Rational Drug Design Research Articles

Water occupancy in the Acinetobacter baumannii F-ATP synthase c-ring and its implications as a novel inhibitor target.

The Acinetobacter baumannii F1FO-ATP synthase is essential for the opportunistic human pathogen. Its membrane-embedded FO domain consists of the c-ring and subunit a. The c-ring translocates protons via a conserved carboxylate across the membrane via two half-channels in subunit a, and its revolution enables the F1 domain to carry out ATP formation. Here, we used molecular dynamics simulations, free energy calculations, and invivo mutational experiments to assess the likely existence of water molecules in the binding site of the A.baumannii c-ring. We first predicted its binding site structure in the ion-locked conformation and extrapolated the presence of two water molecules in the ion-binding site. Based on our predictions, amino acid point mutations confirmed the critical role of key residues involved in the water-binding site upon ATP synthesis ability and cell growth. We discuss the implications of our findings in the context of rational drug design to target the A.baumannii FO domain.

Comparative study of degree and neighborhood degree sum-based topological indices for predicting physicochemical properties of skin cancer drug structures

Quantitative structure property relationship (QSPR) is essential in rational drug design by facilitating the prediction, optimization, and prioritization of potential drug candidates based on their chemical structures and properties, optimizing the utilization of computational resources and minimizing costs. Topological indices play a fundamental role in QSPR studies by providing a quantitative representation of molecular structures and facilitating the prediction of various chemical properties and activities. Metastatic skin cancer can be aggressive and potentially fatal, and thus developing effective drugs can improve patient outcomes, including overall survival rates and progression-free survival. This research work focuses on the structural behaviors of medications used in the treatment of skin cancer, including binimetinib, fisetin, encorafenib, picato, fluorouracil, trametinib, vemurafenib, imiquimod, odomzo, vismodegib, dacarbazine, cobimetinib, dabrafenib, sesamol, curcumin, doxorubicin, temozolomide, paclitaxel, itraconazole, and hyaluronan. We have developed QSPR models involving degree and neighborhood degree sum-based indices and conducted a comparative analysis to highlight the efficacy of the models.

APPLICATION OF COMPUTATIONAL METHODS IN DRUG DISCOVERY

Rational drug design, is the inventive process of finding new medications based on knowledge of the biological target. Drug design involves the design of small molecules that are complementary in shape and charge to the bimolecular target to which they interact and therefore will bind to it. In the experiment based approach, drugs are discovered through trial and error. With high R&D cost and consumption, computational drug discovery helps scientists gain insight into drug receptor interactions and reduce time and cost. Scientists can predict whether the molecule will succeed or fail in the market. Currently, the process of drug designing increasingly relies on computer modeling techniques. This type of modeling is often referred to as computer-aided drug design. In computational drug discovery, different computational tools, methods, and software are used to simulate drug receptor interactions. Using computational drug discovery helps scientists gain insight into drug receptor interactions with less time and cost.

Binding Selectivity of Inhibitors to BRD2 Uncovered by Molecular Docking and Molecular Dynamics Simulations

AbstractBromodomain‐containing protein 2 (BRD2) plays a significant role in the development and progression of various diseases. Investigating the binding selectivity of the two bromodomains BD1 and BD2 of BRD2 (BRD2‐BD1 and BRD2‐BD2) with specific inhibitors can provide valuable insights for rational design of novel therapeutic drugs. Thus, molecular dynamics (MD) simulations are employed to evaluate the selective mechanisms of three BRD2 inhibitors, Spd16, BBC0403, and SJ1461, toward BRD2‐BD1 and BRD2‐BD2. Molecular Mechanics/Generalized Born Surface Area (MM‐GBSA) and Solvation Interaction Energy (SIE) methods are further employed to analyze the interaction modes and compare the binding free energies of BRD2‐BD1 and BRD2‐BD2 with these inhibitors. Although these inhibitors exert different effects on the internal structures of BRD2‐BD1 and BRD2‐BD2, their interaction patterns with these two bromodomains are similar. Phe372, Leu381, Tyr386, and Cys425 play key roles in the interaction between BRD2‐BD2 and these three inhibitors, while Pro98, Leu108, Asn156, and Ile162 are the critical residues for the binding of BRD2‐BD1 with these inhibitors. Non‐polar interactions, particularly van der Waals interactions, serve as the primary driving force behind the binding of these inhibitors with BRD2‐BD1 and BRD2‐BD2. The findings of this study provide valuable insights for the rational design of novel BRD2 inhibitors.

The conformational landscape of human transthyretin revealed by cryo-EM.

Transthyretin (TTR) is a natively tetrameric thyroxine transporter in blood and cerebrospinal fluid whose misfolding and aggregation causes TTR amyloidosis. A rational drug design campaign identified the small molecule tafamidis (Vyndamax) as a stabilizer of the native TTR fold, and this aggregation inhibitor is regulatory agency approved for the treatment of TTR amyloidosis. Here we used cryo-EM to investigate the conformational landscape of this 55 kDa tetramer in the absence and presence of one or two ligands, revealing inherent asymmetries in the tetrameric architecture and previously unobserved conformational states. These findings provide critical mechanistic insights into negatively cooperative ligand binding and the structural pathways responsible for TTR amyloidogenesis, underscoring the capacity of cryo-EM to identify pharmacological targets suppressed by the confines of the crystal lattice, opening uncharted territory in structure-based drug design.

Developing novel Lin28 inhibitors by computer aided drug design

Lin28 is a key regulator of cancer stem cell gene network that promotes therapy-resistant tumor progression in various tumors. However, no Lin28 inhibitor has been approved to treat cancer patients, urging exploration of novel compounds as candidates to be tested for clinical trials. In this contribution, we applied computer-aided drug design (CADD) in combination with quantitative biochemical and biological assays. These efforts led to the discovery of Ln268 as a drug candidate that can block Lin28 from binding to its RNA substrates and inhibit Lin28 activities. Ln268 suppressed Lin28-mediated cancer cell proliferation and spheroid growth. Results from nuclear magnetic resonance spectroscopy confirmed that Ln268 perturbs the conformation of the zinc knuckle domain of Lin28, validating the rational drug design by CADD. The inhibitory effects of Ln268 are dependent on Lin28 protein expression in cancer cells, highlighting limited off-target effects of Ln268. Moreover, Ln268 synergizes with several chemotherapy drugs to suppress tumor cell growth. In summary, Ln268 is a promising candidate for further development to target Lin28 as a cancer therapy.

BK Polyomavirus-associated nephropathy - diagnostic and treatment standard.

BK polyomavirus (BKPyV) is recognised as a significant viral complication of kidney transplantation. Prompt immunosuppression reduction reduces early graft failure rates due to BK polyomavirus-associated nephropathy (BKPyVAN), however modulation of immunosuppression can lead to acute rejection. Medium-to-long term graft outcomes are negatively impacted by BKPyVAN, likely due to a combination of virus-induced graft damage and host immune responses against graft alloantigens potentiated by immunosuppression reduction. Kidney biopsy remains the gold-standard diagnostic test, however false negative findings are common due to the focal nature of BKPyVAN. BKPyV DNAemia, as measured by quantitative polymerase chain reaction (qPCR), is established as a screening test but there is at present no (inter)national standardisation of these assays to allow collation and comparison of data between centres. Randomised controlled trials are lacking both in terms of optimal immunosuppression reduction strategies, and for the medications variably used to attempt treatment in clinical practice. Much of the fundamental biology of BKPyV is not yet understood, and further elucidation is required to promote rational direct-acting antiviral drug design. Insights into the role of adaptive immunity in control of BKPyV have informed the design of novel treatments such as adoptive immunotherapies and neutralizing antibodies which require evaluation in clinical studies. Here, we review the current standards of diagnosis and treatment of BKPyVAN and discuss novel developments in the pathophysiology, diagnosis, outcome prediction and management.

Integrative genomic analyses combined with molecular dynamics simulations reveal the impact of deleterious mutations of Bcl-2 gene on the apoptotic machinery and implications in carcinogenesis.

Unlike other diseases, cancer is not just a genome disease but should broadly be viewed as a disease of the cellular machinery. Therefore, integrative multifaceted approaches are crucial to understanding the complex nature of cancer biology. Bcl-2 (B-cell lymphoma 2), encoded by the human BCL-2 gene, is an anti-apoptotic molecule that plays a key role in apoptosis and genetic variation of Bcl-2 proteins and is vital in disrupting the apoptotic machinery. Single nucleotide polymorphisms (SNPs) are considered viable diagnostic and therapeutic biomarkers for various cancers. Therefore, this study explores the association between SNPs in Bcl-2 and the structural, functional, protein-protein interactions (PPIs), drug binding and dynamic characteristics. Comprehensive cross-validated bioinformatics tools and molecular dynamics (MD) simulations. Multiple sequence, genetic, structural and disease phenotype analyses were applied in this study. Analysis revealed that out of 130 mutations, approximately 8.5% of these mutations were classified as pathogenic. Furthermore, two particular variants, namely, Bcl-2G101V and Bcl-2F104L, were found to be the most deleterious across all analyses. Following 500ns, MD simulations showed that these mutations caused a significant distortion in the protein conformational, protein-protein interactions (PPIs), and drug binding landscape compared to Bcl-2WT. Despite being a predictive study, the findings presented in this report would offer a perspective insight for further experimental investigation, rational drug design, and cancer gene therapy.

Quantum Chemical Calculation and in silico Molecular Modelling Studies on Some Multi-targeting Anti-Inflammatory Inhibitors

Problem Statement: Inflammation plays a key role in many chronic diseases, including autoimmune disorders and arthritis. There are some of the natural compounds, which possess anti-inflammatory properties and offer significant therapeutic potential. Computer-aided molecular design helps to discover the Quantitative Structure Activity Relationship (QSAR) of the molecules. Aims: This study aims to provide a deeper understanding of the electronic structure and reactivity behaviour of natural compounds to design novel leads with enhanced biological activity. Methodology: Natural anti-inflammatory molecules from plant and marine sources were identified through an extensive literature review. Compounds such as Oleocanthal, Viridicatin, Liquiritin, and Nobiletin were selected for analysis. Their electronic structures were studied using Density Functional Theory (DFT) with the B3LYP functional and 6-311G(d,p) basis set to calculate geometric and electronic parameters, reactivity descriptors, and molecular electrostatic potential (MEP) maps. Physicochemical properties and drug-likeness were assessed through in silico ADMET studies. Finally, molecular docking simulations were performed to evaluate the binding affinities and interactions of the selected compounds with key inflammatory targets, including IL-17, MAPK, TNF-α, and MMP-9. Results: The DFT calculations revealed critical insights into the electronic distribution and reactivity patterns of the compounds, identifying potential interaction sites. ADMET predictions confirmed favourable drug-likeness and safety profiles, while docking studies highlighted significant binding affinities, particularly for Liquiritin, which demonstrated the highest binding efficiency among the tested compounds. Conclusion: By integrating quantum chemical calculations and molecular modelling, this study provides a comprehensive framework for exploring the QSARs of natural anti-inflammatory compounds. The findings contribute to the rational design and discovery of novel anti-inflammatory drugs with improved therapeutic potential.

A nanobody-enzyme fusion protein targeting PD-L1 and sialic acid exerts anti-tumor effects by C-type lectin pathway-mediated tumor associated macrophages repolarizing.

Aberrant sialylated glycosylation in the tumor microenvironment is a novel immune suppression pathway, which has garnered significant attention as a targetable glycoimmune checkpoint for cancer immunotherapy to address the dilemma of existing therapies. However, rational drug design and in-depth mechanistic studies are urgently required for tumor sialic acid to become valuable glycoimmune targets. In this study, we explored the positive correlation of PD-L1 and sialyltransferase expression in clinical colorectal cancer tissues and identified their mutual regulation effects in macrophages. Subsequently, we characterized a new sialidase with excellent properties from human oral symbiotic bacteria and then developed a novel nanobody-enzyme fusion protein, designated as Nb16-Sia, to concurrently target the PD-L1 and sialic acid. Results from syngeneic colon tumor models reveal superior efficacy of Nb16-Sia over monotherapy and combinations, which could remodel the tumor immune microenvironment. Mechanistically, Nb16-Sia, which could repolarize macrophages from the tumor-promoting M2 to anti-tumor M1 phenotype via the C-type lectin pathway, exerted its antitumor efficacy mainly by regulating tumor-associated macrophages. Our strategy of nanobody-enzyme fusion protein effectively enables the delivery of sialidase, allows the collaboration between anti-PD-L1 nanobody and sialidase in combating tumors, and holds considerable promise for further development.

Effects of linkers on the development of liposomal docetaxel-glutathione prepared by active click loading.

Loading drug-maleimide (MAL) conjugates into liposomes preloaded with glutathione (GSH) can prepare the liposome encapsulating GSH-conjugated prodrugs, which serve as a feasible way to construct liposomal formulation. However, the effects ofthelinker on the development of this liposomal system remained unclear. Herein, docetaxel (DTX)-MAL conjugates linked by various linkers were used for such studies. It was found that the linker influenced the aqueous solubility of DTX-MALs, which further affected their loading efficiency in liposomes. The linker significantly influenced the DTX release from liposomal DTX-GSH (DTX-LIPs) by impacting the activation rate of DTX-GSH outside liposomes. Notably, DTX-LIPs containing the rapidly-activated DTX-GSH exhibited much more potent antitumor activity in the 4T1 breast cancer xenograft than other DTX-LIPs and commercial DTX injections. Analysis of the drug release mechanism revealed that DTX-GSH was first released from theliposome and consequently activated into DTX, and the prodrug activation was the rate-limiting step for DTX release. These results highlighted the crucial role of linkers in the drug loading, drug release, and antitumor activity of DTX-LIPs prepared by active click loading, which would effectively guide the rational design of liposomal drugs for improved antitumor efficacy.

Structural Bioinformatics for Rational Drug Design

Structural Bioinformatics for Rational Drug Design

Demystifying Small-Molecule Phosphodiesterase-IV Inhibition: Computer-Aided Rational Drug Design for Future Precision Drug Development

Demystifying Small-Molecule Phosphodiesterase-IV Inhibition: Computer-Aided Rational Drug Design for Future Precision Drug Development

Overview of the epigenetic/cytotoxic dual-target inhibitors for cancer therapy.

Epigenetic dysregulation plays a pivotal role in the initiation and progression of various cancers, influencing critical processes such as tumor growth, invasion, migration, survival, apoptosis, and angiogenesis. Consequently, targeting epigenetic pathways has emerged as a promising strategy for anticancer drug discovery in recent years. However, the clinical efficacy of epigenetic inhibitors, such as HDAC inhibitors, has been limited, often accompanied by resistance. To overcome these challenges, innovative therapeutic approaches are required, including the combination of epigenetic inhibitors with cytotoxic agents or the design of dual-acting inhibitors that target both epigenetic and cytotoxic pathways. In this review, we provide a comprehensive overview of the structures, biological functions and inhibitors of epigenetic regulators (such as HDAC, LSD1, PARP, and BET) and cytotoxic targets (including tubulin and topoisomerase). Furthermore, we discuss recent advancement of combination therapies and dual-target inhibitors that target both epigenetic and cytotoxic pathways, with a particular focus on recent advances, including rational drug design, pharmacodynamics, pharmacokinetics, and clinical applications.

Energetics of substrate transport in proton-dependent oligopeptide transporters

The PepTSo transporter mediates the transport of peptides across biological membranes. Despite advancements in structural biology, including cryogenic electron microscopy structures resolving PepTSo in different states, the molecular basis of peptide recognition and transport by PepTSo is not fully elucidated. In this study, we used molecular dynamics simulations, Markov State Models (MSMs), and Transition Path Theory (TPT) to investigate the transport mechanism of an alanine-alanine peptide (Ala-Ala) through the PepTSo transporter. Our simulations revealed conformational changes and key intermediate states involved in peptide translocation. We observed that the presence of the Ala-Ala peptide substrate lowers the free energy barriers associated with transition to the inward-facing state. We also show a proton transport model and analyzed the pharmacophore features of intermediate states, providing insights for rational drug design. These findings highlight the significance of substrate binding in modulating the conformational dynamics of PepTSo and identify critical residues that facilitate transport.

Novel PD-L1/VISTA Dual Inhibitor as Potential Immunotherapy Agents.

Inhibiting the activity of immune checkpoint proteins to reignite the antitumor activity of immune cells has emerged as a pivotal strategy. PD-L1 and VISTA, as critical proteins governing immune regulation, are concurrently upregulated under conditions such as hypoxia. Through a rational drug design process, P17, a dual-target inhibitor for PD-L1 and VISTA is identified. This inhibitor blocks the signaling pathways of both PD-L1 and VISTA at the protein and cellular levels, thereby reactivating the antitumor function of T cells. P17 displays encouraging attributes in terms of druggability and safety assessments. Notably, P17 demonstrates superior antitumor efficacy compared to single-target inhibitors at equivalent doses in in vivo experiments. More crucially, P17 significantly enhances the infiltration of immune cells. This study not only validates the effectiveness of a dual-target inhibitor strategy against PD-L1 and VISTA, but also identifies P17 as a promising candidate molecule with significant therapeutic potential.

Multiple Binding Modes of Inhibitors to Human Carbonic Anhydrases: An Update on the Design of Isoform-Specific Modulators of Activity.

Human carbonic anhydrases (hCAs) are widespread zinc enzymes that catalyze the hydration of CO2 to bicarbonate and a proton. Currently, 15 isoforms have been identified, of which only 12 are catalytically active. Given their involvement in numerous physiological and pathological processes, hCAs are recognized therapeutic targets for the development of inhibitors with biomedical applications. However, despite massive development efforts, very few of the presently available hCA inhibitors show selectivity for a specific isoform. X-ray crystallography is a very useful tool for the rational drug design of enzyme inhibitors. In 2012 we published in Chemical Reviews a highly cited review on hCA family (Alterio, V. et al. Chem Rev. 2012, 112, 4421-4468), analyzing about 300 crystallographic structures of hCA/inhibitor complexes and describing the different CA inhibition mechanisms existing up to that date. However, in the period 2012-2023, almost 700 new hCA/inhibitor complex structures have been deposited in the PDB and a large number of new inhibitor classes have been discovered. Based on these considerations, the aim of this Review is to give a comprehensive update of the structural aspects of hCA/inhibitor interactions covering the period 2012-2023 and to recapitulate how this information can be used for the rational design of more selective versions of such inhibitors.

Ligand Binding and Functional Effect of Novel Bicyclic α5 GABAA Receptor Negative Allosteric Modulators.

The significant importance of GABAA receptors in the treatment of central nervous system (CNS) disorders has been known for a long time. However, only in recent years have experimental protein structures been published that can open the door to understanding protein-ligand interactions and may effectively help the rational drug design for the future. In our previous work (Szabó, G. J. Med. Chem. 2022, 65(11), 7876), where a promising selective α5-GABAA negative allosteric modulator (NAM) was developed containing the 3-(4-fluorophenyl)-5-methyl-1,2-oxazole headgroup, we noticed a switch-like effect of a single nitrogen atom for the receptor function in some derivatives having a dihydro-naphthyridinone or dihydro-isoquinolinone moiety. Here, we focused on this chemotype, and a small set of compounds were designed to investigate ligand-receptor interactions experimentally and through computational methods. Elaborated compounds were tested against GABAA α1 and α5 subunit-containing receptors, and binding affinities and functional activities were measured. Starting from the published experimental structure of an engineered, homopentameric, basmisanil-binding GABAA receptor-like construct consisting of modified α5 subunits and an α1-containing GABAA structure, we created a new model of the ligand binding site at the α5/γ2 interface. Using this model, the measured ligand affinities were able to be reproduced well by free energy perturbation (FEP) calculations. In addition, calculations were able to explain the obtained structure-activity relationships, among others, the switch-like effect of the aromatic nitrogen position in the dihydro-naphthyridinone motif for the functional character, and suggest different binding poses for the ligands presenting silent versus negative allosteric effects in this set (SAMs vs. NAMs, respectively). We believe that our results can help design α5 selective GABAA negative allosteric modulators and better understand the GABAA receptor.

MacGen: A Web Server for Structure-Based Macrocycle Design.

Macrocyclization is a critical strategy in rational drug design that can offer several advantages, such as enhancing binding affinity, increasing selectivity, and improving cellular permeability. Herein, we introduce MacGen, a web tool devised for structure-based macrocycle design. MacGen identifies exit vector pairs within a ligand that are suitable for cyclization and finds 3D linkers that can align with the geometric arrangement of these pairs to form macrocycles. To aid in the fast acquisition of appropriate linkers, we have built an indexed 3D linker database that includes linkers of various lengths and categories. MacGen provides comprehensive configurable parameters that enable users to obtain preferred linkers, meeting unique requirements in practical ligand design scenarios. We hope MacGen will serve as a handy tool that can rapidly explore potential macrocycle space. The MacGen server is freely accessible at https://macgen.xundrug.cn.

Polypharmacological Drug Design Guided by Integrating Phenotypic and Restricted Fragment Docking Strategies.

Polypharmacological drugs are of great value for treating complex human diseases by the combinative modulation of several biological targets. However, multitarget drug design with more than two targets is challenging and generally discovered by serendipity. Herein, a restricted fragment docking (RFD) computational method combined with a phenotypic discovery approach was developed for rational polypharmacological drug design. Via genetic and drug combination studies in a microglial phenotype, we first identified novel synergistic effects by triple target modulation toward RIPK1, MAP4K4, and ALK. Drawing on the RFD method to explore virtual chemical spaces in three target pockets, we identified a lead compound, LP-10d, that precisely modulated RIPK1/MAP4K4/ALK for synergistic microglial protection with low nanomolar potency. LP-10d showed polypharmacology against multiple neuropathologies in the 3xTg Alzheimer's disease mouse model. Our study revealed a potential application of the RFD method, which is valuable to further polypharmacological drug discovery involved in clinical studies for treating complex human diseases.