Neighboring Residues Research Articles

Nanoscale Topography Dictates Residue Hydropathy in Proteins.

Proteins exhibit diverse structures, including pockets, cavities, channels, and bumps, which are crucial in determining their functions. This diversity in topography also introduces significant chemical heterogeneity, with polar and charged domains often juxtaposed with nonpolar domains in proximity. Consequently, accurately assessing the hydropathy of amino acid residues within the intricate nanoscale topology of proteins is essential. This study presents quantitative hydropathy data for 277,877 amino acid residues, computed using the Protocol for Assigning a Residue's Character on a Hydropathy (PARCH) scale. Leveraging this data set comprising 1000 structurally diverse proteins sourced from the Protein Data Bank, we examined residues situated in various nanoscale environments and analyzed hydropathy in relation to protein topography. Our findings indicate that the hydropathy of a residue is intricately linked to both its individual characteristics and the geometric features of its neighboring residues in response to water. Changes in the number and chemical identity of the neighbors, as well as the nanoscale topography surrounding a residue, are mirrored in its hydropathy profile. Our calculations reveal the intricate interplay of hydrophilic, hydroneutral, and hydrophobic residues distributed across the surface and core of proteins. Notably, we observe that protein surfaces can be ten times more hydrophilic than their cores.

PMSFF: Improved Protein Binding Residues Prediction through Multi-Scale Sequence-Based Feature Fusion Strategy.

Proteins perform different biological functions through binding with various molecules which are mediated by a few key residues and accurate prediction of such protein binding residues (PBRs) is crucial for understanding cellular processes and for designing new drugs. Many computational prediction approaches have been proposed to identify PBRs with sequence-based features. However, these approaches face two main challenges: (1) these methods only concatenate residue feature vectors with a simple sliding window strategy, and (2) it is challenging to find a uniform sliding window size suitable for learning embeddings across different types of PBRs. In this study, we propose one novel framework that could apply multiple types of PBRs Prediciton task through Multi-scale Sequence-based Feature Fusion (PMSFF) strategy. Firstly, PMSFF employs a pre-trained language model named ProtT5, to encode amino acid residues in protein sequences. Then, it generates multi-scale residue embeddings by applying multi-size windows to capture effective neighboring residues and multi-size kernels to learn information across different scales. Additionally, the proposed model treats protein sequences as sentences, employing a bidirectional GRU to learn global context. We also collect benchmark datasets encompassing various PBRs types and evaluate our PMSFF approach to these datasets. Compared with state-of-the-art methods, PMSFF demonstrates superior performance on most PBRs prediction tasks.

Identification of Potent Inhibitors of Akt Kinases inhibitors from natural sources for Therapeutic Targeting of Oral Squamous Cell Carcinoma

BackgroundPlant-based natural compounds are effective cancer cell proliferation inhibitors. Consequently, the quest for these compounds for the treatment of cancer has become increasingly competitive and has opened up new avenues for drug development. The current investigation extensively addressed the virtual screening and structure-based prediction of compounds derived from natural products against Protein kinase B-alpha (PKBα, also known as Ak/4GV1).Material and MethodsIn this study, we conducted a thorough screening of putative PKBα inhibitors from a natural products library, and subsequently performed molecular modeling.ResultsThis research identified Irciniastatin B, Irciniastatin A, Pseudoceroxime D, (1'S)-7-chloroaverantin as the top four potential PKBα inhibitors from the library of natural products, whose Glide docking scores range from -10.689 to -7.567 kcal/mol. The RMSD and RMSF analysis reveals that all four ligands remain stable and maintain their interaction throughout the simulation time. The MM/GBSA (ranging from -37.26 to -51.02 kcal/mol) predicted binding affinities are in strong co-relation with that of the docking score, which not only supports the docking results but also suggests that Irciniastatin B exhibits superior binding affinity towards PKBα amongst all four studied compounds. Moreover, the interaction analysis also indicates that Irciniastatin B establishes at least 12 interactions with the neighbouring residues whereas, Irciniastatin A, Pseudoceroxime D, and (1'S)-7-chloroaverantin compounds were able to establish 8-9 interactions in the binding cavity of PKBα. ADMET assessment of the selected compounds was also noted to be within acceptable ranges.ConclusionKeeping in view these findings, Irciniastatin B might be a promising candidate for drug discovery against PKBα inhibitors.

Engineering of Substrate-Binding Domain to Improve Catalytic Activity of Chondroitin B Lyase with Semi-Rational Design.

Dermatan sulfate and chondroitin sulfate are dietary supplements that can be utilized as prophylactics against thrombus formation. Low-molecular-weight dermatan sulfate (LMWDS) is particularly advantageous due to its high absorbability. The enzymatic synthesis of low-molecular-weight dermatan sulfates (LMWDSs) using chondroitin B lyase is a sustainable and environmentally friendly approach to manufacturing. However, the industrial application of chondroitin B lyases is severely hampered by their low catalytic activity. To improve the activity, a semi-rational design strategy of engineering the substrate-binding domain of chondroitin B lyase was performed based on the structure. The binding domain was subjected to screening of critical residues for modification using multiple sequence alignments and molecular docking. A total of thirteen single-point mutants were constructed and analyzed to assess their catalytic characteristics. Out of these, S90T, N103C, H134Y, and R159K exhibited noteworthy enhancements in activity. This study also examined combinatorial mutagenesis and found that the mutant H134Y/R159K exhibited a substantially enhanced catalytic activity of 1266.74 U/mg, which was 3.21-fold that of the wild-type one. Molecular docking revealed that the enhanced activity of the mutant could be attributed to the formation of new hydrogen bonds and hydrophobic interactions with the substrate as well as neighbor residues. The highly active mutant would benefit the utilization of chondroitin B lyase in pharmaceuticals and functional foods.

Electrically Conductive Peptide Fibers as Direct Electron Transfer Scaffolds for Enzymatic Electrocatalysis

Biology provides many sources of inspiration for synthetic and multi-functional nanomaterials. Naturally evolved proteins possess a range of unique functions and self-assembly behavior. Some of these have electron transport functions as part of metabolic processes. Their flexible design and potential for stimuli responsiveness make proteins ideal building blocks of bioelectronic interfaces. In biosensor and electrocatalysis applications, bioelectronic materials are designed to interconvert biological signals or processes into electronic signals and vice versa. In this work, we designed a peptide fiber structure that exhibits stimuli-responsive self-assembly and the capacity to transport electrical current over micrometer long distances. Hierarchically ordered nanofibers of α-helical coiled-coil peptides were assembled using a pH responsive structure ordering motif comprising of two neighboring lysine residues. Cryo-EM structures of these assemblies reveal a novel organization of α-helical peptides in a cross coiled coil arrangement that exhibits electrical conductivity. Both solid-state and solution-based electrochemical characterization show that these fibers are conductive. Single-fiber conductive AFM determined that the solid-state electrical conductivity is on a similar order of magnitude with conductive cytochrome filaments from bacteria. Solution deposited fiber films approximately doubled the electroactive surface area of the electrode, confirming their conductivity in aqueous environments. Furthermore, these fibers can be used as scaffolds for redox enzyme immobilization for electrochemical biosensing. Progress towards immobilized enzymatic devices will be discussed as well. This work further expands the field of stimuli-responsive and multifunctional nanomaterials by using peptide assemblies as structural supports for future implementation in bioelectronic and bioelectrochemical systems.

Constant-pH MD simulations of the protonation-triggered conformational switching in diphtheria toxin translocation domain

Protonation of key residues in the diphtheria toxin translocation (T)-domain triggered by endosomal acidification is critical for inducing a series of conformational transitions critical for the cellular entry of the toxin. Previous experiments revealed the importance of histidine residues in modulating pH-dependent transitions. They suggested the presence of a “safety latch” preventing premature refolding of the T-domain by a yet poorly understood mechanism. Here, we used constant-pH molecular dynamics simulations to systematically investigate the protonation sequence in the wild-type T-domain and the following mutants: H223Q, H257Q, E259Q, and H223Q/H257Q. Comparison of these computational results with previous experimental data on T-domain stability and activity with the H-to-Q replacements confirms the role of H223 (pKa = 6.5) in delaying the protonation of the main trigger, H257 (pKa = 2.2 in the WT and pKa = 4.9 in H223Q). Our calculations also reveal a very low pKa for a neighboring acidic residue E259, which does not get protonated even during simulations at pH 3. This residue also contributes to the formation of the safety latch, with the pKa of H257 increasing from 2.2 to 5.1 upon E259Q replacement. In contrast, the latter replacement has virtually no effect on the protonation of the H223. Thus, we conclude that the interplay of the protonation in the H223/H257/E259 triad has evolved to prevent triggering the accidental refolding of the T-domain by a fluctuation in the protonation of the main trigger at neutral pH, before the incorporation of the toxin inside the endosome. Subsequent acidification of the endosome overcomes the safety latch and triggers conformational switching via repulsion of H223+ and H257+. This protonation/conformation relationship corroborates experimental findings and offers a detailed stepwise molecular description of the transition mechanism, which can be instrumental in optimizing the potential applications of the T-domain for targeted delivery of therapies to tumors and other diseased acidic tissues.

Report of a novel recurrent homozygous variant c.620A>T in three unrelated families with thiamine metabolism dysfunction syndrome 5 and review of literature.

Biallelic variants in thiamine pyrophosphokinase 1 ( TPK1 ) are known to cause thiamine metabolism dysfunction syndrome 5 (THMD5). This disorder is characterized by neuroregression, ataxia and dystonia with basal ganglia abnormalities on neuroimaging. To date, 27 families have been reported with THMD5 due to variants in TPK1 . We ascertained three individuals from three unrelated families. Singleton exome sequencing was performed on all three individuals, followed by in silico mutagenesis of the mutant TPK protein. Additionally, we reviewed the genotypic and phenotypic information of 27 previously reported individuals with THMD5. Singleton exome sequencing revealed a novel homozygous variant c.620A>T p.(Asp207Val) in TPK1 (NM_022445.4) in all three individuals. In silico mutagenesis of the mutant protein revealed a decrease in protein stability and altered interactions with its neighboring residues compared to the wild-type protein. Thus, based on strikingly similar clinical and radiological findings compared to the previously reported individuals and with the support of in silico mutagenesis findings, the above-mentioned variant appears to be the probable cause for the condition observed in the affected individuals in this study. We report a novel homozygous variant in TPK1 , which appears to be recurrent among the Indian population.

DDAffinity: predicting the changes in binding affinity of multiple point mutations using protein 3D structure.

Mutations are the crucial driving force for biological evolution as they can disrupt protein stability and protein-protein interactions which have notable impacts on protein structure, function, and expression. However, existing computational methods for protein mutation effects prediction are generally limited to single point mutations with global dependencies, and do not systematically take into account the local and global synergistic epistasis inherent in multiple point mutations. To this end, we propose a novel spatial and sequential message passing neural network, named DDAffinity, to predict the changes in binding affinity caused by multiple point mutations based on protein 3D structures. Specifically, instead of being on the whole protein, we perform message passing on the k-nearest neighbor residue graphs to extract pocket features of the protein 3D structures. Furthermore, to learn global topological features, a two-step additive Gaussian noising strategy during training is applied to blur out local details of protein geometry. We evaluate DDAffinity on benchmark datasets and external validation datasets. Overall, the predictive performance of DDAffinity is significantly improved compared with state-of-the-art baselines on multiple point mutations, including end-to-end and pre-training based methods. The ablation studies indicate the reasonable design of all components of DDAffinity. In addition, applications in nonredundant blind testing, predicting mutation effects of SARS-CoV-2 RBD variants, and optimizing human antibody against SARS-CoV-2 illustrate the effectiveness of DDAffinity. DDAffinity is available at https://github.com/ak422/DDAffinity.

Molecular docking of nano Zn capped by rhamnolipids

Rhamnolipids has been used as capping agent for ZnO nanoparticles to improving the plant micronutrition. ZnO nanoparticles were synthesized using co-precipitation method, and the prepared nanoparticles were capped with Rhamnolipids. The structural, morphological, optical, and particle stability characteristics of the chelated ZnO nanoparticles were investigated. UV–vis spectroscopy was used to investigate the optical properties of ZnO and Rhamnolipids capped ZnO nanoparticles. The stability of Rhamnolipids capped ZnO nanoparticles is higher (38.45 mV) than that of ZnO nanoparticles alone (32.3 mV). The Zn mineral nutrition in plants is improved by Rhamnolipids capped ZnO nanoparticles. In order to get a broad understanding of the binding of capped ZnO nanoparticles, a detailed molecular docking analysis was taken up. Molecular docking analysis reveals that the binding of Zn atom to LasI protein receptor has more neighboring group amino acid residues and greater binding affinity than the binding to LasR receptor.

Chromophore-Protein Interactions Affecting the Polyene Twist and π-π* Energy Gap of the Retinal Chromophore in Schizorhodopsins.

The properties of a prosthetic group are broadened by interactions with its neighboring residues in proteins. The retinal chromophore in rhodopsins absorbs light, undergoes structural changes, and drives functionally important structural changes in proteins during the photocycle. It is therefore crucial to understand how chromophore-protein interactions regulate the molecular structure and electronic state of chromophores in rhodopsins. Schizorhodopsin is a newly discovered subfamily of rhodopsins found in the genomes of Asgard archaea, which are extant prokaryotes closest to the last common ancestor of eukaryotes and of other microbial species. Here, we report the effects of a hydrogen bond between a retinal Schiff base and its counterion on the twist of the polyene chain and the color of the retinal chromophore. Correlations between spectral features revealed the unexpected fact that the twist of the polyene chain is reduced as the hydrogen bond becomes stronger, suggesting that the twist is caused by tight atomic contacts between the chromophore and nearby residues. In addition, the strength of the hydrogen bond is the primary factor affecting the color-tuning of the retinal chromophore in schizorhodopsins. The findings of this study are valuable for manipulating the molecular structure and electronic state of the chromophore by controlling chromophore-protein interactions.

Exploiting Hierarchical Interactions for Protein Surface Learning.

Predicting interactions between proteins is one of the most important yet challenging problems in structural bioinformatics. Intrinsically, potential function sites in protein surfaces are determined by both geometric and chemical features. However, existing works only consider handcrafted or individually learned chemical features from the atom type and extract geometric features independently. Here, we identify two key properties of effective protein surface learning: 1) relationship among atoms: atoms are linked with each other by covalent bonds to form biomolecules instead of appearing alone, leading to the significance of modeling the relationship among atoms in chemical feature learning. 2) hierarchical feature interaction: the neighboring residue effect validates the significance of hierarchical feature interaction among atoms and between surface points and atoms (or residues). In this paper, we present a principled framework based on deep learning techniques, namely Hierarchical Chemical and Geometric Feature Interaction Network (HCGNet), for protein surface analysis by bridging chemical and geometric features with hierarchical interactions. Extensive experiments demonstrate that our method outperforms the prior state-of-the-art method by 2.3% in site prediction task and 3.2 available at https://github.com/lyqun/HCGNet.

The Conformational Change of the L3 Loop Affects the Structural Changes in the Substrate Binding Pocket Entrance of β-Glucosidase

β-glucosidase (Bgl) hydrolyzes cellobiose to glucose, thereby releasing non-reducing terminal glucosyl residues. Bgl is an essential enzyme belonging to the biomass-degrading enzyme family, which plays a vital role in enzymatic saccharification during biofuel production. The four loops above the Bgl substrate-binding pocket undergo a conformational change upon substrate recognition. However, the structural dynamism of this loop and how it is conserved among Bgl family members remain unknown. Herein, to better understand the four loops above the substrate-binding pocket of Bgl, four Bgl crystal structures in Thermoanaerobacterium saccharolyticum (TsaBgl) were determined at 1.5–2.1 Å. The L1, L2, and L4 loops of TsaBgl showed a rigid conformation stabilized by their neighboring residues via hydrogen bonds and hydrophobic interactions. The TsaBgl L3 loop showed relatively high flexibility and two different N-terminal region conformations. The conformational change in the TsaBgl L3 loop induced a change in charge and shaped at the substrate-binding pocket entrance. The amino acid sequences and structures of the TsaBgl L1–4 loops were compared with other 45 Bgl proteins, and a diversity of the L2 and L3 loops was observed. Differences in amino acids and lengths of Bgls L2–L3 loop induced differences in the conformation and structure of the Bgls substrate-binding pocket entrance. These findings expand our knowledge on the molecular function of the loops in the Bgl enzyme family.

Dynamic Protonation States Underlie Carbene Formation in ThDP-Dependent Enzymes: A Theoretical Study.

The activation mechanism of thiamine diphosphate (ThDP) in enzymes has long been the subject of intense research and controversial discussion. Particularly contentious is the formation of a carbene intermediate, the first one observed in an enzyme. For the formation of the carbene to take place, both intramolecular and intermolecular proton transfer pathways have been proposed. However, the physiologically relevant pH of ThDP-dependent enzymes around neutrality does not seem to be suitable for the formation of such reactive chemical species. Herein, we investigate the general mechanism of activation of the ThDP cofactor in human transketolase (TKT), by means of electronic structure methods. We show that in the case of the human TKT, the carbene species is accessible through a pKa shift induced by the electrostatics of a neighboring histidine residue (H110), whose protonation state change modulates the pKa of ThDP and suppresses the latter by more than 6 pH units. Our findings highlight that ThDP enzymes activate the cofactor beyond simple geometric constraints and the canonical glutamate. Such observations in nature can pave the way for the design of biomimetic carbene catalysts and the engineering of tailored enzymatic carbenes.

Ligand steric effects of nano-inhibitors on Aβ fibrillation at the nano-bio interfaces

Amyloid-β (Aβ) fibrillation is a characteristic feature of Alzheimer's disease. Previous studies have identified several interfacial physicochemical factors, including charge, hydrophobicity, and chirality of multi-scaled biostructures, that determine Aβ fibrillation. However, the impact of ligand steric effects on the nano-bio structure in the Aβ fibrillation process remains unclear, which significantly hinders the development of highly efficient nano-inhibitors. Here we constructed four ligands (N-acetyl-L-cysteine (NAC), N-propionyl-L-cysteine (NPC), N-isobutyryl-L-cysteine (NIBC), and N-pivaloyl-L-cysteine (NPVC)) modified Cu2S quantum dots (QDs) with identical core-size (3.6 ± 0.6 nm) to investigate their respective ligand steric effects on Aβ40 fibrillation at nano-bio interface. Our results demonstrated that all four Cu2S QDs inhibited Aβ40 fibrillation in a dose-dependent manner, however, their inhibitory efficiency varied depending on the different steric structures of the ligands employed. NPC-Cu2S QDs exhibited the highest efficiency followed by NIBC-Cu2S QDs, NPVC-Cu2S QDs and NAC-Cu2S QDs at equivalent dosages. Mechanistic studies revealed that these differences in inhibitory efficiency were primarily attributed to the stereoselective interactions between the distinct steric ligands of Cu2S QDs and the electro-positive amino acid residues (R5, K16 and K28), as well as their neighboring residues within Aβ40 sequence. This work provides valuable insights into understanding the ligand steric effects of nano-inhibitors on Aβ fibrillation at nano-bio interfaces and offers guidance for precise regulation of protein fibrillation through customization of appropriate ligand groups.

The Molecular Mechanism of Positive Allosteric Modulation at the Dopamine D1 Receptor.

The dopamine D1 receptor (D1R) is a promising target for treating various psychiatric disorders. While upregulation of D1R activity has shown potential in alleviating motor and cognitive symptoms, orthosteric agonists have limitations, restricting their clinical applications. However, the discovery of several allosteric compounds specifically targeting the D1R, such as LY3154207, has opened new therapeutic avenues. Based on the cryo-EM structures of the D1R, we conducted molecular dynamics simulations to investigate the binding and allosteric mechanisms of LY3154207. Our simulations revealed that LY3154207 preferred the horizontal orientation above intracellular loop 2 (IL2) and stabilized the helical conformation of IL2. Moreover, LY3154207 binding induced subtle yet significant changes in key structural motifs and their neighboring residues. Notably, a cluster of residues centered around the Na+-binding site became more compact, while interactions involving the PIF motif and its neighboring residues were loosened upon LY3154207 binding, consistent with their role in opening the intracellular crevice for receptor activation. Additionally, we identified an allosteric pathway likely responsible for the positive allosteric effect of LY3154207 in enhancing Gs protein coupling. This mechanistic understanding of LY3154207's allosteric action at the D1R paves the way for the rational design of more potent and effective allosteric modulators.

Insights into the Enhancement of the Poly(ethylene terephthalate) Degradation by FAST-PETase from Computational Modeling.

Polyethylene terephthalate (PET) is the most abundant polyester plastic, widely used in textiles and packaging, but, unfortunately, it is also one of the most discarded plastics after one use. In the last years, the enzymatic biodegradation of PET has sparked great interest owing to the discovery and subsequent mutation of PETase-like enzymes, able to depolymerize PET. FAST-PETase is one of the best enzymes hitherto proposed to efficiently degrade PET, although the origin of its efficiency is not completely clear. To understand the molecular origin of its enhanced catalytic activity, we have carried out a thorough computational study of PET degradation by the FAST-PETase action by employing classical and hybrid (QM/MM) molecular dynamics (MD) simulations. Our findings show that the rate-limiting reaction step for FAST-PETase corresponds to the acylation stage with an estimated free energy barrier of 12.1 kcal mol-1, which is significantly smaller than that calculated for PETase (16.5 kcal mol-1) and, therefore, supports the enhanced catalytic activity of FAST-PETase. The origin of this enhancement is mainly attributed to the N233K mutation, which, although sited relatively far from the active site, induces a chain folding where the Asp206 of the catalytic triad is located, impeding that this residue sets effective H-bonds with its neighboring residues. This effect makes Asp206 hold a more basic character compared to the wild-type PETase and boosts the interaction with the protonated His237 of the catalytic triad in the transition state of acylation, with the consequent decrease of the catalytic barrier and acceleration of the PET degradation reaction.

Two point mutations in protocadherin-1 disrupt hantavirus recognition and afford protection against lethal infection

Andes virus (ANDV) and Sin Nombre virus (SNV) are the etiologic agents of severe hantavirus cardiopulmonary syndrome (HCPS) in the Americas for which no FDA-approved countermeasures are available. Protocadherin-1 (PCDH1), a cadherin-superfamily protein recently identified as a critical host factor for ANDV and SNV, represents a new antiviral target; however, its precise role remains to be elucidated. Here, we use computational and experimental approaches to delineate the binding surface of the hantavirus glycoprotein complex on PCDH1’s first extracellular cadherin repeat domain. Strikingly, a single amino acid residue in this PCDH1 surface influences the host species-specificity of SNV glycoprotein-PCDH1 interaction and cell entry. Mutation of this and a neighboring residue substantially protects Syrian hamsters from pulmonary disease and death caused by ANDV. We conclude that PCDH1 is a bona fide entry receptor for ANDV and SNV whose direct interaction with hantavirus glycoproteins could be targeted to develop new interventions against HCPS.

Gas Phase Fragmentation Behavior of Proline in Macrocyclic b7 Ions.

The fragmentation characteristics of b7 ions produced from proline-containing heptapeptides have been studied in detail. The study has utilized the following C-terminally amidated model peptides: PA6, APA5, A2PA4, A3PA3, A4PA2, A5PA, A6P, PYAGFLV, PAGFLVY, PGFLVYA, PFLVYAG, PLVYAGF, PVYAGFL, YPAGFLV, YAPGFLV, YAGPFLV, YAGFPLV, YAGFLPV, YAGFLVP, PYAFLVG, PVLFYAG, A2PXA3, and A2XPA3 (where X = C, D, F, G, L, V, and Y, respectively). The results have shown that b7 ions undergo head-to-tail cyclization and form a macrocyclic structure. Under the collision-induced dissociation (CID) condition, it generates nondirect sequence ions regardless of the position of the proline and the neighboring amino acid residues. This study highlights the unusual and unique fragmentation behavior of proline-containing heptapeptides. Following the head-to-tail cyclization, the ring opens up and places the proline residue in the N-terminal position while forming a regular oxazolone form of b2 ions for all peptide series. Then, the fragmentation reaction pathway is followed by the elimination of proline with its C-terminal neighbor residue as an oxazolone (e.g., PXoxa) for all proline-containing peptide series.

Modulation of Functional Phosphorylation Sites by Basic Residues in the Unique Domain of c-Src.

In contrast to the well-studied canonical regulatory mechanisms, the way by which the recently discovered Src N-terminal regulatory element (SNRE) modulates Src activity is not yet well understood. Phosphorylation of serine and threonine residues modulates the charge distribution along the disordered region of the SNRE and may affect a fuzzy complex with the SH3 domain that is believed to act as an information transduction element. The pre-existing positively charged sites can interact with the newly introduced phosphate groups by modulating their acidity, introducing local conformational restrictions, or by coupling various phosphosites into a functional unit. In this paper, we use pH-dependent NMR measurements combined with single point mutations to identify the interactions of basic residues with physiologically important phosphorylated residues and to characterize the effect of these interactions in neighbor residues, thus providing insight into the electrostatic network in the isolated disordered regions and in the entire SNRE. From a methodological point of view, the linear relationships observed between the mutation-induced pKa changes of the phosphate groups of phosphoserine and phosphothreonine and the pH-induced chemical shifts of the NH groups of these residues provide a very convenient alternative to identify interacting phosphate groups without the need to introduce point mutations on specific basic residues.

3D interaction homology: The hydrophobic residues alanine, isoleucine, leucine, proline and valine play different structural roles in soluble and membrane proteins.

The aliphatic hydrophobic amino acid residues-alanine, isoleucine, leucine, proline and valine-are among the most common found in proteins. Their structural role in proteins is seemingly obvious: engage in hydrophobic interactions to stabilize secondary, and to a lesser extent, tertiary and quaternary structure. However, favorable hydrophobic interactions involving the sidechains of these residue types are generally less significant than the unfavorable set arising from interactions with polar atoms. Importantly, the constellation of interactions between residue sidechains and their environments can be recorded as three-dimensional maps that, in turn, can be clustered. The clustered average map sets compose a library of interaction profiles encoding interaction strengths, interaction types and the optimal 3D position for the interacting partners. This library is backbone angle-dependent and suggests solvent and lipid accessibility for each unique interaction profile. In this work, in addition to analysis of soluble proteins, a large set of membrane proteins that contained optimized artificial lipids were evaluated by parsing the structures into three distinct components: soluble extramembrane domain, lipid facing transmembrane domain, core transmembrane domain. The aliphatic residues were extracted from each of these sets and passed through our calculation protocol. Notable observations include: the roles of aliphatic residues in soluble proteins and in the membrane protein's soluble domains are nearly identical, although the latter are slightly more solvent accessible; by comparing maps calculated with sidechain-lipid interactions to maps ignoring those interactions, the potential extent of residue-lipid and residue-interactions can be assessed and likely exploited in structure prediction and modeling; amongst these residue types, the levels of lipid engagement show isoleucine as the most engaged, while the other residues are largely interacting with neighboring helical residues.