Side-by-side comparison of Notch- and C83 binding to γ-secretase in a complete membrane model at physiological temperature

Emerging structures and dynamic mechanisms of γ-secretase for Alzheimer's disease

γ-Secretase, called "the proteasome of the membrane," is a membrane-embedded protease complex that cleaves 150+ peptide substrates with central roles in biology and medicine, including amyloid precursor protein and the Notch family of cell-surface receptors. Mutations in γ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer's disease. γ-Secretase has thus served as a critical drug target for treating familial Alzheimer's disease and the more common late-onset Alzheimer's disease as well. However, critical gaps remain in understanding the mechanisms of processive proteolysis of substrates, the effects of familial Alzheimer's disease mutations, and allosteric modulation of substrate cleavage by γ-secretase. In this review, we focus on recent studies of structural dynamic mechanisms of γ-secretase. Different mechanisms, including the "Fit-Stay-Trim," "Sliding-Unwinding," and "Tilting-Unwinding," have been proposed for substrate proteolysis of amyloid precursor protein by γ-secretase based on all-atom molecular dynamics simulations. While an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-bound γ-secretase, molecular dynamics simulations on a resolved model of Notch1-bound γ-secretase that was reconstructed using the amyloid precursor protein-bound γ-secretase as a template successfully captured γ-secretase activation for proper cleavages of both wildtype and mutant Notch, being consistent with biochemical experimental findings. The approach could be potentially applied to decipher the processing mechanisms of various substrates by γ-secretase. In addition, controversy over the effects of familial Alzheimer's disease mutations, particularly the issue of whether they stabilize or destabilize γ-secretase-substrate complexes, is discussed. Finally, an outlook is provided for future studies of γ-secretase, including pathways of substrate binding and product release, effects of modulators on familial Alzheimer's disease mutations of the γ-secretase-substrate complexes. Comprehensive understanding of the functional mechanisms of γ-secretase will greatly facilitate the rational design of effective drug molecules for treating familial Alzheimer's disease and perhaps Alzheimer's disease in general.

Molecular recognition between volatile molecules and odorant binding proteins 7 by homology modeling, molecular docking and molecular dynamics simulation

BACKGROUND

Odorant-binding proteins (OBPs) in insects are key to detection and recognition of external chemical signals associated with survival. OBP7 in Spodoptera frugiperda's larval stage (SfruOBP7) may search for host plants by sensing plant volatiles, which are important sources of pest attractants and repellents. However, the atomic-level basis of binding modes remains elusive.

RESULTS

SfruOBP7 structure was constructed through homology modeling, and complex models of six plant volatiles ((E)-2-hexenol, α-pinene, (Z)-3-hexenyl acetate, lauric acid, O-cymene and 1-octanol) and SfruOBP7 were obtained through molecular docking. To study the detailed interactions between the six plant volatile molecules and SfruOBP7, we conducted three 300 ns molecular dynamics simulations for each study object. The correlation coefficients between binding free energy obtained by molecular mechanics/generalized Born surface area together with solvated interaction energy methods and experimental values are 0.90 and 0.88, respectively, showing a good correlation. By comparing binding free energy along with interaction patterns between SfruOBP7 and the six volatile molecules, hotspot residues of SfruOBP7 when binding with different volatile molecules were determined. Hydrophobic interactions stemming from van der Waals interactions play a significant role in SfruOBP7 and these plant volatile systems.

CONCLUSION

The optimized three-dimensional structure of SfruOBP7 and its binding modes with six plant volatiles revealed their interactions, thus providing a means for estimating the binding energies of other plant volatiles. Our study will help to guide the rational design of effective and selective insect attractants. © 2024 Society of Chemical Industry.

Structural bioinformatics studies of glutamate transporters and their AlphaFold2 predicted water-soluble QTY variants and uncovering the natural mutations of L->Q, I->T, F->Y and Q->L, T->I and Y->F

Glutamate transporters play key roles in nervous physiology by modulating excitatory neurotransmitter levels, when malfunctioning, involving in a wide range of neurological and physiological disorders. However, integral transmembrane proteins including the glutamate transporters remain notoriously difficult to study, due to their localization within the cell membrane. Here we present the structural bioinformatics studies of glutamate transporters and their water-soluble variants generated through QTY-code, a protein design strategy based on systematic amino acid substitutions. These include 2 structures determined by X-ray crystallography, cryo-EM, and 6 predicted by AlphaFold2, and their predicted water-soluble QTY variants. In the native structures of glutamate transporters, transmembrane helices contain hydrophobic amino acids such as leucine (L), isoleucine (I), and phenylalanine (F). To design water-soluble variants, these hydrophobic amino acids are systematically replaced by hydrophilic amino acids, namely glutamine (Q), threonine (T) and tyrosine (Y). The QTY variants exhibited water-solubility, with four having identical isoelectric focusing points (pI) and the other four having very similar pI. We present the superposed structures of the native glutamate transporters and their water-soluble QTY variants. The superposed structures displayed remarkable similarity with RMSD 0.528Å-2.456Å, despite significant protein transmembrane sequence differences (41.1%->53.8%). Additionally, we examined the differences of hydrophobicity patches between the native glutamate transporters and their QTY variants. Upon closer inspection, we discovered multiple natural variations of L->Q, I->T, F->Y and Q->L, T->I, Y->F in these transporters. Some of these natural variations were benign and the remaining were reported in specific neurological disorders. We further investigated the characteristics of hydrophobic to hydrophilic substitutions in glutamate transporters, utilizing variant analysis and evolutionary profiling. Our structural bioinformatics studies not only provided insight into the differences between the hydrophobic helices and hydrophilic helices in the glutamate transporters, but they are also expected to stimulate further study of other water-soluble transmembrane proteins.

Analysis of E2F1 single-nucleotide polymorphisms reveals deleterious non-synonymous substitutions that disrupt E2F1-RB protein interaction in cancer

Cancer is a medical condition that is caused by the abnormal growth and division of cells, leading to the formation of tumors. The E2F1 and RB pathways are critical in regulating cell cycle, and their dysregulation can contribute to the development of cancer. In this study, we analyzed experimentally reported SNPs in E2F1 and assessed their effects on the binding affinity with RB. Out of 46, nine mutations were predicted as deleterious, and further analysis revealed four highly destabilizing mutations (L206W, R232C, I254T, A267T) that significantly altered the protein structure. Molecular docking of wild-type and mutant E2F1 with RB revealed a docking score of -242 kcal/mol for wild-type, while the mutant complexes had scores ranging from -217 to -220 kcal/mol. Molecular simulation analysis revealed variations in the dynamics features of both mutant and wild-type complexes due to the acquired mutations. Furthermore, the total binding free energy for the wild-type E2F1-RB complex was -64.89 kcal/mol, while those of the L206W, R232C, I254T, and A267T E2F1-RB mutants were -45.90 kcal/mol, -53.52 kcal/mol, -55.67 kcal/mol, and -61.22 kcal/mol, respectively. Our study is the first to extensively analyze E2F1 gene mutations and identifies candidate mutations for further validation and potential targeting for cancer therapeutics.

Spectroscopic insights with molecular docking and molecular dynamic simulation studies of anticancer drug 5-Fluorouracil targeting human pyruvate kinase m2

This study was conducted to test the efficacy of 5-fluorouracil (5-FU) as an anticancer drug against the human pyruvate kinase isozyme M2 (PKM2) using spectroscopic, molecular docking and molecular dynamic simulation studies. PKM2 fluorescence quenching studies in the presence of 5-FU performed at three different temperatures indicates dynamic quenching processes with single-set of binding (n ≈ 1) profile. The biomolecular quenching constants (kq) and the effective binding constants (Kb) obtained are shown to increase with temperature. The calculated enthalpy (ΔH) and entropy changes (ΔS) are estimated to be -118.06 kJ/mol and 146.14 kJ/mol/K respectively, which suggest the possible mode of interaction as electrostatic and hydrogen bonding. Further, these values were used to estimate the free energy changes (ΔG) and that increases with temperature. The negative ΔG values clearly indicates spontaneous binding process that stabilizes the complex formed between 5-FU and PKM2. Far-UV CD spectra of PKM2 in the presence of 5-FU shows decrease in α-helix contents which point towards the destabilization of secondary structure that weakens the biological activity of PKM2. The intrinsic fluorescence study and circular dichroism (CD) spectra showed minor conformational changes of PKM2 in the presence of 5-FU. Additionally, the results obtained from molecular docking and all-atom molecular dynamic simulation study supports the insight of the spectroscopic binding studies, and strengthens the dynamic stability of the complex between 5-FU and PKM2 through H-bonding. This study establishes a paradigm of 5-FU-PKM2 complexation and the efficacy of 5-FU that compromises the biological activity of the targeted PKM2.Communicated by Ramaswamy H. Sarma.

Predicting virus Fitness: Towards a structure-based computational model

Predicting the impact of new emerging virus mutations is of major interest in surveillance and for understanding the evolutionary forces of the pathogens. The SARS-CoV-2 surface spike-protein (S-protein) binds to human ACE2 receptors as a critical step in host cell infection. At the same time, S-protein binding to human antibodies neutralizes the virus and prevents interaction with ACE2. Here we combine these two binding properties in a simple virus fitness model, using structure-based computation of all possible mutation effects averaged over 10 ACE2 complexes and 10 antibody complexes of the S-protein (∼380,000 computed mutations), and validated the approach against diverse experimental binding/escape data of ACE2 and antibodies. The ACE2-antibody selectivity change caused by mutation (i.e., the differential change in binding to ACE2 vs. immunity-inducing antibodies) is proposed to be a key metric of fitness model, enabling systematic error cancelation when evaluated. In this model, new mutations become fixated if they increase the selective binding to ACE2 relative to circulating antibodies, assuming that both are present in the host in a competitive binding situation. We use this model to categorize viral mutations that may best reach ACE2 before being captured by antibodies. Our model may aid the understanding of variant-specific vaccines and molecular mechanisms of viral evolution in the context of a human host.

The amyloid cascade hypothesis: an updated critical review

Results from recent clinical trials of antibodies that target amyloid-β (Aβ) for Alzheimer's disease have created excitement and have been heralded as corroboration of the amyloid cascade hypothesis. However, while Aβ may contribute to disease, genetic, clinical, imaging and biochemical data suggest a more complex aetiology. Here we review the history and weaknesses of the amyloid cascade hypothesis in view of the new evidence obtained from clinical trials of anti-amyloid antibodies. These trials indicate that the treatments have either no or uncertain clinical effect on cognition. Despite the importance of amyloid in the definition of Alzheimer's disease, we argue that the data point to Aβ playing a minor aetiological role. We also discuss data suggesting that the concerted activity of many pathogenic factors contribute to Alzheimer's disease and propose that evolving multi-factor disease models will better underpin the search for more effective strategies to treat the disease.

Permissive Conformations of a Transmembrane Helix Allow Intramembrane Proteolysis by γ-Secretase

The intramembrane protease γ-secretase activates important signaling molecules, such as Notch receptors. It is still unclear, however, how different elements within the primary structure of substrate transmembrane domains (TMDs) contribute to their cleavability. Using a newly developed yeast-based cleavage assay, we identified three crucial regions within the TMDs of the paralogs Notch1 and Notch3 by mutational and gain-of-function approaches. The AAAA or AGAV motifs within the N-terminal half of the TMDs were found to confer strong conformational flexibility to these TMD helices, as determined by mutagenesis coupled to deuterium/hydrogen exchange. Crucial amino acids within the C-terminal half may support substrate docking into the catalytic cleft of presenilin, the enzymatic subunit of γ-secretase. Further, residues close to the C-termini of the TMDs may stabilize a tripartite β-sheet in the substrate/enzyme complex. NMR structures reveal different extents of helix bending as well as an ability to adopt widely differing conformational substates, depending on the sequence of the N-terminal half. The difference in cleavability between Notch1 and Notch3 TMDs is jointly determined by the conformational repertoires of the TMD helices and the sequences of the C-terminal half, as suggested by mutagenesis and building molecular models. In sum, cleavability of a γ-secretase substrate is enabled by different functions of cooperating TMD regions, which deepens our mechanistic understanding of substrate/non-substrate discrimination in intramembrane proteolysis.

Exploiting the potential of natural polyphenols as antivirals against monkeypox envelope protein F13 using machine learning and all-atoms MD simulations

The re-emergence of monkeypox (MPX), in the era of COVID-19 pandemic is a new global menace. Regardless of its leniency, there are chances of MPX expediting severe health deterioration. The role of envelope protein, F13 as a critical component for production of extracellular viral particles makes it a crucial drug target. Polyphenols, exhibiting antiviral properties have been acclaimed as an effective alternative to the traditional treatment methods for management of viral diseases. To facilitate the development of potent MPX specific therapeutics, herein, we have employed state-of-the-art machine learning techniques to predict a highly accurate 3-dimensional structure of F13 as well as identify binding hotspots on the protein surface. Additionally, we have effectuated high-throughput virtual screening methodology on 57 potent natural polyphenols having antiviral activities followed by all-atoms molecular dynamics (MD) simulations, to substantiate the mode of interaction of F13 protein and polyphenol complexes. The structure-based virtual screening based on Glide SP, XP and MM/GBSA scores enables the selection of six potent polyphenols having higher binding affinity towards F13. Non-bonded contact analysis, of pre- and post- MD complexes propound the critical role of Glu143, Asp134, Asn345, Ser321 and Tyr320 residues in polyphenol recognition, which is well supported by per-residue decomposition analysis. Close-observation of the structural ensembles from MD suggests that the binding groove of F13 is mostly hydrophobic in nature. Taken together, this structure-based analysis from our study provides a lead on Myricetin, and Demethoxycurcumin, which may act as potent inhibitors of F13. In conclusion, our study provides new insights into the molecular recognition and dynamics of F13-polyphenol bound states, offering new promises for development of antivirals to combat monkeypox. However, further in vitro and in vivo experiments are necessary to validate these results.

Effects of presenilin-1 familial Alzheimer's disease mutations on γ-secretase activation for cleavage of amyloid precursor protein

Presenilin-1 (PS1) is the catalytic subunit of γ-secretase which cleaves within the transmembrane domain of over 150 peptide substrates. Dominant missense mutations in PS1 cause early-onset familial Alzheimer's disease (FAD); however, the exact pathogenic mechanism remains unknown. Here we combined Gaussian accelerated molecular dynamics (GaMD) simulations and biochemical experiments to determine the effects of six representative PS1 FAD mutations (P117L, I143T, L166P, G384A, L435F, and L286V) on the enzyme-substrate interactions between γ-secretase and amyloid precursor protein (APP). Biochemical experiments showed that all six PS1 FAD mutations rendered γ-secretase less active for the endoproteolytic (ε) cleavage of APP. Distinct low-energy conformational states were identified from the free energy profiles of wildtype and PS1 FAD-mutant γ-secretase. The P117L and L286V FAD mutants could still sample the "Active" state for substrate cleavage, but with noticeably reduced conformational space compared with the wildtype. The other mutants hardly visited the "Active" state. The PS1 FAD mutants were found to reduce γ-secretase proteolytic activity by hindering APP residue L49 from proper orientation in the active site and/or disrupting the distance between the catalytic aspartates. Therefore, our findings provide mechanistic insights into how PS1 FAD mutations affect structural dynamics and enzyme-substrate interactions of γ-secretase and APP.

Structural and energetic basis of interaction between human estrogen-related receptor γ and environmental endocrine disruptors from multiple molecular dynamics simulations and free energy predictions

Environmental endocrine disruptors (EEDs), a class of molecules that are widespread in our environment, may adversely affect the endocrine system. Exploring the interactions between these compounds and their potential targets is important for assessing their role in the organism. Focused on the human estrogen-related receptor γ (hERRγ) with BPA, BPB, HPTE, BPE, BP(2,2)(Et), and BP(2,2)(MeO) complexes, respectively, we groped for the mechanisms of conformational changes and interactions of hERRγ when binding to these six EEDs by combining multiple molecular dynamics (MD) simulations with energy prediction (MM-PBSA and solvated interaction energy (SIE)). Dynamics analysis results revealed these six EEDs have different effects on the internal dynamics of hERRγ, resulting in significant changes in the interaction of key residues around Leu268, Val313, Leu345, and Phe435 with EEDs, and thus affected its binding energy with these EEDs. The energy calculations further demonstrated that van der Waals interactions are critical for these EEDs binding to hERRγ. These results present detailed molecular insight into the interaction features between EEDs and hERRγ and help guide the search for safer alternatives to BPA.

Formation of extramembrane β-strands controls dimerization of transmembrane helices in amyloid precursor protein C99

The 99-residue C-terminal domain of amyloid precursor protein (APP-C99), precursor to amyloid beta (Aβ), is a transmembrane (TM) protein containing intrinsically disordered N- and C-terminal extramembrane domains. Using molecular dynamics (MD) simulations, we show that the structural ensemble of the C99 monomer is best described in terms of thousands of states. The C99 monomer has a propensity to form β-strand in the C-terminal extramembrane domain, which explains the slow spin relaxation times observed in paramagnetic probe NMR experiments. Surprisingly, homodimerization of C99 not only narrows the conformational ensemble from thousands to a few states through the formation of metastable β-strands in extramembrane domains but also stabilizes extramembrane α-helices. The extramembrane domain structure is observed to dramatically impact the homodimerization motif, resulting in the modification of TM domain conformations. Our study provides an atomic-level structural basis for communication between the extramembrane domains of the C99 protein and TM homodimer formation. This finding could serve as a general model for understanding the influence of disordered extramembrane domains on TM protein structure.

Sequence-structure functional implications and molecular simulation of high deleterious nonsynonymous substitutions in IDH1 revealed the mechanism of drug resistance in glioma

In the past few years, various somatic point mutations of isocitrate dehydrogenase (IDH) encoding genes (IDH1 and IDH2) have been identified in a broad range of cancers, including glioma. Despite the important function of IDH1 in tumorigenesis and its very polymorphic nature, it is not yet clear how different nsSNPs affect the structure and function of IDH1. In the present study, we employed different machine learning algorithms to screen nsSNPs in the IDH1 gene that are highly deleterious. From a total of 207 SNPs, all of the servers classified 80 mutations as deleterious. Among the 80 deleterious mutations, 14 were reported to be highly destabilizing using structure-based prediction methods. Three highly destabilizing mutations G15E, W92G, and I333S were further subjected to molecular docking and simulation validation. The docking results and molecular simulation analysis further displayed variation in dynamics features. The results from molecular docking and binding free energy demonstrated reduced binding of the drug in contrast to the wild type. This, consequently, shows the impact of these deleterious substitutions on the binding of the small molecule. PCA (principal component analysis) and FEL (free energy landscape) analysis revealed that these mutations had caused different arrangements to bind small molecules than the wild type where the total internal motion is decreased, thus consequently producing minimal binding effects. This study is the first extensive in silico analysis of the IDH1 gene that can narrow down the candidate mutations for further validation and targeting for therapeutic purposes.

Construction of the small intestine on molecular dynamics simulation and preliminary exploration of drug intestinal absorption prediction

In this study, molecular dynamics simulation was applied to the construction of the small intestinal epithelial cell membrane and prediction of drug absorption. First, we constructed a system of a small intestinal epithelial cell membrane that was close to the real proportion and investigated the effects of temperature, water layer thickness, and ionic strength on membrane properties to optimize environmental parameters. Next, three drugs with different absorptivity, including Ephedrine (EPH), Quercetin (QUE), and Baicalin (BAI), were selected as model drugs to study the ability of drugs through the membrane by the free diffusion and umbrella sampling simulation, and the drug permeation ability was characterized by the free diffusion coefficient D and free energy barrier (△G) in the processes. The results showed that the free diffusion coefficient D and △G orders of the three drugs were consistent with the classical experimental absorption order, indicating that these two parameters could be used to jointly characterize the membrane permeability of the drugs.

Mechanism of Tripeptide Trimming of Amyloid β-Peptide 49 by γ-Secretase

The membrane-embedded γ-secretase complex processively cleaves within the transmembrane domain of amyloid precursor protein (APP) to produce 37-to-43-residue amyloid β-peptides (Aβ) of Alzheimer's disease (AD). Despite its importance in pathogenesis, the mechanism of processive proteolysis by γ-secretase remains poorly understood. Here, mass spectrometry and Western blotting were used to quantify the efficiency of tripeptide trimming of wild-type (WT) and familial AD (FAD) mutant Aβ49. In comparison to WT Aβ49, the efficiency of tripeptide trimming was similar for the I45F, A42T, and V46F Aβ49 FAD mutants but substantially diminished for the I45T and T48P mutants. In parallel with biochemical experiments, all-atom simulations using a novel peptide Gaussian accelerated molecular dynamics (Pep-GaMD) method were applied to investigate the tripeptide trimming of Aβ49 by γ-secretase. The starting structure was the active γ-secretase bound to Aβ49 and APP intracellular domain (AICD), as generated from our previous study that captured the activation of γ-secretase for the initial endoproteolytic cleavage of APP (Bhattarai, A., ACS Cent. Sci. 2020, 6, 969-983). Pep-GaMD simulations captured remarkable structural rearrangements of both the enzyme and substrate, in which hydrogen-bonded catalytic aspartates and water became poised for tripeptide trimming of Aβ49 to Aβ46. These structural changes required a positively charged N-terminus of endoproteolytic coproduct AICD, which could dissociate during conformational rearrangements of the protease and Aβ49. The simulation findings were highly consistent with biochemical experimental data. Taken together, our complementary biochemical experiments and Pep-GaMD simulations have enabled elucidation of the mechanism of tripeptide trimming of Aβ49 by γ-secretase.

Mechanistic regulation of γ-secretase by their substrates

γ-Secretase (GS) is a transmembrane (TM) enzyme that plays important roles in the processing of approximately 90 substrates.

Molecular characterization and structural dynamics of Aquaporin1 from walking catfish in lipid bilayers

Aquaporin's (AQPs) are the major superfamily of small integral membrane proteins that facilitates transportation of water, urea, ammonia, glycerol and ions across biological cell membranes. Despite of recent advancements made in understanding the biology of Aquaporin's, only few isoforms of aquaporin 1 (AQP1) some of the teleost fish species have been characterized at molecular scale. In this study, we made an attempt to elucidate the molecular mechanism of water transportation in AQP1 from walking catfish (Clarias batrachus), a model species capable of breathing in air and inhabits in challenging environments. Using state-of-the-art computational modelling and all-atoms molecular dynamics simulation, we explored the structural dynamics of full-length aquaporin 1 from walking catfish (CbAQP1) in lipid mimetic bilayers. Unlike AQP1 of human and bovine, structural ensembles of CbAQP1 from MD revealed discrete positioning of pore lining residues at the intracellular end. Snapshots from MD simulation displayed differential dynamics of aromatic/arginine (ar/R) filter and extracellular loop C bridging transmembrane (TM) helix H3 and H4. Distinct conformation of large extracellular loops, loop bridging TM2 domain and HB helix along with positioning of selectivity filter lining residues controls the permeability of water across the bilayer. Moreover, the identified unique and conserved lipid binding sites with 100% lipid occupancy signifies lipid mediated structural dynamics of CbAQP1. All-together, this is the first ever report on structural-dynamics of aquaporin 1 in walking catfish which will be useful to understand the molecular basis of transportation of water and other small molecules under varying degree of hyperosmotic environment.

Novel dynamic residue network analysis approaches to study allosteric modulation: SARS-CoV-2 Mpro and its evolutionary mutations as a case study

The rational search for allosteric modulators and the allosteric mechanisms of these modulators in the presence of mutations is a relatively unexplored field. Here, we established novel in silico approaches and applied them to SARS-CoV-2 main protease (Mpro) as a case study. First, we identified six potential allosteric modulators. Then, we focused on understanding the allosteric effects of these modulators on each of its protomers. We introduced a new combinatorial approach and dynamic residue network (DRN) analysis algorithms to examine patterns of change and conservation of critical nodes, according to five independent criteria of network centrality. We observed highly conserved network hubs for each averaged DRN metric on the basis of their existence in both protomers in the absence and presence of all ligands (persistent hubs). We also detected ligand specific signal changes. Using eigencentrality (EC) persistent hubs and ligand introduced hubs we identified a residue communication path connecting the allosteric binding site to the catalytic site. Finally, we examined the effects of the mutations on the behavior of the protein in the presence of selected potential allosteric modulators and investigated the ligand stability. One crucial outcome was to show that EC centrality hubs form an allosteric communication path between the allosteric ligand binding site to the active site going through the interface residues of domains I and II; and this path was either weakened or lost in the presence of some of the mutations. Overall, the results revealed crucial aspects that need to be considered in rational computational drug discovery.

MDM-TASK-web: MD-TASK and MODE-TASK web server for analyzing protein dynamics

The web server, MDM-TASK-web, combines the MD-TASK and MODE-TASK software suites, which are aimed at the coarse-grained analysis of static and all-atom MD-simulated proteins, using a variety of non-conventional approaches, such as dynamic residue network analysis, perturbation-response scanning, dynamic cross-correlation, essential dynamics and normal mode analysis. Altogether, these tools allow for the exploration of protein dynamics at various levels of detail, spanning single residue perturbations and weighted contact network representations, to global residue centrality measurements and the investigation of global protein motion. Typically, following molecular dynamic simulations designed to investigate intrinsic and extrinsic protein perturbations (for instance induced by allosteric and orthosteric ligands, protein binding, temperature, pH and mutations), this selection of tools can be used to further describe protein dynamics. This may lead to the discovery of key residues involved in biological processes, such as drug resistance. The server simplifies the set-up required for running these tools and visualizing their results. Several scripts from the tool suites were updated and new ones were also added and integrated with 2D/3D visualization via the web interface. An embedded work-flow, integrated documentation and visualization tools shorten the number of steps to follow, starting from calculations to result visualization. The Django-powered web server (available at https://mdmtaskweb.rubi.ru.ac.za/) is compatible with all major web browsers. All scripts implemented in the web platform are freely available at https://github.com/RUBi-ZA/MD-TASK/tree/mdm-task-web and https://github.com/RUBi-ZA/MODE-TASK/tree/mdm-task-web.