Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings

https://libpls.net/publication/PLS_basic_2001.pdf

PLS-regression: a basic tool of chemometrics

To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours.

/pdf/swissadme-a-free-web-tool-to-evaluate-pharmacokinetics-drug-xebymauqho.pdf

SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules

The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional (3D) atomic models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission numbers and Gene Ontology terms. An estimate of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of online server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhanglab.ccmb.med.umich.edu/I-TASSER.

/pdf/i-tasser-a-unified-platform-for-automated-protein-structure-1ek4kamd4l.pdf

I-TASSER: a unified platform for automated protein structure and function prediction

DrugBank (www.drugbank.ca) is a web-enabled database containing comprehensive molecular information about drugs, their mechanisms, their interactions and their targets. First described in 2006, DrugBank has continued to evolve over the past 12 years in response to marked improvements to web standards and changing needs for drug research and development. This year's update, DrugBank 5.0, represents the most significant upgrade to the database in more than 10 years. In many cases, existing data content has grown by 100% or more over the last update. For instance, the total number of investigational drugs in the database has grown by almost 300%, the number of drug-drug interactions has grown by nearly 600% and the number of SNP-associated drug effects has grown more than 3000%. Significant improvements have been made to the quantity, quality and consistency of drug indications, drug binding data as well as drug-drug and drug-food interactions. A great deal of brand new data have also been added to DrugBank 5.0. This includes information on the influence of hundreds of drugs on metabolite levels (pharmacometabolomics), gene expression levels (pharmacotranscriptomics) and protein expression levels (pharmacoprotoemics). New data have also been added on the status of hundreds of new drug clinical trials and existing drug repurposing trials. Many other important improvements in the content, interface and performance of the DrugBank website have been made and these should greatly enhance its ease of use, utility and potential applications in many areas of pharmacological research, pharmaceutical science and drug education.

DrugBank 5.0: a major update to the DrugBank database for 2018

The concept of emergence dissolvence in drug research, B. Testa and L.B. Kier sense and non-sense in toxicity assessment of medicinal products, A.G. Rauws, E.J. De Waal and J.W. van der Laan the concept of chiral conformers and its significance in molecular pharmacology, M. Simonyi combinational libraries for enhanced drug discovery, E.R. Felder and D. Poppinger reversal of chloroquine resistance in malaria - a new concept of chemotherapy, S. Batra and A.P. Bhaduri.

Advances in Drug Research

Calculated molecular properties from 3D molecular fields of interaction energies have become a valuable approach to correlate 3D molecular structures with physicochemical and pharmacodynamic properties. In contrast, their use in correlations with pharmacokinetic properties is still poorly explored and exploited. 3D molecular fields can be obtained from ab initio, semiempirical or molecular mechanics levels of calculation. The newly developed procedure called VolSurf is able to compress the relevant information present in 3D maps into a few descriptors characterised by the simplicity of their use and interpretation. These descriptors can be quantitatively compared and used to build multivariate models correlating 3D molecular structures with biological responses. The VolSurf procedure is applied here to generate descriptors and models of structure–permeation relationships. The VolSurf procedure, which was originally designed to handle a medium amount of data, can easily be applied to problems of large size such as bioisostere databases, CombyChem databases and related approaches.

Molecular fields in quantitative structure–permeation relationships: the VolSurf approach

Pharmacology over the past 100 years has had a rich tradition of scientists with the ability to form qualitative or semi-quantitative relations between molecular structure and activity in cerebro. To test these hypotheses they have consistently used traditional pharmacology tools such as in vivo and in vitro models. Increasingly over the last decade however we have seen that computational (in silico) methods have been developed and applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, pharmacophores, homology models and other molecular modeling approaches, machine learning, data mining, network analysis tools and data analysis tools that use a computer. In silico methods are primarily used alongside the generation of in vitro data both to create the model and to test it. Such models have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The aim of this review is to illustrate some of the in silico methods for pharmacology that are used in drug discovery. Further applications of these methods to specific targets and their limitations will be discussed in the second accompanying part of this review.

https://bpspubs.onlinelibrary.wiley.com/doi/pdf/10.1038/sj.bjp.0707305

In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling

Prodrug research: futile or fertile?

Predicting blood-brain barrier (BBB) permeation remains a challenge in drug design. Since it is impossible to determine experimentally the BBB partitioning of large numbers of preclinical candidates, alternative evaluation methods based on computerized models are desirable. The present study was conducted to demonstrate the value of descriptors derived from 3D molecular fields in estimating the BBB permeation of a large set of compounds and to produce a simple mathematical model suitable for external prediction. The method used (VolSurf) transforms 3D fields into descriptors and correlates them to the experimental permeation by a discriminant partial least squares procedure. The model obtained here correctly predicts more than 90% of the BBB permeation data. By quantifying the favorable and unfavorable contributions of physicochemical and structural properties, it also offers valuable insights for drug design, pharmacological profiling, and screening. The computational procedure is fully automated and quite fast. The method thus appears as a valuable new tool in virtual screening where selection or prioritization of candidates is required from large collections of compounds.

Bernard Testa

Papers

Advances in Drug Research

Molecular fields in quantitative structure–permeation relationships: the VolSurf approach

In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling

Prodrug research: futile or fertile?

Predicting Blood−Brain Barrier Permeation from Three-Dimensional Molecular Structure