Andrej Sali

Statistical potential for assessment and prediction of protein structures

Protein structures in the Protein Data Bank provide a wealth of data about the interactions that determine the native states of proteins. Using the probability theory, we derive an atomic distance‐dependent statistical potential from a sample of native structures that does not depend on any adjustable parameters (Discrete Optimized Protein Energy, or DOPE). DOPE is based on an improved reference state that corresponds to noninteracting atoms in a homogeneous sphere with the radius dependent on a sample native structure; it thus accounts for the finite and spherical shape of the native structures. The DOPE potential was extracted from a nonredundant set of 1472 crystallographic structures. We tested DOPE and five other scoring functions by the detection of the native state among six multiple target decoy sets, the correlation between the score and model error, and the identification of the most accurate non‐native structure in the decoy set. For all decoy sets, DOPE is the best performing function in terms of all criteria, except for a tie in one criterion for one decoy set. To facilitate its use in various applications, such as model assessment, loop modeling, and fitting into cryo‐electron microscopy mass density maps combined with comparative protein structure modeling, DOPE was incorporated into the modeling package MODELLER‐8.

Modeller: Generation and Refinement of Homology-Based Protein Structure Models

Publisher Summary Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3D model for a protein (target) that is related to at least one known protein structure (template). A 3D structure of proteins from the same family is more conserved than their primary sequences. Therefore, if similarity between two proteins is detectable at the sequence level, structural similarity can usually be assumed. Comparative modeling usually starts by searching the Protein Data Bank (PDB) of known protein structures using the target sequence as the query. This search is generally done by comparing the target sequence with the sequence of each of the structures in the database. Comparative modeling consists of five steps: (1) search for related protein structures, (2) selection of one or more templates, (3) target–template alignment, (4) model building, and (5) model evaluation. If the model is not satisfactory, some or all of the steps can be repeated. There are several computer programs and Web servers that automate the comparative modeling process. The first Web server for automated comparative modeling was the Swiss-Model server, followed by CPHModels and ModWeb. These servers accept a sequence from a user and return an all-atom comparative model when possible.

Protein Structure Modeling with MODELLER

Genome sequencing projects have resulted in a rapid increase in the number of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized using experimental structure determination methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. This chapter presents an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of similar protocols (correction of protcols) has resulted in models of useful accuracy for domains in more than half of all known protein sequences.

MODBASE, a database of annotated comparative protein structure models, and associated resources

ModBase (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by ModPipe, an automated modeling pipeline that relies primarily on Modeller for fold assignment, sequence-structure alignment, model building and model assessment (http://salilab.org/modeller/). ModBase currently contains almost 30 million reliable models for domains in 4.7 million unique protein sequences. ModBase allows users to compute or update comparative models on demand, through an interface to the ModWeb modeling server (http://salilab.org/modweb). ModBase models are also available through the Protein Model Portal (http://www.proteinmodelportal.org/). Recently developed associated resources include the AllosMod server for modeling ligand-induced protein dynamics (http://salilab.org/allosmod), the AllosMod-FoXS server for predicting a structural ensemble that fits an SAXS profile (http://salilab.org/allosmod-foxs), the FoXSDock server for protein–protein docking filtered by an SAXS profile (http://salilab.org/foxsdock), the SAXS Merge server for automatic merging of SAXS profiles (http://salilab.org/saxsmerge) and the Pose & Rank server for scoring protein–ligand complexes (http://salilab.org/poseandrank). In this update, we also highlight two applications of ModBase: a PSI:Biology initiative to maximize the structural coverage of the human alpha-helical transmembrane proteome and a determination of structural determinants of human immunodeficiency virus-1 protease specificity.

The molecular architecture of the nuclear pore complex

Nuclear pore complexes (NPCs) are proteinaceous assemblies of approximately 50 MDa that selectively transport cargoes across the nuclear envelope. To determine the molecular architecture of the yeast NPC, we collected a diverse set of biophysical and proteomic data, and developed a method for using these data to localize the NPC’s 456 constituent proteins (see the accompanying paper). Our structure reveals that half of the NPC is made up of a core scaffold, which is structurally analogous to vesicle-coating complexes. This scaffold forms an interlaced network that coats the entire curved surface of the nuclear envelope membrane within which the NPC is embedded. The selective barrier for transport is formed by large numbers of proteins with disordered regions that line the inner face of the scaffold. The NPC consists of only a few structural modules that resemble each other in terms of the configuration of their homologous constituents, the most striking of these being a 16-fold repetition of ‘columns’. These findings provide clues to the evolutionary origins of the NPC.

Protein Folding: A Perspective from Theory and Experiment

The mechanism of protein folding (represented schematically below) is one of the most fascinating problems in the field of chemical reactions. This review presents the progess made recently in understanding key elements of this reaction and describes a solution to the often quoted Levinthal Paradox.

Definition of general topological equivalence in protein structures: A procedure involving comparison of properties and relationships through simulated annealing and dynamic programming

A protein is defined as an indexed string of elements at each level in the hierarchy of protein structure: sequence, secondary structure, super-secondary structure, etc. The elements, for example, residues or secondary structure segments such as helices or beta-strands, are associated with a series of properties and can be involved in a number of relationships with other elements. Element-by-element dissimilarity matrices are then computed and used in the alignment procedure based on the sequence alignment algorithm of Needleman & Wunsch, expanded by the simulated annealing technique to take into account relationships as well as properties. The utility of this method for exploring the variability of various aspects of protein structure and for comparing distantly related proteins is demonstrated by multiple alignment of serine proteinases, aspartic proteinase lobes and globins.

Comparative Protein Structure Modeling Using MODELLER

Functional characterization of a protein sequence is a common goal in biology, and is usually facilitated by having an accurate three‐dimensional (3‐D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3‐D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3‐D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target‐template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. Curr. Protoc. Protein Sci. 50:2.9.1‐2.9.31.

Structure of the 80S Ribosome from Saccharomyces cerevisiae—tRNA-Ribosome and Subunit-Subunit Interactions

A cryo-EM reconstruction of the translating yeast 80S ribosome was analyzed. Computationally separated rRNA and protein densities were used for docking of appropriately modified rRNA models and homology models of yeast ribosomal proteins. The core of the ribosome shows a remarkable degree of conservation. However, some significant differences in functionally important regions and dramatic changes in the periphery due to expansion segments and additional ribosomal proteins are evident. As in the bacterial ribosome, bridges between the subunits are mainly formed by RNA contacts. Four new bridges are present at the periphery. The position of the P site tRNA coincides precisely with its prokaryotic counterpart, with mainly rRNA contributing to its molecular environment. This analysis presents an exhaustive inventory of an eukaryotic ribosome at the molecular level.

Determining the architectures of macromolecular assemblies

To understand the workings of a living cell, we need to know the architectures of its macromolecular assemblies. Here we show how proteomic data can be used to determine such structures. The process involves the collection of sufficient and diverse high-quality data, translation of these data into spatial restraints, and an optimization that uses the restraints to generate an ensemble of structures consistent with the data. Analysis of the ensemble produces a detailed architectural map of the assembly. We developed our approach on a challenging model system, the nuclear pore complex (NPC). The NPC acts as a dynamic barrier, controlling access to and from the nucleus, and in yeast is a 50 MDa assembly of 456 proteins. The resulting structure, presented in an accompanying paper, reveals the configuration of the proteins in the NPC, providing insights into its evolution and architectural principles. The present approach should be applicable to many other macromolecular assemblies.