chemyang.ccnu.edu.cn/ccb/server/ACID).

Crystal Structure of 4-Hydroxyphenylpyruvate Dioxygenase in Complex with Substrate Reveals a New Starting Point for Herbicide Discovery.

4-Hydroxyphenylpyruvate dioxygenase (HPPD) is a promising target for drug and pesticide discovery. The unknown binding mode of substrate is still a big challenge for the understanding of enzymatic reaction mechanism and novel HPPD inhibitor design. Herein, we determined the first crystal structure of Arabidopsis thaliana HPPD (AtHPPD) in complex with its natural substrate (HPPA) at a resolution of 2.80 Å. Then, combination of hybrid quantum mechanics/molecular mechanics (QM/MM) calculations confirmed that HPPA takes keto rather than enol form inside the HPPD active pocket. Subsequent site-directed mutagenesis and kinetic analysis further showed that residues (Phe424, Asn423, Glu394, Gln307, Asn282, and Ser267) played important roles in substrate binding and catalytic cycle. Structural comparison between HPPA-AtHPPD and holo-AtHPPD revealed that Gln293 underwent a remarkable rotation upon the HPPA binding and formed H-bond network of Ser267-Asn282-Gln307-Gln293, resulting in the transformation of HPPD from an inactive state to active state. Finally, taking the conformation change of Gln293 as a target, we proposed a new strategy of blocking the transformation of HPPD from inactive state to active state to design a novel inhibitor with K i value of 24.10 nM towards AtHPPD. The inhibitor has entered into industry development as the first selective herbicide used for the weed control in sorghum field. The crystal structure of AtHPPD in complex with the inhibitor (2.40 Å) confirmed the rationality of the design strategy. We believe that the present work provides a new starting point for the understanding of enzymatic reaction mechanism and the design of next generation HPPD inhibitors.

Discovery of Specific Nonpeptide Probe for Chymotrypsin via Molecular Docking-Based Virtual Screening and the Application.

Chymotrypsin is a proteolytic enzyme associated with numerous biological processes. Moreover, it has been reported to be significantly involved in pancreatic diseases. Thus, its rapid and sensitive detection is of great significance for early diagnosis and related drug discovery. Herein, a new strategy of molecular docking-based virtual screening (MDVS) was developed for the identification of a new nonpeptide-based biosensor targeting chymotrypsin. The newly discovered probe, numbered probe 20, exhibits about 45-fold specificity toward chymotrypsin over the similar enzyme trypsin and produces about 250-fold higher increase of fluorescence intensity under the catalysis of chymotrypsin. Furthermore, the probe successfully allowed the characterization of the kinetics of chymotrypsin inhibitors. More importantly, the endogenous chymotrypsin in zebrafish was visualized by nonpeptide probe for the first time, demonstrating the potential of the probe 20 for future application in the mechanistic study or clinic diagnosis for pancreatic diseases. Accordingly, the MDVS strategy could be generally applied in the identification of specific fluorescent probe for a particular enzyme.

An Efficient One-Pot Synthesis of 2-(Aryloxyacetyl)cyclohexane-1,3-diones as Herbicidal 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors.

4-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27, HPPD) is an important target for new bleaching herbicides discovery. As a continuous work to discover novel crop selective HPPD inhibitor, a series of 2-(aryloxyacetyl)cyclohexane-1,3-diones were rationally designed and synthesized by an efficient one-pot procedure using N,N'-carbonyldiimidazole (CDI), triethylamine, and acetone cyanohydrin in CH2Cl2. A total of 58 triketone compounds were synthesized in good to excellent yields. Some of the triketones displayed potent in vitro Arabidopsis thaliana HPPD (AtHPPD) inhibitory activity. 2-(2-((1-Bromonaphthalen-2-yl)oxy)acetyl)-3-hydroxycyclohex-2-en-1-one, II-13, displayed high, broad-spectrum, and postemergent herbicidal activity at the dosage of 37.5-150 g ai/ha, nearly as potent as mesotrione against some weeds. Furthermore, II-13 showed good crop safety against maize and canola at the rate of 150 g ai/ha, indicating that II-13 might have potential as a herbicide for weed control in maize and canola fields. II-13 is the first HPPD inhibitor showing good crop safety toward canola.

Synthesis and Herbicidal Activity of Triketone-Quinoline Hybrids as Novel 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors.

4-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27, HPPD) is one of the most important targets for herbicide discovery. In the search for new HPPD inhibitors with novel scaffolds, triketone-quinoline hybrids were designed and subsequently optimized on the basis of the structure-activity relationship (SAR) studies. Most of the synthesized compounds displayed potent inhibition of Arabidopsis thaliana HPPD (AtHPPD), and some of them exhibited broad-spectrum and promising herbicidal activity at the rate of 150 g ai/ha by postemergence application. Most promisingly, compound III-l, 3-hydroxy-2-(2-methoxy-7-(methylthio)quinoline-3-carbonyl)cyclohex-2-enone (Ki = 0.009 µM, AtHPPD), had broader spectrum of weed control than mesotrione. Furthermore, compound III-l was much safer to maize at the rate of 150 g ai/ha than mesotrione, demonstrating its great potential as herbicide for weed control in maize fields. Therefore, triketone-quinoline hybrids may serve as new lead structures for novel herbicide discovery.