Unified Aedes aegypti Protein Resource Database (UAAPRD): An Integrated High-Throughput In Silico Platform for Comprehensive Protein Structure Modeling and Functional Target Analysis to Enhance Vector Control Strategies.

A comprehensive examination of Aedes aegypti's proteome to detect key proteins that can be targeted with small molecules can disrupt blood feeding and disease transmission. However, research currently only focuses on finding repellent-like compounds, limiting studies on identifying unexplored proteins in its proteome. High-throughput analysis generates vast amounts of data, raising concerns about accessibility and usability. Establishing a dedicated database is a solution, centralizing information on identified proteins, functions, and modeled structures for easy access and research. This study focuses on scrutinizing key proteins in A. aegypti, modeling their structures using RaptorX standalone tool, identification of druggable binding sites using BiteNet, validating the models via Ramachandran plot studies and refining them via 50-ns molecular dynamic simulations using Schrodinger Maestro. By analyzing ~ 18 k proteins in the proteome of A. aegypti in our previous studies, all proteins involved in the light and dark circadian rhythm of the mosquito, inclusive of proteins in blood feeding, metabolism, etc. were chosen for the current study. The outcome is UAAPRD, a unique repository housing information on hundreds of previously unmodeled and un-simulated mosquito proteins. This robust MYSQL database ( https://uaaprd.onrender.com/user ) houses data on 309 modeled & simulated proteins of A. aegypti. It allows users to obtain protein data, view evolutionary analysis data of the protein categories, visualize proteins of interest, and send request to screen against the pharmacophore models present in UAAPRD against ligand of interest. This study offers crucial insights for developing targeted studies, which will ultimately contribute to more effective vector control strategies.

Lead Identification Through In Silico Studies: Targeting Acetylcholinesterase Enzyme Against Alzheimer's Disease.

AIMS: In this work, we aimed to acquire the best potential small molecule for Alzheimer's disease (AD) treatment using different models in Biovia Discovery Studio to identify new potential inhibitors of acetylcholinesterase (AChE) via in silico studies. BACKGROUND: The prevalence of cognitive impairment-related neurodegenerative disorders, such as AD, has been observed to escalate rapidly. However, we still know little about the underlying functions, outcome predictors, or intervention targets causing AD. OBJECTIVES: The objective of the study was to optimize and identify the lead compound to target AChE against Alzheimer's disease. METHODS: Different in silico studies were employed, including the pharmacophore model, virtual screening, molecular docking, de novo evolution model, and molecular dynamics. RESULTS: The pharmacophoric features of AChE inhibitors were determined by ligand-based pharmacophore models and 3D QSAR pharmacophore generation. Further validation of the best pharmacophore model was done using the cost analysis method, Fischer's randomization method, and test set. The molecules that harmonized the best pharmacophore model with the estimated activity < 1 nM and ADMET parameters were filtered, and 12 molecules were subjected to molecular docking studies to obtain binding energy. 3vsp_EK8_1 secured the highest binding energy of 65.60 kcal/mol. Further optimization led to a 3v_Evo_4 molecule with a better binding energy of 70.17 kcal/mol. The molecule 3v_evo_4 was subjected to 100 ns molecular simulation compared to donepezil, which showed better stability at the binding site. CONCLUSION: A lead compound, 3v_Evo_4 molecule, was identified to inhibit AChE, and it could be further studied to develop as a drug with better efficacy than the existing available drugs for treating AD.

Exploring the chemical space of functionalized [1,2,4]triazolo[4,3-a]quinoxaline-based compounds targeting the bromodomain of BRD9.

Here we report a detailed structure-activity relationship (SAR) study related to [1,2,4]triazolo[4,3-a]quinoxaline-based compounds targeting the reader module of bromodomain containing-protein 9 (BRD9). 3D structure-based pharmacophore models, previously introduced by us, were here employed to evaluate a second generation of compounds, exploring different substitution patterns on the heterocyclic core. Starting from the promising data obtained from our previously identified [1,2,4]triazolo[4,3-a]quinoxaline-based compounds 1-4, the combination of in silico studies, chemical synthesis, biophysical and in vitro assays led to the identification of a new set of derivatives, selected for thoroughly exploring the chemical space of the bromodomain binding site. In more details, the investigation of different linkers at C-4 position highlighted the amine spacer as mandatory for the binding with the protein counterpart and the crucial role of the alkyl substituents at C-1 for increasing the selectivity toward BRD9. Additionally, the importance of a hydrogen bond donor group, critical to anchor the ZA region and required for the interaction with Ile53 residue, was inferred from the analysis of our collected results. Herein we also propose an optimization and an update of our previously reported "pharm-druglike2" 3D structure-based pharmacophore model, introducing it as "pharm-druglike2.1". Compounds 24-26, 32, 34 and 36 were identified as new valuable BRD9 binders featuring IC50 values in the low micromolar range. Among them, 24 and 36 displayed an excellent selectivity towards BRD9 and a good antiproliferative effect on a panel of leukemia models, especially toward CCRF-CEM cell line, with no cytotoxicity on healthy cells. Notably, the interaction of 24 and 36 with the bromodomain and PHD finger-containing protein 1 (BRPF1) also emerged, disclosing them as new and unexplored dual inhibitors for these two proteins highly involved in leukemia. These findings highlight the potential for the identification of new attractive dual epidrugs as well as a promising starting point for the development of chemical degraders endowed with anticancer activities.

Importance of Pharmacophore in Designing Anticonvulsant Agents.

Drug design is one of the critical aspects of the drug development process. The present review focused on different heterocyclic molecules having anticonvulsant activity with structural diversity and common pharmacophoric features. For the first time (1995), Dimmock and his team introduced specific arrangements of three important pharmacophores for anticonvulsant activity. These pharmacophores include two hydrophobic binding sites and one hydrogen binding site. After a few years (2012), Pandeya modified Dimmock's concept by adding one more pharmacophoric feature as an electron donor in the previously suggested pharmacophoric arrangement of the anticonvulsant. As a result, numerous scientists designed anticonvulsant drugs based on Dimmock's and Pandeya's concept. In addition, marketed anticonvulsant preparation containing Riluzole, Phenobarbital, Progabide, Ralitoline, etc., also holds the suggested pharmacophores by Dimmock and Pandeya's pharmacophoric concept. This review mainly focuses on the compilation of reported scientific literature in the last decade on the pharmacophoric features of different heterocyclic anticonvulsants, which will help develop new anticonvulsants.

Discovery of novel potential CRBN modulators through structure-based virtual screening and bioassay.

CRBN protein is an E3 ubiquitin ligase which plays an important role in the ubiquitin-proteasome system of eukaryotic cells. Small molecules can modulate CRBN and induce multiple target proteins to bind with CRBN, which contributes to ubiquitination and degradation of target proteins. Modulating the CRBN protein through small molecules provides a novel idea for treatment of tumors and immune system disease. Due to most of CRBN modulators containing glutarimide skeleton, we aimed to discover novel potent CRBN modulators. In this study, Lipinski's rule and Veber rule, pharmacophore based virtual screening, docking based virtual screening and ADMET screening methods were performed to discover potential CRBN modulators. The antitumor activity of 11 candidates were evaluated by MTS assay. AN7535 showed potent antitumor activity with IC50 = 0.72 µM against HL-60 and IC50 = 1.438 µM against SMMC-7721. AO6355 showed potent antitumor activity with IC50 = 7.469 µM against SMMC-7721. MD simulations and binding free energy calculations suggested that AN7535 and AO6355 could stabilize the CRBN protein and have favorable binding affinity with CRBN protein. Luciferase complementation assay suggested AN7535 could bind to CRBN with IC50 = 215.9 µM.

Pharmacophore-based drug design of AChE and BChE dual inhibitors as potential anti-Alzheimer's disease agents.

For the Alzheimer's disease (AD) with complex pathogenesis, single target drugs represent one of the most effective therapeutic strategies in clinical. However, the traditional concept of "a disease, a target" is difficult to find very effective drugs, and multi-target drugs have already become new hot spot in drug development for this disease. In our present study, our efforts toward discovering new cholinesterase (ChE) inhibitors aided by computational methods will provide useful information as anti-AD agents in the future. The best 3D-QSAR acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitors pharmacophore hypotheses Hypo1 A and Hypo1 B were generated and validated by HypoGen program in Discovery Studio 2016 based on the training set of flavonoids, and then they were used as 3D query for screening the ZINC database. Next, the hit molecules were then subjected to the ADMET and molecular docking study to prioritize the compounds. Finally, 6 compounds showed good estimated activities and promising ADMET properties. The result of best compound ZINC08751495 with AChE estimate activity (0.028), BChE estimate activity (1.55), AChE fit value (9.369), BChE fit value (8.415), AChE -CDOCKER ENERGY (30.22), BChE -CDOCKER ENERGY (33.13) has the potential for further development as a supplement to treat Alzheimer's disease.

Structure-Based Discovery of ABCG2 Inhibitors: A Homology Protein-Based Pharmacophore Modeling and Molecular Docking Approach.

ABCG2 is an ABC membrane protein reverse transport pump, which removes toxic substances such as medicines out of cells. As a result, drug bioavailability is an unexpected change and negatively influences the ADMET (absorption, distribution, metabolism, excretion, and toxicity), leading to multi-drug resistance (MDR). Currently, in spite of promising studies, screening for ABCG2 inhibitors showed modest results. The aim of this study was to search for small molecules that could inhibit the ABCG2 pump. We first used the WISS MODEL automatic server to build up ABCG2 homology protein from 655 amino acids. Pharmacophore models, which were con-structed based on strong ABCG2 inhibitors (IC50 < 1 µM), consist of two hydrophobic (Hyd) groups, two hydrogen bonding acceptors (Acc2), and an aromatic or conjugated ring (Aro|PiR). Using molecular docking method, 714 substances from the DrugBank and 837 substances from the TCM with potential to inhibit the ABCG2 were obtained. These chemicals maybe favor synthesized or extracted and bioactivity testing.

Discovery of novel potential KIT inhibitors for the treatment of gastrointestinal stromal tumor.

Numerous inhibitors of tyrosine-protein kinase KIT, a receptor tyrosine kinase, have been explored as a viable therapy for the treatment of gastrointestinal stromal tumor (GIST). However, drug resistance due to acquired mutations in KIT makes these drugs almost useless. The present study was designed to screen the novel inhibitors against the activity of the KIT mutants through pharmacophore modeling and molecular docking. The best two pharmacophore models were established using the KIT mutants' crystal complexes and were used to screen the new compounds with possible KIT inhibitory activity against both activation loop and ATP-binding mutants. As a result, two compounds were identified as potential candidates from the virtual screening, which satisfied the potential binding capabilities, molecular modeling characteristics, and predicted absorption, distribution, metabolism, excretion, toxicity (ADMET) properties. Further molecular docking simulations showed that two compounds made strong hydrogen bond interaction with different KIT mutant proteins. Our results indicated that pharmacophore models based on the receptor-ligand complex had excellent ability to screen KIT inhibitors, and two compounds may have the potential to develop further as the future KIT inhibitors for GIST treatment.

Theoretical Design of Biodegradable Phthalic Acid Ester Derivatives in Marine and Freshwater Environments.

The biodegradability of phtalic acid esters in marine and freshwater environments was characterized by their binding free energy with corresponding degrading enzymes. According to comprehensive biodegradation effects weights, the binding free energy values were converted into dimensionless efficacy coefficient using ratio normalization method. Then, considering comprehensive dual biodegradation effects value and the structural parameters of PAEs in both marine and freshwater environments, a 3D-QSAR pharmacophore model was constructed, five PAE derivatives (DBP-COOH, DBP-CHO, DBP-OH, DINP-NH2, and DINP-NO2) were screened out based on their environmental friendliness, functionality and stability. The prediction of biodegradation effects on five PAE derivatives by biodegradation models in marine and freshwater environment increased by 15.90 %, 15.84 %, 27.21 %, 12.33 %, and 8.32 %, and 21.57 %, 15.21 %, 20.99 %, 15.10 %, and 9.74 %, respectively. By simulating the photodegradation path of the PAE derivative molecular, it was found that DBP-OH can generate .OH and provides free radicals for the photodegradation of microplastics in the environment.

Identification of natural products as selective PTP1B inhibitors via virtual screening.

Protein tyrosine phosphatase 1B (PTP1B) is emerging as a promising yet challenging target for drug discovery. To identify natural products as new prototypes for PTP1B inhibitors, we employed a hierarchical protocol combining ligand-based and structure-based approaches for virtual screening against natural product libraries. Twenty-six compounds were prioritized for enzymatic evaluation against PTP1B, and ten of them were recognized as potent PTP1B inhibitors with IC50 values at the micromolar level. Notably, nine compounds demonstrated evident selectivity to PTP1B over four other PTPs, including the most homologous T-cell protein tyrosine phosphatase (TCPTP). The results implicated that the structural uniqueness of the natural products might be a potential solution to the selectivity issue associated with the target PTP1B.

Identification of potential platelet-derived growth factor receptor α inhibitors by computational screening and binding simulations.

Platelet-derived growth factor receptor α (PDGFRα) is considered as a promising target for the treatment of fibrotic diseases. In this study, two types of pharmacophore model, which generated by ligand-based and receptor-based method, were put forward to identify novel chemical entities as PDGFRα inhibitors. It was found that some pharmacophore characteristics established by the two approaches overlap each other. In order to elucidate detailed interactions, representative molecules were selected to predict the conformations and binding modes of the molecules by molecular docking method. The calculation results of binding free energy illustrated that the van der Waals energy and nonpolar solvation were the most prominent contribution to the interactions between the inhibitors and PDGFRα. To further verify the accuracy of the docking results and the stability of the complexes system, the binding modes of two potent PDGFRα inhibitors were examined by 100 ns molecular dynamics simulations. Herein, we reported the basic structural requirements of PDGFRα inhibitors for the first time through molecular docking and molecular dynamics simulations. Subsequently, the two pharmacophore models were used for virtual screening to query potential active molecules from Food and Drug Administration approved database. The hit molecules here might provide additional scaffolds for further optimization of PDGFRα inhibitors.

Discovery of Novel DPP-IV Inhibitors as Potential Candidates for the Treatment of Type 2 Diabetes mellitus Predicted by 3D QSAR Pharmacophore Models, Molecular Docking and de novo Evolution.

Dipeptidyl peptidase-IV (DPP-IV) rapidly breaks down the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP). Thus, the use of DPP-IV inhibitors to retard the degradation of endogenous GLP-1 is a possible mode of therapy correcting the defect in incretin-related physiology. The aim of this study is to find a new small molecule and explore the inhibition activity to the DPP-IV enzyme using a computer aided simulation. In this study, the predicted compounds were suggested as potent anti-diabetic candidates. Chosen structures were applied following computational strategies: The generation of the three-dimensional quantitative structure-activity relationship (3D QSAR) pharmacophore models, virtual screening, molecular docking, and de novo Evolution. The method also validated by performing re-docking and cross-docking studies of seven protein systems for which crystal structures were available for all bound ligands. The molecular docking experiments of predicted compounds within the binding pocket of DPP-IV were conducted. By using 25 training set inhibitors, ten pharmacophore models were generated, among which hypo1 was the best pharmacophore model with the best predictive power on account of the highest cost difference (352.03), the lowest root mean squared deviation (RMSD) (2.234), and the best correlation coefficient (0.925). Hypo1 pharmacophore model was used for virtual screening. A total of 161 compounds including 120 from the databases, 25 from the training set, 16 from the test set were selected for molecular docking. Analyzing the amino acid residues of the ligand-receptor interaction, it can be concluded that Arg125, Glu205, Glu206, Tyr547, Tyr662, and Tyr666 are the main amino acid residues. The last step in this study was de novo Evolution that generated 11 novel compounds. The derivative dpp4_45_Evo_1 by all scores CDOCKER_ENERGY (CDOCKER, -41.79), LigScore1 (LScore1, 5.86), LigScore2 (LScore2, 7.07), PLP1 (-112.01), PLP2 (-105.77), PMF (-162.5)-have exceeded the control compound. Thus the most active compound among 11 derivative compounds is dpp4_45_Evo_1. Additionally, for derivatives dpp4_42_Evo_1, dpp4_43_Evo2, dpp4_46_Evo_4, and dpp4_47_Evo_2, significant upward shifts were recorded. The consensus score for the derivatives of dpp4_45_Evo_1 from 1 to 6, dpp4_43_Evo2 from 4 to 6, dpp4_46_Evo_4 from 1 to 6, and dpp4_47_Evo_2 from 0 to 6 were increased. Generally, predicted candidates can act as potent occurring DPP-IV inhibitors given their ability to bind directly to the active sites of DPP-IV. Our result described that the 6 re-docked and 27 cross-docked protein-ligand complexes showed RMSD values of less than 2 Å. Further investigation will result in the development of novel and potential antidiabetic drugs.

Identification of New Potent Human Uncoupling Protein 1 (UCP1) Agonists Using Virtual Screening and in vitro Approaches.

Recent studies suggested that activation of Uncoupling Protein 1 (UCP1) has become an appealing therapeutic strategy against obesity and diabetes. In our research, the 3D structure of UCP1 was constructed through homology modelling, refined through molecular dynamics simulation, and evaluated by Ramachandran plot, the molecular docking of UCP1 activators brought about the proposal of an interaction mode inside the UCP1 active site. Remarkably, Reside Lys126 formed hydrogen bond; residues Pro121, Val125, Tyr146, Tyr149 and Arg150 formed hydrophobic interaction, which are key amino acids within UCP1 site. Then a pharmacophore model was generated consisting of three hydrophobic groups, a negative center and an additional hydrophobic group. Pharmacophore-based virutal screening of Specs database yield 5 hits. In vitro assay indicated ZINC 04660290 significantly increased the protein expression of UCP1 and decreased the fat droplet in a dose-dependent manner. Besides, pharmacokinetic properties were predicted for those five compounds through ADME/T prediction. All of these will guide us to design new UCP1 activators for the treatment of obesity and diabetes.

Pharmacophore-based drug design for the identification of novel butyrylcholinesterase inhibitors against Alzheimer's disease.

BACKGROUND: Alzheimer's disease is a severe neurodegenerative disease of the central nervous system in the elderly. HYPOTHESIS/PURPOSE: In our study, we aimed to find the best potential small molecule for AD treatment. STUDY DESIGN: We used many models in Discovery Studio 2016 to find new potential inhibitors of butyrylcholinesterase (BChE), including pharmacophore model, virtual screening model, molecular docking model, de novo evolution model. METHODS: Ligand-based pharmacophore models were used to identify the critical chemical features of BChE inhibitors using the module of 3D QSAR Pharmacophore Generation in Discovery Studio 2016. The best pharmacophore model was then validated by cost analysis, Fischer's randomization method, 3D-QSAR Method of the training set and test set. The compounds that match the best pharmacophore model with the predicted activity <1 µM filtered by Lipinski's rule of five were subjected to molecular docking. RESULT: After virtual screening, 35 compounds filtered by Lipinski's rule of five and ADMET analysis were subjected to molecular docking and then the number were narrowed down on 10 compounds based on -CDOCKER_ENERGY. Finally, we obtained and modified the best potential candidate ENA739155. CONCLUSION: Ultimately, ENA739155_Evo with -CDOCKER_ENERGY of 47.12, estimate activity of 0.012, fit value of 10.02 could be further subjected to drug development and forwarded as better alternatives to the current batch of medicines used for the treatment of AD.

Computational insight into dengue virus NS2B-NS3 protease inhibition: A combined ligand- and structure-based approach.

The NS2B-NS3 protease is essential for the replication process of Dengue Virus, which make it an attractive target for anti-virus drugs. Since a considerable number of NS2B-NS3 protease inhibitors have been reported so far, it is significant for the discovery of more effective antivirus compounds with the essential structure-activity relationship extracted from known inhibitors. In this perspective, the relationship between the chemical features of inhibitors and their biological activities was investigated with a combined ligand- and structure-based approach. Furthermore, 3D pharmacophore models were generated with the best selected, which consisted of five chemical features: one ring aromatic group, one hydrophobic group, one hydrogen bond donor and two hydrogen bond acceptors (RHDAA). Subsequently, molecular docking was employed to explore the specific allosteric site for non-peptidic inhibitors to bind, which was proved to be located behind the catalytic triad. Taken the results of both molecular docking and pharmacophore modeling into consideration, a model of receptor-ligand interaction was obtained with four essential chemical features including aromatic rings and hydrogen bonds. This research provided an accurate binding model for the discovery and optimization of NS2B-NS3 protease inhibitors.

In silico insight into voltage-gated sodium channel 1.7 inhibition for anti-pain drug discovery.

Studies on human genetics have implicated the voltage-gated sodium channel Nav1.7 as an appealing target for the treatment of pain. In this study, we put forward a ligand-based pharmacophore for the first time, which was generated by a set of multiple chemical scaffolds including sulfonamide and non-sulfonamide derivatives and consisted of four chemical features: an aromatic ring, a hydrophobic group and two hydrogen acceptors. The active cavity was divided into three regions according to the properties of the amino acids surrounded and was used for the docking of 16 known active inhibitors. Four accurate docking methods were employed to analyze the ligand-protein interactions in our molecular simulation study. Combining pharmacophore model with docking results, an interaction model was obtained with four features that were consistent with one another, which was more powerful in illuminating the binding site. The research elucidated a valuable relationship between structure and activity, at the same time it proposed an accurate binding model that was instructive in the development of novel and potent Nav1.7 inhibitors in the future.

2-Arylthio-5-iodo pyrimidine derivatives as non-nucleoside HBV polymerase inhibitors.

In this study, a series of 2-arylthio-5-iodo pyrimidine derivatives, as non-nucleoside hepatitis B virus inhibitors, were evaluated and firstly reported as potential anti-HBV agents. To probe the mechanism of active agents, DHBV polymerase was isolated and a non-radioisotopic assay was established for measuring HBV polymerase. The biological results demonstrated that 2-arylthio-5-iodo pyrimidine derivatives targeted HBV polymerase. In addition, pharmacophore models were constructed for future optimization of lead compounds. Further study will be performed for the development of non-nucleoside anti-HBV agents.

Predicting tyrosinase inhibition by 3D QSAR pharmacophore models and designing potential tyrosinase inhibitors from Traditional Chinese medicine database.

BACKGROUND: Tyrosinase plays a key role in the formation of skin melanin. The excessive accumulation of skin melanin will cause the serious aesthetic problems for human beings. HYPOTHESIS/PURPOSE: To find the potent tyrosinase inhibitors using computational simulation from TCM Database@Taiwan. STUDY DESIGN: Inhibitors of tyrosinase have been thought as potential drugs for the decrease of melanin synthesis in the process of pigmentation. To develop new tyrosinase inhibitors, we performed a virtual screening from Traditional Chinese medicine (TCM) and Druglike Databases using the best 3D QSAR pharmacophore model as a 3D search query. METHODS: A total of 109 compounds were obtained after filtering by Lipinski's rule of five. Finally, 148 compounds (22 from training set, 17 from test set, 109 from TCM and Druglike databases) were selected for further docking studies. De Novo Evolution designed the top 10 candidates from the docking results. RESULTS: Hypo1 was selected as the best quantitative pharmacophore model, because Hypo1 has characters of the highest cost difference (353.773), the lowest RMS (1.985), the lowest Error (121.440), and the best correlation coefficient (0.933). By the analysis of interaction amino acids in the top 10 hits including two controls, HIS42, HIS60, HIS204, HIS208, ARG209 and VAL218 are identified as the key binding site residues, ARG209 and VAL218 are the critical residues for the inhibitory activity of tyrosinase. This finding is consistent with the results from literatures. CONCLUSION: De Novo Evolution study suggested Tyrosinase_1*_Evo_4, Tyrosinase_23*_Evo_7, magnolone.cdx_15_Evo_4, compound_2.cdx_2_Evo_2, Compound_B_Evo_5, Compound_C_Evo_9, Compound_D_Evo_6 and malabaricone_C.cdx_3_Evo_10 as the potential tyrosinase inhibitor candidates. De Novo Evolution study also suggested compound_2.cdx_2_Evo_2 as the most potential tyrosinase inhibitor candidate. A total of ten novel leading compounds were identified to have the favorable interaction with tyrosinase by the docking analyses.

Structural Basis of Antisickling Effects of Selected FDA Approved Drugs: A Drug Repurposing Study.

INTRODUCTION: Sickle cell disease is characterized by a point mutation involving substitution of glutamic acid at position 6 to valine. Encoded in this hydrophobic mutation is both an intrinsic capacity for the beta globin molecules to assemble into thermodynamically favoured polymeric states as well as a rational way of interrupting the aggregation. METHODS: In this work, starting with a theoretical model that employs occlusive binding onto the beta globin aggregation surface and using a range of computational methods and an effective energy for screening, a number of FDA approved drugs with computed aggregation inhibitory activities were identified. RESULTS AND CONCLUSION: The validity of the model was confirmed using sickling tests, after which pharmacophore models as well the structural basis for the observed antisickling effects were identified.