Synthetic cyclopenta[b]indoles exhibit antineoplastic activity by targeting microtubule dynamics in acute myeloid leukemia cells.

Acute promyelocytic leukemia (APL) is associated with PML-RARα oncogene, which is treated using all-trans retinoic acid (ATRA)-based chemotherapy. However, chemoresistance is observed in 20-30% of treated patients and represents a clinical challenge, raising the importance of the development of new therapeutic options. In the present study, the effects of three synthetic cyclopenta[b]indoles on the leukemia phenotype were investigated using NB4 (ATRA-sensitive) and NB4-R2 (ATRA-resistant) cells.

Structural complementarity of distance constraints obtained from chemical cross-linking and amino acid coevolution.

The analysis of amino acid coevolution has emerged as a practical method for protein structural modeling by providing structural contact information from alignments of amino acid sequences. In parallel, chemical cross-linking/mass spectrometry (XLMS) has gained attention as a universally applicable method for obtaining low-resolution distance constraints to model the quaternary arrangements of proteins, and more recently even protein tertiary structures. Here, we show that the structural information obtained by XLMS and coevolutionary analysis are effectively complementary: the distance constraints obtained by each method are almost exclusively associated with non-coincident pairs of residues, and modeling results obtained by the combination of both sets are improved relative to considering the same total number of constraints of a single type.

Coevolutionary Signals and Structure-Based Models for the Prediction of Protein Native Conformations.

The analysis of coevolutionary signals from families of evolutionarily related sequences is a recent conceptual framework that provides valuable information about unique intramolecular interactions and, therefore, can assist in the elucidation of biomolecular conformations. It is based on the idea that compensatory mutations at specific residue positions in a sequence help preserve stability of protein architecture and function and leave a statistical signature related to residue-residue interactions in the 3D structure of the protein. Consequently, statistical analysis of these correlated mutations in subsets of protein sequence alignments can be used to predict which residue pairs should be in spatial proximity in the native functional protein fold.

Characterization of C-ring component assembly in flagellar motors from amino acid coevolution.

Bacterial flagellar motility, an important virulence factor, is energized by a rotary motor localized within the flagellar basal body. The rotor module consists of a large framework (the C-ring), composed of the FliG, FliM and FliN proteins. FliN and FliM contacts the FliG torque ring to control the direction of flagellar rotation.

Practices in Molecular Docking and Structure-Based Virtual Screening.

Drug discovery has evolved significantly over the past two decades. Progress in key areas such as molecular and structural biology has contributed to the elucidation of the three-dimensional structure and function of a wide range of biological molecules of therapeutic interest. In this context, the integration of experimental techniques, such as X-ray crystallography, and computational methods, such as molecular docking, has promoted the emergence of several areas in drug discovery, such as structure-based drug design (SBDD).

Enhancing protein fold determination by exploring the complementary information of chemical cross-linking and coevolutionary signals.

Motivation: Elucidation of protein native states from amino acid sequences is a primary computational challenge. Modern computational and experimental methodologies, such as molecular coevolution and chemical cross-linking mass-spectrometry allowed protein structural characterization to previously intangible systems. Despite several independent successful examples, data from these distinct methodologies have not been systematically studied in conjunction.

Dimeric interactions and complex formation using direct coevolutionary couplings.

We develop a procedure to characterize the association of protein structures into homodimers using coevolutionary couplings extracted from Direct Coupling Analysis (DCA) in combination with Structure Based Models (SBM). Identification of dimerization contacts using DCA is more challenging than intradomain contacts since direct couplings are mixed with monomeric contacts. Therefore a systematic way to extract dimerization signals has been elusive.

Molecular docking and structure-based drug design strategies.

Pharmaceutical research has successfully incorporated a wealth of molecular modeling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of novel promising compounds. Broadly used in modern drug design, molecular docking methods explore the ligand conformations adopted within the binding sites of macromolecular targets.

Discovery of new inhibitors of Mycobacterium tuberculosis InhA enzyme using virtual screening and a 3D-pharmacophore-based approach.

Mycobacterium tuberculosis InhA (MtInhA) is an attractive enzyme to drug discovery efforts due to its validation as an effective biological target for tuberculosis therapy. In this work, two different virtual-ligand-screening approaches were applied in order to identify new InhA inhibitors' candidates from a library of ligands selected from the ZINC database. First, a 3-D pharmacophore model was built based on 36 available MtInhA crystal structures.

Development of a natural products database from the biodiversity of Brazil.

We describe herein the design and development of an innovative tool called the NuBBE database (NuBBEDB), a new Web-based database, which incorporates several classes of secondary metabolites and derivatives from the biodiversity of Brazil. This natural product database incorporates botanical, chemical, pharmacological, and toxicological compound information. The NuBBEDB provides specialized information to the worldwide scientific community and can serve as a useful tool for studies on the multidisciplinary interfaces related to chemistry and biology, including virtual screening, dereplication, metabolomics, and medicinal chemistry.