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Khan MKA, Akhtar S. Novel drug design and bioinformatics: an introduction. PHYSICAL SCIENCES REVIEWS 2021. [DOI: 10.1515/psr-2018-0158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
In the current era of high-throughput technology, where enormous amounts of biological data are generated day by day via various sequencing projects, thereby the staggering volume of biological targets deciphered. The discovery of new chemical entities and bioisosteres of relatively low molecular weight has been gaining high momentum in the pharmacopoeia, and traditional combinatorial design wherein chemical structure is used as an initial template for enhancing efficacy pharmacokinetic selectivity properties. Once the compound is identified, it undergoes ADMET filtration to ensure whether it has toxic and mutagenic properties or not. If the compound has no toxicity and mutagenicity is either considered a potential lead molecule. Understanding the mechanism of lead molecules with various biological targets is imperative to advance related functions for drug discovery and development. Notwithstanding, a tedious and costly process, taking around 10–15 years and costing around $4 billion, cascaded approached of Bioinformatics and Computational biology viz., structure-based drug design (SBDD) and cognate ligand-based drug design (LBDD) respectively rely on the availability of 3D structure of target biomacromolecules and vice versa has made this process easy and approachable. SBDD encompasses homology modelling, ligand docking, fragment-based drug design and molecular dynamics, while LBDD deals with pharmacophore mapping, QSAR, and similarity search. All the computational methods discussed herein, whether for target identification or novel ligand discovery, continuously evolve and facilitate cost-effective and reliable outcomes in an era of overwhelming data.
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Affiliation(s)
- Mohammad Kalim Ahmad Khan
- Department of Bioengineering, Faculty of Engineering , Integral University , Lucknow , Uttar Pradesh , 226026 , India
| | - Salman Akhtar
- Department of Bioengineering, Faculty of Engineering , Integral University , Lucknow , Uttar Pradesh , 226026 , India
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Sanchez-Pulido L, Ponting CP. Extending the Horizon of Homology Detection with Coevolution-based Structure Prediction. J Mol Biol 2021; 433:167106. [PMID: 34139218 PMCID: PMC8527833 DOI: 10.1016/j.jmb.2021.167106] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 06/09/2021] [Accepted: 06/09/2021] [Indexed: 12/12/2022]
Abstract
Traditional sequence analysis algorithms fail to identify distant homologies when they lie beyond a detection horizon. In this review, we discuss how co-evolution-based contact and distance prediction methods are pushing back this homology detection horizon, thereby yielding new functional insights and experimentally testable hypotheses. Based on correlated substitutions, these methods divine three-dimensional constraints among amino acids in protein sequences that were previously devoid of all annotated domains and repeats. The new algorithms discern hidden structure in an otherwise featureless sequence landscape. Their revelatory impact promises to be as profound as the use, by archaeologists, of ground-penetrating radar to discern long-hidden, subterranean structures. As examples of this, we describe how triplicated structures reflecting longin domains in MON1A-like proteins, or UVR-like repeats in DISC1, emerge from their predicted contact and distance maps. These methods also help to resolve structures that do not conform to a "beads-on-a-string" model of protein domains. In one such example, we describe CFAP298 whose ubiquitin-like domain was previously challenging to perceive owing to a large sequence insertion within it. More generally, the new algorithms permit an easier appreciation of domain families and folds whose evolution involved structural insertion or rearrangement. As we exemplify with α1-antitrypsin, coevolution-based predicted contacts may also yield insights into protein dynamics and conformational change. This new combination of structure prediction (using innovative co-evolution based methods) and homology inference (using more traditional sequence analysis approaches) shows great promise for bringing into view a sea of evolutionary relationships that had hitherto lain far beyond the horizon of homology detection.
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Affiliation(s)
- Luis Sanchez-Pulido
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK.
| | - Chris P Ponting
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK.
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Nunes RR, Fonseca ALD, Pinto ACDS, Maia EHB, Silva AMD, Varotti FDP, Taranto AG. Brazilian malaria molecular targets (BraMMT): selected receptors for virtual high-throughput screening experiments. Mem Inst Oswaldo Cruz 2019; 114:e180465. [PMID: 30810604 PMCID: PMC6388387 DOI: 10.1590/0074-02760180465] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 02/04/2019] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Owing to increased spending on pharmaceuticals since 2010, discussions about rising costs for the development of new medical technologies have been focused on the pharmaceutical industry. Computational techniques have been developed to reduce costs associated with new drug development. Among these techniques, virtual high-throughput screening (vHTS) can contribute to the drug discovery process by providing tools to search for new drugs with the ability to bind a specific molecular target. OBJECTIVES In this context, Brazilian malaria molecular targets (BraMMT) was generated to execute vHTS experiments on selected molecular targets of Plasmodium falciparum. METHODS In this study, 35 molecular targets of P. falciparum were built and evaluated against known antimalarial compounds. FINDINGS As a result, it could predict the correct molecular target of market drugs, such as artemisinin. In addition, our findings suggested a new pharmacological mechanism for quinine, which includes inhibition of falcipain-II and a potential new antimalarial candidate, clioquinol. MAIN CONCLUSIONS The BraMMT is available to perform vHTS experiments using OCTOPUS or Raccoon software to improve the search for new antimalarial compounds. It can be retrieved from www.drugdiscovery.com.br or download of Supplementary data.
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Kamma-Lorger CS, Pinali C, Martínez JC, Harris J, Young RD, Bredrup C, Crosas E, Malfois M, Rødahl E, Meek KM, Knupp C. Role of Decorin Core Protein in Collagen Organisation in Congenital Stromal Corneal Dystrophy (CSCD). PLoS One 2016; 11:e0147948. [PMID: 26828927 PMCID: PMC4734740 DOI: 10.1371/journal.pone.0147948] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Accepted: 01/11/2016] [Indexed: 11/18/2022] Open
Abstract
The role of Decorin in organising the extracellular matrix was examined in normal human corneas and in corneas from patients with Congenital Stromal Corneal Dystrophy (CSCD). In CSCD, corneal clouding occurs due to a truncating mutation (c.967delT) in the decorin (DCN) gene. Normal human Decorin protein and the truncated one were reconstructed in silico using homology modelling techniques to explore structural changes in the diseased protein. Corneal CSCD specimens were also examined using 3-D electron tomography and Small Angle X-ray diffraction (SAXS), to image the collagen-proteoglycan arrangement and to quantify fibrillar diameters, respectively. Homology modelling showed that truncated Decorin had a different spatial geometry to the normal one, with the truncation removing a major part of the site that interacts with collagen, compromising its ability to bind effectively. Electron tomography showed regions of abnormal stroma, where collagen fibrils came together to form thicker fibrillar structures, showing that Decorin plays a key role in the maintenance of the order in the normal corneal extracellular matrix. Average diameter of individual fibrils throughout the thickness of the cornea however remained normal.
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Affiliation(s)
- Christina S. Kamma-Lorger
- NCD-BL11, ALBA Synchrotron Light Source, Cerdanyola del Vallés, 08290, Barcelona, Spain
- Structural Biophysics Research Group, School of Optometry and Vision Sciences, Cardiff University, Cardiff, CF24 4HQ, United Kingdom
| | - Christian Pinali
- Structural Biophysics Research Group, School of Optometry and Vision Sciences, Cardiff University, Cardiff, CF24 4HQ, United Kingdom
| | - Juan Carlos Martínez
- NCD-BL11, ALBA Synchrotron Light Source, Cerdanyola del Vallés, 08290, Barcelona, Spain
| | - Jon Harris
- Structural Biophysics Research Group, School of Optometry and Vision Sciences, Cardiff University, Cardiff, CF24 4HQ, United Kingdom
| | - Robert D. Young
- Structural Biophysics Research Group, School of Optometry and Vision Sciences, Cardiff University, Cardiff, CF24 4HQ, United Kingdom
| | - Cecilie Bredrup
- Department of Ophthalmology, Haukeland University Hospital, 5021 Bergen, Norway
| | - Eva Crosas
- NCD-BL11, ALBA Synchrotron Light Source, Cerdanyola del Vallés, 08290, Barcelona, Spain
| | - Marc Malfois
- NCD-BL11, ALBA Synchrotron Light Source, Cerdanyola del Vallés, 08290, Barcelona, Spain
| | - Eyvind Rødahl
- Department of Ophthalmology, Haukeland University Hospital, 5021 Bergen, Norway
- Department of Clinical Medicine, University of Bergen, 5020 Bergen, Norway
| | - Keith M. Meek
- Structural Biophysics Research Group, School of Optometry and Vision Sciences, Cardiff University, Cardiff, CF24 4HQ, United Kingdom
| | - Carlo Knupp
- Structural Biophysics Research Group, School of Optometry and Vision Sciences, Cardiff University, Cardiff, CF24 4HQ, United Kingdom
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Bastard K, Prévost C, Zacharias M. Accounting for loop flexibility during protein-protein docking. Proteins 2005; 62:956-69. [PMID: 16372349 DOI: 10.1002/prot.20770] [Citation(s) in RCA: 70] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Although reliable docking can now be achieved for systems that do not undergo important induced conformational change upon association, the presence of flexible surface loops, which must adapt to the steric and electrostatic properties of a partner, generally presents a major obstacle. We report here the first docking method that allows large loop movements during a systematic exploration of the possible arrangements of the two partners in terms of position and rotation. Our strategy consists in taking into account an ensemble of possible loop conformations by a multi-copy representation within a reduced protein model. The docking process starts from regularly distributed positions and orientations of the ligand around the whole receptor. Each starting configuration is submitted to energy minimization during which the best-fitting loop conformation is selected based on the mean-field theory. Trials were carried out on proteins with significant differences in the main-chain conformation of the binding loop between isolated form and complexed form, which were docked to their partner considered in their bound form. The method is able to predict complexes very close to the crystal complex both in terms of relative position of the two partners and of the geometry of the flexible loop. We also show that introducing loop flexibility on the isolated protein form during systematic docking largely improves the predictions of relative position of the partners in comparison with rigid-body docking.
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Affiliation(s)
- Karine Bastard
- Computational Biology, School of Engineering and Science, International University Bremen, Bremen, Germany.
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Pei J, Grishin NV. Combining evolutionary and structural information for local protein structure prediction. Proteins 2004; 56:782-94. [PMID: 15281130 DOI: 10.1002/prot.20158] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We study the effects of various factors in representing and combining evolutionary and structural information for local protein structural prediction based on fragment selection. We prepare databases of fragments from a set of non-redundant protein domains. For each fragment, evolutionary information is derived from homologous sequences and represented as estimated effective counts and frequencies of amino acids (evolutionary frequencies) at each position. Position-specific amino acid preferences called structural frequencies are derived from statistical analysis of discrete local structural environments in database structures. Our method for local structure prediction is based on ranking and selecting database fragments that are most similar to a target fragment. Using secondary structure type as a local structural property, we test our method in a number of settings. The major findings are: (1) the COMPASS-type scoring function for fragment similarity comparison gives better prediction accuracy than three other tested scoring functions for profile-profile comparison. We show that the COMPASS-type scoring function can be derived both in the probabilistic framework and in the framework of statistical potentials. (2) Using the evolutionary frequencies of database fragments gives better prediction accuracy than using structural frequencies. (3) Finer definition of local environments, such as including more side-chain solvent accessibility classes and considering the backbone conformations of neighboring residues, gives increasingly better prediction accuracy using structural frequencies. (4) Combining evolutionary and structural frequencies of database fragments, either in a linear fashion or using a pseudocount mixture formula, results in improvement of prediction accuracy. Combination at the log-odds score level is not as effective as combination at the frequency level. This suggests that there might be better ways of combining sequence and structural information than the commonly used linear combination of log-odds scores. Our method of fragment selection and frequency combination gives reasonable results of secondary structure prediction tested on 56 CASP5 targets (average SOV score 0.77), suggesting that it is a valid method for local protein structure prediction. Mixture of predicted structural frequencies and evolutionary frequencies improve the quality of local profile-to-profile alignment by COMPASS.
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Affiliation(s)
- Jimin Pei
- Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9050, USA
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