Insilico study of the A2AR–D2R kinetics and interfacial contact surface for heteromerization

Discovery of novel A2AR antagonist via 3D-QSAR pharmacophore modeling: neuroprotective effects in 6-OHDA-induced SH-SY5Y cells and haloperidol-induced Parkinsonism in C57 bl/6 mice

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder which is caused by abrupt degeneration of dopaminergic neuronal cells in the substantia nigra pars compacta (SNPc) area of the midbrain. Adenosine A2A receptors have become promising therapeutic targets for PD; however, many A2A receptor antagonists face challenges, such as limited accessibility or failure in clinical trials due to poor selectivity and bioavailability. To identify novel A2A receptor antagonists, a 3D-QSAR-pharmacophore modeling approach was employed, involving virtual screening of ZINC, NCI, and MayBridge databases. The virtual hits were filtered via ADMET criteria to select compounds with favorable bioavailability and solubility profiles. From the MayBridge database, a potent monocyclic A2A receptor antagonist, AW00032 (N-(furan-2-ylmethyl)-5-methylthiazole-4-yl) thiophene-2-sulfonamide, was identified. AW00032 possessed key pharmacophoric features: two lipophilic hydrogen bond acceptors, one hydrophobic aliphatic/aromatic group, and one aromatic ring. Docking analysis revealed AW00032 had a strong binding affinity for A2A receptors (1.23 nM, ∆G - 10.49 kcal/mol), and its ADMET profile indicated good bioavailability. In 6-OHDA induced SH-SY5Y cells, AW00032 increased dopamine levels and tyrosine hydroxylase (TH) expression, demonstrating its potential as an A2A receptor antagonist. AW00032, discovered through 3D-QSAR pharmacophore modeling, also reduced reactive oxygen species (ROS) levels and showed depletion in mitochondrial dysfunction in 6-OHDA-induced SH-SY5Y cells. It exhibited A2A receptor antagonist activity comparable to the standard antagonist ZM241385, partially restoring dopamine and TH levels. Furthermore, AW00032 improved behavioral symptoms in haloperidol-induced C-57 bl/6 mice.

Discovering potential inhibitors against SARS-CoV-2 by targeting Nsp13 Helicase

The rise in the incidence of COVID-19 as a result of SARS-CoV-2 infection has threatened public health globally. Till now, there have been no proper prophylactics available to fight COVID-19, necessitating the advancement and evolution of effective curative against SARS-CoV-2. This study aimed at the nonstructural protein 13 (nsp13) helicase as a promising target for drug development against COVID-19. A unique collection of nucleoside analogs was screened against the SARS-CoV-2 helicase protein, for which a molecular docking experiment was executed to depict the selected ligand's binding affinity with the SARS-CoV-2 helicase proteins. Simultaneously, molecular dynamic simulations were performed to examine the protein's binding site's conformational stability, flexibility, and interaction with the ligands. Key nucleoside ligands were selected for pharmacokinetic analysis based on their docking scores. Selected ligands (cordycepin and pritelivir) showed excellent pharmacokinetics and were well stabilized at the proteins' binding site throughout the MD simulation. We have also performed binding free energy analysis or the binding characteristics of ligands with Nsp13 by using MM-PBSA and MM-GBSA. Free energy calculation by MM-PBSA and MM-GBSA analysis suggests that pritelivir may work as viable therapeutics for efficient drug advancement against SARS-CoV-2 Nsp13 helicase, potentially arresting the SARS-CoV-2 replication.Communicated by Ramaswamy H. Sarma.

Identifying the Novel Inhibitors Against the Mycolic Acid Biosynthesis Pathway Target "mtFabH" of Mycobacterium tuberculosis

Mycolic acids are the key constituents of mycobacterial cell wall, which protect the bacteria from antibiotic susceptibility, helping to subvert and escape from the host immune system. Thus, the enzymes involved in regulating and biosynthesis of mycolic acids can be explored as potential drug targets to kill Mycobacterium tuberculosis (Mtb). Herein, Kyoto Encyclopedia of Genes and Genomes is used to understand the fatty acid metabolism signaling pathway and integrative computational approach to identify the novel lead molecules against the mtFabH (β-ketoacyl-acyl carrier protein synthase III), the key regulatory enzyme of the mycolic acid pathway. The structure-based virtual screening of antimycobacterial compounds from ChEMBL library against mtFabH results in the selection of 10 lead molecules. Molecular binding and drug-likeness properties of lead molecules compared with mtFabH inhibitor suggest that only two compounds, ChEMBL414848 (C1) and ChEMBL363794 (C2), may be explored as potential lead molecules. However, the spatial stability and binding free energy estimation of thiolactomycin (TLM) and compounds C1 and C2 with mtFabH using molecular dynamics simulation, followed by molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) indicate the better activity of C2 (ΔG = -14.18 kcal/mol) as compared with TLM (ΔG = -9.21 kcal/mol) and C1 (ΔG = -13.50 kcal/mol). Thus, compound C1 may be explored as promising drug candidate for the structure-based drug designing of mtFabH inhibitors in the therapy of Mtb.

Design, synthesis, and computational studies of benzimidazole derivatives as new antitubercular agents

The increase in the drug-resistant strains of Mycobacterium tuberculosis has led researchers to new drug targets. The development of new compounds that have effective inhibitory properties with the selective vital structure of Mycobacterium tuberculosis is required in new scientific approaches. The most important of these approaches is the development of inhibitor molecules for Mycobacterium cell wall targets. In this study, first of all, the antitubercular activity of 23 benzimidazole derivatives was experimentally determined. And then molecular docking studies were carried out with 4 different targets: Arabinosyltransferase C (EmbC), Filamentous Temperature Sensitive Mutant Z (FtsZ), Protein Tyrosine Phosphatase B (PtpB), and Decaprenylphosphoryl-β-D-ribose-2'-oxidase (DprE1). It has been determined that benzimidazole derivatives show activity through the DprE1 enzyme. It is known that DprE1, which has an important role in the synthesis of the cell envelope from Arabinogalactan, is also effective in the formation of drug resistance. Due to this feature, the DprE1 enzyme has become an important target for drug development studies. Also, it was chosen as a target for this study. This study aims to identify molecules that inhibit DprE1 for the development of more potent and selective antitubercular drugs. For this purpose, molecular docking studies by AutoDock Vina, and CDOCKER and molecular dynamics (MD) simulations and in silico ADME/Tox analysis were implemented for 23 molecules. The molecules exhibited binding affinity values of less than -8.0 kcal/mol. After determining the compound's anti-TB activities by a screening test, the best-docked results were detected using compounds 20, 21, and 30. It was found that 21, was the best molecule with its binding affinity value, which was supported by MD simulations and in silico ADME modeling results.Communicated by Ramaswamy H. Sarma.

Combining SARS-CoV-2 Proofreading Exonuclease and RNA-Dependent RNA Polymerase Inhibitors as a Strategy to Combat COVID-19: A High-Throughput in silico Screening

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected millions of people worldwide. Currently, many clinical trials in search of effective COVID-19 drugs are underway. Viral RNA-dependent RNA polymerase (RdRp) remains the target of choice for prophylactic or curative treatment of COVID-19. Nucleoside analogs are the most promising RdRp inhibitors and have shown effectiveness in vitro, as well as in clinical settings. One limitation of such RdRp inhibitors is the removal of incorporated nucleoside analogs by SARS-CoV-2 exonuclease (ExoN). Thus, ExoN proofreading activity accomplishes resistance to many of the RdRp inhibitors. We hypothesize that in the absence of highly efficient antivirals to treat COVID-19, combinatorial drug therapy with RdRp and ExoN inhibitors will be a promising strategy to combat the disease. To repurpose drugs for COVID-19 treatment, 10,397 conformers of 2,240 approved drugs were screened against the ExoN domain of nsp14 using AutoDock VINA. The molecular docking approach and detailed study of interactions helped us to identify dexamethasone metasulfobenzoate, conivaptan, hesperidin, and glycyrrhizic acid as potential inhibitors of ExoN activity. The results were further confirmed using molecular dynamics (MD) simulations and molecular mechanics combined with generalized Born model and solvent accessibility method (MM-GBSA) calculations. Furthermore, the binding free energy of conivaptan and hesperidin, estimated using MM-GBSA, was -85.86 ± 0.68 and 119.07 ± 0.69 kcal/mol, respectively. Based on docking, MD simulations and known antiviral activities, and conivaptan and hesperidin were identified as potential SARS-CoV-2 ExoN inhibitors. We recommend further investigation of this combinational therapy using RdRp inhibitors with a repurposed ExoN inhibitor as a potential COVID-19 treatment.

Identifying the natural polyphenol catechin as a multi-targeted agent against SARS-CoV-2 for the plausible therapy of COVID-19: an integrated computational approach

The global pandemic crisis, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed the lives of millions of people across the world. Development and testing of anti-SARS-CoV-2 drugs or vaccines have not turned to be realistic within the timeframe needed to combat this pandemic. Here, we report a comprehensive computational approach to identify the multi-targeted drug molecules against the SARS-CoV-2 proteins, whichare crucially involved in the viral-host interaction, replication of the virus inside the host, disease progression and transmission of coronavirus infection. Virtual screening of 75 FDA-approved potential antiviral drugs against the target proteins, spike (S) glycoprotein, human angiotensin-converting enzyme 2 (hACE2), 3-chymotrypsin-like cysteine protease (3CLpro), cathepsin L (CTSL), nucleocapsid protein, RNA-dependent RNA polymerase (RdRp) and non-structural protein 6 (NSP6), resulted in the selection of seven drugs which preferentially bind to the target proteins. Further, the molecular interactions determined by molecular dynamics simulation revealed that among the 75 drug molecules, catechin can effectively bind to 3CLpro, CTSL, RBD of S protein, NSP6 and nucleocapsid protein. It is more conveniently involved in key molecular interactions, showing binding free energy (ΔGbind) in the range of -5.09 kcal/mol (CTSL) to -26.09 kcal/mol (NSP6). At the binding pocket, catechin is majorly stabilized by the hydrophobic interactions, displays ΔEvdW values: -7.59 to -37.39 kcal/mol. Thus, the structural insights of better binding affinity and favorable molecular interaction of catechin toward multiple target proteins signify that catechin can be potentially explored as a multi-targeted agent against COVID-19.

Discovering Potential RNA Dependent RNA Polymerase Inhibitors as Prospective Drugs Against COVID-19: An in silico Approach

COVID-19, caused by Severe Acute Respiratory Syndrome Corona Virus 2, is declared a Global Pandemic by WHO in early 2020. In the present situation, though more than 180 vaccine candidates with some already approved for emergency use, are currently in development against SARS-CoV-2, their safety and efficacy data is still in a very preliminary stage to recognize them as a new treatment, which demands an utmost emergency for the development of an alternative anti-COVID-19 drug sine qua non for a COVID-19 free world. Since RNA-dependent RNA polymerase (RdRp) is an essential protein involved in replicating the virus, it can be held as a potential drug target. We were keen to explore the plant-based product against RdRp and analyze its inhibitory potential to treat COVID-19. A unique collection of 248 plant compounds were selected based on their antiviral activity published in previous literature and were subjected to molecular docking analysis against the catalytic sub-unit of RdRp. The docking study was followed by a pharmacokinetics analysis and molecular dynamics simulation study of the selected best-docked compounds. Tellimagrandin I, SaikosaponinB2, Hesperidin and (-)-Epigallocatechin Gallate were the most prominent ones that showed strong binding affinity toward RdRp. All the compounds mentioned showed satisfactory pharmacokinetics properties and remained stabilized at their respective binding sites during the Molecular dynamics simulation. Additionally, we calculated the free-binding energy/the binding properties of RdRp-ligand complexes with the connection of MM/GBSA. Interestingly, we observe that SaikosaponinB2 gives the best binding affinity (∆Gbinding = -42.43 kcal/mol) in the MM/GBSA assay. Whereas, least activity is observed for Hesperidin (∆Gbinding = -22.72 kcal/mol). Overall our study unveiled the feasibility of the SaikosaponinB2 to serve as potential molecules for developing an effective therapy against COVID-19 by inhibiting one of its most crucial replication proteins, RdRp.

"Identification of Nafamostat and VR23 as COVID-19 drug candidates by targeting 3CLpro and PLpro."

The sudden increase in the COVID-19 epidemic affected by novel coronavirus 2019 has jeopardized public health worldwide. Hence the necessities of a drug or therapeutic agent that heal SARS-CoV-2 infections are essential requirements. The viral genome encodes a large Polyprotein, further processed by the main protease/ 3C-like protease (3CL^pro) and papain-like proteases (PL^pro) into 16 nonstructural proteins to form a viral replication complex. These essential functions of 3CL^pro and PL^pro in virus duplication make these proteases a promising target for discovering potential therapeutic candidates and possible treatment for SARS-CoV-2 infection.

This study aimed to screen a unique set of protease inhibitors library against 3CL^pro and PL^pro of the SARS-CoV-2. A molecular docking study was performed using PyRx to reveal the binding affinity of the selected ligands and molecular dynamic simulations were executed to assess the three-dimensional stability of protein-ligand complexes. The pharmacodynamics parameters of the inhibitors were predicted using admetSAR. The top two ligands (Nafamostat and VR23) based on docking scores were selected for further studies. Selected ligands showed excellent pharmacokinetic properties with proper absorption, bioavailability and minimal toxicity. Due to the emerging and efficiency of remdesivir and dexamethasone in healing COVID-19 patients, ADMET properties of the selected ligands were thus compared with it. MD Simulation studies up to 100 ns revealed the ligands' stability at the target proteins' binding site residues. Therefore, Nafamostat and VR23 may provide potential treatment options against SARS-CoV-2 infections by potentially inhibiting virus duplication though more research is warranted.

Allosteric Interactions between Adenosine A2A and Dopamine D2 Receptors in Heteromeric Complexes: Biochemical and Pharmacological Characteristics, and Opportunities for PET Imaging

Adenosine and dopamine interact antagonistically in living mammals. These interactions are mediated via adenosine A_2A and dopamine D₂ receptors (R). Stimulation of A_2AR inhibits and blockade of A_2AR enhances D₂R-mediated locomotor activation and goal-directed behavior in rodents. In striatal membrane preparations, adenosine decreases both the affinity and the signal transduction of D₂R via its interaction with A_2AR. Reciprocal A_2AR/D₂R interactions occur mainly in striatopallidal GABAergic medium spiny neurons (MSNs) of the indirect pathway that are involved in motor control, and in striatal astrocytes. In the nucleus accumbens, they also take place in MSNs involved in reward-related behavior. A_2AR and D₂R co-aggregate, co-internalize, and co-desensitize. They are at very close distance in biomembranes and form heteromers. Antagonistic interactions between adenosine and dopamine are (at least partially) caused by allosteric receptor–receptor interactions within A_2AR/D₂R heteromeric complexes. Such interactions may be exploited in novel strategies for the treatment of Parkinson’s disease, schizophrenia, substance abuse, and perhaps also attention deficit-hyperactivity disorder. Little is known about shifting A_2AR/D₂R heteromer/homodimer equilibria in the brain. Positron emission tomography with suitable ligands may provide in vivo information about receptor crosstalk in the living organism. Some experimental approaches, and strategies for the design of novel imaging agents (e.g., heterobivalent ligands) are proposed in this review.

Virtual screening and free energy estimation for identifying Mycobacterium tuberculosis flavoenzyme DprE1 inhibitors

In Mycobacterium tuberculosis (MTB), the cell wall synthesis flavoenzyme decaprenylphosphoryl-β-d-ribose 2'-epimerase (DprE1) plays a crucial role in host pathogenesis, virulence, lethality and survival under stress. The emergence of different variants of drug resistant MTB are a major threat worldwide which essentially requires more effective new drug molecules with no major side effects. Here, we used structure based virtual screening of bioactive molecules from the ChEMBL database targeting DprE1, having bioactive 78,713 molecules known for anti-tuberculosis activity. An extensive molecular docking, binding affinity and pharmacokinetics profile filtering results in the selection four compounds, C5 (ChEMBL2441313), C6 (ChEMBL2338605), C8 (ChEMBL441373) and C10 (ChEMBL1607606) which may explore as potential drug candidates. The obtained results were validated with thirteen known DprE1 inhibitors. We further estimated the free-binding energy, solvation and entropy terms underlying the binding properties of DprE1-ligand interactions with the implication of MD simulation, MM/GBSA, MM/PBSA and MM/3D-RISM. Interestingly, we find that C6 shows the highest ΔG scores (-41.28 ± 3.51, -22.36 ± 3.17, -10.33 ± 5.70 kcal mol^-1) in MM/GBSA, MM/PBSA and MM/3D-RISM assay, respectively. Whereas, the lowest ΔG scores (-35.31 ± 3.44, -13.67 ± 2.65, -3.40 ± 4.06 kcal mol^-1) observed for CT319, the inhibitor co-crystallized with DprE1. Collectively, the results demonstrated that hit-molecules: C5, C6, C8 and C10 having better binding free energy and molecular affinity as compared to CT319. Thus, we proposed that selected compounds may be explored as lead molecules in MTB therapy.

Targeting SARS-CoV-2 spike protein of COVID-19 with naturally occurring phytochemicals: an in silico study for drug development

Spike glycoprotein, a class I fusion protein harboring the surface of SARS-CoV-2 (SARS-CoV-2S), plays a seminal role in the viral infection starting from recognition of the host cell surface receptor, attachment to the fusion of the viral envelope with the host cells. Spike glycoprotein engages host Angiotensin-converting enzyme 2 (ACE2) receptors for entry into host cells, where the receptor recognition and attachment of spike glycoprotein to the ACE2 receptors is a prerequisite step and key determinant of the host cell and tissue tropism. Binding of spike glycoprotein to the ACE2 receptor triggers a cascade of structural transitions, including transition from a metastable pre-fusion to a post-fusion form, thereby allowing membrane fusion and internalization of the virus. From ancient times people have relied on naturally occurring substances like phytochemicals to fight against diseases and infection. Among these phytochemicals, flavonoids and non-flavonoids have been the active sources of different anti-microbial agents. We performed molecular docking studies using 10 potential naturally occurring compounds (flavonoids/non-flavonoids) against the SARS-CoV-2 spike protein and compared their affinity with an FDA approved repurposed drug hydroxychloroquine (HCQ). Further, our molecular dynamics (MD) simulation and energy landscape studies with fisetin, quercetin, and kamferol revealed that these molecules bind with the hACE2-S complex with low binding free energy. The study provided an indication that these molecules might have the potential to perturb the binding of hACE2-S complex. In addition, ADME analysis also suggested that these molecules consist of drug-likeness property, which may be further explored as anti-SARS-CoV-2 agents.

Communicated by Ramaswamy H. Sarma

Targeting virus-host interaction by novel pyrimidine derivative: an in silico approach towards discovery of potential drug against COVID-19

The entire human population over the globe is currently facing appalling conditions due to the spread of infection from coronavirus disease-2019 (COVID-19). The spike glycoprotein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) present on the surface of the virion mediates the virus entry into the host cells and therefore is targeted by several scientific groups as a novel drug target site. The spike glycoprotein binds to the human angiotensin-converting enzyme-2 (hACE2) cell surface receptor abundantly expressed in lung tissues, and this binding phenomenon is a primary determinant of cell tropism and pathogenesis. The binding and internalization of the virus is the primary and most crucial step in the process of infection, and therefore the molecules targeting the inhibition of this process certainly hold a significant therapeutic value. Thus, we systematically applied the computational techniques to identify the plausible inhibitor from a chosen set of well characterized diaryl pyrimidine analogues which may disrupt interfacial interaction of spike glycoprotein (S) at the surface of hACE2. Using molecular docking, molecular dynamics (MD) simulation and binding free energy calculation, we have identified AP-NP (2-(2-amino-5-(naphthalen-2-yl)pyrimidin-4-yl)phenol), AP-3-OMe-Ph (2-(2-amino-5-(3-methoxyphenyl)pyrimidin-4-yl)phenol) and AP-4-Me-Ph (2-(2-amino-5-(p-tolyl) pyrimidin-4-yl)phenol) from a group of diaryl pyrimidine derivatives which appears to bind at the interface of the hACE2-S complex with low binding free energy. Thus, pyrimidine derivative AP-NP may be explored as an effective inhibitor for hACE2-S complex. Furthermore, in vitro and in vivo studies will strengthen the use of these inhibitors as suitable drug candidates against SARS-COV-2.

Communicated by Ramaswamy H. Sarma

Delineating the conformational dynamics of intermediate structures on the unfolding pathway of β-lactoglobulin in aqueous urea and dimethyl sulfoxide

The funnel shaped energy landscape model of the protein folding suggests that progression of folding proceeds through multiple pathways, having the multiple intermediates which leads to multidimensional free-energy surface. Herein, we applied all-atom MD simulation to conduct a comparative study on the structure of β-lactoglobulin (β-LgA) in aqueous mixture of 8 M urea and 8 M dimethyl sulfoxide (DMSO), at different temperatures. The cumulative results of multiple simulations suggest a common unfolding pathway of β-LgA, occurred through the stable and meta-stable intermediates (I), in both urea and DMSO. However, the free-energy landscape (FEL) analyses show that the structural transitions of I-states are energetically different. In urea, FEL shows distinct ensemble of intermediates, I1 and I2, separated by the energy barrier of ∼3.0 kcal mol^-1. Similarly, we find the population of two distinct I1 and I2 states in DMSO, however, the I1 appeared transiently around ∼30-35 ns and is short-lived. But, the I2 ensemble is observed structurally compact and long-lived (∼50-150 ns) as compared to unfolding in urea. Furthermore, the I1 and I2 are separated through a high energy barrier of ∼6.0 kcal mol^-1. Thus, our results provide the structural insights of intermediates which essentially bear the signature of a different unfolding pathway of β-LgA in urea and DMSO.Abbreviationsβ-LgAβ-lactoglobulinDMSOdimethyl sulfoxideFELfree-energy landscapeGdmClguanidinium chlorideIintermediate stateMGmolten globule statePMEparticle mesh EwaldQfraction of native contactsRMSDroot mean square deviationRMSFroot mean square fluctuationR_gradius of gyrationSASAsolvent Accessible Surface AreascSASAthe side chain SASATrptryptophanCommunicated by Ramaswamy H. Sarma.

Characterization of heterogeneous intermediate ensembles on the guanidinium chloride-induced unfolding pathway of β-lactoglobulin

Folding pathway of β-LgA (β-lactoglobulin) evolves through the conformational α→β transition. The α→β transition is a molecular hallmark of various neurodegenerative diseases. Thus, β-LgA may serve as a good model for understanding molecular mechanism of protein aggregation involved in neurodegenerative diseases. Here, we studied the conformational dynamics of β-LgA in 6 M GdmCl at different temperatures using MD simulations. Structural order parameters such as RMSD, R_g, SASA, native contacts (Q), hydrophobic distal-matrix and free-energy landscape (FEL) were used to investigate the conformational transitions. Our results show that GdmCl destabilizes secondary and tertiary structure of β-LgA by weakening the hydrophobic interactions and hydrogen bond network. Multidimensional FEL shows the presence of different unfolding intermediates at 400 K. I1 is long-lived intermediate which has mostly intact native secondary structure, but loose tertiary structure. I2 is structurally compact intermediate formed after the partial loss of secondary structure. The transiently and infrequently buried evolution of W19 shows that intermediate conformational ensembles are structurally heterogeneous. We observed that the intermediate conformations are largely stabilized by non-native H-bonds. The outcome of this work provides the molecular details of intermediates trapped due to non-native interactions that may be regarded as pathogenic conformations involved in neurodegenerative diseases.Communicated by Ramaswamy H. Sarma.

Capturing the multiscale dynamics of membrane protein complexes with all-atom, mixed-resolution, and coarse-grained models

The structures and dynamics of protein complexes are often challenging to model in heterogeneous environments such as biological membranes. Herein, we meet this fundamental challenge at attainable cost with all-atom, mixed-resolution, and coarse-grained models of vital membrane proteins. We systematically simulated five complex models formed by two distinct G protein-coupled receptors (GPCRs) in the lipid-bilayer membrane on the ns-to-μs timescales. These models, which suggest the swinging motion of an intracellular loop, for the first time, provide the molecular details for the regulatory role of such a loop. For the models at different resolutions, we observed consistent structural stability but various levels of speed-ups in protein dynamics. The mixed-resolution and coarse-grained models show two and four times faster protein diffusion than the all-atom models, in addition to a 4- and 400-fold speed-up in the simulation performance. Furthermore, by elucidating the strengths and challenges of combining all-atom models with reduced resolution models, this study can serve as a guide to simulating other complex systems in heterogeneous environments efficiently.

Minireview: applied structural bioinformatics in proteomics

The limited sequence similarity of protein sequences with known structures has led to an indispensable need for computational technology to predict their structures. Structural bioinformatics (SB) has become integral in elucidating the sequence-structure-function relationship of a protein. This report focuses on the applications of SB within the context of protein engineering including its limitation and future challenges.