An octamer of histone proteins wraps about 200 base pairs of DNA into two super-helical turns to form nucleosomes found in chromatin. Although the static structure of the nucleosomal core particle has been solved, details of the dynamic interactions between histones and DNA remain elusive. We performed extensively long unconstrained, all-atom microsecond molecular dynamics simulations of nucleosomes including linker DNA segments and full-length histones in explicit solvent. For the first time we were able to identify and characterize the rearrangements in nucleosomes on a microsecond timescale including the coupling between the conformation of the histone tails and the DNA geometry. We found that certain histone tail conformations promoted DNA bulging near its entry/exit sites, resulting in the formation of twist-defects within the DNA. This led to a reorganization of histone-DNA interactions, suggestive of the formation of initial nucleosome sliding intermediates. We characterized the dynamics of the histone tails upon their condensation on the core and linker DNA and showed that tails may adopt conformationally constrained positions due to the insertion of “anchoring” lysines and arginines into the DNA minor grooves. Potentially, these phenomena affect the accessibility of post-translationally modified histone residues which serve as important sites for epigenetic marks (e.g. at H3K9, H3K27, H4K16), suggesting that interactions of the histone tails with the core and linker DNA modulate the processes of histone tail modifications and binding of the effector proteins. We discuss the implications of the observed results on the nucleosome function and compare our results to different experimental studies.

Missense mutations may affect proteostasis by destabilizing or over-stabilizing protein complexes and changing the pathway flux. Predicting the effects of stabilizing mutations on protein-protein interactions is notoriously difficult because existing experimental sets are skewed toward mutations reducing protein-protein binding affinity and many computational methods fail to correctly evaluate their effects. To address this issue, we developed a method MutaBind2, which estimates the impacts of single as well as multiple mutations on protein-protein interactions. MutaBind2 employs only seven features, and the most important of them describe interactions of proteins with the solvent, evolutionary conservation of the site, and thermodynamic stability of the complex and each monomer. This approach shows a distinct improvement especially in evaluating the effects of mutations increasing binding affinity. MutaBind2 can be used for finding disease driver mutations, designing stable protein complexes, and discovering new protein-protein interaction inhibitors.

Abundant and essential motifs, such as phosphate-binding loops (P-loops), are presumed to be the seeds of modern enzymes. The Walker-A P-loop is absolutely essential in modern NTPase enzymes, in mediating binding, and transfer of the terminal phosphate groups of NTPs. However, NTPase function depends on many additional active-site residues placed throughout the protein’s scaffold. Can motifs such as P-loops confer function in a simpler context? We applied a phylogenetic analysis that yielded a sequence logo of the putative ancestral Walker-A P-loop element: a β-strand connected to an α-helix via the P-loop. Computational design incorporated this element into de novo designed β-α repeat proteins with relatively few sequence modifications. We obtained soluble, stable proteins that unlike modern P-loop NTPases bound ATP in a magnesium-independent manner. Foremost, these simple P-loop proteins avidly bound polynucleotides, RNA, and single-strand DNA, and mutations in the P-loop’s key residues abolished binding. Binding appears to be facilitated by the structural plasticity of these proteins, including quaternary structure polymorphism that promotes a combined action of multiple P-loops. Accordingly, oligomerization enabled a 55-aa protein carrying a single P-loop to confer avid polynucleotide binding. Overall, our results show that the P-loop Walker-A motif can be implemented in small and simple β-α repeat proteins, primarily as a polynucleotide binding motif.

Proteins engage in highly selective interactions with their macromolecular partners. Sequence variants that alter protein binding affinity may cause significant perturbations or complete abolishment of function, potentially leading to diseases. There exists a persistent need to develop a mechanistic understanding of impacts of variants on proteins. To address this need we introduce a new computational method MutaBind to evaluate the effects of sequence variants and disease mutations on protein interactions and calculate the quantitative changes in binding affinity. The MutaBind method uses molecular mechanics force fields, statistical potentials and fast side-chain optimization algorithms. The MutaBind server maps mutations on a structural protein complex, calculates the associated changes in binding affinity, determines the deleterious effect of a mutation, estimates the confidence of this prediction and produces a mutant structural model for download. MutaBind can be applied to a large number of problems, including determination of potential driver mutations in cancer and other diseases, elucidation of the effects of sequence variants on protein fitness in evolution and protein design. MutaBind is available at http://www.ncbi.nlm.nih.gov/projects/mutabind/.

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SUMMARY Intratumor mutational heterogeneity has been documented in primary non-small-cell lung cancer. Here, we elucidate mechanisms of tumor evolution and heterogeneity in metastatic thoracic tumors (lung adenocarcinoma and thymic carcinoma) using whole-exome and transcriptome sequencing, SNP array for copy-number alterations (CNAs), and mass-spectrometry-based quantitative proteomics of metastases obtained by rapid autopsy. APOBEC mutagenesis, promoted by increased expression of APOBEC3 region transcripts and associated with a high-risk APOBEC3 germline variant, correlated with mutational tumor heterogeneity. TP53 mutation status was associated with APOBEC hypermutator status. Interferon pathways were enriched in tumors with high APOBEC mutagenesis and IFN-γ-induced expression of APOBEC3B in lung adenocarcinoma cells, suggesting that the immune microenvironment may promote mutational heterogeneity. CNAs occurring late in tumor evolution correlated with downstream transcriptomic and proteomic heterogeneity, although global proteomic heterogeneity was significantly greater than transcriptomic and CNA heterogeneity. These results illustrate key mechanisms underlying multi-dimensional heterogeneity in metastatic thoracic tumors.

Much remains unknown about the progression and heterogeneity of mutational processes in different cancers and their diagnostic and clinical potential. A growing body of evidence supports mutation rate dependence on the local DNA sequence context for various types of mutations. We propose several tools for the analysis of cancer context-dependent mutations, which are implemented in an online computational framework MutaGene. The framework explores DNA context-dependent mutational patterns and underlying somatic cancer mutagenesis, analyzes mutational profiles of cancer samples, identifies the combinations of underlying mutagenic processes including those related to infidelity of DNA replication and repair machinery, and various other endogenous and exogenous mutagenic factors. As a result, the combination of mutagenic processes can be identified in any query sample with subsequent comparison to mutational profiles derived from malignant and benign samples. In addition, mutagen or cancer-specific mutational background models are applied to calculate expected DNA and protein site mutability to decouple relative contributions of mutagenesis and selection in carcinogenesis, thus elucidating the site-specific driving events in cancer. MutaGene is freely available at https://www.ncbi.nlm.nih.gov/projects/mutagene/.

The goal of this work is to learn from nature the rules that govern evolution and the design of protein function. The fundamental laws of physics lie in the foundation of the protein structure and all stages of the protein evolution, determining optimal sizes and shapes at different levels of structural hierarchy. We looked back into the very onset of the protein evolution with a goal to find elementary functions (EFs) that came from the prebiotic world and served as building blocks of the first enzymes. We defined the basic structural and functional units of biochemical reactions-elementary functional loops. The diversity of contemporary enzymes can be described via combinations of a limited number of elementary chemical reactions, many of which are performed by the descendants of primitive prebiotic peptides/proteins. By analyzing protein sequences we were able to identify EFs shared by seemingly unrelated protein superfamilies and folds and to unravel evolutionary relations between them. Binding and metabolic processing of the metal- and nucleotide-containing cofactors and ligands are among the most abundant ancient EFs that became indispensable in many natural enzymes. Highly designable folds provide structural scaffolds for many different biochemical reactions. We show that contemporary proteins are built from a limited number of EFs, making their analysis instrumental for establishing the rules for protein design. Evolutionary studies help us to accumulate the library of essential EFs and to establish intricate relations between different folds and functional superfamilies. Generalized sequence-structure descriptors of the EF will become useful in future design and engineering of desired enzymatic functions.