Synthesis of Novel Hydrazide-Hydrazone Compounds and In Vitro and In Silico Investigation of Their Biological Activities against AChE, BChE, and hCA I and II.

The abnormal levels of the human carbonic anhydrase isoenzymes I and II (hCA I and II) and cholinesterase enzymes, namely, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), are linked with various disorders including Alzheimer's disease. In this study, six new nicotinic hydrazide derivatives (7-12) were designed and synthesized for the first time, and their inhibitory profiles against hCA I, hCA II, AChE, and BChE were investigated by in vitro assays and in silico studies. The structures of novel molecules were elucidated by using spectroscopic techniques and elemental analysis. These molecules showed inhibitory activities against hCA I and II with IC50 values ranging from 7.12 to 45.12 nM. Compared to reference drug acetazolamide (AZA), compound 8 was the most active inhibitor against hCA I and II. On the other hand, it was determined that IC50 values of the tested molecules ranged between 21.45 and 61.37 nM for AChE and between 18.42 and 54.74 nM for BChE. Among them, compound 12 was the most potent inhibitor of AChE and BChE, with IC50 values of 21.45 and 18.42 nM, respectively. In order to better understand the mode of action of these new compounds, state-of-the-art molecular modeling techniques were also conducted.

Discovering allatostatin type-C receptor specific agonists.

Currently, there is no pesticide available for the selective control of the pine processionary moth (Thaumetopoea pityocampa-specific), and conventional methods typically rely on mechanical techniques such as pheromone traps or broad-spectrum larvicidal chemicals. As climate change increases the range and dispersion capacity of crop and forest pests, outbreaks of the pine processionary occur with greater frequency and significantly impact forestry and public health. Our study is carried out to provide a T. pityocampa-specific pesticide targeting the Allatostatin Type-C Receptor (AlstR-C). We use a combination of computational biology methods, a cell-based screening assay, and in vivo toxicity and side effect assays to identify, for the first time, a series of AlstR-C ligands suitable for use as T. pityocampa-specific insecticides. We further demonstrate that the novel AlstR-C targeted agonists are specific to lepidopteran larvae, with no harmful effects on coleopteran larvae or adults. Overall, our study represents an important initial advance toward an insect GPCR-targeted next-generation pesticide design. Our approach may apply to other invertebrate GPCRs involved in vital metabolic pathways.

Enterocin DD14 can inhibit the infection of eukaryotic cells with enveloped viruses.

Bacteriocins are ribosomally synthesized bacterial peptides endowed with antibacterial, antiprotozoal, anticancer and antiviral activities. In the present study, we evaluated the antiviral activities of two bacteriocins, enterocin DD14 (EntDD14) and lacticaseicin 30, against herpes simplex virus type 1 (HSV-1), human coronavirus 229E (HCoV-229E) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Vero, Huh7 and Vero E6 cells, respectively. In addition, the interactions of these bacteriocins with the envelope glycoprotein D of HSV-1 and the receptor binding domains of HCoV-229E and SARS-CoV-2 have been computationally evaluated using protein-protein docking and molecular dynamics simulations. HSV-1 replication in Vero cells was inhibited by EntDD14 and, to a lesser extent, by lacticaseicin 30 added to cells after virus inoculation. EntDD14 and lacticaseicin 30 had no apparent antiviral activity against HCoV-229E; however, EntDD14 was able to inhibit SARS-CoV-2 in Vero E6 cells. Further studies are needed to elucidate the antiviral mechanism of these bacteriocins.

Covalent docking-driven virtual screening of extensive small-molecule libraries against Bruton tyrosine kinase for the identification of highly selective and potent novel therapeutic candidates.

Bruton tyrosine kinases (BTKs) play critical roles in various diseases, including chronic lymphatic leukemia (CLL), Waldenström Macroglobulinemia, Marginal Zone Lymphoma, Mantle Cell Lymphoma (MCL), and Graft Versus Host diseases. BTKs are a family of tyrosine kinases involved in B lymphocyte signal transduction, development, and maturation. Their overexpression can lead to cancer as they are essential for the activation of the B Cell Receptor (BCR) signaling pathway. Blocking the activation of BTKs presents a promising approach for treating CLL. This study was centered around the identification of small-molecule therapeutics that have an impact on human BTK. The covalently bound Ibrutinib molecule, recognized for its ability to inhibit BTK, was used as the query molecule. IUPAC text files containing molecular fragments of Ibrutinib were employed to virtually screen five different libraries comprising small-molecules, resulting in the screening of over 2.4 million synthesized compounds. Covalent docking simulations were applied to the selected small-molecules obtained through text mining from databases. Potent hit molecules capable of inhibiting BTKs through virtual screening algorithms were identified, paving the way for novel therapeutic strategies in the treatment of CLL.

Identifying Potential SOS1 Inhibitors via Virtual Screening of Multiple Small Molecule Libraries against KRAS-SOS1 Interface.

The RAS-MAPK signaling pathway, crucial for cell proliferation and differentiation, involves key proteins KRAS and SOS1. Mutations in the KRAS and SOS1 genes are implicated in various cancer types, including pancreatic, lung, and juvenile myelomonocytic leukemia. There is considerable interest in identifying inhibitors targeting KRAS and SOS1 to explore potential therapeutic strategies for cancer treatment. In this study, advanced in silico techniques were employed to screen small molecule libraries at this interface, leading to the identification of promising lead compounds as potential SOS1 inhibitors. Comparative analysis of the average binding free energies of these predicted potent compounds with known SOS1 small molecule inhibitors revealed that the identified compounds display similar or even superior predicted binding affinities compared to the known inhibitors. These findings offer valuable insights into the potential of these compounds as candidates for further development as effective anti-cancer agents.

Efficient, rapid, and high-yield synthesis of aryl Schiff base derivatives and their in vitro and in silico inhibition studies of hCA I, hCA II, AChE, and BuChE.

This study reports a rapid and efficient synthesis of four novel aryl Schiff base derivatives. Biological activity and molecular modeling studies were conducted to evaluate the inhibitory effects of these compounds on human carbonic anhydrases (hCA) and cholinesterases. The results indicate that the triazole-ring-containing compounds have strong inhibitory effects on hCA I, hCA II, acetylcholinesterase (AChE), and butyrylcholinesterase (BuChE) targets. Besides comparing the Schiff bases synthesized in our study to reference molecules, we conducted in silico investigations to examine how these compounds interact with their targets. Our studies revealed that these compounds can occupy binding sites and establish interactions with crucial residues, thus inhibiting the functions of the targets. These findings have significant implications as they can be utilized to develop more potent compounds for treating the diseases that these target proteins play crucial roles in or to obtain drug precursors with enhanced efficacy.

Dual activity of Minnelide chemosensitize basal/triple negative breast cancer stem cells and reprograms immunosuppressive tumor microenvironment.

Triple negative breast cancer (TNBC) subtype is characterized with higher EMT/stemness properties and immune suppressive tumor microenvironment (TME). Women with advanced TNBC exhibit aggressive disease and have limited treatment options. Although immune suppressive TME is implicated in driving aggressive properties of basal/TNBC subtype and therapy resistance, effectively targeting it remains a challenge. Minnelide, a prodrug of triptolide currently being tested in clinical trials, has shown anti-tumorigenic activity in multiple malignancies via targeting super enhancers, Myc and anti-apoptotic pathways such as HSP70. Distinct super-enhancer landscape drives cancer stem cells (CSC) in TNBC subtype while inducing immune suppressive TME. We show that Minnelide selectively targets CSCs in human and murine TNBC cell lines compared to cell lines of luminal subtype by targeting Myc and HSP70. Minnelide in combination with cyclophosphamide significantly reduces the tumor growth and eliminates metastasis by reprogramming the tumor microenvironment and enhancing cytotoxic T cell infiltration in 4T1 tumor-bearing mice. Resection of residual tumors following the combination treatment leads to complete eradication of disseminated tumor cells as all mice are free of local and distant recurrences. All control mice showed recurrences within 3 weeks of post-resection while single Minnelide treatment delayed recurrence and one mouse was free of tumor. We provide evidence that Minnelide targets tumor intrinsic pathways and reprograms the immune suppressive microenvironment. Our studies also suggest that Minnelide in combination with cyclophosphamide may lead to durable responses in patients with basal/TNBC subtype warranting its clinical investigation.

Developing Dynamic Structure-Based Pharmacophore and ML-Trained QSAR Models for the Discovery of Novel Resistance-Free RET Tyrosine Kinase Inhibitors Through Extensive MD Trajectories and NRI Analysis.

Activation of RET tyrosine kinase plays a critical role in the pathogenesis of various cancers, including non-small cell lung cancer, papillary thyroid cancers, multiple endocrine neoplasia type 2A and 2B (MEN2A, MEN2B), and familial medullary thyroid cancer. Gene fusions and point mutations in the RET proto-oncogene result in constitutive activation of RET signaling pathways. Consequently, developing effective inhibitors to target RET is of utmost importance. Small molecules have shown promise as inhibitors by binding to the kinase domain of RET and blocking its enzymatic activity. However, the emergence of resistance due to single amino acid changes poses a significant challenge. In this study, a structure-based dynamic pharmacophore-driven approach using E-pharmacophore modeling from molecular dynamics trajectories is proposed to select low-energy favorable hypotheses, and ML-trained QSAR models to predict pIC50 values of compounds. For this aim, extensive small molecule libraries were screened using developed ligand-based models, and potent compounds that are capable of inhibiting RET activation were proposed.

Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-Based Classifiers.

The human ether-à-go-go-related gene (hERG) channel plays a crucial role in membrane repolarization. Any disruptions in its function can lead to severe cardiovascular disorders such as long QT syndrome (LQTS), which increases the risk of serious cardiovascular problems such as tachyarrhythmia and sudden cardiac death. Drug-induced LQTS is a significant concern and has resulted in drug withdrawals from the market in the past. The main objective of this study is to pinpoint crucial heteroatoms present in ligands that initiate interactions leading to the effective blocking of the hERG channel. To achieve this aim, ligand-based quantitative structure-activity relationships (QSAR) models were constructed using extensive ligand libraries, considering the heteroatom types and numbers, and their associated hERG channel blockage pIC50 values. Machine learning-assisted QSAR models were developed to analyze the key structural components influencing compound activity. Among the various methods, the KPLS method proved to be the most efficient, allowing the construction of models based on eight distinct fingerprints. The study delved into investigating the influence of heteroatoms on the activity of hERG blockers, revealing their significant role. Furthermore, by quantifying the effect of heteroatom types and numbers on ligand activity at the hERG channel, six compound pairs were selected for molecular docking. Subsequent molecular dynamics simulations and per residue MM/GBSA calculations were performed to comprehensively analyze the interactions of the selected pair compounds.

Cryogenic X-ray crystallographic studies of biomacromolecules at Turkish Light Source "Turkish DeLight".

X-ray crystallography is a robust and powerful structural biology technique that provides high-resolution atomic structures of biomacromolecules. Scientists use this technique to unravel mechanistic and structural details of biological macromolecules (e.g., proteins, nucleic acids, protein complexes, protein-nucleic acid complexes, or large biological compartments). Since its inception, single-crystal cryocrystallography has never been performed in Türkiye due to the lack of a single-crystal X-ray diffractometer. The X-ray diffraction facility recently established at the University of Health Sciences, Istanbul, Türkiye will enable Turkish and international researchers to easily perform high-resolution structural analysis of biomacromolecules from single crystals. Here, we describe the technical and practical outlook of a state-of-the-art home-source X-ray, using lysozyme as a model protein. The methods and practice described in this article can be applied to any biological sample for structural studies. Therefore, this article will be a valuable practical guide from sample preparation to data analysis.

Inhibition of altered Orai1 channels in Müller cells protects photoreceptors in retinal degeneration.

The expressions of ion channels by Müller glial cells (MGCs) may change in response to various retinal pathophysiological conditions. There remains a gap in our understanding of MGCs' responses to photoreceptor degeneration towards finding therapies. The study explores how an inhibition of store-operated Ca2+ entry (SOCE) and its major component, Orai1 channel, in MGCs protects photoreceptors from degeneration. The study revealed increased Orai1 expression in the MGCs of retinal degeneration 10 (rd10) mice. Enhanced expression of oxidative stress markers was confirmed as a crucial pathological mechanism in rd10 retina. Inducing oxidative stress in rat MGCs resulted in increasing SOCE and Ca2+ release-activated Ca2+ (CRAC) currents. SOCE inhibition by 2-Aminoethoxydiphenyl borate (2-APB) protected photoreceptors in degenerated retinas. Finally, molecular simulations proved the structural and dynamical features of 2-APB to the target structure Orai1. Our results provide new insights into the physiology of MGCs regarding retinal degeneration and shed a light on SOCE and Orai1 as new therapeutic targets.

Ab initio and comparative 3D modeling of FAM222A-encoded protein and target-driven-based virtual screening for the identification of novel therapeutics against Alzheimer's disease.

The complex nature of Alzheimer's disease (AD) makes it difficult to understand the exact molecular processes leading to neuron death. However, two molecular factors - the production of amyloid-beta plaques and tau tangles - are considered to be linked to AD. A genetic marker for brain atrophy, FAM222A, has been identified by the unique cross-phenotype meta-analysis of genetics imaging and the molecular features show an interaction between the protein aggregatin encoded by FAM222A and amyloid beta (Aß)-peptide (1-42) via its N-terminal Aß binding domain, thus increasing Aß aggregation. Function of Aggregatin protein is unclear, and its 3D structure has not been investigated in experimental analysis, so far. Hence, in the present study, first time in literature, 3D models of FAM222A-encoded Aggregatin were systematically constructed by applying diverse homology modeling approaches and they were used as target structures at the virtual screening of FDA-approved drugs and drugs currently under research in clinical trials. Then, the identified hit molecules were chosen for further molecular dynamics (MD) simulations and post-MD analyses. Our integrated ligand-based and protein-driven-based virtual screening results show that Cefpiramide, Diniprofylline, Fostriecin, and Droperidol may target Aggregatin.

Rapid and efficient ambient temperature X-ray crystal structure determination at Turkish Light Source.

High-resolution biomacromolecular structure determination is essential to better understand protein function and dynamics. Serial crystallography is an emerging structural biology technique which has fundamental limitations due to either sample volume requirements or immediate access to the competitive X-ray beamtime. Obtaining a high volume of well-diffracting, sufficient-size crystals while mitigating radiation damage remains a critical bottleneck of serial crystallography. As an alternative, we introduce the plate-reader module adapted for using a 72-well Terasaki plate for biomacromolecule structure determination at a convenience of a home X-ray source. We also present the first ambient temperature lysozyme structure determined at the Turkish light source (Turkish DeLight). The complete dataset was collected in 18.5 min with resolution extending to 2.39 Å and 100% completeness. Combined with our previous cryogenic structure (PDB ID: 7Y6A), the ambient temperature structure provides invaluable information about the structural dynamics of the lysozyme. Turkish DeLight provides robust and rapid ambient temperature biomacromolecular structure determination with limited radiation damage.

Prediction of HIV-1 protease resistance using genotypic, phenotypic, and molecular information with artificial neural networks.

Drug resistance is a primary barrier to effective treatments of HIV/AIDS. Calculating quantitative relations between genotype and phenotype observations for each inhibitor with cell-based assays requires time and money-consuming experiments. Machine learning models are good options for tackling these problems by generalizing the available data with suitable linear or nonlinear mappings. The main aim of this study is to construct drug isolate fold (DIF) change-based artificial neural network (ANN) models for estimating the resistance potential of molecules inhibiting the HIV-1 protease (PR) enzyme. Throughout the study, seven of eight protease inhibitors (PIs) have been included in the training set and the remaining ones in the test set. We have obtained 11,803 genotype-phenotype data points for eight PIs from Stanford HIV drug resistance database. Using the leave-one-out (LVO) procedure, eight ANN models have been produced to measure the learning capacity of models from the descriptors of the inhibitors. Mean R2 value of eight ANN models for unseen inhibitors is 0.716, and the 95% confidence interval (CI) is [0.592-0.840]. Predicting the fold change resistance for hundreds of isolates allowed a robust comparison of drug pairs. These eight models have predicted the drug resistance tendencies of each inhibitor pair with the mean 2D correlation coefficient of 0.933 and 95% CI [0.930-0.938]. A classification problem has been created to predict the ordered relationship of the PIs, and the mean accuracy, sensitivity, specificity, and Matthews correlation coefficient (MCC) values are calculated as 0.954, 0.791, 0.791, and 0.688, respectively. Furthermore, we have created an external test dataset consisting of 51 unique known HIV-1 PR inhibitors and 87 genotype-phenotype relations. Our developed ANN model has accuracy and area under the curve (AUC) values of 0.749 and 0.818 to predict the ordered relationships of molecules on the same strain for the external dataset. The currently derived ANN models can accurately predict the drug resistance tendencies of PI pairs. This observation could help test new inhibitors with various isolates.

Exploring the binding capacity of lactic acid bacteria derived bacteriocins against RBD of SARS-CoV-2 Omicron variant by molecular simulations.

The changes in the SARS-CoV-2 genome have resulted in the emergence of new variants. Some of the variants have been classified as variants of concern (VOC). These strains have higher transmission rate and improved fitness. One of the prevalent were the Omicron variant. Unlike previous VOCs, the Omicron possesses fifteen mutations on the spike protein's receptor binding domain (RBD). The modifications of spike protein's key amino acid residues facilitate the virus' binding capability against ACE2, resulting in an increase in the infectiousness of Omicron variant. Consequently, investigating the prevention and treatment of the Omicron variant is crucial. In the present study, we aim to explore the binding capacity of twenty-two bacteriocins derived from Lactic Acid Bacteria (LAB) against the Omicron variant by using protein-peptidedocking and molecular dynamics (MD) simulations. The Omicron variant RBD was prepared by introducing fifteen mutations using PyMol. The protein-peptide complexes were obtained using HADDOCK v2.4 docking webserver. Top scoring complexes obtained from HADDOCK webserver were retrieved and submitted to the PRODIGY server for the prediction of binding energies. RBD-bacteriocin complexes were subjected to MD simulations. We discovered promising peptide-based therapeutic candidates for the inhibition of Omicron variant for example Salivaricin B, Pediocin PA 1, Plantaricin W, Lactococcin mmfii and Enterocin A. The lead bacteriocins, except Enterocin A, are biosynthesized by food-grade lactic acid bacteria. Our study puts forth a preliminary information regarding potential utilization of food-grade LAB-derived bacteriocins, particularly Salivaricin B and Pediocin PA 1, for Covid-19 treatment and prophylaxis.Communicated by Ramaswamy H. Sarma.

In Silico Analysis of Bacteriocins from Lactic Acid Bacteria Against SARS-CoV-2.

The COVID-19 pandemic caused by a novel coronavirus (SARS-CoV-2) is a serious health concern in the twenty-first century for scientists, health workers, and all humans. The absence of specific biotherapeutics requires new strategies to prevent the spread and prophylaxis of the novel virus and its variants. The SARS-CoV-2 virus shows pathogenesis by entering the host cells via spike protein and Angiotensin-Converting Enzyme 2 receptor protein. Thus, the present study aims to compute the binding energies between a wide range of bacteriocins with receptor-binding domain (RBD) on spike proteins of wild type (WT) and beta variant (lineage B.1.351). Molecular docking analyses were performed to evaluate binding energies. Upon achieving the best bio-peptides with the highest docking scores, further molecular dynamics (MD) simulations were performed to validate the structure and interaction stability. Protein-protein docking of the chosen 22 biopeptides with WT-RBD showed docking scores lower than -7.9 kcal/mol. Pediocin PA-1 and salivaricin P showed the lowest (best) docking scores of - 12 kcal/mol. Pediocin PA-1, salivaricin B, and salivaricin P showed a remarkable increase in the double mutant's predicted binding affinity with -13.8 kcal/mol, -13.0 kcal/mol, and -12.5 kcal/mol, respectively. Also, a better predicted binding affinity of pediocin PA-1 and salivaricin B against triple mutant was observed compared to the WT. Thus, pediocin PA-1 binds stronger to mutants of the RBD, particularly to double and triple mutants. Salivaricin B showed a better predicted binding affinity towards triple mutant compared to WT, showing that it might be another bacteriocin with potential activity against the SARS-CoV-2 beta variant. Overall, pediocin PA-1, salivaricin P, and salivaricin B are the most promising candidates for inhibiting SARS-CoV-2 (including lineage B.1.351) entrance into the human cells. These bacteriocins derived from lactic acid bacteria hold promising potential for paving an alternative way for treatment and prophylaxis of WT and beta variants.

A novel BH3 mimetic Bcl-2 inhibitor promotes autophagic cell death and reduces in vivo Glioblastoma tumor growth.

Anti-apoptotic members of the Bcl-2 family proteins play central roles in the regulation of cell death in glioblastoma (GBM), the most malignant type of brain tumor. Despite the advances in GBM treatment, there is still an urgent need for new therapeutic approaches. Here, we report a novel 4-thiazolidinone derivative BH3 mimetic, BAU-243 that binds to Bcl-2 with a high affinity. BAU-243 effectively reduced overall GBM cell proliferation including a subpopulation of cancer-initiating cells in contrast to the selective Bcl-2 inhibitor ABT-199. While ABT-199 successfully induces apoptosis in high BCL2-expressing neuroblastoma SHSY-5Y cells, BAU-243 triggered autophagic cell death rather than apoptosis in GBM A172 cells, indicated by the upregulation of BECN1, ATG5, and MAP1LC3B expression. Lc3b-II, a potent autophagy marker, was significantly upregulated following BAU-243 treatment. Moreover, BAU-243 significantly reduced tumor growth in vivo in orthotopic brain tumor models when compared to the vehicle group, and ABT-199 treated animals. To elucidate the molecular mechanisms of action of BAU-243, we performed computational modeling simulations that were consistent with in vitro results. Our results indicate that BAU-243 activates autophagic cell death by disrupting the Beclin 1:Bcl-2 complex and may serve as a potential small molecule for treating GBM.

Novel etodolac derivatives as eukaryotic elongation factor 2 kinase (eEF2K) inhibitors for targeted cancer therapy.

Eukaryotic elongation factor 2 kinase (eEF2K) has been shown to be an important molecular driver of tumorigenesis and validated as a potential novel molecular target in various solid cancers including triple negative breast cancer (TNBC). Therefore, there has been significant interest in identifying novel inhibitors of eEF2K for the development of targeted therapeutics and clinical translation. Herein, we investigated the effects of indole ring containing derivatives of etodolac, a nonsteroidal anti-inflammatory (NSAID) drug, as potential eEF2K inhibitors and we designed and synthesized seven novel compounds with a pyrano[3,4-b] indole core structure. We evaluated the eEF2K inhibitory activity of seven of these novel compounds using in silico molecular modeling and in vitro studies in TNBC cell lines. We identified two novel compounds (EC1 and EC7) with significant in vitro activity in inhibiting eEF2K in TNBC cells. In conclusion, our studies indicate that pyrano[3,4-b] indole scaffold containing compounds demonstrate marked eEF2K inhibitory activity and they may be used as eEF2K inhibitors for the development of eEF2K-targeted therapeutics.

Virtual drug repurposing study for the CGRPR identifies pentagastrin and leuprorelin as putative candidates.

Calcitonin gene-related peptide receptor (CGRPR) is a heterodimer consisting of CLR and RAMP1 proteins. Activation of the CGRPR with the endogenous peptide CGRP is known to play a crucial role in migraine pathophysiology. CGRP occupies two regions in the CGRPR upon binding, namely ectodomain and transmembrane sites (sites 1 and 2, respectively). The disruption of the CGRPR heterodimer interface is one of the main strategies to prevent CGRPR activation and its resulting effects. So far, FDA approved monoclonal antibodies and small molecule gepant inhibitors are considered for the treatment of acute or chronic migraine symptoms. However, most of these gepants have severe side effects. Thus, in this study, a virtual drug repurposing approach is applied to CGRPR to find alternative or better molecules that would have a potential to inhibit or block the CLR - RAMP1 interface compared to known gepant molecules. A small molecule library of FDA-approved molecules was screened in these two different binding sites, further simulations were performed and analyzed. The objectives of this study are (i) to repurpose an FDA-approved drug having more potent features for CGRPR inhibition compared to gepants, and (ii) to examine whether the transmembrane binding site (site 2) accepts small molecules or small peptide analogues for binding. As a result of this extensive in silico analysis, two molecules were identified, namely pentagastrin and leuprorelin. It is shown that FDA approved compound rimegepant and the identified pentagastrin molecules form and maintain the interactions through CLR W72 and RAMP1 W74, which are the residues revealed to have an important role in CGRPR antagonism at binding site 1. At binding site 2, the interactions needed to be formed for CGRP binding are not captured by rimegepant nor leuprorelin, yet leuprorelin forms more interactions throughout the simulations, meaning that small molecules are also capable of binding to site 2. Moreover, it is found that the crucial interactions for receptor signaling and heterodimerization occurred between CLR and RAMP1 interface are disrupted more with the ligands bound to ectodomain site, rather than the transmembrane domain. These findings of pentagastrin and leuprorelin molecules are recommended to be considered in further de novo drug development and/or experimental studies related to CGRPR signaling blockade and antagonism.

Review on In Silico Methods, High-throughput Screening Techniques, and Cell Culture Based In Vitro Assays for SARS-CoV-2.

The COVID-19 outbreak caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to have high incidence and mortality rate globally. To meet the increasingly growing demand for new therapeutic drugs and vaccines, researchers are developing different diagnostic techniques focused on screening new drugs in clinical use, developing an antibody targeting a SARS-CoV-2 receptor, or interrupting infection/replication mechanisms of SARS-CoV-2. Although many prestigious research publications are addressing this subject, there is no open access platform where all experimental techniques for COVID-19 research can be seen as a whole. Many researchers have accelerated the development of in silico methods, high-throughput screening techniques, and in vitro assays. This development has played an important role in the emergence of improved, innovative strategies, including different antiviral drug development, new drug discovery protocols, combinations of approved drugs, and setting up new drug classes during the COVID-19 outbreak. Hence, the present review discusses the current literature on these modalities, including virtual in silico methods for instant ligand- and target-driven based techniques, nucleic acid amplification tests, and in vitro models based on sensitive cell cultures, tissue equivalents, organoids, and SARS-CoV-2 neutralization systems (lentiviral pseudotype, viral isolates, etc.). This pack of complementary tests informs researchers about the accurate, most relevant emerging techniques available and in vitro assays allow them to understand their strengths and limitations. This review could be a pioneer reference guide for the development of logical algorithmic approaches for new drugs and vaccine strategies against COVID-19.