ABSTRACT
Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.
Subject(s)
Drug Design , Genome-Wide Association Study/trends , Genomics/trends , High-Throughput Nucleotide Sequencing/trends , Pharmacogenetics/trends , Precision Medicine/trends , Systems TheoryABSTRACT
The acquired-immunodeficiency syndrome has evolved into a major worldwide epidemic. Significant effort has been made in the development of antiviral therapies. A new strategy for vaccine and drug design that complements the existing cocktail therapy is to target entry of the human immunodeficiency virus (HIV). Such an approach provides the advantage of interfering with multiple intermediates in this multi-step process. The extraordinary conformational flexibility, glycosylation, and strain variations of viral glycoprotein gp120 cause general viral evasion of humoral immune response and thus complicate the development of an effective vaccine. Especially difficult to define are the conformation of gp120 before CD4 engagement as well as the relative orientations of the V1/V2 and V3 loops with respect to the inner and outer domains. In this study, we used Floppy Inclusion and Rigid Substructure Topography (FIRST), a program based on graph theory, to analyze the flexibility and rigidity of all known HIV-1 gp120 structures. A flexibility index is used to describe and compare the spatial distribution of protein flexibility and rigidity of these structures in isolation and in complex with CD4, CD4-mimics, and neutralizing antibodies. Using this flexibility analysis, we identified a universal rigid region (the alpha2 helix) as well as the consensus largest rigid cluster involving a beta-sheet located on the coreceptor binding face. Both of these regions may serve as stable targets for vaccine design and drug discovery. Detailed comparisons of the changes in flexibility based on strain variations, stabilizing mutations, binding features of CD4 mimics, and impact of b12 binding are reported.
Subject(s)
HIV Envelope Protein gp120/chemistry , HIV-1 , Binding Sites , CD4 Antigens/chemistry , CD4 Antigens/metabolism , HIV Envelope Protein gp120/genetics , HIV Envelope Protein gp120/metabolism , Hydrogen Bonding , Ligands , Models, Molecular , Protein Conformation , Software , Structure-Activity Relationship , ThermodynamicsABSTRACT
Over the last decade, structural biologists have unravelled many proteins that appear natively disordered. Common assumptions are that many of these proteins adopt structure through binding and that the structural flexibility enables them to adopt different functions. Here, we investigated regions of more than 70 sequence-consecutive residues that have no regular secondary structure (NORS). Analysing 31 entirely sequenced organisms, we predicted five times as many proteins with NORS regions (loopy proteins) in eukaryotes (20%) than in prokaryotes and archaeas (4%). Thousands of these NORS regions were over 150 residues long. The amino acid composition of NORS regions differed from that of loops in PDB. Although NORS proteins had significantly more residues in low-complexity regions than other proteins, simple cut-off thresholds for sequence bias missed most NORS regions. On average, NORS regions were evolutionarily at least as conserved as their flanking regions. Furthermore, yeast proteins with NORS regions had more protein-protein interaction partners than other proteins. Regulatory and transcription-related functions were over-represented in loopy proteins, biosynthesis and energy metabolism were under-represented. Overall, our analysis confirmed that proteins with non-regular structures appear to play important functional roles, and they may adopt as yet unknown types of protein structures.
Subject(s)
Conserved Sequence , Evolution, Molecular , Proteins/chemistry , Proteins/metabolism , Amino Acids/analysis , Computational Biology/methods , Databases, Protein , Hydrogen Bonding , Models, Molecular , Pliability , Protein Binding , Protein Folding , Protein Structure, Secondary , Proteins/classification , Proteome/chemistry , Proteome/classification , Proteome/metabolism , Solvents , Structure-Activity Relationship , Transcription, GeneticABSTRACT
The modern target-based drug discovery process, characterized by the one-drug-one-gene paradigm, has been of limited success. In contrast, phenotype-based screening produces thousands of active compounds but gives no hint as to what their molecular targets are or which ones merit further research. This presents a question: What is a suitable target for an efficient and safe drug? In this paper, we argue that target selection should take into account the proteome-wide energetic and kinetic landscape of drug-target interactions, as well as their cellular and organismal consequences. We propose a new paradigm of structural systems pharmacology to deconvolute the molecular targets of successful drugs as well as to identify druggable targets and their drug-like binders. Here we face two major challenges in structural systems pharmacology: How do we characterize and analyze the structural and energetic origins of drug-target interactions on a proteome scale? How do we correlate the dynamic molecular interactions to their in vivo activity? We will review recent advances in developing new computational tools for biophysics, bioinformatics, chemoinformatics, and systems biology related to the identification of genome-wide target profiles. We believe that the integration of these tools will realize structural systems pharmacology, enabling us to both efficiently develop effective therapeutics for complex diseases and combat drug resistance.