Structure-based Screening Research Articles

Deep learning pipeline for accelerating virtual screening in drug discovery

In the race to combat ever-evolving diseases, the drug discovery process often faces the hurdles of high-cost and time-consuming procedures. To tackle these challenges and enhance the efficiency of identifying new therapeutic agents, we introduce VirtuDockDL, which is a streamlined Python-based web platform utilizing deep learning for drug discovery. This pipeline employs a Graph Neural Network to analyze and predict the effectiveness of various compounds as potential drug candidates. During the validation phase, VirtuDockDL was instrumental in identifying non-covalent inhibitors against the VP35 protein of the Marburg virus, a critical target given the virus’s high fatality rate and limited treatment options. Further, in benchmarking, VirtuDockDL achieved 99% accuracy, an F1 score of 0.992, and an AUC of 0.99 on the HER2 dataset, surpassing DeepChem (89% accuracy) and AutoDock Vina (82% accuracy). Compared to RosettaVS, MzDOCK, and PyRMD, VirtuDockDL outperformed them by combining both ligand- and structure-based screening with deep learning. While RosettaVS excels in accurate docking but lacks high-throughput screening, and PyRMD focuses on ligand-based methods without AI integration, VirtuDockDL offers superior predictive accuracy and full automation for large-scale datasets, making it ideal for comprehensive drug discovery workflows. These results underscore the tool’s capability to identify high-affinity inhibitors accurately across various targets, including the HER2 protein for cancer therapy, TEM-1 beta-lactamase for bacterial infections, and the CYP51 enzyme for fungal infections like Candidiasis. To sum up, VirtuDockDL combines user-friendly interface design with powerful computational capabilities to facilitate rapid, cost-effective drug discovery and development. The integration of AI in drug discovery could potentially transform the landscape of pharmaceutical research, providing faster responses to global health challenges. The VirtuDockDL is available at https://github.com/FatimaNoor74/VirtuDockDL.

Structure-based design and screening of hydrogel copolymer/Fe3O4 composite microspheres for magnetic solid phase extraction of bisphenol A from aqueous samples

It is of great significance to monitor bisphenol A (BPA) in the environment because of its potential environmental and health risks. However, the detection of trace or ultratrace BPA in complicated environmental samples is challenging due to the relatively low affinity and poor selectivity of existing adsorbents used in sample pretreatment. Herein, we report a high-affinity, low environment-dependent and strong interference-resistant abiotic affinity ligand, a N-methacryloyl-l-lysine-NH2 (MLys)-based hydrogel copolymer (HP 17) screened from a small focused polymer library engineered by incorporating various combinations and ratios of candidate functional monomers. The selection of these monomers was guided by molecular mechanism between BPA and the ligand-binding pocket of its estrogen receptors. The BPA–HP17 binding is mainly a synergistic effect of π-cation and hydrophobic interactions. The screened HP 17 has high adsorption capacity (349.4 mg/g) for BPA under wide pH (3.0–10.0) and ionic strength (0–150 mM) range. To improve its practicability, a hydrogel copolymer/Fe3O4 composite microspheres (Fe3O4@HP 17) was synthesized and applied for magnetic solid phase extraction–high-performance liquid chromatography (MSPE–HPLC) analysis of BPA in tap water, lake water and industrial effluents. The method shows wide linear range (2.5⁓100 ng/mL), high sensitivity (detection limit of 0.22 ng/mL even without further concentration after desorption), high accuracies (92.6⁓103.0 %) and good precisions (0.57⁓4.53 %), indicating a great potential of this material and method in the detection of trace or ultratrace BPA in complex environmental water samples.

CovalentInDB 2.0: an updated comprehensive database for structure-based and ligand-based covalent inhibitor design and screening.

The rational design of targeted covalent inhibitors (TCIs) has emerged as a powerful strategy in drug discovery, known for its ability to achieve strong binding affinity and prolonged target engagement. However, the development of covalent drugs is often challenged by the need to optimize both covalent warhead and non-covalent interactions, alongside the limitations of existing compound libraries. To address these challenges, we present CovalentInDB 2.0, an updated online database designed to support covalent drug discovery. This updated version includes 8303 inhibitors and 368 targets, supplemented by 3445 newly added cocrystal structures, providing detailed analyses of non-covalent interactions. Furthermore, we have employed an AI-based model to profile the ligandability of 144 864 cysteines across the human proteome. CovalentInDB 2.0 also features the largest covalent virtual screening library with 2 030 192 commercially available compounds and a natural product library with 105 901 molecules, crucial for covalent drug screening and discovery. To enhance the utility of these compounds, we performed structural similarity analysis and drug-likeness predictions. Additionally, a new user data upload feature enables efficient data contribution and continuous updates. CovalentInDB 2.0 is freely accessible at http://cadd.zju.edu.cn/cidb/.

The future of metronomic chemotherapy: experimental and computational approaches of drug repurposing.

Metronomic chemotherapy (MC), long-term continuous administration of anticancer drugs, is gaining attention as an alternative to the traditional maximum tolerated dose (MTD) chemotherapy. By combining MC with other treatments, the therapeutic efficacy is enhanced while minimizing toxicity. MC employs multiple mechanisms, making it a versatile approach against various cancers. However, drug resistance limits the long-term effectiveness of MC, necessitating ongoing development of anticancer drugs. Traditional drug discovery is lengthy and costly due to processes like target protein identification, virtual screening, lead optimization, and safety and efficacy evaluations. Drug repurposing (DR), which screens FDA-approved drugs for new uses, is emerging as a cost-effective alternative. Both experimental and computational methods, such as protein binding assays, in vitro cytotoxicity tests, structure-based screening, and several types of association analyses (Similarity-Based, Network-Based, and Target Gene), along with retrospective clinical analyses, are employed for virtual screening. This review covers the mechanisms of MC, its application in various cancers, DR strategies, examples of repurposed drugs, and the associated challenges and future directions.

A Repurposing Pipeline to Candidate-Suitable Inhibitors of Tyrosinase: Computational and Bioassay Studies.

Tyrosinase, a metalloprotein enzyme, plays a crucial role in melanin synthesis by hydroxylating L-tyrosine to L-dopa. However, the accumulation of melanin can lead to hyperpigmented spots, raising aesthetic concerns. In this study, we developed a pipeline to repurpose FDA-approved drugs as potential tyrosinase inhibitors. A structure-based screening study was conducted using 1,650 drugs to identify probable inhibitors based on binding energies. From the cluster analysis of binding interaction profiles, 16 compounds were selected as candidates. Montelukast emerged as the final candidate due to its favorable ADME properties. Bioassay evaluation revealed an IC50 value of 14.79±0.87 μM for Montelukast, compared to kojic acid (IC50=31.02±2.01 μM). Molecular dynamics simulation and g_MMPBSA free energy calculation studies were performed for the Tyrosinase-Montelukast complex. These findings enhance our understanding of Tyrosinase-Montelukast interactions and underscore Montelukast's potential as a tyrosinase inhibitor. This could have implications in dermatological applications and beyond, suggesting Montelukast as a promising candidate for further development in this regard.

Repurposing Antiviral Drugs as Potential Anti-EGFR Agents in NSCLC: A Structure-Based Screening and Molecular Dynamics Analysis.

One of the problems resulting from recurrent hyperactivated or mutant epidermal growth factor receptors (EGFR) in non-small cell lung cancer (NSCLC) is therapeutic resistance. Consequently, this leads to increased expression of oncogenic proteins and reduces the efficacy of EGFR tyrosine kinase inhibitors (TKIs). This study assessed antiviral drug efficacy as potential anti-EGFR agents for NSCLC. We used structure-based virtual screening to evaluate 66 antiviral drugs thoroughly. The top 6 antiviral drugs exhibiting impressive binding energies (i. e. surpassing a threshold of -8.5 kcal mol-1) were identified. Subsequent bioactivity analysis and ADMET profiling were performed to select the most promising candidates, followed by a molecular dynamic simulation. Among the selected antiviral regimens, dolutegravir demonstrated the highest docking score (-9.8 kcal mol-1), followed by rilpivirine and ensitrelvir, surpassing other candidates and our reference EGFR TKI. Further molecular dynamics simulations revealed promising dynamic interactions of dolutegravir, ensitrelvir, and rilpivirine with the EGFR target as compared with afatinib. Our findings highlight the repositioning potential of antiviral drugs for anti-EGFR drug discovery, supported by their robust docking scores, ADMET profiles, dynamic interactions, and binding free energies. The results open up new avenues for advanced NSCLC therapy. Further in vitro investigations are warranted to evaluate their efficacy and safety.

Targeting STING oligomerization with licochalcone D ameliorates STING-driven inflammatory diseases.

The development of STING inhibitors for the treatment of STING-related inflammatory diseases continues to encounter significant challenges. The activation of STING is a multi-step process that includes binding with cGAMP, self-oligomerization, and translocation from the endoplasmic reticulum to the Golgi apparatus, ultimately inducing the expression of IRF3 and NF-κB-mediated interferons and inflammatory cytokines. It has been demonstrated that disruption of any of these steps can effectively inhibit STING activation. Traditional structure-based drug screening methodologies generally focus on specific binding sites. In this study, a TransformerCPI model based on protein primary sequences and independent of binding sites is employed to identify compounds capable of binding to the STING protein. The natural product Licochalcone D (LicoD) is identified as a potent and selective STING inhibitor. LicoD does not bind to the classical ligand-binding pocket; instead, it covalently modifies the Cys148 residue of STING. This modification inhibits STING oligomerization, consequently suppressing the recruitment of TBK1 and the nuclear translocation of IRF3 and NF-κB. LicoD treatment ameliorates the inflammatory phenotype in Trex1-1- mice and inhibits the progression of DSS-induced colitis and AOM/DSS-induced colitis-associated colon cancer (CAC). In summary, this study reveals the potential of LicoD in treating STING-driven inflammatory diseases. It also demonstrates the utility of the TransformerCPI model in discovering allosteric compounds beyond the conventional binding pockets.

Discovery of Antibacterial Compounds with Potential Multi-Pharmacology against Staphylococcus Mur ligase Family Members by In Silico Structure-Based Drug Screening.

Staphylococcus aureus (S. aureus) is a major bacterial infection in humans, leading to severe disease and causing death. The stagnation of antibiotic development in recent decades has made it difficult to combat drug-resistant infections. In this study, we performed an in silico structure-based drug screening (SBDS) targeting the S. aureus MurE (saMurE) enzyme involved in cell wall synthesis of S. aureus. saMurE is an enzyme that is essential for the survival of S. aureus but not present in humans. SBDS identified nine saMurE inhibitor candidates, Compounds 1-9, from a structural library of 154,118 compounds. Among them, Compound 2 showed strong antibacterial activity against Staphylococcus epidermidis (S. epidermidis) used as a model bacterium. Amino acid sequence homology between saMurE and S. epidermidis MurE is 87.4%, suggesting that Compound 2 has a similar inhibitory effect on S. aureus. Compound 2 showed an IC50 value of 301 nM for S. epidermidis in the dose-dependent growth inhibition assay. Molecular dynamics simulation showed that Compound 2 binds stably to both S. aureus MurD and S. aureus MurF, suggesting that it is a potential multi-pharmacological pharmacological inhibitor. The structural and bioactivity information of Compound 2, as well as its potential multiple-target activity, could contribute to developing new antimicrobial agents based on MurE inhibition.

Structure-based screening, optimization and biological evaluation of novel chrysin-based derivatives as selective PPARγ modulators for the treatment of T2DM and hepatic steatosis

In consideration of several serious side effects induced by the classical AF-2 involved “lock” mechanism, recently disclosed PPARγ-Ser273 phosphorylation mode of action has become an alternative and mainstream mechanism for currently PPARγ-based drug discovery and development with an improved therapeutic index. In this study, by virtue of structure-based virtual high throughput screening (SB-VHTS), structurally chemical optimization by targeting the inhibition of the PPARγ-Ser273 phosphorylation as well as in vitro biological evaluation, which led to the final identification of a chrysin-based potential hit (YGT-31) as a novel selective PPARγ modulator with potent binding affinity and partial agonism. Further in vivo evaluation demonstrated that YGT-31 possessed potent glucose-lowering and relieved hepatic steatosis effects without involving the TZD-associated side effects. Mechanistically, YGT-31 presented such desired therapeutic index, mainly because it effectively inhibited the CDK5-mediated PPARγ-Ser273 phosphorylation, selectively elevated the level of insulin sensitivity-related Glut4 and adiponectin but decreased the expression of insulin-resistance-associated genes PTP1B and SOCS3 as well as inflammation-linked genes IL-6, IL-1β and TNFα. Finally, the molecular docking study was also conducted to uncover an interesting hydrogen-bonding network of YGT-31 with PPARγ-Ser273 phosphorylation-related key residues Ser342 and Glu343, which not only gave a clear verification for our targeting modification but also provided a proof of concept for the abovementioned molecular mechanism.

In Silico Investigation against Inhibitors of Alpha-Amylase Using Structure-based Screening, Molecular Docking, and Molecular Simulations Studies.

Type-II diabetes mellitus is a chronic disorder that results from fluctuations in the glucose level leading to hyperglycemia with severe adverse effects increasing worldwide. Alpha-Amylase is the key enzyme involved in the mechanism of glucose formation therefore Alpha-Amylase inhibitors have become a therapeutic target in the development of new leads as they have the potential to suppress glucose levels. Existing drugs targeting Alpha-Amylase highlight major drawbacks in terms of poor absorption rate that causes several gastrointestinal issues. So, this research is aimed to develop novel inhibitors interacting with Alpha-Amylase's active site using structural-based screening, binding pattern analysis, and molecular dynamic simulation. Hence, to search for a potential lead, we analyzed a total of 133 valiolamine derivatives and 535 desoxynojirimycin derivatives that exhibited drug-like properties screened through Lipinski filters. Virtual screening followed by binding interaction analysis we identified ten compounds that exhibited better binding energy scores compared to the standard drugs voglibose and miglitol, used in our study. The docking analysis, ADMET and metabolic site prediction estimated the best top two compounds with good drug profiles. Further, top compounds VG9 and VG15 were promoted to simulation study using the Biovia Discovery study to access the stability at a time interval of 100 ns. MD simulation results revealed that our compound VG9 possesses better conformational stability in the complex to the active site residues of Alpha-Amylase target protein than standard drug voglibose. Thus, our investigation revealed that compound VG9 also exhibits the best pharmacokinetic as well as binding affinity results and could act as a potential lead compound targeting Alpha-Amylase for Type II diabetes.

Discovery of new cyclopropane sulfonamide derivatives as EGFR inhibitors to overcome C797S-mediated resistance and EGFR double mutation

The C797S mutation of EGFR leads to Osimertinib resistance by blocking the covalent binding of Cys797. To develop new agents that can overcome EGFR mutation resistance, thirty seven new cyclopropane sulfonamide derivatives were synthesized and evaluated as EGFRL858R/T790M/C797S or EGFRDel19/T790M/C797S inhibitors by structure-based screening. Most of the synthesized compounds exhibit good to excellent anti proliferation activity against to BaF3-EGFR L858R/T790M/C797S and BaF3–C797S/Del19/T790M cancer cell lines. Representative compounds 8l showed inhibitory activity against the two cancer cell lines with the IC50 values of 0.0012 and 0.0013 μM, respectively. Another compound 8h, exhibited slightly lower activity (0.0042 and 0.0034 μM of the IC50 values) to both of the two tri-mutation cell lines, but excellent activities against H1975 and PC9 cells with IC50 values of 13 and 19 nM, respectively. Considering the acquired drug resistance of tumors is a gradual process, we chose 8h for further in vivo and mechanism study. 8h was demonstrated significantly inhibited tumor growth with 72.1 % of the TGI in the BaF3/EGFR-TM xenograft tumor model and 83.5 % in the H1975-DM xenograft tumor model. Compound 8h was confirmed to be safe with no significant side effects as showed by the results of in vitro assay of human normal cells and the sections of animals major organs. Mechanism studies showed that in addition to inhibiting EGFR mutations, 8h can also target the tumor microenvironment and induce tumor cell apoptosis. All these results indicate that 8h deserves further investigation as an EGFR inhibitor to overcome C797S-mediated resistance.

Identification of Druggable Binding Sites and Small Molecules as Modulators of TMC1.

Our ability to hear and maintain balance relies on the proper functioning of inner ear sensory hair cells, which translate mechanical stimuli into electrical signals via mechano-electrical transducer (MET) channels, composed of TMC1/2 proteins. However, the therapeutic use of ototoxic drugs, such as aminoglycosides and cisplatin, which can enter hair cells through MET channels, often leads to profound auditory and vestibular dysfunction. Despite extensive research on otoprotective compounds targeting MET channels, our understanding of how small molecule modulators interact with these channels remains limited, hampering the discovery of novel compounds. Here, we propose a structure-based screening approach, integrating 3D-pharmacophore modeling, molecular simulations, and experimental validation. Our pipeline successfully identified several novel compounds and FDA-approved drugs that reduced dye uptake in cultured cochlear explants, indicating MET modulation activity. Molecular docking and free-energy estimations for binding allowed us to identify three potential drug binding sites within the channel pore, phospholipids, and key amino acids involved in modulator interactions. We also identified shared ligand-binding features between TMC and structurally related TMEM16 protein families, providing novel insights into their distinct inhibition, while potentially guiding the rational design of MET-channel-specific modulators. Our pipeline offers a broad application to discover small molecule modulators for a wide spectrum of mechanosensitive ion channels.

Structure-based multitargeted docking screening, pharmacokinetics, DFT, and dynamics simulation studies reveal mitoglitazone as a potent inhibitor of cellular survival and stress response proteins of lung cancer.

Lung cancer is a disease in which lung cells grow abnormally and uncontrollably, and the cause of it is direct smoking, secondhand smoke, radon, asbestos, and certain chemicals. The worldwide leading cause of death is lung cancer, which is responsible for more than 1.8 million deaths yearly and is expected to rise to 2.2 million by 2030. The most common type of lung cancer is non-small cell lung cancer (NSCLC), which accounts for about 80% and small cell lung cancer (SCLC), which is more aggressive than NSCLC and is often diagnosed later and accounts for 20% of cases. The global concern for lung cancer demands efficient drugs with the slightest chance of developing resistance, and the idea of multitargeted drug designing came up with the solution. In this study, we have performed multitargeted molecular docking studies of Drug Bank compounds with HTVS, SP and XP algorithms followed by MM\GBSA against the four proteins of lung cancer cellular survival and stress responses, which revealed Mitoglitazone as a multitargeted inhibitor with a docking and MM\GBSA score ranging from - 5.784 to - 7.739 kcal/mol and - 25.81 to - 47.65kcal/mol, respectively. Moreover, we performed pharmacokinetics studies and QM-based DFT analysis, showing suitable candidate and interaction pattern analysis revealed the most count of interacting residues was 4GLY, 5PHE, 6ASP, 6GLU, 6LYS, and 6THR. Further, the results were validated with SPC water model-based MD simulation for 100ns in neutralised condition, showing the cumulative deviation and fluctuation < 2Å with many intermolecular interactions. The whole analysis has suggested that Mitoglitazone can be used as a multitargeted inhibitor against lung cancer-however, experimental studies are needed before human use.

Abstract 4495: Structure-based screening for potential ROR1 inhibitors and their potential as antitumor agents in pancreatic cancer cells

Abstract Background: The identification of novel compounds that specifically target cancer cells while sparing normal tissues is crucial. The orphan tyrosine kinase-like receptor 1 (ROR1) is one such target expressed exclusively in various human malignancies, including pancreatic cancer, but not in normal adult tissues. Inhibiting ROR1 signaling shows promise in halting pancreatic cancer cell proliferation and invasion. In this study, lead compounds CSF1R-IN-1 and MCULE-8715589337 were found as potential inhibitors of the ROR1 and were further evaluated for its potential effect on pancreatic cancer cell viability. Method: We curated a compound library of 6 million from PubChem, 2 million lead-like compounds from ZINC15, and 2 million compounds from diverse vendors. Employing Glide’s HTVS followed by XP, we refined the selection based on docking scores lower than the reference molecule, Ponatinib. Compounds were shortlisted by pre-simulation MMGBSA calculations with Schrödinger Prime MM-GBSA module, focusing on compounds with energies below -100 kcal/mol. Then we performed MD simulation for 100ns. Post-simulation MMGBSA on the last 1 ns of simulation assessed change in ligands’ binding energies. The selected leads underwent further validation utilizing two pancreatic cancer cell lines, MiaPaCa-2 and PANC-1. Half-maximal inhibitory concentration (IC50) was assessed using MTS cell viability assay. Result: Comparing pre- and post-simulation MMGBSA energies, the reference compound showed increased, while CSF1R-IN-1 and MCULE-8715589337 exhibited decreased energies. The reference ligand's RMSD showed stability with fluctuations of 3 to 3.5 Å, whereas CSF1R-IN-1 and MCULE-8715589337 had stable and lower RMSD values (approximately 3 Å and 2.4 Å). Test compounds, CSF1R-IN-1 and MCULE-8715589337 showed better molecular interactions with ROR1 compared to reference. The reference compound formed hydrogen bonds with ILE555 and ASP633, along with pi-pi stacking with PHE552. CSF1R-IN-1 forms a hydrogen bond with ILE555 and ASP633, pi-pi stacking with PHE552, and interaction with SER632 through a water bridge. Additionally, compound MCULE-8715589337 forms hydrogen bonds with ASP633, SER632, LYS506, and GLU523. CSF1R-IN-1 notably inhibited proliferation in MiaPaCa-2 cells (IC50: 1.29 μM) while no efficacy in PANC-1 cells (IC50: 78.41 μM). MCULE-8715589337 showed relatively similar IC50 values of 39.06 μM and 37.73 μM in MiaPaCa-2 and PANC-1 cells, respectively. Conclusion: The reduction in MMGBSA energies, low RMSD values, and a higher number of interactions highlight the better characteristics of both compounds compared to the reference. Our findings show CSF1R-IN-1 and MCULE-8715589337 have efficacy in pancreatic cancer cells, but further studies are required to validate and to understand the mechanism of action. Citation Format: Indrakant Kumar Singh, Shradheya RR Gupta, Pooja Mittal, Shivani Soni, Jae Ho Lo, Francesca Battaglin, Yan Yang, Lesly Torres-Gonzalez, Sandra Algaze, Priya Jayachandran, Karam Ashouri, Alexandra Wong, Wu Zhang, Joshua Millstein, Heinz Josef Lenz. Structure-based screening for potential ROR1 inhibitors and their potential as antitumor agents in pancreatic cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4495.

Abstract 4493: Protein structure inspired drug discovery

Abstract Introduction: Drug action is mediated by a small molecule therapeutic binding to a specific structural motif on a protein. As structure determines function, it follows that unique structural motifs are enriched for sites of unique function and high therapeutic target value. We hypothesized that protein structure constitutes high value primary information that can drive the discovery of novel therapeutic agents. Method: We developed a unique physics-based protein structure analysis platform scaled to run on a supercomputer, allowing us to consider dynamic protein flexibility and the influence of solvent upon protein structure, and to probe large protein libraries as a primary source of structure information that can support up-front structure-based screens. We developed and then probed a high resolution protein x-ray crystallographic library, created and curated by us. From a 60 million compound library, we conducted virtual screens for docking to identified sites. 8-day colony formation assays were conducted on a panel of 8 human breast, prostate, lung and colon cancer cell lines, as well as 8- and 14-day trilineage hematopoietic colony formation assays on human cord blood stem cells. Findings: From the first 180 deposited protein structures, we screened for unique protein surface structure. Structures were deemed unique if they were not otherwise known to be associated with any particular functional roles and were not the binding site of known therapeutics. Further selection included those that were clefts and possessed physical characteristics compatible with binding small chemicals whose properties have been linked to effective therapeutics. For each of 8 sites on 6 different proteins, a suite of analytics probed docking solutions from the compound library, generating a ranked list of 100 compounds for each site. Based on factors inclusive of availability and low potential for toxicity, compounds were acquired and used in in-parallel selection and de-selection functional assays. Cancer cell growth inhibition was a positive selection criterion, with additional ranking based on greater potency and broader efficacy. Bone marrow toxicity is limiting for most drugs, and inhibition of bone marrow stem cell growth was as a deselection criterion. Multiple compounds clustered around 2 sites on 2 different proteins. One compound, Dxr2-017, exhibited very high relative efficacy against colon and breast cancer cells. Evaluation of Dxr2-017 in the NCI-60 panel corroborated these findings, and showed even higher efficacy against melanoma. We demonstrated that Dxr2-017 inhibited melanoma growth with low nanomolar efficacy, while concentrations of over 2300-fold higher had only limited inhibitory effects on bone marrow stem cells. Conclusions: This study provides proof-of-principle that protein structure constitutes high value primary information that can support identification of novel therapeutics. This approach is widely applicable and expandable. Citation Format: Fangfang Qiao, T. Andrew Binkowski, Wayne Anderson, Weining Chen, Gray Schiltz, Karl Scheidt, Amarnath Natarajan, Raymond Bergan. Protein structure inspired drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4493.

Identification of Novel Antimicrobial Compounds Targeting Mycobacterium tuberculosis S-Adenosyl-L-Homocysteine Hydrolase Using Dual Hierarchical In Silico Structure-Based Drug Screening.

The emergence of multidrug-resistant and extensively drug-resistant Mycobacterium tuberculosis (M. tuberculosis) has become a major medical problem. S-adenosyl-L-homocysteine hydrolase (MtSAHH) was selected as the target protein for the identification of novel anti-TB drugs. Dual hierarchical in silico Structure-Based Drug Screening was performed using a 3D compound structure library (with over 150 thousand synthetic chemicals) to identify compounds that bind to MtSAHH's active site. In vitro experiments were conducted to verify whether the nine compounds selected as new drug candidates exhibited growth-inhibitory effects against mycobacteria. Eight of the nine compounds that were predicted by dual hierarchical screening showed growth-inhibitory effects against Mycobacterium smegmatis (M. smegmatis), a model organism for M. tuberculosis. Compound 7 showed the strongest antibacterial activity, with an IC50 value of 30.2 µM. Compound 7 did not inhibit the growth of Gram-negative bacteria or exert toxic effects on human cells. Molecular dynamics simulations of 40 ns using the MtSAHH-Compound 7 complex structure suggested that Compound 7 interacts stably with the MtSAHH active site. These in silico and in vitro results suggested that Compound 7 is a promising lead compound for the development of new anti-TB drugs.

Mechanistic insights into inhibition of CCL2-guided leukocyte recruitment by oxyresveratrol and its derivatives

Inflammatory responses are the outcomes of coordinated interactions amongst chemokines and their exclusive non-negotiable counterparts such as glycosaminoglycans and GPCRs. CCL2 in conjunction with other immune molecules positively regulates the migration, infiltration, and recruitment of macrophages to the site of inflammation, hence is a promising target from pharmaceutical perspective. Stilbenes such as resveratrol and its derivatives are well documented for their anti-inflammatory responses. The current study presents a structure-based screening and unravels the molecular recognition patterns of stilbene derivatives against CCL2 chemokine to identify their potential to interact and inhibit the proinflammatory activity of CCL2. Structure based in silico screening of aglycosidic stilbenes followed by fluorescence, NMR and in vitro chemotaxis experiments established that oxyresveratrol (ORS), a symmetrical hydroxylated stilbene, prominently binds CCL2 and inhibits macrophage migration. Further, extensive computational analysis reveals the atom level details of molecular recognition events on ORS and its two derivatives ORS10/ORS16, whereby ORS16 demonstrated as a superior CCL2 binding counterpart. Indeed, NMR and computational analysis suggested that ORS interacts through the receptor binding site of CCL2 to attenuate the leukocyte migration. In brief, the current study provides a basis for designing potential inhibitors opting ORS, and more precisely ORS16 as a primary architecture for targeting CCL2-mediated inflammatory proceedings.

In silico Structure-based Screening of Potential Anticancer Bioactive Natural Constituents from African Natural Products

Introduction: Inhibitors of topoisomerases, essential regulators of cancer development, are promising as cancer treatments. These enzymes regulate DNA topology and eliminate topological constraints during various biological processes, including replication, transcription, and recombination. Nature has continually offered scientists pathways to explore the development of new drugs. Indeed, since ancient times, various plant extracts have been utilized in treating multiple pathologies. Objective: It’s intriguing to diversify the therapeutic classes of natural topoisomerase 1 inhibitors. We aimed to explore the relationship between the toxicity of certain medicinal plants in North Africa and their anti-topoisomerase 1 enzyme activity. This investigation aims to discover potentially valuable compounds for fighting cancer by inhibiting the Topo1 enzyme, enriching the anticancer therapeutic class. Methods: This study has conducted a virtual screening of the African Natural Products Database to identify new scaffolds as topoisomerase 1 inhibitors. Molecular docking as a structure-based drug design approach was selected as one of the best approaches, and the complex code ID: 1K4T was used for this purpose. Results and Discussion: The molecular docking of more than 5790 natural products extracted from this database was docked into the binding site of the above-cited complex using the Modlock optimizer and Moldock score as search and scoring function algorithms, respectively. The top-ranked compounds have been assessed, analyzed, and compared to Topotecan and Irinotecan as reference ligands and drugs. Conclusion: Consequently, the seven natural products have shown a strong affinity to topoisomerase 1 and DNA. They establish a clear link between topoisomerase 1 inhibition and the anticancer activity of their corresponding plant extracts. Therefore, these hits are promising and serve as a base for further development of new topoisomerase 1 inhibitors.

Identification of potent inhibitors targeting Tribolium castaneum GSTe2 via structure-based screening and molecular dynamics simulation

Red flour beetle, Tribolium castaneum, has a major negative impact during storage of agricultural products and reveals the negative impacts on human health. Insect-specific epsilon glutathione S-transferase (GSTs) which requires reduced glutathione (GSH) as an essential substrate not only develop insecticide resistance but also play important role in insect metamorphosis. Inhibition of the insect metamorphosis and the development of insecticide resistance could play an important role in pest control, so T. castaneum GSTe2 (TcGSTe2) in our previous study could be an important target protein for this purpose. This study aimed to find a potential TcGSTe2 inhibitors through in silico mothods, including molecular modeling, molecular docking, ADMET assay, followed by molecular dynamics (MD) simulation, principal component analysis and MM/PBSA analysis. The results showed that ZINC000169293362 and ZINC000095566957 were selected as potential TcGSTe2 inhibitors with high-binding affinity and without any toxicity from 3618 of GSH-like compounds obtained from ZINC database. MD simulation results revealed that TcGSTe2-ZINC000169293362 had more stability than that of reference GSH. Moreover, TcGSTe2-ZINC000169293362 and TcGSTe2-ZINC000095566957 showed lower binding free energy (−27.53 ± 0.16 kcal/mol and −18.83 ± 0.15 kcal/mol, respectively) compared with TcGSTe2-GSH (−8.90 ± 0.30 kcal/mol). This study could provide new insight into reduction of insecticide resistance and be used to design new inhibitors of insect GSTs. Communicated by Ramaswamy H. Sarma

Structure-based screening of sp2 hybridized small donor bridges as donor: acceptor switches for optical and photovoltaic applications: DFT way.

This research aims to investigate the potential of pyrazine-based small donor moieties as donor-acceptor switches for optical and photovoltaic applications. The designed organic dyes have a high light harvesting efficiency (LHE) and can potentially generate significant electrical energy. The study focuses on understanding the structural and electronic properties of these dyes through the analysis of dihedral angles, bond lengths, and energies of frontier molecular orbitals The UV-Vis spectroscopy parameters of the designed organic dyes revealed their absorption characteristics, including transition energies, wavelengths (λmax), and oscillator strengths (f). The photovoltaic properties of the developed organic dyes show a range of values: a range of 0.95-0.99 for LHE and a range of 1.77-33.02 W for maximum power output (Pmax) with the highest value for dye DDP5. For their stabilization energies, their natural bond orbitals had values ranging from 0.56 to 128.48kcal/mol, their E(j)E(i) values from 0.22 to 1.29 a.u, and their Fi,j values from 0.024 to 0.213kcal/mol. Out of all dyes, the DDP5 produced highest push-pull effect and can be good choice for further studies. The design of these novel organic materials for effective and economical solar energy conversion will be aided by evaluating the potential of 5,10-diphenyl-5,10-dihydrophenazine as a donor moiety and determining the structure-property correlations controlling the photovoltaic performance of the compounds.