Tautomerism and magnesium chelation of HIV-1 integrase inhibitors: a theoretical study

Quantum mechanics implementation in drug-design workflows: does it really help?

The pharmaceutical industry is progressively operating in an era where development costs are constantly under pressure, higher percentages of drugs are demanded, and the drug-discovery process is a trial-and-error run. The profit that flows in with the discovery of new drugs has always been the motivation for the industry to keep up the pace and keep abreast with the endless demand for medicines. The process of finding a molecule that binds to the target protein using in silico tools has made computational chemistry a valuable tool in drug discovery in both academic research and pharmaceutical industry. However, the complexity of many protein-ligand interactions challenges the accuracy and efficiency of the commonly used empirical methods. The usefulness of quantum mechanics (QM) in drug-protein interaction cannot be overemphasized; however, this approach has little significance in some empirical methods. In this review, we discuss recent developments in, and application of, QM to medically relevant biomolecules. We critically discuss the different types of QM-based methods and their proposed application to incorporating them into drug-design and -discovery workflows while trying to answer a critical question: are QM-based methods of real help in drug-design and -discovery research and industry?

Design, synthesis, and biological evaluation of 1, 3-disubstituted-pyrazole derivatives as new class I and IIb histone deacetylase inhibitors

A novel series of HDAC inhibitors demonstrating class I and IIb subtype selectivity have been identified using a scaffold-hopping strategy. Several designed compounds showed better selectivity for class I and IIb over class IIa HDAC isoforms comparing to the FDA approved HDAC targeting drug SAHA. A representative lead compound 22 bearing a biphenyl moiety demonstrated promising class I and IIb HDAC isoforms selectivity and in vitro anticancer activities against several cancer cell lines. This work could serve as a fundamental platform for further exploration of selective HDAC inhibitors using designed molecular scaffold.

Dual mechanism of HIV-1 integrase and RNase H inhibition by diketo derivatives – a computational study

Dual inhibition of HIV-1 integrase and RNase H by the diketo derivatives is investigated through ligand and structure based computational methods.

Software and resources for computational medicinal chemistry

Computer-aided drug design plays a vital role in drug discovery and development and has become an indispensable tool in the pharmaceutical industry. Computational medicinal chemists can take advantage of all kinds of software and resources in the computer-aided drug design field for the purposes of discovering and optimizing biologically active compounds. This article reviews software and other resources related to computer-aided drug design approaches, putting particular emphasis on structure-based drug design, ligand-based drug design, chemical databases and chemoinformatics tools.

Authentic HIV-1 integrase inhibitors

HIV-1 integrase (IN) is indispensable for HIV-1 replication and has become a validated target for developing anti-AIDS agents. In two decades of development of IN inhibition-based anti-HIV therapeutics, a significant number of compounds were identified as IN inhibitors, but only some of them showed antiviral activity. This article reviews a number of patented HIV-1 IN inhibitors, especially those that possess high selectivity for the strand transfer reaction. These compounds generally have a polar coplanar moiety, which is assumed to chelate two magnesium ions in the binding site. Resistance to those compounds, when given to patients, can develop as a result of IN mutations. We refer to those compounds as authentic IN inhibitors. Continued drug development has so far delivered one authentic IN inhibitor to the market (raltegravir in 2007). Current and future attention will be focused on the development of novel authentic IN inhibitors with the goal of overcoming viral resistance.

Computer tools in the discovery of HIV-1 integrase inhibitors

Computer-aided drug design (CADD) methodologies have made great advances and contributed significantly to the discovery and/or optimization of many clinically used drugs in recent years. CADD tools have likewise been applied to the discovery of inhibitors of HIV-1 integrase, a difficult and worthwhile target for the development of efficient anti-HIV drugs. This article reviews the application of CADD tools, including pharmacophore search, quantitative structure-activity relationships, model building of integrase complexed with viral DNA and quantum-chemical studies in the discovery of HIV-1 integrase inhibitors. Different structurally diverse integrase inhibitors have been identified by, or with significant help from, various CADD tools.