Multidimensional quantitative phenotypic and molecular analysis reveals neomorphic behaviors of p53 missense mutants.

Mutations in the TP53 tumor suppressor gene occur in >80% of the triple-negative or basal-like breast cancer. To test whether neomorphic functions of specific TP53 missense mutations contribute to phenotypic heterogeneity, we characterized phenotypes of non-transformed MCF10A-derived cell lines expressing the ten most common missense mutant p53 proteins and observed a wide spectrum of phenotypic changes in cell survival, resistance to apoptosis and anoikis, cell migration, invasion and 3D mammosphere architecture. The p53 mutants R248W, R273C, R248Q, and Y220C are the most aggressive while G245S and Y234C are the least, which correlates with survival rates of basal-like breast cancer patients. Interestingly, a crucial amino acid difference at one position-R273C vs. R273H-has drastic changes on cellular phenotype. RNA-Seq and ChIP-Seq analyses show distinct DNA binding properties of different p53 mutants, yielding heterogeneous transcriptomics profiles, and MD simulation provided structural basis of differential DNA binding of different p53 mutants. Integrative statistical and machine-learning-based pathway analysis on gene expression profiles with phenotype vectors across the mutant cell lines identifies quantitative association of multiple pathways including the Hippo/YAP/TAZ pathway with phenotypic aggressiveness. Further, comparative analyses of large transcriptomics datasets on breast cancer cell lines and tumors suggest that dysregulation of the Hippo/YAP/TAZ pathway plays a key role in driving the cellular phenotypes towards basal-like in the presence of more aggressive p53 mutants. Overall, our study describes distinct gain-of-function impacts on protein functions, transcriptional profiles, and cellular behaviors of different p53 missense mutants, which contribute to clinical phenotypic heterogeneity of triple-negative breast tumors.

Revealing a Hidden Intermediate of Rotatory Catalysis with X-ray Crystallography and Molecular Simulations.

The mechanism of rotatory catalysis in ATP-hydrolyzing molecular motors remains an unresolved puzzle in biological energy transfer. Notwithstanding the wealth of available biochemical and structural information inferred from years of experiments, knowledge on how the coupling between the chemical and mechanical steps within motors enforces directional rotatory movements remains fragmentary. Even more contentious is to pinpoint the rate-limiting step of a multistep rotation process. Here, using vacuolar or V1-type hexameric ATPase as an exemplary rotational motor, we present a model of the complete 4-step conformational cycle involved in rotatory catalysis. First, using X-ray crystallography, a new intermediate or "dwell" is identified, which enables the release of an inorganic phosphate (or Pi) after ATP hydrolysis. Using molecular dynamics simulations, this new dwell is placed in a sequence with three other crystal structures to derive a putative cyclic rotation path. Free-energy simulations are employed to estimate the rate of the hexameric protein transformations and delineate allosteric effects that allow new reactant ATP entry only after hydrolysis product exit. An analysis of transfer entropy brings to light how the side-chain-level interactions transcend into larger-scale reorganizations, highlighting the role of the ubiquitous arginine-finger residues in coupling chemical and mechanical information. An inspection of all known rates encompassing the 4-step rotation mechanism implicates the overcoming of the ADP interactions with V1-ATPase to be the rate-limiting step of motor action.

The ugly, bad, and good stories of large-scale biomolecular simulations.

Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations.

In Silico Prediction of the Binding, Folding, Insertion, and Overall Stability of Membrane-Active Peptides.

Membrane-active peptides (MAPs) are short-length peptides used for potential biomedical applications in diagnostic imaging of tissues, targeted drug delivery, gene delivery, and antimicrobials and antibiotics. The broad appeal of MAPs is that they are infinitely variable, relatively low cost, and biocompatible. However, experimentally characterizing the specific properties of a MAP or its many variants is a low-resolution and potentially time-consuming endeavor; molecular dynamics (MD) simulations have emerged as an invaluable tool in identifying the biophysical interactions that are fundamental to the function of MAPs. In this chapter, a step-by-step approach to discreetly model the binding, folding, and insertion of a membrane-active peptide to a model lipid bilayer using MD simulations is described. Detailed discussion is devoted to the critical aspects of running these types of simulations: prior knowledge of the system, understanding the strengths and weaknesses of molecular mechanics force fields, proper construction and equilibration of the system, realistically estimating both experimental and computational timescales, and leveraging analysis to make direct comparisons to experimental results as often as possible.

Poor Person's pH Simulation of Membrane Proteins.

pH conditions are central to the functioning of all biomolecules. However, implications of pH changes are nontrivial on a molecular scale. Though a rigorous microscopic definition of pH exists, its implementation in classical molecular dynamics (MD) simulations is cumbersome, and more so in large integral membrane systems. In this chapter, an integrative pipeline is described that combines Multi-Conformation Continuum Electrostatics (MCCE) computations with MD simulations to capture the effect of transient protonation states on the coupled conformational changes in transmembrane proteins. The core methodologies are explained, and all the software required to set up this pipeline are outlined with their key parameters. All associated analyses of structure and function are provided using two case studies, namely those of bioenergetic complexes: NADH dehydrogenase (complex I) and Vo domain of V-type ATPase. The hybrid MCCE-MD pipeline has allowed the discovery of hydrogen bond networks, ligand binding pathways, and disease-causing mutations.

Large-Scale Molecular Dynamics Simulations of Cellular Compartments.

Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.

CryoFold: determining protein structures and data-guided ensembles from cryo-EM density maps.

Cryo-electron microscopy (EM) requires molecular modeling to refine structural details from data. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins that cannot be resolved by cryo-EM. Here, we introduce CryoFold - a pipeline of molecular dynamics simulations that determines ensembles of protein structures directly from sequence by integrating density data of varying sparsity at 3-5 Å resolution with coarse-grained topological knowledge of the protein folds. We present six examples showing its broad applicability for folding proteins between 72 to 2000 residues, including large membrane and multi-domain systems, and results from two EMDB competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations, unseen by traditional methods, are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python GUI.

Mucin-mimetic glycan arrays integrating machine learning for analyzing receptor pattern recognition by influenza A viruses.

Influenza A viruses (IAVs) exploit host glycans in airway mucosa for entry and infection. Detection of changes in IAV glycan-binding phenotype can provide early indication of transmissibility and infection potential. While zoonotic viruses are monitored for mutations, the influence of host glycan presentation on viral specificity remains obscured. Here, we describe an array platform which uses synthetic mimetics of mucin glycoproteins to model how receptor presentation and density in the mucinous glycocalyx may impact IAV recognition. H1N1 and H3N2 binding in arrays of α2,3- and α2,6-sialyllactose receptors confirmed their known sialic acid-binding specificities and revealed their different sensitivities to receptor presentation. Further, the transition of H1N1 from avian to mammalian cell culture improved the ability of the virus to recognize mucin-like displays of α2,6-sialic acid receptors. Support vector machine (SVM) learning efficiently characterized this shift in binding preference and may prove useful to study viral evolution to a new host.

Molecular Dynamics Flexible Fitting: All You Want to Know About Resolution Exchange.

In recent years, owing to the advances in instrumentation, cryo-EM has emerged as the go-to tool for obtaining high-resolution structures of biomolecular systems. However, building three-dimensional atomic structures of biomolecules from these high-resolution maps remains a concern for the traditional map-guided structure-determination schemes. Recently, we developed a computational tool, Resolution Exchange Molecular Dynamics Flexible Fitting (ReMDFF) to address this problem by re-refining a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution (Wang et al., J Struct Biol 204(2):319-328, 2018). In this chapter, we present a step-by-step outline for preparing, executing, and analyzing ReMDFF refinements of simple proteins and multimeric complexes. The structure determination of carbon monoxide dehydrogenase and Mg2+-channel CorA are employed as case studies. All scripts are provided via GitHub (Vant, Resolution exchange molecular dynamics flexible fitting (ReMDFF) all you want to know about flexible fitting, 2019, https://github.com/jvant/ReMDFF_Singharoy_Group.git ).

Hydrogen bond network analysis reveals the pathway for the proton transfer in the E-channel of T. thermophilus Complex I.

Complex I, NADH-ubiquinone oxidoreductase, is the first enzyme in the mitochondrial and bacterial aerobic respiratory chain. It pumps four protons through four transiently open pathways from the high pH, negative, N-side of the membrane to the positive, P-side driven by the exergonic transfer of electrons from NADH to a quinone. Three protons transfer through subunits descended from antiporters, while the fourth, E-channel is unique. The path through the E-channel is determined by a network analysis of hydrogen bonded pathways obtained by Monte Carlo sampling of protonation states, polar hydrogen orientation and water occupancy. Input coordinates are derived from molecular dynamics trajectories comparing oxidized, reduced (dihydro) and no menaquinone-8 (MQ). A complex proton transfer path from the N- to the P-side is found consisting of six clusters of highly connected hydrogen-bonded residues. The network connectivity depends on the presence of quinone and its redox state, supporting a role for this cofactor in coupling electron and proton transfers. The N-side is more organized with MQ-bound complex I facilitating proton entry, while the P-side is more connected in the apo-protein, facilitating proton exit. Subunit Nqo8 forms the core of the E channel; Nqo4 provides the N-side entry, Nqo7 and then Nqo10 join the pathway in the middle, while Nqo11 contributes to the P-side exit.

Charge Transfer and Chemo-Mechanical Coupling in Respiratory Complex I.

The mitochondrial respiratory chain, formed by five protein complexes, utilizes energy from catabolic processes to synthesize ATP. Complex I, the first and the largest protein complex of the chain, harvests electrons from NADH to reduce quinone, while pumping protons across the mitochondrial membrane. Detailed knowledge of the working principle of such coupled charge-transfer processes remains, however, fragmentary due to bottlenecks in understanding redox-driven conformational transitions and their interplay with the hydrated proton pathways. Complex I from Thermus thermophilus encases 16 subunits with nine iron-sulfur clusters, reduced by electrons from NADH. Here, employing the latest crystal structure of T. thermophilus complex I, we have used microsecond-scale molecular dynamics simulations to study the chemo-mechanical coupling between redox changes of the iron-sulfur clusters and conformational transitions across complex I. First, we identify the redox switches within complex I, which allosterically couple the dynamics of the quinone binding pocket to the site of NADH reduction. Second, our free-energy calculations reveal that the affinity of the quinone, specifically menaquinone, for the binding-site is higher than that of its reduced, menaquinol form-a design essential for menaquinol release. Remarkably, the barriers to diffusive menaquinone dynamics are lesser than that of the more ubiquitous ubiquinone, and the naphthoquinone headgroup of the former furnishes stronger binding interactions with the pocket, favoring menaquinone for charge transport in T. thermophilus. Our computations are consistent with experimentally validated mutations and hierarchize the key residues into three functional classes, identifying new mutation targets. Third, long-range hydrogen-bond networks connecting the quinone-binding site to the transmembrane subunits are found to be responsible for proton pumping. Put together, the simulations reveal the molecular design principles linking redox reactions to quinone turnover to proton translocation in complex I.

XFEL and NMR Structures of Francisella Lipoprotein Reveal Conformational Space of Drug Target against Tularemia.

Francisella tularensis is the causative agent for the potentially fatal disease tularemia. The lipoprotein Flpp3 has been identified as a virulence determinant of tularemia with no sequence homology outside the Francisella genus. We report a room temperature structure of Flpp3 determined by serial femtosecond crystallography that exists in a significantly different conformation than previously described by the NMR-determined structure. Furthermore, we investigated the conformational space and energy barriers between these two structures by molecular dynamics umbrella sampling and identified three low-energy intermediate states, transitions between which readily occur at room temperature. We have also begun to investigate organic compounds in silico that may act as inhibitors to Flpp3. This work paves the road to developing targeted therapeutics against tularemia and aides in our understanding of the disease mechanisms of tularemia.

Ions Modulate Key Interactions between pHLIP and Lipid Membranes.

The pH-low insertion peptide (pHLIP) is used for targeted delivery of drug cargoes to acidic tissues such as tumors. The extracellular acidosis found in solid tumors triggers pHLIP to transition from a membrane-adsorbed state to fold into a transmembrane α-helix. Different factors influence the acidity required for pHLIP to insert into lipid membranes. One of them is the lipid headgroup composition, which defines the electrostatic profile of the membrane. However, the molecular interactions that drive the adsorption of pHLIP to the bilayer surface are poorly understood. In this study, we combine biophysical experiments and all-atom molecular dynamics simulations to understand the role played by electrostatics in the interaction between pHLIP and a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine bilayer. We observed that the solution ionic strength affects the structure of pHLIP at the membrane surface as well as the acidity needed for different steps in the membrane insertion process. In particular, our simulations revealed that an increase in ionic strength affected both pHLIP and the bilayer; the coordination of sodium ions with the C-terminus of pHLIP led to localized changes in helicity, whereas the coordination of sodium ions with the phosphate moiety of the phosphocholine headgroups had a condensing effect on our model bilayer. These results are relevant to our understanding of environmental influences on the ability of pHLIP to adsorb to the cell membrane and are useful in our fundamental understanding of the absorption of pH-responsive peptides and cell-penetrating peptides.

Cooperative Nonbonded Forces Control Membrane Binding of the pH-Low Insertion Peptide pHLIP.

Peptides with the ability to bind and insert into the cell membrane have immense potential in biomedical applications. pH (low) insertion peptide (pHLIP), a water-soluble polypeptide derived from helix C of bacteriorhodopsin, can insert into a membrane at acidic pH to form a stable transmembrane α-helix. The insertion process takes place in three stages: pHLIP is unstructured and soluble in water at neutral pH (state I), unstructured and bound to the surface of a membrane at neutral pH (state II), and inserted into the membrane as an α-helix at low pH (state III). Using molecular dynamics simulations, we have modeled state II of pHLIP and a fast-folding variant of pHLIP, in which each peptide is bound to a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine bilayer surface. Our results provide strong support for recently published spectroscopic studies, namely that pHLIP preferentially binds to the bilayer surface as a function of location of anionic amino acids and that backbone dehydration occurs upon binding. Unexpectedly, we also observed several instances of segments of pHLIP folding into a stable helical turn. Our results provide a molecular level of detail that is essential to providing new insights into pHLIP function and to facilitate design of variants with improved membrane-active capabilities.

Peptide bond conformation in peptides and proteins probed by dipolar coupling-chemical shift tensor correlation solid-state NMR.

Multidimensional magic-angle spinning solid-state NMR experiments are described that permit cis and trans peptide bonds in uniformly 13C,15N-labeled peptides and proteins to be unambiguously distinguished in residue-specific manner by determining the relative orientations of the amide 13C' CSA and 1H-15N dipolar coupling tensors. The experiments are demonstrated for model peptides glycylglycine and 2,5-diketopiperazine containing trans and cis peptide bonds, respectively. Subsequently, the measurements are extended to two representative proteins that contain exclusively trans peptide bonds, microcrystalline B3 immunoglobulin domain of protein G and Y145Stop human prion protein amyloid fibrils, to illustrate their applicability to a wide range of protein systems.

Protonation Enhances the Inherent Helix-Forming Propensity of pHLIP.

Cell-penetrating peptides (CPPs) can be potentially used in targeted delivery of therapeutic cargoes. However, their conformation in solution is poorly understood. We employed molecular dynamics simulations to probe the structural fluctuations of an anionic CPP, pH Low Insertion Peptide (pHLIP), in solution to determine the effects of modifications to selected residues on the structure of pHLIP. Two types of modifications were tested: (1) protonation of aspartic acid residues and (2) point mutations known to affect the acid sensitivity of pHLIP. pHLIP samples conformations ranging from coil to helix to sheet, and modifications to pHLIP lead to subtle shifts in the balance between these conformations. In some instances, pHLIP is as likely to form a helical conformation as it is to form an unstructured coil. Understanding the behavior of pHLIP in solution is necessary for determining optimal conditions for administration of pHLIP and design of promising pHLIP variants.