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Potts models and variational autoencoders (VAEs) have recently gained popularity as generative protein sequence models (GPSMs) to explore fitness landscapes and predict mutation effects. Despite encouraging results, current model evaluation metrics leave unclear whether GPSMs faithfully reproduce the complex multi-residue mutational patterns observed in natural sequences due to epistasis. Here, we develop a set of sequence statistics to assess the “generative capacity” of three current GPSMs: the pairwise Potts Hamiltonian, the VAE, and the site-independent model. We show that the Potts model’s generative capacity is largest, as the higher-order mutational statistics generated by the model agree with those observed for natural sequences, while the VAE’s lies between the Potts and site-independent models. Importantly, our work provides a new framework for evaluating and interpreting GPSM accuracy which emphasizes the role of higher-order covariation and epistasis, with broader implications for probabilistic sequence models in general.

 

Water/oxide interfaces are ubiquitous on earth and show significant influence on many chemical processes. For example, understanding water and solute adsorption as well as catalytic water splitting can help build better fuel cells and solar cells to overcome our looming energy crisis; the interaction between biomolecules and water/oxide interfaces is one hypothesis to explain the origin of life. However, knowledge in this area is still limited due to the difficulty of studying water/solid interfaces. As a result, research using increasingly sophisticated experimental techniques and computational simulations has been carried out in recent years. Although it is difficult for experimental techniques to provide detailed microscopic structural information, molecular dynamics (MD) simulations have satisfactory performance. In this review, we discuss classical and ab initio MD simulations of water/oxide interfaces. Generally, we are interested in the following questions: How do solid surfaces perturb interfacial water structure? How do interfacial water molecules and adsorbed solutes affect solid surfaces and how do interfacial environments affect solvent and solute behavior? Finally, we discuss progress in the application of neural network potential based MD simulations, which offer a promising future because this approach has already enabled ab initio level accuracy for very large systems and long trajectories.

This article is categorized under:

Theoretical and Physical Chemistry > Spectroscopy

Molecular and Statistical Mechanics > Molecular Interactions

Structure and Mechanism > Molecular Structures

 

Through the artistic planning tool known to comic book artists and animators as storyboarding, students will embark on comic book–style adventures to plan, describe, and visualize the complex life of genes through the non-Mendelian concept of epistasis. Using storyboard templates, conceptual layouts, sketch booking, and cut-out genetic elements, students will construct their interpretation of the gene-gene interactions of epistasis. The incomplete story of the epistasis of human eye color will serve as the theme for this storyboard, which will also become its own assessment tool, inviting educators into a realm of a true STEAM experience. 

We introduce biology to the artist’s design tool, the storyboard. This versatile organizing and visualizing artistic platform is introduced into the biology classroom to aid in an inventive and focused discovery process. Almost all biological concepts are dynamic, and storyboards offer biology, lecture, wet and computational labs, flexibility, inventiveness, and an opportunity for students to slow down the so-called steps of biological processes and moderate their observations. Storyboarding is a thoughtful and reflective discovery device with enormous potential to break with traditional biology classroom experiences and return to the root of the educational process: storytelling. It will encourage teachers to embark on the remodeling of the biological curriculum with specific technical skills that students and teachers should consider developing to make the STEAM experience tailored to the uniqueness of biological systems. Storyboards offer hands-on, illustrative, and interactive conversations about biology concepts. They are an “unplugged” and contemplative experiences, organizing frameworks for personal expression focused on biological wonders. 

Transient receptor potential (TRP) proteins are a large family of cation-selective channels, surpassed in variety only by voltage-gated potassium channels. Detailed molecular mechanisms governing how membrane voltage, ligand binding, or temperature can induce conformational changes promoting the open state in TRP channels are still a matter of debate. Aiming to unveil distinctive structural features common to the transmembrane domains within the TRP family, we performed phylogenetic reconstruction, sequence statistics, and structural analysis over a large set of TRP channel genes. Here, we report an exceptionally conserved set of residues. This fingerprint is composed of twelve residues localized at equivalent three-dimensional positions in TRP channels from the different subtypes. Moreover, these amino acids are arranged in three groups, connected by a set of aromatics located at the core of the transmembrane structure. We hypothesize that differences in the connectivity between these different groups of residues harbor the apparent differences in coupling strategies used by TRP subgroups. 

Abstract Invariant sites are a common feature of amino acid sequence evolution. The presence of invariant sites is frequently attributed to the need to preserve function through site-specific conservation of amino acid residues. Amino acid substitution models without a provision for invariant sites often fit the data significantly worse than those that allow for an excess of invariant sites beyond those predicted by models that only incorporate rate variation among sites (e.g., a Gamma distribution). An alternative is epistasis between sites to preserve residue interactions that can create invariant sites. Through computer-simulated sequence evolution, we evaluated the relative effects of site-specific preferences and site-site couplings in the generation of invariant sites and the modulation of the rate of molecular evolution. In an analysis of ten major families of protein domains with diverse sequence and functional properties, we find that the negative selection imposed by epistasis creates many more invariant sites than site-specific residue preferences alone. Further, epistasis plays an increasingly larger role in creating invariant sites over longer evolutionary periods. Epistasis also dictates rates of domain evolution over time by exerting significant additional purifying selection to preserve site couplings. These patterns illuminate the mechanistic role of epistasis in the processes underlying observed site invariance and evolutionary rates. 

Many pathogenic missense mutations are found in protein positions that are neither well-conserved nor fall in any known functional domains. Consequently, we lack any mechanistic underpinning of dysfunction caused by such mutations. We explored the disruption of allosteric dynamic coupling between these positions and the known functional sites as a possible mechanism for pathogenesis. In this study, we present an analysis of 591 pathogenic missense variants in 144 human enzymes that suggests that allosteric dynamic coupling of mutated positions with known active sites is a plausible biophysical mechanism and evidence of their functional importance. We illustrate this mechanism in a case study of β-Glucocerebrosidase (GCase) in which a vast majority of 94 sites harboring Gaucher disease-associated missense variants are located some distance away from the active site. An analysis of the conformational dynamics of GCase suggests that mutations on these distal sites cause changes in the flexibility of active site residues despite their distance, indicating a dynamic communication network throughout the protein. The disruption of the long-distance dynamic coupling caused by missense mutations may provide a plausible general mechanistic explanation for biological dysfunction and disease.