Drug Design Techniques Research Articles

Past, present and future of xanthine oxidase inhibitors: design strategies, structural and pharmacological insights, patents and clinical trials.

Xanthine oxidase, a molybdo-flavoenzyme, and an isoform of xanthine dehydrogenase both exist as xanthine oxidoreductase and are responsible for purine catabolism. Xanthine oxidase is more involved in pathological conditions when extensively modulated. Elevation of xanthine oxidase is not only the prime cause of gout but is also responsible for various hyperuricemia associated pathological conditions like diabetes, chronic wounds, cardiovascular disorders, Alzheimer's disease, etc. Currently available xanthine oxidase inhibitors in clinical practice (allopurinol, febuxostat and topiroxostat) suffer from fatal side effects that pose a serious problem to the healthcare system, raising global emergency to develop novel, potent and safer xanthine oxidase inhibitors. This review will provide key and systematic information about: a. design strategies (inspired from both marketed drugs in clinical practice and natural products), structural insights and pharmacological output (xanthine oxidase inhibition and associated activities) of various pre-clinical candidates reported by various research groups across the globe in the past two decades; b. patented xanthine oxidase inhibitors published in the last three decades and c. clinical trials and their outcomes on approved drug candidates. Information generated in this review has suggested fragment-based drug design (FBDD) and molecular hybridization techniques to be most suitable for development of desired xanthine oxidase inhibitors as one provides high selectivity toward the enzyme and the other imparts multifunctional properties to the structure and both may possess capabilities to surpass the limitations of currently available clinical drugs. All in combination will exclusively update researchers working on xanthine oxidase inhibitors and allied areas and potentially help in designing rational, novel, potent and safer xanthine oxidase inhibitors that can effectively tackle xanthine oxidase related disease conditions and disorders.

Obstructing Salmonella typhi's virulence in eukaryotic cells through design of its SipB protein antagonists

ObjectiveTyphoid fever, a disease caused by Salmonella typhi, is a leading cause of morbidity and mortality, particularly in developing nations. The evolution of resistance mechanisms to existing antibiotics has necessitated a search for newer drug candidates. This study used computer aided drug design techniques to design novel antibiotics that function by antagonizing SipB, an effector protein of the bacterium that is responsible for its pathogenicity and virulence in eukaryotic host cells. MethodsA data set of 32 bioactive molecules with established antibacterial activity against S. typhi was retrieved from the PubChem data base; optimized through a DFT approach in Spartan 14 software; and further subjected to QSAR modeling in BIOVIA-Accelrys Material Studio. The validated model (R2 = 0.80, R2Adj = 0.78, Q2LOO = 0.74, R2pred = 0.54, lack of fit = 0.07) revealed the dominant influence of MATS6c and E3p descriptors on the observed antibacterial activity of the compounds. Information from the model was used to optimize the structures of selected lead compounds in the data set, thus leading to the design of a highly potent set of novel analogues denoted D-1, D-2 and D-3. ResultsThe predicted MIC values of D-1, D-2 and D-3 were 1.03, 0.73 and 0.30 μg/mL, respectively. Furthermore, molecular docking studies on these novel ligands against the active sites of SipB revealed binding energy values of −8.0, −7.7 and −7.7 kcal/mol for D-1, D-2 and D-3, respectively. These values were better than the −7.0 kcal/mol recorded for ciprofloxacin, the reference antibiotic used herein for quality assurance. In addition, drug-likeness and ADMET evaluation of the designed compounds revealed that they are orally bioavailable and exhibit excellent pharmacokinetic and toxicological profiles. ConclusionThe current findings may provide a roadmap for the discovery of more potent antibiotics against S. typhi.

Artificial Intelligence: The Milestone in Modern Biomedical Research

In recent years, the advent of new experimental methodologies for studying the high complexity of the human genome and proteome has led to the generation of an increasing amount of digital information, hence bioinformatics, which harnesses computer science, biology, and chemistry, playing a mandatory role for the analysis of the produced datasets. The emerging technology of Artificial Intelligence (AI), including Machine Learning (ML) and Artificial Neural Networks (ANNs), is nowadays at the core of biomedical research and has already paved the way for significant breakthroughs in both biological and medical sciences. AI and computer science have transformed traditional medicine into modern biomedicine, thus promising a new era in systems biology that will enhance drug discovery strategies and facilitate clinical practice. The current review defines the main categories of AI and thoroughly describes the fundamental principles of the widely used ML, ANNs and DL approaches. Furthermore, we aim to underline the determinant role of AI-based methods in various biological research fields, such as proteomics and drug design techniques, and finally, investigate the implication of AI in everyday clinical practice and healthcare systems. Finally, this review also highlights the challenges and future directions of AI in Modern Biomedical study.

In silico investigation of acyclovir derivatives potency against herpes simplex virus

Herpes simplex virus (HSV) is a major human pathogen, sub-divided into two types: HSV-1 which causes oral and perioral infections and HSV-2 which causes genital herpes. The global disease burden is high with 67% and 11% of the World's population being infected with HSV-1 and HSV-2 respectively. Acyclovir, an FDA approved drug, is a synthetic purine nucleoside analogue used for the treatment of HSV infections. The drug acts via the viral encoded thymidine kinase and competitively inhibits viral DNA polymerase. Emerging HSV resistance to acyclovir and lack of approved vaccines necessitates need for effective strategies to circumvent the viral infection. Derivatives of acyclovir were modelled using computer aided drug design techniques through Chemsketch and drugability determined based on Lipinski's Ro5 where a Python filtering code was created and derivatives with zero non-violations were selected. Putative biological targets were determined through network pharmacology and validated through gene ontology. Molecular docking with known and putative targets was done to determine the binding affinities of the acyclovir derivatives. Based on enzyme inhibition scores, pharmacokinetics prediction was done on Molinspiration while pharmacodynamics predictions were done on AdmetSAR based on bioavailability scores. Thirty acyclovir derivatives were modelled of which 22 had zero non-violations. 2-[(3, 6-dihydro-9H-purin-9-yl)methoxy]ethan-1-ol) had the highest enzyme inhibition score at 1.0 compared to 0.84 for acyclovir. The molecule was further optimized generating (2‐[(6‐methyl‐6,9‐dihydro‐3H‐purin‐9‐yl)methoxy]ethan‐1‐ol which had a better bioavailability and a higher blood brain barrier value of 0.9880 indicating possible better patient tolerance. 2‐[(6‐methyl‐6,9‐dihydro‐3H‐purin‐9‐yl)methoxy]ethan‐1‐ol had an enzyme inhibition score of 0.90 and binding energies of -5.1 kcal/mol when docked against thymidine kinase. The intra-viral HSV PPI network was analysed and DNA replication helicase (UL5) and serine /threonine-protein kinase (US3) were selected due to functional similarity with thymidine kinase with kappa statistics value of 0.30 and 0.24 respectively. Gene enrichment analysis indicated that the biological targets UL5 and US3 had a significant P value of 0.62 based on Benjamin Correction at P<0.05. The study recommends in vitro and in vivo validation of this novel compound and molecular validation of the two new potential biological targets for possible development of new anti-herpes therapeutic compounds.

Bridging the Gap in Malaria Parasite Resistance, Current Interventions, and the Way Forward from in Silico Perspective: A Review.

The past decade has seen most antimalarial drugs lose their clinical potency stemming from parasite resistance. Despite immense efforts by researchers to mitigate this global scourge, a breakthrough is yet to be achieved, as most current malaria chemotherapies suffer the same fate. Though the etiology of parasite resistance is not well understood, the parasite's complex life has been implicated. A drug-combination therapy with artemisinin as the central drug, artemisinin-based combination therapy (ACT), is currently the preferred malaria chemotherapy in most endemic zones. The emerging concern of parasite resistance to artemisinin, however, has compromised this treatment paradigm. Membrane-bound Ca2+-transporting ATPase and endocytosis pathway protein, Kelch13, among others, are identified as drivers in plasmodium parasite resistance to artemisinin. To mitigate parasite resistance to current chemotherapy, computer-aided drug design (CADD) techniques have been employed in the discovery of novel drug targets and the development of small molecule inhibitors to provide an intriguing alternative for malaria treatment. The evolution of plasmepsins, a class of aspartyl acid proteases, has gained tremendous attention in drug discovery, especially the non-food vacuole. They are expressed at multi-stage of the parasite's life cycle and involve in hepatocytes' egress, invasion, and dissemination of the parasite within the human host, further highlighting their essentiality. In silico exploration of non-food vacuole plasmepsin, PMIX and PMX unearthed the dual enzymatic inhibitory mechanism of the WM382 and 49c, novel plasmepsin inhibitors presently spearheading the search for potent antimalarial. These inhibitors impose structural compactness on the protease, distorting the characteristic twist motion. Pharmacophore modeling and structure activity of these compounds led to the generation of hits with better affinity and inhibitory prowess towards PMIX and PMX. Despite these headways, the major obstacle in targeting PM is the structural homogeneity among its members and to human Cathepsin D. The incorporation of CADD techniques described in the study at early stages of drug discovery could help in selective inhibition to augment malaria chemotherapy.

Development of novel hydrazidoarylaminopyrimidine-based BTK/FLT3 dual inhibitors with potent in vivo anti-hematological malignancies effects

Computer-aided drug design and structure-based drug design techniques were used to find 18 novel hydrazidoarylaminopyrimidine-based BTK/FLT3 dual inhibitors. At 1 μM and 0.05 μM, the majority of the target compounds inhibited BTK and FLT3 by more than 80%, respectively. Among these, compound RSH-7 inhibited BTK and FLT3 most effectively, with IC50 values of 47 and 12 nM, respectively, which were superior to spebrutinib (BTK IC50 = 54 nM) and sorafenib (FLT3 IC50 = 33 nM). RSH-7 effectively inhibited the proliferation of multiple hematological malignancy cells with IC50 values ranging from 3 to 17 nM, which were 81–133 folds lower than spebrutinib. Furthermore, RSH-7 strongly inhibited BTK and FLT3 signaling and induced apoptosis in jeko-1 cells by upregulating pro-apoptotic proteins and downregulating Bcl-2 levels. RSH-7 showed moderate in vitro ADME properties. Importantly, RSH-7 demonstrated highly efficacious and well-tolerated in jeko-1 (50 mg/kg, TGI = 79.78%) and MV4-11 (20 mg/kg, TGI = 94.84%) xenograft models. These findings indicated that RSH-7 may be a promising lead compound for the treatment of hematological malignancies.

Acyldepsipeptide Analogues: A Future Generation Antibiotics for Tuberculosis Treatment.

Acyldepsipeptides (ADEPs) are a new class of emerging antimicrobial peptides (AMPs), which are currently explored for treatment of pathogenic infections, including tuberculosis (TB). These cyclic hydrophobic peptides have a unique bacterial target to the conventional anti-TB drugs, and present a therapeutic window to overcome Mycobacterium Tuberculosis (M. tb) drug resistance. ADEPs exerts their antibacterial activity on M. tb strains through activation of the protein homeostatic regulatory protease, the caseinolytic protease (ClpP1P2). ClpP1P2 is normally regulated and activated by the ClpP-ATPases to degrade misfolded and toxic peptides and/or short proteins. ADEPs bind and dysregulate all the homeostatic capabilities of ClpP1P2 while inducing non-selective proteolysis. The uncontrolled proteolysis leads to M. tb cell death within the host. ADEPs analogues that have been tested possess cytotoxicity and poor pharmacokinetic and pharmacodynamic properties. However, these can be improved by drug design techniques. Moreover, the use of nanomaterial in conjunction with ADEPs would yield effective synergistic effect. This new mode of action has potential to combat and eradicate the extensive multi-drug resistance (MDR) problem that is currently faced by the public health pertaining bacterial infections, especially TB.

Review on Computer-Aided Drug Design (CADD) Technique in Drug Discovery Researches and Solvent-Free Synthesis of 3,4-Dihydropyrimidin-2-(1H)-Ones/Thiones Catalyzed by Camphor Sulfonic Acid

Combined with various computational and theoretical approaches, computer-aided drug design (CADD) is one of the contemporary approaches to drug discovery. Furthermore, this study briefly assesses the literature on computer-assisted drug design (CADD) techniques used in drug discovery research. An environmentally friendly synthetic route was developed for the convenient Biginelli synthesis of 3,4-dihydropyridine-2-(1H)-ones/thiones when no solvents are involved in the reaction using aromatic derivatives, urea/thiourea, and ethyl/methyl acetoacetate as catalysts in combination with camphor sulfonic acid (CSA). All reactions proceeded rapidly, and good product yields were obtained. Green synthesis in this study has many advantages over conventional synthesis, including a clean and environmentally friendly synthesis, easy operation, the elimination of hazardous organic solvents, a purification step free of chromatography, and the use of a non-corrosive and non-volatile catalyst. Furthermore, the method can be applied to single-tank reactions in a solvent-free environment.

Evolving Experimental Techniques for Structure-Based Drug Design.

Structure-based drug design (SBDD) is a prominent method in rational drug development and has traditionally benefitted from the atomic models of protein targets obtained using X-ray crystallography at cryogenic temperatures. In this perspective, we highlight recent advances in the development of structural techniques that are capable of probing dynamic information about protein targets. First, we discuss advances in the field of X-ray crystallography including serial room-temperature crystallography as a method for obtaining high-resolution conformational dynamics of protein-inhibitor complexes. Next, we look at cryogenic electron microscopy (cryoEM), another high-resolution technique that has recently been used to study proteins and protein complexes that are too difficult to crystallize. Finally, we present small-angle X-ray scattering (SAXS) as a potential high-throughput screening tool to identify inhibitors that target protein complexes and protein oligomerization.

Plant-derived compounds effectively inhibit the main protease of SARS-CoV-2: An in silico approach.

The current coronavirus disease 2019 (COVID-19) pandemic, caused by the coronavirus 2 (SARS-CoV-2), involves severe acute respiratory syndrome and poses unprecedented challenges to global health. Structure-based drug design techniques have been developed targeting the main protease of the SARS-CoV-2, responsible for viral replication and transcription, to rapidly identify effective inhibitors and therapeutic targets. Herein, we constructed a phytochemical dataset of 1154 compounds using deep literature mining and explored their potential to bind with and inhibit the main protease of SARS-CoV-2. The three most effective phytochemicals Cosmosiine, Pelargonidin-3-O-glucoside, and Cleomiscosin A had binding energies of -8.4, -8.4, and -8.2 kcal/mol, respectively, in the docking analysis. These molecules could bind to Gln189, Glu166, Cys145, His41, and Met165 residues on the active site of the targeted protein, leading to specific inhibition. The pharmacological characteristics and toxicity of these compounds, examined using absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses, revealed no carcinogenicity or toxicity. Furthermore, the complexes were simulated with molecular dynamics for 100 ns to calculate the root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen profiles from the simulation trajectories. Our analysis validated the rigidity of the docked protein-ligand. Taken together, our computational study findings might help develop potential drugs to combat the main protease of the SARS-CoV-2 and help alleviate the severity of the pandemic.

Identification of potential inhibitors for N-myristoyltransferase (NMT) protein of Plasmodium vivax

Malaria is a neglected parasitic infection of global importance. It is mainly present in tropical countries and caused by a protozoa that belongs to the genus Plasmodium. The disease vectors are female Anopheles mosquitoes infected with the Plasmodium spp. According to the World Health Organization (WHO), there were 241 million malaria cases worldwide in 2020 and approximately 627 thousand malaria deaths in the same year. The increasing resistance to treatment has been a major problem since the beginning of the 21st century. New studies have been conducted to find possible drugs that can be used for the eradication of the disease. In this scenario, a protein named N-myristoyltransferase (NMT) has been studied as a potential drug target. NMT has an important role on the myristoylation of proteins and binds to the plasma membrane, contributing to the stabilization of protein-protein interactions. Thus, inhibition of NMT can lead to death of the parasite cell. Therefore, in order to predict and detect potential inhibitors against Plasmodium NMT, Computer-Aided Drug Design techniques were used in this research that involve virtual screening, molecular docking, and molecular dynamics. Three potential compounds similar to a benzofuran inhibitor were identified as stable PvNMT ligands. These compounds (EXP90, ZBC205 and ZDD968) originate from three different sources, respectively: a commercial library, a natural product library, and the FDA approved drugs dataset. These compounds may be further tested in in vitro and in vivo inhibition tests against Plasmodium vivax NMT. Communicated by Ramaswamy H. Sarma

Ameliorative Role of In-Silico Study in Phytoconstituents of Cordyceps Used for PCOS

Background: Polycystic ovarian syndrome (PCOS) is a heterogeneous endocrine disease that impacts about one in 15 girls worldwide. It is a major sickness characterized through multiplied ranges of male hormones (androgens), acne and hirsutism. Objective: In silico study of different compounds from Cordyceps into active site of the target protein. (3RUK). Methods: Computer-aided drug plan principles should enhance the discovery of putative Cordyceps-derived medication inside much less time and low budget. The integration of computer-aided drug design techniques with experimental validation has contributed to the profitable discovery of novel drugs. Results: Results indicated that all the ligands have a strong binding affinity for the Human Cytochrome P450 CYP17A1 receptor as indicated by their docking score values that were found to be comparable with the docking score of the molecules1,6-di-o-glloyl-d-glucose (- 12.172) Isoquercitrin acid (-11.366) etc. Conclusion: It has been concluded that computer-aided drug design techniques could influence the multiple target-focused drug design, In silico studies were performed on the different compounds from Cordyceps into active site of the target protein. (3RUK). Compound 1,6-dio-glloyl-d-glucose was found to have highest affinity towards the Human Cytochrome P450 CYP17A1receptor(docking score = -12.172). Other different compounds from Cordyceps have also good dock scores. Keywords: PCOS, In-silico, Cytochrome P450 CYP17A1, Protein, Ligand.

Evaluating the accuracy of the AMBER protein force fields in modeling dihydrofolate reductase structures: misbalance in the conformational arrangements of the flexible loop domains

Protein flexible loop regions were once thought to be simple linkers between other more functional secondary structural elements. However, as it becomes clearer that these loop domains are critical players in a plethora of biological processes, accurate conformational sampling of 3D loop structures is vital to the advancement of drug design techniques and the overall growth of knowledge surrounding molecular systems. While experimental techniques provide a wealth of structural information, the resolution of flexible loop domains is sometimes low or entirely absent due to their complex and dynamic nature. This highlights an opportunity for de novo structure prediction using in silico methods with molecular dynamics (MDs). This study evaluates some of the AMBER protein force field’s (ffs) ability to accurately model dihydrofolate reductase (DHFR) conformations, a protein complex characterized by specific arrangements and interactions of multiple flexible loops whose conformations are determined by the presence or absence of bound ligands and cofactors. Although the AMBER ffs, including ff19SB, studied well model most protein structures with rich secondary structure, results obtained here suggest the inability to significantly sample the expected DHFR loop–loop conformations – of the six distinct protein-ligand systems simulated, a majority lacked consistent stabilization of experimentally derived metrics definitive the three enzyme conformations. Although under-sampling and the chosen ff parameter combinations could be the cause, given past successes with these MD approaches for many protein systems, this suggests a potential misbalance in available ff parameters required to accurately predict the structure of multiple flexible loop regions present in proteins. Communicated by Ramaswamy H. Sarma

Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process.

The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure–activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible.

A Review on Recent Rational Approaches to Drug Design, Development and Its Discovery

The steps involved in drug design, drug development and drug discovery are highly expensive, extremely challenging and time consuming. Although the drug designing, process has been hastened with the development of newer emerging techniques, and the fabrication of novel computational tool. Researchers are working on structure guided drug designing using a 3-D structure of target, the drug molecule identified by the use of target-based drug design shows great potential in preventing various diseases but also possess many side effects. In the rational drug design, structure-based designing, combinatorial drug designing and computer aided drug design techniques are employed. When gene expression and bioinformatics are incorporated with the combinatorial drug designing, that make the rational drug designing, a more powerful tool for drug discovery. The rational drug designing associated with gene expression and bioinformatical estimation is moderately emerging and expeditiously revamping the drug development with less time consuming, economic, effectiveness and cater novel combinatory therapy in addition to minimization of toxicity. This review discusses in detail about the fabrication of a successful drug candidate using multidisciplinary perspective of combinatorial chemistry with gene expression analysis, structure based and artificial intelligence- based drug designing. In future, more sophisticated computer-based methodologies would be required for developing new drug candidate.

Discovering novel inhibitors of P2Y12 receptor using structure-based virtual screening, molecular dynamics simulation and MMPBSA approaches

P2Y12, a G-protein coupled receptor is involved in platelets plug formation and it amplifies and maintains the process of platelet aggregation. P2Y12 is considered as a potent target to inhibit platelet aggregation in thrombotic and cardiac emergencies. This research focuses on in silico inhibition of P2Y12 by structure-based drug design techniques. Initially, drug-like compounds were selected from ZINC database by structure-based pharmacophore model. Subsequently, 4479 compounds matched with the pharmacophore model that were scrutinized by molecular docking. Later, based on docking score and rank, top 10% of the docked library was selected to predict their pharmacokinetic properties and 191 compounds possessed good pharmacokinetic profile. The binding pattern of those compounds were analyzed to select novel, less toxic and more potent P2Y12 antagonists. In protein-ligand interaction analysis, seven compounds showed significant binding potential, therefore examined through molecular dynamic simulation. Among the selected hits, two compounds (CP31 and CP32) exhibited higher binding energies in SANDER Poisson-Boltzmann Surface Area (PBSA) approach than agonist bound P2Y12 (4PXZ) and antithrombotic drug bound P2Y12 (4NTJ), while one compound (CP25) showed comparable binding energy than 4NTJ. The binding free energy analysis reflect that interactions of all selected Hits with P2Y12 are promising and specifically CP25, CP31, and CP32 could serve as novel inhibitors of P2Y12.

Structure-Based Drug Design of Novel Piperazine Containing Hydrazone Derivatives as Potent Alzheimer Inhibitors: Molecular Docking and Drug Kinetics Evaluation

Alzheimer's disease (AD) is a neurodegenerative disorder that causes dementia and cognitive impairment in the elderly. The exact mechanism of the disease is still unknown. There are four medications available, all of which have a slew of negative side effects and only serve to improve patients' warning symptoms. Medicinal chemists are looking for treatments for this illness. The development and application of a novel class of multifunctional small molecule inhibitors is discussed. A variety of compounds were synthesized using the hydrazone scaffold. This is due to the ability of hydrazone derivatives to interfere with Amyloid beta (A) self-assembly, which is one of the causative agents in fibrils and oligomers. they can also counteract the impacts of toxic substances free radicals on useful therapeutic agents such as central nervous system penetrant drugs. In this study, structure-based drug design techniques utilized. Based on established literature studies and reasons such as lower resolution value (2.35), no mutation, Homo Sapiens, and X-ray diffraction method, a protein target (code ID 4EY7) was chosen. The protein target was designed to interact with compounds of interest (a lead compound with a higher binding energy), and was used as a template to design fifteen Hydrazone derivatives with greater interactions, higher binding scores, and improved enhanced drug-like properties and drug kinetic parameters The findings of these studies can be used to create promising pharmacotherapeutic compounds for the treatment of AD.

Focused Design of Novel Cyclic Peptides Endowed with GABARAP-Inhibiting Activity.

(1) Background: Disfunctions in autophagy machinery have been identified in various conditions, including neurodegenerative diseases, cancer, and inflammation. Among mammalian autophagy proteins, the Atg8 family member GABARAP has been shown to be greatly involved in the autophagy process of prostate cancer cells, supporting the idea that GABARAP inhibitors could be valuable tools to fight the progression of tumors. (2) Methods: In this paper, starting from the X-ray crystal structure of GABARAP in a complex with an AnkirinB-LIR domain, we identify two new peptides by applying in silico drug design techniques. The two ligands are synthesized, biophysically assayed, and biologically evaluated to ascertain their potential anticancer profile. (3) Results: Two cyclic peptides (WC8 and WC10) displayed promising biological activity, high conformational stability (due to the presence of disulfide bridges), and Kd values in the low micromolar range. The anticancer assays, performed on PC-3 cells, proved that both peptides exhibit antiproliferative effects comparable to those of peptide K1, a known GABARAP inhibitor. (4) Conclusions: WC8 and WC10 can be considered new GABARAP inhibitors to be employed as pharmacological tools or even templates for the rational design of new small molecules.

Molecular docking-based interactions in QSAR studies on Mycobacterium tuberculosis ATP synthase inhibitors

ABSTRACT Tuberculosis (TB) is a global threat with a large burden across the continents in terms of mortality, morbidity, and financial losses. The disease has evolved into multi-drug-resistant (MDR-TB) and extensively drug-resistant (XDR-TB) tuberculosis owing to numerous factors ranging from patients’ non-compliance to demographical implications. There have been very few new drugs for resistant TB. Resistance has already been reported even for the newly introduced drug bedaquiline. An attempt has been made to integrate both structure-based and QSAR drug design techniques (QSAR-SBDD) for the identification of novel leads. The docking scores normally do not correlate with the activity. Hence, the docking results have been analysed in terms of the number of interactions rather than docking scores. The parameters derived from interactions have been used in developing the QSAR models. The best model shows a good correlation (r = 0.908) between the activity and interaction parameter ‘C’ describing the sum of all the interactions with each amino acid residue. This model also predicts external dataset with a good correlation (r ext = 0.851) and can be used for the identification of novel chemical entities (NCEs) and repurposed drugs for TB therapeutics.

Identification of Some Promising Heterocycles Useful in Treatment of Allergic Rhinitis: Virtual Screening, Pharmacophore Mapping, Molecular Docking, and Molecular Dynamics

Rhinitis is an allergic disease that causes troubles and restlessness for patients. In this research work we will focus on finding promising organic molecules with potential ability to target histamine receptor with no sedative side effect. Phalazines and their isosteres, pyrimidines and pyridines have been reported to target H1 receptors, for this reason we have searched for library of these basic scaffolds, this library which has 184 organic molecules will be subjected for further explorations through computer aided drug design techniques. Swiss ADMET will be used to gather these compounds in clusters. Cluster with low potential to penetrate BBB is selected for virtual screening through pharmacophore model. Then molecular docking that revealed the stability of the complex formed between the investigated molecules and H1 receptor. ADMET profile showed three compounds (XVIII), (XX), and (XXI) with no toxicity on liver and no effect on CYP2D6, these three compounds were subjected to molecular dynamic simulations and compound (XVIII) showed the most stable complex with the target protein (H1). Finally, we can say this work helped us to find new compounds with promising potential to target H1 without ability to penetrate BBB, so they can be used as useful candidates in treatment of rhinitis and deserve to be subjected for preclinical and clinical investigations.Supplementary InformationThe online version contains supplementary material available at 10.1134/S1068162022330019.