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Supporting Information: The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/jacsau.2c00358. MD and SMD simulation parameters, data analysis details of all 50 replicas of SMD simulations, all pre-processed simulation trajectories, and data analysis scripts available at https://unmm-my.sharepoint.com/:f:/g/personal/yihe_unm_edu/EqwwWVZFiTJCmhAXnVCCHkwBgmyDGObyy_F60RJyZKgzFQ?e=rnMbfN (PDF). Copyright © 2022 The Authors. The dynamic association and dissociation between proteins are the basis of cellular signal transduction. This process becomes much more complicated if one or both interaction partners are intrinsically disordered because intrinsically disordered proteins can undergo disorder-to-order transitions upon binding to their partners. p53, a transcription factor with disordered regions, plays significant roles in many cellular signaling pathways. It is critical to understand the binding/unbinding mechanism involving these disordered regions of p53 at the residue level to reveal how p53 performs its biological functions. Here, we studied the dissociation process of the intrinsically disordered N-terminal transactivation domain 2 (TAD2) of p53 and the transcriptional adaptor zinc-binding 2 (Taz2) domain of transcriptional coactivator p300 using a combination of classical molecular dynamics, steered molecular dynamics, self-organizing maps, and time-resolved force distribution analysis (TRFDA). We observed two different dissociation pathways with different probabilities. One dissociation pathway starts from the TAD2 N-terminus and propagates to the α-helix and finally the C-terminus. The other dissociation pathway is in the opposite order. Subsequent TRFDA results reveal that key residues in TAD2 play critical roles. Besides the residues in agreement with previous experimental results, we also highlighted some other residues that play important roles in the disassociation process. In the dissociation process, non-native interactions were formed to partially compensate for the energy loss due to the breaking of surrounding native interactions. Moreover, our statistical analysis results of other experimentally determined complex structures involving either Taz2 or TAD2 suggest that the binding of the Taz2-TAD2 complex is mainly governed by the binding site of Taz2, which includes three main binding regions. Therefore, the complexes involving Taz2 may follow similar binding/unbinding behaviors, which could be studied together to generate common principles. National Science Foundation Graduate Research Fellowship Program (grant no. DGE1939267); the National Science Foundation (grant no. 2137558); Leverhulme Trust (RPG-2017-222); Substance Use Disorders Grand Challenge Pilot Research Award; Research Allocations Committee (RAC) Award; the startup fund from the University of New Mexico; the University of New Mexico Office of the Vice President for Research WeR1 Faculty Success Program.

© 2021 The Authors. Allosteric drugs have been attracting increasing interest over the past few years. In this context, it is common practice to use high-throughput screening for the discovery of non-natural allosteric drugs. While the discovery stage is supported by a growing amount of biological information and increasing computing power, major challenges still remain in selecting allosteric ligands and predicting their effect on the target protein’s function. Indeed, allosteric compounds can act both as inhibitors and activators of biological responses. Computational approaches to the problem have focused on variations on the theme of molecular docking coupled to molecular dynamics with the aim of recovering information on the (long-range) modulation typical of allosteric proteins. AIRC IG 2017 - ID. 20019 project; AIRC Fellowship; EC Research Innovation Action H2020 Programme Project HPC-EUROPA3 (INFRAIA-2016-1-730897)

© 2021 The Authors. Several experimental studies indicated that large conformational changes, including partial domain unfolding, have a role in the functional mechanisms of the basic helix loop helix Per/ARNT/SIM (bHLH-PAS) transcription factors. Recently, single-molecule atomic force microscopy (AFM) revealed two distinct pathways for the mechanical unfolding of the ARNT PAS-B. In this work we used steered molecular dynamics simulations to gain new insights into this process at an atomistic level. To reconstruct and classify pathways sampled in multiple simulations, we designed an original approach based on the use of self-organizing maps (SOMs). This led us to identify two types of unfolding pathways for the ARNT PAS-B, which are in good agreement with the AFM findings. Analysis of average forces mapped on the SOM revealed a stable conformation of the PAS-B along one pathway, which represents a possible structural model for the intermediate state detected by AFM. The approach here proposed will facilitate the study of other signal transmission mechanisms involving the folding/unfolding of PAS domains. National Institutes of Environmental Health Sciences (R01-ES007685); Leverhulme Trust (RPG-2017-222).

Phosphorylation ofEscherichia coliCheY protein transduces chemoreceptor stimulation to a highly cooperative flagellar motor response. CheY binds to the N-terminal peptide of the FliM motor protein (FliMN). Constitutively active D13K-Y106W CheY has been an important tool for motor physiology. The crystal structures of CheY and CheY.FliMNwith and without D13K-Y106W have shown FliMNbound CheY contains features of both active and inactive states. We used molecular dynamics (MD) simulations to characterize the CheY conformational landscape accessed by FliMNand D13K-Y106W. Mutual information measures identified the central features of the long-range CheY allosteric network between D13K at the D57 phosphorylation site and Y/W106 at the FliMNinterface; namely the closure of the α4-β4 hinge and inward rotation of Y/W106 with W58. We used hydroxy-radical foot-printing with mass spectroscopy (XFMS) to track the solvent accessibility of these and other sidechains. The solution XFMS oxidation rate correlated with the solvent-accessible area of the crystal structures. The protection of allosteric relay sidechains reported by XFMS confirmed the intermediate conformation of the native CheY.FliMNcomplex, the inactive state of free D13K-Y106W CheY and the MD-based network architecture. We extended the MD analysis to determine temporal coupling and energetics during activation. Coupled aromatic residue rotation was a graded rather than a binary switch with Y/W106 sidechain burial correlated with increased FliMNaffinity. Activation entrained CheY fold stabilization to FliMNaffinity. The CheY network could be partitioned into four dynamically coordinated community sectors. Residue substitutions mapped to sectors around D57 or the FliMNinterface according to phenotype. FliMNincreased sector size and interactions. These sectors fused between the substituted K13K-W106 residues to organize a tightly packed core and novel surfaces that may bind additional sites to explain the cooperative motor response. The community maps provide a more complete description of CheY priming than proposed thus far.Statement of SignificanceCheY affinity for FliMN, its binding target at the flagellar motor, is increased by phosphorylation to switch rotation sense. Atomistic simulations based on CheY and CheY.FliMNcrystal structures with and without the phospho-mimetic double substitution (D13K-Y106W) showed CheY compaction is entrained to increased FliMNaffinity. Burial of exposed aromatic sidechains drove compaction, as validated by tracking sidechain solvent accessibility with hydroxyl-radical foot-printing. The substitutions were localized at the phosphorylation pocket (D13K) and FliMNinterface (Y106W). Mutual information measures revealed these locations were allosterically coupled by a specialized conduit when the conformational landscape of FliMN-tethered CheY was modified by the substitutions. Novel surfaces stabilized by the conduit may bind additional motor sites, essential for the high cooperativity of the flagellar switch.

Copyright © 2022 The Author(s). Understanding the process of ligand–protein recognition is important to unveil biological mechanisms and to guide drug discovery and design. Enhanced-sampling molecular dynamics is now routinely used to simulate the ligand binding process, resulting in the need for suitable tools for the analysis of large data sets of binding events. Here, we designed, implemented, and tested PathDetect-SOM, a tool based on self-organizing maps to build concise visual models of the ligand binding pathways sampled along single simulations or replicas. The tool performs a geometric clustering of the trajectories and traces the pathways over an easily interpretable 2D map and, using an approximate transition matrix, it can build a graph model of concurrent pathways. The tool was tested on three study cases representing different types of problems and simulation techniques. A clear reconstruction of the sampled pathways was derived in all cases, and useful information on the energetic features of the processes was recovered. The tool is available at https://github.com/MottaStefano/PathDetect-SOM. Leverhulme Trust (An integrated computational-experimental method to redesign protein dynamics, RPG-2017-222).

Signalling through TNFR1 modulates proinflammatory gene transcription and programmed cell death, and its impairment causes autoimmune diseases and cancer. NEDD4-binding protein 1 (N4BP1) was recently identified as a critical suppressor of proinflammatory cytokine production1, whose mode of action remained unknown. Here, we show that N4BP1 is a novel linear ubiquitin reader that negatively regulates NFκB signalling by its unique dimerizationdependent ubiquitin-binding module that we named LUBIN. Dimeric N4BP1 strategically positions two non-selective ubiquitin-binding domains to ensure exclusive recognition of linear ubiquitin. Under proinflammatory conditions, N4BP1 is recruited to the nascent TNFR1 signalling complex, where it regulates duration of proinflammatory signalling in LUBIN-dependent manner. N4BP1 deficiency accelerates TNFα-induced cell death by increasing complex II assembly. Under proapoptotic conditions, Caspase-8 mediates proteolytic processing of N4BP1 and the resulting cleavage fragment of N4BP1, which retains the ability to bind linear ubiquitin, is rapidly degraded by the 26S proteasome, accelerating apoptosis. In summary, our findings demonstrate that N4BP1 dimerization creates a unique linear ubiquitin reader that ensures timely and coordinated regulation of TNFR1-mediated inflammation and cell death.

Data availability statement: The trajectories of Mpro simulations and models of the metastable states can be downloaded from 10.5281/zenodo.4782284. β-coronavirus (CoVs) alone has been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a backup against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensable role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand–protein interactions. Herein, we provide a comprehensive comparison of all nonredundant ligand-binding sites available for SARS-CoV2, SARS-CoV, and MERS-CoV Mpro. Extensive adaptive sampling has been used to investigate structural conservation of ligand-binding sites using Markov state models (MSMs) and compare conformational dynamics employing convolutional variational auto-encoder-based deep learning. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across β-CoV homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor. There was no funding for this work

This article is a preprint and has not been certified by peer review. It was eventually published online on 14 June 2021 by American Chemical Society (ACS Publications) as: Cho, E. et al. (2021) 'Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites', Journal of Chemical Information and Modeling, 61 (6), pp. 3058 - 3073. doi: 10.1021/acs.jcim.1c00449. Data Availability Statement: The trajectories of Mpro simulations and models of the metastable states can be obtained from the corresponding author. Jupyter-notebooks to generate Markov State Models can be downloaded from 10.6084/m9.figshare.14343725 bioRxiv posts many COVID19-related papers. A reminder: they have not been formally peer-reviewed and should not guide health-related behavior or be reported in the press as conclusive. β-coronaviruses alone have been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a back-up against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensible role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand-protein interactions. Herein, we provide a comprehensive comparison of all non-redundant ligand-binding sites available for SARS-CoV2, SARS-CoV and MERS-CoV Mpro. Extensive adaptive sampling has been used to explore conformational dynamics employing convolutional variational auto encoder-based deep learning, and investigates structural conservation of the ligand binding sites using Markov state models across β-coronavirus homologs. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across β-coronavirus homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor. U.S. Department of Energy, Office of Science, through the Advanced Scientific Computing Research (ASCR), under contract number DEAC05-00OR22725 and the Exascale Computing Project (ECP) (17-SC-20-SC). BI would like to acknowledge the COVID-19 pump-priming grant from the University of Huddersfield for funding computing resources for analysis.

Glycosylation of secondary metabolites involves plant UDP-dependent glycosyltransferases (UGTs). UGTs have shown promise as catalysts in the synthesis of glycosides for medical treatment. However, limited understanding at the molecular level due to insufficient biochemical and structural information has hindered potential applications of most of these UGTs. In the absence of experimental crystal structures, we employed advanced molecular modelling and simulations in conjunction with biochemical characterisation to design a workflow to study five Group H Arabidopsis thaliana (76E1, 76E2, 76E4, 76E5, 76D1) UGTs. Based on our rational structural manipulation and analysis, we identified key amino acids (P129 in 76D1; D374 in 76E2; K275 in 76E4), which when mutated improved donor-substrate recognition than wildtype UGTs. Molecular dynamics simulations and deep learning analysis identified structural differences, which drive substrate preferences. The design of these UGTs with broader substrate specificity may play important role in biotechnological and industrial applications. These findings can also serve as basis to study other plant UGTs and thereby advancing UGT enzyme engineering. Federal Scholarship Board/Presidential Special Scholarship Scheme for Innovation and Development (PRESSID), Nigeria; Sichuan Science and Technology Program

Motivation A deleterious amino acid change in a protein can be compensated by a second-site rescue mutation. These compensatory mechanisms can be mimicked by drugs. In particular, the location of rescue mutations can be used to identify protein regions that can be targeted by small molecules to reactivate a damaged mutant. Results We present the first general computational method to detect rescue sites. By mimicking the effect of mutations through the application of forces, the double force scanning (DFS) method identifies the second-site residues that make the protein structure most resilient to the effect of pathogenic mutations. We tested DFS predictions against two datasets containing experimentally validated and putative evolutionary-related rescue sites. A remarkably good agreement was found between predictions and experimental data. Indeed, almost half of the rescue sites in p53 was correctly predicted by DFS, with 65% of remaining sites in contact with DFS predictions. Similar results were found for other proteins in the evolutionary dataset. Availability and implementation The DFS code is available under GPL at https://fornililab.github.io/dfs/ Supplementary information Supplementary data are available at Bioinformatics online.

Proteins are large, complex molecules with crucial roles in the functioning of living organisms. Understanding the underlying mechanisms by which proteins achieve their structures and substructures, as well as those involved in the conformational transitions may contribute to a deeper comprehension of the involved biological processes. This paper investigates a new machine learning perspective upon analyzing protein conformational transitions and introduces a new formalization for the problem, with the more general goal of uncovering interesting patterns in protein conformational transitions. This study represents the starting point of a research which is being conducted in order to obtain a better comprehension of proteins’ structures and, implicitly, functions, by investigating computational intelligence methods for analyzing and deducing proteins conformational transitions.

The calcium calmodulin-dependent protein kinase II (CaMKII) is a dodecameric holoenzyme important for encoding memory. Its activation, triggered by binding of calcium-calmodulin, persists autonomously after calmodulin dissociation. One (receiver) kinase captures and subsequently phosphorylates the regulatory domain peptide of a donor kinase forming a chained dimer as the first stage of autonomous activation. Protein dynamics simulations examined the conformational changes triggered by dimer formation and phosphorylation, aimed to provide a molecular rationale for human mutations that result in learning disabilities. Ensembles generated from X-ray crystal structures were characterized by network centrality and community analysis. Mutual information related collective motions to local fragment dynamics encoded with a structural alphabet. Implicit solvent tCONCOORD conformational ensembles revealed the dynamic architecture of inactive kinase domains was co-opted in the activated dimer but the network hub shifted from the nucleotide binding cleft to the captured peptide. Explicit solvent molecular dynamics (MD) showed nucleotide and substrate binding determinants formed coupled nodes in long-range signal relays between regulatory peptides in the dimer. Strain in the extended captured peptide was balanced by reduced flexibility of the receiver kinase C-lobe core. The relays were organized around a hydrophobic patch between the captured peptide and a key binding helix. The human mutations aligned along the relays. Thus, these mutations could disrupt the allosteric network alternatively, or in addition, to altered binding affinities. Non-binding protein sectors distant from the binding sites mediated the allosteric signalling; providing possible targets for inhibitor design. Phosphorylation of the peptide modulated the dielectric of its binding pocket to strengthen the patch, non-binding sectors, domain interface and temporal correlations between parallel relays. These results provide the molecular details underlying the reported positive kinase cooperativity to enrich the discussion on how autonomous activation by phosphorylation leads to long-term behavioural effects., Author summary Protein kinases play central roles in intracellular signalling. Auto-phosphorylation by bound nucleotide typically precedes phosphate transfer to multiple substrates. Protein conformational changes are central to kinase function, altering binding affinities to change cellular location and shunt from one signal pathway to another. In the brain, the multi-subunit kinase, CaMKII is activated by calcium-calmodulin upon calcium jumps produced by synaptic stimulation. Auto-transphosphorylation of a regulatory peptide enables the kinase to remain activated and mediate long-term behavioural effects after return to basal calcium levels. A database of mutated residues responsible for these effects is difficult to reconcile solely with impaired nucleotide or substrate binding. Therefore, we have computationally generated interaction networks to map the conformational plasticity of the kinase domains where most mutations localize. The network generated from the atomic structure of a phosphorylated dimer resolves protein sectors based on their collective motions. The sectors link nucleotide and substrate binding sites in self-reinforcing relays between regulatory peptides. The self-reinforcement is strengthened by phosphorylation consistent with the reported positive cooperativity of kinase activity with calcium-calmodulin concentration. The network gives a better match with the mutations and, in addition, reveals target sites for drug development.

Hypoxia inducible factors (HIFs) are transcription factors belonging to the basic helix−loop−helix PER-ARNT-SIM (bHLH-PAS) protein family with a role in sensing oxygen levels in the cell. Under hypoxia, the HIF-α degradation pathway is blocked and dimerization with the aryl hydrocarbon receptor nuclear translocator (ARNT) makes HIF-α transcriptionally active. Due to the common hypoxic environment of tumors, inhibition of this mechanism by destabilization of HIF-α:ARNT dimerization has been proposed as a promising therapeutic strategy. Following the discovery of a druggable cavity within the PAS-B domain of HIF-2α, research efforts have been directed to identify artificial ligands that can impair heterodimerization. Although the crystallographic structures of the HIF-2α:ARNT complex have elucidated the dimer architecture and the 0X3-inhibitor placement within the HIF-2α PAS-B, unveiling the inhibition mechanism requires investigation of how ligand-induced perturbations could dynamically propagate through the structure and affect dimerization. To this end, we compared evolutionary features, intrinsic dynamics and energetic properties of the dimerization interfaces of HIF-2α:ARNT in both the apo and holo forms. Residue conservation analysis highlighted inter-domain connecting elements that have a role in dimerization. Analysis of domain contributions to the dimerization energy demonstrated the importance of bHLH and PAS-A of both partners and of HIF-2α PAS-B domain in dimer stabilization. Among quaternary structure oscillations revealed by Molecular Dynamics simulations, the hinge-bending motion of the ARNT PAS-B domain around the flexible PAS-A/PAS-B linker supports a general model for ARNT dimerization in different heterodimers. Comparison of the HIF-2α:ARNT dynamics in the apo and 0X3-bound forms indicated a model of inhibition where the HIF-2α-PAS-B interfaces are destabilised as a result of water-bridged ligand-protein interactions and these local effects allosterically propagate to perturb the correlated motions of the domains and inter-domain communication. These findings will guide the design of improved inhibitors to contrast cell survival in tumor masses., Author summary A low oxygen condition, called hypoxia, often occurs in tumor masses and generally correlates with worse prognosis. Cells in a tumor react to low oxygen levels with a metabolism modification induced by the activation of hypoxia inducible factors (HIFs) through dimerization with a partner protein and binding to a DNA target. Disrupting this protein-protein interaction could be a potential therapeutic strategy, but directly interfering with dimer formation can be troublesome because of the difficulty to design drugs that bind to protein interfaces. However, ligands that bind internal protein cavities can indirectly perturb the interfaces reducing dimers stability. Albeit protein crystallography had offered a detailed static picture of a HIF dimer bound to candidate inhibitors, it is not able to describe either the perturbation caused by binding or the molecular mechanism of dimer destabilization. Here we exploit molecular dynamics to identify the crucial interfaces in the HIF dimer stabilization and, by comparing the results obtained in the bound and unbound forms, we reveal the mechanism of ligand inhibition at atomic detail. All these findings will guide toward the design of improved dimerization inhibitors, to contrast cell survival in tumor masses.

The proton-driven ATP synthase (FoF1) is comprised of two rotary, stepping motors (Fo and F1) coupled by an elastic power transmission. The elastic compliance resides in the rotor module that includes the membrane-embedded FO c-ring. Proton transport by FO is firmly coupled to the rotation of the c-ring relative to other FO subunits (ab2). It drives ATP synthesis. We used a computational method to investigate the contribution of the c-ring to the total elastic compliance. We performed principal component analysis of conformational ensembles built using distance constraints from the bovine mitochondrial c-ring X-ray structure. Angular rotary twist, the dominant ring motion, was estimated to show that the c-ring accounted in part for the measured compliance. Ring rotation was entrained to rotation of the external helix within each hairpin-shaped c-subunit in the ring. Ensembles of monomer and dimers extracted from complete c-rings showed that the coupling between collective ring and the individual subunit motions was independent of the size of the c-ring which varies between organisms. Molecular determinants were identified by covariance analysis of residue co-evolution and a structural alphabet based local dynamics correlations. The residue co-evolution gave a read-out of subunit architecture. The dynamic couplings revealed that the hinge for both ring and subunit helix rotations was constructed from the proton-binding site and the adjacent glycine motif (IB-GGGG) in the mid-membrane plane. IB-GGGG motifs were linked by long-range couplings across the ring, while intra-subunit couplings connected the motif to the conserved cytoplasmic loop and adjacent segments. The correlation with principal collective motions shows that the couplings underlie both ring rotary and bending motions. Non-contact couplings between IB-GGGG motifs matched the co-evolution signal as well as contact couplings. The residue co-evolution reflects the physiological importance of the dynamics that may link proton transfer to ring compliance.

The study of protein dynamics through analysis of conformational transitions represents a significant stage in understanding protein function. Using molecular simulations, large samples of protein transitions can be recorded. However, extracting functional motions from these samples is still not automated and extremely time-consuming. In this paper we investigate the usefulness of unsupervised machine learning methods for uncovering relevant information about protein functional dynamics. Autoencoders are being explored in order to highlight their ability to learn relevant biological patterns, such as structural characteristics. This study is aimed to provide a better comprehension of how protein conformational transitions are evolving in time, within the larger framework of automatically detecting functional motions.

Molecular dynamics simulations examined how single transphosphorylation between adjacent subunits of calcium calmodulin dependent protein kinase II (CaMKII) effects conformational coupling. One (receiver) kinase captures and phosphorylates the regulatory domain of a donor kinase forming a chained dimer. Identified substrate binding sequences formed nodes in long-range, parallel signal relays linking regulatory peptides in adjacent subunits. Monomer subunit architecture was co-opted in the auto-phosphorylating dimer but the community hub shifted from the nucleotide binding pocket to a hydrophobic cluster between the captured peptide and a key helix in its binding pocket. Phosphorylation of this peptide modulated the dielectric of the pocket to reduce helix flexibility and collective motions of the receiver kinase domain. The signal relay was strengthened with phosphorylationdependent conformational transitions completed within hundred nanoseconds. The network couplings should guide allosteric inhibitor design. Chained dimers, in addition to intra-holoenzyme spread, may facilitate exchange between holoenzymes to prolong activated population lifetimes.

Aim of this work is to assess the informativeness of protein dynamics in the detection of similarities among distant homologous proteins. To this end, an approach to perform large-scale comparisons of protein domain flexibilities is proposed. CONCOORD is confirmed as a reliable method for fast conformational sampling. The root mean square fluctuation of alpha carbon positions in the essential dynamics subspace is employed as a measure of local flexibility and a synthetic index of similarity is presented. The dynamics of a large collection of protein domains from ASTRAL/SCOP40 is analyzed and the possibility to identify relationships, at both the family and the superfamily levels, on the basis of the dynamical features is discussed. The obtained picture is in agreement with the SCOP classification, and furthermore suggests the presence of a distinguishable familiar trend in the flexibility profiles. The results support the complementarity of the dynamical and the structural information, suggesting that information from dynamics analysis can arise from functional similarities, often partially hidden by a static comparison. On the basis of this first test, flexibility annotation can be expected to help in automatically detecting functional similarities otherwise unrecoverable. © 2007 The Author(s).

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that is activated by a structurally diverse array of synthetic and natural chemicals, including toxic halogenated aromatic hydrocarbons such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Analysis of the occurring in the AhR ligand binding and activation processes requires structural information on the AhR Per-Arnt-Sim (PAS) B-containing ligand binding domain, for which no experimentally determined structure has been reported. With the availability of extensive structural information on homologous PAS-containing proteins, a reliable model of the mouse AhR PAS B domain was developed by comparative modeling techniques. The PAS domain structures of the functionally related hypoxia-inducible factor 2α (HIF-2α) and AhR nuclear translocator (ARNT) proteins, which exhibit the highest degree of sequence identity and similarity with AhR, were chosen to develop a two-template model. To confirm the features of the modeled domain, the effects of point mutations in selected residue positions on both TCDD binding to the AhR and TCDD-dependent transformation and DNA binding were analyzed. Mutagenesis and functional analysis results are consistent with the proposed model and confirm that the cavity modeled in the interior of the domain is indeed involved in ligand binding. Moreover, the physicochemical characteristics of some residues and of their mutants, along with the effects of mutagenesis on TCDD and DNA binding, also suggest some key features that are required for ligand binding and activation of mAhR at a molecular level, thus providing a framework for further studies. © 2007 American Chemical Society.

Computational approaches based on Molecular Dynamics simulations, Quantum Mechanical methods and 3D Quantitative Structure-Activity Relationships were employed by computational chemistry groups at the University of Milano-Bicocca to study biological processes at the molecular level. The paper reports the methodologies adopted and the results obtained on Aryl hydrocarbon Receptor and homologous PAS proteins mechanisms, the properties of prion protein peptides, the reaction pathway of hydrogenase and peroxidase enzymes and the defibrillogenic activity of tetracyclines. © Springer-Verlag 2007.

The PAS (Per-ARNT-Sim) superfamily is presented as a well-suited study case to demonstrate how comparison of functional motions among distant homologous proteins with conserved fold characteristics may give insight into their functional specialization. Based on the importance of structural flexibility of the receptive structures in anticipating the signal-induced conformational changes of these sensory systems, the dynamics of these structures were analysed. Molecular dynamics was proved to be an effective method to obtain a reliable picture of the dynamics of the crystal structures of HERG, phy3, PYP and FixL, provided that an extensive conformational space sampling is performed. Other reliable sources of dynamic information were the ensembles of NMR structures of hPASK, HIF-2α and PYP. Essential dynamics analysis was successfully employed to extract the relevant information from the sampled conformational spaces. Comparison of motion patterns in the essential subspaces, based on the structural alignment, allowed identification of the specialized region in each domain. This appears to be evolved in the superfamily by following a specific trend, that also suggests the presence of a limited number of general solutions adopted by the PAS domains to sense external signals. These findings may give insight into unknown mechanisms of PAS domains and guide further experimental studies. © The Author 2005. Published by Oxford University Press. All rights reserved.

IntroductionConformational changes associated with protein function often occur at timescales inaccessible to unbiased Molecular Dynamics (MD) simulations, consequently different approaches have been developed to accelerate their sampling. Here we investigate how the knowledge of backbone conformations preferentially adopted by protein fragments, as contained in pre-calculated libraries known as Structural Alphabets (SA)[1], can be used to explore the landscape of global protein conformations in MD simulations.MethodsSAs were successfully used to analyze protein dynamics after simulation[2,3]. Here we define a novel SA-based Collective Variable (CVSA) to bias the sampling of backbone conformations of protein fragments towards experimentally preferred local states[4].ResultsWe find that: a) Enhancing the sampling of native local states allows recovery of global folded states, both in Metadynamics and in Steered MD, when the local states are encoded by strings of SA letters derived from the native structures. b) Global folded states are still recovered when the information on the native local states is reduced by using a low-resolution SA, where the original letters are clustered into macrostates. The macrostates provide the approximate shape of the fragments, while sampling with the atomistic force field allows the structure to adopt the native conformation of the specific amino acid sequence. c) SA strings derived from collections of structural motifs can be effectively used to sample alternative conformations of pre-selected regions. These findings have potential impact on a wide range of applications, from protein model refinement to folding and design.References1. Pandini A., Fornili A., Kleinjung J., BMC Bioinformatics 11:97 (2010).2. Pandini A., Fornili A., Fraternali F., Kleinjung J., FASEB J. 26:868 (2012).3. Pandini A., Fornili A., Fraternali F., Kleinjung J., Bioinformatics 29:2053 (2013).4. Pandini A., Fornili A., submitted.

Switching of bacterial flagellar rotation is caused by large domain movements of the FliG protein triggered by binding of the signal protein CheY to FliM. FliG and FliM form adjacent multi-subunit arrays within the basal body C-ring. The movements alter the interaction of the FliG C-terminal (FliGC) "torque" helix with the stator complexes. Atomic models based on the Salmonella entrovar C-ring electron microscopy reconstruction have implications for switching, but lack consensus on the relative locations of the FliG armadillo (ARM) domains (amino-terminal (FliGN), middle (FliGM) and FliGC) as well as changes during chemotaxis. The generality of the Salmonella model is challenged by the variation in motor morphology and response between species. We studied coevolved residue mutations to determine the unifying elements of switch architecture. Residue interactions, measured by their coevolution, were formalized as a network, guided by structural data. Our measurements reveal a common design with dedicated switch and motor modules. The FliM middle domain (FliMM) has extensive connectivity most simply explained by conserved intra and inter-subunit contacts. In contrast, FliG has patchy, complex architecture. Conserved structural motifs form interacting nodes in the coevolution network that wire FliMM to the FliGC C-terminal, four-helix motor module (C3-6). FliG C3-6 coevolution is organized around the torque helix, differently from other ARM domains. The nodes form separated, surface-proximal patches that are targeted by deleterious mutations as in other allosteric systems. The dominant node is formed by the EHPQ motif at the FliMMFliGM contact interface and adjacent helix residues at a central location within FliGM. The node interacts with nodes in the N-terminal FliGc α-helix triad (ARM-C) and FliGN. ARM-C, separated from C3-6 by the MFVF motif, has poor intra-network connectivity consistent with its variable orientation revealed by structural data. ARM-C could be the convertor element that provides mechanistic and species diversity. JK was supported by Medical Research Council grant U117581331. SK was supported by seed funds from Lahore University of Managment Sciences (LUMS) and the Molecular Biology Consortium.

M10 is the most C-terminal immunoglobulin (Ig) domain of the giant protein titin and a frequent target of disease-linked mutations. Currently, it is the only known muscle Ig domain able to interact with two alternative ligands-obscurin and obscurin-like-1 (Obsl1)-in different sarcomeric subregions. Obscurin and Obsl1 use their homologous N-terminal Ig domain (O1 in obscurin and OL1 in Obsl1) to bind M10 in a mutually exclusive manner. We present here the X-ray structure of the human titin:obscurin M10:O1 complex extending our previous work on the M10:OL1 interaction. Similar to M10:OL1, the M10:O1 complex displays a chevron-shaped antiparallel Ig-Ig architecture held together by a conserved molecular interface, which we validated by isothermal titration calorimetry and sorting experiments in neonatal rat cardiomyocytes. O1, although structurally related to OL1 and M10, both members of the intermediate set (I-set) Ig family, presents an intriguing switch of its βA' strand. This leads to structural differences between the complexes, particularly for the “open side“ of the chevron-shaped assembly. A bioinformatics analysis reveals that the βA'-switch observed for O1 is rare and that it is involved in mediating protein-protein interactions. Molecular dynamics simulations also suggest that this topological alteration substantially increases local flexibility compared to the conventional I-set Ig domains. The O1/OL1 Ig domains are candidate discriminatory structural modules potentially directing the binding of specific additional partners at the M-band. Cellular sorting experiments in neonatal rat cardiomyocytes are consistent with the view that the titin:obscurin/Obsl1 complexes might be a platform for higher-order interactions. This work was supported by a British Heart Foundation grant PG/10/67/28527 awarded to R.A.S. and M.G.

Patients with chronic myeloid leukemia in whom tyrosine kinase inhibitors (TKIs) fail often present mutations in the BCR-ABL catalytic domain. We noticed a lack of substitutions involving 4 amino acids (E286, M318, I360, and D381) that form hydrogen bonds with ponatinib. We therefore introduced mutations in each of these residues, either preserving or altering their physicochemical properties. We found that E286, M318, I360, and D381 are dispensable for ABL and BCR-ABL protein stability but are critical for preserving catalytic activity. Indeed, only a "conservative" I360T substitution retained kinase proficiency and transforming potential. Molecular dynamics simulations of BCR-ABLI360T revealed differences in both helix αC dynamics and protein-correlated motions, consistent with a modified ATP-binding pocket. Nevertheless, this mutant remained sensitive to ponatinib, imatinib, and dasatinib. These results suggest that changes in the 4 BCR-ABL residues described here would be selected against by a lack of kinase activity or by maintained responsiveness to TKIs. Notably, amino acids equivalent to those identified in BCR-ABL are conserved in 51% of human tyrosine kinases. Hence, these residues may represent an appealing target for the design of pharmacological compounds that would inhibit additional oncogenic tyrosine kinases while avoiding the emergence of resistance due to point mutations. This work was supported by an investigator grant to P.V. from Associazione Italiana per la Ricerca sul Cancro (AIRC) and by funding from the Biotechnology and Biological Sciences Research Council (BB/I023291/1 and BB/H018409/1 to AP and FF). P.B. is the recipient of an AIRC - Marie Curie fellowship.

The ability to interact with different partners is one of the most important features in proteins. Proteins that bind a large number of partners (hubs) have been often associated with intrinsic disorder. However, many examples exist of hubs with an ordered structure, and evidence of a general mechanism promoting promiscuity in ordered proteins is still elusive. An intriguing hypothesis is that promiscuous binding sites have specific dynamical properties, distinct from the rest of the interface and pre-existing in the protein isolated state. Here, we present the first comprehensive study of the intrinsic dynamics of promiscuous residues in a large protein data set. Different computational methods, from coarse-grained elastic models to geometry-based sampling methods and to full-atom Molecular Dynamics simulations, were used to generate conformational ensembles for the isolated proteins. The flexibility and dynamic correlations of interface residues with a different degree of binding promiscuity were calculated and compared considering side chain and backbone motions, the latter both on a local and on a global scale. The study revealed that (a) promiscuous residues tend to be more flexible than nonpromiscuous ones, (b) this additional flexibility has a higher degree of organization, and (c) evolutionary conservation and binding promiscuity have opposite effects on intrinsic dynamics. Findings on simulated ensembles were also validated on ensembles of experimental structures extracted from the Protein Data Bank (PDB). Additionally, the low occurrence of single nucleotide polymorphisms observed for promiscuous residues indicated a tendency to preserve binding diversity at these positions. A case study on two ubiquitin-like proteins exemplifies how binding promiscuity in evolutionary related proteins can be modulated by the fine-tuning of the interface dynamics. The interplay between promiscuity and flexibility highlighted here can inspire new directions in protein-protein interaction prediction and design methods. © 2013 American Chemical Society.

The biological function of proteins is strictly related to their molecular flexibility and dynamics: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation are important mechanisms involving protein motions. Computational approaches, such as Molecular Dynamics (MD) simulations, are now routinely used to study the intrinsic dynamics of target proteins as well as to complement molecular docking approaches. These methods have also successfully supported the process of rational design and discovery of new drugs. Identification of functionally relevant conformations is a key step in these studies. This is generally done by cluster analysis of the ensemble of structures in the MD trajectory. Recently Artificial Neural Network (ANN) approaches, in particular methods based on Self-Organising Maps (SOMs), have been reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data-mining problems. In the specific case of conformational analysis, SOMs have been successfully used to compare multiple ensembles of protein conformations demonstrating a potential in efficiently detecting the dynamic signatures central to biological function. Moreover, examples of the use of SOMs to address problems relevant to other stages of the drug-design process, including clustering of docking poses, have been reported. In this contribution we review recent applications of ANN algorithms in analysing conformational and structural ensembles and we discuss their potential in computer-based approaches for medicinal chemistry.

The aryl hydrocarbon receptor (AHR) is a ligand-dependent transcription factor that mediates the biological and toxic effects of a wide variety of structurally diverse chemicals, including the toxic environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). While significant interspecies differences in AHR ligand binding specificity, selectivity, and response have been observed, the structural determinants responsible for those differences have not been determined, and homology models of the AHR ligand-binding domain (LBD) are available for only a few species. Here we describe the development and comparative analysis of homology models of the LBD of 16 AHRs from 12 mammalian and nonmammalian species and identify the specific residues contained within their ligand binding cavities. The ligand-binding cavity of the fish AHR exhibits differences from those of mammalian and avian AHRs, suggesting a slightly different TCDD binding mode. Comparison of the internal cavity in the LBD model of zebrafish (zf) AHR2, which binds TCDD with high affinity, to that of zfAHR1a, which does not bind TCDD, revealed that the latter has a dramatically shortened binding cavity due to the side chains of three residues (Tyr296, Thr386, and His388) that reduce the amount of internal space available to TCDD. Mutagenesis of two of these residues in zfAHR1a to those present in zfAHR2 (Y296H and T386A) restored the ability of zfAHR1a to bind TCDD and to exhibit TCDD-dependent binding to DNA. These results demonstrate the importance of these two amino acids and highlight the predictive potential of comparative analysis of homology models from diverse species. The availability of these AHR LBD homology models will facilitate in-depth comparative studies of AHR ligand binding and ligand-dependent AHR activation and provide a novel avenue for examining species-specific differences in AHR responsiveness. © 2013 American Chemical Society.

Multiple comparison of the Molecular Dynamics (MD) trajectories of mutants in a cold-adapted α-amylase (AHA) could be used to elucidate functional features required to restore mesophilic-like activity. Unfortunately it is challenging to identify the different dynamic behaviors and correctly relate them to functional activity by routine analysis. We here employed a previously developed and robust two-stage approach that combines Self-Organising Maps (SOMs) and hierarchical clustering to compare conformational ensembles of proteins. Moreover, we designed a novel strategy to identify the specific mutations that more efficiently convert the dynamic signature of the psychrophilic enzyme (AHA) to that of the mesophilic counterpart (PPA). The SOM trained on AHA and its variants was used to classify a PPA MD ensemble and successfully highlighted the relationships between the flexibilities of the target enzyme and of the different mutants. Moreover the local features of the mutants that mostly influence their global flexibility in a mesophilic-like direction were detected. It turns out that mutations of the cold-adapted enzyme to hydrophobic and aromatic residues are the most effective in restoring the PPA dynamic features and could guide the design of more mesophilic-like mutants. In conclusion, our strategy can efficiently extract specific dynamic signatures related to function from multiple comparisons of MD conformational ensembles. Therefore, it can be a promising tool for protein engineering.

Background Molecular dynamics (MD) simulations are powerful tools to investigate the conformational dynamics of proteins that is often a critical element of their function. Identification of functionally relevant conformations is generally done clustering the large ensemble of structures that are generated. Recently, Self-Organising Maps (SOMs) were reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data mining problems. We present a novel strategy to analyse and compare conformational ensembles of protein domains using a two-level approach that combines SOMs and hierarchical clustering. Results The conformational dynamics of the α-spectrin SH3 protein domain and six single mutants were analysed by MD simulations. The Cα's Cartesian coordinates of conformations sampled in the essential space were used as input data vectors for SOM training, then complete linkage clustering was performed on the SOM prototype vectors. A specific protocol to optimize a SOM for structural ensembles was proposed: the optimal SOM was selected by means of a Taguchi experimental design plan applied to different data sets, and the optimal sampling rate of the MD trajectory was selected. The proposed two-level approach was applied to single trajectories of the SH3 domain independently as well as to groups of them at the same time. The results demonstrated the potential of this approach in the analysis of large ensembles of molecular structures: the possibility of producing a topological mapping of the conformational space in a simple 2D visualisation, as well as of effectively highlighting differences in the conformational dynamics directly related to biological functions. Conclusions The use of a two-level approach combining SOMs and hierarchical clustering for conformational analysis of structural ensembles of proteins was proposed. It can easily be extended to other study cases and to conformational ensembles from other sources.

Background The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis. Results A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness. Conclusions The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics.

Ligand-protein docking is a computational approach that is increasingly used in Drug Discovery. The initial limitations imposed by a reduced availability of experimental structures of target proteins have been overcome by theoretical modeling with bioinformatics methods as homology modelling.1 While this greatly extended the use of docking simulations, it also introduced the need for general criteria to estimate the reliability of docking results given the model quality.2 To this end, we performed a large-scale experiment on a diverse set including experimental structures and homology models for a group of representative ligandprotein complexes.3 A wide spectrum of model quality was sampled using templates at different evolutionary distances and different strategies for target-template alignment and modelling. The obtained models were evaluated with a selection of model quality indices.4 The binding geometries were generated using AutoDock,5 a widely used docking program. The results demonstrated that general relationships do exist between the accuracy of the binding geometries obtained by docking and the quality of the homology models. In particular, it was highlighted that successful docking requires an accurate modelling of the binding site and that, conversely, the development of docking approaches that allow flexibility in the binding site may have a great impact on the effective use of docking into homology models. More importantly, state-of-the-art indices for model quality assessment are an effective tool for a priori prediction of the accuracy of docking experiments in the context of groups of proteins with conserved structural characteristics. On these bases, we presented a strategy to exploit information on homologous proteins to predict the accuracy of docking results on theoretical models.